id	sid	tid	token	lemma	pos
ajst-10982	1	1	academic	academic	ADJ
ajst-10982	1	2	journal	journal	NOUN
ajst-10982	1	3	of	of	ADP
ajst-10982	1	4	science	science	NOUN
ajst-10982	1	5	and	and	CCONJ
ajst-10982	1	6	technology	technology	NOUN
ajst-10982	1	7	issn	issn	NOUN
ajst-10982	1	8	:	:	PUNCT
ajst-10982	1	9	2771	2771	NUM
ajst-10982	1	10	-	-	SYM
ajst-10982	1	11	3032	3032	NUM
ajst-10982	1	12	|	|	NOUN
ajst-10982	1	13	vol	vol	NOUN
ajst-10982	1	14	.	.	PROPN
ajst-10982	2	1	7	7	NUM
ajst-10982	2	2	,	,	PUNCT
ajst-10982	2	3	no	no	INTJ
ajst-10982	2	4	.	.	NOUN
ajst-10982	2	5	1	1	NUM
ajst-10982	2	6	,	,	PUNCT
ajst-10982	2	7	2023	2023	NUM
ajst-10982	2	8	25	25	NUM
ajst-10982	2	9	a	a	DET
ajst-10982	2	10	review	review	NOUN
ajst-10982	2	11	of	of	ADP
ajst-10982	2	12	deep	deep	ADJ
ajst-10982	2	13	learning	learning	NOUN
ajst-10982	2	14	in	in	ADP
ajst-10982	2	15	the	the	DET
ajst-10982	2	16	field	field	NOUN
ajst-10982	2	17	of	of	ADP
ajst-10982	2	18	plant	plant	NOUN
ajst-10982	2	19	root	root	NOUN
ajst-10982	2	20	segmentation	segmentation	NOUN
ajst-10982	2	21	weichen	weichen	SCONJ
ajst-10982	2	22	liao	liao	PROPN
ajst-10982	2	23	school	school	PROPN
ajst-10982	2	24	of	of	ADP
ajst-10982	2	25	electronic	electronic	ADJ
ajst-10982	2	26	information	information	NOUN
ajst-10982	2	27	,	,	PUNCT
ajst-10982	2	28	southwest	southwest	PROPN
ajst-10982	2	29	university	university	PROPN
ajst-10982	2	30	for	for	ADP
ajst-10982	2	31	nationalities	nationality	NOUN
ajst-10982	2	32	,	,	PUNCT
ajst-10982	2	33	chengdu	chengdu	PROPN
ajst-10982	2	34	610225	610225	NUM
ajst-10982	2	35	,	,	PUNCT
ajst-10982	2	36	china	china	PROPN
ajst-10982	2	37	abstract	abstract	NOUN
ajst-10982	2	38	:	:	PUNCT
ajst-10982	2	39	plant	plant	NOUN
ajst-10982	2	40	root	root	NOUN
ajst-10982	2	41	segmentation	segmentation	NOUN
ajst-10982	2	42	is	be	AUX
ajst-10982	2	43	an	an	DET
ajst-10982	2	44	important	important	ADJ
ajst-10982	2	45	research	research	NOUN
ajst-10982	2	46	task	task	NOUN
ajst-10982	2	47	,	,	PUNCT
ajst-10982	2	48	which	which	PRON
ajst-10982	2	49	is	be	AUX
ajst-10982	2	50	of	of	ADP
ajst-10982	2	51	great	great	ADJ
ajst-10982	2	52	significance	significance	NOUN
ajst-10982	2	53	for	for	ADP
ajst-10982	2	54	understanding	understand	VERB
ajst-10982	2	55	plant	plant	NOUN
ajst-10982	2	56	growth	growth	NOUN
ajst-10982	2	57	and	and	CCONJ
ajst-10982	2	58	development	development	NOUN
ajst-10982	2	59	process	process	NOUN
ajst-10982	2	60	.	.	PUNCT
ajst-10982	3	1	deep	deep	ADJ
ajst-10982	3	2	learning	learning	NOUN
ajst-10982	3	3	has	have	AUX
ajst-10982	3	4	become	become	VERB
ajst-10982	3	5	a	a	DET
ajst-10982	3	6	research	research	NOUN
ajst-10982	3	7	direction	direction	NOUN
ajst-10982	3	8	worthy	worthy	ADJ
ajst-10982	3	9	of	of	ADP
ajst-10982	3	10	attention	attention	NOUN
ajst-10982	3	11	in	in	ADP
ajst-10982	3	12	this	this	DET
ajst-10982	3	13	field	field	NOUN
ajst-10982	3	14	.	.	PUNCT
ajst-10982	4	1	this	this	DET
ajst-10982	4	2	paper	paper	NOUN
ajst-10982	4	3	mainly	mainly	ADV
ajst-10982	4	4	introduces	introduce	VERB
ajst-10982	4	5	plant	plant	NOUN
ajst-10982	4	6	root	root	NOUN
ajst-10982	4	7	segmentation	segmentation	NOUN
ajst-10982	4	8	methods	method	NOUN
ajst-10982	4	9	based	base	VERB
ajst-10982	4	10	on	on	ADP
ajst-10982	4	11	deep	deep	ADJ
ajst-10982	4	12	learning	learning	NOUN
ajst-10982	4	13	,	,	PUNCT
ajst-10982	4	14	and	and	CCONJ
ajst-10982	4	15	reviews	review	VERB
ajst-10982	4	16	the	the	DET
ajst-10982	4	17	application	application	NOUN
ajst-10982	4	18	of	of	ADP
ajst-10982	4	19	various	various	ADJ
ajst-10982	4	20	methods	method	NOUN
ajst-10982	4	21	in	in	ADP
ajst-10982	4	22	different	different	ADJ
ajst-10982	4	23	fields	field	NOUN
ajst-10982	4	24	.	.	PUNCT
ajst-10982	5	1	the	the	DET
ajst-10982	5	2	problems	problem	NOUN
ajst-10982	5	3	of	of	ADP
ajst-10982	5	4	data	datum	NOUN
ajst-10982	5	5	quality	quality	NOUN
ajst-10982	5	6	,	,	PUNCT
ajst-10982	5	7	model	model	NOUN
ajst-10982	5	8	fitting	fitting	ADJ
ajst-10982	5	9	ability	ability	NOUN
ajst-10982	5	10	and	and	CCONJ
ajst-10982	5	11	real	real	ADJ
ajst-10982	5	12	-	-	PUNCT
ajst-10982	5	13	time	time	NOUN
ajst-10982	5	14	performance	performance	NOUN
ajst-10982	5	15	,	,	PUNCT
ajst-10982	5	16	and	and	CCONJ
ajst-10982	5	17	the	the	DET
ajst-10982	5	18	significance	significance	NOUN
ajst-10982	5	19	of	of	ADP
ajst-10982	5	20	transfer	transfer	NOUN
ajst-10982	5	21	learning	learning	NOUN
ajst-10982	5	22	,	,	PUNCT
ajst-10982	5	23	multi	multi	ADJ
ajst-10982	5	24	-	-	ADJ
ajst-10982	5	25	task	task	ADJ
ajst-10982	5	26	learning	learning	NOUN
ajst-10982	5	27	and	and	CCONJ
ajst-10982	5	28	reinforcement	reinforcement	NOUN
ajst-10982	5	29	learning	learning	NOUN
ajst-10982	5	30	in	in	ADP
ajst-10982	5	31	application	application	NOUN
ajst-10982	5	32	are	be	AUX
ajst-10982	5	33	put	put	VERB
ajst-10982	5	34	forward	forward	ADV
ajst-10982	5	35	.	.	PUNCT
ajst-10982	6	1	finally	finally	ADV
ajst-10982	6	2	,	,	PUNCT
ajst-10982	6	3	it	it	PRON
ajst-10982	6	4	is	be	AUX
ajst-10982	6	5	pointed	point	VERB
ajst-10982	6	6	out	out	ADP
ajst-10982	6	7	that	that	SCONJ
ajst-10982	6	8	future	future	ADJ
ajst-10982	6	9	research	research	NOUN
ajst-10982	6	10	should	should	AUX
ajst-10982	6	11	focus	focus	VERB
ajst-10982	6	12	on	on	ADP
ajst-10982	6	13	how	how	SCONJ
ajst-10982	6	14	to	to	PART
ajst-10982	6	15	better	well	ADV
ajst-10982	6	16	cope	cope	VERB
ajst-10982	6	17	with	with	ADP
ajst-10982	6	18	the	the	DET
ajst-10982	6	19	challenges	challenge	NOUN
ajst-10982	6	20	of	of	ADP
ajst-10982	6	21	root	root	NOUN
ajst-10982	6	22	morphology	morphology	NOUN
ajst-10982	6	23	and	and	CCONJ
ajst-10982	6	24	scale	scale	NOUN
ajst-10982	6	25	change	change	NOUN
ajst-10982	6	26	,	,	PUNCT
ajst-10982	6	27	and	and	CCONJ
ajst-10982	6	28	pay	pay	VERB
ajst-10982	6	29	more	more	ADJ
ajst-10982	6	30	attention	attention	NOUN
ajst-10982	6	31	to	to	ADP
ajst-10982	6	32	the	the	DET
ajst-10982	6	33	robustness	robustness	NOUN
ajst-10982	6	34	and	and	CCONJ
ajst-10982	6	35	scalability	scalability	NOUN
ajst-10982	6	36	of	of	ADP
ajst-10982	6	37	the	the	DET
ajst-10982	6	38	algorithm	algorithm	NOUN
ajst-10982	6	39	.	.	PUNCT
ajst-10982	7	1	in	in	ADP
ajst-10982	7	2	conclusion	conclusion	NOUN
ajst-10982	7	3	,	,	PUNCT
ajst-10982	7	4	deep	deep	ADJ
ajst-10982	7	5	learning	learning	NOUN
ajst-10982	7	6	has	have	AUX
ajst-10982	7	7	had	have	VERB
ajst-10982	7	8	an	an	DET
ajst-10982	7	9	important	important	ADJ
ajst-10982	7	10	impact	impact	NOUN
ajst-10982	7	11	on	on	ADP
ajst-10982	7	12	image	image	NOUN
ajst-10982	7	13	segmentation	segmentation	NOUN
ajst-10982	7	14	of	of	ADP
ajst-10982	7	15	plant	plant	NOUN
ajst-10982	7	16	roots	root	NOUN
ajst-10982	7	17	.	.	PUNCT
ajst-10982	8	1	keywords	keyword	NOUN
ajst-10982	8	2	:	:	PUNCT
ajst-10982	8	3	plant	plant	NOUN
ajst-10982	8	4	root	root	NOUN
ajst-10982	8	5	segmentation	segmentation	NOUN
ajst-10982	8	6	,	,	PUNCT
ajst-10982	8	7	deep	deep	ADJ
ajst-10982	8	8	learning	learning	NOUN
ajst-10982	8	9	,	,	PUNCT
ajst-10982	8	10	root	root	NOUN
ajst-10982	8	11	morphology	morphology	NOUN
ajst-10982	8	12	,	,	PUNCT
ajst-10982	8	13	image	image	NOUN
ajst-10982	8	14	segmentation	segmentation	NOUN
ajst-10982	8	15	.	.	PUNCT
ajst-10982	9	1	1	1	X
ajst-10982	9	2	.	.	X
ajst-10982	9	3	introduction	introduction	NOUN
ajst-10982	9	4	in	in	ADP
ajst-10982	9	5	the	the	DET
ajst-10982	9	6	new	new	ADJ
ajst-10982	9	7	era	era	NOUN
ajst-10982	9	8	of	of	ADP
ajst-10982	9	9	socialism	socialism	NOUN
ajst-10982	9	10	,	,	PUNCT
ajst-10982	9	11	where	where	SCONJ
ajst-10982	9	12	science	science	NOUN
ajst-10982	9	13	and	and	CCONJ
ajst-10982	9	14	technology	technology	NOUN
ajst-10982	9	15	are	be	AUX
ajst-10982	9	16	advancing	advance	VERB
ajst-10982	9	17	rapidly	rapidly	ADV
ajst-10982	9	18	,	,	PUNCT
ajst-10982	9	19	studying	study	VERB
ajst-10982	9	20	plant	plant	NOUN
ajst-10982	9	21	roots	root	NOUN
ajst-10982	9	22	is	be	AUX
ajst-10982	9	23	crucial	crucial	ADJ
ajst-10982	9	24	for	for	ADP
ajst-10982	9	25	discovering	discover	VERB
ajst-10982	9	26	the	the	DET
ajst-10982	9	27	beneficial	beneficial	ADJ
ajst-10982	9	28	shape	shape	NOUN
ajst-10982	9	29	of	of	ADP
ajst-10982	9	30	crops	crop	NOUN
ajst-10982	9	31	,	,	PUNCT
ajst-10982	9	32	breeding	breed	VERB
ajst-10982	9	33	new	new	ADJ
ajst-10982	9	34	varieties	variety	NOUN
ajst-10982	9	35	,	,	PUNCT
ajst-10982	9	36	predicting	predict	VERB
ajst-10982	9	37	climate	climate	NOUN
ajst-10982	9	38	change	change	NOUN
ajst-10982	9	39	,	,	PUNCT
ajst-10982	9	40	and	and	CCONJ
ajst-10982	9	41	optimizing	optimize	VERB
ajst-10982	9	42	cultivation	cultivation	NOUN
ajst-10982	9	43	methods	method	NOUN
ajst-10982	9	44	.	.	PUNCT
ajst-10982	10	1	our	our	PRON
ajst-10982	10	2	research	research	NOUN
ajst-10982	10	3	methods	method	NOUN
ajst-10982	10	4	on	on	ADP
ajst-10982	10	5	root	root	NOUN
ajst-10982	10	6	systems	system	NOUN
ajst-10982	10	7	have	have	AUX
ajst-10982	10	8	also	also	ADV
ajst-10982	10	9	changed	change	VERB
ajst-10982	10	10	,	,	PUNCT
ajst-10982	10	11	from	from	ADP
ajst-10982	10	12	destructive	destructive	ADJ
ajst-10982	10	13	to	to	ADP
ajst-10982	10	14	non	non	ADJ
ajst-10982	10	15	-	-	ADJ
ajst-10982	10	16	destructive	destructive	ADJ
ajst-10982	10	17	research	research	NOUN
ajst-10982	10	18	methods	method	NOUN
ajst-10982	10	19	,	,	PUNCT
ajst-10982	10	20	from	from	ADP
ajst-10982	10	21	traditional	traditional	ADJ
ajst-10982	10	22	manual	manual	ADJ
ajst-10982	10	23	root	root	NOUN
ajst-10982	10	24	in	in	ADP
ajst-10982	10	25	situ	situ	ADJ
ajst-10982	10	26	segmentation	segmentation	NOUN
ajst-10982	10	27	methods	method	NOUN
ajst-10982	10	28	to	to	ADP
ajst-10982	10	29	automatic	automatic	ADJ
ajst-10982	10	30	segmentation	segmentation	NOUN
ajst-10982	10	31	methods	method	NOUN
ajst-10982	10	32	,	,	PUNCT
ajst-10982	10	33	and	and	CCONJ
ajst-10982	10	34	more	more	ADV
ajst-10982	10	35	efficient	efficient	ADJ
ajst-10982	10	36	technology	technology	NOUN
ajst-10982	10	37	provides	provide	VERB
ajst-10982	10	38	a	a	DET
ajst-10982	10	39	shortcut	shortcut	NOUN
ajst-10982	10	40	for	for	ADP
ajst-10982	10	41	the	the	DET
ajst-10982	10	42	analysis	analysis	NOUN
ajst-10982	10	43	of	of	ADP
ajst-10982	10	44	root	root	NOUN
ajst-10982	10	45	phenotypic	phenotypic	ADJ
ajst-10982	10	46	characteristics	characteristic	NOUN
ajst-10982	10	47	.	.	PUNCT
ajst-10982	11	1	however	however	ADV
ajst-10982	11	2	,	,	PUNCT
ajst-10982	11	3	due	due	ADP
ajst-10982	11	4	to	to	ADP
ajst-10982	11	5	the	the	DET
ajst-10982	11	6	similar	similar	ADJ
ajst-10982	11	7	color	color	NOUN
ajst-10982	11	8	of	of	ADP
ajst-10982	11	9	plant	plant	NOUN
ajst-10982	11	10	roots	root	NOUN
ajst-10982	11	11	and	and	CCONJ
ajst-10982	11	12	soil	soil	NOUN
ajst-10982	11	13	,	,	PUNCT
ajst-10982	11	14	it	it	PRON
ajst-10982	11	15	is	be	AUX
ajst-10982	11	16	difficult	difficult	ADJ
ajst-10982	11	17	to	to	PART
ajst-10982	11	18	extract	extract	VERB
ajst-10982	11	19	root	root	NOUN
ajst-10982	11	20	characteristics	characteristic	NOUN
ajst-10982	11	21	,	,	PUNCT
ajst-10982	11	22	there	there	PRON
ajst-10982	11	23	are	be	VERB
ajst-10982	11	24	few	few	ADJ
ajst-10982	11	25	image	image	NOUN
ajst-10982	11	26	data	datum	NOUN
ajst-10982	11	27	of	of	ADP
ajst-10982	11	28	plant	plant	NOUN
ajst-10982	11	29	roots	root	NOUN
ajst-10982	11	30	,	,	PUNCT
ajst-10982	11	31	and	and	CCONJ
ajst-10982	11	32	the	the	DET
ajst-10982	11	33	soil	soil	NOUN
ajst-10982	11	34	background	background	NOUN
ajst-10982	11	35	is	be	AUX
ajst-10982	11	36	complex	complex	ADJ
ajst-10982	11	37	,	,	PUNCT
ajst-10982	11	38	usually	usually	ADV
ajst-10982	11	39	containing	contain	VERB
ajst-10982	11	40	impurities	impurity	NOUN
ajst-10982	11	41	such	such	ADJ
ajst-10982	11	42	as	as	ADP
ajst-10982	11	43	soil	soil	NOUN
ajst-10982	11	44	particles	particle	NOUN
ajst-10982	11	45	and	and	CCONJ
ajst-10982	11	46	small	small	ADJ
ajst-10982	11	47	stones	stone	NOUN
ajst-10982	11	48	,	,	PUNCT
ajst-10982	11	49	so	so	CCONJ
ajst-10982	11	50	it	it	PRON
ajst-10982	11	51	is	be	AUX
ajst-10982	11	52	extremely	extremely	ADV
ajst-10982	11	53	challenging	challenging	ADJ
ajst-10982	11	54	to	to	PART
ajst-10982	11	55	apply	apply	VERB
ajst-10982	11	56	deep	deep	ADJ
ajst-10982	11	57	learning	learning	NOUN
ajst-10982	11	58	to	to	PART
ajst-10982	11	59	plant	plant	VERB
ajst-10982	11	60	root	root	NOUN
ajst-10982	11	61	segmentation	segmentation	NOUN
ajst-10982	11	62	.	.	PUNCT
ajst-10982	12	1	2	2	X
ajst-10982	12	2	.	.	X
ajst-10982	12	3	research	research	NOUN
ajst-10982	12	4	on	on	ADP
ajst-10982	12	5	roots	root	NOUN
ajst-10982	12	6	of	of	ADP
ajst-10982	12	7	traditional	traditional	ADJ
ajst-10982	12	8	plants	plant	NOUN
ajst-10982	12	9	the	the	DET
ajst-10982	12	10	roots	root	NOUN
ajst-10982	12	11	of	of	ADP
ajst-10982	12	12	plants	plant	NOUN
ajst-10982	12	13	have	have	AUX
ajst-10982	12	14	been	be	AUX
ajst-10982	12	15	studied	study	VERB
ajst-10982	12	16	since	since	SCONJ
ajst-10982	12	17	the	the	DET
ajst-10982	12	18	18th	18th	ADJ
ajst-10982	12	19	century	century	NOUN
ajst-10982	12	20	[	[	X
ajst-10982	12	21	1	1	NUM
ajst-10982	12	22	]	]	PUNCT
ajst-10982	12	23	.	.	PUNCT
ajst-10982	13	1	early	early	ADJ
ajst-10982	13	2	studies	study	NOUN
ajst-10982	13	3	on	on	ADP
ajst-10982	13	4	root	root	NOUN
ajst-10982	13	5	configuration	configuration	NOUN
ajst-10982	13	6	can	can	AUX
ajst-10982	13	7	be	be	AUX
ajst-10982	13	8	traced	trace	VERB
ajst-10982	13	9	back	back	ADV
ajst-10982	13	10	to	to	ADP
ajst-10982	13	11	the	the	DET
ajst-10982	13	12	early	early	ADJ
ajst-10982	13	13	20th	20th	ADJ
ajst-10982	13	14	century	century	NOUN
ajst-10982	13	15	,	,	PUNCT
ajst-10982	13	16	when	when	SCONJ
ajst-10982	13	17	cannon	cannon	NOUN
ajst-10982	13	18	's	's	PART
ajst-10982	13	19	research	research	NOUN
ajst-10982	13	20	revealed	reveal	VERB
ajst-10982	13	21	the	the	DET
ajst-10982	13	22	variability	variability	NOUN
ajst-10982	13	23	of	of	ADP
ajst-10982	13	24	taproots	taproot	NOUN
ajst-10982	13	25	and	and	CCONJ
ajst-10982	13	26	lateral	lateral	ADJ
ajst-10982	13	27	roots	root	NOUN
ajst-10982	13	28	of	of	ADP
ajst-10982	13	29	desert	desert	NOUN
ajst-10982	13	30	plant	plant	NOUN
ajst-10982	13	31	roots	root	NOUN
ajst-10982	13	32	[	[	X
ajst-10982	13	33	2	2	NUM
ajst-10982	13	34	]	]	PUNCT
ajst-10982	13	35	,	,	PUNCT
ajst-10982	13	36	laying	lay	VERB
ajst-10982	13	37	the	the	DET
ajst-10982	13	38	foundation	foundation	NOUN
ajst-10982	13	39	for	for	ADP
ajst-10982	13	40	later	later	ADJ
ajst-10982	13	41	studies	study	NOUN
ajst-10982	13	42	on	on	ADP
ajst-10982	13	43	plant	plant	NOUN
ajst-10982	13	44	roots	root	NOUN
ajst-10982	13	45	.	.	PUNCT
ajst-10982	14	1	2.1	2.1	NUM
ajst-10982	14	2	.	.	PUNCT
ajst-10982	14	3	collection	collection	NOUN
ajst-10982	14	4	of	of	ADP
ajst-10982	14	5	plant	plant	NOUN
ajst-10982	14	6	root	root	NOUN
ajst-10982	14	7	data	datum	NOUN
ajst-10982	14	8	in	in	ADP
ajst-10982	14	9	the	the	DET
ajst-10982	14	10	early	early	ADJ
ajst-10982	14	11	stage	stage	NOUN
ajst-10982	14	12	,	,	PUNCT
ajst-10982	14	13	researchers	researcher	NOUN
ajst-10982	14	14	usually	usually	ADV
ajst-10982	14	15	used	use	VERB
ajst-10982	14	16	destructive	destructive	ADJ
ajst-10982	14	17	research	research	NOUN
ajst-10982	14	18	methods	method	NOUN
ajst-10982	14	19	such	such	ADJ
ajst-10982	14	20	as	as	ADP
ajst-10982	14	21	excavation	excavation	NOUN
ajst-10982	14	22	method	method	NOUN
ajst-10982	14	23	,	,	PUNCT
ajst-10982	14	24	single	single	ADJ
ajst-10982	14	25	block	block	NOUN
ajst-10982	14	26	method	method	NOUN
ajst-10982	14	27	,	,	PUNCT
ajst-10982	14	28	drilling	drilling	NOUN
ajst-10982	14	29	method	method	NOUN
ajst-10982	14	30	and	and	CCONJ
ajst-10982	14	31	section	section	NOUN
ajst-10982	14	32	wall	wall	PROPN
ajst-10982	14	33	method	method	PROPN
ajst-10982	14	34	to	to	PART
ajst-10982	14	35	study	study	VERB
ajst-10982	14	36	roots	root	NOUN
ajst-10982	14	37	[	[	X
ajst-10982	14	38	3	3	NUM
ajst-10982	14	39	]	]	PUNCT
ajst-10982	14	40	,	,	PUNCT
ajst-10982	14	41	which	which	PRON
ajst-10982	14	42	made	make	VERB
ajst-10982	14	43	it	it	PRON
ajst-10982	14	44	difficult	difficult	ADJ
ajst-10982	14	45	to	to	PART
ajst-10982	14	46	realize	realize	VERB
ajst-10982	14	47	in	in	ADP
ajst-10982	14	48	-	-	PUNCT
ajst-10982	14	49	situ	situ	NOUN
ajst-10982	14	50	sampling	sampling	NOUN
ajst-10982	14	51	and	and	CCONJ
ajst-10982	14	52	accurate	accurate	ADJ
ajst-10982	14	53	measurement	measurement	NOUN
ajst-10982	14	54	of	of	ADP
ajst-10982	14	55	roots	root	NOUN
ajst-10982	14	56	.	.	PUNCT
ajst-10982	15	1	due	due	ADP
ajst-10982	15	2	to	to	ADP
ajst-10982	15	3	the	the	DET
ajst-10982	15	4	lack	lack	NOUN
ajst-10982	15	5	of	of	ADP
ajst-10982	15	6	effective	effective	ADJ
ajst-10982	15	7	non	non	ADJ
ajst-10982	15	8	-	-	ADJ
ajst-10982	15	9	destructive	destructive	ADJ
ajst-10982	15	10	testing	testing	NOUN
ajst-10982	15	11	methods	method	NOUN
ajst-10982	15	12	to	to	PART
ajst-10982	15	13	obtain	obtain	VERB
ajst-10982	15	14	the	the	DET
ajst-10982	15	15	actual	actual	ADJ
ajst-10982	15	16	state	state	NOUN
ajst-10982	15	17	of	of	ADP
ajst-10982	15	18	roots	root	NOUN
ajst-10982	15	19	in	in	ADP
ajst-10982	15	20	soil	soil	NOUN
ajst-10982	15	21	,	,	PUNCT
ajst-10982	15	22	the	the	DET
ajst-10982	15	23	in	in	ADP
ajst-10982	15	24	-	-	PUNCT
ajst-10982	15	25	depth	depth	NOUN
ajst-10982	15	26	study	study	NOUN
ajst-10982	15	27	of	of	ADP
ajst-10982	15	28	root	root	NOUN
ajst-10982	15	29	behavior	behavior	NOUN
ajst-10982	15	30	and	and	CCONJ
ajst-10982	15	31	characteristics	characteristic	NOUN
ajst-10982	15	32	is	be	AUX
ajst-10982	15	33	hindered	hinder	VERB
ajst-10982	15	34	.	.	PUNCT
ajst-10982	16	1	after	after	ADP
ajst-10982	16	2	the	the	DET
ajst-10982	16	3	1950s	1950	NOUN
ajst-10982	16	4	and	and	CCONJ
ajst-10982	16	5	1960s	1960	NOUN
ajst-10982	16	6	,	,	PUNCT
ajst-10982	16	7	due	due	ADP
ajst-10982	16	8	to	to	ADP
ajst-10982	16	9	the	the	DET
ajst-10982	16	10	development	development	NOUN
ajst-10982	16	11	of	of	ADP
ajst-10982	16	12	optical	optical	ADJ
ajst-10982	16	13	and	and	CCONJ
ajst-10982	16	14	microelectronics	microelectronic	NOUN
ajst-10982	16	15	technology	technology	NOUN
ajst-10982	16	16	,	,	PUNCT
ajst-10982	16	17	plant	plant	NOUN
ajst-10982	16	18	root	root	NOUN
ajst-10982	16	19	research	research	NOUN
ajst-10982	16	20	was	be	AUX
ajst-10982	16	21	further	far	ADV
ajst-10982	16	22	strengthened	strengthen	VERB
ajst-10982	16	23	,	,	PUNCT
ajst-10982	16	24	and	and	CCONJ
ajst-10982	16	25	non	non	ADJ
ajst-10982	16	26	-	-	ADJ
ajst-10982	16	27	destructive	destructive	ADJ
ajst-10982	16	28	or	or	CCONJ
ajst-10982	16	29	minimally	minimally	ADV
ajst-10982	16	30	invasive	invasive	ADJ
ajst-10982	16	31	methods	method	NOUN
ajst-10982	16	32	were	be	AUX
ajst-10982	16	33	adopted	adopt	VERB
ajst-10982	16	34	,	,	PUNCT
ajst-10982	16	35	such	such	ADJ
ajst-10982	16	36	as	as	ADP
ajst-10982	16	37	glass	glass	NOUN
ajst-10982	16	38	wall	wall	NOUN
ajst-10982	16	39	method	method	NOUN
ajst-10982	16	40	,	,	PUNCT
ajst-10982	16	41	endoscopy	endoscopy	VERB
ajst-10982	16	42	tube	tube	NOUN
ajst-10982	16	43	method	method	NOUN
ajst-10982	16	44	(	(	PUNCT
ajst-10982	16	45	microroot	microroot	NOUN
ajst-10982	16	46	canal	canal	NOUN
ajst-10982	16	47	)	)	PUNCT
ajst-10982	16	48	,	,	PUNCT
ajst-10982	16	49	container	container	NOUN
ajst-10982	16	50	method	method	NOUN
ajst-10982	16	51	,	,	PUNCT
ajst-10982	16	52	etc	etc	X
ajst-10982	16	53	.	.	X
ajst-10982	16	54	,	,	PUNCT
ajst-10982	16	55	to	to	PART
ajst-10982	16	56	minimize	minimize	VERB
ajst-10982	16	57	root	root	NOUN
ajst-10982	16	58	damage	damage	NOUN
ajst-10982	16	59	.	.	PUNCT
ajst-10982	17	1	among	among	ADP
ajst-10982	17	2	them	they	PRON
ajst-10982	17	3	,	,	PUNCT
ajst-10982	17	4	microroot	microroot	NOUN
ajst-10982	17	5	canal	canal	NOUN
ajst-10982	17	6	technology	technology	NOUN
ajst-10982	17	7	is	be	AUX
ajst-10982	17	8	a	a	DET
ajst-10982	17	9	method	method	NOUN
ajst-10982	17	10	of	of	ADP
ajst-10982	17	11	root	root	NOUN
ajst-10982	17	12	observation	observation	NOUN
ajst-10982	17	13	and	and	CCONJ
ajst-10982	17	14	research	research	NOUN
ajst-10982	17	15	,	,	PUNCT
ajst-10982	17	16	which	which	PRON
ajst-10982	17	17	uses	use	VERB
ajst-10982	17	18	a	a	DET
ajst-10982	17	19	transparent	transparent	ADJ
ajst-10982	17	20	test	test	NOUN
ajst-10982	17	21	tube	tube	NOUN
ajst-10982	17	22	inserted	insert	VERB
ajst-10982	17	23	into	into	ADP
ajst-10982	17	24	the	the	DET
ajst-10982	17	25	soil	soil	NOUN
ajst-10982	17	26	to	to	PART
ajst-10982	17	27	create	create	VERB
ajst-10982	17	28	a	a	DET
ajst-10982	17	29	small	small	ADJ
ajst-10982	17	30	observation	observation	NOUN
ajst-10982	17	31	window	window	NOUN
ajst-10982	17	32	,	,	PUNCT
ajst-10982	17	33	and	and	CCONJ
ajst-10982	17	34	uses	use	VERB
ajst-10982	17	35	a	a	DET
ajst-10982	17	36	multi	multi	ADJ
ajst-10982	17	37	-	-	ADJ
ajst-10982	17	38	tube	tube	ADJ
ajst-10982	17	39	observation	observation	NOUN
ajst-10982	17	40	lens	lens	NOUN
ajst-10982	17	41	or	or	CCONJ
ajst-10982	17	42	a	a	DET
ajst-10982	17	43	miniature	miniature	ADJ
ajst-10982	17	44	digital	digital	ADJ
ajst-10982	17	45	camera	camera	NOUN
ajst-10982	17	46	to	to	PART
ajst-10982	17	47	take	take	VERB
ajst-10982	17	48	pictures	picture	NOUN
ajst-10982	17	49	inside	inside	ADP
ajst-10982	17	50	the	the	DET
ajst-10982	17	51	tube	tube	NOUN
ajst-10982	17	52	,	,	PUNCT
ajst-10982	17	53	record	record	NOUN
ajst-10982	17	54	and	and	CCONJ
ajst-10982	17	55	observe	observe	VERB
ajst-10982	17	56	the	the	DET
ajst-10982	17	57	growth	growth	NOUN
ajst-10982	17	58	dynamics	dynamic	NOUN
ajst-10982	17	59	of	of	ADP
ajst-10982	17	60	new	new	ADJ
ajst-10982	17	61	roots	root	NOUN
ajst-10982	17	62	inside	inside	ADP
ajst-10982	17	63	and	and	CCONJ
ajst-10982	17	64	outside	outside	ADP
ajst-10982	17	65	the	the	DET
ajst-10982	17	66	tube	tube	NOUN
ajst-10982	17	67	[	[	X
ajst-10982	17	68	4	4	NUM
ajst-10982	17	69	]	]	PUNCT
ajst-10982	17	70	.	.	PUNCT
ajst-10982	18	1	the	the	DET
ajst-10982	18	2	image	image	NOUN
ajst-10982	18	3	data	datum	NOUN
ajst-10982	18	4	collected	collect	VERB
ajst-10982	18	5	in	in	ADP
ajst-10982	18	6	the	the	DET
ajst-10982	18	7	field	field	NOUN
ajst-10982	18	8	were	be	AUX
ajst-10982	18	9	applied	apply	VERB
ajst-10982	18	10	to	to	ADP
ajst-10982	18	11	the	the	DET
ajst-10982	18	12	indoor	indoor	ADJ
ajst-10982	18	13	special	special	ADJ
ajst-10982	18	14	computer	computer	NOUN
ajst-10982	18	15	software	software	NOUN
ajst-10982	18	16	to	to	PART
ajst-10982	18	17	calculate	calculate	VERB
ajst-10982	18	18	the	the	DET
ajst-10982	18	19	root	root	NOUN
ajst-10982	18	20	parameters	parameter	NOUN
ajst-10982	18	21	.	.	PUNCT
ajst-10982	19	1	the	the	DET
ajst-10982	19	2	advantage	advantage	NOUN
ajst-10982	19	3	of	of	ADP
ajst-10982	19	4	this	this	DET
ajst-10982	19	5	method	method	NOUN
ajst-10982	19	6	is	be	AUX
ajst-10982	19	7	that	that	SCONJ
ajst-10982	19	8	the	the	DET
ajst-10982	19	9	root	root	NOUN
ajst-10982	19	10	system	system	NOUN
ajst-10982	19	11	can	can	AUX
ajst-10982	19	12	be	be	AUX
ajst-10982	19	13	observed	observe	VERB
ajst-10982	19	14	and	and	CCONJ
ajst-10982	19	15	studied	study	VERB
ajst-10982	19	16	without	without	ADP
ajst-10982	19	17	loss	loss	NOUN
ajst-10982	19	18	,	,	PUNCT
ajst-10982	19	19	and	and	CCONJ
ajst-10982	19	20	the	the	DET
ajst-10982	19	21	dynamic	dynamic	ADJ
ajst-10982	19	22	growth	growth	NOUN
ajst-10982	19	23	process	process	NOUN
ajst-10982	19	24	of	of	ADP
ajst-10982	19	25	the	the	DET
ajst-10982	19	26	same	same	ADJ
ajst-10982	19	27	root	root	NOUN
ajst-10982	19	28	system	system	NOUN
ajst-10982	19	29	can	can	AUX
ajst-10982	19	30	be	be	AUX
ajst-10982	19	31	tracked	track	VERB
ajst-10982	19	32	and	and	CCONJ
ajst-10982	19	33	recorded	record	VERB
ajst-10982	19	34	in	in	ADP
ajst-10982	19	35	real	real	ADJ
ajst-10982	19	36	time	time	NOUN
ajst-10982	19	37	.	.	PUNCT
ajst-10982	20	1	however	however	ADV
ajst-10982	20	2	,	,	PUNCT
ajst-10982	20	3	its	its	PRON
ajst-10982	20	4	limitation	limitation	NOUN
ajst-10982	20	5	lies	lie	VERB
ajst-10982	20	6	in	in	ADP
ajst-10982	20	7	the	the	DET
ajst-10982	20	8	high	high	ADJ
ajst-10982	20	9	cost	cost	NOUN
ajst-10982	20	10	of	of	ADP
ajst-10982	20	11	equipment	equipment	NOUN
ajst-10982	20	12	and	and	CCONJ
ajst-10982	20	13	the	the	DET
ajst-10982	20	14	limited	limited	ADJ
ajst-10982	20	15	application	application	NOUN
ajst-10982	20	16	range	range	NOUN
ajst-10982	20	17	[	[	X
ajst-10982	20	18	5	5	NUM
ajst-10982	20	19	]	]	PUNCT
ajst-10982	20	20	.	.	PUNCT
ajst-10982	21	1	in	in	ADP
ajst-10982	21	2	addition	addition	NOUN
ajst-10982	21	3	,	,	PUNCT
ajst-10982	21	4	there	there	PRON
ajst-10982	21	5	are	be	VERB
ajst-10982	21	6	non	non	ADJ
ajst-10982	21	7	-	-	ADJ
ajst-10982	21	8	invasive	invasive	ADJ
ajst-10982	21	9	methods	method	NOUN
ajst-10982	21	10	sensor	sensor	NOUN
ajst-10982	21	11	method	method	NOUN
ajst-10982	21	12	.	.	PUNCT
ajst-10982	22	1	the	the	DET
ajst-10982	22	2	sensor	sensor	NOUN
ajst-10982	22	3	method	method	NOUN
ajst-10982	22	4	can	can	AUX
ajst-10982	22	5	be	be	AUX
ajst-10982	22	6	used	use	VERB
ajst-10982	22	7	for	for	ADP
ajst-10982	22	8	non	non	ADJ
ajst-10982	22	9	-	-	ADJ
ajst-10982	22	10	invasive	invasive	ADJ
ajst-10982	22	11	detection	detection	NOUN
ajst-10982	22	12	of	of	ADP
ajst-10982	22	13	root	root	NOUN
ajst-10982	22	14	phenotypes	phenotype	NOUN
ajst-10982	22	15	,	,	PUNCT
ajst-10982	22	16	does	do	AUX
ajst-10982	22	17	not	not	PART
ajst-10982	22	18	interfere	interfere	VERB
ajst-10982	22	19	with	with	ADP
ajst-10982	22	20	root	root	NOUN
ajst-10982	22	21	growth	growth	NOUN
ajst-10982	22	22	,	,	PUNCT
ajst-10982	22	23	does	do	AUX
ajst-10982	22	24	not	not	PART
ajst-10982	22	25	affect	affect	VERB
ajst-10982	22	26	soil	soil	NOUN
ajst-10982	22	27	structure	structure	NOUN
ajst-10982	22	28	,	,	PUNCT
ajst-10982	22	29	and	and	CCONJ
ajst-10982	22	30	can	can	AUX
ajst-10982	22	31	be	be	AUX
ajst-10982	22	32	continued	continue	VERB
ajst-10982	22	33	throughout	throughout	ADP
ajst-10982	22	34	the	the	DET
ajst-10982	22	35	breeding	breeding	NOUN
ajst-10982	22	36	period	period	NOUN
ajst-10982	22	37	without	without	ADP
ajst-10982	22	38	changing	change	VERB
ajst-10982	22	39	the	the	DET
ajst-10982	22	40	soil	soil	NOUN
ajst-10982	22	41	environment	environment	NOUN
ajst-10982	22	42	.	.	PUNCT
ajst-10982	23	1	the	the	DET
ajst-10982	23	2	sensor	sensor	NOUN
ajst-10982	23	3	performs	perform	VERB
ajst-10982	23	4	4d	4d	NUM
ajst-10982	23	5	root	root	NOUN
ajst-10982	23	6	imaging	imaging	NOUN
ajst-10982	23	7	,	,	PUNCT
ajst-10982	23	8	relying	rely	VERB
ajst-10982	23	9	on	on	ADP
ajst-10982	23	10	detectors	detector	NOUN
ajst-10982	23	11	placed	place	VERB
ajst-10982	23	12	around	around	ADP
ajst-10982	23	13	or	or	CCONJ
ajst-10982	23	14	inside	inside	ADP
ajst-10982	23	15	the	the	DET
ajst-10982	23	16	culture	culture	NOUN
ajst-10982	23	17	unit	unit	NOUN
ajst-10982	23	18	to	to	PART
ajst-10982	23	19	obtain	obtain	VERB
ajst-10982	23	20	information	information	NOUN
ajst-10982	23	21	through	through	ADP
ajst-10982	23	22	methods	method	NOUN
ajst-10982	23	23	such	such	ADJ
ajst-10982	23	24	as	as	ADP
ajst-10982	23	25	mri	mri	NOUN
ajst-10982	23	26	and	and	CCONJ
ajst-10982	23	27	x	x	NOUN
ajst-10982	23	28	-	-	NOUN
ajst-10982	23	29	ray	ray	NOUN
ajst-10982	23	30	tomography	tomography	NOUN
ajst-10982	23	31	.	.	PUNCT
ajst-10982	24	1	the	the	DET
ajst-10982	24	2	image	image	NOUN
ajst-10982	24	3	obtained	obtain	VERB
ajst-10982	24	4	from	from	ADP
ajst-10982	24	5	a	a	DET
ajst-10982	24	6	single	single	ADJ
ajst-10982	24	7	scan	scan	NOUN
ajst-10982	24	8	needs	need	NOUN
ajst-10982	24	9	to	to	PART
ajst-10982	24	10	be	be	AUX
ajst-10982	24	11	filtered	filter	VERB
ajst-10982	24	12	,	,	PUNCT
ajst-10982	24	13	analyzed	analyze	VERB
ajst-10982	24	14	,	,	PUNCT
ajst-10982	24	15	corrected	correct	VERB
ajst-10982	24	16	,	,	PUNCT
ajst-10982	24	17	fitted	fit	VERB
ajst-10982	24	18	and	and	CCONJ
ajst-10982	24	19	reconstructed	reconstruct	VERB
ajst-10982	24	20	in	in	ADP
ajst-10982	24	21	three	three	NUM
ajst-10982	24	22	dimensions	dimension	NOUN
ajst-10982	24	23	to	to	PART
ajst-10982	24	24	obtain	obtain	VERB
ajst-10982	24	25	the	the	DET
ajst-10982	24	26	final	final	ADJ
ajst-10982	24	27	result	result	NOUN
ajst-10982	24	28	.	.	PUNCT
ajst-10982	25	1	however	however	ADV
ajst-10982	25	2	,	,	PUNCT
ajst-10982	25	3	complex	complex	ADJ
ajst-10982	25	4	soil	soil	NOUN
ajst-10982	25	5	composition	composition	NOUN
ajst-10982	25	6	and	and	CCONJ
ajst-10982	25	7	water	water	NOUN
ajst-10982	25	8	restrictions	restriction	NOUN
ajst-10982	25	9	can	can	AUX
ajst-10982	25	10	interfere	interfere	VERB
ajst-10982	25	11	with	with	ADP
ajst-10982	25	12	the	the	DET
ajst-10982	25	13	results	result	NOUN
ajst-10982	25	14	,	,	PUNCT
ajst-10982	25	15	as	as	SCONJ
