id	sid	tid	token	lemma	pos
brj-24353	1	1	peer	peer	NOUN
brj-24353	1	2	-	-	PUNCT
brj-24353	1	3	review	review	NOUN
brj-24353	1	4	article	article	NOUN
brj-24353	1	5	peer	peer	NOUN
brj-24353	1	6	-	-	PUNCT
brj-24353	1	7	reviewed	review	VERB
brj-24353	1	8	article	article	NOUN
brj-24353	1	9	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	1	10	wang	wang	PROPN
brj-24353	1	11	et	et	PROPN
brj-24353	1	12	al	al	PROPN
brj-24353	1	13	.	.	PROPN
brj-24353	2	1	(	(	PUNCT
brj-24353	2	2	2025	2025	NUM
brj-24353	2	3	)	)	PUNCT
brj-24353	2	4	.	.	PUNCT
brj-24353	3	1	“	"	PUNCT
brj-24353	3	2	wood	wood	NOUN
brj-24353	3	3	i	i	X
brj-24353	3	4	d	d	PROPN
brj-24353	3	5	via	via	ADP
brj-24353	3	6	.	.	PUNCT
brj-24353	4	1	s	s	PROPN
brj-24353	4	2	-	-	PUNCT
brj-24353	4	3	nir	nir	PROPN
brj-24353	4	4	&	&	CCONJ
brj-24353	4	5	dr	dr	PROPN
brj-24353	4	6	-	-	PUNCT
brj-24353	4	7	nir	nir	PROPN
brj-24353	4	8	,	,	PUNCT
brj-24353	4	9	”	"	PUNCT
brj-24353	4	10	bioresources	bioresource	NOUN
brj-24353	4	11	20(3	20(3	NOUN
brj-24353	4	12	)	)	PUNCT
brj-24353	4	13	,	,	PUNCT
brj-24353	4	14	6648	6648	NUM
brj-24353	4	15	-	-	SYM
brj-24353	4	16	6661	6661	NUM
brj-24353	4	17	.	.	PUNCT
brj-24353	5	1	6648	6648	NUM
brj-24353	5	2	comparative	comparative	ADJ
brj-24353	5	3	analysis	analysis	NOUN
brj-24353	5	4	of	of	ADP
brj-24353	5	5	specular	specular	ADJ
brj-24353	5	6	and	and	CCONJ
brj-24353	5	7	diffuse	diffuse	VERB
brj-24353	5	8	reflection	reflection	NOUN
brj-24353	5	9	near	near	ADP
brj-24353	5	10	-	-	PUNCT
brj-24353	5	11	infrared	infrared	ADJ
brj-24353	5	12	spectra	spectra	NOUN
brj-24353	5	13	in	in	ADP
brj-24353	5	14	wood	wood	NOUN
brj-24353	5	15	species	specie	NOUN
brj-24353	5	16	classification	classification	NOUN
brj-24353	5	17	cheng	cheng	PROPN
brj-24353	5	18	-	-	PUNCT
brj-24353	5	19	kun	kun	PROPN
brj-24353	5	20	wang	wang	PROPN
brj-24353	5	21	,	,	PUNCT
brj-24353	5	22	a	a	DET
brj-24353	5	23	peng	peng	PROPN
brj-24353	5	24	zhao	zhao	PROPN
brj-24353	5	25	,	,	PUNCT
brj-24353	5	26	b	b	PROPN
brj-24353	5	27	,	,	PUNCT
brj-24353	5	28	c	c	NOUN
brj-24353	5	29	,	,	PUNCT
brj-24353	5	30	*	*	PUNCT
brj-24353	5	31	li	li	PROPN
brj-24353	5	32	-	-	PUNCT
brj-24353	5	33	na	na	NOUN
brj-24353	5	34	dong	dong	NOUN
brj-24353	5	35	,	,	PUNCT
brj-24353	5	36	a	a	DET
brj-24353	5	37	and	and	CCONJ
brj-24353	5	38	mao	mao	PROPN
brj-24353	5	39	-	-	PUNCT
brj-24353	5	40	ni	ni	PROPN
brj-24353	5	41	zhao	zhao	PROPN
brj-24353	5	42	a	a	DET
brj-24353	5	43	the	the	DET
brj-24353	5	44	near	near	ADV
brj-24353	5	45	-	-	PUNCT
brj-24353	5	46	infrared	infrared	ADJ
brj-24353	5	47	(	(	PUNCT
brj-24353	5	48	nir	nir	ADJ
brj-24353	5	49	)	)	PUNCT
brj-24353	5	50	spectral	spectral	ADJ
brj-24353	5	51	reflectance	reflectance	NOUN
brj-24353	5	52	characteristics	characteristic	NOUN
brj-24353	5	53	of	of	ADP
brj-24353	5	54	wood	wood	NOUN
brj-24353	5	55	cross	cross	NOUN
brj-24353	5	56	sections	section	NOUN
brj-24353	5	57	are	be	AUX
brj-24353	5	58	commonly	commonly	ADV
brj-24353	5	59	employed	employ	VERB
brj-24353	5	60	for	for	ADP
brj-24353	5	61	wood	wood	NOUN
brj-24353	5	62	species	specie	NOUN
brj-24353	5	63	classification	classification	NOUN
brj-24353	5	64	.	.	PUNCT
brj-24353	6	1	both	both	PRON
brj-24353	6	2	specular	specular	ADJ
brj-24353	6	3	and	and	CCONJ
brj-24353	6	4	diffuse	diffuse	VERB
brj-24353	6	5	reflectance	reflectance	NOUN
brj-24353	6	6	spectral	spectral	ADJ
brj-24353	6	7	curves	curve	NOUN
brj-24353	6	8	of	of	ADP
brj-24353	6	9	wood	wood	NOUN
brj-24353	6	10	cross	cross	NOUN
brj-24353	6	11	sections	section	NOUN
brj-24353	6	12	can	can	AUX
brj-24353	6	13	be	be	AUX
brj-24353	6	14	used	use	VERB
brj-24353	6	15	.	.	PUNCT
brj-24353	7	1	however	however	ADV
brj-24353	7	2	,	,	PUNCT
brj-24353	7	3	which	which	DET
brj-24353	7	4	one	one	NOUN
brj-24353	7	5	is	be	AUX
brj-24353	7	6	more	more	ADV
brj-24353	7	7	effective	effective	ADJ
brj-24353	7	8	for	for	ADP
brj-24353	7	9	classification	classification	NOUN
brj-24353	7	10	and	and	CCONJ
brj-24353	7	11	whether	whether	SCONJ
brj-24353	7	12	classification	classification	NOUN
brj-24353	7	13	models	model	NOUN
brj-24353	7	14	trained	train	VERB
brj-24353	7	15	on	on	ADP
brj-24353	7	16	these	these	DET
brj-24353	7	17	two	two	NUM
brj-24353	7	18	spectra	spectra	NOUN
brj-24353	7	19	can	can	AUX
brj-24353	7	20	be	be	AUX
brj-24353	7	21	used	use	VERB
brj-24353	7	22	interchangeably	interchangeably	ADV
brj-24353	7	23	have	have	AUX
brj-24353	7	24	not	not	PART
brj-24353	7	25	yet	yet	ADV
brj-24353	7	26	been	be	AUX
brj-24353	7	27	explored	explore	VERB
brj-24353	7	28	.	.	PUNCT
brj-24353	8	1	in	in	ADP
brj-24353	8	2	this	this	DET
brj-24353	8	3	study	study	NOUN
brj-24353	8	4	,	,	PUNCT
brj-24353	8	5	the	the	DET
brj-24353	8	6	nir	nir	ADJ
brj-24353	8	7	spectral	spectral	ADJ
brj-24353	8	8	curves	curve	NOUN
brj-24353	8	9	of	of	ADP
brj-24353	8	10	wood	wood	NOUN
brj-24353	8	11	cross	cross	NOUN
brj-24353	8	12	sections	section	NOUN
brj-24353	8	13	from	from	ADP
brj-24353	8	14	64	64	NUM
brj-24353	8	15	common	common	ADJ
brj-24353	8	16	timber	timber	NOUN
brj-24353	8	17	species	specie	NOUN
brj-24353	8	18	were	be	AUX
brj-24353	8	19	used	use	VERB
brj-24353	8	20	to	to	PART
brj-24353	8	21	evaluate	evaluate	VERB
brj-24353	8	22	the	the	DET
brj-24353	8	23	specular	specular	ADJ
brj-24353	8	24	and	and	CCONJ
brj-24353	8	25	diffuse	diffuse	VERB
brj-24353	8	26	reflectance	reflectance	NOUN
brj-24353	8	27	spectral	spectral	ADJ
brj-24353	8	28	profiles	profile	NOUN
brj-24353	8	29	through	through	ADP
brj-24353	8	30	five	five	NUM
brj-24353	8	31	classifier	classifier	NOUN
brj-24353	8	32	models	model	NOUN
brj-24353	8	33	—	—	PUNCT
brj-24353	8	34	namely	namely	ADV
brj-24353	8	35	,	,	PUNCT
brj-24353	8	36	the	the	DET
brj-24353	8	37	support	support	NOUN
brj-24353	8	38	vector	vector	NOUN
brj-24353	8	39	machine	machine	NOUN
brj-24353	8	40	(	(	PUNCT
brj-24353	8	41	svm	svm	PROPN
brj-24353	8	42	)	)	PUNCT
brj-24353	8	43	,	,	PUNCT
brj-24353	8	44	knearest	knearest	NOUN
brj-24353	8	45	neighbors	neighbor	NOUN
brj-24353	8	46	(	(	PUNCT
brj-24353	8	47	knn	knn	PROPN
brj-24353	8	48	)	)	PUNCT
brj-24353	8	49	,	,	PUNCT
brj-24353	8	50	convolutional	convolutional	ADJ
brj-24353	8	51	neural	neural	ADJ
brj-24353	8	52	network	network	NOUN
brj-24353	8	53	(	(	PUNCT
brj-24353	8	54	cnn	cnn	PROPN
brj-24353	8	55	)	)	PUNCT
brj-24353	8	56	,	,	PUNCT
brj-24353	8	57	decision	decision	NOUN
brj-24353	8	58	tree	tree	NOUN
brj-24353	8	59	(	(	PUNCT
brj-24353	8	60	dt	dt	NOUN
brj-24353	8	61	)	)	PUNCT
brj-24353	8	62	,	,	PUNCT
brj-24353	8	63	and	and	CCONJ
brj-24353	8	64	nearest	near	ADJ
brj-24353	8	65	class	class	NOUN
brj-24353	8	66	mean	mean	NOUN
brj-24353	8	67	(	(	PUNCT
brj-24353	8	68	ncm	ncm	PROPN
brj-24353	8	69	)	)	PUNCT
brj-24353	8	70	classifiers	classifier	NOUN
brj-24353	8	71	.	.	PUNCT
brj-24353	9	1	the	the	DET
brj-24353	9	2	classification	classification	NOUN
brj-24353	9	3	accuracies	accuracy	NOUN
brj-24353	9	4	of	of	ADP
brj-24353	9	5	specular	specular	ADJ
brj-24353	9	6	and	and	CCONJ
brj-24353	9	7	diffuse	diffuse	VERB
brj-24353	9	8	reflectance	reflectance	NOUN
brj-24353	9	9	curves	curve	NOUN
brj-24353	9	10	using	use	VERB
brj-24353	9	11	svm	svm	PROPN
brj-24353	9	12	classifier	classifier	NOUN
brj-24353	9	13	were	be	AUX
brj-24353	9	14	88.43	88.43	NUM
brj-24353	9	15	%	%	NOUN
brj-24353	9	16	and	and	CCONJ
brj-24353	9	17	88.02	88.02	NUM
brj-24353	9	18	%	%	NOUN
brj-24353	9	19	,	,	PUNCT
brj-24353	9	20	respectively	respectively	ADV
brj-24353	9	21	,	,	PUNCT
brj-24353	9	22	whereas	whereas	SCONJ
brj-24353	9	23	other	other	ADJ
brj-24353	9	24	classifiers	classifier	NOUN
brj-24353	9	25	exhibited	exhibit	VERB
brj-24353	9	26	lower	low	ADJ
brj-24353	9	27	classification	classification	NOUN
brj-24353	9	28	accuracy	accuracy	NOUN
brj-24353	9	29	,	,	PUNCT
brj-24353	9	30	with	with	ADP
brj-24353	9	31	specular	specular	ADJ
brj-24353	9	32	reflectance	reflectance	NOUN
brj-24353	9	33	spectral	spectral	ADJ
brj-24353	9	34	classification	classification	NOUN
brj-24353	9	35	accuracy	accuracy	NOUN
brj-24353	9	36	consistently	consistently	ADV
brj-24353	9	37	outperforming	outperform	VERB
brj-24353	9	38	diffuse	diffuse	PROPN
brj-24353	9	39	spectral	spectral	ADJ
brj-24353	9	40	classification	classification	NOUN
brj-24353	9	41	.	.	PUNCT
brj-24353	10	1	additionally	additionally	ADV
brj-24353	10	2	,	,	PUNCT
brj-24353	10	3	experimental	experimental	ADJ
brj-24353	10	4	results	result	NOUN
brj-24353	10	5	demonstrated	demonstrate	VERB
brj-24353	10	6	that	that	SCONJ
brj-24353	10	7	correct	correct	ADJ
brj-24353	10	8	classification	classification	NOUN
brj-24353	10	9	rate	rate	NOUN
brj-24353	10	10	of	of	ADP
brj-24353	10	11	the	the	DET
brj-24353	10	12	testing	testing	NOUN
brj-24353	10	13	dataset	dataset	VERB
brj-24353	10	14	after	after	SCONJ
brj-24353	10	15	cross	cross	NOUN
brj-24353	10	16	-	-	ADJ
brj-24353	10	17	use	use	NOUN
brj-24353	10	18	was	be	AUX
brj-24353	10	19	less	less	ADJ
brj-24353	10	20	than	than	ADP
brj-24353	10	21	16	16	NUM
brj-24353	10	22	%	%	NOUN
brj-24353	10	23	,	,	PUNCT
brj-24353	10	24	indicating	indicate	VERB
brj-24353	10	25	that	that	SCONJ
brj-24353	10	26	classifier	classifier	NOUN
brj-24353	10	27	models	model	NOUN
brj-24353	10	28	trained	train	VERB
brj-24353	10	29	on	on	ADP
brj-24353	10	30	these	these	DET
brj-24353	10	31	two	two	NUM
brj-24353	10	32	spectra	spectra	NOUN
brj-24353	10	33	could	could	AUX
brj-24353	10	34	not	not	PART
brj-24353	10	35	be	be	AUX
brj-24353	10	36	used	use	VERB
brj-24353	10	37	interchangeably	interchangeably	ADV
brj-24353	10	38	.	.	PUNCT
brj-24353	11	1	in	in	ADP
brj-24353	11	2	conclusion	conclusion	NOUN
brj-24353	11	3	,	,	PUNCT
brj-24353	11	4	this	this	DET
brj-24353	11	5	study	study	NOUN
brj-24353	11	6	suggested	suggest	VERB
brj-24353	11	7	that	that	SCONJ
brj-24353	11	8	specular	specular	ADJ
brj-24353	11	9	reflectance	reflectance	NOUN
brj-24353	11	10	nir	nir	ADJ
brj-24353	11	11	spectral	spectral	ADJ
brj-24353	11	12	curves	curve	NOUN
brj-24353	11	13	are	be	AUX
brj-24353	11	14	more	more	ADV
brj-24353	11	15	suitable	suitable	ADJ
brj-24353	11	16	for	for	ADP
brj-24353	11	17	wood	wood	NOUN
brj-24353	11	18	species	specie	NOUN
brj-24353	11	19	classification	classification	NOUN
brj-24353	11	20	.	.	PUNCT
brj-24353	12	1	doi	doi	NOUN
brj-24353	12	2	:	:	PUNCT
brj-24353	12	3	10.15376	10.15376	NUM
brj-24353	12	4	/	/	SYM
brj-24353	12	5	biores.20.3.6648	biores.20.3.6648	PROPN
brj-24353	12	6	-	-	PUNCT
brj-24353	12	7	6661	6661	NUM
brj-24353	12	8	keywords	keyword	NOUN
brj-24353	12	9	:	:	PUNCT
brj-24353	12	10	wood	wood	NOUN
brj-24353	12	11	species	specie	NOUN
brj-24353	12	12	classification	classification	NOUN
brj-24353	12	13	;	;	PUNCT
brj-24353	12	14	specular	specular	ADJ
brj-24353	12	15	reflectance	reflectance	NOUN
brj-24353	12	16	spectrum	spectrum	NOUN
brj-24353	12	17	;	;	PUNCT
brj-24353	12	18	diffuse	diffuse	NOUN
brj-24353	12	19	reflectance	reflectance	NOUN
brj-24353	12	20	spectrum	spectrum	NOUN
brj-24353	12	21	;	;	PUNCT
brj-24353	12	22	spectral	spectral	ADJ
brj-24353	12	23	analysis	analysis	NOUN
brj-24353	12	24	contact	contact	NOUN
brj-24353	12	25	information	information	NOUN
brj-24353	12	26	:	:	PUNCT
brj-24353	12	27	a	a	DET
brj-24353	12	28	:	:	PUNCT
brj-24353	12	29	school	school	NOUN
brj-24353	12	30	of	of	ADP
brj-24353	12	31	electronic	electronic	ADJ
brj-24353	12	32	and	and	CCONJ
brj-24353	12	33	information	information	NOUN
brj-24353	12	34	engineering	engineering	NOUN
brj-24353	12	35	,	,	PUNCT
brj-24353	12	36	heilongjiang	heilongjiang	PROPN
brj-24353	12	37	university	university	PROPN
brj-24353	12	38	of	of	ADP
brj-24353	12	39	science	science	NOUN
brj-24353	12	40	and	and	CCONJ
brj-24353	12	41	technology	technology	NOUN
brj-24353	12	42	,	,	PUNCT
brj-24353	12	43	harbin	harbin	PROPN
brj-24353	12	44	150010	150010	NUM
brj-24353	12	45	,	,	PUNCT
brj-24353	12	46	china	china	PROPN
brj-24353	12	47	;	;	PUNCT
brj-24353	12	48	b	b	X
brj-24353	12	49	:	:	PUNCT
brj-24353	12	50	school	school	NOUN
brj-24353	12	51	of	of	ADP
brj-24353	12	52	computer	computer	NOUN
brj-24353	12	53	science	science	NOUN
brj-24353	12	54	and	and	CCONJ
brj-24353	12	55	communication	communication	NOUN
brj-24353	12	56	engineering	engineering	NOUN
brj-24353	12	57	,	,	PUNCT
brj-24353	12	58	guangxi	guangxi	PROPN
brj-24353	12	59	university	university	PROPN
brj-24353	12	60	of	of	ADP
brj-24353	12	61	science	science	NOUN
brj-24353	12	62	and	and	CCONJ
brj-24353	12	63	technology	technology	NOUN
brj-24353	12	64	,	,	PUNCT
brj-24353	12	65	liuzhou	liuzhou	PROPN
brj-24353	12	66	545006	545006	NUM
brj-24353	12	67	,	,	PUNCT
brj-24353	12	68	china	china	PROPN
brj-24353	12	69	;	;	PUNCT
brj-24353	12	70	c	c	X
brj-24353	12	71	:	:	PUNCT
brj-24353	12	72	guangxi	guangxi	NOUN
brj-24353	12	73	colleges	college	NOUN
brj-24353	12	74	and	and	CCONJ
brj-24353	12	75	universities	university	NOUN
brj-24353	12	76	key	key	ADJ
brj-24353	12	77	laboratory	laboratory	NOUN
brj-24353	12	78	of	of	ADP
brj-24353	12	79	intelligent	intelligent	ADJ
brj-24353	12	80	computing	computing	NOUN
brj-24353	12	81	and	and	CCONJ
brj-24353	12	82	distributed	distribute	VERB
brj-24353	12	83	information	information	NOUN
brj-24353	12	84	processing	processing	NOUN
brj-24353	12	85	,	,	PUNCT
brj-24353	12	86	liuzhou	liuzhou	PROPN
brj-24353	12	87	545006	545006	NUM
brj-24353	12	88	,	,	PUNCT
brj-24353	12	89	china	china	PROPN
brj-24353	12	90	.	.	PUNCT
brj-24353	13	1	*	*	PUNCT
brj-24353	13	2	corresponding	correspond	VERB
brj-24353	13	3	author	author	NOUN
brj-24353	13	4	:	:	PUNCT
brj-24353	13	5	bit_zhao@aliyun.com	bit_zhao@aliyun.com	X
brj-24353	13	6	introduction	introduction	NOUN
brj-24353	13	7	there	there	PRON
brj-24353	13	8	are	be	VERB
brj-24353	13	9	an	an	DET
brj-24353	13	10	estimated	estimate	VERB
brj-24353	13	11	60,065	60,065	NUM
brj-24353	13	12	timber	timber	NOUN
brj-24353	13	13	species	specie	NOUN
brj-24353	13	14	worldwide	worldwide	ADV
brj-24353	13	15	.	.	PUNCT
brj-24353	14	1	currently	currently	ADV
brj-24353	14	2	,	,	PUNCT
brj-24353	14	3	five	five	NUM
brj-24353	14	4	main	main	ADJ
brj-24353	14	5	methods	method	NOUN
brj-24353	14	6	are	be	AUX
brj-24353	14	7	used	use	VERB
brj-24353	14	8	to	to	PART
brj-24353	14	9	identify	identify	VERB
brj-24353	14	10	them	they	PRON
brj-24353	14	11	,	,	PUNCT
brj-24353	14	12	namely	namely	ADV
brj-24353	14	13	image	image	NOUN
brj-24353	14	14	processing	processing	NOUN
brj-24353	14	15	classification	classification	NOUN
brj-24353	14	16	(	(	PUNCT
brj-24353	14	17	verly	verly	ADV
brj-24353	14	18	lopes	lope	VERB
brj-24353	14	19	et	et	PROPN
brj-24353	14	20	al	al	PROPN
brj-24353	14	21	.	.	PROPN
brj-24353	14	22	2020	2020	NUM
brj-24353	14	23	)	)	PUNCT
brj-24353	14	24	,	,	PUNCT
brj-24353	14	25	spectral	spectral	ADJ
brj-24353	14	26	analysis	analysis	NOUN
brj-24353	14	27	classification	classification	NOUN
brj-24353	14	28	(	(	PUNCT
brj-24353	14	29	ma	ma	PROPN
brj-24353	14	30	et	et	PROPN
brj-24353	14	31	al	al	PROPN
brj-24353	14	32	.	.	PROPN
brj-24353	14	33	2019	2019	NUM
brj-24353	14	34	)	)	PUNCT
brj-24353	14	35	,	,	PUNCT
brj-24353	14	36	wood	wood	NOUN
brj-24353	14	37	microstructure	microstructure	NOUN
brj-24353	14	38	classification	classification	NOUN
brj-24353	14	39	(	(	PUNCT
brj-24353	14	40	zhan	zhan	PROPN
brj-24353	14	41	et	et	PROPN
brj-24353	14	42	al	al	PROPN
brj-24353	14	43	.	.	PROPN
brj-24353	14	44	2023	2023	NUM
brj-24353	14	45	)	)	PUNCT
brj-24353	14	46	,	,	PUNCT
brj-24353	14	47	deoxyribonucleic	deoxyribonucleic	ADJ
brj-24353	14	48	acid	acid	NOUN
brj-24353	14	49	(	(	PUNCT
brj-24353	14	50	dna	dna	NOUN
brj-24353	14	51	)	)	PUNCT
brj-24353	14	52	genetic	genetic	ADJ
brj-24353	14	53	information	information	NOUN
brj-24353	14	54	classification	classification	NOUN
brj-24353	14	55	(	(	PUNCT
brj-24353	14	56	antil	antil	ADP
brj-24353	14	57	et	et	PROPN
brj-24353	14	58	al	al	PROPN
brj-24353	14	59	.	.	PROPN
brj-24353	14	60	2023	2023	NUM
brj-24353	14	61	)	)	PUNCT
brj-24353	14	62	,	,	PUNCT
brj-24353	14	63	and	and	CCONJ
brj-24353	14	64	chemical	chemical	NOUN
brj-24353	14	65	fingerprinting	fingerprint	VERB
brj-24353	14	66	classification	classification	NOUN
brj-24353	14	67	(	(	PUNCT
brj-24353	14	68	deklerck	deklerck	PROPN
brj-24353	14	69	et	et	PROPN
brj-24353	14	70	al	al	PROPN
brj-24353	14	71	.	.	PROPN
brj-24353	14	72	2020	2020	NUM
brj-24353	14	73	)	)	PUNCT
brj-24353	14	74	.	.	PUNCT
brj-24353	15	1	among	among	ADP
brj-24353	15	2	these	these	DET
brj-24353	15	3	methods	method	NOUN
brj-24353	15	4	,	,	PUNCT
brj-24353	15	5	spectral	spectral	ADJ
brj-24353	15	6	analysis	analysis	NOUN
brj-24353	15	7	classification	classification	NOUN
brj-24353	15	8	offers	offer	VERB
brj-24353	15	9	advantages	advantage	NOUN
brj-24353	15	10	that	that	PRON
brj-24353	15	11	include	include	VERB
brj-24353	15	12	its	its	PRON
brj-24353	15	13	high	high	ADJ
brj-24353	15	14	classification	classification	NOUN
brj-24353	15	15	speed	speed	NOUN
brj-24353	15	16	,	,	PUNCT
brj-24353	15	17	high	high	ADJ
brj-24353	15	18	accuracy	accuracy	NOUN
brj-24353	15	19	,	,	PUNCT
brj-24353	15	20	and	and	CCONJ
brj-24353	15	21	low	low	ADJ
brj-24353	15	22	computational	computational	ADJ
brj-24353	15	23	overhead	overhead	NOUN
brj-24353	15	24	.	.	PUNCT
brj-24353	16	1	spectral	spectral	ADJ
brj-24353	16	2	analysis	analysis	NOUN
brj-24353	16	3	itself	itself	PRON
brj-24353	16	4	can	can	AUX
brj-24353	16	5	be	be	AUX
brj-24353	16	6	further	far	ADV
brj-24353	16	7	divided	divide	VERB
brj-24353	16	8	into	into	ADP
brj-24353	16	9	four	four	NUM
brj-24353	16	10	distinct	distinct	ADJ
brj-24353	16	11	categories	category	NOUN
brj-24353	16	12	.	.	PUNCT
brj-24353	17	1	the	the	DET
brj-24353	17	2	first	first	ADJ
brj-24353	17	3	category	category	NOUN
brj-24353	17	4	involves	involve	VERB
brj-24353	17	5	fourier	fouri	ADJ
brj-24353	17	6	transform	transform	NOUN
brj-24353	17	7	infrared	infrared	ADJ
brj-24353	17	8	(	(	PUNCT
brj-24353	17	9	ftir	ftir	NOUN
brj-24353	17	10	)	)	PUNCT
brj-24353	17	11	analysis	analysis	NOUN
brj-24353	17	12	for	for	ADP
brj-24353	17	13	wood	wood	NOUN
brj-24353	17	14	species	specie	NOUN
brj-24353	17	15	classification	classification	NOUN
brj-24353	17	16	,	,	PUNCT
brj-24353	17	17	which	which	DET
brj-24353	17	18	peer	peer	NOUN
brj-24353	17	19	-	-	PUNCT
brj-24353	17	20	reviewed	review	VERB
brj-24353	17	21	article	article	NOUN
brj-24353	17	22	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	17	23	wang	wang	PROPN
brj-24353	17	24	et	et	PROPN
brj-24353	17	25	al	al	PROPN
brj-24353	17	26	.	.	PROPN
brj-24353	18	1	(	(	PUNCT
brj-24353	18	2	2025	2025	NUM
brj-24353	18	3	)	)	PUNCT
brj-24353	18	4	.	.	PUNCT
brj-24353	19	1	“	"	PUNCT
brj-24353	19	2	wood	wood	NOUN
brj-24353	19	3	i	i	X
brj-24353	19	4	d	d	PROPN
brj-24353	19	5	via	via	ADP
brj-24353	19	6	.	.	PUNCT
brj-24353	20	1	s	s	PROPN
brj-24353	20	2	-	-	PUNCT
brj-24353	20	3	nir	nir	PROPN
brj-24353	20	4	&	&	CCONJ
brj-24353	20	5	dr	dr	PROPN
brj-24353	20	6	-	-	PUNCT
brj-24353	20	7	nir	nir	PROPN
brj-24353	20	8	,	,	PUNCT
brj-24353	20	9	”	"	PUNCT
brj-24353	20	10	bioresources	bioresource	NOUN
brj-24353	20	11	20(3	20(3	NOUN
brj-24353	20	12	)	)	PUNCT
brj-24353	20	13	,	,	PUNCT
brj-24353	20	14	6648	6648	NUM
brj-24353	20	15	-	-	SYM
brj-24353	20	16	6661	6661	NUM
brj-24353	20	17	.	.	PUNCT
brj-24353	21	1	6649	6649	NUM
brj-24353	21	2	is	be	AUX
brj-24353	21	3	a	a	DET
brj-24353	21	4	rapid	rapid	ADJ
brj-24353	21	5	,	,	PUNCT
brj-24353	21	6	nondestructive	nondestructive	ADJ
brj-24353	21	7	method	method	NOUN
brj-24353	21	8	(	(	PUNCT
brj-24353	21	9	sharma	sharma	PROPN
brj-24353	21	10	et	et	PROPN
brj-24353	21	11	al	al	PROPN
brj-24353	21	12	.	.	PROPN
brj-24353	21	13	2020	2020	NUM
brj-24353	21	14	)	)	PUNCT
brj-24353	21	15	.	.	PUNCT
brj-24353	22	1	however	however	ADV
brj-24353	22	2	,	,	PUNCT
brj-24353	22	3	it	it	PRON
brj-24353	22	4	requires	require	VERB
brj-24353	22	5	sophisticated	sophisticated	ADJ
brj-24353	22	6	equipment	equipment	NOUN
brj-24353	22	7	and	and	CCONJ
brj-24353	22	8	stringent	stringent	ADJ
brj-24353	22	9	experimental	experimental	ADJ
brj-24353	22	10	conditions	condition	NOUN
brj-24353	22	11	.	.	PUNCT
brj-24353	23	1	the	the	DET
brj-24353	23	2	second	second	ADJ
brj-24353	23	3	category	category	NOUN
brj-24353	23	4	employs	employ	VERB
brj-24353	23	5	terahertz	terahertz	NOUN
brj-24353	23	6	spectroscopy	spectroscopy	NOUN
brj-24353	23	7	to	to	PART
brj-24353	23	8	identify	identify	VERB
brj-24353	23	9	wood	wood	NOUN
brj-24353	23	10	species	specie	NOUN
brj-24353	23	11	.	.	PUNCT
brj-24353	24	1	for	for	ADP
brj-24353	24	2	example	example	NOUN
brj-24353	24	3	,	,	PUNCT
brj-24353	24	4	zhang	zhang	PROPN
brj-24353	24	5	et	et	PROPN
brj-24353	24	6	al	al	PROPN
brj-24353	24	7	.	.	PROPN
brj-24353	24	8	(	(	PUNCT
brj-24353	24	9	2023	2023	NUM
brj-24353	24	10	)	)	PUNCT
brj-24353	24	11	used	use	VERB
brj-24353	24	12	terahertz	terahertz	NOUN
brj-24353	24	13	time	time	NOUN
brj-24353	24	14	-	-	PUNCT
brj-24353	24	15	domain	domain	NOUN
brj-24353	24	16	spectroscopy	spectroscopy	NOUN
brj-24353	24	17	to	to	PART
brj-24353	24	18	classify	classify	VERB
brj-24353	24	19	wood	wood	NOUN
brj-24353	24	20	species	specie	NOUN
brj-24353	24	21	by	by	ADP
brj-24353	24	22	measuring	measure	VERB
brj-24353	24	23	the	the	DET
brj-24353	24	24	spectral	spectral	ADJ
brj-24353	24	25	differences	difference	NOUN
brj-24353	24	26	of	of	ADP
brj-24353	24	27	manglietia	manglietia	NOUN
brj-24353	24	28	,	,	PUNCT
brj-24353	24	29	amur	amur	PROPN
brj-24353	24	30	linden	linden	PROPN
brj-24353	24	31	,	,	PUNCT
brj-24353	24	32	black	black	ADJ
brj-24353	24	33	walnut	walnut	NOUN
brj-24353	24	34	,	,	PUNCT
brj-24353	24	35	and	and	CCONJ
brj-24353	24	36	ebony	ebony	NOUN
brj-24353	24	37	in	in	ADP
brj-24353	24	38	the	the	DET
brj-24353	24	39	0.1	0.1	NUM
brj-24353	24	40	to	to	PART
brj-24353	24	41	0.9	0.9	NUM
brj-24353	24	42	thz	thz	ADJ
brj-24353	24	43	frequency	frequency	NOUN
brj-24353	24	44	range	range	NOUN
brj-24353	24	45	in	in	ADP
brj-24353	24	46	combination	combination	NOUN
brj-24353	24	47	with	with	ADP
brj-24353	24	48	principal	principal	ADJ
brj-24353	24	49	component	component	NOUN
brj-24353	24	50	analysis	analysis	NOUN
brj-24353	24	51	.	.	PUNCT
brj-24353	25	1	however	however	ADV
brj-24353	25	2	,	,	PUNCT
brj-24353	25	3	high	high	ADJ
brj-24353	25	4	-	-	PUNCT
brj-24353	25	5	quality	quality	NOUN
brj-24353	25	6	terahertz	terahertz	NOUN
brj-24353	25	7	equipment	equipment	NOUN
brj-24353	25	8	can	can	AUX
brj-24353	25	9	be	be	AUX
brj-24353	25	10	expensive	expensive	ADJ
brj-24353	25	11	and	and	CCONJ
brj-24353	25	12	requires	require	VERB
brj-24353	25	13	precise	precise	ADJ
brj-24353	25	14	sample	sample	NOUN
brj-24353	25	15	preparation	preparation	NOUN
brj-24353	25	16	.	.	PUNCT
brj-24353	26	1	the	the	DET
brj-24353	26	2	third	third	ADJ
brj-24353	26	3	category	category	NOUN
brj-24353	26	4	leverages	leverage	VERB
brj-24353	26	5	hyperspectral	hyperspectral	ADJ
brj-24353	26	6	imaging	imaging	NOUN
brj-24353	26	7	by	by	ADP
brj-24353	26	8	combining	combine	VERB
brj-24353	26	9	the	the	DET
brj-24353	26	10	spectral	spectral	ADJ
brj-24353	26	11	and	and	CCONJ
brj-24353	26	12	image	image	NOUN
brj-24353	26	13	information	information	NOUN
brj-24353	26	14	from	from	ADP
brj-24353	26	15	wood	wood	NOUN
brj-24353	26	16	surfaces	surface	NOUN
brj-24353	26	17	for	for	ADP
brj-24353	26	18	classification	classification	NOUN
brj-24353	26	19	.	.	PUNCT
brj-24353	27	1	kanayama	kanayama	PROPN
brj-24353	27	2	et	et	PROPN
brj-24353	27	3	al	al	PROPN
brj-24353	27	4	.	.	PROPN
brj-24353	28	1	(	(	PUNCT
brj-24353	28	2	2019	2019	NUM
brj-24353	28	3	)	)	PUNCT
brj-24353	28	4	used	use	VERB
brj-24353	28	5	hyperspectral	hyperspectral	ADJ
brj-24353	28	6	images	image	NOUN
brj-24353	28	7	and	and	CCONJ
brj-24353	28	8	a	a	DET
brj-24353	28	9	convolutional	convolutional	ADJ
brj-24353	28	10	neural	neural	ADJ
brj-24353	28	11	network	network	NOUN
brj-24353	28	12	(	(	PUNCT
brj-24353	28	13	cnn	cnn	PROPN
brj-24353	28	14	)	)	PUNCT
brj-24353	28	15	model	model	NOUN
brj-24353	28	16	to	to	PART
brj-24353	28	17	classify	classify	VERB
brj-24353	28	18	wood	wood	NOUN
brj-24353	28	19	species	specie	NOUN
brj-24353	28	20	.	.	PUNCT
brj-24353	29	1	however	however	ADV
brj-24353	29	2	,	,	PUNCT
brj-24353	29	3	hyperspectral	hyperspectral	ADJ
brj-24353	29	4	imaging	imaging	NOUN
brj-24353	29	5	devices	device	NOUN
brj-24353	29	6	can	can	AUX
brj-24353	29	7	be	be	AUX
brj-24353	29	8	costly	costly	ADJ
brj-24353	29	9	and	and	CCONJ
brj-24353	29	10	the	the	DET
brj-24353	29	11	process	process	NOUN
brj-24353	29	12	of	of	ADP
brj-24353	29	13	collecting	collect	VERB
brj-24353	29	14	hyperspectral	hyperspectral	ADJ
brj-24353	29	15	images	image	NOUN
brj-24353	29	16	from	from	ADP
brj-24353	29	17	wood	wood	NOUN
brj-24353	29	18	surfaces	surface	NOUN
brj-24353	29	19	can	can	AUX
brj-24353	29	20	be	be	AUX
brj-24353	29	21	time	time	NOUN
brj-24353	29	22	-	-	PUNCT
brj-24353	29	23	consuming	consume	VERB
brj-24353	29	24	,	,	PUNCT
brj-24353	29	25	resulting	result	VERB
brj-24353	29	26	in	in	ADP
brj-24353	29	27	poor	poor	ADJ
brj-24353	29	28	real	real	ADJ
brj-24353	29	29	-	-	PUNCT
brj-24353	29	30	time	time	NOUN
brj-24353	29	31	performance	performance	NOUN
brj-24353	29	32	.	.	PUNCT
brj-24353	30	1	in	in	ADP
brj-24353	30	2	summary	summary	NOUN
brj-24353	30	3	,	,	PUNCT
brj-24353	30	4	these	these	DET
brj-24353	30	5	three	three	NUM
brj-24353	30	6	methods	method	NOUN
brj-24353	30	7	rely	rely	VERB
brj-24353	30	8	on	on	ADP
brj-24353	30	9	expensive	expensive	ADJ
brj-24353	30	10	instrumentation	instrumentation	NOUN
brj-24353	30	11	and	and	CCONJ
brj-24353	30	12	are	be	AUX
brj-24353	30	13	generally	generally	ADV
brj-24353	30	14	more	more	ADV
brj-24353	30	15	suitable	suitable	ADJ
brj-24353	30	16	for	for	ADP
brj-24353	30	17	laboratory	laboratory	NOUN
brj-24353	30	18	-	-	PUNCT
brj-24353	30	19	based	base	VERB
brj-24353	30	20	testing	testing	NOUN
brj-24353	30	21	and	and	CCONJ
brj-24353	30	22	processing	processing	NOUN
brj-24353	30	23	.	.	PUNCT
brj-24353	31	1	the	the	DET
brj-24353	31	2	fourth	fourth	ADJ
brj-24353	31	3	category	category	NOUN
brj-24353	31	4	involves	involve	VERB
brj-24353	31	5	the	the	DET
brj-24353	31	6	use	use	NOUN
brj-24353	31	7	of	of	ADP
brj-24353	31	8	a	a	DET
brj-24353	31	9	cheap	cheap	ADJ
brj-24353	31	10	micro	micro	NOUN
brj-24353	31	11	-	-	NOUN
brj-24353	31	12	spectrometer	spectrometer	NOUN
brj-24353	31	13	to	to	PART
brj-24353	31	14	collect	collect	VERB
brj-24353	31	15	spectral	spectral	ADJ
brj-24353	31	16	reflectance	reflectance	NOUN
brj-24353	31	17	curves	curve	NOUN
brj-24353	31	18	from	from	ADP
brj-24353	31	19	wood	wood	NOUN
brj-24353	31	20	cross	cross	NOUN
brj-24353	31	21	sections	section	NOUN
brj-24353	31	22	for	for	ADP
brj-24353	31	23	classification	classification	NOUN
brj-24353	31	24	.	.	PUNCT
brj-24353	32	1	the	the	DET
brj-24353	32	2	cheap	cheap	ADJ
brj-24353	32	3	micro	micro	NOUN
brj-24353	32	4	-	-	NOUN
brj-24353	32	5	spectrometers	spectrometer	NOUN
brj-24353	32	6	employed	employ	VERB
brj-24353	32	7	in	in	ADP
brj-24353	32	8	this	this	DET
brj-24353	32	9	method	method	NOUN
brj-24353	32	10	are	be	AUX
brj-24353	32	11	generally	generally	ADV
brj-24353	32	12	more	more	ADV
brj-24353	32	13	affordable	affordable	ADJ
brj-24353	32	14	and	and	CCONJ
brj-24353	32	15	well	well	ADV
brj-24353	32	16	-	-	PUNCT
brj-24353	32	17	suited	suit	VERB
brj-24353	32	18	for	for	ADP
brj-24353	32	19	on	on	ADP
brj-24353	32	20	-	-	PUNCT
brj-24353	32	21	site	site	NOUN
