id	sid	tid	token	lemma	pos
cana-2825	1	1	communications	communication	NOUN
cana-2825	1	2	on	on	ADP
cana-2825	1	3	applied	apply	VERB
cana-2825	1	4	nonlinear	nonlinear	ADJ
cana-2825	1	5	analysis	analysis	NOUN
cana-2825	1	6	issn	issn	NOUN
cana-2825	1	7	:	:	PUNCT
cana-2825	1	8	1074	1074	NUM
cana-2825	1	9	-	-	PUNCT
cana-2825	1	10	133x	133x	NUM
cana-2825	1	11	vol	vol	NOUN
cana-2825	1	12	32	32	NUM
cana-2825	1	13	no	no	NOUN
cana-2825	1	14	.	.	PUNCT
cana-2825	2	1	4s	4s	NUM
cana-2825	2	2	(	(	PUNCT
cana-2825	2	3	2025	2025	NUM
cana-2825	2	4	)	)	PUNCT
cana-2825	2	5	344	344	NUM
cana-2825	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	2	7	enhancing	enhance	VERB
cana-2825	2	8	crop	crop	NOUN
cana-2825	2	9	yield	yield	NOUN
cana-2825	2	10	prediction	prediction	NOUN
cana-2825	2	11	using	use	VERB
cana-2825	2	12	linear	linear	ADJ
cana-2825	2	13	models	model	NOUN
cana-2825	2	14	and	and	CCONJ
cana-2825	2	15	deep	deep	ADJ
cana-2825	2	16	learning	learning	NOUN
cana-2825	2	17	techniques	technique	NOUN
cana-2825	2	18	in	in	ADP
cana-2825	2	19	precision	precision	PROPN
cana-2825	2	20	agriculture	agriculture	PROPN
cana-2825	2	21	b.	b.	PROPN
cana-2825	2	22	sunitha	sunitha	PROPN
cana-2825	2	23	devi1	devi1	PROPN
cana-2825	2	24	,	,	PUNCT
cana-2825	2	25	k.	k.	PROPN
cana-2825	2	26	shahu	shahu	PROPN
cana-2825	2	27	chatrapati2	chatrapati2	PROPN
cana-2825	2	28	,	,	PUNCT
cana-2825	2	29	n.	n.	PROPN
cana-2825	2	30	sandhya3	sandhya3	PROPN
cana-2825	2	31	1	1	NUM
cana-2825	2	32	department	department	NOUN
cana-2825	2	33	of	of	ADP
cana-2825	2	34	cse	cse	PROPN
cana-2825	2	35	,	,	PUNCT
cana-2825	2	36	cmr	cmr	PROPN
cana-2825	2	37	institute	institute	PROPN
cana-2825	2	38	of	of	ADP
cana-2825	2	39	technology	technology	PROPN
cana-2825	2	40	,	,	PUNCT
cana-2825	2	41	hyderabad	hyderabad	PROPN
cana-2825	2	42	,	,	PUNCT
cana-2825	2	43	india	india	PROPN
cana-2825	2	44	.	.	PUNCT
cana-2825	3	1	sunithadevi.b2022@gmail.com	sunithadevi.b2022@gmail.com	PROPN
cana-2825	3	2	2	2	NUM
cana-2825	3	3	department	department	NOUN
cana-2825	3	4	of	of	ADP
cana-2825	3	5	cse	cse	PROPN
cana-2825	3	6	,	,	PUNCT
cana-2825	3	7	jntuh	jntuh	PROPN
cana-2825	3	8	,	,	PUNCT
cana-2825	3	9	hyderabad	hyderabad	PROPN
cana-2825	3	10	,	,	PUNCT
cana-2825	3	11	india	india	PROPN
cana-2825	3	12	.	.	PUNCT
cana-2825	4	1	shahujntu@gmail.com	shahujntu@gmail.com	X
cana-2825	5	1	3	3	NUM
cana-2825	5	2	department	department	NOUN
cana-2825	5	3	of	of	ADP
cana-2825	5	4	cse	cse	PROPN
cana-2825	5	5	,	,	PUNCT
cana-2825	5	6	vnr	vnr	PROPN
cana-2825	5	7	vignan	vignan	PROPN
cana-2825	5	8	jyothi	jyothi	PROPN
cana-2825	5	9	institute	institute	PROPN
cana-2825	5	10	of	of	ADP
cana-2825	5	11	engineering	engineering	PROPN
cana-2825	5	12	&	&	CCONJ
cana-2825	5	13	technology	technology	PROPN
cana-2825	5	14	,	,	PUNCT
cana-2825	5	15	hyderabad	hyderabad	PROPN
cana-2825	5	16	,	,	PUNCT
cana-2825	5	17	india	india	PROPN
cana-2825	5	18	.	.	PUNCT
cana-2825	6	1	sandhyanadela@gmail.com	sandhyanadela@gmail.com	X
cana-2825	7	1	article	article	NOUN
cana-2825	7	2	history	history	NOUN
cana-2825	7	3	:	:	PUNCT
cana-2825	7	4	received	receive	VERB
cana-2825	7	5	:	:	PUNCT
cana-2825	7	6	23	23	NUM
cana-2825	7	7	-	-	SYM
cana-2825	7	8	09	09	NUM
cana-2825	7	9	-	-	PUNCT
cana-2825	7	10	2024	2024	NUM
cana-2825	7	11	revised	revise	VERB
cana-2825	7	12	:	:	PUNCT
cana-2825	7	13	25	25	NUM
cana-2825	7	14	-	-	SYM
cana-2825	7	15	11	11	NUM
cana-2825	7	16	-	-	PUNCT
cana-2825	7	17	2024	2024	NUM
cana-2825	7	18	accepted	accept	VERB
cana-2825	7	19	:	:	PUNCT
cana-2825	7	20	08	08	NUM
cana-2825	7	21	-	-	SYM
cana-2825	7	22	12	12	NUM
cana-2825	7	23	-	-	PUNCT
cana-2825	7	24	2024	2024	NUM
cana-2825	7	25	abstract	abstract	NOUN
cana-2825	7	26	:	:	PUNCT
cana-2825	7	27	the	the	DET
cana-2825	7	28	substantial	substantial	ADJ
cana-2825	7	29	advancements	advancement	NOUN
cana-2825	7	30	in	in	ADP
cana-2825	7	31	computer	computer	NOUN
cana-2825	7	32	science	science	NOUN
cana-2825	7	33	and	and	CCONJ
cana-2825	7	34	engineering	engineering	NOUN
