id	sid	tid	token	lemma	pos
brj-22095	1	1	peer	peer	NOUN
brj-22095	1	2	-	-	PUNCT
brj-22095	1	3	review	review	NOUN
brj-22095	1	4	article	article	NOUN
brj-22095	1	5	peer	peer	NOUN
brj-22095	1	6	-	-	PUNCT
brj-22095	1	7	reviewed	review	VERB
brj-22095	1	8	article	article	NOUN
brj-22095	1	9	bioresources.com	bioresources.com	X
brj-22095	1	10	he	he	PRON
brj-22095	1	11	et	et	PROPN
brj-22095	1	12	al	al	PROPN
brj-22095	1	13	.	.	PROPN
brj-22095	1	14	(	(	PUNCT
brj-22095	1	15	2022	2022	NUM
brj-22095	1	16	)	)	PUNCT
brj-22095	1	17	.	.	PUNCT
brj-22095	2	1	“	"	PUNCT
brj-22095	2	2	near	near	ADP
brj-22095	2	3	ir	ir	PROPN
brj-22095	2	4	model	model	NOUN
brj-22095	2	5	of	of	ADP
brj-22095	2	6	biomass	biomass	NOUN
brj-22095	2	7	,	,	PUNCT
brj-22095	2	8	”	"	PUNCT
brj-22095	2	9	bioresources	bioresource	NOUN
brj-22095	2	10	17(4	17(4	NUM
brj-22095	2	11	)	)	PUNCT
brj-22095	2	12	,	,	PUNCT
brj-22095	2	13	6476	6476	NUM
brj-22095	2	14	-	-	SYM
brj-22095	2	15	6489	6489	NUM
brj-22095	2	16	.	.	PUNCT
brj-22095	3	1	6476	6476	NUM
brj-22095	3	2	transfer	transfer	NOUN
brj-22095	3	3	strategy	strategy	NOUN
brj-22095	3	4	for	for	ADP
brj-22095	3	5	near	near	ADV
brj-22095	3	6	infrared	infrared	ADJ
brj-22095	3	7	analysis	analysis	NOUN
brj-22095	3	8	model	model	NOUN
brj-22095	3	9	of	of	ADP
brj-22095	3	10	holocellulose	holocellulose	NOUN
brj-22095	3	11	and	and	CCONJ
brj-22095	3	12	lignin	lignin	NOUN
brj-22095	3	13	based	base	VERB
brj-22095	3	14	on	on	ADP
brj-22095	3	15	improved	improved	ADJ
brj-22095	3	16	slope	slope	NOUN
brj-22095	3	17	/	/	SYM
brj-22095	3	18	bias	bias	NOUN
brj-22095	3	19	algorithm	algorithm	PROPN
brj-22095	3	20	honghong	honghong	PROPN
brj-22095	3	21	wang	wang	PROPN
brj-22095	3	22	,	,	PUNCT
brj-22095	3	23	zhixin	zhixin	PROPN
brj-22095	3	24	xiong	xiong	PROPN
brj-22095	3	25	,	,	PUNCT
brj-22095	3	26	*	*	PUNCT
brj-22095	3	27	yunchao	yunchao	PROPN
brj-22095	3	28	hu	hu	PROPN
brj-22095	3	29	,	,	PUNCT
brj-22095	3	30	zhijian	zhijian	PROPN
brj-22095	3	31	liu	liu	PROPN
brj-22095	3	32	,	,	PUNCT
brj-22095	3	33	and	and	CCONJ
brj-22095	3	34	long	long	PROPN
brj-22095	3	35	liang	liang	PROPN
brj-22095	3	36	model	model	NOUN
brj-22095	3	37	transfer	transfer	NOUN
brj-22095	3	38	techniques	technique	NOUN
brj-22095	3	39	in	in	ADP
brj-22095	3	40	near	near	ADP
brj-22095	3	41	infrared	infrared	ADJ
brj-22095	3	42	spectroscopy	spectroscopy	NOUN
brj-22095	3	43	are	be	AUX
brj-22095	3	44	important	important	ADJ
brj-22095	3	45	for	for	ADP
brj-22095	3	46	avoiding	avoid	VERB
brj-22095	3	47	duplicate	duplicate	ADJ
brj-22095	3	48	modeling	modeling	NOUN
brj-22095	3	49	,	,	PUNCT
brj-22095	3	50	sharing	share	VERB
brj-22095	3	51	samples	sample	NOUN
brj-22095	3	52	and	and	CCONJ
brj-22095	3	53	data	datum	NOUN
brj-22095	3	54	resources	resource	NOUN
brj-22095	3	55	,	,	PUNCT
brj-22095	3	56	and	and	CCONJ
brj-22095	3	57	reducing	reduce	VERB
brj-22095	3	58	the	the	DET
brj-22095	3	59	human	human	ADJ
brj-22095	3	60	and	and	CCONJ
brj-22095	3	61	material	material	NOUN
brj-22095	3	62	consumption	consumption	NOUN
brj-22095	3	63	required	require	VERB
brj-22095	3	64	for	for	ADP
brj-22095	3	65	modeling	modeling	NOUN
brj-22095	3	66	.	.	PUNCT
brj-22095	4	1	use	use	NOUN
brj-22095	4	2	of	of	ADP
brj-22095	4	3	the	the	DET
brj-22095	4	4	slope	slope	NOUN
brj-22095	4	5	/	/	SYM
brj-22095	4	6	bias	bias	NOUN
brj-22095	4	7	correction	correction	NOUN
brj-22095	4	8	algorithm	algorithm	NOUN
brj-22095	4	9	(	(	PUNCT
brj-22095	4	10	s	s	PROPN
brj-22095	4	11	/	/	SYM
brj-22095	4	12	b	b	NOUN
brj-22095	4	13	)	)	PUNCT
brj-22095	4	14	based	base	VERB
brj-22095	4	15	on	on	ADP
brj-22095	4	16	screening	screen	VERB
brj-22095	4	17	wavelengths	wavelength	NOUN
brj-22095	4	18	with	with	ADP
brj-22095	4	19	consistent	consistent	ADJ
brj-22095	4	20	and	and	CCONJ
brj-22095	4	21	stable	stable	ADJ
brj-22095	4	22	signals	signal	NOUN
brj-22095	4	23	(	(	PUNCT
brj-22095	4	24	swcss	swcss	PROPN
brj-22095	4	25	)	)	PUNCT
brj-22095	4	26	for	for	ADP
brj-22095	4	27	model	model	NOUN
brj-22095	4	28	transfer	transfer	NOUN
brj-22095	4	29	is	be	AUX
brj-22095	4	30	a	a	DET
brj-22095	4	31	new	new	ADJ
brj-22095	4	32	strategy	strategy	NOUN
brj-22095	4	33	.	.	PUNCT
brj-22095	5	1	to	to	PART
brj-22095	5	2	enable	enable	VERB
brj-22095	5	3	sharing	sharing	NOUN
brj-22095	5	4	of	of	ADP
brj-22095	5	5	near	near	ADP
brj-22095	5	6	infrared	infrared	ADJ
brj-22095	5	7	analysis	analysis	NOUN
brj-22095	5	8	models	model	NOUN
brj-22095	5	9	of	of	ADP
brj-22095	5	10	pulp	pulp	NOUN
brj-22095	5	11	holocellulose	holocellulose	PROPN
brj-22095	5	12	and	and	CCONJ
brj-22095	5	13	lignin	lignin	NOUN
brj-22095	5	14	content	content	NOUN
brj-22095	5	15	in	in	ADP
brj-22095	5	16	two	two	NUM
brj-22095	5	17	different	different	ADJ
brj-22095	5	18	types	type	NOUN
brj-22095	5	19	of	of	ADP
brj-22095	5	20	spectroscopic	spectroscopic	ADJ
brj-22095	5	21	instruments	instrument	NOUN
brj-22095	5	22	,	,	PUNCT
brj-22095	5	23	a	a	DET
brj-22095	5	24	combined	combine	VERB
brj-22095	5	25	swcss	swcss	PROPN
brj-22095	5	26	-	-	PUNCT
brj-22095	5	27	s	s	PROPN
brj-22095	5	28	/	/	SYM
brj-22095	5	29	b	b	NOUN
brj-22095	5	30	algorithm	algorithm	NOUN
brj-22095	5	31	was	be	AUX
brj-22095	5	32	proposed	propose	VERB
brj-22095	5	33	.	.	PUNCT
brj-22095	6	1	the	the	DET
brj-22095	6	2	stable	stable	ADJ
brj-22095	6	3	and	and	CCONJ
brj-22095	6	4	consistent	consistent	ADJ
brj-22095	6	5	wavelengths	wavelength	NOUN
brj-22095	6	6	between	between	ADP
brj-22095	6	7	the	the	DET
brj-22095	6	8	spectroscopic	spectroscopic	ADJ
brj-22095	6	9	instruments	instrument	NOUN
brj-22095	6	10	screened	screen	VERB
brj-22095	6	11	by	by	ADP
brj-22095	6	12	the	the	DET
brj-22095	6	13	swcss	swcss	PROPN
brj-22095	6	14	method	method	NOUN
brj-22095	6	15	reduced	reduce	VERB
brj-22095	6	16	the	the	DET
brj-22095	6	17	differences	difference	NOUN
brj-22095	6	18	between	between	ADP
brj-22095	6	19	the	the	DET
brj-22095	6	20	instruments	instrument	NOUN
brj-22095	6	21	,	,	PUNCT
brj-22095	6	22	thereby	thereby	ADV
brj-22095	6	23	improving	improve	VERB
brj-22095	6	24	the	the	DET
brj-22095	6	25	universality	universality	NOUN
brj-22095	6	26	and	and	CCONJ
brj-22095	6	27	transmission	transmission	NOUN
brj-22095	6	28	accuracy	accuracy	NOUN
brj-22095	6	29	of	of	ADP
brj-22095	6	30	the	the	DET
brj-22095	6	31	s	s	PROPN
brj-22095	6	32	/	/	SYM
brj-22095	6	33	b	b	NOUN
brj-22095	6	34	method	method	NOUN
brj-22095	6	35	.	.	PUNCT
brj-22095	7	1	the	the	DET
brj-22095	7	2	swcss	swcss	PROPN
brj-22095	7	3	-	-	PUNCT
brj-22095	7	4	s	s	PROPN
brj-22095	7	5	/	/	SYM
brj-22095	7	6	b	b	PROPN
brj-22095	7	7	based	base	VERB
brj-22095	7	8	model	model	NOUN
brj-22095	7	9	transfer	transfer	NOUN
brj-22095	7	10	method	method	NOUN
brj-22095	7	11	reduced	reduce	VERB
brj-22095	7	12	the	the	DET
brj-22095	7	13	predicted	predict	VERB
brj-22095	7	14	standard	standard	ADJ
brj-22095	7	15	deviation	deviation	NOUN
brj-22095	7	16	rmsep	rmsep	NOUN
brj-22095	7	17	of	of	ADP
brj-22095	7	18	holocellulose	holocellulose	ADJ
brj-22095	7	19	and	and	CCONJ
brj-22095	7	20	lignin	lignin	NOUN
brj-22095	7	21	contents	content	NOUN
brj-22095	7	22	of	of	ADP
brj-22095	7	23	the	the	DET
brj-22095	7	24	samples	sample	NOUN
brj-22095	7	25	measured	measure	VERB
brj-22095	7	26	on	on	ADP
brj-22095	7	27	the	the	DET
brj-22095	7	28	target	target	NOUN
brj-22095	7	29	spectrometer	spectrometer	NOUN
brj-22095	7	30	of	of	ADP
brj-22095	7	31	the	the	PRON
brj-22095	7	32	from	from	ADP
brj-22095	7	33	5.4686	5.4686	NUM
brj-22095	7	34	and	and	CCONJ
brj-22095	7	35	7.6823	7.6823	NUM
brj-22095	7	36	to	to	ADP
brj-22095	7	37	1.2133	1.2133	NUM
brj-22095	7	38	and	and	CCONJ
brj-22095	7	39	1.3494	1.3494	NUM
brj-22095	7	40	,	,	PUNCT
brj-22095	7	41	respectively	respectively	ADV
brj-22095	7	42	.	.	PUNCT
brj-22095	8	1	this	this	DET
brj-22095	8	2	result	result	NOUN
brj-22095	8	3	showed	show	VERB
brj-22095	8	4	a	a	DET
brj-22095	8	5	significant	significant	ADJ
brj-22095	8	6	improvement	improvement	NOUN
brj-22095	8	7	in	in	ADP
brj-22095	8	8	the	the	DET
brj-22095	8	9	transfer	transfer	NOUN
brj-22095	8	10	effect	effect	NOUN
brj-22095	8	11	compared	compare	VERB
brj-22095	8	12	to	to	ADP
brj-22095	8	13	the	the	DET
brj-22095	8	14	swcss	swcss	PROPN
brj-22095	8	15	and	and	CCONJ
brj-22095	8	16	s	s	PROPN
brj-22095	8	17	/	/	SYM
brj-22095	8	18	b	b	PROPN
brj-22095	8	19	correction	correction	NOUN
brj-22095	8	20	results	result	VERB
brj-22095	8	21	alone	alone	ADV
brj-22095	8	22	,	,	PUNCT
brj-22095	8	23	and	and	CCONJ
brj-22095	8	24	the	the	DET
brj-22095	8	25	prediction	prediction	NOUN
brj-22095	8	26	of	of	ADP
brj-22095	8	27	holocellulose	holocellulose	NOUN
brj-22095	8	28	was	be	AUX
brj-22095	8	29	better	well	ADJ
brj-22095	8	30	than	than	ADP
brj-22095	8	31	that	that	PRON
brj-22095	8	32	of	of	ADP
brj-22095	8	33	the	the	DET
brj-22095	8	34	prediction	prediction	NOUN
brj-22095	8	35	effect	effect	NOUN
brj-22095	8	36	of	of	ADP
brj-22095	8	37	lignin	lignin	NOUN
brj-22095	8	38	.	.	PUNCT
brj-22095	9	1	the	the	DET
brj-22095	9	2	method	method	NOUN
brj-22095	9	3	has	have	VERB
brj-22095	9	4	fewer	few	ADJ
brj-22095	9	5	wavelength	wavelength	NOUN
brj-22095	9	6	variables	variable	NOUN
brj-22095	9	7	involved	involve	VERB
brj-22095	9	8	in	in	ADP
brj-22095	9	9	model	model	NOUN
brj-22095	9	10	transfer	transfer	NOUN
brj-22095	9	11	,	,	PUNCT
brj-22095	9	12	fast	fast	ADJ
brj-22095	9	13	transfer	transfer	NOUN
brj-22095	9	14	speed	speed	NOUN
brj-22095	9	15	,	,	PUNCT
brj-22095	9	16	and	and	CCONJ
brj-22095	9	17	high	high	ADJ
brj-22095	9	18	prediction	prediction	NOUN
brj-22095	9	19	accuracy	accuracy	NOUN
brj-22095	9	20	,	,	PUNCT
brj-22095	9	21	which	which	PRON
brj-22095	9	22	provides	provide	VERB
brj-22095	9	23	a	a	DET
brj-22095	9	24	new	new	ADJ
brj-22095	9	25	solution	solution	NOUN
brj-22095	9	26	for	for	ADP
brj-22095	9	27	the	the	DET
brj-22095	9	28	wide	wide	ADJ
brj-22095	9	29	application	application	NOUN
brj-22095	9	30	of	of	ADP
brj-22095	9	31	nir	nir	ADJ
brj-22095	9	32	analytical	analytical	ADJ
brj-22095	9	33	models	model	NOUN
brj-22095	9	34	.	.	PUNCT
brj-22095	10	1	doi	doi	NOUN
brj-22095	10	2	:	:	PUNCT
brj-22095	10	3	10.15376	10.15376	NUM
brj-22095	10	4	/	/	SYM
brj-22095	10	5	biores.17.4.6476	biores.17.4.6476	NOUN
brj-22095	10	6	-	-	PUNCT
brj-22095	10	7	6489	6489	NUM
brj-22095	10	8	keywords	keyword	NOUN
brj-22095	10	9	:	:	PUNCT
brj-22095	10	10	near	near	ADP
brj-22095	10	11	infrared	infrared	ADJ
brj-22095	10	12	spectroscopy	spectroscopy	NOUN
brj-22095	10	13	;	;	PUNCT
brj-22095	10	14	holocellulose	holocellulose	PRON
brj-22095	10	15	;	;	PUNCT
brj-22095	10	16	lignin	lignin	NOUN
brj-22095	10	17	;	;	PUNCT
brj-22095	10	18	stable	stable	ADJ
brj-22095	10	19	and	and	CCONJ
brj-22095	10	20	consistent	consistent	ADJ
brj-22095	10	21	wavelength	wavelength	NOUN
brj-22095	10	22	;	;	PUNCT
brj-22095	10	23	slope	slope	NOUN
brj-22095	10	24	/	/	SYM
brj-22095	10	25	bias	bias	NOUN
brj-22095	10	26	algorithm	algorithm	NOUN
brj-22095	10	27	;	;	PUNCT
brj-22095	10	28	model	model	NOUN
brj-22095	10	29	transfer	transfer	NOUN
brj-22095	10	30	contact	contact	NOUN
brj-22095	10	31	information	information	NOUN
brj-22095	10	32	:	:	PUNCT
brj-22095	10	33	college	college	NOUN
brj-22095	10	34	of	of	ADP
brj-22095	10	35	light	light	ADJ
brj-22095	10	36	industry	industry	NOUN
brj-22095	10	37	and	and	CCONJ
brj-22095	10	38	food	food	NOUN
brj-22095	10	39	engineering	engineering	NOUN
brj-22095	10	40	,	,	PUNCT
brj-22095	10	41	nanjing	nanjing	PROPN
brj-22095	10	42	forestry	forestry	PROPN
brj-22095	10	43	university	university	PROPN
brj-22095	10	44	,	,	PUNCT
brj-22095	10	45	longpan	longpan	ADJ
brj-22095	10	46	road	road	NOUN
brj-22095	10	47	159	159	NUM
brj-22095	10	48	,	,	PUNCT
brj-22095	10	49	nanjing	nanjing	PROPN
brj-22095	10	50	210037	210037	NUM
brj-22095	10	51	china	china	PROPN
brj-22095	10	52	;	;	PUNCT
brj-22095	10	53	*	*	PUNCT
brj-22095	10	54	corresponding	correspond	VERB
brj-22095	10	55	author	author	NOUN
brj-22095	10	56	:	:	PUNCT
brj-22095	10	57	leo_xzx@njfu.edu.cn	leo_xzx@njfu.edu.cn	NOUN
brj-22095	10	58	introduction	introduction	NOUN
brj-22095	10	59	holocellulose	holocellulose	X
brj-22095	10	60	(	(	PUNCT
brj-22095	10	61	including	include	VERB
brj-22095	10	62	cellulose	cellulose	NOUN
brj-22095	10	63	and	and	CCONJ
brj-22095	10	64	hemicellulose	hemicellulose	NOUN
brj-22095	10	65	)	)	PUNCT
brj-22095	10	66	and	and	CCONJ
brj-22095	10	67	lignin	lignin	NOUN
brj-22095	10	68	are	be	AUX
brj-22095	10	69	the	the	DET
brj-22095	10	70	main	main	ADJ
brj-22095	10	71	components	component	NOUN
brj-22095	10	72	of	of	ADP
brj-22095	10	73	wood	wood	NOUN
brj-22095	10	74	.	.	PUNCT
brj-22095	11	1	they	they	PRON
brj-22095	11	2	are	be	AUX
brj-22095	11	3	closely	closely	ADV
brj-22095	11	4	related	relate	VERB
brj-22095	11	5	to	to	ADP
brj-22095	11	6	other	other	ADJ
brj-22095	11	7	wood	wood	NOUN
brj-22095	11	8	properties	property	NOUN
brj-22095	11	9	as	as	ADV
brj-22095	11	10	well	well	ADV
brj-22095	11	11	as	as	ADP
brj-22095	11	12	to	to	ADP
brj-22095	11	13	the	the	DET
brj-22095	11	14	processing	processing	NOUN
brj-22095	11	15	and	and	CCONJ
brj-22095	11	16	utilization	utilization	NOUN
brj-22095	11	17	of	of	ADP
brj-22095	11	18	wood	wood	NOUN
brj-22095	11	19	.	.	PUNCT
brj-22095	12	1	in	in	ADP
brj-22095	12	2	the	the	DET
brj-22095	12	3	paper	paper	NOUN
brj-22095	12	4	industry	industry	NOUN
brj-22095	12	5	,	,	PUNCT
brj-22095	12	6	the	the	DET
brj-22095	12	7	holocellulose	holocellulose	ADJ
brj-22095	12	8	content	content	NOUN
brj-22095	12	9	is	be	AUX
brj-22095	12	10	closely	closely	ADV
brj-22095	12	11	related	relate	VERB
brj-22095	12	12	to	to	ADP
brj-22095	12	13	the	the	DET
brj-22095	12	14	pulp	pulp	NOUN
brj-22095	12	15	yield	yield	NOUN
brj-22095	12	16	and	and	CCONJ
brj-22095	12	17	pulp	pulp	NOUN
brj-22095	12	18	quality	quality	NOUN
brj-22095	12	19	;	;	PUNCT
brj-22095	12	20	the	the	DET
brj-22095	12	21	lignin	lignin	NOUN
brj-22095	12	22	content	content	NOUN
brj-22095	12	23	is	be	AUX
brj-22095	12	24	an	an	DET
brj-22095	12	25	important	important	ADJ
brj-22095	12	26	basis	basis	NOUN
brj-22095	12	27	for	for	ADP
brj-22095	12	28	the	the	DET
brj-22095	12	29	development	development	NOUN
brj-22095	12	30	of	of	ADP
brj-22095	12	31	cooking	cooking	NOUN
brj-22095	12	32	and	and	CCONJ
brj-22095	12	33	bleaching	bleaching	NOUN
brj-22095	12	34	conditions	condition	NOUN
brj-22095	12	35	(	(	PUNCT
brj-22095	12	36	haque	haque	PROPN
brj-22095	12	37	et	et	PROPN
brj-22095	12	38	al	al	PROPN
brj-22095	12	39	.	.	PROPN
brj-22095	12	40	2019	2019	NUM
brj-22095	12	41	)	)	PUNCT
brj-22095	12	42	.	.	PUNCT
brj-22095	13	1	near	near	ADP
brj-22095	13	2	infrared	infrared	ADJ
brj-22095	13	3	spectroscopy	spectroscopy	NOUN
brj-22095	13	4	(	(	PUNCT
brj-22095	13	5	nirs	nirs	PROPN
brj-22095	13	6	)	)	PUNCT
brj-22095	13	7	is	be	AUX
brj-22095	13	8	widely	widely	ADV
brj-22095	13	9	used	use	VERB
brj-22095	13	10	in	in	ADP
brj-22095	13	11	pharmaceutical	pharmaceutical	NOUN
brj-22095	13	12	,	,	PUNCT
brj-22095	13	13	food	food	NOUN
brj-22095	13	14	,	,	PUNCT
brj-22095	13	15	petrochemical	petrochemical	NOUN
brj-22095	13	16	,	,	PUNCT
brj-22095	13	17	agricultural	agricultural	ADJ
brj-22095	13	18	products	product	NOUN
brj-22095	13	19	,	,	PUNCT
brj-22095	13	20	feed	feed	NOUN
brj-22095	13	21	,	,	PUNCT
brj-22095	13	22	tobacco	tobacco	NOUN
brj-22095	13	23	,	,	PUNCT
brj-22095	13	24	and	and	CCONJ
brj-22095	13	25	other	other	ADJ
brj-22095	13	26	industries	industry	NOUN
brj-22095	13	27	because	because	SCONJ
brj-22095	13	28	it	it	PRON
brj-22095	13	29	does	do	AUX
brj-22095	13	30	not	not	PART
brj-22095	13	31	require	require	VERB
brj-22095	13	32	chemical	chemical	ADJ
brj-22095	13	33	methods	method	NOUN
brj-22095	13	34	for	for	ADP
brj-22095	13	35	sample	sample	NOUN
brj-22095	13	36	pre	pre	NOUN
brj-22095	13	37	-	-	NOUN
brj-22095	13	38	treatment	treatment	NOUN
brj-22095	13	39	and	and	CCONJ
brj-22095	13	40	has	have	VERB
brj-22095	13	41	the	the	DET
brj-22095	13	42	advantages	advantage	NOUN
brj-22095	13	43	of	of	ADP
brj-22095	13	44	being	be	AUX
brj-22095	13	45	green	green	ADJ
brj-22095	13	46	,	,	PUNCT
brj-22095	13	47	efficient	efficient	ADJ
brj-22095	13	48	,	,	PUNCT
brj-22095	13	49	non	non	ADJ
brj-22095	13	50	-	-	ADJ
brj-22095	13	51	destructive	destructive	ADJ
brj-22095	13	52	,	,	PUNCT
brj-22095	13	53	and	and	CCONJ
brj-22095	13	54	easy	easy	ADJ
brj-22095	13	55	to	to	PART
brj-22095	13	56	implement	implement	VERB
brj-22095	13	57	for	for	ADP
brj-22095	13	58	online	online	ADJ
brj-22095	13	59	use	use	NOUN
brj-22095	13	60	(	(	PUNCT
brj-22095	13	61	pažitný	pažitný	NOUN
brj-22095	13	62	et	et	PROPN
brj-22095	13	63	al	al	PROPN
brj-22095	13	64	.	.	PROPN
brj-22095	13	65	2011	2011	NUM
brj-22095	13	66	;	;	PUNCT
brj-22095	13	67	yu	yu	PROPN
brj-22095	13	68	et	et	PROPN
brj-22095	13	69	al	al	PROPN
brj-22095	13	70	.	.	PROPN
brj-22095	13	71	2021	2021	NUM
brj-22095	13	72	;	;	PUNCT
brj-22095	13	73	cao	cao	PROPN
brj-22095	13	74	et	et	PROPN
brj-22095	13	75	al	al	PROPN
brj-22095	13	76	.	.	PROPN
brj-22095	13	77	2022	2022	NUM
brj-22095	13	78	)	)	PUNCT
brj-22095	13	79	.	.	PUNCT
brj-22095	14	1	however	however	ADV
brj-22095	14	2	,	,	PUNCT
brj-22095	14	3	in	in	ADP
brj-22095	14	4	the	the	DET
brj-22095	14	5	practical	practical	ADJ
brj-22095	14	6	application	application	NOUN
brj-22095	14	7	of	of	ADP
brj-22095	14	8	spectroscopic	spectroscopic	ADJ
brj-22095	14	9	measurements	measurement	NOUN
brj-22095	14	10	,	,	PUNCT
brj-22095	14	11	a	a	DET
brj-22095	14	12	model	model	NOUN
brj-22095	14	13	built	build	VERB
brj-22095	14	14	on	on	ADP
brj-22095	14	15	one	one	NUM
brj-22095	14	16	instrument	instrument	NOUN
brj-22095	14	17	(	(	PUNCT
brj-22095	14	18	master	master	NOUN
brj-22095	14	19	instrument	instrument	NOUN
brj-22095	14	20	)	)	PUNCT
brj-22095	14	21	is	be	AUX
brj-22095	14	22	applied	apply	VERB
brj-22095	14	23	to	to	ADP
brj-22095	14	24	another	another	DET
brj-22095	14	25	instrument	instrument	NOUN
brj-22095	14	26	(	(	PUNCT
brj-22095	14	27	target	target	NOUN
brj-22095	14	28	instrument	instrument	NOUN
brj-22095	14	29	)	)	PUNCT
brj-22095	14	30	with	with	ADP
brj-22095	14	31	a	a	DET
brj-22095	14	32	large	large	ADJ
brj-22095	14	33	deviation	deviation	NOUN
brj-22095	14	34	or	or	CCONJ
brj-22095	14	35	even	even	ADV
brj-22095	14	36	unusable	unusable	ADJ
brj-22095	14	37	problem	problem	NOUN
brj-22095	14	38	.	.	PUNCT
brj-22095	15	1	such	such	ADJ
brj-22095	15	2	problems	problem	NOUN
brj-22095	15	3	are	be	AUX
brj-22095	15	4	generally	generally	ADV
brj-22095	15	5	referred	refer	VERB
brj-22095	15	6	to	to	ADP
brj-22095	15	7	as	as	ADP
brj-22095	15	8	model	model	NOUN
brj-22095	15	9	peer	peer	NOUN
brj-22095	15	10	-	-	PUNCT
brj-22095	15	11	reviewed	review	VERB
brj-22095	15	12	article	article	NOUN
brj-22095	15	13	bioresources.com	bioresources.com	X
brj-22095	15	14	he	he	PRON
brj-22095	15	15	et	et	PROPN
brj-22095	15	16	al	al	PROPN
brj-22095	15	17	.	.	PROPN
brj-22095	16	1	(	(	PUNCT
brj-22095	16	2	2022	2022	NUM
brj-22095	16	3	)	)	PUNCT
brj-22095	16	4	.	.	PUNCT
brj-22095	17	1	“	"	PUNCT
brj-22095	17	2	near	near	ADP
brj-22095	17	3	ir	ir	PROPN
brj-22095	17	4	model	model	NOUN
brj-22095	17	5	of	of	ADP
brj-22095	17	6	biomass	biomass	NOUN
brj-22095	17	7	,	,	PUNCT
brj-22095	17	8	”	"	PUNCT
brj-22095	17	9	bioresources	bioresource	NOUN
brj-22095	17	10	17(4	17(4	NUM
brj-22095	17	11	)	)	PUNCT
brj-22095	17	12	,	,	PUNCT
brj-22095	17	13	6476	6476	NUM
brj-22095	17	14	-	-	SYM
brj-22095	17	15	6489	6489	NUM
brj-22095	17	16	.	.	PUNCT
brj-22095	18	1	6477	6477	NUM
brj-22095	18	2	failure	failure	NOUN
brj-22095	18	3	problems	problem	NOUN
brj-22095	18	4	,	,	PUNCT
brj-22095	18	5	and	and	CCONJ
brj-22095	18	6	model	model	NOUN
brj-22095	18	7	transfer	transfer	NOUN
brj-22095	18	8	methods	method	NOUN
brj-22095	18	9	are	be	AUX
brj-22095	18	10	generally	generally	ADV
brj-22095	18	11	used	use	VERB
brj-22095	18	12	to	to	PART
brj-22095	18	13	solve	solve	VERB
brj-22095	18	14	such	such	ADJ
brj-22095	18	15	problems	problem	NOUN
brj-22095	18	16	.	.	PUNCT
brj-22095	19	1	model	model	NOUN
brj-22095	19	2	transfer	transfer	NOUN
brj-22095	19	3	can	can	AUX
brj-22095	19	4	effectively	effectively	ADV
brj-22095	19	5	avoid	avoid	VERB
brj-22095	19	6	duplicate	duplicate	NOUN
brj-22095	19	7	modeling	modeling	NOUN
brj-22095	19	8	and	and	CCONJ
brj-22095	19	9	realize	realize	VERB
brj-22095	19	10	the	the	DET
brj-22095	19	11	sharing	sharing	NOUN
brj-22095	19	12	of	of	ADP
brj-22095	19	13	sample	sample	NOUN
brj-22095	19	14	and	and	CCONJ
brj-22095	19	15	data	datum	NOUN
brj-22095	19	16	resources	resource	NOUN
brj-22095	19	17	;	;	PUNCT
brj-22095	19	18	it	it	PRON
brj-22095	19	19	is	be	AUX
brj-22095	19	20	important	important	ADJ
brj-22095	19	21	for	for	ADP
brj-22095	19	22	the	the	DET
brj-22095	19	23	promotion	promotion	NOUN
brj-22095	19	24	of	of	ADP
brj-22095	19	25	nir	nir	ADJ
brj-22095	19	26	spectroscopy	spectroscopy	NOUN
brj-22095	19	27	applications	application	NOUN
brj-22095	19	28	(	(	PUNCT
brj-22095	19	29	wang	wang	PROPN
brj-22095	19	30	et	et	PROPN
brj-22095	19	31	al	al	PROPN
brj-22095	19	32	.	.	PROPN
brj-22095	19	33	2019	2019	NUM
brj-22095	19	34	;	;	PUNCT
brj-22095	19	35	feudale	feudale	NOUN
brj-22095	19	36	et	et	PROPN
brj-22095	19	37	al	al	PROPN
brj-22095	19	38	.	.	PROPN
brj-22095	19	39	2002	2002	NUM
brj-22095	19	40	)	)	PUNCT
brj-22095	19	41	.	.	PUNCT
brj-22095	20	1	the	the	DET
brj-22095	20	2	model	model	NOUN
brj-22095	20	3	transfer	transfer	NOUN
brj-22095	20	4	algorithm	algorithm	NOUN
brj-22095	20	5	used	use	VERB
brj-22095	20	6	can	can	AUX
brj-22095	20	7	be	be	AUX
brj-22095	20	8	divided	divide	VERB
brj-22095	20	9	into	into	ADP
brj-22095	20	10	methods	method	NOUN
brj-22095	20	11	with	with	ADP
brj-22095	20	12	standard	standard	ADJ
brj-22095	20	13	samples	sample	NOUN
brj-22095	20	14	and	and	CCONJ
brj-22095	20	15	methods	method	NOUN
brj-22095	20	16	without	without	ADP
brj-22095	20	17	standard	standard	ADJ
brj-22095	20	18	samples	sample	NOUN
brj-22095	20	19	according	accord	VERB
brj-22095	20	20	to	to	ADP
brj-22095	20	21	whether	whether	SCONJ
brj-22095	20	22	one	one	NUM
brj-22095	20	23	-	-	PUNCT
brj-22095	20	24	to	to	ADP
brj-22095	20	25	-	-	PUNCT
brj-22095	20	26	one	one	NUM
brj-22095	20	27	correspondence	correspondence	NOUN
brj-22095	20	28	of	of	ADP
brj-22095	20	29	standard	standard	ADJ
brj-22095	20	30	spectra	spectra	NOUN
brj-22095	20	31	should	should	AUX
brj-22095	20	32	be	be	AUX
brj-22095	20	33	collected	collect	VERB
brj-22095	20	34	on	on	ADP
brj-22095	20	35	all	all	DET
brj-22095	20	36	instruments	instrument	NOUN
brj-22095	20	37	(	(	PUNCT
brj-22095	20	38	zhang	zhang	X
brj-22095	20	39	et	et	PROPN
brj-22095	20	40	al	al	PROPN
brj-22095	20	41	.	.	PROPN
brj-22095	20	42	2020	2020	NUM
brj-22095	20	43	)	)	PUNCT
brj-22095	20	44	.	.	PUNCT
brj-22095	21	1	the	the	DET
brj-22095	21	2	model	model	NOUN
brj-22095	21	3	transfer	transfer	NOUN
brj-22095	21	4	algorithm	algorithm	NOUN
brj-22095	21	5	with	with	ADP
brj-22095	21	6	standard	standard	ADJ
brj-22095	21	7	samples	sample	NOUN
brj-22095	21	8	must	must	AUX
brj-22095	21	9	take	take	VERB
brj-22095	21	10	a	a	DET
brj-22095	21	11	certain	certain	ADJ
brj-22095	21	12	number	number	NOUN
brj-22095	21	13	of	of	ADP
brj-22095	21	14	samples	sample	NOUN
brj-22095	21	15	to	to	PART
brj-22095	21	16	form	form	VERB
brj-22095	21	17	a	a	DET
brj-22095	21	18	standard	standard	ADJ
brj-22095	21	19	sample	sample	NOUN
brj-22095	21	20	set	set	NOUN
brj-22095	21	21	,	,	PUNCT
brj-22095	21	22	such	such	ADJ
brj-22095	21	23	as	as	ADP
brj-22095	21	24	slope	slope	NOUN
brj-22095	21	25	/	/	SYM
brj-22095	21	26	bias	bias	NOUN
brj-22095	21	27	(	(	PUNCT
brj-22095	21	28	s	s	NOUN
brj-22095	21	29	/	/	SYM
brj-22095	21	30	b	b	NOUN
brj-22095	21	31	)	)	PUNCT
brj-22095	21	32	(	(	PUNCT
brj-22095	21	33	du	du	PROPN
brj-22095	21	34	et	et	PROPN
brj-22095	21	35	al	al	PROPN
brj-22095	21	36	.	.	PROPN
brj-22095	21	37	2011	2011	NUM
brj-22095	21	38	;	;	PUNCT
brj-22095	21	39	zhao	zhao	PROPN
brj-22095	21	40	et	et	PROPN
brj-22095	21	41	al	al	PROPN
brj-22095	21	42	.	.	PROPN
brj-22095	21	43	2019	2019	NUM
brj-22095	21	44	)	)	PUNCT
brj-22095	21	45	,	,	PUNCT
brj-22095	21	46	direct	direct	ADJ
brj-22095	21	47	standardization	standardization	NOUN
brj-22095	21	48	(	(	PUNCT
brj-22095	21	49	ds	ds	NOUN
brj-22095	21	50	)	)	PUNCT
brj-22095	21	51	(	(	PUNCT
brj-22095	21	52	parrott	parrott	PROPN
brj-22095	21	53	et	et	PROPN
brj-22095	21	54	al	al	PROPN
brj-22095	21	55	.	.	PROPN
brj-22095	21	56	2022	2022	NUM
brj-22095	21	57	)	)	PUNCT
brj-22095	21	58	and	and	CCONJ
brj-22095	21	59	piecewise	piecewise	VERB
brj-22095	21	60	direct	direct	ADJ
brj-22095	21	61	standardization	standardization	NOUN
brj-22095	21	62	(	(	PUNCT
brj-22095	21	63	pds	pds	NOUN
brj-22095	21	64	)	)	PUNCT
brj-22095	21	65	(	(	PUNCT
brj-22095	21	66	bergman	bergman	PROPN
brj-22095	21	67	et	et	PROPN
brj-22095	21	68	al	al	PROPN
brj-22095	21	69	.	.	PROPN
brj-22095	21	70	2006	2006	NUM
brj-22095	21	71	;	;	PUNCT
brj-22095	21	72	peng	peng	PROPN
brj-22095	21	73	et	et	PROPN
brj-22095	21	74	al	al	PROPN
brj-22095	21	75	.	.	PROPN
brj-22095	21	76	2011	2011	NUM
brj-22095	21	77	)	)	PUNCT
brj-22095	21	78	.	.	PUNCT
brj-22095	22	1	commonly	commonly	ADV
brj-22095	22	2	used	use	VERB
brj-22095	22	3	model	model	NOUN
brj-22095	22	4	transfer	transfer	NOUN
brj-22095	22	5	methods	method	NOUN
brj-22095	22	6	without	without	ADP
brj-22095	22	7	standards	standard	NOUN
brj-22095	22	8	include	include	VERB
brj-22095	22	9	signal	signal	ADJ
brj-22095	22	10	processing	processing	NOUN
brj-22095	22	11	methods	method	NOUN
brj-22095	22	12	,	,	PUNCT
brj-22095	22	13	such	such	ADJ
brj-22095	22	14	as	as	ADP
brj-22095	22	15	wavelet	wavelet	NOUN
brj-22095	22	16	transform	transform	NOUN
brj-22095	22	17	(	(	PUNCT
brj-22095	22	18	wt	wt	NOUN
brj-22095	22	19	)	)	PUNCT
brj-22095	22	20	(	(	PUNCT
brj-22095	23	1	bin	bin	NOUN
brj-22095	23	2	et	et	PROPN
brj-22095	23	3	al	al	PROPN
brj-22095	23	4	.	.	PROPN
brj-22095	23	5	2017	2017	NUM
brj-22095	23	6	;	;	PUNCT
brj-22095	23	7	abasi	abasi	NOUN
brj-22095	23	8	et	et	PROPN
brj-22095	23	9	al	al	PROPN
brj-22095	23	10	.	.	PROPN
brj-22095	23	11	2019	2019	NUM
brj-22095	23	12	)	)	PUNCT
brj-22095	23	13	,	,	PUNCT
brj-22095	23	14	orthogonal	orthogonal	ADJ
brj-22095	23	15	projection	projection	NOUN
brj-22095	23	16	(	(	PUNCT
brj-22095	23	17	poerio	poerio	NOUN
brj-22095	23	18	and	and	CCONJ
brj-22095	23	19	brown	brown	ADJ
brj-22095	23	20	2018	2018	NUM
brj-22095	23	21	)	)	PUNCT
brj-22095	23	22	,	,	PUNCT
brj-22095	23	23	and	and	CCONJ
brj-22095	23	24	linear	linear	ADJ
brj-22095	23	25	model	model	NOUN
brj-22095	23	26	correction	correction	NOUN
brj-22095	23	27	(	(	PUNCT
brj-22095	23	28	liu	liu	PROPN
brj-22095	23	29	et	et	PROPN
brj-22095	23	30	al	al	PROPN
brj-22095	23	31	.	.	PROPN
brj-22095	23	32	2016	2016	NUM
brj-22095	23	33	)	)	PUNCT
brj-22095	23	34	.	.	PUNCT
brj-22095	24	1	ni	ni	PROPN
brj-22095	24	2	et	et	PROPN
brj-22095	24	3	al	al	PROPN
brj-22095	24	4	.	.	PROPN
brj-22095	25	1	(	(	PUNCT
brj-22095	25	2	2019	2019	NUM
brj-22095	25	3	)	)	PUNCT
brj-22095	25	4	proposed	propose	VERB
brj-22095	25	5	a	a	DET
brj-22095	25	6	nir	nir	ADJ
brj-22095	25	7	model	model	NOUN
brj-22095	25	8	transfer	transfer	NOUN
brj-22095	25	9	method	method	NOUN
brj-22095	25	10	without	without	ADP
brj-22095	25	11	standards	standard	NOUN
brj-22095	25	12	based	base	VERB
brj-22095	25	13	on	on	ADP
brj-22095	25	14	the	the	DET
brj-22095	25	15	wavelength	wavelength	NOUN
brj-22095	25	16	of	of	ADP
brj-22095	25	17	stable	stable	ADJ
brj-22095	25	18	consistent	consistent	ADJ
brj-22095	25	19	spectral	spectral	ADJ
brj-22095	25	20	signal	signal	NOUN
brj-22095	25	21	(	(	PUNCT
brj-22095	25	22	swcss	swcss	PROPN
brj-22095	25	23	)	)	PUNCT
brj-22095	25	24	by	by	ADP
brj-22095	25	25	screening	screen	VERB
brj-22095	25	26	out	out	ADP
brj-22095	25	27	the	the	DET
brj-22095	25	28	wavelengths	wavelength	NOUN
brj-22095	25	29	with	with	ADP
brj-22095	25	30	stable	stable	ADJ
brj-22095	25	31	consistent	consistent	ADJ
brj-22095	25	32	spectral	spectral	ADJ
brj-22095	25	33	signal	signal	NOUN
brj-22095	25	34	between	between	ADP
brj-22095	25	35	instruments	instrument	NOUN
brj-22095	25	36	and	and	CCONJ
brj-22095	25	37	establishing	establish	VERB
brj-22095	25	38	a	a	DET
brj-22095	25	39	correction	correction	NOUN
brj-22095	25	40	model	model	NOUN
brj-22095	25	41	for	for	ADP
brj-22095	25	42	model	model	NOUN
brj-22095	25	43	transfer	transfer	NOUN
brj-22095	25	44	.	.	PUNCT
brj-22095	26	1	such	such	DET
brj-22095	26	2	an	an	DET
brj-22095	26	3	approach	approach	NOUN
brj-22095	26	4	is	be	AUX
brj-22095	26	5	better	well	ADJ
brj-22095	26	6	for	for	ADP
brj-22095	26	7	model	model	NOUN
brj-22095	26	8	transfer	transfer	NOUN
brj-22095	26	9	prediction	prediction	NOUN
brj-22095	26	10	between	between	ADP
brj-22095	26	11	spectrometers	spectrometer	NOUN
brj-22095	26	12	of	of	ADP
brj-22095	26	13	the	the	DET
brj-22095	26	14	same	same	ADJ
brj-22095	26	15	type	type	NOUN
brj-22095	26	16	and	and	CCONJ
brj-22095	26	17	with	with	ADP
brj-22095	26	18	small	small	ADJ
brj-22095	26	19	differences	difference	NOUN
brj-22095	26	20	,	,	PUNCT
brj-22095	26	21	but	but	CCONJ
brj-22095	26	22	it	it	PRON
brj-22095	26	23	is	be	AUX
brj-22095	26	24	not	not	PART
brj-22095	26	25	suitable	suitable	ADJ
brj-22095	26	26	for	for	ADP
brj-22095	26	27	model	model	NOUN
brj-22095	26	28	transfer	transfer	NOUN
brj-22095	26	29	between	between	ADP
brj-22095	26	30	different	different	ADJ
brj-22095	26	31	types	type	NOUN
brj-22095	26	32	of	of	ADP
brj-22095	26	33	spectrometers	spectrometer	NOUN
brj-22095	26	34	because	because	SCONJ
brj-22095	26	35	it	it	PRON
brj-22095	26	36	does	do	AUX
brj-22095	26	37	not	not	PART
brj-22095	26	38	use	use	VERB
brj-22095	26	39	transformation	transformation	NOUN
brj-22095	26	40	sets	set	NOUN
brj-22095	26	41	for	for	ADP
brj-22095	26	42	spectrum	spectrum	NOUN
brj-22095	26	43	or	or	CCONJ
brj-22095	26	44	model	model	NOUN
brj-22095	26	45	correction	correction	NOUN
brj-22095	26	46	.	.	PUNCT
brj-22095	27	1	li	li	PROPN
brj-22095	27	2	et	et	PROPN
brj-22095	27	3	al	al	PROPN
brj-22095	27	4	.	.	PROPN
brj-22095	28	1	(	(	PUNCT
brj-22095	28	2	2018	2018	NUM
brj-22095	28	3	)	)	PUNCT
brj-22095	28	4	conducted	conduct	VERB
brj-22095	28	5	a	a	DET
brj-22095	28	6	model	model	NOUN
brj-22095	28	7	transfer	transfer	NOUN
brj-22095	28	8	study	study	NOUN
brj-22095	28	9	for	for	ADP
brj-22095	28	10	two	two	NUM
brj-22095	28	11	indexes	index	NOUN
brj-22095	28	12	of	of	ADP
brj-22095	28	13	edible	edible	ADJ
brj-22095	28	14	oil	oil	NOUN
brj-22095	28	15	,	,	PUNCT
brj-22095	28	16	acid	acid	NOUN
brj-22095	28	17	value	value	NOUN
brj-22095	28	18	and	and	CCONJ
brj-22095	28	19	peroxide	peroxide	NOUN
brj-22095	28	20	value	value	NOUN
brj-22095	28	21	,	,	PUNCT
brj-22095	28	22	using	use	VERB
brj-22095	28	23	the	the	DET
brj-22095	28	24	s	s	PROPN
brj-22095	28	25	/	/	SYM
brj-22095	28	26	b	b	NOUN
brj-22095	28	27	algorithm	algorithm	NOUN
brj-22095	28	28	combined	combine	VERB
brj-22095	28	29	with	with	ADP
brj-22095	28	30	partial	partial	ADJ
brj-22095	28	31	least	least	ADJ
brj-22095	28	32	square	square	ADJ
brj-22095	28	33	regression	regression	NOUN
brj-22095	28	34	(	(	PUNCT
brj-22095	28	35	plsr	plsr	PROPN
brj-22095	28	36	)	)	PUNCT
brj-22095	28	37	model	model	NOUN
brj-22095	28	38	established	establish	VERB
