id	sid	tid	token	lemma	pos
ajst-10983	1	1	academic	academic	ADJ
ajst-10983	1	2	journal	journal	NOUN
ajst-10983	1	3	of	of	ADP
ajst-10983	1	4	science	science	NOUN
ajst-10983	1	5	and	and	CCONJ
ajst-10983	1	6	technology	technology	NOUN
ajst-10983	1	7	issn	issn	NOUN
ajst-10983	1	8	:	:	PUNCT
ajst-10983	1	9	2771	2771	NUM
ajst-10983	1	10	-	-	SYM
ajst-10983	1	11	3032	3032	NUM
ajst-10983	1	12	|	|	NOUN
ajst-10983	1	13	vol	vol	NOUN
ajst-10983	1	14	.	.	PROPN
ajst-10983	2	1	7	7	NUM
ajst-10983	2	2	,	,	PUNCT
ajst-10983	2	3	no	no	INTJ
ajst-10983	2	4	.	.	NOUN
ajst-10983	2	5	1	1	NUM
ajst-10983	2	6	,	,	PUNCT
ajst-10983	2	7	2023	2023	NUM
ajst-10983	2	8	25	25	NUM
ajst-10983	2	9	a	a	DET
ajst-10983	2	10	review	review	NOUN
ajst-10983	2	11	of	of	ADP
ajst-10983	2	12	deep	deep	ADJ
ajst-10983	2	13	learning	learning	NOUN
ajst-10983	2	14	in	in	ADP
ajst-10983	2	15	the	the	DET
ajst-10983	2	16	field	field	NOUN
ajst-10983	2	17	of	of	ADP
ajst-10983	2	18	plant	plant	NOUN
ajst-10983	2	19	root	root	NOUN
ajst-10983	2	20	segmentation	segmentation	NOUN
ajst-10983	2	21	weichen	weichen	SCONJ
ajst-10983	2	22	liao	liao	PROPN
ajst-10983	2	23	school	school	PROPN
ajst-10983	2	24	of	of	ADP
ajst-10983	2	25	electronic	electronic	ADJ
ajst-10983	2	26	information	information	NOUN
ajst-10983	2	27	,	,	PUNCT
ajst-10983	2	28	southwest	southwest	PROPN
ajst-10983	2	29	university	university	PROPN
ajst-10983	2	30	for	for	ADP
ajst-10983	2	31	nationalities	nationality	NOUN
ajst-10983	2	32	,	,	PUNCT
ajst-10983	2	33	chengdu	chengdu	PROPN
ajst-10983	2	34	610225	610225	NUM
ajst-10983	2	35	,	,	PUNCT
ajst-10983	2	36	china	china	PROPN
ajst-10983	2	37	abstract	abstract	NOUN
ajst-10983	2	38	:	:	PUNCT
ajst-10983	2	39	plant	plant	NOUN
ajst-10983	2	40	root	root	NOUN
ajst-10983	2	41	segmentation	segmentation	NOUN
ajst-10983	2	42	is	be	AUX
ajst-10983	2	43	an	an	DET
ajst-10983	2	44	important	important	ADJ
ajst-10983	2	45	research	research	NOUN
ajst-10983	2	46	task	task	NOUN
ajst-10983	2	47	,	,	PUNCT
ajst-10983	2	48	which	which	PRON
ajst-10983	2	49	is	be	AUX
ajst-10983	2	50	of	of	ADP
ajst-10983	2	51	great	great	ADJ
ajst-10983	2	52	significance	significance	NOUN
ajst-10983	2	53	for	for	ADP
ajst-10983	2	54	understanding	understand	VERB
ajst-10983	2	55	plant	plant	NOUN
ajst-10983	2	56	growth	growth	NOUN
ajst-10983	2	57	and	and	CCONJ
ajst-10983	2	58	development	development	NOUN
ajst-10983	2	59	process	process	NOUN
ajst-10983	2	60	.	.	PUNCT
ajst-10983	3	1	deep	deep	ADJ
ajst-10983	3	2	learning	learning	NOUN
ajst-10983	3	3	has	have	AUX
ajst-10983	3	4	become	become	VERB
ajst-10983	3	5	a	a	DET
ajst-10983	3	6	research	research	NOUN
ajst-10983	3	7	direction	direction	NOUN
ajst-10983	3	8	worthy	worthy	ADJ
ajst-10983	3	9	of	of	ADP
ajst-10983	3	10	attention	attention	NOUN
ajst-10983	3	11	in	in	ADP
ajst-10983	3	12	this	this	DET
ajst-10983	3	13	field	field	NOUN
ajst-10983	3	14	.	.	PUNCT
ajst-10983	4	1	this	this	DET
ajst-10983	4	2	paper	paper	NOUN
ajst-10983	4	3	mainly	mainly	ADV
ajst-10983	4	4	introduces	introduce	VERB
ajst-10983	4	5	plant	plant	NOUN
ajst-10983	4	6	root	root	NOUN
ajst-10983	4	7	segmentation	segmentation	NOUN
ajst-10983	4	8	methods	method	NOUN
ajst-10983	4	9	based	base	VERB
ajst-10983	4	10	on	on	ADP
ajst-10983	4	11	deep	deep	ADJ
ajst-10983	4	12	learning	learning	NOUN
ajst-10983	4	13	,	,	PUNCT
ajst-10983	4	14	and	and	CCONJ
ajst-10983	4	15	reviews	review	VERB
ajst-10983	4	16	the	the	DET
ajst-10983	4	17	application	application	NOUN
ajst-10983	4	18	of	of	ADP
ajst-10983	4	19	various	various	ADJ
ajst-10983	4	20	methods	method	NOUN
ajst-10983	4	21	in	in	ADP
ajst-10983	4	22	different	different	ADJ
ajst-10983	4	23	fields	field	NOUN
ajst-10983	4	24	.	.	PUNCT
ajst-10983	5	1	the	the	DET
ajst-10983	5	2	problems	problem	NOUN
ajst-10983	5	3	of	of	ADP
ajst-10983	5	4	data	datum	NOUN
ajst-10983	5	5	quality	quality	NOUN
ajst-10983	5	6	,	,	PUNCT
ajst-10983	5	7	model	model	NOUN
ajst-10983	5	8	fitting	fitting	ADJ
ajst-10983	5	9	ability	ability	NOUN
ajst-10983	5	10	and	and	CCONJ
ajst-10983	5	11	real	real	ADJ
ajst-10983	5	12	-	-	PUNCT
ajst-10983	5	13	time	time	NOUN
ajst-10983	5	14	performance	performance	NOUN
ajst-10983	5	15	,	,	PUNCT
ajst-10983	5	16	and	and	CCONJ
ajst-10983	5	17	the	the	DET
ajst-10983	5	18	significance	significance	NOUN
ajst-10983	5	19	of	of	ADP
ajst-10983	5	20	transfer	transfer	NOUN
ajst-10983	5	21	learning	learning	NOUN
ajst-10983	5	22	,	,	PUNCT
ajst-10983	5	23	multi	multi	ADJ
ajst-10983	5	24	-	-	ADJ
ajst-10983	5	25	task	task	ADJ
ajst-10983	5	26	learning	learning	NOUN
ajst-10983	5	27	and	and	CCONJ
ajst-10983	5	28	reinforcement	reinforcement	NOUN
ajst-10983	5	29	learning	learning	NOUN
ajst-10983	5	30	in	in	ADP
ajst-10983	5	31	application	application	NOUN
ajst-10983	5	32	are	be	AUX
ajst-10983	5	33	put	put	VERB
ajst-10983	5	34	forward	forward	ADV
ajst-10983	5	35	.	.	PUNCT
ajst-10983	6	1	finally	finally	ADV
ajst-10983	6	2	,	,	PUNCT
ajst-10983	6	3	it	it	PRON
ajst-10983	6	4	is	be	AUX
ajst-10983	6	5	pointed	point	VERB
ajst-10983	6	6	out	out	ADP
ajst-10983	6	7	that	that	SCONJ
ajst-10983	6	8	future	future	ADJ
ajst-10983	6	9	research	research	NOUN
ajst-10983	6	10	should	should	AUX
ajst-10983	6	11	focus	focus	VERB
ajst-10983	6	12	on	on	ADP
ajst-10983	6	13	how	how	SCONJ
ajst-10983	6	14	to	to	PART
ajst-10983	6	15	better	well	ADV
ajst-10983	6	16	cope	cope	VERB
ajst-10983	6	17	with	with	ADP
ajst-10983	6	18	the	the	DET
ajst-10983	6	19	challenges	challenge	NOUN
ajst-10983	6	20	of	of	ADP
ajst-10983	6	21	root	root	NOUN
ajst-10983	6	22	morphology	morphology	NOUN
ajst-10983	6	23	and	and	CCONJ
ajst-10983	6	24	scale	scale	NOUN
ajst-10983	6	25	change	change	NOUN
ajst-10983	6	26	,	,	PUNCT
ajst-10983	6	27	and	and	CCONJ
ajst-10983	6	28	pay	pay	VERB
ajst-10983	6	29	more	more	ADJ
ajst-10983	6	30	attention	attention	NOUN
ajst-10983	6	31	to	to	ADP
ajst-10983	6	32	the	the	DET
ajst-10983	6	33	robustness	robustness	NOUN
ajst-10983	6	34	and	and	CCONJ
ajst-10983	6	35	scalability	scalability	NOUN
ajst-10983	6	36	of	of	ADP
ajst-10983	6	37	the	the	DET
ajst-10983	6	38	algorithm	algorithm	NOUN
ajst-10983	6	39	.	.	PUNCT
ajst-10983	7	1	in	in	ADP
ajst-10983	7	2	conclusion	conclusion	NOUN
ajst-10983	7	3	,	,	PUNCT
ajst-10983	7	4	deep	deep	ADJ
ajst-10983	7	5	learning	learning	NOUN
ajst-10983	7	6	has	have	AUX
ajst-10983	7	7	had	have	VERB
ajst-10983	7	8	an	an	DET
ajst-10983	7	9	important	important	ADJ
ajst-10983	7	10	impact	impact	NOUN
ajst-10983	7	11	on	on	ADP
ajst-10983	7	12	image	image	NOUN
ajst-10983	7	13	segmentation	segmentation	NOUN
ajst-10983	7	14	of	of	ADP
ajst-10983	7	15	plant	plant	NOUN
ajst-10983	7	16	roots	root	NOUN
ajst-10983	7	17	.	.	PUNCT
ajst-10983	8	1	keywords	keyword	NOUN
ajst-10983	8	2	:	:	PUNCT
ajst-10983	8	3	plant	plant	NOUN
ajst-10983	8	4	root	root	NOUN
ajst-10983	8	5	segmentation	segmentation	NOUN
ajst-10983	8	6	,	,	PUNCT
ajst-10983	8	7	deep	deep	ADJ
ajst-10983	8	8	learning	learning	NOUN
ajst-10983	8	9	,	,	PUNCT
ajst-10983	8	10	root	root	NOUN
ajst-10983	8	11	morphology	morphology	NOUN
ajst-10983	8	12	,	,	PUNCT
ajst-10983	8	13	image	image	NOUN
ajst-10983	8	14	segmentation	segmentation	NOUN
ajst-10983	8	15	.	.	PUNCT
ajst-10983	9	1	1	1	X
ajst-10983	9	2	.	.	X
ajst-10983	9	3	introduction	introduction	NOUN
ajst-10983	9	4	in	in	ADP
ajst-10983	9	5	the	the	DET
ajst-10983	9	6	new	new	ADJ
ajst-10983	9	7	era	era	NOUN
ajst-10983	9	8	of	of	ADP
ajst-10983	9	9	socialism	socialism	NOUN
ajst-10983	9	10	,	,	PUNCT
ajst-10983	9	11	where	where	SCONJ
ajst-10983	9	12	science	science	NOUN
ajst-10983	9	13	and	and	CCONJ
ajst-10983	9	14	technology	technology	NOUN
ajst-10983	9	15	are	be	AUX
ajst-10983	9	16	advancing	advance	VERB
ajst-10983	9	17	rapidly	rapidly	ADV
ajst-10983	9	18	,	,	PUNCT
ajst-10983	9	19	studying	study	VERB
ajst-10983	9	20	plant	plant	NOUN
ajst-10983	9	21	roots	root	NOUN
ajst-10983	9	22	is	be	AUX
ajst-10983	9	23	crucial	crucial	ADJ
ajst-10983	9	24	for	for	ADP
ajst-10983	9	25	discovering	discover	VERB
ajst-10983	9	26	the	the	DET
ajst-10983	9	27	beneficial	beneficial	ADJ
ajst-10983	9	28	shape	shape	NOUN
ajst-10983	9	29	of	of	ADP
ajst-10983	9	30	crops	crop	NOUN
ajst-10983	9	31	,	,	PUNCT
ajst-10983	9	32	breeding	breed	VERB
ajst-10983	9	33	new	new	ADJ
ajst-10983	9	34	varieties	variety	NOUN
ajst-10983	9	35	,	,	PUNCT
ajst-10983	9	36	predicting	predict	VERB
ajst-10983	9	37	climate	climate	NOUN
ajst-10983	9	38	change	change	NOUN
ajst-10983	9	39	,	,	PUNCT
ajst-10983	9	40	and	and	CCONJ
ajst-10983	9	41	optimizing	optimize	VERB
ajst-10983	9	42	cultivation	cultivation	NOUN
ajst-10983	9	43	methods	method	NOUN
ajst-10983	9	44	.	.	PUNCT
ajst-10983	10	1	our	our	PRON
ajst-10983	10	2	research	research	NOUN
ajst-10983	10	3	methods	method	NOUN
ajst-10983	10	4	on	on	ADP
ajst-10983	10	5	root	root	NOUN
ajst-10983	10	6	systems	system	NOUN
ajst-10983	10	7	have	have	AUX
ajst-10983	10	8	also	also	ADV
ajst-10983	10	9	changed	change	VERB
ajst-10983	10	10	,	,	PUNCT
ajst-10983	10	11	from	from	ADP
ajst-10983	10	12	destructive	destructive	ADJ
ajst-10983	10	13	to	to	ADP
ajst-10983	10	14	non	non	ADJ
ajst-10983	10	15	-	-	ADJ
ajst-10983	10	16	destructive	destructive	ADJ
ajst-10983	10	17	research	research	NOUN
ajst-10983	10	18	methods	method	NOUN
ajst-10983	10	19	,	,	PUNCT
ajst-10983	10	20	from	from	ADP
ajst-10983	10	21	traditional	traditional	ADJ
ajst-10983	10	22	manual	manual	ADJ
ajst-10983	10	23	root	root	NOUN
ajst-10983	10	24	in	in	ADP
ajst-10983	10	25	situ	situ	ADJ
ajst-10983	10	26	segmentation	segmentation	NOUN
ajst-10983	10	27	methods	method	NOUN
ajst-10983	10	28	to	to	ADP
ajst-10983	10	29	automatic	automatic	ADJ
ajst-10983	10	30	segmentation	segmentation	NOUN
ajst-10983	10	31	methods	method	NOUN
ajst-10983	10	32	,	,	PUNCT
ajst-10983	10	33	and	and	CCONJ
ajst-10983	10	34	more	more	ADV
ajst-10983	10	35	efficient	efficient	ADJ
ajst-10983	10	36	technology	technology	NOUN
ajst-10983	10	37	provides	provide	VERB
ajst-10983	10	38	a	a	DET
ajst-10983	10	39	shortcut	shortcut	NOUN
ajst-10983	10	40	for	for	ADP
ajst-10983	10	41	the	the	DET
ajst-10983	10	42	analysis	analysis	NOUN
ajst-10983	10	43	of	of	ADP
ajst-10983	10	44	root	root	NOUN
ajst-10983	10	45	phenotypic	phenotypic	ADJ
ajst-10983	10	46	characteristics	characteristic	NOUN
ajst-10983	10	47	.	.	PUNCT
ajst-10983	11	1	however	however	ADV
ajst-10983	11	2	,	,	PUNCT
ajst-10983	11	3	due	due	ADP
ajst-10983	11	4	to	to	ADP
ajst-10983	11	5	the	the	DET
ajst-10983	11	6	similar	similar	ADJ
ajst-10983	11	7	color	color	NOUN
ajst-10983	11	8	of	of	ADP
ajst-10983	11	9	plant	plant	NOUN
ajst-10983	11	10	roots	root	NOUN
ajst-10983	11	11	and	and	CCONJ
ajst-10983	11	12	soil	soil	NOUN
ajst-10983	11	13	,	,	PUNCT
ajst-10983	11	14	it	it	PRON
ajst-10983	11	15	is	be	AUX
ajst-10983	11	16	difficult	difficult	ADJ
ajst-10983	11	17	to	to	PART
ajst-10983	11	18	extract	extract	VERB
ajst-10983	11	19	root	root	NOUN
ajst-10983	11	20	characteristics	characteristic	NOUN
ajst-10983	11	21	,	,	PUNCT
ajst-10983	11	22	there	there	PRON
ajst-10983	11	23	are	be	VERB
ajst-10983	11	24	few	few	ADJ
ajst-10983	11	25	image	image	NOUN
ajst-10983	11	26	data	datum	NOUN
ajst-10983	11	27	of	of	ADP
ajst-10983	11	28	plant	plant	NOUN
ajst-10983	11	29	roots	root	NOUN
ajst-10983	11	30	,	,	PUNCT
ajst-10983	11	31	and	and	CCONJ
ajst-10983	11	32	the	the	DET
ajst-10983	11	33	soil	soil	NOUN
ajst-10983	11	34	background	background	NOUN
ajst-10983	11	35	is	be	AUX
ajst-10983	11	36	complex	complex	ADJ
ajst-10983	11	37	,	,	PUNCT
ajst-10983	11	38	usually	usually	ADV
ajst-10983	11	39	containing	contain	VERB
ajst-10983	11	40	impurities	impurity	NOUN
ajst-10983	11	41	such	such	ADJ
ajst-10983	11	42	as	as	ADP
ajst-10983	11	43	soil	soil	NOUN
ajst-10983	11	44	particles	particle	NOUN
ajst-10983	11	45	and	and	CCONJ
ajst-10983	11	46	small	small	ADJ
ajst-10983	11	47	stones	stone	NOUN
ajst-10983	11	48	,	,	PUNCT
ajst-10983	11	49	so	so	CCONJ
ajst-10983	11	50	it	it	PRON
ajst-10983	11	51	is	be	AUX
ajst-10983	11	52	extremely	extremely	ADV
ajst-10983	11	53	challenging	challenging	ADJ
ajst-10983	11	54	to	to	PART
ajst-10983	11	55	apply	apply	VERB
ajst-10983	11	56	deep	deep	ADJ
ajst-10983	11	57	learning	learning	NOUN
ajst-10983	11	58	to	to	PART
ajst-10983	11	59	plant	plant	VERB
ajst-10983	11	60	root	root	NOUN
ajst-10983	11	61	segmentation	segmentation	NOUN
ajst-10983	11	62	.	.	PUNCT
ajst-10983	12	1	2	2	X
ajst-10983	12	2	.	.	X
ajst-10983	12	3	research	research	NOUN
ajst-10983	12	4	on	on	ADP
ajst-10983	12	5	roots	root	NOUN
ajst-10983	12	6	of	of	ADP
ajst-10983	12	7	traditional	traditional	ADJ
ajst-10983	12	8	plants	plant	NOUN
ajst-10983	12	9	the	the	DET
ajst-10983	12	10	roots	root	NOUN
ajst-10983	12	11	of	of	ADP
ajst-10983	12	12	plants	plant	NOUN
ajst-10983	12	13	have	have	AUX
ajst-10983	12	14	been	be	AUX
ajst-10983	12	15	studied	study	VERB
ajst-10983	12	16	since	since	SCONJ
ajst-10983	12	17	the	the	DET
ajst-10983	12	18	18th	18th	ADJ
ajst-10983	12	19	century	century	NOUN
ajst-10983	12	20	[	[	X
ajst-10983	12	21	1	1	NUM
ajst-10983	12	22	]	]	PUNCT
ajst-10983	12	23	.	.	PUNCT
ajst-10983	13	1	early	early	ADJ
ajst-10983	13	2	studies	study	NOUN
ajst-10983	13	3	on	on	ADP
ajst-10983	13	4	root	root	NOUN
ajst-10983	13	5	configuration	configuration	NOUN
ajst-10983	13	6	can	can	AUX
ajst-10983	13	7	be	be	AUX
ajst-10983	13	8	traced	trace	VERB
ajst-10983	13	9	back	back	ADV
ajst-10983	13	10	to	to	ADP
ajst-10983	13	11	the	the	DET
ajst-10983	13	12	early	early	ADJ
ajst-10983	13	13	20th	20th	ADJ
ajst-10983	13	14	century	century	NOUN
ajst-10983	13	15	,	,	PUNCT
ajst-10983	13	16	when	when	SCONJ
ajst-10983	13	17	cannon	cannon	NOUN
ajst-10983	13	18	's	's	PART
ajst-10983	13	19	research	research	NOUN
ajst-10983	13	20	revealed	reveal	VERB
ajst-10983	13	21	the	the	DET
ajst-10983	13	22	variability	variability	NOUN
ajst-10983	13	23	of	of	ADP
ajst-10983	13	24	taproots	taproot	NOUN
ajst-10983	13	25	and	and	CCONJ
ajst-10983	13	26	lateral	lateral	ADJ
ajst-10983	13	27	roots	root	NOUN
ajst-10983	13	28	of	of	ADP
ajst-10983	13	29	desert	desert	NOUN
ajst-10983	13	30	plant	plant	NOUN
ajst-10983	13	31	roots	root	NOUN
ajst-10983	13	32	[	[	X
ajst-10983	13	33	2	2	NUM
ajst-10983	13	34	]	]	PUNCT
ajst-10983	13	35	,	,	PUNCT
ajst-10983	13	36	laying	lay	VERB
ajst-10983	13	37	the	the	DET
ajst-10983	13	38	foundation	foundation	NOUN
ajst-10983	13	39	for	for	ADP
ajst-10983	13	40	later	later	ADJ
ajst-10983	13	41	studies	study	NOUN
ajst-10983	13	42	on	on	ADP
ajst-10983	13	43	plant	plant	NOUN
ajst-10983	13	44	roots	root	NOUN
ajst-10983	13	45	.	.	PUNCT
ajst-10983	14	1	2.1	2.1	NUM
ajst-10983	14	2	.	.	PUNCT
ajst-10983	14	3	collection	collection	NOUN
ajst-10983	14	4	of	of	ADP
ajst-10983	14	5	plant	plant	NOUN
ajst-10983	14	6	root	root	NOUN
ajst-10983	14	7	data	datum	NOUN
ajst-10983	14	8	in	in	ADP
ajst-10983	14	9	the	the	DET
ajst-10983	14	10	early	early	ADJ
ajst-10983	14	11	stage	stage	NOUN
ajst-10983	14	12	,	,	PUNCT
ajst-10983	14	13	researchers	researcher	NOUN
ajst-10983	14	14	usually	usually	ADV
ajst-10983	14	15	used	use	VERB
ajst-10983	14	16	destructive	destructive	ADJ
ajst-10983	14	17	research	research	NOUN
ajst-10983	14	18	methods	method	NOUN
ajst-10983	14	19	such	such	ADJ
ajst-10983	14	20	as	as	ADP
ajst-10983	14	21	excavation	excavation	NOUN
ajst-10983	14	22	method	method	NOUN
ajst-10983	14	23	,	,	PUNCT
ajst-10983	14	24	single	single	ADJ
ajst-10983	14	25	block	block	NOUN
ajst-10983	14	26	method	method	NOUN
ajst-10983	14	27	,	,	PUNCT
ajst-10983	14	28	drilling	drilling	NOUN
ajst-10983	14	29	method	method	NOUN
ajst-10983	14	30	and	and	CCONJ
ajst-10983	14	31	section	section	NOUN
ajst-10983	14	32	wall	wall	PROPN
ajst-10983	14	33	method	method	PROPN
ajst-10983	14	34	to	to	PART
ajst-10983	14	35	study	study	VERB
ajst-10983	14	36	roots	root	NOUN
ajst-10983	14	37	[	[	X
ajst-10983	14	38	3	3	NUM
ajst-10983	14	39	]	]	PUNCT
ajst-10983	14	40	,	,	PUNCT
ajst-10983	14	41	which	which	PRON
ajst-10983	14	42	made	make	VERB
ajst-10983	14	43	it	it	PRON
ajst-10983	14	44	difficult	difficult	ADJ
ajst-10983	14	45	to	to	PART
ajst-10983	14	46	realize	realize	VERB
ajst-10983	14	47	in	in	ADP
ajst-10983	14	48	-	-	PUNCT
ajst-10983	14	49	situ	situ	NOUN
ajst-10983	14	50	sampling	sampling	NOUN
ajst-10983	14	51	and	and	CCONJ
ajst-10983	14	52	accurate	accurate	ADJ
ajst-10983	14	53	measurement	measurement	NOUN
ajst-10983	14	54	of	of	ADP
ajst-10983	14	55	roots	root	NOUN
ajst-10983	14	56	.	.	PUNCT
ajst-10983	15	1	due	due	ADP
ajst-10983	15	2	to	to	ADP
ajst-10983	15	3	the	the	DET
ajst-10983	15	4	lack	lack	NOUN
ajst-10983	15	5	of	of	ADP
ajst-10983	15	6	effective	effective	ADJ
ajst-10983	15	7	non	non	ADJ
ajst-10983	15	8	-	-	ADJ
ajst-10983	15	9	destructive	destructive	ADJ
ajst-10983	15	10	testing	testing	NOUN
ajst-10983	15	11	methods	method	NOUN
ajst-10983	15	12	to	to	PART
ajst-10983	15	13	obtain	obtain	VERB
ajst-10983	15	14	the	the	DET
ajst-10983	15	15	actual	actual	ADJ
ajst-10983	15	16	state	state	NOUN
ajst-10983	15	17	of	of	ADP
ajst-10983	15	18	roots	root	NOUN
ajst-10983	15	19	in	in	ADP
ajst-10983	15	20	soil	soil	NOUN
ajst-10983	15	21	,	,	PUNCT
ajst-10983	15	22	the	the	DET
ajst-10983	15	23	in	in	ADP
ajst-10983	15	24	-	-	PUNCT
ajst-10983	15	25	depth	depth	NOUN
ajst-10983	15	26	study	study	NOUN
ajst-10983	15	27	of	of	ADP
ajst-10983	15	28	root	root	NOUN
ajst-10983	15	29	behavior	behavior	NOUN
ajst-10983	15	30	and	and	CCONJ
ajst-10983	15	31	characteristics	characteristic	NOUN
ajst-10983	15	32	is	be	AUX
ajst-10983	15	33	hindered	hinder	VERB
ajst-10983	15	34	.	.	PUNCT
ajst-10983	16	1	after	after	ADP
ajst-10983	16	2	the	the	DET
ajst-10983	16	3	1950s	1950	NOUN
ajst-10983	16	4	and	and	CCONJ
ajst-10983	16	5	1960s	1960	NOUN
ajst-10983	16	6	,	,	PUNCT
ajst-10983	16	7	due	due	ADP
ajst-10983	16	8	to	to	ADP
ajst-10983	16	9	the	the	DET
ajst-10983	16	10	development	development	NOUN
ajst-10983	16	11	of	of	ADP
ajst-10983	16	12	optical	optical	ADJ
ajst-10983	16	13	and	and	CCONJ
ajst-10983	16	14	microelectronics	microelectronic	NOUN
ajst-10983	16	15	technology	technology	NOUN
ajst-10983	16	16	,	,	PUNCT
ajst-10983	16	17	plant	plant	NOUN
ajst-10983	16	18	root	root	NOUN
ajst-10983	16	19	research	research	NOUN
ajst-10983	16	20	was	be	AUX
ajst-10983	16	21	further	far	ADV
ajst-10983	16	22	strengthened	strengthen	VERB
ajst-10983	16	23	,	,	PUNCT
ajst-10983	16	24	and	and	CCONJ
ajst-10983	16	25	non	non	ADJ
ajst-10983	16	26	-	-	ADJ
ajst-10983	16	27	destructive	destructive	ADJ
ajst-10983	16	28	or	or	CCONJ
ajst-10983	16	29	minimally	minimally	ADV
ajst-10983	16	30	invasive	invasive	ADJ
ajst-10983	16	31	methods	method	NOUN
ajst-10983	16	32	were	be	AUX
ajst-10983	16	33	adopted	adopt	VERB
ajst-10983	16	34	,	,	PUNCT
ajst-10983	16	35	such	such	ADJ
ajst-10983	16	36	as	as	ADP
ajst-10983	16	37	glass	glass	NOUN
ajst-10983	16	38	wall	wall	NOUN
ajst-10983	16	39	method	method	NOUN
ajst-10983	16	40	,	,	PUNCT
ajst-10983	16	41	endoscopy	endoscopy	VERB
ajst-10983	16	42	tube	tube	NOUN
ajst-10983	16	43	method	method	NOUN
ajst-10983	16	44	(	(	PUNCT
ajst-10983	16	45	microroot	microroot	NOUN
ajst-10983	16	46	canal	canal	NOUN
ajst-10983	16	47	)	)	PUNCT
ajst-10983	16	48	,	,	PUNCT
ajst-10983	16	49	container	container	NOUN
ajst-10983	16	50	method	method	NOUN
ajst-10983	16	51	,	,	PUNCT
ajst-10983	16	52	etc	etc	X
ajst-10983	16	53	.	.	X
ajst-10983	16	54	,	,	PUNCT
ajst-10983	16	55	to	to	PART
ajst-10983	16	56	minimize	minimize	VERB
ajst-10983	16	57	root	root	NOUN
ajst-10983	16	58	damage	damage	NOUN
ajst-10983	16	59	.	.	PUNCT
ajst-10983	17	1	among	among	ADP
ajst-10983	17	2	them	they	PRON
ajst-10983	17	3	,	,	PUNCT
ajst-10983	17	4	microroot	microroot	NOUN
ajst-10983	17	5	canal	canal	NOUN
ajst-10983	17	6	technology	technology	NOUN
ajst-10983	17	7	is	be	AUX
ajst-10983	17	8	a	a	DET
ajst-10983	17	9	method	method	NOUN
ajst-10983	17	10	of	of	ADP
ajst-10983	17	11	root	root	NOUN
ajst-10983	17	12	observation	observation	NOUN
ajst-10983	17	13	and	and	CCONJ
ajst-10983	17	14	research	research	NOUN
ajst-10983	17	15	,	,	PUNCT
ajst-10983	17	16	which	which	PRON
ajst-10983	17	17	uses	use	VERB
ajst-10983	17	18	a	a	DET
ajst-10983	17	19	transparent	transparent	ADJ
ajst-10983	17	20	test	test	NOUN
ajst-10983	17	21	tube	tube	NOUN
ajst-10983	17	22	inserted	insert	VERB
ajst-10983	17	23	into	into	ADP
ajst-10983	17	24	the	the	DET
ajst-10983	17	25	soil	soil	NOUN
ajst-10983	17	26	to	to	PART
ajst-10983	17	27	create	create	VERB
ajst-10983	17	28	a	a	DET
ajst-10983	17	29	small	small	ADJ
ajst-10983	17	30	observation	observation	NOUN
ajst-10983	17	31	window	window	NOUN
ajst-10983	17	32	,	,	PUNCT
ajst-10983	17	33	and	and	CCONJ
ajst-10983	17	34	uses	use	VERB
ajst-10983	17	35	a	a	DET
ajst-10983	17	36	multi	multi	ADJ
ajst-10983	17	37	-	-	ADJ
ajst-10983	17	38	tube	tube	ADJ
ajst-10983	17	39	observation	observation	NOUN
ajst-10983	17	40	lens	lens	NOUN
ajst-10983	17	41	or	or	CCONJ
ajst-10983	17	42	a	a	DET
ajst-10983	17	43	miniature	miniature	ADJ
ajst-10983	17	44	digital	digital	ADJ
ajst-10983	17	45	camera	camera	NOUN
ajst-10983	17	46	to	to	PART
ajst-10983	17	47	take	take	VERB
ajst-10983	17	48	pictures	picture	NOUN
ajst-10983	17	49	inside	inside	ADP
ajst-10983	17	50	the	the	DET
ajst-10983	17	51	tube	tube	NOUN
ajst-10983	17	52	,	,	PUNCT
ajst-10983	17	53	record	record	NOUN
ajst-10983	17	54	and	and	CCONJ
ajst-10983	17	55	observe	observe	VERB
ajst-10983	17	56	the	the	DET
ajst-10983	17	57	growth	growth	NOUN
ajst-10983	17	58	dynamics	dynamic	NOUN
ajst-10983	17	59	of	of	ADP
ajst-10983	17	60	new	new	ADJ
ajst-10983	17	61	roots	root	NOUN
ajst-10983	17	62	inside	inside	ADP
ajst-10983	17	63	and	and	CCONJ
ajst-10983	17	64	outside	outside	ADP
ajst-10983	17	65	the	the	DET
ajst-10983	17	66	tube	tube	NOUN
ajst-10983	17	67	[	[	X
ajst-10983	17	68	4	4	NUM
ajst-10983	17	69	]	]	PUNCT
ajst-10983	17	70	.	.	PUNCT
ajst-10983	18	1	the	the	DET
ajst-10983	18	2	image	image	NOUN
ajst-10983	18	3	data	datum	NOUN
ajst-10983	18	4	collected	collect	VERB
ajst-10983	18	5	in	in	ADP
ajst-10983	18	6	the	the	DET
ajst-10983	18	7	field	field	NOUN
ajst-10983	18	8	were	be	AUX
ajst-10983	18	9	applied	apply	VERB
ajst-10983	18	10	to	to	ADP
ajst-10983	18	11	the	the	DET
ajst-10983	18	12	indoor	indoor	ADJ
ajst-10983	18	13	special	special	ADJ
ajst-10983	18	14	computer	computer	NOUN
ajst-10983	18	15	software	software	NOUN
ajst-10983	18	16	to	to	PART
ajst-10983	18	17	calculate	calculate	VERB
ajst-10983	18	18	the	the	DET
ajst-10983	18	19	root	root	NOUN
ajst-10983	18	20	parameters	parameter	NOUN
ajst-10983	18	21	.	.	PUNCT
ajst-10983	19	1	the	the	DET
ajst-10983	19	2	advantage	advantage	NOUN
ajst-10983	19	3	of	of	ADP
ajst-10983	19	4	this	this	DET
ajst-10983	19	5	method	method	NOUN
ajst-10983	19	6	is	be	AUX
ajst-10983	19	7	that	that	SCONJ
ajst-10983	19	8	the	the	DET
ajst-10983	19	9	root	root	NOUN
ajst-10983	19	10	system	system	NOUN
ajst-10983	19	11	can	can	AUX
ajst-10983	19	12	be	be	AUX
ajst-10983	19	13	observed	observe	VERB
ajst-10983	19	14	and	and	CCONJ
ajst-10983	19	15	studied	study	VERB
ajst-10983	19	16	without	without	ADP
ajst-10983	19	17	loss	loss	NOUN
ajst-10983	19	18	,	,	PUNCT
ajst-10983	19	19	and	and	CCONJ
ajst-10983	19	20	the	the	DET
ajst-10983	19	21	dynamic	dynamic	ADJ
ajst-10983	19	22	growth	growth	NOUN
ajst-10983	19	23	process	process	NOUN
ajst-10983	19	24	of	of	ADP
ajst-10983	19	25	the	the	DET
ajst-10983	19	26	same	same	ADJ
ajst-10983	19	27	root	root	NOUN
ajst-10983	19	28	system	system	NOUN
ajst-10983	19	29	can	can	AUX
ajst-10983	19	30	be	be	AUX
ajst-10983	19	31	tracked	track	VERB
ajst-10983	19	32	and	and	CCONJ
ajst-10983	19	33	recorded	record	VERB
ajst-10983	19	34	in	in	ADP
ajst-10983	19	35	real	real	ADJ
ajst-10983	19	36	time	time	NOUN
ajst-10983	19	37	.	.	PUNCT
ajst-10983	20	1	however	however	ADV
ajst-10983	20	2	,	,	PUNCT
ajst-10983	20	3	its	its	PRON
ajst-10983	20	4	limitation	limitation	NOUN
ajst-10983	20	5	lies	lie	VERB
ajst-10983	20	6	in	in	ADP
ajst-10983	20	7	the	the	DET
ajst-10983	20	8	high	high	ADJ
ajst-10983	20	9	cost	cost	NOUN
ajst-10983	20	10	of	of	ADP
ajst-10983	20	11	equipment	equipment	NOUN
ajst-10983	20	12	and	and	CCONJ
ajst-10983	20	13	the	the	DET
ajst-10983	20	14	limited	limited	ADJ
ajst-10983	20	15	application	application	NOUN
ajst-10983	20	16	range	range	NOUN
ajst-10983	20	17	[	[	X
ajst-10983	20	18	5	5	NUM
ajst-10983	20	19	]	]	PUNCT
ajst-10983	20	20	.	.	PUNCT
ajst-10983	21	1	in	in	ADP
ajst-10983	21	2	addition	addition	NOUN
ajst-10983	21	3	,	,	PUNCT
ajst-10983	21	4	there	there	PRON
ajst-10983	21	5	are	be	VERB
ajst-10983	21	6	non	non	ADJ
ajst-10983	21	7	-	-	ADJ
ajst-10983	21	8	invasive	invasive	ADJ
ajst-10983	21	9	methods	method	NOUN
ajst-10983	21	10	sensor	sensor	NOUN
ajst-10983	21	11	method	method	NOUN
ajst-10983	21	12	.	.	PUNCT
ajst-10983	22	1	the	the	DET
ajst-10983	22	2	sensor	sensor	NOUN
ajst-10983	22	3	method	method	NOUN
ajst-10983	22	4	can	can	AUX
ajst-10983	22	5	be	be	AUX
ajst-10983	22	6	used	use	VERB
ajst-10983	22	7	for	for	ADP
ajst-10983	22	8	non	non	ADJ
ajst-10983	22	9	-	-	ADJ
ajst-10983	22	10	invasive	invasive	ADJ
ajst-10983	22	11	detection	detection	NOUN
ajst-10983	22	12	of	of	ADP
ajst-10983	22	13	root	root	NOUN
ajst-10983	22	14	phenotypes	phenotype	NOUN
ajst-10983	22	15	,	,	PUNCT
ajst-10983	22	16	does	do	AUX
ajst-10983	22	17	not	not	PART
ajst-10983	22	18	interfere	interfere	VERB
ajst-10983	22	19	with	with	ADP
ajst-10983	22	20	root	root	NOUN
ajst-10983	22	21	growth	growth	NOUN
ajst-10983	22	22	,	,	PUNCT
ajst-10983	22	23	does	do	AUX
ajst-10983	22	24	not	not	PART
ajst-10983	22	25	affect	affect	VERB
ajst-10983	22	26	soil	soil	NOUN
ajst-10983	22	27	structure	structure	NOUN
ajst-10983	22	28	,	,	PUNCT
ajst-10983	22	29	and	and	CCONJ
ajst-10983	22	30	can	can	AUX
ajst-10983	22	31	be	be	AUX
ajst-10983	22	32	continued	continue	VERB
ajst-10983	22	33	throughout	throughout	ADP
ajst-10983	22	34	the	the	DET
ajst-10983	22	35	breeding	breeding	NOUN
ajst-10983	22	36	period	period	NOUN
ajst-10983	22	37	without	without	ADP
ajst-10983	22	38	changing	change	VERB
ajst-10983	22	39	the	the	DET
ajst-10983	22	40	soil	soil	NOUN
ajst-10983	22	41	environment	environment	NOUN
ajst-10983	22	42	.	.	PUNCT
ajst-10983	23	1	the	the	DET
ajst-10983	23	2	sensor	sensor	NOUN
ajst-10983	23	3	performs	perform	VERB
ajst-10983	23	4	4d	4d	NUM
ajst-10983	23	5	root	root	NOUN
ajst-10983	23	6	imaging	imaging	NOUN
ajst-10983	23	7	,	,	PUNCT
ajst-10983	23	8	relying	rely	VERB
ajst-10983	23	9	on	on	ADP
ajst-10983	23	10	detectors	detector	NOUN
ajst-10983	23	11	placed	place	VERB
ajst-10983	23	12	around	around	ADP
ajst-10983	23	13	or	or	CCONJ
ajst-10983	23	14	inside	inside	ADP
ajst-10983	23	15	the	the	DET
ajst-10983	23	16	culture	culture	NOUN
ajst-10983	23	17	unit	unit	NOUN
ajst-10983	23	18	to	to	PART
ajst-10983	23	19	obtain	obtain	VERB
ajst-10983	23	20	information	information	NOUN
ajst-10983	23	21	through	through	ADP
ajst-10983	23	22	methods	method	NOUN
ajst-10983	23	23	such	such	ADJ
ajst-10983	23	24	as	as	ADP
ajst-10983	23	25	mri	mri	NOUN
ajst-10983	23	26	and	and	CCONJ
ajst-10983	23	27	x	x	NOUN
ajst-10983	23	28	-	-	NOUN
ajst-10983	23	29	ray	ray	NOUN
ajst-10983	23	30	tomography	tomography	NOUN
ajst-10983	23	31	.	.	PUNCT
ajst-10983	24	1	the	the	DET
ajst-10983	24	2	image	image	NOUN
ajst-10983	24	3	obtained	obtain	VERB
ajst-10983	24	4	from	from	ADP
ajst-10983	24	5	a	a	DET
ajst-10983	24	6	single	single	ADJ
ajst-10983	24	7	scan	scan	NOUN
ajst-10983	24	8	needs	need	NOUN
ajst-10983	24	9	to	to	PART
ajst-10983	24	10	be	be	AUX
ajst-10983	24	11	filtered	filter	VERB
ajst-10983	24	12	,	,	PUNCT
ajst-10983	24	13	analyzed	analyze	VERB
ajst-10983	24	14	,	,	PUNCT
ajst-10983	24	15	corrected	correct	VERB
ajst-10983	24	16	,	,	PUNCT
ajst-10983	24	17	fitted	fit	VERB
ajst-10983	24	18	and	and	CCONJ
ajst-10983	24	19	reconstructed	reconstruct	VERB
ajst-10983	24	20	in	in	ADP
ajst-10983	24	21	three	three	NUM
ajst-10983	24	22	dimensions	dimension	NOUN
ajst-10983	24	23	to	to	PART
ajst-10983	24	24	obtain	obtain	VERB
ajst-10983	24	25	the	the	DET
ajst-10983	24	26	final	final	ADJ
ajst-10983	24	27	result	result	NOUN
ajst-10983	24	28	.	.	PUNCT
ajst-10983	25	1	however	however	ADV
ajst-10983	25	2	,	,	PUNCT
ajst-10983	25	3	complex	complex	ADJ
ajst-10983	25	4	soil	soil	NOUN
ajst-10983	25	5	composition	composition	NOUN
ajst-10983	25	6	and	and	CCONJ
ajst-10983	25	7	water	water	NOUN
ajst-10983	25	8	restrictions	restriction	NOUN
ajst-10983	25	9	can	can	AUX
ajst-10983	25	10	interfere	interfere	VERB
ajst-10983	25	11	with	with	ADP
ajst-10983	25	12	the	the	DET
ajst-10983	25	13	results	result	NOUN
ajst-10983	25	14	,	,	PUNCT