ajst-10982	25	16	can	can	AUX
ajst-10982	25	17	the	the	DET
ajst-10982	25	18	depth	depth	NOUN
ajst-10982	25	19	of	of	ADP
ajst-10982	25	20	penetration	penetration	NOUN
ajst-10982	25	21	of	of	ADP
ajst-10982	25	22	the	the	DET
ajst-10982	25	23	rays	ray	NOUN
ajst-10982	25	24	.	.	PUNCT
ajst-10982	26	1	therefore	therefore	ADV
ajst-10982	26	2	,	,	PUNCT
ajst-10982	26	3	most	most	ADJ
ajst-10982	26	4	of	of	ADP
ajst-10982	26	5	the	the	DET
ajst-10982	26	6	traditional	traditional	ADJ
ajst-10982	26	7	methods	method	NOUN
ajst-10982	26	8	for	for	ADP
ajst-10982	26	9	obtaining	obtain	VERB
ajst-10982	26	10	root	root	NOUN
ajst-10982	26	11	phenotype	phenotype	NOUN
ajst-10982	26	12	information	information	NOUN
ajst-10982	26	13	are	be	AUX
ajst-10982	26	14	difficult	difficult	ADJ
ajst-10982	26	15	to	to	PART
ajst-10982	26	16	achieve	achieve	VERB
ajst-10982	26	17	non	non	ADJ
ajst-10982	26	18	-	-	ADJ
ajst-10982	26	19	destructive	destructive	ADJ
ajst-10982	26	20	,	,	PUNCT
ajst-10982	26	21	dynamic	dynamic	ADJ
ajst-10982	26	22	,	,	PUNCT
ajst-10982	26	23	accurate	accurate	ADJ
ajst-10982	26	24	and	and	CCONJ
ajst-10982	26	25	quantitative	quantitative	ADJ
ajst-10982	26	26	description	description	NOUN
ajst-10982	26	27	of	of	ADP
ajst-10982	26	28	plant	plant	NOUN
ajst-10982	26	29	root	root	NOUN
ajst-10982	26	30	configuration	configuration	NOUN
ajst-10982	26	31	,	,	PUNCT
ajst-10982	26	32	which	which	PRON
ajst-10982	26	33	can	can	AUX
ajst-10982	26	34	not	not	PART
ajst-10982	26	35	meet	meet	VERB
ajst-10982	26	36	the	the	DET
ajst-10982	26	37	actual	actual	ADJ
ajst-10982	26	38	needs	need	NOUN
ajst-10982	26	39	of	of	ADP
ajst-10982	26	40	current	current	ADJ
ajst-10982	26	41	in	in	ADP
ajst-10982	26	42	-	-	PUNCT
ajst-10982	26	43	situ	situ	NOUN
ajst-10982	26	44	root	root	NOUN
ajst-10982	26	45	research	research	NOUN
ajst-10982	26	46	.	.	PUNCT
ajst-10982	27	1	2.2	2.2	NUM
ajst-10982	27	2	.	.	PUNCT
ajst-10982	27	3	plant	plant	NOUN
ajst-10982	27	4	root	root	NOUN
ajst-10982	27	5	imaging	imaging	NOUN
ajst-10982	27	6	in	in	ADP
ajst-10982	27	7	situ	situ	ADJ
ajst-10982	27	8	root	root	NOUN
ajst-10982	27	9	detection	detection	NOUN
ajst-10982	27	10	is	be	AUX
ajst-10982	27	11	the	the	DET
ajst-10982	27	12	imaging	imaging	NOUN
ajst-10982	27	13	detection	detection	NOUN
ajst-10982	27	14	of	of	ADP
ajst-10982	27	15	roots	root	NOUN
ajst-10982	27	16	under	under	ADP
ajst-10982	27	17	the	the	DET
ajst-10982	27	18	condition	condition	NOUN
ajst-10982	27	19	of	of	ADP
ajst-10982	27	20	avoiding	avoid	VERB
ajst-10982	27	21	root	root	NOUN
ajst-10982	27	22	damage	damage	NOUN
ajst-10982	27	23	.	.	PUNCT
ajst-10982	28	1	with	with	ADP
ajst-10982	28	2	the	the	DET
ajst-10982	28	3	continuous	continuous	ADJ
ajst-10982	28	4	development	development	NOUN
ajst-10982	28	5	and	and	CCONJ
ajst-10982	28	6	progress	progress	NOUN
ajst-10982	28	7	of	of	ADP
ajst-10982	28	8	high	high	ADJ
ajst-10982	28	9	and	and	CCONJ
ajst-10982	28	10	new	new	ADJ
ajst-10982	28	11	technologies	technology	NOUN
ajst-10982	28	12	,	,	PUNCT
ajst-10982	28	13	currently	currently	ADV
ajst-10982	28	14	commonly	commonly	ADV
ajst-10982	28	15	used	use	VERB
ajst-10982	28	16	root	root	NOUN
ajst-10982	28	17	in	in	ADP
ajst-10982	28	18	-	-	PUNCT
ajst-10982	28	19	situ	situ	NOUN
ajst-10982	28	20	detection	detection	NOUN
ajst-10982	28	21	methods	method	NOUN
ajst-10982	28	22	include	include	VERB
ajst-10982	28	23	x	x	NOUN
ajst-10982	28	24	-	-	NOUN
ajst-10982	28	25	ray	ray	NOUN
ajst-10982	28	26	tomography	tomography	NOUN
ajst-10982	28	27	(	(	PUNCT
ajst-10982	28	28	xct	xct	PROPN
ajst-10982	28	29	)	)	PUNCT
ajst-10982	29	1	[	[	X
ajst-10982	29	2	6	6	NUM
ajst-10982	29	3	]	]	PUNCT
ajst-10982	29	4	,	,	PUNCT
ajst-10982	29	5	magnetic	magnetic	ADJ
ajst-10982	29	6	resonance	resonance	NOUN
ajst-10982	29	7	imaging	imaging	NOUN
ajst-10982	29	8	(	(	PUNCT
ajst-10982	29	9	mri	mri	NOUN
ajst-10982	29	10	)	)	PUNCT
ajst-10982	30	1	[	[	X
ajst-10982	30	2	7	7	X
ajst-10982	30	3	]	]	PUNCT
ajst-10982	30	4	and	and	CCONJ
ajst-10982	30	5	digital	digital	ADJ
ajst-10982	30	6	device	device	NOUN
ajst-10982	30	7	imaging	imaging	NOUN
ajst-10982	31	1	[	[	X
ajst-10982	31	2	8	8	NUM
ajst-10982	31	3	]	]	PUNCT
ajst-10982	31	4	.	.	PUNCT
ajst-10982	32	1	xct	xct	PROPN
ajst-10982	32	2	of	of	ADP
ajst-10982	32	3	roots	root	NOUN
ajst-10982	32	4	scans	scan	VERB
ajst-10982	32	5	the	the	DET
ajst-10982	32	6	in	in	ADP
ajst-10982	32	7	-	-	PUNCT
ajst-10982	32	8	situ	situ	NOUN
ajst-10982	32	9	root	root	NOUN
ajst-10982	32	10	soil	soil	NOUN
ajst-10982	32	11	with	with	ADP
ajst-10982	32	12	x	x	NOUN
ajst-10982	32	13	-	-	NOUN
ajst-10982	32	14	rays	ray	NOUN
ajst-10982	32	15	to	to	PART
ajst-10982	32	16	obtain	obtain	VERB
ajst-10982	32	17	attenuation	attenuation	NOUN
ajst-10982	32	18	coefficients	coefficient	NOUN
ajst-10982	32	19	of	of	ADP
ajst-10982	32	20	cross	cross	ADJ
ajst-10982	32	21	-	-	ADJ
ajst-10982	32	22	sectional	sectional	ADJ
ajst-10982	32	23	faults	fault	NOUN
ajst-10982	32	24	of	of	ADP
ajst-10982	32	25	different	different	ADJ
ajst-10982	32	26	objects	object	NOUN
ajst-10982	32	27	,	,	PUNCT
ajst-10982	32	28	and	and	CCONJ
ajst-10982	32	29	then	then	ADV
ajst-10982	32	30	realizes	realize	VERB
ajst-10982	32	31	three	three	NUM
ajst-10982	32	32	-	-	PUNCT
ajst-10982	32	33	dimensional	dimensional	ADJ
ajst-10982	32	34	26	26	NUM
ajst-10982	32	35	visualization	visualization	NOUN
ajst-10982	32	36	of	of	ADP
ajst-10982	32	37	plant	plant	NOUN
ajst-10982	32	38	root	root	NOUN
ajst-10982	32	39	configuration	configuration	NOUN
ajst-10982	32	40	through	through	ADP
ajst-10982	32	41	image	image	NOUN
ajst-10982	32	42	fault	fault	NOUN
ajst-10982	32	43	reconstruction	reconstruction	NOUN
ajst-10982	32	44	algorithm	algorithm	NOUN
ajst-10982	33	1	[	[	X
ajst-10982	33	2	9][10][11	9][10][11	X
ajst-10982	33	3	]	]	PUNCT
ajst-10982	33	4	.	.	PUNCT
ajst-10982	34	1	in	in	ADP
ajst-10982	34	2	the	the	DET
ajst-10982	34	3	1990s	1990	NOUN
ajst-10982	34	4	,	,	PUNCT
ajst-10982	34	5	wantanabe	wantanabe	NOUN
ajst-10982	34	6	et	et	PROPN
ajst-10982	34	7	al	al	PROPN
ajst-10982	34	8	.	.	PUNCT
ajst-10982	35	1	[	[	X
ajst-10982	35	2	12	12	NUM
ajst-10982	35	3	]	]	PUNCT
ajst-10982	35	4	first	first	ADV
ajst-10982	35	5	applied	apply	VERB
ajst-10982	35	6	xct	xct	PROPN
ajst-10982	35	7	technology	technology	PROPN
ajst-10982	35	8	to	to	ADP
ajst-10982	35	9	the	the	DET
ajst-10982	35	10	analysis	analysis	NOUN
ajst-10982	35	11	and	and	CCONJ
ajst-10982	35	12	study	study	NOUN
ajst-10982	35	13	of	of	ADP
ajst-10982	35	14	plant	plant	NOUN
ajst-10982	35	15	roots	root	NOUN
ajst-10982	35	16	,	,	PUNCT
ajst-10982	35	17	but	but	CCONJ
ajst-10982	35	18	due	due	ADP
ajst-10982	35	19	to	to	ADP
ajst-10982	35	20	the	the	DET
ajst-10982	35	21	limitations	limitation	NOUN
ajst-10982	35	22	of	of	ADP
ajst-10982	35	23	technical	technical	ADJ
ajst-10982	35	24	conditions	condition	NOUN
ajst-10982	35	25	,	,	PUNCT
ajst-10982	35	26	the	the	DET
ajst-10982	35	27	complete	complete	ADJ
ajst-10982	35	28	form	form	NOUN
ajst-10982	35	29	of	of	ADP
ajst-10982	35	30	plant	plant	NOUN
ajst-10982	35	31	roots	root	NOUN
ajst-10982	35	32	could	could	AUX
ajst-10982	35	33	not	not	PART
ajst-10982	35	34	be	be	AUX
ajst-10982	35	35	clearly	clearly	ADV
ajst-10982	35	36	observed	observe	VERB
ajst-10982	35	37	.	.	PUNCT
ajst-10982	36	1	with	with	ADP
ajst-10982	36	2	the	the	DET
ajst-10982	36	3	advancement	advancement	NOUN
ajst-10982	36	4	of	of	ADP
ajst-10982	36	5	technology	technology	NOUN
ajst-10982	36	6	,	,	PUNCT
ajst-10982	36	7	han	han	PROPN
ajst-10982	36	8	et	et	PROPN
ajst-10982	36	9	al	al	PROPN
ajst-10982	36	10	.	.	PUNCT
ajst-10982	37	1	[	[	X
ajst-10982	37	2	13	13	NUM
ajst-10982	37	3	]	]	PUNCT
ajst-10982	37	4	discussed	discuss	VERB
ajst-10982	37	5	the	the	DET
ajst-10982	37	6	common	common	ADJ
ajst-10982	37	7	diseases	disease	NOUN
ajst-10982	37	8	of	of	ADP
ajst-10982	37	9	potato	potato	NOUN
ajst-10982	37	10	in	in	ADP
ajst-10982	37	11	soil	soil	NOUN
ajst-10982	37	12	on	on	ADP
ajst-10982	37	13	the	the	DET
ajst-10982	37	14	basis	basis	NOUN
ajst-10982	37	15	of	of	ADP
ajst-10982	37	16	xct	xct	PROPN
ajst-10982	37	17	imaging	imaging	PROPN
ajst-10982	37	18	technology	technology	NOUN
ajst-10982	37	19	,	,	PUNCT
ajst-10982	37	20	and	and	CCONJ
ajst-10982	37	21	proved	prove	VERB
ajst-10982	37	22	the	the	DET
ajst-10982	37	23	potential	potential	NOUN
ajst-10982	37	24	of	of	ADP
ajst-10982	37	25	xct	xct	PROPN
ajst-10982	37	26	observation	observation	NOUN
ajst-10982	37	27	method	method	NOUN
ajst-10982	37	28	in	in	ADP
ajst-10982	37	29	plant	plant	NOUN
ajst-10982	37	30	pathology	pathology	NOUN
ajst-10982	37	31	research	research	NOUN
ajst-10982	37	32	.	.	PUNCT
ajst-10982	38	1	subsequently	subsequently	ADV
ajst-10982	38	2	,	,	PUNCT
ajst-10982	38	3	zhou	zhou	PROPN
ajst-10982	38	4	xuecheng	xuecheng	PROPN
ajst-10982	38	5	et	et	PROPN
ajst-10982	38	6	al	al	PROPN
ajst-10982	38	7	.	.	PUNCT
ajst-10982	39	1	[	[	X
ajst-10982	39	2	14	14	NUM
ajst-10982	39	3	]	]	PUNCT
ajst-10982	39	4	conducted	conduct	VERB
ajst-10982	39	5	qualitative	qualitative	ADJ
ajst-10982	39	6	tomography	tomography	NOUN
ajst-10982	39	7	scanning	scanning	NOUN
ajst-10982	39	8	of	of	ADP
ajst-10982	39	9	root	root	NOUN
ajst-10982	39	10	images	image	NOUN
ajst-10982	39	11	by	by	ADP
ajst-10982	39	12	x	x	NOUN
ajst-10982	39	13	-	-	NOUN
ajst-10982	39	14	ray	ray	NOUN
ajst-10982	39	15	,	,	PUNCT
ajst-10982	39	16	and	and	CCONJ
ajst-10982	39	17	used	use	VERB
ajst-10982	39	18	gray	gray	ADJ
ajst-10982	39	19	histogram	histogram	NOUN
ajst-10982	39	20	analysis	analysis	NOUN
ajst-10982	39	21	to	to	PART
ajst-10982	39	22	find	find	VERB
ajst-10982	39	23	the	the	DET
ajst-10982	39	24	overall	overall	ADJ
ajst-10982	39	25	characteristics	characteristic	NOUN
ajst-10982	39	26	of	of	ADP
ajst-10982	39	27	gray	gray	ADJ
ajst-10982	39	28	distribution	distribution	NOUN
ajst-10982	39	29	of	of	ADP
ajst-10982	39	30	in	in	ADP
ajst-10982	39	31	situ	situ	ADJ
ajst-10982	39	32	ct	ct	NOUN
ajst-10982	39	33	images	image	NOUN
ajst-10982	39	34	of	of	ADP
ajst-10982	39	35	plant	plant	NOUN
ajst-10982	39	36	roots	root	NOUN
ajst-10982	39	37	,	,	PUNCT
ajst-10982	39	38	so	so	SCONJ
ajst-10982	39	39	as	as	SCONJ
ajst-10982	39	40	to	to	PART
ajst-10982	39	41	quickly	quickly	ADV
ajst-10982	39	42	and	and	CCONJ
ajst-10982	39	43	accurately	accurately	ADV
ajst-10982	39	44	detect	detect	VERB
ajst-10982	39	45	root	root	NOUN
ajst-10982	39	46	characteristics	characteristic	NOUN
ajst-10982	39	47	.	.	PUNCT
ajst-10982	40	1	in	in	ADP
ajst-10982	40	2	recent	recent	ADJ
ajst-10982	40	3	years	year	NOUN
ajst-10982	40	4	,	,	PUNCT
ajst-10982	40	5	zhao	zhao	PROPN
ajst-10982	40	6	xu	xu	PROPN
ajst-10982	40	7	et	et	PROPN
ajst-10982	40	8	al	al	PROPN
ajst-10982	40	9	.	.	PUNCT
ajst-10982	41	1	[	[	X
ajst-10982	41	2	15	15	NUM
ajst-10982	41	3	]	]	PUNCT
ajst-10982	41	4	constructed	construct	VERB
ajst-10982	41	5	a	a	DET
ajst-10982	41	6	three	three	NUM
ajst-10982	41	7	-	-	PUNCT
ajst-10982	41	8	dimensional	dimensional	ADJ
ajst-10982	41	9	lossless	lossless	ADJ
ajst-10982	41	10	geometric	geometric	ADJ
ajst-10982	41	11	model	model	NOUN
ajst-10982	41	12	of	of	ADP
ajst-10982	41	13	maize	maize	NOUN
ajst-10982	41	14	in	in	ADP
ajst-10982	41	15	-	-	PUNCT
ajst-10982	41	16	situ	situ	NOUN
ajst-10982	41	17	root	root	NOUN
ajst-10982	41	18	system	system	NOUN
ajst-10982	41	19	by	by	ADP
ajst-10982	41	20	combining	combine	VERB
ajst-10982	41	21	xct	xct	PROPN
ajst-10982	41	22	in	in	ADP
ajst-10982	41	23	-	-	PUNCT
ajst-10982	41	24	situ	situ	NOUN
ajst-10982	41	25	scanning	scanning	NOUN
ajst-10982	41	26	technology	technology	NOUN
ajst-10982	41	27	and	and	CCONJ
ajst-10982	41	28	filtered	filter	VERB
ajst-10982	41	29	back	back	ADP
ajst-10982	41	30	projection	projection	NOUN
ajst-10982	41	31	reconstruction	reconstruction	NOUN
ajst-10982	41	32	method	method	NOUN
ajst-10982	41	33	.	.	PUNCT
ajst-10982	42	1	in	in	ADP
ajst-10982	42	2	addition	addition	NOUN
ajst-10982	42	3	,	,	PUNCT
ajst-10982	42	4	chen	chen	PROPN
ajst-10982	42	5	jun	jun	PROPN
ajst-10982	42	6	[	[	X
ajst-10982	42	7	16	16	NUM
ajst-10982	42	8	]	]	PUNCT
ajst-10982	42	9	used	use	VERB
ajst-10982	42	10	ct	ct	NUM
ajst-10982	42	11	imaging	imaging	NOUN
ajst-10982	42	12	technology	technology	NOUN
ajst-10982	42	13	to	to	PART
ajst-10982	42	14	obtain	obtain	VERB
ajst-10982	42	15	ct	ct	NUM
ajst-10982	42	16	images	image	NOUN
ajst-10982	42	17	of	of	ADP
ajst-10982	42	18	corn	corn	NOUN
ajst-10982	42	19	roots	root	NOUN
ajst-10982	42	20	,	,	PUNCT
ajst-10982	42	21	and	and	CCONJ
ajst-10982	42	22	used	use	VERB
ajst-10982	42	23	image	image	NOUN
ajst-10982	42	24	processing	processing	NOUN
ajst-10982	42	25	technology	technology	NOUN
ajst-10982	42	26	to	to	PART
ajst-10982	42	27	conduct	conduct	VERB
ajst-10982	42	28	nondestructive	nondestructive	ADJ
ajst-10982	42	29	testing	testing	NOUN
ajst-10982	42	30	of	of	ADP
ajst-10982	42	31	samples	sample	NOUN
ajst-10982	42	32	.	.	PUNCT
ajst-10982	43	1	xct	xct	PROPN
ajst-10982	43	2	technology	technology	PROPN
ajst-10982	43	3	has	have	AUX
ajst-10982	43	4	played	play	VERB
ajst-10982	43	5	a	a	DET
ajst-10982	43	6	great	great	ADJ
ajst-10982	43	7	role	role	NOUN
ajst-10982	43	8	in	in	ADP
ajst-10982	43	9	promoting	promote	VERB
ajst-10982	43	10	the	the	DET
ajst-10982	43	11	research	research	NOUN
ajst-10982	43	12	of	of	ADP
ajst-10982	43	13	in	in	ADP
ajst-10982	43	14	situ	situ	ADJ
ajst-10982	43	15	root	root	NOUN
ajst-10982	43	16	imaging	imaging	NOUN
ajst-10982	43	17	of	of	ADP
ajst-10982	43	18	plants	plant	NOUN
ajst-10982	43	19	.	.	PUNCT
ajst-10982	44	1	however	however	ADV
ajst-10982	44	2	,	,	PUNCT
ajst-10982	44	3	xct	xct	PROPN
ajst-10982	44	4	technology	technology	PROPN
ajst-10982	44	5	only	only	ADV
ajst-10982	44	6	relies	rely	VERB
ajst-10982	44	7	on	on	ADP
ajst-10982	44	8	the	the	DET
ajst-10982	44	9	difference	difference	NOUN
ajst-10982	44	10	of	of	ADP
ajst-10982	44	11	a	a	DET
ajst-10982	44	12	single	single	ADJ
ajst-10982	44	13	attenuation	attenuation	NOUN
ajst-10982	44	14	coefficient	coefficient	NOUN
ajst-10982	44	15	between	between	ADP
ajst-10982	44	16	substances	substance	NOUN
ajst-10982	44	17	to	to	PART
ajst-10982	44	18	determine	determine	VERB
ajst-10982	44	19	the	the	DET
ajst-10982	44	20	imaging	imaging	NOUN
ajst-10982	44	21	features	feature	NOUN
ajst-10982	44	22	.	.	PUNCT
ajst-10982	45	1	when	when	SCONJ
ajst-10982	45	2	confronted	confront	VERB
ajst-10982	45	3	with	with	ADP
ajst-10982	45	4	complex	complex	ADJ
ajst-10982	45	5	soil	soil	NOUN
ajst-10982	45	6	environment	environment	NOUN
ajst-10982	45	7	and	and	CCONJ
ajst-10982	45	8	root	root	NOUN
ajst-10982	45	9	distribution	distribution	NOUN
ajst-10982	45	10	,	,	PUNCT
ajst-10982	45	11	the	the	DET
ajst-10982	45	12	contrast	contrast	NOUN
ajst-10982	45	13	will	will	AUX
ajst-10982	45	14	deteriorate	deteriorate	VERB
ajst-10982	45	15	and	and	CCONJ
ajst-10982	45	16	root	root	NOUN
ajst-10982	45	17	noise	noise	NOUN
ajst-10982	45	18	will	will	AUX
ajst-10982	45	19	appear	appear	VERB
ajst-10982	45	20	in	in	ADP
ajst-10982	45	21	the	the	DET
ajst-10982	45	22	imaging	imaging	NOUN
ajst-10982	45	23	results	result	NOUN
ajst-10982	45	24	,	,	PUNCT
ajst-10982	45	25	which	which	PRON
ajst-10982	45	26	brings	bring	VERB
ajst-10982	45	27	difficulties	difficulty	NOUN
ajst-10982	45	28	to	to	PART
ajst-10982	45	29	root	root	VERB
ajst-10982	45	30	image	image	NOUN
ajst-10982	45	31	segmentation	segmentation	NOUN
ajst-10982	45	32	research	research	NOUN
ajst-10982	45	33	and	and	CCONJ
ajst-10982	45	34	leads	lead	VERB
ajst-10982	45	35	to	to	ADP
ajst-10982	45	36	errors	error	NOUN
ajst-10982	45	37	in	in	ADP
ajst-10982	45	38	the	the	DET
ajst-10982	45	39	subsequent	subsequent	ADJ
ajst-10982	45	40	statistical	statistical	ADJ
ajst-10982	45	41	data	datum	NOUN
ajst-10982	45	42	of	of	ADP
ajst-10982	45	43	plant	plant	NOUN
ajst-10982	45	44	root	root	NOUN
ajst-10982	45	45	phenotype	phenotype	NOUN
ajst-10982	46	1	[	[	X
ajst-10982	46	2	17	17	NUM
ajst-10982	46	3	]	]	PUNCT
ajst-10982	46	4	.	.	PUNCT
ajst-10982	47	1	magnetic	magnetic	ADJ
ajst-10982	47	2	resonance	resonance	NOUN
ajst-10982	47	3	imaging	imaging	NOUN
ajst-10982	47	4	uses	use	VERB
ajst-10982	47	5	radio	radio	NOUN
ajst-10982	47	6	frequency	frequency	NOUN
ajst-10982	47	7	electromagnetic	electromagnetic	ADJ
ajst-10982	47	8	waves	wave	NOUN
ajst-10982	47	9	to	to	PART
ajst-10982	47	10	obtain	obtain	VERB
ajst-10982	47	11	image	image	NOUN
ajst-10982	47	12	information	information	NOUN
ajst-10982	47	13	,	,	PUNCT
ajst-10982	47	14	codes	code	VERB
ajst-10982	47	15	signals	signal	NOUN
ajst-10982	47	16	sent	send	VERB
ajst-10982	47	17	out	out	ADP
ajst-10982	47	18	by	by	ADP
ajst-10982	47	19	detecting	detect	VERB
ajst-10982	47	20	different	different	ADJ
ajst-10982	47	21	positions	position	NOUN
ajst-10982	47	22	of	of	ADP
ajst-10982	47	23	magnetic	magnetic	ADJ
ajst-10982	47	24	field	field	NOUN
ajst-10982	47	25	cores	core	NOUN
ajst-10982	47	26	,	,	PUNCT
ajst-10982	47	27	and	and	CCONJ
ajst-10982	47	28	presents	present	VERB
ajst-10982	47	29	the	the	DET
ajst-10982	47	30	internal	internal	ADJ
ajst-10982	47	31	structure	structure	NOUN
ajst-10982	47	32	and	and	CCONJ
ajst-10982	47	33	organizational	organizational	ADJ
ajst-10982	47	34	morphology	morphology	NOUN
ajst-10982	47	35	of	of	ADP
ajst-10982	47	36	scanned	scan	VERB
ajst-10982	47	37	objects	object	NOUN
ajst-10982	47	38	on	on	ADP
ajst-10982	47	39	the	the	DET
ajst-10982	47	40	image	image	NOUN
ajst-10982	47	41	,	,	PUNCT
ajst-10982	47	42	thus	thus	ADV
ajst-10982	47	43	using	use	VERB
ajst-10982	47	44	computer	computer	NOUN
ajst-10982	47	45	image	image	NOUN
ajst-10982	47	46	reconstruction	reconstruction	NOUN
ajst-10982	47	47	to	to	PART
ajst-10982	47	48	generate	generate	VERB
ajst-10982	47	49	images	image	NOUN
ajst-10982	47	50	[	[	X
ajst-10982	47	51	18	18	NUM
ajst-10982	47	52	]	]	PUNCT
ajst-10982	47	53	.	.	PUNCT
ajst-10982	48	1	this	this	DET
ajst-10982	48	2	observation	observation	NOUN
ajst-10982	48	3	technology	technology	NOUN
ajst-10982	48	4	has	have	AUX
ajst-10982	48	5	been	be	AUX
ajst-10982	48	6	applied	apply	VERB
ajst-10982	48	7	in	in	ADP
ajst-10982	48	8	many	many	ADJ
ajst-10982	48	9	fields	field	NOUN
ajst-10982	48	10	of	of	ADP
ajst-10982	48	11	plant	plant	NOUN
ajst-10982	48	12	root	root	NOUN
ajst-10982	48	13	research	research	NOUN
ajst-10982	48	14	.	.	PUNCT
ajst-10982	49	1	for	for	ADP
ajst-10982	49	2	example	example	NOUN
ajst-10982	49	3	,	,	PUNCT
ajst-10982	49	4	super	super	ADJ
ajst-10982	49	5	-	-	ADJ
ajst-10982	49	6	resolution	resolution	ADJ
ajst-10982	49	7	images	image	NOUN
ajst-10982	49	8	of	of	ADP
ajst-10982	49	9	plant	plant	NOUN
ajst-10982	49	10	roots	root	NOUN
ajst-10982	49	11	were	be	AUX
ajst-10982	49	12	obtained	obtain	VERB
ajst-10982	49	13	by	by	ADP
ajst-10982	49	14	three	three	NUM
ajst-10982	49	15	-	-	PUNCT
ajst-10982	49	16	dimensional	dimensional	ADJ
ajst-10982	49	17	reconstruction	reconstruction	NOUN
ajst-10982	49	18	of	of	ADP
ajst-10982	49	19	plant	plant	NOUN
ajst-10982	49	20	roots	root	NOUN
ajst-10982	49	21	[	[	X
ajst-10982	49	22	19	19	NUM
ajst-10982	49	23	]	]	PUNCT
ajst-10982	49	24	,	,	PUNCT
ajst-10982	49	25	dynamic	dynamic	ADJ
ajst-10982	49	26	distribution	distribution	NOUN
ajst-10982	49	27	of	of	ADP
ajst-10982	49	28	water	water	NOUN
ajst-10982	49	29	and	and	CCONJ
ajst-10982	49	30	sugar	sugar	NOUN
ajst-10982	49	31	in	in	ADP
ajst-10982	49	32	wheat	wheat	NOUN
ajst-10982	49	33	filling	filling	NOUN
ajst-10982	49	34	period	period	NOUN
ajst-10982	49	35	[	[	X
ajst-10982	49	36	20	20	NUM
ajst-10982	49	37	]	]	PUNCT
ajst-10982	49	38	,	,	PUNCT
ajst-10982	49	39	and	and	CCONJ
ajst-10982	49	40	underground	underground	ADJ
ajst-10982	49	41	pathological	pathological	ADJ
ajst-10982	49	42	symptoms	symptom	NOUN
ajst-10982	49	43	of	of	ADP
ajst-10982	49	44	sugar	sugar	NOUN
ajst-10982	49	45	beet	beet	NOUN
ajst-10982	50	1	[	[	X
ajst-10982	50	2	21	21	NUM
ajst-10982	50	3	]	]	PUNCT
ajst-10982	50	4	.	.	PUNCT
ajst-10982	51	1	although	although	SCONJ
ajst-10982	51	2	the	the	DET
ajst-10982	51	3	technology	technology	NOUN
ajst-10982	51	4	will	will	AUX
ajst-10982	51	5	not	not	PART
ajst-10982	51	6	cause	cause	VERB
ajst-10982	51	7	noise	noise	NOUN
ajst-10982	51	8	due	due	ADP
ajst-10982	51	9	to	to	ADP
ajst-10982	51	10	the	the	DET
ajst-10982	51	11	similar	similar	ADJ
ajst-10982	51	12	density	density	NOUN
ajst-10982	51	13	of	of	ADP
ajst-10982	51	14	soil	soil	NOUN
ajst-10982	51	15	and	and	CCONJ
ajst-10982	51	16	roots	root	NOUN
ajst-10982	51	17	,	,	PUNCT
ajst-10982	51	18	the	the	DET
ajst-10982	51	19	detection	detection	NOUN
ajst-10982	51	20	of	of	ADP
ajst-10982	51	21	trace	trace	NOUN
ajst-10982	51	22	elements	element	NOUN
ajst-10982	51	23	such	such	ADJ
ajst-10982	51	24	as	as	ADP
ajst-10982	51	25	iron	iron	NOUN
ajst-10982	51	26	will	will	AUX
ajst-10982	51	27	interfere	interfere	VERB
ajst-10982	51	28	with	with	ADP
ajst-10982	51	29	the	the	DET
ajst-10982	51	30	nmr	nmr	NOUN
ajst-10982	51	31	signal	signal	NOUN
ajst-10982	51	32	,	,	PUNCT
ajst-10982	51	33	resulting	result	VERB
ajst-10982	51	34	in	in	ADP
ajst-10982	51	35	greater	great	ADJ
ajst-10982	51	36	noise	noise	NOUN
ajst-10982	51	37	in	in	ADP
ajst-10982	51	38	the	the	DET
ajst-10982	51	39	root	root	NOUN
ajst-10982	51	40	image	image	NOUN
ajst-10982	51	41	,	,	PUNCT
ajst-10982	51	42	making	make	VERB
ajst-10982	51	43	it	it	PRON
ajst-10982	51	44	difficult	difficult	ADJ
ajst-10982	51	45	to	to	PART
ajst-10982	51	46	image	image	VERB
ajst-10982	51	47	.	.	PUNCT
ajst-10982	52	1	in	in	ADP
ajst-10982	52	2	recent	recent	ADJ
ajst-10982	52	3	years	year	NOUN
ajst-10982	52	4	,	,	PUNCT
ajst-10982	52	5	digital	digital	ADJ
ajst-10982	52	6	technology	technology	NOUN
ajst-10982	52	7	has	have	AUX
ajst-10982	52	8	become	become	VERB
ajst-10982	52	9	more	more	ADV
ajst-10982	52	10	and	and	CCONJ
ajst-10982	52	11	more	more	ADV
ajst-10982	52	12	powerful	powerful	ADJ
ajst-10982	52	13	,	,	PUNCT
ajst-10982	52	14	and	and	CCONJ
ajst-10982	52	15	the	the	DET
ajst-10982	52	16	research	research	NOUN
ajst-10982	52	17	of	of	ADP
ajst-10982	52	18	plant	plant	NOUN
ajst-10982	52	19	roots	root	NOUN
ajst-10982	52	20	also	also	ADV
ajst-10982	52	21	tends	tend	VERB
ajst-10982	52	22	to	to	PART
ajst-10982	52	23	use	use	VERB
ajst-10982	52	24	digital	digital	ADJ
ajst-10982	52	25	equipment	equipment	NOUN
ajst-10982	52	26	imaging	imaging	NOUN
ajst-10982	52	27	method	method	NOUN
ajst-10982	52	28	.	.	PUNCT
ajst-10982	53	1	digital	digital	ADJ
ajst-10982	53	2	device	device	NOUN
ajst-10982	53	3	imaging	imaging	NOUN
ajst-10982	53	4	refers	refer	VERB
ajst-10982	53	5	to	to	ADP
ajst-10982	53	6	non	non	ADJ
ajst-10982	53	7	-	-	ADJ
ajst-10982	53	8	invasive	invasive	ADJ
ajst-10982	53	9	image	image	NOUN
ajst-10982	53	10	acquisition	acquisition	NOUN
ajst-10982	53	11	of	of	ADP
ajst-10982	53	12	roots	root	NOUN
ajst-10982	53	13	through	through	ADP
ajst-10982	53	14	the	the	DET
ajst-10982	53	15	use	use	NOUN
ajst-10982	53	16	of	of	ADP
ajst-10982	53	17	digital	digital	ADJ
ajst-10982	53	18	devices	device	NOUN
ajst-10982	53	19	such	such	ADJ
ajst-10982	53	20	as	as	ADP
ajst-10982	53	21	smart	smart	ADJ
ajst-10982	53	22	cameras	camera	NOUN
ajst-10982	53	23	,	,	PUNCT
ajst-10982	53	24	scanners	scanner	NOUN
ajst-10982	53	25	and	and	CCONJ
ajst-10982	53	26	smartphones	smartphone	NOUN
ajst-10982	53	27	.	.	PUNCT
ajst-10982	54	1	progress	progress	NOUN
ajst-10982	54	2	has	have	AUX
ajst-10982	54	3	been	be	AUX
ajst-10982	54	4	made	make	VERB
ajst-10982	54	5	in	in	ADP
ajst-10982	54	6	root	root	NOUN
ajst-10982	54	7	segmentation	segmentation	NOUN
ajst-10982	54	8	of	of	ADP
ajst-10982	54	9	many	many	ADJ
ajst-10982	54	10	plants	plant	NOUN
ajst-10982	54	11	.	.	PUNCT
ajst-10982	55	1	firstly	firstly	ADV
ajst-10982	55	2	,	,	PUNCT
ajst-10982	55	3	high	high	ADJ
ajst-10982	55	4	-	-	PUNCT
ajst-10982	55	5	resolution	resolution	NOUN
ajst-10982	55	6	root	root	NOUN
ajst-10982	55	7	growth	growth	NOUN
ajst-10982	55	8	imaging	imaging	NOUN
ajst-10982	55	9	device	device	NOUN
ajst-10982	55	10	based	base	VERB
ajst-10982	55	11	on	on	ADP
ajst-10982	55	12	digital	digital	ADJ
ajst-10982	55	13	equipment	equipment	NOUN
ajst-10982	55	14	was	be	AUX
ajst-10982	55	15	used	use	VERB
ajst-10982	55	16	to	to	PART
ajst-10982	55	17	obtain	obtain	VERB
ajst-10982	55	18	in	in	ADP
ajst-10982	55	19	situ	situ	ADJ
ajst-10982	55	20	root	root	NOUN
ajst-10982	55	21	image	image	NOUN
ajst-10982	55	22	of	of	ADP
ajst-10982	55	23	cotton	cotton	NOUN
ajst-10982	56	1	[	[	X
ajst-10982	56	2	17	17	NUM
ajst-10982	56	3	]	]	PUNCT
ajst-10982	56	4	,	,	PUNCT
ajst-10982	56	5	and	and	CCONJ
ajst-10982	56	6	the	the	DET
ajst-10982	56	7	image	image	NOUN
ajst-10982	56	8	of	of	ADP
ajst-10982	56	9	plant	plant	NOUN
ajst-10982	56	10	in	in	ADP
ajst-10982	56	11	situ	situ	ADJ
ajst-10982	56	12	root	root	NOUN
ajst-10982	56	13	with	with	ADP
ajst-10982	56	14	1920	1920	NUM
ajst-10982	56	15	*	*	SYM
ajst-10982	56	16	1080	1080	NUM
ajst-10982	56	17	pixels	pixel	NOUN
ajst-10982	56	18	was	be	AUX
ajst-10982	56	19	collected	collect	VERB
ajst-10982	56	20	by	by	ADP
ajst-10982	56	21	digital	digital	ADJ
ajst-10982	56	22	equipment	equipment	NOUN
ajst-10982	57	1	[	[	X
ajst-10982	57	2	22	22	NUM
ajst-10982	57	3	]	]	PUNCT
ajst-10982	57	4	,	,	PUNCT
ajst-10982	57	5	or	or	CCONJ
ajst-10982	57	6	the	the	DET
ajst-10982	57	7	morphological	morphological	ADJ
ajst-10982	57	8	changes	change	NOUN
ajst-10982	57	9	of	of	ADP
ajst-10982	57	10	in	in	ADP
ajst-10982	57	11	situ	situ	ADJ
ajst-10982	57	12	root	root	NOUN
ajst-10982	57	13	of	of	ADP
ajst-10982	57	14	potted	pot	VERB
ajst-10982	57	15	castor	castor	NOUN
ajst-10982	57	16	bean	bean	NOUN
ajst-10982	57	17	were	be	AUX
ajst-10982	57	18	dynamically	dynamically	ADV
ajst-10982	57	19	observed	observe	VERB
ajst-10982	57	20	by	by	ADP
ajst-10982	57	21	scanner	scanner	NOUN
ajst-10982	57	22	[	[	X
ajst-10982	57	23	23	23	NUM
ajst-10982	57	24	]	]	PUNCT
ajst-10982	57	25	.	.	PUNCT
ajst-10982	58	1	at	at	ADP
ajst-10982	58	2	the	the	DET
ajst-10982	58	3	same	same	ADJ
ajst-10982	58	4	time	time	NOUN
ajst-10982	58	5	,	,	PUNCT
ajst-10982	58	6	scanning	scan	VERB
ajst-10982	58	7	devices	device	NOUN
ajst-10982	58	8	such	such	ADJ
ajst-10982	58	9	as	as	ADP
ajst-10982	58	10	handheld	handheld	ADJ
ajst-10982	58	11	scanners	scanner	NOUN
ajst-10982	58	12	and	and	CCONJ
ajst-10982	58	13	flatbed	flatbed	ADJ
ajst-10982	58	14	scanners	scanner	NOUN
ajst-10982	58	15	were	be	AUX
ajst-10982	58	16	used	use	VERB
ajst-10982	58	17	to	to	PART
ajst-10982	58	18	detect	detect	VERB
ajst-10982	58	19	walnut	walnut	NOUN
ajst-10982	58	20	roots	root	NOUN
ajst-10982	58	21	,	,	PUNCT
ajst-10982	58	22	so	so	SCONJ
ajst-10982	58	23	as	as	SCONJ
ajst-10982	58	24	to	to	PART
ajst-10982	58	25	extract	extract	VERB
ajst-10982	58	26	the	the	DET
ajst-10982	58	27	organizational	organizational	ADJ
ajst-10982	58	28	characteristics	characteristic	NOUN
ajst-10982	58	29	of	of	ADP
ajst-10982	58	30	the	the	DET
ajst-10982	58	31	huge	huge	ADJ
ajst-10982	58	32	tree	tree	NOUN
ajst-10982	58	33	roots	root	NOUN
ajst-10982	58	34	[	[	X
ajst-10982	58	35	24	24	NUM
ajst-10982	58	36	]	]	PUNCT
ajst-10982	58	37	.	.	PUNCT
ajst-10982	59	1	digital	digital	ADJ
ajst-10982	59	2	imaging	imaging	NOUN
ajst-10982	59	3	of	of	ADP
ajst-10982	59	4	plant	plant	NOUN
ajst-10982	59	5	roots	root	NOUN
ajst-10982	59	6	is	be	AUX
ajst-10982	59	7	a	a	DET
ajst-10982	59	8	non	non	ADJ
ajst-10982	59	9	-	-	ADJ
ajst-10982	59	10	invasive	invasive	ADJ
ajst-10982	59	11	root	root	NOUN
ajst-10982	59	12	analysis	analysis	NOUN
ajst-10982	59	13	method	method	NOUN
ajst-10982	59	14	based	base	VERB
ajst-10982	59	15	on	on	ADP
ajst-10982	59	16	computer	computer	NOUN
ajst-10982	59	17	vision	vision	NOUN
ajst-10982	59	18	technology	technology	NOUN
ajst-10982	59	19	.	.	PUNCT
ajst-10982	60	1	compared	compare	VERB
ajst-10982	60	2	with	with	ADP
ajst-10982	60	3	traditional	traditional	ADJ
ajst-10982	60	4	manual	manual	ADJ
ajst-10982	60	5	operation	operation	NOUN
ajst-10982	60	6	or	or	CCONJ
ajst-10982	60	7	root	root	NOUN
ajst-10982	60	8	dyeing	dyeing	NOUN
ajst-10982	60	9	methods	method	NOUN
ajst-10982	60	10	,	,	PUNCT
ajst-10982	60	11	it	it	PRON
ajst-10982	60	12	has	have	VERB
ajst-10982	60	13	many	many	ADJ
ajst-10982	60	14	advantages	advantage	NOUN
ajst-10982	60	15	.	.	PUNCT
ajst-10982	61	1	first	first	ADV
ajst-10982	61	2	,	,	PUNCT
ajst-10982	61	3	the	the	DET
ajst-10982	61	4	method	method	NOUN
ajst-10982	61	5	can	can	AUX
ajst-10982	61	6	image	image	VERB
ajst-10982	61	7	the	the	DET
ajst-10982	61	8	whole	whole	ADJ
ajst-10982	61	9	root	root	NOUN
ajst-10982	61	10	system	system	NOUN
ajst-10982	61	11	with	with	ADP