cana-2825	7	35	have	have	AUX
cana-2825	7	36	sparked	spark	VERB
cana-2825	7	37	interest	interest	NOUN
cana-2825	7	38	in	in	ADP
cana-2825	7	39	precision	precision	NOUN
cana-2825	7	40	agriculture	agriculture	NOUN
cana-2825	7	41	and	and	CCONJ
cana-2825	7	42	led	lead	VERB
cana-2825	7	43	to	to	ADP
cana-2825	7	44	the	the	DET
cana-2825	7	45	development	development	NOUN
cana-2825	7	46	of	of	ADP
cana-2825	7	47	more	more	ADV
cana-2825	7	48	advanced	advanced	ADJ
cana-2825	7	49	instruments	instrument	NOUN
cana-2825	7	50	and	and	CCONJ
cana-2825	7	51	methods	method	NOUN
cana-2825	7	52	for	for	ADP
cana-2825	7	53	enhancing	enhance	VERB
cana-2825	7	54	farming	farming	NOUN
cana-2825	7	55	practices	practice	NOUN
cana-2825	7	56	.	.	PUNCT
cana-2825	8	1	this	this	DET
cana-2825	8	2	study	study	NOUN
cana-2825	8	3	focuses	focus	VERB
cana-2825	8	4	on	on	ADP
cana-2825	8	5	the	the	DET
cana-2825	8	6	use	use	NOUN
cana-2825	8	7	of	of	ADP
cana-2825	8	8	machine	machine	NOUN
cana-2825	8	9	learning	learning	NOUN
cana-2825	8	10	and	and	CCONJ
cana-2825	8	11	mathematical	mathematical	ADJ
cana-2825	8	12	models	model	NOUN
cana-2825	8	13	for	for	ADP
cana-2825	8	14	fertilisation	fertilisation	NOUN
cana-2825	8	15	optimisation	optimisation	NOUN
cana-2825	8	16	and	and	CCONJ
cana-2825	8	17	yield	yield	NOUN
cana-2825	8	18	prediction	prediction	NOUN
cana-2825	8	19	as	as	ADP
cana-2825	8	20	part	part	NOUN
cana-2825	8	21	of	of	ADP
cana-2825	8	22	a	a	DET
cana-2825	8	23	precision	precision	NOUN
cana-2825	8	24	agriculture	agriculture	NOUN
cana-2825	8	25	strategy	strategy	NOUN
cana-2825	8	26	.	.	PUNCT
cana-2825	9	1	in	in	ADP
cana-2825	9	2	particular	particular	ADJ
cana-2825	9	3	,	,	PUNCT
cana-2825	9	4	provides	provide	VERB
cana-2825	9	5	the	the	DET
cana-2825	9	6	outcomes	outcome	NOUN
cana-2825	9	7	of	of	ADP
cana-2825	9	8	forecasting	forecast	VERB
cana-2825	9	9	winter	winter	NOUN
cana-2825	9	10	wheat	wheat	NOUN
cana-2825	9	11	production	production	NOUN
cana-2825	9	12	and	and	CCONJ
cana-2825	9	13	protein	protein	NOUN
cana-2825	9	14	content	content	NOUN
cana-2825	9	15	across	across	ADP
cana-2825	9	16	four	four	NUM
cana-2825	9	17	farms	farm	NOUN
cana-2825	9	18	using	use	VERB
cana-2825	9	19	the	the	DET
cana-2825	9	20	amounts	amount	NOUN
cana-2825	9	21	of	of	ADP
cana-2825	9	22	nitrogen	nitrogen	NOUN
cana-2825	9	23	fertiliser	fertiliser	NOUN
cana-2825	9	24	sprayed	spray	VERB
cana-2825	9	25	on	on	ADP
cana-2825	9	26	the	the	DET
cana-2825	9	27	fields	field	NOUN
cana-2825	9	28	.	.	PUNCT
cana-2825	10	1	to	to	PART
cana-2825	10	2	maximise	maximise	VERB
cana-2825	10	3	net	net	ADJ
cana-2825	10	4	yields	yield	NOUN
cana-2825	10	5	on	on	ADP
cana-2825	10	6	the	the	DET
cana-2825	10	7	next	next	ADJ
cana-2825	10	8	crop	crop	NOUN
cana-2825	10	9	,	,	PUNCT
cana-2825	10	10	fertiliser	fertiliser	NOUN
cana-2825	10	11	treatments	treatment	NOUN
cana-2825	10	12	have	have	VERB
cana-2825	10	13	to	to	PART
cana-2825	10	14	be	be	AUX
cana-2825	10	15	prescribed	prescribe	VERB
cana-2825	10	16	based	base	VERB
cana-2825	10	17	on	on	ADP
cana-2825	10	18	these	these	DET
cana-2825	10	19	projections	projection	NOUN
cana-2825	10	20	.	.	PUNCT
cana-2825	11	1	in	in	ADP
cana-2825	11	2	particular	particular	ADJ
cana-2825	11	3	,	,	PUNCT
cana-2825	11	4	contrast	contrast	NOUN
cana-2825	11	5	approaches	approach	NOUN
cana-2825	11	6	based	base	VERB
cana-2825	11	7	on	on	ADP
cana-2825	11	8	neural	neural	ADJ
cana-2825	11	9	networks	network	NOUN
cana-2825	11	10	(	(	PUNCT
cana-2825	11	11	deep	deep	ADJ
cana-2825	11	12	and	and	CCONJ
cana-2825	11	13	shallow	shallow	ADJ
cana-2825	11	14	)	)	PUNCT
cana-2825	11	15	and	and	CCONJ
cana-2825	11	16	multiple	multiple	ADJ
cana-2825	11	17	regression	regression	NOUN
cana-2825	11	18	(	(	PUNCT
cana-2825	11	19	linear	linear	ADJ
cana-2825	11	20	and	and	CCONJ
cana-2825	11	21	non	non	ADJ
cana-2825	11	22	-	-	ADJ
cana-2825	11	23	linear	linear	ADJ
cana-2825	11	24	)	)	PUNCT
cana-2825	11	25	.	.	PUNCT
cana-2825	12	1	the	the	DET
cana-2825	12	2	greatest	great	ADJ