ajst-10983	25	15	as	as	SCONJ
ajst-10983	25	16	can	can	AUX
ajst-10983	25	17	the	the	DET
ajst-10983	25	18	depth	depth	NOUN
ajst-10983	25	19	of	of	ADP
ajst-10983	25	20	penetration	penetration	NOUN
ajst-10983	25	21	of	of	ADP
ajst-10983	25	22	the	the	DET
ajst-10983	25	23	rays	ray	NOUN
ajst-10983	25	24	.	.	PUNCT
ajst-10983	26	1	therefore	therefore	ADV
ajst-10983	26	2	,	,	PUNCT
ajst-10983	26	3	most	most	ADJ
ajst-10983	26	4	of	of	ADP
ajst-10983	26	5	the	the	DET
ajst-10983	26	6	traditional	traditional	ADJ
ajst-10983	26	7	methods	method	NOUN
ajst-10983	26	8	for	for	ADP
ajst-10983	26	9	obtaining	obtain	VERB
ajst-10983	26	10	root	root	NOUN
ajst-10983	26	11	phenotype	phenotype	NOUN
ajst-10983	26	12	information	information	NOUN
ajst-10983	26	13	are	be	AUX
ajst-10983	26	14	difficult	difficult	ADJ
ajst-10983	26	15	to	to	PART
ajst-10983	26	16	achieve	achieve	VERB
ajst-10983	26	17	non	non	ADJ
ajst-10983	26	18	-	-	ADJ
ajst-10983	26	19	destructive	destructive	ADJ
ajst-10983	26	20	,	,	PUNCT
ajst-10983	26	21	dynamic	dynamic	ADJ
ajst-10983	26	22	,	,	PUNCT
ajst-10983	26	23	accurate	accurate	ADJ
ajst-10983	26	24	and	and	CCONJ
ajst-10983	26	25	quantitative	quantitative	ADJ
ajst-10983	26	26	description	description	NOUN
ajst-10983	26	27	of	of	ADP
ajst-10983	26	28	plant	plant	NOUN
ajst-10983	26	29	root	root	NOUN
ajst-10983	26	30	configuration	configuration	NOUN
ajst-10983	26	31	,	,	PUNCT
ajst-10983	26	32	which	which	PRON
ajst-10983	26	33	can	can	AUX
ajst-10983	26	34	not	not	PART
ajst-10983	26	35	meet	meet	VERB
ajst-10983	26	36	the	the	DET
ajst-10983	26	37	actual	actual	ADJ
ajst-10983	26	38	needs	need	NOUN
ajst-10983	26	39	of	of	ADP
ajst-10983	26	40	current	current	ADJ
ajst-10983	26	41	in	in	ADP
ajst-10983	26	42	-	-	PUNCT
ajst-10983	26	43	situ	situ	NOUN
ajst-10983	26	44	root	root	NOUN
ajst-10983	26	45	research	research	NOUN
ajst-10983	26	46	.	.	PUNCT
ajst-10983	27	1	2.2	2.2	NUM
ajst-10983	27	2	.	.	PUNCT
ajst-10983	27	3	plant	plant	NOUN
ajst-10983	27	4	root	root	NOUN
ajst-10983	27	5	imaging	imaging	NOUN
ajst-10983	27	6	in	in	ADP
ajst-10983	27	7	situ	situ	ADJ
ajst-10983	27	8	root	root	NOUN
ajst-10983	27	9	detection	detection	NOUN
ajst-10983	27	10	is	be	AUX
ajst-10983	27	11	the	the	DET
ajst-10983	27	12	imaging	imaging	NOUN
ajst-10983	27	13	detection	detection	NOUN
ajst-10983	27	14	of	of	ADP
ajst-10983	27	15	roots	root	NOUN
ajst-10983	27	16	under	under	ADP
ajst-10983	27	17	the	the	DET
ajst-10983	27	18	condition	condition	NOUN
ajst-10983	27	19	of	of	ADP
ajst-10983	27	20	avoiding	avoid	VERB
ajst-10983	27	21	root	root	NOUN
ajst-10983	27	22	damage	damage	NOUN
ajst-10983	27	23	.	.	PUNCT
ajst-10983	28	1	with	with	ADP
ajst-10983	28	2	the	the	DET
ajst-10983	28	3	continuous	continuous	ADJ
ajst-10983	28	4	development	development	NOUN
ajst-10983	28	5	and	and	CCONJ
ajst-10983	28	6	progress	progress	NOUN
ajst-10983	28	7	of	of	ADP
ajst-10983	28	8	high	high	ADJ
ajst-10983	28	9	and	and	CCONJ
ajst-10983	28	10	new	new	ADJ
ajst-10983	28	11	technologies	technology	NOUN
ajst-10983	28	12	,	,	PUNCT
ajst-10983	28	13	currently	currently	ADV
ajst-10983	28	14	commonly	commonly	ADV
ajst-10983	28	15	used	use	VERB
ajst-10983	28	16	root	root	NOUN
ajst-10983	28	17	in	in	ADP
ajst-10983	28	18	-	-	PUNCT
ajst-10983	28	19	situ	situ	NOUN
ajst-10983	28	20	detection	detection	NOUN
ajst-10983	28	21	methods	method	NOUN
ajst-10983	28	22	include	include	VERB
ajst-10983	28	23	x	x	NOUN
ajst-10983	28	24	-	-	NOUN
ajst-10983	28	25	ray	ray	NOUN
ajst-10983	28	26	tomography	tomography	NOUN
ajst-10983	28	27	(	(	PUNCT
ajst-10983	28	28	xct	xct	PROPN
ajst-10983	28	29	)	)	PUNCT
ajst-10983	29	1	[	[	X
ajst-10983	29	2	6	6	NUM
ajst-10983	29	3	]	]	PUNCT
ajst-10983	29	4	,	,	PUNCT
ajst-10983	29	5	magnetic	magnetic	ADJ
ajst-10983	29	6	resonance	resonance	NOUN
ajst-10983	29	7	imaging	imaging	NOUN
ajst-10983	29	8	(	(	PUNCT
ajst-10983	29	9	mri	mri	NOUN
ajst-10983	29	10	)	)	PUNCT
ajst-10983	30	1	[	[	X
ajst-10983	30	2	7	7	X
ajst-10983	30	3	]	]	PUNCT
ajst-10983	30	4	and	and	CCONJ
ajst-10983	30	5	digital	digital	ADJ
ajst-10983	30	6	device	device	NOUN
ajst-10983	30	7	imaging	imaging	NOUN
ajst-10983	31	1	[	[	X
ajst-10983	31	2	8	8	NUM
ajst-10983	31	3	]	]	PUNCT
ajst-10983	31	4	.	.	PUNCT
ajst-10983	32	1	xct	xct	PROPN
ajst-10983	32	2	of	of	ADP
ajst-10983	32	3	roots	root	NOUN
ajst-10983	32	4	scans	scan	VERB
ajst-10983	32	5	the	the	DET
ajst-10983	32	6	in	in	ADP
ajst-10983	32	7	-	-	PUNCT
ajst-10983	32	8	situ	situ	NOUN
ajst-10983	32	9	root	root	NOUN
ajst-10983	32	10	soil	soil	NOUN
ajst-10983	32	11	with	with	ADP
ajst-10983	32	12	x	x	NOUN
ajst-10983	32	13	-	-	NOUN
ajst-10983	32	14	rays	ray	NOUN
ajst-10983	32	15	to	to	PART
ajst-10983	32	16	obtain	obtain	VERB
ajst-10983	32	17	attenuation	attenuation	NOUN
ajst-10983	32	18	coefficients	coefficient	NOUN
ajst-10983	32	19	of	of	ADP
ajst-10983	32	20	cross	cross	ADJ
ajst-10983	32	21	-	-	ADJ
ajst-10983	32	22	sectional	sectional	ADJ
ajst-10983	32	23	faults	fault	NOUN
ajst-10983	32	24	of	of	ADP
ajst-10983	32	25	different	different	ADJ
ajst-10983	32	26	objects	object	NOUN
ajst-10983	32	27	,	,	PUNCT
ajst-10983	32	28	and	and	CCONJ
ajst-10983	32	29	then	then	ADV
ajst-10983	32	30	realizes	realize	VERB
ajst-10983	32	31	three	three	NUM
ajst-10983	32	32	-	-	PUNCT
ajst-10983	32	33	dimensional	dimensional	ADJ
ajst-10983	32	34	26	26	NUM
ajst-10983	32	35	visualization	visualization	NOUN
ajst-10983	32	36	of	of	ADP
ajst-10983	32	37	plant	plant	NOUN
ajst-10983	32	38	root	root	NOUN
ajst-10983	32	39	configuration	configuration	NOUN
ajst-10983	32	40	through	through	ADP
ajst-10983	32	41	image	image	NOUN
ajst-10983	32	42	fault	fault	NOUN
ajst-10983	32	43	reconstruction	reconstruction	NOUN
ajst-10983	32	44	algorithm	algorithm	NOUN
ajst-10983	33	1	[	[	X
ajst-10983	33	2	9][10][11	9][10][11	X
ajst-10983	33	3	]	]	PUNCT
ajst-10983	33	4	.	.	PUNCT
ajst-10983	34	1	in	in	ADP
ajst-10983	34	2	the	the	DET
ajst-10983	34	3	1990s	1990	NOUN
ajst-10983	34	4	,	,	PUNCT
ajst-10983	34	5	wantanabe	wantanabe	NOUN
ajst-10983	34	6	et	et	PROPN
ajst-10983	34	7	al	al	PROPN
ajst-10983	34	8	.	.	PUNCT
ajst-10983	35	1	[	[	X
ajst-10983	35	2	12	12	NUM
ajst-10983	35	3	]	]	PUNCT
ajst-10983	35	4	first	first	ADV
ajst-10983	35	5	applied	apply	VERB
ajst-10983	35	6	xct	xct	PROPN
ajst-10983	35	7	technology	technology	PROPN
ajst-10983	35	8	to	to	ADP
ajst-10983	35	9	the	the	DET
ajst-10983	35	10	analysis	analysis	NOUN
ajst-10983	35	11	and	and	CCONJ
ajst-10983	35	12	study	study	NOUN
ajst-10983	35	13	of	of	ADP
ajst-10983	35	14	plant	plant	NOUN
ajst-10983	35	15	roots	root	NOUN
ajst-10983	35	16	,	,	PUNCT
ajst-10983	35	17	but	but	CCONJ
ajst-10983	35	18	due	due	ADP
ajst-10983	35	19	to	to	ADP
ajst-10983	35	20	the	the	DET
ajst-10983	35	21	limitations	limitation	NOUN
ajst-10983	35	22	of	of	ADP
ajst-10983	35	23	technical	technical	ADJ
ajst-10983	35	24	conditions	condition	NOUN
ajst-10983	35	25	,	,	PUNCT
ajst-10983	35	26	the	the	DET
ajst-10983	35	27	complete	complete	ADJ
ajst-10983	35	28	form	form	NOUN
ajst-10983	35	29	of	of	ADP
ajst-10983	35	30	plant	plant	NOUN
ajst-10983	35	31	roots	root	NOUN
ajst-10983	35	32	could	could	AUX
ajst-10983	35	33	not	not	PART
ajst-10983	35	34	be	be	AUX
ajst-10983	35	35	clearly	clearly	ADV
ajst-10983	35	36	observed	observe	VERB
ajst-10983	35	37	.	.	PUNCT
ajst-10983	36	1	with	with	ADP
ajst-10983	36	2	the	the	DET
ajst-10983	36	3	advancement	advancement	NOUN
ajst-10983	36	4	of	of	ADP
ajst-10983	36	5	technology	technology	NOUN
ajst-10983	36	6	,	,	PUNCT
ajst-10983	36	7	han	han	PROPN
ajst-10983	36	8	et	et	PROPN
ajst-10983	36	9	al	al	PROPN
ajst-10983	36	10	.	.	PUNCT
ajst-10983	37	1	[	[	X
ajst-10983	37	2	13	13	NUM
ajst-10983	37	3	]	]	PUNCT
ajst-10983	37	4	discussed	discuss	VERB
ajst-10983	37	5	the	the	DET
ajst-10983	37	6	common	common	ADJ
ajst-10983	37	7	diseases	disease	NOUN
ajst-10983	37	8	of	of	ADP
ajst-10983	37	9	potato	potato	NOUN
ajst-10983	37	10	in	in	ADP
ajst-10983	37	11	soil	soil	NOUN
ajst-10983	37	12	on	on	ADP
ajst-10983	37	13	the	the	DET
ajst-10983	37	14	basis	basis	NOUN
ajst-10983	37	15	of	of	ADP
ajst-10983	37	16	xct	xct	PROPN
ajst-10983	37	17	imaging	imaging	PROPN
ajst-10983	37	18	technology	technology	NOUN
ajst-10983	37	19	,	,	PUNCT
ajst-10983	37	20	and	and	CCONJ
ajst-10983	37	21	proved	prove	VERB
ajst-10983	37	22	the	the	DET
ajst-10983	37	23	potential	potential	NOUN
ajst-10983	37	24	of	of	ADP
ajst-10983	37	25	xct	xct	PROPN
ajst-10983	37	26	observation	observation	NOUN
ajst-10983	37	27	method	method	NOUN
ajst-10983	37	28	in	in	ADP
ajst-10983	37	29	plant	plant	NOUN
ajst-10983	37	30	pathology	pathology	NOUN
ajst-10983	37	31	research	research	NOUN
ajst-10983	37	32	.	.	PUNCT
ajst-10983	38	1	subsequently	subsequently	ADV
ajst-10983	38	2	,	,	PUNCT
ajst-10983	38	3	zhou	zhou	PROPN
ajst-10983	38	4	xuecheng	xuecheng	PROPN
ajst-10983	38	5	et	et	PROPN
ajst-10983	38	6	al	al	PROPN
ajst-10983	38	7	.	.	PUNCT
ajst-10983	39	1	[	[	X
ajst-10983	39	2	14	14	NUM
ajst-10983	39	3	]	]	PUNCT
ajst-10983	39	4	conducted	conduct	VERB
ajst-10983	39	5	qualitative	qualitative	ADJ
ajst-10983	39	6	tomography	tomography	NOUN
ajst-10983	39	7	scanning	scanning	NOUN
ajst-10983	39	8	of	of	ADP
ajst-10983	39	9	root	root	NOUN
ajst-10983	39	10	images	image	NOUN
ajst-10983	39	11	by	by	ADP
ajst-10983	39	12	x	x	NOUN
ajst-10983	39	13	-	-	NOUN
ajst-10983	39	14	ray	ray	NOUN
ajst-10983	39	15	,	,	PUNCT
ajst-10983	39	16	and	and	CCONJ
ajst-10983	39	17	used	use	VERB
ajst-10983	39	18	gray	gray	ADJ
ajst-10983	39	19	histogram	histogram	NOUN
ajst-10983	39	20	analysis	analysis	NOUN
ajst-10983	39	21	to	to	PART
ajst-10983	39	22	find	find	VERB
ajst-10983	39	23	the	the	DET
ajst-10983	39	24	overall	overall	ADJ
ajst-10983	39	25	characteristics	characteristic	NOUN
ajst-10983	39	26	of	of	ADP
ajst-10983	39	27	gray	gray	ADJ
ajst-10983	39	28	distribution	distribution	NOUN
ajst-10983	39	29	of	of	ADP
ajst-10983	39	30	in	in	ADP
ajst-10983	39	31	situ	situ	ADJ
ajst-10983	39	32	ct	ct	NOUN
ajst-10983	39	33	images	image	NOUN
ajst-10983	39	34	of	of	ADP
ajst-10983	39	35	plant	plant	NOUN
ajst-10983	39	36	roots	root	NOUN
ajst-10983	39	37	,	,	PUNCT
ajst-10983	39	38	so	so	SCONJ
ajst-10983	39	39	as	as	SCONJ
ajst-10983	39	40	to	to	PART
ajst-10983	39	41	quickly	quickly	ADV
ajst-10983	39	42	and	and	CCONJ
ajst-10983	39	43	accurately	accurately	ADV
ajst-10983	39	44	detect	detect	VERB
ajst-10983	39	45	root	root	NOUN
ajst-10983	39	46	characteristics	characteristic	NOUN
ajst-10983	39	47	.	.	PUNCT
ajst-10983	40	1	in	in	ADP
ajst-10983	40	2	recent	recent	ADJ
ajst-10983	40	3	years	year	NOUN
ajst-10983	40	4	,	,	PUNCT
ajst-10983	40	5	zhao	zhao	PROPN
ajst-10983	40	6	xu	xu	PROPN
ajst-10983	40	7	et	et	PROPN
ajst-10983	40	8	al	al	PROPN
ajst-10983	40	9	.	.	PUNCT
ajst-10983	41	1	[	[	X
ajst-10983	41	2	15	15	NUM
ajst-10983	41	3	]	]	PUNCT
ajst-10983	41	4	constructed	construct	VERB
ajst-10983	41	5	a	a	DET
ajst-10983	41	6	three	three	NUM
ajst-10983	41	7	-	-	PUNCT
ajst-10983	41	8	dimensional	dimensional	ADJ
ajst-10983	41	9	lossless	lossless	ADJ
ajst-10983	41	10	geometric	geometric	ADJ
ajst-10983	41	11	model	model	NOUN
ajst-10983	41	12	of	of	ADP
ajst-10983	41	13	maize	maize	NOUN
ajst-10983	41	14	in	in	ADP
ajst-10983	41	15	-	-	PUNCT
ajst-10983	41	16	situ	situ	NOUN
ajst-10983	41	17	root	root	NOUN
ajst-10983	41	18	system	system	NOUN
ajst-10983	41	19	by	by	ADP
ajst-10983	41	20	combining	combine	VERB
ajst-10983	41	21	xct	xct	PROPN
ajst-10983	41	22	in	in	ADP
ajst-10983	41	23	-	-	PUNCT
ajst-10983	41	24	situ	situ	NOUN
ajst-10983	41	25	scanning	scanning	NOUN
ajst-10983	41	26	technology	technology	NOUN
ajst-10983	41	27	and	and	CCONJ
ajst-10983	41	28	filtered	filter	VERB
ajst-10983	41	29	back	back	ADP
ajst-10983	41	30	projection	projection	NOUN
ajst-10983	41	31	reconstruction	reconstruction	NOUN
ajst-10983	41	32	method	method	NOUN
ajst-10983	41	33	.	.	PUNCT
ajst-10983	42	1	in	in	ADP
ajst-10983	42	2	addition	addition	NOUN
ajst-10983	42	3	,	,	PUNCT
ajst-10983	42	4	chen	chen	PROPN
ajst-10983	42	5	jun	jun	PROPN
ajst-10983	42	6	[	[	X
ajst-10983	42	7	16	16	NUM
ajst-10983	42	8	]	]	PUNCT
ajst-10983	42	9	used	use	VERB
ajst-10983	42	10	ct	ct	NUM
ajst-10983	42	11	imaging	imaging	NOUN
ajst-10983	42	12	technology	technology	NOUN
ajst-10983	42	13	to	to	PART
ajst-10983	42	14	obtain	obtain	VERB
ajst-10983	42	15	ct	ct	NUM
ajst-10983	42	16	images	image	NOUN
ajst-10983	42	17	of	of	ADP
ajst-10983	42	18	corn	corn	NOUN
ajst-10983	42	19	roots	root	NOUN
ajst-10983	42	20	,	,	PUNCT
ajst-10983	42	21	and	and	CCONJ
ajst-10983	42	22	used	use	VERB
ajst-10983	42	23	image	image	NOUN
ajst-10983	42	24	processing	processing	NOUN
ajst-10983	42	25	technology	technology	NOUN
ajst-10983	42	26	to	to	PART
ajst-10983	42	27	conduct	conduct	VERB
ajst-10983	42	28	nondestructive	nondestructive	ADJ
ajst-10983	42	29	testing	testing	NOUN
ajst-10983	42	30	of	of	ADP
ajst-10983	42	31	samples	sample	NOUN
ajst-10983	42	32	.	.	PUNCT
ajst-10983	43	1	xct	xct	PROPN
ajst-10983	43	2	technology	technology	PROPN
ajst-10983	43	3	has	have	AUX
ajst-10983	43	4	played	play	VERB
ajst-10983	43	5	a	a	DET
ajst-10983	43	6	great	great	ADJ
ajst-10983	43	7	role	role	NOUN
ajst-10983	43	8	in	in	ADP
ajst-10983	43	9	promoting	promote	VERB
ajst-10983	43	10	the	the	DET
ajst-10983	43	11	research	research	NOUN
ajst-10983	43	12	of	of	ADP
ajst-10983	43	13	in	in	ADP
ajst-10983	43	14	situ	situ	ADJ
ajst-10983	43	15	root	root	NOUN
ajst-10983	43	16	imaging	imaging	NOUN
ajst-10983	43	17	of	of	ADP
ajst-10983	43	18	plants	plant	NOUN
ajst-10983	43	19	.	.	PUNCT
ajst-10983	44	1	however	however	ADV
ajst-10983	44	2	,	,	PUNCT
ajst-10983	44	3	xct	xct	PROPN
ajst-10983	44	4	technology	technology	PROPN
ajst-10983	44	5	only	only	ADV
ajst-10983	44	6	relies	rely	VERB
ajst-10983	44	7	on	on	ADP
ajst-10983	44	8	the	the	DET
ajst-10983	44	9	difference	difference	NOUN
ajst-10983	44	10	of	of	ADP
ajst-10983	44	11	a	a	DET
ajst-10983	44	12	single	single	ADJ
ajst-10983	44	13	attenuation	attenuation	NOUN
ajst-10983	44	14	coefficient	coefficient	NOUN
ajst-10983	44	15	between	between	ADP
ajst-10983	44	16	substances	substance	NOUN
ajst-10983	44	17	to	to	PART
ajst-10983	44	18	determine	determine	VERB
ajst-10983	44	19	the	the	DET
ajst-10983	44	20	imaging	imaging	NOUN
ajst-10983	44	21	features	feature	NOUN
ajst-10983	44	22	.	.	PUNCT
ajst-10983	45	1	when	when	SCONJ
ajst-10983	45	2	confronted	confront	VERB
ajst-10983	45	3	with	with	ADP
ajst-10983	45	4	complex	complex	ADJ
ajst-10983	45	5	soil	soil	NOUN
ajst-10983	45	6	environment	environment	NOUN
ajst-10983	45	7	and	and	CCONJ
ajst-10983	45	8	root	root	NOUN
ajst-10983	45	9	distribution	distribution	NOUN
ajst-10983	45	10	,	,	PUNCT
ajst-10983	45	11	the	the	DET
ajst-10983	45	12	contrast	contrast	NOUN
ajst-10983	45	13	will	will	AUX
ajst-10983	45	14	deteriorate	deteriorate	VERB
ajst-10983	45	15	and	and	CCONJ
ajst-10983	45	16	root	root	NOUN
ajst-10983	45	17	noise	noise	NOUN
ajst-10983	45	18	will	will	AUX
ajst-10983	45	19	appear	appear	VERB
ajst-10983	45	20	in	in	ADP
ajst-10983	45	21	the	the	DET
ajst-10983	45	22	imaging	imaging	NOUN
ajst-10983	45	23	results	result	NOUN
ajst-10983	45	24	,	,	PUNCT
ajst-10983	45	25	which	which	PRON
ajst-10983	45	26	brings	bring	VERB
ajst-10983	45	27	difficulties	difficulty	NOUN
ajst-10983	45	28	to	to	PART
ajst-10983	45	29	root	root	VERB
ajst-10983	45	30	image	image	NOUN
ajst-10983	45	31	segmentation	segmentation	NOUN
ajst-10983	45	32	research	research	NOUN
ajst-10983	45	33	and	and	CCONJ
ajst-10983	45	34	leads	lead	VERB
ajst-10983	45	35	to	to	ADP
ajst-10983	45	36	errors	error	NOUN
ajst-10983	45	37	in	in	ADP
ajst-10983	45	38	the	the	DET
ajst-10983	45	39	subsequent	subsequent	ADJ
ajst-10983	45	40	statistical	statistical	ADJ
ajst-10983	45	41	data	datum	NOUN
ajst-10983	45	42	of	of	ADP
ajst-10983	45	43	plant	plant	NOUN
ajst-10983	45	44	root	root	NOUN
ajst-10983	45	45	phenotype	phenotype	NOUN
ajst-10983	46	1	[	[	X
ajst-10983	46	2	17	17	NUM
ajst-10983	46	3	]	]	PUNCT
ajst-10983	46	4	.	.	PUNCT
ajst-10983	47	1	magnetic	magnetic	ADJ
ajst-10983	47	2	resonance	resonance	NOUN
ajst-10983	47	3	imaging	imaging	NOUN
ajst-10983	47	4	uses	use	VERB
ajst-10983	47	5	radio	radio	NOUN
ajst-10983	47	6	frequency	frequency	NOUN
ajst-10983	47	7	electromagnetic	electromagnetic	ADJ
ajst-10983	47	8	waves	wave	NOUN
ajst-10983	47	9	to	to	PART
ajst-10983	47	10	obtain	obtain	VERB
ajst-10983	47	11	image	image	NOUN
ajst-10983	47	12	information	information	NOUN
ajst-10983	47	13	,	,	PUNCT
ajst-10983	47	14	codes	code	VERB
ajst-10983	47	15	signals	signal	NOUN
ajst-10983	47	16	sent	send	VERB
ajst-10983	47	17	out	out	ADP
ajst-10983	47	18	by	by	ADP
ajst-10983	47	19	detecting	detect	VERB
ajst-10983	47	20	different	different	ADJ
ajst-10983	47	21	positions	position	NOUN
ajst-10983	47	22	of	of	ADP
ajst-10983	47	23	magnetic	magnetic	ADJ
ajst-10983	47	24	field	field	NOUN
ajst-10983	47	25	cores	core	NOUN
ajst-10983	47	26	,	,	PUNCT
ajst-10983	47	27	and	and	CCONJ
ajst-10983	47	28	presents	present	VERB
ajst-10983	47	29	the	the	DET
ajst-10983	47	30	internal	internal	ADJ
ajst-10983	47	31	structure	structure	NOUN
ajst-10983	47	32	and	and	CCONJ
ajst-10983	47	33	organizational	organizational	ADJ
ajst-10983	47	34	morphology	morphology	NOUN
ajst-10983	47	35	of	of	ADP
ajst-10983	47	36	scanned	scan	VERB
ajst-10983	47	37	objects	object	NOUN
ajst-10983	47	38	on	on	ADP
ajst-10983	47	39	the	the	DET
ajst-10983	47	40	image	image	NOUN
ajst-10983	47	41	,	,	PUNCT
ajst-10983	47	42	thus	thus	ADV
ajst-10983	47	43	using	use	VERB
ajst-10983	47	44	computer	computer	NOUN
ajst-10983	47	45	image	image	NOUN
ajst-10983	47	46	reconstruction	reconstruction	NOUN
ajst-10983	47	47	to	to	PART
ajst-10983	47	48	generate	generate	VERB
ajst-10983	47	49	images	image	NOUN
ajst-10983	47	50	[	[	X
ajst-10983	47	51	18	18	NUM
ajst-10983	47	52	]	]	PUNCT
ajst-10983	47	53	.	.	PUNCT
ajst-10983	48	1	this	this	DET
ajst-10983	48	2	observation	observation	NOUN
ajst-10983	48	3	technology	technology	NOUN
ajst-10983	48	4	has	have	AUX
ajst-10983	48	5	been	be	AUX
ajst-10983	48	6	applied	apply	VERB
ajst-10983	48	7	in	in	ADP
ajst-10983	48	8	many	many	ADJ
ajst-10983	48	9	fields	field	NOUN
ajst-10983	48	10	of	of	ADP
ajst-10983	48	11	plant	plant	NOUN
ajst-10983	48	12	root	root	NOUN
ajst-10983	48	13	research	research	NOUN
ajst-10983	48	14	.	.	PUNCT
ajst-10983	49	1	for	for	ADP
ajst-10983	49	2	example	example	NOUN
ajst-10983	49	3	,	,	PUNCT
ajst-10983	49	4	super	super	ADJ
ajst-10983	49	5	-	-	ADJ
ajst-10983	49	6	resolution	resolution	ADJ
ajst-10983	49	7	images	image	NOUN
ajst-10983	49	8	of	of	ADP
ajst-10983	49	9	plant	plant	NOUN
ajst-10983	49	10	roots	root	NOUN
ajst-10983	49	11	were	be	AUX
ajst-10983	49	12	obtained	obtain	VERB
ajst-10983	49	13	by	by	ADP
ajst-10983	49	14	three	three	NUM
ajst-10983	49	15	-	-	PUNCT
ajst-10983	49	16	dimensional	dimensional	ADJ
ajst-10983	49	17	reconstruction	reconstruction	NOUN
ajst-10983	49	18	of	of	ADP
ajst-10983	49	19	plant	plant	NOUN
ajst-10983	49	20	roots	root	NOUN
ajst-10983	49	21	[	[	X
ajst-10983	49	22	19	19	NUM
ajst-10983	49	23	]	]	PUNCT
ajst-10983	49	24	,	,	PUNCT
ajst-10983	49	25	dynamic	dynamic	ADJ
ajst-10983	49	26	distribution	distribution	NOUN
ajst-10983	49	27	of	of	ADP
ajst-10983	49	28	water	water	NOUN
ajst-10983	49	29	and	and	CCONJ
ajst-10983	49	30	sugar	sugar	NOUN
ajst-10983	49	31	in	in	ADP
ajst-10983	49	32	wheat	wheat	NOUN
ajst-10983	49	33	filling	filling	NOUN
ajst-10983	49	34	period	period	NOUN
ajst-10983	49	35	[	[	X
ajst-10983	49	36	20	20	NUM
ajst-10983	49	37	]	]	PUNCT
ajst-10983	49	38	,	,	PUNCT
ajst-10983	49	39	and	and	CCONJ
ajst-10983	49	40	underground	underground	ADJ
ajst-10983	49	41	pathological	pathological	ADJ
ajst-10983	49	42	symptoms	symptom	NOUN
ajst-10983	49	43	of	of	ADP
ajst-10983	49	44	sugar	sugar	NOUN
ajst-10983	49	45	beet	beet	NOUN
ajst-10983	50	1	[	[	X
ajst-10983	50	2	21	21	NUM
ajst-10983	50	3	]	]	PUNCT
ajst-10983	50	4	.	.	PUNCT
ajst-10983	51	1	although	although	SCONJ
ajst-10983	51	2	the	the	DET
ajst-10983	51	3	technology	technology	NOUN
ajst-10983	51	4	will	will	AUX
ajst-10983	51	5	not	not	PART
ajst-10983	51	6	cause	cause	VERB
ajst-10983	51	7	noise	noise	NOUN
ajst-10983	51	8	due	due	ADP
ajst-10983	51	9	to	to	ADP
ajst-10983	51	10	the	the	DET
ajst-10983	51	11	similar	similar	ADJ
ajst-10983	51	12	density	density	NOUN
ajst-10983	51	13	of	of	ADP
ajst-10983	51	14	soil	soil	NOUN
ajst-10983	51	15	and	and	CCONJ
ajst-10983	51	16	roots	root	NOUN
ajst-10983	51	17	,	,	PUNCT
ajst-10983	51	18	the	the	DET
ajst-10983	51	19	detection	detection	NOUN
ajst-10983	51	20	of	of	ADP
ajst-10983	51	21	trace	trace	NOUN
ajst-10983	51	22	elements	element	NOUN
ajst-10983	51	23	such	such	ADJ
ajst-10983	51	24	as	as	ADP
ajst-10983	51	25	iron	iron	NOUN
ajst-10983	51	26	will	will	AUX
ajst-10983	51	27	interfere	interfere	VERB
ajst-10983	51	28	with	with	ADP
ajst-10983	51	29	the	the	DET
ajst-10983	51	30	nmr	nmr	NOUN
ajst-10983	51	31	signal	signal	NOUN
ajst-10983	51	32	,	,	PUNCT
ajst-10983	51	33	resulting	result	VERB
ajst-10983	51	34	in	in	ADP
ajst-10983	51	35	greater	great	ADJ
ajst-10983	51	36	noise	noise	NOUN
ajst-10983	51	37	in	in	ADP
ajst-10983	51	38	the	the	DET
ajst-10983	51	39	root	root	NOUN
ajst-10983	51	40	image	image	NOUN
ajst-10983	51	41	,	,	PUNCT
ajst-10983	51	42	making	make	VERB
ajst-10983	51	43	it	it	PRON
ajst-10983	51	44	difficult	difficult	ADJ
ajst-10983	51	45	to	to	PART
ajst-10983	51	46	image	image	VERB
ajst-10983	51	47	.	.	PUNCT
ajst-10983	52	1	in	in	ADP
ajst-10983	52	2	recent	recent	ADJ
ajst-10983	52	3	years	year	NOUN
ajst-10983	52	4	,	,	PUNCT
ajst-10983	52	5	digital	digital	ADJ
ajst-10983	52	6	technology	technology	NOUN
ajst-10983	52	7	has	have	AUX
ajst-10983	52	8	become	become	VERB
ajst-10983	52	9	more	more	ADV
ajst-10983	52	10	and	and	CCONJ
ajst-10983	52	11	more	more	ADV
ajst-10983	52	12	powerful	powerful	ADJ
ajst-10983	52	13	,	,	PUNCT
ajst-10983	52	14	and	and	CCONJ
ajst-10983	52	15	the	the	DET
ajst-10983	52	16	research	research	NOUN
ajst-10983	52	17	of	of	ADP
ajst-10983	52	18	plant	plant	NOUN
ajst-10983	52	19	roots	root	NOUN
ajst-10983	52	20	also	also	ADV
ajst-10983	52	21	tends	tend	VERB
ajst-10983	52	22	to	to	PART
ajst-10983	52	23	use	use	VERB
ajst-10983	52	24	digital	digital	ADJ
ajst-10983	52	25	equipment	equipment	NOUN
ajst-10983	52	26	imaging	imaging	NOUN
ajst-10983	52	27	method	method	NOUN
ajst-10983	52	28	.	.	PUNCT
ajst-10983	53	1	digital	digital	ADJ
ajst-10983	53	2	device	device	NOUN
ajst-10983	53	3	imaging	imaging	NOUN
ajst-10983	53	4	refers	refer	VERB
ajst-10983	53	5	to	to	ADP
ajst-10983	53	6	non	non	ADJ
ajst-10983	53	7	-	-	ADJ
ajst-10983	53	8	invasive	invasive	ADJ
ajst-10983	53	9	image	image	NOUN
ajst-10983	53	10	acquisition	acquisition	NOUN
ajst-10983	53	11	of	of	ADP
ajst-10983	53	12	roots	root	NOUN
ajst-10983	53	13	through	through	ADP
ajst-10983	53	14	the	the	DET
ajst-10983	53	15	use	use	NOUN
ajst-10983	53	16	of	of	ADP
ajst-10983	53	17	digital	digital	ADJ
ajst-10983	53	18	devices	device	NOUN
ajst-10983	53	19	such	such	ADJ
ajst-10983	53	20	as	as	ADP
ajst-10983	53	21	smart	smart	ADJ
ajst-10983	53	22	cameras	camera	NOUN
ajst-10983	53	23	,	,	PUNCT
ajst-10983	53	24	scanners	scanner	NOUN
ajst-10983	53	25	and	and	CCONJ
ajst-10983	53	26	smartphones	smartphone	NOUN
ajst-10983	53	27	.	.	PUNCT
ajst-10983	54	1	progress	progress	NOUN
ajst-10983	54	2	has	have	AUX
ajst-10983	54	3	been	be	AUX
ajst-10983	54	4	made	make	VERB
ajst-10983	54	5	in	in	ADP
ajst-10983	54	6	root	root	NOUN
ajst-10983	54	7	segmentation	segmentation	NOUN
ajst-10983	54	8	of	of	ADP
ajst-10983	54	9	many	many	ADJ
ajst-10983	54	10	plants	plant	NOUN
ajst-10983	54	11	.	.	PUNCT
ajst-10983	55	1	firstly	firstly	ADV
ajst-10983	55	2	,	,	PUNCT
ajst-10983	55	3	high	high	ADJ
ajst-10983	55	4	-	-	PUNCT
ajst-10983	55	5	resolution	resolution	NOUN
ajst-10983	55	6	root	root	NOUN
ajst-10983	55	7	growth	growth	NOUN
ajst-10983	55	8	imaging	imaging	NOUN
ajst-10983	55	9	device	device	NOUN
ajst-10983	55	10	based	base	VERB
ajst-10983	55	11	on	on	ADP
ajst-10983	55	12	digital	digital	ADJ
ajst-10983	55	13	equipment	equipment	NOUN
ajst-10983	55	14	was	be	AUX
ajst-10983	55	15	used	use	VERB
ajst-10983	55	16	to	to	PART
ajst-10983	55	17	obtain	obtain	VERB
ajst-10983	55	18	in	in	ADP
ajst-10983	55	19	situ	situ	ADJ
ajst-10983	55	20	root	root	NOUN
ajst-10983	55	21	image	image	NOUN
ajst-10983	55	22	of	of	ADP
ajst-10983	55	23	cotton	cotton	NOUN
ajst-10983	56	1	[	[	X
ajst-10983	56	2	17	17	NUM
ajst-10983	56	3	]	]	PUNCT
ajst-10983	56	4	,	,	PUNCT
ajst-10983	56	5	and	and	CCONJ
ajst-10983	56	6	the	the	DET
ajst-10983	56	7	image	image	NOUN
ajst-10983	56	8	of	of	ADP
ajst-10983	56	9	plant	plant	NOUN
ajst-10983	56	10	in	in	ADP
ajst-10983	56	11	situ	situ	ADJ
ajst-10983	56	12	root	root	NOUN
ajst-10983	56	13	with	with	ADP
ajst-10983	56	14	1920	1920	NUM
ajst-10983	56	15	*	*	SYM
ajst-10983	56	16	1080	1080	NUM
ajst-10983	56	17	pixels	pixel	NOUN
ajst-10983	56	18	was	be	AUX
ajst-10983	56	19	collected	collect	VERB
ajst-10983	56	20	by	by	ADP
ajst-10983	56	21	digital	digital	ADJ
ajst-10983	56	22	equipment	equipment	NOUN
ajst-10983	57	1	[	[	X
ajst-10983	57	2	22	22	NUM
ajst-10983	57	3	]	]	PUNCT
ajst-10983	57	4	,	,	PUNCT
ajst-10983	57	5	or	or	CCONJ
ajst-10983	57	6	the	the	DET
ajst-10983	57	7	morphological	morphological	ADJ
ajst-10983	57	8	changes	change	NOUN
ajst-10983	57	9	of	of	ADP
ajst-10983	57	10	in	in	ADP
ajst-10983	57	11	situ	situ	ADJ
ajst-10983	57	12	root	root	NOUN
ajst-10983	57	13	of	of	ADP
ajst-10983	57	14	potted	pot	VERB
ajst-10983	57	15	castor	castor	NOUN
ajst-10983	57	16	bean	bean	NOUN
ajst-10983	57	17	were	be	AUX
ajst-10983	57	18	dynamically	dynamically	ADV
ajst-10983	57	19	observed	observe	VERB
ajst-10983	57	20	by	by	ADP
ajst-10983	57	21	scanner	scanner	NOUN
ajst-10983	57	22	[	[	X
ajst-10983	57	23	23	23	NUM
ajst-10983	57	24	]	]	PUNCT
ajst-10983	57	25	.	.	PUNCT
ajst-10983	58	1	at	at	ADP
ajst-10983	58	2	the	the	DET
ajst-10983	58	3	same	same	ADJ
ajst-10983	58	4	time	time	NOUN
ajst-10983	58	5	,	,	PUNCT
ajst-10983	58	6	scanning	scan	VERB
ajst-10983	58	7	devices	device	NOUN
ajst-10983	58	8	such	such	ADJ
ajst-10983	58	9	as	as	ADP
ajst-10983	58	10	handheld	handheld	ADJ
ajst-10983	58	11	scanners	scanner	NOUN
ajst-10983	58	12	and	and	CCONJ
ajst-10983	58	13	flatbed	flatbed	ADJ
ajst-10983	58	14	scanners	scanner	NOUN
ajst-10983	58	15	were	be	AUX
ajst-10983	58	16	used	use	VERB
ajst-10983	58	17	to	to	PART
ajst-10983	58	18	detect	detect	VERB
ajst-10983	58	19	walnut	walnut	NOUN
ajst-10983	58	20	roots	root	NOUN
ajst-10983	58	21	,	,	PUNCT
ajst-10983	58	22	so	so	SCONJ
ajst-10983	58	23	as	as	SCONJ
ajst-10983	58	24	to	to	PART
ajst-10983	58	25	extract	extract	VERB
ajst-10983	58	26	the	the	DET
ajst-10983	58	27	organizational	organizational	ADJ
ajst-10983	58	28	characteristics	characteristic	NOUN
ajst-10983	58	29	of	of	ADP
ajst-10983	58	30	the	the	DET
ajst-10983	58	31	huge	huge	ADJ
ajst-10983	58	32	tree	tree	NOUN
ajst-10983	58	33	roots	root	NOUN
ajst-10983	58	34	[	[	X
ajst-10983	58	35	24	24	NUM
ajst-10983	58	36	]	]	PUNCT
ajst-10983	58	37	.	.	PUNCT
ajst-10983	59	1	digital	digital	ADJ
ajst-10983	59	2	imaging	imaging	NOUN
ajst-10983	59	3	of	of	ADP
ajst-10983	59	4	plant	plant	NOUN
ajst-10983	59	5	roots	root	NOUN
ajst-10983	59	6	is	be	AUX
ajst-10983	59	7	a	a	DET
ajst-10983	59	8	non	non	ADJ
ajst-10983	59	9	-	-	ADJ
ajst-10983	59	10	invasive	invasive	ADJ
ajst-10983	59	11	root	root	NOUN
ajst-10983	59	12	analysis	analysis	NOUN
ajst-10983	59	13	method	method	NOUN
ajst-10983	59	14	based	base	VERB
ajst-10983	59	15	on	on	ADP
ajst-10983	59	16	computer	computer	NOUN
ajst-10983	59	17	vision	vision	NOUN
ajst-10983	59	18	technology	technology	NOUN
ajst-10983	59	19	.	.	PUNCT
ajst-10983	60	1	compared	compare	VERB
ajst-10983	60	2	with	with	ADP
ajst-10983	60	3	traditional	traditional	ADJ
ajst-10983	60	4	manual	manual	ADJ
ajst-10983	60	5	operation	operation	NOUN
ajst-10983	60	6	or	or	CCONJ
ajst-10983	60	7	root	root	NOUN
ajst-10983	60	8	dyeing	dyeing	NOUN
ajst-10983	60	9	methods	method	NOUN
ajst-10983	60	10	,	,	PUNCT
ajst-10983	60	11	it	it	PRON
ajst-10983	60	12	has	have	VERB
ajst-10983	60	13	many	many	ADJ
ajst-10983	60	14	advantages	advantage	NOUN
ajst-10983	60	15	.	.	PUNCT
ajst-10983	61	1	first	first	ADV
ajst-10983	61	2	,	,	PUNCT
ajst-10983	61	3	the	the	DET
ajst-10983	61	4	method	method	NOUN
ajst-10983	61	5	can	can	AUX
ajst-10983	61	6	image	image	VERB
ajst-10983	61	7	the	the	DET
ajst-10983	61	8	whole	whole	ADJ
ajst-10983	61	9	root	root	NOUN
ajst-10983	61	10	system	system	NOUN
ajst-10983	61	11	with	with	ADP