ajst-10982	61	12	high	high	ADJ
ajst-10982	61	13	resolution	resolution	NOUN
ajst-10982	61	14	and	and	CCONJ
ajst-10982	61	15	large	large	ADJ
ajst-10982	61	16	area	area	NOUN
ajst-10982	61	17	without	without	ADP
ajst-10982	61	18	manual	manual	ADJ
ajst-10982	61	19	reconstruction	reconstruction	NOUN
ajst-10982	61	20	or	or	CCONJ
ajst-10982	61	21	cutting	cutting	NOUN
ajst-10982	61	22	,	,	PUNCT
ajst-10982	61	23	which	which	PRON
ajst-10982	61	24	improves	improve	VERB
ajst-10982	61	25	the	the	DET
ajst-10982	61	26	efficiency	efficiency	NOUN
ajst-10982	61	27	of	of	ADP
ajst-10982	61	28	sample	sample	NOUN
ajst-10982	61	29	processing	processing	NOUN
ajst-10982	61	30	.	.	PUNCT
ajst-10982	62	1	secondly	secondly	ADV
ajst-10982	62	2	,	,	PUNCT
ajst-10982	62	3	because	because	SCONJ
ajst-10982	62	4	there	there	PRON
ajst-10982	62	5	is	be	VERB
ajst-10982	62	6	no	no	DET
ajst-10982	62	7	need	need	NOUN
ajst-10982	62	8	to	to	PART
ajst-10982	62	9	use	use	VERB
ajst-10982	62	10	special	special	ADJ
ajst-10982	62	11	reagents	reagent	NOUN
ajst-10982	62	12	such	such	ADJ
ajst-10982	62	13	as	as	ADP
ajst-10982	62	14	fluorescent	fluorescent	ADJ
ajst-10982	62	15	labeling	labeling	NOUN
ajst-10982	62	16	or	or	CCONJ
ajst-10982	62	17	pigment	pigment	NOUN
ajst-10982	62	18	dyeing	dyeing	NOUN
ajst-10982	62	19	,	,	PUNCT
ajst-10982	62	20	the	the	DET
ajst-10982	62	21	effects	effect	NOUN
ajst-10982	62	22	of	of	ADP
ajst-10982	62	23	these	these	DET
ajst-10982	62	24	reagents	reagent	NOUN
ajst-10982	62	25	on	on	ADP
ajst-10982	62	26	plant	plant	NOUN
ajst-10982	62	27	growth	growth	NOUN
ajst-10982	62	28	and	and	CCONJ
ajst-10982	62	29	morphology	morphology	NOUN
ajst-10982	62	30	can	can	AUX
ajst-10982	62	31	be	be	AUX
ajst-10982	62	32	avoided	avoid	VERB
ajst-10982	62	33	.	.	PUNCT
ajst-10982	63	1	finally	finally	ADV
ajst-10982	63	2	,	,	PUNCT
ajst-10982	63	3	especially	especially	ADV
ajst-10982	63	4	with	with	ADP
ajst-10982	63	5	the	the	DET
ajst-10982	63	6	rapid	rapid	ADJ
ajst-10982	63	7	development	development	NOUN
ajst-10982	63	8	of	of	ADP
ajst-10982	63	9	artificial	artificial	ADJ
ajst-10982	63	10	intelligence	intelligence	NOUN
ajst-10982	63	11	,	,	PUNCT
ajst-10982	63	12	combined	combine	VERB
ajst-10982	63	13	with	with	ADP
ajst-10982	63	14	digital	digital	ADJ
ajst-10982	63	15	image	image	NOUN
ajst-10982	63	16	processing	processing	NOUN
ajst-10982	63	17	[	[	X
ajst-10982	63	18	25	25	NUM
ajst-10982	63	19	]	]	PUNCT
ajst-10982	63	20	and	and	CCONJ
ajst-10982	63	21	deep	deep	ADJ
ajst-10982	63	22	learning	learning	NOUN
ajst-10982	64	1	[	[	X
ajst-10982	64	2	26	26	NUM
ajst-10982	64	3	]	]	PUNCT
ajst-10982	64	4	algorithms	algorithm	NOUN
ajst-10982	64	5	,	,	PUNCT
ajst-10982	64	6	this	this	DET
ajst-10982	64	7	method	method	NOUN
ajst-10982	64	8	can	can	AUX
ajst-10982	64	9	more	more	ADV
ajst-10982	64	10	accurately	accurately	ADV
ajst-10982	64	11	and	and	CCONJ
ajst-10982	64	12	quickly	quickly	ADV
ajst-10982	64	13	analyze	analyze	VERB
ajst-10982	64	14	and	and	CCONJ
ajst-10982	64	15	measure	measure	VERB
ajst-10982	64	16	the	the	DET
ajst-10982	64	17	structure	structure	NOUN
ajst-10982	64	18	and	and	CCONJ
ajst-10982	64	19	physiological	physiological	ADJ
ajst-10982	64	20	indicators	indicator	NOUN
ajst-10982	64	21	of	of	ADP
ajst-10982	64	22	each	each	DET
ajst-10982	64	23	part	part	NOUN
ajst-10982	64	24	of	of	ADP
ajst-10982	64	25	the	the	DET
ajst-10982	64	26	root	root	NOUN
ajst-10982	64	27	system	system	NOUN
ajst-10982	64	28	,	,	PUNCT
ajst-10982	64	29	which	which	PRON
ajst-10982	64	30	is	be	AUX
ajst-10982	64	31	of	of	ADP
ajst-10982	64	32	great	great	ADJ
ajst-10982	64	33	significance	significance	NOUN
ajst-10982	64	34	for	for	ADP
ajst-10982	64	35	accurately	accurately	ADV
ajst-10982	64	36	obtaining	obtain	VERB
ajst-10982	64	37	the	the	DET
ajst-10982	64	38	complete	complete	ADJ
ajst-10982	64	39	configuration	configuration	NOUN
ajst-10982	64	40	of	of	ADP
ajst-10982	64	41	the	the	DET
ajst-10982	64	42	in	in	ADP
ajst-10982	64	43	-	-	PUNCT
ajst-10982	64	44	situ	situ	NOUN
ajst-10982	64	45	root	root	NOUN
ajst-10982	64	46	system	system	NOUN
ajst-10982	64	47	,	,	PUNCT
ajst-10982	64	48	exploring	explore	VERB
ajst-10982	64	49	its	its	PRON
ajst-10982	64	50	development	development	NOUN
ajst-10982	64	51	law	law	NOUN
ajst-10982	64	52	and	and	CCONJ
ajst-10982	64	53	defining	define	VERB
ajst-10982	64	54	its	its	PRON
ajst-10982	64	55	functional	functional	ADJ
ajst-10982	64	56	mechanism	mechanism	NOUN
ajst-10982	64	57	.	.	PUNCT
ajst-10982	65	1	these	these	DET
ajst-10982	65	2	plant	plant	NOUN
ajst-10982	65	3	root	root	NOUN
ajst-10982	65	4	imaging	imaging	NOUN
ajst-10982	65	5	methods	method	NOUN
ajst-10982	65	6	can	can	AUX
ajst-10982	65	7	obtain	obtain	VERB
ajst-10982	65	8	highresolution	highresolution	NOUN
ajst-10982	65	9	plant	plant	NOUN
ajst-10982	65	10	root	root	NOUN
ajst-10982	65	11	images	image	NOUN
ajst-10982	65	12	by	by	ADP
ajst-10982	65	13	adjusting	adjust	VERB
ajst-10982	65	14	and	and	CCONJ
ajst-10982	65	15	combining	combine	VERB
ajst-10982	65	16	different	different	ADJ
ajst-10982	65	17	imaging	imaging	NOUN
ajst-10982	65	18	parameters	parameter	NOUN
ajst-10982	65	19	,	,	PUNCT
ajst-10982	65	20	but	but	CCONJ
ajst-10982	65	21	the	the	DET
ajst-10982	65	22	data	data	NOUN
ajst-10982	65	23	acquisition	acquisition	NOUN
ajst-10982	65	24	process	process	NOUN
ajst-10982	65	25	is	be	AUX
ajst-10982	65	26	time	time	NOUN
ajst-10982	65	27	-	-	PUNCT
ajst-10982	65	28	consuming	consume	VERB
ajst-10982	65	29	and	and	CCONJ
ajst-10982	65	30	has	have	VERB
ajst-10982	65	31	a	a	DET
ajst-10982	65	32	large	large	ADJ
ajst-10982	65	33	amount	amount	NOUN
ajst-10982	65	34	of	of	ADP
ajst-10982	65	35	data	datum	NOUN
ajst-10982	65	36	,	,	PUNCT
ajst-10982	65	37	and	and	CCONJ
ajst-10982	65	38	corresponding	correspond	VERB
ajst-10982	65	39	software	software	NOUN
ajst-10982	65	40	tools	tool	NOUN
ajst-10982	65	41	are	be	AUX
ajst-10982	65	42	required	require	VERB
ajst-10982	65	43	to	to	PART
ajst-10982	65	44	segment	segment	VERB
ajst-10982	65	45	and	and	CCONJ
ajst-10982	65	46	analyze	analyze	VERB
ajst-10982	65	47	the	the	DET
ajst-10982	65	48	data	datum	NOUN
ajst-10982	65	49	to	to	PART
ajst-10982	65	50	obtain	obtain	VERB
ajst-10982	65	51	relevant	relevant	ADJ
ajst-10982	65	52	results	result	NOUN
ajst-10982	65	53	.	.	PUNCT
ajst-10982	66	1	2.3	2.3	NUM
ajst-10982	66	2	.	.	PUNCT
ajst-10982	66	3	plant	plant	NOUN
ajst-10982	66	4	root	root	NOUN
ajst-10982	66	5	segmentation	segmentation	NOUN
ajst-10982	66	6	plant	plant	NOUN
ajst-10982	66	7	root	root	NOUN
ajst-10982	66	8	segmentation	segmentation	NOUN
ajst-10982	66	9	refers	refer	VERB
ajst-10982	66	10	to	to	ADP
ajst-10982	66	11	the	the	DET
ajst-10982	66	12	process	process	NOUN
ajst-10982	66	13	of	of	ADP
ajst-10982	66	14	separating	separate	VERB
ajst-10982	66	15	plant	plant	NOUN
ajst-10982	66	16	roots	root	NOUN
ajst-10982	66	17	from	from	ADP
ajst-10982	66	18	other	other	ADJ
ajst-10982	66	19	backgrounds	background	NOUN
ajst-10982	66	20	through	through	ADP
ajst-10982	66	21	image	image	NOUN
ajst-10982	66	22	processing	processing	NOUN
ajst-10982	66	23	technology	technology	NOUN
ajst-10982	66	24	.	.	PUNCT
ajst-10982	67	1	at	at	ADP
ajst-10982	67	2	present	present	ADJ
ajst-10982	67	3	,	,	PUNCT
ajst-10982	67	4	in	in	ADP
ajst-10982	67	5	the	the	DET
ajst-10982	67	6	study	study	NOUN
ajst-10982	67	7	of	of	ADP
ajst-10982	67	8	plant	plant	NOUN
ajst-10982	67	9	root	root	NOUN
ajst-10982	67	10	phenotype	phenotype	NOUN
ajst-10982	67	11	,	,	PUNCT
ajst-10982	67	12	although	although	SCONJ
ajst-10982	67	13	it	it	PRON
ajst-10982	67	14	is	be	AUX
ajst-10982	67	15	possible	possible	ADJ
ajst-10982	67	16	to	to	PART
ajst-10982	67	17	obtain	obtain	VERB
ajst-10982	67	18	high	high	ADJ
ajst-10982	67	19	-	-	PUNCT
ajst-10982	67	20	resolution	resolution	NOUN
ajst-10982	67	21	root	root	NOUN
ajst-10982	67	22	images	image	NOUN
ajst-10982	67	23	from	from	ADP
ajst-10982	67	24	complex	complex	ADJ
ajst-10982	67	25	soil	soil	NOUN
ajst-10982	67	26	environments	environment	NOUN
ajst-10982	67	27	by	by	ADP
ajst-10982	67	28	using	use	VERB
ajst-10982	67	29	in	in	ADP
ajst-10982	67	30	situ	situ	ADJ
ajst-10982	67	31	root	root	NOUN
ajst-10982	67	32	nondestructive	nondestructive	ADJ
ajst-10982	67	33	observation	observation	NOUN
ajst-10982	67	34	technology	technology	NOUN
ajst-10982	67	35	,	,	PUNCT
ajst-10982	67	36	the	the	DET
ajst-10982	67	37	automatic	automatic	ADJ
ajst-10982	67	38	segmentation	segmentation	NOUN
ajst-10982	67	39	of	of	ADP
ajst-10982	67	40	root	root	NOUN
ajst-10982	67	41	morphology	morphology	NOUN
ajst-10982	67	42	is	be	AUX
ajst-10982	67	43	usually	usually	ADV
ajst-10982	67	44	faced	face	VERB
ajst-10982	67	45	with	with	ADP
ajst-10982	67	46	great	great	ADJ
ajst-10982	67	47	challenges	challenge	NOUN
ajst-10982	67	48	due	due	ADP
ajst-10982	67	49	to	to	ADP
ajst-10982	67	50	the	the	DET
ajst-10982	67	51	opacity	opacity	NOUN
ajst-10982	67	52	of	of	ADP
ajst-10982	67	53	soil	soil	NOUN
ajst-10982	67	54	particles	particle	NOUN
ajst-10982	67	55	.	.	PUNCT
ajst-10982	68	1	traditional	traditional	ADJ
ajst-10982	68	2	root	root	NOUN
ajst-10982	68	3	segmentation	segmentation	NOUN
ajst-10982	68	4	methods	method	NOUN
ajst-10982	68	5	mainly	mainly	ADV
ajst-10982	68	6	include	include	VERB
ajst-10982	68	7	manual	manual	ADJ
ajst-10982	68	8	segmentation	segmentation	NOUN
ajst-10982	68	9	,	,	PUNCT
ajst-10982	68	10	morphological	morphological	ADJ
ajst-10982	68	11	image	image	NOUN
ajst-10982	68	12	processing	processing	NOUN
ajst-10982	68	13	and	and	CCONJ
ajst-10982	68	14	machine	machine	NOUN
ajst-10982	68	15	learning	learning	NOUN
ajst-10982	68	16	based	base	VERB
ajst-10982	68	17	image	image	NOUN
ajst-10982	68	18	segmentation	segmentation	NOUN
ajst-10982	68	19	.	.	PUNCT
ajst-10982	69	1	among	among	ADP
ajst-10982	69	2	them	they	PRON
ajst-10982	69	3	,	,	PUNCT
ajst-10982	69	4	manual	manual	ADJ
ajst-10982	69	5	segmentation	segmentation	NOUN
ajst-10982	69	6	can	can	AUX
ajst-10982	69	7	be	be	AUX
ajst-10982	69	8	further	far	ADV
ajst-10982	69	9	divided	divide	VERB
ajst-10982	69	10	into	into	ADP
ajst-10982	69	11	manual	manual	ADJ
ajst-10982	69	12	characterization	characterization	NOUN
ajst-10982	69	13	and	and	CCONJ
ajst-10982	69	14	semi	semi	ADJ
ajst-10982	69	15	-	-	ADJ
ajst-10982	69	16	automatic	automatic	ADJ
ajst-10982	69	17	interactive	interactive	ADJ
ajst-10982	69	18	segmentation	segmentation	NOUN
ajst-10982	69	19	.	.	PUNCT
ajst-10982	70	1	in	in	ADP
ajst-10982	70	2	the	the	DET
ajst-10982	70	3	manual	manual	ADJ
ajst-10982	70	4	mapping	mapping	NOUN
ajst-10982	70	5	method	method	NOUN
ajst-10982	70	6	,	,	PUNCT
ajst-10982	70	7	researchers	researcher	NOUN
ajst-10982	70	8	need	need	VERB
ajst-10982	70	9	to	to	PART
ajst-10982	70	10	manually	manually	ADV
ajst-10982	70	11	identify	identify	VERB
ajst-10982	70	12	each	each	DET
ajst-10982	70	13	root	root	NOUN
ajst-10982	70	14	system	system	NOUN
ajst-10982	70	15	in	in	ADP
ajst-10982	70	16	a	a	DET
ajst-10982	70	17	complex	complex	ADJ
ajst-10982	70	18	soil	soil	NOUN
ajst-10982	70	19	background	background	NOUN
ajst-10982	70	20	and	and	CCONJ
ajst-10982	70	21	describe	describe	VERB
ajst-10982	70	22	it	it	PRON
ajst-10982	70	23	.	.	PUNCT
ajst-10982	71	1	due	due	ADP
ajst-10982	71	2	to	to	ADP
ajst-10982	71	3	the	the	DET
ajst-10982	71	4	low	low	ADJ
ajst-10982	71	5	efficiency	efficiency	NOUN
ajst-10982	71	6	of	of	ADP
ajst-10982	71	7	this	this	DET
ajst-10982	71	8	method	method	NOUN
ajst-10982	71	9	,	,	PUNCT
ajst-10982	71	10	the	the	DET
ajst-10982	71	11	need	need	NOUN
ajst-10982	71	12	for	for	ADP
ajst-10982	71	13	huge	huge	ADJ
ajst-10982	71	14	workload	workload	NOUN
ajst-10982	71	15	,	,	PUNCT
ajst-10982	71	16	and	and	CCONJ
ajst-10982	71	17	the	the	DET
ajst-10982	71	18	problem	problem	NOUN
ajst-10982	71	19	of	of	ADP
ajst-10982	71	20	visual	visual	ADJ
ajst-10982	71	21	fatigue	fatigue	NOUN
ajst-10982	71	22	,	,	PUNCT
ajst-10982	71	23	the	the	DET
ajst-10982	71	24	segmentation	segmentation	NOUN
ajst-10982	71	25	results	result	NOUN
ajst-10982	71	26	are	be	AUX
ajst-10982	71	27	easy	easy	ADJ
ajst-10982	71	28	to	to	PART
ajst-10982	71	29	be	be	AUX
ajst-10982	71	30	affected	affect	VERB
ajst-10982	71	31	by	by	ADP
ajst-10982	71	32	high	high	ADJ
ajst-10982	71	33	errors	error	NOUN
ajst-10982	71	34	,	,	PUNCT
ajst-10982	71	35	and	and	CCONJ
ajst-10982	71	36	are	be	AUX
ajst-10982	71	37	not	not	PART
ajst-10982	71	38	suitable	suitable	ADJ
ajst-10982	71	39	for	for	ADP
ajst-10982	71	40	practical	practical	ADJ
ajst-10982	71	41	engineering	engineering	NOUN
ajst-10982	71	42	applications	application	NOUN
ajst-10982	71	43	.	.	PUNCT
ajst-10982	72	1	the	the	DET
ajst-10982	72	2	semi	semi	ADJ
ajst-10982	72	3	-	-	ADJ
ajst-10982	72	4	automatic	automatic	ADJ
ajst-10982	72	5	interactive	interactive	ADJ
ajst-10982	72	6	segmentation	segmentation	NOUN
ajst-10982	72	7	method	method	NOUN
ajst-10982	72	8	requires	require	VERB
ajst-10982	72	9	the	the	DET
ajst-10982	72	10	combination	combination	NOUN
ajst-10982	72	11	of	of	ADP
ajst-10982	72	12	human	human	ADJ
ajst-10982	72	13	-	-	PUNCT
ajst-10982	72	14	computer	computer	NOUN
ajst-10982	72	15	interaction	interaction	NOUN
ajst-10982	72	16	,	,	PUNCT
ajst-10982	72	17	and	and	CCONJ
ajst-10982	72	18	the	the	DET
ajst-10982	72	19	researchers	researcher	NOUN
ajst-10982	72	20	use	use	VERB
ajst-10982	72	21	auxiliary	auxiliary	ADJ
ajst-10982	72	22	software	software	NOUN
ajst-10982	72	23	to	to	PART
ajst-10982	72	24	label	label	VERB
ajst-10982	72	25	and	and	CCONJ
ajst-10982	72	26	segment	segment	VERB
ajst-10982	72	27	it	it	PRON
ajst-10982	72	28	.	.	PUNCT
ajst-10982	73	1	for	for	ADP
ajst-10982	73	2	example	example	NOUN
ajst-10982	73	3	,	,	PUNCT
ajst-10982	73	4	matalabr2016a	matalabr2016a	NOUN
ajst-10982	73	5	image	image	NOUN
ajst-10982	73	6	processing	processing	NOUN
ajst-10982	73	7	software	software	NOUN
ajst-10982	73	8	was	be	AUX
ajst-10982	73	9	used	use	VERB
ajst-10982	73	10	to	to	PART
ajst-10982	73	11	segment	segment	VERB
ajst-10982	73	12	plant	plant	NOUN
ajst-10982	73	13	root	root	NOUN
ajst-10982	73	14	images	image	NOUN
ajst-10982	73	15	[	[	X
ajst-10982	73	16	27	27	NUM
ajst-10982	73	17	]	]	PUNCT
ajst-10982	73	18	,	,	PUNCT
ajst-10982	73	19	winrhizo	winrhizo	PROPN
ajst-10982	73	20	tron	tron	PROPN
ajst-10982	73	21	mf	mf	PROPN
ajst-10982	73	22	was	be	AUX
ajst-10982	73	23	used	use	VERB
ajst-10982	73	24	for	for	ADP
ajst-10982	73	25	image	image	NOUN
ajst-10982	73	26	analysis	analysis	NOUN
ajst-10982	74	1	[	[	X
ajst-10982	74	2	28	28	NUM
ajst-10982	74	3	]	]	PUNCT
ajst-10982	74	4	,	,	PUNCT
ajst-10982	74	5	and	and	CCONJ
ajst-10982	74	6	gt	gt	NOUN
ajst-10982	74	7	-	-	PUNCT
ajst-10982	74	8	roots	root	NOUN
ajst-10982	74	9	was	be	AUX
ajst-10982	74	10	used	use	VERB
ajst-10982	74	11	for	for	ADP
ajst-10982	74	12	root	root	NOUN
ajst-10982	74	13	segmentation	segmentation	NOUN
ajst-10982	74	14	in	in	ADP
ajst-10982	74	15	the	the	DET
ajst-10982	74	16	specified	specify	VERB
ajst-10982	74	17	segmentation	segmentation	NOUN
ajst-10982	74	18	region	region	NOUN
ajst-10982	74	19	selection	selection	NOUN
ajst-10982	74	20	method	method	NOUN
ajst-10982	74	21	[	[	X
ajst-10982	74	22	29	29	NUM
ajst-10982	74	23	]	]	PUNCT
ajst-10982	74	24	.	.	PUNCT
ajst-10982	75	1	the	the	DET
ajst-10982	75	2	morphology	morphology	NOUN
ajst-10982	75	3	-	-	PUNCT
ajst-10982	75	4	based	base	VERB
ajst-10982	75	5	image	image	NOUN
ajst-10982	75	6	processing	processing	NOUN
ajst-10982	75	7	method	method	NOUN
ajst-10982	75	8	is	be	AUX
ajst-10982	75	9	to	to	PART
ajst-10982	75	10	continuously	continuously	ADV
ajst-10982	75	11	filter	filter	VERB
ajst-10982	75	12	the	the	DET
ajst-10982	75	13	image	image	NOUN
ajst-10982	75	14	to	to	PART
ajst-10982	75	15	distinguish	distinguish	VERB
ajst-10982	75	16	the	the	DET
ajst-10982	75	17	root	root	NOUN
ajst-10982	75	18	system	system	NOUN
ajst-10982	75	19	from	from	ADP
ajst-10982	75	20	the	the	DET
ajst-10982	75	21	background	background	NOUN
ajst-10982	75	22	.	.	PUNCT
ajst-10982	76	1	it	it	PRON
ajst-10982	76	2	can	can	AUX
ajst-10982	76	3	be	be	AUX
ajst-10982	76	4	divided	divide	VERB
ajst-10982	76	5	into	into	ADP
ajst-10982	76	6	the	the	DET
ajst-10982	76	7	following	follow	VERB
ajst-10982	76	8	types	type	NOUN
ajst-10982	76	9	:	:	PUNCT
ajst-10982	76	10	firstly	firstly	ADV
ajst-10982	76	11	,	,	PUNCT
ajst-10982	76	12	morphological	morphological	ADJ
ajst-10982	76	13	operation	operation	NOUN
ajst-10982	77	1	[	[	X
ajst-10982	77	2	30	30	NUM
ajst-10982	77	3	]	]	PUNCT
ajst-10982	77	4	,	,	PUNCT
ajst-10982	77	5	which	which	PRON
ajst-10982	77	6	is	be	AUX
ajst-10982	77	7	divided	divide	VERB
ajst-10982	77	8	into	into	ADP
ajst-10982	77	9	expansion	expansion	NOUN
ajst-10982	77	10	,	,	PUNCT
ajst-10982	77	11	corrosion	corrosion	NOUN
ajst-10982	77	12	,	,	PUNCT
ajst-10982	77	13	open	open	ADJ
ajst-10982	77	14	operation	operation	NOUN
ajst-10982	77	15	,	,	PUNCT
ajst-10982	77	16	close	close	ADJ
ajst-10982	77	17	operation	operation	NOUN
ajst-10982	77	18	and	and	CCONJ
ajst-10982	77	19	other	other	ADJ
ajst-10982	77	20	specific	specific	ADJ
ajst-10982	77	21	methods	method	NOUN
ajst-10982	77	22	,	,	PUNCT
ajst-10982	77	23	can	can	AUX
ajst-10982	77	24	improve	improve	VERB
ajst-10982	77	25	image	image	NOUN
ajst-10982	77	26	quality	quality	NOUN
ajst-10982	77	27	,	,	PUNCT
ajst-10982	77	28	remove	remove	VERB
ajst-10982	77	29	noise	noise	NOUN
ajst-10982	77	30	,	,	PUNCT
ajst-10982	77	31	and	and	CCONJ
ajst-10982	77	32	enhance	enhance	VERB
ajst-10982	77	33	object	object	NOUN
ajst-10982	77	34	contours	contours	NOUN
ajst-10982	77	35	to	to	ADP
ajst-10982	77	36	a	a	DET
ajst-10982	77	37	certain	certain	ADJ
ajst-10982	77	38	extent	extent	NOUN
ajst-10982	77	39	;	;	PUNCT
ajst-10982	77	40	the	the	DET
ajst-10982	77	41	second	second	ADJ
ajst-10982	77	42	method	method	NOUN
ajst-10982	77	43	is	be	AUX
ajst-10982	77	44	region	region	NOUN
ajst-10982	77	45	growing	grow	VERB
ajst-10982	77	46	[	[	X
ajst-10982	77	47	31	31	NUM
ajst-10982	77	48	]	]	PUNCT
ajst-10982	77	49	,	,	PUNCT
ajst-10982	77	50	which	which	PRON
ajst-10982	77	51	selects	select	VERB
ajst-10982	77	52	a	a	DET
ajst-10982	77	53	point	point	NOUN
ajst-10982	77	54	or	or	CCONJ
ajst-10982	77	55	a	a	DET
ajst-10982	77	56	region	region	NOUN
ajst-10982	77	57	as	as	ADP
ajst-10982	77	58	a	a	DET
ajst-10982	77	59	seed	seed	NOUN
ajst-10982	77	60	and	and	CCONJ
ajst-10982	77	61	grows	grow	VERB
ajst-10982	77	62	along	along	ADP
ajst-10982	77	63	the	the	DET
ajst-10982	77	64	adjacent	adjacent	ADJ
ajst-10982	77	65	pixels	pixel	NOUN
ajst-10982	77	66	until	until	SCONJ
ajst-10982	77	67	some	some	DET
ajst-10982	77	68	stopping	stopping	NOUN
ajst-10982	77	69	criteria	criterion	NOUN
ajst-10982	77	70	are	be	AUX
ajst-10982	77	71	reached	reach	VERB
ajst-10982	77	72	.	.	PUNCT
ajst-10982	78	1	the	the	DET
ajst-10982	78	2	third	third	ADJ
ajst-10982	78	3	method	method	NOUN
ajst-10982	78	4	is	be	AUX
ajst-10982	78	5	thresholding	thresholde	VERB
ajst-10982	78	6	[	[	X
ajst-10982	78	7	32	32	NUM
ajst-10982	78	8	]	]	PUNCT
ajst-10982	78	9	,	,	PUNCT
ajst-10982	78	10	which	which	PRON
ajst-10982	78	11	can	can	AUX
ajst-10982	78	12	divide	divide	VERB
ajst-10982	78	13	the	the	DET
ajst-10982	78	14	image	image	NOUN
ajst-10982	78	15	into	into	ADP
ajst-10982	78	16	several	several	ADJ
ajst-10982	78	17	parts	part	NOUN
ajst-10982	78	18	according	accord	VERB
ajst-10982	78	19	to	to	ADP
ajst-10982	78	20	the	the	DET
ajst-10982	78	21	threshold	threshold	NOUN
ajst-10982	78	22	value	value	NOUN
ajst-10982	78	23	so	so	SCONJ
ajst-10982	78	24	as	as	SCONJ
ajst-10982	78	25	to	to	PART
ajst-10982	78	26	separate	separate	VERB
ajst-10982	78	27	the	the	DET
ajst-10982	78	28	background	background	NOUN
ajst-10982	78	29	from	from	ADP
ajst-10982	78	30	the	the	DET
ajst-10982	78	31	foreground	foreground	NOUN
ajst-10982	78	32	.	.	PUNCT
ajst-10982	79	1	common	common	ADJ
ajst-10982	79	2	threshold	threshold	NOUN
ajst-10982	79	3	selection	selection	NOUN
ajst-10982	79	4	strategies	strategy	NOUN
ajst-10982	79	5	include	include	VERB
ajst-10982	79	6	otsu	otsu	NOUN
ajst-10982	79	7	method	method	NOUN
ajst-10982	79	8	[	[	X
ajst-10982	79	9	33	33	NUM
ajst-10982	79	10	]	]	PUNCT
ajst-10982	79	11	and	and	CCONJ
ajst-10982	79	12	adaptive	adaptive	ADJ
ajst-10982	79	13	27	27	NUM
ajst-10982	79	14	threshold	threshold	NOUN
ajst-10982	79	15	method	method	NOUN
ajst-10982	79	16	[	[	X
ajst-10982	79	17	34	34	NUM
ajst-10982	79	18	]	]	PUNCT
ajst-10982	79	19	.	.	PUNCT
ajst-10982	80	1	there	there	PRON
ajst-10982	80	2	is	be	VERB
ajst-10982	80	3	also	also	ADV
ajst-10982	80	4	a	a	DET
ajst-10982	80	5	method	method	NOUN
ajst-10982	80	6	based	base	VERB
ajst-10982	80	7	on	on	ADP
ajst-10982	80	8	wavelet	wavelet	NOUN
ajst-10982	80	9	transform	transform	NOUN
ajst-10982	80	10	[	[	X
ajst-10982	80	11	35	35	NUM
ajst-10982	80	12	]	]	PUNCT
ajst-10982	80	13	,	,	PUNCT
ajst-10982	80	14	which	which	PRON
ajst-10982	80	15	can	can	AUX
ajst-10982	80	16	realize	realize	VERB
ajst-10982	80	17	multi	multi	ADJ
ajst-10982	80	18	-	-	ADJ
ajst-10982	80	19	scale	scale	ADJ
ajst-10982	80	20	analysis	analysis	NOUN
ajst-10982	80	21	and	and	CCONJ
ajst-10982	80	22	local	local	ADJ
ajst-10982	80	23	processing	processing	NOUN
ajst-10982	80	24	,	,	PUNCT
ajst-10982	80	25	and	and	CCONJ
ajst-10982	80	26	can	can	AUX
ajst-10982	80	27	deal	deal	VERB
ajst-10982	80	28	with	with	ADP
ajst-10982	80	29	noise	noise	NOUN
ajst-10982	80	30	better	well	ADV
ajst-10982	80	31	.	.	PUNCT
ajst-10982	81	1	root	root	NOUN
ajst-10982	81	2	image	image	NOUN
ajst-10982	81	3	segmentation	segmentation	NOUN
ajst-10982	81	4	methods	method	NOUN
ajst-10982	81	5	based	base	VERB
ajst-10982	81	6	on	on	ADP
ajst-10982	81	7	traditional	traditional	ADJ
ajst-10982	81	8	machine	machine	NOUN
ajst-10982	81	9	learning	learning	NOUN
ajst-10982	81	10	are	be	AUX
ajst-10982	81	11	divided	divide	VERB
ajst-10982	81	12	into	into	ADP
ajst-10982	81	13	the	the	DET
ajst-10982	81	14	following	follow	VERB
ajst-10982	81	15	common	common	ADJ
ajst-10982	81	16	methods	method	NOUN
ajst-10982	81	17	.	.	PUNCT
ajst-10982	82	1	the	the	DET
ajst-10982	82	2	first	first	ADJ
ajst-10982	82	3	is	be	AUX
ajst-10982	82	4	based	base	VERB
ajst-10982	82	5	on	on	ADP
ajst-10982	82	6	support	support	NOUN
ajst-10982	82	7	vector	vector	NOUN
ajst-10982	82	8	machines	machine	NOUN
ajst-10982	82	9	,	,	PUNCT
ajst-10982	82	10	(	(	PUNCT
ajst-10982	82	11	svm	svm	PROPN
ajst-10982	82	12	)	)	PUNCT
ajst-10982	83	1	[	[	X
ajst-10982	83	2	36	36	NUM
ajst-10982	83	3	]	]	PUNCT
ajst-10982	83	4	is	be	AUX
ajst-10982	83	5	a	a	DET
ajst-10982	83	6	binary	binary	ADJ
ajst-10982	83	7	classification	classification	NOUN
ajst-10982	83	8	machine	machine	NOUN
ajst-10982	83	9	learning	learning	NOUN
ajst-10982	83	10	method	method	NOUN
ajst-10982	83	11	that	that	PRON
ajst-10982	83	12	classifies	classify	VERB
ajst-10982	83	13	data	datum	NOUN
ajst-10982	83	14	by	by	ADP
ajst-10982	83	15	finding	find	VERB
ajst-10982	83	16	hyperplanes	hyperplane	NOUN
ajst-10982	83	17	with	with	ADP
ajst-10982	83	18	the	the	DET
ajst-10982	83	19	greatest	great	ADJ
ajst-10982	83	20	spacing	spacing	NOUN
ajst-10982	83	21	.	.	PUNCT
ajst-10982	84	1	it	it	PRON
ajst-10982	84	2	is	be	AUX
ajst-10982	84	3	widely	widely	ADV
ajst-10982	84	4	used	use	VERB
ajst-10982	84	5	in	in	ADP
ajst-10982	84	6	root	root	NOUN
ajst-10982	84	7	image	image	NOUN
ajst-10982	84	8	segmentation	segmentation	NOUN
ajst-10982	84	9	,	,	PUNCT
ajst-10982	84	10	and	and	CCONJ
ajst-10982	84	11	can	can	AUX
ajst-10982	84	12	train	train	VERB
ajst-10982	84	13	a	a	DET
ajst-10982	84	14	good	good	ADJ
ajst-10982	84	15	classification	classification	NOUN
ajst-10982	84	16	model	model	NOUN
ajst-10982	84	17	to	to	PART
ajst-10982	84	18	distinguish	distinguish	VERB
ajst-10982	84	19	roots	root	NOUN
ajst-10982	84	20	and	and	CCONJ
ajst-10982	84	21	backgrounds	background	NOUN
ajst-10982	84	22	in	in	ADP
ajst-10982	84	23	images	image	NOUN
ajst-10982	84	24	.	.	PUNCT
ajst-10982	85	1	the	the	DET
ajst-10982	85	2	second	second	ADJ
ajst-10982	85	3	is	be	AUX
ajst-10982	85	4	the	the	DET
ajst-10982	85	5	method	method	NOUN
ajst-10982	85	6	based	base	VERB
ajst-10982	85	7	on	on	ADP
ajst-10982	85	8	decision	decision	NOUN
ajst-10982	85	9	tree	tree	NOUN
ajst-10982	85	10	[	[	X
ajst-10982	85	11	37	37	NUM
ajst-10982	85	12	]	]	PUNCT
ajst-10982	85	13	,	,	PUNCT
ajst-10982	85	14	which	which	PRON
ajst-10982	85	15	is	be	AUX
ajst-10982	85	16	a	a	DET
ajst-10982	85	17	classification	classification	NOUN
ajst-10982	85	18	algorithm	algorithm	NOUN
ajst-10982	85	19	that	that	PRON
ajst-10982	85	20	can	can	AUX
ajst-10982	85	21	classify	classify	VERB
ajst-10982	85	22	data	data	NOUN
ajst-10982	85	23	sets	set	NOUN
ajst-10982	85	24	into	into	ADP
ajst-10982	85	25	different	different	ADJ
ajst-10982	85	26	categories	category	NOUN
ajst-10982	85	27	according	accord	VERB
ajst-10982	85	28	to	to	ADP
ajst-10982	85	29	feature	feature	NOUN
ajst-10982	85	30	attributes	attribute	NOUN
ajst-10982	85	31	.	.	PUNCT
ajst-10982	86	1	by	by	ADP
ajst-10982	86	2	selecting	select	VERB
ajst-10982	86	3	suitable	suitable	ADJ
ajst-10982	86	4	features	feature	NOUN
ajst-10982	86	5	and	and	CCONJ
ajst-10982	86	6	constructing	construct	VERB
ajst-10982	86	7	decision	decision	NOUN
ajst-10982	86	8	tree	tree	NOUN
ajst-10982	86	9	model	model	NOUN
ajst-10982	86	10	,	,	PUNCT
ajst-10982	86	11	it	it	PRON
ajst-10982	86	12	can	can	AUX
ajst-10982	86	13	be	be	AUX
ajst-10982	86	14	used	use	VERB
ajst-10982	86	15	to	to	PART
ajst-10982	86	16	segment	segment	VERB
ajst-10982	86	17	root	root	NOUN
ajst-10982	86	18	image	image	NOUN
ajst-10982	86	19	.	.	PUNCT
ajst-10982	87	1	there	there	PRON
ajst-10982	87	2	are	be	VERB
ajst-10982	87	3	also	also	ADV
ajst-10982	87	4	methods	method	NOUN
ajst-10982	87	5	based	base	VERB
ajst-10982	87	6	on	on	ADP
ajst-10982	87	7	clustering	cluster	VERB
ajst-10982	87	8	[	[	X
ajst-10982	87	9	38	38	NUM
ajst-10982	87	10	]	]	PUNCT
ajst-10982	87	11	analysis	analysis	NOUN
ajst-10982	87	12	,	,	PUNCT
ajst-10982	87	13	which	which	PRON
ajst-10982	87	14	is	be	AUX
ajst-10982	87	15	a	a	DET
ajst-10982	87	16	method	method	NOUN
ajst-10982	87	17	of	of	ADP
ajst-10982	87	18	dividing	divide	VERB
ajst-10982	87	19	data	data	NOUN
ajst-10982	87	20	sets	set	NOUN
ajst-10982	87	21	into	into	ADP
ajst-10982	87	22	multiple	multiple	ADJ
ajst-10982	87	23	categories	category	NOUN
ajst-10982	87	24	.	.	PUNCT
ajst-10982	88	1	by	by	ADP
ajst-10982	88	2	clustering	cluster	VERB
ajst-10982	88	3	the	the	DET
ajst-10982	88	4	pixels	pixel	NOUN
ajst-10982	88	5	in	in	ADP
ajst-10982	88	6	the	the	DET
ajst-10982	88	7	root	root	NOUN
ajst-10982	88	8	image	image	NOUN
ajst-10982	88	9	,	,	PUNCT
ajst-10982	88	10	objects	object	NOUN
ajst-10982	88	11	of	of	ADP
ajst-10982	88	12	different	different	ADJ
ajst-10982	88	13	colors	color	NOUN
ajst-10982	88	14	and	and	CCONJ
ajst-10982	88	15	textures	texture	NOUN
ajst-10982	88	16	can	can	AUX
ajst-10982	88	17	be	be	AUX
ajst-10982	88	18	separated	separate	VERB
ajst-10982	88	19	,	,	PUNCT
ajst-10982	88	20	and	and	CCONJ
ajst-10982	88	21	then	then	ADV
ajst-10982	88	22	the	the	DET
ajst-10982	88	23	clustering	clustering	ADJ
ajst-10982	88	24	results	result	NOUN
ajst-10982	88	25	are	be	AUX
ajst-10982	88	26	used	use	VERB
ajst-10982	88	27	for	for	ADP
ajst-10982	88	28	root	root	NOUN
ajst-10982	88	29	segmentation	segmentation	NOUN
ajst-10982	88	30	.	.	PUNCT
ajst-10982	89	1	in	in	ADP
ajst-10982	89	2	addition	addition	NOUN
ajst-10982	89	3	,	,	PUNCT
ajst-10982	89	4	more	more	ADJ
ajst-10982	89	5	and	and	CCONJ
ajst-10982	89	6	more	more	ADJ
ajst-10982	89	7	researchers	researcher	NOUN
ajst-10982	89	8	are	be	AUX
ajst-10982	89	9	focusing	focus	VERB
ajst-10982	89	10	on	on	ADP
ajst-10982	89	11	the	the	DET
ajst-10982	89	12	development	development	NOUN
ajst-10982	89	13	of	of	ADP
ajst-10982	89	14	automated	automate	VERB
ajst-10982	89	15	tools	tool	NOUN
ajst-10982	89	16	for	for	ADP
ajst-10982	89	17	the	the	DET
ajst-10982	89	18	processing	processing	NOUN
ajst-10982	89	19	of	of	ADP
ajst-10982	89	20	highthroughput	highthroughput	NOUN
ajst-10982	89	21	root	root	NOUN
ajst-10982	89	22	phenotypes	phenotype	NOUN
ajst-10982	89	23	,	,	PUNCT
ajst-10982	89	24	such	such	ADJ
ajst-10982	89	25	as	as	ADP
ajst-10982	89	26	root	root	NOUN
ajst-10982	89	27	scanners	scanner	NOUN
ajst-10982	89	28	.	.	PUNCT
ajst-10982	90	1	although	although	SCONJ
ajst-10982	90	2	these	these	DET
ajst-10982	90	3	systems	system	NOUN
ajst-10982	90	4	can	can	AUX
ajst-10982	90	5	obtain	obtain	VERB
ajst-10982	90	6	relatively	relatively	ADV
ajst-10982	90	7	high	high	ADJ
ajst-10982	90	8	precision	precision	NOUN