cana-2825	12	3	results	result	NOUN
cana-2825	12	4	are	be	AUX
cana-2825	12	5	obtained	obtain	VERB
cana-2825	12	6	by	by	ADP
cana-2825	12	7	a	a	DET
cana-2825	12	8	deep	deep	ADJ
cana-2825	12	9	neural	neural	ADJ
cana-2825	12	10	network	network	NOUN
cana-2825	12	11	that	that	PRON
cana-2825	12	12	incorporates	incorporate	VERB
cana-2825	12	13	spatial	spatial	ADJ
cana-2825	12	14	sampling	sampling	NOUN
cana-2825	12	15	and	and	CCONJ
cana-2825	12	16	is	be	AUX
cana-2825	12	17	based	base	VERB
cana-2825	12	18	on	on	ADP
cana-2825	12	19	the	the	DET
cana-2825	12	20	stacked	stacked	ADJ
cana-2825	12	21	autoencoder	autoencoder	NOUN
cana-2825	12	22	,	,	PUNCT
cana-2825	12	23	according	accord	VERB
cana-2825	12	24	to	to	ADP
cana-2825	12	25	the	the	DET
cana-2825	12	26	findings	finding	NOUN
cana-2825	12	27	.	.	PUNCT
cana-2825	13	1	keywords	keyword	NOUN
cana-2825	13	2	:	:	PUNCT
cana-2825	13	3	precision	precision	NOUN
cana-2825	13	4	agriculture	agriculture	NOUN
cana-2825	13	5	,	,	PUNCT
cana-2825	13	6	agriculture	agriculture	NOUN
cana-2825	13	7	practices	practice	NOUN
cana-2825	13	8	,	,	PUNCT
cana-2825	13	9	mathematical	mathematical	ADJ
cana-2825	13	10	frameworks	framework	NOUN
cana-2825	13	11	,	,	PUNCT
cana-2825	13	12	yield	yield	NOUN
cana-2825	13	13	,	,	PUNCT
cana-2825	13	14	winter	winter	NOUN
cana-2825	13	15	grains	grain	NOUN
cana-2825	13	16	.	.	PUNCT
cana-2825	14	1	1	1	X
cana-2825	14	2	.	.	X
cana-2825	14	3	introduction	introduction	NOUN
cana-2825	14	4	the	the	DET
cana-2825	14	5	quantity	quantity	NOUN
cana-2825	14	6	of	of	ADP
cana-2825	14	7	fertiliser	fertiliser	NOUN
cana-2825	14	8	derived	derive	VERB
cana-2825	14	9	from	from	ADP
cana-2825	14	10	petroleum	petroleum	NOUN
cana-2825	14	11	that	that	PRON
cana-2825	14	12	is	be	AUX
cana-2825	14	13	wasted	waste	VERB
cana-2825	14	14	has	have	AUX
cana-2825	14	15	greatly	greatly	ADV
cana-2825	14	16	grown	grow	VERB
cana-2825	14	17	in	in	ADP
cana-2825	14	18	recent	recent	ADJ
cana-2825	14	19	years	year	NOUN
cana-2825	14	20	.	.	PUNCT
cana-2825	15	1	the	the	DET
cana-2825	15	2	recent	recent	ADJ
cana-2825	15	3	rise	rise	NOUN
cana-2825	15	4	in	in	ADP
cana-2825	15	5	algal	algal	ADJ
cana-2825	15	6	blooms	bloom	NOUN
cana-2825	15	7	,	,	PUNCT
cana-2825	15	8	which	which	PRON
cana-2825	15	9	cause	cause	VERB
cana-2825	15	10	soil	soil	NOUN
cana-2825	15	11	to	to	PART
cana-2825	15	12	become	become	VERB
cana-2825	15	13	more	more	ADV
cana-2825	15	14	toxic	toxic	ADJ
cana-2825	15	15	,	,	PUNCT
cana-2825	15	16	may	may	AUX
cana-2825	15	17	have	have	VERB
cana-2825	15	18	this	this	DET
cana-2825	15	19	increase	increase	NOUN
cana-2825	15	20	as	as	ADP
cana-2825	15	21	one	one	NUM
cana-2825	15	22	of	of	ADP
cana-2825	15	23	its	its	PRON
cana-2825	15	24	primary	primary	ADJ
cana-2825	15	25	reasons	reason	NOUN
cana-2825	15	26	,	,	PUNCT
cana-2825	15	27	according	accord	VERB
cana-2825	15	28	to	to	ADP
cana-2825	15	29	ecologists	ecologist	NOUN
cana-2825	15	30	.	.	PUNCT
cana-2825	16	1	the	the	DET
cana-2825	16	2	pace	pace	NOUN
cana-2825	16	3	of	of	ADP
cana-2825	16	4	carbon	carbon	NOUN
cana-2825	16	5	storage	storage	NOUN
cana-2825	16	6	in	in	ADP
cana-2825	16	7	farmland	farmland	NOUN
cana-2825	16	8	soil	soil	NOUN
cana-2825	16	9	is	be	AUX
cana-2825	16	10	also	also	ADV
cana-2825	16	11	thought	think	VERB
cana-2825	16	12	to	to	PART
cana-2825	16	13	be	be	AUX
cana-2825	16	14	affected	affect	VERB
cana-2825	16	15	by	by	ADP
cana-2825	16	16	climate	climate	NOUN
cana-2825	16	17	change	change	NOUN
cana-2825	16	18	.	.	PUNCT
cana-2825	17	1	in	in	ADP
cana-2825	17	2	light	light	NOUN
cana-2825	17	3	of	of	ADP
cana-2825	17	4	changes	change	NOUN
cana-2825	17	5	in	in	ADP
cana-2825	17	6	the	the	DET
cana-2825	17	7	climate	climate	NOUN
cana-2825	17	8	and	and	CCONJ
cana-2825	17	9	shorter	short	ADJ
cana-2825	17	10	growing	grow	VERB
cana-2825	17	11	seasons	season	NOUN
cana-2825	17	12	,	,	PUNCT
cana-2825	17	13	which	which	PRON
cana-2825	17	14	are	be	AUX
cana-2825	17	15	more	more	ADV
cana-2825	17	16	relevant	relevant	ADJ