ajst-10983	61	12	high	high	ADJ
ajst-10983	61	13	resolution	resolution	NOUN
ajst-10983	61	14	and	and	CCONJ
ajst-10983	61	15	large	large	ADJ
ajst-10983	61	16	area	area	NOUN
ajst-10983	61	17	without	without	ADP
ajst-10983	61	18	manual	manual	ADJ
ajst-10983	61	19	reconstruction	reconstruction	NOUN
ajst-10983	61	20	or	or	CCONJ
ajst-10983	61	21	cutting	cutting	NOUN
ajst-10983	61	22	,	,	PUNCT
ajst-10983	61	23	which	which	PRON
ajst-10983	61	24	improves	improve	VERB
ajst-10983	61	25	the	the	DET
ajst-10983	61	26	efficiency	efficiency	NOUN
ajst-10983	61	27	of	of	ADP
ajst-10983	61	28	sample	sample	NOUN
ajst-10983	61	29	processing	processing	NOUN
ajst-10983	61	30	.	.	PUNCT
ajst-10983	62	1	secondly	secondly	ADV
ajst-10983	62	2	,	,	PUNCT
ajst-10983	62	3	because	because	SCONJ
ajst-10983	62	4	there	there	PRON
ajst-10983	62	5	is	be	VERB
ajst-10983	62	6	no	no	DET
ajst-10983	62	7	need	need	NOUN
ajst-10983	62	8	to	to	PART
ajst-10983	62	9	use	use	VERB
ajst-10983	62	10	special	special	ADJ
ajst-10983	62	11	reagents	reagent	NOUN
ajst-10983	62	12	such	such	ADJ
ajst-10983	62	13	as	as	ADP
ajst-10983	62	14	fluorescent	fluorescent	ADJ
ajst-10983	62	15	labeling	labeling	NOUN
ajst-10983	62	16	or	or	CCONJ
ajst-10983	62	17	pigment	pigment	NOUN
ajst-10983	62	18	dyeing	dyeing	NOUN
ajst-10983	62	19	,	,	PUNCT
ajst-10983	62	20	the	the	DET
ajst-10983	62	21	effects	effect	NOUN
ajst-10983	62	22	of	of	ADP
ajst-10983	62	23	these	these	DET
ajst-10983	62	24	reagents	reagent	NOUN
ajst-10983	62	25	on	on	ADP
ajst-10983	62	26	plant	plant	NOUN
ajst-10983	62	27	growth	growth	NOUN
ajst-10983	62	28	and	and	CCONJ
ajst-10983	62	29	morphology	morphology	NOUN
ajst-10983	62	30	can	can	AUX
ajst-10983	62	31	be	be	AUX
ajst-10983	62	32	avoided	avoid	VERB
ajst-10983	62	33	.	.	PUNCT
ajst-10983	63	1	finally	finally	ADV
ajst-10983	63	2	,	,	PUNCT
ajst-10983	63	3	especially	especially	ADV
ajst-10983	63	4	with	with	ADP
ajst-10983	63	5	the	the	DET
ajst-10983	63	6	rapid	rapid	ADJ
ajst-10983	63	7	development	development	NOUN
ajst-10983	63	8	of	of	ADP
ajst-10983	63	9	artificial	artificial	ADJ
ajst-10983	63	10	intelligence	intelligence	NOUN
ajst-10983	63	11	,	,	PUNCT
ajst-10983	63	12	combined	combine	VERB
ajst-10983	63	13	with	with	ADP
ajst-10983	63	14	digital	digital	ADJ
ajst-10983	63	15	image	image	NOUN
ajst-10983	63	16	processing	processing	NOUN
ajst-10983	63	17	[	[	X
ajst-10983	63	18	25	25	NUM
ajst-10983	63	19	]	]	PUNCT
ajst-10983	63	20	and	and	CCONJ
ajst-10983	63	21	deep	deep	ADJ
ajst-10983	63	22	learning	learning	NOUN
ajst-10983	64	1	[	[	X
ajst-10983	64	2	26	26	NUM
ajst-10983	64	3	]	]	PUNCT
ajst-10983	64	4	algorithms	algorithm	NOUN
ajst-10983	64	5	,	,	PUNCT
ajst-10983	64	6	this	this	DET
ajst-10983	64	7	method	method	NOUN
ajst-10983	64	8	can	can	AUX
ajst-10983	64	9	more	more	ADV
ajst-10983	64	10	accurately	accurately	ADV
ajst-10983	64	11	and	and	CCONJ
ajst-10983	64	12	quickly	quickly	ADV
ajst-10983	64	13	analyze	analyze	VERB
ajst-10983	64	14	and	and	CCONJ
ajst-10983	64	15	measure	measure	VERB
ajst-10983	64	16	the	the	DET
ajst-10983	64	17	structure	structure	NOUN
ajst-10983	64	18	and	and	CCONJ
ajst-10983	64	19	physiological	physiological	ADJ
ajst-10983	64	20	indicators	indicator	NOUN
ajst-10983	64	21	of	of	ADP
ajst-10983	64	22	each	each	DET
ajst-10983	64	23	part	part	NOUN
ajst-10983	64	24	of	of	ADP
ajst-10983	64	25	the	the	DET
ajst-10983	64	26	root	root	NOUN
ajst-10983	64	27	system	system	NOUN
ajst-10983	64	28	,	,	PUNCT
ajst-10983	64	29	which	which	PRON
ajst-10983	64	30	is	be	AUX
ajst-10983	64	31	of	of	ADP
ajst-10983	64	32	great	great	ADJ
ajst-10983	64	33	significance	significance	NOUN
ajst-10983	64	34	for	for	ADP
ajst-10983	64	35	accurately	accurately	ADV
ajst-10983	64	36	obtaining	obtain	VERB
ajst-10983	64	37	the	the	DET
ajst-10983	64	38	complete	complete	ADJ
ajst-10983	64	39	configuration	configuration	NOUN
ajst-10983	64	40	of	of	ADP
ajst-10983	64	41	the	the	DET
ajst-10983	64	42	in	in	ADP
ajst-10983	64	43	-	-	PUNCT
ajst-10983	64	44	situ	situ	NOUN
ajst-10983	64	45	root	root	NOUN
ajst-10983	64	46	system	system	NOUN
ajst-10983	64	47	,	,	PUNCT
ajst-10983	64	48	exploring	explore	VERB
ajst-10983	64	49	its	its	PRON
ajst-10983	64	50	development	development	NOUN
ajst-10983	64	51	law	law	NOUN
ajst-10983	64	52	and	and	CCONJ
ajst-10983	64	53	defining	define	VERB
ajst-10983	64	54	its	its	PRON
ajst-10983	64	55	functional	functional	ADJ
ajst-10983	64	56	mechanism	mechanism	NOUN
ajst-10983	64	57	.	.	PUNCT
ajst-10983	65	1	these	these	DET
ajst-10983	65	2	plant	plant	NOUN
ajst-10983	65	3	root	root	NOUN
ajst-10983	65	4	imaging	imaging	NOUN
ajst-10983	65	5	methods	method	NOUN
ajst-10983	65	6	can	can	AUX
ajst-10983	65	7	obtain	obtain	VERB
ajst-10983	65	8	highresolution	highresolution	NOUN
ajst-10983	65	9	plant	plant	NOUN
ajst-10983	65	10	root	root	NOUN
ajst-10983	65	11	images	image	NOUN
ajst-10983	65	12	by	by	ADP
ajst-10983	65	13	adjusting	adjust	VERB
ajst-10983	65	14	and	and	CCONJ
ajst-10983	65	15	combining	combine	VERB
ajst-10983	65	16	different	different	ADJ
ajst-10983	65	17	imaging	imaging	NOUN
ajst-10983	65	18	parameters	parameter	NOUN
ajst-10983	65	19	,	,	PUNCT
ajst-10983	65	20	but	but	CCONJ
ajst-10983	65	21	the	the	DET
ajst-10983	65	22	data	data	NOUN
ajst-10983	65	23	acquisition	acquisition	NOUN
ajst-10983	65	24	process	process	NOUN
ajst-10983	65	25	is	be	AUX
ajst-10983	65	26	time	time	NOUN
ajst-10983	65	27	-	-	PUNCT
ajst-10983	65	28	consuming	consume	VERB
ajst-10983	65	29	and	and	CCONJ
ajst-10983	65	30	has	have	VERB
ajst-10983	65	31	a	a	DET
ajst-10983	65	32	large	large	ADJ
ajst-10983	65	33	amount	amount	NOUN
ajst-10983	65	34	of	of	ADP
ajst-10983	65	35	data	datum	NOUN
ajst-10983	65	36	,	,	PUNCT
ajst-10983	65	37	and	and	CCONJ
ajst-10983	65	38	corresponding	correspond	VERB
ajst-10983	65	39	software	software	NOUN
ajst-10983	65	40	tools	tool	NOUN
ajst-10983	65	41	are	be	AUX
ajst-10983	65	42	required	require	VERB
ajst-10983	65	43	to	to	PART
ajst-10983	65	44	segment	segment	VERB
ajst-10983	65	45	and	and	CCONJ
ajst-10983	65	46	analyze	analyze	VERB
ajst-10983	65	47	the	the	DET
ajst-10983	65	48	data	datum	NOUN
ajst-10983	65	49	to	to	PART
ajst-10983	65	50	obtain	obtain	VERB
ajst-10983	65	51	relevant	relevant	ADJ
ajst-10983	65	52	results	result	NOUN
ajst-10983	65	53	.	.	PUNCT
ajst-10983	66	1	2.3	2.3	NUM
ajst-10983	66	2	.	.	PUNCT
ajst-10983	66	3	plant	plant	NOUN
ajst-10983	66	4	root	root	NOUN
ajst-10983	66	5	segmentation	segmentation	NOUN
ajst-10983	66	6	plant	plant	NOUN
ajst-10983	66	7	root	root	NOUN
ajst-10983	66	8	segmentation	segmentation	NOUN
ajst-10983	66	9	refers	refer	VERB
ajst-10983	66	10	to	to	ADP
ajst-10983	66	11	the	the	DET
ajst-10983	66	12	process	process	NOUN
ajst-10983	66	13	of	of	ADP
ajst-10983	66	14	separating	separate	VERB
ajst-10983	66	15	plant	plant	NOUN
ajst-10983	66	16	roots	root	NOUN
ajst-10983	66	17	from	from	ADP
ajst-10983	66	18	other	other	ADJ
ajst-10983	66	19	backgrounds	background	NOUN
ajst-10983	66	20	through	through	ADP
ajst-10983	66	21	image	image	NOUN
ajst-10983	66	22	processing	processing	NOUN
ajst-10983	66	23	technology	technology	NOUN
ajst-10983	66	24	.	.	PUNCT
ajst-10983	67	1	at	at	ADP
ajst-10983	67	2	present	present	ADJ
ajst-10983	67	3	,	,	PUNCT
ajst-10983	67	4	in	in	ADP
ajst-10983	67	5	the	the	DET
ajst-10983	67	6	study	study	NOUN
ajst-10983	67	7	of	of	ADP
ajst-10983	67	8	plant	plant	NOUN
ajst-10983	67	9	root	root	NOUN
ajst-10983	67	10	phenotype	phenotype	NOUN
ajst-10983	67	11	,	,	PUNCT
ajst-10983	67	12	although	although	SCONJ
ajst-10983	67	13	it	it	PRON
ajst-10983	67	14	is	be	AUX
ajst-10983	67	15	possible	possible	ADJ
ajst-10983	67	16	to	to	PART
ajst-10983	67	17	obtain	obtain	VERB
ajst-10983	67	18	high	high	ADJ
ajst-10983	67	19	-	-	PUNCT
ajst-10983	67	20	resolution	resolution	NOUN
ajst-10983	67	21	root	root	NOUN
ajst-10983	67	22	images	image	NOUN
ajst-10983	67	23	from	from	ADP
ajst-10983	67	24	complex	complex	ADJ
ajst-10983	67	25	soil	soil	NOUN
ajst-10983	67	26	environments	environment	NOUN
ajst-10983	67	27	by	by	ADP
ajst-10983	67	28	using	use	VERB
ajst-10983	67	29	in	in	ADP
ajst-10983	67	30	situ	situ	ADJ
ajst-10983	67	31	root	root	NOUN
ajst-10983	67	32	nondestructive	nondestructive	ADJ
ajst-10983	67	33	observation	observation	NOUN
ajst-10983	67	34	technology	technology	NOUN
ajst-10983	67	35	,	,	PUNCT
ajst-10983	67	36	the	the	DET
ajst-10983	67	37	automatic	automatic	ADJ
ajst-10983	67	38	segmentation	segmentation	NOUN
ajst-10983	67	39	of	of	ADP
ajst-10983	67	40	root	root	NOUN
ajst-10983	67	41	morphology	morphology	NOUN
ajst-10983	67	42	is	be	AUX
ajst-10983	67	43	usually	usually	ADV
ajst-10983	67	44	faced	face	VERB
ajst-10983	67	45	with	with	ADP
ajst-10983	67	46	great	great	ADJ
ajst-10983	67	47	challenges	challenge	NOUN
ajst-10983	67	48	due	due	ADP
ajst-10983	67	49	to	to	ADP
ajst-10983	67	50	the	the	DET
ajst-10983	67	51	opacity	opacity	NOUN
ajst-10983	67	52	of	of	ADP
ajst-10983	67	53	soil	soil	NOUN
ajst-10983	67	54	particles	particle	NOUN
ajst-10983	67	55	.	.	PUNCT
ajst-10983	68	1	traditional	traditional	ADJ
ajst-10983	68	2	root	root	NOUN
ajst-10983	68	3	segmentation	segmentation	NOUN
ajst-10983	68	4	methods	method	NOUN
ajst-10983	68	5	mainly	mainly	ADV
ajst-10983	68	6	include	include	VERB
ajst-10983	68	7	manual	manual	ADJ
ajst-10983	68	8	segmentation	segmentation	NOUN
ajst-10983	68	9	,	,	PUNCT
ajst-10983	68	10	morphological	morphological	ADJ
ajst-10983	68	11	image	image	NOUN
ajst-10983	68	12	processing	processing	NOUN
ajst-10983	68	13	and	and	CCONJ
ajst-10983	68	14	machine	machine	NOUN
ajst-10983	68	15	learning	learning	NOUN
ajst-10983	68	16	based	base	VERB
ajst-10983	68	17	image	image	NOUN
ajst-10983	68	18	segmentation	segmentation	NOUN
ajst-10983	68	19	.	.	PUNCT
ajst-10983	69	1	among	among	ADP
ajst-10983	69	2	them	they	PRON
ajst-10983	69	3	,	,	PUNCT
ajst-10983	69	4	manual	manual	ADJ
ajst-10983	69	5	segmentation	segmentation	NOUN
ajst-10983	69	6	can	can	AUX
ajst-10983	69	7	be	be	AUX
ajst-10983	69	8	further	far	ADV
ajst-10983	69	9	divided	divide	VERB
ajst-10983	69	10	into	into	ADP
ajst-10983	69	11	manual	manual	ADJ
ajst-10983	69	12	characterization	characterization	NOUN
ajst-10983	69	13	and	and	CCONJ
ajst-10983	69	14	semi	semi	ADJ
ajst-10983	69	15	-	-	ADJ
ajst-10983	69	16	automatic	automatic	ADJ
ajst-10983	69	17	interactive	interactive	ADJ
ajst-10983	69	18	segmentation	segmentation	NOUN
ajst-10983	69	19	.	.	PUNCT
ajst-10983	70	1	in	in	ADP
ajst-10983	70	2	the	the	DET
ajst-10983	70	3	manual	manual	ADJ
ajst-10983	70	4	mapping	mapping	NOUN
ajst-10983	70	5	method	method	NOUN
ajst-10983	70	6	,	,	PUNCT
ajst-10983	70	7	researchers	researcher	NOUN
ajst-10983	70	8	need	need	VERB
ajst-10983	70	9	to	to	PART
ajst-10983	70	10	manually	manually	ADV
ajst-10983	70	11	identify	identify	VERB
ajst-10983	70	12	each	each	DET
ajst-10983	70	13	root	root	NOUN
ajst-10983	70	14	system	system	NOUN
ajst-10983	70	15	in	in	ADP
ajst-10983	70	16	a	a	DET
ajst-10983	70	17	complex	complex	ADJ
ajst-10983	70	18	soil	soil	NOUN
ajst-10983	70	19	background	background	NOUN
ajst-10983	70	20	and	and	CCONJ
ajst-10983	70	21	describe	describe	VERB
ajst-10983	70	22	it	it	PRON
ajst-10983	70	23	.	.	PUNCT
ajst-10983	71	1	due	due	ADP
ajst-10983	71	2	to	to	ADP
ajst-10983	71	3	the	the	DET
ajst-10983	71	4	low	low	ADJ
ajst-10983	71	5	efficiency	efficiency	NOUN
ajst-10983	71	6	of	of	ADP
ajst-10983	71	7	this	this	DET
ajst-10983	71	8	method	method	NOUN
ajst-10983	71	9	,	,	PUNCT
ajst-10983	71	10	the	the	DET
ajst-10983	71	11	need	need	NOUN
ajst-10983	71	12	for	for	ADP
ajst-10983	71	13	huge	huge	ADJ
ajst-10983	71	14	workload	workload	NOUN
ajst-10983	71	15	,	,	PUNCT
ajst-10983	71	16	and	and	CCONJ
ajst-10983	71	17	the	the	DET
ajst-10983	71	18	problem	problem	NOUN
ajst-10983	71	19	of	of	ADP
ajst-10983	71	20	visual	visual	ADJ
ajst-10983	71	21	fatigue	fatigue	NOUN
ajst-10983	71	22	,	,	PUNCT
ajst-10983	71	23	the	the	DET
ajst-10983	71	24	segmentation	segmentation	NOUN
ajst-10983	71	25	results	result	NOUN
ajst-10983	71	26	are	be	AUX
ajst-10983	71	27	easy	easy	ADJ
ajst-10983	71	28	to	to	PART
ajst-10983	71	29	be	be	AUX
ajst-10983	71	30	affected	affect	VERB
ajst-10983	71	31	by	by	ADP
ajst-10983	71	32	high	high	ADJ
ajst-10983	71	33	errors	error	NOUN
ajst-10983	71	34	,	,	PUNCT
ajst-10983	71	35	and	and	CCONJ
ajst-10983	71	36	are	be	AUX
ajst-10983	71	37	not	not	PART
ajst-10983	71	38	suitable	suitable	ADJ
ajst-10983	71	39	for	for	ADP
ajst-10983	71	40	practical	practical	ADJ
ajst-10983	71	41	engineering	engineering	NOUN
ajst-10983	71	42	applications	application	NOUN
ajst-10983	71	43	.	.	PUNCT
ajst-10983	72	1	the	the	DET
ajst-10983	72	2	semi	semi	ADJ
ajst-10983	72	3	-	-	ADJ
ajst-10983	72	4	automatic	automatic	ADJ
ajst-10983	72	5	interactive	interactive	ADJ
ajst-10983	72	6	segmentation	segmentation	NOUN
ajst-10983	72	7	method	method	NOUN
ajst-10983	72	8	requires	require	VERB
ajst-10983	72	9	the	the	DET
ajst-10983	72	10	combination	combination	NOUN
ajst-10983	72	11	of	of	ADP
ajst-10983	72	12	human	human	ADJ
ajst-10983	72	13	-	-	PUNCT
ajst-10983	72	14	computer	computer	NOUN
ajst-10983	72	15	interaction	interaction	NOUN
ajst-10983	72	16	,	,	PUNCT
ajst-10983	72	17	and	and	CCONJ
ajst-10983	72	18	the	the	DET
ajst-10983	72	19	researchers	researcher	NOUN
ajst-10983	72	20	use	use	VERB
ajst-10983	72	21	auxiliary	auxiliary	ADJ
ajst-10983	72	22	software	software	NOUN
ajst-10983	72	23	to	to	PART
ajst-10983	72	24	label	label	VERB
ajst-10983	72	25	and	and	CCONJ
ajst-10983	72	26	segment	segment	VERB
ajst-10983	72	27	it	it	PRON
ajst-10983	72	28	.	.	PUNCT
ajst-10983	73	1	for	for	ADP
ajst-10983	73	2	example	example	NOUN
ajst-10983	73	3	,	,	PUNCT
ajst-10983	73	4	matalabr2016a	matalabr2016a	NOUN
ajst-10983	73	5	image	image	NOUN
ajst-10983	73	6	processing	processing	NOUN
ajst-10983	73	7	software	software	NOUN
ajst-10983	73	8	was	be	AUX
ajst-10983	73	9	used	use	VERB
ajst-10983	73	10	to	to	PART
ajst-10983	73	11	segment	segment	VERB
ajst-10983	73	12	plant	plant	NOUN
ajst-10983	73	13	root	root	NOUN
ajst-10983	73	14	images	image	NOUN
ajst-10983	73	15	[	[	X
ajst-10983	73	16	27	27	NUM
ajst-10983	73	17	]	]	PUNCT
ajst-10983	73	18	,	,	PUNCT
ajst-10983	73	19	winrhizo	winrhizo	PROPN
ajst-10983	73	20	tron	tron	PROPN
ajst-10983	73	21	mf	mf	PROPN
ajst-10983	73	22	was	be	AUX
ajst-10983	73	23	used	use	VERB
ajst-10983	73	24	for	for	ADP
ajst-10983	73	25	image	image	NOUN
ajst-10983	73	26	analysis	analysis	NOUN
ajst-10983	74	1	[	[	X
ajst-10983	74	2	28	28	NUM
ajst-10983	74	3	]	]	PUNCT
ajst-10983	74	4	,	,	PUNCT
ajst-10983	74	5	and	and	CCONJ
ajst-10983	74	6	gt	gt	NOUN
ajst-10983	74	7	-	-	PUNCT
ajst-10983	74	8	roots	root	NOUN
ajst-10983	74	9	was	be	AUX
ajst-10983	74	10	used	use	VERB
ajst-10983	74	11	for	for	ADP
ajst-10983	74	12	root	root	NOUN
ajst-10983	74	13	segmentation	segmentation	NOUN
ajst-10983	74	14	in	in	ADP
ajst-10983	74	15	the	the	DET
ajst-10983	74	16	specified	specify	VERB
ajst-10983	74	17	segmentation	segmentation	NOUN
ajst-10983	74	18	region	region	NOUN
ajst-10983	74	19	selection	selection	NOUN
ajst-10983	74	20	method	method	NOUN
ajst-10983	74	21	[	[	X
ajst-10983	74	22	29	29	NUM
ajst-10983	74	23	]	]	PUNCT
ajst-10983	74	24	.	.	PUNCT
ajst-10983	75	1	the	the	DET
ajst-10983	75	2	morphology	morphology	NOUN
ajst-10983	75	3	-	-	PUNCT
ajst-10983	75	4	based	base	VERB
ajst-10983	75	5	image	image	NOUN
ajst-10983	75	6	processing	processing	NOUN
ajst-10983	75	7	method	method	NOUN
ajst-10983	75	8	is	be	AUX
ajst-10983	75	9	to	to	PART
ajst-10983	75	10	continuously	continuously	ADV
ajst-10983	75	11	filter	filter	VERB
ajst-10983	75	12	the	the	DET
ajst-10983	75	13	image	image	NOUN
ajst-10983	75	14	to	to	PART
ajst-10983	75	15	distinguish	distinguish	VERB
ajst-10983	75	16	the	the	DET
ajst-10983	75	17	root	root	NOUN
ajst-10983	75	18	system	system	NOUN
ajst-10983	75	19	from	from	ADP
ajst-10983	75	20	the	the	DET
ajst-10983	75	21	background	background	NOUN
ajst-10983	75	22	.	.	PUNCT
ajst-10983	76	1	it	it	PRON
ajst-10983	76	2	can	can	AUX
ajst-10983	76	3	be	be	AUX
ajst-10983	76	4	divided	divide	VERB
ajst-10983	76	5	into	into	ADP
ajst-10983	76	6	the	the	DET
ajst-10983	76	7	following	follow	VERB
ajst-10983	76	8	types	type	NOUN
ajst-10983	76	9	:	:	PUNCT
ajst-10983	76	10	firstly	firstly	ADV
ajst-10983	76	11	,	,	PUNCT
ajst-10983	76	12	morphological	morphological	ADJ
ajst-10983	76	13	operation	operation	NOUN
ajst-10983	77	1	[	[	X
ajst-10983	77	2	30	30	NUM
ajst-10983	77	3	]	]	PUNCT
ajst-10983	77	4	,	,	PUNCT
ajst-10983	77	5	which	which	PRON
ajst-10983	77	6	is	be	AUX
ajst-10983	77	7	divided	divide	VERB
ajst-10983	77	8	into	into	ADP
ajst-10983	77	9	expansion	expansion	NOUN
ajst-10983	77	10	,	,	PUNCT
ajst-10983	77	11	corrosion	corrosion	NOUN
ajst-10983	77	12	,	,	PUNCT
ajst-10983	77	13	open	open	ADJ
ajst-10983	77	14	operation	operation	NOUN
ajst-10983	77	15	,	,	PUNCT
ajst-10983	77	16	close	close	ADJ
ajst-10983	77	17	operation	operation	NOUN
ajst-10983	77	18	and	and	CCONJ
ajst-10983	77	19	other	other	ADJ
ajst-10983	77	20	specific	specific	ADJ
ajst-10983	77	21	methods	method	NOUN
ajst-10983	77	22	,	,	PUNCT
ajst-10983	77	23	can	can	AUX
ajst-10983	77	24	improve	improve	VERB
ajst-10983	77	25	image	image	NOUN
ajst-10983	77	26	quality	quality	NOUN
ajst-10983	77	27	,	,	PUNCT
ajst-10983	77	28	remove	remove	VERB
ajst-10983	77	29	noise	noise	NOUN
ajst-10983	77	30	,	,	PUNCT
ajst-10983	77	31	and	and	CCONJ
ajst-10983	77	32	enhance	enhance	VERB
ajst-10983	77	33	object	object	NOUN
ajst-10983	77	34	contours	contours	NOUN
ajst-10983	77	35	to	to	ADP
ajst-10983	77	36	a	a	DET
ajst-10983	77	37	certain	certain	ADJ
ajst-10983	77	38	extent	extent	NOUN
ajst-10983	77	39	;	;	PUNCT
ajst-10983	77	40	the	the	DET
ajst-10983	77	41	second	second	ADJ
ajst-10983	77	42	method	method	NOUN
ajst-10983	77	43	is	be	AUX
ajst-10983	77	44	region	region	NOUN
ajst-10983	77	45	growing	grow	VERB
ajst-10983	77	46	[	[	X
ajst-10983	77	47	31	31	NUM
ajst-10983	77	48	]	]	PUNCT
ajst-10983	77	49	,	,	PUNCT
ajst-10983	77	50	which	which	PRON
ajst-10983	77	51	selects	select	VERB
ajst-10983	77	52	a	a	DET
ajst-10983	77	53	point	point	NOUN
ajst-10983	77	54	or	or	CCONJ
ajst-10983	77	55	a	a	DET
ajst-10983	77	56	region	region	NOUN
ajst-10983	77	57	as	as	ADP
ajst-10983	77	58	a	a	DET
ajst-10983	77	59	seed	seed	NOUN
ajst-10983	77	60	and	and	CCONJ
ajst-10983	77	61	grows	grow	VERB
ajst-10983	77	62	along	along	ADP
ajst-10983	77	63	the	the	DET
ajst-10983	77	64	adjacent	adjacent	ADJ
ajst-10983	77	65	pixels	pixel	NOUN
ajst-10983	77	66	until	until	SCONJ
ajst-10983	77	67	some	some	DET
ajst-10983	77	68	stopping	stopping	NOUN
ajst-10983	77	69	criteria	criterion	NOUN
ajst-10983	77	70	are	be	AUX
ajst-10983	77	71	reached	reach	VERB
ajst-10983	77	72	.	.	PUNCT
ajst-10983	78	1	the	the	DET
ajst-10983	78	2	third	third	ADJ
ajst-10983	78	3	method	method	NOUN
ajst-10983	78	4	is	be	AUX
ajst-10983	78	5	thresholding	thresholde	VERB
ajst-10983	78	6	[	[	X
ajst-10983	78	7	32	32	NUM
ajst-10983	78	8	]	]	PUNCT
ajst-10983	78	9	,	,	PUNCT
ajst-10983	78	10	which	which	PRON
ajst-10983	78	11	can	can	AUX
ajst-10983	78	12	divide	divide	VERB
ajst-10983	78	13	the	the	DET
ajst-10983	78	14	image	image	NOUN
ajst-10983	78	15	into	into	ADP
ajst-10983	78	16	several	several	ADJ
ajst-10983	78	17	parts	part	NOUN
ajst-10983	78	18	according	accord	VERB
ajst-10983	78	19	to	to	ADP
ajst-10983	78	20	the	the	DET
ajst-10983	78	21	threshold	threshold	NOUN
ajst-10983	78	22	value	value	NOUN
ajst-10983	78	23	so	so	SCONJ
ajst-10983	78	24	as	as	SCONJ
ajst-10983	78	25	to	to	PART
ajst-10983	78	26	separate	separate	VERB
ajst-10983	78	27	the	the	DET
ajst-10983	78	28	background	background	NOUN
ajst-10983	78	29	from	from	ADP
ajst-10983	78	30	the	the	DET
ajst-10983	78	31	foreground	foreground	NOUN
ajst-10983	78	32	.	.	PUNCT
ajst-10983	79	1	common	common	ADJ
ajst-10983	79	2	threshold	threshold	NOUN
ajst-10983	79	3	selection	selection	NOUN
ajst-10983	79	4	strategies	strategy	NOUN
ajst-10983	79	5	include	include	VERB
ajst-10983	79	6	otsu	otsu	NOUN
ajst-10983	79	7	method	method	NOUN
ajst-10983	79	8	[	[	X
ajst-10983	79	9	33	33	NUM
ajst-10983	79	10	]	]	PUNCT
ajst-10983	79	11	and	and	CCONJ
ajst-10983	79	12	adaptive	adaptive	ADJ
ajst-10983	79	13	27	27	NUM
ajst-10983	79	14	threshold	threshold	NOUN
ajst-10983	79	15	method	method	NOUN
ajst-10983	79	16	[	[	X
ajst-10983	79	17	34	34	NUM
ajst-10983	79	18	]	]	PUNCT
ajst-10983	79	19	.	.	PUNCT
ajst-10983	80	1	there	there	PRON
ajst-10983	80	2	is	be	VERB
ajst-10983	80	3	also	also	ADV
ajst-10983	80	4	a	a	DET
ajst-10983	80	5	method	method	NOUN
ajst-10983	80	6	based	base	VERB
ajst-10983	80	7	on	on	ADP
ajst-10983	80	8	wavelet	wavelet	NOUN
ajst-10983	80	9	transform	transform	NOUN
ajst-10983	80	10	[	[	X
ajst-10983	80	11	35	35	NUM
ajst-10983	80	12	]	]	PUNCT
ajst-10983	80	13	,	,	PUNCT
ajst-10983	80	14	which	which	PRON
ajst-10983	80	15	can	can	AUX
ajst-10983	80	16	realize	realize	VERB
ajst-10983	80	17	multi	multi	ADJ
ajst-10983	80	18	-	-	ADJ
ajst-10983	80	19	scale	scale	ADJ
ajst-10983	80	20	analysis	analysis	NOUN
ajst-10983	80	21	and	and	CCONJ
ajst-10983	80	22	local	local	ADJ
ajst-10983	80	23	processing	processing	NOUN
ajst-10983	80	24	,	,	PUNCT
ajst-10983	80	25	and	and	CCONJ
ajst-10983	80	26	can	can	AUX
ajst-10983	80	27	deal	deal	VERB
ajst-10983	80	28	with	with	ADP
ajst-10983	80	29	noise	noise	NOUN
ajst-10983	80	30	better	well	ADV
ajst-10983	80	31	.	.	PUNCT
ajst-10983	81	1	root	root	NOUN
ajst-10983	81	2	image	image	NOUN
ajst-10983	81	3	segmentation	segmentation	NOUN
ajst-10983	81	4	methods	method	NOUN
ajst-10983	81	5	based	base	VERB
ajst-10983	81	6	on	on	ADP
ajst-10983	81	7	traditional	traditional	ADJ
ajst-10983	81	8	machine	machine	NOUN
ajst-10983	81	9	learning	learning	NOUN
ajst-10983	81	10	are	be	AUX
ajst-10983	81	11	divided	divide	VERB
ajst-10983	81	12	into	into	ADP
ajst-10983	81	13	the	the	DET
ajst-10983	81	14	following	follow	VERB
ajst-10983	81	15	common	common	ADJ
ajst-10983	81	16	methods	method	NOUN
ajst-10983	81	17	.	.	PUNCT
ajst-10983	82	1	the	the	DET
ajst-10983	82	2	first	first	ADJ
ajst-10983	82	3	is	be	AUX
ajst-10983	82	4	based	base	VERB
ajst-10983	82	5	on	on	ADP
ajst-10983	82	6	support	support	NOUN
ajst-10983	82	7	vector	vector	NOUN
ajst-10983	82	8	machines	machine	NOUN
ajst-10983	82	9	,	,	PUNCT
ajst-10983	82	10	(	(	PUNCT
ajst-10983	82	11	svm	svm	PROPN
ajst-10983	82	12	)	)	PUNCT
ajst-10983	83	1	[	[	X
ajst-10983	83	2	36	36	NUM
ajst-10983	83	3	]	]	PUNCT
ajst-10983	83	4	is	be	AUX
ajst-10983	83	5	a	a	DET
ajst-10983	83	6	binary	binary	ADJ
ajst-10983	83	7	classification	classification	NOUN
ajst-10983	83	8	machine	machine	NOUN
ajst-10983	83	9	learning	learning	NOUN
ajst-10983	83	10	method	method	NOUN
ajst-10983	83	11	that	that	PRON
ajst-10983	83	12	classifies	classify	VERB
ajst-10983	83	13	data	datum	NOUN
ajst-10983	83	14	by	by	ADP
ajst-10983	83	15	finding	find	VERB
ajst-10983	83	16	hyperplanes	hyperplane	NOUN
ajst-10983	83	17	with	with	ADP
ajst-10983	83	18	the	the	DET
ajst-10983	83	19	greatest	great	ADJ
ajst-10983	83	20	spacing	spacing	NOUN
ajst-10983	83	21	.	.	PUNCT
ajst-10983	84	1	it	it	PRON
ajst-10983	84	2	is	be	AUX
ajst-10983	84	3	widely	widely	ADV
ajst-10983	84	4	used	use	VERB
ajst-10983	84	5	in	in	ADP
ajst-10983	84	6	root	root	NOUN
ajst-10983	84	7	image	image	NOUN
ajst-10983	84	8	segmentation	segmentation	NOUN
ajst-10983	84	9	,	,	PUNCT
ajst-10983	84	10	and	and	CCONJ
ajst-10983	84	11	can	can	AUX
ajst-10983	84	12	train	train	VERB
ajst-10983	84	13	a	a	DET
ajst-10983	84	14	good	good	ADJ
ajst-10983	84	15	classification	classification	NOUN
ajst-10983	84	16	model	model	NOUN
ajst-10983	84	17	to	to	PART
ajst-10983	84	18	distinguish	distinguish	VERB
ajst-10983	84	19	roots	root	NOUN
ajst-10983	84	20	and	and	CCONJ
ajst-10983	84	21	backgrounds	background	NOUN
ajst-10983	84	22	in	in	ADP
ajst-10983	84	23	images	image	NOUN
ajst-10983	84	24	.	.	PUNCT
ajst-10983	85	1	the	the	DET
ajst-10983	85	2	second	second	ADJ
ajst-10983	85	3	is	be	AUX
ajst-10983	85	4	the	the	DET
ajst-10983	85	5	method	method	NOUN
ajst-10983	85	6	based	base	VERB
ajst-10983	85	7	on	on	ADP
ajst-10983	85	8	decision	decision	NOUN
ajst-10983	85	9	tree	tree	NOUN
ajst-10983	85	10	[	[	X
ajst-10983	85	11	37	37	NUM
ajst-10983	85	12	]	]	PUNCT
ajst-10983	85	13	,	,	PUNCT
ajst-10983	85	14	which	which	PRON
ajst-10983	85	15	is	be	AUX
ajst-10983	85	16	a	a	DET
ajst-10983	85	17	classification	classification	NOUN
ajst-10983	85	18	algorithm	algorithm	NOUN
ajst-10983	85	19	that	that	PRON
ajst-10983	85	20	can	can	AUX
ajst-10983	85	21	classify	classify	VERB
ajst-10983	85	22	data	data	NOUN
ajst-10983	85	23	sets	set	NOUN
ajst-10983	85	24	into	into	ADP
ajst-10983	85	25	different	different	ADJ
ajst-10983	85	26	categories	category	NOUN
ajst-10983	85	27	according	accord	VERB
ajst-10983	85	28	to	to	ADP
ajst-10983	85	29	feature	feature	NOUN
ajst-10983	85	30	attributes	attribute	NOUN
ajst-10983	85	31	.	.	PUNCT
ajst-10983	86	1	by	by	ADP
ajst-10983	86	2	selecting	select	VERB
ajst-10983	86	3	suitable	suitable	ADJ
ajst-10983	86	4	features	feature	NOUN
ajst-10983	86	5	and	and	CCONJ
ajst-10983	86	6	constructing	construct	VERB
ajst-10983	86	7	decision	decision	NOUN
ajst-10983	86	8	tree	tree	NOUN
ajst-10983	86	9	model	model	NOUN
ajst-10983	86	10	,	,	PUNCT
ajst-10983	86	11	it	it	PRON
ajst-10983	86	12	can	can	AUX
ajst-10983	86	13	be	be	AUX
ajst-10983	86	14	used	use	VERB
ajst-10983	86	15	to	to	PART
ajst-10983	86	16	segment	segment	VERB
ajst-10983	86	17	root	root	NOUN
ajst-10983	86	18	image	image	NOUN
ajst-10983	86	19	.	.	PUNCT
ajst-10983	87	1	there	there	PRON
ajst-10983	87	2	are	be	VERB
ajst-10983	87	3	also	also	ADV
ajst-10983	87	4	methods	method	NOUN
ajst-10983	87	5	based	base	VERB
ajst-10983	87	6	on	on	ADP
ajst-10983	87	7	clustering	cluster	VERB
ajst-10983	87	8	[	[	X
ajst-10983	87	9	38	38	NUM
ajst-10983	87	10	]	]	PUNCT
ajst-10983	87	11	analysis	analysis	NOUN
ajst-10983	87	12	,	,	PUNCT
ajst-10983	87	13	which	which	PRON
ajst-10983	87	14	is	be	AUX
ajst-10983	87	15	a	a	DET
ajst-10983	87	16	method	method	NOUN
ajst-10983	87	17	of	of	ADP
ajst-10983	87	18	dividing	divide	VERB
ajst-10983	87	19	data	data	NOUN
ajst-10983	87	20	sets	set	NOUN
ajst-10983	87	21	into	into	ADP
ajst-10983	87	22	multiple	multiple	ADJ
ajst-10983	87	23	categories	category	NOUN
ajst-10983	87	24	.	.	PUNCT
ajst-10983	88	1	by	by	ADP
ajst-10983	88	2	clustering	cluster	VERB
ajst-10983	88	3	the	the	DET
ajst-10983	88	4	pixels	pixel	NOUN
ajst-10983	88	5	in	in	ADP
ajst-10983	88	6	the	the	DET
ajst-10983	88	7	root	root	NOUN
ajst-10983	88	8	image	image	NOUN
ajst-10983	88	9	,	,	PUNCT
ajst-10983	88	10	objects	object	NOUN
ajst-10983	88	11	of	of	ADP
ajst-10983	88	12	different	different	ADJ
ajst-10983	88	13	colors	color	NOUN
ajst-10983	88	14	and	and	CCONJ
ajst-10983	88	15	textures	texture	NOUN
ajst-10983	88	16	can	can	AUX
ajst-10983	88	17	be	be	AUX
ajst-10983	88	18	separated	separate	VERB
ajst-10983	88	19	,	,	PUNCT
ajst-10983	88	20	and	and	CCONJ
ajst-10983	88	21	then	then	ADV
ajst-10983	88	22	the	the	DET
ajst-10983	88	23	clustering	clustering	ADJ
ajst-10983	88	24	results	result	NOUN
ajst-10983	88	25	are	be	AUX
ajst-10983	88	26	used	use	VERB
ajst-10983	88	27	for	for	ADP
ajst-10983	88	28	root	root	NOUN
ajst-10983	88	29	segmentation	segmentation	NOUN
ajst-10983	88	30	.	.	PUNCT
ajst-10983	89	1	in	in	ADP
ajst-10983	89	2	addition	addition	NOUN
ajst-10983	89	3	,	,	PUNCT
ajst-10983	89	4	more	more	ADJ
ajst-10983	89	5	and	and	CCONJ
ajst-10983	89	6	more	more	ADJ
ajst-10983	89	7	researchers	researcher	NOUN
ajst-10983	89	8	are	be	AUX
ajst-10983	89	9	focusing	focus	VERB
ajst-10983	89	10	on	on	ADP
ajst-10983	89	11	the	the	DET
ajst-10983	89	12	development	development	NOUN
ajst-10983	89	13	of	of	ADP
ajst-10983	89	14	automated	automate	VERB
ajst-10983	89	15	tools	tool	NOUN
ajst-10983	89	16	for	for	ADP
ajst-10983	89	17	the	the	DET
ajst-10983	89	18	processing	processing	NOUN
ajst-10983	89	19	of	of	ADP
ajst-10983	89	20	highthroughput	highthroughput	NOUN
ajst-10983	89	21	root	root	NOUN
ajst-10983	89	22	phenotypes	phenotype	NOUN
ajst-10983	89	23	,	,	PUNCT
ajst-10983	89	24	such	such	ADJ
ajst-10983	89	25	as	as	ADP
ajst-10983	89	26	root	root	NOUN
ajst-10983	89	27	scanners	scanner	NOUN
ajst-10983	89	28	.	.	PUNCT
ajst-10983	90	1	although	although	SCONJ
ajst-10983	90	2	these	these	DET
ajst-10983	90	3	systems	system	NOUN
ajst-10983	90	4	can	can	AUX
ajst-10983	90	5	obtain	obtain	VERB
ajst-10983	90	6	relatively	relatively	ADV
ajst-10983	90	7	high	high	ADJ
ajst-10983	90	8	precision	precision	NOUN