brj-24353	32	22	inspection	inspection	NOUN
brj-24353	32	23	and	and	CCONJ
brj-24353	32	24	processing	processing	NOUN
brj-24353	32	25	.	.	PUNCT
brj-24353	33	1	for	for	ADP
brj-24353	33	2	example	example	NOUN
brj-24353	33	3	,	,	PUNCT
brj-24353	33	4	luo	luo	PROPN
brj-24353	33	5	et	et	PROPN
brj-24353	33	6	al	al	PROPN
brj-24353	33	7	.	.	PROPN
brj-24353	34	1	(	(	PUNCT
brj-24353	34	2	2023	2023	NUM
brj-24353	34	3	)	)	PUNCT
brj-24353	34	4	used	use	VERB
brj-24353	34	5	near	near	ADV
brj-24353	34	6	-	-	PUNCT
brj-24353	34	7	infrared	infrared	ADJ
brj-24353	34	8	(	(	PUNCT
brj-24353	34	9	nir	nir	NOUN
brj-24353	34	10	)	)	PUNCT
brj-24353	34	11	spectroscopy	spectroscopy	VERB
brj-24353	34	12	in	in	ADP
brj-24353	34	13	combination	combination	NOUN
brj-24353	34	14	with	with	ADP
brj-24353	34	15	six	six	NUM
brj-24353	34	16	classifier	classifier	NOUN
brj-24353	34	17	models	model	NOUN
brj-24353	34	18	—	—	PUNCT
brj-24353	34	19	that	that	ADV
brj-24353	34	20	is	is	ADV
brj-24353	34	21	,	,	PUNCT
brj-24353	34	22	that	that	PRON
brj-24353	34	23	support	support	VERB
brj-24353	34	24	vector	vector	NOUN
brj-24353	34	25	machine	machine	NOUN
brj-24353	34	26	(	(	PUNCT
brj-24353	34	27	svm	svm	PROPN
brj-24353	34	28	)	)	PUNCT
brj-24353	34	29	,	,	PUNCT
brj-24353	34	30	logistic	logistic	ADJ
brj-24353	34	31	regression	regression	NOUN
brj-24353	34	32	,	,	PUNCT
brj-24353	34	33	naïve	naïve	ADJ
brj-24353	34	34	bayes	bayes	NOUN
brj-24353	34	35	,	,	PUNCT
brj-24353	34	36	k	k	NOUN
brj-24353	34	37	-	-	PUNCT
brj-24353	34	38	nearest	near	ADJ
brj-24353	34	39	neighbors	neighbor	NOUN
brj-24353	34	40	(	(	PUNCT
brj-24353	34	41	knn	knn	PROPN
brj-24353	34	42	)	)	PUNCT
brj-24353	34	43	,	,	PUNCT
brj-24353	34	44	random	random	ADJ
brj-24353	34	45	forest	forest	NOUN
brj-24353	34	46	,	,	PUNCT
brj-24353	34	47	and	and	CCONJ
brj-24353	34	48	artificial	artificial	ADJ
brj-24353	34	49	neural	neural	ADJ
brj-24353	34	50	network	network	NOUN
brj-24353	34	51	models	model	NOUN
brj-24353	34	52	—	—	PUNCT
brj-24353	34	53	to	to	PART
brj-24353	34	54	classify	classify	VERB
brj-24353	34	55	12	12	NUM
brj-24353	34	56	timber	timber	NOUN
brj-24353	34	57	species	specie	NOUN
brj-24353	34	58	.	.	PUNCT
brj-24353	35	1	the	the	DET
brj-24353	35	2	experimental	experimental	ADJ
brj-24353	35	3	results	result	NOUN
brj-24353	35	4	demonstrated	demonstrate	VERB
brj-24353	35	5	that	that	SCONJ
brj-24353	35	6	the	the	DET
brj-24353	35	7	svm	svm	ADJ
brj-24353	35	8	-	-	PUNCT
brj-24353	35	9	based	base	VERB
brj-24353	35	10	model	model	NOUN
brj-24353	35	11	achieved	achieve	VERB
brj-24353	35	12	the	the	DET
brj-24353	35	13	highest	high	ADJ
brj-24353	35	14	classification	classification	NOUN
brj-24353	35	15	accuracy	accuracy	NOUN
brj-24353	35	16	(	(	PUNCT
brj-24353	35	17	98.24	98.24	NUM
brj-24353	35	18	%	%	NOUN
brj-24353	35	19	)	)	PUNCT
brj-24353	35	20	.	.	PUNCT
brj-24353	36	1	wang	wang	PROPN
brj-24353	36	2	et	et	PROPN
brj-24353	36	3	al	al	PROPN
brj-24353	36	4	.	.	PROPN
brj-24353	36	5	(	(	PUNCT
brj-24353	36	6	2024	2024	NUM
brj-24353	36	7	)	)	PUNCT
brj-24353	36	8	investigated	investigate	VERB
brj-24353	36	9	the	the	DET
brj-24353	36	10	deformation	deformation	NOUN
brj-24353	36	11	of	of	ADP
brj-24353	36	12	the	the	DET
brj-24353	36	13	corresponding	corresponding	ADJ
brj-24353	36	14	nir	nir	ADJ
brj-24353	36	15	spectral	spectral	ADJ
brj-24353	36	16	curves	curve	NOUN
brj-24353	36	17	and	and	CCONJ
brj-24353	36	18	their	their	PRON
brj-24353	36	19	correction	correction	NOUN
brj-24353	36	20	after	after	ADP
brj-24353	36	21	applying	apply	VERB
brj-24353	36	22	a	a	DET
brj-24353	36	23	transparent	transparent	ADJ
brj-24353	36	24	finish	finish	NOUN
brj-24353	36	25	to	to	ADP
brj-24353	36	26	the	the	DET
brj-24353	36	27	wood	wood	NOUN
brj-24353	36	28	surfaces	surface	NOUN
brj-24353	36	29	,	,	PUNCT
brj-24353	36	30	before	before	ADP
brj-24353	36	31	using	use	VERB
brj-24353	36	32	the	the	DET
brj-24353	36	33	corrected	correct	VERB
brj-24353	36	34	nir	nir	ADJ
brj-24353	36	35	spectral	spectral	ADJ
brj-24353	36	36	curves	curve	NOUN
brj-24353	36	37	to	to	PART
brj-24353	36	38	classify	classify	VERB
brj-24353	36	39	and	and	CCONJ
brj-24353	36	40	recognize	recognize	VERB
brj-24353	36	41	the	the	DET
brj-24353	36	42	wood	wood	NOUN
brj-24353	36	43	species	specie	NOUN
brj-24353	36	44	,	,	PUNCT
brj-24353	36	45	achieving	achieve	VERB
brj-24353	36	46	high	high	ADJ
brj-24353	36	47	classification	classification	NOUN
brj-24353	36	48	accuracy	accuracy	NOUN
brj-24353	36	49	.	.	PUNCT
brj-24353	37	1	during	during	ADP
brj-24353	37	2	the	the	DET
brj-24353	37	3	collection	collection	NOUN
brj-24353	37	4	of	of	ADP
brj-24353	37	5	nir	nir	ADJ
brj-24353	37	6	spectral	spectral	ADJ
brj-24353	37	7	reflectance	reflectance	NOUN
brj-24353	37	8	curves	curve	NOUN
brj-24353	37	9	using	use	VERB
brj-24353	37	10	the	the	DET
brj-24353	37	11	miniature	miniature	ADJ
brj-24353	37	12	spectrometer	spectrometer	NOUN
brj-24353	37	13	,	,	PUNCT
brj-24353	37	14	variations	variation	NOUN
brj-24353	37	15	in	in	ADP
brj-24353	37	16	the	the	DET
brj-24353	37	17	incident	incident	NOUN
brj-24353	37	18	angles	angle	NOUN
brj-24353	37	19	of	of	ADP
brj-24353	37	20	the	the	DET
brj-24353	37	21	fiber	fiber	NOUN
brj-24353	37	22	-	-	PUNCT
brj-24353	37	23	optic	optic	NOUN
brj-24353	37	24	probe	probe	NOUN
brj-24353	37	25	relative	relative	ADJ
brj-24353	37	26	to	to	ADP
brj-24353	37	27	the	the	DET
brj-24353	37	28	object	object	NOUN
brj-24353	37	29	’s	’s	PART
brj-24353	37	30	surface	surface	NOUN
brj-24353	37	31	can	can	AUX
brj-24353	37	32	result	result	VERB
brj-24353	37	33	in	in	ADP
brj-24353	37	34	two	two	NUM
brj-24353	37	35	types	type	NOUN
brj-24353	37	36	of	of	ADP
brj-24353	37	37	spectra	spectra	NOUN
brj-24353	37	38	:	:	PUNCT
brj-24353	37	39	specular	specular	ADJ
brj-24353	37	40	reflectance	reflectance	NOUN
brj-24353	37	41	and	and	CCONJ
brj-24353	37	42	diffuse	diffuse	VERB
brj-24353	37	43	reflectance	reflectance	NOUN
brj-24353	37	44	.	.	PUNCT
brj-24353	38	1	the	the	DET
brj-24353	38	2	corresponding	corresponding	ADJ
brj-24353	38	3	spectral	spectral	ADJ
brj-24353	38	4	reflectance	reflectance	NOUN
brj-24353	38	5	curves	curve	NOUN
brj-24353	38	6	exhibit	exhibit	VERB
brj-24353	38	7	distinct	distinct	ADJ
brj-24353	38	8	differences	difference	NOUN
brj-24353	38	9	.	.	PUNCT
brj-24353	39	1	however	however	ADV
brj-24353	39	2	,	,	PUNCT
brj-24353	39	3	the	the	DET
brj-24353	39	4	question	question	NOUN
brj-24353	39	5	of	of	ADP
brj-24353	39	6	which	which	PRON
brj-24353	39	7	spectral	spectral	ADJ
brj-24353	39	8	reflectance	reflectance	NOUN
brj-24353	39	9	curve	curve	NOUN
brj-24353	39	10	provides	provide	VERB
brj-24353	39	11	better	well	ADJ
brj-24353	39	12	classification	classification	NOUN
brj-24353	39	13	and	and	CCONJ
brj-24353	39	14	recognition	recognition	NOUN
brj-24353	39	15	accuracy	accuracy	NOUN
brj-24353	39	16	,	,	PUNCT
brj-24353	39	17	and	and	CCONJ
brj-24353	39	18	whether	whether	SCONJ
brj-24353	39	19	classifier	classifier	NOUN
brj-24353	39	20	models	model	NOUN
brj-24353	39	21	trained	train	VERB
brj-24353	39	22	on	on	ADP
brj-24353	39	23	these	these	DET
brj-24353	39	24	two	two	NUM
brj-24353	39	25	distinct	distinct	ADJ
brj-24353	39	26	spectral	spectral	ADJ
brj-24353	39	27	profiles	profile	NOUN
brj-24353	39	28	can	can	AUX
brj-24353	39	29	be	be	AUX
brj-24353	39	30	used	use	VERB
brj-24353	39	31	interchangeably	interchangeably	ADV
brj-24353	39	32	,	,	PUNCT
brj-24353	39	33	has	have	AUX
brj-24353	39	34	not	not	PART
brj-24353	39	35	yet	yet	ADV
brj-24353	39	36	been	be	AUX
brj-24353	39	37	addressed	address	VERB
brj-24353	39	38	.	.	PUNCT
brj-24353	40	1	consequently	consequently	ADV
brj-24353	40	2	,	,	PUNCT
brj-24353	40	3	this	this	DET
brj-24353	40	4	study	study	NOUN
brj-24353	40	5	focused	focus	VERB
brj-24353	40	6	on	on	ADP
brj-24353	40	7	64	64	NUM
brj-24353	40	8	common	common	ADJ
brj-24353	40	9	wood	wood	NOUN
brj-24353	40	10	species	specie	NOUN
brj-24353	40	11	to	to	PART
brj-24353	40	12	compare	compare	VERB
brj-24353	40	13	and	and	CCONJ
brj-24353	40	14	investigate	investigate	VERB
brj-24353	40	15	the	the	DET
brj-24353	40	16	use	use	NOUN
brj-24353	40	17	of	of	ADP
brj-24353	40	18	specular	specular	ADJ
brj-24353	40	19	and	and	CCONJ
brj-24353	40	20	diffuse	diffuse	VERB
brj-24353	40	21	reflectance	reflectance	NOUN
brj-24353	40	22	spectra	spectra	NOUN
brj-24353	40	23	from	from	ADP
brj-24353	40	24	wood	wood	PROPN
brj-24353	40	25	cross	cross	NOUN
brj-24353	40	26	sections	section	NOUN
brj-24353	40	27	for	for	ADP
brj-24353	40	28	species	species	NOUN
brj-24353	40	29	classification	classification	NOUN
brj-24353	40	30	and	and	CCONJ
brj-24353	40	31	recognition	recognition	NOUN
brj-24353	40	32	.	.	PUNCT
brj-24353	41	1	it	it	PRON
brj-24353	41	2	further	far	ADV
brj-24353	41	3	analyzed	analyze	VERB
brj-24353	41	4	the	the	DET
brj-24353	41	5	classification	classification	NOUN
brj-24353	41	6	accuracy	accuracy	NOUN
brj-24353	41	7	of	of	ADP
brj-24353	41	8	wood	wood	NOUN
brj-24353	41	9	species	specie	NOUN
brj-24353	41	10	in	in	ADP
brj-24353	41	11	both	both	DET
brj-24353	41	12	cases	case	NOUN
brj-24353	41	13	and	and	CCONJ
brj-24353	41	14	explored	explore	VERB
brj-24353	41	15	the	the	DET
brj-24353	41	16	potential	potential	NOUN
brj-24353	41	17	for	for	ADP
brj-24353	41	18	cross	cross	ADJ
brj-24353	41	19	-	-	ADJ
brj-24353	41	20	using	use	VERB
brj-24353	41	21	classifier	classifier	NOUN
brj-24353	41	22	models	model	NOUN
brj-24353	41	23	trained	train	VERB
brj-24353	41	24	on	on	ADP
brj-24353	41	25	them	they	PRON
brj-24353	41	26	both	both	PRON
brj-24353	41	27	.	.	PUNCT
brj-24353	42	1	experimental	experimental	ADJ
brj-24353	42	2	materials	material	NOUN
brj-24353	42	3	in	in	ADP
brj-24353	42	4	this	this	DET
brj-24353	42	5	study	study	NOUN
brj-24353	42	6	,	,	PUNCT
brj-24353	42	7	64	64	NUM
brj-24353	42	8	hardwood	hardwood	ADJ
brj-24353	42	9	and	and	CCONJ
brj-24353	42	10	coniferous	coniferous	ADJ
brj-24353	42	11	wood	wood	NOUN
brj-24353	42	12	species	specie	NOUN
brj-24353	42	13	were	be	AUX
brj-24353	42	14	used	use	VERB
brj-24353	42	15	as	as	ADP
brj-24353	42	16	the	the	DET
brj-24353	42	17	experimental	experimental	ADJ
brj-24353	42	18	subjects	subject	NOUN
brj-24353	42	19	.	.	PUNCT
brj-24353	43	1	the	the	DET
brj-24353	43	2	specific	specific	ADJ
brj-24353	43	3	details	detail	NOUN
brj-24353	43	4	of	of	ADP
brj-24353	43	5	these	these	DET
brj-24353	43	6	wood	wood	NOUN
brj-24353	43	7	species	specie	NOUN
brj-24353	43	8	are	be	AUX
brj-24353	43	9	provided	provide	VERB
brj-24353	43	10	in	in	ADP
brj-24353	43	11	table	table	NOUN
brj-24353	43	12	1	1	NUM
brj-24353	43	13	,	,	PUNCT
brj-24353	43	14	which	which	PRON
brj-24353	43	15	demonstrates	demonstrate	VERB
brj-24353	43	16	that	that	SCONJ
brj-24353	43	17	they	they	PRON
brj-24353	43	18	included	include	VERB
brj-24353	43	19	both	both	DET
brj-24353	43	20	species	specie	NOUN
brj-24353	43	21	from	from	ADP
brj-24353	43	22	the	the	DET
brj-24353	43	23	same	same	ADJ
brj-24353	43	24	genus	genus	NOUN
brj-24353	43	25	and	and	CCONJ
brj-24353	43	26	those	those	PRON
brj-24353	43	27	with	with	ADP
brj-24353	43	28	visually	visually	ADV
brj-24353	43	29	similar	similar	ADJ
brj-24353	43	30	textures	texture	NOUN
brj-24353	43	31	.	.	PUNCT
brj-24353	44	1	the	the	DET
brj-24353	44	2	spectral	spectral	ADJ
brj-24353	44	3	reflectance	reflectance	NOUN
brj-24353	44	4	profiles	profile	NOUN
brj-24353	44	5	of	of	ADP
brj-24353	44	6	the	the	DET
brj-24353	44	7	wood	wood	NOUN
brj-24353	44	8	sample	sample	PROPN
brj-24353	44	9	cross	cross	NOUN
brj-24353	44	10	sections	section	NOUN
brj-24353	44	11	were	be	AUX
brj-24353	44	12	collected	collect	VERB
brj-24353	44	13	using	use	VERB
brj-24353	44	14	a	a	DET
brj-24353	44	15	micro	micro	NOUN
brj-24353	44	16	-	-	NOUN
brj-24353	44	17	spectrometer	spectrometer	NOUN
brj-24353	44	18	.	.	PUNCT
brj-24353	45	1	timber	timber	NOUN
brj-24353	45	2	samples	sample	NOUN
brj-24353	45	3	were	be	AUX
brj-24353	45	4	prepared	prepared	ADJ
brj-24353	45	5	peer	peer	NOUN
brj-24353	45	6	-	-	PUNCT
brj-24353	45	7	reviewed	review	VERB
brj-24353	45	8	article	article	NOUN
brj-24353	45	9	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	45	10	wang	wang	PROPN
brj-24353	45	11	et	et	PROPN
brj-24353	45	12	al	al	PROPN
brj-24353	45	13	.	.	PROPN
brj-24353	46	1	(	(	PUNCT
brj-24353	46	2	2025	2025	NUM
brj-24353	46	3	)	)	PUNCT
brj-24353	46	4	.	.	PUNCT
brj-24353	47	1	“	"	PUNCT
brj-24353	47	2	wood	wood	NOUN
brj-24353	47	3	i	i	X
brj-24353	47	4	d	d	PROPN
brj-24353	47	5	via	via	ADP
brj-24353	47	6	.	.	PUNCT
brj-24353	48	1	s	s	PROPN
brj-24353	48	2	-	-	PUNCT
brj-24353	48	3	nir	nir	PROPN
brj-24353	48	4	&	&	CCONJ
brj-24353	48	5	dr	dr	PROPN
brj-24353	48	6	-	-	PUNCT
brj-24353	48	7	nir	nir	PROPN
brj-24353	48	8	,	,	PUNCT
brj-24353	48	9	”	"	PUNCT
brj-24353	48	10	bioresources	bioresource	NOUN
brj-24353	48	11	20(3	20(3	NOUN
brj-24353	48	12	)	)	PUNCT
brj-24353	48	13	,	,	PUNCT
brj-24353	48	14	6648	6648	NUM
brj-24353	48	15	-	-	SYM
brj-24353	48	16	6661	6661	NUM
brj-24353	48	17	.	.	PUNCT
brj-24353	49	1	6650	6650	NUM
brj-24353	49	2	following	follow	VERB
brj-24353	49	3	national	national	ADJ
brj-24353	49	4	standards	standard	NOUN
brj-24353	49	5	.	.	PUNCT
brj-24353	50	1	for	for	ADP
brj-24353	50	2	each	each	DET
brj-24353	50	3	species	specie	NOUN
brj-24353	50	4	,	,	PUNCT
brj-24353	50	5	25	25	NUM
brj-24353	50	6	pieces	piece	NOUN
brj-24353	50	7	of	of	ADP
brj-24353	50	8	sawn	sawn	NOUN
brj-24353	50	9	timber	timber	NOUN
brj-24353	50	10	pieces	piece	NOUN
brj-24353	50	11	from	from	ADP
brj-24353	50	12	different	different	ADJ
brj-24353	50	13	trees	tree	NOUN
brj-24353	50	14	at	at	ADP
brj-24353	50	15	different	different	ADJ
brj-24353	50	16	locations	location	NOUN
brj-24353	50	17	were	be	AUX
brj-24353	50	18	selected	select	VERB
brj-24353	50	19	.	.	PUNCT
brj-24353	51	1	these	these	DET
brj-24353	51	2	pieces	piece	NOUN
brj-24353	51	3	were	be	AUX
brj-24353	51	4	uniformly	uniformly	ADV
brj-24353	51	5	cut	cut	VERB
brj-24353	51	6	into	into	ADP
brj-24353	51	7	small	small	ADJ
brj-24353	51	8	blocks	block	NOUN
brj-24353	51	9	measuring	measure	VERB
brj-24353	51	10	2	2	NUM
brj-24353	51	11	×	×	NOUN
brj-24353	51	12	2	2	NUM
brj-24353	51	13	×	×	NOUN
brj-24353	51	14	3	3	NUM
brj-24353	51	15	cm3	cm3	NOUN
brj-24353	51	16	,	,	PUNCT
brj-24353	51	17	with	with	ADP
brj-24353	51	18	the	the	DET
brj-24353	51	19	2	2	NUM
brj-24353	51	20	×	×	NOUN
brj-24353	51	21	2	2	NUM
brj-24353	51	22	cm2	cm2	NOUN
brj-24353	51	23	side	side	NOUN
brj-24353	51	24	representing	represent	VERB
brj-24353	51	25	the	the	DET
brj-24353	51	26	cross	cross	NOUN
brj-24353	51	27	section	section	NOUN
brj-24353	51	28	and	and	CCONJ
brj-24353	51	29	the	the	DET
brj-24353	51	30	2	2	NUM
brj-24353	51	31	×	×	NOUN
brj-24353	51	32	3	3	NUM
brj-24353	51	33	cm2	cm2	NOUN
brj-24353	51	34	side	side	NOUN
brj-24353	51	35	representing	represent	VERB
brj-24353	51	36	either	either	CCONJ
brj-24353	51	37	the	the	DET
brj-24353	51	38	tangential	tangential	ADJ
brj-24353	51	39	or	or	CCONJ
brj-24353	51	40	radial	radial	ADJ
brj-24353	51	41	section	section	NOUN
brj-24353	51	42	.	.	PUNCT
brj-24353	52	1	from	from	ADP
brj-24353	52	2	the	the	DET
brj-24353	52	3	cut	cut	NOUN
brj-24353	52	4	pieces	piece	NOUN
brj-24353	52	5	,	,	PUNCT
brj-24353	52	6	50	50	NUM
brj-24353	52	7	small	small	ADJ
brj-24353	52	8	blocks	block	NOUN
brj-24353	52	9	were	be	AUX
brj-24353	52	10	randomly	randomly	ADV
brj-24353	52	11	selected	select	VERB
brj-24353	52	12	as	as	ADP
brj-24353	52	13	experimental	experimental	ADJ
brj-24353	52	14	samples	sample	NOUN
brj-24353	52	15	for	for	ADP
brj-24353	52	16	data	data	NOUN
brj-24353	52	17	collection	collection	NOUN
brj-24353	52	18	,	,	PUNCT
brj-24353	52	19	with	with	ADP
brj-24353	52	20	two	two	NUM
brj-24353	52	21	blocks	block	NOUN
brj-24353	52	22	being	be	AUX
brj-24353	52	23	selected	select	VERB
brj-24353	52	24	from	from	ADP
brj-24353	52	25	each	each	DET
brj-24353	52	26	sawn	sawn	NOUN
brj-24353	52	27	timber	timber	NOUN
brj-24353	52	28	sample	sample	NOUN
brj-24353	52	29	.	.	PUNCT
brj-24353	53	1	prior	prior	ADV
brj-24353	53	2	to	to	ADP
brj-24353	53	3	spectral	spectral	ADJ
brj-24353	53	4	data	datum	NOUN
brj-24353	53	5	collection	collection	NOUN
brj-24353	53	6	,	,	PUNCT
brj-24353	53	7	the	the	DET
brj-24353	53	8	cross	cross	NOUN
brj-24353	53	9	sections	section	NOUN
brj-24353	53	10	of	of	ADP
brj-24353	53	11	the	the	DET
brj-24353	53	12	wood	wood	NOUN
brj-24353	53	13	samples	sample	NOUN
brj-24353	53	14	were	be	AUX
brj-24353	53	15	sanded	sand	VERB
brj-24353	53	16	individually	individually	ADV
brj-24353	53	17	using	use	VERB
brj-24353	53	18	800grit	800grit	PROPN
brj-24353	53	19	and	and	CCONJ
brj-24353	53	20	1200	1200	NUM
brj-24353	53	21	-	-	PUNCT
brj-24353	53	22	grit	grit	NOUN
brj-24353	53	23	sandpaper	sandpaper	NOUN
brj-24353	53	24	to	to	PART
brj-24353	53	25	ensure	ensure	VERB
brj-24353	53	26	that	that	SCONJ
brj-24353	53	27	the	the	DET
brj-24353	53	28	surfaces	surface	NOUN
brj-24353	53	29	were	be	AUX
brj-24353	53	30	smooth	smooth	ADJ
brj-24353	53	31	and	and	CCONJ
brj-24353	53	32	free	free	ADJ
brj-24353	53	33	of	of	ADP
brj-24353	53	34	burrs	burrs	NOUN
brj-24353	53	35	.	.	PUNCT
brj-24353	54	1	in	in	ADP
brj-24353	54	2	practice	practice	NOUN
brj-24353	54	3	,	,	PUNCT
brj-24353	54	4	the	the	DET
brj-24353	54	5	wood	wood	NOUN
brj-24353	54	6	nir	nir	ADJ
brj-24353	54	7	spectral	spectral	ADJ
brj-24353	54	8	curves	curve	NOUN
brj-24353	54	9	may	may	AUX
brj-24353	54	10	be	be	AUX
brj-24353	54	11	sensitive	sensitive	ADJ
brj-24353	54	12	to	to	ADP
brj-24353	54	13	some	some	DET
brj-24353	54	14	external	external	ADJ
brj-24353	54	15	environmental	environmental	ADJ
brj-24353	54	16	factors	factor	NOUN
brj-24353	54	17	,	,	PUNCT
brj-24353	54	18	such	such	ADJ
brj-24353	54	19	as	as	ADP
brj-24353	54	20	temperature	temperature	NOUN
brj-24353	54	21	and	and	CCONJ
brj-24353	54	22	humidity	humidity	NOUN
brj-24353	54	23	,	,	PUNCT
brj-24353	54	24	so	so	CCONJ
brj-24353	54	25	the	the	DET
brj-24353	54	26	spectral	spectral	ADJ
brj-24353	54	27	acquisition	acquisition	NOUN
brj-24353	54	28	was	be	AUX
brj-24353	54	29	performed	perform	VERB
brj-24353	54	30	in	in	ADP
brj-24353	54	31	a	a	DET
brj-24353	54	32	room	room	NOUN
brj-24353	54	33	with	with	ADP
brj-24353	54	34	temperature	temperature	NOUN
brj-24353	54	35	at	at	ADP
brj-24353	54	36	25	25	NUM
brj-24353	54	37	°	°	NOUN
brj-24353	54	38	c	c	NOUN
brj-24353	54	39	and	and	CCONJ
brj-24353	54	40	humidity	humidity	NOUN
brj-24353	54	41	at	at	ADP
brj-24353	54	42	40	40	NUM
brj-24353	54	43	%	%	NOUN
brj-24353	54	44	.	.	PUNCT
brj-24353	55	1	it	it	PRON
brj-24353	55	2	should	should	AUX
brj-24353	55	3	be	be	AUX
brj-24353	55	4	noted	note	VERB
brj-24353	55	5	that	that	SCONJ
brj-24353	55	6	the	the	DET
brj-24353	55	7	physical	physical	ADJ
brj-24353	55	8	property	property	NOUN
brj-24353	55	9	of	of	ADP
brj-24353	55	10	wood	wood	NOUN
brj-24353	55	11	samples	sample	NOUN
brj-24353	55	12	was	be	AUX
brj-24353	55	13	influenced	influence	VERB
brj-24353	55	14	by	by	ADP
brj-24353	55	15	some	some	DET
brj-24353	55	16	variables	variable	NOUN
brj-24353	55	17	such	such	ADJ
brj-24353	55	18	as	as	ADP
brj-24353	55	19	the	the	DET
brj-24353	55	20	age	age	NOUN
brj-24353	55	21	of	of	ADP
brj-24353	55	22	trees	tree	NOUN
brj-24353	55	23	,	,	PUNCT
brj-24353	55	24	geographic	geographic	ADJ
brj-24353	55	25	origin	origin	NOUN
brj-24353	55	26	,	,	PUNCT
brj-24353	55	27	growth	growth	NOUN
brj-24353	55	28	ring	ring	NOUN
brj-24353	55	29	position	position	NOUN
brj-24353	55	30	,	,	PUNCT
brj-24353	55	31	and	and	CCONJ
brj-24353	55	32	proportion	proportion	NOUN
brj-24353	55	33	of	of	ADP
brj-24353	55	34	latewood	latewood	NOUN
brj-24353	55	35	versus	versus	ADP
brj-24353	55	36	earlywood	earlywood	NOUN
brj-24353	55	37	.	.	PUNCT
brj-24353	56	1	these	these	DET
brj-24353	56	2	variables	variable	NOUN
brj-24353	56	3	were	be	AUX
brj-24353	56	4	controlled	control	VERB
brj-24353	56	5	effectively	effectively	ADV
brj-24353	56	6	in	in	ADP
brj-24353	56	7	wood	wood	NOUN
brj-24353	56	8	spectral	spectral	ADJ
brj-24353	56	9	acquisition	acquisition	NOUN
brj-24353	56	10	so	so	SCONJ
brj-24353	56	11	that	that	SCONJ
brj-24353	56	12	the	the	DET
brj-24353	56	13	within	within	ADP
brj-24353	56	14	-	-	PUNCT
brj-24353	56	15	class	class	NOUN
brj-24353	56	16	difference	difference	NOUN
brj-24353	56	17	of	of	ADP
brj-24353	56	18	spectral	spectral	ADJ
brj-24353	56	19	curves	curve	NOUN
brj-24353	56	20	for	for	ADP
brj-24353	56	21	each	each	DET
brj-24353	56	22	wood	wood	NOUN
brj-24353	56	23	species	specie	NOUN
brj-24353	56	24	was	be	AUX
brj-24353	56	25	adequately	adequately	ADV
brj-24353	56	26	small	small	ADJ
brj-24353	56	27	.	.	PUNCT
brj-24353	57	1	this	this	DET
brj-24353	57	2	control	control	NOUN
brj-24353	57	3	was	be	AUX
brj-24353	57	4	implemented	implement	VERB
brj-24353	57	5	in	in	ADP
brj-24353	57	6	practice	practice	NOUN
brj-24353	57	7	in	in	ADP
brj-24353	57	8	the	the	DET
brj-24353	57	9	random	random	ADJ
brj-24353	57	10	selection	selection	NOUN
brj-24353	57	11	of	of	ADP
brj-24353	57	12	50	50	NUM
brj-24353	57	13	wood	wood	NOUN
brj-24353	57	14	blocks	block	NOUN
brj-24353	57	15	for	for	ADP
brj-24353	57	16	every	every	DET
brj-24353	57	17	wood	wood	NOUN
brj-24353	57	18	species	specie	NOUN
brj-24353	57	19	by	by	ADP
brj-24353	57	20	ensuring	ensure	VERB
brj-24353	57	21	that	that	SCONJ
brj-24353	57	22	trace	trace	NOUN
brj-24353	57	23	(	(	PUNCT
brj-24353	57	24	cw	cw	NOUN
brj-24353	57	25	)	)	PUNCT
brj-24353	57	26	was	be	AUX
brj-24353	57	27	small	small	ADJ
brj-24353	57	28	or	or	CCONJ
brj-24353	57	29	less	less	ADJ
brj-24353	57	30	than	than	ADP
brj-24353	57	31	a	a	DET
brj-24353	57	32	threshold	threshold	NOUN
brj-24353	57	33	for	for	ADP
brj-24353	57	34	every	every	DET
brj-24353	57	35	species	specie	NOUN
brj-24353	57	36	(	(	PUNCT
brj-24353	57	37	i.e.	i.e.	X
brj-24353	57	38	,	,	PUNCT
brj-24353	57	39	cw	cw	NOUN
brj-24353	57	40	denoted	denote	VERB
brj-24353	57	41	the	the	DET
brj-24353	57	42	within	within	ADP
brj-24353	57	43	-	-	PUNCT
brj-24353	57	44	class	class	NOUN
brj-24353	57	45	scatter	scatter	NOUN
brj-24353	57	46	matrix	matrix	NOUN
brj-24353	57	47	for	for	ADP
brj-24353	57	48	one	one	NUM
brj-24353	57	49	class	class	NOUN
brj-24353	57	50	in	in	ADP
brj-24353	57	51	terms	term	NOUN
brj-24353	57	52	of	of	ADP
brj-24353	57	53	spectral	spectral	ADJ
brj-24353	57	54	curves	curve	NOUN
brj-24353	57	55	)	)	PUNCT
brj-24353	57	56	.	.	PUNCT
brj-24353	58	1	specifically	specifically	ADV
brj-24353	58	2	,	,	PUNCT
brj-24353	58	3	in	in	ADP
brj-24353	58	4	the	the	DET
brj-24353	58	5	spectral	spectral	ADJ
brj-24353	58	6	acquisition	acquisition	NOUN
brj-24353	58	7	process	process	NOUN
brj-24353	58	8	,	,	PUNCT
brj-24353	58	9	spectral	spectral	ADJ
brj-24353	58	10	curves	curve	NOUN
brj-24353	58	11	were	be	AUX
brj-24353	58	12	collected	collect	VERB
brj-24353	58	13	from	from	ADP
brj-24353	58	14	five	five	NUM
brj-24353	58	15	different	different	ADJ
brj-24353	58	16	positions	position	NOUN
brj-24353	58	17	on	on	ADP
brj-24353	58	18	the	the	DET
brj-24353	58	19	cross	cross	NOUN
brj-24353	58	20	section	section	NOUN
brj-24353	58	21	of	of	ADP
brj-24353	58	22	one	one	NUM
brj-24353	58	23	wood	wood	NOUN
brj-24353	58	24	sample	sample	NOUN
brj-24353	58	25	block	block	NOUN
brj-24353	58	26	,	,	PUNCT
brj-24353	58	27	and	and	CCONJ
brj-24353	58	28	the	the	DET
brj-24353	58	29	mean	mean	ADJ
brj-24353	58	30	spectral	spectral	ADJ
brj-24353	58	31	curve	curve	NOUN
brj-24353	58	32	was	be	AUX
brj-24353	58	33	saved	save	VERB
brj-24353	58	34	as	as	ADP
brj-24353	58	35	the	the	DET
brj-24353	58	36	final	final	ADJ
brj-24353	58	37	curve	curve	NOUN
brj-24353	58	38	.	.	PUNCT
brj-24353	59	1	this	this	PRON
brj-24353	59	2	was	be	AUX
brj-24353	59	3	done	do	VERB
brj-24353	59	4	to	to	PART
brj-24353	59	5	decrease	decrease	VERB
brj-24353	59	6	the	the	DET
brj-24353	59	7	within	within	ADP
brj-24353	59	8	-	-	PUNCT
brj-24353	59	9	class	class	NOUN
brj-24353	59	10	difference	difference	NOUN
brj-24353	59	11	of	of	ADP
brj-24353	59	12	spectral	spectral	ADJ
brj-24353	59	13	curves	curve	NOUN
brj-24353	59	14	for	for	ADP
brj-24353	59	15	each	each	DET
brj-24353	59	16	wood	wood	NOUN
brj-24353	59	17	species	specie	NOUN
brj-24353	59	18	to	to	ADP
brj-24353	59	19	some	some	DET
brj-24353	59	20	extent	extent	NOUN
brj-24353	59	21	.	.	PUNCT
brj-24353	60	1	every	every	DET
brj-24353	60	2	selected	select	VERB
brj-24353	60	3	wood	wood	NOUN
brj-24353	60	4	block	block	NOUN
brj-24353	60	5	was	be	AUX
brj-24353	60	6	used	use	VERB
brj-24353	60	7	in	in	ADP
brj-24353	60	8	spectral	spectral	ADJ
brj-24353	60	9	acquisition	acquisition	NOUN
brj-24353	60	10	for	for	ADP
brj-24353	60	11	both	both	CCONJ
brj-24353	60	12	specular	specular	ADJ
brj-24353	60	13	and	and	CCONJ
brj-24353	60	14	diffuse	diffuse	VERB
brj-24353	60	15	reflection	reflection	NOUN
brj-24353	60	16	spectral	spectral	ADJ
brj-24353	60	17	curves	curve	NOUN
brj-24353	60	18	to	to	PART
brj-24353	60	19	ensure	ensure	VERB
brj-24353	60	20	the	the	DET
brj-24353	60	21	subsequent	subsequent	ADJ
brj-24353	60	22	objective	objective	ADJ
brj-24353	60	23	comparisons	comparison	NOUN
brj-24353	60	24	.	.	PUNCT
brj-24353	61	1	table	table	NOUN
brj-24353	61	2	1	1	NUM
brj-24353	61	3	.	.	PUNCT
brj-24353	62	1	detailed	detailed	ADJ
brj-24353	62	2	information	information	NOUN
brj-24353	62	3	on	on	ADP
brj-24353	62	4	the	the	DET
brj-24353	62	5	wood	wood	NOUN
brj-24353	62	6	species	species	NOUN
brj-24353	62	7	samples	sample	VERB
brj-24353	62	8	number	number	NOUN
brj-24353	62	9	genus	genus	NOUN
brj-24353	62	10	species	species	NOUN
brj-24353	62	11	1	1	NUM
brj-24353	62	12	acer	acer	NOUN
brj-24353	62	13	davidii	davidii	NOUN
brj-24353	62	14	2	2	NUM
brj-24353	62	15	amygdalus	amygdalus	ADJ
brj-24353	62	16	davidiana	davidiana	PROPN
brj-24353	62	17	3	3	NUM
brj-24353	62	18	aucoumea	aucoumea	PROPN
brj-24353	62	19	klaineana	klaineana	VERB
brj-24353	62	20	4	4	NUM
brj-24353	62	21	betula	betula	ADJ
brj-24353	62	22	alnoides	alnoide	NOUN
brj-24353	62	23	5	5	NUM
brj-24353	62	24	betula	betula	ADJ
brj-24353	62	25	platyphylla	platyphylla	NOUN
brj-24353	62	26	6	6	NUM
brj-24353	62	27	calophyllum	calophyllum	PROPN
brj-24353	62	28	inophyllum	inophyllum	VERB
brj-24353	62	29	7	7	NUM
brj-24353	62	30	chamaecyparis	chamaecyparis	NOUN
brj-24353	62	31	nootkatensis	nootkatensis	NOUN
brj-24353	62	32	8	8	NUM
brj-24353	62	33	cinnamomum	cinnamomum	ADJ
brj-24353	62	34	camphora	camphora	NOUN
brj-24353	62	35	9	9	NUM
brj-24353	62	36	cyclobalanopsis	cyclobalanopsis	NOUN
brj-24353	62	37	glauca	glauca	NOUN
brj-24353	62	38	10	10	NUM
brj-24353	62	39	dipterocarpus	dipterocarpu	NOUN
brj-24353	62	40	alatus	alatus	NOUN
brj-24353	62	41	11	11	NUM
brj-24353	62	42	entandrophragma	entandrophragma	NOUN
brj-24353	62	43	candollei	candollei	VERB
brj-24353	62	44	12	12	NUM
brj-24353	62	45	fraxinus	fraxinus	NOUN
brj-24353	62	46	chinensis	chinensis	NOUN
brj-24353	62	47	13	13	NUM
brj-24353	62	48	fraxinus	fraxinus	NOUN
brj-24353	62	49	mandshurica	mandshurica	PROPN
brj-24353	62	50	14	14	NUM
brj-24353	62	51	guibourtia	guibourtia	NOUN
brj-24353	62	52	demeusei	demeusei	VERB
brj-24353	62	53	15	15	NUM
brj-24353	62	54	guibourtia	guibourtia	NOUN
brj-24353	62	55	ehie	ehie	VERB
brj-24353	62	56	16	16	NUM
brj-24353	62	57	intsia	intsia	NOUN
brj-24353	62	58	bijuga	bijuga	ADP
brj-24353	62	59	17	17	NUM
brj-24353	62	60	juglans	juglan	NOUN
brj-24353	62	61	mandshurica	mandshurica	VERB