ajst-10982	90	9	root	root	NOUN
ajst-10982	90	10	phenotypic	phenotypic	ADJ
ajst-10982	90	11	parameter	parameter	NOUN
ajst-10982	90	12	values	value	NOUN
ajst-10982	90	13	,	,	PUNCT
ajst-10982	90	14	they	they	PRON
ajst-10982	90	15	still	still	ADV
ajst-10982	90	16	rely	rely	VERB
ajst-10982	90	17	on	on	ADP
ajst-10982	90	18	subjective	subjective	ADJ
ajst-10982	90	19	factors	factor	NOUN
ajst-10982	90	20	to	to	PART
ajst-10982	90	21	locate	locate	VERB
ajst-10982	90	22	the	the	DET
ajst-10982	90	23	initial	initial	ADJ
ajst-10982	90	24	root	root	NOUN
ajst-10982	90	25	position	position	NOUN
ajst-10982	90	26	,	,	PUNCT
ajst-10982	90	27	and	and	CCONJ
ajst-10982	90	28	the	the	DET
ajst-10982	90	29	imaging	imaging	NOUN
ajst-10982	90	30	equipment	equipment	NOUN
ajst-10982	90	31	used	use	VERB
ajst-10982	90	32	is	be	AUX
ajst-10982	90	33	expensive	expensive	ADJ
ajst-10982	90	34	,	,	PUNCT
ajst-10982	90	35	which	which	PRON
ajst-10982	90	36	belongs	belong	VERB
ajst-10982	90	37	to	to	ADP
ajst-10982	90	38	the	the	DET
ajst-10982	90	39	semiautomatic	semiautomatic	ADJ
ajst-10982	90	40	root	root	NOUN
ajst-10982	90	41	image	image	NOUN
ajst-10982	90	42	segmentation	segmentation	NOUN
ajst-10982	90	43	method	method	NOUN
ajst-10982	90	44	.	.	PUNCT
ajst-10982	91	1	with	with	ADP
ajst-10982	91	2	the	the	DET
ajst-10982	91	3	rapid	rapid	ADJ
ajst-10982	91	4	development	development	NOUN
ajst-10982	91	5	of	of	ADP
ajst-10982	91	6	deep	deep	ADJ
ajst-10982	91	7	learning	learning	NOUN
ajst-10982	91	8	technology	technology	NOUN
ajst-10982	91	9	,	,	PUNCT
ajst-10982	91	10	the	the	DET
ajst-10982	91	11	cross	cross	ADJ
ajst-10982	91	12	-	-	ADJ
ajst-10982	91	13	fusion	fusion	ADJ
ajst-10982	91	14	technology	technology	NOUN
ajst-10982	91	15	based	base	VERB
ajst-10982	91	16	on	on	ADP
ajst-10982	91	17	deep	deep	ADJ
ajst-10982	91	18	learning	learning	NOUN
ajst-10982	91	19	and	and	CCONJ
ajst-10982	91	20	computer	computer	NOUN
ajst-10982	91	21	vision	vision	NOUN
ajst-10982	91	22	technology	technology	NOUN
ajst-10982	91	23	has	have	AUX
ajst-10982	91	24	opened	open	VERB
ajst-10982	91	25	up	up	ADP
ajst-10982	91	26	a	a	DET
ajst-10982	91	27	new	new	ADJ
ajst-10982	91	28	field	field	NOUN
ajst-10982	91	29	,	,	PUNCT
ajst-10982	91	30	providing	provide	VERB
ajst-10982	91	31	a	a	DET
ajst-10982	91	32	more	more	ADV
ajst-10982	91	33	accurate	accurate	ADJ
ajst-10982	91	34	,	,	PUNCT
ajst-10982	91	35	fast	fast	ADJ
ajst-10982	91	36	,	,	PUNCT
ajst-10982	91	37	cheap	cheap	ADJ
ajst-10982	91	38	and	and	CCONJ
ajst-10982	91	39	automated	automate	VERB
ajst-10982	91	40	solution	solution	NOUN
ajst-10982	91	41	for	for	ADP
ajst-10982	91	42	plant	plant	NOUN
ajst-10982	91	43	root	root	NOUN
ajst-10982	91	44	image	image	NOUN
ajst-10982	91	45	segmentation	segmentation	NOUN
ajst-10982	91	46	.	.	PUNCT
ajst-10982	92	1	3	3	X
ajst-10982	92	2	.	.	X
ajst-10982	92	3	research	research	NOUN
ajst-10982	92	4	on	on	ADP
ajst-10982	92	5	plant	plant	NOUN
ajst-10982	92	6	roots	root	NOUN
ajst-10982	92	7	based	base	VERB
ajst-10982	92	8	on	on	ADP
ajst-10982	92	9	deep	deep	ADJ
ajst-10982	92	10	learning	learning	NOUN
ajst-10982	92	11	with	with	ADP
ajst-10982	92	12	the	the	DET
ajst-10982	92	13	continuous	continuous	ADJ
ajst-10982	92	14	development	development	NOUN
ajst-10982	92	15	of	of	ADP
ajst-10982	92	16	computer	computer	NOUN
ajst-10982	92	17	vision	vision	NOUN
ajst-10982	92	18	and	and	CCONJ
ajst-10982	92	19	deep	deep	ADJ
ajst-10982	92	20	learning	learning	NOUN
ajst-10982	92	21	technology	technology	NOUN
ajst-10982	92	22	,	,	PUNCT
ajst-10982	92	23	deep	deep	ADJ
ajst-10982	92	24	learning	learning	NOUN
ajst-10982	92	25	-	-	PUNCT
ajst-10982	92	26	based	base	VERB
ajst-10982	92	27	plant	plant	NOUN
ajst-10982	92	28	root	root	NOUN
ajst-10982	92	29	segmentation	segmentation	NOUN
ajst-10982	92	30	has	have	AUX
ajst-10982	92	31	become	become	VERB
ajst-10982	92	32	a	a	DET
ajst-10982	92	33	research	research	NOUN
ajst-10982	92	34	hotspot	hotspot	NOUN
ajst-10982	92	35	.	.	PUNCT
ajst-10982	93	1	traditional	traditional	ADJ
ajst-10982	93	2	root	root	NOUN
ajst-10982	93	3	analysis	analysis	NOUN
ajst-10982	93	4	methods	method	NOUN
ajst-10982	93	5	require	require	VERB
ajst-10982	93	6	a	a	DET
ajst-10982	93	7	lot	lot	NOUN
ajst-10982	93	8	of	of	ADP
ajst-10982	93	9	manual	manual	ADJ
ajst-10982	93	10	processing	processing	NOUN
ajst-10982	93	11	work	work	NOUN
ajst-10982	93	12	and	and	CCONJ
ajst-10982	93	13	are	be	AUX
ajst-10982	93	14	prone	prone	ADJ
ajst-10982	93	15	to	to	ADP
ajst-10982	93	16	subjective	subjective	ADJ
ajst-10982	93	17	errors	error	NOUN
ajst-10982	93	18	,	,	PUNCT
ajst-10982	93	19	while	while	SCONJ
ajst-10982	93	20	deep	deep	ADJ
ajst-10982	93	21	learning	learning	NOUN
ajst-10982	93	22	technology	technology	NOUN
ajst-10982	93	23	can	can	AUX
ajst-10982	93	24	effectively	effectively	ADV
ajst-10982	93	25	realize	realize	VERB
ajst-10982	93	26	automated	automated	ADJ
ajst-10982	93	27	analysis	analysis	NOUN
ajst-10982	93	28	,	,	PUNCT
ajst-10982	93	29	and	and	CCONJ
ajst-10982	93	30	use	use	VERB
ajst-10982	93	31	multilayer	multilayer	ADJ
ajst-10982	93	32	neural	neural	ADJ
ajst-10982	93	33	networks	network	NOUN
ajst-10982	93	34	to	to	PART
ajst-10982	93	35	learn	learn	VERB
ajst-10982	93	36	and	and	CCONJ
ajst-10982	93	37	extract	extract	VERB
ajst-10982	93	38	complex	complex	ADJ
ajst-10982	93	39	image	image	NOUN
ajst-10982	93	40	information	information	NOUN
ajst-10982	93	41	accurately	accurately	ADV
ajst-10982	93	42	.	.	PUNCT
ajst-10982	94	1	3.1	3.1	NUM
ajst-10982	94	2	.	.	PUNCT
ajst-10982	94	3	deep	deep	ADJ
ajst-10982	94	4	learning	learn	VERB
ajst-10982	94	5	plant	plant	NOUN
ajst-10982	94	6	root	root	NOUN
ajst-10982	94	7	segmentation	segmentation	NOUN
ajst-10982	94	8	method	method	NOUN
ajst-10982	94	9	at	at	ADP
ajst-10982	94	10	present	present	ADJ
ajst-10982	94	11	,	,	PUNCT
ajst-10982	94	12	a	a	DET
ajst-10982	94	13	large	large	ADJ
ajst-10982	94	14	number	number	NOUN
ajst-10982	94	15	of	of	ADP
ajst-10982	94	16	studies	study	NOUN
ajst-10982	94	17	have	have	AUX
ajst-10982	94	18	explored	explore	VERB
ajst-10982	94	19	the	the	DET
ajst-10982	94	20	application	application	NOUN
ajst-10982	94	21	of	of	ADP
ajst-10982	94	22	deep	deep	ADJ
ajst-10982	94	23	learning	learning	NOUN
ajst-10982	94	24	in	in	ADP
ajst-10982	94	25	plant	plant	NOUN
ajst-10982	94	26	root	root	NOUN
ajst-10982	94	27	image	image	NOUN
ajst-10982	94	28	segmentation	segmentation	NOUN
ajst-10982	94	29	.	.	PUNCT
ajst-10982	95	1	two	two	NUM
ajst-10982	95	2	kinds	kind	NOUN
ajst-10982	95	3	of	of	ADP
ajst-10982	95	4	methods	method	NOUN
ajst-10982	95	5	are	be	AUX
ajst-10982	95	6	mainly	mainly	ADV
ajst-10982	95	7	used	use	VERB
ajst-10982	95	8	in	in	ADP
ajst-10982	95	9	deep	deep	ADJ
ajst-10982	95	10	learning	learning	NOUN
ajst-10982	95	11	-	-	PUNCT
ajst-10982	95	12	based	base	VERB
ajst-10982	95	13	plant	plant	NOUN
ajst-10982	95	14	root	root	NOUN
ajst-10982	95	15	segmentation	segmentation	NOUN
ajst-10982	95	16	:	:	PUNCT
ajst-10982	95	17	object	object	VERB
ajst-10982	95	18	detection	detection	NOUN
ajst-10982	95	19	and	and	CCONJ
ajst-10982	95	20	semantic	semantic	ADJ
ajst-10982	95	21	segmentation	segmentation	NOUN
ajst-10982	95	22	.	.	PUNCT
ajst-10982	96	1	the	the	DET
ajst-10982	96	2	object	object	NOUN
ajst-10982	96	3	detection	detection	NOUN
ajst-10982	96	4	method	method	NOUN
ajst-10982	96	5	can	can	AUX
ajst-10982	96	6	find	find	VERB
ajst-10982	96	7	the	the	DET
ajst-10982	96	8	region	region	NOUN
ajst-10982	96	9	of	of	ADP
ajst-10982	96	10	interest	interest	NOUN
ajst-10982	96	11	first	first	ADV
ajst-10982	96	12	,	,	PUNCT
ajst-10982	96	13	and	and	CCONJ
ajst-10982	96	14	then	then	ADV
ajst-10982	96	15	further	further	ADJ
ajst-10982	96	16	segment	segment	NOUN
ajst-10982	96	17	and	and	CCONJ
ajst-10982	96	18	extract	extract	VERB
ajst-10982	96	19	the	the	DET
ajst-10982	96	20	region	region	NOUN
ajst-10982	96	21	,	,	PUNCT
ajst-10982	96	22	so	so	CCONJ
ajst-10982	96	23	it	it	PRON
ajst-10982	96	24	has	have	VERB
ajst-10982	96	25	high	high	ADJ
ajst-10982	96	26	speed	speed	NOUN
ajst-10982	96	27	and	and	CCONJ
ajst-10982	96	28	robustness	robustness	NOUN
ajst-10982	96	29	.	.	PUNCT
ajst-10982	97	1	however	however	ADV
ajst-10982	97	2	,	,	PUNCT
ajst-10982	97	3	the	the	DET
ajst-10982	97	4	semantic	semantic	ADJ
ajst-10982	97	5	segmentation	segmentation	NOUN
ajst-10982	97	6	method	method	NOUN
ajst-10982	97	7	pays	pay	VERB
ajst-10982	97	8	more	more	ADJ
ajst-10982	97	9	attention	attention	NOUN
ajst-10982	97	10	to	to	ADP
ajst-10982	97	11	details	detail	NOUN
ajst-10982	97	12	and	and	CCONJ
ajst-10982	97	13	precision	precision	NOUN
ajst-10982	97	14	,	,	PUNCT
ajst-10982	97	15	and	and	CCONJ
ajst-10982	97	16	can	can	AUX
ajst-10982	97	17	accurately	accurately	ADV
ajst-10982	97	18	segment	segment	VERB
ajst-10982	97	19	each	each	DET
ajst-10982	97	20	part	part	NOUN
ajst-10982	97	21	of	of	ADP
ajst-10982	97	22	plant	plant	NOUN
ajst-10982	97	23	root	root	NOUN
ajst-10982	97	24	system	system	NOUN
ajst-10982	97	25	.	.	PUNCT
ajst-10982	98	1	root	root	NOUN
ajst-10982	98	2	segmentation	segmentation	NOUN
ajst-10982	98	3	methods	method	NOUN
ajst-10982	98	4	include	include	VERB
ajst-10982	98	5	convolutional	convolutional	ADJ
ajst-10982	98	6	neural	neural	ADJ
ajst-10982	98	7	network	network	NOUN
ajst-10982	98	8	(	(	PUNCT
ajst-10982	98	9	cnn	cnn	PROPN
ajst-10982	98	10	)	)	PUNCT
ajst-10982	99	1	[	[	X
ajst-10982	99	2	39	39	NUM
ajst-10982	99	3	]	]	PUNCT
ajst-10982	99	4	,	,	PUNCT
ajst-10982	99	5	full	full	ADJ
ajst-10982	99	6	convolutional	convolutional	ADJ
ajst-10982	99	7	neural	neural	ADJ
ajst-10982	99	8	network	network	NOUN
ajst-10982	99	9	(	(	PUNCT
ajst-10982	99	10	cnn	cnn	PROPN
ajst-10982	99	11	)	)	PUNCT
ajst-10982	99	12	,	,	PUNCT
ajst-10982	99	13	fcnn	fcnn	ADJ
ajst-10982	99	14	)	)	PUNCT
ajst-10982	100	1	[	[	X
ajst-10982	100	2	40	40	NUM
ajst-10982	100	3	]	]	PUNCT
ajst-10982	100	4	and	and	CCONJ
ajst-10982	100	5	deep	deep	ADJ
ajst-10982	100	6	convolutional	convolutional	ADJ
ajst-10982	100	7	neural	neural	ADJ
ajst-10982	100	8	network	network	NOUN
ajst-10982	100	9	(	(	PUNCT
ajst-10982	100	10	dcnn	dcnn	PROPN
ajst-10982	100	11	)	)	PUNCT
ajst-10982	101	1	[	[	X
ajst-10982	101	2	41	41	NUM
ajst-10982	101	3	]	]	PUNCT
ajst-10982	101	4	.	.	PUNCT
ajst-10982	102	1	among	among	ADP
ajst-10982	102	2	them	they	PRON
ajst-10982	102	3	,	,	PUNCT
ajst-10982	102	4	convolutional	convolutional	ADJ
ajst-10982	102	5	neural	neural	ADJ
ajst-10982	102	6	network	network	NOUN
ajst-10982	102	7	is	be	AUX
ajst-10982	102	8	the	the	DET
ajst-10982	102	9	most	most	ADV
ajst-10982	102	10	widely	widely	ADV
ajst-10982	102	11	used	use	VERB
ajst-10982	102	12	architecture	architecture	NOUN
ajst-10982	102	13	in	in	ADP
ajst-10982	102	14	deep	deep	ADJ
ajst-10982	102	15	learning	learning	NOUN
ajst-10982	102	16	,	,	PUNCT
ajst-10982	102	17	which	which	PRON
ajst-10982	102	18	has	have	VERB
ajst-10982	102	19	a	a	DET
ajst-10982	102	20	good	good	ADJ
ajst-10982	102	21	performance	performance	NOUN
ajst-10982	102	22	in	in	ADP
ajst-10982	102	23	the	the	DET
ajst-10982	102	24	root	root	NOUN
ajst-10982	102	25	image	image	NOUN
ajst-10982	102	26	segmentation	segmentation	NOUN
ajst-10982	102	27	task	task	NOUN
ajst-10982	102	28	.	.	PUNCT
ajst-10982	103	1	by	by	ADP
ajst-10982	103	2	constructing	construct	VERB
ajst-10982	103	3	appropriate	appropriate	ADJ
ajst-10982	103	4	network	network	NOUN
ajst-10982	103	5	structure	structure	NOUN
ajst-10982	103	6	and	and	CCONJ
ajst-10982	103	7	training	training	NOUN
ajst-10982	103	8	sample	sample	NOUN
ajst-10982	103	9	data	datum	NOUN
ajst-10982	103	10	set	set	VERB
ajst-10982	103	11	,	,	PUNCT
ajst-10982	103	12	high	high	ADJ
ajst-10982	103	13	precision	precision	NOUN
ajst-10982	103	14	root	root	NOUN
ajst-10982	103	15	segmentation	segmentation	NOUN
ajst-10982	103	16	results	result	NOUN
ajst-10982	103	17	can	can	AUX
ajst-10982	103	18	be	be	AUX
ajst-10982	103	19	obtained	obtain	VERB
ajst-10982	103	20	.	.	PUNCT
ajst-10982	104	1	therefore	therefore	ADV
ajst-10982	104	2	,	,	PUNCT
ajst-10982	104	3	in	in	ADP
ajst-10982	104	4	recent	recent	ADJ
ajst-10982	104	5	years	year	NOUN
ajst-10982	104	6	,	,	PUNCT
ajst-10982	104	7	many	many	ADJ
ajst-10982	104	8	scholars	scholar	NOUN
ajst-10982	104	9	have	have	AUX
ajst-10982	104	10	conducted	conduct	VERB
ajst-10982	104	11	research	research	NOUN
ajst-10982	104	12	on	on	ADP
ajst-10982	104	13	it	it	PRON
ajst-10982	104	14	.	.	PUNCT
ajst-10982	105	1	for	for	ADP
ajst-10982	105	2	example	example	NOUN
ajst-10982	105	3	,	,	PUNCT
ajst-10982	105	4	tao	tao	PROPN
ajst-10982	105	5	et	et	PROPN
ajst-10982	105	6	al	al	PROPN
ajst-10982	105	7	.	.	PUNCT
ajst-10982	106	1	[	[	X
ajst-10982	106	2	42	42	NUM
ajst-10982	106	3	]	]	PUNCT
ajst-10982	106	4	adopted	adopt	VERB
ajst-10982	106	5	the	the	DET
ajst-10982	106	6	convolutional	convolutional	ADJ
ajst-10982	106	7	neural	neural	ADJ
ajst-10982	106	8	network	network	NOUN
ajst-10982	106	9	architecture	architecture	NOUN
ajst-10982	106	10	and	and	CCONJ
ajst-10982	106	11	segroot	segroot	ADJ
ajst-10982	106	12	network	network	NOUN
ajst-10982	106	13	to	to	PART
ajst-10982	106	14	directly	directly	ADV
ajst-10982	106	15	learn	learn	VERB
ajst-10982	106	16	morphological	morphological	ADJ
ajst-10982	106	17	features	feature	NOUN
ajst-10982	106	18	with	with	ADP
ajst-10982	106	19	different	different	ADJ
ajst-10982	106	20	abstraction	abstraction	NOUN
ajst-10982	106	21	levels	level	NOUN
ajst-10982	106	22	from	from	ADP
ajst-10982	106	23	root	root	NOUN
ajst-10982	106	24	images	image	NOUN
ajst-10982	106	25	for	for	ADP
ajst-10982	106	26	pixel	pixel	ADJ
ajst-10982	106	27	-	-	PUNCT
ajst-10982	106	28	level	level	NOUN
ajst-10982	106	29	classification	classification	NOUN
ajst-10982	106	30	,	,	PUNCT
ajst-10982	106	31	so	so	SCONJ
ajst-10982	106	32	as	as	SCONJ
ajst-10982	106	33	to	to	PART
ajst-10982	106	34	achieve	achieve	VERB
ajst-10982	106	35	high	high	ADJ
ajst-10982	106	36	-	-	PUNCT
ajst-10982	106	37	throughput	throughput	NOUN
ajst-10982	106	38	segmentation	segmentation	NOUN
ajst-10982	106	39	of	of	ADP
ajst-10982	106	40	root	root	NOUN
ajst-10982	106	41	images	image	NOUN
ajst-10982	106	42	.	.	PUNCT
ajst-10982	107	1	in	in	ADP
ajst-10982	107	2	addition	addition	NOUN
ajst-10982	107	3	,	,	PUNCT
ajst-10982	107	4	the	the	DET
ajst-10982	107	5	idea	idea	NOUN
ajst-10982	107	6	of	of	ADP
ajst-10982	107	7	pixelsuffle	pixelsuffle	PROPN
ajst-10982	107	8	algorithm	algorithm	PROPN
ajst-10982	107	9	is	be	AUX
ajst-10982	107	10	used	use	VERB
ajst-10982	107	11	to	to	PART
ajst-10982	107	12	enhance	enhance	VERB
ajst-10982	107	13	the	the	DET
ajst-10982	107	14	fusion	fusion	NOUN
ajst-10982	107	15	features	feature	NOUN
ajst-10982	107	16	before	before	ADP
ajst-10982	107	17	the	the	DET
ajst-10982	107	18	decoder	decoder	NOUN
ajst-10982	107	19	output	output	NOUN
ajst-10982	107	20	,	,	PUNCT
ajst-10982	107	21	so	so	SCONJ
ajst-10982	107	22	as	as	SCONJ
ajst-10982	107	23	to	to	PART
ajst-10982	107	24	achieve	achieve	VERB
ajst-10982	107	25	high	high	ADJ
ajst-10982	107	26	-	-	PUNCT
ajst-10982	107	27	throughput	throughput	NOUN
ajst-10982	107	28	in	in	ADP
ajst-10982	107	29	-	-	PUNCT
ajst-10982	107	30	situ	situ	NOUN
ajst-10982	107	31	root	root	NOUN
ajst-10982	107	32	image	image	NOUN
ajst-10982	107	33	segmentation	segmentation	NOUN
ajst-10982	108	1	[	[	X
ajst-10982	108	2	28	28	NUM
ajst-10982	108	3	]	]	PUNCT
ajst-10982	108	4	.	.	PUNCT
ajst-10982	109	1	tao	tao	PROPN
ajst-10982	109	2	and	and	CCONJ
ajst-10982	109	3	shen	shen	PROPN
ajst-10982	109	4	et	et	PROPN
ajst-10982	109	5	al	al	PROPN
ajst-10982	109	6	.	.	PROPN
ajst-10982	109	7	achieved	achieve	VERB
ajst-10982	109	8	segmentation	segmentation	NOUN
ajst-10982	109	9	on	on	ADP
ajst-10982	109	10	two	two	NUM
ajst-10982	109	11	-	-	PUNCT
ajst-10982	109	12	dimensional	dimensional	ADJ
ajst-10982	109	13	root	root	NOUN
ajst-10982	109	14	images	image	NOUN
ajst-10982	109	15	,	,	PUNCT
ajst-10982	109	16	which	which	PRON
ajst-10982	109	17	can	can	AUX
ajst-10982	109	18	be	be	AUX
ajst-10982	109	19	used	use	VERB
ajst-10982	109	20	to	to	PART
ajst-10982	109	21	analyze	analyze	VERB
ajst-10982	109	22	the	the	DET
ajst-10982	109	23	growth	growth	NOUN
ajst-10982	109	24	of	of	ADP
ajst-10982	109	25	plants	plant	NOUN
ajst-10982	109	26	on	on	ADP
ajst-10982	109	27	the	the	DET
ajst-10982	109	28	plane	plane	NOUN
ajst-10982	109	29	,	,	PUNCT
ajst-10982	109	30	but	but	CCONJ
ajst-10982	109	31	the	the	DET
ajst-10982	109	32	internal	internal	ADJ
ajst-10982	109	33	morphological	morphological	ADJ
ajst-10982	109	34	structure	structure	NOUN
ajst-10982	109	35	of	of	ADP
ajst-10982	109	36	the	the	DET
ajst-10982	109	37	root	root	NOUN
ajst-10982	109	38	system	system	NOUN
ajst-10982	109	39	is	be	AUX
ajst-10982	109	40	not	not	PART
ajst-10982	109	41	well	well	ADV
ajst-10982	109	42	analyzed	analyze	VERB
ajst-10982	109	43	and	and	CCONJ
ajst-10982	109	44	studied	study	VERB
ajst-10982	109	45	.	.	PUNCT
ajst-10982	110	1	subsequently	subsequently	ADV
ajst-10982	110	2	,	,	PUNCT
ajst-10982	110	3	zhao	zhao	PROPN
ajst-10982	110	4	et	et	PROPN
ajst-10982	110	5	al	al	PROPN
ajst-10982	110	6	.	.	PUNCT
ajst-10982	111	1	[	[	X
ajst-10982	111	2	43	43	NUM
ajst-10982	111	3	]	]	PUNCT
ajst-10982	111	4	utilized	utilize	VERB
ajst-10982	111	5	a	a	DET
ajst-10982	111	6	convolutional	convolutional	ADJ
ajst-10982	111	7	neural	neural	ADJ
ajst-10982	111	8	network	network	NOUN
ajst-10982	111	9	composed	compose	VERB
ajst-10982	111	10	of	of	ADP
ajst-10982	111	11	an	an	DET
ajst-10982	111	12	encoder	encoder	NOUN
ajst-10982	111	13	and	and	CCONJ
ajst-10982	111	14	a	a	DET
ajst-10982	111	15	decoder	decoder	NOUN
ajst-10982	111	16	,	,	PUNCT
ajst-10982	111	17	and	and	CCONJ
ajst-10982	111	18	the	the	DET
ajst-10982	111	19	encoder	encoder	NOUN
ajst-10982	111	20	was	be	AUX
ajst-10982	111	21	composed	compose	VERB
ajst-10982	111	22	of	of	ADP
ajst-10982	111	23	three	three	NUM
ajst-10982	111	24	convolutional	convolutional	ADJ
ajst-10982	111	25	modules	module	NOUN
ajst-10982	111	26	to	to	PART
ajst-10982	111	27	achieve	achieve	VERB
ajst-10982	111	28	three	three	NUM
ajst-10982	111	29	-	-	PUNCT
ajst-10982	111	30	dimensional	dimensional	ADJ
ajst-10982	111	31	superresolution	superresolution	NOUN
ajst-10982	111	32	image	image	NOUN
ajst-10982	111	33	segmentation	segmentation	NOUN
ajst-10982	111	34	of	of	ADP
ajst-10982	111	35	plant	plant	NOUN
ajst-10982	111	36	root	root	NOUN
ajst-10982	111	37	mri	mri	NOUN
ajst-10982	111	38	.	.	PUNCT
ajst-10982	112	1	thus	thus	ADV
ajst-10982	112	2	,	,	PUNCT
ajst-10982	112	3	the	the	DET
ajst-10982	112	4	morphological	morphological	ADJ
ajst-10982	112	5	characteristics	characteristic	NOUN
ajst-10982	112	6	inside	inside	ADP
ajst-10982	112	7	the	the	DET
ajst-10982	112	8	root	root	NOUN
ajst-10982	112	9	system	system	NOUN
ajst-10982	112	10	can	can	AUX
ajst-10982	112	11	be	be	AUX
ajst-10982	112	12	further	far	ADV
ajst-10982	112	13	analyzed	analyze	VERB
ajst-10982	112	14	,	,	PUNCT
ajst-10982	112	15	and	and	CCONJ
ajst-10982	112	16	the	the	DET
ajst-10982	112	17	changes	change	NOUN
ajst-10982	112	18	of	of	ADP
ajst-10982	112	19	nutrients	nutrient	NOUN
ajst-10982	112	20	absorbed	absorb	VERB
ajst-10982	112	21	by	by	ADP
ajst-10982	112	22	plants	plant	NOUN
ajst-10982	112	23	can	can	AUX
ajst-10982	112	24	be	be	AUX
ajst-10982	112	25	obtained	obtain	VERB
ajst-10982	112	26	by	by	ADP
ajst-10982	112	27	using	use	VERB
ajst-10982	112	28	the	the	DET
ajst-10982	112	29	root	root	NOUN
ajst-10982	112	30	structure	structure	NOUN
ajst-10982	112	31	.	.	PUNCT
ajst-10982	113	1	some	some	DET
ajst-10982	113	2	scholars	scholar	NOUN
ajst-10982	113	3	also	also	ADV
ajst-10982	113	4	designed	design	VERB
ajst-10982	113	5	the	the	DET
ajst-10982	113	6	root	root	NOUN
ajst-10982	113	7	segmentation	segmentation	NOUN
ajst-10982	113	8	network	network	NOUN
ajst-10982	113	9	in	in	ADP
ajst-10982	113	10	order	order	NOUN
ajst-10982	113	11	to	to	PART
ajst-10982	113	12	realize	realize	VERB
ajst-10982	113	13	the	the	DET
ajst-10982	113	14	research	research	NOUN
ajst-10982	113	15	of	of	ADP
ajst-10982	113	16	a	a	DET
ajst-10982	113	17	certain	certain	ADJ
ajst-10982	113	18	growth	growth	NOUN
ajst-10982	113	19	parameter	parameter	NOUN
ajst-10982	113	20	of	of	ADP
ajst-10982	113	21	plant	plant	NOUN
ajst-10982	113	22	roots	root	NOUN
ajst-10982	113	23	.	.	PUNCT
ajst-10982	114	1	just	just	ADV
ajst-10982	114	2	as	as	SCONJ
ajst-10982	114	3	seidenthal	seidenthal	NOUN
ajst-10982	114	4	et	et	PROPN
ajst-10982	114	5	al	al	PROPN
ajst-10982	114	6	.	.	PUNCT
ajst-10982	115	1	[	[	X
ajst-10982	115	2	44	44	NUM
ajst-10982	115	3	]	]	PUNCT
ajst-10982	115	4	obtained	obtain	VERB
ajst-10982	115	5	a	a	DET
ajst-10982	115	6	high	high	ADJ
ajst-10982	115	7	-	-	PUNCT
ajst-10982	115	8	quality	quality	NOUN
ajst-10982	115	9	two	two	NUM
ajst-10982	115	10	-	-	PUNCT
ajst-10982	115	11	dimensional	dimensional	ADJ
ajst-10982	115	12	root	root	NOUN
ajst-10982	115	13	segmentation	segmentation	NOUN
ajst-10982	115	14	model	model	NOUN
ajst-10982	115	15	by	by	ADP
ajst-10982	115	16	using	use	VERB
ajst-10982	115	17	the	the	DET
ajst-10982	115	18	iterative	iterative	ADJ
ajst-10982	115	19	neural	neural	ADJ
ajst-10982	115	20	network	network	NOUN
ajst-10982	115	21	architecture	architecture	NOUN
ajst-10982	115	22	to	to	PART
ajst-10982	115	23	accurately	accurately	ADV
ajst-10982	115	24	segment	segment	VERB
ajst-10982	115	25	the	the	DET
ajst-10982	115	26	thin	thin	ADJ
ajst-10982	115	27	and	and	CCONJ
ajst-10982	115	28	highly	highly	ADV
ajst-10982	115	29	branched	branched	ADJ
ajst-10982	115	30	roots	root	NOUN
ajst-10982	115	31	.	.	PUNCT
ajst-10982	116	1	based	base	VERB
ajst-10982	116	2	on	on	ADP
ajst-10982	116	3	deeplabv3	deeplabv3	ADJ
ajst-10982	116	4	+	+	CCONJ
ajst-10982	116	5	semantic	semantic	ADJ
ajst-10982	116	6	segmentation	segmentation	NOUN
ajst-10982	116	7	model	model	NOUN
ajst-10982	116	8	,	,	PUNCT
ajst-10982	116	9	kang	kang	PROPN
ajst-10982	116	10	et	et	PROPN
ajst-10982	116	11	al	al	PROPN
ajst-10982	116	12	.	.	PUNCT
ajst-10982	117	1	[	[	X
ajst-10982	117	2	45	45	NUM
ajst-10982	117	3	]	]	PUNCT
ajst-10982	117	4	introduced	introduce	VERB
ajst-10982	117	5	subpixel	subpixel	ADJ
ajst-10982	117	6	convolution	convolution	NOUN
ajst-10982	117	7	and	and	CCONJ
ajst-10982	117	8	added	add	VERB
ajst-10982	117	9	attention	attention	NOUN
ajst-10982	117	10	mechanism	mechanism	NOUN
ajst-10982	117	11	structure	structure	NOUN
ajst-10982	117	12	.	.	PUNCT
ajst-10982	118	1	more	more	ADJ
ajst-10982	118	2	weight	weight	NOUN
ajst-10982	118	3	is	be	AUX
ajst-10982	118	4	given	give	VERB
ajst-10982	118	5	to	to	ADP
ajst-10982	118	6	fine	fine	ADJ
ajst-10982	118	7	root	root	NOUN
ajst-10982	118	8	pixels	pixel	NOUN
ajst-10982	118	9	and	and	CCONJ
ajst-10982	118	10	root	root	NOUN
ajst-10982	118	11	hairs	hair	NOUN
ajst-10982	118	12	,	,	PUNCT
ajst-10982	118	13	and	and	CCONJ
ajst-10982	118	14	a	a	DET
ajst-10982	118	15	more	more	ADV
ajst-10982	118	16	accurate	accurate	ADJ
ajst-10982	118	17	semantic	semantic	ADJ
ajst-10982	118	18	segmentation	segmentation	NOUN
ajst-10982	118	19	model	model	NOUN
ajst-10982	118	20	of	of	ADP
ajst-10982	118	21	cotton	cotton	NOUN
ajst-10982	118	22	root	root	NOUN
ajst-10982	118	23	in	in	ADP
ajst-10982	118	24	situ	situ	ADJ
ajst-10982	118	25	image	image	NOUN
ajst-10982	118	26	is	be	AUX
ajst-10982	118	27	obtained	obtain	VERB
ajst-10982	118	28	.	.	PUNCT
ajst-10982	119	1	on	on	ADP
ajst-10982	119	2	this	this	DET
ajst-10982	119	3	basis	basis	NOUN
ajst-10982	119	4	,	,	PUNCT
ajst-10982	119	5	the	the	DET
ajst-10982	119	6	network	network	NOUN
ajst-10982	119	7	model	model	NOUN
ajst-10982	119	8	is	be	AUX
ajst-10982	119	9	improved	improve	VERB
ajst-10982	119	10	to	to	PART
ajst-10982	119	11	obtain	obtain	VERB
ajst-10982	119	12	a	a	DET
ajst-10982	119	13	more	more	ADV
ajst-10982	119	14	accurate	accurate	ADJ
ajst-10982	119	15	and	and	CCONJ
ajst-10982	119	16	effective	effective	ADJ
ajst-10982	119	17	root	root	NOUN
ajst-10982	119	18	extraction	extraction	NOUN
ajst-10982	119	19	network	network	NOUN
ajst-10982	119	20	.	.	PUNCT
ajst-10982	120	1	alle	alle	NOUN
ajst-10982	120	2	et	et	PROPN
ajst-10982	120	3	al	al	PROPN
ajst-10982	120	4	.	.	PUNCT
ajst-10982	121	1	[	[	X
ajst-10982	121	2	46	46	NUM
ajst-10982	121	3	]	]	PUNCT
ajst-10982	121	4	used	use	VERB
ajst-10982	121	5	the	the	DET
ajst-10982	121	6	combination	combination	NOUN
ajst-10982	121	7	of	of	ADP
ajst-10982	121	8	deep	deep	ADJ
ajst-10982	121	9	convolutional	convolutional	ADJ
ajst-10982	121	10	neural	neural	ADJ
ajst-10982	121	11	network	network	NOUN
ajst-10982	121	12	and	and	CCONJ
ajst-10982	121	13	weakly	weakly	ADJ
ajst-10982	121	14	supervised	supervised	ADJ
ajst-10982	121	15	learning	learning	NOUN
ajst-10982	121	16	paradigm	paradigm	NOUN
ajst-10982	121	17	to	to	PART
ajst-10982	121	18	detect	detect	VERB
ajst-10982	121	19	finer	fine	ADJ
ajst-10982	121	20	root	root	NOUN
ajst-10982	121	21	structures	structure	NOUN
ajst-10982	121	22	,	,	PUNCT
ajst-10982	121	23	thereby	thereby	ADV
ajst-10982	121	24	improving	improve	VERB
ajst-10982	121	25	the	the	DET
ajst-10982	121	26	accuracy	accuracy	NOUN
ajst-10982	121	27	of	of	ADP
ajst-10982	121	28	root	root	NOUN
ajst-10982	121	29	extraction	extraction	NOUN
ajst-10982	121	30	.	.	PUNCT
ajst-10982	122	1	shen	shen	PROPN
ajst-10982	122	2	chen	chen	PROPN
ajst-10982	123	1	[	[	X
ajst-10982	123	2	17	17	NUM
ajst-10982	123	3	]	]	X
ajst-10982	123	4	uses	use	VERB
ajst-10982	123	5	sp	sp	NOUN
ajst-10982	123	6	-	-	PUNCT
ajst-10982	123	7	deeplavb3	deeplavb3	NOUN
ajst-10982	123	8	+	+	NOUN
ajst-10982	123	9	model	model	NOUN
ajst-10982	123	10	based	base	VERB
ajst-10982	123	11	on	on	ADP
ajst-10982	123	12	subpixel	subpixel	ADJ
ajst-10982	123	13	convolution	convolution	NOUN
ajst-10982	123	14	[	[	X
ajst-10982	123	15	47	47	NUM
ajst-10982	123	16	]	]	PUNCT
ajst-10982	123	17	to	to	PART
ajst-10982	123	18	segment	segment	VERB
ajst-10982	123	19	cotton	cotton	NOUN
ajst-10982	123	20	root	root	NOUN
ajst-10982	123	21	images	image	NOUN
ajst-10982	123	22	in	in	ADP
ajst-10982	123	23	situ	situ	NOUN
ajst-10982	123	24	and	and	CCONJ
ajst-10982	123	25	improve	improve	VERB
ajst-10982	123	26	the	the	DET
ajst-10982	123	27	segmentation	segmentation	NOUN
ajst-10982	123	28	accuracy	accuracy	NOUN
ajst-10982	123	29	of	of	ADP
ajst-10982	123	30	small	small	ADJ
ajst-10982	123	31	branch	branch	NOUN
ajst-10982	123	32	contours	contours	NOUN
ajst-10982	123	33	.	.	PUNCT
ajst-10982	124	1	huang	huang	PROPN
ajst-10982	124	2	et	et	PROPN
ajst-10982	124	3	al	al	PROPN
ajst-10982	124	4	.	.	PUNCT
ajst-10982	125	1	[	[	X
ajst-10982	125	2	48	48	NUM
ajst-10982	125	3	]	]	PUNCT
ajst-10982	125	4	added	add	VERB
ajst-10982	125	5	a	a	DET
ajst-10982	125	6	global	global	ADJ
ajst-10982	125	7	attention	attention	NOUN
ajst-10982	125	8	mechanism	mechanism	NOUN
ajst-10982	125	9	(	(	PUNCT
ajst-10982	125	10	gam	gam	NOUN
ajst-10982	125	11	)	)	PUNCT
ajst-10982	126	1	[	[	X
ajst-10982	126	2	49	49	NUM
ajst-10982	126	3	]	]	PUNCT
ajst-10982	126	4	to	to	ADP
ajst-10982	126	5	the	the	DET
ajst-10982	126	6	ocrnet	ocrnet	NOUN
ajst-10982	126	7	network	network	NOUN
ajst-10982	126	8	to	to	PART
ajst-10982	126	9	increase	increase	VERB
ajst-10982	126	10	the	the	DET
ajst-10982	126	11	focus	focus	NOUN
ajst-10982	126	12	on	on	ADP
ajst-10982	126	13	root	root	NOUN
ajst-10982	126	14	targets	target	NOUN
ajst-10982	126	15	and	and	CCONJ
ajst-10982	126	16	improve	improve	VERB
ajst-10982	126	17	the	the	DET
ajst-10982	126	18	accuracy	accuracy	NOUN
ajst-10982	126	19	of	of	ADP
ajst-10982	126	20	automatic	automatic	ADJ
ajst-10982	126	21	root	root	NOUN
ajst-10982	126	22	segmentation	segmentation	NOUN
ajst-10982	126	23	.	.	PUNCT
ajst-10982	127	1	on	on	ADP
ajst-10982	127	2	the	the	DET
ajst-10982	127	3	premise	premise	NOUN
ajst-10982	127	4	of	of	ADP
ajst-10982	127	5	certain	certain	ADJ
ajst-10982	127	6	accuracy	accuracy	NOUN
ajst-10982	127	7	,	,	PUNCT
ajst-10982	127	8	the	the	DET
ajst-10982	127	9	root	root	NOUN
ajst-10982	127	10	morphological	morphological	ADJ
ajst-10982	127	11	structure	structure	NOUN
ajst-10982	127	12	was	be	AUX
ajst-10982	127	13	studied	study	VERB
ajst-10982	127	14	.	.	PUNCT
ajst-10982	128	1	wulan	wulan	VERB
ajst-10982	128	2	et	et	PROPN
ajst-10982	128	3	al	al	PROPN
ajst-10982	128	4	.	.	PUNCT
ajst-10982	129	1	[	[	X
ajst-10982	129	2	50	50	NUM
ajst-10982	129	3	]	]	PUNCT
ajst-10982	129	4	based	base	VERB
ajst-10982	129	5	on	on	ADP
ajst-10982	129	6	the	the	DET
ajst-10982	129	7	improved	improved	ADJ
ajst-10982	129	8	deeplabv3+[51	deeplabv3+[51	NOUN
ajst-10982	129	9	]	]	PUNCT
ajst-10982	129	10	network	network	NOUN