brj-22095	28	39	on	on	ADP
brj-22095	28	40	a	a	DET
brj-22095	28	41	master	master	NOUN
brj-22095	28	42	spectroscopy	spectroscopy	NOUN
brj-22095	28	43	instrument	instrument	NOUN
brj-22095	28	44	.	.	PUNCT
brj-22095	29	1	the	the	DET
brj-22095	29	2	results	result	NOUN
brj-22095	29	3	show	show	VERB
brj-22095	29	4	that	that	SCONJ
brj-22095	29	5	the	the	DET
brj-22095	29	6	model	model	NOUN
brj-22095	29	7	prediction	prediction	NOUN
brj-22095	29	8	results	result	NOUN
brj-22095	29	9	were	be	AUX
brj-22095	29	10	improved	improve	VERB
brj-22095	29	11	to	to	ADP
brj-22095	29	12	different	different	ADJ
brj-22095	29	13	degrees	degree	NOUN
brj-22095	29	14	after	after	ADP
brj-22095	29	15	the	the	DET
brj-22095	29	16	s	s	PROPN
brj-22095	29	17	/	/	SYM
brj-22095	29	18	b	b	NOUN
brj-22095	29	19	algorithm	algorithm	NOUN
brj-22095	29	20	transfer	transfer	NOUN
brj-22095	29	21	,	,	PUNCT
brj-22095	29	22	but	but	CCONJ
brj-22095	29	23	the	the	DET
brj-22095	29	24	model	model	NOUN
brj-22095	29	25	prediction	prediction	NOUN
brj-22095	29	26	results	result	VERB
brj-22095	29	27	after	after	SCONJ
brj-22095	29	28	the	the	DET
brj-22095	29	29	s	s	PROPN
brj-22095	29	30	/	/	SYM
brj-22095	29	31	b	b	NOUN
brj-22095	29	32	algorithm	algorithm	NOUN
brj-22095	29	33	transfer	transfer	NOUN
brj-22095	29	34	still	still	ADV
brj-22095	29	35	had	have	VERB
brj-22095	29	36	a	a	DET
brj-22095	29	37	big	big	ADJ
brj-22095	29	38	gap	gap	NOUN
brj-22095	29	39	with	with	ADP
brj-22095	29	40	the	the	DET
brj-22095	29	41	ideal	ideal	ADJ
brj-22095	29	42	results	result	NOUN
brj-22095	29	43	.	.	PUNCT
brj-22095	30	1	in	in	ADP
brj-22095	30	2	previous	previous	ADJ
brj-22095	30	3	studies	study	NOUN
brj-22095	30	4	(	(	PUNCT
brj-22095	30	5	liu	liu	PROPN
brj-22095	30	6	et	et	PROPN
brj-22095	30	7	al	al	PROPN
brj-22095	30	8	.	.	PROPN
brj-22095	30	9	2019a	2019a	NUM
brj-22095	30	10	,	,	PUNCT
brj-22095	30	11	b	b	NOUN
brj-22095	30	12	)	)	PUNCT
brj-22095	30	13	,	,	PUNCT
brj-22095	30	14	the	the	DET
brj-22095	30	15	s	s	PROPN
brj-22095	30	16	/	/	SYM
brj-22095	30	17	b	b	PROPN
brj-22095	30	18	method	method	NOUN
brj-22095	30	19	was	be	AUX
brj-22095	30	20	applied	apply	VERB
brj-22095	30	21	to	to	ADP
brj-22095	30	22	the	the	DET
brj-22095	30	23	transfer	transfer	NOUN
brj-22095	30	24	of	of	ADP
brj-22095	30	25	pulp	pulp	NOUN
brj-22095	30	26	wood	wood	NOUN
brj-22095	30	27	lignin	lignin	NOUN
brj-22095	30	28	nir	nir	NOUN
brj-22095	30	29	spectroscopy	spectroscopy	NOUN
brj-22095	30	30	models	model	NOUN
brj-22095	30	31	between	between	ADP
brj-22095	30	32	two	two	NUM
brj-22095	30	33	different	different	ADJ
brj-22095	30	34	types	type	NOUN
brj-22095	30	35	of	of	ADP
brj-22095	30	36	convenient	convenient	ADJ
brj-22095	30	37	nir	nir	ADJ
brj-22095	30	38	spectrometers	spectrometer	NOUN
brj-22095	30	39	,	,	PUNCT
brj-22095	30	40	and	and	CCONJ
brj-22095	30	41	the	the	DET
brj-22095	30	42	model	model	NOUN
brj-22095	30	43	transfer	transfer	NOUN
brj-22095	30	44	effects	effect	NOUN
brj-22095	30	45	of	of	ADP
brj-22095	30	46	the	the	DET
brj-22095	30	47	s	s	PROPN
brj-22095	30	48	/	/	SYM
brj-22095	30	49	b	b	NOUN
brj-22095	30	50	,	,	PUNCT
brj-22095	30	51	ds	ds	ADJ
brj-22095	30	52	and	and	CCONJ
brj-22095	30	53	canonical	canonical	ADJ
brj-22095	30	54	correlation	correlation	NOUN
brj-22095	30	55	analysis	analysis	NOUN
brj-22095	30	56	(	(	PUNCT
brj-22095	30	57	cca	cca	NOUN
brj-22095	30	58	)	)	PUNCT
brj-22095	30	59	algorithms	algorithm	NOUN
brj-22095	30	60	(	(	PUNCT
brj-22095	30	61	li	li	PROPN
brj-22095	30	62	et	et	PROPN
brj-22095	30	63	al	al	PROPN
brj-22095	30	64	.	.	PROPN
brj-22095	30	65	2022	2022	NUM
brj-22095	30	66	)	)	PUNCT
brj-22095	30	67	were	be	AUX
brj-22095	30	68	compared	compare	VERB
brj-22095	30	69	.	.	PUNCT
brj-22095	31	1	the	the	DET
brj-22095	31	2	s	s	PROPN
brj-22095	31	3	/	/	SYM
brj-22095	31	4	b	b	NOUN
brj-22095	31	5	algorithm	algorithm	NOUN
brj-22095	31	6	based	base	VERB
brj-22095	31	7	on	on	ADP
brj-22095	31	8	linear	linear	ADJ
brj-22095	31	9	correction	correction	NOUN
brj-22095	31	10	among	among	ADP
brj-22095	31	11	these	these	DET
brj-22095	31	12	three	three	NUM
brj-22095	31	13	algorithms	algorithm	NOUN
brj-22095	31	14	could	could	AUX
brj-22095	31	15	not	not	PART
brj-22095	31	16	obtain	obtain	VERB
brj-22095	31	17	the	the	DET
brj-22095	31	18	model	model	NOUN
brj-22095	31	19	transfer	transfer	NOUN
brj-22095	31	20	effect	effect	NOUN
brj-22095	31	21	to	to	PART
brj-22095	31	22	meet	meet	VERB
brj-22095	31	23	the	the	DET
brj-22095	31	24	accuracy	accuracy	NOUN
brj-22095	31	25	requirements	requirement	NOUN
brj-22095	31	26	.	.	PUNCT
brj-22095	32	1	the	the	DET
brj-22095	32	2	applicability	applicability	NOUN
brj-22095	32	3	is	be	AUX
brj-22095	32	4	low	low	ADJ
brj-22095	32	5	when	when	SCONJ
brj-22095	32	6	using	use	VERB
brj-22095	32	7	swcss	swcss	PROPN
brj-22095	32	8	and	and	CCONJ
brj-22095	32	9	s	s	PROPN
brj-22095	32	10	/	/	SYM
brj-22095	32	11	b	b	NOUN
brj-22095	32	12	algorithms	algorithm	NOUN
brj-22095	32	13	alone	alone	ADV
brj-22095	32	14	for	for	ADP
brj-22095	32	15	model	model	NOUN
brj-22095	32	16	transfer	transfer	NOUN
brj-22095	32	17	,	,	PUNCT
brj-22095	32	18	and	and	CCONJ
brj-22095	32	19	the	the	DET
brj-22095	32	20	model	model	NOUN
brj-22095	32	21	transfer	transfer	NOUN
brj-22095	32	22	between	between	ADP
brj-22095	32	23	spectrometers	spectrometer	NOUN
brj-22095	32	24	with	with	ADP
brj-22095	32	25	large	large	ADJ
brj-22095	32	26	differences	difference	NOUN
brj-22095	32	27	is	be	AUX
brj-22095	32	28	poor	poor	ADJ
brj-22095	32	29	.	.	PUNCT
brj-22095	33	1	in	in	ADP
brj-22095	33	2	the	the	DET
brj-22095	33	3	present	present	ADJ
brj-22095	33	4	study	study	NOUN
brj-22095	33	5	,	,	PUNCT
brj-22095	33	6	a	a	DET
brj-22095	33	7	model	model	NOUN
brj-22095	33	8	transfer	transfer	NOUN
brj-22095	33	9	method	method	NOUN
brj-22095	33	10	of	of	ADP
brj-22095	33	11	swcss	swcss	PROPN
brj-22095	33	12	combined	combine	VERB
brj-22095	33	13	with	with	ADP
brj-22095	33	14	s	s	PROPN
brj-22095	33	15	/	/	SYM
brj-22095	33	16	b	b	NOUN
brj-22095	33	17	algorithm	algorithm	NOUN
brj-22095	33	18	is	be	AUX
brj-22095	33	19	proposed	propose	VERB
brj-22095	33	20	.	.	PUNCT
brj-22095	34	1	the	the	DET
brj-22095	34	2	method	method	NOUN
brj-22095	34	3	reduces	reduce	VERB
brj-22095	34	4	the	the	DET
brj-22095	34	5	differences	difference	NOUN
brj-22095	34	6	between	between	ADP
brj-22095	34	7	different	different	ADJ
brj-22095	34	8	nir	nir	ADJ
brj-22095	34	9	spectrometers	spectrometer	NOUN
brj-22095	34	10	by	by	ADP
brj-22095	34	11	screening	screen	VERB
brj-22095	34	12	out	out	ADP
brj-22095	34	13	the	the	DET
brj-22095	34	14	consistent	consistent	ADJ
brj-22095	34	15	wavelengths	wavelength	NOUN
brj-22095	34	16	with	with	ADP
brj-22095	34	17	small	small	ADJ
brj-22095	34	18	differences	difference	NOUN
brj-22095	34	19	between	between	ADP
brj-22095	34	20	instruments	instrument	NOUN
brj-22095	34	21	and	and	CCONJ
brj-22095	34	22	improves	improve	VERB
brj-22095	34	23	the	the	DET
brj-22095	34	24	transfer	transfer	NOUN
brj-22095	34	25	accuracy	accuracy	NOUN
brj-22095	34	26	and	and	CCONJ
brj-22095	34	27	applicability	applicability	NOUN
brj-22095	34	28	of	of	ADP
brj-22095	34	29	s	s	PROPN
brj-22095	34	30	/	/	SYM
brj-22095	34	31	b	b	NOUN
brj-22095	34	32	algorithm	algorithm	NOUN
brj-22095	34	33	,	,	PUNCT
brj-22095	34	34	which	which	PRON
brj-22095	34	35	makes	make	VERB
brj-22095	34	36	up	up	ADP
brj-22095	34	37	for	for	ADP
brj-22095	34	38	the	the	DET
brj-22095	34	39	shortcomings	shortcoming	NOUN
brj-22095	34	40	of	of	ADP
brj-22095	34	41	using	use	VERB
brj-22095	34	42	swcss	swcss	PROPN
brj-22095	34	43	and	and	CCONJ
brj-22095	34	44	s	s	PROPN
brj-22095	34	45	/	/	SYM
brj-22095	34	46	b	b	NOUN
brj-22095	34	47	algorithm	algorithm	NOUN
brj-22095	34	48	alone	alone	ADV
brj-22095	34	49	.	.	PUNCT
brj-22095	35	1	using	use	VERB
brj-22095	35	2	82	82	NUM
brj-22095	35	3	wood	wood	NOUN
brj-22095	35	4	flour	flour	NOUN
brj-22095	35	5	samples	sample	NOUN
brj-22095	35	6	,	,	PUNCT
brj-22095	35	7	the	the	DET
brj-22095	35	8	transfer	transfer	NOUN
brj-22095	35	9	effect	effect	NOUN
brj-22095	35	10	of	of	ADP
brj-22095	35	11	the	the	DET
brj-22095	35	12	holocellulose	holocellulose	ADJ
brj-22095	35	13	and	and	CCONJ
brj-22095	35	14	lignin	lignin	NOUN
brj-22095	35	15	content	content	NOUN
brj-22095	35	16	models	model	NOUN
brj-22095	35	17	based	base	VERB
brj-22095	35	18	on	on	ADP
brj-22095	35	19	the	the	DET
brj-22095	35	20	swcss	swcss	PROPN
brj-22095	35	21	-	-	PUNCT
brj-22095	35	22	s	s	PROPN
brj-22095	35	23	/	/	SYM
brj-22095	35	24	b	b	NOUN
brj-22095	35	25	method	method	NOUN
brj-22095	35	26	was	be	AUX
brj-22095	35	27	investigated	investigate	VERB
brj-22095	35	28	between	between	ADP
brj-22095	35	29	two	two	NUM
brj-22095	35	30	ias	ias	ADJ
brj-22095	35	31	nir	nir	ADJ
brj-22095	35	32	spectrometers	spectrometer	NOUN
brj-22095	35	33	of	of	ADP
brj-22095	35	34	different	different	ADJ
brj-22095	35	35	types	type	NOUN
brj-22095	35	36	;	;	PUNCT
brj-22095	35	37	it	it	PRON
brj-22095	35	38	was	be	AUX
brj-22095	35	39	compared	compare	VERB
brj-22095	35	40	with	with	ADP
brj-22095	35	41	the	the	DET
brj-22095	35	42	transfer	transfer	NOUN
brj-22095	35	43	effect	effect	NOUN
brj-22095	35	44	of	of	ADP
brj-22095	35	45	the	the	DET
brj-22095	35	46	swcss	swcss	PROPN
brj-22095	35	47	,	,	PUNCT
brj-22095	35	48	s	s	PROPN
brj-22095	35	49	/	/	SYM
brj-22095	35	50	b	b	NOUN
brj-22095	35	51	and	and	CCONJ
brj-22095	35	52	pds	pds	NOUN
brj-22095	35	53	and	and	CCONJ
brj-22095	35	54	ds	ds	ADJ
brj-22095	35	55	algorithms	algorithm	NOUN
brj-22095	35	56	alone	alone	ADV
brj-22095	35	57	.	.	PUNCT
brj-22095	36	1	the	the	DET
brj-22095	36	2	aim	aim	NOUN
brj-22095	36	3	was	be	AUX
brj-22095	36	4	to	to	PART
brj-22095	36	5	improve	improve	VERB
brj-22095	36	6	the	the	DET
brj-22095	36	7	robustness	robustness	NOUN
brj-22095	36	8	and	and	CCONJ
brj-22095	36	9	sharing	sharing	NOUN
brj-22095	36	10	of	of	ADP
brj-22095	36	11	nir	nir	ADJ
brj-22095	36	12	correction	correction	NOUN
brj-22095	36	13	models	model	NOUN
brj-22095	36	14	with	with	ADP
brj-22095	36	15	a	a	DET
brj-22095	36	16	view	view	NOUN
brj-22095	36	17	to	to	ADP
brj-22095	36	18	providing	provide	VERB
brj-22095	36	19	methodological	methodological	ADJ
brj-22095	36	20	references	reference	NOUN
brj-22095	36	21	for	for	ADP
brj-22095	36	22	the	the	DET
brj-22095	36	23	application	application	NOUN
brj-22095	36	24	of	of	ADP
brj-22095	36	25	nir	nir	ADJ
brj-22095	36	26	spectroscopy	spectroscopy	NOUN
brj-22095	36	27	detection	detection	NOUN
brj-22095	36	28	techniques	technique	NOUN
brj-22095	36	29	in	in	ADP
brj-22095	36	30	the	the	DET
brj-22095	36	31	determination	determination	NOUN
brj-22095	36	32	of	of	ADP
brj-22095	36	33	the	the	DET
brj-22095	36	34	integrated	integrate	VERB
brj-22095	36	35	holocellulose	holocellulose	ADJ
brj-22095	36	36	and	and	CCONJ
brj-22095	36	37	lignin	lignin	NOUN
brj-22095	36	38	contents	content	NOUN
brj-22095	36	39	of	of	ADP
brj-22095	36	40	pulpwood	pulpwood	NOUN
brj-22095	36	41	.	.	PUNCT
brj-22095	37	1	peer	peer	NOUN
brj-22095	37	2	-	-	PUNCT
brj-22095	37	3	reviewed	review	VERB
brj-22095	37	4	article	article	NOUN
brj-22095	37	5	bioresources.com	bioresources.com	X
brj-22095	37	6	he	he	PRON
brj-22095	37	7	et	et	PROPN
brj-22095	37	8	al	al	PROPN
brj-22095	37	9	.	.	PROPN
brj-22095	37	10	(	(	PUNCT
brj-22095	37	11	2022	2022	NUM
brj-22095	37	12	)	)	PUNCT
brj-22095	37	13	.	.	PUNCT
brj-22095	38	1	“	"	PUNCT
brj-22095	38	2	near	near	ADP
brj-22095	38	3	ir	ir	PROPN
brj-22095	38	4	model	model	NOUN
brj-22095	38	5	of	of	ADP
brj-22095	38	6	biomass	biomass	NOUN
brj-22095	38	7	,	,	PUNCT
brj-22095	38	8	”	"	PUNCT
brj-22095	38	9	bioresources	bioresource	NOUN
brj-22095	38	10	17(4	17(4	NUM
brj-22095	38	11	)	)	PUNCT
brj-22095	38	12	,	,	PUNCT
brj-22095	38	13	6476	6476	NUM
brj-22095	38	14	-	-	SYM
brj-22095	38	15	6489	6489	NUM
brj-22095	38	16	.	.	PUNCT
brj-22095	39	1	6478	6478	NUM
brj-22095	39	2	principle	principle	NOUN
brj-22095	39	3	and	and	CCONJ
brj-22095	39	4	algorithm	algorithm	NOUN
brj-22095	39	5	screening	screen	VERB
brj-22095	39	6	wavelengths	wavelength	NOUN
brj-22095	39	7	with	with	ADP
brj-22095	39	8	consistent	consistent	ADJ
brj-22095	39	9	and	and	CCONJ
brj-22095	39	10	stable	stable	ADJ
brj-22095	39	11	signals	signal	NOUN
brj-22095	39	12	the	the	DET
brj-22095	39	13	standard	standard	ADJ
brj-22095	39	14	deviations	deviation	NOUN
brj-22095	39	15	of	of	ADP
brj-22095	39	16	the	the	DET
brj-22095	39	17	following	follow	VERB
brj-22095	39	18	two	two	NUM
brj-22095	39	19	spectra	spectra	NOUN
brj-22095	39	20	were	be	AUX
brj-22095	39	21	calculated	calculate	VERB
brj-22095	39	22	based	base	VERB
brj-22095	39	23	on	on	ADP
brj-22095	39	24	the	the	DET
brj-22095	39	25	spectral	spectral	ADJ
brj-22095	39	26	information	information	NOUN
brj-22095	39	27	of	of	ADP
brj-22095	39	28	the	the	DET
brj-22095	39	29	sample	sample	NOUN
brj-22095	39	30	.	.	PUNCT
brj-22095	40	1	standard	standard	ADJ
brj-22095	40	2	deviation	deviation	NOUN
brj-22095	40	3	of	of	ADP
brj-22095	40	4	precision	precision	NOUN
brj-22095	40	5	detection	detection	NOUN
brj-22095	40	6	spectra	spectra	NOUN
brj-22095	40	7	the	the	DET
brj-22095	40	8	standard	standard	ADJ
brj-22095	40	9	deviation	deviation	NOUN
brj-22095	40	10	sdpds	sdpds	NOUN
brj-22095	40	11	of	of	ADP
brj-22095	40	12	the	the	DET
brj-22095	40	13	spectrum	spectrum	NOUN
brj-22095	40	14	of	of	ADP
brj-22095	40	15	the	the	DET
brj-22095	40	16	same	same	ADJ
brj-22095	40	17	sample	sample	NOUN
brj-22095	40	18	taken	take	VERB
brj-22095	40	19	n	n	PRON
brj-22095	40	20	times	time	NOUN
brj-22095	40	21	in	in	ADP
brj-22095	40	22	succession	succession	NOUN
brj-22095	40	23	on	on	ADP
brj-22095	40	24	the	the	DET
brj-22095	40	25	master	master	NOUN
brj-22095	40	26	spectrometer	spectrometer	NOUN
brj-22095	40	27	was	be	AUX
brj-22095	40	28	calculated	calculate	VERB
brj-22095	40	29	using	use	VERB
brj-22095	40	30	eq	eq	ADP
brj-22095	40	31	.	.	PROPN
brj-22095	40	32	1	1	NUM
brj-22095	40	33	,	,	PUNCT
brj-22095	40	34	(	(	PUNCT
brj-22095	40	35	)	)	PUNCT
brj-22095	40	36	2	2	NUM
brj-22095	40	37	1sdpds	1sdpds	NUM
brj-22095	40	38	(	(	PUNCT
brj-22095	40	39	)	)	PUNCT
brj-22095	40	40	1	1	NUM
brj-22095	40	41	n	n	NUM
brj-22095	40	42	ij	ij	INTJ
brj-22095	40	43	j	j	PROPN
brj-22095	41	1	i	i	INTJ
brj-22095	41	2	x	x	X
brj-22095	41	3	x	x	VERB
brj-22095	41	4	j	j	PROPN
brj-22095	41	5	n	n	NOUN
brj-22095	41	6	=	=	SYM
brj-22095	41	7	−	−	PROPN
brj-22095	41	8	=	=	SYM
brj-22095	41	9	−	−	PROPN
brj-22095	41	10			X
brj-22095	41	11	(	(	PUNCT
brj-22095	41	12	1	1	X
brj-22095	41	13	)	)	PUNCT
brj-22095	41	14	where	where	SCONJ
brj-22095	41	15	xij	xij	PRON
brj-22095	41	16	is	be	AUX
brj-22095	41	17	the	the	DET
brj-22095	41	18	spectral	spectral	ADJ
brj-22095	41	19	information	information	NOUN
brj-22095	41	20	of	of	ADP
brj-22095	41	21	the	the	DET
brj-22095	41	22	jth	jth	PROPN
brj-22095	41	23	wavelength	wavelength	NOUN
brj-22095	41	24	of	of	ADP
brj-22095	41	25	the	the	DET
brj-22095	41	26	measured	measured	ADJ
brj-22095	41	27	sample	sample	NOUN
brj-22095	41	28	at	at	ADP
brj-22095	41	29	the	the	DET
brj-22095	41	30	ith	ith	PROPN
brj-22095	41	31	acquisition	acquisition	NOUN
brj-22095	41	32	,	,	PUNCT
brj-22095	41	33	and	and	CCONJ
brj-22095	41	34	n	n	PRON
brj-22095	41	35	is	be	AUX
brj-22095	41	36	the	the	DET
brj-22095	41	37	number	number	NOUN
brj-22095	41	38	of	of	ADP
brj-22095	41	39	acquisitions	acquisition	NOUN
brj-22095	41	40	.	.	PUNCT
brj-22095	42	1	�	�	NOUN
brj-22095	42	2	̅	̅	NOUN
brj-22095	42	3	�	�	NOUN
brj-22095	42	4	j	j	PROPN
brj-22095	42	5	is	be	AUX
brj-22095	42	6	the	the	DET
brj-22095	42	7	average	average	ADJ
brj-22095	42	8	value	value	NOUN
brj-22095	42	9	of	of	ADP
brj-22095	42	10	the	the	DET
brj-22095	42	11	spectral	spectral	ADJ
brj-22095	42	12	information	information	NOUN
brj-22095	42	13	of	of	ADP
brj-22095	42	14	the	the	DET
brj-22095	42	15	jth	jth	PROPN
brj-22095	42	16	wavelength	wavelength	NOUN
brj-22095	42	17	.	.	PUNCT
brj-22095	43	1	sdpds	sdpds	PROPN
brj-22095	43	2	reflects	reflect	VERB
brj-22095	43	3	the	the	DET
brj-22095	43	4	size	size	NOUN
brj-22095	43	5	of	of	ADP
brj-22095	43	6	the	the	DET
brj-22095	43	7	variation	variation	NOUN
brj-22095	43	8	of	of	ADP
brj-22095	43	9	the	the	DET
brj-22095	43	10	instrument	instrument	NOUN
brj-22095	43	11	noise	noise	NOUN
brj-22095	43	12	and	and	CCONJ
brj-22095	43	13	measurement	measurement	NOUN
brj-22095	43	14	error	error	NOUN
brj-22095	43	15	within	within	ADP
brj-22095	43	16	a	a	DET
brj-22095	43	17	short	short	ADJ
brj-22095	43	18	period	period	NOUN
brj-22095	43	19	of	of	ADP
brj-22095	43	20	time	time	NOUN
brj-22095	43	21	.	.	PUNCT
brj-22095	44	1	the	the	DET
brj-22095	44	2	smaller	small	ADJ
brj-22095	44	3	the	the	DET
brj-22095	44	4	sdpds	sdpds	NOUN
brj-22095	44	5	,	,	PUNCT
brj-22095	44	6	indicates	indicate	VERB
brj-22095	44	7	a	a	DET
brj-22095	44	8	more	more	ADV
brj-22095	44	9	stable	stable	ADJ
brj-22095	44	10	spectral	spectral	ADJ
brj-22095	44	11	signal	signal	NOUN
brj-22095	44	12	of	of	ADP
brj-22095	44	13	that	that	DET
brj-22095	44	14	wavelength	wavelength	NOUN
brj-22095	44	15	.	.	PUNCT
brj-22095	45	1	standard	standard	ADJ
brj-22095	45	2	deviation	deviation	NOUN
brj-22095	45	3	of	of	ADP
brj-22095	45	4	difference	difference	NOUN
brj-22095	45	5	spectra	spectra	NOUN
brj-22095	45	6	between	between	ADP
brj-22095	45	7	master	master	NOUN
brj-22095	45	8	and	and	CCONJ
brj-22095	45	9	target	target	NOUN
brj-22095	45	10	instruments	instrument	NOUN
brj-22095	45	11	sddsi	sddsi	NOUN
brj-22095	45	12	reflects	reflect	VERB
brj-22095	45	13	the	the	DET
brj-22095	45	14	size	size	NOUN
brj-22095	45	15	of	of	ADP
brj-22095	45	16	the	the	DET
brj-22095	45	17	variation	variation	NOUN
brj-22095	45	18	of	of	ADP
brj-22095	45	19	the	the	DET
brj-22095	45	20	master	master	NOUN
brj-22095	45	21	and	and	CCONJ
brj-22095	45	22	target	target	NOUN
brj-22095	45	23	difference	difference	NOUN
brj-22095	45	24	spectra	spectra	NOUN
brj-22095	45	25	.	.	PUNCT
brj-22095	46	1	this	this	DET
brj-22095	46	2	quantity	quantity	NOUN
brj-22095	46	3	was	be	AUX
brj-22095	46	4	calculated	calculate	VERB
brj-22095	46	5	using	use	VERB
brj-22095	46	6	eq	eq	ADP
brj-22095	46	7	.	.	PROPN
brj-22095	46	8	2	2	NUM
brj-22095	46	9	,	,	PUNCT
brj-22095	46	10	(	(	PUNCT
brj-22095	46	11	)	)	PUNCT
brj-22095	46	12	2	2	NUM
brj-22095	46	13	1sddsi	1sddsi	NUM
brj-22095	46	14	(	(	PUNCT
brj-22095	46	15	)	)	PUNCT
brj-22095	46	16	1	1	NUM
brj-22095	46	17	m	m	NOUN
brj-22095	47	1	ij	ij	INTJ
brj-22095	48	1	j	j	PROPN
brj-22095	49	1	i	i	PRON
brj-22095	49	2	a	a	PRON
brj-22095	49	3	a	a	DET
brj-22095	49	4	j	j	NOUN
brj-22095	49	5	m	m	NOUN
brj-22095	49	6	=	=	SYM
brj-22095	50	1	−	−	PROPN
brj-22095	50	2	=	=	SYM
brj-22095	50	3	−	−	PROPN
brj-22095	50	4			X
brj-22095	50	5	(	(	PUNCT
brj-22095	50	6	2	2	NUM
brj-22095	50	7	)	)	PUNCT
brj-22095	50	8	where	where	SCONJ
brj-22095	50	9	m	m	NOUN
brj-22095	50	10	is	be	AUX
brj-22095	50	11	the	the	DET
brj-22095	50	12	number	number	NOUN
brj-22095	50	13	of	of	ADP
brj-22095	50	14	samples	sample	NOUN
brj-22095	50	15	,	,	PUNCT
brj-22095	50	16	mij	mij	NOUN
brj-22095	50	17	and	and	CCONJ
brj-22095	50	18	sij	sij	PROPN
brj-22095	50	19	are	be	AUX
brj-22095	50	20	the	the	DET
brj-22095	50	21	spectral	spectral	ADJ
brj-22095	50	22	response	response	NOUN
brj-22095	50	23	values	value	NOUN
brj-22095	50	24	of	of	ADP
brj-22095	50	25	sample	sample	NOUN
brj-22095	50	26	i	i	PRON
brj-22095	50	27	measured	measure	VERB
brj-22095	50	28	by	by	ADP
brj-22095	50	29	the	the	DET
brj-22095	50	30	master	master	NOUN
brj-22095	50	31	and	and	CCONJ
brj-22095	50	32	target	target	NOUN
brj-22095	50	33	at	at	ADP
brj-22095	50	34	wavelength	wavelength	PROPN
brj-22095	50	35	j	j	PROPN
brj-22095	50	36	,	,	PUNCT
brj-22095	50	37	separately	separately	ADV
brj-22095	50	38	,	,	PUNCT
brj-22095	50	39	and	and	CCONJ
brj-22095	50	40	aij	aij	PROPN
brj-22095	50	41	=	=	SYM
brj-22095	50	42	mij	mij	NOUN
brj-22095	50	43	-	-	ADJ
brj-22095	50	44	sij	sij	PROPN
brj-22095	50	45	is	be	AUX
brj-22095	50	46	the	the	DET
brj-22095	50	47	difference	difference	NOUN
brj-22095	50	48	spectrum	spectrum	NOUN
brj-22095	50	49	between	between	ADP
brj-22095	50	50	the	the	DET
brj-22095	50	51	two	two	NUM
brj-22095	50	52	spectroscopic	spectroscopic	ADJ
brj-22095	50	53	instruments	instrument	NOUN
brj-22095	50	54	.	.	PUNCT
brj-22095	51	1	a	a	DET
brj-22095	51	2	smaller	small	ADJ
brj-22095	51	3	sddsij	sddsij	NOUN
brj-22095	51	4	,	,	PUNCT
brj-22095	51	5	demonstrates	demonstrate	VERB
brj-22095	51	6	a	a	DET
brj-22095	51	7	smaller	small	ADJ
brj-22095	51	8	difference	difference	NOUN
brj-22095	51	9	between	between	ADP
brj-22095	51	10	the	the	DET
brj-22095	51	11	spectral	spectral	ADJ
brj-22095	51	12	signals	signal	NOUN
brj-22095	51	13	of	of	ADP
brj-22095	51	14	these	these	DET
brj-22095	51	15	two	two	NUM
brj-22095	51	16	spectroscopic	spectroscopic	ADJ
brj-22095	51	17	instruments	instrument	NOUN
brj-22095	51	18	at	at	ADP
brj-22095	51	19	wavelength	wavelength	NOUN
brj-22095	51	20	j	j	PROPN
brj-22095	51	21	,	,	PUNCT
brj-22095	51	22	suggesting	suggest	VERB
brj-22095	51	23	that	that	SCONJ
brj-22095	51	24	the	the	DET
brj-22095	51	25	wavelength	wavelength	NOUN
brj-22095	51	26	is	be	AUX
brj-22095	51	27	more	more	ADV
brj-22095	51	28	stable	stable	ADJ
brj-22095	51	29	.	.	PUNCT
brj-22095	52	1	screening	screening	NOUN
brj-22095	52	2	and	and	CCONJ
brj-22095	52	3	optimization	optimization	NOUN
brj-22095	52	4	of	of	ADP
brj-22095	52	5	stable	stable	ADJ
brj-22095	52	6	and	and	CCONJ
brj-22095	52	7	consistent	consistent	ADJ
brj-22095	52	8	wavelengths	wavelength	NOUN
brj-22095	52	9	a	a	DET
brj-22095	52	10	certain	certain	ADJ
brj-22095	52	11	number	number	NOUN
brj-22095	52	12	of	of	ADP
brj-22095	52	13	representative	representative	ADJ
brj-22095	52	14	samples	sample	NOUN
brj-22095	52	15	are	be	AUX
brj-22095	52	16	selected	select	VERB
brj-22095	52	17	by	by	ADP
brj-22095	52	18	kennard	kennard	NOUN
brj-22095	52	19	-	-	PUNCT
brj-22095	52	20	stone	stone	NOUN
brj-22095	52	21	(	(	PUNCT
brj-22095	52	22	zhang	zhang	PROPN
brj-22095	52	23	et	et	PROPN
brj-22095	52	24	al	al	PROPN
brj-22095	52	25	.	.	PROPN
brj-22095	52	26	2017	2017	NUM
brj-22095	52	27	;	;	PUNCT
brj-22095	52	28	sadergaski	sadergaski	NOUN
brj-22095	52	29	et	et	PROPN
brj-22095	52	30	al	al	PROPN
brj-22095	52	31	.	.	PROPN
brj-22095	52	32	2022	2022	NUM
brj-22095	52	33	)	)	PUNCT
brj-22095	52	34	algorithm	algorithm	NOUN
brj-22095	52	35	,	,	PUNCT
brj-22095	52	36	and	and	CCONJ
brj-22095	52	37	then	then	ADV
brj-22095	52	38	,	,	PUNCT
brj-22095	52	39	the	the	DET
brj-22095	52	40	sddsij	sddsij	NOUN
brj-22095	52	41	and	and	CCONJ
brj-22095	52	42	sdpdsj	sdpdsj	NOUN
brj-22095	52	43	at	at	ADP
brj-22095	52	44	wavelength	wavelength	NOUN
brj-22095	52	45	j	j	PROPN
brj-22095	52	46	are	be	AUX
brj-22095	52	47	calculated	calculate	VERB
brj-22095	52	48	according	accord	VERB
brj-22095	52	49	to	to	ADP
brj-22095	52	50	eqs	eqs	PROPN
brj-22095	52	51	.	.	PROPN
brj-22095	52	52	1	1	NUM
brj-22095	52	53	and	and	CCONJ
brj-22095	52	54	2	2	NUM
brj-22095	52	55	above	above	ADV
brj-22095	52	56	.	.	PUNCT
brj-22095	53	1	the	the	DET
brj-22095	53	2	ratio	ratio	NOUN
brj-22095	53	3	of	of	ADP
brj-22095	53	4	these	these	DET
brj-22095	53	5	two	two	NUM
brj-22095	53	6	is	be	AUX
brj-22095	53	7	defined	define	VERB
brj-22095	53	8	as	as	ADP
brj-22095	53	9	the	the	DET
brj-22095	53	10	consistency	consistency	NOUN
brj-22095	53	11	parameter	parameter	NOUN
brj-22095	53	12	,	,	PUNCT
brj-22095	53	13	sddsi	sddsi	INTJ
brj-22095	53	14	(	(	PUNCT
brj-22095	53	15	1,2,3	1,2,3	NUM
brj-22095	53	16	,	,	PUNCT
brj-22095	53	17	,	,	PUNCT
brj-22095	53	18	)	)	PUNCT
brj-22095	53	19	sdpds	sdpds	PROPN
brj-22095	53	20	j	j	PROPN
brj-22095	53	21	j	j	PROPN
brj-22095	53	22	j	j	PROPN
brj-22095	53	23	b	b	PROPN
brj-22095	53	24	j	j	PROPN
brj-22095	53	25	n=	n=	PROPN
brj-22095	53	26	=	=	SYM
brj-22095	53	27	(	(	PUNCT
brj-22095	53	28	3	3	NUM
brj-22095	53	29	)	)	PUNCT
brj-22095	53	30	where	where	SCONJ
brj-22095	53	31	n	n	PRON
brj-22095	53	32	is	be	AUX
brj-22095	53	33	the	the	DET
brj-22095	53	34	number	number	NOUN
brj-22095	53	35	of	of	ADP
brj-22095	53	36	wavelengths	wavelength	NOUN
brj-22095	53	37	.	.	PUNCT
brj-22095	54	1	usually	usually	ADV
brj-22095	54	2	,	,	PUNCT
brj-22095	54	3	sddsij	sddsij	PROPN
brj-22095	54	4	is	be	AUX
brj-22095	54	5	larger	large	ADJ
brj-22095	54	6	than	than	ADP
brj-22095	54	7	sdpdsj	sdpdsj	NOUN
brj-22095	54	8	.	.	PUNCT
brj-22095	55	1	the	the	DET
brj-22095	55	2	closer	close	ADJ
brj-22095	55	3	bj	bj	NOUN
brj-22095	55	4	is	be	AUX
brj-22095	55	5	to	to	ADP
brj-22095	55	6	1	1	NUM
brj-22095	55	7	,	,	PUNCT
brj-22095	55	8	the	the	PRON
brj-22095	55	9	smaller	small	ADJ
brj-22095	55	10	the	the	DET
brj-22095	55	11	spectral	spectral	ADJ
brj-22095	55	12	difference	difference	NOUN
brj-22095	55	13	between	between	ADP
brj-22095	55	14	instruments	instrument	NOUN
brj-22095	55	15	at	at	ADP
brj-22095	55	16	that	that	DET
brj-22095	55	17	wavelength	wavelength	NOUN
brj-22095	55	18	and	and	CCONJ
brj-22095	55	19	the	the	PRON
brj-22095	55	20	better	well	ADJ
brj-22095	55	21	the	the	DET
brj-22095	55	22	spectral	spectral	ADJ
brj-22095	55	23	signal	signal	NOUN
brj-22095	55	24	stability	stability	NOUN
brj-22095	55	25	.	.	PUNCT
brj-22095	56	1	in	in	ADP
brj-22095	56	2	practical	practical	ADJ
brj-22095	56	3	applications	application	NOUN
brj-22095	56	4	the	the	DET
brj-22095	56	5	b	b	PROPN
brj-22095	56	6	value	value	NOUN
brj-22095	56	7	is	be	AUX
brj-22095	56	8	set	set	VERB
brj-22095	56	9	to	to	PART
brj-22095	56	10	filter	filter	VERB
brj-22095	56	11	out	out	ADP
brj-22095	56	12	wavelengths	wavelength	NOUN
brj-22095	56	13	with	with	ADP
brj-22095	56	14	sddsi1	sddsi1	PROPN
brj-22095	56	15	/	/	SYM
brj-22095	56	16	sdpds	sdpds	PROPN
brj-22095	56	17	<	<	X
brj-22095	56	18	b	b	PROPN
brj-22095	56	19	for	for	ADP
brj-22095	56	20	the	the	DET
brj-22095	56	21	wavelength	wavelength	NOUN
brj-22095	56	22	.	.	PUNCT
brj-22095	57	1	in	in	ADP
brj-22095	57	2	addition	addition	NOUN
brj-22095	57	3	,	,	PUNCT
brj-22095	57	4	the	the	DET
brj-22095	57	5	set	set	NOUN
brj-22095	57	6	of	of	ADP
brj-22095	57	7	wavelengths	wavelength	NOUN
brj-22095	57	8	between	between	ADP
brj-22095	57	9	the	the	DET
brj-22095	57	10	master	master	NOUN
brj-22095	57	11	and	and	CCONJ
brj-22095	57	12	target	target	NOUN
brj-22095	57	13	instruments	instrument	NOUN
brj-22095	57	14	screened	screen	VERB
brj-22095	57	15	according	accord	VERB
brj-22095	57	16	to	to	ADP
brj-22095	57	17	the	the	DET
brj-22095	57	18	above	above	ADJ
brj-22095	57	19	method	method	NOUN
brj-22095	57	20	is	be	AUX
brj-22095	57	21	noted	note	VERB
brj-22095	57	22	as	as	ADP
brj-22095	57	23	uc	uc	PROPN
brj-22095	57	24	,	,	PUNCT
brj-22095	57	25	from	from	ADP
brj-22095	57	26	which	which	PRON
brj-22095	57	27	the	the	DET
brj-22095	57	28	wavelengths	wavelength	NOUN
brj-22095	57	29	with	with	ADP
brj-22095	57	30	large	large	ADJ
brj-22095	57	31	sdpds	sdpds	NOUN
brj-22095	57	32	values	value	NOUN
brj-22095	57	33	are	be	AUX
brj-22095	57	34	excluded	exclude	VERB
brj-22095	57	35	to	to	PART
brj-22095	57	36	arrive	arrive	VERB
brj-22095	57	37	at	at	ADP
brj-22095	57	38	the	the	DET
brj-22095	57	39	wavelength	wavelength	NOUN
brj-22095	57	40	set	set	VERB
brj-22095	57	41	with	with	ADP
brj-22095	57	42	better	well	ADJ
brj-22095	57	43	stability	stability	NOUN
brj-22095	57	44	usc	usc	PROPN
brj-22095	57	45	.	.	PROPN
brj-22095	57	46	peer	peer	NOUN
brj-22095	57	47	-	-	PUNCT
brj-22095	57	48	reviewed	review	VERB
brj-22095	57	49	article	article	NOUN
brj-22095	57	50	bioresources.com	bioresources.com	X
brj-22095	57	51	he	he	PRON
brj-22095	57	52	et	et	PROPN
brj-22095	57	53	al	al	PROPN
brj-22095	57	54	.	.	PROPN
brj-22095	58	1	(	(	PUNCT
brj-22095	58	2	2022	2022	NUM
brj-22095	58	3	)	)	PUNCT
brj-22095	58	4	.	.	PUNCT
brj-22095	59	1	“	"	PUNCT
brj-22095	59	2	near	near	ADP
brj-22095	59	3	ir	ir	PROPN
brj-22095	59	4	model	model	NOUN
brj-22095	59	5	of	of	ADP
brj-22095	59	6	biomass	biomass	NOUN
brj-22095	59	7	,	,	PUNCT
brj-22095	59	8	”	"	PUNCT
brj-22095	59	9	bioresources	bioresource	NOUN
brj-22095	59	10	17(4	17(4	NUM
brj-22095	59	11	)	)	PUNCT
brj-22095	59	12	,	,	PUNCT
brj-22095	59	13	6476	6476	NUM
brj-22095	59	14	-	-	SYM
brj-22095	59	15	6489	6489	NUM
brj-22095	59	16	.	.	PUNCT
brj-22095	60	1	6479	6479	NUM
brj-22095	60	2	slope	slope	NOUN
brj-22095	60	3	/bias	/bias	SYM
brj-22095	60	4	correction	correction	NOUN
brj-22095	60	5	algorithm	algorithm	VERB
brj-22095	60	6	the	the	DET
brj-22095	60	7	s	s	PROPN
brj-22095	60	8	/	/	SYM
brj-22095	60	9	b	b	NOUN
brj-22095	60	10	algorithm	algorithm	NOUN
brj-22095	60	11	is	be	AUX
brj-22095	60	12	a	a	DET
brj-22095	60	13	standardized	standardized	ADJ
brj-22095	60	14	correction	correction	NOUN
brj-22095	60	15	method	method	NOUN
brj-22095	60	16	for	for	ADP
brj-22095	60	17	model	model	NOUN
brj-22095	60	18	prediction	prediction	NOUN
brj-22095	60	19	results	result	NOUN
brj-22095	60	20	.	.	PUNCT
brj-22095	61	1	the	the	DET
brj-22095	61	2	calibration	calibration	NOUN
brj-22095	61	3	model	model	NOUN
brj-22095	61	4	built	build	VERB
brj-22095	61	5	on	on	ADP
brj-22095	61	6	the	the	DET
brj-22095	61	7	master	master	NOUN
brj-22095	61	8	machine	machine	NOUN
brj-22095	61	9	is	be	AUX
brj-22095	61	10	used	use	VERB
brj-22095	61	11	to	to	PART
brj-22095	61	12	predict	predict	VERB
brj-22095	61	13	the	the	DET
brj-22095	61	14	predicted	predict	VERB
brj-22095	61	15	values	value	NOUN
brj-22095	61	16	xm	xm	PROPN
brj-22095	61	17	and	and	CCONJ
brj-22095	61	18	xs	xs	PROPN
brj-22095	61	19	of	of	ADP
brj-22095	61	20	the	the	DET
brj-22095	61	21	spectral	spectral	ADJ
brj-22095	61	22	matrix	matrix	NOUN
brj-22095	61	23	xm	xm	PROPN
brj-22095	61	24	measured	measure	VERB
brj-22095	61	25	on	on	ADP
brj-22095	61	26	the	the	DET
brj-22095	61	27	master	master	NOUN
brj-22095	61	28	and	and	CCONJ
brj-22095	61	29	target	target	NOUN
brj-22095	61	30	machines	machine	NOUN
brj-22095	61	31	for	for	ADP
brj-22095	61	32	the	the	DET
brj-22095	61	33	specimen	speciman	NOUN
brj-22095	61	34	set	set	VERB
brj-22095	61	35	to	to	PART
brj-22095	61	36	obtain	obtain	VERB
brj-22095	61	37	the	the	DET
brj-22095	61	38	spectra	spectra	ADJ
brj-22095	61	39	ym	ym	PROPN
brj-22095	61	40	and	and	CCONJ
brj-22095	61	41	ys	ys	PRON
brj-22095	61	42	,	,	PUNCT
brj-22095	61	43	respectively	respectively	ADV
brj-22095	61	44	.	.	PUNCT
brj-22095	62	1	the	the	DET
brj-22095	62	2	parameters	parameter	NOUN
brj-22095	62	3	ym	ym	PROPN
brj-22095	62	4	and	and	CCONJ
brj-22095	62	5	ys	ys	PROPN
brj-22095	62	6	are	be	AUX
brj-22095	62	7	assumed	assume	VERB
brj-22095	62	8	to	to	PART
brj-22095	62	9	have	have	VERB
brj-22095	62	10	the	the	DET
brj-22095	62	11	following	following	ADJ
brj-22095	62	12	relationship	relationship	NOUN
brj-22095	62	13	,	,	PUNCT
brj-22095	62	14	slope	slope	NOUN
brj-22095	62	15	biass	biass	NOUN
brj-22095	62	16	my	my	PRON
brj-22095	62	17	y=	y=	NOUN
brj-22095	62	18	+	+	CCONJ
brj-22095	62	19	(	(	PUNCT
brj-22095	62	20	4	4	X
brj-22095	62	21	)	)	PUNCT
brj-22095	62	22	where	where	SCONJ
brj-22095	62	23	slope	slope	NOUN
brj-22095	62	24	is	be	AUX
brj-22095	62	25	the	the	DET
brj-22095	62	26	slope	slope	NOUN
brj-22095	62	27	of	of	ADP
brj-22095	62	28	the	the	DET
brj-22095	62	29	linear	linear	ADJ
brj-22095	62	30	equation	equation	NOUN