brj-24353	62	62	18	18	NUM
brj-24353	62	63	juglans	juglan	NOUN
brj-24353	62	64	nigra	nigra	PROPN
brj-24353	62	65	19	19	NUM
brj-24353	62	66	larix	larix	NOUN
brj-24353	62	67	gmelinii	gmelinii	ADJ
brj-24353	62	68	20	20	NUM
brj-24353	62	69	magnolia	magnolia	NOUN
brj-24353	62	70	fordiana	fordiana	PROPN
brj-24353	62	71	21	21	NUM
brj-24353	62	72	millettia	millettia	NOUN
brj-24353	62	73	laurentii	laurentii	VERB
brj-24353	62	74	22	22	NUM
brj-24353	62	75	picea	picea	NOUN
brj-24353	62	76	asperata	asperata	NOUN
brj-24353	62	77	23	23	NUM
brj-24353	62	78	pinups	pinup	NOUN
brj-24353	62	79	radiata	radiata	ADJ
brj-24353	62	80	24	24	NUM
brj-24353	62	81	pinups	pinup	NOUN
brj-24353	62	82	koraiensis	koraiensis	NOUN
brj-24353	62	83	peer	peer	NOUN
brj-24353	62	84	-	-	PUNCT
brj-24353	62	85	reviewed	review	VERB
brj-24353	62	86	article	article	NOUN
brj-24353	62	87	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	62	88	wang	wang	PROPN
brj-24353	62	89	et	et	PROPN
brj-24353	62	90	al	al	PROPN
brj-24353	62	91	.	.	PROPN
brj-24353	63	1	(	(	PUNCT
brj-24353	63	2	2025	2025	NUM
brj-24353	63	3	)	)	PUNCT
brj-24353	63	4	.	.	PUNCT
brj-24353	64	1	“	"	PUNCT
brj-24353	64	2	wood	wood	NOUN
brj-24353	64	3	i	i	X
brj-24353	64	4	d	d	PROPN
brj-24353	64	5	via	via	ADP
brj-24353	64	6	.	.	PUNCT
brj-24353	65	1	s	s	PROPN
brj-24353	65	2	-	-	PUNCT
brj-24353	65	3	nir	nir	PROPN
brj-24353	65	4	&	&	CCONJ
brj-24353	65	5	dr	dr	PROPN
brj-24353	65	6	-	-	PUNCT
brj-24353	65	7	nir	nir	PROPN
brj-24353	65	8	,	,	PUNCT
brj-24353	65	9	”	"	PUNCT
brj-24353	65	10	bioresources	bioresource	NOUN
brj-24353	65	11	20(3	20(3	NOUN
brj-24353	65	12	)	)	PUNCT
brj-24353	65	13	,	,	PUNCT
brj-24353	65	14	6648	6648	NUM
brj-24353	65	15	-	-	SYM
brj-24353	65	16	6661	6661	NUM
brj-24353	65	17	.	.	PUNCT
brj-24353	66	1	6651	6651	NUM
brj-24353	66	2	25	25	NUM
brj-24353	66	3	pinups	pinup	NOUN
brj-24353	66	4	massoniana	massoniana	NOUN
brj-24353	66	5	26	26	NUM
brj-24353	66	6	pinups	pinup	NOUN
brj-24353	66	7	sylvestris	sylvestris	NOUN
brj-24353	66	8	27	27	NUM
brj-24353	66	9	platanus	platanus	NOUN
brj-24353	66	10	orientalis	orientali	NOUN
brj-24353	66	11	28	28	NUM
brj-24353	66	12	pometia	pometia	NOUN
brj-24353	66	13	pinnata	pinnata	NOUN
brj-24353	66	14	29	29	NUM
brj-24353	66	15	populus	populus	PROPN
brj-24353	66	16	alba	alba	NOUN
brj-24353	66	17	30	30	NUM
brj-24353	66	18	populus	populus	PROPN
brj-24353	66	19	cathayana	cathayana	ADJ
brj-24353	66	20	31	31	NUM
brj-24353	66	21	populus	populus	PROPN
brj-24353	66	22	tomentosa	tomentosa	PROPN
brj-24353	66	23	32	32	NUM
brj-24353	66	24	pouteria	pouteria	NOUN
brj-24353	66	25	speciosa	speciosa	NOUN
brj-24353	66	26	33	33	NUM
brj-24353	66	27	prunus	prunus	NOUN
brj-24353	66	28	avium	avium	NOUN
brj-24353	66	29	34	34	NUM
brj-24353	66	30	pseudotsuga	pseudotsuga	PROPN
brj-24353	66	31	menziesii	menziesii	NOUN
brj-24353	66	32	35	35	NUM
brj-24353	66	33	pterocarpus	pterocarpus	NOUN
brj-24353	66	34	soyauxii	soyauxii	NOUN
brj-24353	66	35	36	36	NUM
brj-24353	66	36	quercus	quercus	ADJ
brj-24353	66	37	mongolica	mongolica	NOUN
brj-24353	66	38	37	37	NUM
brj-24353	66	39	quercus	quercus	ADJ
brj-24353	66	40	acutissima	acutissima	ADJ
brj-24353	66	41	38	38	NUM
brj-24353	66	42	rhodamnia	rhodamnia	NOUN
brj-24353	66	43	dumetorum	dumetorum	NOUN
brj-24353	66	44	39	39	NUM
brj-24353	66	45	robinia	robinia	NOUN
brj-24353	66	46	pseudoacacia	pseudoacacia	NOUN
brj-24353	66	47	40	40	NUM
brj-24353	66	48	sailx	sailx	NOUN
brj-24353	66	49	matsudana	matsudana	VERB
brj-24353	66	50	41	41	NUM
brj-24353	66	51	shorea	shorea	NOUN
brj-24353	66	52	contorta	contorta	PROPN
brj-24353	66	53	42	42	NUM
brj-24353	66	54	shorea	shorea	NOUN
brj-24353	66	55	laevis	laevis	ADJ
brj-24353	66	56	43	43	NUM
brj-24353	66	57	sophora	sophora	NOUN
brj-24353	66	58	japonica	japonica	NOUN
brj-24353	66	59	44	44	NUM
brj-24353	66	60	swietenia	swietenia	NOUN
brj-24353	66	61	mahagoni	mahagoni	VERB
brj-24353	66	62	45	45	NUM
brj-24353	66	63	tectona	tectona	NOUN
brj-24353	66	64	grandis	grandis	NOUN
brj-24353	66	65	46	46	NUM
brj-24353	66	66	terminalia	terminalia	NOUN
brj-24353	66	67	cattapa	cattapa	VERB
brj-24353	66	68	47	47	NUM
brj-24353	66	69	tilia	tilia	PROPN
brj-24353	66	70	mandshurica	mandshurica	PROPN
brj-24353	66	71	48	48	NUM
brj-24353	66	72	toona	toona	PROPN
brj-24353	66	73	ciliata	ciliata	PROPN
brj-24353	66	74	49	49	NUM
brj-24353	66	75	ulmus	ulmus	PROPN
brj-24353	66	76	glabra	glabra	VERB
brj-24353	66	77	50	50	NUM
brj-24353	66	78	vernicia	vernicia	NOUN
brj-24353	66	79	fordii	fordii	NOUN
brj-24353	66	80	51	51	NUM
brj-24353	66	81	pterocarpus	pterocarpus	NOUN
brj-24353	66	82	antunesii	antunesii	VERB
brj-24353	66	83	52	52	NUM
brj-24353	66	84	pterocarpus	pterocarpus	NOUN
brj-24353	66	85	erinaceus	erinaceus	NOUN
brj-24353	66	86	53	53	NUM
brj-24353	66	87	pterocarpus	pterocarpus	NOUN
brj-24353	66	88	macrocarpus	macrocarpus	NOUN
brj-24353	66	89	54	54	NUM
brj-24353	66	90	pterocarpus	pterocarpus	NOUN
brj-24353	66	91	tinctorius	tinctorius	NUM
brj-24353	66	92	55	55	NUM
brj-24353	66	93	cryptomeria	cryptomeria	NOUN
brj-24353	66	94	fortune	fortune	NOUN
brj-24353	66	95	56	56	NUM
brj-24353	66	96	distemonanthus	distemonanthu	NOUN
brj-24353	66	97	benthaminanus	benthaminanus	NOUN
brj-24353	66	98	57	57	NUM
brj-24353	66	99	cylicodiscus	cylicodiscus	NOUN
brj-24353	66	100	gabunensis	gabunensis	NOUN
brj-24353	66	101	58	58	NUM
brj-24353	66	102	albizia	albizia	PROPN
brj-24353	66	103	kalkora	kalkora	PROPN
brj-24353	66	104	59	59	NUM
brj-24353	66	105	berlinia	berlinia	NOUN
brj-24353	66	106	confusa	confusa	PROPN
brj-24353	66	107	60	60	NUM
brj-24353	66	108	daniellia	daniellia	PROPN
brj-24353	66	109	oliveri	oliveri	ADJ
brj-24353	66	110	61	61	NUM
brj-24353	66	111	sabina	sabina	ADJ
brj-24353	66	112	chinensis	chinensis	NOUN
brj-24353	66	113	62	62	NUM
brj-24353	66	114	acer	acer	NOUN
brj-24353	66	115	pictum	pictum	NOUN
brj-24353	66	116	63	63	NUM
brj-24353	66	117	phellodendron	phellodendron	ADJ
brj-24353	66	118	amurense	amurense	NOUN
brj-24353	66	119	64	64	NUM
brj-24353	66	120	hovenia	hovenia	NOUN
brj-24353	66	121	dulcis	dulcis	PROPN
brj-24353	66	122	a	a	DET
brj-24353	66	123	flame	flame	PROPN
brj-24353	66	124	-	-	PUNCT
brj-24353	66	125	nir	nir	NOUN
brj-24353	66	126	mini	mini	NOUN
brj-24353	66	127	-	-	NOUN
brj-24353	66	128	spectrometer	spectrometer	NOUN
brj-24353	66	129	(	(	PUNCT
brj-24353	66	130	ocean	ocean	NOUN
brj-24353	66	131	optics	optics	PROPN
brj-24353	66	132	,	,	PUNCT
brj-24353	66	133	orlando	orlando	PROPN
brj-24353	66	134	,	,	PUNCT
brj-24353	66	135	fl	fl	PROPN
brj-24353	66	136	,	,	PUNCT
brj-24353	66	137	usa	usa	PROPN
brj-24353	66	138	)	)	PUNCT
brj-24353	66	139	,	,	PUNCT
brj-24353	66	140	which	which	PRON
brj-24353	66	141	offers	offer	VERB
brj-24353	66	142	advantages	advantage	NOUN
brj-24353	66	143	,	,	PUNCT
brj-24353	66	144	such	such	ADJ
brj-24353	66	145	as	as	ADP
brj-24353	66	146	portability	portability	NOUN
brj-24353	66	147	,	,	PUNCT
brj-24353	66	148	high	high	ADJ
brj-24353	66	149	accuracy	accuracy	NOUN
brj-24353	66	150	,	,	PUNCT
brj-24353	66	151	and	and	CCONJ
brj-24353	66	152	rapid	rapid	ADJ
brj-24353	66	153	acquisition	acquisition	NOUN
brj-24353	66	154	,	,	PUNCT
brj-24353	66	155	was	be	AUX
brj-24353	66	156	used	use	VERB
brj-24353	66	157	in	in	ADP
brj-24353	66	158	this	this	DET
brj-24353	66	159	study	study	NOUN
brj-24353	66	160	.	.	PUNCT
brj-24353	67	1	its	its	PRON
brj-24353	67	2	operating	operating	NOUN
brj-24353	67	3	range	range	NOUN
brj-24353	67	4	was	be	AUX
brj-24353	67	5	950	950	NUM
brj-24353	67	6	to	to	PART
brj-24353	67	7	1650	1650	NUM
brj-24353	67	8	nm	nm	NOUN
brj-24353	67	9	;	;	PUNCT
brj-24353	67	10	the	the	DET
brj-24353	67	11	nir	nir	NOUN
brj-24353	67	12	spectrum	spectrum	NOUN
brj-24353	67	13	within	within	ADP
brj-24353	67	14	this	this	DET
brj-24353	67	15	range	range	NOUN
brj-24353	67	16	provides	provide	VERB
brj-24353	67	17	greater	great	ADJ
brj-24353	67	18	stability	stability	NOUN
brj-24353	67	19	compared	compare	VERB
brj-24353	67	20	to	to	ADP
brj-24353	67	21	the	the	DET
brj-24353	67	22	visible	visible	ADJ
brj-24353	67	23	light	light	ADJ
brj-24353	67	24	spectra	spectra	NOUN
brj-24353	67	25	.	.	PUNCT
brj-24353	68	1	to	to	PART
brj-24353	68	2	ensure	ensure	VERB
brj-24353	68	3	spectral	spectral	ADJ
brj-24353	68	4	accuracy	accuracy	NOUN
brj-24353	68	5	,	,	PUNCT
brj-24353	68	6	both	both	CCONJ
brj-24353	68	7	the	the	DET
brj-24353	68	8	indoor	indoor	ADJ
brj-24353	68	9	temperature	temperature	NOUN
brj-24353	68	10	and	and	CCONJ
brj-24353	68	11	light	light	ADJ
brj-24353	68	12	conditions	condition	NOUN
brj-24353	68	13	were	be	AUX
brj-24353	68	14	stabilized	stabilize	VERB
brj-24353	68	15	during	during	ADP
brj-24353	68	16	spectrum	spectrum	NOUN
brj-24353	68	17	collection	collection	NOUN
brj-24353	68	18	.	.	PUNCT
brj-24353	69	1	the	the	DET
brj-24353	69	2	environment	environment	NOUN
brj-24353	69	3	for	for	ADP
brj-24353	69	4	spectrum	spectrum	NOUN
brj-24353	69	5	acquisition	acquisition	NOUN
brj-24353	69	6	in	in	ADP
brj-24353	69	7	this	this	DET
brj-24353	69	8	study	study	NOUN
brj-24353	69	9	was	be	AUX
brj-24353	69	10	maintained	maintain	VERB
brj-24353	69	11	at	at	ADP
brj-24353	69	12	25	25	NUM
brj-24353	69	13	℃	℃	PROPN
brj-24353	69	14	and	and	CCONJ
brj-24353	69	15	40	40	NUM
brj-24353	69	16	%	%	NOUN
brj-24353	69	17	relative	relative	ADJ
brj-24353	69	18	humidity	humidity	NOUN
brj-24353	69	19	.	.	PUNCT
brj-24353	70	1	the	the	DET
brj-24353	70	2	spectral	spectral	ADJ
brj-24353	70	3	data	data	PROPN
brj-24353	70	4	acquisition	acquisition	NOUN
brj-24353	70	5	platform	platform	NOUN
brj-24353	70	6	used	use	VERB
brj-24353	70	7	in	in	ADP
brj-24353	70	8	the	the	DET
brj-24353	70	9	experiment	experiment	NOUN
brj-24353	70	10	is	be	AUX
brj-24353	70	11	illustrated	illustrate	VERB
brj-24353	70	12	in	in	ADP
brj-24353	70	13	(	(	PUNCT
brj-24353	70	14	fig	fig	NOUN
brj-24353	70	15	.	.	NOUN
brj-24353	71	1	1	1	NUM
brj-24353	71	2	)	)	PUNCT
brj-24353	71	3	,	,	PUNCT
brj-24353	71	4	where	where	SCONJ
brj-24353	71	5	①	①	PROPN
brj-24353	71	6	is	be	AUX
brj-24353	71	7	the	the	DET
brj-24353	71	8	sample	sample	NOUN
brj-24353	71	9	under	under	ADP
brj-24353	71	10	test	test	NOUN
brj-24353	71	11	,	,	PUNCT
brj-24353	71	12	②	②	NUM
brj-24353	71	13	is	be	AUX
brj-24353	71	14	the	the	DET
brj-24353	71	15	spectral	spectral	ADJ
brj-24353	71	16	reflectance	reflectance	NOUN
brj-24353	71	17	acquisition	acquisition	NOUN
brj-24353	71	18	kit	kit	PROPN
brj-24353	71	19	,	,	PUNCT
brj-24353	71	20	③	③	PROPN
brj-24353	71	21	is	be	AUX
brj-24353	71	22	the	the	DET
brj-24353	71	23	cold	cold	ADJ
brj-24353	71	24	light	light	PROPN
brj-24353	71	25	source	source	NOUN
brj-24353	71	26	,	,	PUNCT
brj-24353	71	27	④	④	NUM
brj-24353	71	28	is	be	AUX
brj-24353	71	29	the	the	DET
brj-24353	71	30	computer	computer	NOUN
brj-24353	71	31	,	,	PUNCT
brj-24353	71	32	⑤	⑤	NUM
brj-24353	71	33	is	be	AUX
brj-24353	71	34	the	the	DET
brj-24353	71	35	flame	flame	NOUN
brj-24353	71	36	-	-	PUNCT
brj-24353	71	37	nir	nir	NOUN
brj-24353	71	38	spectrometer	spectrometer	NOUN
brj-24353	71	39	,	,	PUNCT
brj-24353	71	40	and	and	CCONJ
brj-24353	71	41	⑥	⑥	NUM
brj-24353	71	42	is	be	AUX
brj-24353	71	43	the	the	DET
brj-24353	71	44	calibration	calibration	NOUN
brj-24353	71	45	plate	plate	NOUN
brj-24353	71	46	.	.	PUNCT
brj-24353	72	1	the	the	DET
brj-24353	72	2	spectral	spectral	ADJ
brj-24353	72	3	reflectance	reflectance	NOUN
brj-24353	72	4	collection	collection	NOUN
brj-24353	72	5	process	process	NOUN
brj-24353	72	6	proceeded	proceed	VERB
brj-24353	72	7	as	as	SCONJ
brj-24353	72	8	follows	follow	VERB
brj-24353	72	9	.	.	PUNCT
brj-24353	73	1	first	first	ADV
brj-24353	73	2	,	,	PUNCT
brj-24353	73	3	the	the	DET
brj-24353	73	4	equipment	equipment	NOUN
brj-24353	73	5	and	and	CCONJ
brj-24353	73	6	light	light	ADJ
brj-24353	73	7	source	source	NOUN
brj-24353	73	8	were	be	AUX
brj-24353	73	9	powered	power	VERB
brj-24353	73	10	on	on	ADP
brj-24353	73	11	and	and	CCONJ
brj-24353	73	12	allowed	allow	VERB
brj-24353	73	13	to	to	PART
brj-24353	73	14	run	run	VERB
brj-24353	73	15	for	for	ADP
brj-24353	73	16	a	a	DET
brj-24353	73	17	period	period	NOUN
brj-24353	73	18	to	to	PART
brj-24353	73	19	ensure	ensure	VERB
brj-24353	73	20	peer	peer	NOUN
brj-24353	73	21	-	-	PUNCT
brj-24353	73	22	reviewed	review	VERB
brj-24353	73	23	article	article	NOUN
brj-24353	73	24	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	73	25	wang	wang	PROPN
brj-24353	73	26	et	et	PROPN
brj-24353	73	27	al	al	PROPN
brj-24353	73	28	.	.	PROPN
brj-24353	74	1	(	(	PUNCT
brj-24353	74	2	2025	2025	NUM
brj-24353	74	3	)	)	PUNCT
brj-24353	74	4	.	.	PUNCT
brj-24353	75	1	“	"	PUNCT
brj-24353	75	2	wood	wood	NOUN
brj-24353	75	3	i	i	X
brj-24353	75	4	d	d	PROPN
brj-24353	75	5	via	via	ADP
brj-24353	75	6	.	.	PUNCT
brj-24353	76	1	s	s	PROPN
brj-24353	76	2	-	-	PUNCT
brj-24353	76	3	nir	nir	PROPN
brj-24353	76	4	&	&	CCONJ
brj-24353	76	5	dr	dr	PROPN
brj-24353	76	6	-	-	PUNCT
brj-24353	76	7	nir	nir	PROPN
brj-24353	76	8	,	,	PUNCT
brj-24353	76	9	”	"	PUNCT
brj-24353	76	10	bioresources	bioresource	NOUN
brj-24353	76	11	20(3	20(3	NOUN
brj-24353	76	12	)	)	PUNCT
brj-24353	76	13	,	,	PUNCT
brj-24353	76	14	6648	6648	NUM
brj-24353	76	15	-	-	SYM
brj-24353	76	16	6661	6661	NUM
brj-24353	76	17	.	.	PUNCT
brj-24353	77	1	6652	6652	NUM
brj-24353	77	2	system	system	NOUN
brj-24353	77	3	stabilization	stabilization	NOUN
brj-24353	77	4	.	.	PUNCT
brj-24353	78	1	the	the	DET
brj-24353	78	2	integration	integration	NOUN
brj-24353	78	3	time	time	NOUN
brj-24353	78	4	was	be	AUX
brj-24353	78	5	set	set	VERB
brj-24353	78	6	to	to	ADP
brj-24353	78	7	auto	auto	NOUN
brj-24353	78	8	-	-	PUNCT
brj-24353	78	9	mode	mode	NOUN
brj-24353	78	10	,	,	PUNCT
brj-24353	78	11	and	and	CCONJ
brj-24353	78	12	calibration	calibration	NOUN
brj-24353	78	13	was	be	AUX
brj-24353	78	14	performed	perform	VERB
brj-24353	78	15	using	use	VERB
brj-24353	78	16	black	black	ADJ
brj-24353	78	17	and	and	CCONJ
brj-24353	78	18	white	white	ADJ
brj-24353	78	19	calibration	calibration	NOUN
brj-24353	78	20	plates	plate	NOUN
brj-24353	78	21	.	.	PUNCT
brj-24353	79	1	following	follow	VERB
brj-24353	79	2	calibration	calibration	NOUN
brj-24353	79	3	,	,	PUNCT
brj-24353	79	4	a	a	DET
brj-24353	79	5	wood	wood	NOUN
brj-24353	79	6	sample	sample	NOUN
brj-24353	79	7	was	be	AUX
brj-24353	79	8	placed	place	VERB
brj-24353	79	9	at	at	ADP
brj-24353	79	10	the	the	DET
brj-24353	79	11	designated	designate	VERB
brj-24353	79	12	position	position	NOUN
brj-24353	79	13	,	,	PUNCT
brj-24353	79	14	and	and	CCONJ
brj-24353	79	15	the	the	DET
brj-24353	79	16	spectral	spectral	ADJ
brj-24353	79	17	data	datum	NOUN
brj-24353	79	18	were	be	AUX
brj-24353	79	19	collected	collect	VERB
brj-24353	79	20	.	.	PUNCT
brj-24353	80	1	because	because	SCONJ
brj-24353	80	2	the	the	DET
brj-24353	80	3	spectral	spectral	ADJ
brj-24353	80	4	reflectance	reflectance	NOUN
brj-24353	80	5	of	of	ADP
brj-24353	80	6	the	the	DET
brj-24353	80	7	wood	wood	NOUN
brj-24353	80	8	sample	sample	NOUN
brj-24353	80	9	correlated	correlate	VERB
brj-24353	80	10	with	with	ADP
brj-24353	80	11	the	the	DET
brj-24353	80	12	location	location	NOUN
brj-24353	80	13	of	of	ADP
brj-24353	80	14	data	datum	NOUN
brj-24353	80	15	collection	collection	NOUN
brj-24353	80	16	,	,	PUNCT
brj-24353	80	17	slight	slight	ADJ
brj-24353	80	18	differences	difference	NOUN
brj-24353	80	19	in	in	ADP
brj-24353	80	20	spectral	spectral	ADJ
brj-24353	80	21	reflectance	reflectance	NOUN
brj-24353	80	22	were	be	AUX
brj-24353	80	23	evident	evident	ADJ
brj-24353	80	24	when	when	SCONJ
brj-24353	80	25	the	the	DET
brj-24353	80	26	fiber	fiber	NOUN
brj-24353	80	27	-	-	PUNCT
brj-24353	80	28	optic	optic	NOUN
brj-24353	80	29	probe	probe	NOUN
brj-24353	80	30	was	be	AUX
brj-24353	80	31	positioned	position	VERB
brj-24353	80	32	at	at	ADP
brj-24353	80	33	different	different	ADJ
brj-24353	80	34	points	point	NOUN
brj-24353	80	35	on	on	ADP
brj-24353	80	36	the	the	DET
brj-24353	80	37	wood	wood	NOUN
brj-24353	80	38	cross	cross	PROPN
brj-24353	80	39	section	section	NOUN
brj-24353	80	40	.	.	PUNCT
brj-24353	81	1	consequently	consequently	ADV
brj-24353	81	2	,	,	PUNCT
brj-24353	81	3	during	during	ADP
brj-24353	81	4	the	the	DET
brj-24353	81	5	spectral	spectral	ADJ
brj-24353	81	6	acquisition	acquisition	NOUN
brj-24353	81	7	process	process	NOUN
brj-24353	81	8	,	,	PUNCT
brj-24353	81	9	spectral	spectral	ADJ
brj-24353	81	10	data	datum	NOUN
brj-24353	81	11	were	be	AUX
brj-24353	81	12	collected	collect	VERB
brj-24353	81	13	from	from	ADP
brj-24353	81	14	five	five	NUM
brj-24353	81	15	different	different	ADJ
brj-24353	81	16	positions	position	NOUN
brj-24353	81	17	on	on	ADP
brj-24353	81	18	the	the	DET
brj-24353	81	19	wood	wood	NOUN
brj-24353	81	20	sample	sample	NOUN
brj-24353	81	21	and	and	CCONJ
brj-24353	81	22	the	the	DET
brj-24353	81	23	mean	mean	ADJ
brj-24353	81	24	spectral	spectral	ADJ
brj-24353	81	25	curve	curve	NOUN
brj-24353	81	26	was	be	AUX
brj-24353	81	27	saved	save	VERB
brj-24353	81	28	as	as	ADP
brj-24353	81	29	the	the	DET
brj-24353	81	30	final	final	ADJ
brj-24353	81	31	curve	curve	NOUN
brj-24353	81	32	to	to	PART
brj-24353	81	33	decrease	decrease	VERB
brj-24353	81	34	the	the	DET
brj-24353	81	35	withinclass	withinclass	NOUN
brj-24353	81	36	difference	difference	NOUN
brj-24353	81	37	of	of	ADP
brj-24353	81	38	spectral	spectral	ADJ
brj-24353	81	39	curves	curve	NOUN
brj-24353	81	40	for	for	ADP
brj-24353	81	41	each	each	DET
brj-24353	81	42	wood	wood	NOUN
brj-24353	81	43	species	specie	NOUN
brj-24353	81	44	to	to	ADP
brj-24353	81	45	some	some	DET
brj-24353	81	46	extent	extent	NOUN
brj-24353	81	47	.	.	PUNCT
brj-24353	82	1	additionally	additionally	ADV
brj-24353	82	2	,	,	PUNCT
brj-24353	82	3	calibration	calibration	NOUN
brj-24353	82	4	was	be	AUX
brj-24353	82	5	performed	perform	VERB
brj-24353	82	6	for	for	ADP
brj-24353	82	7	every	every	DET
brj-24353	82	8	20	20	NUM
brj-24353	82	9	samples	sample	NOUN
brj-24353	82	10	to	to	PART
brj-24353	82	11	ensure	ensure	VERB
brj-24353	82	12	the	the	DET
brj-24353	82	13	accuracy	accuracy	NOUN
brj-24353	82	14	of	of	ADP
brj-24353	82	15	the	the	DET
brj-24353	82	16	spectral	spectral	ADJ
brj-24353	82	17	data	data	PROPN
brj-24353	82	18	.	.	PUNCT
brj-24353	83	1	fig	fig	NOUN
brj-24353	83	2	.	.	PUNCT
brj-24353	84	1	1	1	NUM
brj-24353	84	2	.	.	X
brj-24353	84	3	near	near	ADV
brj-24353	84	4	-	-	PUNCT
brj-24353	84	5	infrared	infrared	ADJ
brj-24353	84	6	spectral	spectral	ADJ
brj-24353	84	7	data	data	PROPN
brj-24353	84	8	acquisition	acquisition	NOUN
brj-24353	84	9	platform	platform	NOUN
brj-24353	84	10	for	for	ADP
brj-24353	84	11	the	the	DET
brj-24353	84	12	wood	wood	NOUN
brj-24353	84	13	samples	sample	NOUN
brj-24353	84	14	a	a	DET
brj-24353	84	15	b	b	NOUN
brj-24353	84	16	fig	fig	NOUN
brj-24353	84	17	.	.	PUNCT
brj-24353	85	1	2	2	X
brj-24353	85	2	.	.	X
brj-24353	85	3	spectral	spectral	ADJ
brj-24353	85	4	reflectance	reflectance	NOUN
brj-24353	85	5	acquisition	acquisition	NOUN
brj-24353	85	6	kit	kit	PROPN
brj-24353	85	7	:	:	PUNCT
brj-24353	85	8	a.	a.	NOUN
brj-24353	85	9	front	front	ADJ
brj-24353	85	10	view	view	NOUN
brj-24353	85	11	of	of	ADP
brj-24353	85	12	the	the	DET
brj-24353	85	13	kit	kit	NOUN
brj-24353	85	14	;	;	PUNCT
brj-24353	85	15	b.	b.	PROPN
brj-24353	85	16	back	back	ADJ
brj-24353	85	17	view	view	NOUN
brj-24353	85	18	of	of	ADP
brj-24353	85	19	the	the	DET
brj-24353	85	20	kit	kit	NOUN
brj-24353	85	21	in	in	ADP
brj-24353	85	22	the	the	DET
brj-24353	85	23	process	process	NOUN
brj-24353	85	24	of	of	ADP
brj-24353	85	25	collecting	collect	VERB
brj-24353	85	26	spectral	spectral	ADJ
brj-24353	85	27	data	datum	NOUN
brj-24353	85	28	,	,	PUNCT
brj-24353	85	29	the	the	DET
brj-24353	85	30	specular	specular	ADJ
brj-24353	85	31	reflectance	reflectance	NOUN
brj-24353	85	32	and	and	CCONJ
brj-24353	85	33	diffuse	diffuse	VERB
brj-24353	85	34	reflectance	reflectance	NOUN
brj-24353	85	35	spectra	spectra	NOUN
brj-24353	85	36	of	of	ADP
brj-24353	85	37	the	the	DET
brj-24353	85	38	wood	wood	NOUN
brj-24353	85	39	cross	cross	PROPN
brj-24353	85	40	section	section	NOUN
brj-24353	85	41	were	be	AUX
brj-24353	85	42	collected	collect	VERB
brj-24353	85	43	separately	separately	ADV
brj-24353	85	44	,	,	PUNCT
brj-24353	85	45	and	and	CCONJ
brj-24353	85	46	a	a	DET
brj-24353	85	47	spectral	spectral	ADJ
brj-24353	85	48	reflectance	reflectance	NOUN
brj-24353	85	49	acquisition	acquisition	NOUN
brj-24353	85	50	kit	kit	NOUN
brj-24353	85	51	from	from	ADP
brj-24353	85	52	ocean	ocean	NOUN
brj-24353	85	53	optics	optic	NOUN
brj-24353	85	54	was	be	AUX
brj-24353	85	55	assembled	assemble	VERB
brj-24353	85	56	,	,	PUNCT
brj-24353	85	57	as	as	SCONJ
brj-24353	85	58	illustrated	illustrate	VERB
brj-24353	85	59	in	in	ADP
brj-24353	85	60	(	(	PUNCT
brj-24353	85	61	fig	fig	NOUN
brj-24353	85	62	.	.	PUNCT
brj-24353	85	63	2	2	NUM
brj-24353	85	64	)	)	PUNCT
brj-24353	85	65	.	.	PUNCT
brj-24353	86	1	the	the	DET
brj-24353	86	2	kit	kit	NOUN
brj-24353	86	3	comprised	comprise	VERB
brj-24353	86	4	a	a	DET
brj-24353	86	5	fixed	fix	VERB
brj-24353	86	6	stand	stand	NOUN
brj-24353	86	7	with	with	ADP
brj-24353	86	8	two	two	NUM
brj-24353	86	9	openings	opening	NOUN
brj-24353	86	10	facing	face	VERB
brj-24353	86	11	upwards	upwards	ADV
brj-24353	86	12	,	,	PUNCT
brj-24353	86	13	marked	mark	VERB
brj-24353	86	14	as	as	ADP
brj-24353	86	15	①	①	NUM
brj-24353	86	16	and	and	CCONJ
brj-24353	86	17	②	②	NUM
brj-24353	86	18	in	in	ADP
brj-24353	86	19	(	(	PUNCT
brj-24353	86	20	fig	fig	NOUN
brj-24353	86	21	.	.	PUNCT
brj-24353	87	1	2a	2a	NUM
brj-24353	87	2	and	and	CCONJ
brj-24353	87	3	fig	fig	NOUN
brj-24353	87	4	.	.	PUNCT
brj-24353	88	1	3a	3a	NUM
brj-24353	88	2	)	)	PUNCT
brj-24353	88	3	,	,	PUNCT
brj-24353	88	4	which	which	PRON
brj-24353	88	5	were	be	AUX
brj-24353	88	6	internally	internally	ADV
brj-24353	88	7	connected	connect	VERB
brj-24353	88	8	.	.	PUNCT
brj-24353	89	1	the	the	DET
brj-24353	89	2	back	back	NOUN
brj-24353	89	3	of	of	ADP
brj-24353	89	4	the	the	DET
brj-24353	89	5	kit	kit	NOUN
brj-24353	89	6	had	have	VERB
brj-24353	89	7	one	one	NUM
brj-24353	89	8	additional	additional	ADJ
brj-24353	89	9	opening	opening	NOUN
brj-24353	89	10	,	,	PUNCT
brj-24353	89	11	as	as	SCONJ
brj-24353	89	12	illustrated	illustrate	VERB
brj-24353	89	13	in	in	ADP
brj-24353	89	14	(	(	PUNCT
brj-24353	89	15	fig	fig	NOUN
brj-24353	89	16	.	.	PUNCT
brj-24353	89	17	2b	2b	NUM
brj-24353	89	18	and	and	CCONJ
brj-24353	89	19	fig	fig	NOUN
brj-24353	89	20	.	.	PUNCT
brj-24353	90	1	3a	3a	NUM
brj-24353	90	2	)	)	PUNCT
brj-24353	90	3	.	.	PUNCT
brj-24353	91	1	when	when	SCONJ
brj-24353	91	2	inserting	insert	VERB
brj-24353	91	3	the	the	DET
brj-24353	91	4	optical	optical	ADJ
brj-24353	91	5	fiber	fiber	NOUN
brj-24353	91	6	into	into	ADP
brj-24353	91	7	①	①	PROPN
brj-24353	91	8	(	(	PUNCT
brj-24353	91	9	as	as	SCONJ
brj-24353	91	10	shown	show	VERB
brj-24353	91	11	in	in	ADP
brj-24353	91	12	(	(	PUNCT
brj-24353	91	13	fig	fig	NOUN
brj-24353	91	14	.	.	PUNCT
brj-24353	92	1	3a	3a	NUM
brj-24353	92	2	and	and	CCONJ
brj-24353	92	3	fig	fig	NOUN
brj-24353	92	4	.	.	PUNCT
brj-24353	93	1	3b	3b	NUM
brj-24353	93	2	)	)	PUNCT
brj-24353	93	3	)	)	PUNCT
brj-24353	94	1	,	,	PUNCT
brj-24353	94	2	the	the	DET
brj-24353	94	3	optical	optical	ADJ
brj-24353	94	4	fiber	fiber	NOUN
brj-24353	94	5	probe	probe	NOUN
brj-24353	94	6	could	could	AUX
brj-24353	94	7	vertically	vertically	ADV
brj-24353	94	8	illuminate	illuminate	VERB
brj-24353	94	9	the	the	DET
brj-24353	94	10	surface	surface	NOUN
brj-24353	94	11	of	of	ADP
brj-24353	94	12	the	the	DET
brj-24353	94	13	wood	wood	NOUN
brj-24353	94	14	,	,	PUNCT
brj-24353	94	15	enabling	enable	VERB
brj-24353	94	16	the	the	DET
brj-24353	94	17	collection	collection	NOUN
brj-24353	94	18	of	of	ADP
brj-24353	94	19	the	the	DET
brj-24353	94	20	specular	specular	ADJ
brj-24353	94	21	reflectance	reflectance	NOUN
brj-24353	94	22	spectrum	spectrum	NOUN
brj-24353	94	23	from	from	ADP
brj-24353	94	24	the	the	DET
brj-24353	94	25	cross	cross	NOUN
brj-24353	94	26	section	section	NOUN
brj-24353	94	27	of	of	ADP
brj-24353	94	28	the	the	DET
brj-24353	94	29	sample	sample	NOUN
brj-24353	94	30	.	.	PUNCT
brj-24353	95	1	by	by	ADP
brj-24353	95	2	inserting	insert	VERB
brj-24353	95	3	the	the	DET
brj-24353	95	4	optical	optical	ADJ
brj-24353	95	5	fiber	fiber	NOUN
brj-24353	95	6	into	into	ADP
brj-24353	95	7	②	②	NUM
brj-24353	95	8	(	(	PUNCT
brj-24353	95	9	as	as	SCONJ
brj-24353	95	10	shown	show	VERB
brj-24353	95	11	in	in	ADP
brj-24353	95	12	(	(	PUNCT
brj-24353	95	13	fig	fig	NOUN
brj-24353	95	14	.	.	PUNCT
brj-24353	95	15	3a	3a	NUM
brj-24353	95	16	and	and	CCONJ
brj-24353	95	17	fig	fig	NOUN
brj-24353	95	18	.	.	PUNCT
brj-24353	95	19	3c	3c	NUM
brj-24353	95	20	)	)	PUNCT
brj-24353	95	21	)	)	PUNCT
brj-24353	95	22	,	,	PUNCT
brj-24353	95	23	the	the	DET
brj-24353	95	24	optical	optical	ADJ
brj-24353	95	25	fiber	fiber	NOUN
brj-24353	95	26	probe	probe	NOUN
brj-24353	95	27	could	could	AUX
brj-24353	95	28	be	be	AUX
brj-24353	95	29	tilted	tilt	VERB
brj-24353	95	30	at	at	ADP
brj-24353	95	31	a	a	DET
brj-24353	95	32	45	45	NUM
brj-24353	95	33	°	°	PROPN
brj-24353	95	34	angle	angle	NOUN
brj-24353	95	35	to	to	PART
brj-24353	95	36	irradiate	irradiate	VERB
brj-24353	95	37	the	the	DET
brj-24353	95	38	wood	wood	NOUN
brj-24353	95	39	’s	’s	PART
brj-24353	95	40	surface	surface	NOUN
brj-24353	95	41	,	,	PUNCT
brj-24353	95	42	allowing	allow	VERB
brj-24353	95	43	for	for	ADP
brj-24353	95	44	the	the	DET
brj-24353	95	45	capture	capture	NOUN
brj-24353	95	46	of	of	ADP
brj-24353	95	47	the	the	DET
brj-24353	95	48	diffuse	diffuse	NOUN
brj-24353	95	49	reflectance	reflectance	NOUN
brj-24353	95	50	spectrum	spectrum	NOUN
brj-24353	95	51	from	from	ADP
brj-24353	95	52	the	the	DET
brj-24353	95	53	cross	cross	NOUN
brj-24353	95	54	section	section	NOUN
brj-24353	95	55	of	of	ADP
brj-24353	95	56	the	the	DET
brj-24353	95	57	sample	sample	NOUN
brj-24353	95	58	.	.	PUNCT
brj-24353	96	1	as	as	SCONJ
brj-24353	96	2	illustrated	illustrate	VERB
brj-24353	96	3	in	in	ADP
brj-24353	96	4	(	(	PUNCT
brj-24353	96	5	fig	fig	NOUN
brj-24353	96	6	.	.	PUNCT
brj-24353	97	1	3b	3b	NOUN
brj-24353	97	2	and	and	CCONJ
brj-24353	97	3	fig	fig	NOUN
brj-24353	97	4	.	.	PUNCT
brj-24353	98	1	3c	3c	NUM
brj-24353	98	2	)	)	PUNCT
brj-24353	98	3	,	,	PUNCT
brj-24353	98	4	the	the	DET
brj-24353	98	5	specular	specular	ADJ
brj-24353	98	6	and	and	CCONJ
brj-24353	98	7	diffuse	diffuse	VERB
brj-24353	98	8	reflectance	reflectance	NOUN
brj-24353	98	9	rays	ray	NOUN
brj-24353	98	10	returned	return	VERB
brj-24353	98	11	along	along	ADP
brj-24353	98	12	the	the	DET
brj-24353	98	13	same	same	ADJ
brj-24353	98	14	way	way	NOUN
brj-24353	98	15	that	that	PRON
brj-24353	98	16	the	the	DET
brj-24353	98	17	incident	incident	NOUN
brj-24353	98	18	ray	ray	NOUN
brj-24353	98	19	has	have	AUX
brj-24353	98	20	just	just	ADV
brj-24353	98	21	come	come	VERB
brj-24353	98	22	along	along	ADV
brj-24353	98	23	,	,	PUNCT
brj-24353	98	24	respectively	respectively	ADV
brj-24353	98	25	.	.	PUNCT
brj-24353	99	1	peer	peer	NOUN
brj-24353	99	2	-	-	PUNCT
brj-24353	99	3	reviewed	review	VERB
brj-24353	99	4	article	article	NOUN
brj-24353	99	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	99	6	wang	wang	PROPN
brj-24353	99	7	et	et	PROPN
brj-24353	99	8	al	al	PROPN
brj-24353	99	9	.	.	PROPN
brj-24353	100	1	(	(	PUNCT
brj-24353	100	2	2025	2025	NUM
brj-24353	100	3	)	)	PUNCT
brj-24353	100	4	.	.	PUNCT