cana-2825	17	17	to	to	ADP
cana-2825	17	18	the	the	DET
cana-2825	17	19	present	present	ADJ
cana-2825	17	20	investigation	investigation	NOUN
cana-2825	17	21	,	,	PUNCT
cana-2825	17	22	farmers	farmer	NOUN
cana-2825	17	23	are	be	AUX
cana-2825	17	24	trying	try	VERB
cana-2825	17	25	to	to	PART
cana-2825	17	26	find	find	VERB
cana-2825	17	27	innovative	innovative	ADJ
cana-2825	17	28	methods	method	NOUN
cana-2825	17	29	to	to	PART
cana-2825	17	30	increase	increase	VERB
cana-2825	17	31	their	their	PRON
cana-2825	17	32	earnings	earning	NOUN
cana-2825	17	33	.	.	PUNCT
cana-2825	18	1	one	one	NUM
cana-2825	18	2	of	of	ADP
cana-2825	18	3	the	the	DET
cana-2825	18	4	main	main	ADJ
cana-2825	18	5	reasons	reason	NOUN
cana-2825	18	6	people	people	NOUN
cana-2825	18	7	work	work	VERB
cana-2825	18	8	is	be	AUX
cana-2825	18	9	for	for	ADP
cana-2825	18	10	the	the	DET
cana-2825	18	11	second	second	ADJ
cana-2825	18	12	reason	reason	NOUN
cana-2825	18	13	.	.	PUNCT
cana-2825	19	1	precision	precision	NOUN
cana-2825	19	2	agriculture	agriculture	NOUN
cana-2825	19	3	draws	draw	VERB
cana-2825	19	4	on	on	ADP
cana-2825	19	5	cutting	cut	VERB
cana-2825	19	6	-	-	PUNCT
cana-2825	19	7	edge	edge	NOUN
cana-2825	19	8	technology	technology	NOUN
cana-2825	19	9	,	,	PUNCT
cana-2825	19	10	generally	generally	ADV
cana-2825	19	11	from	from	ADP
cana-2825	19	12	the	the	DET
cana-2825	19	13	fields	field	NOUN
cana-2825	19	14	of	of	ADP
cana-2825	19	15	engineering	engineering	NOUN
cana-2825	19	16	and	and	CCONJ
cana-2825	19	17	computer	computer	NOUN
cana-2825	19	18	science	science	NOUN
cana-2825	19	19	to	to	PART
cana-2825	19	20	solve	solve	VERB
cana-2825	19	21	these	these	DET
cana-2825	19	22	issues	issue	NOUN
cana-2825	19	23	and	and	CCONJ
cana-2825	19	24	facilitate	facilitate	VERB
cana-2825	19	25	well	well	ADV
cana-2825	19	26	-	-	PUNCT
cana-2825	19	27	informed	inform	VERB
cana-2825	19	28	decision	decision	NOUN
cana-2825	19	29	-	-	PUNCT
cana-2825	19	30	making	making	NOUN
cana-2825	19	31	in	in	ADP
cana-2825	19	32	the	the	DET
cana-2825	19	33	agriculture	agriculture	NOUN
cana-2825	19	34	sector	sector	NOUN
cana-2825	19	35	.	.	PUNCT
cana-2825	20	1	two	two	NUM
cana-2825	20	2	features	feature	NOUN
cana-2825	20	3	of	of	ADP
cana-2825	20	4	precision	precision	NOUN
cana-2825	20	5	agriculture	agriculture	NOUN
cana-2825	20	6	have	have	VERB
cana-2825	20	7	the	the	DET
cana-2825	20	8	potential	potential	NOUN
cana-2825	20	9	to	to	PART
cana-2825	20	10	solve	solve	VERB
cana-2825	20	11	these	these	DET
cana-2825	20	12	problems	problem	NOUN
cana-2825	20	13	.	.	PUNCT
cana-2825	21	1	the	the	DET
cana-2825	21	2	first	first	ADJ
cana-2825	21	3	is	be	AUX
cana-2825	21	4	to	to	PART
cana-2825	21	5	determine	determine	VERB
cana-2825	21	6	the	the	DET
cana-2825	21	7	best	good	ADJ
cana-2825	21	8	fertiliser	fertiliser	NOUN
cana-2825	21	9	rates	rate	NOUN
cana-2825	21	10	and	and	CCONJ
cana-2825	21	11	then	then	ADV
cana-2825	21	12	use	use	VERB
cana-2825	21	13	that	that	DET
cana-2825	21	14	information	information	NOUN
cana-2825	21	15	to	to	PART
cana-2825	21	16	make	make	VERB
cana-2825	21	17	predictions	prediction	NOUN
cana-2825	21	18	that	that	PRON
cana-2825	21	19	will	will	AUX
cana-2825	21	20	help	help	VERB
cana-2825	21	21	farmers	farmer	NOUN
cana-2825	21	22	save	save	VERB
cana-2825	21	23	money	money	NOUN
cana-2825	21	24	and	and	CCONJ
cana-2825	21	25	use	use	VERB
cana-2825	21	26	less	less	ADJ
cana-2825	21	27	fertiliser	fertiliser	NOUN
cana-2825	21	28	.	.	PUNCT
cana-2825	22	1	however	however	ADV
cana-2825	22	2	,	,	PUNCT
cana-2825	22	3	this	this	PRON
cana-2825	22	4	can	can	AUX
cana-2825	22	5	only	only	ADV
cana-2825	22	6	be	be	AUX
cana-2825	22	7	achieved	achieve	VERB
cana-2825	22	8	if	if	SCONJ
cana-2825	22	9	the	the	DET
cana-2825	22	10	yield	yield	NOUN
cana-2825	22	11	and	and	CCONJ
cana-2825	22	12	protein	protein	NOUN
cana-2825	22	13	concentrations	concentration	NOUN
cana-2825	22	14	are	be	AUX
cana-2825	22	15	anticipated	anticipate	VERB
cana-2825	22	16	in	in	ADP
cana-2825	22	17	light	light	NOUN