brj-22095	62	31	and	and	CCONJ
brj-22095	62	32	bias	bias	NOUN
brj-22095	62	33	is	be	AUX
brj-22095	62	34	the	the	DET
brj-22095	62	35	intercept	intercept	NOUN
brj-22095	62	36	of	of	ADP
brj-22095	62	37	the	the	DET
brj-22095	62	38	linear	linear	ADJ
brj-22095	62	39	equation	equation	NOUN
brj-22095	62	40	,	,	PUNCT
brj-22095	62	41	which	which	PRON
brj-22095	62	42	can	can	AUX
brj-22095	62	43	be	be	AUX
brj-22095	62	44	calculated	calculate	VERB
brj-22095	62	45	by	by	ADP
brj-22095	62	46	least	least	ADJ
brj-22095	62	47	square	square	ADJ
brj-22095	62	48	(	(	PUNCT
brj-22095	62	49	ls	ls	PROPN
brj-22095	62	50	)	)	PUNCT
brj-22095	62	51	.	.	PUNCT
brj-22095	63	1	for	for	ADP
brj-22095	63	2	the	the	DET
brj-22095	63	3	unknown	unknown	ADJ
brj-22095	63	4	sample	sample	NOUN
brj-22095	63	5	spectral	spectral	ADJ
brj-22095	63	6	matrix	matrix	NOUN
brj-22095	63	7	xs	xs	PROPN
brj-22095	63	8	,	,	PUNCT
brj-22095	63	9	un	un	PROPN
brj-22095	63	10	measured	measure	VERB
brj-22095	63	11	on	on	ADP
brj-22095	63	12	the	the	DET
brj-22095	63	13	target	target	NOUN
brj-22095	63	14	instrument	instrument	NOUN
brj-22095	63	15	;	;	PUNCT
brj-22095	63	16	first	first	ADV
brj-22095	63	17	,	,	PUNCT
brj-22095	63	18	ys	ys	INTJ
brj-22095	63	19	,	,	PUNCT
brj-22095	63	20	un	un	PROPN
brj-22095	63	21	is	be	AUX
brj-22095	63	22	predicted	predict	VERB
brj-22095	63	23	by	by	ADP
brj-22095	63	24	the	the	DET
brj-22095	63	25	calibration	calibration	NOUN
brj-22095	63	26	model	model	NOUN
brj-22095	63	27	built	build	VERB
brj-22095	63	28	on	on	ADP
brj-22095	63	29	the	the	DET
brj-22095	63	30	master	master	NOUN
brj-22095	63	31	instrument	instrument	NOUN
brj-22095	63	32	,	,	PUNCT
brj-22095	63	33	and	and	CCONJ
brj-22095	63	34	then	then	ADV
brj-22095	63	35	,	,	PUNCT
brj-22095	63	36	the	the	DET
brj-22095	63	37	passed	pass	VERB
brj-22095	63	38	prediction	prediction	NOUN
brj-22095	63	39	ys	ys	NOUN
brj-22095	63	40	,	,	PUNCT
brj-22095	63	41	tr	tr	PRON
brj-22095	63	42	can	can	AUX
brj-22095	63	43	be	be	AUX
brj-22095	63	44	found	find	VERB
brj-22095	63	45	by	by	ADP
brj-22095	63	46	the	the	DET
brj-22095	63	47	following	follow	VERB
brj-22095	63	48	equation	equation	NOUN
brj-22095	63	49	,	,	PUNCT
brj-22095	63	50	,	,	PUNCT
brj-22095	63	51	,	,	PUNCT
brj-22095	63	52	slope	slope	NOUN
brj-22095	63	53	biass	biass	NOUN
brj-22095	63	54	tr	tr	NOUN
brj-22095	63	55	s	s	VERB
brj-22095	63	56	uny	uny	PROPN
brj-22095	63	57	y=	y=	PROPN
brj-22095	63	58	+	+	CCONJ
brj-22095	63	59	(	(	PUNCT
brj-22095	63	60	5	5	X
brj-22095	63	61	)	)	PUNCT
brj-22095	63	62	where	where	SCONJ
brj-22095	63	63	ys	ys	PROPN
brj-22095	63	64	,	,	PUNCT
brj-22095	63	65	un	un	PROPN
brj-22095	63	66	is	be	AUX
brj-22095	63	67	the	the	DET
brj-22095	63	68	predicted	predict	VERB
brj-22095	63	69	value	value	NOUN
brj-22095	63	70	of	of	ADP
brj-22095	63	71	the	the	DET
brj-22095	63	72	unknown	unknown	ADJ
brj-22095	63	73	sample	sample	NOUN
brj-22095	63	74	and	and	CCONJ
brj-22095	63	75	ys	ys	NOUN
brj-22095	63	76	,	,	PUNCT
brj-22095	63	77	tr	tr	VERB
brj-22095	63	78	is	be	AUX
brj-22095	63	79	the	the	DET
brj-22095	63	80	predicted	predict	VERB
brj-22095	63	81	value	value	NOUN
brj-22095	63	82	of	of	ADP
brj-22095	63	83	the	the	DET
brj-22095	63	84	unknown	unknown	ADJ
brj-22095	63	85	sample	sample	NOUN
brj-22095	63	86	after	after	ADP
brj-22095	63	87	passing	pass	VERB
brj-22095	63	88	.	.	PUNCT
brj-22095	64	1	experimental	experimental	ADJ
brj-22095	64	2	sample	sample	NOUN
brj-22095	64	3	preparation	preparation	NOUN
brj-22095	64	4	and	and	CCONJ
brj-22095	64	5	analysis	analysis	NOUN
brj-22095	64	6	of	of	ADP
brj-22095	64	7	holocellulose	holocellulose	ADJ
brj-22095	64	8	and	and	CCONJ
brj-22095	64	9	lignin	lignin	PROPN
brj-22095	64	10	content	content	NOUN
brj-22095	64	11	a	a	DET
brj-22095	64	12	total	total	NOUN
brj-22095	64	13	of	of	ADP
brj-22095	64	14	82	82	NUM
brj-22095	64	15	log	log	NOUN
brj-22095	64	16	samples	sample	NOUN
brj-22095	64	17	were	be	AUX
brj-22095	64	18	cut	cut	VERB
brj-22095	64	19	into	into	ADP
brj-22095	64	20	chips	chip	NOUN
brj-22095	64	21	and	and	CCONJ
brj-22095	64	22	ground	ground	NOUN
brj-22095	64	23	,	,	PUNCT
brj-22095	64	24	and	and	CCONJ
brj-22095	64	25	the	the	DET
brj-22095	64	26	wood	wood	NOUN
brj-22095	64	27	flour	flour	NOUN
brj-22095	64	28	samples	sample	NOUN
brj-22095	64	29	with	with	ADP
brj-22095	64	30	particle	particle	NOUN
brj-22095	64	31	sizes	size	NOUN
brj-22095	64	32	of	of	ADP
brj-22095	64	33	0.250	0.250	NUM
brj-22095	64	34	to	to	ADP
brj-22095	64	35	0.425	0.425	NUM
brj-22095	64	36	mm	mm	NOUN
brj-22095	64	37	(	(	PUNCT
brj-22095	64	38	40	40	NUM
brj-22095	64	39	to	to	PART
brj-22095	64	40	60	60	NUM
brj-22095	64	41	mesh	mesh	NOUN
brj-22095	64	42	)	)	PUNCT
brj-22095	64	43	were	be	AUX
brj-22095	64	44	selected	select	VERB
brj-22095	64	45	to	to	PART
brj-22095	64	46	determine	determine	VERB
brj-22095	64	47	their	their	PRON
brj-22095	64	48	holocellulose	holocellulose	ADJ
brj-22095	64	49	and	and	CCONJ
brj-22095	64	50	lignin	lignin	NOUN
brj-22095	64	51	contents	content	NOUN
brj-22095	64	52	according	accord	VERB
brj-22095	64	53	to	to	ADP
brj-22095	64	54	gb	gb	ADP
brj-22095	64	55	/	/	SYM
brj-22095	64	56	t	t	NOUN
brj-22095	64	57	2677.8	2677.8	NUM
brj-22095	64	58	(	(	PUNCT
brj-22095	64	59	1994	1994	NUM
brj-22095	64	60	)	)	PUNCT
brj-22095	64	61	.	.	PUNCT
brj-22095	65	1	the	the	DET
brj-22095	65	2	results	result	NOUN
brj-22095	65	3	of	of	ADP
brj-22095	65	4	are	be	AUX
brj-22095	65	5	shown	show	VERB
brj-22095	65	6	in	in	ADP
brj-22095	65	7	table	table	NOUN
brj-22095	65	8	1	1	NUM
brj-22095	65	9	.	.	PUNCT
brj-22095	65	10	table	table	NOUN
brj-22095	65	11	1	1	NUM
brj-22095	65	12	.	.	PUNCT
brj-22095	65	13	statistical	statistical	ADJ
brj-22095	65	14	table	table	NOUN
brj-22095	65	15	of	of	ADP
brj-22095	65	16	the	the	DET
brj-22095	65	17	content	content	NOUN
brj-22095	65	18	of	of	ADP
brj-22095	65	19	holocellulose	holocellulose	NOUN
brj-22095	65	20	and	and	CCONJ
brj-22095	65	21	lignin	lignin	NOUN
brj-22095	65	22	in	in	ADP
brj-22095	65	23	wood	wood	NOUN
brj-22095	65	24	component	component	NOUN
brj-22095	65	25	number	number	NOUN
brj-22095	65	26	of	of	ADP
brj-22095	65	27	samples	sample	NOUN
brj-22095	65	28	minimum	minimum	ADJ
brj-22095	65	29	value	value	NOUN
brj-22095	65	30	maximum	maximum	ADJ
brj-22095	65	31	value	value	NOUN
brj-22095	65	32	average	average	ADJ
brj-22095	65	33	value	value	NOUN
brj-22095	65	34	standard	standard	ADJ
brj-22095	65	35	deviation	deviation	NOUN
brj-22095	65	36	holocellulose	holocellulose	VERB
brj-22095	65	37	82	82	NUM
brj-22095	65	38	66.08	66.08	NUM
brj-22095	65	39	86.28	86.28	NUM
brj-22095	65	40	76.14	76.14	NUM
brj-22095	65	41	5.97	5.97	NUM
brj-22095	65	42	lignin	lignin	NOUN
brj-22095	65	43	82	82	NUM
brj-22095	65	44	14.82	14.82	NUM
brj-22095	65	45	34.20	34.20	NUM
brj-22095	65	46	26.43	26.43	NUM
brj-22095	65	47	5.42	5.42	NUM
brj-22095	65	48	instrumentation	instrumentation	NOUN
brj-22095	65	49	and	and	CCONJ
brj-22095	65	50	spectral	spectral	ADJ
brj-22095	65	51	acquisition	acquisition	NOUN
brj-22095	65	52	the	the	DET
brj-22095	65	53	experimental	experimental	ADJ
brj-22095	65	54	instrument	instrument	NOUN
brj-22095	65	55	adopts	adopt	VERB
brj-22095	65	56	two	two	NUM
brj-22095	65	57	ias	ias	PROPN
brj-22095	65	58	series	series	NOUN
brj-22095	65	59	portable	portable	ADJ
brj-22095	65	60	spectrometers	spectrometer	NOUN
brj-22095	65	61	from	from	ADP
brj-22095	65	62	the	the	DET
brj-22095	65	63	same	same	ADJ
brj-22095	65	64	company	company	NOUN
brj-22095	65	65	(	(	PUNCT
brj-22095	65	66	wuxi	wuxi	PROPN
brj-22095	65	67	intelligent	intelligent	ADJ
brj-22095	65	68	analysis	analysis	NOUN
brj-22095	65	69	service	service	PROPN
brj-22095	65	70	co.	co.	PROPN
brj-22095	65	71	ltd	ltd	PROPN
brj-22095	65	72	,	,	PUNCT
brj-22095	65	73	wuxi	wuxi	PROPN
brj-22095	65	74	,	,	PUNCT
brj-22095	65	75	china	china	PROPN
brj-22095	65	76	)	)	PUNCT
brj-22095	65	77	.	.	PUNCT
brj-22095	66	1	the	the	DET
brj-22095	66	2	core	core	ADJ
brj-22095	66	3	components	component	NOUN
brj-22095	66	4	of	of	ADP
brj-22095	66	5	the	the	DET
brj-22095	66	6	instruments	instrument	NOUN
brj-22095	66	7	are	be	AUX
brj-22095	66	8	digital	digital	ADJ
brj-22095	66	9	micromirror	micromirror	NOUN
brj-22095	66	10	device	device	NOUN
brj-22095	66	11	grating	grate	VERB
brj-22095	66	12	spectrometers	spectrometer	NOUN
brj-22095	66	13	based	base	VERB
brj-22095	66	14	on	on	ADP
brj-22095	66	15	micro	micro	ADJ
brj-22095	66	16	-	-	ADJ
brj-22095	66	17	electromechanical	electromechanical	ADJ
brj-22095	66	18	systems	system	NOUN
brj-22095	66	19	,	,	PUNCT
brj-22095	66	20	with	with	ADP
brj-22095	66	21	a	a	DET
brj-22095	66	22	wavelength	wavelength	NOUN
brj-22095	66	23	range	range	NOUN
brj-22095	66	24	of	of	ADP
brj-22095	66	25	900	900	NUM
brj-22095	66	26	to	to	PART
brj-22095	66	27	1700	1700	NUM
brj-22095	66	28	nm	nm	NOUN
brj-22095	66	29	and	and	CCONJ
brj-22095	66	30	a	a	DET
brj-22095	66	31	resolution	resolution	NOUN
brj-22095	66	32	of	of	ADP
brj-22095	66	33	10	10	NUM
brj-22095	66	34	nm	nm	NOUN
brj-22095	66	35	.	.	PUNCT
brj-22095	67	1	one	one	NUM
brj-22095	67	2	of	of	ADP
brj-22095	67	3	them	they	PRON
brj-22095	67	4	is	be	AUX
brj-22095	67	5	an	an	DET
brj-22095	67	6	ias-5000	ias-5000	NOUN
brj-22095	67	7	type	type	NOUN
brj-22095	67	8	,	,	PUNCT
brj-22095	67	9	marked	mark	VERB
brj-22095	67	10	as	as	ADP
brj-22095	67	11	5000b	5000b	NUM
brj-22095	67	12	(	(	PUNCT
brj-22095	67	13	master	master	NOUN
brj-22095	67	14	instrument	instrument	NOUN
brj-22095	67	15	)	)	PUNCT
brj-22095	67	16	,	,	PUNCT
brj-22095	67	17	using	use	VERB
brj-22095	67	18	a	a	DET
brj-22095	67	19	down	down	ADV
brj-22095	67	20	-	-	PUNCT
brj-22095	67	21	illuminated	illuminate	VERB
brj-22095	67	22	5w	5w	PROPN
brj-22095	67	23	halogen	halogen	NOUN
brj-22095	67	24	tungsten	tungsten	VERB
brj-22095	67	25	light	light	NOUN
brj-22095	67	26	source	source	NOUN
brj-22095	67	27	;	;	PUNCT
brj-22095	67	28	the	the	DET
brj-22095	67	29	other	other	ADJ
brj-22095	67	30	is	be	AUX
brj-22095	67	31	an	an	DET
brj-22095	67	32	ias-2000	ias-2000	ADJ
brj-22095	67	33	type	type	NOUN
brj-22095	67	34	,	,	PUNCT
brj-22095	67	35	marked	mark	VERB
brj-22095	67	36	as	as	ADP
brj-22095	67	37	2000	2000	NUM
brj-22095	67	38	(	(	PUNCT
brj-22095	67	39	target	target	NOUN
brj-22095	67	40	instrument	instrument	NOUN
brj-22095	67	41	)	)	PUNCT
brj-22095	67	42	,	,	PUNCT
brj-22095	67	43	with	with	ADP
brj-22095	67	44	an	an	DET
brj-22095	67	45	up	up	ADV
brj-22095	67	46	-	-	PUNCT
brj-22095	67	47	illuminated	illuminated	ADJ
brj-22095	67	48	10w	10w	NOUN
brj-22095	67	49	tungstenhalogen	tungstenhalogen	PRON
brj-22095	67	50	lamp	lamp	PROPN
brj-22095	67	51	light	light	PROPN
brj-22095	67	52	source	source	NOUN
brj-22095	67	53	.	.	PUNCT
brj-22095	68	1	the	the	DET
brj-22095	68	2	two	two	NUM
brj-22095	68	3	types	type	NOUN
brj-22095	68	4	of	of	ADP
brj-22095	68	5	instruments	instrument	NOUN
brj-22095	68	6	are	be	AUX
brj-22095	68	7	shown	show	VERB
brj-22095	68	8	in	in	ADP
brj-22095	68	9	fig	fig	NOUN
brj-22095	68	10	.	.	PUNCT
brj-22095	69	1	1	1	NUM
brj-22095	69	2	.	.	X
brj-22095	69	3	when	when	SCONJ
brj-22095	69	4	collecting	collect	VERB
brj-22095	69	5	the	the	DET
brj-22095	69	6	sample	sample	NOUN
brj-22095	69	7	spectrum	spectrum	NOUN
brj-22095	69	8	,	,	PUNCT
brj-22095	69	9	the	the	DET
brj-22095	69	10	sample	sample	NOUN
brj-22095	69	11	was	be	AUX
brj-22095	69	12	put	put	VERB
brj-22095	69	13	into	into	ADP
brj-22095	69	14	the	the	DET
brj-22095	69	15	measuring	measure	VERB
brj-22095	69	16	cup	cup	NOUN
brj-22095	69	17	and	and	CCONJ
brj-22095	69	18	flattened	flatten	VERB
brj-22095	69	19	with	with	ADP
brj-22095	69	20	a	a	DET
brj-22095	69	21	50	50	NUM
brj-22095	69	22	g	g	NOUN
brj-22095	69	23	weight	weight	NOUN
brj-22095	69	24	to	to	PART
brj-22095	69	25	make	make	VERB
brj-22095	69	26	it	it	PRON
brj-22095	69	27	evenly	evenly	ADV
brj-22095	69	28	distributed	distribute	VERB
brj-22095	69	29	,	,	PUNCT
brj-22095	69	30	and	and	CCONJ
brj-22095	69	31	each	each	DET
brj-22095	69	32	sample	sample	NOUN
brj-22095	69	33	was	be	AUX
brj-22095	69	34	repeatedly	repeatedly	ADV
brj-22095	69	35	loaded	load	VERB
brj-22095	69	36	three	three	NUM
brj-22095	69	37	times	time	NOUN
brj-22095	69	38	to	to	PART
brj-22095	69	39	take	take	VERB
brj-22095	69	40	the	the	DET
brj-22095	69	41	average	average	ADJ
brj-22095	69	42	spectrum	spectrum	NOUN
brj-22095	69	43	.	.	PUNCT
brj-22095	70	1	the	the	DET
brj-22095	70	2	number	number	NOUN
brj-22095	70	3	of	of	ADP
brj-22095	70	4	spectral	spectral	ADJ
brj-22095	70	5	scans	scan	NOUN
brj-22095	70	6	was	be	AUX
brj-22095	70	7	50	50	NUM
brj-22095	70	8	,	,	PUNCT
brj-22095	70	9	and	and	CCONJ
brj-22095	70	10	for	for	SCONJ
brj-22095	70	11	each	each	DET
brj-22095	70	12	sample	sample	NOUN
brj-22095	70	13	measured	measure	VERB
brj-22095	70	14	,	,	PUNCT
brj-22095	70	15	the	the	DET
brj-22095	70	16	residual	residual	ADJ
brj-22095	70	17	wood	wood	NOUN
brj-22095	70	18	powder	powder	NOUN
brj-22095	70	19	in	in	ADP
brj-22095	70	20	the	the	DET
brj-22095	70	21	sample	sample	NOUN
brj-22095	70	22	cup	cup	NOUN
brj-22095	70	23	was	be	AUX
brj-22095	70	24	removed	remove	VERB
brj-22095	70	25	with	with	ADP
brj-22095	70	26	a	a	DET
brj-22095	70	27	brush	brush	NOUN
brj-22095	70	28	to	to	PART
brj-22095	70	29	avoid	avoid	VERB
brj-22095	70	30	affecting	affect	VERB
brj-22095	70	31	the	the	DET
brj-22095	70	32	accuracy	accuracy	NOUN
brj-22095	70	33	of	of	ADP
brj-22095	70	34	subsequent	subsequent	ADJ
brj-22095	70	35	sample	sample	NOUN
brj-22095	70	36	spectra	spectra	ADJ
brj-22095	70	37	acquisition	acquisition	NOUN
brj-22095	70	38	.	.	PUNCT
brj-22095	71	1	the	the	DET
brj-22095	71	2	spectra	spectra	ADJ
brj-22095	71	3	peer	peer	NOUN
brj-22095	71	4	-	-	PUNCT
brj-22095	71	5	reviewed	review	VERB
brj-22095	71	6	article	article	NOUN
brj-22095	71	7	bioresources.com	bioresources.com	X
brj-22095	71	8	he	he	PRON
brj-22095	71	9	et	et	PROPN
brj-22095	71	10	al	al	PROPN
brj-22095	71	11	.	.	PROPN
brj-22095	71	12	(	(	PUNCT
brj-22095	71	13	2022	2022	NUM
brj-22095	71	14	)	)	PUNCT
brj-22095	71	15	.	.	PUNCT
brj-22095	72	1	“	"	PUNCT
brj-22095	72	2	near	near	ADP
brj-22095	72	3	ir	ir	PROPN
brj-22095	72	4	model	model	NOUN
brj-22095	72	5	of	of	ADP
brj-22095	72	6	biomass	biomass	NOUN
brj-22095	72	7	,	,	PUNCT
brj-22095	72	8	”	"	PUNCT
brj-22095	72	9	bioresources	bioresource	NOUN
brj-22095	72	10	17(4	17(4	NUM
brj-22095	72	11	)	)	PUNCT
brj-22095	72	12	,	,	PUNCT
brj-22095	72	13	6476	6476	NUM
brj-22095	72	14	-	-	SYM
brj-22095	72	15	6489	6489	NUM
brj-22095	72	16	.	.	PUNCT
brj-22095	73	1	6480	6480	NUM
brj-22095	73	2	of	of	ADP
brj-22095	73	3	82	82	NUM
brj-22095	73	4	wood	wood	NOUN
brj-22095	73	5	powder	powder	NOUN
brj-22095	73	6	samples	sample	NOUN
brj-22095	73	7	were	be	AUX
brj-22095	73	8	collected	collect	VERB
brj-22095	73	9	by	by	ADP
brj-22095	73	10	the	the	DET
brj-22095	73	11	above	above	ADJ
brj-22095	73	12	method	method	NOUN
brj-22095	73	13	on	on	ADP
brj-22095	73	14	two	two	NUM
brj-22095	73	15	types	type	NOUN
brj-22095	73	16	of	of	ADP
brj-22095	73	17	instruments	instrument	NOUN
brj-22095	73	18	under	under	ADP
brj-22095	73	19	the	the	DET
brj-22095	73	20	same	same	ADJ
brj-22095	73	21	environmental	environmental	ADJ
brj-22095	73	22	conditions	condition	NOUN
brj-22095	73	23	,	,	PUNCT
brj-22095	73	24	respectively	respectively	ADV
brj-22095	73	25	.	.	PUNCT
brj-22095	74	1	the	the	DET
brj-22095	74	2	collected	collect	VERB
brj-22095	74	3	spectral	spectral	ADJ
brj-22095	74	4	data	datum	NOUN
brj-22095	74	5	were	be	AUX
brj-22095	74	6	preprocessed	preprocesse	VERB
brj-22095	74	7	using	use	VERB
brj-22095	74	8	standard	standard	ADJ
brj-22095	74	9	normal	normal	ADJ
brj-22095	74	10	variate	variate	NOUN
brj-22095	74	11	transformation	transformation	NOUN
brj-22095	74	12	(	(	PUNCT
brj-22095	74	13	snv	snv	PROPN
brj-22095	74	14	)	)	PUNCT
brj-22095	74	15	(	(	PUNCT
brj-22095	74	16	kang	kang	PROPN
brj-22095	74	17	et	et	PROPN
brj-22095	74	18	al	al	PROPN
brj-22095	74	19	.	.	PROPN
brj-22095	74	20	2022	2022	NUM
brj-22095	74	21	;	;	PUNCT
brj-22095	74	22	maraphum	maraphum	NOUN
brj-22095	74	23	et	et	PROPN
brj-22095	74	24	al	al	PROPN
brj-22095	74	25	.	.	PROPN
brj-22095	74	26	2022	2022	NUM
brj-22095	74	27	)	)	PUNCT
brj-22095	74	28	to	to	PART
brj-22095	74	29	eliminate	eliminate	VERB
brj-22095	74	30	the	the	DET
brj-22095	74	31	interference	interference	NOUN
brj-22095	74	32	of	of	ADP
brj-22095	74	33	surface	surface	NOUN
brj-22095	74	34	scattering	scattering	NOUN
brj-22095	74	35	and	and	CCONJ
brj-22095	74	36	light	light	ADJ
brj-22095	74	37	range	range	NOUN
brj-22095	74	38	variation	variation	NOUN
brj-22095	74	39	of	of	ADP
brj-22095	74	40	wood	wood	NOUN
brj-22095	74	41	samples	sample	NOUN
brj-22095	74	42	on	on	ADP
brj-22095	74	43	the	the	DET
brj-22095	74	44	nir	nir	ADJ
brj-22095	74	45	diffuse	diffuse	NOUN
brj-22095	74	46	reflectance	reflectance	NOUN
brj-22095	74	47	spectra	spectra	NOUN
brj-22095	74	48	for	for	ADP
brj-22095	74	49	the	the	DET
brj-22095	74	50	subsequent	subsequent	ADJ
brj-22095	74	51	wavelength	wavelength	NOUN
brj-22095	74	52	screening	screening	NOUN
brj-22095	74	53	and	and	CCONJ
brj-22095	74	54	modeling	modeling	NOUN
brj-22095	74	55	process	process	NOUN
brj-22095	74	56	.	.	PUNCT
brj-22095	75	1	fig	fig	NOUN
brj-22095	75	2	.	.	PUNCT
brj-22095	76	1	1	1	X
brj-22095	76	2	.	.	X
brj-22095	76	3	diagram	diagram	NOUN
brj-22095	76	4	of	of	ADP
brj-22095	76	5	two	two	NUM
brj-22095	76	6	irradiation	irradiation	NOUN
brj-22095	76	7	modes	mode	NOUN
brj-22095	76	8	,	,	PUNCT
brj-22095	76	9	(	(	PUNCT
brj-22095	76	10	a	a	X
brj-22095	76	11	)	)	PUNCT
brj-22095	76	12	bottom	bottom	ADJ
brj-22095	76	13	-	-	PUNCT
brj-22095	76	14	up	up	ADP
brj-22095	76	15	irradiation	irradiation	NOUN
brj-22095	76	16	(	(	PUNCT
brj-22095	76	17	b	b	NOUN
brj-22095	76	18	)	)	PUNCT
brj-22095	76	19	top	top	ADJ
brj-22095	76	20	-	-	PUNCT
brj-22095	76	21	down	down	ADP
brj-22095	76	22	irradiation	irradiation	NOUN
brj-22095	76	23	sample	sample	NOUN
brj-22095	76	24	set	set	NOUN
brj-22095	76	25	division	division	NOUN
brj-22095	76	26	aiming	aim	VERB
brj-22095	76	27	at	at	ADP
brj-22095	76	28	the	the	DET
brj-22095	76	29	spectral	spectral	ADJ
brj-22095	76	30	data	datum	NOUN
brj-22095	76	31	of	of	ADP
brj-22095	76	32	82	82	NUM
brj-22095	76	33	samples	sample	NOUN
brj-22095	76	34	used	use	VERB
brj-22095	76	35	in	in	ADP
brj-22095	76	36	this	this	DET
brj-22095	76	37	paper	paper	NOUN
brj-22095	76	38	,	,	PUNCT
brj-22095	76	39	after	after	ADP
brj-22095	76	40	extracting	extract	VERB
brj-22095	76	41	3	3	NUM
brj-22095	76	42	principal	principal	ADJ
brj-22095	76	43	components	component	NOUN
brj-22095	76	44	by	by	ADP
brj-22095	76	45	pca	pca	PROPN
brj-22095	76	46	algorithm	algorithm	NOUN
brj-22095	76	47	,	,	PUNCT
brj-22095	76	48	the	the	DET
brj-22095	76	49	kennard	kennard	NOUN
brj-22095	76	50	-	-	PUNCT
brj-22095	76	51	stone	stone	NOUN
brj-22095	76	52	method	method	NOUN
brj-22095	76	53	was	be	AUX
brj-22095	76	54	used	use	VERB
brj-22095	76	55	to	to	PART
brj-22095	76	56	divide	divide	VERB
brj-22095	76	57	56	56	NUM
brj-22095	76	58	calibration	calibration	NOUN
brj-22095	76	59	sets	set	NOUN
brj-22095	76	60	and	and	CCONJ
brj-22095	76	61	26	26	NUM
brj-22095	76	62	prediction	prediction	NOUN
brj-22095	76	63	set	set	VERB
brj-22095	76	64	samples.the	samples.the	DET
brj-22095	76	65	calibration	calibration	NOUN
brj-22095	76	66	set	set	NOUN
brj-22095	76	67	and	and	CCONJ
brj-22095	76	68	prediction	prediction	NOUN
brj-22095	76	69	set	set	VERB
brj-22095	76	70	samples	sample	NOUN
brj-22095	76	71	of	of	ADP
brj-22095	76	72	the	the	DET
brj-22095	76	73	master	master	NOUN
brj-22095	76	74	and	and	CCONJ
brj-22095	76	75	target	target	NOUN
brj-22095	76	76	instruments	instrument	NOUN
brj-22095	76	77	corresponded	correspond	VERB
brj-22095	76	78	to	to	ADP
brj-22095	76	79	each	each	DET
brj-22095	76	80	other	other	ADJ
brj-22095	76	81	.	.	PUNCT
brj-22095	77	1	the	the	DET
brj-22095	77	2	distribution	distribution	NOUN
brj-22095	77	3	of	of	ADP
brj-22095	77	4	holocellulose	holocellulose	ADJ
brj-22095	77	5	and	and	CCONJ
brj-22095	77	6	lignin	lignin	NOUN
brj-22095	77	7	contents	content	NOUN
brj-22095	77	8	of	of	ADP
brj-22095	77	9	pulpwood	pulpwood	NOUN
brj-22095	77	10	is	be	AUX
brj-22095	77	11	shown	show	VERB
brj-22095	77	12	in	in	ADP
brj-22095	77	13	table	table	NOUN
brj-22095	77	14	2	2	NUM
brj-22095	77	15	.	.	PUNCT
brj-22095	77	16	table	table	NOUN
brj-22095	77	17	2	2	NUM
brj-22095	77	18	.	.	X
brj-22095	77	19	holocellulose	holocellulose	ADJ
brj-22095	77	20	and	and	CCONJ
brj-22095	77	21	lignin	lignin	NOUN
brj-22095	77	22	contents	content	NOUN
brj-22095	77	23	of	of	ADP
brj-22095	77	24	wood	wood	NOUN
brj-22095	77	25	powder	powder	NOUN
brj-22095	77	26	in	in	ADP
brj-22095	77	27	correction	correction	NOUN
brj-22095	77	28	set	set	VERB
brj-22095	77	29	and	and	CCONJ
brj-22095	77	30	prediction	prediction	NOUN
brj-22095	77	31	set	set	VERB
brj-22095	77	32	component	component	NOUN
brj-22095	77	33	sample	sample	NOUN
brj-22095	77	34	set	set	NOUN
brj-22095	77	35	division	division	NOUN
brj-22095	77	36	number	number	NOUN
brj-22095	77	37	of	of	ADP
brj-22095	77	38	samples	sample	NOUN
brj-22095	77	39	minimum	minimum	ADJ
brj-22095	77	40	value	value	NOUN
brj-22095	77	41	maximum	maximum	ADJ
brj-22095	77	42	value	value	NOUN
brj-22095	77	43	average	average	ADJ
brj-22095	77	44	value	value	NOUN
brj-22095	77	45	standard	standard	ADJ
brj-22095	77	46	deviation	deviation	NOUN
brj-22095	77	47	holocellulose	holocellulose	VERB
brj-22095	77	48	calibration	calibration	NOUN
brj-22095	77	49	set	set	VERB
brj-22095	77	50	56	56	NUM
brj-22095	77	51	66.08	66.08	NUM
brj-22095	77	52	86.28	86.28	NUM
brj-22095	77	53	77.18	77.18	NUM
brj-22095	77	54	5.70	5.70	NUM
brj-22095	77	55	prediction	prediction	NOUN
brj-22095	77	56	set	set	VERB
brj-22095	77	57	26	26	NUM
brj-22095	77	58	66.22	66.22	NUM
brj-22095	77	59	81.70	81.70	NUM
brj-22095	77	60	73.89	73.89	NUM
brj-22095	77	61	6.03	6.03	NUM
brj-22095	77	62	lignin	lignin	NOUN
brj-22095	77	63	calibration	calibration	NOUN
brj-22095	77	64	set	set	VERB
brj-22095	77	65	56	56	NUM
brj-22095	77	66	14.82	14.82	NUM
brj-22095	77	67	34.20	34.20	NUM
brj-22095	77	68	25.45	25.45	NUM
brj-22095	77	69	5.32	5.32	NUM
brj-22095	77	70	prediction	prediction	NOUN
brj-22095	77	71	set	set	VERB
brj-22095	77	72	26	26	NUM
brj-22095	77	73	18.20	18.20	NUM
brj-22095	77	74	33.84	33.84	NUM
brj-22095	77	75	28.55	28.55	NUM
brj-22095	77	76	5.11	5.11	NUM
brj-22095	77	77	modeling	modeling	NOUN
brj-22095	77	78	and	and	CCONJ
brj-22095	77	79	model	model	NOUN
brj-22095	77	80	evaluation	evaluation	NOUN
brj-22095	77	81	methods	method	NOUN
brj-22095	77	82	the	the	DET
brj-22095	77	83	partial	partial	ADJ
brj-22095	77	84	least	least	ADJ
brj-22095	77	85	squares	square	NOUN
brj-22095	77	86	regression	regression	NOUN
brj-22095	77	87	(	(	PUNCT
brj-22095	77	88	plsr	plsr	PROPN
brj-22095	77	89	)	)	PUNCT
brj-22095	77	90	method	method	NOUN
brj-22095	77	91	was	be	AUX
brj-22095	77	92	used	use	VERB
brj-22095	77	93	for	for	ADP
brj-22095	77	94	modeling	modeling	NOUN
brj-22095	77	95	(	(	PUNCT
brj-22095	77	96	moreira	moreira	PROPN
brj-22095	77	97	et	et	PROPN
brj-22095	77	98	al	al	PROPN
brj-22095	77	99	.	.	PROPN
brj-22095	77	100	2015	2015	NUM
brj-22095	77	101	)	)	PUNCT
brj-22095	77	102	.	.	PUNCT
brj-22095	78	1	the	the	DET
brj-22095	78	2	number	number	NOUN
brj-22095	78	3	of	of	ADP
brj-22095	78	4	latent	latent	NOUN
brj-22095	78	5	variables	variable	NOUN
brj-22095	78	6	was	be	AUX
brj-22095	78	7	set	set	VERB
brj-22095	78	8	in	in	ADP
brj-22095	78	9	the	the	DET
brj-22095	78	10	range	range	NOUN
brj-22095	78	11	of	of	ADP
brj-22095	78	12	2	2	NUM
brj-22095	78	13	-	-	SYM
brj-22095	78	14	14	14	NUM
brj-22095	78	15	,	,	PUNCT
brj-22095	78	16	and	and	CCONJ
brj-22095	78	17	determined	determine	VERB
brj-22095	78	18	by	by	ADP
brj-22095	78	19	leave	leave	VERB
brj-22095	78	20	-	-	PUNCT
brj-22095	78	21	one	one	NUM
brj-22095	78	22	-	-	PUNCT
brj-22095	78	23	out	out	ADP
brj-22095	78	24	cross	cross	NOUN
brj-22095	78	25	validation	validation	NOUN
brj-22095	78	26	(	(	PUNCT
brj-22095	78	27	zhang	zhang	X
brj-22095	78	28	et	et	PROPN
brj-22095	78	29	al	al	PROPN
brj-22095	78	30	.	.	PROPN
brj-22095	78	31	2022	2022	NUM
brj-22095	78	32	)	)	PUNCT
brj-22095	78	33	.	.	PUNCT
brj-22095	79	1	the	the	DET
brj-22095	79	2	calibration	calibration	NOUN
brj-22095	79	3	model	model	NOUN
brj-22095	79	4	and	and	CCONJ
brj-22095	79	5	model	model	NOUN
brj-22095	79	6	transfer	transfer	NOUN
brj-22095	79	7	effect	effect	NOUN
brj-22095	79	8	established	establish	VERB
brj-22095	79	9	using	use	VERB
brj-22095	79	10	plsr	plsr	NOUN
brj-22095	79	11	and	and	CCONJ
brj-22095	79	12	the	the	DET
brj-22095	79	13	model	model	NOUN
brj-22095	79	14	prediction	prediction	NOUN
brj-22095	79	15	ability	ability	NOUN
brj-22095	79	16	were	be	AUX
brj-22095	79	17	evaluated	evaluate	VERB
brj-22095	79	18	comprehensively	comprehensively	ADV
brj-22095	79	19	by	by	ADP
brj-22095	79	20	the	the	DET
brj-22095	79	21	coefficient	coefficient	NOUN
brj-22095	79	22	of	of	ADP
brj-22095	79	23	determination	determination	NOUN
brj-22095	79	24	(	(	PUNCT
brj-22095	79	25	r2	r2	PROPN
brj-22095	79	26	)	)	PUNCT
brj-22095	79	27	,	,	PUNCT
brj-22095	79	28	root	root	NOUN
brj-22095	79	29	-	-	PUNCT
brj-22095	79	30	mean	mean	NOUN
brj-22095	79	31	standard	standard	ADJ
brj-22095	79	32	error	error	NOUN
brj-22095	79	33	for	for	ADP
brj-22095	79	34	cross	cross	NOUN
brj-22095	79	35	-	-	ADJ
brj-22095	79	36	validation	validation	ADJ
brj-22095	79	37	(	(	PUNCT
brj-22095	79	38	rmsecv	rmsecv	NOUN
brj-22095	79	39	)	)	PUNCT
brj-22095	79	40	,	,	PUNCT
brj-22095	79	41	root	root	NOUN
brj-22095	79	42	mean	mean	VERB
brj-22095	79	43	square	square	ADJ
brj-22095	79	44	error	error	NOUN
brj-22095	79	45	of	of	ADP
brj-22095	79	46	prediction	prediction	NOUN
brj-22095	79	47	(	(	PUNCT
brj-22095	79	48	rmsep	rmsep	NOUN
brj-22095	79	49	)	)	PUNCT
brj-22095	79	50	,	,	PUNCT
brj-22095	79	51	and	and	CCONJ
brj-22095	79	52	relative	relative	ADJ
brj-22095	79	53	predictive	predictive	ADJ
brj-22095	79	54	determinant	determinant	ADJ
brj-22095	79	55	(	(	PUNCT
brj-22095	79	56	rpd	rpd	PROPN
brj-22095	79	57	)	)	PUNCT
brj-22095	79	58	between	between	ADP
brj-22095	79	59	the	the	DET
brj-22095	79	60	predicted	predict	VERB
brj-22095	79	61	and	and	CCONJ
brj-22095	79	62	true	true	ADJ
brj-22095	79	63	values	value	NOUN
brj-22095	79	64	of	of	ADP
brj-22095	79	65	the	the	DET
brj-22095	79	66	samples	sample	NOUN
brj-22095	79	67	in	in	ADP
brj-22095	79	68	order	order	NOUN
brj-22095	79	69	to	to	PART
brj-22095	79	70	establish	establish	VERB
brj-22095	79	71	the	the	DET
brj-22095	79	72	optimal	optimal	ADJ
brj-22095	79	73	prediction	prediction	NOUN
brj-22095	79	74	model	model	NOUN
brj-22095	79	75	.	.	PUNCT
brj-22095	80	1	among	among	ADP
brj-22095	80	2	them	they	PRON
brj-22095	80	3	,	,	PUNCT
brj-22095	80	4	the	the	PRON
brj-22095	80	5	closer	close	ADV
brj-22095	80	6	the	the	DET
brj-22095	80	7	coefficient	coefficient	NOUN
brj-22095	80	8	of	of	ADP
brj-22095	80	9	determination	determination	NOUN
brj-22095	80	10	r2	r2	PROPN
brj-22095	80	11	is	be	AUX
brj-22095	80	12	to	to	ADP
brj-22095	80	13	1	1	NUM
brj-22095	80	14	,	,	PUNCT
brj-22095	80	15	the	the	PRON
brj-22095	80	16	better	well	ADJ
brj-22095	80	17	the	the	DET
brj-22095	80	18	regression	regression	NOUN
brj-22095	80	19	or	or	CCONJ
brj-22095	80	20	prediction	prediction	NOUN
brj-22095	80	21	result	result	NOUN
brj-22095	80	22	of	of	ADP
brj-22095	80	23	the	the	DET
brj-22095	80	24	model	model	NOUN
brj-22095	80	25	,	,	PUNCT
brj-22095	80	26	and	and	CCONJ
brj-22095	80	27	if	if	SCONJ
brj-22095	80	28	r2	r2	PROPN
brj-22095	80	29	is	be	AUX
brj-22095	80	30	small	small	ADJ
brj-22095	80	31	,	,	PUNCT
brj-22095	80	32	it	it	PRON
brj-22095	80	33	indicates	indicate	VERB
brj-22095	80	34	a	a	DET
brj-22095	80	35	very	very	ADV
brj-22095	80	36	poor	poor	ADJ
brj-22095	80	37	fit	fit	NOUN
brj-22095	80	38	.	.	PUNCT
brj-22095	81	1	smaller	small	ADJ
brj-22095	81	2	rmsecv	rmsecv	ADJ
brj-22095	81	3	and	and	CCONJ
brj-22095	81	4	rmsep	rmsep	ADJ
brj-22095	81	5	values	value	NOUN
brj-22095	81	6	indicate	indicate	VERB
brj-22095	81	7	a	a	DET
brj-22095	81	8	better	well	ADJ
brj-22095	81	9	model	model	NOUN
brj-22095	81	10	effect	effect	NOUN
brj-22095	81	11	(	(	PUNCT
brj-22095	81	12	zhang	zhang	X
brj-22095	81	13	et	et	PROPN
brj-22095	81	14	al	al	PROPN
brj-22095	81	15	.	.	PROPN
brj-22095	81	16	2019	2019	NUM
brj-22095	81	17	;	;	PUNCT
brj-22095	81	18	fatchurrahman	fatchurrahman	NOUN
brj-22095	81	19	et	et	PROPN
brj-22095	81	20	al	al	PROPN
brj-22095	81	21	.	.	PROPN
brj-22095	81	22	2021	2021	NUM
brj-22095	81	23	)	)	PUNCT
brj-22095	81	24	;	;	PUNCT
brj-22095	81	25	rpd	rpd	PROPN
brj-22095	81	26	is	be	AUX
brj-22095	81	27	used	use	VERB
brj-22095	81	28	to	to	PART
brj-22095	81	29	verify	verify	VERB
brj-22095	81	30	sample	sample	NOUN
brj-22095	81	31	light	light	NOUN
brj-22095	81	32	source	source	NOUN
brj-22095	81	33	detector	detector	NOUN
brj-22095	81	34	45	45	NUM
brj-22095	81	35	°	°	NOUN
brj-22095	81	36	a	a	DET
brj-22095	81	37	b	b	PROPN
brj-22095	81	38	sample	sample	NOUN
brj-22095	81	39	detector	detector	NOUN
brj-22095	81	40	45	45	NUM
brj-22095	81	41	lig	lig	PROPN
brj-22095	81	42	t	t	PROPN
brj-22095	81	43	source	source	NOUN
brj-22095	81	44	a	a	DET
brj-22095	81	45	b	b	NOUN
brj-22095	81	46	peer	peer	NOUN
brj-22095	81	47	-	-	PUNCT
brj-22095	81	48	reviewed	review	VERB
brj-22095	81	49	article	article	NOUN
brj-22095	81	50	bioresources.com	bioresources.com	X
brj-22095	81	51	he	he	PRON
brj-22095	81	52	et	et	PROPN
brj-22095	81	53	al	al	PROPN
brj-22095	81	54	.	.	PROPN
brj-22095	82	1	(	(	PUNCT
brj-22095	82	2	2022	2022	NUM
brj-22095	82	3	)	)	PUNCT
brj-22095	82	4	.	.	PUNCT
brj-22095	83	1	“	"	PUNCT
brj-22095	83	2	near	near	ADP
brj-22095	83	3	ir	ir	PROPN
brj-22095	83	4	model	model	NOUN
brj-22095	83	5	of	of	ADP
brj-22095	83	6	biomass	biomass	NOUN
brj-22095	83	7	,	,	PUNCT
brj-22095	83	8	”	"	PUNCT
brj-22095	83	9	bioresources	bioresource	NOUN
brj-22095	83	10	17(4	17(4	NUM
brj-22095	83	11	)	)	PUNCT
brj-22095	83	12	,	,	PUNCT
brj-22095	83	13	6476	6476	NUM
brj-22095	83	14	-	-	SYM
brj-22095	83	15	6489	6489	NUM
brj-22095	83	16	.	.	PUNCT
brj-22095	84	1	6481	6481	NUM
brj-22095	84	2	the	the	DET
brj-22095	84	3	stability	stability	NOUN
brj-22095	84	4	and	and	CCONJ
brj-22095	84	5	predictive	predictive	ADJ
brj-22095	84	6	ability	ability	NOUN
brj-22095	84	7	of	of	ADP
brj-22095	84	8	the	the	DET
brj-22095	84	9	model	model	NOUN
brj-22095	84	10	.	.	PUNCT
brj-22095	85	1	the	the	DET
brj-22095	85	2	model	model	NOUN
brj-22095	85	3	is	be	AUX
brj-22095	85	4	good	good	ADJ
brj-22095	85	5	when	when	SCONJ
brj-22095	85	6	rpd>2.5	rpd>2.5	NOUN
brj-22095	85	7	,	,	PUNCT
brj-22095	85	8	average	average	ADJ
brj-22095	85	9	but	but	CCONJ
brj-22095	85	10	usable	usable	ADJ
brj-22095	85	11	when	when	SCONJ
brj-22095	85	12	rpd	rpd	PROPN
brj-22095	85	13	is	be	AUX
brj-22095	85	14	2	2	NUM
brj-22095	85	15	to	to	ADP
brj-22095	85	16	2.5	2.5	NUM
brj-22095	85	17	,	,	PUNCT
brj-22095	85	18	and	and	CCONJ
brj-22095	85	19	unusable	unusable	ADJ
brj-22095	85	20	when	when	SCONJ
brj-22095	85	21	rpd<2	rpd<2	NOUN
brj-22095	85	22	(	(	PUNCT
brj-22095	85	23	hao	hao	PROPN
brj-22095	85	24	et	et	PROPN
brj-22095	85	25	al	al	PROPN
brj-22095	85	26	.	.	PROPN