brj-24353	101	1	“	"	PUNCT
brj-24353	101	2	wood	wood	NOUN
brj-24353	101	3	i	i	X
brj-24353	101	4	d	d	PROPN
brj-24353	101	5	via	via	ADP
brj-24353	101	6	.	.	PUNCT
brj-24353	102	1	s	s	PROPN
brj-24353	102	2	-	-	PUNCT
brj-24353	102	3	nir	nir	PROPN
brj-24353	102	4	&	&	CCONJ
brj-24353	102	5	dr	dr	PROPN
brj-24353	102	6	-	-	PUNCT
brj-24353	102	7	nir	nir	PROPN
brj-24353	102	8	,	,	PUNCT
brj-24353	102	9	”	"	PUNCT
brj-24353	102	10	bioresources	bioresource	NOUN
brj-24353	102	11	20(3	20(3	NOUN
brj-24353	102	12	)	)	PUNCT
brj-24353	102	13	,	,	PUNCT
brj-24353	102	14	6648	6648	NUM
brj-24353	102	15	-	-	SYM
brj-24353	102	16	6661	6661	NUM
brj-24353	102	17	.	.	PUNCT
brj-24353	103	1	6653	6653	NUM
brj-24353	103	2	a	a	DET
brj-24353	103	3	b	b	PROPN
brj-24353	103	4	c	c	X
brj-24353	103	5	fig	fig	NOUN
brj-24353	103	6	.	.	PUNCT
brj-24353	104	1	3	3	X
brj-24353	104	2	.	.	X
brj-24353	104	3	specular	specular	ADJ
brj-24353	104	4	and	and	CCONJ
brj-24353	104	5	diffuse	diffuse	VERB
brj-24353	104	6	reflectance	reflectance	NOUN
brj-24353	104	7	spectral	spectral	ADJ
brj-24353	104	8	acquisition	acquisition	NOUN
brj-24353	104	9	:	:	PUNCT
brj-24353	104	10	a.	a.	NOUN
brj-24353	104	11	side	side	NOUN
brj-24353	104	12	view	view	NOUN
brj-24353	104	13	of	of	ADP
brj-24353	104	14	the	the	DET
brj-24353	104	15	kit	kit	NOUN
brj-24353	104	16	;	;	PUNCT
brj-24353	104	17	b.	b.	PROPN
brj-24353	104	18	specular	specular	ADJ
brj-24353	104	19	reflectance	reflectance	NOUN
brj-24353	104	20	optical	optical	ADJ
brj-24353	104	21	route	route	NOUN
brj-24353	104	22	;	;	PUNCT
brj-24353	104	23	c.	c.	NOUN
brj-24353	104	24	diffuse	diffuse	PROPN
brj-24353	104	25	reflectance	reflectance	NOUN
brj-24353	104	26	optical	optical	ADJ
brj-24353	104	27	route	route	NOUN
brj-24353	104	28	basic	basic	ADJ
brj-24353	104	29	process	process	NOUN
brj-24353	104	30	the	the	DET
brj-24353	104	31	basic	basic	ADJ
brj-24353	104	32	process	process	NOUN
brj-24353	104	33	used	use	VERB
brj-24353	104	34	in	in	ADP
brj-24353	104	35	this	this	DET
brj-24353	104	36	study	study	NOUN
brj-24353	104	37	is	be	AUX
brj-24353	104	38	illustrated	illustrate	VERB
brj-24353	104	39	in	in	ADP
brj-24353	104	40	fig	fig	NOUN
brj-24353	104	41	.	.	PUNCT
brj-24353	105	1	4	4	X
brj-24353	105	2	.	.	X
brj-24353	105	3	first	first	ADV
brj-24353	105	4	,	,	PUNCT
brj-24353	105	5	the	the	DET
brj-24353	105	6	specular	specular	ADJ
brj-24353	105	7	and	and	CCONJ
brj-24353	105	8	diffuse	diffuse	VERB
brj-24353	105	9	reflectance	reflectance	NOUN
brj-24353	105	10	spectra	spectra	NOUN
brj-24353	105	11	for	for	ADP
brj-24353	105	12	the	the	DET
brj-24353	105	13	wood	wood	NOUN
brj-24353	105	14	samples	sample	NOUN
brj-24353	105	15	listed	list	VERB
brj-24353	105	16	in	in	ADP
brj-24353	105	17	table	table	NOUN
brj-24353	105	18	1	1	NUM
brj-24353	105	19	were	be	AUX
brj-24353	105	20	collected	collect	VERB
brj-24353	105	21	,	,	PUNCT
brj-24353	105	22	and	and	CCONJ
brj-24353	105	23	datasets	dataset	NOUN
brj-24353	105	24	were	be	AUX
brj-24353	105	25	constructed	construct	VERB
brj-24353	105	26	for	for	ADP
brj-24353	105	27	the	the	DET
brj-24353	105	28	wood	wood	NOUN
brj-24353	105	29	sample	sample	PROPN
brj-24353	105	30	cross	cross	PROPN
brj-24353	105	31	sections	section	NOUN
brj-24353	105	32	.	.	PUNCT
brj-24353	106	1	fig	fig	NOUN
brj-24353	106	2	.	.	PUNCT
brj-24353	107	1	4	4	X
brj-24353	107	2	.	.	X
brj-24353	107	3	flowchart	flowchart	NOUN
brj-24353	107	4	of	of	ADP
brj-24353	107	5	the	the	DET
brj-24353	107	6	basic	basic	ADJ
brj-24353	107	7	process	process	NOUN
brj-24353	107	8	used	use	VERB
brj-24353	107	9	in	in	ADP
brj-24353	107	10	this	this	DET
brj-24353	107	11	study	study	NOUN
brj-24353	107	12	spectral	spectral	ADJ
brj-24353	107	13	preprocessing	preprocessing	NOUN
brj-24353	107	14	was	be	AUX
brj-24353	107	15	conducted	conduct	VERB
brj-24353	107	16	first	first	ADV
brj-24353	107	17	,	,	PUNCT
brj-24353	107	18	including	include	VERB
brj-24353	107	19	standard	standard	ADJ
brj-24353	107	20	normal	normal	ADJ
brj-24353	107	21	variate	variate	NOUN
brj-24353	107	22	correction	correction	NOUN
brj-24353	107	23	and	and	CCONJ
brj-24353	107	24	normalization	normalization	NOUN
brj-24353	107	25	of	of	ADP
brj-24353	107	26	the	the	DET
brj-24353	107	27	spectra	spectra	NOUN
brj-24353	107	28	using	use	VERB
brj-24353	107	29	the	the	DET
brj-24353	107	30	min	min	ADJ
brj-24353	107	31	-	-	ADJ
brj-24353	107	32	max	max	ADJ
brj-24353	107	33	scaling	scaling	NOUN
brj-24353	107	34	method	method	NOUN
brj-24353	107	35	.	.	PUNCT
brj-24353	108	1	to	to	PART
brj-24353	108	2	prevent	prevent	VERB
brj-24353	108	3	overfitting	overfitting	NOUN
brj-24353	108	4	,	,	PUNCT
brj-24353	108	5	the	the	DET
brj-24353	108	6	dataset	dataset	NOUN
brj-24353	108	7	was	be	AUX
brj-24353	108	8	randomly	randomly	ADV
brj-24353	108	9	divided	divide	VERB
brj-24353	108	10	into	into	ADP
brj-24353	108	11	training	training	NOUN
brj-24353	108	12	and	and	CCONJ
brj-24353	108	13	test	test	NOUN
brj-24353	108	14	datasets	dataset	NOUN
brj-24353	108	15	in	in	ADP
brj-24353	108	16	a	a	DET
brj-24353	108	17	7:3	7:3	NUM
brj-24353	108	18	ratio	ratio	NOUN
brj-24353	108	19	.	.	PUNCT
brj-24353	109	1	peer	peer	NOUN
brj-24353	109	2	-	-	PUNCT
brj-24353	109	3	reviewed	review	VERB
brj-24353	109	4	article	article	NOUN
brj-24353	109	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	109	6	wang	wang	PROPN
brj-24353	109	7	et	et	PROPN
brj-24353	109	8	al	al	PROPN
brj-24353	109	9	.	.	PROPN
brj-24353	110	1	(	(	PUNCT
brj-24353	110	2	2025	2025	NUM
brj-24353	110	3	)	)	PUNCT
brj-24353	110	4	.	.	PUNCT
brj-24353	111	1	“	"	PUNCT
brj-24353	111	2	wood	wood	NOUN
brj-24353	111	3	i	i	X
brj-24353	111	4	d	d	PROPN
brj-24353	111	5	via	via	ADP
brj-24353	111	6	.	.	PUNCT
brj-24353	112	1	s	s	PROPN
brj-24353	112	2	-	-	PUNCT
brj-24353	112	3	nir	nir	PROPN
brj-24353	112	4	&	&	CCONJ
brj-24353	112	5	dr	dr	PROPN
brj-24353	112	6	-	-	PUNCT
brj-24353	112	7	nir	nir	PROPN
brj-24353	112	8	,	,	PUNCT
brj-24353	112	9	”	"	PUNCT
brj-24353	112	10	bioresources	bioresource	NOUN
brj-24353	112	11	20(3	20(3	NOUN
brj-24353	112	12	)	)	PUNCT
brj-24353	112	13	,	,	PUNCT
brj-24353	112	14	6648	6648	NUM
brj-24353	112	15	-	-	SYM
brj-24353	112	16	6661	6661	NUM
brj-24353	112	17	.	.	PUNCT
brj-24353	113	1	6654	6654	NUM
brj-24353	113	2	each	each	DET
brj-24353	113	3	wood	wood	NOUN
brj-24353	113	4	species	specie	NOUN
brj-24353	113	5	in	in	ADP
brj-24353	113	6	the	the	DET
brj-24353	113	7	training	training	NOUN
brj-24353	113	8	dataset	dataset	NOUN
brj-24353	113	9	contained	contain	VERB
brj-24353	113	10	35	35	NUM
brj-24353	113	11	samples	sample	NOUN
brj-24353	113	12	,	,	PUNCT
brj-24353	113	13	resulting	result	VERB
brj-24353	113	14	in	in	ADP
brj-24353	113	15	a	a	DET
brj-24353	113	16	training	training	NOUN
brj-24353	113	17	dataset	dataset	NOUN
brj-24353	113	18	size	size	NOUN
brj-24353	113	19	of	of	ADP
brj-24353	113	20	128	128	NUM
brj-24353	113	21	×	×	NOUN
brj-24353	113	22	2240	2240	NUM
brj-24353	113	23	,	,	PUNCT
brj-24353	113	24	and	and	CCONJ
brj-24353	113	25	each	each	DET
brj-24353	113	26	wood	wood	NOUN
brj-24353	113	27	species	specie	NOUN
brj-24353	113	28	in	in	ADP
brj-24353	113	29	the	the	DET
brj-24353	113	30	test	test	NOUN
brj-24353	113	31	dataset	dataset	NOUN
brj-24353	113	32	contained	contain	VERB
brj-24353	113	33	15	15	NUM
brj-24353	113	34	samples	sample	NOUN
brj-24353	113	35	,	,	PUNCT
brj-24353	113	36	resulting	result	VERB
brj-24353	113	37	in	in	ADP
brj-24353	113	38	a	a	DET
brj-24353	113	39	test	test	NOUN
brj-24353	113	40	dataset	dataset	VERB
brj-24353	113	41	size	size	NOUN
brj-24353	113	42	of	of	ADP
brj-24353	113	43	128	128	NUM
brj-24353	113	44	×	×	NOUN
brj-24353	113	45	960	960	NUM
brj-24353	113	46	.	.	PUNCT
brj-24353	114	1	the	the	DET
brj-24353	114	2	nir	nir	ADJ
brj-24353	114	3	spectral	spectral	ADJ
brj-24353	114	4	vectors	vector	NOUN
brj-24353	114	5	were	be	AUX
brj-24353	114	6	128	128	NUM
brj-24353	114	7	-	-	PUNCT
brj-24353	114	8	dimensional	dimensional	ADJ
brj-24353	114	9	(	(	PUNCT
brj-24353	114	10	128d	128d	NOUN
brj-24353	114	11	)	)	PUNCT
brj-24353	114	12	.	.	PUNCT
brj-24353	115	1	the	the	DET
brj-24353	115	2	svm	svm	PROPN
brj-24353	115	3	,	,	PUNCT
brj-24353	115	4	knn	knn	PROPN
brj-24353	115	5	,	,	PUNCT
brj-24353	115	6	cnn	cnn	PROPN
brj-24353	115	7	,	,	PUNCT
brj-24353	115	8	decision	decision	NOUN
brj-24353	115	9	tree	tree	NOUN
brj-24353	115	10	(	(	PUNCT
brj-24353	115	11	dt	dt	NOUN
brj-24353	115	12	)	)	PUNCT
brj-24353	115	13	,	,	PUNCT
brj-24353	115	14	and	and	CCONJ
brj-24353	115	15	nearest	near	ADJ
brj-24353	115	16	class	class	NOUN
brj-24353	115	17	mean	mean	NOUN
brj-24353	115	18	(	(	PUNCT
brj-24353	115	19	ncm	ncm	PROPN
brj-24353	115	20	)	)	PUNCT
brj-24353	115	21	classifiers	classifier	NOUN
brj-24353	115	22	were	be	AUX
brj-24353	115	23	used	use	VERB
brj-24353	115	24	to	to	PART
brj-24353	115	25	train	train	VERB
brj-24353	115	26	and	and	CCONJ
brj-24353	115	27	test	test	VERB
brj-24353	115	28	the	the	DET
brj-24353	115	29	specular	specular	ADJ
brj-24353	115	30	and	and	CCONJ
brj-24353	115	31	diffuse	diffuse	PROPN
brj-24353	115	32	reflection	reflection	NOUN
brj-24353	115	33	spectra	spectra	NOUN
brj-24353	115	34	.	.	PUNCT
brj-24353	116	1	next	next	ADV
brj-24353	116	2	,	,	PUNCT
brj-24353	116	3	a	a	DET
brj-24353	116	4	comparative	comparative	ADJ
brj-24353	116	5	analysis	analysis	NOUN
brj-24353	116	6	was	be	AUX
brj-24353	116	7	conducted	conduct	VERB
brj-24353	116	8	to	to	PART
brj-24353	116	9	examine	examine	VERB
brj-24353	116	10	the	the	DET
brj-24353	116	11	differences	difference	NOUN
brj-24353	116	12	in	in	ADP
brj-24353	116	13	classification	classification	NOUN
brj-24353	116	14	accuracy	accuracy	NOUN
brj-24353	116	15	between	between	ADP
brj-24353	116	16	the	the	DET
brj-24353	116	17	specular	specular	ADJ
brj-24353	116	18	and	and	CCONJ
brj-24353	116	19	diffuse	diffuse	ADJ
brj-24353	116	20	reflection	reflection	NOUN
brj-24353	116	21	spectra	spectra	NOUN
brj-24353	116	22	for	for	ADP
brj-24353	116	23	wood	wood	NOUN
brj-24353	116	24	species	specie	NOUN
brj-24353	116	25	recognition	recognition	NOUN
brj-24353	116	26	.	.	PUNCT
brj-24353	117	1	the	the	DET
brj-24353	117	2	possibility	possibility	NOUN
brj-24353	117	3	of	of	ADP
brj-24353	117	4	cross	cross	VERB
brj-24353	117	5	-	-	ADJ
brj-24353	117	6	using	use	VERB
brj-24353	117	7	classifier	classifier	NOUN
brj-24353	117	8	models	model	NOUN
brj-24353	117	9	trained	train	VERB
brj-24353	117	10	on	on	ADP
brj-24353	117	11	these	these	DET
brj-24353	117	12	two	two	NUM
brj-24353	117	13	types	type	NOUN
brj-24353	117	14	of	of	ADP
brj-24353	117	15	spectra	spectra	NOUN
brj-24353	117	16	was	be	AUX
brj-24353	117	17	also	also	ADV
brj-24353	117	18	explored	explore	VERB
brj-24353	117	19	.	.	PUNCT
brj-24353	118	1	it	it	PRON
brj-24353	118	2	is	be	AUX
brj-24353	118	3	important	important	ADJ
brj-24353	118	4	to	to	PART
brj-24353	118	5	note	note	VERB
brj-24353	118	6	that	that	SCONJ
brj-24353	118	7	the	the	DET
brj-24353	118	8	dataset	dataset	NOUN
brj-24353	118	9	was	be	AUX
brj-24353	118	10	randomly	randomly	ADV
brj-24353	118	11	divided	divide	VERB
brj-24353	118	12	each	each	DET
brj-24353	118	13	time	time	NOUN
brj-24353	118	14	training	training	NOUN
brj-24353	118	15	occurred	occur	VERB
brj-24353	118	16	;	;	PUNCT
brj-24353	118	17	therefore	therefore	ADV
brj-24353	118	18	,	,	PUNCT
brj-24353	118	19	the	the	DET
brj-24353	118	20	classification	classification	NOUN
brj-24353	118	21	accuracy	accuracy	NOUN
brj-24353	118	22	of	of	ADP
brj-24353	118	23	the	the	DET
brj-24353	118	24	trained	train	VERB
brj-24353	118	25	classifier	classifier	NOUN
brj-24353	118	26	models	model	NOUN
brj-24353	118	27	varied	varied	ADJ
brj-24353	118	28	across	across	ADP
brj-24353	118	29	the	the	DET
brj-24353	118	30	test	test	NOUN
brj-24353	118	31	datasets	dataset	NOUN
brj-24353	118	32	.	.	PUNCT
brj-24353	119	1	consequently	consequently	ADV
brj-24353	119	2	,	,	PUNCT
brj-24353	119	3	for	for	ADP
brj-24353	119	4	each	each	DET
brj-24353	119	5	classifier	classifier	NOUN
brj-24353	119	6	,	,	PUNCT
brj-24353	119	7	the	the	DET
brj-24353	119	8	training	training	NOUN
brj-24353	119	9	and	and	CCONJ
brj-24353	119	10	test	test	NOUN
brj-24353	119	11	datasets	dataset	NOUN
brj-24353	119	12	were	be	AUX
brj-24353	119	13	randomly	randomly	ADV
brj-24353	119	14	divided	divide	VERB
brj-24353	119	15	,	,	PUNCT
brj-24353	119	16	trained	train	VERB
brj-24353	119	17	,	,	PUNCT
brj-24353	119	18	and	and	CCONJ
brj-24353	119	19	tested	test	VERB
brj-24353	119	20	20	20	NUM
brj-24353	119	21	times	time	NOUN
brj-24353	119	22	,	,	PUNCT
brj-24353	119	23	with	with	SCONJ
brj-24353	119	24	the	the	DET
brj-24353	119	25	average	average	ADJ
brj-24353	119	26	classification	classification	NOUN
brj-24353	119	27	accuracy	accuracy	NOUN
brj-24353	119	28	being	be	AUX
brj-24353	119	29	calculated	calculate	VERB
brj-24353	119	30	.	.	PUNCT
brj-24353	120	1	classifier	classifier	NOUN
brj-24353	120	2	parameter	parameter	NOUN
brj-24353	120	3	setting	set	VERB
brj-24353	120	4	the	the	DET
brj-24353	120	5	svm	svm	NOUN
brj-24353	120	6	is	be	AUX
brj-24353	120	7	a	a	DET
brj-24353	120	8	supervised	supervised	ADJ
brj-24353	120	9	learning	learning	NOUN
brj-24353	120	10	model	model	NOUN
brj-24353	120	11	used	use	VERB
brj-24353	120	12	for	for	ADP
brj-24353	120	13	classification	classification	NOUN
brj-24353	120	14	and	and	CCONJ
brj-24353	120	15	regression	regression	NOUN
brj-24353	120	16	.	.	PUNCT
brj-24353	121	1	it	it	PRON
brj-24353	121	2	performs	perform	VERB
brj-24353	121	3	classification	classification	NOUN
brj-24353	121	4	by	by	ADP
brj-24353	121	5	finding	find	VERB
brj-24353	121	6	a	a	DET
brj-24353	121	7	hyperplane	hyperplane	NOUN
brj-24353	121	8	that	that	PRON
brj-24353	121	9	maximizes	maximize	VERB
brj-24353	121	10	the	the	DET
brj-24353	121	11	distance	distance	NOUN
brj-24353	121	12	between	between	ADP
brj-24353	121	13	different	different	ADJ
brj-24353	121	14	categories	category	NOUN
brj-24353	121	15	(	(	PUNCT
brj-24353	121	16	hearst	hearst	PROPN
brj-24353	121	17	et	et	PROPN
brj-24353	121	18	al	al	PROPN
brj-24353	121	19	.	.	PROPN
brj-24353	121	20	1998	1998	NUM
brj-24353	121	21	)	)	PUNCT
brj-24353	121	22	.	.	PUNCT
brj-24353	122	1	in	in	ADP
brj-24353	122	2	this	this	DET
brj-24353	122	3	study	study	NOUN
brj-24353	122	4	,	,	PUNCT
brj-24353	122	5	a	a	DET
brj-24353	122	6	radial	radial	ADJ
brj-24353	122	7	basis	basis	NOUN
brj-24353	122	8	function	function	NOUN
brj-24353	122	9	was	be	AUX
brj-24353	122	10	employed	employ	VERB
brj-24353	122	11	,	,	PUNCT
brj-24353	122	12	with	with	ADP
brj-24353	122	13	optimal	optimal	ADJ
brj-24353	122	14	parameters	parameter	NOUN
brj-24353	122	15	determined	determine	VERB
brj-24353	122	16	through	through	ADP
brj-24353	122	17	a	a	DET
brj-24353	122	18	grid	grid	NOUN
brj-24353	122	19	search	search	NOUN
brj-24353	122	20	method	method	NOUN
brj-24353	122	21	.	.	PUNCT
brj-24353	123	1	to	to	PART
brj-24353	123	2	prevent	prevent	VERB
brj-24353	123	3	overfitting	overfitting	NOUN
brj-24353	123	4	,	,	PUNCT
brj-24353	123	5	the	the	DET
brj-24353	123	6	classification	classification	NOUN
brj-24353	123	7	accuracy	accuracy	NOUN
brj-24353	123	8	was	be	AUX
brj-24353	123	9	determined	determine	VERB
brj-24353	123	10	via	via	ADP
brj-24353	123	11	cross	cross	NOUN
brj-24353	123	12	-	-	NOUN
brj-24353	123	13	validation	validation	NOUN
brj-24353	123	14	.	.	PUNCT
brj-24353	124	1	the	the	DET
brj-24353	124	2	knn	knn	PROPN
brj-24353	124	3	model	model	NOUN
brj-24353	124	4	classifies	classify	VERB
brj-24353	124	5	samples	sample	NOUN
brj-24353	124	6	by	by	ADP
brj-24353	124	7	calculating	calculate	VERB
brj-24353	124	8	the	the	DET
brj-24353	124	9	distance	distance	NOUN
brj-24353	124	10	between	between	ADP
brj-24353	124	11	the	the	DET
brj-24353	124	12	sample	sample	NOUN
brj-24353	124	13	to	to	PART
brj-24353	124	14	be	be	AUX
brj-24353	124	15	classified	classify	VERB
brj-24353	124	16	and	and	CCONJ
brj-24353	124	17	all	all	DET
brj-24353	124	18	samples	sample	NOUN
brj-24353	124	19	in	in	ADP
brj-24353	124	20	the	the	DET
brj-24353	124	21	training	training	NOUN
brj-24353	124	22	dataset	dataset	NOUN
brj-24353	124	23	,	,	PUNCT
brj-24353	124	24	identifying	identify	VERB
brj-24353	124	25	the	the	DET
brj-24353	124	26	k	k	NOUN
brj-24353	124	27	-	-	PUNCT
brj-24353	124	28	nearest	near	ADJ
brj-24353	124	29	neighbors	neighbor	NOUN
brj-24353	124	30	and	and	CCONJ
brj-24353	124	31	then	then	ADV
brj-24353	124	32	voting	vote	VERB
brj-24353	124	33	or	or	CCONJ
brj-24353	124	34	performing	perform	VERB
brj-24353	124	35	weighted	weight	VERB
brj-24353	124	36	voting	voting	NOUN
brj-24353	124	37	based	base	VERB
brj-24353	124	38	on	on	ADP
brj-24353	124	39	their	their	PRON
brj-24353	124	40	labels	label	NOUN
brj-24353	124	41	(	(	PUNCT
brj-24353	124	42	peterson	peterson	NOUN
brj-24353	124	43	2009	2009	NUM
brj-24353	124	44	)	)	PUNCT
brj-24353	124	45	.	.	PUNCT
brj-24353	125	1	in	in	ADP
brj-24353	125	2	this	this	DET
brj-24353	125	3	study	study	NOUN
brj-24353	125	4	,	,	PUNCT
brj-24353	125	5	the	the	DET
brj-24353	125	6	euclidean	euclidean	ADJ
brj-24353	125	7	distance	distance	NOUN
brj-24353	125	8	was	be	AUX
brj-24353	125	9	used	use	VERB
brj-24353	125	10	,	,	PUNCT
brj-24353	125	11	with	with	ADP
brj-24353	125	12	parameter	parameter	NOUN
brj-24353	125	13	k	k	PROPN
brj-24353	125	14	set	set	VERB
brj-24353	125	15	to	to	ADP
brj-24353	125	16	3	3	NUM
brj-24353	125	17	.	.	PUNCT
brj-24353	126	1	the	the	DET
brj-24353	126	2	cnns	cnn	NOUN
brj-24353	126	3	typically	typically	ADV
brj-24353	126	4	comprise	comprise	VERB
brj-24353	126	5	three	three	NUM
brj-24353	126	6	parts	part	NOUN
brj-24353	126	7	—	—	PUNCT
brj-24353	126	8	that	that	ADV
brj-24353	126	9	is	is	ADV
brj-24353	126	10	,	,	PUNCT
brj-24353	126	11	a	a	DET
brj-24353	126	12	convolutional	convolutional	ADJ
brj-24353	126	13	layer	layer	NOUN
brj-24353	126	14	,	,	PUNCT
brj-24353	126	15	a	a	DET
brj-24353	126	16	pooling	pool	VERB
brj-24353	126	17	layer	layer	NOUN
brj-24353	126	18	,	,	PUNCT
brj-24353	126	19	and	and	CCONJ
brj-24353	126	20	a	a	DET
brj-24353	126	21	fully	fully	ADV
brj-24353	126	22	connected	connect	VERB
brj-24353	126	23	layer	layer	NOUN
brj-24353	126	24	(	(	PUNCT
brj-24353	126	25	pan	pan	NOUN
brj-24353	126	26	et	et	PROPN
brj-24353	126	27	al	al	PROPN
brj-24353	126	28	.	.	PROPN
brj-24353	126	29	2023	2023	NUM
brj-24353	126	30	)	)	PUNCT
brj-24353	126	31	.	.	PUNCT
brj-24353	127	1	the	the	DET
brj-24353	127	2	cnn	cnn	PROPN
brj-24353	127	3	structure	structure	NOUN
brj-24353	127	4	used	use	VERB
brj-24353	127	5	in	in	ADP
brj-24353	127	6	this	this	DET
brj-24353	127	7	study	study	NOUN
brj-24353	127	8	comprised	comprise	VERB
brj-24353	127	9	two	two	NUM
brj-24353	127	10	convolutional	convolutional	ADJ
brj-24353	127	11	layers	layer	NOUN
brj-24353	127	12	,	,	PUNCT
brj-24353	127	13	two	two	NUM
brj-24353	127	14	pooling	pool	VERB
brj-24353	127	15	layers	layer	NOUN
brj-24353	127	16	,	,	PUNCT
brj-24353	127	17	one	one	NUM
brj-24353	127	18	fully	fully	ADV
brj-24353	127	19	connected	connect	VERB
brj-24353	127	20	layer	layer	NOUN
brj-24353	127	21	,	,	PUNCT
brj-24353	127	22	and	and	CCONJ
brj-24353	127	23	one	one	NUM
brj-24353	127	24	output	output	NOUN
brj-24353	127	25	layer	layer	NOUN
brj-24353	127	26	.	.	PUNCT
brj-24353	128	1	because	because	SCONJ
brj-24353	128	2	the	the	DET
brj-24353	128	3	spectral	spectral	ADJ
brj-24353	128	4	reflectance	reflectance	NOUN
brj-24353	128	5	of	of	ADP
brj-24353	128	6	wood	wood	NOUN
brj-24353	128	7	is	be	AUX
brj-24353	128	8	one	one	NUM
brj-24353	128	9	-	-	PUNCT
brj-24353	128	10	dimensional	dimensional	ADJ
brj-24353	128	11	,	,	PUNCT
brj-24353	128	12	it	it	PRON
brj-24353	128	13	must	must	AUX
brj-24353	128	14	be	be	AUX
brj-24353	128	15	processed	process	VERB
brj-24353	128	16	using	use	VERB
brj-24353	128	17	a	a	DET
brj-24353	128	18	one	one	NUM
brj-24353	128	19	-	-	PUNCT
brj-24353	128	20	dimensional	dimensional	ADJ
brj-24353	128	21	convolution	convolution	NOUN
brj-24353	128	22	kernel	kernel	NOUN
brj-24353	128	23	.	.	PUNCT
brj-24353	129	1	in	in	ADP
brj-24353	129	2	contrast	contrast	NOUN
brj-24353	129	3	,	,	PUNCT
brj-24353	129	4	128d	128d	PROPN
brj-24353	129	5	spectral	spectral	ADJ
brj-24353	129	6	vectors	vector	NOUN
brj-24353	129	7	exhibit	exhibit	VERB
brj-24353	129	8	low	low	ADJ
brj-24353	129	9	dimensionality	dimensionality	NOUN
brj-24353	129	10	,	,	PUNCT
brj-24353	129	11	leading	lead	VERB
brj-24353	129	12	the	the	DET
brj-24353	129	13	cnn	cnn	PROPN
brj-24353	129	14	to	to	PART
brj-24353	129	15	perform	perform	VERB
brj-24353	129	16	two	two	NUM
brj-24353	129	17	rounds	round	NOUN
brj-24353	129	18	of	of	ADP
brj-24353	129	19	convolution	convolution	NOUN
brj-24353	129	20	and	and	CCONJ
brj-24353	129	21	pooling	pooling	NOUN
brj-24353	129	22	.	.	PUNCT
brj-24353	130	1	increasing	increase	VERB
brj-24353	130	2	the	the	DET
brj-24353	130	3	number	number	NOUN
brj-24353	130	4	of	of	ADP
brj-24353	130	5	convolutions	convolution	NOUN
brj-24353	130	6	and	and	CCONJ
brj-24353	130	7	pooling	pool	VERB
brj-24353	130	8	layers	layer	NOUN
brj-24353	130	9	further	far	ADV
brj-24353	130	10	reduces	reduce	VERB
brj-24353	130	11	the	the	DET
brj-24353	130	12	dimensionality	dimensionality	NOUN
brj-24353	130	13	of	of	ADP
brj-24353	130	14	the	the	DET
brj-24353	130	15	convolutional	convolutional	ADJ
brj-24353	130	16	features	feature	NOUN
brj-24353	130	17	to	to	ADP
brj-24353	130	18	an	an	DET
brj-24353	130	19	excessively	excessively	ADV
brj-24353	130	20	small	small	ADJ
brj-24353	130	21	scale	scale	NOUN
brj-24353	130	22	.	.	PUNCT
brj-24353	131	1	the	the	DET
brj-24353	131	2	specific	specific	ADJ
brj-24353	131	3	parameters	parameter	NOUN
brj-24353	131	4	of	of	ADP
brj-24353	131	5	the	the	DET
brj-24353	131	6	cnn	cnn	PROPN
brj-24353	131	7	used	use	VERB
brj-24353	131	8	in	in	ADP
brj-24353	131	9	this	this	DET
brj-24353	131	10	study	study	NOUN
brj-24353	131	11	were	be	AUX
brj-24353	131	12	a	a	DET
brj-24353	131	13	one	one	NUM
brj-24353	131	14	-	-	PUNCT
brj-24353	131	15	dimensional	dimensional	ADJ
brj-24353	131	16	convolution	convolution	NOUN
brj-24353	131	17	kernel	kernel	NOUN
brj-24353	131	18	of	of	ADP
brj-24353	131	19	[	[	X
brj-24353	131	20	−2,2,1	−2,2,1	X
brj-24353	131	21	]	]	X
brj-24353	131	22	with	with	ADP
brj-24353	131	23	valid	valid	ADJ
brj-24353	131	24	convolution	convolution	NOUN
brj-24353	131	25	(	(	PUNCT
brj-24353	131	26	without	without	ADP
brj-24353	131	27	padding	padding	NOUN
brj-24353	131	28	)	)	PUNCT
brj-24353	131	29	,	,	PUNCT
brj-24353	131	30	and	and	CCONJ
brj-24353	131	31	a	a	DET
brj-24353	131	32	pooling	pool	VERB
brj-24353	131	33	layer	layer	NOUN
brj-24353	131	34	using	use	VERB
brj-24353	131	35	the	the	DET
brj-24353	131	36	maxpooling	maxpooling	NOUN
brj-24353	131	37	method	method	NOUN
brj-24353	131	38	.	.	PUNCT
brj-24353	132	1	the	the	DET
brj-24353	132	2	original	original	ADJ
brj-24353	132	3	nir	nir	ADJ
brj-24353	132	4	spectrum	spectrum	NOUN
brj-24353	132	5	was	be	AUX
brj-24353	132	6	128d	128d	NOUN
brj-24353	132	7	,	,	PUNCT
brj-24353	132	8	with	with	ADP
brj-24353	132	9	the	the	DET
brj-24353	132	10	dimension	dimension	NOUN
brj-24353	132	11	reduced	reduce	VERB
brj-24353	132	12	to	to	ADP
brj-24353	132	13	126d	126d	PROPN
brj-24353	132	14	after	after	ADP
brj-24353	132	15	the	the	DET
brj-24353	132	16	first	first	ADJ
brj-24353	132	17	convolution	convolution	NOUN
brj-24353	132	18	layer	layer	NOUN
brj-24353	132	19	.	.	PUNCT
brj-24353	133	1	the	the	DET
brj-24353	133	2	pooling	pooling	NOUN
brj-24353	133	3	step	step	NOUN
brj-24353	133	4	was	be	AUX
brj-24353	133	5	set	set	VERB
brj-24353	133	6	to	to	ADP
brj-24353	133	7	1	1	NUM
brj-24353	133	8	,	,	PUNCT
brj-24353	133	9	with	with	ADP
brj-24353	133	10	a	a	DET
brj-24353	133	11	pooling	pool	VERB
brj-24353	133	12	width	width	NOUN
brj-24353	133	13	of	of	ADP
brj-24353	133	14	4	4	NUM
brj-24353	133	15	,	,	PUNCT
brj-24353	133	16	resulting	result	VERB
brj-24353	133	17	in	in	ADP
brj-24353	133	18	a	a	DET
brj-24353	133	19	dimensionality	dimensionality	NOUN
brj-24353	133	20	of	of	ADP
brj-24353	133	21	32d	32d	NUM
brj-24353	133	22	following	follow	VERB
brj-24353	133	23	the	the	DET
brj-24353	133	24	pooling	pooling	NOUN
brj-24353	133	25	operation	operation	NOUN
brj-24353	133	26	.	.	PUNCT
brj-24353	134	1	after	after	ADP
brj-24353	134	2	further	further	ADJ
brj-24353	134	3	convolution	convolution	NOUN
brj-24353	134	4	and	and	CCONJ
brj-24353	134	5	pooling	pooling	NOUN
brj-24353	134	6	,	,	PUNCT
brj-24353	134	7	the	the	DET
brj-24353	134	8	final	final	ADJ
brj-24353	134	9	dimension	dimension	NOUN
brj-24353	134	10	was	be	AUX
brj-24353	134	11	8d	8d	NUM
brj-24353	134	12	.	.	PUNCT
brj-24353	135	1	the	the	DET
brj-24353	135	2	dt	dt	PROPN
brj-24353	135	3	is	be	AUX
brj-24353	135	4	a	a	DET
brj-24353	135	5	tree	tree	NOUN
brj-24353	135	6	-	-	PUNCT
brj-24353	135	7	structured	structure	VERB
brj-24353	135	8	supervised	supervised	ADJ
brj-24353	135	9	learning	learn	VERB
brj-24353	135	10	algorithm	algorithm	NOUN
brj-24353	135	11	that	that	PRON
brj-24353	135	12	classifies	classify	VERB
brj-24353	135	13	a	a	DET
brj-24353	135	14	dataset	dataset	NOUN
brj-24353	135	15	using	use	VERB
brj-24353	135	16	a	a	DET
brj-24353	135	17	series	series	NOUN
brj-24353	135	18	of	of	ADP
brj-24353	135	19	conditional	conditional	ADJ
brj-24353	135	20	judgments	judgment	NOUN
brj-24353	135	21	(	(	PUNCT
brj-24353	135	22	safavian	safavian	ADJ
brj-24353	135	23	and	and	CCONJ
brj-24353	135	24	landgrebe	landgrebe	VERB
brj-24353	135	25	1991	1991	NUM
brj-24353	135	26	)	)	PUNCT
brj-24353	135	27	.	.	PUNCT
brj-24353	136	1	in	in	ADP
brj-24353	136	2	this	this	DET
brj-24353	136	3	study	study	NOUN
brj-24353	136	4	,	,	PUNCT
brj-24353	136	5	a	a	DET
brj-24353	136	6	fine	fine	ADJ
brj-24353	136	7	tree	tree	NOUN
brj-24353	136	8	was	be	AUX
brj-24353	136	9	used	use	VERB
brj-24353	136	10	,	,	PUNCT
brj-24353	136	11	and	and	CCONJ
brj-24353	136	12	the	the	DET
brj-24353	136	13	maximum	maximum	ADJ
brj-24353	136	14	number	number	NOUN
brj-24353	136	15	of	of	ADP
brj-24353	136	16	splits	split	NOUN
brj-24353	136	17	was	be	AUX
brj-24353	136	18	set	set	VERB
brj-24353	136	19	at	at	ADP
brj-24353	136	20	100	100	NUM
brj-24353	136	21	.	.	PUNCT
brj-24353	137	1	the	the	DET
brj-24353	137	2	ncm	ncm	PROPN
brj-24353	137	3	classifier	classifier	NOUN
brj-24353	137	4	is	be	AUX
brj-24353	137	5	a	a	DET
brj-24353	137	6	class	class	NOUN
brj-24353	137	7	-	-	PUNCT
brj-24353	137	8	centered	center	VERB
brj-24353	137	9	classification	classification	NOUN
brj-24353	137	10	method	method	NOUN
brj-24353	137	11	that	that	PRON
brj-24353	137	12	compares	compare	VERB
brj-24353	137	13	the	the	DET
brj-24353	137	14	distances	distance	NOUN
brj-24353	137	15	between	between	ADP
brj-24353	137	16	the	the	DET
brj-24353	137	17	sample	sample	NOUN
brj-24353	137	18	to	to	PART
brj-24353	137	19	be	be	AUX
brj-24353	137	20	classified	classify	VERB
brj-24353	137	21	and	and	CCONJ
brj-24353	137	22	the	the	DET
brj-24353	137	23	class	class	NOUN
brj-24353	137	24	centers	center	NOUN
brj-24353	137	25	of	of	ADP
brj-24353	137	26	all	all	DET
brj-24353	137	27	categories	category	NOUN
brj-24353	137	28	,	,	PUNCT
brj-24353	137	29	assigning	assign	VERB
brj-24353	137	30	the	the	DET
brj-24353	137	31	sample	sample	NOUN
brj-24353	137	32	to	to	ADP
brj-24353	137	33	the	the	DET
brj-24353	137	34	closest	close	ADJ
brj-24353	137	35	class	class	NOUN
brj-24353	137	36	(	(	PUNCT