ajst-10982	129	11	to	to	PART
ajst-10982	129	12	segment	segment	VERB
ajst-10982	129	13	potato	potato	NOUN
ajst-10982	129	14	root	root	NOUN
ajst-10982	129	15	image	image	NOUN
ajst-10982	129	16	and	and	CCONJ
ajst-10982	129	17	calculate	calculate	VERB
ajst-10982	129	18	potato	potato	NOUN
ajst-10982	129	19	root	root	NOUN
ajst-10982	129	20	length	length	NOUN
ajst-10982	129	21	and	and	CCONJ
ajst-10982	129	22	other	other	ADJ
ajst-10982	129	23	features	feature	NOUN
ajst-10982	129	24	,	,	PUNCT
ajst-10982	129	25	they	they	PRON
ajst-10982	129	26	can	can	AUX
ajst-10982	129	27	have	have	VERB
ajst-10982	129	28	a	a	DET
ajst-10982	129	29	more	more	ADV
ajst-10982	129	30	comprehensive	comprehensive	ADJ
ajst-10982	129	31	understanding	understanding	NOUN
ajst-10982	129	32	of	of	ADP
ajst-10982	129	33	plant	plant	NOUN
ajst-10982	129	34	growth	growth	NOUN
ajst-10982	129	35	under	under	ADP
ajst-10982	129	36	different	different	ADJ
ajst-10982	129	37	environmental	environmental	ADJ
ajst-10982	129	38	conditions	condition	NOUN
ajst-10982	129	39	,	,	PUNCT
ajst-10982	129	40	which	which	PRON
ajst-10982	129	41	is	be	AUX
ajst-10982	129	42	helpful	helpful	ADJ
ajst-10982	129	43	to	to	PART
ajst-10982	129	44	explore	explore	VERB
ajst-10982	129	45	plant	plant	NOUN
ajst-10982	129	46	physiological	physiological	ADJ
ajst-10982	129	47	ecology	ecology	NOUN
ajst-10982	129	48	and	and	CCONJ
ajst-10982	129	49	optimize	optimize	VERB
ajst-10982	129	50	plant	plant	NOUN
ajst-10982	129	51	planting	planting	NOUN
ajst-10982	129	52	management	management	NOUN
ajst-10982	129	53	.	.	PUNCT
ajst-10982	130	1	robail	robail	PROPN
ajst-10982	130	2	et	et	PROPN
ajst-10982	130	3	al	al	PROPN
ajst-10982	130	4	.	.	PUNCT
ajst-10982	131	1	[	[	X
ajst-10982	131	2	52	52	NUM
ajst-10982	131	3	]	]	PUNCT
ajst-10982	131	4	used	use	VERB
ajst-10982	131	5	a	a	DET
ajst-10982	131	6	multi	multi	ADJ
ajst-10982	131	7	-	-	ADJ
ajst-10982	131	8	task	task	ADJ
ajst-10982	131	9	convolutional	convolutional	ADJ
ajst-10982	131	10	neural	neural	ADJ
ajst-10982	131	11	network	network	NOUN
ajst-10982	131	12	to	to	PART
ajst-10982	131	13	extract	extract	VERB
ajst-10982	131	14	image	image	NOUN
ajst-10982	131	15	features	feature	NOUN
ajst-10982	131	16	from	from	ADP
ajst-10982	131	17	the	the	DET
ajst-10982	131	18	encoder	encoder	NOUN
ajst-10982	131	19	,	,	PUNCT
ajst-10982	131	20	and	and	CCONJ
ajst-10982	131	21	then	then	ADV
ajst-10982	131	22	used	use	VERB
ajst-10982	131	23	the	the	DET
ajst-10982	131	24	seeds	seed	NOUN
ajst-10982	131	25	,	,	PUNCT
ajst-10982	131	26	primary	primary	ADJ
ajst-10982	131	27	and	and	CCONJ
ajst-10982	131	28	secondary	secondary	ADJ
ajst-10982	131	29	root	root	NOUN
ajst-10982	131	30	tips	tip	NOUN
ajst-10982	131	31	located	locate	VERB
ajst-10982	131	32	by	by	ADP
ajst-10982	131	33	the	the	DET
ajst-10982	131	34	network	network	NOUN
ajst-10982	131	35	to	to	PART
ajst-10982	131	36	drive	drive	VERB
ajst-10982	131	37	the	the	DET
ajst-10982	131	38	search	search	NOUN
ajst-10982	131	39	algorithm	algorithm	NOUN
ajst-10982	131	40	to	to	PART
ajst-10982	131	41	find	find	VERB
ajst-10982	131	42	the	the	DET
ajst-10982	131	43	best	good	ADJ
ajst-10982	131	44	path	path	NOUN
ajst-10982	131	45	and	and	CCONJ
ajst-10982	131	46	extract	extract	VERB
ajst-10982	131	47	root	root	NOUN
ajst-10982	131	48	structure	structure	NOUN
ajst-10982	131	49	to	to	PART
ajst-10982	131	50	achieve	achieve	VERB
ajst-10982	131	51	automated	automate	VERB
ajst-10982	131	52	root	root	NOUN
ajst-10982	131	53	structure	structure	NOUN
ajst-10982	131	54	navigation	navigation	NOUN
ajst-10982	131	55	,	,	PUNCT
ajst-10982	131	56	thereby	thereby	ADV
ajst-10982	131	57	quantification	quantification	NOUN
ajst-10982	131	58	and	and	CCONJ
ajst-10982	131	59	recording	recording	NOUN
ajst-10982	131	60	of	of	ADP
ajst-10982	131	61	various	various	ADJ
ajst-10982	131	62	plant	plant	NOUN
ajst-10982	131	63	growth	growth	NOUN
ajst-10982	131	64	parameters	parameter	NOUN
ajst-10982	131	65	(	(	PUNCT
ajst-10982	131	66	such	such	ADJ
ajst-10982	131	67	as	as	ADP
ajst-10982	131	68	taproot	taproot	ADJ
ajst-10982	131	69	length	length	NOUN
ajst-10982	131	70	or	or	CCONJ
ajst-10982	131	71	total	total	ADJ
ajst-10982	131	72	area	area	NOUN
ajst-10982	131	73	,	,	PUNCT
ajst-10982	131	74	etc	etc	X
ajst-10982	131	75	.	.	X
ajst-10982	131	76	)	)	PUNCT
ajst-10982	131	77	.	.	PUNCT
ajst-10982	132	1	allowing	allow	VERB
ajst-10982	132	2	for	for	ADP
ajst-10982	132	3	more	more	ADV
ajst-10982	132	4	detailed	detailed	ADJ
ajst-10982	132	5	structural	structural	ADJ
ajst-10982	132	6	analysis	analysis	NOUN
ajst-10982	132	7	.	.	PUNCT
ajst-10982	133	1	although	although	SCONJ
ajst-10982	133	2	the	the	DET
ajst-10982	133	3	current	current	ADJ
ajst-10982	133	4	research	research	NOUN
ajst-10982	133	5	has	have	AUX
ajst-10982	133	6	achieved	achieve	VERB
ajst-10982	133	7	good	good	ADJ
ajst-10982	133	8	results	result	NOUN
ajst-10982	133	9	in	in	ADP
ajst-10982	133	10	the	the	DET
ajst-10982	133	11	accurate	accurate	ADJ
ajst-10982	133	12	acquisition	acquisition	NOUN
ajst-10982	133	13	of	of	ADP
ajst-10982	133	14	roots	root	NOUN
ajst-10982	133	15	,	,	PUNCT
ajst-10982	133	16	the	the	DET
ajst-10982	133	17	requirements	requirement	NOUN
ajst-10982	133	18	for	for	ADP
ajst-10982	133	19	equipment	equipment	NOUN
ajst-10982	133	20	are	be	AUX
ajst-10982	133	21	becoming	become	VERB
ajst-10982	133	22	higher	high	ADJ
ajst-10982	133	23	and	and	CCONJ
ajst-10982	133	24	higher	high	ADJ
ajst-10982	133	25	,	,	PUNCT
ajst-10982	133	26	28	28	NUM
ajst-10982	133	27	resulting	result	VERB
ajst-10982	133	28	in	in	ADP
ajst-10982	133	29	increasing	increase	VERB
ajst-10982	133	30	costs	cost	NOUN
ajst-10982	133	31	.	.	PUNCT
ajst-10982	134	1	yu	yu	PROPN
ajst-10982	134	2	et	et	PROPN
ajst-10982	134	3	al	al	PROPN
ajst-10982	134	4	.	.	PUNCT
ajst-10982	135	1	[	[	X
ajst-10982	135	2	53	53	NUM
ajst-10982	135	3	]	]	PUNCT
ajst-10982	135	4	used	use	VERB
ajst-10982	135	5	deeplabv3	deeplabv3	ADV
ajst-10982	135	6	+	+	CCONJ
ajst-10982	135	7	semantic	semantic	ADJ
ajst-10982	135	8	segmentation	segmentation	NOUN
ajst-10982	135	9	model	model	NOUN
ajst-10982	135	10	to	to	PART
ajst-10982	135	11	design	design	VERB
ajst-10982	135	12	a	a	DET
ajst-10982	135	13	time	time	NOUN
ajst-10982	135	14	-	-	PUNCT
ajst-10982	135	15	saving	save	VERB
ajst-10982	135	16	fast	fast	ADJ
ajst-10982	135	17	prediction	prediction	NOUN
ajst-10982	135	18	strategy	strategy	NOUN
ajst-10982	135	19	to	to	PART
ajst-10982	135	20	achieve	achieve	VERB
ajst-10982	135	21	low	low	ADJ
ajst-10982	135	22	-	-	PUNCT
ajst-10982	135	23	cost	cost	NOUN
ajst-10982	135	24	and	and	CCONJ
ajst-10982	135	25	portable	portable	ADJ
ajst-10982	135	26	root	root	NOUN
ajst-10982	135	27	image	image	NOUN
ajst-10982	135	28	acquisition	acquisition	NOUN
ajst-10982	135	29	and	and	CCONJ
ajst-10982	135	30	segmentation	segmentation	NOUN
ajst-10982	135	31	.	.	PUNCT
ajst-10982	136	1	although	although	SCONJ
ajst-10982	136	2	the	the	DET
ajst-10982	136	3	time	time	NOUN
ajst-10982	136	4	and	and	CCONJ
ajst-10982	136	5	cost	cost	NOUN
ajst-10982	136	6	were	be	AUX
ajst-10982	136	7	reduced	reduce	VERB
ajst-10982	136	8	,	,	PUNCT
ajst-10982	136	9	the	the	DET
ajst-10982	136	10	extraction	extraction	NOUN
ajst-10982	136	11	accuracy	accuracy	NOUN
ajst-10982	136	12	would	would	AUX
ajst-10982	136	13	also	also	ADV
ajst-10982	136	14	be	be	AUX
ajst-10982	136	15	reduced	reduce	VERB
ajst-10982	136	16	.	.	PUNCT
ajst-10982	137	1	however	however	ADV
ajst-10982	137	2	,	,	PUNCT
ajst-10982	137	3	in	in	ADP
ajst-10982	137	4	general	general	ADJ
ajst-10982	137	5	,	,	PUNCT
ajst-10982	137	6	as	as	ADP
ajst-10982	137	7	one	one	NUM
ajst-10982	137	8	of	of	ADP
ajst-10982	137	9	the	the	DET
ajst-10982	137	10	current	current	ADJ
ajst-10982	137	11	research	research	NOUN
ajst-10982	137	12	hotspots	hotspot	NOUN
ajst-10982	137	13	in	in	ADP
ajst-10982	137	14	this	this	DET
ajst-10982	137	15	field	field	NOUN
ajst-10982	137	16	,	,	PUNCT
ajst-10982	137	17	many	many	ADJ
ajst-10982	137	18	scholars	scholar	NOUN
ajst-10982	137	19	have	have	AUX
ajst-10982	137	20	carried	carry	VERB
ajst-10982	137	21	out	out	ADP
ajst-10982	137	22	a	a	DET
ajst-10982	137	23	lot	lot	NOUN
ajst-10982	137	24	of	of	ADP
ajst-10982	137	25	work	work	NOUN
ajst-10982	137	26	on	on	ADP
ajst-10982	137	27	plant	plant	NOUN
ajst-10982	137	28	root	root	NOUN
ajst-10982	137	29	segmentation	segmentation	NOUN
ajst-10982	137	30	based	base	VERB
ajst-10982	137	31	on	on	ADP
ajst-10982	137	32	deep	deep	ADJ
ajst-10982	137	33	learning	learning	NOUN
ajst-10982	137	34	in	in	ADP
ajst-10982	137	35	this	this	DET
ajst-10982	137	36	direction	direction	NOUN
ajst-10982	137	37	,	,	PUNCT
ajst-10982	137	38	and	and	CCONJ
ajst-10982	137	39	gradually	gradually	ADV
ajst-10982	137	40	achieved	achieve	VERB
ajst-10982	137	41	good	good	ADJ
ajst-10982	137	42	results	result	NOUN
ajst-10982	137	43	.	.	PUNCT
ajst-10982	138	1	among	among	ADP
ajst-10982	138	2	them	they	PRON
ajst-10982	138	3	,	,	PUNCT
ajst-10982	138	4	the	the	DET
ajst-10982	138	5	most	most	ADV
ajst-10982	138	6	common	common	ADJ
ajst-10982	138	7	deep	deep	ADJ
ajst-10982	138	8	learning	learning	NOUN
ajst-10982	138	9	model	model	NOUN
ajst-10982	138	10	is	be	AUX
ajst-10982	138	11	convolutional	convolutional	ADJ
ajst-10982	138	12	neural	neural	ADJ
ajst-10982	138	13	network	network	NOUN
ajst-10982	138	14	,	,	PUNCT
ajst-10982	138	15	such	such	ADJ
ajst-10982	138	16	as	as	ADP
ajst-10982	138	17	u	u	NOUN
ajst-10982	138	18	-	-	NOUN
ajst-10982	138	19	net[54	net[54	NOUN
ajst-10982	138	20	]	]	PUNCT
ajst-10982	138	21	,	,	PUNCT
ajst-10982	138	22	fcn	fcn	PROPN
ajst-10982	138	23	,	,	PUNCT
ajst-10982	138	24	deeplab[55	deeplab[55	NOUN
ajst-10982	138	25	]	]	PUNCT
ajst-10982	138	26	,	,	PUNCT
ajst-10982	138	27	etc	etc	X
ajst-10982	138	28	.	.	X
ajst-10982	138	29	for	for	ADP
ajst-10982	138	30	different	different	ADJ
ajst-10982	138	31	plant	plant	NOUN
ajst-10982	138	32	root	root	NOUN
ajst-10982	138	33	image	image	NOUN
ajst-10982	138	34	characteristics	characteristic	NOUN
ajst-10982	138	35	,	,	PUNCT
ajst-10982	138	36	the	the	DET
ajst-10982	138	37	researchers	researcher	NOUN
ajst-10982	138	38	also	also	ADV
ajst-10982	138	39	combined	combine	VERB
ajst-10982	138	40	the	the	DET
ajst-10982	138	41	deep	deep	ADJ
ajst-10982	138	42	learning	learning	NOUN
ajst-10982	138	43	model	model	NOUN
ajst-10982	138	44	with	with	ADP
ajst-10982	138	45	other	other	ADJ
ajst-10982	138	46	methods	method	NOUN
ajst-10982	138	47	,	,	PUNCT
ajst-10982	138	48	including	include	VERB
ajst-10982	138	49	preprocessing	preprocessing	NOUN
ajst-10982	138	50	,	,	PUNCT
ajst-10982	138	51	image	image	NOUN
ajst-10982	138	52	enhancement	enhancement	NOUN
ajst-10982	138	53	,	,	PUNCT
ajst-10982	138	54	feature	feature	NOUN
ajst-10982	138	55	fusion	fusion	NOUN
ajst-10982	138	56	,	,	PUNCT
ajst-10982	138	57	etc	etc	X
ajst-10982	138	58	.	.	X
ajst-10982	138	59	,	,	PUNCT
ajst-10982	138	60	to	to	PART
ajst-10982	138	61	improve	improve	VERB
ajst-10982	138	62	the	the	DET
ajst-10982	138	63	performance	performance	NOUN
ajst-10982	138	64	of	of	ADP
ajst-10982	138	65	the	the	DET
ajst-10982	138	66	algorithm	algorithm	NOUN
ajst-10982	138	67	.	.	PUNCT
ajst-10982	139	1	at	at	ADP
ajst-10982	139	2	the	the	DET
ajst-10982	139	3	same	same	ADJ
ajst-10982	139	4	time	time	NOUN
ajst-10982	139	5	,	,	PUNCT
ajst-10982	139	6	more	more	ADJ
ajst-10982	139	7	and	and	CCONJ
ajst-10982	139	8	more	more	ADJ
ajst-10982	139	9	scholars	scholar	NOUN
ajst-10982	139	10	have	have	AUX
ajst-10982	139	11	begun	begin	VERB
ajst-10982	139	12	to	to	PART
ajst-10982	139	13	apply	apply	VERB
ajst-10982	139	14	this	this	DET
ajst-10982	139	15	technology	technology	NOUN
ajst-10982	139	16	in	in	ADP
ajst-10982	139	17	actual	actual	ADJ
ajst-10982	139	18	agricultural	agricultural	ADJ
ajst-10982	139	19	production	production	NOUN
ajst-10982	139	20	to	to	PART
ajst-10982	139	21	solve	solve	VERB
ajst-10982	139	22	practical	practical	ADJ
ajst-10982	139	23	problems	problem	NOUN
ajst-10982	139	24	and	and	CCONJ
ajst-10982	139	25	promote	promote	VERB
ajst-10982	139	26	sustainable	sustainable	ADJ
ajst-10982	139	27	development	development	NOUN
ajst-10982	139	28	of	of	ADP
ajst-10982	139	29	agriculture	agriculture	NOUN
ajst-10982	139	30	and	and	CCONJ
ajst-10982	139	31	ecology	ecology	NOUN
ajst-10982	139	32	.	.	PUNCT
ajst-10982	140	1	3.2	3.2	NUM
ajst-10982	140	2	.	.	PUNCT
ajst-10982	140	3	application	application	NOUN
ajst-10982	140	4	areas	area	NOUN
ajst-10982	140	5	with	with	ADP
ajst-10982	140	6	the	the	DET
ajst-10982	140	7	development	development	NOUN
ajst-10982	140	8	and	and	CCONJ
ajst-10982	140	9	progress	progress	NOUN
ajst-10982	140	10	of	of	ADP
ajst-10982	140	11	science	science	NOUN
ajst-10982	140	12	and	and	CCONJ
ajst-10982	140	13	technology	technology	NOUN
ajst-10982	140	14	,	,	PUNCT
ajst-10982	140	15	deep	deep	ADJ
ajst-10982	140	16	learning	learning	NOUN
ajst-10982	140	17	-	-	PUNCT
ajst-10982	140	18	based	base	VERB
ajst-10982	140	19	plant	plant	NOUN
ajst-10982	140	20	root	root	NOUN
ajst-10982	140	21	segmentation	segmentation	NOUN
ajst-10982	140	22	technology	technology	NOUN
ajst-10982	140	23	can	can	AUX
ajst-10982	140	24	be	be	AUX
ajst-10982	140	25	widely	widely	ADV
ajst-10982	140	26	used	use	VERB
ajst-10982	140	27	in	in	ADP
ajst-10982	140	28	plant	plant	NOUN
ajst-10982	140	29	science	science	NOUN
ajst-10982	140	30	,	,	PUNCT
ajst-10982	140	31	ecology	ecology	NOUN
ajst-10982	140	32	and	and	CCONJ
ajst-10982	140	33	agronomy	agronomy	NOUN
ajst-10982	140	34	.	.	PUNCT
ajst-10982	141	1	in	in	ADP
ajst-10982	141	2	the	the	DET
ajst-10982	141	3	field	field	NOUN
ajst-10982	141	4	of	of	ADP
ajst-10982	141	5	plant	plant	NOUN
ajst-10982	141	6	science	science	NOUN
ajst-10982	141	7	,	,	PUNCT
ajst-10982	141	8	deep	deep	ADJ
ajst-10982	141	9	learning	learning	NOUN
ajst-10982	141	10	-	-	PUNCT
ajst-10982	141	11	based	base	VERB
ajst-10982	141	12	techniques	technique	NOUN
ajst-10982	141	13	can	can	AUX
ajst-10982	141	14	be	be	AUX
ajst-10982	141	15	used	use	VERB
ajst-10982	141	16	to	to	PART
ajst-10982	141	17	study	study	VERB
ajst-10982	141	18	root	root	NOUN
ajst-10982	141	19	development	development	NOUN
ajst-10982	141	20	and	and	CCONJ
ajst-10982	141	21	structure	structure	NOUN
ajst-10982	141	22	.	.	PUNCT
ajst-10982	142	1	by	by	ADP
ajst-10982	142	2	segmentation	segmentation	NOUN
ajst-10982	142	3	of	of	ADP
ajst-10982	142	4	root	root	NOUN
ajst-10982	142	5	images	image	NOUN
ajst-10982	142	6	,	,	PUNCT
ajst-10982	142	7	the	the	DET
ajst-10982	142	8	morphological	morphological	ADJ
ajst-10982	142	9	parameters	parameter	NOUN
ajst-10982	142	10	of	of	ADP
ajst-10982	142	11	each	each	DET
ajst-10982	142	12	root	root	NOUN
ajst-10982	142	13	system	system	NOUN
ajst-10982	142	14	,	,	PUNCT
ajst-10982	142	15	such	such	ADJ
ajst-10982	142	16	as	as	ADP
ajst-10982	142	17	length	length	NOUN
ajst-10982	142	18	,	,	PUNCT
ajst-10982	142	19	diameter	diameter	NOUN
ajst-10982	142	20	and	and	CCONJ
ajst-10982	142	21	volume	volume	NOUN
ajst-10982	142	22	,	,	PUNCT
ajst-10982	142	23	can	can	AUX
ajst-10982	142	24	be	be	AUX
ajst-10982	142	25	extracted	extract	VERB
ajst-10982	142	26	,	,	PUNCT
ajst-10982	142	27	so	so	SCONJ
ajst-10982	142	28	as	as	SCONJ
ajst-10982	142	29	to	to	PART
ajst-10982	142	30	study	study	VERB
ajst-10982	142	31	the	the	DET
ajst-10982	142	32	adaptability	adaptability	NOUN
ajst-10982	142	33	and	and	CCONJ
ajst-10982	142	34	growth	growth	NOUN
ajst-10982	142	35	of	of	ADP
ajst-10982	142	36	plant	plant	NOUN
ajst-10982	142	37	roots	root	NOUN
ajst-10982	142	38	in	in	ADP
ajst-10982	142	39	different	different	ADJ
ajst-10982	142	40	environments	environment	NOUN
ajst-10982	142	41	.	.	PUNCT
ajst-10982	143	1	in	in	ADP
ajst-10982	143	2	the	the	DET
ajst-10982	143	3	field	field	NOUN
ajst-10982	143	4	of	of	ADP
ajst-10982	143	5	ecology	ecology	NOUN
ajst-10982	143	6	,	,	PUNCT
ajst-10982	143	7	combined	combine	VERB
ajst-10982	143	8	deep	deep	ADJ
ajst-10982	143	9	learning	learning	NOUN
ajst-10982	143	10	techniques	technique	NOUN
ajst-10982	143	11	can	can	AUX
ajst-10982	143	12	be	be	AUX
ajst-10982	143	13	used	use	VERB
ajst-10982	143	14	to	to	PART
ajst-10982	143	15	study	study	VERB
ajst-10982	143	16	the	the	DET
ajst-10982	143	17	structure	structure	NOUN
ajst-10982	143	18	and	and	CCONJ
ajst-10982	143	19	function	function	NOUN
ajst-10982	143	20	of	of	ADP
ajst-10982	143	21	plant	plant	NOUN
ajst-10982	143	22	communities	community	NOUN
ajst-10982	143	23	.	.	PUNCT
ajst-10982	144	1	by	by	ADP
ajst-10982	144	2	segmentation	segmentation	NOUN
ajst-10982	144	3	of	of	ADP
ajst-10982	144	4	a	a	DET
ajst-10982	144	5	large	large	ADJ
ajst-10982	144	6	number	number	NOUN
ajst-10982	144	7	of	of	ADP
ajst-10982	144	8	plant	plant	NOUN
ajst-10982	144	9	root	root	NOUN
ajst-10982	144	10	images	image	NOUN
ajst-10982	144	11	,	,	PUNCT
ajst-10982	144	12	various	various	ADJ
ajst-10982	144	13	types	type	NOUN
ajst-10982	144	14	of	of	ADP
ajst-10982	144	15	root	root	NOUN
ajst-10982	144	16	information	information	NOUN
ajst-10982	144	17	can	can	AUX
ajst-10982	144	18	be	be	AUX
ajst-10982	144	19	obtained	obtain	VERB
ajst-10982	144	20	,	,	PUNCT
ajst-10982	144	21	such	such	ADJ
ajst-10982	144	22	as	as	ADP
ajst-10982	144	23	root	root	NOUN
ajst-10982	144	24	density	density	NOUN
ajst-10982	144	25	,	,	PUNCT
ajst-10982	144	26	depth	depth	NOUN
ajst-10982	144	27	,	,	PUNCT
ajst-10982	144	28	distribution	distribution	NOUN
ajst-10982	144	29	area	area	NOUN
ajst-10982	144	30	,	,	PUNCT
ajst-10982	144	31	etc	etc	X
ajst-10982	144	32	.	.	X
ajst-10982	144	33	,	,	PUNCT
ajst-10982	144	34	so	so	SCONJ
ajst-10982	144	35	as	as	SCONJ
ajst-10982	144	36	to	to	PART
ajst-10982	144	37	better	well	ADV
ajst-10982	144	38	grasp	grasp	VERB
ajst-10982	144	39	the	the	DET
ajst-10982	144	40	root	root	NOUN
ajst-10982	144	41	composition	composition	NOUN
ajst-10982	144	42	and	and	CCONJ
ajst-10982	144	43	functional	functional	ADJ
ajst-10982	144	44	characteristics	characteristic	NOUN
ajst-10982	144	45	of	of	ADP
ajst-10982	144	46	plant	plant	NOUN
ajst-10982	144	47	communities	community	NOUN
ajst-10982	144	48	.	.	PUNCT
ajst-10982	145	1	in	in	ADP
ajst-10982	145	2	agronomy	agronomy	NOUN
ajst-10982	145	3	,	,	PUNCT
ajst-10982	145	4	deep	deep	ADJ
ajst-10982	145	5	learning	learning	NOUN
ajst-10982	145	6	techniques	technique	NOUN
ajst-10982	145	7	can	can	AUX
ajst-10982	145	8	be	be	AUX
ajst-10982	145	9	used	use	VERB
ajst-10982	145	10	to	to	PART
ajst-10982	145	11	study	study	VERB
ajst-10982	145	12	the	the	DET
ajst-10982	145	13	impact	impact	NOUN
ajst-10982	145	14	of	of	ADP
ajst-10982	145	15	plant	plant	NOUN
ajst-10982	145	16	roots	root	NOUN
ajst-10982	145	17	on	on	ADP
ajst-10982	145	18	agricultural	agricultural	ADJ
ajst-10982	145	19	production	production	NOUN
ajst-10982	145	20	.	.	PUNCT
ajst-10982	146	1	through	through	ADP
ajst-10982	146	2	the	the	DET
ajst-10982	146	3	segmentation	segmentation	NOUN
ajst-10982	146	4	of	of	ADP
ajst-10982	146	5	plant	plant	NOUN
ajst-10982	146	6	root	root	NOUN
ajst-10982	146	7	images	image	NOUN
ajst-10982	146	8	in	in	ADP
ajst-10982	146	9	farmland	farmland	NOUN
ajst-10982	146	10	,	,	PUNCT
ajst-10982	146	11	the	the	DET
ajst-10982	146	12	information	information	NOUN
ajst-10982	146	13	of	of	ADP
ajst-10982	146	14	root	root	NOUN
ajst-10982	146	15	morphology	morphology	NOUN
ajst-10982	146	16	and	and	CCONJ
ajst-10982	146	17	structure	structure	NOUN
ajst-10982	146	18	is	be	AUX
ajst-10982	146	19	used	use	VERB
ajst-10982	146	20	to	to	PART
ajst-10982	146	21	predict	predict	VERB
ajst-10982	146	22	climate	climate	NOUN
ajst-10982	146	23	change	change	NOUN
ajst-10982	146	24	,	,	PUNCT
ajst-10982	146	25	and	and	CCONJ
ajst-10982	146	26	the	the	DET
ajst-10982	146	27	growth	growth	NOUN
ajst-10982	146	28	of	of	ADP
ajst-10982	146	29	agricultural	agricultural	ADJ
ajst-10982	146	30	products	product	NOUN
ajst-10982	146	31	under	under	ADP
ajst-10982	146	32	different	different	ADJ
ajst-10982	146	33	climate	climate	NOUN
ajst-10982	146	34	and	and	CCONJ
ajst-10982	146	35	environment	environment	NOUN
ajst-10982	146	36	changes	change	NOUN
ajst-10982	146	37	is	be	AUX
ajst-10982	146	38	understood	understand	VERB
ajst-10982	146	39	,	,	PUNCT
ajst-10982	146	40	so	so	SCONJ
ajst-10982	146	41	as	as	SCONJ
ajst-10982	146	42	to	to	PART
ajst-10982	146	43	provide	provide	VERB
ajst-10982	146	44	manufacturing	manufacturing	NOUN
ajst-10982	146	45	tools	tool	NOUN
ajst-10982	146	46	for	for	ADP
ajst-10982	146	47	digital	digital	ADJ
ajst-10982	146	48	agriculture	agriculture	NOUN
ajst-10982	146	49	.	.	PUNCT
ajst-10982	147	1	4	4	X
ajst-10982	147	2	.	.	X
ajst-10982	147	3	conclusion	conclusion	NOUN
ajst-10982	147	4	in	in	ADP
ajst-10982	147	5	summary	summary	NOUN
ajst-10982	147	6	,	,	PUNCT
ajst-10982	147	7	compared	compare	VERB
ajst-10982	147	8	with	with	ADP
ajst-10982	147	9	traditional	traditional	ADJ
ajst-10982	147	10	methods	method	NOUN
ajst-10982	147	11	,	,	PUNCT
ajst-10982	147	12	deep	deep	ADJ
ajst-10982	147	13	learning	learning	NOUN
ajst-10982	147	14	models	model	NOUN
ajst-10982	147	15	can	can	AUX
ajst-10982	147	16	automatically	automatically	ADV
ajst-10982	147	17	segment	segment	VERB
ajst-10982	147	18	plant	plant	NOUN
ajst-10982	147	19	roots	root	NOUN
ajst-10982	147	20	and	and	CCONJ
ajst-10982	147	21	produce	produce	VERB
ajst-10982	147	22	more	more	ADV
ajst-10982	147	23	accurate	accurate	ADJ
ajst-10982	147	24	root	root	NOUN
ajst-10982	147	25	segmentation	segmentation	NOUN
ajst-10982	147	26	results	result	NOUN
ajst-10982	147	27	.	.	PUNCT
ajst-10982	148	1	but	but	CCONJ
ajst-10982	148	2	its	its	PRON
ajst-10982	148	3	shortcomings	shortcoming	NOUN
ajst-10982	148	4	are	be	AUX
ajst-10982	148	5	also	also	ADV
ajst-10982	148	6	obvious	obvious	ADJ
ajst-10982	148	7	.	.	PUNCT
ajst-10982	149	1	since	since	SCONJ
ajst-10982	149	2	there	there	PRON
ajst-10982	149	3	are	be	VERB
ajst-10982	149	4	few	few	ADJ
ajst-10982	149	5	image	image	NOUN
ajst-10982	149	6	data	datum	NOUN
ajst-10982	149	7	of	of	ADP
ajst-10982	149	8	plant	plant	NOUN
ajst-10982	149	9	roots	root	NOUN
ajst-10982	149	10	,	,	PUNCT
ajst-10982	149	11	it	it	PRON
ajst-10982	149	12	is	be	AUX
ajst-10982	149	13	difficult	difficult	ADJ
ajst-10982	149	14	to	to	PART
ajst-10982	149	15	obtain	obtain	VERB
ajst-10982	149	16	large	large	ADJ
ajst-10982	149	17	-	-	PUNCT
ajst-10982	149	18	scale	scale	NOUN
ajst-10982	149	19	labeled	label	VERB
ajst-10982	149	20	data	data	NOUN
ajst-10982	149	21	sets	set	NOUN
ajst-10982	149	22	,	,	PUNCT
ajst-10982	149	23	which	which	PRON
ajst-10982	149	24	makes	make	VERB
ajst-10982	149	25	it	it	PRON
ajst-10982	149	26	difficult	difficult	ADJ
ajst-10982	149	27	to	to	PART
ajst-10982	149	28	train	train	VERB
ajst-10982	149	29	deep	deep	ADJ
ajst-10982	149	30	learning	learning	NOUN
ajst-10982	149	31	models	model	NOUN
ajst-10982	149	32	.	.	PUNCT
ajst-10982	150	1	in	in	ADP
ajst-10982	150	2	addition	addition	NOUN
ajst-10982	150	3	,	,	PUNCT
ajst-10982	150	4	due	due	ADP
ajst-10982	150	5	to	to	ADP
ajst-10982	150	6	the	the	DET
ajst-10982	150	7	complex	complex	ADJ
ajst-10982	150	8	and	and	CCONJ
ajst-10982	150	9	varied	varied	ADJ
ajst-10982	150	10	soil	soil	NOUN
ajst-10982	150	11	background	background	NOUN
ajst-10982	150	12	,	,	PUNCT
ajst-10982	150	13	inconsistent	inconsistent	ADJ
ajst-10982	150	14	lighting	lighting	NOUN
ajst-10982	150	15	conditions	condition	NOUN
ajst-10982	150	16	and	and	CCONJ
ajst-10982	150	17	many	many	ADJ
ajst-10982	150	18	small	small	ADJ
ajst-10982	150	19	roots	root	NOUN
ajst-10982	150	20	,	,	PUNCT
ajst-10982	150	21	the	the	DET
ajst-10982	150	22	model	model	NOUN
ajst-10982	150	23	has	have	VERB
ajst-10982	150	24	limited	limit	VERB
ajst-10982	150	25	generalization	generalization	NOUN
ajst-10982	150	26	performance	performance	NOUN
ajst-10982	150	27	in	in	ADP
ajst-10982	150	28	the	the	DET
ajst-10982	150	29	new	new	ADJ
ajst-10982	150	30	scenario	scenario	NOUN
ajst-10982	150	31	.	.	PUNCT
ajst-10982	151	1	therefore	therefore	ADV
ajst-10982	151	2	,	,	PUNCT
ajst-10982	151	3	deep	deep	ADJ
ajst-10982	151	4	learning	learning	NOUN
ajst-10982	151	5	-	-	PUNCT
ajst-10982	151	6	based	base	VERB
ajst-10982	151	7	methods	method	NOUN
ajst-10982	151	8	often	often	ADV
ajst-10982	151	9	lack	lack	VERB
ajst-10982	151	10	explainability	explainability	NOUN
ajst-10982	151	11	,	,	PUNCT
ajst-10982	151	12	and	and	CCONJ
ajst-10982	151	13	there	there	PRON
ajst-10982	151	14	are	be	VERB
ajst-10982	151	15	certain	certain	ADJ
ajst-10982	151	16	limitations	limitation	NOUN
ajst-10982	151	17	to	to	ADP
ajst-10982	151	18	the	the	DET
ajst-10982	151	19	morphological	morphological	ADJ
ajst-10982	151	20	analysis	analysis	NOUN
ajst-10982	151	21	and	and	CCONJ
ajst-10982	151	22	physiological	physiological	ADJ
ajst-10982	151	23	characteristics	characteristic	NOUN
ajst-10982	151	24	of	of	ADP
ajst-10982	151	25	roots	root	NOUN
ajst-10982	151	26	.	.	PUNCT
ajst-10982	152	1	5	5	X
ajst-10982	152	2	.	.	X
ajst-10982	152	3	current	current	ADJ
ajst-10982	152	4	challenges	challenge	NOUN
ajst-10982	152	5	and	and	CCONJ
ajst-10982	152	6	future	future	ADJ
ajst-10982	152	7	trends	trend	NOUN
ajst-10982	152	8	with	with	ADP
ajst-10982	152	9	the	the	DET
ajst-10982	152	10	acceleration	acceleration	NOUN
ajst-10982	152	11	of	of	ADP
ajst-10982	152	12	the	the	DET
ajst-10982	152	13	new	new	ADJ
ajst-10982	152	14	round	round	NOUN
ajst-10982	152	15	of	of	ADP
ajst-10982	152	16	scientific	scientific	ADJ
ajst-10982	152	17	and	and	CCONJ
ajst-10982	152	18	technological	technological	ADJ
ajst-10982	152	19	revolution	revolution	NOUN
ajst-10982	152	20	and	and	CCONJ
ajst-10982	152	21	industrial	industrial	ADJ
ajst-10982	152	22	change	change	NOUN
ajst-10982	152	23	,	,	PUNCT
ajst-10982	152	24	many	many	ADJ
ajst-10982	152	25	key	key	ADJ
ajst-10982	152	26	subject	subject	ADJ
ajst-10982	152	27	issues	issue	NOUN
ajst-10982	152	28	and	and	CCONJ
ajst-10982	152	29	core	core	NOUN
ajst-10982	152	30	technologies	technology	NOUN
ajst-10982	152	31	have	have	AUX
ajst-10982	152	32	appeared	appear	VERB
ajst-10982	152	33	the	the	DET
ajst-10982	152	34	precursor	precursor	NOUN
ajst-10982	152	35	of	of	ADP
ajst-10982	152	36	revolutionary	revolutionary	ADJ
ajst-10982	152	37	change	change	NOUN
ajst-10982	152	38	.	.	PUNCT
ajst-10982	153	1	in	in	ADP
ajst-10982	153	2	this	this	DET
ajst-10982	153	3	context	context	NOUN
ajst-10982	153	4	,	,	PUNCT
ajst-10982	153	5	new	new	ADJ
ajst-10982	153	6	subject	subject	ADJ
ajst-10982	153	7	areas	area	NOUN
ajst-10982	153	8	and	and	CCONJ
ajst-10982	153	9	growth	growth	NOUN
ajst-10982	153	10	points	point	NOUN
ajst-10982	153	11	continue	continue	VERB
ajst-10982	153	12	to	to	PART
ajst-10982	153	13	emerge	emerge	VERB
ajst-10982	153	14	,	,	PUNCT
ajst-10982	153	15	and	and	CCONJ
ajst-10982	153	16	the	the	DET
ajst-10982	153	17	deep	deep	ADJ
ajst-10982	153	18	integration	integration	NOUN
ajst-10982	153	19	of	of	ADP
ajst-10982	153	20	interdisciplinary	interdisciplinary	NOUN
ajst-10982	153	21	has	have	AUX
ajst-10982	153	22	become	become	VERB
ajst-10982	153	23	an	an	DET
ajst-10982	153	24	irresistible	irresistible	ADJ
ajst-10982	153	25	trend	trend	NOUN
ajst-10982	153	26	.	.	PUNCT
ajst-10982	154	1	plant	plant	NOUN
ajst-10982	154	2	root	root	NOUN
ajst-10982	154	3	segmentation	segmentation	NOUN
ajst-10982	154	4	based	base	VERB
ajst-10982	154	5	on	on	ADP
ajst-10982	154	6	deep	deep	ADJ
ajst-10982	154	7	learning	learning	NOUN
ajst-10982	154	8	plays	play	VERB
ajst-10982	154	9	an	an	DET
ajst-10982	154	10	important	important	ADJ
ajst-10982	154	11	role	role	NOUN
ajst-10982	154	12	in	in	ADP
ajst-10982	154	13	promoting	promote	VERB
ajst-10982	154	14	interdisciplinary	interdisciplinary	ADJ
ajst-10982	154	15	integration	integration	NOUN
ajst-10982	154	16	.	.	PUNCT
ajst-10982	155	1	however	however	ADV
ajst-10982	155	2	,	,	PUNCT
ajst-10982	155	3	there	there	PRON
ajst-10982	155	4	are	be	VERB
ajst-10982	155	5	still	still	ADV
ajst-10982	155	6	some	some	DET
ajst-10982	155	7	challenges	challenge	NOUN
ajst-10982	155	8	and	and	CCONJ
ajst-10982	155	9	problems	problem	NOUN
ajst-10982	155	10	in	in	ADP
ajst-10982	155	11	this	this	DET
ajst-10982	155	12	field	field	NOUN
ajst-10982	155	13	.	.	PUNCT
ajst-10982	156	1	firstly	firstly	ADV
ajst-10982	156	2	,	,	PUNCT
ajst-10982	156	3	the	the	DET
ajst-10982	156	4	quality	quality	NOUN
ajst-10982	156	5	of	of	ADP
ajst-10982	156	6	plant	plant	NOUN
ajst-10982	156	7	root	root	NOUN
ajst-10982	156	8	data	datum	NOUN
ajst-10982	156	9	directly	directly	ADV
ajst-10982	156	10	affects	affect	VERB
ajst-10982	156	11	the	the	DET
ajst-10982	156	12	performance	performance	NOUN