ajst-10983	90	9	root	root	NOUN
ajst-10983	90	10	phenotypic	phenotypic	ADJ
ajst-10983	90	11	parameter	parameter	NOUN
ajst-10983	90	12	values	value	NOUN
ajst-10983	90	13	,	,	PUNCT
ajst-10983	90	14	they	they	PRON
ajst-10983	90	15	still	still	ADV
ajst-10983	90	16	rely	rely	VERB
ajst-10983	90	17	on	on	ADP
ajst-10983	90	18	subjective	subjective	ADJ
ajst-10983	90	19	factors	factor	NOUN
ajst-10983	90	20	to	to	PART
ajst-10983	90	21	locate	locate	VERB
ajst-10983	90	22	the	the	DET
ajst-10983	90	23	initial	initial	ADJ
ajst-10983	90	24	root	root	NOUN
ajst-10983	90	25	position	position	NOUN
ajst-10983	90	26	,	,	PUNCT
ajst-10983	90	27	and	and	CCONJ
ajst-10983	90	28	the	the	DET
ajst-10983	90	29	imaging	imaging	NOUN
ajst-10983	90	30	equipment	equipment	NOUN
ajst-10983	90	31	used	use	VERB
ajst-10983	90	32	is	be	AUX
ajst-10983	90	33	expensive	expensive	ADJ
ajst-10983	90	34	,	,	PUNCT
ajst-10983	90	35	which	which	PRON
ajst-10983	90	36	belongs	belong	VERB
ajst-10983	90	37	to	to	ADP
ajst-10983	90	38	the	the	DET
ajst-10983	90	39	semiautomatic	semiautomatic	ADJ
ajst-10983	90	40	root	root	NOUN
ajst-10983	90	41	image	image	NOUN
ajst-10983	90	42	segmentation	segmentation	NOUN
ajst-10983	90	43	method	method	NOUN
ajst-10983	90	44	.	.	PUNCT
ajst-10983	91	1	with	with	ADP
ajst-10983	91	2	the	the	DET
ajst-10983	91	3	rapid	rapid	ADJ
ajst-10983	91	4	development	development	NOUN
ajst-10983	91	5	of	of	ADP
ajst-10983	91	6	deep	deep	ADJ
ajst-10983	91	7	learning	learning	NOUN
ajst-10983	91	8	technology	technology	NOUN
ajst-10983	91	9	,	,	PUNCT
ajst-10983	91	10	the	the	DET
ajst-10983	91	11	cross	cross	ADJ
ajst-10983	91	12	-	-	ADJ
ajst-10983	91	13	fusion	fusion	ADJ
ajst-10983	91	14	technology	technology	NOUN
ajst-10983	91	15	based	base	VERB
ajst-10983	91	16	on	on	ADP
ajst-10983	91	17	deep	deep	ADJ
ajst-10983	91	18	learning	learning	NOUN
ajst-10983	91	19	and	and	CCONJ
ajst-10983	91	20	computer	computer	NOUN
ajst-10983	91	21	vision	vision	NOUN
ajst-10983	91	22	technology	technology	NOUN
ajst-10983	91	23	has	have	AUX
ajst-10983	91	24	opened	open	VERB
ajst-10983	91	25	up	up	ADP
ajst-10983	91	26	a	a	DET
ajst-10983	91	27	new	new	ADJ
ajst-10983	91	28	field	field	NOUN
ajst-10983	91	29	,	,	PUNCT
ajst-10983	91	30	providing	provide	VERB
ajst-10983	91	31	a	a	DET
ajst-10983	91	32	more	more	ADV
ajst-10983	91	33	accurate	accurate	ADJ
ajst-10983	91	34	,	,	PUNCT
ajst-10983	91	35	fast	fast	ADJ
ajst-10983	91	36	,	,	PUNCT
ajst-10983	91	37	cheap	cheap	ADJ
ajst-10983	91	38	and	and	CCONJ
ajst-10983	91	39	automated	automate	VERB
ajst-10983	91	40	solution	solution	NOUN
ajst-10983	91	41	for	for	ADP
ajst-10983	91	42	plant	plant	NOUN
ajst-10983	91	43	root	root	NOUN
ajst-10983	91	44	image	image	NOUN
ajst-10983	91	45	segmentation	segmentation	NOUN
ajst-10983	91	46	.	.	PUNCT
ajst-10983	92	1	3	3	X
ajst-10983	92	2	.	.	X
ajst-10983	92	3	research	research	NOUN
ajst-10983	92	4	on	on	ADP
ajst-10983	92	5	plant	plant	NOUN
ajst-10983	92	6	roots	root	NOUN
ajst-10983	92	7	based	base	VERB
ajst-10983	92	8	on	on	ADP
ajst-10983	92	9	deep	deep	ADJ
ajst-10983	92	10	learning	learning	NOUN
ajst-10983	92	11	with	with	ADP
ajst-10983	92	12	the	the	DET
ajst-10983	92	13	continuous	continuous	ADJ
ajst-10983	92	14	development	development	NOUN
ajst-10983	92	15	of	of	ADP
ajst-10983	92	16	computer	computer	NOUN
ajst-10983	92	17	vision	vision	NOUN
ajst-10983	92	18	and	and	CCONJ
ajst-10983	92	19	deep	deep	ADJ
ajst-10983	92	20	learning	learning	NOUN
ajst-10983	92	21	technology	technology	NOUN
ajst-10983	92	22	,	,	PUNCT
ajst-10983	92	23	deep	deep	ADJ
ajst-10983	92	24	learning	learning	NOUN
ajst-10983	92	25	-	-	PUNCT
ajst-10983	92	26	based	base	VERB
ajst-10983	92	27	plant	plant	NOUN
ajst-10983	92	28	root	root	NOUN
ajst-10983	92	29	segmentation	segmentation	NOUN
ajst-10983	92	30	has	have	AUX
ajst-10983	92	31	become	become	VERB
ajst-10983	92	32	a	a	DET
ajst-10983	92	33	research	research	NOUN
ajst-10983	92	34	hotspot	hotspot	NOUN
ajst-10983	92	35	.	.	PUNCT
ajst-10983	93	1	traditional	traditional	ADJ
ajst-10983	93	2	root	root	NOUN
ajst-10983	93	3	analysis	analysis	NOUN
ajst-10983	93	4	methods	method	NOUN
ajst-10983	93	5	require	require	VERB
ajst-10983	93	6	a	a	DET
ajst-10983	93	7	lot	lot	NOUN
ajst-10983	93	8	of	of	ADP
ajst-10983	93	9	manual	manual	ADJ
ajst-10983	93	10	processing	processing	NOUN
ajst-10983	93	11	work	work	NOUN
ajst-10983	93	12	and	and	CCONJ
ajst-10983	93	13	are	be	AUX
ajst-10983	93	14	prone	prone	ADJ
ajst-10983	93	15	to	to	ADP
ajst-10983	93	16	subjective	subjective	ADJ
ajst-10983	93	17	errors	error	NOUN
ajst-10983	93	18	,	,	PUNCT
ajst-10983	93	19	while	while	SCONJ
ajst-10983	93	20	deep	deep	ADJ
ajst-10983	93	21	learning	learning	NOUN
ajst-10983	93	22	technology	technology	NOUN
ajst-10983	93	23	can	can	AUX
ajst-10983	93	24	effectively	effectively	ADV
ajst-10983	93	25	realize	realize	VERB
ajst-10983	93	26	automated	automated	ADJ
ajst-10983	93	27	analysis	analysis	NOUN
ajst-10983	93	28	,	,	PUNCT
ajst-10983	93	29	and	and	CCONJ
ajst-10983	93	30	use	use	VERB
ajst-10983	93	31	multilayer	multilayer	ADJ
ajst-10983	93	32	neural	neural	ADJ
ajst-10983	93	33	networks	network	NOUN
ajst-10983	93	34	to	to	PART
ajst-10983	93	35	learn	learn	VERB
ajst-10983	93	36	and	and	CCONJ
ajst-10983	93	37	extract	extract	VERB
ajst-10983	93	38	complex	complex	ADJ
ajst-10983	93	39	image	image	NOUN
ajst-10983	93	40	information	information	NOUN
ajst-10983	93	41	accurately	accurately	ADV
ajst-10983	93	42	.	.	PUNCT
ajst-10983	94	1	3.1	3.1	NUM
ajst-10983	94	2	.	.	PUNCT
ajst-10983	94	3	deep	deep	ADJ
ajst-10983	94	4	learning	learn	VERB
ajst-10983	94	5	plant	plant	NOUN
ajst-10983	94	6	root	root	NOUN
ajst-10983	94	7	segmentation	segmentation	NOUN
ajst-10983	94	8	method	method	NOUN
ajst-10983	94	9	at	at	ADP
ajst-10983	94	10	present	present	ADJ
ajst-10983	94	11	,	,	PUNCT
ajst-10983	94	12	a	a	DET
ajst-10983	94	13	large	large	ADJ
ajst-10983	94	14	number	number	NOUN
ajst-10983	94	15	of	of	ADP
ajst-10983	94	16	studies	study	NOUN
ajst-10983	94	17	have	have	AUX
ajst-10983	94	18	explored	explore	VERB
ajst-10983	94	19	the	the	DET
ajst-10983	94	20	application	application	NOUN
ajst-10983	94	21	of	of	ADP
ajst-10983	94	22	deep	deep	ADJ
ajst-10983	94	23	learning	learning	NOUN
ajst-10983	94	24	in	in	ADP
ajst-10983	94	25	plant	plant	NOUN
ajst-10983	94	26	root	root	NOUN
ajst-10983	94	27	image	image	NOUN
ajst-10983	94	28	segmentation	segmentation	NOUN
ajst-10983	94	29	.	.	PUNCT
ajst-10983	95	1	two	two	NUM
ajst-10983	95	2	kinds	kind	NOUN
ajst-10983	95	3	of	of	ADP
ajst-10983	95	4	methods	method	NOUN
ajst-10983	95	5	are	be	AUX
ajst-10983	95	6	mainly	mainly	ADV
ajst-10983	95	7	used	use	VERB
ajst-10983	95	8	in	in	ADP
ajst-10983	95	9	deep	deep	ADJ
ajst-10983	95	10	learning	learning	NOUN
ajst-10983	95	11	-	-	PUNCT
ajst-10983	95	12	based	base	VERB
ajst-10983	95	13	plant	plant	NOUN
ajst-10983	95	14	root	root	NOUN
ajst-10983	95	15	segmentation	segmentation	NOUN
ajst-10983	95	16	:	:	PUNCT
ajst-10983	95	17	object	object	VERB
ajst-10983	95	18	detection	detection	NOUN
ajst-10983	95	19	and	and	CCONJ
ajst-10983	95	20	semantic	semantic	ADJ
ajst-10983	95	21	segmentation	segmentation	NOUN
ajst-10983	95	22	.	.	PUNCT
ajst-10983	96	1	the	the	DET
ajst-10983	96	2	object	object	NOUN
ajst-10983	96	3	detection	detection	NOUN
ajst-10983	96	4	method	method	NOUN
ajst-10983	96	5	can	can	AUX
ajst-10983	96	6	find	find	VERB
ajst-10983	96	7	the	the	DET
ajst-10983	96	8	region	region	NOUN
ajst-10983	96	9	of	of	ADP
ajst-10983	96	10	interest	interest	NOUN
ajst-10983	96	11	first	first	ADV
ajst-10983	96	12	,	,	PUNCT
ajst-10983	96	13	and	and	CCONJ
ajst-10983	96	14	then	then	ADV
ajst-10983	96	15	further	further	ADJ
ajst-10983	96	16	segment	segment	NOUN
ajst-10983	96	17	and	and	CCONJ
ajst-10983	96	18	extract	extract	VERB
ajst-10983	96	19	the	the	DET
ajst-10983	96	20	region	region	NOUN
ajst-10983	96	21	,	,	PUNCT
ajst-10983	96	22	so	so	CCONJ
ajst-10983	96	23	it	it	PRON
ajst-10983	96	24	has	have	VERB
ajst-10983	96	25	high	high	ADJ
ajst-10983	96	26	speed	speed	NOUN
ajst-10983	96	27	and	and	CCONJ
ajst-10983	96	28	robustness	robustness	NOUN
ajst-10983	96	29	.	.	PUNCT
ajst-10983	97	1	however	however	ADV
ajst-10983	97	2	,	,	PUNCT
ajst-10983	97	3	the	the	DET
ajst-10983	97	4	semantic	semantic	ADJ
ajst-10983	97	5	segmentation	segmentation	NOUN
ajst-10983	97	6	method	method	NOUN
ajst-10983	97	7	pays	pay	VERB
ajst-10983	97	8	more	more	ADJ
ajst-10983	97	9	attention	attention	NOUN
ajst-10983	97	10	to	to	ADP
ajst-10983	97	11	details	detail	NOUN
ajst-10983	97	12	and	and	CCONJ
ajst-10983	97	13	precision	precision	NOUN
ajst-10983	97	14	,	,	PUNCT
ajst-10983	97	15	and	and	CCONJ
ajst-10983	97	16	can	can	AUX
ajst-10983	97	17	accurately	accurately	ADV
ajst-10983	97	18	segment	segment	VERB
ajst-10983	97	19	each	each	DET
ajst-10983	97	20	part	part	NOUN
ajst-10983	97	21	of	of	ADP
ajst-10983	97	22	plant	plant	NOUN
ajst-10983	97	23	root	root	NOUN
ajst-10983	97	24	system	system	NOUN
ajst-10983	97	25	.	.	PUNCT
ajst-10983	98	1	root	root	NOUN
ajst-10983	98	2	segmentation	segmentation	NOUN
ajst-10983	98	3	methods	method	NOUN
ajst-10983	98	4	include	include	VERB
ajst-10983	98	5	convolutional	convolutional	ADJ
ajst-10983	98	6	neural	neural	ADJ
ajst-10983	98	7	network	network	NOUN
ajst-10983	98	8	(	(	PUNCT
ajst-10983	98	9	cnn	cnn	PROPN
ajst-10983	98	10	)	)	PUNCT
ajst-10983	99	1	[	[	X
ajst-10983	99	2	39	39	NUM
ajst-10983	99	3	]	]	PUNCT
ajst-10983	99	4	,	,	PUNCT
ajst-10983	99	5	full	full	ADJ
ajst-10983	99	6	convolutional	convolutional	ADJ
ajst-10983	99	7	neural	neural	ADJ
ajst-10983	99	8	network	network	NOUN
ajst-10983	99	9	(	(	PUNCT
ajst-10983	99	10	cnn	cnn	PROPN
ajst-10983	99	11	)	)	PUNCT
ajst-10983	99	12	,	,	PUNCT
ajst-10983	99	13	fcnn	fcnn	ADJ
ajst-10983	99	14	)	)	PUNCT
ajst-10983	100	1	[	[	X
ajst-10983	100	2	40	40	NUM
ajst-10983	100	3	]	]	PUNCT
ajst-10983	100	4	and	and	CCONJ
ajst-10983	100	5	deep	deep	ADJ
ajst-10983	100	6	convolutional	convolutional	ADJ
ajst-10983	100	7	neural	neural	ADJ
ajst-10983	100	8	network	network	NOUN
ajst-10983	100	9	(	(	PUNCT
ajst-10983	100	10	dcnn	dcnn	PROPN
ajst-10983	100	11	)	)	PUNCT
ajst-10983	101	1	[	[	X
ajst-10983	101	2	41	41	NUM
ajst-10983	101	3	]	]	PUNCT
ajst-10983	101	4	.	.	PUNCT
ajst-10983	102	1	among	among	ADP
ajst-10983	102	2	them	they	PRON
ajst-10983	102	3	,	,	PUNCT
ajst-10983	102	4	convolutional	convolutional	ADJ
ajst-10983	102	5	neural	neural	ADJ
ajst-10983	102	6	network	network	NOUN
ajst-10983	102	7	is	be	AUX
ajst-10983	102	8	the	the	DET
ajst-10983	102	9	most	most	ADV
ajst-10983	102	10	widely	widely	ADV
ajst-10983	102	11	used	use	VERB
ajst-10983	102	12	architecture	architecture	NOUN
ajst-10983	102	13	in	in	ADP
ajst-10983	102	14	deep	deep	ADJ
ajst-10983	102	15	learning	learning	NOUN
ajst-10983	102	16	,	,	PUNCT
ajst-10983	102	17	which	which	PRON
ajst-10983	102	18	has	have	VERB
ajst-10983	102	19	a	a	DET
ajst-10983	102	20	good	good	ADJ
ajst-10983	102	21	performance	performance	NOUN
ajst-10983	102	22	in	in	ADP
ajst-10983	102	23	the	the	DET
ajst-10983	102	24	root	root	NOUN
ajst-10983	102	25	image	image	NOUN
ajst-10983	102	26	segmentation	segmentation	NOUN
ajst-10983	102	27	task	task	NOUN
ajst-10983	102	28	.	.	PUNCT
ajst-10983	103	1	by	by	ADP
ajst-10983	103	2	constructing	construct	VERB
ajst-10983	103	3	appropriate	appropriate	ADJ
ajst-10983	103	4	network	network	NOUN
ajst-10983	103	5	structure	structure	NOUN
ajst-10983	103	6	and	and	CCONJ
ajst-10983	103	7	training	training	NOUN
ajst-10983	103	8	sample	sample	NOUN
ajst-10983	103	9	data	datum	NOUN
ajst-10983	103	10	set	set	VERB
ajst-10983	103	11	,	,	PUNCT
ajst-10983	103	12	high	high	ADJ
ajst-10983	103	13	precision	precision	NOUN
ajst-10983	103	14	root	root	NOUN
ajst-10983	103	15	segmentation	segmentation	NOUN
ajst-10983	103	16	results	result	NOUN
ajst-10983	103	17	can	can	AUX
ajst-10983	103	18	be	be	AUX
ajst-10983	103	19	obtained	obtain	VERB
ajst-10983	103	20	.	.	PUNCT
ajst-10983	104	1	therefore	therefore	ADV
ajst-10983	104	2	,	,	PUNCT
ajst-10983	104	3	in	in	ADP
ajst-10983	104	4	recent	recent	ADJ
ajst-10983	104	5	years	year	NOUN
ajst-10983	104	6	,	,	PUNCT
ajst-10983	104	7	many	many	ADJ
ajst-10983	104	8	scholars	scholar	NOUN
ajst-10983	104	9	have	have	AUX
ajst-10983	104	10	conducted	conduct	VERB
ajst-10983	104	11	research	research	NOUN
ajst-10983	104	12	on	on	ADP
ajst-10983	104	13	it	it	PRON
ajst-10983	104	14	.	.	PUNCT
ajst-10983	105	1	for	for	ADP
ajst-10983	105	2	example	example	NOUN
ajst-10983	105	3	,	,	PUNCT
ajst-10983	105	4	tao	tao	PROPN
ajst-10983	105	5	et	et	PROPN
ajst-10983	105	6	al	al	PROPN
ajst-10983	105	7	.	.	PUNCT
ajst-10983	106	1	[	[	X
ajst-10983	106	2	42	42	NUM
ajst-10983	106	3	]	]	PUNCT
ajst-10983	106	4	adopted	adopt	VERB
ajst-10983	106	5	the	the	DET
ajst-10983	106	6	convolutional	convolutional	ADJ
ajst-10983	106	7	neural	neural	ADJ
ajst-10983	106	8	network	network	NOUN
ajst-10983	106	9	architecture	architecture	NOUN
ajst-10983	106	10	and	and	CCONJ
ajst-10983	106	11	segroot	segroot	ADJ
ajst-10983	106	12	network	network	NOUN
ajst-10983	106	13	to	to	PART
ajst-10983	106	14	directly	directly	ADV
ajst-10983	106	15	learn	learn	VERB
ajst-10983	106	16	morphological	morphological	ADJ
ajst-10983	106	17	features	feature	NOUN
ajst-10983	106	18	with	with	ADP
ajst-10983	106	19	different	different	ADJ
ajst-10983	106	20	abstraction	abstraction	NOUN
ajst-10983	106	21	levels	level	NOUN
ajst-10983	106	22	from	from	ADP
ajst-10983	106	23	root	root	NOUN
ajst-10983	106	24	images	image	NOUN
ajst-10983	106	25	for	for	ADP
ajst-10983	106	26	pixel	pixel	ADJ
ajst-10983	106	27	-	-	PUNCT
ajst-10983	106	28	level	level	NOUN
ajst-10983	106	29	classification	classification	NOUN
ajst-10983	106	30	,	,	PUNCT
ajst-10983	106	31	so	so	SCONJ
ajst-10983	106	32	as	as	SCONJ
ajst-10983	106	33	to	to	PART
ajst-10983	106	34	achieve	achieve	VERB
ajst-10983	106	35	high	high	ADJ
ajst-10983	106	36	-	-	PUNCT
ajst-10983	106	37	throughput	throughput	NOUN
ajst-10983	106	38	segmentation	segmentation	NOUN
ajst-10983	106	39	of	of	ADP
ajst-10983	106	40	root	root	NOUN
ajst-10983	106	41	images	image	NOUN
ajst-10983	106	42	.	.	PUNCT
ajst-10983	107	1	in	in	ADP
ajst-10983	107	2	addition	addition	NOUN
ajst-10983	107	3	,	,	PUNCT
ajst-10983	107	4	the	the	DET
ajst-10983	107	5	idea	idea	NOUN
ajst-10983	107	6	of	of	ADP
ajst-10983	107	7	pixelsuffle	pixelsuffle	PROPN
ajst-10983	107	8	algorithm	algorithm	PROPN
ajst-10983	107	9	is	be	AUX
ajst-10983	107	10	used	use	VERB
ajst-10983	107	11	to	to	PART
ajst-10983	107	12	enhance	enhance	VERB
ajst-10983	107	13	the	the	DET
ajst-10983	107	14	fusion	fusion	NOUN
ajst-10983	107	15	features	feature	NOUN
ajst-10983	107	16	before	before	ADP
ajst-10983	107	17	the	the	DET
ajst-10983	107	18	decoder	decoder	NOUN
ajst-10983	107	19	output	output	NOUN
ajst-10983	107	20	,	,	PUNCT
ajst-10983	107	21	so	so	SCONJ
ajst-10983	107	22	as	as	SCONJ
ajst-10983	107	23	to	to	PART
ajst-10983	107	24	achieve	achieve	VERB
ajst-10983	107	25	high	high	ADJ
ajst-10983	107	26	-	-	PUNCT
ajst-10983	107	27	throughput	throughput	NOUN
ajst-10983	107	28	in	in	ADP
ajst-10983	107	29	-	-	PUNCT
ajst-10983	107	30	situ	situ	NOUN
ajst-10983	107	31	root	root	NOUN
ajst-10983	107	32	image	image	NOUN
ajst-10983	107	33	segmentation	segmentation	NOUN
ajst-10983	108	1	[	[	X
ajst-10983	108	2	28	28	NUM
ajst-10983	108	3	]	]	PUNCT
ajst-10983	108	4	.	.	PUNCT
ajst-10983	109	1	tao	tao	PROPN
ajst-10983	109	2	and	and	CCONJ
ajst-10983	109	3	shen	shen	PROPN
ajst-10983	109	4	et	et	PROPN
ajst-10983	109	5	al	al	PROPN
ajst-10983	109	6	.	.	PROPN
ajst-10983	109	7	achieved	achieve	VERB
ajst-10983	109	8	segmentation	segmentation	NOUN
ajst-10983	109	9	on	on	ADP
ajst-10983	109	10	two	two	NUM
ajst-10983	109	11	-	-	PUNCT
ajst-10983	109	12	dimensional	dimensional	ADJ
ajst-10983	109	13	root	root	NOUN
ajst-10983	109	14	images	image	NOUN
ajst-10983	109	15	,	,	PUNCT
ajst-10983	109	16	which	which	PRON
ajst-10983	109	17	can	can	AUX
ajst-10983	109	18	be	be	AUX
ajst-10983	109	19	used	use	VERB
ajst-10983	109	20	to	to	PART
ajst-10983	109	21	analyze	analyze	VERB
ajst-10983	109	22	the	the	DET
ajst-10983	109	23	growth	growth	NOUN
ajst-10983	109	24	of	of	ADP
ajst-10983	109	25	plants	plant	NOUN
ajst-10983	109	26	on	on	ADP
ajst-10983	109	27	the	the	DET
ajst-10983	109	28	plane	plane	NOUN
ajst-10983	109	29	,	,	PUNCT
ajst-10983	109	30	but	but	CCONJ
ajst-10983	109	31	the	the	DET
ajst-10983	109	32	internal	internal	ADJ
ajst-10983	109	33	morphological	morphological	ADJ
ajst-10983	109	34	structure	structure	NOUN
ajst-10983	109	35	of	of	ADP
ajst-10983	109	36	the	the	DET
ajst-10983	109	37	root	root	NOUN
ajst-10983	109	38	system	system	NOUN
ajst-10983	109	39	is	be	AUX
ajst-10983	109	40	not	not	PART
ajst-10983	109	41	well	well	ADV
ajst-10983	109	42	analyzed	analyze	VERB
ajst-10983	109	43	and	and	CCONJ
ajst-10983	109	44	studied	study	VERB
ajst-10983	109	45	.	.	PUNCT
ajst-10983	110	1	subsequently	subsequently	ADV
ajst-10983	110	2	,	,	PUNCT
ajst-10983	110	3	zhao	zhao	PROPN
ajst-10983	110	4	et	et	PROPN
ajst-10983	110	5	al	al	PROPN
ajst-10983	110	6	.	.	PUNCT
ajst-10983	111	1	[	[	X
ajst-10983	111	2	43	43	NUM
ajst-10983	111	3	]	]	PUNCT
ajst-10983	111	4	utilized	utilize	VERB
ajst-10983	111	5	a	a	DET
ajst-10983	111	6	convolutional	convolutional	ADJ
ajst-10983	111	7	neural	neural	ADJ
ajst-10983	111	8	network	network	NOUN
ajst-10983	111	9	composed	compose	VERB
ajst-10983	111	10	of	of	ADP
ajst-10983	111	11	an	an	DET
ajst-10983	111	12	encoder	encoder	NOUN
ajst-10983	111	13	and	and	CCONJ
ajst-10983	111	14	a	a	DET
ajst-10983	111	15	decoder	decoder	NOUN
ajst-10983	111	16	,	,	PUNCT
ajst-10983	111	17	and	and	CCONJ
ajst-10983	111	18	the	the	DET
ajst-10983	111	19	encoder	encoder	NOUN
ajst-10983	111	20	was	be	AUX
ajst-10983	111	21	composed	compose	VERB
ajst-10983	111	22	of	of	ADP
ajst-10983	111	23	three	three	NUM
ajst-10983	111	24	convolutional	convolutional	ADJ
ajst-10983	111	25	modules	module	NOUN
ajst-10983	111	26	to	to	PART
ajst-10983	111	27	achieve	achieve	VERB
ajst-10983	111	28	three	three	NUM
ajst-10983	111	29	-	-	PUNCT
ajst-10983	111	30	dimensional	dimensional	ADJ
ajst-10983	111	31	superresolution	superresolution	NOUN
ajst-10983	111	32	image	image	NOUN
ajst-10983	111	33	segmentation	segmentation	NOUN
ajst-10983	111	34	of	of	ADP
ajst-10983	111	35	plant	plant	NOUN
ajst-10983	111	36	root	root	NOUN
ajst-10983	111	37	mri	mri	NOUN
ajst-10983	111	38	.	.	PUNCT
ajst-10983	112	1	thus	thus	ADV
ajst-10983	112	2	,	,	PUNCT
ajst-10983	112	3	the	the	DET
ajst-10983	112	4	morphological	morphological	ADJ
ajst-10983	112	5	characteristics	characteristic	NOUN
ajst-10983	112	6	inside	inside	ADP
ajst-10983	112	7	the	the	DET
ajst-10983	112	8	root	root	NOUN
ajst-10983	112	9	system	system	NOUN
ajst-10983	112	10	can	can	AUX
ajst-10983	112	11	be	be	AUX
ajst-10983	112	12	further	far	ADV
ajst-10983	112	13	analyzed	analyze	VERB
ajst-10983	112	14	,	,	PUNCT
ajst-10983	112	15	and	and	CCONJ
ajst-10983	112	16	the	the	DET
ajst-10983	112	17	changes	change	NOUN
ajst-10983	112	18	of	of	ADP
ajst-10983	112	19	nutrients	nutrient	NOUN
ajst-10983	112	20	absorbed	absorb	VERB
ajst-10983	112	21	by	by	ADP
ajst-10983	112	22	plants	plant	NOUN
ajst-10983	112	23	can	can	AUX
ajst-10983	112	24	be	be	AUX
ajst-10983	112	25	obtained	obtain	VERB
ajst-10983	112	26	by	by	ADP
ajst-10983	112	27	using	use	VERB
ajst-10983	112	28	the	the	DET
ajst-10983	112	29	root	root	NOUN
ajst-10983	112	30	structure	structure	NOUN
ajst-10983	112	31	.	.	PUNCT
ajst-10983	113	1	some	some	DET
ajst-10983	113	2	scholars	scholar	NOUN
ajst-10983	113	3	also	also	ADV
ajst-10983	113	4	designed	design	VERB
ajst-10983	113	5	the	the	DET
ajst-10983	113	6	root	root	NOUN
ajst-10983	113	7	segmentation	segmentation	NOUN
ajst-10983	113	8	network	network	NOUN
ajst-10983	113	9	in	in	ADP
ajst-10983	113	10	order	order	NOUN
ajst-10983	113	11	to	to	PART
ajst-10983	113	12	realize	realize	VERB
ajst-10983	113	13	the	the	DET
ajst-10983	113	14	research	research	NOUN
ajst-10983	113	15	of	of	ADP
ajst-10983	113	16	a	a	DET
ajst-10983	113	17	certain	certain	ADJ
ajst-10983	113	18	growth	growth	NOUN
ajst-10983	113	19	parameter	parameter	NOUN
ajst-10983	113	20	of	of	ADP
ajst-10983	113	21	plant	plant	NOUN
ajst-10983	113	22	roots	root	NOUN
ajst-10983	113	23	.	.	PUNCT
ajst-10983	114	1	just	just	ADV
ajst-10983	114	2	as	as	SCONJ
ajst-10983	114	3	seidenthal	seidenthal	NOUN
ajst-10983	114	4	et	et	PROPN
ajst-10983	114	5	al	al	PROPN
ajst-10983	114	6	.	.	PUNCT
ajst-10983	115	1	[	[	X
ajst-10983	115	2	44	44	NUM
ajst-10983	115	3	]	]	PUNCT
ajst-10983	115	4	obtained	obtain	VERB
ajst-10983	115	5	a	a	DET
ajst-10983	115	6	high	high	ADJ
ajst-10983	115	7	-	-	PUNCT
ajst-10983	115	8	quality	quality	NOUN
ajst-10983	115	9	two	two	NUM
ajst-10983	115	10	-	-	PUNCT
ajst-10983	115	11	dimensional	dimensional	ADJ
ajst-10983	115	12	root	root	NOUN
ajst-10983	115	13	segmentation	segmentation	NOUN
ajst-10983	115	14	model	model	NOUN
ajst-10983	115	15	by	by	ADP
ajst-10983	115	16	using	use	VERB
ajst-10983	115	17	the	the	DET
ajst-10983	115	18	iterative	iterative	ADJ
ajst-10983	115	19	neural	neural	ADJ
ajst-10983	115	20	network	network	NOUN
ajst-10983	115	21	architecture	architecture	NOUN
ajst-10983	115	22	to	to	PART
ajst-10983	115	23	accurately	accurately	ADV
ajst-10983	115	24	segment	segment	VERB
ajst-10983	115	25	the	the	DET
ajst-10983	115	26	thin	thin	ADJ
ajst-10983	115	27	and	and	CCONJ
ajst-10983	115	28	highly	highly	ADV
ajst-10983	115	29	branched	branched	ADJ
ajst-10983	115	30	roots	root	NOUN
ajst-10983	115	31	.	.	PUNCT
ajst-10983	116	1	based	base	VERB
ajst-10983	116	2	on	on	ADP
ajst-10983	116	3	deeplabv3	deeplabv3	ADJ
ajst-10983	116	4	+	+	CCONJ
ajst-10983	116	5	semantic	semantic	ADJ
ajst-10983	116	6	segmentation	segmentation	NOUN
ajst-10983	116	7	model	model	NOUN
ajst-10983	116	8	,	,	PUNCT
ajst-10983	116	9	kang	kang	PROPN
ajst-10983	116	10	et	et	PROPN
ajst-10983	116	11	al	al	PROPN
ajst-10983	116	12	.	.	PUNCT
ajst-10983	117	1	[	[	X
ajst-10983	117	2	45	45	NUM
ajst-10983	117	3	]	]	PUNCT
ajst-10983	117	4	introduced	introduce	VERB
ajst-10983	117	5	subpixel	subpixel	ADJ
ajst-10983	117	6	convolution	convolution	NOUN
ajst-10983	117	7	and	and	CCONJ
ajst-10983	117	8	added	add	VERB
ajst-10983	117	9	attention	attention	NOUN
ajst-10983	117	10	mechanism	mechanism	NOUN
ajst-10983	117	11	structure	structure	NOUN
ajst-10983	117	12	.	.	PUNCT
ajst-10983	118	1	more	more	ADJ
ajst-10983	118	2	weight	weight	NOUN
ajst-10983	118	3	is	be	AUX
ajst-10983	118	4	given	give	VERB
ajst-10983	118	5	to	to	ADP
ajst-10983	118	6	fine	fine	ADJ
ajst-10983	118	7	root	root	NOUN
ajst-10983	118	8	pixels	pixel	NOUN
ajst-10983	118	9	and	and	CCONJ
ajst-10983	118	10	root	root	NOUN
ajst-10983	118	11	hairs	hair	NOUN
ajst-10983	118	12	,	,	PUNCT
ajst-10983	118	13	and	and	CCONJ
ajst-10983	118	14	a	a	DET
ajst-10983	118	15	more	more	ADV
ajst-10983	118	16	accurate	accurate	ADJ
ajst-10983	118	17	semantic	semantic	ADJ
ajst-10983	118	18	segmentation	segmentation	NOUN
ajst-10983	118	19	model	model	NOUN
ajst-10983	118	20	of	of	ADP
ajst-10983	118	21	cotton	cotton	NOUN
ajst-10983	118	22	root	root	NOUN
ajst-10983	118	23	in	in	ADP
ajst-10983	118	24	situ	situ	ADJ
ajst-10983	118	25	image	image	NOUN
ajst-10983	118	26	is	be	AUX
ajst-10983	118	27	obtained	obtain	VERB
ajst-10983	118	28	.	.	PUNCT
ajst-10983	119	1	on	on	ADP
ajst-10983	119	2	this	this	DET
ajst-10983	119	3	basis	basis	NOUN
ajst-10983	119	4	,	,	PUNCT
ajst-10983	119	5	the	the	DET
ajst-10983	119	6	network	network	NOUN
ajst-10983	119	7	model	model	NOUN
ajst-10983	119	8	is	be	AUX
ajst-10983	119	9	improved	improve	VERB
ajst-10983	119	10	to	to	PART
ajst-10983	119	11	obtain	obtain	VERB
ajst-10983	119	12	a	a	DET
ajst-10983	119	13	more	more	ADV
ajst-10983	119	14	accurate	accurate	ADJ
ajst-10983	119	15	and	and	CCONJ
ajst-10983	119	16	effective	effective	ADJ
ajst-10983	119	17	root	root	NOUN
ajst-10983	119	18	extraction	extraction	NOUN
ajst-10983	119	19	network	network	NOUN
ajst-10983	119	20	.	.	PUNCT
ajst-10983	120	1	alle	alle	NOUN
ajst-10983	120	2	et	et	PROPN
ajst-10983	120	3	al	al	PROPN
ajst-10983	120	4	.	.	PUNCT
ajst-10983	121	1	[	[	X
ajst-10983	121	2	46	46	NUM
ajst-10983	121	3	]	]	PUNCT
ajst-10983	121	4	used	use	VERB
ajst-10983	121	5	the	the	DET
ajst-10983	121	6	combination	combination	NOUN
ajst-10983	121	7	of	of	ADP
ajst-10983	121	8	deep	deep	ADJ
ajst-10983	121	9	convolutional	convolutional	ADJ
ajst-10983	121	10	neural	neural	ADJ
ajst-10983	121	11	network	network	NOUN
ajst-10983	121	12	and	and	CCONJ
ajst-10983	121	13	weakly	weakly	ADJ
ajst-10983	121	14	supervised	supervised	ADJ
ajst-10983	121	15	learning	learning	NOUN
ajst-10983	121	16	paradigm	paradigm	NOUN
ajst-10983	121	17	to	to	PART
ajst-10983	121	18	detect	detect	VERB
ajst-10983	121	19	finer	fine	ADJ
ajst-10983	121	20	root	root	NOUN
ajst-10983	121	21	structures	structure	NOUN
ajst-10983	121	22	,	,	PUNCT
ajst-10983	121	23	thereby	thereby	ADV
ajst-10983	121	24	improving	improve	VERB
ajst-10983	121	25	the	the	DET
ajst-10983	121	26	accuracy	accuracy	NOUN
ajst-10983	121	27	of	of	ADP
ajst-10983	121	28	root	root	NOUN
ajst-10983	121	29	extraction	extraction	NOUN
ajst-10983	121	30	.	.	PUNCT
ajst-10983	122	1	shen	shen	PROPN
ajst-10983	122	2	chen	chen	PROPN
ajst-10983	123	1	[	[	X
ajst-10983	123	2	17	17	NUM
ajst-10983	123	3	]	]	X
ajst-10983	123	4	uses	use	VERB
ajst-10983	123	5	sp	sp	NOUN
ajst-10983	123	6	-	-	PUNCT
ajst-10983	123	7	deeplavb3	deeplavb3	NOUN
ajst-10983	123	8	+	+	NOUN
ajst-10983	123	9	model	model	NOUN
ajst-10983	123	10	based	base	VERB
ajst-10983	123	11	on	on	ADP
ajst-10983	123	12	subpixel	subpixel	ADJ
ajst-10983	123	13	convolution	convolution	NOUN
ajst-10983	123	14	[	[	X
ajst-10983	123	15	47	47	NUM
ajst-10983	123	16	]	]	PUNCT
ajst-10983	123	17	to	to	PART
ajst-10983	123	18	segment	segment	VERB
ajst-10983	123	19	cotton	cotton	NOUN
ajst-10983	123	20	root	root	NOUN
ajst-10983	123	21	images	image	NOUN
ajst-10983	123	22	in	in	ADP
ajst-10983	123	23	situ	situ	NOUN
ajst-10983	123	24	and	and	CCONJ
ajst-10983	123	25	improve	improve	VERB
ajst-10983	123	26	the	the	DET
ajst-10983	123	27	segmentation	segmentation	NOUN
ajst-10983	123	28	accuracy	accuracy	NOUN
ajst-10983	123	29	of	of	ADP
ajst-10983	123	30	small	small	ADJ
ajst-10983	123	31	branch	branch	NOUN
ajst-10983	123	32	contours	contours	NOUN
ajst-10983	123	33	.	.	PUNCT
ajst-10983	124	1	huang	huang	PROPN
ajst-10983	124	2	et	et	PROPN
ajst-10983	124	3	al	al	PROPN
ajst-10983	124	4	.	.	PUNCT
ajst-10983	125	1	[	[	X
ajst-10983	125	2	48	48	NUM
ajst-10983	125	3	]	]	PUNCT
ajst-10983	125	4	added	add	VERB
ajst-10983	125	5	a	a	DET
ajst-10983	125	6	global	global	ADJ
ajst-10983	125	7	attention	attention	NOUN
ajst-10983	125	8	mechanism	mechanism	NOUN
ajst-10983	125	9	(	(	PUNCT
ajst-10983	125	10	gam	gam	NOUN
ajst-10983	125	11	)	)	PUNCT
ajst-10983	126	1	[	[	X
ajst-10983	126	2	49	49	NUM
ajst-10983	126	3	]	]	PUNCT
ajst-10983	126	4	to	to	ADP
ajst-10983	126	5	the	the	DET
ajst-10983	126	6	ocrnet	ocrnet	NOUN
ajst-10983	126	7	network	network	NOUN
ajst-10983	126	8	to	to	PART
ajst-10983	126	9	increase	increase	VERB
ajst-10983	126	10	the	the	DET
ajst-10983	126	11	focus	focus	NOUN
ajst-10983	126	12	on	on	ADP
ajst-10983	126	13	root	root	NOUN
ajst-10983	126	14	targets	target	NOUN
ajst-10983	126	15	and	and	CCONJ
ajst-10983	126	16	improve	improve	VERB
ajst-10983	126	17	the	the	DET
ajst-10983	126	18	accuracy	accuracy	NOUN
ajst-10983	126	19	of	of	ADP
ajst-10983	126	20	automatic	automatic	ADJ
ajst-10983	126	21	root	root	NOUN
ajst-10983	126	22	segmentation	segmentation	NOUN
ajst-10983	126	23	.	.	PUNCT
ajst-10983	127	1	on	on	ADP
ajst-10983	127	2	the	the	DET
ajst-10983	127	3	premise	premise	NOUN
ajst-10983	127	4	of	of	ADP
ajst-10983	127	5	certain	certain	ADJ
ajst-10983	127	6	accuracy	accuracy	NOUN
ajst-10983	127	7	,	,	PUNCT
ajst-10983	127	8	the	the	DET
ajst-10983	127	9	root	root	NOUN
ajst-10983	127	10	morphological	morphological	ADJ
ajst-10983	127	11	structure	structure	NOUN
ajst-10983	127	12	was	be	AUX
ajst-10983	127	13	studied	study	VERB
ajst-10983	127	14	.	.	PUNCT
ajst-10983	128	1	wulan	wulan	VERB
ajst-10983	128	2	et	et	PROPN
ajst-10983	128	3	al	al	PROPN
ajst-10983	128	4	.	.	PUNCT
ajst-10983	129	1	[	[	X
ajst-10983	129	2	50	50	NUM
ajst-10983	129	3	]	]	PUNCT
ajst-10983	129	4	based	base	VERB
ajst-10983	129	5	on	on	ADP
ajst-10983	129	6	the	the	DET
ajst-10983	129	7	improved	improved	ADJ
ajst-10983	129	8	deeplabv3+[51	deeplabv3+[51	NOUN
ajst-10983	129	9	]	]	PUNCT