brj-24353	137	37	veenman	veenman	NOUN
brj-24353	137	38	and	and	CCONJ
brj-24353	137	39	reinders	reinder	NOUN
brj-24353	137	40	2005	2005	NUM
brj-24353	137	41	)	)	PUNCT
brj-24353	137	42	.	.	PUNCT
brj-24353	138	1	peer	peer	NOUN
brj-24353	138	2	-	-	PUNCT
brj-24353	138	3	reviewed	review	VERB
brj-24353	138	4	article	article	NOUN
brj-24353	138	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	138	6	wang	wang	PROPN
brj-24353	138	7	et	et	PROPN
brj-24353	138	8	al	al	PROPN
brj-24353	138	9	.	.	PROPN
brj-24353	139	1	(	(	PUNCT
brj-24353	139	2	2025	2025	NUM
brj-24353	139	3	)	)	PUNCT
brj-24353	139	4	.	.	PUNCT
brj-24353	140	1	“	"	PUNCT
brj-24353	140	2	wood	wood	NOUN
brj-24353	140	3	i	i	X
brj-24353	140	4	d	d	PROPN
brj-24353	140	5	via	via	ADP
brj-24353	140	6	.	.	PUNCT
brj-24353	141	1	s	s	PROPN
brj-24353	141	2	-	-	PUNCT
brj-24353	141	3	nir	nir	PROPN
brj-24353	141	4	&	&	CCONJ
brj-24353	141	5	dr	dr	PROPN
brj-24353	141	6	-	-	PUNCT
brj-24353	141	7	nir	nir	PROPN
brj-24353	141	8	,	,	PUNCT
brj-24353	141	9	”	"	PUNCT
brj-24353	141	10	bioresources	bioresource	NOUN
brj-24353	141	11	20(3	20(3	NOUN
brj-24353	141	12	)	)	PUNCT
brj-24353	141	13	,	,	PUNCT
brj-24353	141	14	6648	6648	NUM
brj-24353	141	15	-	-	SYM
brj-24353	141	16	6661	6661	NUM
brj-24353	141	17	.	.	PUNCT
brj-24353	142	1	6655	6655	NUM
brj-24353	142	2	results	result	NOUN
brj-24353	142	3	and	and	CCONJ
brj-24353	142	4	discussion	discussion	NOUN
brj-24353	142	5	comparison	comparison	NOUN
brj-24353	142	6	of	of	ADP
brj-24353	142	7	spectral	spectral	ADJ
brj-24353	142	8	curves	curve	NOUN
brj-24353	142	9	of	of	ADP
brj-24353	142	10	specular	specular	ADJ
brj-24353	142	11	and	and	CCONJ
brj-24353	142	12	diffuse	diffuse	VERB
brj-24353	142	13	reflections	reflection	NOUN
brj-24353	142	14	the	the	DET
brj-24353	142	15	specular	specular	ADJ
brj-24353	142	16	and	and	CCONJ
brj-24353	142	17	diffuse	diffuse	VERB
brj-24353	142	18	reflectance	reflectance	NOUN
brj-24353	142	19	spectra	spectra	NOUN
brj-24353	142	20	of	of	ADP
brj-24353	142	21	the	the	DET
brj-24353	142	22	five	five	NUM
brj-24353	142	23	wood	wood	NOUN
brj-24353	142	24	cross	cross	NOUN
brj-24353	142	25	sections	section	NOUN
brj-24353	142	26	are	be	AUX
brj-24353	142	27	illustrated	illustrate	VERB
brj-24353	142	28	in	in	ADP
brj-24353	142	29	fig	fig	NOUN
brj-24353	142	30	.	.	PUNCT
brj-24353	143	1	5	5	X
brj-24353	143	2	.	.	X
brj-24353	143	3	the	the	DET
brj-24353	143	4	spectral	spectral	ADJ
brj-24353	143	5	curves	curve	NOUN
brj-24353	143	6	for	for	ADP
brj-24353	143	7	the	the	DET
brj-24353	143	8	specular	specular	ADJ
brj-24353	143	9	and	and	CCONJ
brj-24353	143	10	diffuse	diffuse	VERB
brj-24353	143	11	reflections	reflection	NOUN
brj-24353	143	12	of	of	ADP
brj-24353	143	13	the	the	DET
brj-24353	143	14	same	same	ADJ
brj-24353	143	15	wood	wood	NOUN
brj-24353	143	16	species	specie	NOUN
brj-24353	143	17	followed	follow	VERB
brj-24353	143	18	similar	similar	ADJ
brj-24353	143	19	trends	trend	NOUN
brj-24353	143	20	,	,	PUNCT
brj-24353	143	21	with	with	ADP
brj-24353	143	22	only	only	ADJ
brj-24353	143	23	slight	slight	ADJ
brj-24353	143	24	shifts	shift	NOUN
brj-24353	143	25	in	in	ADP
brj-24353	143	26	their	their	PRON
brj-24353	143	27	values	value	NOUN
brj-24353	143	28	.	.	PUNCT
brj-24353	144	1	additionally	additionally	ADV
brj-24353	144	2	,	,	PUNCT
brj-24353	144	3	the	the	DET
brj-24353	144	4	reflectance	reflectance	NOUN
brj-24353	144	5	of	of	ADP
brj-24353	144	6	the	the	DET
brj-24353	144	7	diffuse	diffuse	NOUN
brj-24353	144	8	reflections	reflection	NOUN
brj-24353	144	9	was	be	AUX
brj-24353	144	10	generally	generally	ADV
brj-24353	144	11	higher	high	ADJ
brj-24353	144	12	than	than	ADP
brj-24353	144	13	that	that	PRON
brj-24353	144	14	of	of	ADP
brj-24353	144	15	the	the	DET
brj-24353	144	16	specular	specular	ADJ
brj-24353	144	17	reflections	reflection	NOUN
brj-24353	144	18	.	.	PUNCT
brj-24353	145	1	to	to	PART
brj-24353	145	2	quantitatively	quantitatively	ADV
brj-24353	145	3	analyze	analyze	VERB
brj-24353	145	4	the	the	DET
brj-24353	145	5	difference	difference	NOUN
brj-24353	145	6	in	in	ADP
brj-24353	145	7	mode	mode	NOUN
brj-24353	145	8	separability	separability	NOUN
brj-24353	145	9	information	information	NOUN
brj-24353	145	10	between	between	ADP
brj-24353	145	11	the	the	DET
brj-24353	145	12	specular	specular	ADJ
brj-24353	145	13	and	and	CCONJ
brj-24353	145	14	diffuse	diffuse	PROPN
brj-24353	145	15	reflectance	reflectance	NOUN
brj-24353	145	16	spectra	spectra	NOUN
brj-24353	145	17	,	,	PUNCT
brj-24353	145	18	three	three	NUM
brj-24353	145	19	metrics	metric	NOUN
brj-24353	145	20	based	base	VERB
brj-24353	145	21	on	on	ADP
brj-24353	145	22	scatter	scatter	NOUN
brj-24353	145	23	matrices	matrix	NOUN
brj-24353	145	24	were	be	AUX
brj-24353	145	25	employed	employ	VERB
brj-24353	145	26	.	.	PUNCT
brj-24353	146	1	these	these	DET
brj-24353	146	2	metrics	metric	NOUN
brj-24353	146	3	can	can	AUX
brj-24353	146	4	be	be	AUX
brj-24353	146	5	defined	define	VERB
brj-24353	146	6	as	as	SCONJ
brj-24353	146	7	follows	follow	VERB
brj-24353	146	8	:	:	PUNCT
brj-24353	146	9	𝐽1	𝐽1	PROPN
brj-24353	146	10	=	=	SYM
brj-24353	146	11	𝑡𝑟(𝑆𝑏	𝑡𝑟(𝑆𝑏	PROPN
brj-24353	146	12	)	)	PUNCT
brj-24353	146	13	𝑡𝑟(𝑆𝑤	𝑡𝑟(𝑆𝑤	PROPN
brj-24353	146	14	)	)	PUNCT
brj-24353	146	15	,	,	PUNCT
brj-24353	146	16	(	(	PUNCT
brj-24353	146	17	1	1	X
brj-24353	146	18	)	)	PUNCT
brj-24353	146	19	𝐽2	𝐽2	NOUN
brj-24353	146	20	=	=	SYM
brj-24353	146	21	𝑡𝑟(𝑆𝑤	𝑡𝑟(𝑆𝑤	PROPN
brj-24353	146	22	−1𝑆𝑏	−1𝑆𝑏	NOUN
brj-24353	146	23	)	)	PUNCT
brj-24353	146	24	,	,	PUNCT
brj-24353	146	25	(	(	PUNCT
brj-24353	146	26	2	2	X
brj-24353	146	27	)	)	PUNCT
brj-24353	146	28	𝐽3	𝐽3	NOUN
brj-24353	146	29	=	=	SYM
brj-24353	146	30	|𝑆𝑤	|𝑆𝑤	PROPN
brj-24353	146	31	−1𝑆𝑏|	−1𝑆𝑏|	NOUN
brj-24353	146	32	(	(	PUNCT
brj-24353	146	33	3	3	NUM
brj-24353	146	34	)	)	PUNCT
brj-24353	146	35	where	where	SCONJ
brj-24353	146	36	𝑆𝑤	𝑆𝑤	PROPN
brj-24353	146	37	denotes	denote	VERB
brj-24353	146	38	the	the	DET
brj-24353	146	39	total	total	ADJ
brj-24353	146	40	within	within	ADP
brj-24353	146	41	-	-	PUNCT
brj-24353	146	42	class	class	NOUN
brj-24353	146	43	scatter	scatter	NOUN
brj-24353	146	44	matrix	matrix	NOUN
brj-24353	146	45	for	for	ADP
brj-24353	146	46	all	all	DET
brj-24353	146	47	classes	class	NOUN
brj-24353	146	48	,	,	PUNCT
brj-24353	146	49	and	and	CCONJ
brj-24353	147	1	𝑆𝑏	𝑆𝑏	PROPN
brj-24353	147	2	denotes	denote	VERB
brj-24353	147	3	the	the	DET
brj-24353	147	4	total	total	NOUN
brj-24353	147	5	between	between	ADP
brj-24353	147	6	-	-	PUNCT
brj-24353	147	7	class	class	NOUN
brj-24353	147	8	scatter	scatter	NOUN
brj-24353	147	9	matrix	matrix	NOUN
brj-24353	147	10	for	for	ADP
brj-24353	147	11	all	all	DET
brj-24353	147	12	classes	class	NOUN
brj-24353	147	13	.	.	PUNCT
brj-24353	148	1	consequently	consequently	ADV
brj-24353	148	2	,	,	PUNCT
brj-24353	148	3	larger	large	ADJ
brj-24353	148	4	𝐽1	𝐽1	NOUN
brj-24353	148	5	,	,	PUNCT
brj-24353	148	6	𝐽2	𝐽2	NOUN
brj-24353	148	7	,	,	PUNCT
brj-24353	148	8	and	and	CCONJ
brj-24353	148	9	𝐽3	𝐽3	PROPN
brj-24353	148	10	,	,	PUNCT
brj-24353	148	11	values	value	NOUN
brj-24353	148	12	resulted	result	VERB
brj-24353	148	13	in	in	ADP
brj-24353	148	14	better	well	ADJ
brj-24353	148	15	separability	separability	NOUN
brj-24353	148	16	of	of	ADP
brj-24353	148	17	the	the	DET
brj-24353	148	18	sample	sample	NOUN
brj-24353	148	19	patterns	pattern	NOUN
brj-24353	148	20	.	.	PUNCT
brj-24353	149	1	table	table	NOUN
brj-24353	149	2	2	2	NUM
brj-24353	149	3	lists	list	VERB
brj-24353	149	4	the	the	DET
brj-24353	149	5	three	three	NUM
brj-24353	149	6	metrics	metric	NOUN
brj-24353	149	7	calculated	calculate	VERB
brj-24353	149	8	from	from	ADP
brj-24353	149	9	the	the	DET
brj-24353	149	10	specular	specular	ADJ
brj-24353	149	11	and	and	CCONJ
brj-24353	149	12	diffuse	diffuse	VERB
brj-24353	149	13	reflectance	reflectance	NOUN
brj-24353	149	14	spectra	spectra	NOUN
brj-24353	149	15	of	of	ADP
brj-24353	149	16	the	the	DET
brj-24353	149	17	64	64	NUM
brj-24353	149	18	wood	wood	NOUN
brj-24353	149	19	species	specie	NOUN
brj-24353	149	20	listed	list	VERB
brj-24353	149	21	in	in	ADP
brj-24353	149	22	table	table	NOUN
brj-24353	149	23	1	1	NUM
brj-24353	149	24	.	.	PUNCT
brj-24353	150	1	the	the	DET
brj-24353	150	2	specular	specular	ADJ
brj-24353	150	3	reflectance	reflectance	NOUN
brj-24353	150	4	spectra	spectra	NOUN
brj-24353	150	5	provided	provide	VERB
brj-24353	150	6	better	well	ADJ
brj-24353	150	7	pattern	pattern	NOUN
brj-24353	150	8	separability	separability	NOUN
brj-24353	150	9	,	,	PUNCT
brj-24353	150	10	suggesting	suggest	VERB
brj-24353	150	11	that	that	SCONJ
brj-24353	150	12	they	they	PRON
brj-24353	150	13	should	should	AUX
brj-24353	150	14	yield	yield	VERB
brj-24353	150	15	higher	high	ADJ
brj-24353	150	16	classification	classification	NOUN
brj-24353	150	17	accuracy	accuracy	NOUN
brj-24353	150	18	when	when	SCONJ
brj-24353	150	19	applied	apply	VERB
brj-24353	150	20	to	to	ADP
brj-24353	150	21	wood	wood	NOUN
brj-24353	150	22	species	specie	NOUN
brj-24353	150	23	classification	classification	NOUN
brj-24353	150	24	and	and	CCONJ
brj-24353	150	25	recognition	recognition	NOUN
brj-24353	150	26	.	.	PUNCT
brj-24353	151	1	fig	fig	NOUN
brj-24353	151	2	.	.	PUNCT
brj-24353	152	1	5	5	NUM
brj-24353	152	2	.	.	X
brj-24353	152	3	comparison	comparison	NOUN
brj-24353	152	4	of	of	ADP
brj-24353	152	5	specular	specular	ADJ
brj-24353	152	6	and	and	CCONJ
brj-24353	152	7	diffuse	diffuse	VERB
brj-24353	152	8	spectral	spectral	ADJ
brj-24353	152	9	reflectance	reflectance	NOUN
brj-24353	152	10	curves	curve	NOUN
brj-24353	152	11	for	for	ADP
brj-24353	152	12	cross	cross	NOUN
brj-24353	152	13	sections	section	NOUN
brj-24353	152	14	of	of	ADP
brj-24353	152	15	the	the	DET
brj-24353	152	16	same	same	ADJ
brj-24353	152	17	wood	wood	NOUN
brj-24353	152	18	sample	sample	NOUN
brj-24353	152	19	peer	peer	NOUN
brj-24353	152	20	-	-	PUNCT
brj-24353	152	21	reviewed	review	VERB
brj-24353	152	22	article	article	NOUN
brj-24353	152	23	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	152	24	wang	wang	PROPN
brj-24353	152	25	et	et	PROPN
brj-24353	152	26	al	al	PROPN
brj-24353	152	27	.	.	PROPN
brj-24353	153	1	(	(	PUNCT
brj-24353	153	2	2025	2025	NUM
brj-24353	153	3	)	)	PUNCT
brj-24353	153	4	.	.	PUNCT
brj-24353	154	1	“	"	PUNCT
brj-24353	154	2	wood	wood	NOUN
brj-24353	154	3	i	i	X
brj-24353	154	4	d	d	PROPN
brj-24353	154	5	via	via	ADP
brj-24353	154	6	.	.	PUNCT
brj-24353	155	1	s	s	PROPN
brj-24353	155	2	-	-	PUNCT
brj-24353	155	3	nir	nir	PROPN
brj-24353	155	4	&	&	CCONJ
brj-24353	155	5	dr	dr	PROPN
brj-24353	155	6	-	-	PUNCT
brj-24353	155	7	nir	nir	PROPN
brj-24353	155	8	,	,	PUNCT
brj-24353	155	9	”	"	PUNCT
brj-24353	155	10	bioresources	bioresource	NOUN
brj-24353	155	11	20(3	20(3	NOUN
brj-24353	155	12	)	)	PUNCT
brj-24353	155	13	,	,	PUNCT
brj-24353	155	14	6648	6648	NUM
brj-24353	155	15	-	-	SYM
brj-24353	155	16	6661	6661	NUM
brj-24353	155	17	.	.	PUNCT
brj-24353	156	1	6656	6656	NUM
brj-24353	156	2	table	table	NOUN
brj-24353	156	3	2	2	NUM
brj-24353	156	4	.	.	PUNCT
brj-24353	156	5	comparison	comparison	NOUN
brj-24353	156	6	of	of	ADP
brj-24353	156	7	mode	mode	PROPN
brj-24353	156	8	separability	separability	NOUN
brj-24353	156	9	informativeness	informativeness	NOUN
brj-24353	156	10	of	of	ADP
brj-24353	156	11	specular	specular	ADJ
brj-24353	156	12	and	and	CCONJ
brj-24353	156	13	diffuse	diffuse	VERB
brj-24353	156	14	reflectance	reflectance	NOUN
brj-24353	156	15	spectra	spectra	NOUN
brj-24353	156	16	j1	j1	PROPN
brj-24353	156	17	j2	j2	PROPN
brj-24353	156	18	j3	j3	PROPN
brj-24353	156	19	specular	specular	PROPN
brj-24353	156	20	reflectance	reflectance	NOUN
brj-24353	156	21	spectrum	spectrum	VERB
brj-24353	156	22	52.19	52.19	NUM
brj-24353	156	23	11338	11338	NUM
brj-24353	156	24	3.82	3.82	NUM
brj-24353	156	25	×	×	NOUN
brj-24353	156	26	10	10	NUM
brj-24353	156	27	-	-	SYM
brj-24353	156	28	4	4	NUM
brj-24353	156	29	diffuse	diffuse	NOUN
brj-24353	156	30	reflectance	reflectance	NOUN
brj-24353	156	31	spectrum	spectrum	VERB
brj-24353	156	32	12.23	12.23	NUM
brj-24353	156	33	1915	1915	NUM
brj-24353	156	34	2.14	2.14	NUM
brj-24353	156	35	×	×	NOUN
brj-24353	156	36	10	10	NUM
brj-24353	156	37	-	-	SYM
brj-24353	156	38	32	32	NUM
brj-24353	156	39	comparison	comparison	NOUN
brj-24353	156	40	of	of	ADP
brj-24353	156	41	specular	specular	ADJ
brj-24353	156	42	and	and	CCONJ
brj-24353	156	43	diffuse	diffuse	VERB
brj-24353	156	44	spectral	spectral	ADJ
brj-24353	156	45	classification	classification	NOUN
brj-24353	156	46	accuracy	accuracy	NOUN
brj-24353	156	47	the	the	DET
brj-24353	156	48	average	average	ADJ
brj-24353	156	49	correct	correct	ADJ
brj-24353	156	50	classification	classification	NOUN
brj-24353	156	51	rates	rate	NOUN
brj-24353	156	52	of	of	ADP
brj-24353	156	53	the	the	DET
brj-24353	156	54	five	five	NUM
brj-24353	156	55	classifiers	classifier	NOUN
brj-24353	156	56	after	after	SCONJ
brj-24353	156	57	20	20	NUM
brj-24353	156	58	training	training	NOUN
brj-24353	156	59	and	and	CCONJ
brj-24353	156	60	testing	testing	NOUN
brj-24353	156	61	sessions	session	NOUN
brj-24353	156	62	are	be	AUX
brj-24353	156	63	listed	list	VERB
brj-24353	156	64	in	in	ADP
brj-24353	156	65	table	table	NOUN
brj-24353	156	66	3	3	NUM
brj-24353	156	67	.	.	PUNCT
brj-24353	157	1	the	the	DET
brj-24353	157	2	classification	classification	NOUN
brj-24353	157	3	accuracies	accuracy	NOUN
brj-24353	157	4	of	of	ADP
brj-24353	157	5	the	the	DET
brj-24353	157	6	specular	specular	ADJ
brj-24353	157	7	and	and	CCONJ
brj-24353	157	8	diffuse	diffuse	VERB
brj-24353	157	9	reflectance	reflectance	NOUN
brj-24353	157	10	spectra	spectra	NOUN
brj-24353	157	11	under	under	ADP
brj-24353	157	12	the	the	DET
brj-24353	157	13	svm	svm	ADJ
brj-24353	157	14	classifier	classifier	NOUN
brj-24353	157	15	were	be	AUX
brj-24353	157	16	essentially	essentially	ADV
brj-24353	157	17	the	the	DET
brj-24353	157	18	same	same	ADJ
brj-24353	157	19	.	.	PUNCT
brj-24353	158	1	for	for	ADP
brj-24353	158	2	the	the	DET
brj-24353	158	3	other	other	ADJ
brj-24353	158	4	classifiers	classifier	NOUN
brj-24353	158	5	,	,	PUNCT
brj-24353	158	6	the	the	DET
brj-24353	158	7	classification	classification	NOUN
brj-24353	158	8	accuracy	accuracy	NOUN
brj-24353	158	9	of	of	ADP
brj-24353	158	10	the	the	DET
brj-24353	158	11	specular	specular	ADJ
brj-24353	158	12	reflectance	reflectance	NOUN
brj-24353	158	13	spectra	spectra	NOUN
brj-24353	158	14	was	be	AUX
brj-24353	158	15	higher	high	ADJ
brj-24353	158	16	than	than	ADP
brj-24353	158	17	that	that	PRON
brj-24353	158	18	of	of	ADP
brj-24353	158	19	the	the	DET
brj-24353	158	20	diffuse	diffuse	PROPN
brj-24353	158	21	reflectance	reflectance	NOUN
brj-24353	158	22	spectra	spectra	NOUN
brj-24353	158	23	,	,	PUNCT
brj-24353	158	24	consistent	consistent	ADJ
brj-24353	158	25	with	with	ADP
brj-24353	158	26	the	the	DET
brj-24353	158	27	three	three	NUM
brj-24353	158	28	metrics	metric	NOUN
brj-24353	158	29	𝐽1	𝐽1	NOUN
brj-24353	158	30	,	,	PUNCT
brj-24353	158	31	𝐽2	𝐽2	NOUN
brj-24353	158	32	,	,	PUNCT
brj-24353	158	33	and	and	CCONJ
brj-24353	158	34	𝐽3	𝐽3	NOUN
brj-24353	158	35	in	in	ADP
brj-24353	158	36	table	table	NOUN
brj-24353	158	37	2	2	NUM
brj-24353	158	38	.	.	PUNCT
brj-24353	158	39	figure	figure	NOUN
brj-24353	158	40	6	6	NUM
brj-24353	158	41	illustrates	illustrate	VERB
brj-24353	158	42	the	the	DET
brj-24353	158	43	classification	classification	NOUN
brj-24353	158	44	accuracy	accuracy	NOUN
brj-24353	158	45	of	of	ADP
brj-24353	158	46	the	the	DET
brj-24353	158	47	svm	svm	ADJ
brj-24353	158	48	classifier	classifier	NOUN
brj-24353	158	49	over	over	ADP
brj-24353	158	50	20	20	NUM
brj-24353	158	51	training	training	NOUN
brj-24353	158	52	and	and	CCONJ
brj-24353	158	53	testing	testing	NOUN
brj-24353	158	54	sessions	session	NOUN
brj-24353	158	55	.	.	PUNCT
brj-24353	159	1	the	the	DET
brj-24353	159	2	classification	classification	NOUN
brj-24353	159	3	accuracies	accuracy	NOUN
brj-24353	159	4	of	of	ADP
brj-24353	159	5	specular	specular	ADJ
brj-24353	159	6	and	and	CCONJ
brj-24353	159	7	diffuse	diffuse	ADJ
brj-24353	159	8	reflectance	reflectance	NOUN
brj-24353	159	9	spectra	spectra	NOUN
brj-24353	159	10	were	be	AUX
brj-24353	159	11	similar	similar	ADJ
brj-24353	159	12	,	,	PUNCT
brj-24353	159	13	though	though	SCONJ
brj-24353	159	14	the	the	DET
brj-24353	159	15	accuracy	accuracy	NOUN
brj-24353	159	16	of	of	ADP
brj-24353	159	17	the	the	DET
brj-24353	159	18	diffuse	diffuse	NOUN
brj-24353	159	19	reflectance	reflectance	NOUN
brj-24353	159	20	spectra	spectra	NOUN
brj-24353	159	21	exhibited	exhibit	VERB
brj-24353	159	22	slightly	slightly	ADV
brj-24353	159	23	more	more	ADJ
brj-24353	159	24	fluctuation	fluctuation	NOUN
brj-24353	159	25	compared	compare	VERB
brj-24353	159	26	to	to	ADP
brj-24353	159	27	that	that	PRON
brj-24353	159	28	of	of	ADP
brj-24353	159	29	the	the	DET
brj-24353	159	30	specular	specular	ADJ
brj-24353	159	31	reflectance	reflectance	NOUN
brj-24353	159	32	spectra	spectra	NOUN
brj-24353	159	33	.	.	PUNCT
brj-24353	160	1	the	the	DET
brj-24353	160	2	classification	classification	NOUN
brj-24353	160	3	accuracy	accuracy	NOUN
brj-24353	160	4	values	value	NOUN
brj-24353	160	5	for	for	ADP
brj-24353	160	6	the	the	DET
brj-24353	160	7	svm	svm	ADJ
brj-24353	160	8	model	model	NOUN
brj-24353	160	9	for	for	ADP
brj-24353	160	10	each	each	DET
brj-24353	160	11	wood	wood	NOUN
brj-24353	160	12	species	specie	NOUN
brj-24353	160	13	are	be	AUX
brj-24353	160	14	summarized	summarize	VERB
brj-24353	160	15	in	in	ADP
brj-24353	160	16	table	table	NOUN
brj-24353	160	17	4	4	NUM
brj-24353	160	18	.	.	PUNCT
brj-24353	160	19	table	table	NOUN
brj-24353	160	20	3	3	NUM
brj-24353	160	21	.	.	PUNCT
brj-24353	160	22	classification	classification	NOUN
brj-24353	160	23	correctness	correctness	NOUN
brj-24353	160	24	of	of	ADP
brj-24353	160	25	specular	specular	ADJ
brj-24353	160	26	and	and	CCONJ
brj-24353	160	27	diffuse	diffuse	VERB
brj-24353	160	28	reflectance	reflectance	NOUN
brj-24353	160	29	spectra	spectra	NOUN
brj-24353	160	30	under	under	ADP
brj-24353	160	31	different	different	ADJ
brj-24353	160	32	classifiers	classifier	NOUN
brj-24353	160	33	svm	svm	PROPN
brj-24353	160	34	knn	knn	PROPN
brj-24353	160	35	cnn	cnn	PROPN
brj-24353	160	36	dt	dt	PROPN
brj-24353	161	1	ncm	ncm	PROPN
brj-24353	162	1	specular	specular	ADJ
brj-24353	162	2	reflectance	reflectance	NOUN
brj-24353	162	3	spectrum	spectrum	VERB
brj-24353	162	4	88.43	88.43	NUM
brj-24353	162	5	%	%	NOUN
brj-24353	162	6	80.00	80.00	NUM
brj-24353	162	7	%	%	NOUN
brj-24353	162	8	64.48	64.48	NUM
brj-24353	162	9	%	%	NOUN
brj-24353	162	10	72.19	72.19	NUM
brj-24353	162	11	%	%	NOUN
brj-24353	162	12	56.97	56.97	NUM
brj-24353	162	13	%	%	NOUN
brj-24353	162	14	diffuse	diffuse	NOUN
brj-24353	162	15	reflectance	reflectance	NOUN
brj-24353	162	16	spectrum	spectrum	NOUN
brj-24353	162	17	88.02	88.02	NUM
brj-24353	162	18	%	%	NOUN
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brj-24353	162	20	%	%	NOUN
brj-24353	162	21	62.81	62.81	NUM
brj-24353	162	22	%	%	NOUN
brj-24353	162	23	65.10	65.10	NUM
brj-24353	162	24	%	%	NOUN
brj-24353	162	25	48.33	48.33	NUM
brj-24353	162	26	%	%	NOUN
brj-24353	162	27	fig	fig	NOUN
brj-24353	162	28	.	.	PUNCT
brj-24353	163	1	6	6	X
brj-24353	163	2	.	.	X
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brj-24353	163	4	results	result	NOUN
brj-24353	163	5	of	of	ADP
brj-24353	163	6	svm	svm	ADJ
brj-24353	163	7	classifier	classifier	NOUN
brj-24353	163	8	for	for	ADP
brj-24353	163	9	two	two	NUM
brj-24353	163	10	types	type	NOUN
brj-24353	163	11	of	of	ADP
brj-24353	163	12	spectra	spectra	NOUN
brj-24353	163	13	for	for	ADP
brj-24353	163	14	20	20	NUM
brj-24353	163	15	training	training	NOUN
brj-24353	163	16	and	and	CCONJ
brj-24353	163	17	testing	testing	NOUN
brj-24353	163	18	cases	case	NOUN
brj-24353	163	19	peer	peer	NOUN
brj-24353	163	20	-	-	PUNCT
brj-24353	163	21	reviewed	review	VERB
brj-24353	163	22	article	article	NOUN
brj-24353	163	23	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	163	24	wang	wang	PROPN
brj-24353	163	25	et	et	PROPN
brj-24353	163	26	al	al	PROPN
brj-24353	163	27	.	.	PROPN
brj-24353	164	1	(	(	PUNCT
brj-24353	164	2	2025	2025	NUM
brj-24353	164	3	)	)	PUNCT
brj-24353	164	4	.	.	PUNCT
brj-24353	165	1	“	"	PUNCT
brj-24353	165	2	wood	wood	NOUN
brj-24353	165	3	i	i	X
brj-24353	165	4	d	d	PROPN
brj-24353	165	5	via	via	ADP
brj-24353	165	6	.	.	PUNCT
brj-24353	166	1	s	s	PROPN
brj-24353	166	2	-	-	PUNCT
brj-24353	166	3	nir	nir	PROPN
brj-24353	166	4	&	&	CCONJ
brj-24353	166	5	dr	dr	PROPN
brj-24353	166	6	-	-	PUNCT
brj-24353	166	7	nir	nir	PROPN
brj-24353	166	8	,	,	PUNCT
brj-24353	166	9	”	"	PUNCT
brj-24353	166	10	bioresources	bioresource	NOUN
brj-24353	166	11	20(3	20(3	NOUN
brj-24353	166	12	)	)	PUNCT
brj-24353	166	13	,	,	PUNCT
brj-24353	166	14	6648	6648	NUM
brj-24353	166	15	-	-	SYM
brj-24353	166	16	6661	6661	NUM
brj-24353	166	17	.	.	PUNCT
brj-24353	167	1	6657	6657	NUM
brj-24353	167	2	table	table	NOUN
brj-24353	167	3	4	4	NUM
brj-24353	167	4	.	.	PUNCT
brj-24353	167	5	correct	correct	ADJ
brj-24353	167	6	classification	classification	NOUN
brj-24353	167	7	rate	rate	NOUN
brj-24353	167	8	for	for	ADP
brj-24353	167	9	each	each	DET
brj-24353	167	10	wood	wood	NOUN
brj-24353	167	11	species	specie	NOUN
brj-24353	167	12	under	under	ADP
brj-24353	167	13	the	the	DET
brj-24353	167	14	svm	svm	PROPN
brj-24353	167	15	classifier	classifier	NOUN
brj-24353	167	16	serial	serial	ADJ
brj-24353	167	17	number	number	NOUN
brj-24353	167	18	1	1	NUM
brj-24353	167	19	2	2	NUM
brj-24353	167	20	3	3	NUM
brj-24353	167	21	4	4	NUM
brj-24353	167	22	5	5	NUM
brj-24353	167	23	6	6	NUM
brj-24353	167	24	7	7	NUM
brj-24353	167	25	8	8	NUM
brj-24353	167	26	specular	specular	ADJ
brj-24353	167	27	100	100	NUM
brj-24353	167	28	%	%	NOUN
brj-24353	167	29	86.67	86.67	NUM
brj-24353	167	30	%	%	NOUN
brj-24353	167	31	100	100	NUM
brj-24353	167	32	%	%	NOUN
brj-24353	167	33	100	100	NUM
brj-24353	167	34	%	%	NOUN
brj-24353	167	35	100	100	NUM
brj-24353	167	36	%	%	NOUN
brj-24353	167	37	93.33	93.33	NUM
brj-24353	167	38	%	%	NOUN
brj-24353	167	39	100	100	NUM
brj-24353	167	40	%	%	NOUN
brj-24353	167	41	93.33	93.33	NUM
brj-24353	167	42	%	%	NOUN
brj-24353	167	43	diffuse	diffuse	NOUN
brj-24353	167	44	100	100	NUM
brj-24353	167	45	%	%	NOUN
brj-24353	167	46	93.33	93.33	NUM
brj-24353	167	47	%	%	NOUN
brj-24353	167	48	100	100	NUM
brj-24353	167	49	%	%	NOUN
brj-24353	167	50	100	100	NUM
brj-24353	167	51	%	%	NOUN
brj-24353	167	52	66.67	66.67	NUM
brj-24353	167	53	%	%	NOUN
brj-24353	167	54	93.33	93.33	NUM
brj-24353	167	55	%	%	NOUN
brj-24353	167	56	93.33	93.33	NUM
brj-24353	167	57	%	%	NOUN
brj-24353	167	58	66.67	66.67	NUM
brj-24353	167	59	%	%	NOUN
brj-24353	167	60	serial	serial	ADJ
brj-24353	167	61	number	number	NOUN
brj-24353	167	62	9	9	NUM
brj-24353	167	63	10	10	NUM
brj-24353	167	64	11	11	NUM
brj-24353	167	65	12	12	NUM
brj-24353	167	66	13	13	NUM
brj-24353	167	67	14	14	NUM
brj-24353	167	68	15	15	NUM
brj-24353	167	69	16	16	NUM
brj-24353	167	70	specular	specular	ADJ
brj-24353	167	71	86.67	86.67	NUM
brj-24353	167	72	%	%	NOUN
brj-24353	167	73	86.67	86.67	NUM
brj-24353	167	74	%	%	NOUN
brj-24353	167	75	100	100	NUM
brj-24353	167	76	%	%	NOUN
brj-24353	167	77	60	60	NUM
brj-24353	167	78	%	%	NOUN
brj-24353	167	79	100	100	NUM
brj-24353	167	80	%	%	NOUN
brj-24353	167	81	66.67	66.67	NUM
brj-24353	167	82	%	%	NOUN
brj-24353	167	83	93.33	93.33	NUM
brj-24353	167	84	%	%	NOUN
brj-24353	167	85	93.33	93.33	NUM
brj-24353	167	86	%	%	NOUN
brj-24353	167	87	diffuse	diffuse	NOUN
brj-24353	167	88	80	80	NUM
brj-24353	167	89	%	%	NOUN
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brj-24353	167	91	%	%	NOUN
brj-24353	167	92	93.33	93.33	NUM
brj-24353	167	93	%	%	NOUN
brj-24353	167	94	100	100	NUM
brj-24353	167	95	%	%	NOUN
brj-24353	167	96	93.33	93.33	NUM
brj-24353	167	97	%	%	NOUN
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brj-24353	167	99	%	%	NOUN
brj-24353	167	100	86.67	86.67	NUM
brj-24353	167	101	%	%	NOUN
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brj-24353	167	103	%	%	NOUN
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brj-24353	167	113	24	24	NUM
brj-24353	167	114	specular	specular	ADJ
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brj-24353	167	116	%	%	NOUN
brj-24353	167	117	86.67	86.67	NUM
brj-24353	167	118	%	%	NOUN
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brj-24353	167	120	%	%	NOUN
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brj-24353	167	122	%	%	NOUN
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brj-24353	167	124	%	%	NOUN
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brj-24353	167	126	%	%	NOUN
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brj-24353	167	128	%	%	NOUN
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brj-24353	167	130	%	%	NOUN
brj-24353	167	131	diffuse	diffuse	NOUN
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brj-24353	167	134	93.33	93.33	NUM
brj-24353	167	135	%	%	NOUN
brj-24353	167	136	73.33	73.33	NUM
brj-24353	167	137	%	%	NOUN
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brj-24353	167	139	%	%	NOUN
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brj-24353	167	141	%	%	NOUN
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brj-24353	167	143	%	%	NOUN
brj-24353	167	144	73.33	73.33	NUM
brj-24353	167	145	%	%	NOUN
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brj-24353	167	147	%	%	NOUN
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brj-24353	167	150	25	25	NUM
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brj-24353	167	160	%	%	NOUN
brj-24353	167	161	86.67	86.67	NUM
brj-24353	167	162	%	%	NOUN
brj-24353	167	163	86.67	86.67	NUM
brj-24353	167	164	%	%	NOUN
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brj-24353	167	166	%	%	NOUN
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brj-24353	167	170	%	%	NOUN
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brj-24353	167	172	%	%	NOUN
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brj-24353	167	178	66.67	66.67	NUM
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brj-24353	167	183	%	%	NOUN
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brj-24353	167	185	%	%	NOUN
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brj-24353	167	189	%	%	NOUN
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brj-24353	167	204	%	%	NOUN
brj-24353	167	205	100	100	NUM
brj-24353	167	206	%	%	NOUN
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brj-24353	167	212	%	%	NOUN
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brj-24353	167	214	%	%	NOUN
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brj-24353	167	216	%	%	NOUN
brj-24353	167	217	86.67	86.67	NUM
brj-24353	167	218	%	%	NOUN
brj-24353	167	219	diffuse	diffuse	NOUN
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brj-24353	167	221	%	%	NOUN
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brj-24353	167	223	%	%	NOUN
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brj-24353	167	225	%	%	NOUN
brj-24353	167	226	93.33	93.33	NUM
brj-24353	167	227	%	%	NOUN
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brj-24353	167	229	%	%	NOUN
brj-24353	167	230	80	80	NUM
brj-24353	167	231	%	%	NOUN
brj-24353	167	232	73.33	73.33	NUM
brj-24353	167	233	%	%	NOUN
brj-24353	167	234	66.67	66.67	NUM
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brj-24353	167	248	%	%	NOUN