brj-22095	85	27	2022	2022	NUM
brj-22095	85	28	)	)	PUNCT
brj-22095	85	29	.	.	PUNCT
brj-22095	86	1	results	result	NOUN
brj-22095	86	2	and	and	CCONJ
brj-22095	86	3	discussion	discussion	NOUN
brj-22095	86	4	screening	screen	VERB
brj-22095	86	5	for	for	ADP
brj-22095	86	6	stable	stable	ADJ
brj-22095	86	7	and	and	CCONJ
brj-22095	86	8	consistent	consistent	ADJ
brj-22095	86	9	wavelengths	wavelength	NOUN
brj-22095	86	10	the	the	DET
brj-22095	86	11	number	number	NOUN
brj-22095	86	12	of	of	ADP
brj-22095	86	13	representative	representative	ADJ
brj-22095	86	14	samples	sample	NOUN
brj-22095	86	15	k	k	PROPN
brj-22095	86	16	selected	select	VERB
brj-22095	86	17	from	from	ADP
brj-22095	86	18	the	the	DET
brj-22095	86	19	master	master	NOUN
brj-22095	86	20	instrument	instrument	NOUN
brj-22095	86	21	samples	sample	NOUN
brj-22095	86	22	by	by	ADP
brj-22095	86	23	kennard	kennard	NOUN
brj-22095	86	24	-	-	PUNCT
brj-22095	86	25	stone	stone	NOUN
brj-22095	86	26	method	method	NOUN
brj-22095	86	27	was	be	AUX
brj-22095	86	28	5	5	NUM
brj-22095	86	29	,	,	PUNCT
brj-22095	86	30	10	10	NUM
brj-22095	86	31	,	,	PUNCT
brj-22095	86	32	15	15	NUM
brj-22095	86	33	,	,	PUNCT
brj-22095	86	34	and	and	CCONJ
brj-22095	86	35	20	20	NUM
brj-22095	86	36	,	,	PUNCT
brj-22095	86	37	and	and	CCONJ
brj-22095	86	38	these	these	DET
brj-22095	86	39	representative	representative	ADJ
brj-22095	86	40	samples	sample	NOUN
brj-22095	86	41	were	be	AUX
brj-22095	86	42	used	use	VERB
brj-22095	86	43	to	to	PART
brj-22095	86	44	screen	screen	VERB
brj-22095	86	45	the	the	DET
brj-22095	86	46	wavelength	wavelength	NOUN
brj-22095	86	47	uc	uc	INTJ
brj-22095	86	48	with	with	ADP
brj-22095	86	49	consistent	consistent	ADJ
brj-22095	86	50	and	and	CCONJ
brj-22095	86	51	stable	stable	ADJ
brj-22095	86	52	spectral	spectral	ADJ
brj-22095	86	53	signals	signal	NOUN
brj-22095	86	54	between	between	ADP
brj-22095	86	55	the	the	DET
brj-22095	86	56	master	master	NOUN
brj-22095	86	57	and	and	CCONJ
brj-22095	86	58	the	the	DET
brj-22095	86	59	target	target	NOUN
brj-22095	86	60	instruments	instrument	NOUN
brj-22095	86	61	.	.	PUNCT
brj-22095	87	1	the	the	DET
brj-22095	87	2	wavelength	wavelength	NOUN
brj-22095	87	3	set	set	VERB
brj-22095	87	4	uc	uc	PROPN
brj-22095	87	5	of	of	ADP
brj-22095	87	6	the	the	DET
brj-22095	87	7	master	master	NOUN
brj-22095	87	8	and	and	CCONJ
brj-22095	87	9	the	the	DET
brj-22095	87	10	target	target	NOUN
brj-22095	87	11	was	be	AUX
brj-22095	87	12	screened	screen	VERB
brj-22095	87	13	by	by	ADP
brj-22095	87	14	swcss	swcss	PROPN
brj-22095	87	15	method	method	NOUN
brj-22095	87	16	according	accord	VERB
brj-22095	87	17	to	to	ADP
brj-22095	87	18	the	the	DET
brj-22095	87	19	number	number	NOUN
brj-22095	87	20	of	of	ADP
brj-22095	87	21	different	different	ADJ
brj-22095	87	22	representative	representative	ADJ
brj-22095	87	23	samples	sample	NOUN
brj-22095	87	24	k.	k.	NOUN
brj-22095	88	1	using	use	VERB
brj-22095	88	2	the	the	DET
brj-22095	88	3	wavelength	wavelength	NOUN
brj-22095	88	4	set	set	VERB
brj-22095	88	5	uc	uc	PROPN
brj-22095	88	6	to	to	PART
brj-22095	88	7	build	build	VERB
brj-22095	88	8	a	a	DET
brj-22095	88	9	master	master	NOUN
brj-22095	88	10	model	model	NOUN
brj-22095	88	11	to	to	PART
brj-22095	88	12	predict	predict	VERB
brj-22095	88	13	the	the	DET
brj-22095	88	14	variation	variation	NOUN
brj-22095	88	15	of	of	ADP
brj-22095	88	16	rmsep	rmsep	NOUN
brj-22095	88	17	with	with	ADP
brj-22095	88	18	consistency	consistency	NOUN
brj-22095	88	19	parameter	parameter	NOUN
brj-22095	88	20	b	b	PROPN
brj-22095	88	21	value	value	NOUN
brj-22095	88	22	for	for	ADP
brj-22095	88	23	the	the	DET
brj-22095	88	24	prediction	prediction	NOUN
brj-22095	88	25	set	set	VERB
brj-22095	88	26	samples	sample	NOUN
brj-22095	88	27	of	of	ADP
brj-22095	88	28	the	the	DET
brj-22095	88	29	target	target	NOUN
brj-22095	88	30	(	(	PUNCT
brj-22095	88	31	as	as	SCONJ
brj-22095	88	32	shown	show	VERB
brj-22095	88	33	in	in	ADP
brj-22095	88	34	fig	fig	NOUN
brj-22095	88	35	.	.	PUNCT
brj-22095	89	1	2	2	NUM
brj-22095	89	2	)	)	PUNCT
brj-22095	89	3	.	.	PUNCT
brj-22095	90	1	during	during	ADP
brj-22095	90	2	the	the	DET
brj-22095	90	3	experiment	experiment	NOUN
brj-22095	90	4	,	,	PUNCT
brj-22095	90	5	the	the	DET
brj-22095	90	6	wavelength	wavelength	NOUN
brj-22095	90	7	set	set	NOUN
brj-22095	90	8	uc	uc	INTJ
brj-22095	90	9	was	be	AUX
brj-22095	90	10	screened	screen	VERB
brj-22095	90	11	by	by	ADP
brj-22095	90	12	setting	set	VERB
brj-22095	90	13	b	b	NOUN
brj-22095	90	14	to	to	PART
brj-22095	90	15	be	be	AUX
brj-22095	90	16	taken	take	VERB
brj-22095	90	17	from	from	ADP
brj-22095	90	18	1	1	NUM
brj-22095	90	19	to	to	ADP
brj-22095	90	20	10	10	NUM
brj-22095	90	21	,	,	PUNCT
brj-22095	90	22	but	but	CCONJ
brj-22095	90	23	when	when	SCONJ
brj-22095	90	24	b=1	b=1	PUNCT
brj-22095	90	25	the	the	DET
brj-22095	90	26	number	number	NOUN
brj-22095	90	27	of	of	ADP
brj-22095	90	28	wavelengths	wavelength	NOUN
brj-22095	90	29	selected	select	VERB
brj-22095	90	30	according	accord	VERB
brj-22095	90	31	to	to	ADP
brj-22095	90	32	the	the	DET
brj-22095	90	33	swcss	swcss	PROPN
brj-22095	90	34	algorithm	algorithm	PROPN
brj-22095	90	35	step	step	NOUN
brj-22095	90	36	was	be	AUX
brj-22095	90	37	0	0	NUM
brj-22095	90	38	,	,	PUNCT
brj-22095	90	39	and	and	CCONJ
brj-22095	90	40	the	the	DET
brj-22095	90	41	model	model	NOUN
brj-22095	90	42	could	could	AUX
brj-22095	90	43	not	not	PART
brj-22095	90	44	be	be	AUX
brj-22095	90	45	built	build	VERB
brj-22095	90	46	.	.	PUNCT
brj-22095	91	1	therefore	therefore	ADV
brj-22095	91	2	,	,	PUNCT
brj-22095	91	3	uc	uc	PROPN
brj-22095	91	4	was	be	AUX
brj-22095	91	5	screened	screen	VERB
brj-22095	91	6	by	by	ADP
brj-22095	91	7	setting	set	VERB
brj-22095	91	8	consistency	consistency	NOUN
brj-22095	91	9	the	the	DET
brj-22095	91	10	parameter	parameter	PROPN
brj-22095	91	11	b	b	PROPN
brj-22095	91	12	to	to	PART
brj-22095	91	13	take	take	VERB
brj-22095	91	14	2	2	NUM
brj-22095	91	15	to	to	ADP
brj-22095	91	16	10	10	NUM
brj-22095	91	17	.	.	PUNCT
brj-22095	92	1	the	the	DET
brj-22095	92	2	suitable	suitable	ADJ
brj-22095	92	3	b	b	PROPN
brj-22095	92	4	value	value	NOUN
brj-22095	92	5	was	be	AUX
brj-22095	92	6	selected	select	VERB
brj-22095	92	7	by	by	ADP
brj-22095	92	8	predicting	predict	VERB
brj-22095	92	9	the	the	DET
brj-22095	92	10	minimum	minimum	ADJ
brj-22095	92	11	rmsep	rmsep	NOUN
brj-22095	92	12	of	of	ADP
brj-22095	92	13	the	the	DET
brj-22095	92	14	target	target	NOUN
brj-22095	92	15	samples	sample	NOUN
brj-22095	92	16	with	with	ADP
brj-22095	92	17	the	the	DET
brj-22095	92	18	master	master	NOUN
brj-22095	92	19	plsr	plsr	NOUN
brj-22095	92	20	model	model	NOUN
brj-22095	92	21	for	for	ADP
brj-22095	92	22	both	both	CCONJ
brj-22095	92	23	the	the	DET
brj-22095	92	24	integrated	integrate	VERB
brj-22095	92	25	holocellulose	holocellulose	ADJ
brj-22095	92	26	and	and	CCONJ
brj-22095	92	27	lignin	lignin	NOUN
brj-22095	92	28	indexes	index	NOUN
brj-22095	92	29	,	,	PUNCT
brj-22095	92	30	respectively	respectively	ADV
brj-22095	92	31	.	.	PUNCT
brj-22095	93	1	from	from	ADP
brj-22095	93	2	fig	fig	NOUN
brj-22095	93	3	.	.	PUNCT
brj-22095	94	1	2	2	NUM
brj-22095	94	2	,	,	PUNCT
brj-22095	94	3	it	it	PRON
brj-22095	94	4	can	can	AUX
brj-22095	94	5	be	be	AUX
brj-22095	94	6	seen	see	VERB
brj-22095	94	7	that	that	SCONJ
brj-22095	94	8	the	the	DET
brj-22095	94	9	master	master	NOUN
brj-22095	94	10	model	model	NOUN
brj-22095	94	11	established	establish	VERB
brj-22095	94	12	by	by	ADP
brj-22095	94	13	the	the	DET
brj-22095	94	14	uc	uc	PROPN
brj-22095	94	15	wavelength	wavelength	NOUN
brj-22095	94	16	set	set	NOUN
brj-22095	94	17	screened	screen	VERB
brj-22095	94	18	by	by	ADP
brj-22095	94	19	selecting	select	VERB
brj-22095	94	20	5	5	NUM
brj-22095	94	21	representative	representative	NOUN
brj-22095	94	22	samples	sample	NOUN
brj-22095	94	23	for	for	ADP
brj-22095	94	24	holocellulose	holocellulose	ADJ
brj-22095	94	25	and	and	CCONJ
brj-22095	94	26	setting	set	VERB
brj-22095	94	27	b=7	b=7	NOUN
brj-22095	94	28	had	have	VERB
brj-22095	94	29	the	the	DET
brj-22095	94	30	best	good	ADJ
brj-22095	94	31	prediction	prediction	NOUN
brj-22095	94	32	effect	effect	NOUN
brj-22095	94	33	on	on	ADP
brj-22095	94	34	the	the	DET
brj-22095	94	35	target	target	NOUN
brj-22095	94	36	samples	sample	NOUN
brj-22095	94	37	.	.	PUNCT
brj-22095	95	1	the	the	DET
brj-22095	95	2	wavelength	wavelength	NOUN
brj-22095	95	3	set	set	NOUN
brj-22095	95	4	screened	screen	VERB
brj-22095	95	5	by	by	ADP
brj-22095	95	6	the	the	DET
brj-22095	95	7	swcss	swcss	PROPN
brj-22095	95	8	method	method	NOUN
brj-22095	95	9	based	base	VERB
brj-22095	95	10	on	on	ADP
brj-22095	95	11	holocellulose	holocellulose	PROPN
brj-22095	95	12	was	be	AUX
brj-22095	95	13	denoted	denote	VERB
brj-22095	95	14	as	as	ADP
brj-22095	95	15	uch	uch	ADJ
brj-22095	95	16	,	,	PUNCT
brj-22095	95	17	and	and	CCONJ
brj-22095	95	18	it	it	PRON
brj-22095	95	19	contained	contain	VERB
brj-22095	95	20	449	449	NUM
brj-22095	95	21	characteristic	characteristic	ADJ
brj-22095	95	22	wavelengths	wavelength	NOUN
brj-22095	95	23	with	with	ADP
brj-22095	95	24	consistent	consistent	ADJ
brj-22095	95	25	and	and	CCONJ
brj-22095	95	26	stable	stable	ADJ
brj-22095	95	27	signals	signal	NOUN
brj-22095	95	28	.	.	PUNCT
brj-22095	96	1	for	for	ADP
brj-22095	96	2	lignin	lignin	PROPN
brj-22095	96	3	,	,	PUNCT
brj-22095	96	4	20	20	NUM
brj-22095	96	5	representative	representative	NOUN
brj-22095	96	6	samples	sample	NOUN
brj-22095	96	7	were	be	AUX
brj-22095	96	8	selected	select	VERB
brj-22095	96	9	,	,	PUNCT
brj-22095	96	10	and	and	CCONJ
brj-22095	96	11	the	the	DET
brj-22095	96	12	uc	uc	PROPN
brj-22095	96	13	wavelength	wavelength	NOUN
brj-22095	96	14	set	set	VERB
brj-22095	96	15	with	with	ADP
brj-22095	96	16	b=8	b=8	NOUN
brj-22095	96	17	had	have	VERB
brj-22095	96	18	the	the	DET
brj-22095	96	19	best	good	ADJ
brj-22095	96	20	prediction	prediction	NOUN
brj-22095	96	21	.	.	PUNCT
brj-22095	97	1	the	the	DET
brj-22095	97	2	wavelength	wavelength	NOUN
brj-22095	97	3	set	set	NOUN
brj-22095	97	4	screened	screen	VERB
brj-22095	97	5	by	by	ADP
brj-22095	97	6	the	the	DET
brj-22095	97	7	swcss	swcss	PROPN
brj-22095	97	8	method	method	NOUN
brj-22095	97	9	based	base	VERB
brj-22095	97	10	on	on	ADP
brj-22095	97	11	lignin	lignin	PROPN
brj-22095	97	12	was	be	AUX
brj-22095	97	13	denoted	denote	VERB
brj-22095	97	14	as	as	ADP
brj-22095	97	15	ucl	ucl	PROPN
brj-22095	97	16	,	,	PUNCT
brj-22095	97	17	which	which	PRON
brj-22095	97	18	contained	contain	VERB
brj-22095	97	19	659	659	NUM
brj-22095	97	20	consistent	consistent	ADJ
brj-22095	97	21	and	and	CCONJ
brj-22095	97	22	stable	stable	ADJ
brj-22095	97	23	characteristic	characteristic	ADJ
brj-22095	97	24	wavelengths	wavelength	NOUN
brj-22095	97	25	.	.	PUNCT
brj-22095	98	1	since	since	SCONJ
brj-22095	98	2	there	there	PRON
brj-22095	98	3	were	be	VERB
brj-22095	98	4	no	no	DET
brj-22095	98	5	wavelength	wavelength	NOUN
brj-22095	98	6	points	point	NOUN
brj-22095	98	7	with	with	ADP
brj-22095	98	8	excessive	excessive	ADJ
brj-22095	98	9	sdpds	sdpds	ADJ
brj-22095	98	10	values	value	NOUN
brj-22095	98	11	in	in	ADP
brj-22095	98	12	uch	uch	NOUN
brj-22095	98	13	and	and	CCONJ
brj-22095	98	14	ucl	ucl	PROPN
brj-22095	98	15	,	,	PUNCT
brj-22095	98	16	the	the	DET
brj-22095	98	17	wavelength	wavelength	NOUN
brj-22095	98	18	sets	set	VERB
brj-22095	98	19	usch	usch	NOUN
brj-22095	98	20	and	and	CCONJ
brj-22095	98	21	uscl	uscl	NOUN
brj-22095	98	22	screened	screen	VERB
brj-22095	98	23	by	by	ADP
brj-22095	98	24	the	the	DET
brj-22095	98	25	swcss	swcss	PROPN
brj-22095	98	26	method	method	NOUN
brj-22095	98	27	based	base	VERB
brj-22095	98	28	on	on	ADP
brj-22095	98	29	holocellulose	holocellulose	NOUN
brj-22095	98	30	and	and	CCONJ
brj-22095	98	31	lignin	lignin	PROPN
brj-22095	98	32	have	have	VERB
brj-22095	98	33	449	449	NUM
brj-22095	98	34	and	and	CCONJ
brj-22095	98	35	659	659	NUM
brj-22095	98	36	consistent	consistent	ADJ
brj-22095	98	37	wavelengths	wavelength	NOUN
brj-22095	98	38	,	,	PUNCT
brj-22095	98	39	respectively	respectively	ADV
brj-22095	98	40	,	,	PUNCT
brj-22095	98	41	and	and	CCONJ
brj-22095	98	42	their	their	PRON
brj-22095	98	43	distributions	distribution	NOUN
brj-22095	98	44	are	be	AUX
brj-22095	98	45	shown	show	VERB
brj-22095	98	46	in	in	ADP
brj-22095	98	47	fig	fig	NOUN
brj-22095	98	48	.	.	PUNCT
brj-22095	99	1	3	3	X
brj-22095	99	2	.	.	X
brj-22095	99	3	fig	fig	NOUN
brj-22095	99	4	.	.	PUNCT
brj-22095	100	1	2	2	X
brj-22095	100	2	.	.	X
brj-22095	100	3	prediction	prediction	NOUN
brj-22095	100	4	of	of	ADP
brj-22095	100	5	rmsep	rmsep	NOUN
brj-22095	100	6	of	of	ADP
brj-22095	100	7	target	target	NOUN
brj-22095	100	8	instrument	instrument	NOUN
brj-22095	100	9	samples	sample	NOUN
brj-22095	100	10	with	with	ADP
brj-22095	100	11	the	the	DET
brj-22095	100	12	value	value	NOUN
brj-22095	100	13	of	of	ADP
brj-22095	100	14	consistency	consistency	NOUN
brj-22095	100	15	parameter	parameter	PROPN
brj-22095	100	16	b	b	PROPN
brj-22095	100	17	based	base	VERB
brj-22095	100	18	on	on	ADP
brj-22095	100	19	a	a	DET
brj-22095	100	20	master	master	NOUN
brj-22095	100	21	instrument	instrument	NOUN
brj-22095	100	22	holocellulose	holocellulose	PROPN
brj-22095	100	23	and	and	CCONJ
brj-22095	100	24	lignin	lignin	NOUN
brj-22095	100	25	model	model	NOUN
brj-22095	100	26	built	build	VERB
brj-22095	100	27	on	on	ADP
brj-22095	100	28	stable	stable	ADJ
brj-22095	100	29	consistency	consistency	NOUN
brj-22095	100	30	wavelengths	wavelength	NOUN
brj-22095	100	31	b	b	PROPN
brj-22095	100	32	value	value	NOUN
brj-22095	100	33	b	b	NOUN
brj-22095	100	34	value	value	NOUN
brj-22095	100	35	r	r	NOUN
brj-22095	100	36	m	m	NOUN
brj-22095	101	1	s	s	NOUN
brj-22095	101	2	e	e	NOUN
brj-22095	101	3	p	p	NOUN
brj-22095	101	4	r	r	NOUN
brj-22095	101	5	m	m	NOUN
brj-22095	101	6	s	s	X
brj-22095	101	7	e	e	NOUN
brj-22095	101	8	p	p	NOUN
brj-22095	101	9	holocellulose	holocellulose	VERB
brj-22095	101	10	lignin	lignin	PROPN
brj-22095	101	11	peer	peer	NOUN
brj-22095	101	12	-	-	PUNCT
brj-22095	101	13	reviewed	review	VERB
brj-22095	101	14	article	article	NOUN
brj-22095	101	15	bioresources.com	bioresources.com	X
brj-22095	101	16	he	he	PRON
brj-22095	101	17	et	et	PROPN
brj-22095	101	18	al	al	PROPN
brj-22095	101	19	.	.	PROPN
brj-22095	102	1	(	(	PUNCT
brj-22095	102	2	2022	2022	NUM
brj-22095	102	3	)	)	PUNCT
brj-22095	102	4	.	.	PUNCT
brj-22095	103	1	“	"	PUNCT
brj-22095	103	2	near	near	ADP
brj-22095	103	3	ir	ir	PROPN
brj-22095	103	4	model	model	NOUN
brj-22095	103	5	of	of	ADP
brj-22095	103	6	biomass	biomass	NOUN
brj-22095	103	7	,	,	PUNCT
brj-22095	103	8	”	"	PUNCT
brj-22095	103	9	bioresources	bioresource	NOUN
brj-22095	103	10	17(4	17(4	NUM
brj-22095	103	11	)	)	PUNCT
brj-22095	103	12	,	,	PUNCT
brj-22095	103	13	6476	6476	NUM
brj-22095	103	14	-	-	SYM
brj-22095	103	15	6489	6489	NUM
brj-22095	103	16	.	.	PUNCT
brj-22095	104	1	6482	6482	NUM
brj-22095	104	2	as	as	SCONJ
brj-22095	104	3	shown	show	VERB
brj-22095	104	4	in	in	ADP
brj-22095	104	5	fig	fig	NOUN
brj-22095	104	6	.	.	PUNCT
brj-22095	105	1	3	3	NUM
brj-22095	105	2	,	,	PUNCT
brj-22095	105	3	the	the	DET
brj-22095	105	4	wavelength	wavelength	NOUN
brj-22095	105	5	points	point	NOUN
brj-22095	105	6	usch	usch	VERB
brj-22095	105	7	and	and	CCONJ
brj-22095	105	8	uscl	uscl	NOUN
brj-22095	105	9	selected	select	VERB
brj-22095	105	10	by	by	ADP
brj-22095	105	11	the	the	DET
brj-22095	105	12	swcss	swcss	PROPN
brj-22095	105	13	method	method	NOUN
brj-22095	105	14	based	base	VERB
brj-22095	105	15	on	on	ADP
brj-22095	105	16	the	the	DET
brj-22095	105	17	two	two	NUM
brj-22095	105	18	indicators	indicator	NOUN
brj-22095	105	19	of	of	ADP
brj-22095	105	20	holocellulose	holocellulose	NOUN
brj-22095	105	21	and	and	CCONJ
brj-22095	105	22	lignin	lignin	NOUN
brj-22095	105	23	were	be	AUX
brj-22095	105	24	mainly	mainly	ADV
brj-22095	105	25	located	locate	VERB
brj-22095	105	26	in	in	ADP
brj-22095	105	27	the	the	DET
brj-22095	105	28	region	region	NOUN
brj-22095	105	29	where	where	SCONJ
brj-22095	105	30	the	the	DET
brj-22095	105	31	standard	standard	ADJ
brj-22095	105	32	deviation	deviation	NOUN
brj-22095	105	33	sddsi	sddsi	NOUN
brj-22095	105	34	between	between	ADP
brj-22095	105	35	the	the	DET
brj-22095	105	36	master	master	NOUN
brj-22095	105	37	and	and	CCONJ
brj-22095	105	38	the	the	DET
brj-22095	105	39	target	target	NOUN
brj-22095	105	40	was	be	AUX
brj-22095	105	41	small	small	ADJ
brj-22095	105	42	,	,	PUNCT
brj-22095	105	43	while	while	SCONJ
brj-22095	105	44	in	in	ADP
brj-22095	105	45	the	the	DET
brj-22095	105	46	regions	region	NOUN
brj-22095	105	47	with	with	ADP
brj-22095	105	48	large	large	ADJ
brj-22095	105	49	differences	difference	NOUN
brj-22095	105	50	such	such	ADJ
brj-22095	105	51	as	as	ADP
brj-22095	105	52	900	900	NUM
brj-22095	105	53	to	to	ADP
brj-22095	105	54	965	965	NUM
brj-22095	105	55	,	,	PUNCT
brj-22095	105	56	1056	1056	NUM
brj-22095	105	57	to	to	ADP
brj-22095	105	58	1058	1058	NUM
brj-22095	105	59	,	,	PUNCT
brj-22095	105	60	1064	1064	NUM
brj-22095	105	61	to	to	ADP
brj-22095	105	62	1068	1068	NUM
brj-22095	105	63	,	,	PUNCT
brj-22095	105	64	1072	1072	NUM
brj-22095	105	65	to	to	ADP
brj-22095	105	66	1079	1079	NUM
brj-22095	105	67	,	,	PUNCT
brj-22095	105	68	1630	1630	NUM
brj-22095	105	69	,	,	PUNCT
brj-22095	105	70	1636	1636	NUM
brj-22095	105	71	,	,	PUNCT
brj-22095	105	72	1640	1640	NUM
brj-22095	105	73	to	to	ADP
brj-22095	105	74	1641	1641	NUM
brj-22095	105	75	and	and	CCONJ
brj-22095	105	76	1644	1644	NUM
brj-22095	105	77	to	to	ADP
brj-22095	105	78	1700	1700	NUM
brj-22095	105	79	nm	nm	NOUN
brj-22095	105	80	,	,	PUNCT
brj-22095	105	81	none	none	NOUN
brj-22095	105	82	of	of	ADP
brj-22095	105	83	them	they	PRON
brj-22095	105	84	could	could	AUX
brj-22095	105	85	pass	pass	VERB
brj-22095	105	86	the	the	DET
brj-22095	105	87	swcss	swcss	PROPN
brj-22095	105	88	screening	screening	NOUN
brj-22095	105	89	.	.	PUNCT
brj-22095	106	1	fig	fig	NOUN
brj-22095	106	2	.	.	PUNCT
brj-22095	107	1	3	3	X
brj-22095	107	2	.	.	X
brj-22095	107	3	location	location	NOUN
brj-22095	107	4	distribution	distribution	NOUN
brj-22095	107	5	of	of	ADP
brj-22095	107	6	usch	usch	NOUN
brj-22095	107	7	and	and	CCONJ
brj-22095	107	8	uscl	uscl	NOUN
brj-22095	107	9	of	of	ADP
brj-22095	107	10	consistent	consistent	ADJ
brj-22095	107	11	wavelength	wavelength	NOUN
brj-22095	107	12	sets	set	NOUN
brj-22095	107	13	of	of	ADP
brj-22095	107	14	holocellulose	holocellulose	NOUN
brj-22095	107	15	and	and	CCONJ
brj-22095	107	16	lignin	lignin	NOUN
brj-22095	107	17	screened	screen	VERB
brj-22095	107	18	by	by	ADP
brj-22095	107	19	swcss	swcss	PROPN
brj-22095	107	20	method	method	NOUN
brj-22095	107	21	as	as	ADP
brj-22095	107	22	a	a	DET
brj-22095	107	23	further	further	ADJ
brj-22095	107	24	analysis	analysis	NOUN
brj-22095	107	25	,	,	PUNCT
brj-22095	107	26	the	the	DET
brj-22095	107	27	pca	pca	NOUN
brj-22095	107	28	method	method	NOUN
brj-22095	107	29	(	(	PUNCT
brj-22095	107	30	ferrara	ferrara	NOUN
brj-22095	107	31	et	et	PROPN
brj-22095	107	32	al	al	PROPN
brj-22095	107	33	.	.	PROPN
brj-22095	107	34	2022	2022	NUM
brj-22095	107	35	;	;	PUNCT
brj-22095	107	36	hasan	hasan	PROPN
brj-22095	107	37	et	et	PROPN
brj-22095	107	38	al	al	PROPN
brj-22095	107	39	.	.	PROPN
brj-22095	107	40	2022	2022	NUM
brj-22095	107	41	)	)	PUNCT
brj-22095	107	42	was	be	AUX
brj-22095	107	43	used	use	VERB
brj-22095	107	44	in	in	ADP
brj-22095	107	45	this	this	DET
brj-22095	107	46	study	study	NOUN
brj-22095	107	47	to	to	PART
brj-22095	107	48	characterize	characterize	VERB
brj-22095	107	49	the	the	DET
brj-22095	107	50	differences	difference	NOUN
brj-22095	107	51	in	in	ADP
brj-22095	107	52	spectra	spectra	NOUN
brj-22095	107	53	between	between	ADP
brj-22095	107	54	nir	nir	NOUN
brj-22095	107	55	spectroscopy	spectroscopy	NOUN
brj-22095	107	56	instruments	instrument	NOUN
brj-22095	107	57	.	.	PUNCT
brj-22095	108	1	the	the	DET
brj-22095	108	2	pca	pca	PROPN
brj-22095	108	3	scores	score	NOUN
brj-22095	108	4	of	of	ADP
brj-22095	108	5	56	56	NUM
brj-22095	108	6	calibration	calibration	NOUN
brj-22095	108	7	set	set	VERB
brj-22095	108	8	samples	sample	NOUN
brj-22095	108	9	for	for	ADP
brj-22095	108	10	the	the	DET
brj-22095	108	11	full	full	ADJ
brj-22095	108	12	spectra	spectra	NOUN
brj-22095	108	13	of	of	ADP
brj-22095	108	14	the	the	DET
brj-22095	108	15	2	2	NUM
brj-22095	108	16	instruments	instrument	NOUN
brj-22095	108	17	(	(	PUNCT
brj-22095	108	18	master	master	NOUN
brj-22095	108	19	and	and	CCONJ
brj-22095	108	20	target	target	VERB
brj-22095	108	21	)	)	PUNCT
brj-22095	108	22	and	and	CCONJ
brj-22095	108	23	the	the	DET
brj-22095	108	24	wavelength	wavelength	NOUN
brj-22095	108	25	set	set	NOUN
brj-22095	108	26	screened	screen	VERB
brj-22095	108	27	based	base	VERB
brj-22095	108	28	on	on	ADP
brj-22095	108	29	the	the	DET
brj-22095	108	30	swcss	swcss	PROPN
brj-22095	108	31	method	method	NOUN
brj-22095	108	32	were	be	AUX
brj-22095	108	33	calculated	calculate	VERB
brj-22095	108	34	,	,	PUNCT
brj-22095	108	35	and	and	CCONJ
brj-22095	108	36	the	the	DET
brj-22095	108	37	results	result	NOUN
brj-22095	108	38	are	be	AUX
brj-22095	108	39	shown	show	VERB
brj-22095	108	40	in	in	ADP
brj-22095	108	41	fig	fig	NOUN
brj-22095	108	42	.	.	PUNCT
brj-22095	109	1	4(a	4(a	NUM
brj-22095	109	2	)	)	PUNCT
brj-22095	109	3	and	and	CCONJ
brj-22095	109	4	fig	fig	NOUN
brj-22095	109	5	.	.	PUNCT
brj-22095	110	1	4(b	4(b	NUM
brj-22095	110	2	)	)	PUNCT
brj-22095	110	3	,	,	PUNCT
brj-22095	110	4	separately	separately	ADV
brj-22095	110	5	.	.	PUNCT
brj-22095	111	1	fig	fig	NOUN
brj-22095	111	2	.	.	PUNCT
brj-22095	112	1	4	4	X
brj-22095	112	2	.	.	X
brj-22095	112	3	principal	principal	ADJ
brj-22095	112	4	components	component	NOUN
brj-22095	112	5	2d	2d	NUM
brj-22095	112	6	score	score	NOUN
brj-22095	112	7	plot	plot	NOUN
brj-22095	112	8	of	of	ADP
brj-22095	112	9	2	2	NUM
brj-22095	112	10	instruments	instrument	NOUN
brj-22095	112	11	as	as	SCONJ
brj-22095	112	12	can	can	AUX
brj-22095	112	13	be	be	AUX
brj-22095	112	14	seen	see	VERB
brj-22095	112	15	in	in	ADP
brj-22095	112	16	fig	fig	NOUN
brj-22095	112	17	.	.	PUNCT
brj-22095	113	1	4(a	4(a	NUM
brj-22095	113	2	)	)	PUNCT
brj-22095	114	1	,	,	PUNCT
brj-22095	114	2	the	the	DET
brj-22095	114	3	differences	difference	NOUN
brj-22095	114	4	between	between	ADP
brj-22095	114	5	the	the	DET
brj-22095	114	6	master	master	NOUN
brj-22095	114	7	and	and	CCONJ
brj-22095	114	8	target	target	NOUN
brj-22095	114	9	instruments	instrument	NOUN
brj-22095	114	10	characterized	characterize	VERB
brj-22095	114	11	using	use	VERB
brj-22095	114	12	the	the	DET
brj-22095	114	13	full	full	ADJ
brj-22095	114	14	spectrum	spectrum	NOUN
brj-22095	114	15	pca	pca	NOUN
brj-22095	114	16	scores	score	NOUN
brj-22095	114	17	were	be	AUX
brj-22095	114	18	significant	significant	ADJ
brj-22095	114	19	because	because	SCONJ
brj-22095	114	20	the	the	DET
brj-22095	114	21	target	target	NOUN
brj-22095	114	22	and	and	CCONJ
brj-22095	114	23	master	master	NOUN
brj-22095	114	24	were	be	AUX
brj-22095	114	25	different	different	ADJ
brj-22095	114	26	types	type	NOUN
brj-22095	114	27	of	of	ADP
brj-22095	114	28	instruments	instrument	NOUN
brj-22095	114	29	,	,	PUNCT
brj-22095	114	30	and	and	CCONJ
brj-22095	114	31	their	their	PRON
brj-22095	114	32	irradiation	irradiation	NOUN
brj-22095	114	33	directions	direction	NOUN
brj-22095	114	34	,	,	PUNCT
brj-22095	114	35	light	light	ADJ
brj-22095	114	36	source	source	NOUN
brj-22095	114	37	power	power	NOUN
brj-22095	114	38	and	and	CCONJ
brj-22095	114	39	assembly	assembly	NOUN
brj-22095	114	40	processes	process	NOUN
brj-22095	114	41	were	be	AUX
brj-22095	114	42	different	different	ADJ
brj-22095	114	43	.	.	PUNCT
brj-22095	115	1	the	the	DET
brj-22095	115	2	average	average	ADJ
brj-22095	115	3	martensite	martensite	NOUN
brj-22095	115	4	distance	distance	NOUN
brj-22095	115	5	between	between	ADP
brj-22095	115	6	the	the	DET
brj-22095	115	7	master	master	NOUN
brj-22095	115	8	and	and	CCONJ
brj-22095	115	9	the	the	DET
brj-22095	115	10	target	target	NOUN
brj-22095	115	11	was	be	AUX
brj-22095	115	12	2.3679	2.3679	NUM
brj-22095	115	13	calculated	calculate	VERB
brj-22095	115	14	from	from	ADP
brj-22095	115	15	the	the	DET
brj-22095	115	16	sample	sample	NOUN
brj-22095	115	17	spectra	spectra	NOUN
brj-22095	115	18	.	.	PUNCT
brj-22095	116	1	as	as	SCONJ
brj-22095	116	2	can	can	AUX
brj-22095	116	3	be	be	AUX
brj-22095	116	4	seen	see	VERB
brj-22095	116	5	in	in	ADP
brj-22095	116	6	figs	fig	NOUN
brj-22095	116	7	.	.	PUNCT
brj-22095	117	1	3	3	NUM
brj-22095	117	2	and	and	CCONJ
brj-22095	117	3	4(b	4(b	NUM
brj-22095	117	4	)	)	PUNCT
brj-22095	117	5	,	,	PUNCT
brj-22095	117	6	the	the	DET
brj-22095	117	7	wavelengths	wavelength	NOUN
brj-22095	117	8	screened	screen	VERB
brj-22095	117	9	by	by	ADP
brj-22095	117	10	the	the	DET
brj-22095	117	11	swcss	swcss	PROPN
brj-22095	117	12	method	method	NOUN
brj-22095	117	13	were	be	AUX
brj-22095	117	14	mainly	mainly	ADV
brj-22095	117	15	located	locate	VERB
brj-22095	117	16	in	in	ADP
brj-22095	117	17	the	the	DET
brj-22095	117	18	wavelength	wavelength	NOUN
brj-22095	117	19	region	region	NOUN
brj-22095	117	20	where	where	SCONJ
brj-22095	117	21	the	the	DET
brj-22095	117	22	standard	standard	ADJ
brj-22095	117	23	deviation	deviation	NOUN
brj-22095	117	24	sddsi	sddsi	NOUN
brj-22095	117	25	of	of	ADP
brj-22095	117	26	the	the	DET
brj-22095	117	27	master	master	NOUN
brj-22095	117	28	and	and	CCONJ
brj-22095	117	29	pc1	pc1	PROPN
brj-22095	117	30	pc1	pc1	PROPN
brj-22095	118	1	p	p	PROPN
brj-22095	118	2	c	c	PROPN
brj-22095	118	3	2	2	NUM
brj-22095	118	4	p	p	NOUN
brj-22095	118	5	c	c	NOUN
brj-22095	118	6	2	2	NUM
brj-22095	118	7	a	a	DET
brj-22095	118	8	b	b	NOUN
brj-22095	118	9	wavelength	wavelength	NOUN
brj-22095	118	10	(	(	PUNCT
brj-22095	118	11	nm	nm	NOUN
brj-22095	118	12	)	)	PUNCT
brj-22095	118	13	wavelength	wavelength	NOUN
brj-22095	118	14	(	(	PUNCT
brj-22095	118	15	nm	nm	NOUN
brj-22095	118	16	)	)	PUNCT
brj-22095	118	17	a	a	DET
brj-22095	118	18	b	b	NOUN
brj-22095	118	19	s	s	PART
brj-22095	118	20	o	o	NOUN
brj-22095	118	21	rb	rb	NOUN
brj-22095	118	22	a	a	DET
brj-22095	118	23	n	n	NOUN
brj-22095	118	24	c	c	NOUN
brj-22095	118	25	e	e	NOUN
brj-22095	118	26	a	a	PRON
brj-22095	118	27	b	b	PROPN
brj-22095	118	28	s	s	PART
brj-22095	118	29	o	o	NOUN
brj-22095	118	30	rb	rb	NOUN
brj-22095	118	31	a	a	DET
brj-22095	118	32	n	n	NOUN
brj-22095	118	33	c	c	NOUN
brj-22095	118	34	e	e	NOUN
brj-22095	118	35	holocellulose	holocellulose	VERB
brj-22095	118	36	lignin	lignin	PROPN
brj-22095	118	37	peer	peer	NOUN
brj-22095	118	38	-	-	PUNCT
brj-22095	118	39	reviewed	review	VERB
brj-22095	118	40	article	article	NOUN
brj-22095	118	41	bioresources.com	bioresources.com	X
brj-22095	118	42	he	he	PRON
brj-22095	118	43	et	et	PROPN
brj-22095	118	44	al	al	PROPN
brj-22095	118	45	.	.	PROPN
brj-22095	119	1	(	(	PUNCT
brj-22095	119	2	2022	2022	NUM
brj-22095	119	3	)	)	PUNCT
brj-22095	119	4	.	.	PUNCT
brj-22095	120	1	“	"	PUNCT
brj-22095	120	2	near	near	ADP
brj-22095	120	3	ir	ir	PROPN
brj-22095	120	4	model	model	NOUN
brj-22095	120	5	of	of	ADP
brj-22095	120	6	biomass	biomass	NOUN
brj-22095	120	7	,	,	PUNCT
brj-22095	120	8	”	"	PUNCT
brj-22095	120	9	bioresources	bioresource	NOUN
brj-22095	120	10	17(4	17(4	NUM
brj-22095	120	11	)	)	PUNCT
brj-22095	120	12	,	,	PUNCT
brj-22095	120	13	6476	6476	NUM
brj-22095	120	14	-	-	SYM
brj-22095	120	15	6489	6489	NUM
brj-22095	120	16	.	.	PUNCT
brj-22095	121	1	6483	6483	NUM
brj-22095	121	2	target	target	NOUN
brj-22095	121	3	instruments	instrument	NOUN
brj-22095	121	4	is	be	AUX
brj-22095	121	5	small	small	ADJ
brj-22095	121	6	,	,	PUNCT
brj-22095	121	7	indicating	indicate	VERB
brj-22095	121	8	that	that	SCONJ
brj-22095	121	9	the	the	DET
brj-22095	121	10	selected	select	VERB
brj-22095	121	11	wavelengths	wavelength	NOUN
brj-22095	121	12	have	have	VERB
brj-22095	121	13	good	good	ADJ
brj-22095	121	14	consistency	consistency	NOUN
brj-22095	121	15	and	and	CCONJ
brj-22095	121	16	can	can	AUX
brj-22095	121	17	be	be	AUX
brj-22095	121	18	effectively	effectively	ADV
brj-22095	121	19	reduced	reduce	VERB
brj-22095	121	20	.	.	PUNCT
brj-22095	122	1	the	the	DET
brj-22095	122	2	difference	difference	NOUN
brj-22095	122	3	between	between	ADP
brj-22095	122	4	the	the	DET
brj-22095	122	5	two	two	NUM
brj-22095	122	6	spectrometers	spectrometer	NOUN
brj-22095	122	7	,	,	PUNCT
brj-22095	122	8	the	the	DET
brj-22095	122	9	average	average	ADJ
brj-22095	122	10	mahalanobis	mahalanobis	ADJ
brj-22095	122	11	distance	distance	NOUN
brj-22095	122	12	between	between	ADP
brj-22095	122	13	the	the	DET
brj-22095	122	14	master	master	NOUN
brj-22095	122	15	and	and	CCONJ
brj-22095	122	16	the	the	DET
brj-22095	122	17	target	target	NOUN
brj-22095	122	18	was	be	AUX
brj-22095	122	19	0.9585	0.9585	NUM
brj-22095	122	20	.	.	PUNCT
brj-22095	123	1	therefore	therefore	ADV
brj-22095	123	2	,	,	PUNCT
brj-22095	123	3	further	further	ADJ
brj-22095	123	4	correction	correction	NOUN
brj-22095	123	5	using	use	VERB
brj-22095	123	6	the	the	DET
brj-22095	123	7	s	s	PROPN
brj-22095	123	8	/	/	SYM
brj-22095	123	9	b	b	PROPN
brj-22095	123	10	method	method	NOUN
brj-22095	123	11	based	base	VERB
brj-22095	123	12	on	on	ADP
brj-22095	123	13	the	the	DET
brj-22095	123	14	consistent	consistent	ADJ
brj-22095	123	15	wavelengths	wavelength	NOUN
brj-22095	123	16	screened	screen	VERB
brj-22095	123	17	by	by	ADP
brj-22095	123	18	the	the	DET
brj-22095	123	19	swcss	swcss	PROPN
brj-22095	123	20	method	method	NOUN
brj-22095	123	21	may	may	AUX
brj-22095	123	22	enable	enable	VERB
brj-22095	123	23	the	the	DET
brj-22095	123	24	model	model	NOUN
brj-22095	123	25	built	build	VERB
brj-22095	123	26	on	on	ADP
brj-22095	123	27	the	the	DET
brj-22095	123	28	master	master	NOUN
brj-22095	123	29	instrument	instrument	NOUN
brj-22095	123	30	to	to	PART
brj-22095	123	31	achieve	achieve	VERB
brj-22095	123	32	higher	high	ADJ
brj-22095	123	33	prediction	prediction	NOUN
brj-22095	123	34	accuracy	accuracy	NOUN
brj-22095	123	35	on	on	ADP
brj-22095	123	36	the	the	DET
brj-22095	123	37	target	target	NOUN
brj-22095	123	38	instrument	instrument	NOUN
brj-22095	123	39	.	.	PUNCT
brj-22095	124	1	results	result	NOUN
brj-22095	124	2	and	and	CCONJ
brj-22095	124	3	analysis	analysis	NOUN
brj-22095	124	4	of	of	ADP
brj-22095	124	5	model	model	NOUN
brj-22095	124	6	transfer	transfer	NOUN
brj-22095	124	7	of	of	ADP
brj-22095	124	8	holocellulose	holocellulose	NOUN
brj-22095	124	9	and	and	CCONJ
brj-22095	124	10	lignin	lignin	NOUN
brj-22095	124	11	in	in	ADP
brj-22095	124	12	pulpwood	pulpwood	NOUN
brj-22095	124	13	synthesis	synthesis	NOUN
brj-22095	124	14	pre	pre	NOUN
brj-22095	124	15	-	-	NOUN
brj-22095	124	16	transfer	transfer	NOUN
brj-22095	124	17	modeling	modeling	NOUN
brj-22095	124	18	and	and	CCONJ
brj-22095	124	19	prediction	prediction	NOUN
brj-22095	124	20	of	of	ADP
brj-22095	124	21	holocellulose	holocellulose	ADJ
brj-22095	124	22	and	and	CCONJ
brj-22095	124	23	lignin	lignin	NOUN
brj-22095	124	24	models	model	NOUN
brj-22095	124	25	in	in	ADP
brj-22095	124	26	this	this	DET
brj-22095	124	27	study	study	NOUN
brj-22095	124	28	,	,	PUNCT
brj-22095	124	29	56	56	NUM
brj-22095	124	30	calibration	calibration	NOUN
brj-22095	124	31	set	set	VERB
brj-22095	124	32	samples	sample	NOUN