ajst-10983	129	10	network	network	NOUN
ajst-10983	129	11	to	to	PART
ajst-10983	129	12	segment	segment	VERB
ajst-10983	129	13	potato	potato	NOUN
ajst-10983	129	14	root	root	NOUN
ajst-10983	129	15	image	image	NOUN
ajst-10983	129	16	and	and	CCONJ
ajst-10983	129	17	calculate	calculate	VERB
ajst-10983	129	18	potato	potato	NOUN
ajst-10983	129	19	root	root	NOUN
ajst-10983	129	20	length	length	NOUN
ajst-10983	129	21	and	and	CCONJ
ajst-10983	129	22	other	other	ADJ
ajst-10983	129	23	features	feature	NOUN
ajst-10983	129	24	,	,	PUNCT
ajst-10983	129	25	they	they	PRON
ajst-10983	129	26	can	can	AUX
ajst-10983	129	27	have	have	VERB
ajst-10983	129	28	a	a	DET
ajst-10983	129	29	more	more	ADV
ajst-10983	129	30	comprehensive	comprehensive	ADJ
ajst-10983	129	31	understanding	understanding	NOUN
ajst-10983	129	32	of	of	ADP
ajst-10983	129	33	plant	plant	NOUN
ajst-10983	129	34	growth	growth	NOUN
ajst-10983	129	35	under	under	ADP
ajst-10983	129	36	different	different	ADJ
ajst-10983	129	37	environmental	environmental	ADJ
ajst-10983	129	38	conditions	condition	NOUN
ajst-10983	129	39	,	,	PUNCT
ajst-10983	129	40	which	which	PRON
ajst-10983	129	41	is	be	AUX
ajst-10983	129	42	helpful	helpful	ADJ
ajst-10983	129	43	to	to	PART
ajst-10983	129	44	explore	explore	VERB
ajst-10983	129	45	plant	plant	NOUN
ajst-10983	129	46	physiological	physiological	ADJ
ajst-10983	129	47	ecology	ecology	NOUN
ajst-10983	129	48	and	and	CCONJ
ajst-10983	129	49	optimize	optimize	VERB
ajst-10983	129	50	plant	plant	NOUN
ajst-10983	129	51	planting	planting	NOUN
ajst-10983	129	52	management	management	NOUN
ajst-10983	129	53	.	.	PUNCT
ajst-10983	130	1	robail	robail	PROPN
ajst-10983	130	2	et	et	PROPN
ajst-10983	130	3	al	al	PROPN
ajst-10983	130	4	.	.	PUNCT
ajst-10983	131	1	[	[	X
ajst-10983	131	2	52	52	NUM
ajst-10983	131	3	]	]	PUNCT
ajst-10983	131	4	used	use	VERB
ajst-10983	131	5	a	a	DET
ajst-10983	131	6	multi	multi	ADJ
ajst-10983	131	7	-	-	ADJ
ajst-10983	131	8	task	task	ADJ
ajst-10983	131	9	convolutional	convolutional	ADJ
ajst-10983	131	10	neural	neural	ADJ
ajst-10983	131	11	network	network	NOUN
ajst-10983	131	12	to	to	PART
ajst-10983	131	13	extract	extract	VERB
ajst-10983	131	14	image	image	NOUN
ajst-10983	131	15	features	feature	NOUN
ajst-10983	131	16	from	from	ADP
ajst-10983	131	17	the	the	DET
ajst-10983	131	18	encoder	encoder	NOUN
ajst-10983	131	19	,	,	PUNCT
ajst-10983	131	20	and	and	CCONJ
ajst-10983	131	21	then	then	ADV
ajst-10983	131	22	used	use	VERB
ajst-10983	131	23	the	the	DET
ajst-10983	131	24	seeds	seed	NOUN
ajst-10983	131	25	,	,	PUNCT
ajst-10983	131	26	primary	primary	ADJ
ajst-10983	131	27	and	and	CCONJ
ajst-10983	131	28	secondary	secondary	ADJ
ajst-10983	131	29	root	root	NOUN
ajst-10983	131	30	tips	tip	NOUN
ajst-10983	131	31	located	locate	VERB
ajst-10983	131	32	by	by	ADP
ajst-10983	131	33	the	the	DET
ajst-10983	131	34	network	network	NOUN
ajst-10983	131	35	to	to	PART
ajst-10983	131	36	drive	drive	VERB
ajst-10983	131	37	the	the	DET
ajst-10983	131	38	search	search	NOUN
ajst-10983	131	39	algorithm	algorithm	NOUN
ajst-10983	131	40	to	to	PART
ajst-10983	131	41	find	find	VERB
ajst-10983	131	42	the	the	DET
ajst-10983	131	43	best	good	ADJ
ajst-10983	131	44	path	path	NOUN
ajst-10983	131	45	and	and	CCONJ
ajst-10983	131	46	extract	extract	VERB
ajst-10983	131	47	root	root	NOUN
ajst-10983	131	48	structure	structure	NOUN
ajst-10983	131	49	to	to	PART
ajst-10983	131	50	achieve	achieve	VERB
ajst-10983	131	51	automated	automate	VERB
ajst-10983	131	52	root	root	NOUN
ajst-10983	131	53	structure	structure	NOUN
ajst-10983	131	54	navigation	navigation	NOUN
ajst-10983	131	55	,	,	PUNCT
ajst-10983	131	56	thereby	thereby	ADV
ajst-10983	131	57	quantification	quantification	NOUN
ajst-10983	131	58	and	and	CCONJ
ajst-10983	131	59	recording	recording	NOUN
ajst-10983	131	60	of	of	ADP
ajst-10983	131	61	various	various	ADJ
ajst-10983	131	62	plant	plant	NOUN
ajst-10983	131	63	growth	growth	NOUN
ajst-10983	131	64	parameters	parameter	NOUN
ajst-10983	131	65	(	(	PUNCT
ajst-10983	131	66	such	such	ADJ
ajst-10983	131	67	as	as	ADP
ajst-10983	131	68	taproot	taproot	ADJ
ajst-10983	131	69	length	length	NOUN
ajst-10983	131	70	or	or	CCONJ
ajst-10983	131	71	total	total	ADJ
ajst-10983	131	72	area	area	NOUN
ajst-10983	131	73	,	,	PUNCT
ajst-10983	131	74	etc	etc	X
ajst-10983	131	75	.	.	X
ajst-10983	131	76	)	)	PUNCT
ajst-10983	131	77	.	.	PUNCT
ajst-10983	132	1	allowing	allow	VERB
ajst-10983	132	2	for	for	ADP
ajst-10983	132	3	more	more	ADV
ajst-10983	132	4	detailed	detailed	ADJ
ajst-10983	132	5	structural	structural	ADJ
ajst-10983	132	6	analysis	analysis	NOUN
ajst-10983	132	7	.	.	PUNCT
ajst-10983	133	1	although	although	SCONJ
ajst-10983	133	2	the	the	DET
ajst-10983	133	3	current	current	ADJ
ajst-10983	133	4	research	research	NOUN
ajst-10983	133	5	has	have	AUX
ajst-10983	133	6	achieved	achieve	VERB
ajst-10983	133	7	good	good	ADJ
ajst-10983	133	8	results	result	NOUN
ajst-10983	133	9	in	in	ADP
ajst-10983	133	10	the	the	DET
ajst-10983	133	11	accurate	accurate	ADJ
ajst-10983	133	12	acquisition	acquisition	NOUN
ajst-10983	133	13	of	of	ADP
ajst-10983	133	14	roots	root	NOUN
ajst-10983	133	15	,	,	PUNCT
ajst-10983	133	16	the	the	DET
ajst-10983	133	17	requirements	requirement	NOUN
ajst-10983	133	18	for	for	ADP
ajst-10983	133	19	equipment	equipment	NOUN
ajst-10983	133	20	are	be	AUX
ajst-10983	133	21	becoming	become	VERB
ajst-10983	133	22	higher	high	ADJ
ajst-10983	133	23	and	and	CCONJ
ajst-10983	133	24	higher	high	ADJ
ajst-10983	133	25	,	,	PUNCT
ajst-10983	133	26	28	28	NUM
ajst-10983	133	27	resulting	result	VERB
ajst-10983	133	28	in	in	ADP
ajst-10983	133	29	increasing	increase	VERB
ajst-10983	133	30	costs	cost	NOUN
ajst-10983	133	31	.	.	PUNCT
ajst-10983	134	1	yu	yu	PROPN
ajst-10983	134	2	et	et	PROPN
ajst-10983	134	3	al	al	PROPN
ajst-10983	134	4	.	.	PUNCT
ajst-10983	135	1	[	[	X
ajst-10983	135	2	53	53	NUM
ajst-10983	135	3	]	]	PUNCT
ajst-10983	135	4	used	use	VERB
ajst-10983	135	5	deeplabv3	deeplabv3	ADV
ajst-10983	135	6	+	+	CCONJ
ajst-10983	135	7	semantic	semantic	ADJ
ajst-10983	135	8	segmentation	segmentation	NOUN
ajst-10983	135	9	model	model	NOUN
ajst-10983	135	10	to	to	PART
ajst-10983	135	11	design	design	VERB
ajst-10983	135	12	a	a	DET
ajst-10983	135	13	time	time	NOUN
ajst-10983	135	14	-	-	PUNCT
ajst-10983	135	15	saving	save	VERB
ajst-10983	135	16	fast	fast	ADJ
ajst-10983	135	17	prediction	prediction	NOUN
ajst-10983	135	18	strategy	strategy	NOUN
ajst-10983	135	19	to	to	PART
ajst-10983	135	20	achieve	achieve	VERB
ajst-10983	135	21	low	low	ADJ
ajst-10983	135	22	-	-	PUNCT
ajst-10983	135	23	cost	cost	NOUN
ajst-10983	135	24	and	and	CCONJ
ajst-10983	135	25	portable	portable	ADJ
ajst-10983	135	26	root	root	NOUN
ajst-10983	135	27	image	image	NOUN
ajst-10983	135	28	acquisition	acquisition	NOUN
ajst-10983	135	29	and	and	CCONJ
ajst-10983	135	30	segmentation	segmentation	NOUN
ajst-10983	135	31	.	.	PUNCT
ajst-10983	136	1	although	although	SCONJ
ajst-10983	136	2	the	the	DET
ajst-10983	136	3	time	time	NOUN
ajst-10983	136	4	and	and	CCONJ
ajst-10983	136	5	cost	cost	NOUN
ajst-10983	136	6	were	be	AUX
ajst-10983	136	7	reduced	reduce	VERB
ajst-10983	136	8	,	,	PUNCT
ajst-10983	136	9	the	the	DET
ajst-10983	136	10	extraction	extraction	NOUN
ajst-10983	136	11	accuracy	accuracy	NOUN
ajst-10983	136	12	would	would	AUX
ajst-10983	136	13	also	also	ADV
ajst-10983	136	14	be	be	AUX
ajst-10983	136	15	reduced	reduce	VERB
ajst-10983	136	16	.	.	PUNCT
ajst-10983	137	1	however	however	ADV
ajst-10983	137	2	,	,	PUNCT
ajst-10983	137	3	in	in	ADP
ajst-10983	137	4	general	general	ADJ
ajst-10983	137	5	,	,	PUNCT
ajst-10983	137	6	as	as	ADP
ajst-10983	137	7	one	one	NUM
ajst-10983	137	8	of	of	ADP
ajst-10983	137	9	the	the	DET
ajst-10983	137	10	current	current	ADJ
ajst-10983	137	11	research	research	NOUN
ajst-10983	137	12	hotspots	hotspot	NOUN
ajst-10983	137	13	in	in	ADP
ajst-10983	137	14	this	this	DET
ajst-10983	137	15	field	field	NOUN
ajst-10983	137	16	,	,	PUNCT
ajst-10983	137	17	many	many	ADJ
ajst-10983	137	18	scholars	scholar	NOUN
ajst-10983	137	19	have	have	AUX
ajst-10983	137	20	carried	carry	VERB
ajst-10983	137	21	out	out	ADP
ajst-10983	137	22	a	a	DET
ajst-10983	137	23	lot	lot	NOUN
ajst-10983	137	24	of	of	ADP
ajst-10983	137	25	work	work	NOUN
ajst-10983	137	26	on	on	ADP
ajst-10983	137	27	plant	plant	NOUN
ajst-10983	137	28	root	root	NOUN
ajst-10983	137	29	segmentation	segmentation	NOUN
ajst-10983	137	30	based	base	VERB
ajst-10983	137	31	on	on	ADP
ajst-10983	137	32	deep	deep	ADJ
ajst-10983	137	33	learning	learning	NOUN
ajst-10983	137	34	in	in	ADP
ajst-10983	137	35	this	this	DET
ajst-10983	137	36	direction	direction	NOUN
ajst-10983	137	37	,	,	PUNCT
ajst-10983	137	38	and	and	CCONJ
ajst-10983	137	39	gradually	gradually	ADV
ajst-10983	137	40	achieved	achieve	VERB
ajst-10983	137	41	good	good	ADJ
ajst-10983	137	42	results	result	NOUN
ajst-10983	137	43	.	.	PUNCT
ajst-10983	138	1	among	among	ADP
ajst-10983	138	2	them	they	PRON
ajst-10983	138	3	,	,	PUNCT
ajst-10983	138	4	the	the	DET
ajst-10983	138	5	most	most	ADV
ajst-10983	138	6	common	common	ADJ
ajst-10983	138	7	deep	deep	ADJ
ajst-10983	138	8	learning	learning	NOUN
ajst-10983	138	9	model	model	NOUN
ajst-10983	138	10	is	be	AUX
ajst-10983	138	11	convolutional	convolutional	ADJ
ajst-10983	138	12	neural	neural	ADJ
ajst-10983	138	13	network	network	NOUN
ajst-10983	138	14	,	,	PUNCT
ajst-10983	138	15	such	such	ADJ
ajst-10983	138	16	as	as	ADP
ajst-10983	138	17	u	u	NOUN
ajst-10983	138	18	-	-	NOUN
ajst-10983	138	19	net[54	net[54	NOUN
ajst-10983	138	20	]	]	PUNCT
ajst-10983	138	21	,	,	PUNCT
ajst-10983	138	22	fcn	fcn	PROPN
ajst-10983	138	23	,	,	PUNCT
ajst-10983	138	24	deeplab[55	deeplab[55	NOUN
ajst-10983	138	25	]	]	PUNCT
ajst-10983	138	26	,	,	PUNCT
ajst-10983	138	27	etc	etc	X
ajst-10983	138	28	.	.	X
ajst-10983	138	29	for	for	ADP
ajst-10983	138	30	different	different	ADJ
ajst-10983	138	31	plant	plant	NOUN
ajst-10983	138	32	root	root	NOUN
ajst-10983	138	33	image	image	NOUN
ajst-10983	138	34	characteristics	characteristic	NOUN
ajst-10983	138	35	,	,	PUNCT
ajst-10983	138	36	the	the	DET
ajst-10983	138	37	researchers	researcher	NOUN
ajst-10983	138	38	also	also	ADV
ajst-10983	138	39	combined	combine	VERB
ajst-10983	138	40	the	the	DET
ajst-10983	138	41	deep	deep	ADJ
ajst-10983	138	42	learning	learning	NOUN
ajst-10983	138	43	model	model	NOUN
ajst-10983	138	44	with	with	ADP
ajst-10983	138	45	other	other	ADJ
ajst-10983	138	46	methods	method	NOUN
ajst-10983	138	47	,	,	PUNCT
ajst-10983	138	48	including	include	VERB
ajst-10983	138	49	preprocessing	preprocessing	NOUN
ajst-10983	138	50	,	,	PUNCT
ajst-10983	138	51	image	image	NOUN
ajst-10983	138	52	enhancement	enhancement	NOUN
ajst-10983	138	53	,	,	PUNCT
ajst-10983	138	54	feature	feature	NOUN
ajst-10983	138	55	fusion	fusion	NOUN
ajst-10983	138	56	,	,	PUNCT
ajst-10983	138	57	etc	etc	X
ajst-10983	138	58	.	.	X
ajst-10983	138	59	,	,	PUNCT
ajst-10983	138	60	to	to	PART
ajst-10983	138	61	improve	improve	VERB
ajst-10983	138	62	the	the	DET
ajst-10983	138	63	performance	performance	NOUN
ajst-10983	138	64	of	of	ADP
ajst-10983	138	65	the	the	DET
ajst-10983	138	66	algorithm	algorithm	NOUN
ajst-10983	138	67	.	.	PUNCT
ajst-10983	139	1	at	at	ADP
ajst-10983	139	2	the	the	DET
ajst-10983	139	3	same	same	ADJ
ajst-10983	139	4	time	time	NOUN
ajst-10983	139	5	,	,	PUNCT
ajst-10983	139	6	more	more	ADJ
ajst-10983	139	7	and	and	CCONJ
ajst-10983	139	8	more	more	ADJ
ajst-10983	139	9	scholars	scholar	NOUN
ajst-10983	139	10	have	have	AUX
ajst-10983	139	11	begun	begin	VERB
ajst-10983	139	12	to	to	PART
ajst-10983	139	13	apply	apply	VERB
ajst-10983	139	14	this	this	DET
ajst-10983	139	15	technology	technology	NOUN
ajst-10983	139	16	in	in	ADP
ajst-10983	139	17	actual	actual	ADJ
ajst-10983	139	18	agricultural	agricultural	ADJ
ajst-10983	139	19	production	production	NOUN
ajst-10983	139	20	to	to	PART
ajst-10983	139	21	solve	solve	VERB
ajst-10983	139	22	practical	practical	ADJ
ajst-10983	139	23	problems	problem	NOUN
ajst-10983	139	24	and	and	CCONJ
ajst-10983	139	25	promote	promote	VERB
ajst-10983	139	26	sustainable	sustainable	ADJ
ajst-10983	139	27	development	development	NOUN
ajst-10983	139	28	of	of	ADP
ajst-10983	139	29	agriculture	agriculture	NOUN
ajst-10983	139	30	and	and	CCONJ
ajst-10983	139	31	ecology	ecology	NOUN
ajst-10983	139	32	.	.	PUNCT
ajst-10983	140	1	3.2	3.2	NUM
ajst-10983	140	2	.	.	PUNCT
ajst-10983	140	3	application	application	NOUN
ajst-10983	140	4	areas	area	NOUN
ajst-10983	140	5	with	with	ADP
ajst-10983	140	6	the	the	DET
ajst-10983	140	7	development	development	NOUN
ajst-10983	140	8	and	and	CCONJ
ajst-10983	140	9	progress	progress	NOUN
ajst-10983	140	10	of	of	ADP
ajst-10983	140	11	science	science	NOUN
ajst-10983	140	12	and	and	CCONJ
ajst-10983	140	13	technology	technology	NOUN
ajst-10983	140	14	,	,	PUNCT
ajst-10983	140	15	deep	deep	ADJ
ajst-10983	140	16	learning	learning	NOUN
ajst-10983	140	17	-	-	PUNCT
ajst-10983	140	18	based	base	VERB
ajst-10983	140	19	plant	plant	NOUN
ajst-10983	140	20	root	root	NOUN
ajst-10983	140	21	segmentation	segmentation	NOUN
ajst-10983	140	22	technology	technology	NOUN
ajst-10983	140	23	can	can	AUX
ajst-10983	140	24	be	be	AUX
ajst-10983	140	25	widely	widely	ADV
ajst-10983	140	26	used	use	VERB
ajst-10983	140	27	in	in	ADP
ajst-10983	140	28	plant	plant	NOUN
ajst-10983	140	29	science	science	NOUN
ajst-10983	140	30	,	,	PUNCT
ajst-10983	140	31	ecology	ecology	NOUN
ajst-10983	140	32	and	and	CCONJ
ajst-10983	140	33	agronomy	agronomy	NOUN
ajst-10983	140	34	.	.	PUNCT
ajst-10983	141	1	in	in	ADP
ajst-10983	141	2	the	the	DET
ajst-10983	141	3	field	field	NOUN
ajst-10983	141	4	of	of	ADP
ajst-10983	141	5	plant	plant	NOUN
ajst-10983	141	6	science	science	NOUN
ajst-10983	141	7	,	,	PUNCT
ajst-10983	141	8	deep	deep	ADJ
ajst-10983	141	9	learning	learning	NOUN
ajst-10983	141	10	-	-	PUNCT
ajst-10983	141	11	based	base	VERB
ajst-10983	141	12	techniques	technique	NOUN
ajst-10983	141	13	can	can	AUX
ajst-10983	141	14	be	be	AUX
ajst-10983	141	15	used	use	VERB
ajst-10983	141	16	to	to	PART
ajst-10983	141	17	study	study	VERB
ajst-10983	141	18	root	root	NOUN
ajst-10983	141	19	development	development	NOUN
ajst-10983	141	20	and	and	CCONJ
ajst-10983	141	21	structure	structure	NOUN
ajst-10983	141	22	.	.	PUNCT
ajst-10983	142	1	by	by	ADP
ajst-10983	142	2	segmentation	segmentation	NOUN
ajst-10983	142	3	of	of	ADP
ajst-10983	142	4	root	root	NOUN
ajst-10983	142	5	images	image	NOUN
ajst-10983	142	6	,	,	PUNCT
ajst-10983	142	7	the	the	DET
ajst-10983	142	8	morphological	morphological	ADJ
ajst-10983	142	9	parameters	parameter	NOUN
ajst-10983	142	10	of	of	ADP
ajst-10983	142	11	each	each	DET
ajst-10983	142	12	root	root	NOUN
ajst-10983	142	13	system	system	NOUN
ajst-10983	142	14	,	,	PUNCT
ajst-10983	142	15	such	such	ADJ
ajst-10983	142	16	as	as	ADP
ajst-10983	142	17	length	length	NOUN
ajst-10983	142	18	,	,	PUNCT
ajst-10983	142	19	diameter	diameter	NOUN
ajst-10983	142	20	and	and	CCONJ
ajst-10983	142	21	volume	volume	NOUN
ajst-10983	142	22	,	,	PUNCT
ajst-10983	142	23	can	can	AUX
ajst-10983	142	24	be	be	AUX
ajst-10983	142	25	extracted	extract	VERB
ajst-10983	142	26	,	,	PUNCT
ajst-10983	142	27	so	so	SCONJ
ajst-10983	142	28	as	as	SCONJ
ajst-10983	142	29	to	to	PART
ajst-10983	142	30	study	study	VERB
ajst-10983	142	31	the	the	DET
ajst-10983	142	32	adaptability	adaptability	NOUN
ajst-10983	142	33	and	and	CCONJ
ajst-10983	142	34	growth	growth	NOUN
ajst-10983	142	35	of	of	ADP
ajst-10983	142	36	plant	plant	NOUN
ajst-10983	142	37	roots	root	NOUN
ajst-10983	142	38	in	in	ADP
ajst-10983	142	39	different	different	ADJ
ajst-10983	142	40	environments	environment	NOUN
ajst-10983	142	41	.	.	PUNCT
ajst-10983	143	1	in	in	ADP
ajst-10983	143	2	the	the	DET
ajst-10983	143	3	field	field	NOUN
ajst-10983	143	4	of	of	ADP
ajst-10983	143	5	ecology	ecology	NOUN
ajst-10983	143	6	,	,	PUNCT
ajst-10983	143	7	combined	combine	VERB
ajst-10983	143	8	deep	deep	ADJ
ajst-10983	143	9	learning	learning	NOUN
ajst-10983	143	10	techniques	technique	NOUN
ajst-10983	143	11	can	can	AUX
ajst-10983	143	12	be	be	AUX
ajst-10983	143	13	used	use	VERB
ajst-10983	143	14	to	to	PART
ajst-10983	143	15	study	study	VERB
ajst-10983	143	16	the	the	DET
ajst-10983	143	17	structure	structure	NOUN
ajst-10983	143	18	and	and	CCONJ
ajst-10983	143	19	function	function	NOUN
ajst-10983	143	20	of	of	ADP
ajst-10983	143	21	plant	plant	NOUN
ajst-10983	143	22	communities	community	NOUN
ajst-10983	143	23	.	.	PUNCT
ajst-10983	144	1	by	by	ADP
ajst-10983	144	2	segmentation	segmentation	NOUN
ajst-10983	144	3	of	of	ADP
ajst-10983	144	4	a	a	DET
ajst-10983	144	5	large	large	ADJ
ajst-10983	144	6	number	number	NOUN
ajst-10983	144	7	of	of	ADP
ajst-10983	144	8	plant	plant	NOUN
ajst-10983	144	9	root	root	NOUN
ajst-10983	144	10	images	image	NOUN
ajst-10983	144	11	,	,	PUNCT
ajst-10983	144	12	various	various	ADJ
ajst-10983	144	13	types	type	NOUN
ajst-10983	144	14	of	of	ADP
ajst-10983	144	15	root	root	NOUN
ajst-10983	144	16	information	information	NOUN
ajst-10983	144	17	can	can	AUX
ajst-10983	144	18	be	be	AUX
ajst-10983	144	19	obtained	obtain	VERB
ajst-10983	144	20	,	,	PUNCT
ajst-10983	144	21	such	such	ADJ
ajst-10983	144	22	as	as	ADP
ajst-10983	144	23	root	root	NOUN
ajst-10983	144	24	density	density	NOUN
ajst-10983	144	25	,	,	PUNCT
ajst-10983	144	26	depth	depth	NOUN
ajst-10983	144	27	,	,	PUNCT
ajst-10983	144	28	distribution	distribution	NOUN
ajst-10983	144	29	area	area	NOUN
ajst-10983	144	30	,	,	PUNCT
ajst-10983	144	31	etc	etc	X
ajst-10983	144	32	.	.	X
ajst-10983	144	33	,	,	PUNCT
ajst-10983	144	34	so	so	SCONJ
ajst-10983	144	35	as	as	SCONJ
ajst-10983	144	36	to	to	PART
ajst-10983	144	37	better	well	ADV
ajst-10983	144	38	grasp	grasp	VERB
ajst-10983	144	39	the	the	DET
ajst-10983	144	40	root	root	NOUN
ajst-10983	144	41	composition	composition	NOUN
ajst-10983	144	42	and	and	CCONJ
ajst-10983	144	43	functional	functional	ADJ
ajst-10983	144	44	characteristics	characteristic	NOUN
ajst-10983	144	45	of	of	ADP
ajst-10983	144	46	plant	plant	NOUN
ajst-10983	144	47	communities	community	NOUN
ajst-10983	144	48	.	.	PUNCT
ajst-10983	145	1	in	in	ADP
ajst-10983	145	2	agronomy	agronomy	NOUN
ajst-10983	145	3	,	,	PUNCT
ajst-10983	145	4	deep	deep	ADJ
ajst-10983	145	5	learning	learning	NOUN
ajst-10983	145	6	techniques	technique	NOUN
ajst-10983	145	7	can	can	AUX
ajst-10983	145	8	be	be	AUX
ajst-10983	145	9	used	use	VERB
ajst-10983	145	10	to	to	PART
ajst-10983	145	11	study	study	VERB
ajst-10983	145	12	the	the	DET
ajst-10983	145	13	impact	impact	NOUN
ajst-10983	145	14	of	of	ADP
ajst-10983	145	15	plant	plant	NOUN
ajst-10983	145	16	roots	root	NOUN
ajst-10983	145	17	on	on	ADP
ajst-10983	145	18	agricultural	agricultural	ADJ
ajst-10983	145	19	production	production	NOUN
ajst-10983	145	20	.	.	PUNCT
ajst-10983	146	1	through	through	ADP
ajst-10983	146	2	the	the	DET
ajst-10983	146	3	segmentation	segmentation	NOUN
ajst-10983	146	4	of	of	ADP
ajst-10983	146	5	plant	plant	NOUN
ajst-10983	146	6	root	root	NOUN
ajst-10983	146	7	images	image	NOUN
ajst-10983	146	8	in	in	ADP
ajst-10983	146	9	farmland	farmland	NOUN
ajst-10983	146	10	,	,	PUNCT
ajst-10983	146	11	the	the	DET
ajst-10983	146	12	information	information	NOUN
ajst-10983	146	13	of	of	ADP
ajst-10983	146	14	root	root	NOUN
ajst-10983	146	15	morphology	morphology	NOUN
ajst-10983	146	16	and	and	CCONJ
ajst-10983	146	17	structure	structure	NOUN
ajst-10983	146	18	is	be	AUX
ajst-10983	146	19	used	use	VERB
ajst-10983	146	20	to	to	PART
ajst-10983	146	21	predict	predict	VERB
ajst-10983	146	22	climate	climate	NOUN
ajst-10983	146	23	change	change	NOUN
ajst-10983	146	24	,	,	PUNCT
ajst-10983	146	25	and	and	CCONJ
ajst-10983	146	26	the	the	DET
ajst-10983	146	27	growth	growth	NOUN
ajst-10983	146	28	of	of	ADP
ajst-10983	146	29	agricultural	agricultural	ADJ
ajst-10983	146	30	products	product	NOUN
ajst-10983	146	31	under	under	ADP
ajst-10983	146	32	different	different	ADJ
ajst-10983	146	33	climate	climate	NOUN
ajst-10983	146	34	and	and	CCONJ
ajst-10983	146	35	environment	environment	NOUN
ajst-10983	146	36	changes	change	NOUN
ajst-10983	146	37	is	be	AUX
ajst-10983	146	38	understood	understand	VERB
ajst-10983	146	39	,	,	PUNCT
ajst-10983	146	40	so	so	SCONJ
ajst-10983	146	41	as	as	SCONJ
ajst-10983	146	42	to	to	PART
ajst-10983	146	43	provide	provide	VERB
ajst-10983	146	44	manufacturing	manufacturing	NOUN
ajst-10983	146	45	tools	tool	NOUN
ajst-10983	146	46	for	for	ADP
ajst-10983	146	47	digital	digital	ADJ
ajst-10983	146	48	agriculture	agriculture	NOUN
ajst-10983	146	49	.	.	PUNCT
ajst-10983	147	1	4	4	X
ajst-10983	147	2	.	.	X
ajst-10983	147	3	conclusion	conclusion	NOUN
ajst-10983	147	4	in	in	ADP
ajst-10983	147	5	summary	summary	NOUN
ajst-10983	147	6	,	,	PUNCT
ajst-10983	147	7	compared	compare	VERB
ajst-10983	147	8	with	with	ADP
ajst-10983	147	9	traditional	traditional	ADJ
ajst-10983	147	10	methods	method	NOUN
ajst-10983	147	11	,	,	PUNCT
ajst-10983	147	12	deep	deep	ADJ
ajst-10983	147	13	learning	learning	NOUN
ajst-10983	147	14	models	model	NOUN
ajst-10983	147	15	can	can	AUX
ajst-10983	147	16	automatically	automatically	ADV
ajst-10983	147	17	segment	segment	VERB
ajst-10983	147	18	plant	plant	NOUN
ajst-10983	147	19	roots	root	NOUN
ajst-10983	147	20	and	and	CCONJ
ajst-10983	147	21	produce	produce	VERB
ajst-10983	147	22	more	more	ADV
ajst-10983	147	23	accurate	accurate	ADJ
ajst-10983	147	24	root	root	NOUN
ajst-10983	147	25	segmentation	segmentation	NOUN
ajst-10983	147	26	results	result	NOUN
ajst-10983	147	27	.	.	PUNCT
ajst-10983	148	1	but	but	CCONJ
ajst-10983	148	2	its	its	PRON
ajst-10983	148	3	shortcomings	shortcoming	NOUN
ajst-10983	148	4	are	be	AUX
ajst-10983	148	5	also	also	ADV
ajst-10983	148	6	obvious	obvious	ADJ
ajst-10983	148	7	.	.	PUNCT
ajst-10983	149	1	since	since	SCONJ
ajst-10983	149	2	there	there	PRON
ajst-10983	149	3	are	be	VERB
ajst-10983	149	4	few	few	ADJ
ajst-10983	149	5	image	image	NOUN
ajst-10983	149	6	data	datum	NOUN
ajst-10983	149	7	of	of	ADP
ajst-10983	149	8	plant	plant	NOUN
ajst-10983	149	9	roots	root	NOUN
ajst-10983	149	10	,	,	PUNCT
ajst-10983	149	11	it	it	PRON
ajst-10983	149	12	is	be	AUX
ajst-10983	149	13	difficult	difficult	ADJ
ajst-10983	149	14	to	to	PART
ajst-10983	149	15	obtain	obtain	VERB
ajst-10983	149	16	large	large	ADJ
ajst-10983	149	17	-	-	PUNCT
ajst-10983	149	18	scale	scale	NOUN
ajst-10983	149	19	labeled	label	VERB
ajst-10983	149	20	data	data	NOUN
ajst-10983	149	21	sets	set	NOUN
ajst-10983	149	22	,	,	PUNCT
ajst-10983	149	23	which	which	PRON
ajst-10983	149	24	makes	make	VERB
ajst-10983	149	25	it	it	PRON
ajst-10983	149	26	difficult	difficult	ADJ
ajst-10983	149	27	to	to	PART
ajst-10983	149	28	train	train	VERB
ajst-10983	149	29	deep	deep	ADJ
ajst-10983	149	30	learning	learning	NOUN
ajst-10983	149	31	models	model	NOUN
ajst-10983	149	32	.	.	PUNCT
ajst-10983	150	1	in	in	ADP
ajst-10983	150	2	addition	addition	NOUN
ajst-10983	150	3	,	,	PUNCT
ajst-10983	150	4	due	due	ADP
ajst-10983	150	5	to	to	ADP
ajst-10983	150	6	the	the	DET
ajst-10983	150	7	complex	complex	ADJ
ajst-10983	150	8	and	and	CCONJ
ajst-10983	150	9	varied	varied	ADJ
ajst-10983	150	10	soil	soil	NOUN
ajst-10983	150	11	background	background	NOUN
ajst-10983	150	12	,	,	PUNCT
ajst-10983	150	13	inconsistent	inconsistent	ADJ
ajst-10983	150	14	lighting	lighting	NOUN
ajst-10983	150	15	conditions	condition	NOUN
ajst-10983	150	16	and	and	CCONJ
ajst-10983	150	17	many	many	ADJ
ajst-10983	150	18	small	small	ADJ
ajst-10983	150	19	roots	root	NOUN
ajst-10983	150	20	,	,	PUNCT
ajst-10983	150	21	the	the	DET
ajst-10983	150	22	model	model	NOUN
ajst-10983	150	23	has	have	VERB
ajst-10983	150	24	limited	limit	VERB
ajst-10983	150	25	generalization	generalization	NOUN
ajst-10983	150	26	performance	performance	NOUN
ajst-10983	150	27	in	in	ADP
ajst-10983	150	28	the	the	DET
ajst-10983	150	29	new	new	ADJ
ajst-10983	150	30	scenario	scenario	NOUN
ajst-10983	150	31	.	.	PUNCT
ajst-10983	151	1	therefore	therefore	ADV
ajst-10983	151	2	,	,	PUNCT
ajst-10983	151	3	deep	deep	ADJ
ajst-10983	151	4	learning	learning	NOUN
ajst-10983	151	5	-	-	PUNCT
ajst-10983	151	6	based	base	VERB
ajst-10983	151	7	methods	method	NOUN
ajst-10983	151	8	often	often	ADV
ajst-10983	151	9	lack	lack	VERB
ajst-10983	151	10	explainability	explainability	NOUN
ajst-10983	151	11	,	,	PUNCT
ajst-10983	151	12	and	and	CCONJ
ajst-10983	151	13	there	there	PRON
ajst-10983	151	14	are	be	VERB
ajst-10983	151	15	certain	certain	ADJ
ajst-10983	151	16	limitations	limitation	NOUN
ajst-10983	151	17	to	to	ADP
ajst-10983	151	18	the	the	DET
ajst-10983	151	19	morphological	morphological	ADJ
ajst-10983	151	20	analysis	analysis	NOUN
ajst-10983	151	21	and	and	CCONJ
ajst-10983	151	22	physiological	physiological	ADJ
ajst-10983	151	23	characteristics	characteristic	NOUN
ajst-10983	151	24	of	of	ADP
ajst-10983	151	25	roots	root	NOUN
ajst-10983	151	26	.	.	PUNCT
ajst-10983	152	1	5	5	X
ajst-10983	152	2	.	.	X
ajst-10983	152	3	current	current	ADJ
ajst-10983	152	4	challenges	challenge	NOUN
ajst-10983	152	5	and	and	CCONJ
ajst-10983	152	6	future	future	ADJ
ajst-10983	152	7	trends	trend	NOUN
ajst-10983	152	8	with	with	ADP
ajst-10983	152	9	the	the	DET
ajst-10983	152	10	acceleration	acceleration	NOUN
ajst-10983	152	11	of	of	ADP
ajst-10983	152	12	the	the	DET
ajst-10983	152	13	new	new	ADJ
ajst-10983	152	14	round	round	NOUN
ajst-10983	152	15	of	of	ADP
ajst-10983	152	16	scientific	scientific	ADJ
ajst-10983	152	17	and	and	CCONJ
ajst-10983	152	18	technological	technological	ADJ
ajst-10983	152	19	revolution	revolution	NOUN
ajst-10983	152	20	and	and	CCONJ
ajst-10983	152	21	industrial	industrial	ADJ
ajst-10983	152	22	change	change	NOUN
ajst-10983	152	23	,	,	PUNCT
ajst-10983	152	24	many	many	ADJ
ajst-10983	152	25	key	key	ADJ
ajst-10983	152	26	subject	subject	ADJ
ajst-10983	152	27	issues	issue	NOUN
ajst-10983	152	28	and	and	CCONJ
ajst-10983	152	29	core	core	NOUN
ajst-10983	152	30	technologies	technology	NOUN
ajst-10983	152	31	have	have	AUX
ajst-10983	152	32	appeared	appear	VERB
ajst-10983	152	33	the	the	DET
ajst-10983	152	34	precursor	precursor	NOUN
ajst-10983	152	35	of	of	ADP
ajst-10983	152	36	revolutionary	revolutionary	ADJ
ajst-10983	152	37	change	change	NOUN
ajst-10983	152	38	.	.	PUNCT
ajst-10983	153	1	in	in	ADP
ajst-10983	153	2	this	this	DET
ajst-10983	153	3	context	context	NOUN
ajst-10983	153	4	,	,	PUNCT
ajst-10983	153	5	new	new	ADJ
ajst-10983	153	6	subject	subject	ADJ
ajst-10983	153	7	areas	area	NOUN
ajst-10983	153	8	and	and	CCONJ
ajst-10983	153	9	growth	growth	NOUN
ajst-10983	153	10	points	point	NOUN
ajst-10983	153	11	continue	continue	VERB
ajst-10983	153	12	to	to	PART
ajst-10983	153	13	emerge	emerge	VERB
ajst-10983	153	14	,	,	PUNCT
ajst-10983	153	15	and	and	CCONJ
ajst-10983	153	16	the	the	DET
ajst-10983	153	17	deep	deep	ADJ
ajst-10983	153	18	integration	integration	NOUN
ajst-10983	153	19	of	of	ADP
ajst-10983	153	20	interdisciplinary	interdisciplinary	NOUN
ajst-10983	153	21	has	have	AUX
ajst-10983	153	22	become	become	VERB
ajst-10983	153	23	an	an	DET
ajst-10983	153	24	irresistible	irresistible	ADJ
ajst-10983	153	25	trend	trend	NOUN
ajst-10983	153	26	.	.	PUNCT
ajst-10983	154	1	plant	plant	NOUN
ajst-10983	154	2	root	root	NOUN
ajst-10983	154	3	segmentation	segmentation	NOUN
ajst-10983	154	4	based	base	VERB
ajst-10983	154	5	on	on	ADP
ajst-10983	154	6	deep	deep	ADJ
ajst-10983	154	7	learning	learning	NOUN
ajst-10983	154	8	plays	play	VERB
ajst-10983	154	9	an	an	DET
ajst-10983	154	10	important	important	ADJ
ajst-10983	154	11	role	role	NOUN
ajst-10983	154	12	in	in	ADP
ajst-10983	154	13	promoting	promote	VERB
ajst-10983	154	14	interdisciplinary	interdisciplinary	ADJ
ajst-10983	154	15	integration	integration	NOUN
ajst-10983	154	16	.	.	PUNCT
ajst-10983	155	1	however	however	ADV
ajst-10983	155	2	,	,	PUNCT
ajst-10983	155	3	there	there	PRON
ajst-10983	155	4	are	be	VERB
ajst-10983	155	5	still	still	ADV
ajst-10983	155	6	some	some	DET
ajst-10983	155	7	challenges	challenge	NOUN
ajst-10983	155	8	and	and	CCONJ
ajst-10983	155	9	problems	problem	NOUN
ajst-10983	155	10	in	in	ADP
ajst-10983	155	11	this	this	DET
ajst-10983	155	12	field	field	NOUN
ajst-10983	155	13	.	.	PUNCT
ajst-10983	156	1	firstly	firstly	ADV
ajst-10983	156	2	,	,	PUNCT
ajst-10983	156	3	the	the	DET
ajst-10983	156	4	quality	quality	NOUN
ajst-10983	156	5	of	of	ADP
ajst-10983	156	6	plant	plant	NOUN
ajst-10983	156	7	root	root	NOUN
ajst-10983	156	8	data	datum	NOUN
ajst-10983	156	9	directly	directly	ADV
ajst-10983	156	10	affects	affect	VERB
ajst-10983	156	11	the	the	DET