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brj-24353	167	250	%	%	NOUN
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brj-24353	167	252	%	%	NOUN
brj-24353	167	253	100	100	NUM
brj-24353	167	254	%	%	NOUN
brj-24353	167	255	93.33	93.33	NUM
brj-24353	167	256	%	%	NOUN
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brj-24353	167	258	%	%	NOUN
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brj-24353	167	265	%	%	NOUN
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brj-24353	167	267	%	%	NOUN
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brj-24353	167	296	%	%	NOUN
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brj-24353	167	300	%	%	NOUN
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brj-24353	167	302	%	%	NOUN
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brj-24353	167	304	%	%	NOUN
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brj-24353	167	306	%	%	NOUN
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brj-24353	167	315	%	%	NOUN
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brj-24353	167	317	%	%	NOUN
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brj-24353	167	319	%	%	NOUN
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brj-24353	167	321	%	%	NOUN
brj-24353	167	322	93.33	93.33	NUM
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brj-24353	167	331	62	62	NUM
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brj-24353	167	335	100	100	NUM
brj-24353	167	336	%	%	NOUN
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brj-24353	167	338	%	%	NOUN
brj-24353	167	339	86.67	86.67	NUM
brj-24353	167	340	%	%	NOUN
brj-24353	167	341	100	100	NUM
brj-24353	167	342	%	%	NOUN
brj-24353	167	343	100	100	NUM
brj-24353	167	344	%	%	NOUN
brj-24353	167	345	93.33	93.33	NUM
brj-24353	167	346	%	%	NOUN
brj-24353	167	347	100	100	NUM
brj-24353	167	348	%	%	NOUN
brj-24353	167	349	100	100	NUM
brj-24353	167	350	%	%	NOUN
brj-24353	167	351	diffuse	diffuse	NOUN
brj-24353	167	352	93.33	93.33	NUM
brj-24353	167	353	%	%	NOUN
brj-24353	167	354	93.33	93.33	NUM
brj-24353	167	355	%	%	NOUN
brj-24353	167	356	93.33	93.33	NUM
brj-24353	167	357	%	%	NOUN
brj-24353	167	358	100	100	NUM
brj-24353	167	359	%	%	NOUN
brj-24353	167	360	33.33	33.33	NUM
brj-24353	167	361	%	%	NOUN
brj-24353	167	362	66.67	66.67	NUM
brj-24353	167	363	%	%	NOUN
brj-24353	167	364	100	100	NUM
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brj-24353	167	367	%	%	NOUN
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brj-24353	167	375	species	specie	NOUN
brj-24353	167	376	in	in	ADP
brj-24353	167	377	the	the	DET
brj-24353	167	378	specular	specular	ADJ
brj-24353	167	379	reflectance	reflectance	NOUN
brj-24353	167	380	spectra	spectra	NOUN
brj-24353	167	381	and	and	CCONJ
brj-24353	167	382	16	16	NUM
brj-24353	167	383	species	specie	NOUN
brj-24353	167	384	in	in	ADP
brj-24353	167	385	the	the	DET
brj-24353	167	386	diffuse	diffuse	NOUN
brj-24353	167	387	reflectance	reflectance	NOUN
brj-24353	167	388	spectra	spectra	NOUN
brj-24353	167	389	achieved	achieve	VERB
brj-24353	167	390	100	100	NUM
brj-24353	167	391	%	%	NOUN
brj-24353	167	392	classification	classification	NOUN
brj-24353	167	393	accuracy	accuracy	NOUN
brj-24353	167	394	.	.	PUNCT
brj-24353	168	1	in	in	ADP
brj-24353	168	2	the	the	DET
brj-24353	168	3	specular	specular	ADJ
brj-24353	168	4	reflectance	reflectance	NOUN
brj-24353	168	5	spectra	spectra	NOUN
brj-24353	168	6	,	,	PUNCT
brj-24353	168	7	species	specie	NOUN
brj-24353	168	8	19	19	NUM
brj-24353	168	9	,	,	PUNCT
brj-24353	168	10	50	50	NUM
brj-24353	168	11	,	,	PUNCT
brj-24353	168	12	and	and	CCONJ
brj-24353	168	13	53	53	NUM
brj-24353	168	14	exhibited	exhibit	VERB
brj-24353	168	15	lower	low	ADJ
brj-24353	168	16	classification	classification	NOUN
brj-24353	168	17	accuracy	accuracy	NOUN
brj-24353	168	18	.	.	PUNCT
brj-24353	169	1	a	a	DET
brj-24353	169	2	common	common	ADJ
brj-24353	169	3	characteristic	characteristic	NOUN
brj-24353	169	4	of	of	ADP
brj-24353	169	5	these	these	DET
brj-24353	169	6	species	specie	NOUN
brj-24353	169	7	is	be	AUX
brj-24353	169	8	the	the	DET
brj-24353	169	9	distinct	distinct	ADJ
brj-24353	169	10	color	color	NOUN
brj-24353	169	11	variation	variation	NOUN
brj-24353	169	12	bands	band	NOUN
brj-24353	169	13	in	in	ADP
brj-24353	169	14	the	the	DET
brj-24353	169	15	cross	cross	NOUN
brj-24353	169	16	sections	section	NOUN
brj-24353	169	17	of	of	ADP
brj-24353	169	18	the	the	DET
brj-24353	169	19	wood	wood	NOUN
brj-24353	169	20	samples	sample	NOUN
brj-24353	169	21	,	,	PUNCT
brj-24353	169	22	as	as	SCONJ
brj-24353	169	23	illustrated	illustrate	VERB
brj-24353	169	24	in	in	ADP
brj-24353	169	25	(	(	PUNCT
brj-24353	169	26	fig	fig	NOUN
brj-24353	169	27	.	.	PUNCT
brj-24353	170	1	7	7	NUM
brj-24353	170	2	)	)	PUNCT
brj-24353	170	3	.	.	PUNCT
brj-24353	171	1	in	in	ADP
brj-24353	171	2	the	the	DET
brj-24353	171	3	diffuse	diffuse	PROPN
brj-24353	171	4	reflectance	reflectance	NOUN
brj-24353	171	5	spectra	spectra	NOUN
brj-24353	171	6	,	,	PUNCT
brj-24353	171	7	species	specie	NOUN
brj-24353	171	8	35	35	NUM
brj-24353	171	9	,	,	PUNCT
brj-24353	171	10	43	43	NUM
brj-24353	171	11	,	,	PUNCT
brj-24353	171	12	and	and	CCONJ
brj-24353	171	13	61	61	NUM
brj-24353	171	14	exhibited	exhibit	VERB
brj-24353	171	15	lower	low	ADJ
brj-24353	171	16	classification	classification	NOUN
brj-24353	171	17	accuracy	accuracy	NOUN
brj-24353	171	18	.	.	PUNCT
brj-24353	172	1	these	these	DET
brj-24353	172	2	species	specie	NOUN
brj-24353	172	3	can	can	AUX
brj-24353	172	4	be	be	AUX
brj-24353	172	5	grouped	group	VERB
brj-24353	172	6	into	into	ADP
brj-24353	172	7	two	two	NUM
brj-24353	172	8	categories	category	NOUN
brj-24353	172	9	—	—	PUNCT
brj-24353	172	10	that	that	ADV
brj-24353	172	11	is	is	ADV
brj-24353	172	12	,	,	PUNCT
brj-24353	172	13	species	specie	NOUN
brj-24353	172	14	with	with	ADP
brj-24353	172	15	considerable	considerable	ADJ
brj-24353	172	16	variation	variation	NOUN
brj-24353	172	17	in	in	ADP
brj-24353	172	18	black	black	ADJ
brj-24353	172	19	tubular	tubular	ADJ
brj-24353	172	20	holes	hole	NOUN
brj-24353	172	21	in	in	ADP
brj-24353	172	22	the	the	DET
brj-24353	172	23	cross	cross	NOUN
brj-24353	172	24	section	section	NOUN
brj-24353	172	25	(	(	PUNCT
brj-24353	172	26	such	such	ADJ
brj-24353	172	27	as	as	ADP
brj-24353	172	28	species	specie	NOUN
brj-24353	172	29	35	35	NUM
brj-24353	172	30	and	and	CCONJ
brj-24353	172	31	43	43	NUM
brj-24353	172	32	)	)	PUNCT
brj-24353	172	33	,	,	PUNCT
brj-24353	172	34	species	specie	NOUN
brj-24353	172	35	with	with	ADP
brj-24353	172	36	more	more	ADJ
brj-24353	172	37	uniform	uniform	ADJ
brj-24353	172	38	color	color	NOUN
brj-24353	172	39	in	in	ADP
brj-24353	172	40	the	the	DET
brj-24353	172	41	cross	cross	NOUN
brj-24353	172	42	section	section	NOUN
brj-24353	172	43	,	,	PUNCT
brj-24353	172	44	and	and	CCONJ
brj-24353	172	45	less	less	ADV
brj-24353	172	46	distinct	distinct	ADJ
brj-24353	172	47	grain	grain	NOUN
brj-24353	172	48	features	feature	NOUN
brj-24353	172	49	(	(	PUNCT
brj-24353	172	50	such	such	ADJ
brj-24353	172	51	as	as	ADP
brj-24353	172	52	species	specie	NOUN
brj-24353	172	53	61	61	NUM
brj-24353	172	54	)	)	PUNCT
brj-24353	172	55	.	.	PUNCT
brj-24353	173	1	figure	figure	NOUN
brj-24353	173	2	7	7	NUM
brj-24353	173	3	illustrates	illustrate	VERB
brj-24353	173	4	the	the	DET
brj-24353	173	5	schematic	schematic	PROPN
brj-24353	173	6	cross	cross	NOUN
brj-24353	173	7	sections	section	NOUN
brj-24353	173	8	of	of	ADP
brj-24353	173	9	these	these	DET
brj-24353	173	10	wood	wood	NOUN
brj-24353	173	11	species	specie	NOUN
brj-24353	173	12	.	.	PUNCT
brj-24353	174	1	no	no	INTJ
brj-24353	174	2	.	.	NOUN
brj-24353	175	1	19	19	NUM
brj-24353	175	2	.	.	PUNCT
brj-24353	176	1	no	no	INTJ
brj-24353	176	2	.	.	NOUN
brj-24353	177	1	50	50	NUM
brj-24353	177	2	.	.	PUNCT
brj-24353	178	1	no	no	INTJ
brj-24353	178	2	.	.	NOUN
brj-24353	179	1	53	53	NUM
brj-24353	179	2	.	.	PUNCT
brj-24353	180	1	no	no	INTJ
brj-24353	180	2	.	.	NOUN
brj-24353	181	1	35	35	NUM
brj-24353	181	2	.	.	PUNCT
brj-24353	182	1	no	no	INTJ
brj-24353	182	2	.	.	NOUN
brj-24353	183	1	43	43	NUM
brj-24353	183	2	.	.	PUNCT
brj-24353	184	1	no	no	INTJ
brj-24353	184	2	.	.	NOUN
brj-24353	184	3	61	61	NUM
brj-24353	184	4	.	.	X
brj-24353	184	5	fig	fig	NOUN
brj-24353	184	6	.	.	PUNCT
brj-24353	185	1	7	7	X
brj-24353	185	2	.	.	X
brj-24353	185	3	schematic	schematic	PROPN
brj-24353	185	4	cross	cross	NOUN
brj-24353	185	5	sections	section	NOUN
brj-24353	185	6	of	of	ADP
brj-24353	185	7	wood	wood	NOUN
brj-24353	185	8	species	specie	NOUN
brj-24353	185	9	with	with	ADP
brj-24353	185	10	low	low	ADJ
brj-24353	185	11	correct	correct	ADJ
brj-24353	185	12	classification	classification	NOUN
brj-24353	185	13	in	in	ADP
brj-24353	185	14	specular	specular	ADJ
brj-24353	185	15	and	and	CCONJ
brj-24353	185	16	diffuse	diffuse	VERB
brj-24353	185	17	reflectance	reflectance	NOUN
brj-24353	185	18	spectra	spectra	NOUN
brj-24353	185	19	additionally	additionally	ADV
brj-24353	185	20	,	,	PUNCT
brj-24353	185	21	three	three	NUM
brj-24353	185	22	tree	tree	NOUN
brj-24353	185	23	species	specie	NOUN
brj-24353	185	24	were	be	AUX
brj-24353	185	25	classified	classify	VERB
brj-24353	185	26	with	with	ADP
brj-24353	185	27	an	an	DET
brj-24353	185	28	accuracy	accuracy	NOUN
brj-24353	185	29	of	of	ADP
brj-24353	185	30	less	less	ADJ
brj-24353	185	31	than	than	ADP
brj-24353	185	32	50	50	NUM
brj-24353	185	33	%	%	NOUN
brj-24353	185	34	in	in	ADP
brj-24353	185	35	the	the	DET
brj-24353	185	36	specular	specular	ADJ
brj-24353	185	37	reflectance	reflectance	NOUN
brj-24353	185	38	spectrum	spectrum	NOUN
brj-24353	185	39	,	,	PUNCT
brj-24353	185	40	whereas	whereas	SCONJ
brj-24353	185	41	only	only	ADV
brj-24353	185	42	one	one	NUM
brj-24353	185	43	species	specie	NOUN
brj-24353	185	44	had	have	VERB
brj-24353	185	45	an	an	DET
brj-24353	185	46	accuracy	accuracy	NOUN
brj-24353	185	47	of	of	ADP
brj-24353	185	48	less	less	ADJ
brj-24353	185	49	than	than	ADP
brj-24353	185	50	50	50	NUM
brj-24353	185	51	%	%	NOUN
brj-24353	185	52	in	in	ADP
brj-24353	185	53	the	the	DET
brj-24353	185	54	diffuse	diffuse	NOUN
brj-24353	185	55	reflectance	reflectance	NOUN
brj-24353	185	56	spectrum	spectrum	NOUN
brj-24353	185	57	.	.	PUNCT
brj-24353	186	1	in	in	ADP
brj-24353	186	2	other	other	ADJ
brj-24353	186	3	words	word	NOUN
brj-24353	186	4	,	,	PUNCT
brj-24353	186	5	although	although	SCONJ
brj-24353	186	6	the	the	DET
brj-24353	186	7	overall	overall	ADJ
brj-24353	186	8	classification	classification	NOUN
brj-24353	186	9	accuracy	accuracy	NOUN
brj-24353	186	10	of	of	ADP
brj-24353	186	11	the	the	DET
brj-24353	186	12	specular	specular	ADJ
brj-24353	186	13	reflectance	reflectance	NOUN
brj-24353	186	14	spectrum	spectrum	NOUN
brj-24353	186	15	was	be	AUX
brj-24353	186	16	slightly	slightly	ADV
brj-24353	186	17	higher	high	ADJ
brj-24353	186	18	than	than	ADP
brj-24353	186	19	that	that	PRON
brj-24353	186	20	of	of	ADP
brj-24353	186	21	the	the	DET
brj-24353	186	22	diffuse	diffuse	PROPN
brj-24353	186	23	peer	peer	NOUN
brj-24353	186	24	-	-	PUNCT
brj-24353	186	25	reviewed	review	VERB
brj-24353	186	26	article	article	NOUN
brj-24353	186	27	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	186	28	wang	wang	PROPN
brj-24353	186	29	et	et	PROPN
brj-24353	186	30	al	al	PROPN
brj-24353	186	31	.	.	PROPN
brj-24353	187	1	(	(	PUNCT
brj-24353	187	2	2025	2025	NUM
brj-24353	187	3	)	)	PUNCT
brj-24353	187	4	.	.	PUNCT
brj-24353	188	1	“	"	PUNCT
brj-24353	188	2	wood	wood	NOUN
brj-24353	188	3	i	i	X
brj-24353	188	4	d	d	PROPN
brj-24353	188	5	via	via	ADP
brj-24353	188	6	.	.	PUNCT
brj-24353	189	1	s	s	PROPN
brj-24353	189	2	-	-	PUNCT
brj-24353	189	3	nir	nir	PROPN
brj-24353	189	4	&	&	CCONJ
brj-24353	189	5	dr	dr	PROPN
brj-24353	189	6	-	-	PUNCT
brj-24353	189	7	nir	nir	PROPN
brj-24353	189	8	,	,	PUNCT
brj-24353	189	9	”	"	PUNCT
brj-24353	189	10	bioresources	bioresource	NOUN
brj-24353	189	11	20(3	20(3	NOUN
brj-24353	189	12	)	)	PUNCT
brj-24353	189	13	,	,	PUNCT
brj-24353	189	14	6648	6648	NUM
brj-24353	189	15	-	-	SYM
brj-24353	189	16	6661	6661	NUM
brj-24353	189	17	.	.	PUNCT
brj-24353	190	1	6658	6658	NUM
brj-24353	190	2	reflectance	reflectance	NOUN
brj-24353	190	3	spectrum	spectrum	NOUN
brj-24353	190	4	,	,	PUNCT
brj-24353	190	5	the	the	DET
brj-24353	190	6	accuracy	accuracy	NOUN
brj-24353	190	7	was	be	AUX
brj-24353	190	8	lower	low	ADJ
brj-24353	190	9	for	for	ADP
brj-24353	190	10	species	specie	NOUN
brj-24353	190	11	with	with	ADP
brj-24353	190	12	distinct	distinct	ADJ
brj-24353	190	13	color	color	NOUN
brj-24353	190	14	bands	band	NOUN
brj-24353	190	15	in	in	ADP
brj-24353	190	16	wood	wood	NOUN
brj-24353	190	17	sample	sample	PROPN
brj-24353	190	18	cross	cross	NOUN
brj-24353	190	19	sections	section	NOUN
brj-24353	190	20	.	.	PUNCT
brj-24353	191	1	in	in	ADP
brj-24353	191	2	contrast	contrast	NOUN
brj-24353	191	3	,	,	PUNCT
brj-24353	191	4	the	the	DET
brj-24353	191	5	diffuse	diffuse	NOUN
brj-24353	191	6	reflectance	reflectance	NOUN
brj-24353	191	7	spectrum	spectrum	NOUN
brj-24353	191	8	exhibited	exhibit	VERB
brj-24353	191	9	a	a	DET
brj-24353	191	10	more	more	ADV
brj-24353	191	11	stable	stable	ADJ
brj-24353	191	12	classification	classification	NOUN
brj-24353	191	13	performance	performance	NOUN
brj-24353	191	14	,	,	PUNCT
brj-24353	191	15	with	with	ADP
brj-24353	191	16	fewer	few	ADJ
brj-24353	191	17	species	specie	NOUN
brj-24353	191	18	exhibiting	exhibit	VERB
brj-24353	191	19	low	low	ADJ
brj-24353	191	20	classification	classification	NOUN
brj-24353	191	21	accuracy	accuracy	NOUN
brj-24353	191	22	.	.	PUNCT
brj-24353	192	1	next	next	ADV
brj-24353	192	2	,	,	PUNCT
brj-24353	192	3	the	the	DET
brj-24353	192	4	classification	classification	NOUN
brj-24353	192	5	accuracy	accuracy	NOUN
brj-24353	192	6	of	of	ADP
brj-24353	192	7	the	the	DET
brj-24353	192	8	nir	nir	ADJ
brj-24353	192	9	spectra	spectra	NOUN
brj-24353	192	10	across	across	ADP
brj-24353	192	11	different	different	ADJ
brj-24353	192	12	wavelength	wavelength	NOUN
brj-24353	192	13	bands	band	NOUN
brj-24353	192	14	was	be	AUX
brj-24353	192	15	explored	explore	VERB
brj-24353	192	16	.	.	PUNCT
brj-24353	193	1	from	from	ADP
brj-24353	193	2	fig	fig	NOUN
brj-24353	193	3	.	.	PUNCT
brj-24353	194	1	5	5	NUM
brj-24353	194	2	it	it	PRON
brj-24353	194	3	is	be	AUX
brj-24353	194	4	evident	evident	ADJ
brj-24353	194	5	that	that	SCONJ
brj-24353	194	6	the	the	DET
brj-24353	194	7	spectral	spectral	ADJ
brj-24353	194	8	reflectance	reflectance	NOUN
brj-24353	194	9	curves	curve	NOUN
brj-24353	194	10	of	of	ADP
brj-24353	194	11	the	the	DET
brj-24353	194	12	cross	cross	NOUN
brj-24353	194	13	sections	section	NOUN
brj-24353	194	14	of	of	ADP
brj-24353	194	15	the	the	DET
brj-24353	194	16	wood	wood	NOUN
brj-24353	194	17	samples	sample	NOUN
brj-24353	194	18	exhibited	exhibit	VERB
brj-24353	194	19	more	more	ADJ
brj-24353	194	20	complex	complex	ADJ
brj-24353	194	21	waveform	waveform	NOUN
brj-24353	194	22	changes	change	NOUN
brj-24353	194	23	within	within	ADP
brj-24353	194	24	the	the	DET
brj-24353	194	25	1200	1200	NUM
brj-24353	194	26	to	to	ADP
brj-24353	194	27	1500	1500	NUM
brj-24353	194	28	nm	nm	ADJ
brj-24353	194	29	range	range	NOUN
brj-24353	194	30	,	,	PUNCT
brj-24353	194	31	whereas	whereas	SCONJ
brj-24353	194	32	they	they	PRON
brj-24353	194	33	remained	remain	VERB
brj-24353	194	34	smoother	smooth	ADJ
brj-24353	194	35	in	in	ADP
brj-24353	194	36	other	other	ADJ
brj-24353	194	37	wavelength	wavelength	NOUN
brj-24353	194	38	ranges	range	NOUN
brj-24353	194	39	.	.	PUNCT
brj-24353	195	1	consequently	consequently	ADV
brj-24353	195	2	,	,	PUNCT
brj-24353	195	3	the	the	DET
brj-24353	195	4	entire	entire	ADJ
brj-24353	195	5	spectral	spectral	ADJ
brj-24353	195	6	reflectance	reflectance	NOUN
brj-24353	195	7	curve	curve	NOUN
brj-24353	195	8	could	could	AUX
brj-24353	195	9	be	be	AUX
brj-24353	195	10	divided	divide	VERB
brj-24353	195	11	into	into	ADP
brj-24353	195	12	three	three	NUM
brj-24353	195	13	bands	band	NOUN
brj-24353	195	14	—	—	PUNCT
brj-24353	195	15	that	that	ADV
brj-24353	195	16	is	is	ADV
brj-24353	195	17	,	,	PUNCT
brj-24353	195	18	the	the	DET
brj-24353	195	19	939	939	NUM
brj-24353	195	20	to	to	ADP
brj-24353	195	21	1181	1181	NUM
brj-24353	195	22	,	,	PUNCT
brj-24353	195	23	1186	1186	NUM
brj-24353	195	24	to	to	ADP
brj-24353	195	25	1423	1423	NUM
brj-24353	195	26	,	,	PUNCT
brj-24353	195	27	and	and	CCONJ
brj-24353	195	28	1428	1428	NUM
brj-24353	195	29	to	to	ADP
brj-24353	195	30	1671	1671	NUM
brj-24353	195	31	nm	nm	NOUN
brj-24353	195	32	bands	band	NOUN
brj-24353	195	33	.	.	PUNCT
brj-24353	196	1	table	table	NOUN
brj-24353	196	2	5	5	NUM
brj-24353	196	3	presents	present	VERB
brj-24353	196	4	the	the	DET
brj-24353	196	5	classification	classification	NOUN
brj-24353	196	6	accuracies	accuracy	NOUN
brj-24353	196	7	of	of	ADP
brj-24353	196	8	different	different	ADJ
brj-24353	196	9	classifiers	classifier	NOUN
brj-24353	196	10	for	for	ADP
brj-24353	196	11	these	these	DET
brj-24353	196	12	wavelength	wavelength	NOUN
brj-24353	196	13	bands	band	NOUN
brj-24353	196	14	.	.	PUNCT
brj-24353	197	1	from	from	ADP
brj-24353	197	2	table	table	NOUN
brj-24353	197	3	5	5	NUM
brj-24353	197	4	,	,	PUNCT
brj-24353	197	5	it	it	PRON
brj-24353	197	6	is	be	AUX
brj-24353	197	7	evident	evident	ADJ
brj-24353	197	8	that	that	SCONJ
brj-24353	197	9	the	the	DET
brj-24353	197	10	classification	classification	NOUN
brj-24353	197	11	performance	performance	NOUN
brj-24353	197	12	of	of	ADP
brj-24353	197	13	the	the	DET
brj-24353	197	14	svm	svm	ADJ
brj-24353	197	15	classifier	classifier	NOUN
brj-24353	197	16	in	in	ADP
brj-24353	197	17	the	the	DET
brj-24353	197	18	two	two	NUM
brj-24353	197	19	end	end	NOUN
brj-24353	197	20	bands	band	NOUN
brj-24353	197	21	was	be	AUX
brj-24353	197	22	inferior	inferior	ADJ
brj-24353	197	23	to	to	ADP
brj-24353	197	24	that	that	PRON
brj-24353	197	25	in	in	ADP
brj-24353	197	26	the	the	DET
brj-24353	197	27	middle	middle	ADJ
brj-24353	197	28	band	band	NOUN
brj-24353	197	29	.	.	PUNCT
brj-24353	198	1	additionally	additionally	ADV
brj-24353	198	2	,	,	PUNCT
brj-24353	198	3	after	after	ADP
brj-24353	198	4	segmenting	segment	VERB
brj-24353	198	5	the	the	DET
brj-24353	198	6	entire	entire	ADJ
brj-24353	198	7	spectral	spectral	ADJ
brj-24353	198	8	band	band	NOUN
brj-24353	198	9	into	into	ADP
brj-24353	198	10	three	three	NUM
brj-24353	198	11	parts	part	NOUN
brj-24353	198	12	,	,	PUNCT
brj-24353	198	13	the	the	DET
brj-24353	198	14	classification	classification	NOUN
brj-24353	198	15	accuracy	accuracy	NOUN
brj-24353	198	16	decreased	decrease	VERB
brj-24353	198	17	compared	compare	VERB
brj-24353	198	18	with	with	ADP
brj-24353	198	19	that	that	PRON
brj-24353	198	20	of	of	ADP
brj-24353	198	21	the	the	DET
brj-24353	198	22	original	original	ADJ
brj-24353	198	23	unsegmented	unsegmente	VERB
brj-24353	198	24	band	band	NOUN
brj-24353	198	25	.	.	PUNCT
brj-24353	199	1	all	all	DET
brj-24353	199	2	classifiers	classifier	NOUN
brj-24353	199	3	,	,	PUNCT
brj-24353	199	4	except	except	SCONJ
brj-24353	199	5	the	the	DET
brj-24353	199	6	svm	svm	PROPN
brj-24353	199	7	,	,	PUNCT
brj-24353	199	8	exhibited	exhibit	VERB
brj-24353	199	9	higher	high	ADJ
brj-24353	199	10	classification	classification	NOUN
brj-24353	199	11	accuracy	accuracy	NOUN
brj-24353	199	12	for	for	ADP
brj-24353	199	13	the	the	DET
brj-24353	199	14	specular	specular	ADJ
brj-24353	199	15	reflectance	reflectance	NOUN
brj-24353	199	16	spectrum	spectrum	NOUN
brj-24353	199	17	than	than	ADP
brj-24353	199	18	for	for	ADP
brj-24353	199	19	the	the	DET
brj-24353	199	20	diffuse	diffuse	NOUN
brj-24353	199	21	reflectance	reflectance	NOUN
brj-24353	199	22	spectrum	spectrum	NOUN
brj-24353	199	23	across	across	ADP
brj-24353	199	24	different	different	ADJ
brj-24353	199	25	bands	band	NOUN
brj-24353	199	26	.	.	PUNCT
brj-24353	200	1	it	it	PRON
brj-24353	200	2	is	be	AUX
brj-24353	200	3	worth	worth	ADJ
brj-24353	200	4	noting	note	VERB
brj-24353	200	5	that	that	SCONJ
brj-24353	200	6	the	the	DET
brj-24353	200	7	cnn	cnn	PROPN
brj-24353	200	8	classifier	classifier	NOUN
brj-24353	200	9	was	be	AUX
brj-24353	200	10	not	not	PART
brj-24353	200	11	included	include	VERB
brj-24353	200	12	in	in	ADP
brj-24353	200	13	table	table	NOUN
brj-24353	200	14	5	5	NUM
brj-24353	200	15	because	because	SCONJ
brj-24353	200	16	each	each	DET
brj-24353	200	17	segmented	segment	VERB
brj-24353	200	18	band	band	NOUN
brj-24353	200	19	contained	contain	VERB
brj-24353	200	20	only	only	ADV
brj-24353	200	21	42	42	NUM
brj-24353	200	22	dimensions	dimension	NOUN
brj-24353	200	23	.	.	PUNCT
brj-24353	201	1	following	follow	VERB
brj-24353	201	2	feature	feature	NOUN
brj-24353	201	3	extraction	extraction	NOUN
brj-24353	201	4	using	use	VERB
brj-24353	201	5	a	a	DET
brj-24353	201	6	cnn	cnn	NOUN
brj-24353	201	7	,	,	PUNCT
brj-24353	201	8	the	the	DET
brj-24353	201	9	feature	feature	NOUN
brj-24353	201	10	dimensions	dimension	NOUN
brj-24353	201	11	were	be	AUX
brj-24353	201	12	reduced	reduce	VERB
brj-24353	201	13	to	to	ADP
brj-24353	201	14	only	only	ADV
brj-24353	201	15	two	two	NUM
brj-24353	201	16	,	,	PUNCT
brj-24353	201	17	limiting	limit	VERB
brj-24353	201	18	its	its	PRON
brj-24353	201	19	utility	utility	NOUN
brj-24353	201	20	in	in	ADP
brj-24353	201	21	this	this	DET
brj-24353	201	22	context	context	NOUN
brj-24353	201	23	.	.	PUNCT
brj-24353	202	1	table	table	NOUN
brj-24353	202	2	5	5	NUM
brj-24353	202	3	.	.	PUNCT
brj-24353	202	4	comparison	comparison	NOUN
brj-24353	202	5	of	of	ADP
brj-24353	202	6	classification	classification	NOUN
brj-24353	202	7	accuracies	accuracy	NOUN
brj-24353	202	8	of	of	ADP
brj-24353	202	9	specular	specular	ADJ
brj-24353	202	10	and	and	CCONJ
brj-24353	202	11	diffuse	diffuse	VERB
brj-24353	202	12	reflectance	reflectance	NOUN
brj-24353	202	13	spectra	spectra	NOUN
brj-24353	202	14	across	across	ADP
brj-24353	202	15	different	different	ADJ
brj-24353	202	16	wavelength	wavelength	NOUN
brj-24353	202	17	bands	band	NOUN
brj-24353	202	18	model	model	VERB
brj-24353	202	19	specular	specular	ADJ
brj-24353	202	20	reflection	reflection	NOUN
brj-24353	202	21	939	939	NUM
brj-24353	202	22	to	to	ADP
brj-24353	202	23	1181	1181	NUM
brj-24353	202	24	nm	nm	NOUN
brj-24353	202	25	1186	1186	NUM
brj-24353	202	26	to	to	ADP
brj-24353	202	27	1423	1423	NUM
brj-24353	202	28	nm	nm	ADV
brj-24353	202	29	1428	1428	NUM
brj-24353	202	30	to	to	ADP
brj-24353	202	31	1671	1671	NUM
brj-24353	202	32	nm	nm	NOUN
brj-24353	202	33	svm	svm	NOUN
brj-24353	202	34	74.24	74.24	NUM
brj-24353	202	35	%	%	NOUN
brj-24353	202	36	74.75	74.75	NUM
brj-24353	202	37	%	%	NOUN
brj-24353	202	38	65.00	65.00	NUM
brj-24353	202	39	%	%	NOUN
brj-24353	202	40	knn	knn	NOUN
brj-24353	202	41	72.71	72.71	NUM
brj-24353	202	42	%	%	NOUN
brj-24353	202	43	40.31	40.31	NUM
brj-24353	202	44	%	%	NOUN
brj-24353	202	45	74.17	74.17	NUM
brj-24353	202	46	%	%	NOUN
brj-24353	202	47	dt	dt	X
brj-24353	202	48	53.90	53.90	NUM
brj-24353	202	49	%	%	NOUN
brj-24353	202	50	48.70	48.70	NUM
brj-24353	202	51	%	%	NOUN
brj-24353	202	52	45.00	45.00	NUM
brj-24353	202	53	%	%	NOUN
brj-24353	202	54	ncm	ncm	NOUN
brj-24353	202	55	49.48	49.48	NUM
brj-24353	202	56	%	%	NOUN
brj-24353	202	57	42.81	42.81	NUM
brj-24353	202	58	%	%	NOUN
brj-24353	202	59	42.92	42.92	NUM
brj-24353	202	60	%	%	NOUN
brj-24353	202	61	model	model	NOUN
brj-24353	202	62	diffuse	diffuse	PROPN
brj-24353	202	63	reflection	reflection	NOUN
brj-24353	202	64	939	939	NUM
brj-24353	202	65	to	to	ADP
brj-24353	202	66	1181	1181	NUM
brj-24353	202	67	nm	nm	NOUN
brj-24353	202	68	1186	1186	NUM
brj-24353	202	69	to	to	ADP
brj-24353	202	70	1423	1423	NUM
brj-24353	202	71	nm	nm	ADV
brj-24353	202	72	1428	1428	NUM
brj-24353	202	73	to	to	ADP
brj-24353	202	74	1671	1671	NUM
brj-24353	202	75	nm	nm	ADV
brj-24353	202	76	svm	svm	NOUN
brj-24353	202	77	69.34	69.34	NUM
brj-24353	202	78	%	%	NOUN
brj-24353	202	79	81.18	81.18	NUM
brj-24353	202	80	%	%	NOUN
brj-24353	202	81	67.22	67.22	NUM
brj-24353	202	82	%	%	NOUN
brj-24353	202	83	knn	knn	PROPN
brj-24353	202	84	67.60	67.60	NUM
brj-24353	202	85	%	%	NOUN
brj-24353	202	86	34.69	34.69	NUM
brj-24353	202	87	%	%	NOUN
brj-24353	202	88	72.08	72.08	NUM
brj-24353	202	89	%	%	NOUN
brj-24353	202	90	dt	dt	X
brj-24353	202	91	48.30	48.30	NUM
brj-24353	202	92	%	%	NOUN
brj-24353	202	93	43.50	43.50	NUM
brj-24353	202	94	%	%	NOUN
brj-24353	202	95	35.30	35.30	NUM
brj-24353	202	96	%	%	NOUN
brj-24353	202	97	ncm	ncm	PROPN
brj-24353	202	98	44.90	44.90	NUM
brj-24353	202	99	%	%	NOUN
brj-24353	202	100	34.79	34.79	NUM
brj-24353	202	101	%	%	NOUN
brj-24353	202	102	34.79	34.79	NUM
brj-24353	202	103	%	%	NOUN
brj-24353	202	104	cross	cross	NOUN
brj-24353	202	105	use	use	NOUN
brj-24353	202	106	of	of	ADP
brj-24353	202	107	classifier	classifier	NOUN
brj-24353	202	108	models	model	NOUN
brj-24353	202	109	trained	train	VERB
brj-24353	202	110	with	with	ADP
brj-24353	202	111	two	two	NUM
brj-24353	202	112	types	type	NOUN
brj-24353	202	113	of	of	ADP
brj-24353	202	114	spectra	spectra	NOUN
brj-24353	202	115	this	this	DET
brj-24353	202	116	section	section	NOUN
brj-24353	202	117	discusses	discuss	VERB
brj-24353	202	118	the	the	DET
brj-24353	202	119	feasibility	feasibility	NOUN
brj-24353	202	120	of	of	ADP
brj-24353	202	121	cross	cross	ADJ
brj-24353	202	122	-	-	ADJ
brj-24353	202	123	using	use	VERB
brj-24353	202	124	classifier	classifier	NOUN
brj-24353	202	125	models	model	NOUN
brj-24353	202	126	trained	train	VERB
brj-24353	202	127	with	with	ADP
brj-24353	202	128	specular	specular	ADJ
brj-24353	202	129	and	and	CCONJ
brj-24353	202	130	diffuse	diffuse	VERB
brj-24353	202	131	reflectance	reflectance	NOUN
brj-24353	202	132	spectra	spectra	NOUN
brj-24353	202	133	,	,	PUNCT
brj-24353	202	134	with	with	ADP
brj-24353	202	135	the	the	DET
brj-24353	202	136	specific	specific	ADJ
brj-24353	202	137	classification	classification	NOUN
brj-24353	202	138	results	result	NOUN
brj-24353	202	139	provided	provide	VERB
brj-24353	202	140	in	in	ADP
brj-24353	202	141	table	table	NOUN
brj-24353	202	142	6	6	NUM
brj-24353	202	143	.	.	PUNCT
brj-24353	203	1	it	it	PRON
brj-24353	203	2	is	be	AUX
brj-24353	203	3	evident	evident	ADJ
brj-24353	203	4	that	that	SCONJ
brj-24353	203	5	neither	neither	CCONJ
brj-24353	203	6	the	the	DET
brj-24353	203	7	classifier	classifier	PROPN
brj-24353	203	8	model	model	NOUN
brj-24353	203	9	trained	train	VERB
brj-24353	203	10	with	with	ADP
brj-24353	203	11	specular	specular	ADJ
brj-24353	203	12	reflectance	reflectance	NOUN
brj-24353	203	13	spectra	spectra	NOUN
brj-24353	203	14	,	,	PUNCT
brj-24353	203	15	nor	nor	CCONJ
brj-24353	203	16	the	the	DET
brj-24353	203	17	model	model	NOUN
brj-24353	203	18	trained	train	VERB
brj-24353	203	19	with	with	ADP
brj-24353	203	20	diffuse	diffuse	NOUN
brj-24353	203	21	reflectance	reflectance	NOUN
brj-24353	203	22	spectra	spectra	NOUN
brj-24353	203	23	can	can	AUX
brj-24353	203	24	be	be	AUX
brj-24353	203	25	used	use	VERB
brj-24353	203	26	interchangeably	interchangeably	ADV
brj-24353	203	27	.	.	PUNCT
brj-24353	204	1	in	in	ADP
brj-24353	204	2	terms	term	NOUN
brj-24353	204	3	of	of	ADP
brj-24353	204	4	classification	classification	NOUN
brj-24353	204	5	accuracy	accuracy	NOUN
brj-24353	204	6	,	,	PUNCT
brj-24353	204	7	the	the	DET
brj-24353	204	8	ncm	ncm	PROPN
brj-24353	204	9	classifier	classifier	NOUN
brj-24353	204	10	performed	perform	VERB
brj-24353	204	11	slightly	slightly	ADV
brj-24353	204	12	better	well	ADJ