brj-22095	124	33	were	be	AUX
brj-22095	124	34	used	use	VERB
brj-22095	124	35	to	to	PART
brj-22095	124	36	build	build	VERB
brj-22095	124	37	plsr	plsr	NOUN
brj-22095	124	38	models	model	NOUN
brj-22095	124	39	for	for	ADP
brj-22095	124	40	holocellulose	holocellulose	ADJ
brj-22095	124	41	and	and	CCONJ
brj-22095	124	42	lignin	lignin	NOUN
brj-22095	124	43	contents	content	NOUN
brj-22095	124	44	of	of	ADP
brj-22095	124	45	the	the	DET
brj-22095	124	46	master	master	NOUN
brj-22095	124	47	instrument	instrument	NOUN
brj-22095	124	48	based	base	VERB
brj-22095	124	49	on	on	ADP
brj-22095	124	50	swcss	swcss	PROPN
brj-22095	124	51	and	and	CCONJ
brj-22095	124	52	fullspectrum	fullspectrum	ADJ
brj-22095	124	53	wavelengths	wavelength	NOUN
brj-22095	124	54	,	,	PUNCT
brj-22095	124	55	respectively	respectively	ADV
brj-22095	124	56	.	.	PUNCT
brj-22095	125	1	the	the	DET
brj-22095	125	2	appropriate	appropriate	ADJ
brj-22095	125	3	number	number	NOUN
brj-22095	125	4	of	of	ADP
brj-22095	125	5	latent	latent	NOUN
brj-22095	125	6	variables	variable	NOUN
brj-22095	125	7	(	(	PUNCT
brj-22095	125	8	lv	lv	PROPN
brj-22095	125	9	)	)	PUNCT
brj-22095	125	10	was	be	AUX
brj-22095	125	11	selected	select	VERB
brj-22095	125	12	by	by	ADP
brj-22095	125	13	the	the	DET
brj-22095	125	14	leave	leave	VERB
brj-22095	125	15	-	-	PUNCT
brj-22095	125	16	one	one	NUM
brj-22095	125	17	-	-	PUNCT
brj-22095	125	18	out	out	ADP
brj-22095	125	19	cross	cross	ADJ
brj-22095	125	20	-	-	ADJ
brj-22095	125	21	validation	validation	ADJ
brj-22095	125	22	method	method	NOUN
brj-22095	125	23	(	(	PUNCT
brj-22095	125	24	zhang	zhang	PROPN
brj-22095	125	25	et	et	PROPN
brj-22095	125	26	al	al	PROPN
brj-22095	125	27	.	.	PROPN
brj-22095	125	28	2022	2022	NUM
brj-22095	125	29	)	)	PUNCT
brj-22095	125	30	,	,	PUNCT
brj-22095	125	31	and	and	CCONJ
brj-22095	125	32	the	the	DET
brj-22095	125	33	results	result	NOUN
brj-22095	125	34	are	be	AUX
brj-22095	125	35	shown	show	VERB
brj-22095	125	36	in	in	ADP
brj-22095	125	37	table	table	NOUN
brj-22095	125	38	3	3	NUM
brj-22095	125	39	.	.	PUNCT
brj-22095	125	40	table	table	NOUN
brj-22095	125	41	3	3	NUM
brj-22095	125	42	.	.	PUNCT
brj-22095	125	43	prediction	prediction	NOUN
brj-22095	125	44	results	result	NOUN
brj-22095	125	45	of	of	ADP
brj-22095	125	46	master	master	NOUN
brj-22095	125	47	and	and	CCONJ
brj-22095	125	48	target	target	NOUN
brj-22095	125	49	prediction	prediction	NOUN
brj-22095	125	50	sets	set	NOUN
brj-22095	125	51	by	by	ADP
brj-22095	125	52	master	master	NOUN
brj-22095	125	53	instrument	instrument	PROPN
brj-22095	125	54	calibration	calibration	NOUN
brj-22095	125	55	model	model	NOUN
brj-22095	125	56	before	before	SCONJ
brj-22095	125	57	model	model	NOUN
brj-22095	125	58	transfer	transfer	NOUN
brj-22095	125	59	component	component	NOUN
brj-22095	125	60	met	meet	VERB
brj-22095	125	61	ods	ods	PROPN
brj-22095	125	62	lv	lv	PROPN
brj-22095	125	63	correction	correction	NOUN
brj-22095	125	64	set	set	VERB
brj-22095	125	65	prediction	prediction	NOUN
brj-22095	125	66	set	set	VERB
brj-22095	126	1	r2	r2	PROPN
brj-22095	126	2	rpd	rpd	PROPN
brj-22095	126	3	rmsep	rmsep	PROPN
brj-22095	126	4	r2	r2	PROPN
brj-22095	126	5	rpd	rpd	PROPN
brj-22095	126	6	rmsep	rmsep	PROPN
brj-22095	126	7	holocellulose	holocellulose	VERB
brj-22095	126	8	full	full	ADJ
brj-22095	126	9	spectrum	spectrum	NOUN
brj-22095	126	10	10	10	NUM
brj-22095	126	11	0.9641	0.9641	NUM
brj-22095	126	12	5.2796	5.2796	NUM
brj-22095	126	13	1.1202	1.1202	NUM
brj-22095	126	14	0.9598	0.9598	NUM
brj-22095	126	15	4.9847	4.9847	NUM
brj-22095	126	16	1.1335	1.1335	NUM
brj-22095	126	17	swcss	swcss	NOUN
brj-22095	126	18	9	9	NUM
brj-22095	126	19	0.9662	0.9662	NUM
brj-22095	126	20	5.4393	5.4393	NUM
brj-22095	126	21	1.0382	1.0382	NUM
brj-22095	126	22	0.9593	0.9593	NUM
brj-22095	126	23	4.9546	4.9546	NUM
brj-22095	126	24	1.1937	1.1937	NUM
brj-22095	126	25	lignin	lignin	PROPN
brj-22095	126	26	full	full	ADJ
brj-22095	126	27	spectrum	spectrum	NOUN
brj-22095	126	28	10	10	NUM
brj-22095	126	29	0.9644	0.9644	NUM
brj-22095	126	30	5.3000	5.3000	NUM
brj-22095	126	31	0.9945	0.9945	NUM
brj-22095	126	32	0.9475	0.9475	NUM
brj-22095	126	33	4.3638	4.3638	NUM
brj-22095	126	34	1.1490	1.1490	NUM
brj-22095	126	35	swcss	swcss	NOUN
brj-22095	126	36	8	8	NUM
brj-22095	126	37	0.9681	0.9681	NUM
brj-22095	126	38	5.5989	5.5989	NUM
brj-22095	126	39	0.9412	0.9412	NUM
brj-22095	126	40	0.9339	0.9339	NUM
brj-22095	126	41	3.8898	3.8898	NUM
brj-22095	126	42	1.2890	1.2890	NUM
brj-22095	126	43	fig	fig	NOUN
brj-22095	126	44	.	.	PUNCT
brj-22095	127	1	5	5	X
brj-22095	127	2	.	.	X
brj-22095	127	3	correlation	correlation	NOUN
brj-22095	127	4	diagram	diagram	NOUN
brj-22095	127	5	between	between	ADP
brj-22095	127	6	the	the	DET
brj-22095	127	7	measured	measured	ADJ
brj-22095	127	8	value	value	NOUN
brj-22095	127	9	and	and	CCONJ
brj-22095	127	10	the	the	DET
brj-22095	127	11	predicted	predict	VERB
brj-22095	127	12	value	value	NOUN
brj-22095	127	13	of	of	ADP
brj-22095	127	14	the	the	DET
brj-22095	127	15	master	master	NOUN
brj-22095	127	16	instrument	instrument	NOUN
brj-22095	127	17	sample	sample	NOUN
brj-22095	127	18	predicted	predict	VERB
brj-22095	127	19	by	by	ADP
brj-22095	127	20	the	the	DET
brj-22095	127	21	master	master	PROPN
brj-22095	127	22	instrument	instrument	PROPN
brj-22095	127	23	model	model	NOUN
brj-22095	127	24	established	establish	VERB
brj-22095	127	25	based	base	VERB
brj-22095	127	26	on	on	ADP
brj-22095	127	27	different	different	ADJ
brj-22095	127	28	wavelength	wavelength	NOUN
brj-22095	127	29	sets	set	NOUN
brj-22095	127	30	figure	figure	VERB
brj-22095	127	31	5	5	NUM
brj-22095	127	32	shows	show	VERB
brj-22095	127	33	the	the	DET
brj-22095	127	34	correlation	correlation	NOUN
brj-22095	127	35	plots	plot	NOUN
brj-22095	127	36	between	between	ADP
brj-22095	127	37	the	the	DET
brj-22095	127	38	measured	measure	VERB
brj-22095	127	39	and	and	CCONJ
brj-22095	127	40	predicted	predict	VERB
brj-22095	127	41	values	value	NOUN
brj-22095	127	42	of	of	ADP
brj-22095	127	43	holocellulose	holocellulose	ADJ
brj-22095	127	44	and	and	CCONJ
brj-22095	127	45	lignin	lignin	NOUN
brj-22095	127	46	contents	content	NOUN
brj-22095	127	47	for	for	ADP
brj-22095	127	48	the	the	DET
brj-22095	127	49	2	2	NUM
brj-22095	127	50	master	master	NOUN
brj-22095	127	51	calibration	calibration	NOUN
brj-22095	127	52	models	model	NOUN
brj-22095	127	53	in	in	ADP
brj-22095	127	54	table	table	NOUN
brj-22095	127	55	3	3	NUM
brj-22095	127	56	,	,	PUNCT
brj-22095	127	57	which	which	PRON
brj-22095	127	58	contains	contain	VERB
brj-22095	127	59	the	the	DET
brj-22095	127	60	fitted	fit	VERB
brj-22095	127	61	straight	straight	ADJ
brj-22095	127	62	lines	line	NOUN
brj-22095	127	63	of	of	ADP
brj-22095	127	64	the	the	DET
brj-22095	127	65	one	one	NUM
brj-22095	127	66	-	-	PUNCT
brj-22095	127	67	element	element	NOUN
brj-22095	127	68	regression	regression	NOUN
brj-22095	127	69	between	between	ADP
brj-22095	127	70	the	the	DET
brj-22095	127	71	predicted	predict	VERB
brj-22095	127	72	set	set	NOUN
brj-22095	127	73	of	of	ADP
brj-22095	127	74	p	p	PROPN
brj-22095	127	75	re	re	PROPN
brj-22095	127	76	d	d	NOUN
brj-22095	127	77	ic	ic	X
brj-22095	127	78	ti	ti	X
brj-22095	127	79	v	v	ADP
brj-22095	127	80	e	e	PROPN
brj-22095	127	81	v	v	ADP
brj-22095	127	82	a	a	DET
brj-22095	127	83	lu	lu	NOUN
brj-22095	127	84	e	e	NOUN
brj-22095	127	85	p	p	NOUN
brj-22095	127	86	re	re	PROPN
brj-22095	127	87	d	d	X
brj-22095	127	88	ic	ic	X
brj-22095	127	89	ti	ti	X
brj-22095	127	90	v	v	ADP
brj-22095	127	91	e	e	PROPN
brj-22095	127	92	v	v	ADP
brj-22095	127	93	a	a	DET
brj-22095	127	94	lu	lu	NOUN
brj-22095	127	95	e	e	NOUN
brj-22095	127	96	measured	measure	VERB
brj-22095	127	97	value	value	NOUN
brj-22095	127	98	measured	measure	VERB
brj-22095	127	99	value	value	NOUN
brj-22095	127	100	peer	peer	NOUN
brj-22095	127	101	-	-	PUNCT
brj-22095	127	102	reviewed	review	VERB
brj-22095	127	103	article	article	NOUN
brj-22095	127	104	bioresources.com	bioresources.com	X
brj-22095	127	105	he	he	PRON
brj-22095	127	106	et	et	PROPN
brj-22095	127	107	al	al	PROPN
brj-22095	127	108	.	.	PROPN
brj-22095	128	1	(	(	PUNCT
brj-22095	128	2	2022	2022	NUM
brj-22095	128	3	)	)	PUNCT
brj-22095	128	4	.	.	PUNCT
brj-22095	129	1	“	"	PUNCT
brj-22095	129	2	near	near	ADP
brj-22095	129	3	ir	ir	PROPN
brj-22095	129	4	model	model	NOUN
brj-22095	129	5	of	of	ADP
brj-22095	129	6	biomass	biomass	NOUN
brj-22095	129	7	,	,	PUNCT
brj-22095	129	8	”	"	PUNCT
brj-22095	129	9	bioresources	bioresource	NOUN
brj-22095	129	10	17(4	17(4	NUM
brj-22095	129	11	)	)	PUNCT
brj-22095	129	12	,	,	PUNCT
brj-22095	129	13	6476	6476	NUM
brj-22095	129	14	-	-	SYM
brj-22095	129	15	6489	6489	NUM
brj-22095	129	16	.	.	PUNCT
brj-22095	130	1	6484	6484	NUM
brj-22095	130	2	holocellulose	holocellulose	VERB
brj-22095	130	3	and	and	CCONJ
brj-22095	130	4	lignin	lignin	NOUN
brj-22095	130	5	contents	content	NOUN
brj-22095	130	6	and	and	CCONJ
brj-22095	130	7	the	the	DET
brj-22095	130	8	actual	actual	ADJ
brj-22095	130	9	contents	content	NOUN
brj-22095	130	10	of	of	ADP
brj-22095	130	11	the	the	DET
brj-22095	130	12	master	master	NOUN
brj-22095	130	13	samples	sample	NOUN
brj-22095	130	14	from	from	ADP
brj-22095	130	15	the	the	DET
brj-22095	130	16	master	master	NOUN
brj-22095	130	17	full	full	ADJ
brj-22095	130	18	-	-	PUNCT
brj-22095	130	19	spectrum	spectrum	NOUN
brj-22095	130	20	model	model	NOUN
brj-22095	130	21	analysis	analysis	NOUN
brj-22095	130	22	before	before	ADP
brj-22095	130	23	model	model	NOUN
brj-22095	130	24	transfer	transfer	NOUN
brj-22095	130	25	.	.	PUNCT
brj-22095	131	1	as	as	SCONJ
brj-22095	131	2	shown	show	VERB
brj-22095	131	3	in	in	ADP
brj-22095	131	4	table	table	NOUN
brj-22095	131	5	3	3	NUM
brj-22095	131	6	and	and	CCONJ
brj-22095	131	7	fig	fig	NOUN
brj-22095	131	8	.	.	PUNCT
brj-22095	132	1	5	5	NUM
brj-22095	132	2	,	,	PUNCT
brj-22095	132	3	the	the	DET
brj-22095	132	4	rpds	rpds	NOUN
brj-22095	132	5	of	of	ADP
brj-22095	132	6	the	the	DET
brj-22095	132	7	predicted	predict	VERB
brj-22095	132	8	results	result	NOUN
brj-22095	132	9	of	of	ADP
brj-22095	132	10	the	the	DET
brj-22095	132	11	master	master	NOUN
brj-22095	132	12	instrument	instrument	NOUN
brj-22095	132	13	calibration	calibration	NOUN
brj-22095	132	14	models	model	NOUN
brj-22095	132	15	based	base	VERB
brj-22095	132	16	on	on	ADP
brj-22095	132	17	the	the	DET
brj-22095	132	18	above	above	ADJ
brj-22095	132	19	different	different	ADJ
brj-22095	132	20	wavelength	wavelength	NOUN
brj-22095	132	21	sets	set	NOUN
brj-22095	132	22	are	be	AUX
brj-22095	132	23	all	all	ADV
brj-22095	132	24	greater	great	ADJ
brj-22095	132	25	than	than	ADP
brj-22095	132	26	3.8	3.8	NUM
brj-22095	132	27	.	.	PUNCT
brj-22095	133	1	the	the	DET
brj-22095	133	2	points	point	NOUN
brj-22095	133	3	corresponding	correspond	VERB
brj-22095	133	4	to	to	ADP
brj-22095	133	5	the	the	DET
brj-22095	133	6	predicted	predict	VERB
brj-22095	133	7	values	value	NOUN
brj-22095	133	8	are	be	AUX
brj-22095	133	9	all	all	PRON
brj-22095	133	10	roughly	roughly	ADV
brj-22095	133	11	distributed	distribute	VERB
brj-22095	133	12	around	around	ADP
brj-22095	133	13	the	the	DET
brj-22095	133	14	fitted	fit	VERB
brj-22095	133	15	straight	straight	ADJ
brj-22095	133	16	lines	line	NOUN
brj-22095	133	17	in	in	ADP
brj-22095	133	18	fig	fig	NOUN
brj-22095	133	19	.	.	PUNCT
brj-22095	134	1	5	5	NUM
brj-22095	134	2	,	,	PUNCT
brj-22095	134	3	and	and	CCONJ
brj-22095	134	4	the	the	DET
brj-22095	134	5	offset	offset	NOUN
brj-22095	134	6	is	be	AUX
brj-22095	134	7	small	small	ADJ
brj-22095	134	8	.	.	PUNCT
brj-22095	135	1	this	this	PRON
brj-22095	135	2	shows	show	VERB
brj-22095	135	3	that	that	SCONJ
brj-22095	135	4	the	the	DET
brj-22095	135	5	master	master	NOUN
brj-22095	135	6	instrument	instrument	NOUN
brj-22095	135	7	models	model	NOUN
brj-22095	135	8	established	establish	VERB
brj-22095	135	9	by	by	ADP
brj-22095	135	10	the	the	DET
brj-22095	135	11	above	above	ADJ
brj-22095	135	12	different	different	ADJ
brj-22095	135	13	wavelength	wavelength	NOUN
brj-22095	135	14	selection	selection	NOUN
brj-22095	135	15	methods	method	NOUN
brj-22095	135	16	can	can	AUX
brj-22095	135	17	meet	meet	VERB
brj-22095	135	18	the	the	DET
brj-22095	135	19	requirements	requirement	NOUN
brj-22095	135	20	of	of	ADP
brj-22095	135	21	practical	practical	ADJ
brj-22095	135	22	applications	application	NOUN
brj-22095	135	23	.	.	PUNCT
brj-22095	136	1	model	model	NOUN
brj-22095	136	2	transfer	transfer	NOUN
brj-22095	136	3	results	result	NOUN
brj-22095	136	4	and	and	CCONJ
brj-22095	136	5	analysis	analysis	NOUN
brj-22095	136	6	both	both	CCONJ
brj-22095	136	7	the	the	DET
brj-22095	136	8	full	full	ADJ
brj-22095	136	9	-	-	PUNCT
brj-22095	136	10	spectrum	spectrum	NOUN
brj-22095	136	11	-	-	PUNCT
brj-22095	136	12	based	base	VERB
brj-22095	136	13	s	s	PROPN
brj-22095	136	14	/	/	SYM
brj-22095	136	15	b	b	PROPN
brj-22095	136	16	and	and	CCONJ
brj-22095	136	17	swcss	swcss	PROPN
brj-22095	136	18	-	-	PUNCT
brj-22095	136	19	s	s	PROPN
brj-22095	136	20	/	/	SYM
brj-22095	136	21	b	b	NOUN
brj-22095	136	22	algorithms	algorithm	NOUN
brj-22095	136	23	are	be	AUX
brj-22095	136	24	standard	standard	ADJ
brj-22095	136	25	samples	sample	NOUN
brj-22095	136	26	algorithms	algorithm	NOUN
brj-22095	136	27	,	,	PUNCT
brj-22095	136	28	which	which	PRON
brj-22095	136	29	require	require	VERB
brj-22095	136	30	the	the	DET
brj-22095	136	31	selection	selection	NOUN
brj-22095	136	32	of	of	ADP
brj-22095	136	33	transfer	transfer	NOUN
brj-22095	136	34	set	set	VERB
brj-22095	136	35	samples	sample	NOUN
brj-22095	136	36	in	in	ADP
brj-22095	136	37	the	the	DET
brj-22095	136	38	scale	scale	NOUN
brj-22095	136	39	-	-	PUNCT
brj-22095	136	40	sets	set	NOUN
brj-22095	136	41	of	of	ADP
brj-22095	136	42	the	the	DET
brj-22095	136	43	master	master	NOUN
brj-22095	136	44	and	and	CCONJ
brj-22095	136	45	the	the	DET
brj-22095	136	46	target	target	NOUN
brj-22095	136	47	,	,	PUNCT
brj-22095	136	48	respectively	respectively	ADV
brj-22095	136	49	.	.	PUNCT
brj-22095	137	1	therefore	therefore	ADV
brj-22095	137	2	,	,	PUNCT
brj-22095	137	3	the	the	DET
brj-22095	137	4	kennard	kennard	NOUN
brj-22095	137	5	-	-	PUNCT
brj-22095	137	6	stone	stone	NOUN
brj-22095	137	7	algorithm	algorithm	NOUN
brj-22095	137	8	was	be	AUX
brj-22095	137	9	used	use	VERB
brj-22095	137	10	to	to	PART
brj-22095	137	11	take	take	VERB
brj-22095	137	12	5	5	NUM
brj-22095	137	13	,	,	PUNCT
brj-22095	137	14	10	10	NUM
brj-22095	137	15	,	,	PUNCT
brj-22095	137	16	15	15	NUM
brj-22095	137	17	,	,	PUNCT
brj-22095	137	18	20	20	NUM
brj-22095	137	19	,	,	PUNCT
brj-22095	137	20	25	25	NUM
brj-22095	137	21	,	,	PUNCT
brj-22095	137	22	30	30	NUM
brj-22095	137	23	,	,	PUNCT
brj-22095	137	24	35	35	NUM
brj-22095	137	25	,	,	PUNCT
brj-22095	137	26	and	and	CCONJ
brj-22095	137	27	40	40	NUM
brj-22095	137	28	samples	sample	NOUN
brj-22095	137	29	in	in	ADP
brj-22095	137	30	the	the	DET
brj-22095	137	31	specimen	speciman	NOUN
brj-22095	137	32	sets	set	NOUN
brj-22095	137	33	of	of	ADP
brj-22095	137	34	the	the	DET
brj-22095	137	35	master	master	NOUN
brj-22095	137	36	and	and	CCONJ
brj-22095	137	37	target	target	NOUN
brj-22095	137	38	instruments	instrument	NOUN
brj-22095	137	39	respectively	respectively	ADV
brj-22095	137	40	as	as	ADP
brj-22095	137	41	the	the	DET
brj-22095	137	42	transfer	transfer	NOUN
brj-22095	137	43	sets	set	NOUN
brj-22095	137	44	for	for	ADP
brj-22095	137	45	model	model	NOUN
brj-22095	137	46	transfer	transfer	NOUN
brj-22095	137	47	.	.	PUNCT
brj-22095	138	1	the	the	DET
brj-22095	138	2	relationship	relationship	NOUN
brj-22095	138	3	between	between	ADP
brj-22095	138	4	the	the	DET
brj-22095	138	5	number	number	NOUN
brj-22095	138	6	of	of	ADP
brj-22095	138	7	samples	sample	NOUN
brj-22095	138	8	in	in	ADP
brj-22095	138	9	the	the	DET
brj-22095	138	10	transfer	transfer	NOUN
brj-22095	138	11	set	set	VERB
brj-22095	138	12	and	and	CCONJ
brj-22095	138	13	the	the	DET
brj-22095	138	14	rmsep	rmsep	NOUN
brj-22095	138	15	is	be	AUX
brj-22095	138	16	shown	show	VERB
brj-22095	138	17	in	in	ADP
brj-22095	138	18	fig	fig	NOUN
brj-22095	138	19	.	.	PUNCT
brj-22095	139	1	6	6	NUM
brj-22095	139	2	.	.	X
brj-22095	139	3	the	the	DET
brj-22095	139	4	best	good	ADJ
brj-22095	139	5	prediction	prediction	NOUN
brj-22095	139	6	of	of	ADP
brj-22095	139	7	holocellulose	holocellulose	NOUN
brj-22095	139	8	and	and	CCONJ
brj-22095	139	9	lignin	lignin	NOUN
brj-22095	139	10	was	be	AUX
brj-22095	139	11	achieved	achieve	VERB
brj-22095	139	12	by	by	ADP
brj-22095	139	13	selecting	select	VERB
brj-22095	139	14	5	5	NUM
brj-22095	139	15	and	and	CCONJ
brj-22095	139	16	20	20	NUM
brj-22095	139	17	transfer	transfer	NOUN
brj-22095	139	18	set	set	VERB
brj-22095	139	19	samples	sample	NOUN
brj-22095	139	20	respectively	respectively	ADV
brj-22095	139	21	in	in	ADP
brj-22095	139	22	the	the	DET
brj-22095	139	23	model	model	NOUN
brj-22095	139	24	transfer	transfer	NOUN
brj-22095	139	25	process	process	NOUN
brj-22095	139	26	using	use	VERB
brj-22095	139	27	s	s	PART
brj-22095	139	28	/	/	SYM
brj-22095	139	29	b	b	NOUN
brj-22095	139	30	algorithm	algorithm	NOUN
brj-22095	139	31	.	.	PUNCT
brj-22095	140	1	the	the	DET
brj-22095	140	2	best	good	ADJ
brj-22095	140	3	prediction	prediction	NOUN
brj-22095	140	4	of	of	ADP
brj-22095	140	5	holocellulose	holocellulose	NOUN
brj-22095	140	6	and	and	CCONJ
brj-22095	140	7	lignin	lignin	NOUN
brj-22095	140	8	was	be	AUX
brj-22095	140	9	achieved	achieve	VERB
brj-22095	140	10	by	by	ADP
brj-22095	140	11	selecting	select	VERB
brj-22095	140	12	25	25	NUM
brj-22095	140	13	and	and	CCONJ
brj-22095	140	14	30	30	NUM
brj-22095	140	15	transfer	transfer	NOUN
brj-22095	140	16	set	set	VERB
brj-22095	140	17	samples	sample	NOUN
brj-22095	140	18	respectively	respectively	ADV
brj-22095	140	19	in	in	ADP
brj-22095	140	20	the	the	DET
brj-22095	140	21	model	model	NOUN
brj-22095	140	22	transfer	transfer	NOUN
brj-22095	140	23	process	process	NOUN
brj-22095	140	24	between	between	ADP
brj-22095	140	25	the	the	DET
brj-22095	140	26	master	master	NOUN
brj-22095	140	27	and	and	CCONJ
brj-22095	140	28	target	target	NOUN
brj-22095	140	29	instruments	instrument	NOUN
brj-22095	140	30	using	use	VERB
brj-22095	140	31	the	the	DET
brj-22095	140	32	swcss	swcss	PROPN
brj-22095	140	33	-	-	PUNCT
brj-22095	140	34	s	s	PROPN
brj-22095	140	35	/	/	SYM
brj-22095	140	36	b	b	NOUN
brj-22095	140	37	algorithm	algorithm	NOUN
brj-22095	140	38	.	.	PUNCT
brj-22095	141	1	fig	fig	NOUN
brj-22095	141	2	.	.	PUNCT
brj-22095	142	1	6	6	X
brj-22095	142	2	.	.	X
brj-22095	142	3	master	master	NOUN
brj-22095	142	4	's	's	PART
brj-22095	142	5	holocellulose	holocellulose	ADJ
brj-22095	142	6	and	and	CCONJ
brj-22095	142	7	lignin	lignin	NOUN
brj-22095	142	8	models	model	NOUN
brj-22095	142	9	predict	predict	VERB
brj-22095	142	10	target	target	NOUN
brj-22095	142	11	's	's	PART
brj-22095	142	12	rmsep	rmsep	NOUN
brj-22095	142	13	as	as	ADP
brj-22095	142	14	a	a	DET
brj-22095	142	15	function	function	NOUN
brj-22095	142	16	of	of	ADP
brj-22095	142	17	the	the	DET
brj-22095	142	18	number	number	NOUN
brj-22095	142	19	of	of	ADP
brj-22095	142	20	samples	sample	NOUN
brj-22095	142	21	in	in	ADP
brj-22095	142	22	the	the	DET
brj-22095	142	23	transform	transform	NOUN
brj-22095	142	24	set	set	VERB
brj-22095	142	25	to	to	PART
brj-22095	142	26	further	far	ADV
brj-22095	142	27	analyze	analyze	VERB
brj-22095	142	28	the	the	DET
brj-22095	142	29	transfer	transfer	NOUN
brj-22095	142	30	effect	effect	NOUN
brj-22095	142	31	of	of	ADP
brj-22095	142	32	the	the	DET
brj-22095	142	33	swcss	swcss	PROPN
brj-22095	142	34	-	-	PUNCT
brj-22095	142	35	s	s	PROPN
brj-22095	142	36	/	/	SYM
brj-22095	142	37	b	b	NOUN
brj-22095	142	38	algorithm	algorithm	NOUN
brj-22095	142	39	proposed	propose	VERB
brj-22095	142	40	in	in	ADP
brj-22095	142	41	this	this	DET
brj-22095	142	42	study	study	NOUN
brj-22095	142	43	,	,	PUNCT
brj-22095	142	44	the	the	DET
brj-22095	142	45	optimal	optimal	ADJ
brj-22095	142	46	number	number	NOUN
brj-22095	142	47	of	of	ADP
brj-22095	142	48	transfer	transfer	NOUN
brj-22095	142	49	set	set	VERB
brj-22095	142	50	samples	sample	NOUN
brj-22095	142	51	selected	select	VERB
brj-22095	142	52	by	by	ADP
brj-22095	142	53	the	the	DET
brj-22095	142	54	s	s	PROPN
brj-22095	142	55	/	/	SYM
brj-22095	142	56	b	b	PROPN
brj-22095	142	57	and	and	CCONJ
brj-22095	142	58	swcss	swcss	PROPN
brj-22095	142	59	-	-	PUNCT
brj-22095	142	60	s	s	PROPN
brj-22095	142	61	/	/	SYM
brj-22095	142	62	b	b	NOUN
brj-22095	142	63	algorithms	algorithm	NOUN
brj-22095	142	64	were	be	AUX
brj-22095	142	65	used	use	VERB
brj-22095	142	66	for	for	ADP
brj-22095	142	67	model	model	NOUN
brj-22095	142	68	transfer	transfer	NOUN
brj-22095	142	69	of	of	ADP
brj-22095	142	70	26	26	NUM
brj-22095	142	71	prediction	prediction	NOUN
brj-22095	142	72	set	set	VERB
brj-22095	142	73	samples	sample	NOUN
brj-22095	142	74	from	from	ADP
brj-22095	142	75	the	the	DET
brj-22095	142	76	target	target	NOUN
brj-22095	142	77	instrument	instrument	NOUN
brj-22095	142	78	,	,	PUNCT
brj-22095	142	79	separately	separately	ADV
brj-22095	142	80	,	,	PUNCT
brj-22095	142	81	and	and	CCONJ
brj-22095	142	82	compared	compare	VERB
brj-22095	142	83	with	with	ADP
brj-22095	142	84	the	the	DET
brj-22095	142	85	swcss	swcss	PROPN
brj-22095	142	86	,	,	PUNCT
brj-22095	142	87	s	s	PROPN
brj-22095	142	88	/	/	SYM
brj-22095	142	89	b	b	PROPN
brj-22095	142	90	,	,	PUNCT
brj-22095	142	91	pds	pds	NOUN
brj-22095	142	92	,	,	PUNCT
brj-22095	142	93	and	and	CCONJ
brj-22095	142	94	ds	ds	PRON
brj-22095	142	95	algorithms	algorithm	NOUN
brj-22095	142	96	alone	alone	ADV
brj-22095	142	97	.	.	PUNCT
brj-22095	143	1	results	result	NOUN
brj-22095	143	2	are	be	AUX
brj-22095	143	3	shown	show	VERB
brj-22095	143	4	in	in	ADP
brj-22095	143	5	table	table	NOUN
brj-22095	143	6	4	4	NUM
brj-22095	143	7	.	.	PUNCT
brj-22095	144	1	there	there	PRON
brj-22095	144	2	was	be	VERB
brj-22095	144	3	a	a	DET
brj-22095	144	4	large	large	ADJ
brj-22095	144	5	prediction	prediction	NOUN
brj-22095	144	6	error	error	NOUN
brj-22095	144	7	when	when	SCONJ
brj-22095	144	8	the	the	DET
brj-22095	144	9	fullspectrum	fullspectrum	ADJ
brj-22095	144	10	model	model	NOUN
brj-22095	144	11	of	of	ADP
brj-22095	144	12	the	the	DET
brj-22095	144	13	master	master	NOUN
brj-22095	144	14	was	be	AUX
brj-22095	144	15	used	use	VERB
brj-22095	144	16	to	to	PART
brj-22095	144	17	analyze	analyze	VERB
brj-22095	144	18	the	the	DET
brj-22095	144	19	target	target	NOUN
brj-22095	144	20	measurement	measurement	NOUN
brj-22095	144	21	samples	sample	NOUN
brj-22095	144	22	directly	directly	ADV
brj-22095	144	23	,	,	PUNCT
brj-22095	144	24	and	and	CCONJ
brj-22095	144	25	the	the	DET
brj-22095	144	26	rpds	rpds	NOUN
brj-22095	144	27	of	of	ADP
brj-22095	144	28	the	the	DET
brj-22095	144	29	predicted	predict	VERB
brj-22095	144	30	holocellulose	holocellulose	NOUN
brj-22095	144	31	and	and	CCONJ
brj-22095	144	32	lignin	lignin	NOUN
brj-22095	144	33	were	be	AUX
brj-22095	144	34	1.0815	1.0815	NUM
brj-22095	144	35	and	and	CCONJ
brj-22095	144	36	0.6527	0.6527	NUM
brj-22095	144	37	,	,	PUNCT
brj-22095	144	38	respectively	respectively	ADV
brj-22095	144	39	,	,	PUNCT
brj-22095	144	40	which	which	PRON
brj-22095	144	41	can	can	AUX
brj-22095	144	42	not	not	PART
brj-22095	144	43	meet	meet	VERB
brj-22095	144	44	the	the	DET
brj-22095	144	45	practical	practical	ADJ
brj-22095	144	46	application	application	NOUN
brj-22095	144	47	requirements	requirement	NOUN
brj-22095	144	48	.	.	PUNCT
brj-22095	145	1	the	the	DET
brj-22095	145	2	prediction	prediction	NOUN
brj-22095	145	3	effect	effect	NOUN
brj-22095	145	4	of	of	ADP
brj-22095	145	5	the	the	DET
brj-22095	145	6	pds	pds	NOUN
brj-22095	145	7	and	and	CCONJ
brj-22095	145	8	s	s	PROPN
brj-22095	145	9	/	/	SYM
brj-22095	145	10	b	b	NOUN
brj-22095	145	11	algorithms	algorithm	NOUN
brj-22095	145	12	alone	alone	ADV
brj-22095	145	13	for	for	ADP
brj-22095	145	14	the	the	DET
brj-22095	145	15	target	target	NOUN
brj-22095	145	16	instrument	instrument	NOUN
brj-22095	145	17	was	be	AUX
brj-22095	145	18	somewhat	somewhat	ADV
brj-22095	145	19	improved	improve	VERB
brj-22095	145	20	relative	relative	ADJ
brj-22095	145	21	to	to	ADP
brj-22095	145	22	that	that	PRON
brj-22095	145	23	before	before	ADP
brj-22095	145	24	model	model	NOUN
brj-22095	145	25	transfer	transfer	NOUN
brj-22095	145	26	,	,	PUNCT
brj-22095	145	27	but	but	CCONJ
brj-22095	145	28	the	the	DET
brj-22095	145	29	rpds	rpds	NOUN
brj-22095	145	30	of	of	ADP
brj-22095	145	31	both	both	DET
brj-22095	145	32	algorithms	algorithm	NOUN
brj-22095	145	33	were	be	AUX
brj-22095	145	34	less	less	ADJ
brj-22095	145	35	than	than	ADP
brj-22095	145	36	2.5	2.5	NUM
brj-22095	145	37	,	,	PUNCT
brj-22095	145	38	and	and	CCONJ
brj-22095	145	39	the	the	DET
brj-22095	145	40	prediction	prediction	NOUN
brj-22095	145	41	accuracy	accuracy	NOUN
brj-22095	145	42	was	be	AUX
brj-22095	145	43	not	not	PART
brj-22095	145	44	high	high	ADJ
brj-22095	145	45	.	.	PUNCT
brj-22095	146	1	in	in	ADP
brj-22095	146	2	contrast	contrast	NOUN
brj-22095	146	3	,	,	PUNCT
brj-22095	146	4	the	the	DET
brj-22095	146	5	transfer	transfer	NOUN
brj-22095	146	6	effect	effect	NOUN
brj-22095	146	7	of	of	ADP
brj-22095	146	8	using	use	VERB
brj-22095	146	9	number	number	NOUN
brj-22095	146	10	of	of	ADP
brj-22095	146	11	transfer	transfer	NOUN
brj-22095	146	12	set	set	VERB
brj-22095	146	13	samples	sample	NOUN
brj-22095	146	14	number	number	NOUN
brj-22095	146	15	of	of	ADP
brj-22095	146	16	transfer	transfer	NOUN
brj-22095	146	17	set	set	VERB
brj-22095	146	18	samples	sample	NOUN
brj-22095	147	1	r	r	NOUN
brj-22095	147	2	m	m	NOUN
brj-22095	147	3	s	s	NOUN
brj-22095	147	4	e	e	NOUN
brj-22095	147	5	p	p	NOUN
brj-22095	147	6	r	r	NOUN
brj-22095	147	7	m	m	NOUN
brj-22095	147	8	s	s	NOUN
brj-22095	147	9	e	e	NOUN
brj-22095	147	10	p	p	NOUN
brj-22095	147	11	peer	peer	NOUN
brj-22095	147	12	-	-	PUNCT
brj-22095	147	13	reviewed	review	VERB
brj-22095	147	14	article	article	NOUN
brj-22095	147	15	bioresources.com	bioresources.com	X
brj-22095	147	16	he	he	PRON
brj-22095	147	17	et	et	PROPN
brj-22095	147	18	al	al	PROPN
brj-22095	147	19	.	.	PROPN
brj-22095	147	20	(	(	PUNCT
brj-22095	147	21	2022	2022	NUM
brj-22095	147	22	)	)	PUNCT
brj-22095	147	23	.	.	PUNCT
brj-22095	148	1	“	"	PUNCT
brj-22095	148	2	near	near	ADP
brj-22095	148	3	ir	ir	PROPN
brj-22095	148	4	model	model	NOUN
brj-22095	148	5	of	of	ADP
brj-22095	148	6	biomass	biomass	NOUN
brj-22095	148	7	,	,	PUNCT
brj-22095	148	8	”	"	PUNCT
brj-22095	148	9	bioresources	bioresource	NOUN
brj-22095	148	10	17(4	17(4	NUM
brj-22095	148	11	)	)	PUNCT
brj-22095	148	12	,	,	PUNCT
brj-22095	148	13	6476	6476	NUM
brj-22095	148	14	-	-	SYM
brj-22095	148	15	6489	6489	NUM
brj-22095	148	16	.	.	PUNCT
brj-22095	149	1	6485	6485	NUM
brj-22095	149	2	the	the	DET
brj-22095	149	3	swcss	swcss	PROPN
brj-22095	149	4	-	-	PUNCT
brj-22095	149	5	s	s	PROPN
brj-22095	149	6	/	/	SYM
brj-22095	149	7	b	b	NOUN
brj-22095	149	8	algorithm	algorithm	NOUN
brj-22095	149	9	was	be	AUX
brj-22095	149	10	significantly	significantly	ADV
brj-22095	149	11	improved	improve	VERB
brj-22095	149	12	,	,	PUNCT
brj-22095	149	13	and	and	CCONJ
brj-22095	149	14	the	the	DET
brj-22095	149	15	rpds	rpds	NOUN
brj-22095	149	16	of	of	ADP
brj-22095	149	17	predicting	predict	VERB
brj-22095	149	18	the	the	DET
brj-22095	149	19	target	target	NOUN
brj-22095	149	20	instrument	instrument	NOUN
brj-22095	149	21	holocellulose	holocellulose	NOUN
brj-22095	149	22	and	and	CCONJ
brj-22095	149	23	lignin	lignin	NOUN
brj-22095	149	24	were	be	AUX
brj-22095	149	25	4.8746	4.8746	NUM
brj-22095	149	26	and	and	CCONJ
brj-22095	149	27	3.7157	3.7157	NUM
brj-22095	149	28	,	,	PUNCT
brj-22095	149	29	respectively	respectively	ADV
brj-22095	149	30	,	,	PUNCT
brj-22095	149	31	which	which	PRON
brj-22095	149	32	were	be	AUX
brj-22095	149	33	close	close	ADJ
brj-22095	149	34	to	to	ADP
brj-22095	149	35	the	the	DET
brj-22095	149	36	transfer	transfer	NOUN
brj-22095	149	37	results	result	NOUN
brj-22095	149	38	of	of	ADP
brj-22095	149	39	the	the	DET
brj-22095	149	40	ds	ds	ADJ
brj-22095	149	41	algorithm	algorithm	NOUN
brj-22095	149	42	.	.	PUNCT
brj-22095	150	1	this	this	PRON
brj-22095	150	2	indicates	indicate	VERB
brj-22095	150	3	that	that	SCONJ
brj-22095	150	4	the	the	DET
brj-22095	150	5	swcss	swcss	PROPN
brj-22095	150	6	-	-	PUNCT
brj-22095	150	7	s	s	PROPN
brj-22095	150	8	/	/	SYM
brj-22095	150	9	b	b	PROPN
brj-22095	150	10	method	method	NOUN
brj-22095	150	11	had	have	VERB
brj-22095	150	12	better	well	ADJ
brj-22095	150	13	stability	stability	NOUN
brj-22095	150	14	and	and	CCONJ
brj-22095	150	15	transfer	transfer	VERB
brj-22095	150	16	effect	effect	NOUN
brj-22095	150	17	than	than	ADP
brj-22095	150	18	the	the	DET
brj-22095	150	19	swcss	swcss	PROPN
brj-22095	150	20	and	and	CCONJ
brj-22095	150	21	s	s	PROPN
brj-22095	150	22	/	/	SYM
brj-22095	150	23	b	b	NOUN
brj-22095	150	24	algorithms	algorithm	NOUN
brj-22095	150	25	alone	alone	ADV
brj-22095	150	26	.	.	PUNCT
brj-22095	151	1	this	this	PRON
brj-22095	151	2	is	be	AUX
brj-22095	151	3	because	because	SCONJ
brj-22095	151	4	the	the	DET
brj-22095	151	5	consistent	consistent	ADJ
brj-22095	151	6	wavelengths	wavelength	NOUN
brj-22095	151	7	screened	screen	VERB
brj-22095	151	8	by	by	ADP
brj-22095	151	9	the	the	DET
brj-22095	151	10	swcss	swcss	PROPN
brj-22095	151	11	method	method	NOUN
brj-22095	151	12	are	be	AUX
brj-22095	151	13	located	locate	VERB
brj-22095	151	14	in	in	ADP
brj-22095	151	15	the	the	DET
brj-22095	151	16	wavelength	wavelength	NOUN
brj-22095	151	17	region	region	NOUN
brj-22095	151	18	with	with	ADP
brj-22095	151	19	small	small	ADJ
brj-22095	151	20	differences	difference	NOUN
brj-22095	151	21	between	between	ADP
brj-22095	151	22	instruments	instrument	NOUN
brj-22095	151	23	,	,	PUNCT
brj-22095	151	24	which	which	PRON
brj-22095	151	25	greatly	greatly	ADV
brj-22095	151	26	reduces	reduce	VERB
brj-22095	151	27	the	the	DET
brj-22095	151	28	differences	difference	NOUN
brj-22095	151	29	between	between	ADP
brj-22095	151	30	the	the	DET
brj-22095	151	31	master	master	NOUN
brj-22095	151	32	and	and	CCONJ
brj-22095	151	33	target	target	NOUN
brj-22095	151	34	instruments	instrument	NOUN
brj-22095	151	35	,	,	PUNCT
brj-22095	151	36	and	and	CCONJ
brj-22095	151	37	then	then	ADV
brj-22095	151	38	the	the	DET
brj-22095	151	39	s	s	PROPN
brj-22095	151	40	/	/	SYM
brj-22095	151	41	b	b	NOUN
brj-22095	151	42	algorithm	algorithm	NOUN
brj-22095	151	43	is	be	AUX
brj-22095	151	44	used	use	VERB
brj-22095	151	45	to	to	PART
brj-22095	151	46	further	far	ADV
brj-22095	151	47	correct	correct	VERB
brj-22095	151	48	the	the	DET
brj-22095	151	49	systematic	systematic	ADJ
brj-22095	151	50	errors	error	NOUN
brj-22095	151	51	that	that	PRON
brj-22095	151	52	still	still	ADV
brj-22095	151	53	exist	exist	VERB
brj-22095	151	54	after	after	SCONJ
brj-22095	151	55	the	the	DET
brj-22095	151	56	swcss	swcss	PROPN
brj-22095	151	57	correction	correction	NOUN
brj-22095	151	58	can	can	AUX
brj-22095	151	59	achieve	achieve	VERB
brj-22095	151	60	better	well	ADJ
brj-22095	151	61	model	model	NOUN
brj-22095	151	62	transfer	transfer	NOUN
brj-22095	151	63	results	result	NOUN
brj-22095	151	64	.	.	PUNCT
brj-22095	152	1	although	although	SCONJ
brj-22095	152	2	the	the	DET
brj-22095	152	3	transfer	transfer	NOUN