cana-2825	22	18	of	of	ADP
cana-2825	22	19	weather	weather	NOUN
cana-2825	22	20	conditions	condition	NOUN
cana-2825	22	21	and	and	CCONJ
cana-2825	22	22	the	the	DET
cana-2825	22	23	field	field	NOUN
cana-2825	22	24	's	's	PART
cana-2825	22	25	present	present	ADJ
cana-2825	22	26	and	and	CCONJ
cana-2825	22	27	past	past	ADJ
cana-2825	22	28	characteristics	characteristic	NOUN
cana-2825	22	29	.	.	PUNCT
cana-2825	23	1	that	that	PRON
cana-2825	23	2	brings	bring	VERB
cana-2825	23	3	the	the	DET
cana-2825	23	4	second	second	ADJ
cana-2825	23	5	point	point	NOUN
cana-2825	23	6	and	and	CCONJ
cana-2825	23	7	the	the	DET
cana-2825	23	8	main	main	ADJ
cana-2825	23	9	point	point	NOUN
cana-2825	23	10	of	of	ADP
cana-2825	23	11	this	this	DET
cana-2825	23	12	study	study	NOUN
cana-2825	23	13	.	.	PUNCT
cana-2825	24	1	in	in	ADP
cana-2825	24	2	this	this	DET
cana-2825	24	3	publication	publication	NOUN
cana-2825	24	4	,	,	PUNCT
cana-2825	24	5	the	the	DET
cana-2825	24	6	researchers	researcher	NOUN
cana-2825	24	7	lay	lie	VERB
cana-2825	24	8	out	out	ADP
cana-2825	24	9	their	their	PRON
cana-2825	24	10	strategy	strategy	NOUN
cana-2825	24	11	,	,	PUNCT
cana-2825	24	12	which	which	PRON
cana-2825	24	13	involves	involve	VERB
cana-2825	24	14	using	use	VERB
cana-2825	24	15	machine	machine	NOUN
cana-2825	24	16	learning	learning	NOUN
cana-2825	24	17	methods	method	NOUN
cana-2825	24	18	to	to	PART
cana-2825	24	19	forecast	forecast	VERB
cana-2825	24	20	yield	yield	NOUN
cana-2825	24	21	and	and	CCONJ
cana-2825	24	22	protein	protein	NOUN
cana-2825	24	23	content	content	NOUN
cana-2825	24	24	in	in	ADP
cana-2825	24	25	particular	particular	ADJ
cana-2825	24	26	areas	area	NOUN
cana-2825	24	27	of	of	ADP
cana-2825	24	28	interest	interest	NOUN
cana-2825	24	29	.	.	PUNCT
cana-2825	25	1	a	a	DET
cana-2825	25	2	multitude	multitude	NOUN
cana-2825	25	3	of	of	ADP
cana-2825	25	4	machine	machine	NOUN
cana-2825	25	5	learning	learn	VERB
cana-2825	25	6	fields	field	NOUN
cana-2825	25	7	,	,	PUNCT
cana-2825	25	8	including	include	VERB
cana-2825	25	9	medical	medical	ADJ
cana-2825	25	10	diagnosis	diagnosis	NOUN
cana-2825	25	11	,	,	PUNCT
cana-2825	25	12	forecasting	forecast	VERB
cana-2825	25	13	the	the	DET
cana-2825	25	14	stock	stock	NOUN
cana-2825	25	15	market	market	NOUN
cana-2825	25	16	,	,	PUNCT
cana-2825	25	17	and	and	CCONJ
cana-2825	25	18	natural	natural	ADJ
cana-2825	25	19	language	language	NOUN
cana-2825	25	20	sunithadevi.b2022@gmail.com	sunithadevi.b2022@gmail.com	ADJ
cana-2825	25	21	communications	communication	NOUN
cana-2825	25	22	on	on	ADP
cana-2825	25	23	applied	apply	VERB
cana-2825	25	24	nonlinear	nonlinear	ADJ
cana-2825	25	25	analysis	analysis	NOUN
cana-2825	25	26	issn	issn	NOUN
cana-2825	25	27	:	:	PUNCT
cana-2825	25	28	1074	1074	NUM
cana-2825	25	29	-	-	PUNCT
cana-2825	25	30	133x	133x	NUM
cana-2825	25	31	vol	vol	NOUN
cana-2825	25	32	32	32	NUM
cana-2825	25	33	no	no	NOUN
cana-2825	25	34	.	.	PUNCT
cana-2825	26	1	4s	4s	NUM
cana-2825	26	2	(	(	PUNCT
cana-2825	26	3	2025	2025	NUM
cana-2825	26	4	)	)	PUNCT
cana-2825	26	5	345	345	NUM
cana-2825	26	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	26	7	processing	processing	NOUN
cana-2825	26	8	,	,	PUNCT
cana-2825	26	9	have	have	AUX
cana-2825	26	10	shown	show	VERB
cana-2825	26	11	an	an	DET
cana-2825	26	12	increasing	increase	VERB
cana-2825	26	13	interest	interest	NOUN
cana-2825	26	14	in	in	ADP
cana-2825	26	15	the	the	DET
cana-2825	26	16	use	use	NOUN
cana-2825	26	17	of	of	ADP
cana-2825	26	18	neural	neural	ADJ
cana-2825	26	19	network	network	NOUN
cana-2825	26	20	algorithms	algorithm	NOUN
cana-2825	26	21	,	,	PUNCT
cana-2825	26	22	particularly	particularly	ADV
cana-2825	26	23	within	within	ADP
cana-2825	26	24	the	the	DET
cana-2825	26	25	framework	framework	NOUN
cana-2825	26	26	of	of	ADP
cana-2825	26	27	deep	deep	ADJ
cana-2825	26	28	learning	learning	NOUN
cana-2825	26	29	.	.	PUNCT
cana-2825	27	1	with	with	ADP
cana-2825	27	2	anns	ann	NOUN
cana-2825	27	3	,	,	PUNCT
cana-2825	27	4	the	the	DET