ajst-10983	156	12	performance	performance	NOUN
ajst-10983	156	13	of	of	ADP
ajst-10983	156	14	the	the	DET
ajst-10983	156	15	segmentation	segmentation	NOUN
ajst-10983	156	16	model	model	NOUN
ajst-10983	156	17	.	.	PUNCT
ajst-10983	157	1	since	since	SCONJ
ajst-10983	157	2	roots	root	NOUN
ajst-10983	157	3	grow	grow	VERB
ajst-10983	157	4	in	in	ADP
ajst-10983	157	5	soil	soil	NOUN
ajst-10983	157	6	,	,	PUNCT
ajst-10983	157	7	obtaining	obtain	VERB
ajst-10983	157	8	clear	clear	ADJ
ajst-10983	157	9	,	,	PUNCT
ajst-10983	157	10	high	high	ADJ
ajst-10983	157	11	-	-	PUNCT
ajst-10983	157	12	quality	quality	NOUN
ajst-10983	157	13	images	image	NOUN
ajst-10983	157	14	of	of	ADP
ajst-10983	157	15	roots	root	NOUN
ajst-10983	157	16	is	be	AUX
ajst-10983	157	17	a	a	DET
ajst-10983	157	18	challenging	challenging	ADJ
ajst-10983	157	19	task	task	NOUN
ajst-10983	157	20	.	.	PUNCT
ajst-10983	158	1	in	in	ADP
ajst-10983	158	2	the	the	DET
ajst-10983	158	3	image	image	NOUN
ajst-10983	158	4	,	,	PUNCT
ajst-10983	158	5	there	there	PRON
ajst-10983	158	6	may	may	AUX
ajst-10983	158	7	be	be	AUX
ajst-10983	158	8	noise	noise	NOUN
ajst-10983	158	9	interference	interference	NOUN
ajst-10983	158	10	such	such	ADJ
ajst-10983	158	11	as	as	ADP
ajst-10983	158	12	soil	soil	NOUN
ajst-10983	158	13	particles	particle	NOUN
ajst-10983	158	14	and	and	CCONJ
ajst-10983	158	15	weed	weed	NOUN
ajst-10983	158	16	cover	cover	NOUN
ajst-10983	158	17	,	,	PUNCT
ajst-10983	158	18	and	and	CCONJ
ajst-10983	158	19	the	the	DET
ajst-10983	158	20	root	root	NOUN
ajst-10983	158	21	structure	structure	NOUN
ajst-10983	158	22	is	be	AUX
ajst-10983	158	23	complex	complex	ADJ
ajst-10983	158	24	and	and	CCONJ
ajst-10983	158	25	diverse	diverse	ADJ
ajst-10983	158	26	,	,	PUNCT
ajst-10983	158	27	and	and	CCONJ
ajst-10983	158	28	its	its	PRON
ajst-10983	158	29	shape	shape	NOUN
ajst-10983	158	30	will	will	AUX
ajst-10983	158	31	change	change	VERB
ajst-10983	158	32	with	with	ADP
ajst-10983	158	33	the	the	DET
ajst-10983	158	34	change	change	NOUN
ajst-10983	158	35	of	of	ADP
ajst-10983	158	36	environment	environment	NOUN
ajst-10983	158	37	and	and	CCONJ
ajst-10983	158	38	growth	growth	NOUN
ajst-10983	158	39	conditions	condition	NOUN
ajst-10983	158	40	.	.	PUNCT
ajst-10983	159	1	these	these	DET
ajst-10983	159	2	factors	factor	NOUN
ajst-10983	159	3	may	may	AUX
ajst-10983	159	4	lead	lead	VERB
ajst-10983	159	5	to	to	ADP
ajst-10983	159	6	the	the	DET
ajst-10983	159	7	instability	instability	NOUN
ajst-10983	159	8	of	of	ADP
ajst-10983	159	9	data	datum	NOUN
ajst-10983	159	10	quality	quality	NOUN
ajst-10983	159	11	,	,	PUNCT
ajst-10983	159	12	which	which	PRON
ajst-10983	159	13	in	in	ADP
ajst-10983	159	14	turn	turn	NOUN
ajst-10983	159	15	affects	affect	VERB
ajst-10983	159	16	the	the	DET
ajst-10983	159	17	accuracy	accuracy	NOUN
ajst-10983	159	18	and	and	CCONJ
ajst-10983	159	19	generalization	generalization	NOUN
ajst-10983	159	20	ability	ability	NOUN
ajst-10983	159	21	of	of	ADP
ajst-10983	159	22	the	the	DET
ajst-10983	159	23	model	model	NOUN
ajst-10983	159	24	.	.	PUNCT
ajst-10983	160	1	secondly	secondly	ADV
ajst-10983	160	2	,	,	PUNCT
ajst-10983	160	3	the	the	DET
ajst-10983	160	4	fitting	fitting	ADJ
ajst-10983	160	5	ability	ability	NOUN
ajst-10983	160	6	of	of	ADP
ajst-10983	160	7	root	root	NOUN
ajst-10983	160	8	segmentation	segmentation	NOUN
ajst-10983	160	9	model	model	NOUN
ajst-10983	160	10	is	be	AUX
ajst-10983	160	11	limited	limit	VERB
ajst-10983	160	12	by	by	ADP
ajst-10983	160	13	traditional	traditional	ADJ
ajst-10983	160	14	segmentation	segmentation	NOUN
ajst-10983	160	15	methods	method	NOUN
ajst-10983	160	16	.	.	PUNCT
ajst-10983	161	1	previous	previous	ADJ
ajst-10983	161	2	studies	study	NOUN
ajst-10983	161	3	have	have	AUX
ajst-10983	161	4	used	use	VERB
ajst-10983	161	5	rule	rule	NOUN
ajst-10983	161	6	-	-	PUNCT
ajst-10983	161	7	based	base	VERB
ajst-10983	161	8	,	,	PUNCT
ajst-10983	161	9	threshold	threshold	NOUN
ajst-10983	161	10	-	-	PUNCT
ajst-10983	161	11	based	base	VERB
ajst-10983	161	12	,	,	PUNCT
ajst-10983	161	13	or	or	CCONJ
ajst-10983	161	14	feature	feature	NOUN
ajst-10983	161	15	-	-	PUNCT
ajst-10983	161	16	based	base	VERB
ajst-10983	161	17	methods	method	NOUN
ajst-10983	161	18	to	to	PART
ajst-10983	161	19	extract	extract	VERB
ajst-10983	161	20	root	root	NOUN
ajst-10983	161	21	profiles	profile	NOUN
ajst-10983	161	22	,	,	PUNCT
ajst-10983	161	23	but	but	CCONJ
ajst-10983	161	24	these	these	DET
ajst-10983	161	25	methods	method	NOUN
ajst-10983	161	26	tend	tend	VERB
ajst-10983	161	27	to	to	PART
ajst-10983	161	28	be	be	AUX
ajst-10983	161	29	less	less	ADV
ajst-10983	161	30	effective	effective	ADJ
ajst-10983	161	31	for	for	ADP
ajst-10983	161	32	complex	complex	ADJ
ajst-10983	161	33	root	root	NOUN
ajst-10983	161	34	structures	structure	NOUN
ajst-10983	161	35	.	.	PUNCT
ajst-10983	162	1	deep	deep	ADJ
ajst-10983	162	2	learning	learning	NOUN
ajst-10983	162	3	models	model	NOUN
ajst-10983	162	4	perform	perform	VERB
ajst-10983	162	5	significantly	significantly	ADV
ajst-10983	162	6	better	well	ADJ
ajst-10983	162	7	than	than	ADP
ajst-10983	162	8	traditional	traditional	ADJ
ajst-10983	162	9	methods	method	NOUN
ajst-10983	162	10	in	in	ADP
ajst-10983	162	11	root	root	NOUN
ajst-10983	162	12	segmentation	segmentation	NOUN
ajst-10983	162	13	,	,	PUNCT
ajst-10983	162	14	but	but	CCONJ
ajst-10983	162	15	there	there	PRON
ajst-10983	162	16	are	be	VERB
ajst-10983	162	17	still	still	ADV
ajst-10983	162	18	difficulties	difficulty	NOUN
ajst-10983	162	19	in	in	ADP
ajst-10983	162	20	some	some	DET
ajst-10983	162	21	cases	case	NOUN
ajst-10983	162	22	.	.	PUNCT
ajst-10983	163	1	for	for	ADP
ajst-10983	163	2	example	example	NOUN
ajst-10983	163	3	,	,	PUNCT
ajst-10983	163	4	in	in	ADP
ajst-10983	163	5	cases	case	NOUN
ajst-10983	163	6	where	where	SCONJ
ajst-10983	163	7	roots	root	NOUN
ajst-10983	163	8	are	be	AUX
ajst-10983	163	9	crossed	cross	VERB
ajst-10983	163	10	or	or	CCONJ
ajst-10983	163	11	obscured	obscure	VERB
ajst-10983	163	12	,	,	PUNCT
ajst-10983	163	13	the	the	DET
ajst-10983	163	14	model	model	NOUN
ajst-10983	163	15	may	may	AUX
ajst-10983	163	16	not	not	PART
ajst-10983	163	17	accurately	accurately	ADV
ajst-10983	163	18	segment	segment	VERB
ajst-10983	163	19	the	the	DET
ajst-10983	163	20	roots	root	NOUN
ajst-10983	163	21	or	or	CCONJ
ajst-10983	163	22	have	have	VERB
ajst-10983	163	23	difficulty	difficulty	NOUN
ajst-10983	163	24	distinguishing	distinguish	VERB
ajst-10983	163	25	between	between	ADP
ajst-10983	163	26	roots	root	NOUN
ajst-10983	163	27	and	and	CCONJ
ajst-10983	163	28	background	background	NOUN
ajst-10983	163	29	.	.	PUNCT
ajst-10983	164	1	in	in	ADP
ajst-10983	164	2	order	order	NOUN
ajst-10983	164	3	to	to	PART
ajst-10983	164	4	overcome	overcome	VERB
ajst-10983	164	5	these	these	DET
ajst-10983	164	6	challenges	challenge	NOUN
ajst-10983	164	7	,	,	PUNCT
ajst-10983	164	8	we	we	PRON
ajst-10983	164	9	can	can	AUX
ajst-10983	164	10	concentrate	concentrate	VERB
ajst-10983	164	11	on	on	ADP
ajst-10983	164	12	collecting	collect	VERB
ajst-10983	164	13	more	more	ADJ
ajst-10983	164	14	high	high	ADJ
ajst-10983	164	15	-	-	PUNCT
ajst-10983	164	16	quality	quality	NOUN
ajst-10983	164	17	root	root	NOUN
ajst-10983	164	18	image	image	NOUN
ajst-10983	164	19	data	datum	NOUN
ajst-10983	164	20	,	,	PUNCT
ajst-10983	164	21	establish	establish	VERB
ajst-10983	164	22	a	a	DET
ajst-10983	164	23	larger	large	ADJ
ajst-10983	164	24	dataset	dataset	NOUN
ajst-10983	164	25	of	of	ADP
ajst-10983	164	26	plant	plant	NOUN
ajst-10983	164	27	root	root	NOUN
ajst-10983	164	28	image	image	NOUN
ajst-10983	164	29	,	,	PUNCT
ajst-10983	164	30	and	and	CCONJ
ajst-10983	164	31	optimize	optimize	VERB
ajst-10983	164	32	and	and	CCONJ
ajst-10983	164	33	improve	improve	VERB
ajst-10983	164	34	the	the	DET
ajst-10983	164	35	segmentation	segmentation	NOUN
ajst-10983	164	36	model	model	NOUN
ajst-10983	164	37	for	for	ADP
ajst-10983	164	38	different	different	ADJ
ajst-10983	164	39	types	type	NOUN
ajst-10983	164	40	of	of	ADP
ajst-10983	164	41	root	root	NOUN
ajst-10983	164	42	structure	structure	NOUN
ajst-10983	164	43	to	to	PART
ajst-10983	164	44	improve	improve	VERB
ajst-10983	164	45	the	the	DET
ajst-10983	164	46	accuracy	accuracy	NOUN
ajst-10983	164	47	and	and	CCONJ
ajst-10983	164	48	robustness	robustness	NOUN
ajst-10983	164	49	of	of	ADP
ajst-10983	164	50	root	root	NOUN
ajst-10983	164	51	segmentation	segmentation	NOUN
ajst-10983	164	52	.	.	PUNCT
ajst-10983	165	1	secondly	secondly	ADV
ajst-10983	165	2	,	,	PUNCT
ajst-10983	165	3	multi	multi	ADJ
ajst-10983	165	4	-	-	ADJ
ajst-10983	165	5	source	source	NOUN
ajst-10983	165	6	data	datum	NOUN
ajst-10983	165	7	can	can	AUX
ajst-10983	165	8	be	be	AUX
ajst-10983	165	9	used	use	VERB
ajst-10983	165	10	for	for	ADP
ajst-10983	165	11	joint	joint	ADJ
ajst-10983	165	12	analysis	analysis	NOUN
ajst-10983	165	13	.	.	PUNCT
ajst-10983	166	1	at	at	ADP
ajst-10983	166	2	present	present	ADJ
ajst-10983	166	3	,	,	PUNCT
ajst-10983	166	4	plant	plant	NOUN
ajst-10983	166	5	root	root	NOUN
ajst-10983	166	6	segmentation	segmentation	NOUN
ajst-10983	166	7	based	base	VERB
ajst-10983	166	8	on	on	ADP
ajst-10983	166	9	deep	deep	ADJ
ajst-10983	166	10	learning	learning	NOUN
ajst-10983	166	11	can	can	AUX
ajst-10983	166	12	use	use	VERB
ajst-10983	166	13	different	different	ADJ
ajst-10983	166	14	types	type	NOUN
ajst-10983	166	15	of	of	ADP
ajst-10983	166	16	data	datum	NOUN
ajst-10983	166	17	such	such	ADJ
ajst-10983	166	18	as	as	ADP
ajst-10983	166	19	rgb	rgb	PROPN
ajst-10983	166	20	image	image	NOUN
ajst-10983	166	21	,	,	PUNCT
ajst-10983	166	22	infrared	infrared	ADJ
ajst-10983	166	23	image	image	NOUN
ajst-10983	166	24	and	and	CCONJ
ajst-10983	166	25	x	x	NOUN
ajst-10983	166	26	-	-	NOUN
ajst-10983	166	27	ray	ray	NOUN
ajst-10983	166	28	image	image	NOUN
ajst-10983	166	29	to	to	PART
ajst-10983	166	30	obtain	obtain	VERB
ajst-10983	166	31	more	more	ADV
ajst-10983	166	32	comprehensive	comprehensive	ADJ
ajst-10983	166	33	root	root	NOUN
ajst-10983	166	34	characteristic	characteristic	ADJ
ajst-10983	166	35	information	information	NOUN
ajst-10983	166	36	.	.	PUNCT
ajst-10983	167	1	further	far	ADV
ajst-10983	167	2	,	,	PUNCT
ajst-10983	167	3	future	future	ADJ
ajst-10983	167	4	studies	study	NOUN
ajst-10983	167	5	can	can	AUX
ajst-10983	167	6	explore	explore	VERB
ajst-10983	167	7	how	how	SCONJ
ajst-10983	167	8	to	to	PART
ajst-10983	167	9	organically	organically	ADV
ajst-10983	167	10	combine	combine	VERB
ajst-10983	167	11	data	datum	NOUN
ajst-10983	167	12	from	from	ADP
ajst-10983	167	13	these	these	DET
ajst-10983	167	14	different	different	ADJ
ajst-10983	167	15	sources	source	NOUN
ajst-10983	167	16	,	,	PUNCT
ajst-10983	167	17	and	and	CCONJ
ajst-10983	167	18	transfer	transfer	VERB
ajst-10983	167	19	the	the	DET
ajst-10983	167	20	model	model	NOUN
ajst-10983	167	21	training	training	NOUN
ajst-10983	167	22	from	from	ADP
ajst-10983	167	23	large	large	ADJ
ajst-10983	167	24	-	-	PUNCT
ajst-10983	167	25	scale	scale	NOUN
ajst-10983	167	26	image	image	NOUN
ajst-10983	167	27	data	datum	NOUN
ajst-10983	167	28	sets	set	NOUN
ajst-10983	167	29	to	to	PART
ajst-10983	167	30	plant	plant	VERB
ajst-10983	167	31	root	root	NOUN
ajst-10983	167	32	images	image	NOUN
ajst-10983	167	33	by	by	ADP
ajst-10983	167	34	means	mean	NOUN
ajst-10983	167	35	of	of	ADP
ajst-10983	167	36	transfer	transfer	NOUN
ajst-10983	167	37	learning	learning	NOUN
ajst-10983	167	38	,	,	PUNCT
ajst-10983	167	39	so	so	SCONJ
ajst-10983	167	40	as	as	SCONJ
ajst-10983	167	41	to	to	PART
ajst-10983	167	42	make	make	VERB
ajst-10983	167	43	the	the	DET
ajst-10983	167	44	model	model	NOUN
ajst-10983	167	45	more	more	ADJ
ajst-10983	167	46	generalization	generalization	NOUN
ajst-10983	167	47	ability	ability	NOUN
ajst-10983	167	48	,	,	PUNCT
ajst-10983	167	49	so	so	SCONJ
ajst-10983	167	50	as	as	SCONJ
ajst-10983	167	51	to	to	PART
ajst-10983	167	52	achieve	achieve	VERB
ajst-10983	167	53	more	more	ADV
ajst-10983	167	54	accurate	accurate	ADJ
ajst-10983	167	55	and	and	CCONJ
ajst-10983	167	56	comprehensive	comprehensive	ADJ
ajst-10983	167	57	plant	plant	NOUN
ajst-10983	167	58	root	root	NOUN
ajst-10983	167	59	segmentation	segmentation	NOUN
ajst-10983	167	60	.	.	PUNCT
ajst-10983	168	1	plant	plant	NOUN
ajst-10983	168	2	root	root	NOUN
ajst-10983	168	3	segmentation	segmentation	NOUN
ajst-10983	168	4	can	can	AUX
ajst-10983	168	5	also	also	ADV
ajst-10983	168	6	be	be	AUX
ajst-10983	168	7	combined	combine	VERB
ajst-10983	168	8	with	with	ADP
ajst-10983	168	9	animal	animal	NOUN
ajst-10983	168	10	or	or	CCONJ
ajst-10983	168	11	human	human	ADJ
ajst-10983	168	12	medical	medical	ADJ
ajst-10983	168	13	image	image	NOUN
ajst-10983	168	14	segmentation	segmentation	NOUN
ajst-10983	168	15	to	to	PART
ajst-10983	168	16	conduct	conduct	VERB
ajst-10983	168	17	cross	cross	ADJ
ajst-10983	168	18	-	-	ADJ
ajst-10983	168	19	species	species	ADJ
ajst-10983	168	20	comparative	comparative	ADJ
ajst-10983	168	21	studies	study	NOUN
ajst-10983	168	22	to	to	PART
ajst-10983	168	23	discover	discover	VERB
ajst-10983	168	24	common	common	ADJ
ajst-10983	168	25	algorithms	algorithm	NOUN
ajst-10983	168	26	and	and	CCONJ
ajst-10983	168	27	techniques	technique	NOUN
ajst-10983	168	28	.	.	PUNCT
ajst-10983	169	1	in	in	ADP
ajst-10983	169	2	addition	addition	NOUN
ajst-10983	169	3	,	,	PUNCT
ajst-10983	169	4	the	the	DET
ajst-10983	169	5	introduction	introduction	NOUN
ajst-10983	169	6	of	of	ADP
ajst-10983	169	7	advanced	advanced	ADJ
ajst-10983	169	8	technical	technical	ADJ
ajst-10983	169	9	means	mean	NOUN
ajst-10983	169	10	and	and	CCONJ
ajst-10983	169	11	framework	framework	NOUN
ajst-10983	169	12	.	.	PUNCT
ajst-10983	170	1	at	at	ADP
ajst-10983	170	2	present	present	ADJ
ajst-10983	170	3	,	,	PUNCT
ajst-10983	170	4	deep	deep	ADJ
ajst-10983	170	5	learning	learning	NOUN
ajst-10983	170	6	is	be	AUX
ajst-10983	170	7	the	the	DET
ajst-10983	170	8	mainstream	mainstream	NOUN
ajst-10983	170	9	method	method	NOUN
ajst-10983	170	10	to	to	PART
ajst-10983	170	11	deal	deal	VERB
ajst-10983	170	12	with	with	ADP
ajst-10983	170	13	the	the	DET
ajst-10983	170	14	problem	problem	NOUN
ajst-10983	170	15	of	of	ADP
ajst-10983	170	16	plant	plant	NOUN
ajst-10983	170	17	root	root	NOUN
ajst-10983	170	18	segmentation	segmentation	NOUN
ajst-10983	170	19	,	,	PUNCT
ajst-10983	170	20	and	and	CCONJ
ajst-10983	170	21	other	other	ADJ
ajst-10983	170	22	advanced	advanced	ADJ
ajst-10983	170	23	technical	technical	ADJ
ajst-10983	170	24	means	mean	NOUN
ajst-10983	170	25	and	and	CCONJ
ajst-10983	170	26	frameworks	framework	NOUN
ajst-10983	170	27	can	can	AUX
ajst-10983	170	28	be	be	AUX
ajst-10983	170	29	considered	consider	VERB
ajst-10983	170	30	in	in	ADP
ajst-10983	170	31	the	the	DET
ajst-10983	170	32	future	future	NOUN
ajst-10983	170	33	.	.	PUNCT
ajst-10983	171	1	for	for	ADP
ajst-10983	171	2	example	example	NOUN
ajst-10983	171	3	,	,	PUNCT
ajst-10983	171	4	some	some	DET
ajst-10983	171	5	new	new	ADJ
ajst-10983	171	6	image	image	NOUN
ajst-10983	171	7	processing	processing	NOUN
ajst-10983	171	8	algorithms	algorithm	NOUN
ajst-10983	171	9	,	,	PUNCT
ajst-10983	171	10	3d	3d	NUM
ajst-10983	171	11	vision	vision	NOUN
ajst-10983	171	12	reconstruction	reconstruction	NOUN
ajst-10983	171	13	from	from	ADP
ajst-10983	171	14	two	two	NUM
ajst-10983	171	15	-	-	PUNCT
ajst-10983	171	16	dimensional	dimensional	ADJ
ajst-10983	171	17	image	image	NOUN
ajst-10983	171	18	training	training	NOUN
ajst-10983	171	19	,	,	PUNCT
ajst-10983	171	20	natural	natural	ADJ
ajst-10983	171	21	language	language	NOUN
ajst-10983	171	22	processing	processing	NOUN
ajst-10983	171	23	technology	technology	NOUN
ajst-10983	171	24	and	and	CCONJ
ajst-10983	171	25	biological	biological	ADJ
ajst-10983	171	26	computing	computing	NOUN
ajst-10983	171	27	methods	method	NOUN
ajst-10983	171	28	also	also	ADV
ajst-10983	171	29	have	have	VERB
ajst-10983	171	30	a	a	DET
ajst-10983	171	31	wide	wide	ADJ
ajst-10983	171	32	range	range	NOUN
ajst-10983	171	33	of	of	ADP
ajst-10983	171	34	application	application	NOUN
ajst-10983	171	35	prospects	prospect	NOUN
ajst-10983	171	36	in	in	ADP
ajst-10983	171	37	the	the	DET
ajst-10983	171	38	analysis	analysis	NOUN
ajst-10983	171	39	and	and	CCONJ
ajst-10983	171	40	identification	identification	NOUN
ajst-10983	171	41	of	of	ADP
ajst-10983	171	42	plant	plant	NOUN
ajst-10983	171	43	roots	root	NOUN
ajst-10983	171	44	.	.	PUNCT
ajst-10983	172	1	all	all	ADV
ajst-10983	172	2	in	in	ADV
ajst-10983	172	3	all	all	PRON
ajst-10983	172	4	,	,	PUNCT
ajst-10983	172	5	for	for	ADP
ajst-10983	172	6	plant	plant	NOUN
ajst-10983	172	7	root	root	NOUN
ajst-10983	172	8	segmentation	segmentation	NOUN
ajst-10983	172	9	based	base	VERB
ajst-10983	172	10	on	on	ADP
ajst-10983	172	11	deep	deep	ADJ
ajst-10983	172	12	learning	learning	NOUN
ajst-10983	172	13	algorithm	algorithm	NOUN
ajst-10983	172	14	,	,	PUNCT
ajst-10983	172	15	further	far	ADV
ajst-10983	172	16	relevant	relevant	ADJ
ajst-10983	172	17	research	research	NOUN
ajst-10983	172	18	needs	need	VERB
ajst-10983	172	19	to	to	PART
ajst-10983	172	20	be	be	AUX
ajst-10983	172	21	carried	carry	VERB
ajst-10983	172	22	out	out	ADP
ajst-10983	172	23	in	in	ADP
ajst-10983	172	24	the	the	DET
ajst-10983	172	25	future	future	NOUN
ajst-10983	172	26	to	to	PART
ajst-10983	172	27	inject	inject	VERB
ajst-10983	172	28	new	new	ADJ
ajst-10983	172	29	ideas	idea	NOUN
ajst-10983	172	30	to	to	PART
ajst-10983	172	31	achieve	achieve	VERB
ajst-10983	172	32	more	more	ADV
ajst-10983	172	33	accurate	accurate	ADJ
ajst-10983	172	34	,	,	PUNCT
ajst-10983	172	35	faster	fast	ADJ
ajst-10983	172	36	and	and	CCONJ
ajst-10983	172	37	higher	high	ADJ
ajst-10983	172	38	level	level	NOUN
ajst-10983	172	39	plant	plant	NOUN
ajst-10983	172	40	root	root	NOUN
ajst-10983	172	41	segmentation	segmentation	NOUN
ajst-10983	172	42	.	.	PUNCT
ajst-10983	173	1	acknowledgment	acknowledgment	NOUN
ajst-10983	173	2	fund	fund	NOUN
ajst-10983	173	3	project	project	PROPN
ajst-10983	173	4	:	:	PUNCT
ajst-10983	173	5	special	special	ADJ
ajst-10983	173	6	fund	fund	NOUN
ajst-10983	173	7	for	for	ADP
ajst-10983	173	8	basic	basic	ADJ
ajst-10983	173	9	scientific	scientific	ADJ
ajst-10983	173	10	research	research	NOUN
ajst-10983	173	11	expenses	expense	NOUN
ajst-10983	173	12	of	of	ADP
ajst-10983	173	13	central	central	ADJ
ajst-10983	173	14	universities	university	NOUN
ajst-10983	173	15	(	(	PUNCT
ajst-10983	173	16	project	project	NOUN
ajst-10983	173	17	number	number	NOUN
ajst-10983	173	18	:	:	PUNCT
ajst-10983	173	19	29	29	NUM
ajst-10983	173	20	2022nyxxs093	2022nyxxs093	NUM
ajst-10983	173	21	)	)	PUNCT
ajst-10983	173	22	references	reference	NOUN
ajst-10983	173	23	[	[	X
ajst-10983	173	24	1	1	NUM
ajst-10983	173	25	]	]	X
ajst-10983	173	26	li	li	PROPN
ajst-10983	173	27	kexin	kexin	PROPN
ajst-10983	173	28	,	,	PUNCT
ajst-10983	173	29	song	song	NOUN
ajst-10983	173	30	wenlong	wenlong	PROPN
ajst-10983	173	31	,	,	PUNCT
ajst-10983	173	32	zhu	zhu	PROPN
ajst-10983	173	33	liangkuan	liangkuan	PROPN
ajst-10983	173	34	.	.	PUNCT
ajst-10983	174	1	research	research	NOUN
ajst-10983	174	2	progress	progress	NOUN
ajst-10983	174	3	of	of	ADP
ajst-10983	174	4	in	in	ADP
ajst-10983	174	5	situ	situ	ADJ
ajst-10983	174	6	observation	observation	NOUN
ajst-10983	174	7	and	and	CCONJ
ajst-10983	174	8	identification	identification	NOUN
ajst-10983	174	9	of	of	ADP
ajst-10983	174	10	plant	plant	NOUN
ajst-10983	174	11	root	root	NOUN
ajst-10983	174	12	configuration	configuration	NOUN
ajst-10983	175	1	[	[	X
ajst-10983	175	2	j	j	X
ajst-10983	175	3	]	]	X
ajst-10983	175	4	.	.	PUNCT
ajst-10983	176	1	chinese	chinese	ADJ
ajst-10983	176	2	journal	journal	PROPN
ajst-10983	176	3	of	of	ADP
ajst-10983	176	4	ecology	ecology	NOUN
ajst-10983	176	5	,	,	PUNCT
ajst-10983	176	6	2011,30(9):2066	2011,30(9):2066	NUM
ajst-10983	176	7	-	-	SYM
ajst-10983	176	8	2071	2071	NUM
ajst-10983	176	9	.	.	PUNCT
ajst-10983	177	1	(	(	PUNCT
ajst-10983	177	2	in	in	ADP
ajst-10983	177	3	chinese	chinese	PROPN
ajst-10983	177	4	)	)	PUNCT
ajst-10983	178	1	[	[	X
ajst-10983	178	2	2	2	NUM
ajst-10983	178	3	]	]	X
ajst-10983	178	4	crocker	crocker	PROPN
ajst-10983	178	5	,	,	PUNCT
ajst-10983	178	6	w.	w.	PROPN
ajst-10983	178	7	root	root	PROPN
ajst-10983	178	8	development	development	NOUN
ajst-10983	178	9	of	of	ADP
ajst-10983	178	10	field	field	NOUN
ajst-10983	178	11	crops	crop	NOUN
ajst-10983	178	12	.	.	PUNCT
ajst-10983	179	1	j.	j.	PROPN
ajst-10983	179	2	e.	e.	PROPN
ajst-10983	179	3	weaver[j	weaver[j	PROPN
ajst-10983	179	4	]	]	PUNCT
ajst-10983	179	5	.	.	PUNCT
ajst-10983	180	1	botanical	botanical	ADJ
ajst-10983	180	2	gazette	gazette	PROPN
ajst-10983	180	3	,	,	PUNCT
ajst-10983	180	4	1926	1926	NUM
ajst-10983	180	5	,	,	PUNCT
ajst-10983	180	6	82(2):228	82(2):228	PROPN
ajst-10983	180	7	-	-	SYM
ajst-10983	180	8	228	228	NUM
ajst-10983	180	9	.	.	PUNCT
ajst-10983	181	1	[	[	X
ajst-10983	181	2	3	3	X
ajst-10983	181	3	]	]	X
ajst-10983	181	4	boehm	boehm	PROPN
ajst-10983	181	5	w	w	PROPN
ajst-10983	181	6	.	.	PUNCT
ajst-10983	181	7	methods	method	NOUN
ajst-10983	181	8	of	of	ADP
ajst-10983	181	9	studying	study	VERB
ajst-10983	181	10	root	root	NOUN
ajst-10983	181	11	systems[m	systems[m	NOUN
ajst-10983	181	12	]	]	PUNCT
ajst-10983	181	13	.	.	PUNCT
ajst-10983	182	1	springerverlag	springerverlag	PROPN
ajst-10983	182	2	,	,	PUNCT
ajst-10983	182	3	1979	1979	NUM
ajst-10983	182	4	.	.	PUNCT
ajst-10983	183	1	[	[	X
ajst-10983	183	2	4	4	NUM
ajst-10983	183	3	]	]	X
ajst-10983	183	4	zhou	zhou	PROPN
ajst-10983	183	5	benzhi	benzhi	PROPN
ajst-10983	183	6	,	,	PUNCT
ajst-10983	183	7	zhang	zhang	PROPN
ajst-10983	183	8	shougong	shougong	PROPN
ajst-10983	183	9	,	,	PUNCT
ajst-10983	183	10	fu	fu	PROPN
ajst-10983	183	11	maoyi	maoyi	PROPN
ajst-10983	183	12	.	.	PUNCT
ajst-10983	184	1	the	the	DET
ajst-10983	184	2	origin	origin	NOUN
ajst-10983	184	3	,	,	PUNCT
ajst-10983	184	4	development	development	NOUN
ajst-10983	184	5	and	and	CCONJ
ajst-10983	184	6	application	application	NOUN
ajst-10983	184	7	of	of	ADP
ajst-10983	184	8	the	the	DET
ajst-10983	184	9	minirhizotron	minirhizotron	NOUN
ajst-10983	184	10	,	,	PUNCT
ajst-10983	184	11	a	a	DET
ajst-10983	184	12	new	new	ADJ
ajst-10983	184	13	technology	technology	NOUN
ajst-10983	184	14	for	for	ADP
ajst-10983	184	15	plant	plant	NOUN
ajst-10983	184	16	root	root	NOUN
ajst-10983	184	17	research[j	research[j	NOUN
ajst-10983	184	18	]	]	PUNCT
ajst-10983	184	19	.	.	PUNCT
ajst-10983	185	1	journal	journal	PROPN
ajst-10983	185	2	of	of	ADP
ajst-10983	185	3	ecology	ecology	NOUN
ajst-10983	185	4	,	,	PUNCT
ajst-10983	185	5	2007	2007	NUM
ajst-10983	185	6	,	,	PUNCT
ajst-10983	185	7	26(2):8	26(2):8	PROPN
ajst-10983	185	8	[	[	X
ajst-10983	185	9	5	5	NUM
ajst-10983	185	10	]	]	X
ajst-10983	185	11	guo	guo	PROPN
ajst-10983	185	12	qiqiang	qiqiang	PROPN
ajst-10983	185	13	,	,	PUNCT
ajst-10983	185	14	li	li	PROPN
ajst-10983	185	15	jiangrong	jiangrong	PROPN
ajst-10983	185	16	,	,	PUNCT
ajst-10983	185	17	bianba	bianba	PROPN
ajst-10983	185	18	duoji	duoji	PROPN
ajst-10983	185	19	,	,	PUNCT
ajst-10983	185	20	ma	ma	PROPN
ajst-10983	185	21	heping	heping	PROPN
ajst-10983	185	22	.	.	PUNCT
ajst-10983	186	1	a	a	DET
ajst-10983	186	2	review	review	NOUN
ajst-10983	186	3	of	of	ADP
ajst-10983	186	4	plant	plant	NOUN
ajst-10983	186	5	root	root	NOUN
ajst-10983	186	6	research	research	NOUN
ajst-10983	186	7	methods	method	NOUN
ajst-10983	186	8	[	[	X
ajst-10983	186	9	j	j	X
ajst-10983	186	10	]	]	X
ajst-10983	186	11	.	.	PUNCT
ajst-10983	187	1	jilin	jilin	PROPN
ajst-10983	187	2	agriculture	agriculture	PROPN
ajst-10983	187	3	,	,	PUNCT
ajst-10983	187	4	2015	2015	NUM
ajst-10983	187	5	,	,	PUNCT
ajst-10983	187	6	000(017):122	000(017):122	NOUN
ajst-10983	187	7	-	-	PUNCT
ajst-10983	187	8	123	123	NUM
ajst-10983	187	9	.	.	PUNCT
ajst-10983	188	1	[	[	X
ajst-10983	188	2	6	6	NUM
ajst-10983	188	3	]	]	PUNCT
ajst-10983	188	4	joschko	joschko	PROPN
ajst-10983	188	5	m	m	PROPN
ajst-10983	188	6	,	,	PUNCT
ajst-10983	188	7	graff	graff	VERB
ajst-10983	188	8	o	o	NOUN
ajst-10983	188	9	,	,	PUNCT
ajst-10983	188	10	müller	müller	PROPN
ajst-10983	188	11	p	p	PROPN
ajst-10983	188	12	c	c	PROPN
ajst-10983	188	13	,	,	PUNCT
ajst-10983	188	14	et	et	PROPN
ajst-10983	188	15	al	al	PROPN
ajst-10983	188	16	.	.	PUNCT
ajst-10983	189	1	a	a	DET
ajst-10983	189	2	non	non	ADJ
ajst-10983	189	3	-	-	ADJ
ajst-10983	189	4	destructive	destructive	ADJ
ajst-10983	189	5	method	method	NOUN
ajst-10983	189	6	for	for	ADP
ajst-10983	189	7	the	the	DET
ajst-10983	189	8	morphological	morphological	ADJ
ajst-10983	189	9	assessment	assessment	NOUN
ajst-10983	189	10	of	of	ADP
ajst-10983	189	11	earthworm	earthworm	NOUN
ajst-10983	189	12	burrow	burrow	NOUN
ajst-10983	189	13	systems	system	NOUN
ajst-10983	189	14	in	in	ADP
ajst-10983	189	15	three	three	NUM
ajst-10983	189	16	dimensions	dimension	NOUN
ajst-10983	189	17	by	by	ADP
ajst-10983	189	18	x	x	NOUN
ajst-10983	189	19	-	-	NOUN
ajst-10983	189	20	ray	ray	NOUN
ajst-10983	189	21	computed	compute	VERB
ajst-10983	189	22	tomography[j	tomography[j	PROPN
ajst-10983	189	23	]	]	PUNCT
ajst-10983	189	24	.	.	PUNCT
ajst-10983	190	1	biology	biology	NOUN
ajst-10983	190	2	and	and	CCONJ
ajst-10983	190	3	fertility	fertility	NOUN
ajst-10983	190	4	of	of	ADP
ajst-10983	190	5	soils	soil	NOUN
ajst-10983	190	6	,	,	PUNCT
ajst-10983	190	7	1991	1991	NUM
ajst-10983	190	8	,	,	PUNCT
ajst-10983	190	9	11	11	NUM
ajst-10983	190	10	:	:	SYM
ajst-10983	190	11	88	88	NUM
ajst-10983	190	12	-	-	SYM
ajst-10983	190	13	92	92	NUM
ajst-10983	190	14	.	.	PUNCT
ajst-10983	191	1	[	[	X
ajst-10983	191	2	7	7	NUM
ajst-10983	191	3	]	]	X
ajst-10983	191	4	damadian	damadian	PROPN
ajst-10983	191	5	r.	r.	PROPN
ajst-10983	191	6	tumor	tumor	PROPN
ajst-10983	191	7	detection	detection	NOUN
ajst-10983	191	8	by	by	ADP
ajst-10983	191	9	nuclear	nuclear	ADJ
ajst-10983	191	10	magnetic	magnetic	PROPN
ajst-10983	191	11	resonance[j	resonance[j	PROPN
ajst-10983	191	12	]	]	PUNCT
ajst-10983	191	13	.	.	PUNCT
ajst-10983	192	1	science	science	NOUN
ajst-10983	192	2	,	,	PUNCT
ajst-10983	192	3	1971	1971	NUM
ajst-10983	192	4	,	,	PUNCT
ajst-10983	192	5	171(3976	171(3976	NUM
ajst-10983	192	6	):	):	PUNCT
ajst-10983	192	7	1151	1151	NUM
ajst-10983	192	8	-	-	SYM
ajst-10983	192	9	1153	1153	NUM
ajst-10983	192	10	.	.	PUNCT
ajst-10983	193	1	[	[	X
ajst-10983	193	2	8	8	NUM
ajst-10983	193	3	]	]	X
ajst-10983	193	4	xiao	xiao	PROPN
ajst-10983	193	5	shuang	shuang	PROPN
ajst-10983	193	6	,	,	PUNCT
ajst-10983	193	7	liu	liu	PROPN
ajst-10983	193	8	liantao	liantao	PROPN
ajst-10983	193	9	,	,	PUNCT
ajst-10983	193	10	zhang	zhang	PROPN
ajst-10983	193	11	yongjiang	yongjiang	PROPN
ajst-10983	193	12	,	,	PUNCT
ajst-10983	193	13	etc	etc	X
ajst-10983	193	14	.	.	X
ajst-10983	193	15	advances	advance	NOUN
ajst-10983	193	16	in	in	ADP
ajst-10983	193	17	research	research	NOUN
ajst-10983	193	18	methods	method	NOUN
ajst-10983	193	19	for	for	ADP
ajst-10983	193	20	in	in	ADP
ajst-10983	193	21	situ	situ	ADJ
ajst-10983	193	22	observation	observation	NOUN
ajst-10983	193	23	of	of	ADP
ajst-10983	193	24	plant	plant	NOUN
ajst-10983	193	25	microroots	microroot	NOUN
ajst-10983	193	26	[	[	X
ajst-10983	193	27	j	j	X
ajst-10983	193	28	]	]	X
ajst-10983	193	29	.	.	PUNCT
ajst-10983	194	1	journal	journal	PROPN
ajst-10983	194	2	of	of	ADP
ajst-10983	194	3	plant	plant	NOUN
ajst-10983	194	4	nutrition	nutrition	NOUN
ajst-10983	194	5	and	and	CCONJ
ajst-10983	194	6	fertilizer	fertilizer	NOUN
ajst-10983	194	7	,	,	PUNCT
ajst-10983	194	8	2020,26(2):1	2020,26(2):1	NUM
ajst-10983	194	9	-	-	SYM
ajst-10983	194	10	16	16	NUM
ajst-10983	194	11	.	.	PUNCT
ajst-10983	195	1	[	[	X
ajst-10983	195	2	9	9	NUM
ajst-10983	195	3	]	]	PUNCT
ajst-10983	195	4	metzner	metzner	NOUN
ajst-10983	195	5	r	r	NOUN
ajst-10983	195	6	,	,	PUNCT
ajst-10983	195	7	eggert	eggert	PROPN
ajst-10983	195	8	a	a	PROPN
ajst-10983	195	9	,	,	PUNCT
ajst-10983	195	10	van	van	PROPN
ajst-10983	195	11	dusschoten	dusschoten	PROPN
ajst-10983	195	12	d	d	PROPN
ajst-10983	195	13	,	,	PUNCT
ajst-10983	195	14	et	et	PROPN
ajst-10983	195	15	al	al	PROPN
ajst-10983	195	16	.	.	PUNCT
ajst-10983	196	1	direct	direct	ADJ
ajst-10983	196	2	comparison	comparison	NOUN
ajst-10983	196	3	of	of	ADP
ajst-10983	196	4	mri	mri	NOUN
ajst-10983	196	5	and	and	CCONJ
ajst-10983	196	6	x	x	NOUN
ajst-10983	196	7	-	-	NOUN
ajst-10983	196	8	ray	ray	NOUN
ajst-10983	196	9	ct	ct	PROPN
ajst-10983	196	10	technologies	technology	NOUN
ajst-10983	196	11	for	for	ADP
ajst-10983	196	12	3d	3d	NUM
ajst-10983	196	13	imaging	imaging	NOUN
ajst-10983	196	14	of	of	ADP
ajst-10983	196	15	root	root	NOUN
ajst-10983	196	16	systems	system	NOUN