brj-22095	152	4	effect	effect	NOUN
brj-22095	152	5	of	of	ADP
brj-22095	152	6	the	the	DET
brj-22095	152	7	swcss	swcss	PROPN
brj-22095	152	8	-	-	PUNCT
brj-22095	152	9	s	s	PROPN
brj-22095	152	10	/	/	SYM
brj-22095	152	11	b	b	NOUN
brj-22095	152	12	method	method	NOUN
brj-22095	152	13	is	be	AUX
brj-22095	152	14	slightly	slightly	ADV
brj-22095	152	15	inferior	inferior	ADJ
brj-22095	152	16	to	to	ADP
brj-22095	152	17	that	that	PRON
brj-22095	152	18	of	of	ADP
brj-22095	152	19	the	the	DET
brj-22095	152	20	ds	ds	ADJ
brj-22095	152	21	algorithm	algorithm	NOUN
brj-22095	152	22	,	,	PUNCT
brj-22095	152	23	in	in	ADP
brj-22095	152	24	practical	practical	ADJ
brj-22095	152	25	applications	application	NOUN
brj-22095	152	26	the	the	DET
brj-22095	152	27	former	former	ADJ
brj-22095	152	28	is	be	AUX
brj-22095	152	29	involved	involve	VERB
brj-22095	152	30	in	in	ADP
brj-22095	152	31	holocellulose	holocellulose	ADJ
brj-22095	152	32	and	and	CCONJ
brj-22095	152	33	lignin	lignin	NOUN
brj-22095	152	34	model	model	NOUN
brj-22095	152	35	transfer	transfer	NOUN
brj-22095	152	36	at	at	ADP
brj-22095	152	37	449	449	NUM
brj-22095	152	38	and	and	CCONJ
brj-22095	152	39	659	659	NUM
brj-22095	152	40	wavelengths	wavelength	NOUN
brj-22095	152	41	,	,	PUNCT
brj-22095	152	42	respectively	respectively	ADV
brj-22095	152	43	,	,	PUNCT
brj-22095	152	44	with	with	ADP
brj-22095	152	45	fewer	few	ADJ
brj-22095	152	46	wavelength	wavelength	NOUN
brj-22095	152	47	variables	variable	NOUN
brj-22095	152	48	and	and	CCONJ
brj-22095	152	49	faster	fast	ADJ
brj-22095	152	50	computing	computing	NOUN
brj-22095	152	51	speed	speed	NOUN
brj-22095	152	52	,	,	PUNCT
brj-22095	152	53	which	which	PRON
brj-22095	152	54	is	be	AUX
brj-22095	152	55	convenient	convenient	ADJ
brj-22095	152	56	for	for	ADP
brj-22095	152	57	practical	practical	ADJ
brj-22095	152	58	applications	application	NOUN
brj-22095	152	59	.	.	PUNCT
brj-22095	153	1	table	table	NOUN
brj-22095	153	2	4	4	NUM
brj-22095	153	3	.	.	PUNCT
brj-22095	154	1	transfer	transfer	NOUN
brj-22095	154	2	effect	effect	NOUN
brj-22095	154	3	of	of	ADP
brj-22095	154	4	different	different	ADJ
brj-22095	154	5	model	model	NOUN
brj-22095	154	6	transfer	transfer	NOUN
brj-22095	154	7	methods	method	NOUN
brj-22095	154	8	component	component	NOUN
brj-22095	154	9	met	meet	VERB
brj-22095	154	10	ods	ods	PROPN
brj-22095	154	11	master	master	PROPN
brj-22095	154	12	target	target	PROPN
brj-22095	154	13	r2	r2	PROPN
brj-22095	154	14	rpd	rpd	PROPN
brj-22095	154	15	rmsep	rmsep	PROPN
brj-22095	154	16	r2	r2	PROPN
brj-22095	154	17	rpd	rpd	PROPN
brj-22095	154	18	rmsep	rmsep	PROPN
brj-22095	154	19	holocellulose	holocellulose	VERB
brj-22095	154	20	full	full	ADJ
brj-22095	154	21	spectrum	spectrum	NOUN
brj-22095	154	22	0.9598	0.9598	NUM
brj-22095	154	23	4.9847	4.9847	NUM
brj-22095	154	24	1.1335	1.1335	NUM
brj-22095	154	25	0.1450	0.1450	NUM
brj-22095	154	26	1.0815	1.0815	NUM
brj-22095	154	27	5.4686	5.4686	NUM
brj-22095	154	28	pds	pds	NOUN
brj-22095	154	29	0.8058	0.8058	NUM
brj-22095	154	30	2.2695	2.2695	NUM
brj-22095	154	31	2.3030	2.3030	NUM
brj-22095	154	32	ds	ds	NOUN
brj-22095	154	33	0.9645	0.9645	NUM
brj-22095	154	34	5.3051	5.3051	NUM
brj-22095	154	35	1.1148	1.1148	NUM
brj-22095	154	36	s	s	NOUN
brj-22095	154	37	/	/	SYM
brj-22095	154	38	b	b	NOUN
brj-22095	154	39	0.8042	0.8042	NUM
brj-22095	154	40	2.2599	2.2599	NUM
brj-22095	154	41	2.6169	2.6169	NUM
brj-22095	154	42	swcss	swcss	NOUN
brj-22095	154	43	0.9593	0.9593	NUM
brj-22095	154	44	4.9546	4.9546	NUM
brj-22095	154	45	1.1937	1.1937	NUM
brj-22095	154	46	0.9205	0.9205	NUM
brj-22095	155	1	3.5475	3.5475	NUM
brj-22095	155	2	1.6671	1.6671	NUM
brj-22095	155	3	swcsss	swcsss	NOUN
brj-22095	155	4	/	/	SYM
brj-22095	155	5	b	b	NOUN
brj-22095	155	6	0.9579	0.9579	NUM
brj-22095	155	7	4.8746	4.8746	NUM
brj-22095	155	8	1.2133	1.2133	NUM
brj-22095	155	9	lignin	lignin	NOUN
brj-22095	155	10	full	full	ADJ
brj-22095	155	11	spectrum	spectrum	NOUN
brj-22095	155	12	0.9475	0.9475	NUM
brj-22095	155	13	4.3638	4.3638	NUM
brj-22095	155	14	1.1490	1.1490	NUM
brj-22095	155	15	-1.3475	-1.3475	NOUN
brj-22095	155	16	0.6527	0.6527	NUM
brj-22095	155	17	7.6823	7.6823	NUM
brj-22095	155	18	pds	pds	NOUN
brj-22095	155	19	0.8050	0.8050	NUM
brj-22095	155	20	2.2647	2.2647	NUM
brj-22095	155	21	2.2140	2.2140	NUM
brj-22095	155	22	ds	ds	PRON
brj-22095	155	23	0.9481	0.9481	NUM
brj-22095	155	24	4.3914	4.3914	NUM
brj-22095	155	25	1.1418	1.1418	NUM
brj-22095	155	26	s	s	NOUN
brj-22095	155	27	/	/	SYM
brj-22095	155	28	b	b	NOUN
brj-22095	155	29	0.7549	0.7549	NUM
brj-22095	155	30	2.0199	2.0199	NUM
brj-22095	155	31	2.4825	2.4825	NUM
brj-22095	155	32	swcss	swcss	NOUN
brj-22095	155	33	0.9339	0.9339	NUM
brj-22095	155	34	3.8898	3.8898	NUM
brj-22095	155	35	1.2890	1.2890	NUM
brj-22095	155	36	0.8700	0.8700	NUM
brj-22095	155	37	2.7733	2.7733	NUM
brj-22095	155	38	1.8079	1.8079	NUM
brj-22095	155	39	swcsss	swcsss	NOUN
brj-22095	155	40	/	/	SYM
brj-22095	155	41	b	b	NOUN
brj-22095	155	42	0.9276	0.9276	NUM
brj-22095	155	43	3.7157	3.7157	NUM
brj-22095	155	44	1.3494	1.3494	NUM
brj-22095	155	45	figures	figure	NOUN
brj-22095	155	46	7	7	NUM
brj-22095	155	47	and	and	CCONJ
brj-22095	155	48	8	8	NUM
brj-22095	155	49	are	be	AUX
brj-22095	155	50	the	the	DET
brj-22095	155	51	correlation	correlation	NOUN
brj-22095	155	52	diagrams	diagram	NOUN
brj-22095	155	53	and	and	CCONJ
brj-22095	155	54	their	their	PRON
brj-22095	155	55	distribution	distribution	NOUN
brj-22095	155	56	diagrams	diagram	NOUN
brj-22095	155	57	of	of	ADP
brj-22095	155	58	the	the	DET
brj-22095	155	59	measured	measure	VERB
brj-22095	155	60	and	and	CCONJ
brj-22095	155	61	predicted	predict	VERB
brj-22095	155	62	values	value	NOUN
brj-22095	155	63	of	of	ADP
brj-22095	155	64	the	the	DET
brj-22095	155	65	holocellulose	holocellulose	ADJ
brj-22095	155	66	and	and	CCONJ
brj-22095	155	67	lignin	lignin	NOUN
brj-22095	155	68	contents	content	NOUN
brj-22095	155	69	of	of	ADP
brj-22095	155	70	the	the	DET
brj-22095	155	71	target	target	NOUN
brj-22095	155	72	instrument	instrument	NOUN
brj-22095	155	73	before	before	ADV
brj-22095	155	74	and	and	CCONJ
brj-22095	155	75	after	after	ADP
brj-22095	155	76	transfer	transfer	NOUN
brj-22095	155	77	using	use	VERB
brj-22095	155	78	different	different	ADJ
brj-22095	155	79	models	model	NOUN
brj-22095	155	80	such	such	ADJ
brj-22095	155	81	as	as	ADP
brj-22095	155	82	ds	ds	ADJ
brj-22095	155	83	,	,	PUNCT
brj-22095	155	84	pds	pds	NOUN
brj-22095	155	85	,	,	PUNCT
brj-22095	155	86	swcss	swcss	PROPN
brj-22095	155	87	,	,	PUNCT
brj-22095	155	88	and	and	CCONJ
brj-22095	155	89	s	s	X
brj-22095	155	90	/	/	SYM
brj-22095	155	91	b	b	NOUN
brj-22095	155	92	independently	independently	ADV
brj-22095	155	93	and	and	CCONJ
brj-22095	155	94	in	in	ADP
brj-22095	155	95	combination	combination	NOUN
brj-22095	155	96	.	.	PUNCT
brj-22095	156	1	as	as	ADP
brj-22095	156	2	a	a	DET
brj-22095	156	3	reference	reference	NOUN
brj-22095	156	4	,	,	PUNCT
brj-22095	156	5	the	the	DET
brj-22095	156	6	figure	figure	NOUN
brj-22095	156	7	also	also	ADV
brj-22095	156	8	draws	draw	VERB
brj-22095	156	9	a	a	DET
brj-22095	156	10	single	single	ADJ
brj-22095	156	11	regression	regression	NOUN
brj-22095	156	12	fitting	fitting	ADJ
brj-22095	156	13	straight	straight	ADJ
brj-22095	156	14	line	line	NOUN
brj-22095	156	15	between	between	ADP
brj-22095	156	16	the	the	DET
brj-22095	156	17	predicted	predict	VERB
brj-22095	156	18	and	and	CCONJ
brj-22095	156	19	actual	actual	ADJ
brj-22095	156	20	content	content	NOUN
brj-22095	156	21	of	of	ADP
brj-22095	156	22	holocellulose	holocellulose	NOUN
brj-22095	156	23	and	and	CCONJ
brj-22095	156	24	lignin	lignin	NOUN
brj-22095	156	25	in	in	ADP
brj-22095	156	26	the	the	DET
brj-22095	156	27	master	master	NOUN
brj-22095	156	28	instrument	instrument	NOUN
brj-22095	156	29	samples	sample	NOUN
brj-22095	156	30	analyzed	analyze	VERB
brj-22095	156	31	by	by	ADP
brj-22095	156	32	the	the	DET
brj-22095	156	33	master	master	PROPN
brj-22095	156	34	instrument	instrument	NOUN
brj-22095	156	35	full	full	ADJ
brj-22095	156	36	spectrum	spectrum	NOUN
brj-22095	156	37	model	model	NOUN
brj-22095	156	38	.	.	PUNCT
brj-22095	157	1	as	as	SCONJ
brj-22095	157	2	can	can	AUX
brj-22095	157	3	be	be	AUX
brj-22095	157	4	seen	see	VERB
brj-22095	157	5	in	in	ADP
brj-22095	157	6	figs	fig	NOUN
brj-22095	157	7	.	.	PUNCT
brj-22095	158	1	7	7	NUM
brj-22095	158	2	and	and	CCONJ
brj-22095	158	3	8	8	NUM
brj-22095	158	4	,	,	PUNCT
brj-22095	158	5	before	before	ADP
brj-22095	158	6	the	the	DET
brj-22095	158	7	model	model	NOUN
brj-22095	158	8	transfer	transfer	NOUN
brj-22095	158	9	,	,	PUNCT
brj-22095	158	10	the	the	DET
brj-22095	158	11	master	master	NOUN
brj-22095	158	12	instrument	instrument	NOUN
brj-22095	158	13	model	model	NOUN
brj-22095	158	14	had	have	VERB
brj-22095	158	15	the	the	DET
brj-22095	158	16	worst	bad	ADJ
brj-22095	158	17	prediction	prediction	NOUN
brj-22095	158	18	results	result	NOUN
brj-22095	158	19	for	for	ADP
brj-22095	158	20	the	the	DET
brj-22095	158	21	holocellulose	holocellulose	ADJ
brj-22095	158	22	and	and	CCONJ
brj-22095	158	23	lignin	lignin	NOUN
brj-22095	158	24	content	content	NOUN
brj-22095	158	25	of	of	ADP
brj-22095	158	26	the	the	DET
brj-22095	158	27	target	target	NOUN
brj-22095	158	28	instrument	instrument	NOUN
brj-22095	158	29	samples	sample	NOUN
brj-22095	158	30	,	,	PUNCT
brj-22095	158	31	and	and	CCONJ
brj-22095	158	32	the	the	DET
brj-22095	158	33	longitudinal	longitudinal	ADJ
brj-22095	158	34	offset	offset	NOUN
brj-22095	158	35	was	be	AUX
brj-22095	158	36	also	also	ADV
brj-22095	158	37	the	the	DET
brj-22095	158	38	largest	large	ADJ
brj-22095	158	39	.	.	PUNCT
brj-22095	159	1	the	the	DET
brj-22095	159	2	transfer	transfer	NOUN
brj-22095	159	3	results	result	NOUN
brj-22095	159	4	of	of	ADP
brj-22095	159	5	the	the	DET
brj-22095	159	6	pds	pds	NOUN
brj-22095	159	7	and	and	CCONJ
brj-22095	159	8	s	s	PROPN
brj-22095	159	9	/	/	SYM
brj-22095	159	10	b	b	NOUN
brj-22095	159	11	methods	method	NOUN
brj-22095	159	12	were	be	AUX
brj-22095	159	13	poor	poor	ADJ
brj-22095	159	14	,	,	PUNCT
brj-22095	159	15	the	the	DET
brj-22095	159	16	predicted	predict	VERB
brj-22095	159	17	values	value	NOUN
brj-22095	159	18	were	be	AUX
brj-22095	159	19	obviously	obviously	ADV
brj-22095	159	20	distributed	distribute	VERB
brj-22095	159	21	on	on	ADP
brj-22095	159	22	both	both	DET
brj-22095	159	23	sides	side	NOUN
brj-22095	159	24	of	of	ADP
brj-22095	159	25	the	the	DET
brj-22095	159	26	fitted	fit	VERB
brj-22095	159	27	line	line	NOUN
brj-22095	159	28	in	in	ADP
brj-22095	159	29	a	a	DET
brj-22095	159	30	wider	wide	ADJ
brj-22095	159	31	range	range	NOUN
brj-22095	159	32	,	,	PUNCT
brj-22095	159	33	and	and	CCONJ
brj-22095	159	34	the	the	DET
brj-22095	159	35	longitudinal	longitudinal	ADJ
brj-22095	159	36	offset	offset	NOUN
brj-22095	159	37	was	be	AUX
brj-22095	159	38	large	large	ADJ
brj-22095	159	39	(	(	PUNCT
brj-22095	159	40	fig	fig	NOUN
brj-22095	159	41	.	.	PUNCT
brj-22095	160	1	7(a	7(a	NUM
brj-22095	160	2	)	)	PUNCT
brj-22095	160	3	,	,	PUNCT
brj-22095	160	4	fig	fig	NOUN
brj-22095	160	5	.	.	PUNCT
brj-22095	161	1	7(b	7(b	X
brj-22095	161	2	)	)	PUNCT
brj-22095	161	3	and	and	CCONJ
brj-22095	161	4	fig	fig	NOUN
brj-22095	161	5	.	.	PUNCT
brj-22095	162	1	8(a	8(a	NUM
brj-22095	162	2	)	)	PUNCT
brj-22095	162	3	,	,	PUNCT
brj-22095	162	4	fig	fig	NOUN
brj-22095	162	5	.	.	PUNCT
brj-22095	163	1	8(b	8(b	NUM
brj-22095	163	2	)	)	PUNCT
brj-22095	163	3	)	)	PUNCT
brj-22095	163	4	.	.	PUNCT
brj-22095	164	1	however	however	ADV
brj-22095	164	2	,	,	PUNCT
brj-22095	164	3	the	the	DET
brj-22095	164	4	prediction	prediction	NOUN
brj-22095	164	5	errors	error	NOUN
brj-22095	164	6	of	of	ADP
brj-22095	164	7	the	the	DET
brj-22095	164	8	master	master	PROPN
brj-22095	164	9	instrument	instrument	NOUN
brj-22095	164	10	holocellulose	holocellulose	PROPN
brj-22095	164	11	and	and	CCONJ
brj-22095	164	12	lignin	lignin	NOUN
brj-22095	164	13	models	model	NOUN
brj-22095	164	14	established	establish	VERB
brj-22095	164	15	by	by	ADP
brj-22095	164	16	the	the	DET
brj-22095	164	17	swcss	swcss	PROPN
brj-22095	164	18	and	and	CCONJ
brj-22095	164	19	swcss	swcss	PROPN
brj-22095	164	20	-	-	PUNCT
brj-22095	164	21	s	s	PROPN
brj-22095	164	22	/	/	SYM
brj-22095	164	23	b	b	NOUN
brj-22095	164	24	methods	method	NOUN
brj-22095	164	25	when	when	SCONJ
brj-22095	164	26	applied	apply	VERB
brj-22095	164	27	to	to	ADP
brj-22095	164	28	the	the	DET
brj-22095	164	29	target	target	NOUN
brj-22095	164	30	instrument	instrument	NOUN
brj-22095	164	31	samples	sample	NOUN
brj-22095	164	32	were	be	AUX
brj-22095	164	33	reduced	reduce	VERB
brj-22095	164	34	,	,	PUNCT
brj-22095	164	35	and	and	CCONJ
brj-22095	164	36	the	the	DET
brj-22095	164	37	predicted	predict	VERB
brj-22095	164	38	values	value	NOUN
brj-22095	164	39	were	be	AUX
brj-22095	164	40	roughly	roughly	ADV
brj-22095	164	41	distributed	distribute	VERB
brj-22095	164	42	in	in	ADP
brj-22095	164	43	a	a	DET
brj-22095	164	44	narrow	narrow	ADJ
brj-22095	164	45	range	range	NOUN
brj-22095	164	46	along	along	ADP
brj-22095	164	47	the	the	DET
brj-22095	164	48	fitted	fit	VERB
brj-22095	164	49	straight	straight	ADJ
brj-22095	164	50	line	line	NOUN
brj-22095	164	51	.	.	PUNCT
brj-22095	165	1	peer	peer	NOUN
brj-22095	165	2	-	-	PUNCT
brj-22095	165	3	reviewed	review	VERB
brj-22095	165	4	article	article	NOUN
brj-22095	165	5	bioresources.com	bioresources.com	X
brj-22095	165	6	he	he	PRON
brj-22095	165	7	et	et	PROPN
brj-22095	165	8	al	al	PROPN
brj-22095	165	9	.	.	PROPN
brj-22095	165	10	(	(	PUNCT
brj-22095	165	11	2022	2022	NUM
brj-22095	165	12	)	)	PUNCT
brj-22095	165	13	.	.	PUNCT
brj-22095	166	1	“	"	PUNCT
brj-22095	166	2	near	near	ADP
brj-22095	166	3	ir	ir	PROPN
brj-22095	166	4	model	model	NOUN
brj-22095	166	5	of	of	ADP
brj-22095	166	6	biomass	biomass	NOUN
brj-22095	166	7	,	,	PUNCT
brj-22095	166	8	”	"	PUNCT
brj-22095	166	9	bioresources	bioresource	NOUN
brj-22095	166	10	17(4	17(4	NUM
brj-22095	166	11	)	)	PUNCT
brj-22095	166	12	,	,	PUNCT
brj-22095	166	13	6476	6476	NUM
brj-22095	166	14	-	-	SYM
brj-22095	166	15	6489	6489	NUM
brj-22095	166	16	.	.	PUNCT
brj-22095	167	1	6486	6486	NUM
brj-22095	167	2	the	the	DET
brj-22095	167	3	offset	offset	NOUN
brj-22095	167	4	was	be	AUX
brj-22095	167	5	small	small	ADJ
brj-22095	167	6	,	,	PUNCT
brj-22095	167	7	and	and	CCONJ
brj-22095	167	8	most	most	ADJ
brj-22095	167	9	of	of	ADP
brj-22095	167	10	the	the	DET
brj-22095	167	11	predicted	predict	VERB
brj-22095	167	12	values	value	NOUN
brj-22095	167	13	of	of	ADP
brj-22095	167	14	the	the	DET
brj-22095	167	15	master	master	PROPN
brj-22095	167	16	instrument	instrument	NOUN
brj-22095	167	17	model	model	NOUN
brj-22095	167	18	corrected	correct	VERB
brj-22095	167	19	by	by	ADP
brj-22095	167	20	the	the	DET
brj-22095	167	21	swcss	swcss	PROPN
brj-22095	167	22	-	-	PUNCT
brj-22095	167	23	s	s	PROPN
brj-22095	167	24	/	/	SYM
brj-22095	167	25	b	b	NOUN
brj-22095	167	26	method	method	NOUN
brj-22095	167	27	for	for	ADP
brj-22095	167	28	the	the	DET
brj-22095	167	29	target	target	NOUN
brj-22095	167	30	were	be	AUX
brj-22095	167	31	closer	close	ADJ
brj-22095	167	32	to	to	ADP
brj-22095	167	33	the	the	DET
brj-22095	167	34	fitted	fit	VERB
brj-22095	167	35	straight	straight	ADJ
brj-22095	167	36	line	line	NOUN
brj-22095	167	37	.	.	PUNCT
brj-22095	168	1	this	this	PRON
brj-22095	168	2	further	far	ADV
brj-22095	168	3	indicates	indicate	VERB
brj-22095	168	4	that	that	SCONJ
brj-22095	168	5	the	the	DET
brj-22095	168	6	model	model	NOUN
brj-22095	168	7	prediction	prediction	NOUN
brj-22095	168	8	statistical	statistical	ADJ
brj-22095	168	9	error	error	NOUN
brj-22095	168	10	after	after	SCONJ
brj-22095	168	11	the	the	DET
brj-22095	168	12	transfer	transfer	NOUN
brj-22095	168	13	of	of	ADP
brj-22095	168	14	the	the	DET
brj-22095	168	15	swcss	swcss	PROPN
brj-22095	168	16	-	-	PUNCT
brj-22095	168	17	s	s	PROPN
brj-22095	168	18	/	/	SYM
brj-22095	168	19	b	b	PROPN
brj-22095	168	20	method	method	NOUN
brj-22095	168	21	was	be	AUX
brj-22095	168	22	smaller	small	ADJ
brj-22095	168	23	,	,	PUNCT
brj-22095	168	24	and	and	CCONJ
brj-22095	168	25	the	the	DET
brj-22095	168	26	prediction	prediction	NOUN
brj-22095	168	27	effect	effect	NOUN
brj-22095	168	28	of	of	ADP
brj-22095	168	29	holocellulose	holocellulose	PROPN
brj-22095	168	30	was	be	AUX
brj-22095	168	31	better	well	ADJ
brj-22095	168	32	than	than	ADP
brj-22095	168	33	that	that	PRON
brj-22095	168	34	of	of	ADP
brj-22095	168	35	lignin	lignin	PROPN
brj-22095	168	36	.	.	PUNCT
brj-22095	169	1	fig	fig	NOUN
brj-22095	169	2	.	.	PUNCT
brj-22095	170	1	7	7	X
brj-22095	170	2	.	.	X
brj-22095	170	3	correlation	correlation	NOUN
brj-22095	170	4	diagram	diagram	NOUN
brj-22095	170	5	and	and	CCONJ
brj-22095	170	6	distribution	distribution	NOUN
brj-22095	170	7	diagram	diagram	NOUN
brj-22095	170	8	of	of	ADP
brj-22095	170	9	the	the	DET
brj-22095	170	10	measured	measure	VERB
brj-22095	170	11	and	and	CCONJ
brj-22095	170	12	predicted	predict	VERB
brj-22095	170	13	values	value	NOUN
brj-22095	170	14	of	of	ADP
brj-22095	170	15	the	the	DET
brj-22095	170	16	predicted	predict	VERB
brj-22095	170	17	concentration	concentration	NOUN
brj-22095	170	18	of	of	ADP
brj-22095	170	19	holocellulose	holocellulose	NOUN
brj-22095	170	20	content	content	PROPN
brj-22095	170	21	fig	fig	NOUN
brj-22095	170	22	.	.	PUNCT
brj-22095	171	1	8	8	X
brj-22095	171	2	.	.	X
brj-22095	171	3	correlation	correlation	NOUN
brj-22095	171	4	diagram	diagram	NOUN
brj-22095	171	5	and	and	CCONJ
brj-22095	171	6	distribution	distribution	NOUN
brj-22095	171	7	diagram	diagram	NOUN
brj-22095	171	8	of	of	ADP
brj-22095	171	9	the	the	DET
brj-22095	171	10	measured	measure	VERB
brj-22095	171	11	and	and	CCONJ
brj-22095	171	12	predicted	predict	VERB
brj-22095	171	13	lignin	lignin	NOUN
brj-22095	171	14	content	content	NOUN
brj-22095	171	15	in	in	ADP
brj-22095	171	16	the	the	DET
brj-22095	171	17	predicted	predict	VERB
brj-22095	171	18	concentration	concentration	NOUN
brj-22095	171	19	conclusions	conclusion	NOUN
brj-22095	171	20	1	1	NUM
brj-22095	171	21	.	.	PUNCT
brj-22095	172	1	the	the	DET
brj-22095	172	2	research	research	NOUN
brj-22095	172	3	showed	show	VERB
brj-22095	172	4	that	that	SCONJ
brj-22095	172	5	the	the	DET
brj-22095	172	6	swcss	swcss	PROPN
brj-22095	172	7	-	-	PUNCT
brj-22095	172	8	s	s	PROPN
brj-22095	172	9	/	/	SYM
brj-22095	172	10	b	b	PROPN
brj-22095	172	11	method	method	NOUN
brj-22095	172	12	achieved	achieve	VERB
brj-22095	172	13	good	good	ADJ
brj-22095	172	14	results	result	NOUN
brj-22095	172	15	in	in	ADP
brj-22095	172	16	the	the	DET
brj-22095	172	17	transfer	transfer	NOUN
brj-22095	172	18	process	process	NOUN
brj-22095	172	19	of	of	ADP
brj-22095	172	20	the	the	DET
brj-22095	172	21	model	model	NOUN
brj-22095	172	22	of	of	ADP
brj-22095	172	23	pulp	pulp	NOUN
brj-22095	172	24	wood	wood	NOUN
brj-22095	172	25	holocellulose	holocellulose	NOUN
brj-22095	172	26	and	and	CCONJ
brj-22095	172	27	lignin	lignin	NOUN
brj-22095	172	28	content	content	NOUN
brj-22095	172	29	between	between	ADP
brj-22095	172	30	two	two	NUM
brj-22095	172	31	different	different	ADJ
brj-22095	172	32	types	type	NOUN
brj-22095	172	33	of	of	ADP
brj-22095	172	34	spectrometers	spectrometer	NOUN
brj-22095	172	35	.	.	PUNCT
brj-22095	173	1	the	the	DET
brj-22095	173	2	model	model	NOUN
brj-22095	173	3	transfer	transfer	NOUN
brj-22095	173	4	effect	effect	NOUN
brj-22095	173	5	of	of	ADP
brj-22095	173	6	holocellulose	holocellulose	NOUN
brj-22095	173	7	content	content	NOUN
brj-22095	173	8	was	be	AUX
brj-22095	173	9	better	well	ADJ
brj-22095	173	10	than	than	ADP
brj-22095	173	11	that	that	PRON
brj-22095	173	12	of	of	ADP
brj-22095	173	13	lignin	lignin	NOUN
brj-22095	173	14	.	.	PUNCT
brj-22095	174	1	2	2	X
brj-22095	174	2	.	.	X
brj-22095	174	3	the	the	DET
brj-22095	174	4	stable	stable	ADJ
brj-22095	174	5	consistent	consistent	ADJ
brj-22095	174	6	wavelengths	wavelength	NOUN
brj-22095	174	7	screened	screen	VERB
brj-22095	174	8	by	by	ADP
brj-22095	174	9	the	the	DET
brj-22095	174	10	swcss	swcss	PROPN
brj-22095	174	11	method	method	NOUN
brj-22095	174	12	can	can	AUX
brj-22095	174	13	effectively	effectively	ADV
brj-22095	174	14	reduce	reduce	VERB
brj-22095	174	15	the	the	DET
brj-22095	174	16	differences	difference	NOUN
brj-22095	174	17	between	between	ADP
brj-22095	174	18	these	these	DET
brj-22095	174	19	two	two	NUM
brj-22095	174	20	spectral	spectral	ADJ
brj-22095	174	21	instruments	instrument	NOUN
brj-22095	174	22	,	,	PUNCT
brj-22095	174	23	and	and	CCONJ
brj-22095	174	24	then	then	ADV
brj-22095	174	25	the	the	DET
brj-22095	174	26	systematic	systematic	ADJ
brj-22095	174	27	errors	error	NOUN
brj-22095	174	28	that	that	PRON
brj-22095	174	29	still	still	ADV
brj-22095	174	30	exist	exist	VERB
brj-22095	174	31	after	after	SCONJ
brj-22095	174	32	the	the	DET
brj-22095	174	33	swcss	swcss	PROPN
brj-22095	174	34	correction	correction	NOUN
brj-22095	174	35	can	can	AUX
brj-22095	174	36	be	be	AUX
brj-22095	174	37	further	far	ADV
brj-22095	174	38	corrected	correct	VERB
brj-22095	174	39	by	by	ADP
brj-22095	174	40	the	the	DET
brj-22095	174	41	s	s	PROPN
brj-22095	174	42	/	/	SYM
brj-22095	174	43	b	b	NOUN
brj-22095	174	44	method	method	NOUN
brj-22095	174	45	,	,	PUNCT
brj-22095	174	46	and	and	CCONJ
brj-22095	174	47	the	the	DET
brj-22095	174	48	predictive	predictive	ADJ
brj-22095	174	49	power	power	NOUN
brj-22095	174	50	of	of	ADP
brj-22095	174	51	the	the	DET
brj-22095	174	52	spectral	spectral	ADJ
brj-22095	174	53	analysis	analysis	NOUN
brj-22095	174	54	model	model	NOUN
brj-22095	174	55	will	will	AUX
brj-22095	174	56	be	be	AUX
brj-22095	174	57	significantly	significantly	ADV
brj-22095	174	58	improved	improve	VERB
brj-22095	174	59	.	.	PUNCT
brj-22095	175	1	p	p	X
brj-22095	176	1	re	re	VERB
brj-22095	176	2	d	d	X
brj-22095	176	3	ic	ic	X
brj-22095	176	4	ti	ti	X
brj-22095	176	5	v	v	ADP
brj-22095	176	6	e	e	PROPN
brj-22095	176	7	v	v	ADP
brj-22095	176	8	a	a	DET
brj-22095	176	9	lu	lu	NOUN
brj-22095	176	10	e	e	NOUN
brj-22095	176	11	p	p	NOUN
brj-22095	176	12	re	re	PROPN
brj-22095	176	13	d	d	X
brj-22095	176	14	ic	ic	X
brj-22095	176	15	ti	ti	X
brj-22095	176	16	v	v	ADP
brj-22095	176	17	e	e	PROPN
brj-22095	176	18	v	v	ADP
brj-22095	176	19	a	a	DET
brj-22095	176	20	lu	lu	NOUN
brj-22095	176	21	e	e	NOUN
brj-22095	176	22	measured	measure	VERB
brj-22095	176	23	value	value	NOUN
brj-22095	176	24	measured	measure	VERB
brj-22095	176	25	value	value	NOUN
brj-22095	176	26	number	number	NOUN
brj-22095	176	27	of	of	ADP
brj-22095	176	28	samples	sample	NOUN
brj-22095	176	29	in	in	ADP
brj-22095	176	30	prediction	prediction	NOUN
brj-22095	176	31	set	set	VERB
brj-22095	176	32	number	number	NOUN
brj-22095	176	33	of	of	ADP
brj-22095	176	34	samples	sample	NOUN
brj-22095	176	35	in	in	ADP
brj-22095	176	36	prediction	prediction	NOUN
brj-22095	176	37	set	set	VERB
brj-22095	177	1	h	h	NOUN
brj-22095	177	2	o	o	NOUN
brj-22095	177	3	lo	lo	INTJ
brj-22095	178	1	c	c	NOUN
brj-22095	178	2	e	e	NOUN
brj-22095	178	3	ll	ll	AUX
brj-22095	178	4	u	u	NOUN
brj-22095	178	5	lo	lo	NOUN
brj-22095	178	6	s	s	NOUN
brj-22095	178	7	e	e	NOUN
brj-22095	178	8	c	c	NOUN
brj-22095	178	9	o	o	X
brj-22095	178	10	n	n	X
brj-22095	178	11	te	te	INTJ
brj-22095	178	12	n	n	PRON
brj-22095	178	13	t	t	PROPN
brj-22095	178	14	a	a	DET
brj-22095	178	15	b	b	PROPN
brj-22095	178	16	b	b	PROPN
brj-22095	178	17	a	a	DET
brj-22095	178	18	peer	peer	NOUN
brj-22095	178	19	-	-	PUNCT
brj-22095	178	20	reviewed	review	VERB
brj-22095	178	21	article	article	NOUN
brj-22095	178	22	bioresources.com	bioresources.com	X
brj-22095	178	23	he	he	PRON
brj-22095	178	24	et	et	PROPN
brj-22095	178	25	al	al	PROPN
brj-22095	178	26	.	.	PROPN
brj-22095	179	1	(	(	PUNCT
brj-22095	179	2	2022	2022	NUM
brj-22095	179	3	)	)	PUNCT
brj-22095	179	4	.	.	PUNCT
brj-22095	180	1	“	"	PUNCT
brj-22095	180	2	near	near	ADP
brj-22095	180	3	ir	ir	PROPN
brj-22095	180	4	model	model	NOUN
brj-22095	180	5	of	of	ADP
brj-22095	180	6	biomass	biomass	NOUN
brj-22095	180	7	,	,	PUNCT
brj-22095	180	8	”	"	PUNCT
brj-22095	180	9	bioresources	bioresource	NOUN
brj-22095	180	10	17(4	17(4	NUM
brj-22095	180	11	)	)	PUNCT
brj-22095	180	12	,	,	PUNCT
brj-22095	180	13	6476	6476	NUM
brj-22095	180	14	-	-	SYM
brj-22095	180	15	6489	6489	NUM
brj-22095	180	16	.	.	PUNCT
brj-22095	181	1	6487	6487	NUM
brj-22095	181	2	3	3	X
brj-22095	181	3	.	.	PUNCT
brj-22095	182	1	the	the	DET
brj-22095	182	2	model	model	NOUN
brj-22095	182	3	transfer	transfer	NOUN
brj-22095	182	4	process	process	NOUN
brj-22095	182	5	using	use	VERB
brj-22095	182	6	the	the	DET
brj-22095	182	7	swcss	swcss	PROPN
brj-22095	182	8	-	-	PUNCT
brj-22095	182	9	s	s	PROPN
brj-22095	182	10	/	/	SYM
brj-22095	182	11	b	b	PROPN
brj-22095	182	12	method	method	NOUN
brj-22095	182	13	involves	involve	VERB
brj-22095	182	14	fewer	few	ADJ
brj-22095	182	15	wavelength	wavelength	NOUN
brj-22095	182	16	variables	variable	NOUN
brj-22095	182	17	,	,	PUNCT
brj-22095	182	18	reduces	reduce	VERB
brj-22095	182	19	the	the	DET
brj-22095	182	20	dimensionality	dimensionality	NOUN
brj-22095	182	21	of	of	ADP
brj-22095	182	22	the	the	DET
brj-22095	182	23	spectral	spectral	ADJ
brj-22095	182	24	matrix	matrix	NOUN
brj-22095	182	25	,	,	PUNCT
brj-22095	182	26	and	and	CCONJ
brj-22095	182	27	greatly	greatly	ADV
brj-22095	182	28	improves	improve	VERB
brj-22095	182	29	the	the	DET
brj-22095	182	30	transfer	transfer	NOUN
brj-22095	182	31	efficiency	efficiency	NOUN
brj-22095	182	32	.	.	PUNCT
brj-22095	183	1	4	4	X
brj-22095	183	2	.	.	X
brj-22095	183	3	although	although	SCONJ
brj-22095	183	4	the	the	DET
brj-22095	183	5	analysis	analysis	NOUN
brj-22095	183	6	object	object	NOUN
brj-22095	183	7	of	of	ADP
brj-22095	183	8	this	this	DET
brj-22095	183	9	paper	paper	NOUN
brj-22095	183	10	is	be	AUX
brj-22095	183	11	only	only	ADV
brj-22095	183	12	for	for	ADP
brj-22095	183	13	the	the	DET
brj-22095	183	14	near	near	ADV
brj-22095	183	15	infrared	infrared	ADJ
brj-22095	183	16	analysis	analysis	NOUN
brj-22095	183	17	model	model	NOUN
brj-22095	183	18	of	of	ADP
brj-22095	183	19	holocellulose	holocellulose	NOUN
brj-22095	183	20	and	and	CCONJ
brj-22095	183	21	lignin	lignin	NOUN
brj-22095	183	22	in	in	ADP
brj-22095	183	23	pulp	pulp	NOUN
brj-22095	183	24	,	,	PUNCT
brj-22095	183	25	the	the	DET
brj-22095	183	26	research	research	NOUN
brj-22095	183	27	methods	method	NOUN
brj-22095	183	28	and	and	CCONJ
brj-22095	183	29	paths	path	NOUN
brj-22095	183	30	used	use	VERB
brj-22095	183	31	are	be	AUX
brj-22095	183	32	also	also	ADV
brj-22095	183	33	instructive	instructive	ADJ
brj-22095	183	34	and	and	CCONJ
brj-22095	183	35	applicable	applicable	ADJ
brj-22095	183	36	to	to	ADP
brj-22095	183	37	other	other	ADJ
brj-22095	183	38	indicators	indicator	NOUN
brj-22095	183	39	of	of	ADP
brj-22095	183	40	pulp	pulp	NOUN
brj-22095	183	41	materials	material	NOUN
brj-22095	183	42	,	,	PUNCT
brj-22095	183	43	such	such	ADJ
brj-22095	183	44	as	as	ADP
brj-22095	183	45	moisture	moisture	NOUN
brj-22095	183	46	and	and	CCONJ
brj-22095	183	47	density	density	NOUN
brj-22095	183	48	,	,	PUNCT
brj-22095	183	49	as	as	ADV
brj-22095	183	50	well	well	ADV
brj-22095	183	51	as	as	ADP
brj-22095	183	52	to	to	PART
brj-22095	183	53	nir	nir	VERB
brj-22095	183	54	analysis	analysis	NOUN
brj-22095	183	55	modeling	modeling	NOUN
brj-22095	183	56	in	in	ADP
brj-22095	183	57	other	other	ADJ
brj-22095	183	58	industry	industry	NOUN
brj-22095	183	59	sectors	sector	NOUN
brj-22095	183	60	.	.	PUNCT
brj-22095	184	1	acknowledgments	acknowledgment	NOUN
brj-22095	184	2	this	this	DET
brj-22095	184	3	work	work	NOUN
brj-22095	184	4	was	be	AUX
brj-22095	184	5	funded	fund	VERB
brj-22095	184	6	by	by	ADP
brj-22095	184	7	the	the	DET
brj-22095	184	8	support	support	NOUN
brj-22095	184	9	of	of	ADP
brj-22095	184	10	the	the	DET
brj-22095	184	11	fundamental	fundamental	ADJ
brj-22095	184	12	research	research	NOUN
brj-22095	184	13	funds	fund	NOUN
brj-22095	184	14	of	of	ADP
brj-22095	184	15	research	research	PROPN
brj-22095	184	16	institute	institute	PROPN
brj-22095	184	17	of	of	ADP
brj-22095	184	18	forest	forest	PROPN
brj-22095	184	19	new	new	ADJ
brj-22095	184	20	technology，caf(cafybb2019sy039	technology，caf(cafybb2019sy039	NOUN
brj-22095	184	21	)	)	PUNCT
brj-22095	184	22	.	.	PUNCT
brj-22095	185	1	references	reference	NOUN
brj-22095	185	2	cited	cite	VERB
brj-22095	185	3	abasi	abasi	NOUN
brj-22095	185	4	,	,	PUNCT
brj-22095	185	5	s.	s.	PROPN
brj-22095	185	6	,	,	PUNCT
brj-22095	185	7	minaei	minaei	PROPN
brj-22095	185	8	,	,	PUNCT
brj-22095	185	9	s.	s.	PROPN
brj-22095	185	10	,	,	PUNCT
brj-22095	185	11	jamshidi	jamshidi	PROPN
brj-22095	185	12	,	,	PUNCT
brj-22095	185	13	b.	b.	PROPN
brj-22095	185	14	,	,	PUNCT
brj-22095	185	15	fathi	fathi	PROPN
brj-22095	185	16	,	,	PUNCT
brj-22095	185	17	d.	d.	PROPN
brj-22095	185	18	,	,	PUNCT
brj-22095	185	19	and	and	CCONJ
brj-22095	185	20	khoshtaghaza	khoshtaghaza	PROPN
brj-22095	185	21	,	,	PUNCT
brj-22095	185	22	m.	m.	NOUN
brj-22095	185	23	h.	h.	PROPN
brj-22095	185	24	(	(	PUNCT
brj-22095	185	25	2019	2019	NUM
brj-22095	185	26	)	)	PUNCT
brj-22095	185	27	.	.	PUNCT
brj-22095	186	1	“	"	PUNCT
brj-22095	186	2	rapid	rapid	ADJ
brj-22095	186	3	measurement	measurement	NOUN
brj-22095	186	4	of	of	ADP
brj-22095	186	5	apple	apple	NOUN
brj-22095	186	6	quality	quality	NOUN
brj-22095	186	7	parameters	parameter	NOUN
brj-22095	186	8	using	use	VERB
brj-22095	186	9	wavelet	wavelet	NOUN
brj-22095	186	10	de	de	X
brj-22095	186	11	-	-	ADJ
brj-22095	186	12	noising	noising	ADJ
brj-22095	186	13	transform	transform	NOUN
brj-22095	186	14	with	with	ADP
brj-22095	186	15	vis	vis	X
brj-22095	186	16	/	/	SYM
brj-22095	186	17	nir	nir	ADJ
brj-22095	186	18	analysis	analysis	NOUN
brj-22095	186	19	,	,	PUNCT
brj-22095	186	20	”	"	PUNCT
brj-22095	186	21	scientia	scientia	PROPN
brj-22095	186	22	horticulturae	horticulturae	PROPN
brj-22095	186	23	252	252	NUM
brj-22095	186	24	,	,	PUNCT
brj-22095	186	25	7	7	NUM
brj-22095	186	26	-	-	SYM
brj-22095	186	27	13	13	NUM
brj-22095	186	28	.	.	PUNCT
brj-22095	187	1	doi	doi	NOUN
brj-22095	187	2	:	:	PUNCT
brj-22095	187	3	10.1016	10.1016	NUM
brj-22095	187	4	/	/	SYM
brj-22095	187	5	j.scienta.2019.02.085	j.scienta.2019.02.085	PROPN
brj-22095	187	6	bergman	bergman	PROPN
brj-22095	187	7	,	,	PUNCT
brj-22095	187	8	e.	e.	PROPN
brj-22095	187	9	l.	l.	PROPN
brj-22095	187	10	,	,	PUNCT
brj-22095	187	11	brage	brage	NOUN
brj-22095	187	12	,	,	PUNCT
brj-22095	187	13	h.	h.	PROPN
brj-22095	187	14	,	,	PUNCT
brj-22095	187	15	josefson	josefson	PROPN
brj-22095	187	16	,	,	PUNCT
brj-22095	187	17	m.	m.	NOUN
brj-22095	187	18	,	,	PUNCT
brj-22095	187	19	svensson	svensson	PROPN
brj-22095	187	20	,	,	PUNCT
brj-22095	187	21	o.	o.	PROPN
brj-22095	187	22	,	,	PUNCT
brj-22095	187	23	and	and	CCONJ
brj-22095	187	24	sparén	sparén	NOUN
brj-22095	187	25	,	,	PUNCT
brj-22095	187	26	a.	a.	NOUN
brj-22095	187	27	(	(	PUNCT
brj-22095	187	28	2006	2006	NUM
brj-22095	187	29	)	)	PUNCT
brj-22095	187	30	.	.	PUNCT
brj-22095	188	1	“	"	PUNCT
brj-22095	188	2	transfer	transfer	NOUN
brj-22095	188	3	of	of	ADP
brj-22095	188	4	nir	nir	ADJ
brj-22095	188	5	calibrations	calibration	NOUN
brj-22095	188	6	for	for	ADP
brj-22095	188	7	pharmaceutical	pharmaceutical	NOUN
brj-22095	188	8	formulations	formulation	NOUN
brj-22095	188	9	between	between	ADP