brj-24353	204	13	than	than	ADP
brj-24353	204	14	the	the	DET
brj-24353	204	15	other	other	ADJ
brj-24353	204	16	classifiers	classifier	NOUN
brj-24353	204	17	;	;	PUNCT
brj-24353	204	18	however	however	ADV
brj-24353	204	19	,	,	PUNCT
brj-24353	204	20	all	all	DET
brj-24353	204	21	the	the	DET
brj-24353	204	22	classifiers	classifier	NOUN
brj-24353	204	23	exhibited	exhibit	VERB
brj-24353	204	24	accuracies	accuracy	NOUN
brj-24353	204	25	below	below	ADP
brj-24353	204	26	16	16	NUM
brj-24353	204	27	%	%	NOUN
brj-24353	204	28	.	.	PUNCT
brj-24353	205	1	this	this	PRON
brj-24353	205	2	was	be	AUX
brj-24353	205	3	due	due	ADJ
brj-24353	205	4	to	to	ADP
brj-24353	205	5	the	the	DET
brj-24353	205	6	sensitivity	sensitivity	NOUN
brj-24353	205	7	of	of	ADP
brj-24353	205	8	the	the	DET
brj-24353	205	9	spectral	spectral	ADJ
brj-24353	205	10	reflectance	reflectance	NOUN
brj-24353	205	11	curve	curve	NOUN
brj-24353	205	12	to	to	ADP
brj-24353	205	13	the	the	DET
brj-24353	205	14	surface	surface	NOUN
brj-24353	205	15	properties	property	NOUN
brj-24353	205	16	of	of	ADP
brj-24353	205	17	the	the	DET
brj-24353	205	18	object	object	NOUN
brj-24353	205	19	.	.	PUNCT
brj-24353	206	1	although	although	SCONJ
brj-24353	206	2	the	the	DET
brj-24353	206	3	specular	specular	ADJ
brj-24353	206	4	and	and	CCONJ
brj-24353	206	5	diffuse	diffuse	ADJ
brj-24353	206	6	reflectance	reflectance	NOUN
brj-24353	206	7	spectra	spectra	NOUN
brj-24353	206	8	exhibited	exhibit	VERB
brj-24353	206	9	similar	similar	ADJ
brj-24353	206	10	trends	trend	NOUN
brj-24353	206	11	(	(	PUNCT
brj-24353	206	12	mathematically	mathematically	ADV
brj-24353	206	13	expressible	expressible	ADJ
brj-24353	206	14	as	as	ADP
brj-24353	206	15	differentials	differential	NOUN
brj-24353	206	16	)	)	PUNCT
brj-24353	206	17	,	,	PUNCT
brj-24353	206	18	differences	difference	NOUN
brj-24353	206	19	in	in	ADP
brj-24353	206	20	their	their	PRON
brj-24353	206	21	values	value	NOUN
brj-24353	206	22	led	lead	VERB
brj-24353	206	23	to	to	ADP
brj-24353	206	24	considerably	considerably	ADV
brj-24353	206	25	lower	lower	VERB
brj-24353	206	26	classification	classification	NOUN
brj-24353	206	27	accuracy	accuracy	NOUN
brj-24353	206	28	when	when	SCONJ
brj-24353	206	29	the	the	DET
brj-24353	206	30	classifiers	classifier	NOUN
brj-24353	206	31	were	be	AUX
brj-24353	206	32	cross	cross	NOUN
brj-24353	206	33	used	use	VERB
brj-24353	206	34	.	.	PUNCT
brj-24353	207	1	consequently	consequently	ADV
brj-24353	207	2	,	,	PUNCT
brj-24353	207	3	when	when	SCONJ
brj-24353	207	4	collecting	collect	VERB
brj-24353	207	5	spectral	spectral	ADJ
brj-24353	207	6	profiles	profile	NOUN
brj-24353	207	7	of	of	ADP
brj-24353	207	8	wood	wood	NOUN
brj-24353	207	9	cross	cross	PROPN
brj-24353	207	10	sections	section	NOUN
brj-24353	207	11	,	,	PUNCT
brj-24353	207	12	it	it	PRON
brj-24353	207	13	is	be	AUX
brj-24353	207	14	essential	essential	ADJ
brj-24353	207	15	to	to	PART
brj-24353	207	16	distinguish	distinguish	VERB
brj-24353	207	17	between	between	ADP
brj-24353	207	18	diffuse	diffuse	NOUN
brj-24353	207	19	and	and	CCONJ
brj-24353	207	20	specular	specular	ADJ
brj-24353	207	21	reflectance	reflectance	NOUN
brj-24353	207	22	spectra	spectra	NOUN
brj-24353	207	23	.	.	PUNCT
brj-24353	208	1	the	the	DET
brj-24353	208	2	classifier	classifier	NOUN
brj-24353	208	3	models	model	NOUN
brj-24353	208	4	generated	generate	VERB
brj-24353	208	5	by	by	ADP
brj-24353	208	6	training	train	VERB
brj-24353	208	7	each	each	DET
brj-24353	208	8	type	type	NOUN
brj-24353	208	9	can	can	AUX
brj-24353	208	10	not	not	PART
brj-24353	208	11	be	be	AUX
brj-24353	208	12	used	use	VERB
brj-24353	208	13	interchangeably	interchangeably	ADV
brj-24353	208	14	.	.	PUNCT
brj-24353	209	1	peer	peer	NOUN
brj-24353	209	2	-	-	PUNCT
brj-24353	209	3	reviewed	review	VERB
brj-24353	209	4	article	article	NOUN
brj-24353	209	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	209	6	wang	wang	PROPN
brj-24353	209	7	et	et	PROPN
brj-24353	209	8	al	al	PROPN
brj-24353	209	9	.	.	PROPN
brj-24353	210	1	(	(	PUNCT
brj-24353	210	2	2025	2025	NUM
brj-24353	210	3	)	)	PUNCT
brj-24353	210	4	.	.	PUNCT
brj-24353	211	1	“	"	PUNCT
brj-24353	211	2	wood	wood	NOUN
brj-24353	211	3	i	i	X
brj-24353	211	4	d	d	PROPN
brj-24353	211	5	via	via	ADP
brj-24353	211	6	.	.	PUNCT
brj-24353	212	1	s	s	PROPN
brj-24353	212	2	-	-	PUNCT
brj-24353	212	3	nir	nir	PROPN
brj-24353	212	4	&	&	CCONJ
brj-24353	212	5	dr	dr	PROPN
brj-24353	212	6	-	-	PUNCT
brj-24353	212	7	nir	nir	PROPN
brj-24353	212	8	,	,	PUNCT
brj-24353	212	9	”	"	PUNCT
brj-24353	212	10	bioresources	bioresource	NOUN
brj-24353	212	11	20(3	20(3	NOUN
brj-24353	212	12	)	)	PUNCT
brj-24353	212	13	,	,	PUNCT
brj-24353	212	14	6648	6648	NUM
brj-24353	212	15	-	-	SYM
brj-24353	212	16	6661	6661	NUM
brj-24353	212	17	.	.	PUNCT
brj-24353	213	1	6659	6659	NUM
brj-24353	213	2	table	table	NOUN
brj-24353	213	3	6	6	NUM
brj-24353	213	4	.	.	PUNCT
brj-24353	213	5	comparison	comparison	NOUN
brj-24353	213	6	of	of	ADP
brj-24353	213	7	classification	classification	NOUN
brj-24353	213	8	accuracies	accuracy	NOUN
brj-24353	213	9	after	after	ADP
brj-24353	213	10	cross	cross	NOUN
brj-24353	213	11	use	use	NOUN
brj-24353	213	12	of	of	ADP
brj-24353	213	13	classifier	classifier	NOUN
brj-24353	213	14	models	model	NOUN
brj-24353	213	15	for	for	ADP
brj-24353	213	16	the	the	DET
brj-24353	213	17	two	two	NUM
brj-24353	213	18	spectral	spectral	ADJ
brj-24353	213	19	classes	class	NOUN
brj-24353	213	20	classifier	classifier	NOUN
brj-24353	213	21	models	model	NOUN
brj-24353	213	22	trained	train	VERB
brj-24353	213	23	on	on	ADP
brj-24353	213	24	specular	specular	ADJ
brj-24353	213	25	reflection	reflection	NOUN
brj-24353	213	26	spectrum	spectrum	NOUN
brj-24353	213	27	classifier	classifier	PROPN
brj-24353	213	28	model	model	PROPN
brj-24353	213	29	svm	svm	PROPN
brj-24353	213	30	knn	knn	PROPN
brj-24353	213	31	cnn	cnn	PROPN
brj-24353	213	32	dt	dt	PROPN
brj-24353	213	33	ncm	ncm	PROPN
brj-24353	213	34	diffuse	diffuse	PROPN
brj-24353	213	35	reflection	reflection	NOUN
brj-24353	213	36	12.08	12.08	NUM
brj-24353	213	37	%	%	NOUN
brj-24353	213	38	13.65	13.65	NUM
brj-24353	213	39	%	%	NOUN
brj-24353	213	40	12.80	12.80	NUM
brj-24353	213	41	%	%	NOUN
brj-24353	213	42	11.25	11.25	NUM
brj-24353	213	43	%	%	NOUN
brj-24353	213	44	15.94	15.94	NUM
brj-24353	213	45	%	%	NOUN
brj-24353	213	46	classifier	classifier	NOUN
brj-24353	213	47	model	model	NOUN
brj-24353	213	48	trained	train	VERB
brj-24353	213	49	on	on	ADP
brj-24353	213	50	diffuse	diffuse	NOUN
brj-24353	213	51	reflectance	reflectance	NOUN
brj-24353	213	52	spectrum	spectrum	NOUN
brj-24353	213	53	classifier	classifier	PROPN
brj-24353	213	54	model	model	PROPN
brj-24353	213	55	svm	svm	PROPN
brj-24353	213	56	knn	knn	PROPN
brj-24353	213	57	cnn	cnn	PROPN
brj-24353	214	1	dt	dt	PROPN
brj-24353	214	2	ncm	ncm	PROPN
brj-24353	214	3	specular	specular	ADJ
brj-24353	214	4	reflection	reflection	NOUN
brj-24353	214	5	13.12	13.12	NUM
brj-24353	214	6	%	%	NOUN
brj-24353	214	7	13.54	13.54	NUM
brj-24353	214	8	%	%	NOUN
brj-24353	214	9	11.40	11.40	NUM
brj-24353	214	10	%	%	NOUN
brj-24353	214	11	8.20	8.20	NUM
brj-24353	214	12	%	%	NOUN
brj-24353	214	13	12.08	12.08	NUM
brj-24353	214	14	%	%	NOUN
brj-24353	214	15	conclusions	conclusion	NOUN
brj-24353	214	16	in	in	ADP
brj-24353	214	17	this	this	DET
brj-24353	214	18	study	study	NOUN
brj-24353	214	19	,	,	PUNCT
brj-24353	214	20	the	the	DET
brj-24353	214	21	characteristics	characteristic	NOUN
brj-24353	214	22	of	of	ADP
brj-24353	214	23	the	the	DET
brj-24353	214	24	specular	specular	ADJ
brj-24353	214	25	and	and	CCONJ
brj-24353	214	26	diffuse	diffuse	VERB
brj-24353	214	27	reflectance	reflectance	NOUN
brj-24353	214	28	spectra	spectra	NOUN
brj-24353	214	29	from	from	ADP
brj-24353	214	30	the	the	DET
brj-24353	214	31	cross	cross	NOUN
brj-24353	214	32	sections	section	NOUN
brj-24353	214	33	of	of	ADP
brj-24353	214	34	timber	timber	NOUN
brj-24353	214	35	samples	sample	NOUN
brj-24353	214	36	were	be	AUX
brj-24353	214	37	examined	examine	VERB
brj-24353	214	38	,	,	PUNCT
brj-24353	214	39	along	along	ADP
brj-24353	214	40	with	with	ADP
brj-24353	214	41	a	a	DET
brj-24353	214	42	comparison	comparison	NOUN
brj-24353	214	43	of	of	ADP
brj-24353	214	44	their	their	PRON
brj-24353	214	45	classification	classification	NOUN
brj-24353	214	46	performance	performance	NOUN
brj-24353	214	47	in	in	ADP
brj-24353	214	48	identifying	identify	VERB
brj-24353	214	49	timber	timber	NOUN
brj-24353	214	50	species	specie	NOUN
brj-24353	214	51	using	use	VERB
brj-24353	214	52	nir	nir	ADJ
brj-24353	214	53	spectra	spectra	NOUN
brj-24353	214	54	.	.	PUNCT
brj-24353	215	1	a	a	DET
brj-24353	215	2	total	total	NOUN
brj-24353	215	3	of	of	ADP
brj-24353	215	4	64	64	NUM
brj-24353	215	5	experimental	experimental	ADJ
brj-24353	215	6	timber	timber	NOUN
brj-24353	215	7	samples	sample	NOUN
brj-24353	215	8	were	be	AUX
brj-24353	215	9	used	use	VERB
brj-24353	215	10	.	.	PUNCT
brj-24353	216	1	the	the	DET
brj-24353	216	2	following	follow	VERB
brj-24353	216	3	conclusions	conclusion	NOUN
brj-24353	216	4	were	be	AUX
brj-24353	216	5	drawn	draw	VERB
brj-24353	216	6	:	:	PUNCT
brj-24353	217	1	1	1	X
brj-24353	217	2	.	.	X
brj-24353	217	3	the	the	DET
brj-24353	217	4	specular	specular	ADJ
brj-24353	217	5	reflectance	reflectance	NOUN
brj-24353	217	6	spectra	spectra	NOUN
brj-24353	217	7	generally	generally	ADV
brj-24353	217	8	exhibited	exhibit	VERB
brj-24353	217	9	superior	superior	ADJ
brj-24353	217	10	classification	classification	NOUN
brj-24353	217	11	performance	performance	NOUN
brj-24353	217	12	compared	compare	VERB
brj-24353	217	13	to	to	ADP
brj-24353	217	14	the	the	DET
brj-24353	217	15	diffuse	diffuse	NOUN
brj-24353	217	16	reflectance	reflectance	NOUN
brj-24353	217	17	spectra	spectra	NOUN
brj-24353	217	18	,	,	PUNCT
brj-24353	217	19	as	as	SCONJ
brj-24353	217	20	confirmed	confirm	VERB
brj-24353	217	21	by	by	ADP
brj-24353	217	22	the	the	DET
brj-24353	217	23	evaluation	evaluation	NOUN
brj-24353	217	24	metrics	metric	NOUN
brj-24353	217	25	based	base	VERB
brj-24353	217	26	on	on	ADP
brj-24353	217	27	the	the	DET
brj-24353	217	28	intraclass	intraclass	NOUN
brj-24353	217	29	and	and	CCONJ
brj-24353	217	30	interclass	interclass	VERB
brj-24353	217	31	scatter	scatter	NOUN
brj-24353	217	32	matrices	matrix	NOUN
brj-24353	217	33	.	.	PUNCT
brj-24353	218	1	consequently	consequently	ADV
brj-24353	218	2	,	,	PUNCT
brj-24353	218	3	it	it	PRON
brj-24353	218	4	is	be	AUX
brj-24353	218	5	recommended	recommend	VERB
brj-24353	218	6	that	that	SCONJ
brj-24353	218	7	the	the	DET
brj-24353	218	8	specular	specular	ADJ
brj-24353	218	9	reflection	reflection	NOUN
brj-24353	218	10	nir	nir	PROPN
brj-24353	218	11	spectral	spectral	ADJ
brj-24353	218	12	profile	profile	NOUN
brj-24353	218	13	should	should	AUX
brj-24353	218	14	be	be	AUX
brj-24353	218	15	selected	select	VERB
brj-24353	218	16	as	as	ADP
brj-24353	218	17	a	a	DET
brj-24353	218	18	feature	feature	NOUN
brj-24353	218	19	for	for	ADP
brj-24353	218	20	classifying	classify	VERB
brj-24353	218	21	and	and	CCONJ
brj-24353	218	22	identifying	identify	VERB
brj-24353	218	23	timber	timber	NOUN
brj-24353	218	24	species	specie	NOUN
brj-24353	218	25	.	.	PUNCT
brj-24353	219	1	2	2	X
brj-24353	219	2	.	.	X
brj-24353	219	3	among	among	ADP
brj-24353	219	4	the	the	DET
brj-24353	219	5	tested	test	VERB
brj-24353	219	6	classifiers	classifier	NOUN
brj-24353	219	7	,	,	PUNCT
brj-24353	219	8	the	the	DET
brj-24353	219	9	svm	svm	PROPN
brj-24353	219	10	classifier	classifier	NOUN
brj-24353	219	11	demonstrated	demonstrate	VERB
brj-24353	219	12	the	the	DET
brj-24353	219	13	highest	high	ADJ
brj-24353	219	14	classification	classification	NOUN
brj-24353	219	15	accuracy	accuracy	NOUN
brj-24353	219	16	,	,	PUNCT
brj-24353	219	17	with	with	ADP
brj-24353	219	18	both	both	DET
brj-24353	219	19	types	type	NOUN
brj-24353	219	20	of	of	ADP
brj-24353	219	21	spectra	spectra	ADJ
brj-24353	219	22	achieving	achieving	NOUN
brj-24353	219	23	similarly	similarly	ADV
brj-24353	219	24	high	high	ADJ
brj-24353	219	25	classification	classification	NOUN
brj-24353	219	26	rates	rate	NOUN
brj-24353	219	27	.	.	PUNCT
brj-24353	220	1	this	this	PRON
brj-24353	220	2	can	can	AUX
brj-24353	220	3	be	be	AUX
brj-24353	220	4	attributed	attribute	VERB
brj-24353	220	5	to	to	ADP
brj-24353	220	6	the	the	DET
brj-24353	220	7	fact	fact	NOUN
brj-24353	220	8	that	that	SCONJ
brj-24353	220	9	svms	svms	NOUN
brj-24353	220	10	use	use	VERB
brj-24353	220	11	a	a	DET
brj-24353	220	12	combination	combination	NOUN
brj-24353	220	13	of	of	ADP
brj-24353	220	14	binary	binary	ADJ
brj-24353	220	15	classifiers	classifier	NOUN
brj-24353	220	16	for	for	ADP
brj-24353	220	17	multiclass	multiclass	ADJ
brj-24353	220	18	classification	classification	NOUN
brj-24353	220	19	,	,	PUNCT
brj-24353	220	20	employing	employ	VERB
brj-24353	220	21	three	three	NUM
brj-24353	220	22	strategies	strategy	NOUN
brj-24353	220	23	—	—	PUNCT
brj-24353	220	24	that	that	PRON
brj-24353	220	25	is	be	AUX
brj-24353	220	26	,	,	PUNCT
brj-24353	220	27	1vs-1	1vs-1	NUM
brj-24353	220	28	,	,	PUNCT
brj-24353	220	29	1	1	NUM
brj-24353	220	30	-	-	PUNCT
brj-24353	220	31	vs	vs	ADP
brj-24353	220	32	-	-	PUNCT
brj-24353	220	33	rest	rest	NOUN
brj-24353	220	34	,	,	PUNCT
brj-24353	220	35	and	and	CCONJ
brj-24353	220	36	one	one	NUM
brj-24353	220	37	-	-	PUNCT
brj-24353	220	38	class	class	NOUN
brj-24353	220	39	svm	svm	NOUN
brj-24353	220	40	.	.	PUNCT
brj-24353	221	1	the	the	DET
brj-24353	221	2	effective	effective	ADJ
brj-24353	221	3	combination	combination	NOUN
brj-24353	221	4	of	of	ADP
brj-24353	221	5	these	these	DET
brj-24353	221	6	binary	binary	ADJ
brj-24353	221	7	classifiers	classifier	NOUN
brj-24353	221	8	enhances	enhance	VERB
brj-24353	221	9	the	the	DET
brj-24353	221	10	generalization	generalization	NOUN
brj-24353	221	11	ability	ability	NOUN
brj-24353	221	12	of	of	ADP
brj-24353	221	13	the	the	DET
brj-24353	221	14	svm	svm	ADJ
brj-24353	221	15	model	model	NOUN
brj-24353	221	16	.	.	PUNCT
brj-24353	222	1	moreover	moreover	ADV
brj-24353	222	2	,	,	PUNCT
brj-24353	222	3	the	the	DET
brj-24353	222	4	svm	svm	PROPN
brj-24353	222	5	model	model	NOUN
brj-24353	222	6	uses	use	VERB
brj-24353	222	7	kernel	kernel	PROPN
brj-24353	222	8	functions	function	NOUN
brj-24353	222	9	to	to	PART
brj-24353	222	10	map	map	VERB
brj-24353	222	11	samples	sample	NOUN
brj-24353	222	12	that	that	PRON
brj-24353	222	13	are	be	AUX
brj-24353	222	14	challenging	challenge	VERB
brj-24353	222	15	to	to	PART
brj-24353	222	16	classify	classify	VERB
brj-24353	222	17	in	in	ADP
brj-24353	222	18	a	a	DET
brj-24353	222	19	lowdimensional	lowdimensional	ADJ
brj-24353	222	20	space	space	NOUN
brj-24353	222	21	into	into	ADP
brj-24353	222	22	a	a	DET
brj-24353	222	23	higher	higher	ADV
brj-24353	222	24	-	-	PUNCT
brj-24353	222	25	dimensional	dimensional	ADJ
brj-24353	222	26	space	space	NOUN
brj-24353	222	27	,	,	PUNCT
brj-24353	222	28	thereby	thereby	ADV
brj-24353	222	29	facilitating	facilitate	VERB
brj-24353	222	30	a	a	DET
brj-24353	222	31	more	more	ADV
brj-24353	222	32	effective	effective	ADJ
brj-24353	222	33	classification	classification	NOUN
brj-24353	222	34	.	.	PUNCT
brj-24353	223	1	these	these	DET
brj-24353	223	2	advantages	advantage	NOUN
brj-24353	223	3	enable	enable	VERB
brj-24353	223	4	the	the	DET
brj-24353	223	5	svm	svm	ADJ
brj-24353	223	6	classifier	classifier	NOUN
brj-24353	223	7	to	to	PART
brj-24353	223	8	overcome	overcome	VERB
brj-24353	223	9	the	the	DET
brj-24353	223	10	inherent	inherent	ADJ
brj-24353	223	11	distributional	distributional	ADJ
brj-24353	223	12	differences	difference	NOUN
brj-24353	223	13	between	between	ADP
brj-24353	223	14	the	the	DET
brj-24353	223	15	two	two	NUM
brj-24353	223	16	types	type	NOUN
brj-24353	223	17	of	of	ADP
brj-24353	223	18	spectra	spectra	NOUN
brj-24353	223	19	,	,	PUNCT
brj-24353	223	20	resulting	result	VERB
brj-24353	223	21	in	in	ADP
brj-24353	223	22	consistently	consistently	ADV
brj-24353	223	23	high	high	ADJ
brj-24353	223	24	classification	classification	NOUN
brj-24353	223	25	accuracy	accuracy	NOUN
brj-24353	223	26	.	.	PUNCT
brj-24353	224	1	3	3	X
brj-24353	224	2	.	.	X
brj-24353	224	3	in	in	ADP
brj-24353	224	4	contrast	contrast	NOUN
brj-24353	224	5	,	,	PUNCT
brj-24353	224	6	the	the	DET
brj-24353	224	7	generalized	generalized	ADJ
brj-24353	224	8	classification	classification	NOUN
brj-24353	224	9	performance	performance	NOUN
brj-24353	224	10	of	of	ADP
brj-24353	224	11	the	the	DET
brj-24353	224	12	other	other	ADJ
brj-24353	224	13	classifiers	classifier	NOUN
brj-24353	224	14	was	be	AUX
brj-24353	224	15	limited	limit	VERB
brj-24353	224	16	,	,	PUNCT
brj-24353	224	17	and	and	CCONJ
brj-24353	224	18	their	their	PRON
brj-24353	224	19	accuracy	accuracy	NOUN
brj-24353	224	20	was	be	AUX
brj-24353	224	21	heavily	heavily	ADV
brj-24353	224	22	influenced	influence	VERB
brj-24353	224	23	by	by	ADP
brj-24353	224	24	the	the	DET
brj-24353	224	25	separability	separability	NOUN
brj-24353	224	26	of	of	ADP
brj-24353	224	27	the	the	DET
brj-24353	224	28	patterns	pattern	NOUN
brj-24353	224	29	within	within	ADP
brj-24353	224	30	the	the	DET
brj-24353	224	31	two	two	NUM
brj-24353	224	32	types	type	NOUN
brj-24353	224	33	of	of	ADP
brj-24353	224	34	spectra	spectra	NOUN
brj-24353	224	35	.	.	PUNCT
brj-24353	225	1	consequently	consequently	ADV
brj-24353	225	2	,	,	PUNCT
brj-24353	225	3	these	these	DET
brj-24353	225	4	classifiers	classifier	NOUN
brj-24353	225	5	also	also	ADV
brj-24353	225	6	performed	perform	VERB
brj-24353	225	7	better	well	ADV
brj-24353	225	8	on	on	ADP
brj-24353	225	9	the	the	DET
brj-24353	225	10	specular	specular	ADJ
brj-24353	225	11	reflectance	reflectance	NOUN
brj-24353	225	12	spectra	spectra	NOUN
brj-24353	225	13	than	than	ADP
brj-24353	225	14	on	on	ADP
brj-24353	225	15	the	the	DET
brj-24353	225	16	diffuse	diffuse	NOUN
brj-24353	225	17	reflectance	reflectance	NOUN
brj-24353	225	18	spectra	spectra	NOUN
brj-24353	225	19	.	.	PUNCT
brj-24353	226	1	4	4	X
brj-24353	226	2	.	.	X
brj-24353	227	1	the	the	DET
brj-24353	227	2	classifier	classifier	NOUN
brj-24353	227	3	models	model	NOUN
brj-24353	227	4	trained	train	VERB
brj-24353	227	5	on	on	ADP
brj-24353	227	6	the	the	DET
brj-24353	227	7	specular	specular	ADJ
brj-24353	227	8	and	and	CCONJ
brj-24353	227	9	diffuse	diffuse	ADJ
brj-24353	227	10	reflection	reflection	NOUN
brj-24353	227	11	spectra	spectra	NOUN
brj-24353	227	12	were	be	AUX
brj-24353	227	13	found	find	VERB
brj-24353	227	14	to	to	PART
brj-24353	227	15	be	be	AUX
brj-24353	227	16	non	non	ADJ
brj-24353	227	17	-	-	ADJ
brj-24353	227	18	interchangeable	interchangeable	ADJ
brj-24353	227	19	,	,	PUNCT
brj-24353	227	20	indicating	indicate	VERB
brj-24353	227	21	that	that	SCONJ
brj-24353	227	22	the	the	DET
brj-24353	227	23	models	model	NOUN
brj-24353	227	24	developed	develop	VERB
brj-24353	227	25	for	for	ADP
brj-24353	227	26	one	one	NUM
brj-24353	227	27	type	type	NOUN
brj-24353	227	28	of	of	ADP
brj-24353	227	29	spectrum	spectrum	NOUN
brj-24353	227	30	could	could	AUX
brj-24353	227	31	not	not	PART
brj-24353	227	32	be	be	AUX
brj-24353	227	33	substituted	substitute	VERB
brj-24353	227	34	for	for	ADP
brj-24353	227	35	the	the	DET
brj-24353	227	36	other	other	ADJ
brj-24353	227	37	.	.	PUNCT
brj-24353	228	1	peer	peer	NOUN
brj-24353	228	2	-	-	PUNCT
brj-24353	228	3	reviewed	review	VERB
brj-24353	228	4	article	article	NOUN
brj-24353	228	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	228	6	wang	wang	PROPN
brj-24353	228	7	et	et	PROPN
brj-24353	228	8	al	al	PROPN
brj-24353	228	9	.	.	PROPN
brj-24353	229	1	(	(	PUNCT
brj-24353	229	2	2025	2025	NUM
brj-24353	229	3	)	)	PUNCT
brj-24353	229	4	.	.	PUNCT
brj-24353	230	1	“	"	PUNCT
brj-24353	230	2	wood	wood	NOUN
brj-24353	230	3	i	i	X
brj-24353	230	4	d	d	PROPN
brj-24353	230	5	via	via	ADP
brj-24353	230	6	.	.	PUNCT
brj-24353	231	1	s	s	PROPN
brj-24353	231	2	-	-	PUNCT
brj-24353	231	3	nir	nir	PROPN
brj-24353	231	4	&	&	CCONJ
brj-24353	231	5	dr	dr	PROPN
brj-24353	231	6	-	-	PUNCT
brj-24353	231	7	nir	nir	PROPN
brj-24353	231	8	,	,	PUNCT
brj-24353	231	9	”	"	PUNCT
brj-24353	231	10	bioresources	bioresource	NOUN
brj-24353	231	11	20(3	20(3	NOUN
brj-24353	231	12	)	)	PUNCT
brj-24353	231	13	,	,	PUNCT
brj-24353	231	14	6648	6648	NUM
brj-24353	231	15	-	-	SYM
brj-24353	231	16	6661	6661	NUM
brj-24353	231	17	.	.	PUNCT
brj-24353	232	1	6660	6660	NUM
brj-24353	232	2	acknowledgments	acknowledgment	NOUN
brj-24353	232	3	this	this	DET
brj-24353	232	4	study	study	NOUN
brj-24353	232	5	was	be	AUX
brj-24353	232	6	supported	support	VERB
brj-24353	232	7	by	by	ADP
brj-24353	232	8	the	the	DET
brj-24353	232	9	following	follow	VERB
brj-24353	232	10	grants	grant	NOUN
brj-24353	232	11	,	,	PUNCT
brj-24353	232	12	which	which	PRON
brj-24353	232	13	are	be	AUX
brj-24353	232	14	gratefully	gratefully	ADV
brj-24353	232	15	acknowledged	acknowledge	VERB
brj-24353	232	16	.	.	PUNCT
brj-24353	233	1	national	national	ADJ
brj-24353	233	2	natural	natural	PROPN
brj-24353	233	3	science	science	PROPN
brj-24353	233	4	foundation	foundation	PROPN
brj-24353	233	5	of	of	ADP
brj-24353	233	6	china	china	PROPN
brj-24353	233	7	(	(	PUNCT
brj-24353	233	8	grant	grant	VERB
brj-24353	233	9	number	number	NOUN
brj-24353	233	10	62265001	62265001	NUM
brj-24353	233	11	)	)	PUNCT
brj-24353	233	12	,	,	PUNCT
brj-24353	233	13	and	and	CCONJ
brj-24353	233	14	the	the	DET
brj-24353	233	15	guangxi	guangxi	PROPN
brj-24353	233	16	university	university	PROPN
brj-24353	233	17	of	of	ADP
brj-24353	233	18	science	science	NOUN
brj-24353	233	19	and	and	CCONJ
brj-24353	233	20	technology	technology	NOUN
brj-24353	233	21	doctoral	doctoral	ADJ
brj-24353	233	22	research	research	NOUN
brj-24353	233	23	fund	fund	NOUN
brj-24353	233	24	(	(	PUNCT
brj-24353	233	25	grant	grant	VERB
brj-24353	233	26	number	number	NOUN
brj-24353	233	27	22z07	22z07	NUM
brj-24353	233	28	)	)	PUNCT
brj-24353	233	29	.	.	PUNCT
brj-24353	234	1	availability	availability	NOUN
brj-24353	234	2	of	of	ADP
brj-24353	234	3	data	datum	NOUN
brj-24353	234	4	and	and	CCONJ
brj-24353	234	5	materials	material	NOUN
brj-24353	234	6	the	the	DET
brj-24353	234	7	wood	wood	NOUN
brj-24353	234	8	spectral	spectral	ADJ
brj-24353	234	9	dataset	dataset	NOUN
brj-24353	234	10	used	use	VERB
brj-24353	234	11	in	in	ADP
brj-24353	234	12	this	this	DET
brj-24353	234	13	work	work	NOUN
brj-24353	234	14	is	be	AUX
brj-24353	234	15	confidential	confidential	ADJ
brj-24353	234	16	,	,	PUNCT
brj-24353	234	17	but	but	CCONJ
brj-24353	234	18	this	this	DET
brj-24353	234	19	dataset	dataset	NOUN
brj-24353	234	20	used	use	VERB
brj-24353	234	21	to	to	PART
brj-24353	234	22	support	support	VERB
brj-24353	234	23	the	the	DET
brj-24353	234	24	findings	finding	NOUN
brj-24353	234	25	of	of	ADP
brj-24353	234	26	this	this	DET
brj-24353	234	27	study	study	NOUN
brj-24353	234	28	is	be	AUX
brj-24353	234	29	available	available	ADJ
brj-24353	234	30	from	from	ADP
brj-24353	234	31	the	the	DET
brj-24353	234	32	corresponding	corresponding	ADJ
brj-24353	234	33	author	author	NOUN
brj-24353	234	34	upon	upon	SCONJ
brj-24353	234	35	request	request	NOUN
brj-24353	234	36	after	after	SCONJ
brj-24353	234	37	this	this	DET
brj-24353	234	38	article	article	NOUN
brj-24353	234	39	is	be	AUX
brj-24353	234	40	accepted	accept	VERB
brj-24353	234	41	and	and	CCONJ
brj-24353	234	42	published	publish	VERB
brj-24353	234	43	online	online	ADV
brj-24353	234	44	.	.	PUNCT
brj-24353	235	1	competing	compete	VERB
brj-24353	235	2	interests	interest	NOUN
brj-24353	235	3	the	the	DET
brj-24353	235	4	authors	author	NOUN
brj-24353	235	5	declare	declare	VERB
brj-24353	235	6	that	that	SCONJ
brj-24353	235	7	they	they	PRON
brj-24353	235	8	have	have	VERB
brj-24353	235	9	no	no	DET
brj-24353	235	10	competing	compete	VERB
brj-24353	235	11	interests	interest	NOUN
brj-24353	235	12	.	.	PUNCT
brj-24353	236	1	author	author	NOUN
brj-24353	236	2	contributions	contribution	VERB
brj-24353	236	3	peng	peng	PROPN
brj-24353	236	4	zhao	zhao	PROPN
brj-24353	236	5	proposed	propose	VERB
brj-24353	236	6	the	the	DET
brj-24353	236	7	research	research	NOUN
brj-24353	236	8	idea	idea	NOUN
brj-24353	236	9	and	and	CCONJ
brj-24353	236	10	the	the	DET
brj-24353	236	11	experimental	experimental	ADJ
brj-24353	236	12	framework	framework	NOUN
brj-24353	236	13	,	,	PUNCT
brj-24353	236	14	writing	write	VERB
brj-24353	236	15	the	the	DET
brj-24353	236	16	whole	whole	ADJ
brj-24353	236	17	manuscript	manuscript	NOUN
brj-24353	236	18	.	.	PUNCT
brj-24353	237	1	cheng	cheng	PROPN
brj-24353	237	2	-	-	PUNCT
brj-24353	237	3	kun	kun	PROPN
brj-24353	237	4	wang	wang	PROPN
brj-24353	237	5	carried	carry	VERB
brj-24353	237	6	out	out	ADP
brj-24353	237	7	the	the	DET
brj-24353	237	8	wood	wood	NOUN
brj-24353	237	9	species	species	NOUN
brj-24353	237	10	recognition	recognition	NOUN
brj-24353	237	11	comparative	comparative	ADJ
brj-24353	237	12	experiments	experiment	NOUN
brj-24353	237	13	and	and	CCONJ
brj-24353	237	14	collated	collate	VERB
brj-24353	237	15	the	the	DET
brj-24353	237	16	experimental	experimental	ADJ
brj-24353	237	17	results	result	NOUN
brj-24353	237	18	.	.	PUNCT
brj-24353	238	1	li	li	PROPN
brj-24353	238	2	-	-	PUNCT
brj-24353	238	3	na	na	NOUN
brj-24353	238	4	dong	dong	PROPN
brj-24353	238	5	and	and	CCONJ
brj-24353	238	6	mao	mao	PROPN
brj-24353	238	7	-	-	PUNCT
brj-24353	238	8	ni	ni	PROPN
brj-24353	238	9	zhao	zhao	PROPN
brj-24353	238	10	collated	collate	VERB
brj-24353	238	11	the	the	DET
brj-24353	238	12	experimental	experimental	ADJ
brj-24353	238	13	results	result	NOUN
brj-24353	238	14	.	.	PUNCT
brj-24353	239	1	all	all	DET
brj-24353	239	2	authors	author	NOUN
brj-24353	239	3	read	read	VERB
brj-24353	239	4	and	and	CCONJ
brj-24353	239	5	approved	approve	VERB
brj-24353	239	6	the	the	DET
brj-24353	239	7	final	final	ADJ
brj-24353	239	8	manuscript	manuscript	NOUN
brj-24353	239	9	.	.	PUNCT
brj-24353	240	1	references	reference	NOUN
brj-24353	240	2	cited	cite	VERB
brj-24353	240	3	antil	antil	ADV
brj-24353	240	4	,	,	PUNCT
brj-24353	240	5	s.	s.	PROPN
brj-24353	240	6	,	,	PUNCT
brj-24353	240	7	abraham	abraham	PROPN
brj-24353	240	8	,	,	PUNCT
brj-24353	240	9	j.	j.	PROPN
brj-24353	240	10	s.	s.	PROPN
brj-24353	240	11	,	,	PUNCT
brj-24353	240	12	sripoorna	sripoorna	PROPN
brj-24353	240	13	,	,	PUNCT
brj-24353	240	14	s.	s.	PROPN
brj-24353	240	15	,	,	PUNCT
brj-24353	240	16	maurya	maurya	PROPN
brj-24353	240	17	,	,	PUNCT
brj-24353	240	18	s.	s.	PROPN
brj-24353	240	19	,	,	PUNCT
brj-24353	240	20	dagar	dagar	PROPN
brj-24353	240	21	,	,	PUNCT
brj-24353	240	22	j.	j.	PROPN
brj-24353	240	23	,	,	PUNCT
brj-24353	240	24	makhija	makhija	NOUN
brj-24353	240	25	,	,	PUNCT
brj-24353	240	26	s.	s.	PROPN
brj-24353	240	27	,	,	PUNCT
brj-24353	240	28	bhagat	bhagat	PROPN
brj-24353	240	29	,	,	PUNCT
brj-24353	240	30	p.	p.	NOUN
brj-24353	240	31	,	,	PUNCT
brj-24353	240	32	gupta	gupta	PROPN
brj-24353	240	33	,	,	PUNCT
brj-24353	240	34	r.	r.	PROPN
brj-24353	240	35	,	,	PUNCT
brj-24353	240	36	sood	sood	PROPN
brj-24353	240	37	,	,	PUNCT
brj-24353	240	38	u.	u.	PROPN
brj-24353	240	39	,	,	PUNCT
brj-24353	240	40	and	and	CCONJ
brj-24353	240	41	lal	lal	PROPN
brj-24353	240	42	,	,	PUNCT
brj-24353	240	43	r.	r.	PROPN
brj-24353	240	44	(	(	PUNCT
brj-24353	240	45	2023	2023	NUM
brj-24353	240	46	)	)	PUNCT
brj-24353	240	47	.	.	PUNCT
brj-24353	241	1	“	"	PUNCT
brj-24353	241	2	dna	dna	PROPN
brj-24353	241	3	barcoding	barcoding	NOUN