cana-2825	27	5	network	network	NOUN
cana-2825	27	6	's	's	PART
cana-2825	27	7	"	"	PUNCT
cana-2825	27	8	neurones	neurone	NOUN
cana-2825	27	9	"	"	PUNCT
cana-2825	27	10	analyse	analyse	NOUN
cana-2825	27	11	the	the	DET
cana-2825	27	12	input	input	NOUN
cana-2825	27	13	signals	signal	NOUN
cana-2825	27	14	independently	independently	ADV
cana-2825	27	15	and	and	CCONJ
cana-2825	27	16	concurrently	concurrently	ADV
cana-2825	27	17	,	,	PUNCT
cana-2825	27	18	which	which	PRON
cana-2825	27	19	allows	allow	VERB
cana-2825	27	20	them	they	PRON
cana-2825	27	21	to	to	PART
cana-2825	27	22	learn	learn	VERB
cana-2825	27	23	and	and	CCONJ
cana-2825	27	24	recognise	recognise	VERB
cana-2825	27	25	patterns	pattern	NOUN
cana-2825	27	26	from	from	ADP
cana-2825	27	27	various	various	ADJ
cana-2825	27	28	input	input	NOUN
cana-2825	27	29	signals	signal	NOUN
cana-2825	27	30	.	.	PUNCT
cana-2825	28	1	this	this	PRON
cana-2825	28	2	is	be	AUX
cana-2825	28	3	one	one	NUM
cana-2825	28	4	of	of	ADP
cana-2825	28	5	the	the	DET
cana-2825	28	6	most	most	ADV
cana-2825	28	7	intriguing	intriguing	ADJ
cana-2825	28	8	benefits	benefit	NOUN
cana-2825	28	9	of	of	ADP
cana-2825	28	10	anns	ann	NOUN
cana-2825	28	11	.	.	PUNCT
cana-2825	29	1	a	a	DET
cana-2825	29	2	more	more	ADV
cana-2825	29	3	recent	recent	ADJ
cana-2825	29	4	innovation	innovation	NOUN
cana-2825	29	5	is	be	AUX
cana-2825	29	6	the	the	DET
cana-2825	29	7	use	use	NOUN
cana-2825	29	8	of	of	ADP
cana-2825	29	9	anns	anns	NOUN
cana-2825	29	10	in	in	ADP
cana-2825	29	11	precision	precision	NOUN
cana-2825	29	12	agriculture	agriculture	NOUN
cana-2825	29	13	.	.	PUNCT
cana-2825	30	1	there	there	PRON
cana-2825	30	2	are	be	VERB
cana-2825	30	3	two	two	NUM
cana-2825	30	4	main	main	ADJ
cana-2825	30	5	ways	way	NOUN
cana-2825	30	6	to	to	PART
cana-2825	30	7	use	use	VERB
cana-2825	30	8	anns	anns	NOUN
cana-2825	30	9	in	in	ADP
cana-2825	30	10	this	this	DET
cana-2825	30	11	context	context	NOUN
cana-2825	30	12	:	:	PUNCT
cana-2825	30	13	one	one	NUM
cana-2825	30	14	models	model	NOUN
cana-2825	30	15	field	field	NOUN
cana-2825	30	16	attributes	attribute	VERB
cana-2825	30	17	at	at	ADP
cana-2825	30	18	the	the	DET
cana-2825	30	19	local	local	ADJ
cana-2825	30	20	level	level	NOUN
cana-2825	30	21	,	,	PUNCT
cana-2825	30	22	while	while	SCONJ
cana-2825	30	23	the	the	DET
cana-2825	30	24	other	other	ADJ
cana-2825	30	25	expands	expand	VERB
cana-2825	30	26	the	the	DET
cana-2825	30	27	inputs	input	NOUN
cana-2825	30	28	to	to	PART
cana-2825	30	29	include	include	VERB
cana-2825	30	30	spatial	spatial	ADJ
cana-2825	30	31	context	context	NOUN
cana-2825	30	32	.	.	PUNCT
cana-2825	31	1	examine	examine	VERB
cana-2825	31	2	the	the	DET
cana-2825	31	3	differences	difference	NOUN
cana-2825	31	4	and	and	CCONJ
cana-2825	31	5	similarities	similarity	NOUN
cana-2825	31	6	between	between	ADP
cana-2825	31	7	training	train	VERB
cana-2825	31	8	basic	basic	ADJ
cana-2825	31	9	feedforward	feedforward	NOUN
cana-2825	31	10	neural	neural	ADJ
cana-2825	31	11	networks	network	NOUN
cana-2825	31	12	and	and	CCONJ
cana-2825	31	13	stacked	stack	VERB
cana-2825	31	14	autoencoders	autoencoder	NOUN
cana-2825	31	15	,	,	PUNCT
cana-2825	31	16	a	a	DET
cana-2825	31	17	kind	kind	NOUN
cana-2825	31	18	of	of	ADP
cana-2825	31	19	deep	deep	ADJ
cana-2825	31	20	learning	learning	NOUN
cana-2825	31	21	model	model	NOUN
cana-2825	31	22	.	.	PUNCT
cana-2825	32	1	next	next	ADV
cana-2825	32	2	,	,	PUNCT
cana-2825	32	3	review	review	VERB
cana-2825	32	4	the	the	DET
cana-2825	32	5	outcomes	outcome	NOUN
cana-2825	32	6	of	of	ADP
cana-2825	32	7	both	both	CCONJ
cana-2825	32	8	neural	neural	ADJ
cana-2825	32	9	nets	net	NOUN
cana-2825	32	10	about	about	ADP
cana-2825	32	11	multiple	multiple	ADJ
cana-2825	32	12	linear	linear	ADJ
cana-2825	32	13	and	and	CCONJ
cana-2825	32	14	multiple	multiple	ADJ
cana-2825	32	15	nonlinear	nonlinear	ADJ
cana-2825	32	16	regression	regression	NOUN
cana-2825	32	17	models	model	NOUN
cana-2825	32	18	.	.	PUNCT
cana-2825	33	1	researchers	researcher	NOUN