brj-22095	188	10	different	different	ADJ
brj-22095	188	11	instruments	instrument	NOUN
brj-22095	188	12	,	,	PUNCT
brj-22095	188	13	”	"	PUNCT
brj-22095	188	14	journal	journal	NOUN
brj-22095	188	15	of	of	ADP
brj-22095	188	16	pharmaceutical	pharmaceutical	NOUN
brj-22095	188	17	and	and	CCONJ
brj-22095	188	18	biomedical	biomedical	ADJ
brj-22095	188	19	analysis	analysis	NOUN
brj-22095	188	20	41(1	41(1	NOUN
brj-22095	188	21	)	)	PUNCT
brj-22095	188	22	,	,	PUNCT
brj-22095	188	23	89	89	NUM
brj-22095	188	24	-	-	SYM
brj-22095	188	25	98	98	NUM
brj-22095	188	26	.	.	PUNCT
brj-22095	189	1	bin	bin	PROPN
brj-22095	189	2	,	,	PUNCT
brj-22095	189	3	j.	j.	PROPN
brj-22095	189	4	,	,	PUNCT
brj-22095	189	5	li	li	PROPN
brj-22095	189	6	,	,	PUNCT
brj-22095	189	7	x.	x.	PROPN
brj-22095	189	8	,	,	PUNCT
brj-22095	189	9	fan	fan	PROPN
brj-22095	189	10	,	,	PUNCT
brj-22095	189	11	w.	w.	PROPN
brj-22095	189	12	,	,	PUNCT
brj-22095	189	13	zhou	zhou	PROPN
brj-22095	189	14	,	,	PUNCT
brj-22095	189	15	j.	j.	PROPN
brj-22095	189	16	h.	h.	PROPN
brj-22095	189	17	,	,	PUNCT
brj-22095	189	18	and	and	CCONJ
brj-22095	189	19	wang	wang	PROPN
brj-22095	189	20	,	,	PUNCT
brj-22095	189	21	c.	c.	PROPN
brj-22095	189	22	w.	w.	PROPN
brj-22095	189	23	(	(	PUNCT
brj-22095	189	24	2017	2017	NUM
brj-22095	189	25	)	)	PUNCT
brj-22095	189	26	.	.	PUNCT
brj-22095	190	1	“	"	PUNCT
brj-22095	190	2	calibration	calibration	NOUN
brj-22095	190	3	transfer	transfer	NOUN
brj-22095	190	4	of	of	ADP
brj-22095	190	5	near	near	ADV
brj-22095	190	6	-	-	PUNCT
brj-22095	190	7	infrared	infrared	ADJ
brj-22095	190	8	spectroscopy	spectroscopy	NOUN
brj-22095	190	9	by	by	ADP
brj-22095	190	10	canonical	canonical	ADJ
brj-22095	190	11	correlation	correlation	NOUN
brj-22095	190	12	analysis	analysis	NOUN
brj-22095	190	13	coupled	couple	VERB
brj-22095	190	14	with	with	ADP
brj-22095	190	15	wavelet	wavelet	NOUN
brj-22095	190	16	transform	transform	NOUN
brj-22095	190	17	,	,	PUNCT
brj-22095	190	18	”	"	PUNCT
brj-22095	190	19	analyst	analyst	NOUN
brj-22095	190	20	142(12	142(12	NUM
brj-22095	190	21	)	)	PUNCT
brj-22095	190	22	,	,	PUNCT
brj-22095	190	23	2229	2229	NUM
brj-22095	190	24	-	-	SYM
brj-22095	190	25	2238	2238	NUM
brj-22095	190	26	.	.	PUNCT
brj-22095	191	1	doi	doi	NOUN
brj-22095	191	2	:	:	PUNCT
brj-22095	191	3	10.1039	10.1039	NUM
brj-22095	191	4	/	/	SYM
brj-22095	191	5	c7an00280	c7an00280	PROPN
brj-22095	191	6	g	g	NOUN
brj-22095	191	7	cao	cao	NOUN
brj-22095	191	8	,	,	PUNCT
brj-22095	191	9	x.	x.	NOUN
brj-22095	191	10	,	,	PUNCT
brj-22095	191	11	ding	ding	NOUN
brj-22095	191	12	,	,	PUNCT
brj-22095	191	13	h.	h.	PROPN
brj-22095	191	14	,	,	PUNCT
brj-22095	191	15	yang	yang	PROPN
brj-22095	191	16	,	,	PUNCT
brj-22095	191	17	l.	l.	PROPN
brj-22095	191	18	,	,	PUNCT
brj-22095	191	19	huang	huang	PROPN
brj-22095	191	20	,	,	PUNCT
brj-22095	191	21	j.	j.	PROPN
brj-22095	191	22	,	,	PUNCT
brj-22095	191	23	zeng	zeng	PROPN
brj-22095	191	24	,	,	PUNCT
brj-22095	191	25	l.	l.	PROPN
brj-22095	191	26	,	,	PUNCT
brj-22095	191	27	tong	tong	PROPN
brj-22095	191	28	,	,	PUNCT
brj-22095	191	29	h.	h.	PROPN
brj-22095	191	30	,	,	PUNCT
brj-22095	191	31	su	su	PROPN
brj-22095	191	32	,	,	PUNCT
brj-22095	191	33	l.	l.	PROPN
brj-22095	191	34	,	,	PUNCT
brj-22095	191	35	ji	ji	PROPN
brj-22095	191	36	,	,	PUNCT
brj-22095	191	37	x.	x.	PROPN
brj-22095	191	38	,	,	PUNCT
brj-22095	191	39	wu	wu	PROPN
brj-22095	191	40	,	,	PUNCT
brj-22095	191	41	m.	m.	NOUN
brj-22095	191	42	,	,	PUNCT
brj-22095	191	43	and	and	CCONJ
brj-22095	191	44	yang	yang	PROPN
brj-22095	191	45	,	,	PUNCT
brj-22095	191	46	y.	y.	PROPN
brj-22095	191	47	(	(	PUNCT
brj-22095	191	48	2022	2022	NUM
brj-22095	191	49	)	)	PUNCT
brj-22095	191	50	.	.	PUNCT
brj-22095	192	1	“	"	PUNCT
brj-22095	192	2	near	near	ADV
brj-22095	192	3	-	-	PUNCT
brj-22095	192	4	infrared	infrared	ADJ
brj-22095	192	5	spectroscopy	spectroscopy	NOUN
brj-22095	192	6	as	as	ADP
brj-22095	192	7	a	a	DET
brj-22095	192	8	tool	tool	NOUN
brj-22095	192	9	to	to	PART
brj-22095	192	10	assist	assist	VERB
brj-22095	192	11	sargassum	sargassum	NOUN
brj-22095	192	12	fusiforme	fusiforme	PROPN
brj-22095	192	13	quality	quality	NOUN
brj-22095	192	14	grading	grading	NOUN
brj-22095	192	15	:	:	PUNCT
brj-22095	192	16	harvest	harvest	NOUN
brj-22095	192	17	time	time	NOUN
brj-22095	192	18	discrimination	discrimination	NOUN
brj-22095	192	19	and	and	CCONJ
brj-22095	192	20	polyphenol	polyphenol	NOUN
brj-22095	192	21	prediction	prediction	NOUN
brj-22095	192	22	,	,	PUNCT
brj-22095	192	23	”	"	PUNCT
brj-22095	192	24	postharvest	postharvest	NOUN
brj-22095	192	25	biology	biology	NOUN
brj-22095	192	26	and	and	CCONJ
brj-22095	192	27	technology	technology	NOUN
brj-22095	192	28	192	192	NUM
brj-22095	192	29	,	,	PUNCT
brj-22095	192	30	article	article	NOUN
brj-22095	192	31	no	no	NOUN
brj-22095	192	32	.	.	PROPN
brj-22095	192	33	112030	112030	NUM
brj-22095	192	34	.	.	PUNCT
brj-22095	193	1	doi	doi	NOUN
brj-22095	193	2	:	:	PUNCT
brj-22095	193	3	10.1016	10.1016	NUM
brj-22095	193	4	/	/	SYM
brj-22095	193	5	j.postharvbio.2022.112030	j.postharvbio.2022.112030	PROPN
brj-22095	193	6	du	du	PROPN
brj-22095	193	7	,	,	PUNCT
brj-22095	193	8	w.	w.	PROPN
brj-22095	193	9	,	,	PUNCT
brj-22095	193	10	chen	chen	PROPN
brj-22095	193	11	,	,	PUNCT
brj-22095	193	12	z.	z.	PROPN
brj-22095	193	13	p.	p.	PROPN
brj-22095	193	14	,	,	PUNCT
brj-22095	193	15	zhong	zhong	PROPN
brj-22095	193	16	,	,	PUNCT
brj-22095	193	17	l.	l.	PROPN
brj-22095	193	18	j.	j.	PROPN
brj-22095	193	19	,	,	PUNCT
brj-22095	193	20	wang	wang	PROPN
brj-22095	193	21	,	,	PUNCT
brj-22095	193	22	s.	s.	PROPN
brj-22095	193	23	x.	x.	PROPN
brj-22095	193	24	,	,	PUNCT
brj-22095	193	25	yu	yu	PROPN
brj-22095	193	26	,	,	PUNCT
brj-22095	193	27	r.	r.	PROPN
brj-22095	193	28	q.	q.	PROPN
brj-22095	193	29	,	,	PUNCT
brj-22095	193	30	nordon	nordon	PROPN
brj-22095	193	31	,	,	PUNCT
brj-22095	193	32	a.	a.	NOUN
brj-22095	193	33	,	,	PUNCT
brj-22095	193	34	and	and	CCONJ
brj-22095	193	35	holden	holden	PROPN
brj-22095	193	36	,	,	PUNCT
brj-22095	193	37	m.	m.	NOUN
brj-22095	193	38	(	(	PUNCT
brj-22095	193	39	2011	2011	NUM
brj-22095	193	40	)	)	PUNCT
brj-22095	193	41	.	.	PUNCT
brj-22095	194	1	“	"	PUNCT
brj-22095	194	2	maintaining	maintain	VERB
brj-22095	194	3	the	the	DET
brj-22095	194	4	predictive	predictive	ADJ
brj-22095	194	5	abilities	ability	NOUN
brj-22095	194	6	of	of	ADP
brj-22095	194	7	multivariate	multivariate	NOUN
brj-22095	194	8	calibration	calibration	NOUN
brj-22095	194	9	models	model	NOUN
brj-22095	194	10	by	by	ADP
brj-22095	194	11	spectral	spectral	ADJ
brj-22095	194	12	space	space	NOUN
brj-22095	194	13	transformation	transformation	NOUN
brj-22095	194	14	,	,	PUNCT
brj-22095	194	15	”	"	PUNCT
brj-22095	194	16	analytica	analytica	PROPN
brj-22095	194	17	chimica	chimica	PROPN
brj-22095	194	18	acta	acta	PROPN
brj-22095	194	19	690(1	690(1	NUM
brj-22095	194	20	)	)	PUNCT
brj-22095	194	21	,	,	PUNCT
brj-22095	194	22	64	64	NUM
brj-22095	194	23	-	-	SYM
brj-22095	194	24	70	70	NUM
brj-22095	194	25	.	.	PUNCT
brj-22095	195	1	doi	doi	NOUN
brj-22095	195	2	:	:	PUNCT
brj-22095	195	3	10.1016	10.1016	NUM
brj-22095	195	4	/	/	SYM
brj-22095	195	5	j.aca.2011.02.014	j.aca.2011.02.014	PROPN
brj-22095	195	6	fatchurrahman	fatchurrahman	NOUN
brj-22095	195	7	,	,	PUNCT
brj-22095	195	8	d.	d.	PROPN
brj-22095	195	9	,	,	PUNCT
brj-22095	195	10	nosrati	nosrati	PROPN
brj-22095	195	11	,	,	PUNCT
brj-22095	195	12	m.	m.	NOUN
brj-22095	195	13	,	,	PUNCT
brj-22095	195	14	amodio	amodio	NOUN
brj-22095	195	15	,	,	PUNCT
brj-22095	195	16	m.	m.	NOUN
brj-22095	195	17	l.	l.	PROPN
brj-22095	195	18	,	,	PUNCT
brj-22095	195	19	chaudhry	chaudhry	PROPN
brj-22095	195	20	,	,	PUNCT
brj-22095	195	21	m.	m.	NOUN
brj-22095	195	22	m.	m.	PROPN
brj-22095	195	23	a.	a.	PROPN
brj-22095	195	24	,	,	PUNCT
brj-22095	195	25	de	de	X
brj-22095	195	26	chiara	chiara	X
brj-22095	195	27	,	,	PUNCT
brj-22095	196	1	m.	m.	NOUN
brj-22095	196	2	l.	l.	PROPN
brj-22095	197	1	v.	v.	PROPN
brj-22095	197	2	,	,	PUNCT
brj-22095	197	3	mastrandrea	mastrandrea	PROPN
brj-22095	197	4	,	,	PUNCT
brj-22095	197	5	l.	l.	PROPN
brj-22095	197	6	,	,	PUNCT
brj-22095	197	7	and	and	CCONJ
brj-22095	197	8	colelli	colelli	PROPN
brj-22095	197	9	,	,	PUNCT
brj-22095	197	10	g.	g.	PROPN
brj-22095	197	11	(	(	PUNCT
brj-22095	197	12	2021	2021	NUM
brj-22095	197	13	)	)	PUNCT
brj-22095	197	14	.	.	PUNCT
brj-22095	198	1	“	"	PUNCT
brj-22095	198	2	comparison	comparison	NOUN
brj-22095	198	3	performance	performance	NOUN
brj-22095	198	4	of	of	ADP
brj-22095	198	5	visible	visible	ADJ
brj-22095	198	6	-	-	PUNCT
brj-22095	198	7	nir	nir	ADJ
brj-22095	198	8	and	and	CCONJ
brj-22095	198	9	near	near	ADV
brj-22095	198	10	-	-	PUNCT
brj-22095	198	11	infrared	infrared	ADJ
brj-22095	198	12	hyperspectral	hyperspectral	ADJ
brj-22095	198	13	imaging	imaging	NOUN
brj-22095	198	14	for	for	ADP
brj-22095	198	15	prediction	prediction	NOUN
brj-22095	198	16	of	of	ADP
brj-22095	198	17	nutritional	nutritional	ADJ
brj-22095	198	18	quality	quality	NOUN
brj-22095	198	19	of	of	ADP
brj-22095	198	20	goji	goji	NOUN
brj-22095	198	21	berry	berry	NOUN
brj-22095	198	22	,	,	PUNCT
brj-22095	198	23	”	"	PUNCT
brj-22095	198	24	foods	food	NOUN
brj-22095	198	25	10(7	10(7	NUM
brj-22095	198	26	)	)	PUNCT
brj-22095	198	27	,	,	PUNCT
brj-22095	198	28	1676	1676	NUM
brj-22095	198	29	.	.	PUNCT
brj-22095	199	1	doi	doi	NOUN
brj-22095	199	2	:	:	PUNCT
brj-22095	199	3	10.3390	10.3390	NUM
brj-22095	199	4	/	/	SYM
brj-22095	199	5	foods10071676	foods10071676	PROPN
brj-22095	199	6	ferrara	ferrara	NOUN
brj-22095	199	7	,	,	PUNCT
brj-22095	199	8	g.	g.	PROPN
brj-22095	199	9	,	,	PUNCT
brj-22095	199	10	marcotuli	marcotuli	PROPN
brj-22095	199	11	,	,	PUNCT
brj-22095	199	12	v.	v.	PROPN
brj-22095	199	13	,	,	PUNCT
brj-22095	199	14	didonna	didonna	PROPN
brj-22095	199	15	,	,	PUNCT
brj-22095	199	16	a.	a.	NOUN
brj-22095	199	17	,	,	PUNCT
brj-22095	199	18	stellacci	stellacci	PROPN
brj-22095	199	19	,	,	PUNCT
brj-22095	199	20	a.	a.	NOUN
brj-22095	199	21	m.	m.	NOUN
brj-22095	199	22	,	,	PUNCT
brj-22095	199	23	palasciano	palasciano	NOUN
brj-22095	199	24	,	,	PUNCT
brj-22095	199	25	m.	m.	NOUN
brj-22095	199	26	,	,	PUNCT
brj-22095	199	27	and	and	CCONJ
brj-22095	199	28	mazzeo	mazzeo	NOUN
brj-22095	199	29	,	,	PUNCT
brj-22095	199	30	a.	a.	NOUN
brj-22095	199	31	(	(	PUNCT
brj-22095	199	32	2022	2022	NUM
brj-22095	199	33	)	)	PUNCT
brj-22095	199	34	.	.	PUNCT
brj-22095	200	1	“	"	PUNCT
brj-22095	200	2	ripeness	ripeness	NOUN
brj-22095	200	3	prediction	prediction	NOUN
brj-22095	200	4	in	in	ADP
brj-22095	200	5	table	table	NOUN
brj-22095	200	6	grape	grape	NOUN
brj-22095	200	7	cultivars	cultivar	NOUN
brj-22095	200	8	by	by	ADP
brj-22095	200	9	using	use	VERB
brj-22095	200	10	a	a	DET
brj-22095	200	11	portable	portable	ADJ
brj-22095	200	12	nir	nir	ADJ
brj-22095	200	13	device	device	NOUN
brj-22095	200	14	,	,	PUNCT
brj-22095	200	15	”	"	PUNCT
brj-22095	200	16	horticulturae	horticulturae	PROPN
brj-22095	200	17	8(7	8(7	NUM
brj-22095	200	18	)	)	PUNCT
brj-22095	200	19	,	,	PUNCT
brj-22095	200	20	613	613	NUM
brj-22095	200	21	.	.	PUNCT
brj-22095	200	22	doi	doi	NOUN
brj-22095	200	23	:	:	PUNCT
brj-22095	200	24	10.3390	10.3390	NUM
brj-22095	200	25	/	/	SYM
brj-22095	200	26	horticulturae8070613	horticulturae8070613	PROPN
brj-22095	200	27	feudale	feudale	NOUN
brj-22095	200	28	,	,	PUNCT
brj-22095	200	29	r.	r.	PROPN
brj-22095	200	30	n.	n.	PROPN
brj-22095	200	31	,	,	PUNCT
brj-22095	200	32	woody	woody	NOUN
brj-22095	200	33	,	,	PUNCT
brj-22095	200	34	n.	n.	PROPN
brj-22095	200	35	a.	a.	PROPN
brj-22095	200	36	,	,	PUNCT
brj-22095	200	37	tan	tan	PROPN
brj-22095	200	38	,	,	PUNCT
brj-22095	200	39	h.	h.	PROPN
brj-22095	200	40	,	,	PUNCT
brj-22095	200	41	myles	myles	PROPN
brj-22095	200	42	,	,	PUNCT
brj-22095	200	43	a.	a.	PROPN
brj-22095	200	44	j.	j.	PROPN
brj-22095	200	45	,	,	PUNCT
brj-22095	200	46	brown	brown	PROPN
brj-22095	200	47	,	,	PUNCT
brj-22095	200	48	s.	s.	PROPN
brj-22095	200	49	d.	d.	PROPN
brj-22095	200	50	,	,	PUNCT
brj-22095	200	51	and	and	CCONJ
brj-22095	200	52	ferré	ferré	NOUN
brj-22095	200	53	,	,	PUNCT
brj-22095	200	54	j.	j.	PROPN
brj-22095	200	55	(	(	PUNCT
brj-22095	200	56	2002	2002	NUM
brj-22095	200	57	)	)	PUNCT
brj-22095	200	58	.	.	PUNCT
brj-22095	201	1	“	"	PUNCT
brj-22095	201	2	transfer	transfer	NOUN
brj-22095	201	3	of	of	ADP
brj-22095	201	4	multivariate	multivariate	NOUN
brj-22095	201	5	calibration	calibration	NOUN
brj-22095	201	6	models	model	NOUN
brj-22095	201	7	:	:	PUNCT
brj-22095	201	8	a	a	DET
brj-22095	201	9	review	review	NOUN
brj-22095	201	10	,	,	PUNCT
brj-22095	201	11	”	"	PUNCT
brj-22095	201	12	chemometrics	chemometric	NOUN
brj-22095	201	13	and	and	CCONJ
brj-22095	201	14	intelligent	intelligent	ADJ
brj-22095	201	15	laboratory	laboratory	NOUN
brj-22095	201	16	systems	system	NOUN
brj-22095	201	17	64(2	64(2	NOUN
brj-22095	201	18	)	)	PUNCT
brj-22095	201	19	,	,	PUNCT
brj-22095	201	20	181	181	NUM
brj-22095	201	21	-	-	SYM
brj-22095	201	22	192	192	NUM
brj-22095	201	23	.	.	PUNCT
brj-22095	202	1	doi	doi	NOUN
brj-22095	202	2	:	:	PUNCT
brj-22095	202	3	10.1016	10.1016	NUM
brj-22095	202	4	/	/	SYM
brj-22095	202	5	s0169	s0169	PROPN
brj-22095	202	6	-	-	PUNCT
brj-22095	202	7	7439(02)00085	7439(02)00085	NUM
brj-22095	202	8	-	-	PUNCT
brj-22095	202	9	0	0	NUM
brj-22095	202	10	peer	peer	NOUN
brj-22095	202	11	-	-	PUNCT
brj-22095	202	12	reviewed	review	VERB
brj-22095	202	13	article	article	NOUN
brj-22095	202	14	bioresources.com	bioresources.com	X
brj-22095	202	15	he	he	PRON
brj-22095	202	16	et	et	PROPN
brj-22095	202	17	al	al	PROPN
brj-22095	202	18	.	.	PROPN
brj-22095	202	19	(	(	PUNCT
brj-22095	202	20	2022	2022	NUM
brj-22095	202	21	)	)	PUNCT
brj-22095	202	22	.	.	PUNCT
brj-22095	203	1	“	"	PUNCT
brj-22095	203	2	near	near	ADP
brj-22095	203	3	ir	ir	PROPN
brj-22095	203	4	model	model	NOUN
brj-22095	203	5	of	of	ADP
brj-22095	203	6	biomass	biomass	NOUN
brj-22095	203	7	,	,	PUNCT
brj-22095	203	8	”	"	PUNCT
brj-22095	203	9	bioresources	bioresource	NOUN
brj-22095	203	10	17(4	17(4	NUM
brj-22095	203	11	)	)	PUNCT
brj-22095	203	12	,	,	PUNCT
brj-22095	203	13	6476	6476	NUM
brj-22095	203	14	-	-	SYM
brj-22095	203	15	6489	6489	NUM
brj-22095	203	16	.	.	PUNCT
brj-22095	204	1	6488	6488	NUM
brj-22095	204	2	hao	hao	PROPN
brj-22095	204	3	,	,	PUNCT
brj-22095	204	4	y.	y.	PROPN
brj-22095	204	5	,	,	PUNCT
brj-22095	204	6	li	li	PROPN
brj-22095	204	7	,	,	PUNCT
brj-22095	204	8	z.	z.	PROPN
brj-22095	204	9	,	,	PUNCT
brj-22095	204	10	ding	ding	NOUN
brj-22095	204	11	,	,	PUNCT
brj-22095	204	12	n.	n.	NOUN
brj-22095	204	13	,	,	PUNCT
brj-22095	204	14	tang	tang	PROPN
brj-22095	204	15	,	,	PUNCT
brj-22095	204	16	x.	x.	NOUN
brj-22095	204	17	,	,	PUNCT
brj-22095	204	18	and	and	CCONJ
brj-22095	204	19	zhang	zhang	PROPN
brj-22095	204	20	,	,	PUNCT
brj-22095	204	21	c.	c.	PROPN
brj-22095	204	22	(	(	PUNCT
brj-22095	204	23	2022	2022	NUM
brj-22095	204	24	)	)	PUNCT
brj-22095	204	25	.	.	PUNCT
brj-22095	205	1	“	"	PUNCT
brj-22095	205	2	a	a	DET
brj-22095	205	3	new	new	ADJ
brj-22095	205	4	near	near	ADV
brj-22095	205	5	-	-	PUNCT
brj-22095	205	6	infrared	infrared	ADJ
brj-22095	205	7	fluorescence	fluorescence	NOUN
brj-22095	205	8	probe	probe	NOUN
brj-22095	205	9	synthesized	synthesize	VERB
brj-22095	205	10	from	from	ADP
brj-22095	205	11	ir-783	ir-783	PROPN
brj-22095	205	12	for	for	ADP
brj-22095	205	13	detection	detection	NOUN
brj-22095	205	14	and	and	CCONJ
brj-22095	205	15	bioimaging	bioimaging	NOUN
brj-22095	205	16	of	of	ADP
brj-22095	205	17	hydrogen	hydrogen	NOUN
brj-22095	205	18	peroxide	peroxide	NOUN
brj-22095	205	19	in	in	ADP
brj-22095	205	20	vitro	vitro	X
brj-22095	205	21	and	and	CCONJ
brj-22095	205	22	in	in	ADP
brj-22095	205	23	vivo	vivo	NOUN
brj-22095	205	24	,	,	PUNCT
brj-22095	205	25	”	"	PUNCT
brj-22095	205	26	spectrochimica	spectrochimica	NOUN
brj-22095	205	27	acta	acta	PROPN
brj-22095	205	28	part	part	NOUN
brj-22095	205	29	a	a	DET
brj-22095	205	30	:	:	PUNCT
brj-22095	205	31	molecular	molecular	ADJ
brj-22095	205	32	and	and	CCONJ
brj-22095	205	33	biomolecular	biomolecular	ADJ
brj-22095	205	34	spectroscopy	spectroscopy	NOUN
brj-22095	205	35	268	268	NUM
brj-22095	205	36	,	,	PUNCT
brj-22095	205	37	article	article	NOUN
brj-22095	205	38	no	no	NOUN
brj-22095	205	39	.	.	PUNCT
brj-22095	205	40	120642	120642	NUM
brj-22095	205	41	.	.	PUNCT
brj-22095	206	1	doi	doi	NOUN
brj-22095	206	2	:	:	PUNCT
brj-22095	206	3	10.1016	10.1016	NUM
brj-22095	206	4	/	/	SYM
brj-22095	206	5	j.saa.2021.120642	j.saa.2021.120642	PROPN
brj-22095	206	6	haque	haque	PROPN
brj-22095	206	7	,	,	PUNCT
brj-22095	206	8	m.	m.	NOUN
brj-22095	206	9	m.	m.	NOUN
brj-22095	206	10	,	,	PUNCT
brj-22095	206	11	uddin	uddin	PROPN
brj-22095	206	12	,	,	PUNCT
brj-22095	206	13	m.	m.	NOUN
brj-22095	206	14	n.	n.	PROPN
brj-22095	206	15	,	,	PUNCT
brj-22095	206	16	quaiyyum	quaiyyum	INTJ
brj-22095	206	17	,	,	PUNCT
brj-22095	206	18	m.	m.	NOUN
brj-22095	206	19	a.	a.	PROPN
brj-22095	206	20	,	,	PUNCT
brj-22095	206	21	nayeem	nayeem	PROPN
brj-22095	206	22	,	,	PUNCT
brj-22095	206	23	j.	j.	PROPN
brj-22095	206	24	,	,	PUNCT
brj-22095	206	25	alam	alam	PROPN
brj-22095	206	26	,	,	PUNCT
brj-22095	206	27	m.	m.	NOUN
brj-22095	206	28	z.	z.	PROPN
brj-22095	206	29	,	,	PUNCT
brj-22095	206	30	and	and	CCONJ
brj-22095	206	31	jahan	jahan	PROPN
brj-22095	206	32	,	,	PUNCT
brj-22095	206	33	m.	m.	PROPN
brj-22095	206	34	s.	s.	PROPN
brj-22095	206	35	(	(	PUNCT
brj-22095	206	36	2019	2019	NUM
brj-22095	206	37	)	)	PUNCT
brj-22095	206	38	.	.	PUNCT
brj-22095	207	1	“	"	PUNCT
brj-22095	207	2	pulpwood	pulpwood	NOUN
brj-22095	207	3	quality	quality	NOUN
brj-22095	207	4	of	of	ADP
brj-22095	207	5	the	the	DET
brj-22095	207	6	second	second	ADJ
brj-22095	207	7	generation	generation	NOUN
brj-22095	207	8	acacia	acacia	NOUN
brj-22095	207	9	auriculiformis	auriculiformis	NOUN
brj-22095	207	10	,	,	PUNCT
brj-22095	207	11	”	"	PUNCT
brj-22095	207	12	journal	journal	NOUN
brj-22095	207	13	of	of	ADP
brj-22095	207	14	bioresources	bioresource	NOUN
brj-22095	207	15	and	and	CCONJ
brj-22095	207	16	bioproducts	bioproduct	NOUN
brj-22095	207	17	4(2	4(2	NUM
brj-22095	207	18	)	)	PUNCT
brj-22095	207	19	,	,	PUNCT
brj-22095	207	20	73	73	NUM
brj-22095	207	21	-	-	SYM
brj-22095	207	22	79	79	NUM
brj-22095	207	23	.	.	PUNCT
brj-22095	208	1	doi	doi	NOUN
brj-22095	208	2	:	:	PUNCT
brj-22095	208	3	10.21967	10.21967	NUM
brj-22095	208	4	/	/	SYM
brj-22095	208	5	jbb.v4i2.227	jbb.v4i2.227	PROPN
brj-22095	208	6	hasan	hasan	PROPN
brj-22095	208	7	,	,	PUNCT
brj-22095	208	8	m.	m.	NOUN
brj-22095	208	9	m.	m.	NOUN
brj-22095	208	10	,	,	PUNCT
brj-22095	208	11	chaudhry	chaudhry	PROPN
brj-22095	208	12	,	,	PUNCT
brj-22095	208	13	m.	m.	NOUN
brj-22095	208	14	m.	m.	PROPN
brj-22095	208	15	a.	a.	PROPN
brj-22095	208	16	,	,	PUNCT
brj-22095	208	17	erkinbaev	erkinbaev	PROPN
brj-22095	208	18	,	,	PUNCT
brj-22095	208	19	c.	c.	PROPN
brj-22095	208	20	,	,	PUNCT
brj-22095	208	21	paliwal	paliwal	NOUN
brj-22095	208	22	,	,	PUNCT
brj-22095	208	23	j.	j.	PROPN
brj-22095	208	24	,	,	PUNCT
brj-22095	208	25	suman	suman	PROPN
brj-22095	208	26	,	,	PUNCT
brj-22095	208	27	s.	s.	PROPN
brj-22095	208	28	p.	p.	PROPN
brj-22095	208	29	,	,	PUNCT
brj-22095	208	30	and	and	CCONJ
brj-22095	208	31	rodasgonzalez	rodasgonzalez	PROPN
brj-22095	208	32	,	,	PUNCT
brj-22095	208	33	a.	a.	NOUN
brj-22095	208	34	(	(	PUNCT
brj-22095	208	35	2022	2022	NUM
brj-22095	208	36	)	)	PUNCT
brj-22095	208	37	.	.	PUNCT
brj-22095	209	1	“	"	PUNCT
brj-22095	209	2	application	application	NOUN
brj-22095	209	3	of	of	ADP
brj-22095	209	4	vis	vis	X
brj-22095	209	5	-	-	ADJ
brj-22095	209	6	nir	nir	ADJ
brj-22095	209	7	and	and	CCONJ
brj-22095	209	8	swir	swir	NOUN
brj-22095	209	9	spectroscopy	spectroscopy	NOUN
brj-22095	209	10	for	for	ADP
brj-22095	209	11	the	the	DET
brj-22095	209	12	segregation	segregation	NOUN
brj-22095	209	13	of	of	ADP
brj-22095	209	14	bison	bison	NOUN
brj-22095	209	15	muscles	muscle	NOUN
brj-22095	209	16	based	base	VERB
brj-22095	209	17	on	on	ADP
brj-22095	209	18	their	their	PRON
brj-22095	209	19	color	color	NOUN
brj-22095	209	20	stability	stability	NOUN
brj-22095	209	21	,	,	PUNCT
brj-22095	209	22	”	"	PUNCT
brj-22095	209	23	meat	meat	NOUN
brj-22095	209	24	science	science	NOUN
brj-22095	209	25	188	188	NUM
brj-22095	209	26	,	,	PUNCT
brj-22095	209	27	article	article	NOUN
brj-22095	209	28	no	no	NOUN
brj-22095	209	29	.	.	PROPN
brj-22095	209	30	108774	108774	NUM
brj-22095	209	31	.	.	PUNCT
brj-22095	210	1	doi	doi	NOUN
brj-22095	210	2	:	:	PUNCT
brj-22095	210	3	10.1016	10.1016	NUM
brj-22095	210	4	/	/	SYM
brj-22095	210	5	j.meatsci.2022.108774	j.meatsci.2022.108774	PROPN
brj-22095	210	6	kang	kang	PROPN
brj-22095	210	7	,	,	PUNCT
brj-22095	210	8	w.	w.	PROPN
brj-22095	210	9	,	,	PUNCT
brj-22095	210	10	lin	lin	PROPN
brj-22095	210	11	,	,	PUNCT
brj-22095	210	12	h.	h.	PROPN
brj-22095	210	13	,	,	PUNCT
brj-22095	210	14	jiang	jiang	PROPN
brj-22095	210	15	,	,	PUNCT
brj-22095	210	16	r.	r.	PROPN
brj-22095	210	17	,	,	PUNCT
brj-22095	210	18	yan	yan	PROPN
brj-22095	210	19	,	,	PUNCT
brj-22095	210	20	y.	y.	PROPN
brj-22095	210	21	,	,	PUNCT
brj-22095	210	22	ahmad	ahmad	PROPN
brj-22095	210	23	,	,	PUNCT
brj-22095	210	24	w.	w.	PROPN
brj-22095	210	25	,	,	PUNCT
brj-22095	210	26	ouyang	ouyang	PROPN
brj-22095	210	27	,	,	PUNCT
brj-22095	210	28	q.	q.	PROPN
brj-22095	210	29	,	,	PUNCT
brj-22095	210	30	and	and	CCONJ
brj-22095	210	31	chen	chen	PROPN
brj-22095	210	32	,	,	PUNCT
brj-22095	210	33	q.	q.	PROPN
brj-22095	210	34	(	(	PUNCT
brj-22095	210	35	2022	2022	NUM
brj-22095	210	36	)	)	PUNCT
brj-22095	210	37	.	.	PUNCT
brj-22095	211	1	“	"	PUNCT
brj-22095	211	2	emerging	emerge	VERB
brj-22095	211	3	applications	application	NOUN
brj-22095	211	4	of	of	ADP
brj-22095	211	5	nano	nano	NOUN
brj-22095	211	6	-	-	ADJ
brj-22095	211	7	optical	optical	ADJ
brj-22095	211	8	sensors	sensor	NOUN
brj-22095	211	9	combined	combine	VERB
brj-22095	211	10	with	with	ADP
brj-22095	211	11	near	near	ADV
brj-22095	211	12	-	-	PUNCT
brj-22095	211	13	infrared	infrared	ADJ
brj-22095	211	14	spectroscopy	spectroscopy	NOUN
brj-22095	211	15	for	for	ADP
brj-22095	211	16	detecting	detect	VERB
brj-22095	211	17	tea	tea	NOUN
brj-22095	211	18	extract	extract	NOUN
brj-22095	211	19	fermentation	fermentation	NOUN
brj-22095	211	20	aroma	aroma	NOUN
brj-22095	211	21	under	under	ADP
brj-22095	211	22	ultrasound	ultrasound	NOUN
brj-22095	211	23	-	-	PUNCT
brj-22095	211	24	assisted	assist	VERB
brj-22095	211	25	sonication	sonication	NOUN
brj-22095	211	26	,	,	PUNCT
brj-22095	211	27	”	"	PUNCT
brj-22095	211	28	ultrasonics	ultrasonic	NOUN
brj-22095	211	29	sonochemistry	sonochemistry	NOUN
brj-22095	211	30	,	,	PUNCT
brj-22095	211	31	article	article	NOUN
brj-22095	211	32	no	no	NOUN
brj-22095	211	33	.	.	PROPN
brj-22095	211	34	106095	106095	NUM
brj-22095	211	35	.	.	PUNCT
brj-22095	212	1	doi	doi	NOUN
brj-22095	212	2	:	:	PUNCT
brj-22095	212	3	10.1016	10.1016	NUM
brj-22095	212	4	/	/	SYM
brj-22095	212	5	j.ultsonch.2022.106095	j.ultsonch.2022.106095	PROPN
brj-22095	212	6	li	li	PROPN
brj-22095	212	7	,	,	PUNCT
brj-22095	212	8	l.	l.	PROPN
brj-22095	212	9	,	,	PUNCT
brj-22095	212	10	huang	huang	PROPN
brj-22095	212	11	,	,	PUNCT
brj-22095	212	12	w.	w.	PROPN
brj-22095	212	13	,	,	PUNCT
brj-22095	212	14	wang	wang	PROPN
brj-22095	212	15	,	,	PUNCT
brj-22095	212	16	z.	z.	PROPN
brj-22095	212	17	,	,	PUNCT
brj-22095	212	18	liu	liu	PROPN
brj-22095	212	19	,	,	PUNCT
brj-22095	212	20	s.	s.	PROPN
brj-22095	212	21	,	,	PUNCT
brj-22095	212	22	he	he	PRON
brj-22095	212	23	,	,	PUNCT
brj-22095	212	24	x.	x.	NOUN
brj-22095	212	25	,	,	PUNCT
brj-22095	212	26	and	and	CCONJ
brj-22095	212	27	fan	fan	PROPN
brj-22095	212	28	,	,	PUNCT
brj-22095	212	29	s.	s.	PROPN
brj-22095	212	30	(	(	PUNCT
brj-22095	212	31	2022	2022	NUM
brj-22095	212	32	)	)	PUNCT
brj-22095	212	33	.	.	PUNCT
brj-22095	213	1	“	"	PUNCT
brj-22095	213	2	calibration	calibration	NOUN
brj-22095	213	3	transfer	transfer	NOUN
brj-22095	213	4	between	between	ADP
brj-22095	213	5	developed	develop	VERB
brj-22095	213	6	portable	portable	ADJ
brj-22095	213	7	vis	vis	X
brj-22095	213	8	/	/	SYM
brj-22095	213	9	nir	nir	ADJ
brj-22095	213	10	devices	device	NOUN
brj-22095	213	11	for	for	ADP
brj-22095	213	12	detection	detection	NOUN
brj-22095	213	13	of	of	ADP
brj-22095	213	14	soluble	soluble	ADJ
brj-22095	213	15	solids	solid	NOUN
brj-22095	213	16	contents	content	NOUN
brj-22095	213	17	in	in	ADP
brj-22095	213	18	apple	apple	NOUN
brj-22095	213	19	,	,	PUNCT
brj-22095	213	20	”	"	PUNCT
brj-22095	213	21	postharvest	postharvest	NOUN
brj-22095	213	22	biology	biology	NOUN
brj-22095	213	23	and	and	CCONJ
brj-22095	213	24	technology	technology	NOUN
brj-22095	213	25	183	183	NUM
brj-22095	213	26	,	,	PUNCT
brj-22095	213	27	article	article	NOUN
brj-22095	213	28	no	no	NOUN
brj-22095	213	29	.	.	PROPN
brj-22095	213	30	111720	111720	NUM
brj-22095	213	31	.	.	PUNCT
brj-22095	214	1	doi	doi	NOUN
brj-22095	214	2	:	:	PUNCT
brj-22095	214	3	10.1016	10.1016	NUM
brj-22095	214	4	/	/	SYM
brj-22095	214	5	j.postharvbio.2021.111720	j.postharvbio.2021.111720	PROPN
brj-22095	214	6	li	li	PROPN
brj-22095	214	7	,	,	PUNCT
brj-22095	214	8	t.	t.	PROPN
brj-22095	214	9	,	,	PUNCT
brj-22095	214	10	liu	liu	PROPN
brj-22095	214	11	,	,	PUNCT
brj-22095	214	12	c.	c.	PROPN
brj-22095	214	13	,	,	PUNCT
brj-22095	214	14	and	and	CCONJ
brj-22095	214	15	bit	bit	NOUN
brj-22095	214	16	,	,	PUNCT
brj-22095	214	17	l.	l.	PROPN
brj-22095	214	18	(	(	PUNCT
brj-22095	214	19	2018	2018	NUM
brj-22095	214	20	)	)	PUNCT
brj-22095	214	21	.	.	PUNCT
brj-22095	215	1	“	"	PUNCT
brj-22095	215	2	study	study	VERB
brj-22095	215	3	on	on	ADP
brj-22095	215	4	near	near	ADV
brj-22095	215	5	-	-	PUNCT
brj-22095	215	6	infrared	infrared	ADJ
brj-22095	215	7	spectral	spectral	ADJ
brj-22095	215	8	model	model	NOUN
brj-22095	215	9	transfer	transfer	NOUN
brj-22095	215	10	of	of	ADP
brj-22095	215	11	slope	slope	NOUN
brj-22095	215	12	intercept	intercept	NOUN
brj-22095	215	13	correction	correction	NOUN
brj-22095	215	14	algorithm	algorithm	NOUN
brj-22095	215	15	on	on	ADP
brj-22095	215	16	acid	acid	NOUN
brj-22095	215	17	value	value	NOUN
brj-22095	215	18	and	and	CCONJ
brj-22095	215	19	peroxide	peroxide	NOUN
brj-22095	215	20	value	value	NOUN
brj-22095	215	21	of	of	ADP
brj-22095	215	22	edible	edible	ADJ
brj-22095	215	23	oil	oil	NOUN
brj-22095	215	24	,	,	PUNCT
brj-22095	215	25	”	"	PUNCT
brj-22095	215	26	chinese	chinese	ADJ
brj-22095	215	27	journal	journal	NOUN
brj-22095	215	28	of	of	ADP
brj-22095	215	29	cereals	cereal	NOUN
brj-22095	215	30	and	and	CCONJ
brj-22095	215	31	oils	oil	NOUN
brj-22095	215	32	33(01	33(01	NUM
brj-22095	215	33	)	)	PUNCT
brj-22095	215	34	,	,	PUNCT
brj-22095	215	35	118	118	NUM
brj-22095	215	36	-	-	SYM
brj-22095	215	37	124	124	NUM
brj-22095	215	38	,	,	PUNCT
brj-22095	215	39	139	139	NUM
brj-22095	215	40	.	.	PUNCT
brj-22095	216	1	liu	liu	PROPN
brj-22095	216	2	,	,	PUNCT
brj-22095	216	3	y.	y.	PROPN
brj-22095	216	4	,	,	PUNCT
brj-22095	216	5	cai	cai	PROPN
brj-22095	216	6	,	,	PUNCT
brj-22095	216	7	w.	w.	PROPN
brj-22095	216	8	,	,	PUNCT
brj-22095	216	9	and	and	CCONJ
brj-22095	216	10	shao	shao	PROPN
brj-22095	216	11	,	,	PUNCT
brj-22095	216	12	x.	x.	NOUN
brj-22095	216	13	(	(	PUNCT
brj-22095	216	14	2016	2016	NUM
brj-22095	216	15	)	)	PUNCT
brj-22095	216	16	.	.	PUNCT
brj-22095	217	1	“	"	PUNCT
brj-22095	217	2	linear	linear	ADJ
brj-22095	217	3	model	model	NOUN
brj-22095	217	4	correction	correction	NOUN
brj-22095	217	5	:	:	PUNCT
brj-22095	217	6	a	a	DET
brj-22095	217	7	method	method	NOUN
brj-22095	217	8	for	for	ADP
brj-22095	217	9	transferring	transfer	VERB
brj-22095	217	10	a	a	DET
brj-22095	217	11	near	near	ADV
brj-22095	217	12	-	-	PUNCT
brj-22095	217	13	infrared	infrare	VERB
brj-22095	217	14	multivariate	multivariate	NOUN
brj-22095	217	15	calibration	calibration	NOUN
brj-22095	217	16	model	model	NOUN
brj-22095	217	17	without	without	ADP
brj-22095	217	18	standard	standard	ADJ
brj-22095	217	19	samples	sample	NOUN
brj-22095	217	20	,	,	PUNCT
brj-22095	217	21	”	"	PUNCT
brj-22095	217	22	spectrochimica	spectrochimica	NOUN
brj-22095	217	23	acta	acta	PROPN
brj-22095	217	24	part	part	NOUN
brj-22095	217	25	a	a	DET
brj-22095	217	26	:	:	PUNCT
brj-22095	217	27	molecular	molecular	ADJ
brj-22095	217	28	and	and	CCONJ
brj-22095	217	29	biomolecular	biomolecular	ADJ
brj-22095	217	30	spectroscopy	spectroscopy	VERB
brj-22095	217	31	169	169	NUM
brj-22095	217	32	,	,	PUNCT
brj-22095	217	33	197	197	NUM
brj-22095	217	34	-	-	SYM
brj-22095	217	35	201	201	NUM
brj-22095	217	36	.	.	PUNCT
brj-22095	218	1	doi	doi	NOUN
brj-22095	218	2	:	:	PUNCT
brj-22095	218	3	10.1016	10.1016	NUM
brj-22095	218	4	/	/	SYM
brj-22095	218	5	j.saa.2016.06.041	j.saa.2016.06.041	PROPN
brj-22095	218	6	liu	liu	PROPN
brj-22095	218	7	,	,	PUNCT
brj-22095	218	8	y.	y.	PROPN
brj-22095	218	9	,	,	PUNCT
brj-22095	218	10	xiong	xiong	PROPN
brj-22095	218	11	,	,	PUNCT
brj-22095	218	12	z.	z.	PROPN
brj-22095	218	13	,	,	PUNCT
brj-22095	218	14	and	and	CCONJ
brj-22095	218	15	wang	wang	PROPN
brj-22095	218	16	,	,	PUNCT
brj-22095	218	17	y.	y.	PROPN
brj-22095	218	18	(	(	PUNCT
brj-22095	218	19	2019a	2019a	NUM
brj-22095	218	20	)	)	PUNCT
brj-22095	218	21	.	.	PUNCT
brj-22095	219	1	“	"	PUNCT
brj-22095	219	2	model	model	NOUN
brj-22095	219	3	transfer	transfer	NOUN
brj-22095	219	4	study	study	NOUN
brj-22095	219	5	of	of	ADP
brj-22095	219	6	lignin	lignin	PROPN
brj-22095	219	7	near	near	ADV
brj-22095	219	8	-	-	PUNCT
brj-22095	219	9	infrared	infrared	ADJ
brj-22095	219	10	spectral	spectral	ADJ
brj-22095	219	11	analysis	analysis	NOUN
brj-22095	219	12	between	between	ADP
brj-22095	219	13	different	different	ADJ
brj-22095	219	14	models	model	NOUN
brj-22095	219	15	of	of	ADP
brj-22095	219	16	portable	portable	ADJ
brj-22095	219	17	spectrometers	spectrometer	NOUN
brj-22095	219	18	,	,	PUNCT
brj-22095	219	19	”	"	PUNCT
brj-22095	219	20	journal	journal	NOUN
brj-22095	219	21	of	of	ADP
brj-22095	219	22	forestry	forestry	NOUN
brj-22095	219	23	engineering	engineering	NOUN
brj-22095	219	24	4(04	4(04	NUM
brj-22095	219	25	)	)	PUNCT
brj-22095	219	26	,	,	PUNCT
brj-22095	219	27	93	93	NUM
brj-22095	219	28	-	-	SYM
brj-22095	219	29	98	98	NUM
brj-22095	219	30	.	.	PUNCT
brj-22095	220	1	doi	doi	NOUN
brj-22095	220	2	:	:	PUNCT
brj-22095	220	3	10.13360	10.13360	NUM
brj-22095	220	4	/	/	SYM
brj-22095	220	5	j.issn.2096	j.issn.2096	NOUN
brj-22095	220	6	-	-	PUNCT
brj-22095	220	7	1359.2019.04.014	1359.2019.04.014	PROPN
brj-22095	220	8	liu	liu	PROPN
brj-22095	220	9	,	,	PUNCT
brj-22095	220	10	y.	y.	PROPN
brj-22095	220	11	,	,	PUNCT
brj-22095	220	12	yang	yang	PROPN
brj-22095	220	13	h.	h.	PROPN
brj-22095	220	14	,	,	PUNCT
brj-22095	220	15	and	and	CCONJ
brj-22095	220	16	xiong	xiong	PROPN
brj-22095	220	17	,	,	PUNCT
brj-22095	220	18	z.	z.	PROPN
brj-22095	220	19	(	(	PUNCT
brj-22095	220	20	2019b	2019b	NUM
brj-22095	220	21	)	)	PUNCT
brj-22095	220	22	.	.	PUNCT
brj-22095	221	1	“	"	PUNCT
brj-22095	221	2	model	model	NOUN
brj-22095	221	3	transfer	transfer	NOUN
brj-22095	221	4	study	study	NOUN
brj-22095	221	5	of	of	ADP
brj-22095	221	6	near	near	ADV
brj-22095	221	7	-	-	PUNCT
brj-22095	221	8	infrared	infrare	VERB
brj-22095	221	9	analysis	analysis	NOUN
brj-22095	221	10	of	of	ADP
brj-22095	221	11	lignin	lignin	NOUN
brj-22095	221	12	content	content	NOUN
brj-22095	221	13	in	in	ADP
brj-22095	221	14	pulpwood	pulpwood	NOUN