ajst-10982	156	13	of	of	ADP
ajst-10982	156	14	the	the	DET
ajst-10982	156	15	segmentation	segmentation	NOUN
ajst-10982	156	16	model	model	NOUN
ajst-10982	156	17	.	.	PUNCT
ajst-10982	157	1	since	since	SCONJ
ajst-10982	157	2	roots	root	NOUN
ajst-10982	157	3	grow	grow	VERB
ajst-10982	157	4	in	in	ADP
ajst-10982	157	5	soil	soil	NOUN
ajst-10982	157	6	,	,	PUNCT
ajst-10982	157	7	obtaining	obtain	VERB
ajst-10982	157	8	clear	clear	ADJ
ajst-10982	157	9	,	,	PUNCT
ajst-10982	157	10	high	high	ADJ
ajst-10982	157	11	-	-	PUNCT
ajst-10982	157	12	quality	quality	NOUN
ajst-10982	157	13	images	image	NOUN
ajst-10982	157	14	of	of	ADP
ajst-10982	157	15	roots	root	NOUN
ajst-10982	157	16	is	be	AUX
ajst-10982	157	17	a	a	DET
ajst-10982	157	18	challenging	challenging	ADJ
ajst-10982	157	19	task	task	NOUN
ajst-10982	157	20	.	.	PUNCT
ajst-10982	158	1	in	in	ADP
ajst-10982	158	2	the	the	DET
ajst-10982	158	3	image	image	NOUN
ajst-10982	158	4	,	,	PUNCT
ajst-10982	158	5	there	there	PRON
ajst-10982	158	6	may	may	AUX
ajst-10982	158	7	be	be	AUX
ajst-10982	158	8	noise	noise	NOUN
ajst-10982	158	9	interference	interference	NOUN
ajst-10982	158	10	such	such	ADJ
ajst-10982	158	11	as	as	ADP
ajst-10982	158	12	soil	soil	NOUN
ajst-10982	158	13	particles	particle	NOUN
ajst-10982	158	14	and	and	CCONJ
ajst-10982	158	15	weed	weed	NOUN
ajst-10982	158	16	cover	cover	NOUN
ajst-10982	158	17	,	,	PUNCT
ajst-10982	158	18	and	and	CCONJ
ajst-10982	158	19	the	the	DET
ajst-10982	158	20	root	root	NOUN
ajst-10982	158	21	structure	structure	NOUN
ajst-10982	158	22	is	be	AUX
ajst-10982	158	23	complex	complex	ADJ
ajst-10982	158	24	and	and	CCONJ
ajst-10982	158	25	diverse	diverse	ADJ
ajst-10982	158	26	,	,	PUNCT
ajst-10982	158	27	and	and	CCONJ
ajst-10982	158	28	its	its	PRON
ajst-10982	158	29	shape	shape	NOUN
ajst-10982	158	30	will	will	AUX
ajst-10982	158	31	change	change	VERB
ajst-10982	158	32	with	with	ADP
ajst-10982	158	33	the	the	DET
ajst-10982	158	34	change	change	NOUN
ajst-10982	158	35	of	of	ADP
ajst-10982	158	36	environment	environment	NOUN
ajst-10982	158	37	and	and	CCONJ
ajst-10982	158	38	growth	growth	NOUN
ajst-10982	158	39	conditions	condition	NOUN
ajst-10982	158	40	.	.	PUNCT
ajst-10982	159	1	these	these	DET
ajst-10982	159	2	factors	factor	NOUN
ajst-10982	159	3	may	may	AUX
ajst-10982	159	4	lead	lead	VERB
ajst-10982	159	5	to	to	ADP
ajst-10982	159	6	the	the	DET
ajst-10982	159	7	instability	instability	NOUN
ajst-10982	159	8	of	of	ADP
ajst-10982	159	9	data	datum	NOUN
ajst-10982	159	10	quality	quality	NOUN
ajst-10982	159	11	,	,	PUNCT
ajst-10982	159	12	which	which	PRON
ajst-10982	159	13	in	in	ADP
ajst-10982	159	14	turn	turn	NOUN
ajst-10982	159	15	affects	affect	VERB
ajst-10982	159	16	the	the	DET
ajst-10982	159	17	accuracy	accuracy	NOUN
ajst-10982	159	18	and	and	CCONJ
ajst-10982	159	19	generalization	generalization	NOUN
ajst-10982	159	20	ability	ability	NOUN
ajst-10982	159	21	of	of	ADP
ajst-10982	159	22	the	the	DET
ajst-10982	159	23	model	model	NOUN
ajst-10982	159	24	.	.	PUNCT
ajst-10982	160	1	secondly	secondly	ADV
ajst-10982	160	2	,	,	PUNCT
ajst-10982	160	3	the	the	DET
ajst-10982	160	4	fitting	fitting	ADJ
ajst-10982	160	5	ability	ability	NOUN
ajst-10982	160	6	of	of	ADP
ajst-10982	160	7	root	root	NOUN
ajst-10982	160	8	segmentation	segmentation	NOUN
ajst-10982	160	9	model	model	NOUN
ajst-10982	160	10	is	be	AUX
ajst-10982	160	11	limited	limit	VERB
ajst-10982	160	12	by	by	ADP
ajst-10982	160	13	traditional	traditional	ADJ
ajst-10982	160	14	segmentation	segmentation	NOUN
ajst-10982	160	15	methods	method	NOUN
ajst-10982	160	16	.	.	PUNCT
ajst-10982	161	1	previous	previous	ADJ
ajst-10982	161	2	studies	study	NOUN
ajst-10982	161	3	have	have	AUX
ajst-10982	161	4	used	use	VERB
ajst-10982	161	5	rule	rule	NOUN
ajst-10982	161	6	-	-	PUNCT
ajst-10982	161	7	based	base	VERB
ajst-10982	161	8	,	,	PUNCT
ajst-10982	161	9	threshold	threshold	NOUN
ajst-10982	161	10	-	-	PUNCT
ajst-10982	161	11	based	base	VERB
ajst-10982	161	12	,	,	PUNCT
ajst-10982	161	13	or	or	CCONJ
ajst-10982	161	14	feature	feature	NOUN
ajst-10982	161	15	-	-	PUNCT
ajst-10982	161	16	based	base	VERB
ajst-10982	161	17	methods	method	NOUN
ajst-10982	161	18	to	to	PART
ajst-10982	161	19	extract	extract	VERB
ajst-10982	161	20	root	root	NOUN
ajst-10982	161	21	profiles	profile	NOUN
ajst-10982	161	22	,	,	PUNCT
ajst-10982	161	23	but	but	CCONJ
ajst-10982	161	24	these	these	DET
ajst-10982	161	25	methods	method	NOUN
ajst-10982	161	26	tend	tend	VERB
ajst-10982	161	27	to	to	PART
ajst-10982	161	28	be	be	AUX
ajst-10982	161	29	less	less	ADV
ajst-10982	161	30	effective	effective	ADJ
ajst-10982	161	31	for	for	ADP
ajst-10982	161	32	complex	complex	ADJ
ajst-10982	161	33	root	root	NOUN
ajst-10982	161	34	structures	structure	NOUN
ajst-10982	161	35	.	.	PUNCT
ajst-10982	162	1	deep	deep	ADJ
ajst-10982	162	2	learning	learning	NOUN
ajst-10982	162	3	models	model	NOUN
ajst-10982	162	4	perform	perform	VERB
ajst-10982	162	5	significantly	significantly	ADV
ajst-10982	162	6	better	well	ADJ
ajst-10982	162	7	than	than	ADP
ajst-10982	162	8	traditional	traditional	ADJ
ajst-10982	162	9	methods	method	NOUN
ajst-10982	162	10	in	in	ADP
ajst-10982	162	11	root	root	NOUN
ajst-10982	162	12	segmentation	segmentation	NOUN
ajst-10982	162	13	,	,	PUNCT
ajst-10982	162	14	but	but	CCONJ
ajst-10982	162	15	there	there	PRON
ajst-10982	162	16	are	be	VERB
ajst-10982	162	17	still	still	ADV
ajst-10982	162	18	difficulties	difficulty	NOUN
ajst-10982	162	19	in	in	ADP
ajst-10982	162	20	some	some	DET
ajst-10982	162	21	cases	case	NOUN
ajst-10982	162	22	.	.	PUNCT
ajst-10982	163	1	for	for	ADP
ajst-10982	163	2	example	example	NOUN
ajst-10982	163	3	,	,	PUNCT
ajst-10982	163	4	in	in	ADP
ajst-10982	163	5	cases	case	NOUN
ajst-10982	163	6	where	where	SCONJ
ajst-10982	163	7	roots	root	NOUN
ajst-10982	163	8	are	be	AUX
ajst-10982	163	9	crossed	cross	VERB
ajst-10982	163	10	or	or	CCONJ
ajst-10982	163	11	obscured	obscure	VERB
ajst-10982	163	12	,	,	PUNCT
ajst-10982	163	13	the	the	DET
ajst-10982	163	14	model	model	NOUN
ajst-10982	163	15	may	may	AUX
ajst-10982	163	16	not	not	PART
ajst-10982	163	17	accurately	accurately	ADV
ajst-10982	163	18	segment	segment	VERB
ajst-10982	163	19	the	the	DET
ajst-10982	163	20	roots	root	NOUN
ajst-10982	163	21	or	or	CCONJ
ajst-10982	163	22	have	have	VERB
ajst-10982	163	23	difficulty	difficulty	NOUN
ajst-10982	163	24	distinguishing	distinguish	VERB
ajst-10982	163	25	between	between	ADP
ajst-10982	163	26	roots	root	NOUN
ajst-10982	163	27	and	and	CCONJ
ajst-10982	163	28	background	background	NOUN
ajst-10982	163	29	.	.	PUNCT
ajst-10982	164	1	in	in	ADP
ajst-10982	164	2	order	order	NOUN
ajst-10982	164	3	to	to	PART
ajst-10982	164	4	overcome	overcome	VERB
ajst-10982	164	5	these	these	DET
ajst-10982	164	6	challenges	challenge	NOUN
ajst-10982	164	7	,	,	PUNCT
ajst-10982	164	8	we	we	PRON
ajst-10982	164	9	can	can	AUX
ajst-10982	164	10	concentrate	concentrate	VERB
ajst-10982	164	11	on	on	ADP
ajst-10982	164	12	collecting	collect	VERB
ajst-10982	164	13	more	more	ADJ
ajst-10982	164	14	high	high	ADJ
ajst-10982	164	15	-	-	PUNCT
ajst-10982	164	16	quality	quality	NOUN
ajst-10982	164	17	root	root	NOUN
ajst-10982	164	18	image	image	NOUN
ajst-10982	164	19	data	datum	NOUN
ajst-10982	164	20	,	,	PUNCT
ajst-10982	164	21	establish	establish	VERB
ajst-10982	164	22	a	a	DET
ajst-10982	164	23	larger	large	ADJ
ajst-10982	164	24	dataset	dataset	NOUN
ajst-10982	164	25	of	of	ADP
ajst-10982	164	26	plant	plant	NOUN
ajst-10982	164	27	root	root	NOUN
ajst-10982	164	28	image	image	NOUN
ajst-10982	164	29	,	,	PUNCT
ajst-10982	164	30	and	and	CCONJ
ajst-10982	164	31	optimize	optimize	VERB
ajst-10982	164	32	and	and	CCONJ
ajst-10982	164	33	improve	improve	VERB
ajst-10982	164	34	the	the	DET
ajst-10982	164	35	segmentation	segmentation	NOUN
ajst-10982	164	36	model	model	NOUN
ajst-10982	164	37	for	for	ADP
ajst-10982	164	38	different	different	ADJ
ajst-10982	164	39	types	type	NOUN
ajst-10982	164	40	of	of	ADP
ajst-10982	164	41	root	root	NOUN
ajst-10982	164	42	structure	structure	NOUN
ajst-10982	164	43	to	to	PART
ajst-10982	164	44	improve	improve	VERB
ajst-10982	164	45	the	the	DET
ajst-10982	164	46	accuracy	accuracy	NOUN
ajst-10982	164	47	and	and	CCONJ
ajst-10982	164	48	robustness	robustness	NOUN
ajst-10982	164	49	of	of	ADP
ajst-10982	164	50	root	root	NOUN
ajst-10982	164	51	segmentation	segmentation	NOUN
ajst-10982	164	52	.	.	PUNCT
ajst-10982	165	1	secondly	secondly	ADV
ajst-10982	165	2	,	,	PUNCT
ajst-10982	165	3	multi	multi	ADJ
ajst-10982	165	4	-	-	ADJ
ajst-10982	165	5	source	source	NOUN
ajst-10982	165	6	data	datum	NOUN
ajst-10982	165	7	can	can	AUX
ajst-10982	165	8	be	be	AUX
ajst-10982	165	9	used	use	VERB
ajst-10982	165	10	for	for	ADP
ajst-10982	165	11	joint	joint	ADJ
ajst-10982	165	12	analysis	analysis	NOUN
ajst-10982	165	13	.	.	PUNCT
ajst-10982	166	1	at	at	ADP
ajst-10982	166	2	present	present	ADJ
ajst-10982	166	3	,	,	PUNCT
ajst-10982	166	4	plant	plant	NOUN
ajst-10982	166	5	root	root	NOUN
ajst-10982	166	6	segmentation	segmentation	NOUN
ajst-10982	166	7	based	base	VERB
ajst-10982	166	8	on	on	ADP
ajst-10982	166	9	deep	deep	ADJ
ajst-10982	166	10	learning	learning	NOUN
ajst-10982	166	11	can	can	AUX
ajst-10982	166	12	use	use	VERB
ajst-10982	166	13	different	different	ADJ
ajst-10982	166	14	types	type	NOUN
ajst-10982	166	15	of	of	ADP
ajst-10982	166	16	data	datum	NOUN
ajst-10982	166	17	such	such	ADJ
ajst-10982	166	18	as	as	ADP
ajst-10982	166	19	rgb	rgb	PROPN
ajst-10982	166	20	image	image	NOUN
ajst-10982	166	21	,	,	PUNCT
ajst-10982	166	22	infrared	infrared	ADJ
ajst-10982	166	23	image	image	NOUN
ajst-10982	166	24	and	and	CCONJ
ajst-10982	166	25	x	x	NOUN
ajst-10982	166	26	-	-	NOUN
ajst-10982	166	27	ray	ray	NOUN
ajst-10982	166	28	image	image	NOUN
ajst-10982	166	29	to	to	PART
ajst-10982	166	30	obtain	obtain	VERB
ajst-10982	166	31	more	more	ADV
ajst-10982	166	32	comprehensive	comprehensive	ADJ
ajst-10982	166	33	root	root	NOUN
ajst-10982	166	34	characteristic	characteristic	ADJ
ajst-10982	166	35	information	information	NOUN
ajst-10982	166	36	.	.	PUNCT
ajst-10982	167	1	further	far	ADV
ajst-10982	167	2	,	,	PUNCT
ajst-10982	167	3	future	future	ADJ
ajst-10982	167	4	studies	study	NOUN
ajst-10982	167	5	can	can	AUX
ajst-10982	167	6	explore	explore	VERB
ajst-10982	167	7	how	how	SCONJ
ajst-10982	167	8	to	to	PART
ajst-10982	167	9	organically	organically	ADV
ajst-10982	167	10	combine	combine	VERB
ajst-10982	167	11	data	datum	NOUN
ajst-10982	167	12	from	from	ADP
ajst-10982	167	13	these	these	DET
ajst-10982	167	14	different	different	ADJ
ajst-10982	167	15	sources	source	NOUN
ajst-10982	167	16	,	,	PUNCT
ajst-10982	167	17	and	and	CCONJ
ajst-10982	167	18	transfer	transfer	VERB
ajst-10982	167	19	the	the	DET
ajst-10982	167	20	model	model	NOUN
ajst-10982	167	21	training	training	NOUN
ajst-10982	167	22	from	from	ADP
ajst-10982	167	23	large	large	ADJ
ajst-10982	167	24	-	-	PUNCT
ajst-10982	167	25	scale	scale	NOUN
ajst-10982	167	26	image	image	NOUN
ajst-10982	167	27	data	datum	NOUN
ajst-10982	167	28	sets	set	NOUN
ajst-10982	167	29	to	to	PART
ajst-10982	167	30	plant	plant	VERB
ajst-10982	167	31	root	root	NOUN
ajst-10982	167	32	images	image	NOUN
ajst-10982	167	33	by	by	ADP
ajst-10982	167	34	means	mean	NOUN
ajst-10982	167	35	of	of	ADP
ajst-10982	167	36	transfer	transfer	NOUN
ajst-10982	167	37	learning	learning	NOUN
ajst-10982	167	38	,	,	PUNCT
ajst-10982	167	39	so	so	SCONJ
ajst-10982	167	40	as	as	SCONJ
ajst-10982	167	41	to	to	PART
ajst-10982	167	42	make	make	VERB
ajst-10982	167	43	the	the	DET
ajst-10982	167	44	model	model	NOUN
ajst-10982	167	45	more	more	ADJ
ajst-10982	167	46	generalization	generalization	NOUN
ajst-10982	167	47	ability	ability	NOUN
ajst-10982	167	48	,	,	PUNCT
ajst-10982	167	49	so	so	SCONJ
ajst-10982	167	50	as	as	SCONJ
ajst-10982	167	51	to	to	PART
ajst-10982	167	52	achieve	achieve	VERB
ajst-10982	167	53	more	more	ADV
ajst-10982	167	54	accurate	accurate	ADJ
ajst-10982	167	55	and	and	CCONJ
ajst-10982	167	56	comprehensive	comprehensive	ADJ
ajst-10982	167	57	plant	plant	NOUN
ajst-10982	167	58	root	root	NOUN
ajst-10982	167	59	segmentation	segmentation	NOUN
ajst-10982	167	60	.	.	PUNCT
ajst-10982	168	1	plant	plant	NOUN
ajst-10982	168	2	root	root	NOUN
ajst-10982	168	3	segmentation	segmentation	NOUN
ajst-10982	168	4	can	can	AUX
ajst-10982	168	5	also	also	ADV
ajst-10982	168	6	be	be	AUX
ajst-10982	168	7	combined	combine	VERB
ajst-10982	168	8	with	with	ADP
ajst-10982	168	9	animal	animal	NOUN
ajst-10982	168	10	or	or	CCONJ
ajst-10982	168	11	human	human	ADJ
ajst-10982	168	12	medical	medical	ADJ
ajst-10982	168	13	image	image	NOUN
ajst-10982	168	14	segmentation	segmentation	NOUN
ajst-10982	168	15	to	to	PART
ajst-10982	168	16	conduct	conduct	VERB
ajst-10982	168	17	cross	cross	ADJ
ajst-10982	168	18	-	-	ADJ
ajst-10982	168	19	species	species	ADJ
ajst-10982	168	20	comparative	comparative	ADJ
ajst-10982	168	21	studies	study	NOUN
ajst-10982	168	22	to	to	PART
ajst-10982	168	23	discover	discover	VERB
ajst-10982	168	24	common	common	ADJ
ajst-10982	168	25	algorithms	algorithm	NOUN
ajst-10982	168	26	and	and	CCONJ
ajst-10982	168	27	techniques	technique	NOUN
ajst-10982	168	28	.	.	PUNCT
ajst-10982	169	1	in	in	ADP
ajst-10982	169	2	addition	addition	NOUN
ajst-10982	169	3	,	,	PUNCT
ajst-10982	169	4	the	the	DET
ajst-10982	169	5	introduction	introduction	NOUN
ajst-10982	169	6	of	of	ADP
ajst-10982	169	7	advanced	advanced	ADJ
ajst-10982	169	8	technical	technical	ADJ
ajst-10982	169	9	means	mean	NOUN
ajst-10982	169	10	and	and	CCONJ
ajst-10982	169	11	framework	framework	NOUN
ajst-10982	169	12	.	.	PUNCT
ajst-10982	170	1	at	at	ADP
ajst-10982	170	2	present	present	ADJ
ajst-10982	170	3	,	,	PUNCT
ajst-10982	170	4	deep	deep	ADJ
ajst-10982	170	5	learning	learning	NOUN
ajst-10982	170	6	is	be	AUX
ajst-10982	170	7	the	the	DET
ajst-10982	170	8	mainstream	mainstream	NOUN
ajst-10982	170	9	method	method	NOUN
ajst-10982	170	10	to	to	PART
ajst-10982	170	11	deal	deal	VERB
ajst-10982	170	12	with	with	ADP
ajst-10982	170	13	the	the	DET
ajst-10982	170	14	problem	problem	NOUN
ajst-10982	170	15	of	of	ADP
ajst-10982	170	16	plant	plant	NOUN
ajst-10982	170	17	root	root	NOUN
ajst-10982	170	18	segmentation	segmentation	NOUN
ajst-10982	170	19	,	,	PUNCT
ajst-10982	170	20	and	and	CCONJ
ajst-10982	170	21	other	other	ADJ
ajst-10982	170	22	advanced	advanced	ADJ
ajst-10982	170	23	technical	technical	ADJ
ajst-10982	170	24	means	mean	NOUN
ajst-10982	170	25	and	and	CCONJ
ajst-10982	170	26	frameworks	framework	NOUN
ajst-10982	170	27	can	can	AUX
ajst-10982	170	28	be	be	AUX
ajst-10982	170	29	considered	consider	VERB
ajst-10982	170	30	in	in	ADP
ajst-10982	170	31	the	the	DET
ajst-10982	170	32	future	future	NOUN
ajst-10982	170	33	.	.	PUNCT
ajst-10982	171	1	for	for	ADP
ajst-10982	171	2	example	example	NOUN
ajst-10982	171	3	,	,	PUNCT
ajst-10982	171	4	some	some	DET
ajst-10982	171	5	new	new	ADJ
ajst-10982	171	6	image	image	NOUN
ajst-10982	171	7	processing	processing	NOUN
ajst-10982	171	8	algorithms	algorithm	NOUN
ajst-10982	171	9	,	,	PUNCT
ajst-10982	171	10	3d	3d	NUM
ajst-10982	171	11	vision	vision	NOUN
ajst-10982	171	12	reconstruction	reconstruction	NOUN
ajst-10982	171	13	from	from	ADP
ajst-10982	171	14	two	two	NUM
ajst-10982	171	15	-	-	PUNCT
ajst-10982	171	16	dimensional	dimensional	ADJ
ajst-10982	171	17	image	image	NOUN
ajst-10982	171	18	training	training	NOUN
ajst-10982	171	19	,	,	PUNCT
ajst-10982	171	20	natural	natural	ADJ
ajst-10982	171	21	language	language	NOUN
ajst-10982	171	22	processing	processing	NOUN
ajst-10982	171	23	technology	technology	NOUN
ajst-10982	171	24	and	and	CCONJ
ajst-10982	171	25	biological	biological	ADJ
ajst-10982	171	26	computing	computing	NOUN
ajst-10982	171	27	methods	method	NOUN
ajst-10982	171	28	also	also	ADV
ajst-10982	171	29	have	have	VERB
ajst-10982	171	30	a	a	DET
ajst-10982	171	31	wide	wide	ADJ
ajst-10982	171	32	range	range	NOUN
ajst-10982	171	33	of	of	ADP
ajst-10982	171	34	application	application	NOUN
ajst-10982	171	35	prospects	prospect	NOUN
ajst-10982	171	36	in	in	ADP
ajst-10982	171	37	the	the	DET
ajst-10982	171	38	analysis	analysis	NOUN
ajst-10982	171	39	and	and	CCONJ
ajst-10982	171	40	identification	identification	NOUN
ajst-10982	171	41	of	of	ADP
ajst-10982	171	42	plant	plant	NOUN
ajst-10982	171	43	roots	root	NOUN
ajst-10982	171	44	.	.	PUNCT
ajst-10982	172	1	all	all	ADV
ajst-10982	172	2	in	in	ADV
ajst-10982	172	3	all	all	PRON
ajst-10982	172	4	,	,	PUNCT
ajst-10982	172	5	for	for	ADP
ajst-10982	172	6	plant	plant	NOUN
ajst-10982	172	7	root	root	NOUN
ajst-10982	172	8	segmentation	segmentation	NOUN
ajst-10982	172	9	based	base	VERB
ajst-10982	172	10	on	on	ADP
ajst-10982	172	11	deep	deep	ADJ
ajst-10982	172	12	learning	learning	NOUN
ajst-10982	172	13	algorithm	algorithm	NOUN
ajst-10982	172	14	,	,	PUNCT
ajst-10982	172	15	further	far	ADV
ajst-10982	172	16	relevant	relevant	ADJ
ajst-10982	172	17	research	research	NOUN
ajst-10982	172	18	needs	need	VERB
ajst-10982	172	19	to	to	PART
ajst-10982	172	20	be	be	AUX
ajst-10982	172	21	carried	carry	VERB
ajst-10982	172	22	out	out	ADP
ajst-10982	172	23	in	in	ADP
ajst-10982	172	24	the	the	DET
ajst-10982	172	25	future	future	NOUN
ajst-10982	172	26	to	to	PART
ajst-10982	172	27	inject	inject	VERB
ajst-10982	172	28	new	new	ADJ
ajst-10982	172	29	ideas	idea	NOUN
ajst-10982	172	30	to	to	PART
ajst-10982	172	31	achieve	achieve	VERB
ajst-10982	172	32	more	more	ADV
ajst-10982	172	33	accurate	accurate	ADJ
ajst-10982	172	34	,	,	PUNCT
ajst-10982	172	35	faster	fast	ADJ
ajst-10982	172	36	and	and	CCONJ
ajst-10982	172	37	higher	high	ADJ
ajst-10982	172	38	level	level	NOUN
ajst-10982	172	39	plant	plant	NOUN
ajst-10982	172	40	root	root	NOUN
ajst-10982	172	41	segmentation	segmentation	NOUN
ajst-10982	172	42	.	.	PUNCT
ajst-10982	173	1	acknowledgment	acknowledgment	NOUN
ajst-10982	173	2	fund	fund	NOUN
ajst-10982	173	3	project	project	PROPN
ajst-10982	173	4	:	:	PUNCT
ajst-10982	173	5	special	special	ADJ
ajst-10982	173	6	fund	fund	NOUN
ajst-10982	173	7	for	for	ADP
ajst-10982	173	8	basic	basic	ADJ
ajst-10982	173	9	scientific	scientific	ADJ
ajst-10982	173	10	research	research	NOUN
ajst-10982	173	11	expenses	expense	NOUN
ajst-10982	173	12	of	of	ADP
ajst-10982	173	13	central	central	ADJ
ajst-10982	173	14	universities	university	NOUN
ajst-10982	173	15	(	(	PUNCT
ajst-10982	173	16	project	project	NOUN
ajst-10982	173	17	number	number	NOUN
ajst-10982	173	18	:	:	PUNCT
ajst-10982	173	19	29	29	NUM
ajst-10982	173	20	2022nyxxs093	2022nyxxs093	NUM
ajst-10982	173	21	)	)	PUNCT
ajst-10982	173	22	references	reference	NOUN
ajst-10982	173	23	[	[	X
ajst-10982	173	24	1	1	NUM
ajst-10982	173	25	]	]	X
ajst-10982	173	26	li	li	PROPN
ajst-10982	173	27	kexin	kexin	PROPN
ajst-10982	173	28	,	,	PUNCT
ajst-10982	173	29	song	song	NOUN
ajst-10982	173	30	wenlong	wenlong	PROPN
ajst-10982	173	31	,	,	PUNCT
ajst-10982	173	32	zhu	zhu	PROPN
ajst-10982	173	33	liangkuan	liangkuan	PROPN
ajst-10982	173	34	.	.	PUNCT
ajst-10982	174	1	research	research	NOUN
ajst-10982	174	2	progress	progress	NOUN
ajst-10982	174	3	of	of	ADP
ajst-10982	174	4	in	in	ADP
ajst-10982	174	5	situ	situ	ADJ
ajst-10982	174	6	observation	observation	NOUN
ajst-10982	174	7	and	and	CCONJ
ajst-10982	174	8	identification	identification	NOUN
ajst-10982	174	9	of	of	ADP
ajst-10982	174	10	plant	plant	NOUN
ajst-10982	174	11	root	root	NOUN
ajst-10982	174	12	configuration	configuration	NOUN
ajst-10982	175	1	[	[	X
ajst-10982	175	2	j	j	X
ajst-10982	175	3	]	]	X
ajst-10982	175	4	.	.	PUNCT
ajst-10982	176	1	chinese	chinese	ADJ
ajst-10982	176	2	journal	journal	PROPN
ajst-10982	176	3	of	of	ADP
ajst-10982	176	4	ecology	ecology	NOUN
ajst-10982	176	5	,	,	PUNCT
ajst-10982	176	6	2011,30(9):2066	2011,30(9):2066	NUM
ajst-10982	176	7	-	-	SYM
ajst-10982	176	8	2071	2071	NUM
ajst-10982	176	9	.	.	PUNCT
ajst-10982	177	1	(	(	PUNCT
ajst-10982	177	2	in	in	ADP
ajst-10982	177	3	chinese	chinese	PROPN
ajst-10982	177	4	)	)	PUNCT
ajst-10982	178	1	[	[	X
ajst-10982	178	2	2	2	NUM
ajst-10982	178	3	]	]	X
ajst-10982	178	4	crocker	crocker	PROPN
ajst-10982	178	5	,	,	PUNCT
ajst-10982	178	6	w.	w.	PROPN
ajst-10982	178	7	root	root	PROPN
ajst-10982	178	8	development	development	NOUN
ajst-10982	178	9	of	of	ADP
ajst-10982	178	10	field	field	NOUN
ajst-10982	178	11	crops	crop	NOUN
ajst-10982	178	12	.	.	PUNCT
ajst-10982	179	1	j.	j.	PROPN
ajst-10982	179	2	e.	e.	PROPN
ajst-10982	179	3	weaver[j	weaver[j	PROPN
ajst-10982	179	4	]	]	PUNCT
ajst-10982	179	5	.	.	PUNCT
ajst-10982	180	1	botanical	botanical	ADJ
ajst-10982	180	2	gazette	gazette	PROPN
ajst-10982	180	3	,	,	PUNCT
ajst-10982	180	4	1926	1926	NUM
ajst-10982	180	5	,	,	PUNCT
ajst-10982	180	6	82(2):228	82(2):228	PROPN
ajst-10982	180	7	-	-	SYM
ajst-10982	180	8	228	228	NUM
ajst-10982	180	9	.	.	PUNCT
ajst-10982	181	1	[	[	X
ajst-10982	181	2	3	3	X
ajst-10982	181	3	]	]	X
ajst-10982	181	4	boehm	boehm	PROPN
ajst-10982	181	5	w	w	PROPN
ajst-10982	181	6	.	.	PUNCT
ajst-10982	181	7	methods	method	NOUN
ajst-10982	181	8	of	of	ADP
ajst-10982	181	9	studying	study	VERB
ajst-10982	181	10	root	root	NOUN
ajst-10982	181	11	systems[m	systems[m	NOUN
ajst-10982	181	12	]	]	PUNCT
ajst-10982	181	13	.	.	PUNCT
ajst-10982	182	1	springerverlag	springerverlag	PROPN
ajst-10982	182	2	,	,	PUNCT
ajst-10982	182	3	1979	1979	NUM
ajst-10982	182	4	.	.	PUNCT
ajst-10982	183	1	[	[	X
ajst-10982	183	2	4	4	NUM
ajst-10982	183	3	]	]	X
ajst-10982	183	4	zhou	zhou	PROPN
ajst-10982	183	5	benzhi	benzhi	PROPN
ajst-10982	183	6	,	,	PUNCT
ajst-10982	183	7	zhang	zhang	PROPN
ajst-10982	183	8	shougong	shougong	PROPN
ajst-10982	183	9	,	,	PUNCT
ajst-10982	183	10	fu	fu	PROPN
ajst-10982	183	11	maoyi	maoyi	PROPN
ajst-10982	183	12	.	.	PUNCT
ajst-10982	184	1	the	the	DET
ajst-10982	184	2	origin	origin	NOUN
ajst-10982	184	3	,	,	PUNCT
ajst-10982	184	4	development	development	NOUN
ajst-10982	184	5	and	and	CCONJ
ajst-10982	184	6	application	application	NOUN
ajst-10982	184	7	of	of	ADP
ajst-10982	184	8	the	the	DET
ajst-10982	184	9	minirhizotron	minirhizotron	NOUN
ajst-10982	184	10	,	,	PUNCT
ajst-10982	184	11	a	a	DET
ajst-10982	184	12	new	new	ADJ
ajst-10982	184	13	technology	technology	NOUN
ajst-10982	184	14	for	for	ADP
ajst-10982	184	15	plant	plant	NOUN
ajst-10982	184	16	root	root	NOUN
ajst-10982	184	17	research[j	research[j	NOUN
ajst-10982	184	18	]	]	PUNCT
ajst-10982	184	19	.	.	PUNCT
ajst-10982	185	1	journal	journal	PROPN
ajst-10982	185	2	of	of	ADP
ajst-10982	185	3	ecology	ecology	NOUN
ajst-10982	185	4	,	,	PUNCT
ajst-10982	185	5	2007	2007	NUM
ajst-10982	185	6	,	,	PUNCT
ajst-10982	185	7	26(2):8	26(2):8	PROPN
ajst-10982	185	8	[	[	X
ajst-10982	185	9	5	5	NUM
ajst-10982	185	10	]	]	X
ajst-10982	185	11	guo	guo	PROPN
ajst-10982	185	12	qiqiang	qiqiang	PROPN
ajst-10982	185	13	,	,	PUNCT
ajst-10982	185	14	li	li	PROPN
ajst-10982	185	15	jiangrong	jiangrong	PROPN
ajst-10982	185	16	,	,	PUNCT
ajst-10982	185	17	bianba	bianba	PROPN
ajst-10982	185	18	duoji	duoji	PROPN
ajst-10982	185	19	,	,	PUNCT
ajst-10982	185	20	ma	ma	PROPN
ajst-10982	185	21	heping	heping	PROPN
ajst-10982	185	22	.	.	PUNCT
ajst-10982	186	1	a	a	DET
ajst-10982	186	2	review	review	NOUN
ajst-10982	186	3	of	of	ADP
ajst-10982	186	4	plant	plant	NOUN
ajst-10982	186	5	root	root	NOUN
ajst-10982	186	6	research	research	NOUN
ajst-10982	186	7	methods	method	NOUN
ajst-10982	186	8	[	[	X
ajst-10982	186	9	j	j	X
ajst-10982	186	10	]	]	X
ajst-10982	186	11	.	.	PUNCT
ajst-10982	187	1	jilin	jilin	PROPN
ajst-10982	187	2	agriculture	agriculture	PROPN
ajst-10982	187	3	,	,	PUNCT
ajst-10982	187	4	2015	2015	NUM
ajst-10982	187	5	,	,	PUNCT
ajst-10982	187	6	000(017):122	000(017):122	NOUN
ajst-10982	187	7	-	-	PUNCT
ajst-10982	187	8	123	123	NUM
ajst-10982	187	9	.	.	PUNCT
ajst-10982	188	1	[	[	X
ajst-10982	188	2	6	6	NUM
ajst-10982	188	3	]	]	PUNCT
ajst-10982	188	4	joschko	joschko	PROPN
ajst-10982	188	5	m	m	PROPN
ajst-10982	188	6	,	,	PUNCT
ajst-10982	188	7	graff	graff	VERB
ajst-10982	188	8	o	o	NOUN
ajst-10982	188	9	,	,	PUNCT
ajst-10982	188	10	müller	müller	PROPN
ajst-10982	188	11	p	p	PROPN
ajst-10982	188	12	c	c	PROPN
ajst-10982	188	13	,	,	PUNCT
ajst-10982	188	14	et	et	PROPN
ajst-10982	188	15	al	al	PROPN
ajst-10982	188	16	.	.	PUNCT
ajst-10982	189	1	a	a	DET
ajst-10982	189	2	non	non	ADJ
ajst-10982	189	3	-	-	ADJ
ajst-10982	189	4	destructive	destructive	ADJ
ajst-10982	189	5	method	method	NOUN
ajst-10982	189	6	for	for	ADP
ajst-10982	189	7	the	the	DET
ajst-10982	189	8	morphological	morphological	ADJ
ajst-10982	189	9	assessment	assessment	NOUN
ajst-10982	189	10	of	of	ADP
ajst-10982	189	11	earthworm	earthworm	NOUN
ajst-10982	189	12	burrow	burrow	NOUN
ajst-10982	189	13	systems	system	NOUN
ajst-10982	189	14	in	in	ADP
ajst-10982	189	15	three	three	NUM
ajst-10982	189	16	dimensions	dimension	NOUN
ajst-10982	189	17	by	by	ADP
ajst-10982	189	18	x	x	NOUN
ajst-10982	189	19	-	-	NOUN
ajst-10982	189	20	ray	ray	NOUN
ajst-10982	189	21	computed	compute	VERB
ajst-10982	189	22	tomography[j	tomography[j	PROPN
ajst-10982	189	23	]	]	PUNCT
ajst-10982	189	24	.	.	PUNCT
ajst-10982	190	1	biology	biology	NOUN
ajst-10982	190	2	and	and	CCONJ
ajst-10982	190	3	fertility	fertility	NOUN
ajst-10982	190	4	of	of	ADP
ajst-10982	190	5	soils	soil	NOUN
ajst-10982	190	6	,	,	PUNCT
ajst-10982	190	7	1991	1991	NUM
ajst-10982	190	8	,	,	PUNCT
ajst-10982	190	9	11	11	NUM
ajst-10982	190	10	:	:	SYM
ajst-10982	190	11	88	88	NUM
ajst-10982	190	12	-	-	SYM
ajst-10982	190	13	92	92	NUM
ajst-10982	190	14	.	.	PUNCT
ajst-10982	191	1	[	[	X
ajst-10982	191	2	7	7	NUM
ajst-10982	191	3	]	]	X
ajst-10982	191	4	damadian	damadian	PROPN
ajst-10982	191	5	r.	r.	PROPN
ajst-10982	191	6	tumor	tumor	PROPN
ajst-10982	191	7	detection	detection	NOUN
ajst-10982	191	8	by	by	ADP
ajst-10982	191	9	nuclear	nuclear	ADJ
ajst-10982	191	10	magnetic	magnetic	PROPN
ajst-10982	191	11	resonance[j	resonance[j	PROPN
ajst-10982	191	12	]	]	PUNCT
ajst-10982	191	13	.	.	PUNCT
ajst-10982	192	1	science	science	NOUN
ajst-10982	192	2	,	,	PUNCT
ajst-10982	192	3	1971	1971	NUM
ajst-10982	192	4	,	,	PUNCT
ajst-10982	192	5	171(3976	171(3976	NUM
ajst-10982	192	6	):	):	PUNCT
ajst-10982	192	7	1151	1151	NUM
ajst-10982	192	8	-	-	SYM
ajst-10982	192	9	1153	1153	NUM
ajst-10982	192	10	.	.	PUNCT
ajst-10982	193	1	[	[	X
ajst-10982	193	2	8	8	NUM
ajst-10982	193	3	]	]	X
ajst-10982	193	4	xiao	xiao	PROPN
ajst-10982	193	5	shuang	shuang	PROPN
ajst-10982	193	6	,	,	PUNCT
ajst-10982	193	7	liu	liu	PROPN
ajst-10982	193	8	liantao	liantao	PROPN
ajst-10982	193	9	,	,	PUNCT
ajst-10982	193	10	zhang	zhang	PROPN
ajst-10982	193	11	yongjiang	yongjiang	PROPN
ajst-10982	193	12	,	,	PUNCT
ajst-10982	193	13	etc	etc	X
ajst-10982	193	14	.	.	X
ajst-10982	193	15	advances	advance	NOUN
ajst-10982	193	16	in	in	ADP
ajst-10982	193	17	research	research	NOUN
ajst-10982	193	18	methods	method	NOUN
ajst-10982	193	19	for	for	ADP
ajst-10982	193	20	in	in	ADP
ajst-10982	193	21	situ	situ	ADJ
ajst-10982	193	22	observation	observation	NOUN
ajst-10982	193	23	of	of	ADP
ajst-10982	193	24	plant	plant	NOUN
ajst-10982	193	25	microroots	microroot	NOUN
ajst-10982	193	26	[	[	X
ajst-10982	193	27	j	j	X
ajst-10982	193	28	]	]	X
ajst-10982	193	29	.	.	PUNCT
ajst-10982	194	1	journal	journal	PROPN
ajst-10982	194	2	of	of	ADP
ajst-10982	194	3	plant	plant	NOUN
ajst-10982	194	4	nutrition	nutrition	NOUN
ajst-10982	194	5	and	and	CCONJ
ajst-10982	194	6	fertilizer	fertilizer	NOUN
ajst-10982	194	7	,	,	PUNCT
ajst-10982	194	8	2020,26(2):1	2020,26(2):1	NUM
ajst-10982	194	9	-	-	SYM
ajst-10982	194	10	16	16	NUM
ajst-10982	194	11	.	.	PUNCT
ajst-10982	195	1	[	[	X
ajst-10982	195	2	9	9	NUM
ajst-10982	195	3	]	]	PUNCT
ajst-10982	195	4	metzner	metzner	NOUN
ajst-10982	195	5	r	r	NOUN
ajst-10982	195	6	,	,	PUNCT
ajst-10982	195	7	eggert	eggert	PROPN
ajst-10982	195	8	a	a	PROPN
ajst-10982	195	9	,	,	PUNCT
ajst-10982	195	10	van	van	PROPN
ajst-10982	195	11	dusschoten	dusschoten	PROPN
ajst-10982	195	12	d	d	PROPN
ajst-10982	195	13	,	,	PUNCT
ajst-10982	195	14	et	et	PROPN
ajst-10982	195	15	al	al	PROPN
ajst-10982	195	16	.	.	PUNCT
ajst-10982	196	1	direct	direct	ADJ
ajst-10982	196	2	comparison	comparison	NOUN
ajst-10982	196	3	of	of	ADP
ajst-10982	196	4	mri	mri	NOUN
ajst-10982	196	5	and	and	CCONJ
ajst-10982	196	6	x	x	NOUN
ajst-10982	196	7	-	-	NOUN
ajst-10982	196	8	ray	ray	NOUN
ajst-10982	196	9	ct	ct	PROPN
ajst-10982	196	10	technologies	technology	NOUN
ajst-10982	196	11	for	for	ADP
ajst-10982	196	12	3d	3d	NUM
ajst-10982	196	13	imaging	imaging	NOUN
ajst-10982	196	14	of	of	ADP
ajst-10982	196	15	root	root	NOUN
ajst-10982	196	16	systems	system	NOUN
ajst-10982	196	17	in	in	ADP