cana-2825	33	2	found	find	VERB
cana-2825	33	3	that	that	SCONJ
cana-2825	33	4	deep	deep	ADJ
cana-2825	33	5	and	and	CCONJ
cana-2825	33	6	shallow	shallow	ADJ
cana-2825	33	7	neural	neural	ADJ
cana-2825	33	8	nets	net	NOUN
cana-2825	33	9	models	model	NOUN
cana-2825	33	10	outperformed	outperform	VERB
cana-2825	33	11	the	the	DET
cana-2825	33	12	more	more	ADV
cana-2825	33	13	conventional	conventional	ADJ
cana-2825	33	14	regression	regression	NOUN
cana-2825	33	15	techniques	technique	NOUN
cana-2825	33	16	.	.	PUNCT
cana-2825	34	1	additionally	additionally	ADV
cana-2825	34	2	,	,	PUNCT
cana-2825	34	3	discovered	discover	VERB
cana-2825	34	4	that	that	SCONJ
cana-2825	34	5	including	include	VERB
cana-2825	34	6	the	the	DET
cana-2825	34	7	geographical	geographical	ADJ
cana-2825	34	8	context	context	NOUN
cana-2825	34	9	results	result	NOUN
cana-2825	34	10	in	in	ADP
cana-2825	34	11	a	a	DET
cana-2825	34	12	statistically	statistically	ADV
cana-2825	34	13	significant	significant	ADJ
cana-2825	34	14	performance	performance	NOUN
cana-2825	34	15	improvement	improvement	NOUN
cana-2825	34	16	.	.	PUNCT
cana-2825	35	1	the	the	DET
cana-2825	35	2	remaining	remain	VERB
cana-2825	35	3	sections	section	NOUN
cana-2825	35	4	of	of	ADP
cana-2825	35	5	the	the	DET
cana-2825	35	6	article	article	NOUN
cana-2825	35	7	are	be	AUX
cana-2825	35	8	organised	organise	VERB
cana-2825	35	9	as	as	SCONJ
cana-2825	35	10	follows	follow	VERB
cana-2825	35	11	.	.	PUNCT
cana-2825	36	1	the	the	DET
cana-2825	36	2	second	second	ADJ
cana-2825	36	3	section	section	NOUN
cana-2825	36	4	discusses	discuss	VERB
cana-2825	36	5	related	related	ADJ
cana-2825	36	6	work	work	NOUN
cana-2825	36	7	.	.	PUNCT
cana-2825	37	1	section	section	NOUN
cana-2825	37	2	3	3	NUM
cana-2825	37	3	delves	delve	VERB
cana-2825	37	4	more	more	ADV
cana-2825	37	5	into	into	ADP
cana-2825	37	6	each	each	PRON
cana-2825	37	7	of	of	ADP
cana-2825	37	8	the	the	DET
cana-2825	37	9	models	model	NOUN
cana-2825	37	10	.	.	PUNCT
cana-2825	38	1	furthermore	furthermore	ADV
cana-2825	38	2	,	,	PUNCT
cana-2825	38	3	this	this	DET
cana-2825	38	4	part	part	NOUN
cana-2825	38	5	gives	give	VERB
cana-2825	38	6	some	some	DET
cana-2825	38	7	history	history	NOUN
cana-2825	38	8	of	of	ADP
cana-2825	38	9	precision	precision	NOUN
cana-2825	38	10	agriculture	agriculture	NOUN
cana-2825	38	11	.	.	PUNCT
cana-2825	39	1	part	part	NOUN
cana-2825	39	2	4	4	NUM
cana-2825	39	3	describes	describe	VERB
cana-2825	39	4	in	in	ADP
cana-2825	39	5	-	-	PUNCT
cana-2825	39	6	depth	depth	NOUN
cana-2825	39	7	experimental	experimental	ADJ
cana-2825	39	8	strategy	strategy	NOUN
cana-2825	39	9	,	,	PUNCT
cana-2825	39	10	experimental	experimental	ADJ
cana-2825	39	11	findings	finding	NOUN
cana-2825	39	12	,	,	PUNCT
cana-2825	39	13	and	and	CCONJ
cana-2825	39	14	analyses	analysis	NOUN
cana-2825	39	15	of	of	ADP
cana-2825	39	16	these	these	DET
cana-2825	39	17	findings	finding	NOUN
cana-2825	39	18	.	.	PUNCT
cana-2825	40	1	lastly	lastly	ADV
cana-2825	40	2	,	,	PUNCT
cana-2825	40	3	section	section	NOUN
cana-2825	40	4	5	5	NUM
cana-2825	40	5	presents	present	VERB
cana-2825	40	6	potential	potential	ADJ
cana-2825	40	7	areas	area	NOUN
cana-2825	40	8	for	for	ADP
cana-2825	40	9	further	further	ADJ
cana-2825	40	10	investigation	investigation	NOUN
cana-2825	40	11	,	,	PUNCT
cana-2825	40	12	and	and	CCONJ
cana-2825	40	13	section	section	NOUN
cana-2825	40	14	6	6	NUM
cana-2825	40	15	provides	provide	VERB
cana-2825	40	16	a	a	DET
cana-2825	40	17	conclusion	conclusion	NOUN
cana-2825	40	18	.	.	PUNCT
cana-2825	41	1	2	2	X
cana-2825	41	2	.	.	X
cana-2825	41	3	related	relate	VERB
cana-2825	41	4	work	work	NOUN
cana-2825	41	5	an	an	DET
cana-2825	41	6	area	area	NOUN
cana-2825	41	7	known	know	VERB
cana-2825	41	8	as	as	ADP
cana-2825	41	9	precision	precision	NOUN
cana-2825	41	10	agriculture	agriculture	NOUN
cana-2825	41	11	(	(	PUNCT
cana-2825	41	12	pa	pa	PROPN
cana-2825	41	13	)	)	PUNCT
cana-2825	41	14	has	have	AUX
cana-2825	41	15	recently	recently	ADV
cana-2825	41	16	attracted	attract	VERB