brj-22095	221	15	,	,	PUNCT
brj-22095	221	16	”	"	PUNCT
brj-22095	221	17	chinese	chinese	ADJ
brj-22095	221	18	journal	journal	NOUN
brj-22095	221	19	of	of	ADP
brj-22095	221	20	paper	paper	NOUN
brj-22095	221	21	making	make	VERB
brj-22095	221	22	34(03	34(03	PROPN
brj-22095	221	23	)	)	PUNCT
brj-22095	221	24	,	,	PUNCT
brj-22095	221	25	43	43	NUM
brj-22095	221	26	-	-	SYM
brj-22095	221	27	49	49	NUM
brj-22095	221	28	.	.	PUNCT
brj-22095	222	1	maraphum	maraphum	NOUN
brj-22095	222	2	,	,	PUNCT
brj-22095	222	3	k.	k.	PROPN
brj-22095	222	4	,	,	PUNCT
brj-22095	222	5	saengprachatanarug	saengprachatanarug	PROPN
brj-22095	222	6	,	,	PUNCT
brj-22095	222	7	k.	k.	PROPN
brj-22095	222	8	,	,	PUNCT
brj-22095	222	9	wongpichet	wongpichet	NOUN
brj-22095	222	10	,	,	PUNCT
brj-22095	222	11	s.	s.	PROPN
brj-22095	222	12	,	,	PUNCT
brj-22095	222	13	phuphuphud	phuphuphud	PROPN
brj-22095	222	14	,	,	PUNCT
brj-22095	222	15	a.	a.	NOUN
brj-22095	222	16	,	,	PUNCT
brj-22095	222	17	and	and	CCONJ
brj-22095	222	18	posom	posom	NOUN
brj-22095	222	19	,	,	PUNCT
brj-22095	222	20	j.	j.	PROPN
brj-22095	222	21	(	(	PUNCT
brj-22095	222	22	2022	2022	NUM
brj-22095	222	23	)	)	PUNCT
brj-22095	222	24	.	.	PUNCT
brj-22095	223	1	“	"	PUNCT
brj-22095	223	2	achieving	achieve	VERB
brj-22095	223	3	robustness	robustness	NOUN
brj-22095	223	4	across	across	ADP
brj-22095	223	5	different	different	ADJ
brj-22095	223	6	ages	age	NOUN
brj-22095	223	7	and	and	CCONJ
brj-22095	223	8	cultivars	cultivar	NOUN
brj-22095	223	9	for	for	ADP
brj-22095	223	10	an	an	DET
brj-22095	223	11	nirs	nir	NOUN
brj-22095	223	12	-	-	PUNCT
brj-22095	223	13	plsr	plsr	PROPN
brj-22095	223	14	model	model	NOUN
brj-22095	223	15	of	of	ADP
brj-22095	223	16	fresh	fresh	ADJ
brj-22095	223	17	cassava	cassava	NOUN
brj-22095	223	18	root	root	NOUN
brj-22095	223	19	starch	starch	NOUN
brj-22095	223	20	and	and	CCONJ
brj-22095	223	21	dry	dry	ADJ
brj-22095	223	22	matter	matter	NOUN
brj-22095	223	23	content	content	NOUN
brj-22095	223	24	,	,	PUNCT
brj-22095	223	25	”	"	PUNCT
brj-22095	223	26	computers	computer	NOUN
brj-22095	223	27	and	and	CCONJ
brj-22095	223	28	electronics	electronic	NOUN
brj-22095	223	29	in	in	ADP
brj-22095	223	30	agriculture	agriculture	NOUN
brj-22095	223	31	196	196	NUM
brj-22095	223	32	,	,	PUNCT
brj-22095	223	33	article	article	NOUN
brj-22095	223	34	no	no	NOUN
brj-22095	223	35	.	.	PROPN
brj-22095	223	36	106872	106872	NUM
brj-22095	223	37	.	.	PUNCT
brj-22095	224	1	doi	doi	NOUN
brj-22095	224	2	:	:	PUNCT
brj-22095	224	3	10.1016	10.1016	NUM
brj-22095	224	4	/	/	SYM
brj-22095	224	5	j.compag.2022.106872	j.compag.2022.106872	PROPN
brj-22095	224	6	moreira	moreira	PROPN
brj-22095	224	7	,	,	PUNCT
brj-22095	224	8	s.	s.	PROPN
brj-22095	224	9	a.	a.	PROPN
brj-22095	224	10	,	,	PUNCT
brj-22095	224	11	sarraguca	sarraguca	PROPN
brj-22095	224	12	,	,	PUNCT
brj-22095	224	13	j.	j.	PROPN
brj-22095	224	14	,	,	PUNCT
brj-22095	224	15	saraiva	saraiva	PROPN
brj-22095	224	16	,	,	PUNCT
brj-22095	224	17	d.	d.	PROPN
brj-22095	224	18	f.	f.	PROPN
brj-22095	224	19	,	,	PUNCT
brj-22095	224	20	carvalho	carvalho	PROPN
brj-22095	224	21	,	,	PUNCT
brj-22095	224	22	r.	r.	PROPN
brj-22095	224	23	,	,	PUNCT
brj-22095	224	24	and	and	CCONJ
brj-22095	224	25	lopes	lopes	PROPN
brj-22095	224	26	,	,	PUNCT
brj-22095	224	27	j.	j.	PROPN
brj-22095	224	28	a.	a.	PROPN
brj-22095	224	29	(	(	PUNCT
brj-22095	224	30	2015	2015	NUM
brj-22095	224	31	)	)	PUNCT
brj-22095	224	32	.	.	PUNCT
brj-22095	225	1	“	"	PUNCT
brj-22095	225	2	optimization	optimization	NOUN
brj-22095	225	3	of	of	ADP
brj-22095	225	4	nir	nir	ADJ
brj-22095	225	5	spectroscopy	spectroscopy	NOUN
brj-22095	225	6	based	base	VERB
brj-22095	225	7	plsr	plsr	NOUN
brj-22095	225	8	models	model	NOUN
brj-22095	225	9	for	for	ADP
brj-22095	225	10	critical	critical	ADJ
brj-22095	225	11	properties	property	NOUN
brj-22095	225	12	of	of	ADP
brj-22095	225	13	vegetable	vegetable	NOUN
brj-22095	225	14	oils	oil	NOUN
brj-22095	225	15	used	use	VERB
brj-22095	225	16	in	in	ADP
brj-22095	225	17	biodiesel	biodiesel	NOUN
brj-22095	225	18	production	production	NOUN
brj-22095	225	19	,	,	PUNCT
brj-22095	225	20	”	"	PUNCT
brj-22095	225	21	fuel	fuel	NOUN
brj-22095	225	22	150	150	NUM
brj-22095	225	23	,	,	PUNCT
brj-22095	225	24	697	697	NUM
brj-22095	225	25	-	-	SYM
brj-22095	225	26	704	704	NUM
brj-22095	225	27	.	.	PUNCT
brj-22095	226	1	doi	doi	NOUN
brj-22095	226	2	:	:	PUNCT
brj-22095	226	3	10.1016	10.1016	NUM
brj-22095	226	4	/	/	SYM
brj-22095	226	5	j.fuel.2015.02.082	j.fuel.2015.02.082	PROPN
brj-22095	226	6	ni	ni	PROPN
brj-22095	226	7	,	,	PUNCT
brj-22095	226	8	l.	l.	PROPN
brj-22095	226	9	,	,	PUNCT
brj-22095	226	10	han	han	PROPN
brj-22095	226	11	,	,	PUNCT
brj-22095	226	12	m.	m.	NOUN
brj-22095	226	13	,	,	PUNCT
brj-22095	226	14	luan	luan	PROPN
brj-22095	226	15	,	,	PUNCT
brj-22095	226	16	s.	s.	PROPN
brj-22095	226	17	,	,	PUNCT
brj-22095	226	18	and	and	CCONJ
brj-22095	226	19	zhang	zhang	PROPN
brj-22095	226	20	,	,	PUNCT
brj-22095	226	21	l.	l.	PROPN
brj-22095	226	22	(	(	PUNCT
brj-22095	226	23	2019	2019	NUM
brj-22095	226	24	)	)	PUNCT
brj-22095	226	25	.	.	PUNCT
brj-22095	227	1	“	"	PUNCT
brj-22095	227	2	screening	screen	VERB
brj-22095	227	3	wavelengths	wavelength	NOUN
brj-22095	227	4	with	with	ADP
brj-22095	227	5	consistent	consistent	ADJ
brj-22095	227	6	and	and	CCONJ
brj-22095	227	7	stable	stable	ADJ
brj-22095	227	8	signals	signal	NOUN
brj-22095	227	9	to	to	PART
brj-22095	227	10	realize	realize	VERB
brj-22095	227	11	calibration	calibration	NOUN
brj-22095	227	12	model	model	NOUN
brj-22095	227	13	transfer	transfer	NOUN
brj-22095	227	14	of	of	ADP
brj-22095	227	15	near	near	ADP
brj-22095	227	16	infrared	infrared	PROPN
brj-22095	227	17	spectra	spectra	PROPN
brj-22095	227	18	,	,	PUNCT
brj-22095	227	19	”	"	PUNCT
brj-22095	227	20	spectrochimica	spectrochimica	NOUN
brj-22095	227	21	acta	acta	PROPN
brj-22095	227	22	part	part	NOUN
brj-22095	227	23	a	a	PRON
brj-22095	227	24	:	:	PUNCT
brj-22095	227	25	molecular	molecular	ADJ
brj-22095	227	26	and	and	CCONJ
brj-22095	227	27	biomolecular	biomolecular	ADJ
brj-22095	227	28	spectroscopy	spectroscopy	VERB
brj-22095	227	29	206	206	NUM
brj-22095	227	30	,	,	PUNCT
brj-22095	227	31	350358	350358	NUM
brj-22095	227	32	.	.	PUNCT
brj-22095	228	1	doi	doi	NOUN
brj-22095	228	2	:	:	PUNCT
brj-22095	228	3	10.1016	10.1016	NUM
brj-22095	228	4	/	/	SYM
brj-22095	228	5	j.saa.2018.08.027	j.saa.2018.08.027	PROPN
brj-22095	228	6	parrott	parrott	PROPN
brj-22095	228	7	,	,	PUNCT
brj-22095	228	8	a.	a.	PROPN
brj-22095	228	9	j.	j.	PROPN
brj-22095	228	10	,	,	PUNCT
brj-22095	228	11	mcintyre	mcintyre	PROPN
brj-22095	228	12	,	,	PUNCT
brj-22095	228	13	a.	a.	PROPN
brj-22095	228	14	c.	c.	PROPN
brj-22095	228	15	,	,	PUNCT
brj-22095	228	16	holden	holden	PROPN
brj-22095	228	17	,	,	PUNCT
brj-22095	228	18	m.	m.	NOUN
brj-22095	228	19	,	,	PUNCT
brj-22095	228	20	colquhoun	colquhoun	PROPN
brj-22095	228	21	,	,	PUNCT
brj-22095	228	22	g.	g.	PROPN
brj-22095	228	23	,	,	PUNCT
brj-22095	228	24	chen	chen	PROPN
brj-22095	228	25	,	,	PUNCT
brj-22095	228	26	z.	z.	PROPN
brj-22095	228	27	p.	p.	PROPN
brj-22095	228	28	,	,	PUNCT
brj-22095	228	29	littlejohn	littlejohn	PROPN
brj-22095	228	30	,	,	PUNCT
brj-22095	228	31	d.	d.	PROPN
brj-22095	228	32	,	,	PUNCT
brj-22095	228	33	and	and	CCONJ
brj-22095	228	34	nordon	nordon	NOUN
brj-22095	228	35	,	,	PUNCT
brj-22095	228	36	a.	a.	NOUN
brj-22095	228	37	(	(	PUNCT
brj-22095	228	38	2022	2022	NUM
brj-22095	228	39	)	)	PUNCT
brj-22095	228	40	.	.	PUNCT
brj-22095	229	1	“	"	PUNCT
brj-22095	229	2	calibration	calibration	NOUN
brj-22095	229	3	model	model	NOUN
brj-22095	229	4	transfer	transfer	NOUN
brj-22095	229	5	in	in	ADP
brj-22095	229	6	mid	mid	ADJ
brj-22095	229	7	-	-	ADJ
brj-22095	229	8	infrared	infrared	ADJ
brj-22095	229	9	process	process	NOUN
brj-22095	229	10	analysis	analysis	NOUN
brj-22095	229	11	peer	peer	NOUN
brj-22095	229	12	-	-	PUNCT
brj-22095	229	13	reviewed	review	VERB
brj-22095	229	14	article	article	NOUN
brj-22095	229	15	bioresources.com	bioresources.com	X
brj-22095	229	16	he	he	PRON
brj-22095	229	17	et	et	PROPN
brj-22095	229	18	al	al	PROPN
brj-22095	229	19	.	.	PROPN
brj-22095	229	20	(	(	PUNCT
brj-22095	229	21	2022	2022	NUM
brj-22095	229	22	)	)	PUNCT
brj-22095	229	23	.	.	PUNCT
brj-22095	230	1	“	"	PUNCT
brj-22095	230	2	near	near	ADP
brj-22095	230	3	ir	ir	PROPN
brj-22095	230	4	model	model	NOUN
brj-22095	230	5	of	of	ADP
brj-22095	230	6	biomass	biomass	NOUN
brj-22095	230	7	,	,	PUNCT
brj-22095	230	8	”	"	PUNCT
brj-22095	230	9	bioresources	bioresource	NOUN
brj-22095	230	10	17(4	17(4	NUM
brj-22095	230	11	)	)	PUNCT
brj-22095	230	12	,	,	PUNCT
brj-22095	230	13	6476	6476	NUM
brj-22095	230	14	-	-	SYM
brj-22095	230	15	6489	6489	NUM
brj-22095	230	16	.	.	PUNCT
brj-22095	231	1	6489	6489	NUM
brj-22095	231	2	with	with	ADP
brj-22095	231	3	in	in	ADP
brj-22095	231	4	situ	situ	NOUN
brj-22095	231	5	attenuated	attenuate	VERB
brj-22095	231	6	total	total	ADJ
brj-22095	231	7	reflectance	reflectance	NOUN
brj-22095	231	8	immersion	immersion	NOUN
brj-22095	231	9	probes	probe	NOUN
brj-22095	231	10	,	,	PUNCT
brj-22095	231	11	”	"	PUNCT
brj-22095	231	12	analytical	analytical	ADJ
brj-22095	231	13	methods	method	NOUN
brj-22095	231	14	14(19	14(19	NUM
brj-22095	231	15	)	)	PUNCT
brj-22095	231	16	,	,	PUNCT
brj-22095	231	17	1889	1889	NUM
brj-22095	231	18	-	-	SYM
brj-22095	231	19	1896	1896	NUM
brj-22095	231	20	.	.	PUNCT
brj-22095	232	1	doi	doi	NOUN
brj-22095	232	2	:	:	PUNCT
brj-22095	232	3	10.1039	10.1039	NUM
brj-22095	232	4	/	/	SYM
brj-22095	232	5	d2ay00116k	d2ay00116k	PROPN
brj-22095	232	6	peng	peng	PROPN
brj-22095	232	7	,	,	PUNCT
brj-22095	232	8	j.	j.	PROPN
brj-22095	232	9	,	,	PUNCT
brj-22095	232	10	peng	peng	PROPN
brj-22095	232	11	,	,	PUNCT
brj-22095	232	12	s.	s.	PROPN
brj-22095	232	13	,	,	PUNCT
brj-22095	232	14	jiang	jiang	PROPN
brj-22095	232	15	,	,	PUNCT
brj-22095	232	16	a.	a.	PROPN
brj-22095	232	17	,	,	PUNCT
brj-22095	232	18	and	and	CCONJ
brj-22095	232	19	tan	tan	PROPN
brj-22095	232	20	,	,	PUNCT
brj-22095	232	21	j.	j.	PROPN
brj-22095	232	22	(	(	PUNCT
brj-22095	232	23	2011	2011	NUM
brj-22095	232	24	)	)	PUNCT
brj-22095	232	25	.	.	PUNCT
brj-22095	233	1	“	"	PUNCT
brj-22095	233	2	near	near	ADV
brj-22095	233	3	-	-	PUNCT
brj-22095	233	4	infrared	infrared	ADJ
brj-22095	233	5	calibration	calibration	NOUN
brj-22095	233	6	transfer	transfer	NOUN
brj-22095	233	7	based	base	VERB
brj-22095	233	8	on	on	ADP
brj-22095	233	9	spectral	spectral	ADJ
brj-22095	233	10	regression	regression	NOUN
brj-22095	233	11	,	,	PUNCT
brj-22095	233	12	”	"	PUNCT
brj-22095	233	13	spectrochimica	spectrochimica	NOUN
brj-22095	233	14	acta	acta	PROPN
brj-22095	233	15	part	part	NOUN
brj-22095	233	16	a	a	DET
brj-22095	233	17	:	:	PUNCT
brj-22095	233	18	molecular	molecular	ADJ
brj-22095	233	19	and	and	CCONJ
brj-22095	233	20	biomolecular	biomolecular	ADJ
brj-22095	233	21	spectroscopy	spectroscopy	NOUN
brj-22095	233	22	78(4	78(4	NUM
brj-22095	233	23	)	)	PUNCT
brj-22095	233	24	,	,	PUNCT
brj-22095	233	25	1315	1315	NUM
brj-22095	233	26	-	-	SYM
brj-22095	233	27	1320	1320	NUM
brj-22095	233	28	.	.	PUNCT
brj-22095	234	1	doi	doi	NOUN
brj-22095	234	2	:	:	PUNCT
brj-22095	234	3	10.1016	10.1016	NUM
brj-22095	234	4	/	/	SYM
brj-22095	234	5	j.saa.2011.01.004	j.saa.2011.01.004	PROPN
brj-22095	234	6	poerio	poerio	NOUN
brj-22095	234	7	,	,	PUNCT
brj-22095	234	8	d.	d.	PROPN
brj-22095	234	9	v.	v.	PROPN
brj-22095	234	10	,	,	PUNCT
brj-22095	234	11	and	and	CCONJ
brj-22095	234	12	brown	brown	PROPN
brj-22095	234	13	,	,	PUNCT
brj-22095	234	14	s.	s.	PROPN
brj-22095	234	15	d.	d.	PROPN
brj-22095	234	16	(	(	PUNCT
brj-22095	234	17	2018	2018	NUM
brj-22095	234	18	)	)	PUNCT
brj-22095	234	19	.	.	PUNCT
brj-22095	235	1	“	"	PUNCT
brj-22095	235	2	dual	dual	ADJ
brj-22095	235	3	-	-	PUNCT
brj-22095	235	4	domain	domain	NOUN
brj-22095	235	5	calibration	calibration	NOUN
brj-22095	235	6	transfer	transfer	NOUN
brj-22095	235	7	using	use	VERB
brj-22095	235	8	orthogonal	orthogonal	ADJ
brj-22095	235	9	projection	projection	NOUN
brj-22095	235	10	,	,	PUNCT
brj-22095	235	11	”	"	PUNCT
brj-22095	235	12	applied	apply	VERB
brj-22095	235	13	spectroscopy	spectroscopy	NOUN
brj-22095	235	14	72(3	72(3	NUM
brj-22095	235	15	)	)	PUNCT
brj-22095	235	16	,	,	PUNCT
brj-22095	235	17	378	378	NUM
brj-22095	235	18	-	-	SYM
brj-22095	235	19	391	391	NUM
brj-22095	235	20	.	.	PUNCT
brj-22095	236	1	doi	doi	NOUN
brj-22095	236	2	:	:	PUNCT
brj-22095	236	3	10.1177/0003702817724164	10.1177/0003702817724164	NUM
brj-22095	236	4	sadergaski	sadergaski	NOUN
brj-22095	236	5	,	,	PUNCT
brj-22095	236	6	l.	l.	PROPN
brj-22095	236	7	r.	r.	PROPN
brj-22095	236	8	,	,	PUNCT
brj-22095	236	9	myhre	myhre	PROPN
brj-22095	236	10	,	,	PUNCT
brj-22095	236	11	k.	k.	PROPN
brj-22095	236	12	g.	g.	PROPN
brj-22095	236	13	,	,	PUNCT
brj-22095	236	14	and	and	CCONJ
brj-22095	236	15	delmau	delmau	NOUN
brj-22095	236	16	,	,	PUNCT
brj-22095	236	17	l.	l.	PROPN
brj-22095	236	18	h.	h.	PROPN
brj-22095	236	19	(	(	PUNCT
brj-22095	236	20	2022	2022	NUM
brj-22095	236	21	)	)	PUNCT
brj-22095	236	22	.	.	PUNCT
brj-22095	237	1	“	"	PUNCT
brj-22095	237	2	multivariate	multivariate	VERB
brj-22095	237	3	chemometric	chemometric	ADJ
brj-22095	237	4	methods	method	NOUN
brj-22095	237	5	and	and	CCONJ
brj-22095	237	6	vis	vis	X
brj-22095	237	7	-	-	ADJ
brj-22095	237	8	nir	nir	ADJ
brj-22095	237	9	spectrophotometry	spectrophotometry	NOUN
brj-22095	237	10	for	for	ADP
brj-22095	237	11	monitoring	monitor	VERB
brj-22095	237	12	plutonium-238	plutonium-238	ADJ
brj-22095	237	13	anion	anion	NOUN
brj-22095	237	14	exchange	exchange	NOUN
brj-22095	237	15	column	column	NOUN
brj-22095	237	16	effluent	effluent	NOUN
brj-22095	237	17	in	in	ADP
brj-22095	237	18	a	a	DET
brj-22095	237	19	radiochemical	radiochemical	ADJ
brj-22095	237	20	hot	hot	ADJ
brj-22095	237	21	cell	cell	NOUN
brj-22095	237	22	,	,	PUNCT
brj-22095	237	23	”	"	PUNCT
brj-22095	237	24	talanta	talanta	ADJ
brj-22095	237	25	open	open	NOUN
brj-22095	237	26	,	,	PUNCT
brj-22095	237	27	article	article	NOUN
brj-22095	237	28	no	no	NOUN
brj-22095	237	29	.	.	PROPN
brj-22095	237	30	100120	100120	NUM
brj-22095	237	31	.	.	PUNCT
brj-22095	238	1	doi	doi	NOUN
brj-22095	238	2	:	:	PUNCT
brj-22095	238	3	10.1016	10.1016	NUM
brj-22095	238	4	/	/	SYM
brj-22095	238	5	j.talo.2022.100120	j.talo.2022.100120	PROPN
brj-22095	238	6	wang	wang	PROPN
brj-22095	238	7	,	,	PUNCT
brj-22095	238	8	a.	a.	PROPN
brj-22095	238	9	,	,	PUNCT
brj-22095	238	10	yang	yang	PROPN
brj-22095	238	11	,	,	PUNCT
brj-22095	238	12	p.	p.	PROPN
brj-22095	238	13	,	,	PUNCT
brj-22095	238	14	chen	chen	PROPN
brj-22095	238	15	,	,	PUNCT
brj-22095	238	16	j.	j.	PROPN
brj-22095	238	17	,	,	PUNCT
brj-22095	238	18	wu	wu	PROPN
brj-22095	238	19	,	,	PUNCT
brj-22095	238	20	z.	z.	PROPN
brj-22095	238	21	,	,	PUNCT
brj-22095	238	22	jia	jia	PROPN
brj-22095	238	23	,	,	PUNCT
brj-22095	238	24	y.	y.	PROPN
brj-22095	238	25	,	,	PUNCT
brj-22095	238	26	ma	ma	PROPN
brj-22095	238	27	,	,	PUNCT
brj-22095	238	28	c.	c.	PROPN
brj-22095	238	29	,	,	PUNCT
brj-22095	238	30	and	and	CCONJ
brj-22095	238	31	zhan	zhan	NUM
brj-22095	238	32	,	,	PUNCT
brj-22095	238	33	x.	x.	NOUN
brj-22095	238	34	(	(	PUNCT
brj-22095	238	35	2019	2019	NUM
brj-22095	238	36	)	)	PUNCT
brj-22095	238	37	.	.	PUNCT
brj-22095	239	1	“	"	PUNCT
brj-22095	239	2	a	a	DET
brj-22095	239	3	new	new	ADJ
brj-22095	239	4	calibration	calibration	NOUN
brj-22095	239	5	model	model	NOUN
brj-22095	239	6	transferring	transfer	VERB
brj-22095	239	7	strategy	strategy	NOUN
brj-22095	239	8	maintaining	maintain	VERB
brj-22095	239	9	the	the	DET
brj-22095	239	10	predictive	predictive	ADJ
brj-22095	239	11	abilities	ability	NOUN
brj-22095	239	12	of	of	ADP
brj-22095	239	13	nir	nir	ADJ
brj-22095	239	14	multivariate	multivariate	NOUN
brj-22095	239	15	calibration	calibration	NOUN
brj-22095	239	16	model	model	NOUN
brj-22095	239	17	applied	apply	VERB
brj-22095	239	18	in	in	ADP
brj-22095	239	19	different	different	ADJ
brj-22095	239	20	batches	batch	NOUN
brj-22095	239	21	process	process	NOUN
brj-22095	239	22	of	of	ADP
brj-22095	239	23	extraction	extraction	NOUN
brj-22095	239	24	,	,	PUNCT
brj-22095	239	25	”	"	PUNCT
brj-22095	239	26	infrared	infrared	PROPN
brj-22095	239	27	physics	physics	NOUN
brj-22095	239	28	and	and	CCONJ
brj-22095	239	29	technology	technology	NOUN
brj-22095	239	30	103	103	NUM
brj-22095	239	31	,	,	PUNCT
brj-22095	239	32	article	article	NOUN
brj-22095	239	33	no	no	NOUN
brj-22095	239	34	.	.	PROPN
brj-22095	239	35	103046	103046	NUM
brj-22095	239	36	.	.	PUNCT
brj-22095	240	1	doi	doi	NOUN
brj-22095	240	2	:	:	PUNCT
brj-22095	240	3	10.1016	10.1016	NUM
brj-22095	240	4	/	/	SYM
brj-22095	240	5	j.infrared.2019.103046	j.infrared.2019.103046	PROPN
brj-22095	240	6	pažitný	pažitný	PROPN
brj-22095	240	7	,	,	PUNCT
brj-22095	240	8	a.	a.	PROPN
brj-22095	240	9	,	,	PUNCT
brj-22095	240	10	boháček	boháček	NOUN
brj-22095	240	11	,	,	PUNCT
brj-22095	240	12	š	š	PROPN
brj-22095	240	13	.	.	PROPN
brj-22095	240	14	,	,	PUNCT
brj-22095	240	15	and	and	CCONJ
brj-22095	240	16	russ	russ	NOUN
brj-22095	240	17	,	,	PUNCT
brj-22095	240	18	a.	a.	NOUN
brj-22095	240	19	(	(	PUNCT
brj-22095	240	20	2011	2011	NUM
brj-22095	240	21	)	)	PUNCT
brj-22095	240	22	.	.	PUNCT
brj-22095	241	1	“	"	PUNCT
brj-22095	241	2	application	application	NOUN
brj-22095	241	3	of	of	ADP
brj-22095	241	4	distillery	distillery	NOUN
brj-22095	241	5	refuse	refuse	VERB
brj-22095	241	6	in	in	ADP
brj-22095	241	7	papermaking	papermaking	NOUN
brj-22095	241	8	:	:	PUNCT
brj-22095	241	9	novel	novel	ADJ
brj-22095	241	10	methods	method	NOUN
brj-22095	241	11	of	of	ADP
brj-22095	241	12	treated	treat	VERB
brj-22095	241	13	distillery	distillery	NOUN
brj-22095	241	14	refuse	refuse	VERB
brj-22095	241	15	spectral	spectral	ADJ
brj-22095	241	16	analysis	analysis	NOUN
brj-22095	241	17	,	,	PUNCT
brj-22095	241	18	”	"	PUNCT
brj-22095	241	19	wood	wood	NOUN
brj-22095	241	20	res	re	NOUN
brj-22095	241	21	.	.	PUNCT
brj-22095	242	1	56(4	56(4	NUM
brj-22095	242	2	)	)	PUNCT
brj-22095	242	3	,	,	PUNCT
brj-22095	242	4	533	533	NUM
brj-22095	242	5	-	-	SYM
brj-22095	242	6	544	544	NUM
brj-22095	242	7	.	.	PUNCT
brj-22095	242	8	yu	yu	PROPN
brj-22095	242	9	,	,	PUNCT
brj-22095	242	10	y.	y.	PROPN
brj-22095	242	11	,	,	PUNCT
brj-22095	242	12	huang	huang	PROPN
brj-22095	242	13	,	,	PUNCT
brj-22095	242	14	y.	y.	PROPN
brj-22095	242	15	,	,	PUNCT
brj-22095	242	16	feng	feng	PROPN
brj-22095	242	17	,	,	PUNCT
brj-22095	242	18	w.	w.	PROPN
brj-22095	242	19	,	,	PUNCT
brj-22095	242	20	yang	yang	PROPN
brj-22095	242	21	,	,	PUNCT
brj-22095	242	22	m.	m.	NOUN
brj-22095	242	23	,	,	PUNCT
brj-22095	242	24	shao	shao	PROPN
brj-22095	242	25	,	,	PUNCT
brj-22095	242	26	b.	b.	PROPN
brj-22095	242	27	,	,	PUNCT
brj-22095	242	28	li	li	PROPN
brj-22095	242	29	,	,	PUNCT
brj-22095	242	30	j.	j.	PROPN
brj-22095	242	31	,	,	PUNCT
brj-22095	242	32	and	and	CCONJ
brj-22095	242	33	ye	ye	NOUN
brj-22095	242	34	,	,	PUNCT
brj-22095	242	35	f.	f.	PROPN
brj-22095	242	36	(	(	PUNCT
brj-22095	242	37	2021	2021	NUM
brj-22095	242	38	)	)	PUNCT
brj-22095	242	39	.	.	PUNCT
brj-22095	243	1	“	"	PUNCT
brj-22095	243	2	nirtriggered	nirtriggere	VERB
brj-22095	243	3	upconversion	upconversion	NOUN
brj-22095	243	4	nanoparticles@	nanoparticles@	PRON
brj-22095	243	5	thermo	thermo	NOUN
brj-22095	243	6	-	-	PUNCT
brj-22095	243	7	sensitive	sensitive	ADJ
brj-22095	243	8	liposome	liposome	NOUN
brj-22095	243	9	hybrid	hybrid	ADJ
brj-22095	243	10	theranostic	theranostic	ADJ
brj-22095	243	11	nanoplatform	nanoplatform	NOUN
brj-22095	243	12	for	for	ADP
brj-22095	243	13	controlled	control	VERB
brj-22095	243	14	drug	drug	NOUN
brj-22095	243	15	delivery	delivery	NOUN
brj-22095	243	16	,	,	PUNCT
brj-22095	243	17	”	"	PUNCT
brj-22095	243	18	rsc	rsc	PROPN
brj-22095	243	19	advances	advance	VERB
brj-22095	243	20	11(46	11(46	NOUN
brj-22095	243	21	)	)	PUNCT
brj-22095	243	22	,	,	PUNCT
brj-22095	243	23	29065	29065	NUM
brj-22095	243	24	-	-	SYM
brj-22095	243	25	29072	29072	NUM
brj-22095	243	26	zhang	zhang	PROPN
brj-22095	243	27	,	,	PUNCT
brj-22095	243	28	l.	l.	PROPN
brj-22095	243	29	,	,	PUNCT
brj-22095	243	30	li	li	PROPN
brj-22095	243	31	,	,	PUNCT
brj-22095	243	32	g.	g.	PROPN
brj-22095	243	33	,	,	PUNCT
brj-22095	243	34	sun	sun	NOUN
brj-22095	243	35	,	,	PUNCT
brj-22095	243	36	m.	m.	NOUN
brj-22095	243	37	,	,	PUNCT
brj-22095	243	38	li	li	PROPN
brj-22095	243	39	,	,	PUNCT
brj-22095	243	40	h.	h.	PROPN
brj-22095	243	41	,	,	PUNCT
brj-22095	243	42	wang	wang	PROPN
brj-22095	243	43	,	,	PUNCT
brj-22095	243	44	z.	z.	PROPN
brj-22095	243	45	,	,	PUNCT
brj-22095	243	46	li	li	PROPN
brj-22095	243	47	,	,	PUNCT
brj-22095	243	48	y.	y.	PROPN
brj-22095	243	49	,	,	PUNCT
brj-22095	243	50	and	and	CCONJ
brj-22095	243	51	lin	lin	PROPN
brj-22095	243	52	,	,	PUNCT
brj-22095	243	53	l.	l.	PROPN
brj-22095	243	54	(	(	PUNCT
brj-22095	243	55	2017	2017	NUM
brj-22095	243	56	)	)	PUNCT
brj-22095	243	57	.	.	PUNCT
brj-22095	244	1	“	"	PUNCT
brj-22095	244	2	kennard	kennard	NOUN
brj-22095	244	3	-	-	PUNCT
brj-22095	244	4	stone	stone	NOUN
brj-22095	244	5	combined	combine	VERB
brj-22095	244	6	with	with	ADP
brj-22095	244	7	least	least	ADJ
brj-22095	244	8	square	square	ADJ
brj-22095	244	9	support	support	NOUN
brj-22095	244	10	vector	vector	NOUN
brj-22095	244	11	machine	machine	NOUN
brj-22095	244	12	method	method	NOUN
brj-22095	244	13	for	for	ADP
brj-22095	244	14	noncontact	noncontact	ADJ
brj-22095	244	15	discriminating	discriminate	VERB
brj-22095	244	16	human	human	ADJ
brj-22095	244	17	blood	blood	NOUN
brj-22095	244	18	species	specie	NOUN
brj-22095	244	19	,	,	PUNCT
brj-22095	244	20	”	"	PUNCT
brj-22095	244	21	infrared	infrared	PROPN
brj-22095	244	22	physics	physics	NOUN
brj-22095	244	23	and	and	CCONJ
brj-22095	244	24	technology	technology	NOUN
brj-22095	244	25	86	86	NUM
brj-22095	244	26	,	,	PUNCT
brj-22095	244	27	116	116	NUM
brj-22095	244	28	-	-	SYM
brj-22095	244	29	119	119	NUM
brj-22095	244	30	.	.	PUNCT
brj-22095	245	1	doi	doi	NOUN
brj-22095	245	2	:	:	PUNCT
brj-22095	245	3	10.1016	10.1016	NUM
brj-22095	245	4	/	/	SYM
brj-22095	245	5	j.infrared.2017.08.020	j.infrared.2017.08.020	PROPN
brj-22095	245	6	zhang	zhang	PROPN
brj-22095	245	7	,	,	PUNCT
brj-22095	245	8	y.	y.	PROPN
brj-22095	245	9	,	,	PUNCT
brj-22095	245	10	nock	nock	PROPN
brj-22095	245	11	,	,	PUNCT
brj-22095	245	12	j.	j.	PROPN
brj-22095	245	13	f.	f.	PROPN
brj-22095	245	14	,	,	PUNCT
brj-22095	245	15	al	al	PROPN
brj-22095	245	16	shoffe	shoffe	PROPN
brj-22095	245	17	,	,	PUNCT
brj-22095	245	18	y.	y.	NOUN
brj-22095	245	19	,	,	PUNCT
brj-22095	245	20	and	and	CCONJ
brj-22095	245	21	watkins	watkin	NOUN
brj-22095	245	22	,	,	PUNCT
brj-22095	245	23	c.	c.	PROPN
brj-22095	245	24	b.	b.	PROPN
brj-22095	246	1	(	(	PUNCT
brj-22095	246	2	2019	2019	NUM
brj-22095	246	3	)	)	PUNCT
brj-22095	246	4	.	.	PUNCT
brj-22095	247	1	“	"	PUNCT
brj-22095	247	2	non	non	ADJ
brj-22095	247	3	-	-	ADJ
brj-22095	247	4	destructive	destructive	ADJ
brj-22095	247	5	prediction	prediction	NOUN
brj-22095	247	6	of	of	ADP
brj-22095	247	7	soluble	soluble	ADJ
brj-22095	247	8	solids	solid	NOUN
brj-22095	247	9	and	and	CCONJ
brj-22095	247	10	dry	dry	ADJ
brj-22095	247	11	matter	matter	NOUN
brj-22095	247	12	contents	content	NOUN
brj-22095	247	13	in	in	ADP
brj-22095	247	14	eight	eight	NUM
brj-22095	247	15	apple	apple	NOUN
brj-22095	247	16	cultivars	cultivar	NOUN
brj-22095	247	17	using	use	VERB
brj-22095	247	18	near	near	ADV
brj-22095	247	19	-	-	PUNCT
brj-22095	247	20	infrared	infrared	ADJ
brj-22095	247	21	spectroscopy	spectroscopy	NOUN
brj-22095	247	22	,	,	PUNCT
brj-22095	247	23	”	"	PUNCT
brj-22095	247	24	postharvest	postharvest	NOUN
brj-22095	247	25	biology	biology	NOUN
brj-22095	247	26	and	and	CCONJ
brj-22095	247	27	technology	technology	NOUN
brj-22095	247	28	151	151	NUM
brj-22095	247	29	,	,	PUNCT
brj-22095	247	30	111	111	NUM
brj-22095	247	31	-	-	SYM
brj-22095	247	32	118	118	NUM
brj-22095	247	33	.	.	PUNCT
brj-22095	248	1	doi	doi	NOUN
brj-22095	248	2	:	:	PUNCT
brj-22095	248	3	10.1016	10.1016	NUM
brj-22095	248	4	/	/	SYM
brj-22095	248	5	j.postharvbio.2019.01.009	j.postharvbio.2019.01.009	PROPN
brj-22095	248	6	zhang	zhang	PROPN
brj-22095	248	7	,	,	PUNCT
brj-22095	248	8	l.	l.	PROPN
brj-22095	248	9	,	,	PUNCT
brj-22095	248	10	li	li	PROPN
brj-22095	248	11	,	,	PUNCT
brj-22095	248	12	y.	y.	PROPN
brj-22095	248	13	,	,	PUNCT
brj-22095	248	14	huang	huang	PROPN
brj-22095	248	15	,	,	PUNCT
brj-22095	248	16	w.	w.	PROPN
brj-22095	248	17	,	,	PUNCT
brj-22095	248	18	ni	ni	PROPN
brj-22095	248	19	,	,	PUNCT
brj-22095	248	20	l.	l.	PROPN
brj-22095	248	21	,	,	PUNCT
brj-22095	248	22	and	and	CCONJ
brj-22095	248	23	ge	ge	PROPN
brj-22095	248	24	,	,	PUNCT
brj-22095	248	25	j.	j.	PROPN
brj-22095	248	26	(	(	PUNCT
brj-22095	248	27	2020	2020	NUM
brj-22095	248	28	)	)	PUNCT
brj-22095	248	29	.	.	PUNCT
brj-22095	249	1	“	"	PUNCT
brj-22095	249	2	the	the	DET
brj-22095	249	3	method	method	NOUN
brj-22095	249	4	of	of	ADP
brj-22095	249	5	calibration	calibration	NOUN
brj-22095	249	6	model	model	NOUN
brj-22095	249	7	transfer	transfer	NOUN
brj-22095	249	8	by	by	ADP
brj-22095	249	9	optimizing	optimize	VERB
brj-22095	249	10	wavelength	wavelength	NOUN
brj-22095	249	11	combinations	combination	NOUN
brj-22095	249	12	based	base	VERB
brj-22095	249	13	on	on	ADP
brj-22095	249	14	consistent	consistent	ADJ
brj-22095	249	15	and	and	CCONJ
brj-22095	249	16	stable	stable	ADJ
brj-22095	249	17	spectral	spectral	ADJ
brj-22095	249	18	signals	signal	NOUN
brj-22095	249	19	,	,	PUNCT
brj-22095	249	20	”	"	PUNCT
brj-22095	249	21	spectrochimica	spectrochimica	NOUN
brj-22095	249	22	acta	acta	PROPN
brj-22095	249	23	part	part	NOUN
brj-22095	249	24	a	a	PRON
brj-22095	249	25	:	:	PUNCT
brj-22095	249	26	molecular	molecular	ADJ
brj-22095	249	27	and	and	CCONJ
brj-22095	249	28	biomolecular	biomolecular	ADJ
brj-22095	249	29	spectroscopy	spectroscopy	VERB
brj-22095	249	30	227	227	NUM
brj-22095	249	31	,	,	PUNCT
brj-22095	249	32	117647	117647	NUM
brj-22095	249	33	.	.	PUNCT
brj-22095	250	1	doi	doi	NOUN
brj-22095	250	2	:	:	PUNCT
brj-22095	250	3	10.1016	10.1016	NUM
brj-22095	250	4	/	/	SYM
brj-22095	250	5	j.saa.2019.117647	j.saa.2019.117647	PROPN
brj-22095	250	6	zhang	zhang	PROPN
brj-22095	250	7	,	,	PUNCT
brj-22095	250	8	l.	l.	PROPN
brj-22095	250	9	,	,	PUNCT
brj-22095	250	10	wang	wang	PROPN
brj-22095	250	11	,	,	PUNCT
brj-22095	250	12	y.	y.	PROPN
brj-22095	250	13	,	,	PUNCT
brj-22095	250	14	wei	wei	PROPN
brj-22095	250	15	,	,	PUNCT
brj-22095	250	16	y.	y.	PROPN
brj-22095	250	17	,	,	PUNCT
brj-22095	250	18	and	and	CCONJ
brj-22095	250	19	an	an	DET
brj-22095	250	20	,	,	PUNCT
brj-22095	250	21	d.	d.	PROPN
brj-22095	250	22	(	(	PUNCT
brj-22095	250	23	2022	2022	NUM
brj-22095	250	24	)	)	PUNCT
brj-22095	250	25	.	.	PUNCT
brj-22095	251	1	“	"	PUNCT
brj-22095	251	2	near	near	ADV
brj-22095	251	3	-	-	PUNCT
brj-22095	251	4	infrared	infrared	ADJ
brj-22095	251	5	hyperspectral	hyperspectral	ADJ
brj-22095	251	6	imaging	imaging	NOUN
brj-22095	251	7	technology	technology	NOUN
brj-22095	251	8	combined	combine	VERB
brj-22095	251	9	with	with	ADP
brj-22095	251	10	deep	deep	ADJ
brj-22095	251	11	convolutional	convolutional	ADJ
brj-22095	251	12	generative	generative	ADJ
brj-22095	251	13	adversarial	adversarial	ADJ
brj-22095	251	14	network	network	NOUN
brj-22095	251	15	to	to	PART
brj-22095	251	16	predict	predict	VERB
brj-22095	251	17	oil	oil	NOUN
brj-22095	251	18	content	content	NOUN
brj-22095	251	19	of	of	ADP
brj-22095	251	20	single	single	ADJ
brj-22095	251	21	maize	maize	NOUN
brj-22095	251	22	kernel	kernel	NOUN
brj-22095	251	23	,	,	PUNCT
brj-22095	251	24	”	"	PUNCT
brj-22095	251	25	food	food	NOUN
brj-22095	251	26	chemistry	chemistry	NOUN
brj-22095	251	27	370	370	NUM
brj-22095	251	28	,	,	PUNCT
brj-22095	251	29	article	article	NOUN
brj-22095	251	30	no	no	NOUN
brj-22095	251	31	.	.	PROPN
brj-22095	251	32	131047	131047	NUM
brj-22095	251	33	.	.	PUNCT
brj-22095	252	1	doi	doi	NOUN
brj-22095	252	2	:	:	PUNCT
brj-22095	252	3	10.1016	10.1016	NUM
brj-22095	252	4	/	/	SYM
brj-22095	252	5	j.foodchem.2021.131047	j.foodchem.2021.131047	PROPN
brj-22095	252	6	zhao	zhao	PROPN
brj-22095	252	7	,	,	PUNCT
brj-22095	252	8	y.	y.	PROPN
brj-22095	252	9	,	,	PUNCT
brj-22095	252	10	yu	yu	PROPN
brj-22095	252	11	,	,	PUNCT
brj-22095	252	12	j.	j.	PROPN
brj-22095	252	13	,	,	PUNCT
brj-22095	252	14	shan	shan	PROPN
brj-22095	252	15	,	,	PUNCT
brj-22095	252	16	p.	p.	PROPN
brj-22095	252	17	,	,	PUNCT
brj-22095	252	18	zhao	zhao	PROPN
brj-22095	252	19	,	,	PUNCT
brj-22095	252	20	z.	z.	PROPN
brj-22095	252	21	,	,	PUNCT
brj-22095	252	22	jiang	jiang	PROPN
brj-22095	252	23	,	,	PUNCT
brj-22095	252	24	x.	x.	NOUN
brj-22095	252	25	,	,	PUNCT
brj-22095	252	26	and	and	CCONJ
brj-22095	252	27	gao	gao	PROPN
brj-22095	252	28	,	,	PUNCT
brj-22095	252	29	s.	s.	PROPN
brj-22095	252	30	(	(	PUNCT
brj-22095	252	31	2019	2019	NUM
brj-22095	252	32	)	)	PUNCT
brj-22095	252	33	.	.	PUNCT
brj-22095	253	1	“	"	PUNCT
brj-22095	253	2	pls	pls	INTJ
brj-22095	253	3	subspace	subspace	NOUN
brj-22095	253	4	-	-	PUNCT
brj-22095	253	5	based	base	VERB
brj-22095	253	6	calibration	calibration	NOUN
brj-22095	253	7	transfer	transfer	NOUN
brj-22095	253	8	for	for	ADP
brj-22095	253	9	near	near	ADV
brj-22095	253	10	-	-	PUNCT
brj-22095	253	11	infrared	infrared	ADJ
brj-22095	253	12	spectroscopy	spectroscopy	NOUN
brj-22095	253	13	quantitative	quantitative	ADJ
brj-22095	253	14	analysis	analysis	NOUN
brj-22095	253	15	,	,	PUNCT
brj-22095	253	16	”	"	PUNCT
brj-22095	253	17	molecules	molecule	NOUN
brj-22095	253	18	24(7	24(7	NUM
brj-22095	253	19	)	)	PUNCT
brj-22095	253	20	,	,	PUNCT
brj-22095	253	21	article	article	NOUN
brj-22095	253	22	no	no	NOUN
brj-22095	253	23	.	.	PROPN
brj-22095	253	24	1289	1289	NUM
brj-22095	253	25	.	.	PUNCT
brj-22095	254	1	doi	doi	NOUN
brj-22095	254	2	:	:	PUNCT
brj-22095	254	3	10.3390	10.3390	NUM
brj-22095	254	4	/	/	SYM
brj-22095	254	5	molecules24071289	molecules24071289	NOUN
brj-22095	254	6	article	article	NOUN
brj-22095	254	7	submitted	submit	VERB
brj-22095	254	8	:	:	PUNCT
brj-22095	254	9	august	august	PROPN
brj-22095	254	10	3	3	NUM
brj-22095	254	11	,	,	PUNCT
brj-22095	254	12	2022	2022	NUM
brj-22095	254	13	;	;	PUNCT
brj-22095	254	14	peer	peer	NOUN
brj-22095	254	15	review	review	NOUN
brj-22095	254	16	completed	complete	VERB
brj-22095	254	17	:	:	PUNCT
brj-22095	254	18	september	september	PROPN
brj-22095	254	19	24	24	NUM
brj-22095	254	20	,	,	PUNCT
brj-22095	254	21	2022	2022	NUM
brj-22095	254	22	;	;	PUNCT
brj-22095	254	23	revised	revise	VERB
brj-22095	254	24	version	version	NOUN
brj-22095	254	25	received	receive	VERB
brj-22095	254	26	and	and	CCONJ
brj-22095	254	27	accepted	accept	VERB
brj-22095	254	28	:	:	PUNCT
brj-22095	254	29	september	september	PROPN
brj-22095	254	30	28	28	NUM
brj-22095	254	31	,	,	PUNCT
brj-22095	254	32	2022	2022	NUM
brj-22095	254	33	;	;	PUNCT
brj-22095	254	34	published	publish	VERB
brj-22095	254	35	:	:	PUNCT
brj-22095	254	36	october	october	PROPN
brj-22095	254	37	3	3	NUM
brj-22095	254	38	,	,	PUNCT
brj-22095	254	39	2022	2022	NUM
brj-22095	254	40	.	.	PUNCT
brj-22095	255	1	doi	doi	NOUN
brj-22095	255	2	:	:	PUNCT
brj-22095	255	3	10.15376	10.15376	NUM
brj-22095	255	4	/	/	SYM
brj-22095	255	5	biores.17.4.6476	biores.17.4.6476	NOUN
brj-22095	255	6	-	-	PUNCT
brj-22095	255	7	6489	6489	NUM