ajst-10983	196	17	in	in	ADP
ajst-10983	196	18	soil	soil	NOUN
ajst-10983	196	19	:	:	PUNCT
ajst-10983	196	20	potential	potential	NOUN
ajst-10983	196	21	and	and	CCONJ
ajst-10983	196	22	challenges	challenge	NOUN
ajst-10983	196	23	for	for	ADP
ajst-10983	196	24	root	root	NOUN
ajst-10983	196	25	trait	trait	NOUN
ajst-10983	196	26	quantification[j	quantification[j	NOUN
ajst-10983	196	27	]	]	PUNCT
ajst-10983	196	28	.	.	PUNCT
ajst-10983	197	1	plant	plant	NOUN
ajst-10983	197	2	methods	method	NOUN
ajst-10983	197	3	,	,	PUNCT
ajst-10983	197	4	2015	2015	NUM
ajst-10983	197	5	,	,	PUNCT
ajst-10983	197	6	11(1	11(1	NUM
ajst-10983	197	7	):	):	PUNCT
ajst-10983	197	8	1	1	NUM
ajst-10983	197	9	-	-	SYM
ajst-10983	197	10	11	11	NUM
ajst-10983	197	11	.	.	PUNCT
ajst-10983	198	1	[	[	X
ajst-10983	198	2	10	10	NUM
ajst-10983	198	3	]	]	X
ajst-10983	198	4	moran	moran	PROPN
ajst-10983	198	5	c	c	PROPN
ajst-10983	198	6	j	j	PROPN
ajst-10983	198	7	,	,	PUNCT
ajst-10983	198	8	pierret	pierret	VERB
ajst-10983	198	9	a	a	PRON
ajst-10983	198	10	,	,	PUNCT
ajst-10983	198	11	stevenson	stevenson	PROPN
ajst-10983	198	12	a	a	DET
ajst-10983	198	13	w.	w.	PROPN
ajst-10983	198	14	x	x	PROPN
ajst-10983	198	15	-	-	NOUN
ajst-10983	198	16	ray	ray	NOUN
ajst-10983	198	17	absorption	absorption	NOUN
ajst-10983	198	18	and	and	CCONJ
ajst-10983	198	19	phase	phase	NOUN
ajst-10983	198	20	contrast	contrast	NOUN
ajst-10983	198	21	imaging	imaging	NOUN
ajst-10983	198	22	to	to	PART
ajst-10983	198	23	study	study	VERB
ajst-10983	198	24	the	the	DET
ajst-10983	198	25	interplay	interplay	NOUN
ajst-10983	198	26	between	between	ADP
ajst-10983	198	27	plant	plant	NOUN
ajst-10983	198	28	roots	root	NOUN
ajst-10983	198	29	and	and	CCONJ
ajst-10983	198	30	soil	soil	NOUN
ajst-10983	198	31	structure[j	structure[j	NOUN
ajst-10983	198	32	]	]	PUNCT
ajst-10983	198	33	.	.	PUNCT
ajst-10983	199	1	plant	plant	NOUN
ajst-10983	199	2	and	and	CCONJ
ajst-10983	199	3	soil	soil	NOUN
ajst-10983	199	4	,	,	PUNCT
ajst-10983	199	5	2000	2000	NUM
ajst-10983	199	6	,	,	PUNCT
ajst-10983	199	7	223(1	223(1	NUM
ajst-10983	199	8	-	-	SYM
ajst-10983	199	9	2	2	NUM
ajst-10983	199	10	):	):	PUNCT
ajst-10983	199	11	101117	101117	NUM
ajst-10983	199	12	.	.	PUNCT
ajst-10983	200	1	[	[	X
ajst-10983	200	2	11	11	NUM
ajst-10983	200	3	]	]	PUNCT
ajst-10983	200	4	mcneill	mcneill	NOUN
ajst-10983	200	5	a，kolesik	a，kolesik	PROPN
ajst-10983	200	6	p.	p.	PROPN
ajst-10983	200	7	x	x	PROPN
ajst-10983	200	8	-	-	PUNCT
ajst-10983	200	9	ray	ray	NOUN
ajst-10983	200	10	ct	ct	NOUN
ajst-10983	200	11	investigations	investigation	NOUN
ajst-10983	200	12	of	of	ADP
ajst-10983	200	13	intact	intact	ADJ
ajst-10983	200	14	soil	soil	NOUN
ajst-10983	200	15	cores	core	NOUN
ajst-10983	200	16	with	with	ADP
ajst-10983	200	17	and	and	CCONJ
ajst-10983	200	18	without	without	ADP
ajst-10983	200	19	living	live	VERB
ajst-10983	200	20	crop	crop	NOUN
ajst-10983	200	21	roots[c].proceedings	roots[c].proceeding	NOUN
ajst-10983	200	22	of	of	ADP
ajst-10983	200	23	the	the	DET
ajst-10983	200	24	3rd	3rd	ADJ
ajst-10983	200	25	australian	australian	ADJ
ajst-10983	200	26	new	new	PROPN
ajst-10983	200	27	zealand	zealand	PROPN
ajst-10983	200	28	soils	soils	PROPN
ajst-10983	200	29	conference，university	conference，university	NOUN
ajst-10983	200	30	of	of	ADP
ajst-10983	200	31	sydney,2004,5	sydney,2004,5	NOUN
ajst-10983	200	32	-	-	X
ajst-10983	200	33	9	9	NUM
ajst-10983	200	34	.	.	PUNCT
ajst-10983	201	1	[	[	X
ajst-10983	201	2	12	12	NUM
ajst-10983	201	3	]	]	X
ajst-10983	201	4	watanabe	watanabe	PROPN
ajst-10983	201	5	k.	k.	PROPN
ajst-10983	201	6	nondestructive	nondestructive	PROPN
ajst-10983	201	7	root	root	NOUN
ajst-10983	201	8	-	-	PUNCT
ajst-10983	201	9	zone	zone	NOUN
ajst-10983	201	10	analysis	analysis	NOUN
ajst-10983	201	11	with	with	ADP
ajst-10983	201	12	x	x	NOUN
ajst-10983	201	13	-	-	NOUN
ajst-10983	201	14	ray	ray	NOUN
ajst-10983	201	15	ct	ct	NUM
ajst-10983	201	16	scanners[j	scanners[j	PROPN
ajst-10983	201	17	]	]	PUNCT
ajst-10983	201	18	.	.	PUNCT
ajst-10983	202	1	engineering	engineer	VERB
ajst-10983	202	2	for	for	ADP
ajst-10983	202	3	biological	biological	ADJ
ajst-10983	202	4	production	production	NOUN
ajst-10983	202	5	systems	system	NOUN
ajst-10983	202	6	,	,	PUNCT
ajst-10983	202	7	1993	1993	NUM
ajst-10983	202	8	.	.	PUNCT
ajst-10983	203	1	[	[	X
ajst-10983	203	2	13	13	NUM
ajst-10983	203	3	]	]	X
ajst-10983	203	4	han	han	PROPN
ajst-10983	203	5	l	l	PROPN
ajst-10983	203	6	,	,	PUNCT
ajst-10983	203	7	dutilleul	dutilleul	PROPN
ajst-10983	203	8	p	p	NOUN
ajst-10983	203	9	,	,	PUNCT
ajst-10983	203	10	prasher	prasher	NOUN
ajst-10983	203	11	s	s	PART
ajst-10983	203	12	o	o	NOUN
ajst-10983	203	13	,	,	PUNCT
ajst-10983	203	14	et	et	PROPN
ajst-10983	203	15	al	al	PROPN
ajst-10983	203	16	.	.	PROPN
ajst-10983	203	17	assessment	assessment	NOUN
ajst-10983	203	18	of	of	ADP
ajst-10983	203	19	density	density	NOUN
ajst-10983	203	20	effects	effect	NOUN
ajst-10983	203	21	of	of	ADP
ajst-10983	203	22	the	the	DET
ajst-10983	203	23	common	common	ADJ
ajst-10983	203	24	scab	scab	NOUN
ajst-10983	203	25	-	-	PUNCT
ajst-10983	203	26	inducing	induce	VERB
ajst-10983	203	27	pathogen	pathogen	NOUN
ajst-10983	203	28	on	on	ADP
ajst-10983	203	29	the	the	DET
ajst-10983	203	30	seed	seed	NOUN
ajst-10983	203	31	and	and	CCONJ
ajst-10983	203	32	peripheral	peripheral	ADJ
ajst-10983	203	33	organs	organ	NOUN
ajst-10983	203	34	of	of	ADP
ajst-10983	203	35	potato	potato	NOUN
ajst-10983	203	36	during	during	ADP
ajst-10983	203	37	growth	growth	NOUN
ajst-10983	203	38	using	use	VERB
ajst-10983	203	39	computed	compute	VERB
ajst-10983	203	40	tomography	tomography	NOUN
ajst-10983	203	41	scanning	scanning	NOUN
ajst-10983	203	42	data[j].transactions	data[j].transaction	NOUN
ajst-10983	203	43	of	of	ADP
ajst-10983	203	44	the	the	DET
ajst-10983	203	45	asabe	asabe	PROPN
ajst-10983	203	46	，	，	PROPN
ajst-10983	203	47	2009，52(1):305	2009，52(1):305	PROPN
ajst-10983	203	48	-	-	PUNCT
ajst-10983	203	49	311	311	NUM
ajst-10983	203	50	.	.	PUNCT
ajst-10983	204	1	[	[	X
ajst-10983	204	2	14	14	NUM
ajst-10983	204	3	]	]	X
ajst-10983	204	4	zhou	zhou	PROPN
ajst-10983	204	5	xuecheng	xuecheng	PROPN
ajst-10983	204	6	,	,	PUNCT
ajst-10983	204	7	luo	luo	PROPN
ajst-10983	204	8	xiwen	xiwen	PROPN
ajst-10983	204	9	,	,	PUNCT
ajst-10983	204	10	yan	yan	PROPN
ajst-10983	204	11	xiaolong	xiaolong	PROPN
ajst-10983	204	12	,	,	PUNCT
ajst-10983	204	13	et	et	PROPN
ajst-10983	204	14	al	al	PROPN
ajst-10983	204	15	.	.	PROPN
ajst-10983	204	16	fuzzy	fuzzy	ADJ
ajst-10983	204	17	threshold	threshold	NOUN
ajst-10983	204	18	segmentation	segmentation	NOUN
ajst-10983	204	19	of	of	ADP
ajst-10983	204	20	in	in	ADP
ajst-10983	204	21	situ	situ	ADJ
ajst-10983	204	22	root	root	NOUN
ajst-10983	204	23	ct	ct	NUM
ajst-10983	204	24	images	image	NOUN
ajst-10983	204	25	based	base	VERB
ajst-10983	204	26	on	on	ADP
ajst-10983	204	27	genetic	genetic	ADJ
ajst-10983	204	28	algorithm[j	algorithm[j	PROPN
ajst-10983	204	29	]	]	PUNCT
ajst-10983	204	30	.	.	PUNCT
ajst-10983	205	1	chinese	chinese	ADJ
ajst-10983	205	2	journal	journal	PROPN
ajst-10983	205	3	of	of	ADP
ajst-10983	205	4	image	image	NOUN
ajst-10983	205	5	and	and	CCONJ
ajst-10983	205	6	graphics	graphic	NOUN
ajst-10983	205	7	,	,	PUNCT
ajst-10983	205	8	2009	2009	NUM
ajst-10983	205	9	,	,	PUNCT
ajst-10983	205	10	14(4	14(4	NUM
ajst-10983	205	11	):	):	PUNCT
ajst-10983	205	12	681	681	NUM
ajst-10983	205	13	-	-	NOUN
ajst-10983	205	14	687	687	NUM
ajst-10983	205	15	.	.	PUNCT
ajst-10983	206	1	[	[	X
ajst-10983	206	2	15	15	NUM
ajst-10983	206	3	]	]	X
ajst-10983	206	4	zhao	zhao	PROPN
ajst-10983	206	5	x	x	PROPN
ajst-10983	206	6	,	,	PUNCT
ajst-10983	206	7	xing	xing	PROPN
ajst-10983	206	8	l	l	PROPN
ajst-10983	206	9	,	,	PUNCT
ajst-10983	206	10	shen	shen	PROPN
ajst-10983	206	11	s	s	PROPN
ajst-10983	206	12	,	,	PUNCT
ajst-10983	206	13	et	et	PROPN
ajst-10983	206	14	al	al	PROPN
ajst-10983	206	15	.	.	PUNCT
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ajst-10983	207	3	destructive	destructive	ADJ
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ajst-10983	207	8	maize	maize	NOUN
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ajst-10983	207	10	-	-	PUNCT
ajst-10983	207	11	stubble	stubble	ADJ
ajst-10983	207	12	in	in	ADP
ajst-10983	207	13	-	-	PUNCT
ajst-10983	207	14	situ	situ	NOUN
ajst-10983	207	15	via	via	ADP
ajst-10983	207	16	x	x	X
ajst-10983	207	17	-	-	NOUN
ajst-10983	207	18	ray	ray	NOUN
ajst-10983	207	19	computed	compute	VERB
ajst-10983	207	20	tomography[j	tomography[j	PROPN
ajst-10983	207	21	]	]	PUNCT
ajst-10983	207	22	.	.	PUNCT
ajst-10983	208	1	international	international	ADJ
ajst-10983	208	2	journal	journal	PROPN
ajst-10983	208	3	of	of	ADP
ajst-10983	208	4	agricultural	agricultural	ADJ
ajst-10983	208	5	and	and	CCONJ
ajst-10983	208	6	biological	biological	ADJ
ajst-10983	208	7	engineering	engineering	NOUN
ajst-10983	208	8	,	,	PUNCT
ajst-10983	208	9	2020	2020	NUM
ajst-10983	208	10	,	,	PUNCT
ajst-10983	208	11	13(3	13(3	NUM
ajst-10983	208	12	):	):	PUNCT
ajst-10983	208	13	174	174	NUM
ajst-10983	208	14	-	-	SYM
ajst-10983	208	15	179	179	NUM
ajst-10983	208	16	.	.	PUNCT
ajst-10983	209	1	[	[	X
ajst-10983	209	2	16	16	NUM
ajst-10983	209	3	]	]	X
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ajst-10983	209	6	.	.	PROPN
ajst-10983	209	7	research	research	NOUN
ajst-10983	209	8	on	on	ADP
ajst-10983	209	9	3d	3d	NUM
ajst-10983	209	10	segmentation	segmentation	NOUN
ajst-10983	209	11	algorithm	algorithm	NOUN
ajst-10983	209	12	of	of	ADP
ajst-10983	209	13	corn	corn	NOUN
ajst-10983	209	14	root	root	NOUN
ajst-10983	209	15	ct	ct	PROPN
ajst-10983	209	16	image[d	image[d	PROPN
ajst-10983	209	17	]	]	PUNCT
ajst-10983	209	18	.	.	PUNCT
ajst-10983	210	1	huazhong	huazhong	PROPN
ajst-10983	210	2	agricultural	agricultural	PROPN
ajst-10983	210	3	university	university	NOUN
ajst-10983	210	4	,	,	PUNCT
ajst-10983	210	5	2022	2022	NUM
ajst-10983	210	6	.	.	PUNCT
ajst-10983	211	1	doi	doi	NOUN
ajst-10983	211	2	:	:	PUNCT
ajst-10983	211	3	10.27158	10.27158	NUM
ajst-10983	211	4	/	/	SYM
ajst-10983	211	5	d.cnki.ghznu.2022.001341	d.cnki.ghznu.2022.001341	NOUN
ajst-10983	211	6	.	.	PUNCT
ajst-10983	212	1	[	[	X
ajst-10983	212	2	17	17	NUM
ajst-10983	212	3	]	]	X
ajst-10983	212	4	shen	shen	PROPN
ajst-10983	212	5	chen	chen	PROPN
ajst-10983	212	6	.	.	PUNCT
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ajst-10983	213	2	on	on	ADP
ajst-10983	213	3	in	in	ADP
ajst-10983	213	4	-	-	PUNCT
ajst-10983	213	5	situ	situ	ADJ
ajst-10983	213	6	root	root	NOUN
ajst-10983	213	7	segmentation	segmentation	NOUN
ajst-10983	213	8	technology	technology	NOUN
ajst-10983	213	9	of	of	ADP
ajst-10983	213	10	cotton	cotton	NOUN
ajst-10983	213	11	based	base	VERB
ajst-10983	213	12	on	on	ADP
ajst-10983	213	13	deep	deep	ADJ
ajst-10983	213	14	learning[d	learning[d	PROPN
ajst-10983	213	15	]	]	PUNCT
ajst-10983	213	16	.	.	PUNCT
ajst-10983	214	1	hebei	hebei	PROPN
ajst-10983	214	2	agricultural	agricultural	PROPN
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ajst-10983	214	4	,	,	PUNCT
ajst-10983	214	5	2021	2021	NUM
ajst-10983	214	6	.	.	PUNCT
ajst-10983	215	1	doi	doi	NOUN
ajst-10983	215	2	:	:	PUNCT
ajst-10983	215	3	10.27109	10.27109	NUM
ajst-10983	215	4	/	/	SYM
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ajst-10983	215	6	.	.	PUNCT
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ajst-10983	216	2	18	18	NUM
ajst-10983	216	3	]	]	PUNCT
ajst-10983	216	4	borisjuk	borisjuk	NOUN
ajst-10983	216	5	l	l	NOUN
ajst-10983	216	6	,	,	PUNCT
ajst-10983	216	7	rolletschek	rolletschek	PROPN
ajst-10983	216	8	h	h	NOUN
ajst-10983	216	9	,	,	PUNCT
ajst-10983	216	10	neuberger	neuberger	NOUN
ajst-10983	216	11	t.	t.	PROPN
ajst-10983	216	12	surveying	survey	VERB
ajst-10983	216	13	the	the	DET
ajst-10983	216	14	plant	plant	NOUN
ajst-10983	216	15	’s	’s	PART
ajst-10983	216	16	world	world	NOUN
ajst-10983	216	17	by	by	ADP
ajst-10983	216	18	magnetic	magnetic	ADJ
ajst-10983	216	19	resonance	resonance	NOUN
ajst-10983	216	20	imaging[j	imaging[j	PROPN
ajst-10983	216	21	]	]	PUNCT
ajst-10983	216	22	.	.	PUNCT
ajst-10983	217	1	the	the	DET
ajst-10983	217	2	plant	plant	NOUN
ajst-10983	217	3	journal,201270(1	journal,201270(1	PROPN
ajst-10983	217	4	):	):	PUNCT
ajst-10983	217	5	129	129	NUM
ajst-10983	217	6	-	-	SYM
ajst-10983	217	7	146	146	NUM
ajst-10983	217	8	.	.	PUNCT
ajst-10983	218	1	[	[	X
ajst-10983	218	2	19	19	NUM
ajst-10983	218	3	]	]	X
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ajst-10983	218	5	y	y	PROPN
ajst-10983	218	6	,	,	PUNCT
ajst-10983	218	7	wandel	wandel	PROPN
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ajst-10983	218	9	,	,	PUNCT
ajst-10983	218	10	landl	landl	VERB
ajst-10983	218	11	m	m	PRON
ajst-10983	218	12	,	,	PUNCT
ajst-10983	218	13	et	et	PROPN
ajst-10983	218	14	al	al	PROPN
ajst-10983	218	15	.	.	PROPN
ajst-10983	219	1	3d	3d	NUM
ajst-10983	219	2	u	u	NOUN
ajst-10983	219	3	-	-	NOUN
ajst-10983	219	4	net	net	ADJ
ajst-10983	219	5	for	for	ADP
ajst-10983	219	6	segmentation	segmentation	NOUN
ajst-10983	219	7	of	of	ADP
ajst-10983	219	8	plant	plant	NOUN
ajst-10983	219	9	root	root	NOUN
ajst-10983	219	10	mri	mri	NOUN
ajst-10983	219	11	images	image	NOUN
ajst-10983	219	12	in	in	ADP
ajst-10983	219	13	super	super	NOUN
ajst-10983	219	14	-	-	ADJ
ajst-10983	219	15	resolution[j	resolution[j	NUM
ajst-10983	219	16	]	]	PUNCT
ajst-10983	219	17	.	.	PUNCT
ajst-10983	220	1	arxiv	arxiv	PROPN
ajst-10983	220	2	preprint	preprint	VERB
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ajst-10983	220	4	,	,	PUNCT
ajst-10983	220	5	2020	2020	NUM
ajst-10983	220	6	.	.	PUNCT
ajst-10983	221	1	[	[	X
ajst-10983	221	2	20	20	NUM
ajst-10983	221	3	]	]	SYM
ajst-10983	221	4	du	du	NOUN
ajst-10983	221	5	guangyuan.nmr	guangyuan.nmr	PROPN
ajst-10983	221	6	study	study	NOUN
ajst-10983	221	7	on	on	ADP
ajst-10983	221	8	the	the	DET
ajst-10983	221	9	dynamic	dynamic	ADJ
ajst-10983	221	10	distribution	distribution	NOUN
ajst-10983	221	11	of	of	ADP
ajst-10983	221	12	water	water	NOUN
ajst-10983	221	13	and	and	CCONJ
ajst-10983	221	14	sugar	sugar	NOUN
ajst-10983	221	15	in	in	ADP
ajst-10983	221	16	wheat	wheat	NOUN
ajst-10983	221	17	during	during	ADP
ajst-10983	221	18	grain	grain	NOUN
ajst-10983	221	19	filling[d].northwest	filling[d].northw	ADJ
ajst-10983	221	20	a&f	a&f	PROPN
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ajst-10983	221	22	/	/	SYM
ajst-10983	221	23	d.cnki.gxbnu.2013.000010	d.cnki.gxbnu.2013.000010	NOUN
ajst-10983	221	24	.	.	PUNCT
ajst-10983	222	1	[	[	X
ajst-10983	222	2	21	21	NUM
ajst-10983	222	3	]	]	X
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ajst-10983	222	5	c	c	NOUN
ajst-10983	222	6	,	,	PUNCT
ajst-10983	222	7	sikora	sikora	PROPN
ajst-10983	222	8	r	r	PROPN
ajst-10983	222	9	a	a	PRON
ajst-10983	222	10	,	,	PUNCT
ajst-10983	222	11	oerke	oerke	NOUN
ajst-10983	222	12	e	e	NOUN
ajst-10983	222	13	,	,	PUNCT
ajst-10983	222	14	et	et	PROPN
ajst-10983	222	15	al	al	PROPN
ajst-10983	222	16	.	.	PUNCT
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ajst-10983	222	18	magnetic	magnetic	ADJ
ajst-10983	222	19	resonance	resonance	NOUN
ajst-10983	222	20	:	:	PUNCT
ajst-10983	222	21	a	a	DET
ajst-10983	222	22	tool	tool	NOUN
ajst-10983	222	23	for	for	ADP
ajst-10983	222	24	imaging	imaging	NOUN
ajst-10983	222	25	belowground	belowground	ADJ
ajst-10983	222	26	damage	damage	NOUN
ajst-10983	222	27	caused	cause	VERB
ajst-10983	222	28	by	by	ADP
ajst-10983	222	29	heterodera	heterodera	NOUN
ajst-10983	222	30	schachtii	schachtii	NOUN
ajst-10983	222	31	and	and	CCONJ
ajst-10983	222	32	rhizoctonia	rhizoctonia	PROPN
ajst-10983	222	33	solani	solani	PROPN
ajst-10983	222	34	on	on	ADP
ajst-10983	222	35	sugar	sugar	NOUN
ajst-10983	222	36	beet[j	beet[j	PROPN
ajst-10983	222	37	]	]	PUNCT
ajst-10983	222	38	.	.	PUNCT
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ajst-10983	223	2	of	of	ADP
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ajst-10983	223	4	botany,201163(1):319	botany,201163(1):319	PROPN
ajst-10983	223	5	-	-	PUNCT
ajst-10983	223	6	327	327	NUM
ajst-10983	223	7	.	.	PUNCT
ajst-10983	224	1	[	[	X
ajst-10983	224	2	22	22	NUM
ajst-10983	224	3	]	]	X
ajst-10983	224	4	li	li	PROPN
ajst-10983	224	5	y	y	PROPN
ajst-10983	224	6	,	,	PUNCT
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ajst-10983	224	8	y	y	PROPN
ajst-10983	224	9	,	,	PUNCT
ajst-10983	224	10	wang	wang	PROPN
ajst-10983	224	11	m	m	PROPN
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ajst-10983	224	13	et	et	PROPN
ajst-10983	224	14	al	al	PROPN
ajst-10983	224	15	.	.	PUNCT
ajst-10983	225	1	an	an	DET
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ajst-10983	225	3	u	u	NOUN
ajst-10983	225	4	-	-	ADJ
ajst-10983	225	5	net	net	NOUN
ajst-10983	225	6	-	-	PUNCT
ajst-10983	225	7	based	base	VERB
ajst-10983	225	8	in	in	ADP
ajst-10983	225	9	situ	situ	ADJ
ajst-10983	225	10	root	root	NOUN
ajst-10983	225	11	system	system	NOUN
ajst-10983	225	12	phenotype	phenotype	NOUN
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ajst-10983	225	14	method	method	NOUN
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ajst-10983	225	16	plants[j	plants[j	NOUN
ajst-10983	225	17	]	]	PUNCT
ajst-10983	225	18	.	.	PUNCT
ajst-10983	226	1	frontiers	frontier	NOUN
ajst-10983	226	2	in	in	ADP
ajst-10983	226	3	plant	plant	NOUN
ajst-10983	226	4	science	science	NOUN
ajst-10983	226	5	,	,	PUNCT
ajst-10983	226	6	2023	2023	NUM
ajst-10983	226	7	,	,	PUNCT
ajst-10983	226	8	14	14	NUM
ajst-10983	226	9	.	.	PUNCT
ajst-10983	227	1	[	[	X
ajst-10983	227	2	23	23	NUM
ajst-10983	227	3	]	]	X
ajst-10983	227	4	nahar	nahar	PROPN
ajst-10983	227	5	k	k	PROPN
ajst-10983	227	6	,	,	PUNCT
ajst-10983	227	7	pan	pan	PROPN
ajst-10983	227	8	w	w	PROPN
ajst-10983	227	9	l.	l.	PROPN
ajst-10983	227	10	high	high	ADJ
ajst-10983	227	11	resolution	resolution	NOUN
ajst-10983	227	12	in	in	ADP
ajst-10983	227	13	situ	situ	NOUN
ajst-10983	227	14	rhizosphere	rhizosphere	ADJ
ajst-10983	227	15	imaging	imaging	NOUN
ajst-10983	227	16	of	of	ADP
ajst-10983	227	17	root	root	NOUN
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ajst-10983	227	19	dynamics	dynamic	NOUN
ajst-10983	227	20	in	in	ADP
ajst-10983	227	21	oilseed	oilseed	NOUN
ajst-10983	227	22	castor	castor	NOUN
ajst-10983	227	23	plant	plant	NOUN
ajst-10983	227	24	(	(	PUNCT
ajst-10983	227	25	ricinus	ricinus	PROPN
ajst-10983	227	26	communis	communis	PROPN
ajst-10983	227	27	l.	l.	PROPN
ajst-10983	227	28	)	)	PUNCT
ajst-10983	227	29	using	use	VERB
ajst-10983	227	30	digital	digital	ADJ
ajst-10983	227	31	scanners[jl	scanners[jl	PROPN
ajst-10983	227	32	.	.	PUNCT
ajst-10983	228	1	modeling	model	VERB
ajst-10983	228	2	earth	earth	NOUN
ajst-10983	228	3	systems	system	NOUN
ajst-10983	228	4	and	and	CCONJ
ajst-10983	228	5	environment,2019,5(3):781	environment,2019,5(3):781	PROPN
ajst-10983	228	6	-	-	PUNCT
ajst-10983	228	7	792	792	NUM
ajst-10983	228	8	.	.	PUNCT
ajst-10983	229	1	[	[	X
ajst-10983	229	2	24	24	NUM
ajst-10983	229	3	]	]	PUNCT
ajst-10983	229	4	mohamed	mohame	VERB
ajst-10983	229	5	a	a	PROPN
ajst-10983	229	6	,	,	PUNCT
ajst-10983	229	7	monnier	monni	ADJ
ajst-10983	229	8	y	y	PROPN
ajst-10983	229	9	,	,	PUNCT
ajst-10983	229	10	mao	mao	PROPN
ajst-10983	230	1	z	z	NOUN
ajst-10983	230	2	,	,	PUNCT
ajst-10983	230	3	et	et	PROPN
ajst-10983	230	4	al	al	PROPN
ajst-10983	230	5	.	.	PUNCT
ajst-10983	231	1	an	an	DET
ajst-10983	231	2	evaluation	evaluation	NOUN
ajst-10983	231	3	of	of	ADP
ajst-10983	231	4	inexpensive	inexpensive	ADJ
ajst-10983	231	5	methods	method	NOUN
ajst-10983	231	6	for	for	ADP
ajst-10983	231	7	root	root	NOUN
ajst-10983	231	8	image	image	NOUN
ajst-10983	231	9	acquisition	acquisition	NOUN
ajst-10983	231	10	when	when	SCONJ
ajst-10983	231	11	using	use	VERB
ajst-10983	231	12	rhizotrons[j	rhizotrons[j	PROPN
ajst-10983	231	13	]	]	PUNCT
ajst-10983	231	14	.	.	PUNCT
ajst-10983	232	1	plant	plant	NOUN
ajst-10983	232	2	methods	method	NOUN
ajst-10983	232	3	,	,	PUNCT
ajst-10983	232	4	2017	2017	NUM
ajst-10983	232	5	,	,	PUNCT
ajst-10983	232	6	13(1	13(1	NUM
ajst-10983	232	7	):	):	PUNCT
ajst-10983	232	8	1	1	NUM
ajst-10983	232	9	-	-	SYM
ajst-10983	232	10	13	13	NUM
ajst-10983	232	11	.	.	PUNCT
ajst-10983	233	1	[	[	X
ajst-10983	233	2	25	25	NUM
ajst-10983	233	3	]	]	PUNCT
ajst-10983	233	4	castleman	castleman	NOUN
ajst-10983	233	5	k	k	PROPN
ajst-10983	233	6	r.	r.	PROPN
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ajst-10983	233	8	image	image	NOUN
ajst-10983	233	9	processing[m	processing[m	NOUN
ajst-10983	233	10	]	]	PUNCT
ajst-10983	233	11	.	.	PUNCT
ajst-10983	234	1	prentice	prentice	PROPN
ajst-10983	234	2	hall	hall	PROPN
ajst-10983	234	3	press	press	PROPN
ajst-10983	234	4	,	,	PUNCT
ajst-10983	234	5	1996	1996	NUM
ajst-10983	234	6	.	.	PUNCT
ajst-10983	235	1	[	[	X
ajst-10983	235	2	26	26	NUM
ajst-10983	235	3	]	]	X
ajst-10983	235	4	lecun	lecun	PROPN
ajst-10983	235	5	y	y	PROPN
ajst-10983	235	6	,	,	PUNCT
ajst-10983	235	7	bengio	bengio	PROPN
ajst-10983	235	8	y	y	PROPN
ajst-10983	235	9	,	,	PUNCT
ajst-10983	235	10	hinton	hinton	PROPN
ajst-10983	235	11	g.	g.	PROPN
ajst-10983	235	12	deep	deep	PROPN
ajst-10983	235	13	learning[j	learning[j	PROPN
ajst-10983	235	14	]	]	PUNCT
ajst-10983	235	15	.	.	PUNCT
ajst-10983	236	1	nature	nature	NOUN
ajst-10983	236	2	,	,	PUNCT
ajst-10983	236	3	2015	2015	NUM
ajst-10983	236	4	,	,	PUNCT
ajst-10983	236	5	521(7553	521(7553	NUM
ajst-10983	236	6	):	):	PUNCT
ajst-10983	236	7	436	436	NUM
ajst-10983	236	8	-	-	SYM
ajst-10983	236	9	444	444	NUM
ajst-10983	236	10	.	.	PUNCT
ajst-10983	237	1	[	[	X
ajst-10983	237	2	27	27	NUM
ajst-10983	237	3	]	]	X
ajst-10983	237	4	liang	liang	PROPN
ajst-10983	237	5	lixiu	lixiu	PROPN
ajst-10983	237	6	,	,	PUNCT
ajst-10983	237	7	ye	ye	PROPN
ajst-10983	237	8	junli	junli	NOUN
ajst-10983	237	9	,	,	PUNCT
ajst-10983	237	10	wu	wu	PROPN
ajst-10983	237	11	dan	dan	PROPN
ajst-10983	237	12	,	,	PUNCT
ajst-10983	237	13	et	et	PROPN
ajst-10983	237	14	al	al	PROPN
ajst-10983	237	15	.	.	PROPN
ajst-10983	237	16	research	research	NOUN
ajst-10983	237	17	on	on	ADP
ajst-10983	237	18	image	image	NOUN
ajst-10983	237	19	segmentation	segmentation	NOUN
ajst-10983	237	20	algorithm	algorithm	NOUN
ajst-10983	237	21	of	of	ADP
ajst-10983	237	22	surface	surface	NOUN
ajst-10983	237	23	root	root	NOUN
ajst-10983	237	24	system	system	NOUN
ajst-10983	237	25	of	of	ADP
ajst-10983	237	26	rice	rice	NOUN
ajst-10983	238	1	[	[	X
ajst-10983	238	2	j	j	X
ajst-10983	238	3	]	]	X
ajst-10983	238	4	.	.	PUNCT
ajst-10983	239	1	china	china	PROPN
ajst-10983	239	2	agricultural	agricultural	PROPN
ajst-10983	239	3	science	science	PROPN
ajst-10983	239	4	and	and	CCONJ
ajst-10983	239	5	technology	technology	PROPN
ajst-10983	239	6	herald	herald	PROPN
ajst-10983	239	7	,	,	PUNCT
ajst-10983	239	8	2019	2019	NUM
ajst-10983	239	9	,	,	PUNCT
ajst-10983	239	10	21(1	21(1	NUM
ajst-10983	239	11	):	):	PUNCT
ajst-10983	239	12	70	70	NUM
ajst-10983	239	13	-	-	SYM
ajst-10983	239	14	79	79	NUM
ajst-10983	239	15	.	.	PUNCT
ajst-10983	240	1	[	[	X
ajst-10983	240	2	28	28	NUM
ajst-10983	240	3	]	]	X
ajst-10983	240	4	shen	shen	NOUN
ajst-10983	240	5	c	c	X
ajst-10983	240	6	,	,	PUNCT
ajst-10983	240	7	liu	liu	PROPN
ajst-10983	240	8	l	l	PROPN
ajst-10983	240	9	,	,	PUNCT
ajst-10983	240	10	zhu	zhu	PROPN
ajst-10983	240	11	l	l	NOUN
ajst-10983	240	12	,	,	PUNCT
ajst-10983	240	13	et	et	PROPN
ajst-10983	240	14	al	al	PROPN
ajst-10983	240	15	.	.	PROPN
ajst-10983	240	16	high	high	ADJ
ajst-10983	240	17	-	-	PUNCT
ajst-10983	240	18	throughput	throughput	NOUN
ajst-10983	240	19	in	in	ADP
ajst-10983	240	20	situ	situ	ADJ
ajst-10983	240	21	root	root	NOUN
ajst-10983	240	22	image	image	NOUN
ajst-10983	240	23	segmentation	segmentation	NOUN
ajst-10983	240	24	based	base	VERB
ajst-10983	240	25	on	on	ADP
ajst-10983	240	26	the	the	DET
ajst-10983	240	27	improved	improved	ADJ
ajst-10983	240	28	deeplabv3	deeplabv3	NOUN
ajst-10983	240	29	+	+	CCONJ
ajst-10983	240	30	method[j	method[j	NOUN
ajst-10983	240	31	]	]	PUNCT
ajst-10983	240	32	.	.	PUNCT
ajst-10983	241	1	frontiers	frontier	NOUN
ajst-10983	241	2	in	in	ADP
ajst-10983	241	3	plant	plant	NOUN
ajst-10983	241	4	science	science	NOUN
ajst-10983	241	5	,	,	PUNCT
ajst-10983	241	6	2020	2020	NUM
ajst-10983	241	7	,	,	PUNCT
ajst-10983	241	8	11	11	NUM
ajst-10983	241	9	:	:	SYM
ajst-10983	241	10	576791	576791	NUM
ajst-10983	241	11	.	.	PUNCT
ajst-10983	242	1	[	[	X
ajst-10983	242	2	29	29	NUM
ajst-10983	242	3	]	]	X
ajst-10983	242	4	borianne	borianne	NOUN
ajst-10983	242	5	p	p	NOUN
ajst-10983	242	6	,	,	PUNCT
ajst-10983	242	7	subsol	subsol	NOUN
ajst-10983	242	8	g	g	NOUN
ajst-10983	242	9	,	,	PUNCT
ajst-10983	242	10	fallavier	fallavier	NOUN
ajst-10983	242	11	f	f	NOUN
ajst-10983	242	12	,	,	PUNCT
ajst-10983	242	13	et	et	PROPN
ajst-10983	242	14	al	al	PROPN
ajst-10983	242	15	.	.	PUNCT
ajst-10983	242	16	gt	gt	PROPN
ajst-10983	242	17	-	-	PUNCT
ajst-10983	242	18	roots	root	NOUN
ajst-10983	242	19	an	an	DET
ajst-10983	242	20	integrated	integrated	ADJ
ajst-10983	242	21	software	software	NOUN
ajst-10983	242	22	for	for	ADP
ajst-10983	242	23	automated	automate	VERB
ajst-10983	242	24	root	root	NOUN
ajst-10983	242	25	system	system	NOUN
ajst-10983	242	26	measurement	measurement	NOUN
ajst-10983	242	27	from	from	ADP
ajst-10983	242	28	high	high	ADJ
ajst-10983	242	29	-	-	PUNCT
ajst-10983	242	30	throughput	throughput	NOUN
ajst-10983	242	31	phenotyping	phenotype	VERB
ajst-10983	242	32	platform	platform	NOUN
ajst-10983	242	33	images[j	images[j	PROPN
ajst-10983	242	34	]	]	PUNCT
ajst-10983	242	35	.	.	PUNCT
ajst-10983	243	1	computers	computer	NOUN
ajst-10983	243	2	and	and	CCONJ
ajst-10983	243	3	electronics	electronic	NOUN
ajst-10983	243	4	in	in	ADP
ajst-10983	243	5	ariculture2018150:328	ariculture2018150:328	NOUN
ajst-10983	243	6	-	-	PUNCT
ajst-10983	243	7	342	342	NUM
ajst-10983	243	8	.	.	PUNCT
ajst-10983	244	1	[	[	X
ajst-10983	244	2	30	30	NUM
ajst-10983	244	3	]	]	X
ajst-10983	244	4	haralick	haralick	NOUN
ajst-10983	244	5	r	r	PROPN
ajst-10983	244	6	m	m	PROPN
ajst-10983	244	7	,	,	PUNCT
ajst-10983	244	8	sternberg	sternberg	PROPN
ajst-10983	244	9	s	s	PROPN
ajst-10983	244	10	r	r	PROPN
ajst-10983	244	11	,	,	PUNCT
ajst-10983	244	12	zhuang	zhuang	PROPN
ajst-10983	244	13	x.	x.	PROPN
ajst-10983	244	14	image	image	NOUN
ajst-10983	244	15	analysis	analysis	NOUN
ajst-10983	244	16	using	use	VERB
ajst-10983	244	17	mathematical	mathematical	ADJ
ajst-10983	244	18	morphology[j	morphology[j	PROPN
ajst-10983	244	19	]	]	PUNCT
ajst-10983	244	20	.	.	PUNCT
ajst-10983	245	1	ieee	ieee	NOUN
ajst-10983	245	2	transactions	transaction	NOUN
ajst-10983	245	3	on	on	ADP
ajst-10983	245	4	pattern	pattern	NOUN
ajst-10983	245	5	analysis	analysis	NOUN
ajst-10983	245	6	and	and	CCONJ
ajst-10983	245	7	machine	machine	NOUN
ajst-10983	245	8	intelligence	intelligence	NOUN
ajst-10983	245	9	,	,	PUNCT
ajst-10983	245	10	1987	1987	NUM
ajst-10983	245	11	(	(	PUNCT
ajst-10983	245	12	4	4	NUM
ajst-10983	245	13	):	):	PUNCT
ajst-10983	245	14	532	532	NUM
ajst-10983	245	15	-	-	SYM
ajst-10983	245	16	550	550	NUM
ajst-10983	245	17	.	.	PUNCT
ajst-10983	246	1	[	[	X
ajst-10983	246	2	31	31	NUM
ajst-10983	246	3	]	]	PUNCT
ajst-10983	246	4	rosenfeld	rosenfeld	PROPN
ajst-10983	246	5	a	a	PRON
ajst-10983	246	6	,	,	PUNCT
ajst-10983	246	7	pfaltz	pfaltz	NOUN
ajst-10983	246	8	j	j	PROPN
ajst-10983	246	9	l.	l.	PROPN
ajst-10983	246	10	sequential	sequential	ADJ
ajst-10983	246	11	operations	operation	NOUN
ajst-10983	246	12	in	in	ADP
ajst-10983	246	13	digital	digital	ADJ
ajst-10983	246	14	picture	picture	NOUN
ajst-10983	246	15	processing[j	processing[j	NOUN
ajst-10983	246	16	]	]	PUNCT
ajst-10983	246	17	.	.	PUNCT
ajst-10983	247	1	journal	journal	PROPN
ajst-10983	247	2	of	of	ADP
ajst-10983	247	3	the	the	DET
ajst-10983	247	4	acm	acm	PROPN
ajst-10983	247	5	(	(	PUNCT
ajst-10983	247	6	jacm	jacm	PROPN
ajst-10983	247	7	)	)	PUNCT
ajst-10983	247	8	,	,	PUNCT
ajst-10983	247	9	1966	1966	NUM
ajst-10983	247	10	,	,	PUNCT
ajst-10983	247	11	13(4	13(4	NUM
ajst-10983	247	12	):	):	PUNCT
ajst-10983	247	13	471494	471494	NUM
ajst-10983	247	14	.	.	PUNCT
ajst-10983	248	1	[	[	X
ajst-10983	248	2	32	32	NUM
ajst-10983	248	3	]	]	PUNCT
ajst-10983	248	4	felzenszwalb	felzenszwalb	NOUN
ajst-10983	248	5	p	p	PROPN
ajst-10983	248	6	f	f	NOUN
ajst-10983	248	7	,	,	PUNCT
ajst-10983	248	8	huttenlocher	huttenlocher	ADJ
ajst-10983	248	9	d	d	PROPN
ajst-10983	248	10	p.	p.	NOUN
ajst-10983	248	11	efficient	efficient	ADJ
ajst-10983	248	12	graph	graph	NOUN
ajst-10983	248	13	-	-	PUNCT
ajst-10983	248	14	based	base	VERB
ajst-10983	248	15	image	image	NOUN
ajst-10983	248	16	segmentation[j	segmentation[j	PROPN
ajst-10983	248	17	]	]	PUNCT