ajst-10982	196	18	soil	soil	NOUN
ajst-10982	196	19	:	:	PUNCT
ajst-10982	196	20	potential	potential	NOUN
ajst-10982	196	21	and	and	CCONJ
ajst-10982	196	22	challenges	challenge	NOUN
ajst-10982	196	23	for	for	ADP
ajst-10982	196	24	root	root	NOUN
ajst-10982	196	25	trait	trait	NOUN
ajst-10982	196	26	quantification[j	quantification[j	NOUN
ajst-10982	196	27	]	]	PUNCT
ajst-10982	196	28	.	.	PUNCT
ajst-10982	197	1	plant	plant	NOUN
ajst-10982	197	2	methods	method	NOUN
ajst-10982	197	3	,	,	PUNCT
ajst-10982	197	4	2015	2015	NUM
ajst-10982	197	5	,	,	PUNCT
ajst-10982	197	6	11(1	11(1	NUM
ajst-10982	197	7	):	):	PUNCT
ajst-10982	197	8	1	1	NUM
ajst-10982	197	9	-	-	SYM
ajst-10982	197	10	11	11	NUM
ajst-10982	197	11	.	.	PUNCT
ajst-10982	198	1	[	[	X
ajst-10982	198	2	10	10	NUM
ajst-10982	198	3	]	]	X
ajst-10982	198	4	moran	moran	PROPN
ajst-10982	198	5	c	c	PROPN
ajst-10982	198	6	j	j	PROPN
ajst-10982	198	7	,	,	PUNCT
ajst-10982	198	8	pierret	pierret	VERB
ajst-10982	198	9	a	a	PRON
ajst-10982	198	10	,	,	PUNCT
ajst-10982	198	11	stevenson	stevenson	PROPN
ajst-10982	198	12	a	a	DET
ajst-10982	198	13	w.	w.	PROPN
ajst-10982	198	14	x	x	PROPN
ajst-10982	198	15	-	-	NOUN
ajst-10982	198	16	ray	ray	NOUN
ajst-10982	198	17	absorption	absorption	NOUN
ajst-10982	198	18	and	and	CCONJ
ajst-10982	198	19	phase	phase	NOUN
ajst-10982	198	20	contrast	contrast	NOUN
ajst-10982	198	21	imaging	imaging	NOUN
ajst-10982	198	22	to	to	PART
ajst-10982	198	23	study	study	VERB
ajst-10982	198	24	the	the	DET
ajst-10982	198	25	interplay	interplay	NOUN
ajst-10982	198	26	between	between	ADP
ajst-10982	198	27	plant	plant	NOUN
ajst-10982	198	28	roots	root	NOUN
ajst-10982	198	29	and	and	CCONJ
ajst-10982	198	30	soil	soil	NOUN
ajst-10982	198	31	structure[j	structure[j	NOUN
ajst-10982	198	32	]	]	PUNCT
ajst-10982	198	33	.	.	PUNCT
ajst-10982	199	1	plant	plant	NOUN
ajst-10982	199	2	and	and	CCONJ
ajst-10982	199	3	soil	soil	NOUN
ajst-10982	199	4	,	,	PUNCT
ajst-10982	199	5	2000	2000	NUM
ajst-10982	199	6	,	,	PUNCT
ajst-10982	199	7	223(1	223(1	NUM
ajst-10982	199	8	-	-	SYM
ajst-10982	199	9	2	2	NUM
ajst-10982	199	10	):	):	PUNCT
ajst-10982	199	11	101117	101117	NUM
ajst-10982	199	12	.	.	PUNCT
ajst-10982	200	1	[	[	X
ajst-10982	200	2	11	11	NUM
ajst-10982	200	3	]	]	PUNCT
ajst-10982	200	4	mcneill	mcneill	NOUN
ajst-10982	200	5	a，kolesik	a，kolesik	PROPN
ajst-10982	200	6	p.	p.	PROPN
ajst-10982	200	7	x	x	PROPN
ajst-10982	200	8	-	-	PUNCT
ajst-10982	200	9	ray	ray	NOUN
ajst-10982	200	10	ct	ct	NOUN
ajst-10982	200	11	investigations	investigation	NOUN
ajst-10982	200	12	of	of	ADP
ajst-10982	200	13	intact	intact	ADJ
ajst-10982	200	14	soil	soil	NOUN
ajst-10982	200	15	cores	core	NOUN
ajst-10982	200	16	with	with	ADP
ajst-10982	200	17	and	and	CCONJ
ajst-10982	200	18	without	without	ADP
ajst-10982	200	19	living	live	VERB
ajst-10982	200	20	crop	crop	NOUN
ajst-10982	200	21	roots[c].proceedings	roots[c].proceeding	NOUN
ajst-10982	200	22	of	of	ADP
ajst-10982	200	23	the	the	DET
ajst-10982	200	24	3rd	3rd	ADJ
ajst-10982	200	25	australian	australian	ADJ
ajst-10982	200	26	new	new	PROPN
ajst-10982	200	27	zealand	zealand	PROPN
ajst-10982	200	28	soils	soils	PROPN
ajst-10982	200	29	conference，university	conference，university	NOUN
ajst-10982	200	30	of	of	ADP
ajst-10982	200	31	sydney,2004,5	sydney,2004,5	NOUN
ajst-10982	200	32	-	-	X
ajst-10982	200	33	9	9	NUM
ajst-10982	200	34	.	.	PUNCT
ajst-10982	201	1	[	[	X
ajst-10982	201	2	12	12	NUM
ajst-10982	201	3	]	]	X
ajst-10982	201	4	watanabe	watanabe	PROPN
ajst-10982	201	5	k.	k.	PROPN
ajst-10982	201	6	nondestructive	nondestructive	PROPN
ajst-10982	201	7	root	root	NOUN
ajst-10982	201	8	-	-	PUNCT
ajst-10982	201	9	zone	zone	NOUN
ajst-10982	201	10	analysis	analysis	NOUN
ajst-10982	201	11	with	with	ADP
ajst-10982	201	12	x	x	NOUN
ajst-10982	201	13	-	-	NOUN
ajst-10982	201	14	ray	ray	NOUN
ajst-10982	201	15	ct	ct	NUM
ajst-10982	201	16	scanners[j	scanners[j	PROPN
ajst-10982	201	17	]	]	PUNCT
ajst-10982	201	18	.	.	PUNCT
ajst-10982	202	1	engineering	engineer	VERB
ajst-10982	202	2	for	for	ADP
ajst-10982	202	3	biological	biological	ADJ
ajst-10982	202	4	production	production	NOUN
ajst-10982	202	5	systems	system	NOUN
ajst-10982	202	6	,	,	PUNCT
ajst-10982	202	7	1993	1993	NUM
ajst-10982	202	8	.	.	PUNCT
ajst-10982	203	1	[	[	X
ajst-10982	203	2	13	13	NUM
ajst-10982	203	3	]	]	X
ajst-10982	203	4	han	han	PROPN
ajst-10982	203	5	l	l	PROPN
ajst-10982	203	6	,	,	PUNCT
ajst-10982	203	7	dutilleul	dutilleul	PROPN
ajst-10982	203	8	p	p	NOUN
ajst-10982	203	9	,	,	PUNCT
ajst-10982	203	10	prasher	prasher	NOUN
ajst-10982	203	11	s	s	PART
ajst-10982	203	12	o	o	NOUN
ajst-10982	203	13	,	,	PUNCT
ajst-10982	203	14	et	et	PROPN
ajst-10982	203	15	al	al	PROPN
ajst-10982	203	16	.	.	PROPN
ajst-10982	203	17	assessment	assessment	NOUN
ajst-10982	203	18	of	of	ADP
ajst-10982	203	19	density	density	NOUN
ajst-10982	203	20	effects	effect	NOUN
ajst-10982	203	21	of	of	ADP
ajst-10982	203	22	the	the	DET
ajst-10982	203	23	common	common	ADJ
ajst-10982	203	24	scab	scab	NOUN
ajst-10982	203	25	-	-	PUNCT
ajst-10982	203	26	inducing	induce	VERB
ajst-10982	203	27	pathogen	pathogen	NOUN
ajst-10982	203	28	on	on	ADP
ajst-10982	203	29	the	the	DET
ajst-10982	203	30	seed	seed	NOUN
ajst-10982	203	31	and	and	CCONJ
ajst-10982	203	32	peripheral	peripheral	ADJ
ajst-10982	203	33	organs	organ	NOUN
ajst-10982	203	34	of	of	ADP
ajst-10982	203	35	potato	potato	NOUN
ajst-10982	203	36	during	during	ADP
ajst-10982	203	37	growth	growth	NOUN
ajst-10982	203	38	using	use	VERB
ajst-10982	203	39	computed	compute	VERB
ajst-10982	203	40	tomography	tomography	NOUN
ajst-10982	203	41	scanning	scanning	NOUN
ajst-10982	203	42	data[j].transactions	data[j].transaction	NOUN
ajst-10982	203	43	of	of	ADP
ajst-10982	203	44	the	the	DET
ajst-10982	203	45	asabe	asabe	PROPN
ajst-10982	203	46	，	，	PROPN
ajst-10982	203	47	2009，52(1):305	2009，52(1):305	PROPN
ajst-10982	203	48	-	-	PUNCT
ajst-10982	203	49	311	311	NUM
ajst-10982	203	50	.	.	PUNCT
ajst-10982	204	1	[	[	X
ajst-10982	204	2	14	14	NUM
ajst-10982	204	3	]	]	X
ajst-10982	204	4	zhou	zhou	PROPN
ajst-10982	204	5	xuecheng	xuecheng	PROPN
ajst-10982	204	6	,	,	PUNCT
ajst-10982	204	7	luo	luo	PROPN
ajst-10982	204	8	xiwen	xiwen	PROPN
ajst-10982	204	9	,	,	PUNCT
ajst-10982	204	10	yan	yan	PROPN
ajst-10982	204	11	xiaolong	xiaolong	PROPN
ajst-10982	204	12	,	,	PUNCT
ajst-10982	204	13	et	et	PROPN
ajst-10982	204	14	al	al	PROPN
ajst-10982	204	15	.	.	PROPN
ajst-10982	204	16	fuzzy	fuzzy	ADJ
ajst-10982	204	17	threshold	threshold	NOUN
ajst-10982	204	18	segmentation	segmentation	NOUN
ajst-10982	204	19	of	of	ADP
ajst-10982	204	20	in	in	ADP
ajst-10982	204	21	situ	situ	ADJ
ajst-10982	204	22	root	root	NOUN
ajst-10982	204	23	ct	ct	NUM
ajst-10982	204	24	images	image	NOUN
ajst-10982	204	25	based	base	VERB
ajst-10982	204	26	on	on	ADP
ajst-10982	204	27	genetic	genetic	ADJ
ajst-10982	204	28	algorithm[j	algorithm[j	PROPN
ajst-10982	204	29	]	]	PUNCT
ajst-10982	204	30	.	.	PUNCT
ajst-10982	205	1	chinese	chinese	ADJ
ajst-10982	205	2	journal	journal	PROPN
ajst-10982	205	3	of	of	ADP
ajst-10982	205	4	image	image	NOUN
ajst-10982	205	5	and	and	CCONJ
ajst-10982	205	6	graphics	graphic	NOUN
ajst-10982	205	7	,	,	PUNCT
ajst-10982	205	8	2009	2009	NUM
ajst-10982	205	9	,	,	PUNCT
ajst-10982	205	10	14(4	14(4	NUM
ajst-10982	205	11	):	):	PUNCT
ajst-10982	205	12	681	681	NUM
ajst-10982	205	13	-	-	NOUN
ajst-10982	205	14	687	687	NUM
ajst-10982	205	15	.	.	PUNCT
ajst-10982	206	1	[	[	X
ajst-10982	206	2	15	15	NUM
ajst-10982	206	3	]	]	X
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ajst-10982	206	5	x	x	PROPN
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ajst-10982	206	7	xing	xing	PROPN
ajst-10982	206	8	l	l	PROPN
ajst-10982	206	9	,	,	PUNCT
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ajst-10982	206	11	s	s	PROPN
ajst-10982	206	12	,	,	PUNCT
ajst-10982	206	13	et	et	PROPN
ajst-10982	206	14	al	al	PROPN
ajst-10982	206	15	.	.	PUNCT
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ajst-10982	207	8	maize	maize	NOUN
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ajst-10982	207	10	-	-	PUNCT
ajst-10982	207	11	stubble	stubble	ADJ
ajst-10982	207	12	in	in	ADP
ajst-10982	207	13	-	-	PUNCT
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ajst-10982	207	15	via	via	ADP
ajst-10982	207	16	x	x	X
ajst-10982	207	17	-	-	NOUN
ajst-10982	207	18	ray	ray	NOUN
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ajst-10982	207	20	tomography[j	tomography[j	PROPN
ajst-10982	207	21	]	]	PUNCT
ajst-10982	207	22	.	.	PUNCT
ajst-10982	208	1	international	international	ADJ
ajst-10982	208	2	journal	journal	PROPN
ajst-10982	208	3	of	of	ADP
ajst-10982	208	4	agricultural	agricultural	ADJ
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ajst-10982	208	6	biological	biological	ADJ
ajst-10982	208	7	engineering	engineering	NOUN
ajst-10982	208	8	,	,	PUNCT
ajst-10982	208	9	2020	2020	NUM
ajst-10982	208	10	,	,	PUNCT
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ajst-10982	208	12	):	):	PUNCT
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ajst-10982	208	14	-	-	SYM
ajst-10982	208	15	179	179	NUM
ajst-10982	208	16	.	.	PUNCT
ajst-10982	209	1	[	[	X
ajst-10982	209	2	16	16	NUM
ajst-10982	209	3	]	]	X
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ajst-10982	209	6	.	.	PROPN
ajst-10982	209	7	research	research	NOUN
ajst-10982	209	8	on	on	ADP
ajst-10982	209	9	3d	3d	NUM
ajst-10982	209	10	segmentation	segmentation	NOUN
ajst-10982	209	11	algorithm	algorithm	NOUN
ajst-10982	209	12	of	of	ADP
ajst-10982	209	13	corn	corn	NOUN
ajst-10982	209	14	root	root	NOUN
ajst-10982	209	15	ct	ct	PROPN
ajst-10982	209	16	image[d	image[d	PROPN
ajst-10982	209	17	]	]	PUNCT
ajst-10982	209	18	.	.	PUNCT
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ajst-10982	210	2	agricultural	agricultural	PROPN
ajst-10982	210	3	university	university	NOUN
ajst-10982	210	4	,	,	PUNCT
ajst-10982	210	5	2022	2022	NUM
ajst-10982	210	6	.	.	PUNCT
ajst-10982	211	1	doi	doi	NOUN
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ajst-10982	211	3	10.27158	10.27158	NUM
ajst-10982	211	4	/	/	SYM
ajst-10982	211	5	d.cnki.ghznu.2022.001341	d.cnki.ghznu.2022.001341	NOUN
ajst-10982	211	6	.	.	PUNCT
ajst-10982	212	1	[	[	X
ajst-10982	212	2	17	17	NUM
ajst-10982	212	3	]	]	X
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ajst-10982	212	5	chen	chen	PROPN
ajst-10982	212	6	.	.	PUNCT
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ajst-10982	213	2	on	on	ADP
ajst-10982	213	3	in	in	ADP
ajst-10982	213	4	-	-	PUNCT
ajst-10982	213	5	situ	situ	ADJ
ajst-10982	213	6	root	root	NOUN
ajst-10982	213	7	segmentation	segmentation	NOUN
ajst-10982	213	8	technology	technology	NOUN
ajst-10982	213	9	of	of	ADP
ajst-10982	213	10	cotton	cotton	NOUN
ajst-10982	213	11	based	base	VERB
ajst-10982	213	12	on	on	ADP
ajst-10982	213	13	deep	deep	ADJ
ajst-10982	213	14	learning[d	learning[d	PROPN
ajst-10982	213	15	]	]	PUNCT
ajst-10982	213	16	.	.	PUNCT
ajst-10982	214	1	hebei	hebei	PROPN
ajst-10982	214	2	agricultural	agricultural	PROPN
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ajst-10982	214	4	,	,	PUNCT
ajst-10982	214	5	2021	2021	NUM
ajst-10982	214	6	.	.	PUNCT
ajst-10982	215	1	doi	doi	NOUN
ajst-10982	215	2	:	:	PUNCT
ajst-10982	215	3	10.27109	10.27109	NUM
ajst-10982	215	4	/	/	SYM
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ajst-10982	215	6	.	.	PUNCT
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ajst-10982	216	2	18	18	NUM
ajst-10982	216	3	]	]	PUNCT
ajst-10982	216	4	borisjuk	borisjuk	NOUN
ajst-10982	216	5	l	l	NOUN
ajst-10982	216	6	,	,	PUNCT
ajst-10982	216	7	rolletschek	rolletschek	PROPN
ajst-10982	216	8	h	h	NOUN
ajst-10982	216	9	,	,	PUNCT
ajst-10982	216	10	neuberger	neuberger	NOUN
ajst-10982	216	11	t.	t.	PROPN
ajst-10982	216	12	surveying	survey	VERB
ajst-10982	216	13	the	the	DET
ajst-10982	216	14	plant	plant	NOUN
ajst-10982	216	15	’s	’s	PART
ajst-10982	216	16	world	world	NOUN
ajst-10982	216	17	by	by	ADP
ajst-10982	216	18	magnetic	magnetic	ADJ
ajst-10982	216	19	resonance	resonance	NOUN
ajst-10982	216	20	imaging[j	imaging[j	PROPN
ajst-10982	216	21	]	]	PUNCT
ajst-10982	216	22	.	.	PUNCT
ajst-10982	217	1	the	the	DET
ajst-10982	217	2	plant	plant	NOUN
ajst-10982	217	3	journal,201270(1	journal,201270(1	PROPN
ajst-10982	217	4	):	):	PUNCT
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ajst-10982	217	6	-	-	SYM
ajst-10982	217	7	146	146	NUM
ajst-10982	217	8	.	.	PUNCT
ajst-10982	218	1	[	[	X
ajst-10982	218	2	19	19	NUM
ajst-10982	218	3	]	]	X
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ajst-10982	218	5	y	y	PROPN
ajst-10982	218	6	,	,	PUNCT
ajst-10982	218	7	wandel	wandel	PROPN
ajst-10982	218	8	n	n	PROPN
ajst-10982	218	9	,	,	PUNCT
ajst-10982	218	10	landl	landl	VERB
ajst-10982	218	11	m	m	PRON
ajst-10982	218	12	,	,	PUNCT
ajst-10982	218	13	et	et	PROPN
ajst-10982	218	14	al	al	PROPN
ajst-10982	218	15	.	.	PROPN
ajst-10982	219	1	3d	3d	NUM
ajst-10982	219	2	u	u	NOUN
ajst-10982	219	3	-	-	NOUN
ajst-10982	219	4	net	net	ADJ
ajst-10982	219	5	for	for	ADP
ajst-10982	219	6	segmentation	segmentation	NOUN
ajst-10982	219	7	of	of	ADP
ajst-10982	219	8	plant	plant	NOUN
ajst-10982	219	9	root	root	NOUN
ajst-10982	219	10	mri	mri	NOUN
ajst-10982	219	11	images	image	NOUN
ajst-10982	219	12	in	in	ADP
ajst-10982	219	13	super	super	NOUN
ajst-10982	219	14	-	-	ADJ
ajst-10982	219	15	resolution[j	resolution[j	NUM
ajst-10982	219	16	]	]	PUNCT
ajst-10982	219	17	.	.	PUNCT
ajst-10982	220	1	arxiv	arxiv	PROPN
ajst-10982	220	2	preprint	preprint	VERB
ajst-10982	220	3	arxiv:2002.09317	arxiv:2002.09317	NOUN
ajst-10982	220	4	,	,	PUNCT
ajst-10982	220	5	2020	2020	NUM
ajst-10982	220	6	.	.	PUNCT
ajst-10982	221	1	[	[	X
ajst-10982	221	2	20	20	NUM
ajst-10982	221	3	]	]	SYM
ajst-10982	221	4	du	du	NOUN
ajst-10982	221	5	guangyuan.nmr	guangyuan.nmr	PROPN
ajst-10982	221	6	study	study	NOUN
ajst-10982	221	7	on	on	ADP
ajst-10982	221	8	the	the	DET
ajst-10982	221	9	dynamic	dynamic	ADJ
ajst-10982	221	10	distribution	distribution	NOUN
ajst-10982	221	11	of	of	ADP
ajst-10982	221	12	water	water	NOUN
ajst-10982	221	13	and	and	CCONJ
ajst-10982	221	14	sugar	sugar	NOUN
ajst-10982	221	15	in	in	ADP
ajst-10982	221	16	wheat	wheat	NOUN
ajst-10982	221	17	during	during	ADP
ajst-10982	221	18	grain	grain	NOUN
ajst-10982	221	19	filling[d].northwest	filling[d].northw	ADJ
ajst-10982	221	20	a&f	a&f	PROPN
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ajst-10982	221	22	/	/	SYM
ajst-10982	221	23	d.cnki.gxbnu.2013.000010	d.cnki.gxbnu.2013.000010	NOUN
ajst-10982	221	24	.	.	PUNCT
ajst-10982	222	1	[	[	X
ajst-10982	222	2	21	21	NUM
ajst-10982	222	3	]	]	X
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ajst-10982	222	5	c	c	NOUN
ajst-10982	222	6	,	,	PUNCT
ajst-10982	222	7	sikora	sikora	PROPN
ajst-10982	222	8	r	r	PROPN
ajst-10982	222	9	a	a	PRON
ajst-10982	222	10	,	,	PUNCT
ajst-10982	222	11	oerke	oerke	NOUN
ajst-10982	222	12	e	e	NOUN
ajst-10982	222	13	,	,	PUNCT
ajst-10982	222	14	et	et	PROPN
ajst-10982	222	15	al	al	PROPN
ajst-10982	222	16	.	.	PUNCT
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ajst-10982	222	18	magnetic	magnetic	ADJ
ajst-10982	222	19	resonance	resonance	NOUN
ajst-10982	222	20	:	:	PUNCT
ajst-10982	222	21	a	a	DET
ajst-10982	222	22	tool	tool	NOUN
ajst-10982	222	23	for	for	ADP
ajst-10982	222	24	imaging	imaging	NOUN
ajst-10982	222	25	belowground	belowground	ADJ
ajst-10982	222	26	damage	damage	NOUN
ajst-10982	222	27	caused	cause	VERB
ajst-10982	222	28	by	by	ADP
ajst-10982	222	29	heterodera	heterodera	NOUN
ajst-10982	222	30	schachtii	schachtii	NOUN
ajst-10982	222	31	and	and	CCONJ
ajst-10982	222	32	rhizoctonia	rhizoctonia	PROPN
ajst-10982	222	33	solani	solani	PROPN
ajst-10982	222	34	on	on	ADP
ajst-10982	222	35	sugar	sugar	NOUN
ajst-10982	222	36	beet[j	beet[j	PROPN
ajst-10982	222	37	]	]	PUNCT
ajst-10982	222	38	.	.	PUNCT
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ajst-10982	223	2	of	of	ADP
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ajst-10982	223	4	botany,201163(1):319	botany,201163(1):319	PROPN
ajst-10982	223	5	-	-	PUNCT
ajst-10982	223	6	327	327	NUM
ajst-10982	223	7	.	.	PUNCT
ajst-10982	224	1	[	[	X
ajst-10982	224	2	22	22	NUM
ajst-10982	224	3	]	]	X
ajst-10982	224	4	li	li	PROPN
ajst-10982	224	5	y	y	PROPN
ajst-10982	224	6	,	,	PUNCT
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ajst-10982	224	8	y	y	PROPN
ajst-10982	224	9	,	,	PUNCT
ajst-10982	224	10	wang	wang	PROPN
ajst-10982	224	11	m	m	PROPN
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ajst-10982	224	13	et	et	PROPN
ajst-10982	224	14	al	al	PROPN
ajst-10982	224	15	.	.	PUNCT
ajst-10982	225	1	an	an	DET
ajst-10982	225	2	improved	improve	VERB
ajst-10982	225	3	u	u	NOUN
ajst-10982	225	4	-	-	ADJ
ajst-10982	225	5	net	net	NOUN
ajst-10982	225	6	-	-	PUNCT
ajst-10982	225	7	based	base	VERB
ajst-10982	225	8	in	in	ADP
ajst-10982	225	9	situ	situ	ADJ
ajst-10982	225	10	root	root	NOUN
ajst-10982	225	11	system	system	NOUN
ajst-10982	225	12	phenotype	phenotype	NOUN
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ajst-10982	225	14	method	method	NOUN
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ajst-10982	225	16	plants[j	plants[j	NOUN
ajst-10982	225	17	]	]	PUNCT
ajst-10982	225	18	.	.	PUNCT
ajst-10982	226	1	frontiers	frontier	NOUN
ajst-10982	226	2	in	in	ADP
ajst-10982	226	3	plant	plant	NOUN
ajst-10982	226	4	science	science	NOUN
ajst-10982	226	5	,	,	PUNCT
ajst-10982	226	6	2023	2023	NUM
ajst-10982	226	7	,	,	PUNCT
ajst-10982	226	8	14	14	NUM
ajst-10982	226	9	.	.	PUNCT
ajst-10982	227	1	[	[	X
ajst-10982	227	2	23	23	NUM
ajst-10982	227	3	]	]	X
ajst-10982	227	4	nahar	nahar	PROPN
ajst-10982	227	5	k	k	PROPN
ajst-10982	227	6	,	,	PUNCT
ajst-10982	227	7	pan	pan	PROPN
ajst-10982	227	8	w	w	PROPN
ajst-10982	227	9	l.	l.	PROPN
ajst-10982	227	10	high	high	ADJ
ajst-10982	227	11	resolution	resolution	NOUN
ajst-10982	227	12	in	in	ADP
ajst-10982	227	13	situ	situ	NOUN
ajst-10982	227	14	rhizosphere	rhizosphere	ADJ
ajst-10982	227	15	imaging	imaging	NOUN
ajst-10982	227	16	of	of	ADP
ajst-10982	227	17	root	root	NOUN
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ajst-10982	227	20	in	in	ADP
ajst-10982	227	21	oilseed	oilseed	NOUN
ajst-10982	227	22	castor	castor	NOUN
ajst-10982	227	23	plant	plant	NOUN
ajst-10982	227	24	(	(	PUNCT
ajst-10982	227	25	ricinus	ricinus	PROPN
ajst-10982	227	26	communis	communis	PROPN
ajst-10982	227	27	l.	l.	PROPN
ajst-10982	227	28	)	)	PUNCT
ajst-10982	227	29	using	use	VERB
ajst-10982	227	30	digital	digital	ADJ
ajst-10982	227	31	scanners[jl	scanners[jl	PROPN
ajst-10982	227	32	.	.	PUNCT
ajst-10982	228	1	modeling	model	VERB
ajst-10982	228	2	earth	earth	NOUN
ajst-10982	228	3	systems	system	NOUN
ajst-10982	228	4	and	and	CCONJ
ajst-10982	228	5	environment,2019,5(3):781	environment,2019,5(3):781	PROPN
ajst-10982	228	6	-	-	PUNCT
ajst-10982	228	7	792	792	NUM
ajst-10982	228	8	.	.	PUNCT
ajst-10982	229	1	[	[	X
ajst-10982	229	2	24	24	NUM
ajst-10982	229	3	]	]	PUNCT
ajst-10982	229	4	mohamed	mohame	VERB
ajst-10982	229	5	a	a	PROPN
ajst-10982	229	6	,	,	PUNCT
ajst-10982	229	7	monnier	monni	ADJ
ajst-10982	229	8	y	y	PROPN
ajst-10982	229	9	,	,	PUNCT
ajst-10982	229	10	mao	mao	PROPN
ajst-10982	230	1	z	z	NOUN
ajst-10982	230	2	,	,	PUNCT
ajst-10982	230	3	et	et	PROPN
ajst-10982	230	4	al	al	PROPN
ajst-10982	230	5	.	.	PUNCT
ajst-10982	231	1	an	an	DET
ajst-10982	231	2	evaluation	evaluation	NOUN
ajst-10982	231	3	of	of	ADP
ajst-10982	231	4	inexpensive	inexpensive	ADJ
ajst-10982	231	5	methods	method	NOUN
ajst-10982	231	6	for	for	ADP
ajst-10982	231	7	root	root	NOUN
ajst-10982	231	8	image	image	NOUN
ajst-10982	231	9	acquisition	acquisition	NOUN
ajst-10982	231	10	when	when	SCONJ
ajst-10982	231	11	using	use	VERB
ajst-10982	231	12	rhizotrons[j	rhizotrons[j	PROPN
ajst-10982	231	13	]	]	PUNCT
ajst-10982	231	14	.	.	PUNCT
ajst-10982	232	1	plant	plant	NOUN
ajst-10982	232	2	methods	method	NOUN
ajst-10982	232	3	,	,	PUNCT
ajst-10982	232	4	2017	2017	NUM
ajst-10982	232	5	,	,	PUNCT
ajst-10982	232	6	13(1	13(1	NUM
ajst-10982	232	7	):	):	PUNCT
ajst-10982	232	8	1	1	NUM
ajst-10982	232	9	-	-	SYM
ajst-10982	232	10	13	13	NUM
ajst-10982	232	11	.	.	PUNCT
ajst-10982	233	1	[	[	X
ajst-10982	233	2	25	25	NUM
ajst-10982	233	3	]	]	PUNCT
ajst-10982	233	4	castleman	castleman	NOUN
ajst-10982	233	5	k	k	PROPN
ajst-10982	233	6	r.	r.	PROPN
ajst-10982	233	7	digital	digital	PROPN
ajst-10982	233	8	image	image	NOUN
ajst-10982	233	9	processing[m	processing[m	NOUN
ajst-10982	233	10	]	]	PUNCT
ajst-10982	233	11	.	.	PUNCT
ajst-10982	234	1	prentice	prentice	PROPN
ajst-10982	234	2	hall	hall	PROPN
ajst-10982	234	3	press	press	PROPN
ajst-10982	234	4	,	,	PUNCT
ajst-10982	234	5	1996	1996	NUM
ajst-10982	234	6	.	.	PUNCT
ajst-10982	235	1	[	[	X
ajst-10982	235	2	26	26	NUM
ajst-10982	235	3	]	]	X
ajst-10982	235	4	lecun	lecun	PROPN
ajst-10982	235	5	y	y	PROPN
ajst-10982	235	6	,	,	PUNCT
ajst-10982	235	7	bengio	bengio	PROPN
ajst-10982	235	8	y	y	PROPN
ajst-10982	235	9	,	,	PUNCT
ajst-10982	235	10	hinton	hinton	PROPN
ajst-10982	235	11	g.	g.	PROPN
ajst-10982	235	12	deep	deep	PROPN
ajst-10982	235	13	learning[j	learning[j	PROPN
ajst-10982	235	14	]	]	PUNCT
ajst-10982	235	15	.	.	PUNCT
ajst-10982	236	1	nature	nature	NOUN
ajst-10982	236	2	,	,	PUNCT
ajst-10982	236	3	2015	2015	NUM
ajst-10982	236	4	,	,	PUNCT
ajst-10982	236	5	521(7553	521(7553	NUM
ajst-10982	236	6	):	):	PUNCT
ajst-10982	236	7	436	436	NUM
ajst-10982	236	8	-	-	SYM
ajst-10982	236	9	444	444	NUM
ajst-10982	236	10	.	.	PUNCT
ajst-10982	237	1	[	[	X
ajst-10982	237	2	27	27	NUM
ajst-10982	237	3	]	]	X
ajst-10982	237	4	liang	liang	PROPN
ajst-10982	237	5	lixiu	lixiu	PROPN
ajst-10982	237	6	,	,	PUNCT
ajst-10982	237	7	ye	ye	PROPN
ajst-10982	237	8	junli	junli	NOUN
ajst-10982	237	9	,	,	PUNCT
ajst-10982	237	10	wu	wu	PROPN
ajst-10982	237	11	dan	dan	PROPN
ajst-10982	237	12	,	,	PUNCT
ajst-10982	237	13	et	et	PROPN
ajst-10982	237	14	al	al	PROPN
ajst-10982	237	15	.	.	PROPN
ajst-10982	237	16	research	research	NOUN
ajst-10982	237	17	on	on	ADP
ajst-10982	237	18	image	image	NOUN
ajst-10982	237	19	segmentation	segmentation	NOUN
ajst-10982	237	20	algorithm	algorithm	NOUN
ajst-10982	237	21	of	of	ADP
ajst-10982	237	22	surface	surface	NOUN
ajst-10982	237	23	root	root	NOUN
ajst-10982	237	24	system	system	NOUN
ajst-10982	237	25	of	of	ADP
ajst-10982	237	26	rice	rice	NOUN
ajst-10982	238	1	[	[	X
ajst-10982	238	2	j	j	X
ajst-10982	238	3	]	]	X
ajst-10982	238	4	.	.	PUNCT
ajst-10982	239	1	china	china	PROPN
ajst-10982	239	2	agricultural	agricultural	PROPN
ajst-10982	239	3	science	science	PROPN
ajst-10982	239	4	and	and	CCONJ
ajst-10982	239	5	technology	technology	PROPN
ajst-10982	239	6	herald	herald	PROPN
ajst-10982	239	7	,	,	PUNCT
ajst-10982	239	8	2019	2019	NUM
ajst-10982	239	9	,	,	PUNCT
ajst-10982	239	10	21(1	21(1	NUM
ajst-10982	239	11	):	):	PUNCT
ajst-10982	239	12	70	70	NUM
ajst-10982	239	13	-	-	SYM
ajst-10982	239	14	79	79	NUM
ajst-10982	239	15	.	.	PUNCT
ajst-10982	240	1	[	[	X
ajst-10982	240	2	28	28	NUM
ajst-10982	240	3	]	]	X
ajst-10982	240	4	shen	shen	NOUN
ajst-10982	240	5	c	c	X
ajst-10982	240	6	,	,	PUNCT
ajst-10982	240	7	liu	liu	PROPN
ajst-10982	240	8	l	l	PROPN
ajst-10982	240	9	,	,	PUNCT
ajst-10982	240	10	zhu	zhu	PROPN
ajst-10982	240	11	l	l	NOUN
ajst-10982	240	12	,	,	PUNCT
ajst-10982	240	13	et	et	PROPN
ajst-10982	240	14	al	al	PROPN
ajst-10982	240	15	.	.	PROPN
ajst-10982	240	16	high	high	ADJ
ajst-10982	240	17	-	-	PUNCT
ajst-10982	240	18	throughput	throughput	NOUN
ajst-10982	240	19	in	in	ADP
ajst-10982	240	20	situ	situ	ADJ
ajst-10982	240	21	root	root	NOUN
ajst-10982	240	22	image	image	NOUN
ajst-10982	240	23	segmentation	segmentation	NOUN
ajst-10982	240	24	based	base	VERB
ajst-10982	240	25	on	on	ADP
ajst-10982	240	26	the	the	DET
ajst-10982	240	27	improved	improved	ADJ
ajst-10982	240	28	deeplabv3	deeplabv3	NOUN
ajst-10982	240	29	+	+	CCONJ
ajst-10982	240	30	method[j	method[j	NOUN
ajst-10982	240	31	]	]	PUNCT
ajst-10982	240	32	.	.	PUNCT
ajst-10982	241	1	frontiers	frontier	NOUN
ajst-10982	241	2	in	in	ADP
ajst-10982	241	3	plant	plant	NOUN
ajst-10982	241	4	science	science	NOUN
ajst-10982	241	5	,	,	PUNCT
ajst-10982	241	6	2020	2020	NUM
ajst-10982	241	7	,	,	PUNCT
ajst-10982	241	8	11	11	NUM
ajst-10982	241	9	:	:	SYM
ajst-10982	241	10	576791	576791	NUM
ajst-10982	241	11	.	.	PUNCT
ajst-10982	242	1	[	[	X
ajst-10982	242	2	29	29	NUM
ajst-10982	242	3	]	]	X
ajst-10982	242	4	borianne	borianne	NOUN
ajst-10982	242	5	p	p	NOUN
ajst-10982	242	6	,	,	PUNCT
ajst-10982	242	7	subsol	subsol	NOUN
ajst-10982	242	8	g	g	NOUN
ajst-10982	242	9	,	,	PUNCT
ajst-10982	242	10	fallavier	fallavier	NOUN
ajst-10982	242	11	f	f	NOUN
ajst-10982	242	12	,	,	PUNCT
ajst-10982	242	13	et	et	PROPN
ajst-10982	242	14	al	al	PROPN
ajst-10982	242	15	.	.	PUNCT
ajst-10982	242	16	gt	gt	PROPN
ajst-10982	242	17	-	-	PUNCT
ajst-10982	242	18	roots	root	NOUN
ajst-10982	242	19	an	an	DET
ajst-10982	242	20	integrated	integrated	ADJ
ajst-10982	242	21	software	software	NOUN
ajst-10982	242	22	for	for	ADP
ajst-10982	242	23	automated	automate	VERB
ajst-10982	242	24	root	root	NOUN
ajst-10982	242	25	system	system	NOUN
ajst-10982	242	26	measurement	measurement	NOUN
ajst-10982	242	27	from	from	ADP
ajst-10982	242	28	high	high	ADJ
ajst-10982	242	29	-	-	PUNCT
ajst-10982	242	30	throughput	throughput	NOUN
ajst-10982	242	31	phenotyping	phenotype	VERB
ajst-10982	242	32	platform	platform	NOUN
ajst-10982	242	33	images[j	images[j	PROPN
ajst-10982	242	34	]	]	PUNCT
ajst-10982	242	35	.	.	PUNCT
ajst-10982	243	1	computers	computer	NOUN
ajst-10982	243	2	and	and	CCONJ
ajst-10982	243	3	electronics	electronic	NOUN
ajst-10982	243	4	in	in	ADP
ajst-10982	243	5	ariculture2018150:328	ariculture2018150:328	NOUN
ajst-10982	243	6	-	-	PUNCT
ajst-10982	243	7	342	342	NUM
ajst-10982	243	8	.	.	PUNCT
ajst-10982	244	1	[	[	X
ajst-10982	244	2	30	30	NUM
ajst-10982	244	3	]	]	X
ajst-10982	244	4	haralick	haralick	NOUN
ajst-10982	244	5	r	r	PROPN
ajst-10982	244	6	m	m	PROPN
ajst-10982	244	7	,	,	PUNCT
ajst-10982	244	8	sternberg	sternberg	PROPN
ajst-10982	244	9	s	s	PROPN
ajst-10982	244	10	r	r	PROPN
ajst-10982	244	11	,	,	PUNCT
ajst-10982	244	12	zhuang	zhuang	PROPN
ajst-10982	244	13	x.	x.	PROPN
ajst-10982	244	14	image	image	NOUN
ajst-10982	244	15	analysis	analysis	NOUN
ajst-10982	244	16	using	use	VERB
ajst-10982	244	17	mathematical	mathematical	ADJ
ajst-10982	244	18	morphology[j	morphology[j	PROPN
ajst-10982	244	19	]	]	PUNCT
ajst-10982	244	20	.	.	PUNCT
ajst-10982	245	1	ieee	ieee	NOUN
ajst-10982	245	2	transactions	transaction	NOUN
ajst-10982	245	3	on	on	ADP
ajst-10982	245	4	pattern	pattern	NOUN
ajst-10982	245	5	analysis	analysis	NOUN
ajst-10982	245	6	and	and	CCONJ
ajst-10982	245	7	machine	machine	NOUN
ajst-10982	245	8	intelligence	intelligence	NOUN
ajst-10982	245	9	,	,	PUNCT
ajst-10982	245	10	1987	1987	NUM
ajst-10982	245	11	(	(	PUNCT
ajst-10982	245	12	4	4	NUM
ajst-10982	245	13	):	):	PUNCT
ajst-10982	245	14	532	532	NUM
ajst-10982	245	15	-	-	SYM
ajst-10982	245	16	550	550	NUM
ajst-10982	245	17	.	.	PUNCT
ajst-10982	246	1	[	[	X
ajst-10982	246	2	31	31	NUM
ajst-10982	246	3	]	]	PUNCT
ajst-10982	246	4	rosenfeld	rosenfeld	PROPN
ajst-10982	246	5	a	a	PRON
ajst-10982	246	6	,	,	PUNCT
ajst-10982	246	7	pfaltz	pfaltz	NOUN
ajst-10982	246	8	j	j	PROPN
ajst-10982	246	9	l.	l.	PROPN
ajst-10982	246	10	sequential	sequential	ADJ
ajst-10982	246	11	operations	operation	NOUN
ajst-10982	246	12	in	in	ADP
ajst-10982	246	13	digital	digital	ADJ
ajst-10982	246	14	picture	picture	NOUN
ajst-10982	246	15	processing[j	processing[j	NOUN
ajst-10982	246	16	]	]	PUNCT
ajst-10982	246	17	.	.	PUNCT
ajst-10982	247	1	journal	journal	PROPN
ajst-10982	247	2	of	of	ADP
ajst-10982	247	3	the	the	DET
ajst-10982	247	4	acm	acm	PROPN
ajst-10982	247	5	(	(	PUNCT
ajst-10982	247	6	jacm	jacm	PROPN
ajst-10982	247	7	)	)	PUNCT
ajst-10982	247	8	,	,	PUNCT
ajst-10982	247	9	1966	1966	NUM
ajst-10982	247	10	,	,	PUNCT
ajst-10982	247	11	13(4	13(4	NUM
ajst-10982	247	12	):	):	PUNCT
ajst-10982	247	13	471494	471494	NUM
ajst-10982	247	14	.	.	PUNCT
ajst-10982	248	1	[	[	X
ajst-10982	248	2	32	32	NUM
ajst-10982	248	3	]	]	PUNCT
ajst-10982	248	4	felzenszwalb	felzenszwalb	NOUN
ajst-10982	248	5	p	p	PROPN
ajst-10982	248	6	f	f	NOUN
ajst-10982	248	7	,	,	PUNCT
ajst-10982	248	8	huttenlocher	huttenlocher	ADJ
ajst-10982	248	9	d	d	PROPN
ajst-10982	248	10	p.	p.	NOUN
ajst-10982	248	11	efficient	efficient	ADJ
ajst-10982	248	12	graph	graph	NOUN
ajst-10982	248	13	-	-	PUNCT
ajst-10982	248	14	based	base	VERB
ajst-10982	248	15	image	image	NOUN
ajst-10982	248	16	segmentation[j	segmentation[j	PROPN
ajst-10982	248	17	]	]	PUNCT