brj-24353	241	4	,	,	PUNCT
brj-24353	241	5	an	an	DET
brj-24353	241	6	effective	effective	ADJ
brj-24353	241	7	tool	tool	NOUN
brj-24353	241	8	for	for	ADP
brj-24353	241	9	species	species	NOUN
brj-24353	241	10	identification	identification	NOUN
brj-24353	241	11	:	:	PUNCT
brj-24353	241	12	a	a	DET
brj-24353	241	13	review	review	NOUN
brj-24353	241	14	,	,	PUNCT
brj-24353	241	15	”	"	PUNCT
brj-24353	241	16	molecular	molecular	ADJ
brj-24353	241	17	biology	biology	NOUN
brj-24353	241	18	reports	report	VERB
brj-24353	241	19	50(1	50(1	NUM
brj-24353	241	20	)	)	PUNCT
brj-24353	241	21	,	,	PUNCT
brj-24353	241	22	761	761	NUM
brj-24353	241	23	-	-	SYM
brj-24353	241	24	775	775	NUM
brj-24353	241	25	.	.	PUNCT
brj-24353	242	1	doi	doi	NOUN
brj-24353	242	2	:	:	PUNCT
brj-24353	242	3	10.1007	10.1007	NUM
brj-24353	242	4	/	/	SYM
brj-24353	242	5	s11033	s11033	NOUN
brj-24353	242	6	-	-	PUNCT
brj-24353	242	7	022	022	NUM
brj-24353	242	8	-	-	PUNCT
brj-24353	242	9	08015	08015	NUM
brj-24353	242	10	-	-	SYM
brj-24353	242	11	7	7	NUM
brj-24353	242	12	deklerck	deklerck	ADJ
brj-24353	242	13	,	,	PUNCT
brj-24353	242	14	v.	v.	ADV
brj-24353	242	15	,	,	PUNCT
brj-24353	242	16	lancaster	lancaster	PROPN
brj-24353	242	17	,	,	PUNCT
brj-24353	242	18	c.	c.	PROPN
brj-24353	242	19	a.	a.	PROPN
brj-24353	242	20	,	,	PUNCT
brj-24353	242	21	van	van	PROPN
brj-24353	242	22	acker	acker	PROPN
brj-24353	242	23	,	,	PUNCT
brj-24353	242	24	j.	j.	PROPN
brj-24353	242	25	,	,	PUNCT
brj-24353	242	26	espinoza	espinoza	PROPN
brj-24353	242	27	,	,	PUNCT
brj-24353	242	28	e.	e.	PROPN
brj-24353	242	29	o.	o.	PROPN
brj-24353	242	30	,	,	PUNCT
brj-24353	242	31	van	van	PROPN
brj-24353	242	32	den	den	PROPN
brj-24353	242	33	bulcke	bulcke	PROPN
brj-24353	242	34	,	,	PUNCT
brj-24353	242	35	j.	j.	PROPN
brj-24353	242	36	,	,	PUNCT
brj-24353	242	37	and	and	CCONJ
brj-24353	242	38	beeckman	beeckman	NOUN
brj-24353	242	39	,	,	PUNCT
brj-24353	242	40	h.	h.	PROPN
brj-24353	242	41	(	(	PUNCT
brj-24353	242	42	2020	2020	NUM
brj-24353	242	43	)	)	PUNCT
brj-24353	242	44	.	.	PUNCT
brj-24353	243	1	“	"	PUNCT
brj-24353	243	2	chemical	chemical	ADJ
brj-24353	243	3	fingerprinting	fingerprinting	NOUN
brj-24353	243	4	of	of	ADP
brj-24353	243	5	wood	wood	NOUN
brj-24353	243	6	sampled	sample	VERB
brj-24353	243	7	along	along	ADP
brj-24353	243	8	a	a	DET
brj-24353	243	9	pith	pith	NOUN
brj-24353	243	10	-	-	PUNCT
brj-24353	243	11	tobark	tobark	NOUN
brj-24353	243	12	gradient	gradient	NOUN
brj-24353	243	13	for	for	ADP
brj-24353	243	14	individual	individual	ADJ
brj-24353	243	15	comparison	comparison	NOUN
brj-24353	243	16	and	and	CCONJ
brj-24353	243	17	provenance	provenance	NOUN
brj-24353	243	18	identification	identification	NOUN
brj-24353	243	19	,	,	PUNCT
brj-24353	243	20	”	"	PUNCT
brj-24353	243	21	forests	forest	NOUN
brj-24353	243	22	11(1	11(1	NUM
brj-24353	243	23	)	)	PUNCT
brj-24353	243	24	,	,	PUNCT
brj-24353	243	25	article	article	NOUN
brj-24353	243	26	107	107	NUM
brj-24353	243	27	.	.	PUNCT
brj-24353	244	1	doi	doi	NOUN
brj-24353	244	2	:	:	PUNCT
brj-24353	244	3	10.3390	10.3390	NUM
brj-24353	244	4	/	/	SYM
brj-24353	244	5	f11010107	f11010107	NOUN
brj-24353	244	6	hearst	hearst	ADJ
brj-24353	244	7	,	,	PUNCT
brj-24353	244	8	m.	m.	NOUN
brj-24353	244	9	a.	a.	PROPN
brj-24353	244	10	,	,	PUNCT
brj-24353	244	11	dumais	dumais	PROPN
brj-24353	244	12	,	,	PUNCT
brj-24353	244	13	s.	s.	PROPN
brj-24353	244	14	t.	t.	PROPN
brj-24353	244	15	,	,	PUNCT
brj-24353	244	16	osuna	osuna	PROPN
brj-24353	244	17	,	,	PUNCT
brj-24353	244	18	e.	e.	PROPN
brj-24353	244	19	,	,	PUNCT
brj-24353	244	20	platt	platt	PROPN
brj-24353	244	21	,	,	PUNCT
brj-24353	244	22	j.	j.	PROPN
brj-24353	244	23	,	,	PUNCT
brj-24353	244	24	and	and	CCONJ
brj-24353	244	25	scholkopf	scholkopf	PROPN
brj-24353	244	26	,	,	PUNCT
brj-24353	244	27	b.	b.	PROPN
brj-24353	244	28	(	(	PUNCT
brj-24353	244	29	1998	1998	NUM
brj-24353	244	30	)	)	PUNCT
brj-24353	244	31	.	.	PUNCT
brj-24353	245	1	“	"	PUNCT
brj-24353	245	2	support	support	VERB
brj-24353	245	3	vector	vector	NOUN
brj-24353	245	4	machines	machine	NOUN
brj-24353	245	5	,	,	PUNCT
brj-24353	245	6	”	"	PUNCT
brj-24353	245	7	ieee	ieee	NOUN
brj-24353	245	8	intelligent	intelligent	ADJ
brj-24353	245	9	systems	system	NOUN
brj-24353	245	10	and	and	CCONJ
brj-24353	245	11	their	their	PRON
brj-24353	245	12	applications	application	NOUN
brj-24353	245	13	13(4	13(4	NUM
brj-24353	245	14	)	)	PUNCT
brj-24353	245	15	,	,	PUNCT
brj-24353	245	16	18	18	NUM
brj-24353	245	17	-	-	SYM
brj-24353	245	18	28	28	NUM
brj-24353	245	19	.	.	PUNCT
brj-24353	246	1	doi	doi	NOUN
brj-24353	246	2	:	:	PUNCT
brj-24353	246	3	10.1109/5254.708428	10.1109/5254.708428	NUM
brj-24353	246	4	kanayama	kanayama	NOUN
brj-24353	246	5	,	,	PUNCT
brj-24353	246	6	h.	h.	PROPN
brj-24353	246	7	,	,	PUNCT
brj-24353	246	8	ma	ma	PROPN
brj-24353	246	9	,	,	PUNCT
brj-24353	246	10	t.	t.	PROPN
brj-24353	246	11	,	,	PUNCT
brj-24353	246	12	tsuchikawa	tsuchikawa	PROPN
brj-24353	246	13	,	,	PUNCT
brj-24353	246	14	s.	s.	PROPN
brj-24353	246	15	,	,	PUNCT
brj-24353	246	16	and	and	CCONJ
brj-24353	246	17	inagaki	inagaki	ADV
brj-24353	246	18	,	,	PUNCT
brj-24353	246	19	t.	t.	PROPN
brj-24353	246	20	(	(	PUNCT
brj-24353	246	21	2019	2019	NUM
brj-24353	246	22	)	)	PUNCT
brj-24353	246	23	.	.	PUNCT
brj-24353	247	1	“	"	PUNCT
brj-24353	247	2	cognitive	cognitive	ADJ
brj-24353	247	3	spectroscopy	spectroscopy	NOUN
brj-24353	247	4	for	for	ADP
brj-24353	247	5	wood	wood	NOUN
brj-24353	247	6	species	specie	NOUN
brj-24353	247	7	identification	identification	NOUN
brj-24353	247	8	:	:	PUNCT
brj-24353	247	9	near	near	ADP
brj-24353	247	10	infrared	infrared	ADJ
brj-24353	247	11	hyperspectral	hyperspectral	ADJ
brj-24353	247	12	imaging	imaging	NOUN
brj-24353	247	13	combined	combine	VERB
brj-24353	247	14	with	with	ADP
brj-24353	247	15	convolutional	convolutional	ADJ
brj-24353	247	16	neural	neural	ADJ
brj-24353	247	17	networks	network	NOUN
brj-24353	247	18	,	,	PUNCT
brj-24353	247	19	”	"	PUNCT
brj-24353	247	20	analyst	analyst	NOUN
brj-24353	247	21	144(21	144(21	NUM
brj-24353	247	22	)	)	PUNCT
brj-24353	247	23	,	,	PUNCT
brj-24353	247	24	6438	6438	NUM
brj-24353	247	25	-	-	SYM
brj-24353	247	26	6446	6446	NUM
brj-24353	247	27	.	.	PUNCT
brj-24353	248	1	doi	doi	NOUN
brj-24353	248	2	:	:	PUNCT
brj-24353	248	3	10.1039	10.1039	NUM
brj-24353	248	4	/	/	SYM
brj-24353	248	5	c9an01180c	c9an01180c	PROPN
brj-24353	248	6	luo	luo	PROPN
brj-24353	248	7	,	,	PUNCT
brj-24353	248	8	l.	l.	PROPN
brj-24353	248	9	,	,	PUNCT
brj-24353	248	10	xu	xu	PROPN
brj-24353	248	11	,	,	PUNCT
brj-24353	248	12	z.	z.	PROPN
brj-24353	248	13	j.	j.	PROPN
brj-24353	248	14	,	,	PUNCT
brj-24353	248	15	and	and	CCONJ
brj-24353	248	16	na	na	PROPN
brj-24353	248	17	,	,	PUNCT
brj-24353	248	18	b.	b.	PROPN
brj-24353	248	19	(	(	PUNCT
brj-24353	248	20	2023	2023	NUM
brj-24353	248	21	)	)	PUNCT
brj-24353	248	22	.	.	PUNCT
brj-24353	249	1	“	"	PUNCT
brj-24353	249	2	building	build	VERB
brj-24353	249	3	machine	machine	NOUN
brj-24353	249	4	learning	learning	NOUN
brj-24353	249	5	models	model	NOUN
brj-24353	249	6	to	to	PART
brj-24353	249	7	identify	identify	VERB
brj-24353	249	8	wood	wood	NOUN
brj-24353	249	9	species	specie	NOUN
brj-24353	249	10	based	base	VERB
brj-24353	249	11	on	on	ADP
brj-24353	249	12	near	near	ADV
brj-24353	249	13	-	-	PUNCT
brj-24353	249	14	infrared	infrared	ADJ
brj-24353	249	15	spectroscopy	spectroscopy	NOUN
brj-24353	249	16	,	,	PUNCT
brj-24353	249	17	”	"	PUNCT
brj-24353	249	18	holzforschung	holzforschung	NOUN
brj-24353	249	19	77(5	77(5	NUM
brj-24353	249	20	)	)	PUNCT
brj-24353	249	21	,	,	PUNCT
brj-24353	249	22	326	326	NUM
brj-24353	249	23	-	-	SYM
brj-24353	249	24	337	337	NUM
brj-24353	249	25	.	.	PUNCT
brj-24353	249	26	doi	doi	NOUN
brj-24353	249	27	:	:	PUNCT
brj-24353	249	28	10.1515	10.1515	NUM
brj-24353	249	29	/	/	SYM
brj-24353	249	30	hf-2022	hf-2022	NOUN
brj-24353	249	31	-	-	PUNCT
brj-24353	249	32	0122	0122	NUM
brj-24353	249	33	ma	ma	PROPN
brj-24353	249	34	,	,	PUNCT
brj-24353	249	35	t.	t.	PROPN
brj-24353	249	36	,	,	PUNCT
brj-24353	249	37	inagaki	inagaki	PROPN
brj-24353	249	38	,	,	PUNCT
brj-24353	249	39	t.	t.	NOUN
brj-24353	249	40	,	,	PUNCT
brj-24353	249	41	ban	ban	NOUN
brj-24353	249	42	,	,	PUNCT
brj-24353	249	43	m.	m.	NOUN
brj-24353	249	44	,	,	PUNCT
brj-24353	249	45	and	and	CCONJ
brj-24353	249	46	tsuchikawa	tsuchikawa	PROPN
brj-24353	249	47	,	,	PUNCT
brj-24353	249	48	s.	s.	PROPN
brj-24353	249	49	(	(	PUNCT
brj-24353	249	50	2019	2019	NUM
brj-24353	249	51	)	)	PUNCT
brj-24353	249	52	.	.	PUNCT
brj-24353	250	1	“	"	PUNCT
brj-24353	250	2	rapid	rapid	ADJ
brj-24353	250	3	identification	identification	NOUN
brj-24353	250	4	of	of	ADP
brj-24353	250	5	wood	wood	NOUN
brj-24353	250	6	species	specie	NOUN
brj-24353	250	7	by	by	ADP
brj-24353	250	8	near	near	ADV
brj-24353	250	9	-	-	PUNCT
brj-24353	250	10	infrared	infrare	VERB
brj-24353	250	11	spatially	spatially	ADV
brj-24353	250	12	resolved	resolve	VERB
brj-24353	250	13	spectroscopy	spectroscopy	NOUN
brj-24353	250	14	(	(	PUNCT
brj-24353	250	15	nir	nir	PROPN
brj-24353	250	16	-	-	PUNCT
brj-24353	250	17	srs	srs	NOUN
brj-24353	250	18	)	)	PUNCT
brj-24353	250	19	based	base	VERB
brj-24353	250	20	on	on	ADP
brj-24353	250	21	hyperspectral	hyperspectral	ADJ
brj-24353	250	22	imaging	imaging	NOUN
brj-24353	250	23	(	(	PUNCT
brj-24353	250	24	hsi	hsi	PROPN
brj-24353	250	25	)	)	PUNCT
brj-24353	250	26	,	,	PUNCT
brj-24353	250	27	”	"	PUNCT
brj-24353	250	28	holzforschung	holzforschung	PROPN
brj-24353	250	29	73(4	73(4	NOUN
brj-24353	250	30	)	)	PUNCT
brj-24353	250	31	,	,	PUNCT
brj-24353	250	32	323	323	NUM
brj-24353	250	33	-	-	SYM
brj-24353	250	34	330	330	NUM
brj-24353	250	35	.	.	PUNCT
brj-24353	251	1	doi	doi	NOUN
brj-24353	251	2	:	:	PUNCT
brj-24353	251	3	10.1515	10.1515	NUM
brj-24353	251	4	/	/	SYM
brj-24353	251	5	hf-20180128	hf-20180128	NOUN
brj-24353	251	6	peer	peer	NOUN
brj-24353	251	7	-	-	PUNCT
brj-24353	251	8	reviewed	review	VERB
brj-24353	251	9	article	article	NOUN
brj-24353	251	10	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-24353	251	11	wang	wang	PROPN
brj-24353	251	12	et	et	PROPN
brj-24353	251	13	al	al	PROPN
brj-24353	251	14	.	.	PROPN
brj-24353	252	1	(	(	PUNCT
brj-24353	252	2	2025	2025	NUM
brj-24353	252	3	)	)	PUNCT
brj-24353	252	4	.	.	PUNCT
brj-24353	253	1	“	"	PUNCT
brj-24353	253	2	wood	wood	NOUN
brj-24353	253	3	i	i	X
brj-24353	253	4	d	d	PROPN
brj-24353	253	5	via	via	ADP
brj-24353	253	6	.	.	PUNCT
brj-24353	254	1	s	s	PROPN
brj-24353	254	2	-	-	PUNCT
brj-24353	254	3	nir	nir	PROPN
brj-24353	254	4	&	&	CCONJ
brj-24353	254	5	dr	dr	PROPN
brj-24353	254	6	-	-	PUNCT
brj-24353	254	7	nir	nir	PROPN
brj-24353	254	8	,	,	PUNCT
brj-24353	254	9	”	"	PUNCT
brj-24353	254	10	bioresources	bioresource	NOUN
brj-24353	254	11	20(3	20(3	NOUN
brj-24353	254	12	)	)	PUNCT
brj-24353	254	13	,	,	PUNCT
brj-24353	254	14	6648	6648	NUM
brj-24353	254	15	-	-	SYM
brj-24353	254	16	6661	6661	NUM
brj-24353	254	17	.	.	PUNCT
brj-24353	255	1	6661	6661	NUM
brj-24353	255	2	pan	pan	PROPN
brj-24353	255	3	,	,	PUNCT
brj-24353	255	4	x.	x.	PROPN
brj-24353	255	5	,	,	PUNCT
brj-24353	255	6	qiu	qiu	PROPN
brj-24353	255	7	,	,	PUNCT
brj-24353	255	8	j.	j.	PROPN
brj-24353	255	9	,	,	PUNCT
brj-24353	255	10	and	and	CCONJ
brj-24353	255	11	yang	yang	PROPN
brj-24353	255	12	,	,	PUNCT
brj-24353	255	13	z.	z.	PROPN
brj-24353	255	14	(	(	PUNCT
brj-24353	255	15	2023	2023	NUM
brj-24353	255	16	)	)	PUNCT
brj-24353	255	17	.	.	PUNCT
brj-24353	256	1	“	"	PUNCT
brj-24353	256	2	identification	identification	NOUN
brj-24353	256	3	of	of	ADP
brj-24353	256	4	softwood	softwood	NOUN
brj-24353	256	5	species	specie	NOUN
brj-24353	256	6	using	use	VERB
brj-24353	256	7	convolutional	convolutional	ADJ
brj-24353	256	8	neural	neural	ADJ
brj-24353	256	9	networks	network	NOUN
brj-24353	256	10	and	and	CCONJ
brj-24353	256	11	raw	raw	ADJ
brj-24353	256	12	near	near	ADP
brj-24353	256	13	-	-	PUNCT
brj-24353	256	14	infrared	infrared	ADJ
brj-24353	256	15	spectroscopy	spectroscopy	NOUN
brj-24353	256	16	,	,	PUNCT
brj-24353	256	17	”	"	PUNCT
brj-24353	256	18	wood	wood	NOUN
brj-24353	256	19	material	material	NOUN
brj-24353	256	20	science	science	NOUN
brj-24353	256	21	&	&	CCONJ
brj-24353	256	22	engineering	engineering	PROPN
brj-24353	256	23	18(4	18(4	NUM
brj-24353	256	24	)	)	PUNCT
brj-24353	256	25	,	,	PUNCT
brj-24353	256	26	1338	1338	NUM
brj-24353	256	27	-	-	SYM
brj-24353	256	28	1348	1348	NUM
brj-24353	256	29	.	.	PUNCT
brj-24353	257	1	doi	doi	NOUN
brj-24353	257	2	:	:	PUNCT
brj-24353	257	3	10.1080/17480272.2022.2130822	10.1080/17480272.2022.2130822	NUM
brj-24353	257	4	peterson	peterson	NOUN
brj-24353	257	5	,	,	PUNCT
brj-24353	257	6	l.	l.	PROPN
brj-24353	257	7	e.	e.	PROPN
brj-24353	257	8	(	(	PUNCT
brj-24353	257	9	2009	2009	NUM
brj-24353	257	10	)	)	PUNCT
brj-24353	257	11	.	.	PUNCT
brj-24353	258	1	“	"	PUNCT
brj-24353	258	2	k	k	X
brj-24353	258	3	-	-	PUNCT
brj-24353	258	4	nearest	near	ADJ
brj-24353	258	5	neighbor	neighbor	NOUN
brj-24353	258	6	,	,	PUNCT
brj-24353	258	7	”	"	PUNCT
brj-24353	258	8	scholarpedia	scholarpedia	NOUN
brj-24353	258	9	4(2	4(2	NUM
brj-24353	258	10	)	)	PUNCT
brj-24353	258	11	,	,	PUNCT
brj-24353	258	12	article	article	NOUN
brj-24353	258	13	1883	1883	NUM
brj-24353	258	14	.	.	PUNCT
brj-24353	259	1	doi	doi	NOUN
brj-24353	259	2	:	:	PUNCT
brj-24353	259	3	10.4249	10.4249	NUM
brj-24353	259	4	/	/	SYM
brj-24353	259	5	scholarpedia.1883	scholarpedia.1883	PROPN
brj-24353	259	6	safavian	safavian	NOUN
brj-24353	259	7	,	,	PUNCT
brj-24353	259	8	s.	s.	PROPN
brj-24353	259	9	r.	r.	PROPN
brj-24353	259	10	,	,	PUNCT
brj-24353	259	11	and	and	CCONJ
brj-24353	259	12	landgrebe	landgrebe	PROPN
brj-24353	259	13	,	,	PUNCT
brj-24353	259	14	d.	d.	PROPN
brj-24353	259	15	(	(	PUNCT
brj-24353	259	16	1991	1991	NUM
brj-24353	259	17	)	)	PUNCT
brj-24353	259	18	.	.	PUNCT
brj-24353	260	1	“	"	PUNCT
brj-24353	260	2	a	a	DET
brj-24353	260	3	survey	survey	NOUN
brj-24353	260	4	of	of	ADP
brj-24353	260	5	decision	decision	NOUN
brj-24353	260	6	tree	tree	NOUN
brj-24353	260	7	classifier	classifier	NOUN
brj-24353	260	8	methodology	methodology	NOUN
brj-24353	260	9	,	,	PUNCT
brj-24353	260	10	”	"	PUNCT
brj-24353	260	11	ieee	ieee	NOUN
brj-24353	260	12	transactions	transaction	NOUN
brj-24353	260	13	on	on	ADP
brj-24353	260	14	systems	system	NOUN
brj-24353	260	15	,	,	PUNCT
brj-24353	260	16	man	man	NOUN
brj-24353	260	17	,	,	PUNCT
brj-24353	260	18	and	and	CCONJ
brj-24353	260	19	cybernetics	cybernetic	NOUN
brj-24353	260	20	21(3	21(3	NUM
brj-24353	260	21	)	)	PUNCT
brj-24353	260	22	,	,	PUNCT
brj-24353	260	23	660	660	NUM
brj-24353	260	24	-	-	SYM
brj-24353	260	25	674	674	NUM
brj-24353	260	26	.	.	PUNCT
brj-24353	261	1	doi	doi	NOUN
brj-24353	261	2	:	:	PUNCT
brj-24353	261	3	10.1109/21.97458	10.1109/21.97458	NUM
brj-24353	261	4	sharma	sharma	PROPN
brj-24353	261	5	,	,	PUNCT
brj-24353	261	6	v.	v.	PROPN
brj-24353	261	7	,	,	PUNCT
brj-24353	261	8	yadav	yadav	PROPN
brj-24353	261	9	,	,	PUNCT
brj-24353	261	10	j.	j.	PROPN
brj-24353	261	11	,	,	PUNCT
brj-24353	261	12	kumar	kumar	PROPN
brj-24353	261	13	,	,	PUNCT
brj-24353	261	14	r.	r.	PROPN
brj-24353	261	15	,	,	PUNCT
brj-24353	261	16	tesarova	tesarova	PROPN
brj-24353	261	17	,	,	PUNCT
brj-24353	261	18	d.	d.	PROPN
brj-24353	261	19	,	,	PUNCT
brj-24353	261	20	ekielski	ekielski	PROPN
brj-24353	261	21	,	,	PUNCT
brj-24353	261	22	a.	a.	NOUN
brj-24353	261	23	,	,	PUNCT
brj-24353	261	24	and	and	CCONJ
brj-24353	261	25	mishra	mishra	PROPN
brj-24353	261	26	,	,	PUNCT
brj-24353	261	27	p.	p.	PROPN
brj-24353	261	28	k.	k.	PROPN
brj-24353	261	29	(	(	PUNCT
brj-24353	261	30	2020	2020	NUM
brj-24353	261	31	)	)	PUNCT
brj-24353	261	32	.	.	PUNCT
brj-24353	262	1	“	"	PUNCT
brj-24353	262	2	on	on	ADP
brj-24353	262	3	the	the	DET
brj-24353	262	4	rapid	rapid	ADJ
brj-24353	262	5	and	and	CCONJ
brj-24353	262	6	non	non	ADJ
brj-24353	262	7	-	-	ADJ
brj-24353	262	8	destructive	destructive	ADJ
brj-24353	262	9	approach	approach	NOUN
brj-24353	262	10	for	for	ADP
brj-24353	262	11	wood	wood	NOUN
brj-24353	262	12	identification	identification	NOUN
brj-24353	262	13	using	use	VERB
brj-24353	262	14	atr	atr	PROPN
brj-24353	262	15	-	-	PUNCT
brj-24353	262	16	ftir	ftir	ADJ
brj-24353	262	17	spectroscopy	spectroscopy	NOUN
brj-24353	262	18	and	and	CCONJ
brj-24353	262	19	chemometric	chemometric	ADJ
brj-24353	262	20	methods	method	NOUN
brj-24353	262	21	,	,	PUNCT
brj-24353	262	22	”	"	PUNCT
brj-24353	262	23	vibrational	vibrational	ADJ
brj-24353	262	24	spectroscopy	spectroscopy	NOUN
brj-24353	262	25	110	110	NUM
brj-24353	262	26	,	,	PUNCT
brj-24353	262	27	article	article	NOUN
brj-24353	262	28	i	i	PROPN
brj-24353	262	29	d	d	PROPN
brj-24353	262	30	103097	103097	NUM
brj-24353	262	31	.	.	PUNCT
brj-24353	263	1	doi	doi	NOUN
brj-24353	263	2	:	:	PUNCT
brj-24353	263	3	10.1016	10.1016	NUM
brj-24353	263	4	/	/	SYM
brj-24353	263	5	j.vibspec.2020.103097	j.vibspec.2020.103097	ADJ
brj-24353	263	6	veenman	veenman	NOUN
brj-24353	263	7	,	,	PUNCT
brj-24353	263	8	c.	c.	PROPN
brj-24353	263	9	j.	j.	PROPN
brj-24353	263	10	,	,	PUNCT
brj-24353	263	11	and	and	CCONJ
brj-24353	263	12	reinders	reinder	NOUN
brj-24353	263	13	,	,	PUNCT
brj-24353	263	14	m.	m.	NOUN
brj-24353	263	15	j.	j.	PROPN
brj-24353	263	16	t.	t.	PROPN
brj-24353	263	17	(	(	PUNCT
brj-24353	263	18	2005	2005	NUM
brj-24353	263	19	)	)	PUNCT
brj-24353	263	20	.	.	PUNCT
brj-24353	264	1	“	"	PUNCT
brj-24353	264	2	the	the	DET
brj-24353	264	3	nearest	near	ADJ
brj-24353	264	4	subclass	subclass	NOUN
brj-24353	264	5	classifier	classifier	NOUN
brj-24353	264	6	:	:	PUNCT
brj-24353	264	7	a	a	DET
brj-24353	264	8	compromise	compromise	NOUN
brj-24353	264	9	between	between	ADP
brj-24353	264	10	the	the	DET
brj-24353	264	11	nearest	near	ADJ
brj-24353	264	12	mean	mean	ADJ
brj-24353	264	13	and	and	CCONJ
brj-24353	264	14	nearest	near	ADJ
brj-24353	264	15	neighbor	neighbor	NOUN
brj-24353	264	16	classifier	classifier	NOUN
brj-24353	264	17	,	,	PUNCT
brj-24353	264	18	”	"	PUNCT
brj-24353	264	19	ieee	ieee	NOUN
brj-24353	264	20	transactions	transaction	NOUN
brj-24353	264	21	on	on	ADP
brj-24353	264	22	pattern	pattern	NOUN
brj-24353	264	23	analysis	analysis	NOUN
brj-24353	264	24	and	and	CCONJ
brj-24353	264	25	machine	machine	NOUN
brj-24353	264	26	intelligence	intelligence	NOUN
brj-24353	264	27	27(9	27(9	PROPN
brj-24353	264	28	)	)	PUNCT
brj-24353	264	29	,	,	PUNCT
brj-24353	264	30	1417	1417	NUM
brj-24353	264	31	-	-	SYM
brj-24353	264	32	1429	1429	NUM
brj-24353	264	33	.	.	PUNCT
brj-24353	265	1	doi	doi	NOUN
brj-24353	265	2	:	:	PUNCT
brj-24353	265	3	10.1109	10.1109	NUM
brj-24353	265	4	/	/	SYM
brj-24353	265	5	tpami.2005.187	tpami.2005.187	PROPN
brj-24353	265	6	verly	verly	ADV
brj-24353	265	7	lopes	lope	NOUN
brj-24353	265	8	,	,	PUNCT
brj-24353	265	9	d.	d.	PROPN
brj-24353	265	10	j.	j.	PROPN
brj-24353	265	11	,	,	PUNCT
brj-24353	265	12	burgreen	burgreen	PROPN
brj-24353	265	13	,	,	PUNCT
brj-24353	265	14	g.	g.	PROPN
brj-24353	265	15	w.	w.	PROPN
brj-24353	265	16	,	,	PUNCT
brj-24353	265	17	and	and	CCONJ
brj-24353	265	18	entsminger	entsminger	NOUN
brj-24353	265	19	,	,	PUNCT
brj-24353	265	20	e.	e.	PROPN
brj-24353	265	21	d.	d.	PROPN
brj-24353	265	22	(	(	PUNCT
brj-24353	265	23	2020	2020	NUM
brj-24353	265	24	)	)	PUNCT
brj-24353	265	25	.	.	PUNCT
brj-24353	266	1	“	"	PUNCT
brj-24353	266	2	north	north	ADJ
brj-24353	266	3	american	american	ADJ
brj-24353	266	4	hardwoods	hardwood	NOUN
brj-24353	266	5	identification	identification	NOUN
brj-24353	266	6	using	use	VERB
brj-24353	266	7	machine	machine	NOUN
brj-24353	266	8	-	-	PUNCT
brj-24353	266	9	learning	learning	NOUN
brj-24353	266	10	,	,	PUNCT
brj-24353	266	11	”	"	PUNCT
brj-24353	266	12	forests	forest	NOUN
brj-24353	266	13	11(3	11(3	NUM
brj-24353	266	14	)	)	PUNCT
brj-24353	266	15	,	,	PUNCT
brj-24353	266	16	article	article	NOUN
brj-24353	266	17	298	298	NUM
brj-24353	266	18	.	.	PUNCT
brj-24353	267	1	doi	doi	NOUN
brj-24353	267	2	:	:	PUNCT
brj-24353	267	3	10.3390	10.3390	NUM
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brj-24353	267	5	f11030298	f11030298	PROPN
brj-24353	267	6	wang	wang	PROPN
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brj-24353	267	8	c.	c.	PROPN
brj-24353	267	9	k.	k.	PROPN
brj-24353	267	10	,	,	PUNCT
brj-24353	267	11	zhao	zhao	PROPN
brj-24353	267	12	,	,	PUNCT
brj-24353	267	13	p.	p.	PROPN
brj-24353	267	14	,	,	PUNCT
brj-24353	267	15	and	and	CCONJ
brj-24353	267	16	yang	yang	PROPN
brj-24353	267	17	,	,	PUNCT
brj-24353	267	18	j.	j.	PROPN
brj-24353	267	19	l.	l.	PROPN
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brj-24353	267	21	2024	2024	NUM
brj-24353	267	22	)	)	PUNCT
brj-24353	267	23	.	.	PUNCT
brj-24353	268	1	“	"	PUNCT
brj-24353	268	2	effect	effect	NOUN
brj-24353	268	3	of	of	ADP
brj-24353	268	4	wood	wood	NOUN
brj-24353	268	5	surface	surface	NOUN
brj-24353	268	6	finish	finish	NOUN
brj-24353	268	7	on	on	ADP
brj-24353	268	8	wood	wood	NOUN
brj-24353	268	9	species	species	NOUN
brj-24353	268	10	classification	classification	NOUN
brj-24353	268	11	using	use	VERB
brj-24353	268	12	spectral	spectral	ADJ
brj-24353	268	13	reflectance	reflectance	NOUN
brj-24353	268	14	,	,	PUNCT
brj-24353	268	15	”	"	PUNCT
brj-24353	268	16	bioresources	bioresource	NOUN
brj-24353	268	17	19(2	19(2	NUM
brj-24353	268	18	)	)	PUNCT
brj-24353	268	19	,	,	PUNCT
brj-24353	268	20	3060	3060	NUM
brj-24353	268	21	-	-	SYM
brj-24353	268	22	3077	3077	NUM
brj-24353	268	23	.	.	PUNCT
brj-24353	269	1	doi	doi	NOUN
brj-24353	269	2	:	:	PUNCT
brj-24353	269	3	10.15376	10.15376	NUM
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brj-24353	269	7	3077	3077	NUM
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brj-24353	269	9	,	,	PUNCT
brj-24353	269	10	w.	w.	PROPN
brj-24353	269	11	,	,	PUNCT
brj-24353	269	12	chen	chen	PROPN
brj-24353	269	13	,	,	PUNCT
brj-24353	269	14	b.	b.	PROPN
brj-24353	269	15	,	,	PUNCT
brj-24353	269	16	wu	wu	PROPN
brj-24353	269	17	,	,	PUNCT
brj-24353	269	18	x.	x.	PROPN
brj-24353	269	19	,	,	PUNCT
brj-24353	269	20	yang	yang	PROPN
brj-24353	269	21	,	,	PUNCT
brj-24353	269	22	z.	z.	PROPN
brj-24353	269	23	,	,	PUNCT
brj-24353	269	24	lin	lin	PROPN
brj-24353	269	25	,	,	PUNCT
brj-24353	269	26	c.	c.	PROPN
brj-24353	269	27	,	,	PUNCT
brj-24353	269	28	lin	lin	PROPN
brj-24353	269	29	,	,	PUNCT
brj-24353	269	30	j.	j.	PROPN
brj-24353	269	31	,	,	PUNCT
brj-24353	269	32	and	and	CCONJ
brj-24353	269	33	guan	guan	PROPN
brj-24353	269	34	,	,	PUNCT
brj-24353	269	35	x.	x.	NOUN
brj-24353	269	36	(	(	PUNCT
brj-24353	269	37	2023	2023	NUM
brj-24353	269	38	)	)	PUNCT
brj-24353	269	39	.	.	PUNCT
brj-24353	270	1	“	"	PUNCT
brj-24353	270	2	wood	wood	NOUN
brj-24353	270	3	identification	identification	NOUN
brj-24353	270	4	of	of	ADP
brj-24353	270	5	cyclobalanopsis	cyclobalanopsis	NOUN
brj-24353	270	6	(	(	PUNCT
brj-24353	270	7	endl	endl	NOUN
brj-24353	270	8	.	.	PUNCT
brj-24353	270	9	)	)	PUNCT
brj-24353	271	1	oerst	oerst	NOUN
brj-24353	271	2	based	base	VERB
brj-24353	271	3	on	on	ADP
brj-24353	271	4	microscopic	microscopic	ADJ
brj-24353	271	5	features	feature	NOUN
brj-24353	271	6	and	and	CCONJ
brj-24353	271	7	ctgan	ctgan	VERB
brj-24353	271	8	-	-	PUNCT
brj-24353	271	9	enhanced	enhance	VERB
brj-24353	271	10	explainable	explainable	ADJ
brj-24353	271	11	machine	machine	NOUN
brj-24353	271	12	learning	learning	NOUN
brj-24353	271	13	models	model	NOUN
brj-24353	271	14	,	,	PUNCT
brj-24353	271	15	”	"	PUNCT
brj-24353	271	16	frontiers	frontier	NOUN
brj-24353	271	17	in	in	ADP
brj-24353	271	18	plant	plant	NOUN
brj-24353	271	19	science	science	NOUN
brj-24353	271	20	14	14	NUM
brj-24353	271	21	,	,	PUNCT
brj-24353	271	22	article	article	NOUN
brj-24353	271	23	i	i	PROPN
brj-24353	271	24	d	d	PROPN
brj-24353	271	25	1203836	1203836	NUM
brj-24353	271	26	.	.	PUNCT
brj-24353	272	1	doi	doi	NOUN
brj-24353	272	2	:	:	PUNCT
brj-24353	272	3	10.3389	10.3389	NUM
brj-24353	272	4	/	/	SYM
brj-24353	272	5	fpls.2023.1203836	fpls.2023.1203836	PROPN
brj-24353	272	6	zhang	zhang	PROPN
brj-24353	272	7	,	,	PUNCT
brj-24353	272	8	m.	m.	NOUN
brj-24353	272	9	,	,	PUNCT
brj-24353	272	10	xie	xie	PROPN
brj-24353	272	11	,	,	PUNCT
brj-24353	272	12	x.	x.	PROPN
brj-24353	272	13	,	,	PUNCT
brj-24353	272	14	zhang	zhang	PROPN
brj-24353	272	15	,	,	PUNCT
brj-24353	272	16	d.	d.	PROPN
brj-24353	272	17	,	,	PUNCT
brj-24353	272	18	chen	chen	PROPN
brj-24353	272	19	,	,	PUNCT
brj-24353	272	20	r.	r.	PROPN
brj-24353	272	21	,	,	PUNCT
brj-24353	272	22	xu	xu	PROPN
brj-24353	272	23	,	,	PUNCT
brj-24353	272	24	y.	y.	PROPN
brj-24353	272	25	,	,	PUNCT
brj-24353	272	26	wang	wang	PROPN
brj-24353	272	27	,	,	PUNCT
brj-24353	272	28	j.	j.	PROPN
brj-24353	272	29	,	,	PUNCT
brj-24353	272	30	liu	liu	PROPN
brj-24353	272	31	,	,	PUNCT
brj-24353	272	32	j.	j.	PROPN
brj-24353	272	33	,	,	PUNCT
brj-24353	272	34	and	and	CCONJ
brj-24353	272	35	xu	xu	PROPN
brj-24353	272	36	,	,	PUNCT
brj-24353	272	37	x.	x.	NOUN
brj-24353	272	38	(	(	PUNCT
brj-24353	272	39	2023	2023	NUM
brj-24353	272	40	)	)	PUNCT
brj-24353	272	41	.	.	PUNCT
brj-24353	273	1	“	"	PUNCT
brj-24353	273	2	nondestructive	nondestructive	ADJ
brj-24353	273	3	identification	identification	NOUN
brj-24353	273	4	of	of	ADP
brj-24353	273	5	wood	wood	NOUN
brj-24353	273	6	species	specie	NOUN
brj-24353	273	7	by	by	ADP
brj-24353	273	8	terahertz	terahertz	NOUN
brj-24353	273	9	spectrum	spectrum	NOUN
brj-24353	273	10	,	,	PUNCT
brj-24353	273	11	”	"	PUNCT
brj-24353	273	12	microwave	microwave	NOUN
brj-24353	273	13	and	and	CCONJ
brj-24353	273	14	optical	optical	ADJ
brj-24353	273	15	technology	technology	NOUN
brj-24353	273	16	letters	letter	NOUN
brj-24353	273	17	65(5	65(5	NUM
brj-24353	273	18	)	)	PUNCT
brj-24353	273	19	,	,	PUNCT
brj-24353	273	20	1117	1117	NUM
brj-24353	273	21	-	-	SYM
brj-24353	273	22	1121	1121	NUM
brj-24353	273	23	.	.	PUNCT
brj-24353	274	1	doi	doi	NOUN
brj-24353	274	2	:	:	PUNCT
brj-24353	274	3	10.1002	10.1002	NUM
brj-24353	274	4	/	/	SYM
brj-24353	274	5	mop.33195	mop.33195	NOUN
brj-24353	274	6	article	article	NOUN
brj-24353	274	7	submitted	submit	VERB
brj-24353	274	8	:	:	PUNCT
brj-24353	274	9	december	december	PROPN
brj-24353	274	10	31	31	NUM
brj-24353	274	11	,	,	PUNCT
brj-24353	274	12	2024	2024	NUM
brj-24353	274	13	;	;	PUNCT
brj-24353	274	14	peer	peer	NOUN
brj-24353	274	15	review	review	NOUN
brj-24353	274	16	completed	complete	VERB
brj-24353	274	17	:	:	PUNCT
brj-24353	274	18	february	february	PROPN
brj-24353	274	19	1	1	NUM
brj-24353	274	20	,	,	PUNCT
brj-24353	274	21	2025	2025	NUM
brj-24353	274	22	;	;	PUNCT
brj-24353	274	23	revised	revise	VERB
brj-24353	274	24	version	version	NOUN
brj-24353	274	25	received	receive	VERB
brj-24353	274	26	:	:	PUNCT
brj-24353	274	27	february	february	NOUN
brj-24353	274	28	12	12	NUM
brj-24353	274	29	,	,	PUNCT
brj-24353	274	30	2025	2025	NUM
brj-24353	274	31	;	;	PUNCT
brj-24353	274	32	accepted	accept	VERB
brj-24353	274	33	:	:	PUNCT
brj-24353	274	34	february	february	PROPN
brj-24353	274	35	28	28	NUM
brj-24353	274	36	,	,	PUNCT
brj-24353	274	37	2025	2025	NUM
brj-24353	274	38	;	;	PUNCT
brj-24353	274	39	published	publish	VERB
brj-24353	274	40	:	:	PUNCT
brj-24353	274	41	june	june	PROPN
brj-24353	274	42	24	24	NUM
brj-24353	274	43	,	,	PUNCT
brj-24353	274	44	2025	2025	NUM
brj-24353	274	45	.	.	PUNCT
brj-24353	275	1	doi	doi	NOUN
brj-24353	275	2	:	:	PUNCT
brj-24353	275	3	10.15376	10.15376	NUM
brj-24353	275	4	/	/	SYM
brj-24353	275	5	biores.20.3.6648	biores.20.3.6648	PROPN
brj-24353	275	6	-	-	PUNCT
brj-24353	275	7	6661	6661	NUM