ajst-10983	248	18	.	.	PUNCT
ajst-10983	249	1	international	international	ADJ
ajst-10983	249	2	journal	journal	PROPN
ajst-10983	249	3	of	of	ADP
ajst-10983	249	4	computer	computer	NOUN
ajst-10983	249	5	vision	vision	NOUN
ajst-10983	249	6	,	,	PUNCT
ajst-10983	249	7	2004	2004	NUM
ajst-10983	249	8	,	,	PUNCT
ajst-10983	249	9	59(2	59(2	NUM
ajst-10983	249	10	):	):	PUNCT
ajst-10983	249	11	167–181	167–181	NUM
ajst-10983	249	12	.	.	PUNCT
ajst-10983	250	1	[	[	X
ajst-10983	250	2	33	33	NUM
ajst-10983	250	3	]	]	X
ajst-10983	250	4	otsu	otsu	PROPN
ajst-10983	250	5	n.	n.	NOUN
ajst-10983	250	6	a	a	DET
ajst-10983	250	7	threshold	threshold	NOUN
ajst-10983	250	8	selection	selection	NOUN
ajst-10983	250	9	method	method	NOUN
ajst-10983	250	10	from	from	ADP
ajst-10983	250	11	gray	gray	ADJ
ajst-10983	250	12	-	-	PUNCT
ajst-10983	250	13	level	level	NOUN
ajst-10983	250	14	histograms[j	histograms[j	NOUN
ajst-10983	250	15	]	]	PUNCT
ajst-10983	250	16	.	.	PUNCT
ajst-10983	251	1	ieee	ieee	NOUN
ajst-10983	251	2	transactions	transaction	NOUN
ajst-10983	251	3	on	on	ADP
ajst-10983	251	4	systems	system	NOUN
ajst-10983	251	5	,	,	PUNCT
ajst-10983	251	6	man	man	NOUN
ajst-10983	251	7	,	,	PUNCT
ajst-10983	251	8	and	and	CCONJ
ajst-10983	251	9	cybernetics	cybernetic	NOUN
ajst-10983	251	10	,	,	PUNCT
ajst-10983	251	11	1979	1979	NUM
ajst-10983	251	12	,	,	PUNCT
ajst-10983	251	13	9(1	9(1	NUM
ajst-10983	251	14	):	):	PUNCT
ajst-10983	251	15	62	62	NUM
ajst-10983	251	16	-	-	SYM
ajst-10983	251	17	66	66	NUM
ajst-10983	251	18	.	.	PUNCT
ajst-10983	252	1	[	[	X
ajst-10983	252	2	34	34	NUM
ajst-10983	252	3	]	]	PUNCT
ajst-10983	252	4	niblack	niblack	NOUN
ajst-10983	252	5	w.	w.	PROPN
ajst-10983	252	6	an	an	DET
ajst-10983	252	7	introduction	introduction	NOUN
ajst-10983	252	8	to	to	ADP
ajst-10983	252	9	digital	digital	ADJ
ajst-10983	252	10	image	image	NOUN
ajst-10983	252	11	processing[m	processing[m	NOUN
ajst-10983	252	12	]	]	PUNCT
ajst-10983	252	13	.	.	PUNCT
ajst-10983	253	1	strandberg	strandberg	PROPN
ajst-10983	253	2	publishing	publishing	PROPN
ajst-10983	253	3	company	company	NOUN
ajst-10983	253	4	,	,	PUNCT
ajst-10983	253	5	1985	1985	NUM
ajst-10983	253	6	.	.	PUNCT
ajst-10983	254	1	[	[	X
ajst-10983	254	2	35	35	NUM
ajst-10983	254	3	]	]	X
ajst-10983	254	4	mallat	mallat	PROPN
ajst-10983	254	5	s.	s.	PROPN
ajst-10983	254	6	a	a	DET
ajst-10983	254	7	wavelet	wavelet	NOUN
ajst-10983	254	8	tour	tour	NOUN
ajst-10983	254	9	of	of	ADP
ajst-10983	254	10	signal	signal	ADJ
ajst-10983	254	11	processing[m	processing[m	NOUN
ajst-10983	254	12	]	]	PUNCT
ajst-10983	254	13	.	.	PUNCT
ajst-10983	255	1	elsevier	elsevier	NOUN
ajst-10983	255	2	,	,	PUNCT
ajst-10983	255	3	1999	1999	NUM
ajst-10983	255	4	.	.	PUNCT
ajst-10983	256	1	[	[	X
ajst-10983	256	2	36	36	NUM
ajst-10983	256	3	]	]	X
ajst-10983	256	4	sain	sain	PROPN
ajst-10983	256	5	s	s	PROPN
ajst-10983	256	6	r.	r.	NOUN
ajst-10983	256	7	the	the	DET
ajst-10983	256	8	nature	nature	NOUN
ajst-10983	256	9	of	of	ADP
ajst-10983	256	10	statistical	statistical	ADJ
ajst-10983	256	11	learning	learning	NOUN
ajst-10983	256	12	theory[j	theory[j	NOUN
ajst-10983	256	13	]	]	PUNCT
ajst-10983	256	14	.	.	PUNCT
ajst-10983	257	1	1996	1996	NUM
ajst-10983	257	2	.	.	PUNCT
ajst-10983	258	1	[	[	X
ajst-10983	258	2	37	37	NUM
ajst-10983	258	3	]	]	X
ajst-10983	258	4	quinlan	quinlan	PROPN
ajst-10983	258	5	j	j	PROPN
ajst-10983	258	6	r.	r.	PROPN
ajst-10983	258	7	c4	c4	PROPN
ajst-10983	258	8	.	.	PUNCT
ajst-10983	259	1	5	5	NUM
ajst-10983	259	2	:	:	PUNCT
ajst-10983	259	3	programs	program	NOUN
ajst-10983	259	4	for	for	ADP
ajst-10983	259	5	machine	machine	NOUN
ajst-10983	259	6	learning[m	learning[m	PROPN
ajst-10983	259	7	]	]	PUNCT
ajst-10983	259	8	.	.	PUNCT
ajst-10983	260	1	elsevier	elsevier	NOUN
ajst-10983	260	2	,	,	PUNCT
ajst-10983	260	3	2014	2014	NUM
ajst-10983	260	4	.	.	PUNCT
ajst-10983	261	1	[	[	X
ajst-10983	261	2	38	38	NUM
ajst-10983	261	3	]	]	PUNCT
ajst-10983	261	4	jain	jain	NOUN
ajst-10983	261	5	a	a	DET
ajst-10983	261	6	k	k	PROPN
ajst-10983	261	7	,	,	PUNCT
ajst-10983	261	8	murty	murty	PROPN
ajst-10983	261	9	m	m	PROPN
ajst-10983	261	10	n	n	NOUN
ajst-10983	261	11	,	,	PUNCT
ajst-10983	261	12	flynn	flynn	PROPN
ajst-10983	261	13	p	p	PROPN
ajst-10983	261	14	j.	j.	PROPN
ajst-10983	261	15	data	data	PROPN
ajst-10983	261	16	clustering	cluster	VERB
ajst-10983	261	17	:	:	PUNCT
ajst-10983	261	18	a	a	DET
ajst-10983	261	19	review[j	review[j	PROPN
ajst-10983	261	20	]	]	PUNCT
ajst-10983	261	21	.	.	PUNCT
ajst-10983	262	1	acm	acm	PROPN
ajst-10983	262	2	computing	computing	NOUN
ajst-10983	262	3	surveys	survey	NOUN
ajst-10983	262	4	(	(	PUNCT
ajst-10983	262	5	csur	csur	NOUN
ajst-10983	262	6	)	)	PUNCT
ajst-10983	262	7	,	,	PUNCT
ajst-10983	262	8	1999	1999	NUM
ajst-10983	262	9	,	,	PUNCT
ajst-10983	262	10	31(3	31(3	NUM
ajst-10983	262	11	):	):	PUNCT
ajst-10983	262	12	264	264	NUM
ajst-10983	262	13	-	-	SYM
ajst-10983	262	14	323	323	NUM
ajst-10983	262	15	.	.	PUNCT
ajst-10983	262	16	30	30	NUM
ajst-10983	263	1	[	[	SYM
ajst-10983	263	2	39	39	NUM
ajst-10983	263	3	]	]	PUNCT
ajst-10983	263	4	lecun	lecun	PROPN
ajst-10983	263	5	y	y	PROPN
ajst-10983	263	6	,	,	PUNCT
ajst-10983	263	7	bottou	bottou	PROPN
ajst-10983	263	8	l	l	PROPN
ajst-10983	263	9	,	,	PUNCT
ajst-10983	263	10	bengio	bengio	PROPN
ajst-10983	263	11	y	y	PROPN
ajst-10983	263	12	,	,	PUNCT
ajst-10983	263	13	et	et	PROPN
ajst-10983	263	14	al	al	PROPN
ajst-10983	263	15	.	.	PUNCT
ajst-10983	263	16	gradient	gradient	NOUN
ajst-10983	263	17	-	-	PUNCT
ajst-10983	263	18	based	base	VERB
ajst-10983	263	19	learning	learning	NOUN
ajst-10983	263	20	applied	apply	VERB
ajst-10983	263	21	to	to	ADP
ajst-10983	263	22	document	document	NOUN
ajst-10983	263	23	recognition[j	recognition[j	NOUN
ajst-10983	263	24	]	]	PUNCT
ajst-10983	263	25	.	.	PUNCT
ajst-10983	264	1	proceedings	proceeding	NOUN
ajst-10983	264	2	of	of	ADP
ajst-10983	264	3	the	the	DET
ajst-10983	264	4	ieee	ieee	NOUN
ajst-10983	264	5	,	,	PUNCT
ajst-10983	264	6	1998	1998	NUM
ajst-10983	264	7	,	,	PUNCT
ajst-10983	264	8	86(11	86(11	NUM
ajst-10983	264	9	):	):	PUNCT
ajst-10983	264	10	2278	2278	NUM
ajst-10983	264	11	-	-	SYM
ajst-10983	264	12	2324	2324	NUM
ajst-10983	264	13	.	.	PUNCT
ajst-10983	265	1	[	[	X
ajst-10983	265	2	40	40	NUM
ajst-10983	265	3	]	]	X
ajst-10983	265	4	long	long	PROPN
ajst-10983	265	5	j	j	PROPN
ajst-10983	265	6	,	,	PUNCT
ajst-10983	265	7	shelhamer	shelhamer	NOUN
ajst-10983	265	8	e	e	NOUN
ajst-10983	265	9	,	,	PUNCT
ajst-10983	265	10	darrell	darrell	PROPN
ajst-10983	265	11	t.	t.	PROPN
ajst-10983	265	12	fully	fully	ADV
ajst-10983	265	13	convolutional	convolutional	ADJ
ajst-10983	265	14	networks	network	NOUN
ajst-10983	265	15	for	for	ADP
ajst-10983	265	16	semantic	semantic	ADJ
ajst-10983	265	17	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-10983	265	18	of	of	ADP
ajst-10983	265	19	the	the	DET
ajst-10983	265	20	ieee	ieee	NOUN
ajst-10983	265	21	conference	conference	NOUN
ajst-10983	265	22	on	on	ADP
ajst-10983	265	23	computer	computer	NOUN
ajst-10983	265	24	vision	vision	NOUN
ajst-10983	265	25	and	and	CCONJ
ajst-10983	265	26	pattern	pattern	NOUN
ajst-10983	265	27	recognition	recognition	NOUN
ajst-10983	265	28	.	.	PUNCT
ajst-10983	266	1	2015	2015	NUM
ajst-10983	266	2	:	:	PUNCT
ajst-10983	266	3	3431	3431	NUM
ajst-10983	266	4	-	-	SYM
ajst-10983	266	5	3440	3440	NUM
ajst-10983	266	6	.	.	PUNCT
ajst-10983	267	1	[	[	X
ajst-10983	267	2	41	41	NUM
ajst-10983	267	3	]	]	X
ajst-10983	267	4	krizhevsky	krizhevsky	NOUN
ajst-10983	267	5	a	a	PROPN
ajst-10983	267	6	,	,	PUNCT
ajst-10983	267	7	sutskever	sutskever	VERB
ajst-10983	267	8	i	i	PRON
ajst-10983	267	9	,	,	PUNCT
ajst-10983	267	10	hinton	hinton	PROPN
ajst-10983	267	11	g	g	PROPN
ajst-10983	267	12	e.	e.	PROPN
ajst-10983	267	13	imagenet	imagenet	PROPN
ajst-10983	267	14	classification	classification	NOUN
ajst-10983	267	15	with	with	ADP
ajst-10983	267	16	deep	deep	ADJ
ajst-10983	267	17	convolutional	convolutional	ADJ
ajst-10983	267	18	neural	neural	ADJ
ajst-10983	267	19	networks[j	networks[j	NOUN
ajst-10983	267	20	]	]	X
ajst-10983	267	21	.	.	PUNCT
ajst-10983	268	1	communications	communication	NOUN
ajst-10983	268	2	of	of	ADP
ajst-10983	268	3	the	the	DET
ajst-10983	268	4	acm	acm	NOUN
ajst-10983	268	5	,	,	PUNCT
ajst-10983	268	6	2017	2017	NUM
ajst-10983	268	7	,	,	PUNCT
ajst-10983	268	8	60(6	60(6	NOUN
ajst-10983	268	9	):	):	PUNCT
ajst-10983	268	10	84	84	NUM
ajst-10983	268	11	-	-	SYM
ajst-10983	268	12	90	90	NUM
ajst-10983	268	13	.	.	PUNCT
ajst-10983	269	1	[	[	X
ajst-10983	269	2	42	42	NUM
ajst-10983	269	3	]	]	X
ajst-10983	269	4	tao	tao	PROPN
ajst-10983	269	5	w	w	PROPN
ajst-10983	269	6	a	a	PROPN
ajst-10983	269	7	,	,	PUNCT
ajst-10983	269	8	mrb	mrb	PROPN
ajst-10983	269	9	c	c	PROPN
ajst-10983	269	10	,	,	PUNCT
ajst-10983	269	11	zs	zs	PROPN
ajst-10983	269	12	d	d	PROPN
ajst-10983	269	13	,	,	PUNCT
ajst-10983	269	14	et	et	PROPN
ajst-10983	269	15	al	al	PROPN
ajst-10983	269	16	.	.	PUNCT
ajst-10983	269	17	segroot	segroot	PROPN
ajst-10983	269	18	:	:	PUNCT
ajst-10983	269	19	a	a	DET
ajst-10983	269	20	high	high	ADJ
ajst-10983	269	21	throughput	throughput	NOUN
ajst-10983	269	22	segmentation	segmentation	NOUN
ajst-10983	269	23	method	method	NOUN
ajst-10983	269	24	for	for	ADP
ajst-10983	269	25	root	root	NOUN
ajst-10983	269	26	image	image	NOUN
ajst-10983	269	27	analysis[j	analysis[j	PROPN
ajst-10983	269	28	]	]	PUNCT
ajst-10983	269	29	.	.	PUNCT
ajst-10983	270	1	computers	computer	NOUN
ajst-10983	270	2	and	and	CCONJ
ajst-10983	270	3	electronics	electronic	NOUN
ajst-10983	270	4	in	in	ADP
ajst-10983	270	5	agriculture	agriculture	NOUN
ajst-10983	270	6	,	,	PUNCT
ajst-10983	270	7	2019	2019	NUM
ajst-10983	270	8	,	,	PUNCT
ajst-10983	270	9	162:845	162:845	NOUN
ajst-10983	270	10	-	-	PUNCT
ajst-10983	270	11	854	854	NUM
ajst-10983	270	12	.	.	PUNCT
ajst-10983	271	1	[	[	X
ajst-10983	271	2	43	43	NUM
ajst-10983	271	3	]	]	X
ajst-10983	271	4	zhao	zhao	PROPN
ajst-10983	271	5	y	y	PROPN
ajst-10983	271	6	,	,	PUNCT
ajst-10983	271	7	wandel	wandel	PROPN
ajst-10983	271	8	n	n	PROPN
ajst-10983	271	9	,	,	PUNCT
ajst-10983	271	10	landl	landl	VERB
ajst-10983	271	11	m	m	PRON
ajst-10983	271	12	,	,	PUNCT
ajst-10983	271	13	et	et	PROPN
ajst-10983	271	14	al	al	PROPN
ajst-10983	271	15	.	.	PROPN
ajst-10983	272	1	3d	3d	NUM
ajst-10983	272	2	u	u	NOUN
ajst-10983	272	3	-	-	NOUN
ajst-10983	272	4	net	net	ADJ
ajst-10983	272	5	for	for	ADP
ajst-10983	272	6	segmentation	segmentation	NOUN
ajst-10983	272	7	of	of	ADP
ajst-10983	272	8	plant	plant	NOUN
ajst-10983	272	9	root	root	NOUN
ajst-10983	272	10	mri	mri	NOUN
ajst-10983	272	11	images	image	NOUN
ajst-10983	272	12	in	in	ADP
ajst-10983	272	13	super	super	NOUN
ajst-10983	272	14	-	-	ADJ
ajst-10983	272	15	resolution[j	resolution[j	NUM
ajst-10983	272	16	]	]	PUNCT
ajst-10983	272	17	.	.	PUNCT
ajst-10983	273	1	arxiv	arxiv	PROPN
ajst-10983	273	2	preprint	preprint	VERB
ajst-10983	273	3	arxiv:2002.09317	arxiv:2002.09317	NOUN
ajst-10983	273	4	,	,	PUNCT
ajst-10983	273	5	2020	2020	NUM
ajst-10983	273	6	.	.	PUNCT
ajst-10983	274	1	[	[	X
ajst-10983	274	2	44	44	NUM
ajst-10983	274	3	]	]	SYM
ajst-10983	274	4	seidenthal	seidenthal	PROPN
ajst-10983	274	5	k	k	PROPN
ajst-10983	274	6	,	,	PUNCT
ajst-10983	274	7	panjvani	panjvani	PROPN
ajst-10983	274	8	k	k	PROPN
ajst-10983	274	9	,	,	PUNCT
ajst-10983	274	10	chandnani	chandnani	ADJ
ajst-10983	274	11	r	r	NOUN
ajst-10983	274	12	,	,	PUNCT
ajst-10983	274	13	et	et	PROPN
ajst-10983	274	14	al	al	PROPN
ajst-10983	274	15	.	.	PROPN
ajst-10983	274	16	iterative	iterative	PROPN
ajst-10983	274	17	image	image	NOUN
ajst-10983	274	18	segmentation	segmentation	NOUN
ajst-10983	274	19	of	of	ADP
ajst-10983	274	20	plant	plant	NOUN
ajst-10983	274	21	roots	root	NOUN
ajst-10983	274	22	for	for	ADP
ajst-10983	274	23	high	high	ADJ
ajst-10983	274	24	-	-	PUNCT
ajst-10983	274	25	throughput	throughput	NOUN
ajst-10983	274	26	phenotyping[j	phenotyping[j	NOUN
ajst-10983	274	27	]	]	PUNCT
ajst-10983	274	28	.	.	PUNCT
ajst-10983	275	1	scientific	scientific	ADJ
ajst-10983	275	2	reports	report	NOUN
ajst-10983	275	3	,	,	PUNCT
ajst-10983	275	4	2022	2022	NUM
ajst-10983	275	5	,	,	PUNCT
ajst-10983	275	6	12(1	12(1	NUM
ajst-10983	275	7	):	):	PUNCT
ajst-10983	275	8	16563	16563	NUM
ajst-10983	275	9	.	.	PUNCT
ajst-10983	276	1	[	[	X
ajst-10983	276	2	45	45	NUM
ajst-10983	276	3	]	]	X
ajst-10983	276	4	kang	kang	PROPN
ajst-10983	276	5	j	j	PROPN
ajst-10983	276	6	,	,	PUNCT
ajst-10983	276	7	liu	liu	PROPN
ajst-10983	276	8	l	l	PROPN
ajst-10983	276	9	,	,	PUNCT
ajst-10983	276	10	zhang	zhang	PROPN
ajst-10983	277	1	f	f	PROPN
ajst-10983	277	2	,	,	PUNCT
ajst-10983	277	3	et	et	PROPN
ajst-10983	277	4	al	al	PROPN
ajst-10983	277	5	.	.	PUNCT
ajst-10983	277	6	semantic	semantic	ADJ
ajst-10983	277	7	segmentation	segmentation	NOUN
ajst-10983	277	8	model	model	NOUN
ajst-10983	277	9	of	of	ADP
ajst-10983	277	10	cotton	cotton	NOUN
ajst-10983	277	11	roots	root	NOUN
ajst-10983	277	12	in	in	ADP
ajst-10983	277	13	-	-	PUNCT
ajst-10983	277	14	situ	situ	NOUN
ajst-10983	277	15	image	image	NOUN
ajst-10983	277	16	based	base	VERB
ajst-10983	277	17	on	on	ADP
ajst-10983	277	18	attention	attention	NOUN
ajst-10983	277	19	mechanism[j	mechanism[j	PROPN
ajst-10983	277	20	]	]	PUNCT
ajst-10983	277	21	.	.	PUNCT
ajst-10983	278	1	computers	computer	NOUN
ajst-10983	278	2	and	and	CCONJ
ajst-10983	278	3	electronics	electronic	NOUN
ajst-10983	278	4	in	in	ADP
ajst-10983	278	5	agriculture	agriculture	NOUN
ajst-10983	278	6	,	,	PUNCT
ajst-10983	278	7	2021	2021	NUM
ajst-10983	278	8	,	,	PUNCT
ajst-10983	278	9	189	189	NUM
ajst-10983	278	10	:	:	SYM
ajst-10983	278	11	106370	106370	NUM
ajst-10983	278	12	.	.	PUNCT
ajst-10983	279	1	[	[	X
ajst-10983	279	2	46	46	NUM
ajst-10983	279	3	]	]	X
ajst-10983	279	4	alle	alle	PROPN
ajst-10983	279	5	j	j	PROPN
ajst-10983	279	6	,	,	PUNCT
ajst-10983	279	7	gruber	gruber	PROPN
ajst-10983	279	8	r	r	PROPN
ajst-10983	279	9	,	,	PUNCT
ajst-10983	279	10	wöhrlein	wöhrlein	ADJ
ajst-10983	279	11	n	n	CCONJ
ajst-10983	279	12	,	,	PUNCT
ajst-10983	279	13	et	et	PROPN
ajst-10983	279	14	al	al	PROPN
ajst-10983	279	15	.	.	PROPN
ajst-10983	279	16	3d	3d	NUM
ajst-10983	279	17	segmentation	segmentation	NOUN
ajst-10983	279	18	of	of	ADP
ajst-10983	279	19	plant	plant	NOUN
ajst-10983	279	20	root	root	NOUN
ajst-10983	279	21	systems	system	NOUN
ajst-10983	279	22	using	use	VERB
ajst-10983	279	23	spatial	spatial	ADJ
ajst-10983	279	24	pyramid	pyramid	NOUN
ajst-10983	279	25	pooling	pooling	NOUN
ajst-10983	279	26	and	and	CCONJ
ajst-10983	279	27	locally	locally	ADV
ajst-10983	279	28	adaptive	adaptive	ADJ
ajst-10983	279	29	field	field	NOUN
ajst-10983	279	30	-	-	PUNCT
ajst-10983	279	31	of	of	ADP
ajst-10983	279	32	-	-	PUNCT
ajst-10983	279	33	view	view	NOUN
ajst-10983	279	34	inference[j	inference[j	NOUN
ajst-10983	279	35	]	]	PUNCT
ajst-10983	279	36	.	.	PUNCT
ajst-10983	280	1	frontiers	frontier	NOUN
ajst-10983	280	2	in	in	ADP
ajst-10983	280	3	plant	plant	NOUN
ajst-10983	280	4	science	science	NOUN
ajst-10983	280	5	,	,	PUNCT
ajst-10983	280	6	2023	2023	NUM
ajst-10983	280	7	,	,	PUNCT
ajst-10983	280	8	14	14	NUM
ajst-10983	280	9	:	:	SYM
ajst-10983	280	10	1055	1055	NUM
ajst-10983	280	11	.	.	PUNCT
ajst-10983	281	1	[	[	X
ajst-10983	281	2	47	47	NUM
ajst-10983	281	3	]	]	X
ajst-10983	281	4	shi	shi	PROPN
ajst-10983	281	5	w	w	PROPN
ajst-10983	281	6	,	,	PUNCT
ajst-10983	281	7	caballero	caballero	PROPN
ajst-10983	281	8	j	j	PROPN
ajst-10983	281	9	,	,	PUNCT
ajst-10983	281	10	huszár	huszár	PROPN
ajst-10983	281	11	f	f	X
ajst-10983	281	12	,	,	PUNCT
ajst-10983	281	13	et	et	PROPN
ajst-10983	281	14	al	al	PROPN
ajst-10983	281	15	.	.	PUNCT
ajst-10983	281	16	real	real	ADJ
ajst-10983	281	17	-	-	PUNCT
ajst-10983	281	18	time	time	NOUN
ajst-10983	281	19	single	single	ADJ
ajst-10983	281	20	image	image	NOUN
ajst-10983	281	21	and	and	CCONJ
ajst-10983	281	22	video	video	NOUN
ajst-10983	281	23	super	super	NOUN
ajst-10983	281	24	-	-	NOUN
ajst-10983	281	25	resolution	resolution	NOUN
ajst-10983	281	26	using	use	VERB
ajst-10983	281	27	an	an	DET
ajst-10983	281	28	efficient	efficient	ADJ
ajst-10983	281	29	sub	sub	ADJ
ajst-10983	281	30	-	-	ADJ
ajst-10983	281	31	pixel	pixel	ADJ
ajst-10983	281	32	convolutional	convolutional	ADJ
ajst-10983	281	33	neural	neural	ADJ
ajst-10983	281	34	network[c]//proceedings	network[c]//proceeding	NOUN
ajst-10983	281	35	of	of	ADP
ajst-10983	281	36	the	the	DET
ajst-10983	281	37	ieee	ieee	NOUN
ajst-10983	281	38	conference	conference	NOUN
ajst-10983	281	39	on	on	ADP
ajst-10983	281	40	computer	computer	NOUN
ajst-10983	281	41	vision	vision	NOUN
ajst-10983	281	42	and	and	CCONJ
ajst-10983	281	43	pattern	pattern	NOUN
ajst-10983	281	44	recognition	recognition	NOUN
ajst-10983	281	45	.	.	PUNCT
ajst-10983	282	1	2016	2016	NUM
ajst-10983	282	2	:	:	PUNCT
ajst-10983	282	3	1874	1874	NUM
ajst-10983	282	4	-	-	SYM
ajst-10983	282	5	1883	1883	NUM
ajst-10983	282	6	.	.	PUNCT
ajst-10983	283	1	[	[	X
ajst-10983	283	2	48	48	NUM
ajst-10983	283	3	]	]	X
ajst-10983	283	4	huang	huang	PROPN
ajst-10983	283	5	y	y	PROPN
ajst-10983	283	6	,	,	PUNCT
ajst-10983	283	7	yan	yan	PROPN
ajst-10983	283	8	j	j	PROPN
ajst-10983	283	9	,	,	PUNCT
ajst-10983	283	10	zhang	zhang	PROPN
ajst-10983	283	11	y	y	PROPN
ajst-10983	283	12	,	,	PUNCT
ajst-10983	283	13	et	et	PROPN
ajst-10983	283	14	al	al	PROPN
ajst-10983	283	15	.	.	PROPN
ajst-10983	284	1	automatic	automatic	ADJ
ajst-10983	284	2	segmentation	segmentation	NOUN
ajst-10983	284	3	of	of	ADP
ajst-10983	284	4	cotton	cotton	NOUN
ajst-10983	284	5	roots	root	NOUN
ajst-10983	284	6	in	in	ADP
ajst-10983	284	7	high	high	ADJ
ajst-10983	284	8	-	-	PUNCT
ajst-10983	284	9	resolution	resolution	NOUN
ajst-10983	284	10	minirhizotron	minirhizotron	ADJ
ajst-10983	284	11	images	image	NOUN
ajst-10983	284	12	based	base	VERB
ajst-10983	284	13	on	on	ADP
ajst-10983	284	14	improved	improve	VERB
ajst-10983	284	15	ocrnet[j	ocrnet[j	NOUN
ajst-10983	284	16	]	]	PUNCT
ajst-10983	284	17	.	.	PUNCT
ajst-10983	285	1	frontiers	frontier	NOUN
ajst-10983	285	2	in	in	ADP
ajst-10983	285	3	plant	plant	NOUN
ajst-10983	285	4	science	science	NOUN
ajst-10983	285	5	,	,	PUNCT
ajst-10983	285	6	2023	2023	NUM
ajst-10983	285	7	,	,	PUNCT
ajst-10983	285	8	14	14	NUM
ajst-10983	285	9	.	.	PUNCT
ajst-10983	286	1	[	[	X
ajst-10983	286	2	49	49	NUM
ajst-10983	286	3	]	]	PUNCT
ajst-10983	286	4	vaswani	vaswani	NOUN
ajst-10983	286	5	a	a	PRON
ajst-10983	286	6	,	,	PUNCT
ajst-10983	286	7	shazeer	shazeer	NOUN
ajst-10983	286	8	n	n	SYM
ajst-10983	286	9	,	,	PUNCT
ajst-10983	286	10	parmar	parmar	PROPN
ajst-10983	286	11	n	n	CCONJ
ajst-10983	286	12	,	,	PUNCT
ajst-10983	286	13	et	et	PROPN
ajst-10983	286	14	al	al	PROPN
ajst-10983	286	15	.	.	PUNCT
ajst-10983	286	16	attention	attention	NOUN
ajst-10983	286	17	is	be	AUX
ajst-10983	286	18	all	all	PRON
ajst-10983	286	19	you	you	PRON
ajst-10983	286	20	need[j	need[j	VERB
ajst-10983	286	21	]	]	PUNCT
ajst-10983	286	22	.	.	PUNCT
ajst-10983	287	1	advances	advance	NOUN
ajst-10983	287	2	in	in	ADP
ajst-10983	287	3	neural	neural	ADJ
ajst-10983	287	4	information	information	NOUN
ajst-10983	287	5	processing	processing	NOUN
ajst-10983	287	6	systems	system	NOUN
ajst-10983	287	7	,	,	PUNCT
ajst-10983	287	8	2017	2017	NUM
ajst-10983	287	9	,	,	PUNCT
ajst-10983	287	10	30	30	NUM
ajst-10983	287	11	.	.	PUNCT
ajst-10983	288	1	[	[	X
ajst-10983	288	2	50	50	NUM
ajst-10983	288	3	]	]	X
ajst-10983	288	4	wu	wu	PROPN
ajst-10983	288	5	lan	lan	PROPN
ajst-10983	288	6	,	,	PUNCT
ajst-10983	288	7	su	su	PROPN
ajst-10983	288	8	lide	lide	PROPN
ajst-10983	288	9	,	,	PUNCT
ajst-10983	288	10	jia	jia	PROPN
ajst-10983	288	11	liguo	liguo	PROPN
ajst-10983	288	12	,	,	PUNCT
ajst-10983	288	13	qin	qin	PROPN
ajst-10983	288	14	yonglin	yonglin	PROPN
ajst-10983	288	15	,	,	PUNCT
ajst-10983	288	16	fan	fan	PROPN
ajst-10983	288	17	mingshou.potato	mingshou.potato	PROPN
ajst-10983	288	18	root	root	NOUN
ajst-10983	288	19	image	image	NOUN
ajst-10983	288	20	segmentation	segmentation	NOUN
ajst-10983	288	21	method	method	NOUN
ajst-10983	288	22	based	base	VERB
ajst-10983	288	23	on	on	ADP
ajst-10983	288	24	improved	improved	ADJ
ajst-10983	288	25	deeplabv3	deeplabv3	NOUN
ajst-10983	288	26	+	+	CCONJ
ajst-10983	288	27	network[j].journal	network[j].journal	ADJ
ajst-10983	288	28	of	of	ADP
ajst-10983	288	29	agricultural	agricultural	ADJ
ajst-10983	288	30	engineering,2023,39(03):134	engineering,2023,39(03):134	PROPN
ajst-10983	288	31	-	-	SYM
ajst-10983	288	32	144	144	NUM
ajst-10983	288	33	.	.	PUNCT
ajst-10983	289	1	[	[	X
ajst-10983	289	2	51	51	NUM
ajst-10983	289	3	]	]	X
ajst-10983	289	4	firdaus	firdaus	PROPN
ajst-10983	289	5	-	-	PUNCT
ajst-10983	289	6	nawi	nawi	PROPN
ajst-10983	289	7	m	m	PROPN
ajst-10983	289	8	,	,	PUNCT
ajst-10983	289	9	noraini	noraini	ADJ
ajst-10983	289	10	o	o	NOUN
ajst-10983	289	11	,	,	PUNCT
ajst-10983	290	1	sabri	sabri	PROPN
ajst-10983	290	2	m	m	PROPN
ajst-10983	290	3	y	y	PROPN
ajst-10983	290	4	,	,	PUNCT
ajst-10983	290	5	et	et	PROPN
ajst-10983	290	6	al	al	PROPN
ajst-10983	290	7	.	.	PUNCT
ajst-10983	291	1	deeplabv3	deeplabv3	PROPN
ajst-10983	292	1	+	+	X
ajst-10983	292	2	_	_	PRON
ajst-10983	292	3	encoder	encoder	NOUN
ajst-10983	292	4	-	-	PUNCT
ajst-10983	292	5	decoder	decoder	NOUN
ajst-10983	292	6	with	with	ADP
ajst-10983	292	7	atrous	atrous	ADJ
ajst-10983	292	8	separable	separable	ADJ
ajst-10983	292	9	convolution	convolution	NOUN
ajst-10983	292	10	for	for	ADP
ajst-10983	292	11	semantic	semantic	ADJ
ajst-10983	292	12	image	image	NOUN
ajst-10983	292	13	segmentation[j	segmentation[j	PROPN
ajst-10983	292	14	]	]	PUNCT
ajst-10983	292	15	.	.	PUNCT
ajst-10983	293	1	pertanika	pertanika	PROPN
ajst-10983	293	2	j.	j.	PROPN
ajst-10983	293	3	trop	trop	PROPN
ajst-10983	293	4	.	.	PUNCT
ajst-10983	294	1	agric	agric	PROPN
ajst-10983	294	2	.	.	PUNCT
ajst-10983	295	1	sci	sci	PROPN
ajst-10983	295	2	,	,	PUNCT
ajst-10983	295	3	2011	2011	NUM
ajst-10983	295	4	,	,	PUNCT
ajst-10983	295	5	34(1	34(1	NUM
ajst-10983	295	6	):	):	PUNCT
ajst-10983	295	7	137	137	NUM
ajst-10983	295	8	-	-	SYM
ajst-10983	295	9	143	143	NUM
ajst-10983	295	10	.	.	PUNCT
ajst-10983	296	1	[	[	X
ajst-10983	296	2	52	52	NUM
ajst-10983	296	3	]	]	PUNCT
ajst-10983	296	4	yasrab	yasrab	NOUN
ajst-10983	296	5	r	r	NOUN
ajst-10983	296	6	,	,	PUNCT
ajst-10983	296	7	atkinson	atkinson	PROPN
ajst-10983	296	8	j	j	PROPN
ajst-10983	296	9	a	a	PROPN
ajst-10983	296	10	,	,	PUNCT
ajst-10983	296	11	wells	wells	PROPN
ajst-10983	296	12	d	d	PROPN
ajst-10983	296	13	m	m	PROPN
ajst-10983	296	14	,	,	PUNCT
ajst-10983	296	15	et	et	PROPN
ajst-10983	296	16	al	al	PROPN
ajst-10983	296	17	.	.	PROPN
ajst-10983	296	18	rootnav	rootnav	PROPN
ajst-10983	296	19	2.0	2.0	NUM
ajst-10983	296	20	:	:	PUNCT
ajst-10983	296	21	deep	deep	ADJ
ajst-10983	296	22	learning	learning	NOUN
ajst-10983	296	23	for	for	ADP
ajst-10983	296	24	automatic	automatic	ADJ
ajst-10983	296	25	navigation	navigation	NOUN
ajst-10983	296	26	of	of	ADP
ajst-10983	296	27	complex	complex	ADJ
ajst-10983	296	28	plant	plant	NOUN
ajst-10983	296	29	root	root	NOUN
ajst-10983	296	30	architectures[j	architectures[j	PROPN
ajst-10983	296	31	]	]	PUNCT
ajst-10983	296	32	.	.	PUNCT
ajst-10983	297	1	gigascience	gigascience	NOUN
ajst-10983	297	2	,	,	PUNCT
ajst-10983	297	3	2019	2019	NUM
ajst-10983	297	4	,	,	PUNCT
ajst-10983	297	5	8(11	8(11	NUM
ajst-10983	297	6	):	):	PUNCT
ajst-10983	297	7	giz123	giz123	PROPN
ajst-10983	297	8	.	.	PUNCT
ajst-10983	298	1	[	[	X
ajst-10983	298	2	53	53	NUM
ajst-10983	298	3	]	]	PUNCT
ajst-10983	298	4	yu	yu	PROPN
ajst-10983	298	5	q	q	PROPN
ajst-10983	298	6	,	,	PUNCT
ajst-10983	298	7	tang	tang	PROPN
ajst-10983	298	8	h	h	PROPN
ajst-10983	298	9	y	y	PROPN
ajst-10983	298	10	,	,	PUNCT
ajst-10983	298	11	zhu	zhu	PROPN
ajst-10983	298	12	l	l	PROPN
ajst-10983	299	1	q	q	X
ajst-10983	299	2	,	,	PUNCT
ajst-10983	299	3	zhang	zhang	PROPN
ajst-10983	299	4	w	w	PROPN
ajst-10983	299	5	,	,	PUNCT
ajst-10983	299	6	liu	liu	PROPN
ajst-10983	299	7	l	l	PROPN
ajst-10983	299	8	n	n	CCONJ
ajst-10983	299	9	,	,	PUNCT
ajst-10983	299	10	wang	wang	PROPN
ajst-10983	299	11	n.	n.	PROPN
ajst-10983	299	12	a	a	DET
ajst-10983	299	13	method	method	NOUN
ajst-10983	299	14	of	of	ADP
ajst-10983	299	15	cotton	cotton	NOUN
ajst-10983	299	16	root	root	NOUN
ajst-10983	299	17	segmentation	segmentation	NOUN
ajst-10983	299	18	based	base	VERB
ajst-10983	299	19	on	on	ADP
ajst-10983	299	20	edge	edge	NOUN
ajst-10983	299	21	devices	device	NOUN
ajst-10983	299	22	.	.	PUNCT
ajst-10983	300	1	frontiers	frontier	NOUN
ajst-10983	300	2	in	in	ADP
ajst-10983	300	3	plant	plant	NOUN
ajst-10983	300	4	science	science	NOUN
ajst-10983	300	5	,	,	PUNCT
ajst-10983	300	6	2023	2023	NUM
ajst-10983	300	7	,	,	PUNCT
ajst-10983	300	8	14	14	NUM
ajst-10983	300	9	:	:	SYM
ajst-10983	300	10	550	550	NUM
ajst-10983	300	11	.	.	PUNCT
ajst-10983	301	1	[	[	X
ajst-10983	301	2	54	54	NUM
ajst-10983	301	3	]	]	PUNCT
ajst-10983	301	4	ronneberger	ronneberger	NOUN
ajst-10983	301	5	o	o	NOUN
ajst-10983	301	6	,	,	PUNCT
ajst-10983	301	7	fischer	fischer	PROPN
ajst-10983	301	8	p	p	PROPN
ajst-10983	301	9	,	,	PUNCT
ajst-10983	301	10	brox	brox	PROPN
ajst-10983	301	11	t.	t.	PROPN
ajst-10983	301	12	u	u	PROPN
ajst-10983	301	13	-	-	NOUN
ajst-10983	301	14	net	net	ADJ
ajst-10983	301	15	:	:	PUNCT
ajst-10983	301	16	convolutional	convolutional	ADJ
ajst-10983	301	17	networks	network	NOUN
ajst-10983	301	18	for	for	ADP
ajst-10983	301	19	biomedical	biomedical	ADJ
ajst-10983	301	20	image	image	NOUN
ajst-10983	301	21	segmentation[c]//medical	segmentation[c]//medical	ADJ
ajst-10983	301	22	image	image	NOUN
ajst-10983	301	23	computing	computing	NOUN
ajst-10983	301	24	and	and	CCONJ
ajst-10983	301	25	computer	computer	NOUN
ajst-10983	301	26	-	-	PUNCT
ajst-10983	301	27	assisted	assist	VERB
ajst-10983	301	28	intervention	intervention	NOUN
ajst-10983	301	29	–	–	PUNCT
ajst-10983	301	30	miccai	miccai	NOUN
ajst-10983	301	31	2015	2015	NUM
ajst-10983	301	32	:	:	PUNCT
ajst-10983	301	33	18th	18th	ADJ
ajst-10983	301	34	international	international	ADJ
ajst-10983	301	35	conference	conference	NOUN
ajst-10983	301	36	,	,	PUNCT
ajst-10983	301	37	munich	munich	PROPN
ajst-10983	301	38	,	,	PUNCT
ajst-10983	301	39	germany	germany	PROPN
ajst-10983	301	40	,	,	PUNCT
ajst-10983	301	41	october	october	PROPN
ajst-10983	301	42	5	5	NUM
ajst-10983	301	43	-	-	SYM
ajst-10983	301	44	9	9	NUM
ajst-10983	301	45	,	,	PUNCT
ajst-10983	301	46	2015	2015	NUM
ajst-10983	301	47	,	,	PUNCT
ajst-10983	301	48	proceedings	proceeding	NOUN
ajst-10983	301	49	,	,	PUNCT
ajst-10983	301	50	part	part	NOUN
ajst-10983	301	51	iii	iii	NUM
ajst-10983	301	52	18	18	NUM
ajst-10983	301	53	.	.	PUNCT
ajst-10983	301	54	springer	springer	NOUN
ajst-10983	301	55	international	international	ADJ
ajst-10983	301	56	publishing	publishing	NOUN
ajst-10983	301	57	,	,	PUNCT
ajst-10983	301	58	2015	2015	NUM
ajst-10983	301	59	:	:	PUNCT
ajst-10983	301	60	234	234	NUM
ajst-10983	301	61	-	-	SYM
ajst-10983	301	62	241	241	NUM
ajst-10983	301	63	.	.	PUNCT
ajst-10983	302	1	[	[	X
ajst-10983	302	2	55	55	NUM
ajst-10983	302	3	]	]	X
ajst-10983	302	4	chen	chen	PROPN
ajst-10983	302	5	l	l	PROPN
ajst-10983	302	6	c	c	PROPN
ajst-10983	302	7	,	,	PUNCT
ajst-10983	302	8	papandreou	papandreou	ADV
ajst-10983	302	9	g	g	NOUN
ajst-10983	302	10	,	,	PUNCT
ajst-10983	302	11	kokkinos	kokkinos	PROPN
ajst-10983	302	12	i	i	PRON
ajst-10983	302	13	,	,	PUNCT
ajst-10983	302	14	et	et	PROPN
ajst-10983	302	15	al	al	PROPN
ajst-10983	302	16	.	.	PUNCT
ajst-10983	303	1	deeplab	deeplab	PROPN
ajst-10983	303	2	:	:	PUNCT
ajst-10983	303	3	semantic	semantic	ADJ
ajst-10983	303	4	image	image	NOUN
ajst-10983	303	5	segmentation	segmentation	NOUN
ajst-10983	303	6	with	with	ADP
ajst-10983	303	7	deep	deep	ADJ
ajst-10983	303	8	convolutional	convolutional	ADJ
ajst-10983	303	9	nets	net	NOUN
ajst-10983	303	10	,	,	PUNCT
ajst-10983	303	11	atrous	atrous	ADJ
ajst-10983	303	12	convolution	convolution	NOUN
ajst-10983	303	13	,	,	PUNCT
ajst-10983	303	14	and	and	CCONJ
ajst-10983	303	15	fully	fully	ADV
ajst-10983	303	16	connected	connected	ADJ
ajst-10983	303	17	crfs[j	crfs[j	NOUN
ajst-10983	303	18	]	]	PUNCT
ajst-10983	303	19	.	.	PUNCT
ajst-10983	304	1	ieee	ieee	NOUN
ajst-10983	304	2	transactions	transaction	NOUN
ajst-10983	304	3	on	on	ADP
ajst-10983	304	4	pattern	pattern	NOUN
ajst-10983	304	5	analysis	analysis	NOUN
ajst-10983	304	6	and	and	CCONJ
ajst-10983	304	7	machine	machine	NOUN
ajst-10983	304	8	intelligence	intelligence	NOUN
ajst-10983	304	9	,	,	PUNCT
ajst-10983	304	10	2017	2017	NUM
ajst-10983	304	11	,	,	PUNCT
ajst-10983	304	12	40(4	40(4	NUM
ajst-10983	304	13	):	):	PUNCT
ajst-10983	304	14	834848	834848	NUM
ajst-10983	304	15	.	.	PUNCT