ajst-10982	248	18	.	.	PUNCT
ajst-10982	249	1	international	international	ADJ
ajst-10982	249	2	journal	journal	PROPN
ajst-10982	249	3	of	of	ADP
ajst-10982	249	4	computer	computer	NOUN
ajst-10982	249	5	vision	vision	NOUN
ajst-10982	249	6	,	,	PUNCT
ajst-10982	249	7	2004	2004	NUM
ajst-10982	249	8	,	,	PUNCT
ajst-10982	249	9	59(2	59(2	NUM
ajst-10982	249	10	):	):	PUNCT
ajst-10982	249	11	167–181	167–181	NUM
ajst-10982	249	12	.	.	PUNCT
ajst-10982	250	1	[	[	X
ajst-10982	250	2	33	33	NUM
ajst-10982	250	3	]	]	X
ajst-10982	250	4	otsu	otsu	PROPN
ajst-10982	250	5	n.	n.	NOUN
ajst-10982	250	6	a	a	DET
ajst-10982	250	7	threshold	threshold	NOUN
ajst-10982	250	8	selection	selection	NOUN
ajst-10982	250	9	method	method	NOUN
ajst-10982	250	10	from	from	ADP
ajst-10982	250	11	gray	gray	ADJ
ajst-10982	250	12	-	-	PUNCT
ajst-10982	250	13	level	level	NOUN
ajst-10982	250	14	histograms[j	histograms[j	NOUN
ajst-10982	250	15	]	]	PUNCT
ajst-10982	250	16	.	.	PUNCT
ajst-10982	251	1	ieee	ieee	NOUN
ajst-10982	251	2	transactions	transaction	NOUN
ajst-10982	251	3	on	on	ADP
ajst-10982	251	4	systems	system	NOUN
ajst-10982	251	5	,	,	PUNCT
ajst-10982	251	6	man	man	NOUN
ajst-10982	251	7	,	,	PUNCT
ajst-10982	251	8	and	and	CCONJ
ajst-10982	251	9	cybernetics	cybernetic	NOUN
ajst-10982	251	10	,	,	PUNCT
ajst-10982	251	11	1979	1979	NUM
ajst-10982	251	12	,	,	PUNCT
ajst-10982	251	13	9(1	9(1	NUM
ajst-10982	251	14	):	):	PUNCT
ajst-10982	251	15	62	62	NUM
ajst-10982	251	16	-	-	SYM
ajst-10982	251	17	66	66	NUM
ajst-10982	251	18	.	.	PUNCT
ajst-10982	252	1	[	[	X
ajst-10982	252	2	34	34	NUM
ajst-10982	252	3	]	]	PUNCT
ajst-10982	252	4	niblack	niblack	NOUN
ajst-10982	252	5	w.	w.	PROPN
ajst-10982	252	6	an	an	DET
ajst-10982	252	7	introduction	introduction	NOUN
ajst-10982	252	8	to	to	ADP
ajst-10982	252	9	digital	digital	ADJ
ajst-10982	252	10	image	image	NOUN
ajst-10982	252	11	processing[m	processing[m	NOUN
ajst-10982	252	12	]	]	PUNCT
ajst-10982	252	13	.	.	PUNCT
ajst-10982	253	1	strandberg	strandberg	PROPN
ajst-10982	253	2	publishing	publishing	PROPN
ajst-10982	253	3	company	company	NOUN
ajst-10982	253	4	,	,	PUNCT
ajst-10982	253	5	1985	1985	NUM
ajst-10982	253	6	.	.	PUNCT
ajst-10982	254	1	[	[	X
ajst-10982	254	2	35	35	NUM
ajst-10982	254	3	]	]	X
ajst-10982	254	4	mallat	mallat	PROPN
ajst-10982	254	5	s.	s.	PROPN
ajst-10982	254	6	a	a	DET
ajst-10982	254	7	wavelet	wavelet	NOUN
ajst-10982	254	8	tour	tour	NOUN
ajst-10982	254	9	of	of	ADP
ajst-10982	254	10	signal	signal	ADJ
ajst-10982	254	11	processing[m	processing[m	NOUN
ajst-10982	254	12	]	]	PUNCT
ajst-10982	254	13	.	.	PUNCT
ajst-10982	255	1	elsevier	elsevier	NOUN
ajst-10982	255	2	,	,	PUNCT
ajst-10982	255	3	1999	1999	NUM
ajst-10982	255	4	.	.	PUNCT
ajst-10982	256	1	[	[	X
ajst-10982	256	2	36	36	NUM
ajst-10982	256	3	]	]	X
ajst-10982	256	4	sain	sain	PROPN
ajst-10982	256	5	s	s	PROPN
ajst-10982	256	6	r.	r.	NOUN
ajst-10982	256	7	the	the	DET
ajst-10982	256	8	nature	nature	NOUN
ajst-10982	256	9	of	of	ADP
ajst-10982	256	10	statistical	statistical	ADJ
ajst-10982	256	11	learning	learning	NOUN
ajst-10982	256	12	theory[j	theory[j	NOUN
ajst-10982	256	13	]	]	PUNCT
ajst-10982	256	14	.	.	PUNCT
ajst-10982	257	1	1996	1996	NUM
ajst-10982	257	2	.	.	PUNCT
ajst-10982	258	1	[	[	X
ajst-10982	258	2	37	37	NUM
ajst-10982	258	3	]	]	X
ajst-10982	258	4	quinlan	quinlan	PROPN
ajst-10982	258	5	j	j	PROPN
ajst-10982	258	6	r.	r.	PROPN
ajst-10982	258	7	c4	c4	PROPN
ajst-10982	258	8	.	.	PUNCT
ajst-10982	259	1	5	5	NUM
ajst-10982	259	2	:	:	PUNCT
ajst-10982	259	3	programs	program	NOUN
ajst-10982	259	4	for	for	ADP
ajst-10982	259	5	machine	machine	NOUN
ajst-10982	259	6	learning[m	learning[m	PROPN
ajst-10982	259	7	]	]	PUNCT
ajst-10982	259	8	.	.	PUNCT
ajst-10982	260	1	elsevier	elsevier	NOUN
ajst-10982	260	2	,	,	PUNCT
ajst-10982	260	3	2014	2014	NUM
ajst-10982	260	4	.	.	PUNCT
ajst-10982	261	1	[	[	X
ajst-10982	261	2	38	38	NUM
ajst-10982	261	3	]	]	PUNCT
ajst-10982	261	4	jain	jain	NOUN
ajst-10982	261	5	a	a	DET
ajst-10982	261	6	k	k	PROPN
ajst-10982	261	7	,	,	PUNCT
ajst-10982	261	8	murty	murty	PROPN
ajst-10982	261	9	m	m	PROPN
ajst-10982	261	10	n	n	NOUN
ajst-10982	261	11	,	,	PUNCT
ajst-10982	261	12	flynn	flynn	PROPN
ajst-10982	261	13	p	p	PROPN
ajst-10982	261	14	j.	j.	PROPN
ajst-10982	261	15	data	data	PROPN
ajst-10982	261	16	clustering	cluster	VERB
ajst-10982	261	17	:	:	PUNCT
ajst-10982	261	18	a	a	DET
ajst-10982	261	19	review[j	review[j	PROPN
ajst-10982	261	20	]	]	PUNCT
ajst-10982	261	21	.	.	PUNCT
ajst-10982	262	1	acm	acm	PROPN
ajst-10982	262	2	computing	computing	NOUN
ajst-10982	262	3	surveys	survey	NOUN
ajst-10982	262	4	(	(	PUNCT
ajst-10982	262	5	csur	csur	NOUN
ajst-10982	262	6	)	)	PUNCT
ajst-10982	262	7	,	,	PUNCT
ajst-10982	262	8	1999	1999	NUM
ajst-10982	262	9	,	,	PUNCT
ajst-10982	262	10	31(3	31(3	NUM
ajst-10982	262	11	):	):	PUNCT
ajst-10982	262	12	264	264	NUM
ajst-10982	262	13	-	-	SYM
ajst-10982	262	14	323	323	NUM
ajst-10982	262	15	.	.	PUNCT
ajst-10982	262	16	30	30	NUM
ajst-10982	263	1	[	[	SYM
ajst-10982	263	2	39	39	NUM
ajst-10982	263	3	]	]	PUNCT
ajst-10982	263	4	lecun	lecun	PROPN
ajst-10982	263	5	y	y	PROPN
ajst-10982	263	6	,	,	PUNCT
ajst-10982	263	7	bottou	bottou	PROPN
ajst-10982	263	8	l	l	PROPN
ajst-10982	263	9	,	,	PUNCT
ajst-10982	263	10	bengio	bengio	PROPN
ajst-10982	263	11	y	y	PROPN
ajst-10982	263	12	,	,	PUNCT
ajst-10982	263	13	et	et	PROPN
ajst-10982	263	14	al	al	PROPN
ajst-10982	263	15	.	.	PUNCT
ajst-10982	263	16	gradient	gradient	NOUN
ajst-10982	263	17	-	-	PUNCT
ajst-10982	263	18	based	base	VERB
ajst-10982	263	19	learning	learning	NOUN
ajst-10982	263	20	applied	apply	VERB
ajst-10982	263	21	to	to	ADP
ajst-10982	263	22	document	document	NOUN
ajst-10982	263	23	recognition[j	recognition[j	NOUN
ajst-10982	263	24	]	]	PUNCT
ajst-10982	263	25	.	.	PUNCT
ajst-10982	264	1	proceedings	proceeding	NOUN
ajst-10982	264	2	of	of	ADP
ajst-10982	264	3	the	the	DET
ajst-10982	264	4	ieee	ieee	NOUN
ajst-10982	264	5	,	,	PUNCT
ajst-10982	264	6	1998	1998	NUM
ajst-10982	264	7	,	,	PUNCT
ajst-10982	264	8	86(11	86(11	NUM
ajst-10982	264	9	):	):	PUNCT
ajst-10982	264	10	2278	2278	NUM
ajst-10982	264	11	-	-	SYM
ajst-10982	264	12	2324	2324	NUM
ajst-10982	264	13	.	.	PUNCT
ajst-10982	265	1	[	[	X
ajst-10982	265	2	40	40	NUM
ajst-10982	265	3	]	]	X
ajst-10982	265	4	long	long	PROPN
ajst-10982	265	5	j	j	PROPN
ajst-10982	265	6	,	,	PUNCT
ajst-10982	265	7	shelhamer	shelhamer	NOUN
ajst-10982	265	8	e	e	NOUN
ajst-10982	265	9	,	,	PUNCT
ajst-10982	265	10	darrell	darrell	PROPN
ajst-10982	265	11	t.	t.	PROPN
ajst-10982	265	12	fully	fully	ADV
ajst-10982	265	13	convolutional	convolutional	ADJ
ajst-10982	265	14	networks	network	NOUN
ajst-10982	265	15	for	for	ADP
ajst-10982	265	16	semantic	semantic	ADJ
ajst-10982	265	17	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-10982	265	18	of	of	ADP
ajst-10982	265	19	the	the	DET
ajst-10982	265	20	ieee	ieee	NOUN
ajst-10982	265	21	conference	conference	NOUN
ajst-10982	265	22	on	on	ADP
ajst-10982	265	23	computer	computer	NOUN
ajst-10982	265	24	vision	vision	NOUN
ajst-10982	265	25	and	and	CCONJ
ajst-10982	265	26	pattern	pattern	NOUN
ajst-10982	265	27	recognition	recognition	NOUN
ajst-10982	265	28	.	.	PUNCT
ajst-10982	266	1	2015	2015	NUM
ajst-10982	266	2	:	:	PUNCT
ajst-10982	266	3	3431	3431	NUM
ajst-10982	266	4	-	-	SYM
ajst-10982	266	5	3440	3440	NUM
ajst-10982	266	6	.	.	PUNCT
ajst-10982	267	1	[	[	X
ajst-10982	267	2	41	41	NUM
ajst-10982	267	3	]	]	X
ajst-10982	267	4	krizhevsky	krizhevsky	NOUN
ajst-10982	267	5	a	a	PROPN
ajst-10982	267	6	,	,	PUNCT
ajst-10982	267	7	sutskever	sutskever	VERB
ajst-10982	267	8	i	i	PRON
ajst-10982	267	9	,	,	PUNCT
ajst-10982	267	10	hinton	hinton	PROPN
ajst-10982	267	11	g	g	PROPN
ajst-10982	267	12	e.	e.	PROPN
ajst-10982	267	13	imagenet	imagenet	PROPN
ajst-10982	267	14	classification	classification	NOUN
ajst-10982	267	15	with	with	ADP
ajst-10982	267	16	deep	deep	ADJ
ajst-10982	267	17	convolutional	convolutional	ADJ
ajst-10982	267	18	neural	neural	ADJ
ajst-10982	267	19	networks[j	networks[j	NOUN
ajst-10982	267	20	]	]	X
ajst-10982	267	21	.	.	PUNCT
ajst-10982	268	1	communications	communication	NOUN
ajst-10982	268	2	of	of	ADP
ajst-10982	268	3	the	the	DET
ajst-10982	268	4	acm	acm	NOUN
ajst-10982	268	5	,	,	PUNCT
ajst-10982	268	6	2017	2017	NUM
ajst-10982	268	7	,	,	PUNCT
ajst-10982	268	8	60(6	60(6	NOUN
ajst-10982	268	9	):	):	PUNCT
ajst-10982	268	10	84	84	NUM
ajst-10982	268	11	-	-	SYM
ajst-10982	268	12	90	90	NUM
ajst-10982	268	13	.	.	PUNCT
ajst-10982	269	1	[	[	X
ajst-10982	269	2	42	42	NUM
ajst-10982	269	3	]	]	X
ajst-10982	269	4	tao	tao	PROPN
ajst-10982	269	5	w	w	PROPN
ajst-10982	269	6	a	a	PROPN
ajst-10982	269	7	,	,	PUNCT
ajst-10982	269	8	mrb	mrb	PROPN
ajst-10982	269	9	c	c	PROPN
ajst-10982	269	10	,	,	PUNCT
ajst-10982	269	11	zs	zs	PROPN
ajst-10982	269	12	d	d	PROPN
ajst-10982	269	13	,	,	PUNCT
ajst-10982	269	14	et	et	PROPN
ajst-10982	269	15	al	al	PROPN
ajst-10982	269	16	.	.	PUNCT
ajst-10982	269	17	segroot	segroot	PROPN
ajst-10982	269	18	:	:	PUNCT
ajst-10982	269	19	a	a	DET
ajst-10982	269	20	high	high	ADJ
ajst-10982	269	21	throughput	throughput	NOUN
ajst-10982	269	22	segmentation	segmentation	NOUN
ajst-10982	269	23	method	method	NOUN
ajst-10982	269	24	for	for	ADP
ajst-10982	269	25	root	root	NOUN
ajst-10982	269	26	image	image	NOUN
ajst-10982	269	27	analysis[j	analysis[j	PROPN
ajst-10982	269	28	]	]	PUNCT
ajst-10982	269	29	.	.	PUNCT
ajst-10982	270	1	computers	computer	NOUN
ajst-10982	270	2	and	and	CCONJ
ajst-10982	270	3	electronics	electronic	NOUN
ajst-10982	270	4	in	in	ADP
ajst-10982	270	5	agriculture	agriculture	NOUN
ajst-10982	270	6	,	,	PUNCT
ajst-10982	270	7	2019	2019	NUM
ajst-10982	270	8	,	,	PUNCT
ajst-10982	270	9	162:845	162:845	NOUN
ajst-10982	270	10	-	-	PUNCT
ajst-10982	270	11	854	854	NUM
ajst-10982	270	12	.	.	PUNCT
ajst-10982	271	1	[	[	X
ajst-10982	271	2	43	43	NUM
ajst-10982	271	3	]	]	X
ajst-10982	271	4	zhao	zhao	PROPN
ajst-10982	271	5	y	y	PROPN
ajst-10982	271	6	,	,	PUNCT
ajst-10982	271	7	wandel	wandel	PROPN
ajst-10982	271	8	n	n	PROPN
ajst-10982	271	9	,	,	PUNCT
ajst-10982	271	10	landl	landl	VERB
ajst-10982	271	11	m	m	PRON
ajst-10982	271	12	,	,	PUNCT
ajst-10982	271	13	et	et	PROPN
ajst-10982	271	14	al	al	PROPN
ajst-10982	271	15	.	.	PROPN
ajst-10982	272	1	3d	3d	NUM
ajst-10982	272	2	u	u	NOUN
ajst-10982	272	3	-	-	NOUN
ajst-10982	272	4	net	net	ADJ
ajst-10982	272	5	for	for	ADP
ajst-10982	272	6	segmentation	segmentation	NOUN
ajst-10982	272	7	of	of	ADP
ajst-10982	272	8	plant	plant	NOUN
ajst-10982	272	9	root	root	NOUN
ajst-10982	272	10	mri	mri	NOUN
ajst-10982	272	11	images	image	NOUN
ajst-10982	272	12	in	in	ADP
ajst-10982	272	13	super	super	NOUN
ajst-10982	272	14	-	-	ADJ
ajst-10982	272	15	resolution[j	resolution[j	NUM
ajst-10982	272	16	]	]	PUNCT
ajst-10982	272	17	.	.	PUNCT
ajst-10982	273	1	arxiv	arxiv	PROPN
ajst-10982	273	2	preprint	preprint	VERB
ajst-10982	273	3	arxiv:2002.09317	arxiv:2002.09317	NOUN
ajst-10982	273	4	,	,	PUNCT
ajst-10982	273	5	2020	2020	NUM
ajst-10982	273	6	.	.	PUNCT
ajst-10982	274	1	[	[	X
ajst-10982	274	2	44	44	NUM
ajst-10982	274	3	]	]	SYM
ajst-10982	274	4	seidenthal	seidenthal	PROPN
ajst-10982	274	5	k	k	PROPN
ajst-10982	274	6	,	,	PUNCT
ajst-10982	274	7	panjvani	panjvani	PROPN
ajst-10982	274	8	k	k	PROPN
ajst-10982	274	9	,	,	PUNCT
ajst-10982	274	10	chandnani	chandnani	ADJ
ajst-10982	274	11	r	r	NOUN
ajst-10982	274	12	,	,	PUNCT
ajst-10982	274	13	et	et	PROPN
ajst-10982	274	14	al	al	PROPN
ajst-10982	274	15	.	.	PROPN
ajst-10982	274	16	iterative	iterative	PROPN
ajst-10982	274	17	image	image	NOUN
ajst-10982	274	18	segmentation	segmentation	NOUN
ajst-10982	274	19	of	of	ADP
ajst-10982	274	20	plant	plant	NOUN
ajst-10982	274	21	roots	root	NOUN
ajst-10982	274	22	for	for	ADP
ajst-10982	274	23	high	high	ADJ
ajst-10982	274	24	-	-	PUNCT
ajst-10982	274	25	throughput	throughput	NOUN
ajst-10982	274	26	phenotyping[j	phenotyping[j	NOUN
ajst-10982	274	27	]	]	PUNCT
ajst-10982	274	28	.	.	PUNCT
ajst-10982	275	1	scientific	scientific	ADJ
ajst-10982	275	2	reports	report	NOUN
ajst-10982	275	3	,	,	PUNCT
ajst-10982	275	4	2022	2022	NUM
ajst-10982	275	5	,	,	PUNCT
ajst-10982	275	6	12(1	12(1	NUM
ajst-10982	275	7	):	):	PUNCT
ajst-10982	275	8	16563	16563	NUM
ajst-10982	275	9	.	.	PUNCT
ajst-10982	276	1	[	[	X
ajst-10982	276	2	45	45	NUM
ajst-10982	276	3	]	]	X
ajst-10982	276	4	kang	kang	PROPN
ajst-10982	276	5	j	j	PROPN
ajst-10982	276	6	,	,	PUNCT
ajst-10982	276	7	liu	liu	PROPN
ajst-10982	276	8	l	l	PROPN
ajst-10982	276	9	,	,	PUNCT
ajst-10982	276	10	zhang	zhang	PROPN
ajst-10982	277	1	f	f	PROPN
ajst-10982	277	2	,	,	PUNCT
ajst-10982	277	3	et	et	PROPN
ajst-10982	277	4	al	al	PROPN
ajst-10982	277	5	.	.	PUNCT
ajst-10982	277	6	semantic	semantic	ADJ
ajst-10982	277	7	segmentation	segmentation	NOUN
ajst-10982	277	8	model	model	NOUN
ajst-10982	277	9	of	of	ADP
ajst-10982	277	10	cotton	cotton	NOUN
ajst-10982	277	11	roots	root	NOUN
ajst-10982	277	12	in	in	ADP
ajst-10982	277	13	-	-	PUNCT
ajst-10982	277	14	situ	situ	NOUN
ajst-10982	277	15	image	image	NOUN
ajst-10982	277	16	based	base	VERB
ajst-10982	277	17	on	on	ADP
ajst-10982	277	18	attention	attention	NOUN
ajst-10982	277	19	mechanism[j	mechanism[j	PROPN
ajst-10982	277	20	]	]	PUNCT
ajst-10982	277	21	.	.	PUNCT
ajst-10982	278	1	computers	computer	NOUN
ajst-10982	278	2	and	and	CCONJ
ajst-10982	278	3	electronics	electronic	NOUN
ajst-10982	278	4	in	in	ADP
ajst-10982	278	5	agriculture	agriculture	NOUN
ajst-10982	278	6	,	,	PUNCT
ajst-10982	278	7	2021	2021	NUM
ajst-10982	278	8	,	,	PUNCT
ajst-10982	278	9	189	189	NUM
ajst-10982	278	10	:	:	SYM
ajst-10982	278	11	106370	106370	NUM
ajst-10982	278	12	.	.	PUNCT
ajst-10982	279	1	[	[	X
ajst-10982	279	2	46	46	NUM
ajst-10982	279	3	]	]	X
ajst-10982	279	4	alle	alle	PROPN
ajst-10982	279	5	j	j	PROPN
ajst-10982	279	6	,	,	PUNCT
ajst-10982	279	7	gruber	gruber	PROPN
ajst-10982	279	8	r	r	PROPN
ajst-10982	279	9	,	,	PUNCT
ajst-10982	279	10	wöhrlein	wöhrlein	ADJ
ajst-10982	279	11	n	n	CCONJ
ajst-10982	279	12	,	,	PUNCT
ajst-10982	279	13	et	et	PROPN
ajst-10982	279	14	al	al	PROPN
ajst-10982	279	15	.	.	PROPN
ajst-10982	279	16	3d	3d	NUM
ajst-10982	279	17	segmentation	segmentation	NOUN
ajst-10982	279	18	of	of	ADP
ajst-10982	279	19	plant	plant	NOUN
ajst-10982	279	20	root	root	NOUN
ajst-10982	279	21	systems	system	NOUN
ajst-10982	279	22	using	use	VERB
ajst-10982	279	23	spatial	spatial	ADJ
ajst-10982	279	24	pyramid	pyramid	NOUN
ajst-10982	279	25	pooling	pooling	NOUN
ajst-10982	279	26	and	and	CCONJ
ajst-10982	279	27	locally	locally	ADV
ajst-10982	279	28	adaptive	adaptive	ADJ
ajst-10982	279	29	field	field	NOUN
ajst-10982	279	30	-	-	PUNCT
ajst-10982	279	31	of	of	ADP
ajst-10982	279	32	-	-	PUNCT
ajst-10982	279	33	view	view	NOUN
ajst-10982	279	34	inference[j	inference[j	NOUN
ajst-10982	279	35	]	]	PUNCT
ajst-10982	279	36	.	.	PUNCT
ajst-10982	280	1	frontiers	frontier	NOUN
ajst-10982	280	2	in	in	ADP
ajst-10982	280	3	plant	plant	NOUN
ajst-10982	280	4	science	science	NOUN
ajst-10982	280	5	,	,	PUNCT
ajst-10982	280	6	2023	2023	NUM
ajst-10982	280	7	,	,	PUNCT
ajst-10982	280	8	14	14	NUM
ajst-10982	280	9	:	:	SYM
ajst-10982	280	10	1055	1055	NUM
ajst-10982	280	11	.	.	PUNCT
ajst-10982	281	1	[	[	X
ajst-10982	281	2	47	47	NUM
ajst-10982	281	3	]	]	X
ajst-10982	281	4	shi	shi	PROPN
ajst-10982	281	5	w	w	PROPN
ajst-10982	281	6	,	,	PUNCT
ajst-10982	281	7	caballero	caballero	PROPN
ajst-10982	281	8	j	j	PROPN
ajst-10982	281	9	,	,	PUNCT
ajst-10982	281	10	huszár	huszár	PROPN
ajst-10982	281	11	f	f	X
ajst-10982	281	12	,	,	PUNCT
ajst-10982	281	13	et	et	PROPN
ajst-10982	281	14	al	al	PROPN
ajst-10982	281	15	.	.	PUNCT
ajst-10982	281	16	real	real	ADJ
ajst-10982	281	17	-	-	PUNCT
ajst-10982	281	18	time	time	NOUN
ajst-10982	281	19	single	single	ADJ
ajst-10982	281	20	image	image	NOUN
ajst-10982	281	21	and	and	CCONJ
ajst-10982	281	22	video	video	NOUN
ajst-10982	281	23	super	super	NOUN
ajst-10982	281	24	-	-	NOUN
ajst-10982	281	25	resolution	resolution	NOUN
ajst-10982	281	26	using	use	VERB
ajst-10982	281	27	an	an	DET
ajst-10982	281	28	efficient	efficient	ADJ
ajst-10982	281	29	sub	sub	ADJ
ajst-10982	281	30	-	-	ADJ
ajst-10982	281	31	pixel	pixel	ADJ
ajst-10982	281	32	convolutional	convolutional	ADJ
ajst-10982	281	33	neural	neural	ADJ
ajst-10982	281	34	network[c]//proceedings	network[c]//proceeding	NOUN
ajst-10982	281	35	of	of	ADP
ajst-10982	281	36	the	the	DET
ajst-10982	281	37	ieee	ieee	NOUN
ajst-10982	281	38	conference	conference	NOUN
ajst-10982	281	39	on	on	ADP
ajst-10982	281	40	computer	computer	NOUN
ajst-10982	281	41	vision	vision	NOUN
ajst-10982	281	42	and	and	CCONJ
ajst-10982	281	43	pattern	pattern	NOUN
ajst-10982	281	44	recognition	recognition	NOUN
ajst-10982	281	45	.	.	PUNCT
ajst-10982	282	1	2016	2016	NUM
ajst-10982	282	2	:	:	PUNCT
ajst-10982	282	3	1874	1874	NUM
ajst-10982	282	4	-	-	SYM
ajst-10982	282	5	1883	1883	NUM
ajst-10982	282	6	.	.	PUNCT
ajst-10982	283	1	[	[	X
ajst-10982	283	2	48	48	NUM
ajst-10982	283	3	]	]	X
ajst-10982	283	4	huang	huang	PROPN
ajst-10982	283	5	y	y	PROPN
ajst-10982	283	6	,	,	PUNCT
ajst-10982	283	7	yan	yan	PROPN
ajst-10982	283	8	j	j	PROPN
ajst-10982	283	9	,	,	PUNCT
ajst-10982	283	10	zhang	zhang	PROPN
ajst-10982	283	11	y	y	PROPN
ajst-10982	283	12	,	,	PUNCT
ajst-10982	283	13	et	et	PROPN
ajst-10982	283	14	al	al	PROPN
ajst-10982	283	15	.	.	PROPN
ajst-10982	284	1	automatic	automatic	ADJ
ajst-10982	284	2	segmentation	segmentation	NOUN
ajst-10982	284	3	of	of	ADP
ajst-10982	284	4	cotton	cotton	NOUN
ajst-10982	284	5	roots	root	NOUN
ajst-10982	284	6	in	in	ADP
ajst-10982	284	7	high	high	ADJ
ajst-10982	284	8	-	-	PUNCT
ajst-10982	284	9	resolution	resolution	NOUN
ajst-10982	284	10	minirhizotron	minirhizotron	ADJ
ajst-10982	284	11	images	image	NOUN
ajst-10982	284	12	based	base	VERB
ajst-10982	284	13	on	on	ADP
ajst-10982	284	14	improved	improve	VERB
ajst-10982	284	15	ocrnet[j	ocrnet[j	NOUN
ajst-10982	284	16	]	]	PUNCT
ajst-10982	284	17	.	.	PUNCT
ajst-10982	285	1	frontiers	frontier	NOUN
ajst-10982	285	2	in	in	ADP
ajst-10982	285	3	plant	plant	NOUN
ajst-10982	285	4	science	science	NOUN
ajst-10982	285	5	,	,	PUNCT
ajst-10982	285	6	2023	2023	NUM
ajst-10982	285	7	,	,	PUNCT
ajst-10982	285	8	14	14	NUM
ajst-10982	285	9	.	.	PUNCT
ajst-10982	286	1	[	[	X
ajst-10982	286	2	49	49	NUM
ajst-10982	286	3	]	]	PUNCT
ajst-10982	286	4	vaswani	vaswani	NOUN
ajst-10982	286	5	a	a	PRON
ajst-10982	286	6	,	,	PUNCT
ajst-10982	286	7	shazeer	shazeer	NOUN
ajst-10982	286	8	n	n	SYM
ajst-10982	286	9	,	,	PUNCT
ajst-10982	286	10	parmar	parmar	PROPN
ajst-10982	286	11	n	n	CCONJ
ajst-10982	286	12	,	,	PUNCT
ajst-10982	286	13	et	et	PROPN
ajst-10982	286	14	al	al	PROPN
ajst-10982	286	15	.	.	PUNCT
ajst-10982	286	16	attention	attention	NOUN
ajst-10982	286	17	is	be	AUX
ajst-10982	286	18	all	all	PRON
ajst-10982	286	19	you	you	PRON
ajst-10982	286	20	need[j	need[j	VERB
ajst-10982	286	21	]	]	PUNCT
ajst-10982	286	22	.	.	PUNCT
ajst-10982	287	1	advances	advance	NOUN
ajst-10982	287	2	in	in	ADP
ajst-10982	287	3	neural	neural	ADJ
ajst-10982	287	4	information	information	NOUN
ajst-10982	287	5	processing	processing	NOUN
ajst-10982	287	6	systems	system	NOUN
ajst-10982	287	7	,	,	PUNCT
ajst-10982	287	8	2017	2017	NUM
ajst-10982	287	9	,	,	PUNCT
ajst-10982	287	10	30	30	NUM
ajst-10982	287	11	.	.	PUNCT
ajst-10982	288	1	[	[	X
ajst-10982	288	2	50	50	NUM
ajst-10982	288	3	]	]	X
ajst-10982	288	4	wu	wu	PROPN
ajst-10982	288	5	lan	lan	PROPN
ajst-10982	288	6	,	,	PUNCT
ajst-10982	288	7	su	su	PROPN
ajst-10982	288	8	lide	lide	PROPN
ajst-10982	288	9	,	,	PUNCT
ajst-10982	288	10	jia	jia	PROPN
ajst-10982	288	11	liguo	liguo	PROPN
ajst-10982	288	12	,	,	PUNCT
ajst-10982	288	13	qin	qin	PROPN
ajst-10982	288	14	yonglin	yonglin	PROPN
ajst-10982	288	15	,	,	PUNCT
ajst-10982	288	16	fan	fan	PROPN
ajst-10982	288	17	mingshou.potato	mingshou.potato	PROPN
ajst-10982	288	18	root	root	NOUN
ajst-10982	288	19	image	image	NOUN
ajst-10982	288	20	segmentation	segmentation	NOUN
ajst-10982	288	21	method	method	NOUN
ajst-10982	288	22	based	base	VERB
ajst-10982	288	23	on	on	ADP
ajst-10982	288	24	improved	improved	ADJ
ajst-10982	288	25	deeplabv3	deeplabv3	NOUN
ajst-10982	288	26	+	+	CCONJ
ajst-10982	288	27	network[j].journal	network[j].journal	ADJ
ajst-10982	288	28	of	of	ADP
ajst-10982	288	29	agricultural	agricultural	ADJ
ajst-10982	288	30	engineering,2023,39(03):134	engineering,2023,39(03):134	PROPN
ajst-10982	288	31	-	-	SYM
ajst-10982	288	32	144	144	NUM
ajst-10982	288	33	.	.	PUNCT
ajst-10982	289	1	[	[	X
ajst-10982	289	2	51	51	NUM
ajst-10982	289	3	]	]	X
ajst-10982	289	4	firdaus	firdaus	PROPN
ajst-10982	289	5	-	-	PUNCT
ajst-10982	289	6	nawi	nawi	PROPN
ajst-10982	289	7	m	m	PROPN
ajst-10982	289	8	,	,	PUNCT
ajst-10982	289	9	noraini	noraini	ADJ
ajst-10982	289	10	o	o	NOUN
ajst-10982	289	11	,	,	PUNCT
ajst-10982	290	1	sabri	sabri	PROPN
ajst-10982	290	2	m	m	PROPN
ajst-10982	290	3	y	y	PROPN
ajst-10982	290	4	,	,	PUNCT
ajst-10982	290	5	et	et	PROPN
ajst-10982	290	6	al	al	PROPN
ajst-10982	290	7	.	.	PUNCT
ajst-10982	291	1	deeplabv3	deeplabv3	PROPN
ajst-10982	292	1	+	+	X
ajst-10982	292	2	_	_	PRON
ajst-10982	292	3	encoder	encoder	NOUN
ajst-10982	292	4	-	-	PUNCT
ajst-10982	292	5	decoder	decoder	NOUN
ajst-10982	292	6	with	with	ADP
ajst-10982	292	7	atrous	atrous	ADJ
ajst-10982	292	8	separable	separable	ADJ
ajst-10982	292	9	convolution	convolution	NOUN
ajst-10982	292	10	for	for	ADP
ajst-10982	292	11	semantic	semantic	ADJ
ajst-10982	292	12	image	image	NOUN
ajst-10982	292	13	segmentation[j	segmentation[j	PROPN
ajst-10982	292	14	]	]	PUNCT
ajst-10982	292	15	.	.	PUNCT
ajst-10982	293	1	pertanika	pertanika	PROPN
ajst-10982	293	2	j.	j.	PROPN
ajst-10982	293	3	trop	trop	PROPN
ajst-10982	293	4	.	.	PUNCT
ajst-10982	294	1	agric	agric	PROPN
ajst-10982	294	2	.	.	PUNCT
ajst-10982	295	1	sci	sci	PROPN
ajst-10982	295	2	,	,	PUNCT
ajst-10982	295	3	2011	2011	NUM
ajst-10982	295	4	,	,	PUNCT
ajst-10982	295	5	34(1	34(1	NUM
ajst-10982	295	6	):	):	PUNCT
ajst-10982	295	7	137	137	NUM
ajst-10982	295	8	-	-	SYM
ajst-10982	295	9	143	143	NUM
ajst-10982	295	10	.	.	PUNCT
ajst-10982	296	1	[	[	X
ajst-10982	296	2	52	52	NUM
ajst-10982	296	3	]	]	PUNCT
ajst-10982	296	4	yasrab	yasrab	NOUN
ajst-10982	296	5	r	r	NOUN
ajst-10982	296	6	,	,	PUNCT
ajst-10982	296	7	atkinson	atkinson	PROPN
ajst-10982	296	8	j	j	PROPN
ajst-10982	296	9	a	a	PROPN
ajst-10982	296	10	,	,	PUNCT
ajst-10982	296	11	wells	wells	PROPN
ajst-10982	296	12	d	d	PROPN
ajst-10982	296	13	m	m	PROPN
ajst-10982	296	14	,	,	PUNCT
ajst-10982	296	15	et	et	PROPN
ajst-10982	296	16	al	al	PROPN
ajst-10982	296	17	.	.	PROPN
ajst-10982	296	18	rootnav	rootnav	PROPN
ajst-10982	296	19	2.0	2.0	NUM
ajst-10982	296	20	:	:	PUNCT
ajst-10982	296	21	deep	deep	ADJ
ajst-10982	296	22	learning	learning	NOUN
ajst-10982	296	23	for	for	ADP
ajst-10982	296	24	automatic	automatic	ADJ
ajst-10982	296	25	navigation	navigation	NOUN
ajst-10982	296	26	of	of	ADP
ajst-10982	296	27	complex	complex	ADJ
ajst-10982	296	28	plant	plant	NOUN
ajst-10982	296	29	root	root	NOUN
ajst-10982	296	30	architectures[j	architectures[j	PROPN
ajst-10982	296	31	]	]	PUNCT
ajst-10982	296	32	.	.	PUNCT
ajst-10982	297	1	gigascience	gigascience	NOUN
ajst-10982	297	2	,	,	PUNCT
ajst-10982	297	3	2019	2019	NUM
ajst-10982	297	4	,	,	PUNCT
ajst-10982	297	5	8(11	8(11	NUM
ajst-10982	297	6	):	):	PUNCT
ajst-10982	297	7	giz123	giz123	PROPN
ajst-10982	297	8	.	.	PUNCT
ajst-10982	298	1	[	[	X
ajst-10982	298	2	53	53	NUM
ajst-10982	298	3	]	]	PUNCT
ajst-10982	298	4	yu	yu	PROPN
ajst-10982	298	5	q	q	PROPN
ajst-10982	298	6	,	,	PUNCT
ajst-10982	298	7	tang	tang	PROPN
ajst-10982	298	8	h	h	PROPN
ajst-10982	298	9	y	y	PROPN
ajst-10982	298	10	,	,	PUNCT
ajst-10982	298	11	zhu	zhu	PROPN
ajst-10982	298	12	l	l	PROPN
ajst-10982	299	1	q	q	X
ajst-10982	299	2	,	,	PUNCT
ajst-10982	299	3	zhang	zhang	PROPN
ajst-10982	299	4	w	w	PROPN
ajst-10982	299	5	,	,	PUNCT
ajst-10982	299	6	liu	liu	PROPN
ajst-10982	299	7	l	l	PROPN
ajst-10982	299	8	n	n	CCONJ
ajst-10982	299	9	,	,	PUNCT
ajst-10982	299	10	wang	wang	PROPN
ajst-10982	299	11	n.	n.	PROPN
ajst-10982	299	12	a	a	DET
ajst-10982	299	13	method	method	NOUN
ajst-10982	299	14	of	of	ADP
ajst-10982	299	15	cotton	cotton	NOUN
ajst-10982	299	16	root	root	NOUN
ajst-10982	299	17	segmentation	segmentation	NOUN
ajst-10982	299	18	based	base	VERB
ajst-10982	299	19	on	on	ADP
ajst-10982	299	20	edge	edge	NOUN
ajst-10982	299	21	devices	device	NOUN
ajst-10982	299	22	.	.	PUNCT
ajst-10982	300	1	frontiers	frontier	NOUN
ajst-10982	300	2	in	in	ADP
ajst-10982	300	3	plant	plant	NOUN
ajst-10982	300	4	science	science	NOUN
ajst-10982	300	5	,	,	PUNCT
ajst-10982	300	6	2023	2023	NUM
ajst-10982	300	7	,	,	PUNCT
ajst-10982	300	8	14	14	NUM
ajst-10982	300	9	:	:	SYM
ajst-10982	300	10	550	550	NUM
ajst-10982	300	11	.	.	PUNCT
ajst-10982	301	1	[	[	X
ajst-10982	301	2	54	54	NUM
ajst-10982	301	3	]	]	PUNCT
ajst-10982	301	4	ronneberger	ronneberger	NOUN
ajst-10982	301	5	o	o	NOUN
ajst-10982	301	6	,	,	PUNCT
ajst-10982	301	7	fischer	fischer	PROPN
ajst-10982	301	8	p	p	PROPN
ajst-10982	301	9	,	,	PUNCT
ajst-10982	301	10	brox	brox	PROPN
ajst-10982	301	11	t.	t.	PROPN
ajst-10982	301	12	u	u	PROPN
ajst-10982	301	13	-	-	NOUN
ajst-10982	301	14	net	net	ADJ
ajst-10982	301	15	:	:	PUNCT
ajst-10982	301	16	convolutional	convolutional	ADJ
ajst-10982	301	17	networks	network	NOUN
ajst-10982	301	18	for	for	ADP
ajst-10982	301	19	biomedical	biomedical	ADJ
ajst-10982	301	20	image	image	NOUN
ajst-10982	301	21	segmentation[c]//medical	segmentation[c]//medical	ADJ
ajst-10982	301	22	image	image	NOUN
ajst-10982	301	23	computing	computing	NOUN
ajst-10982	301	24	and	and	CCONJ
ajst-10982	301	25	computer	computer	NOUN
ajst-10982	301	26	-	-	PUNCT
ajst-10982	301	27	assisted	assist	VERB
ajst-10982	301	28	intervention	intervention	NOUN
ajst-10982	301	29	–	–	PUNCT
ajst-10982	301	30	miccai	miccai	NOUN
ajst-10982	301	31	2015	2015	NUM
ajst-10982	301	32	:	:	PUNCT
ajst-10982	301	33	18th	18th	ADJ
ajst-10982	301	34	international	international	ADJ
ajst-10982	301	35	conference	conference	NOUN
ajst-10982	301	36	,	,	PUNCT
ajst-10982	301	37	munich	munich	PROPN
ajst-10982	301	38	,	,	PUNCT
ajst-10982	301	39	germany	germany	PROPN
ajst-10982	301	40	,	,	PUNCT
ajst-10982	301	41	october	october	PROPN
ajst-10982	301	42	5	5	NUM
ajst-10982	301	43	-	-	SYM
ajst-10982	301	44	9	9	NUM
ajst-10982	301	45	,	,	PUNCT
ajst-10982	301	46	2015	2015	NUM
ajst-10982	301	47	,	,	PUNCT
ajst-10982	301	48	proceedings	proceeding	NOUN
ajst-10982	301	49	,	,	PUNCT
ajst-10982	301	50	part	part	NOUN
ajst-10982	301	51	iii	iii	NUM
ajst-10982	301	52	18	18	NUM
ajst-10982	301	53	.	.	PUNCT
ajst-10982	301	54	springer	springer	NOUN
ajst-10982	301	55	international	international	ADJ
ajst-10982	301	56	publishing	publishing	NOUN
ajst-10982	301	57	,	,	PUNCT
ajst-10982	301	58	2015	2015	NUM
ajst-10982	301	59	:	:	PUNCT
ajst-10982	301	60	234	234	NUM
ajst-10982	301	61	-	-	SYM
ajst-10982	301	62	241	241	NUM
ajst-10982	301	63	.	.	PUNCT
ajst-10982	302	1	[	[	X
ajst-10982	302	2	55	55	NUM
ajst-10982	302	3	]	]	X
ajst-10982	302	4	chen	chen	PROPN
ajst-10982	302	5	l	l	PROPN
ajst-10982	302	6	c	c	PROPN
ajst-10982	302	7	,	,	PUNCT
ajst-10982	302	8	papandreou	papandreou	ADV
ajst-10982	302	9	g	g	NOUN
ajst-10982	302	10	,	,	PUNCT
ajst-10982	302	11	kokkinos	kokkinos	PROPN
ajst-10982	302	12	i	i	PRON
ajst-10982	302	13	,	,	PUNCT
ajst-10982	302	14	et	et	PROPN
ajst-10982	302	15	al	al	PROPN
ajst-10982	302	16	.	.	PUNCT
ajst-10982	303	1	deeplab	deeplab	PROPN
ajst-10982	303	2	:	:	PUNCT
ajst-10982	303	3	semantic	semantic	ADJ
ajst-10982	303	4	image	image	NOUN
ajst-10982	303	5	segmentation	segmentation	NOUN
ajst-10982	303	6	with	with	ADP
ajst-10982	303	7	deep	deep	ADJ
ajst-10982	303	8	convolutional	convolutional	ADJ
ajst-10982	303	9	nets	net	NOUN
ajst-10982	303	10	,	,	PUNCT
ajst-10982	303	11	atrous	atrous	ADJ
ajst-10982	303	12	convolution	convolution	NOUN
ajst-10982	303	13	,	,	PUNCT
ajst-10982	303	14	and	and	CCONJ
ajst-10982	303	15	fully	fully	ADV
ajst-10982	303	16	connected	connected	ADJ
ajst-10982	303	17	crfs[j	crfs[j	NOUN
ajst-10982	303	18	]	]	PUNCT
ajst-10982	303	19	.	.	PUNCT
ajst-10982	304	1	ieee	ieee	NOUN
ajst-10982	304	2	transactions	transaction	NOUN
ajst-10982	304	3	on	on	ADP
ajst-10982	304	4	pattern	pattern	NOUN
ajst-10982	304	5	analysis	analysis	NOUN
ajst-10982	304	6	and	and	CCONJ
ajst-10982	304	7	machine	machine	NOUN
ajst-10982	304	8	intelligence	intelligence	NOUN
ajst-10982	304	9	,	,	PUNCT
ajst-10982	304	10	2017	2017	NUM
ajst-10982	304	11	,	,	PUNCT
ajst-10982	304	12	40(4	40(4	NUM
ajst-10982	304	13	):	):	PUNCT
ajst-10982	304	14	834848	834848	NUM
ajst-10982	304	15	.	.	PUNCT