cana-2825	41	17	a	a	DET
cana-2825	41	18	lot	lot	NOUN
cana-2825	41	19	of	of	ADP
cana-2825	41	20	interest	interest	NOUN
cana-2825	41	21	.	.	PUNCT
cana-2825	42	1	a	a	DET
cana-2825	42	2	growing	grow	VERB
cana-2825	42	3	number	number	NOUN
cana-2825	42	4	of	of	ADP
cana-2825	42	5	studies	study	NOUN
cana-2825	42	6	are	be	AUX
cana-2825	42	7	turning	turn	VERB
cana-2825	42	8	to	to	ADP
cana-2825	42	9	artificial	artificial	ADJ
cana-2825	42	10	neural	neural	ADJ
cana-2825	42	11	networks	network	NOUN
cana-2825	42	12	(	(	PUNCT
cana-2825	42	13	anns	anns	PROPN
cana-2825	42	14	)	)	PUNCT
cana-2825	42	15	to	to	PART
cana-2825	42	16	forecast	forecast	VERB
cana-2825	42	17	agricultural	agricultural	ADJ
cana-2825	42	18	production	production	NOUN
cana-2825	42	19	and	and	CCONJ
cana-2825	42	20	other	other	ADJ
cana-2825	42	21	related	related	ADJ
cana-2825	42	22	outcomes	outcome	NOUN
cana-2825	42	23	,	,	PUNCT
cana-2825	42	24	as	as	SCONJ
cana-2825	42	25	opposed	oppose	VERB
cana-2825	42	26	to	to	ADP
cana-2825	42	27	the	the	DET
cana-2825	42	28	more	more	ADV
cana-2825	42	29	traditional	traditional	ADJ
cana-2825	42	30	linear	linear	NOUN
cana-2825	42	31	and	and	CCONJ
cana-2825	42	32	nonlinear	nonlinear	ADJ
cana-2825	42	33	regression	regression	NOUN
cana-2825	42	34	models	model	NOUN
cana-2825	42	35	.	.	PUNCT
cana-2825	43	1	maximise	maximise	PROPN
cana-2825	43	2	fertilisation	fertilisation	NOUN
cana-2825	43	3	.	.	PUNCT
cana-2825	44	1	an	an	DET
cana-2825	44	2	outline	outline	NOUN
cana-2825	44	3	of	of	ADP
cana-2825	44	4	the	the	DET
cana-2825	44	5	most	most	ADV
cana-2825	44	6	important	important	ADJ
cana-2825	44	7	pa	pa	NOUN
cana-2825	44	8	-	-	PUNCT
cana-2825	44	9	related	relate	VERB
cana-2825	44	10	studies	study	NOUN
cana-2825	44	11	using	use	VERB
cana-2825	44	12	the	the	DET
cana-2825	44	13	models	model	NOUN
cana-2825	44	14	mentioned	mention	VERB
cana-2825	44	15	above	above	ADV
cana-2825	44	16	is	be	AUX
cana-2825	44	17	provided	provide	VERB
cana-2825	44	18	in	in	ADP
cana-2825	44	19	the	the	DET
cana-2825	44	20	following	follow	VERB
cana-2825	44	21	sections	section	NOUN
cana-2825	44	22	.	.	PUNCT
cana-2825	45	1	2.1	2.1	NUM
cana-2825	45	2	models	model	NOUN
cana-2825	45	3	:	:	PUNCT
cana-2825	45	4	linear	linear	ADJ
cana-2825	45	5	and	and	CCONJ
cana-2825	45	6	non	non	ADJ
cana-2825	45	7	-	-	ADJ
cana-2825	45	8	linear	linear	ADJ
cana-2825	45	9	for	for	ADP
cana-2825	45	10	empirical	empirical	ADJ
cana-2825	45	11	model	model	NOUN
cana-2825	45	12	development	development	NOUN
cana-2825	45	13	using	use	VERB
cana-2825	45	14	massive	massive	ADJ
cana-2825	45	15	data	data	NOUN
cana-2825	45	16	sets	set	NOUN
cana-2825	45	17	,	,	PUNCT
cana-2825	45	18	one	one	NUM
cana-2825	45	19	popular	popular	ADJ
cana-2825	45	20	approach	approach	NOUN
cana-2825	45	21	is	be	AUX
cana-2825	45	22	stepwise	stepwise	ADJ
cana-2825	45	23	multiple	multiple	ADJ
cana-2825	45	24	linear	linear	PROPN
cana-2825	45	25	regression	regression	NOUN
cana-2825	45	26	(	(	PUNCT
cana-2825	45	27	smlr	smlr	NOUN
cana-2825	45	28	)	)	PUNCT
cana-2825	45	29	.	.	PUNCT
cana-2825	46	1	when	when	SCONJ
cana-2825	46	2	growing	grow	VERB
cana-2825	46	3	maize	maize	NOUN
cana-2825	46	4	under	under	ADP
cana-2825	46	5	conditions	condition	NOUN
cana-2825	46	6	of	of	ADP
cana-2825	46	7	nitrogen	nitrogen	NOUN
cana-2825	46	8	and	and	CCONJ
cana-2825	46	9	water	water	NOUN
cana-2825	46	10	stress	stress	NOUN
cana-2825	46	11	,	,	PUNCT
cana-2825	46	12	this	this	PRON
cana-2825	46	13	is	be	AUX
cana-2825	46	14	what	what	PRON
cana-2825	46	15	smlr	smlr	NOUN
cana-2825	46	16	uses	use	VERB
cana-2825	46	17	to	to	PART
cana-2825	46	18	predict	predict	VERB
cana-2825	46	19	grain	grain	NOUN
cana-2825	46	20	production	production	NOUN
cana-2825	46	21	.	.	PUNCT
cana-2825	47	1	in	in	ADP
cana-2825	47	2	particular	particular	ADJ
cana-2825	47	3	,	,	PUNCT
cana-2825	47	4	they	they	PRON
cana-2825	47	5	anticipated	anticipate	VERB
cana-2825	47	6	chlorophyll	chlorophyll	NOUN
cana-2825	47	7	meter	meter	NOUN
cana-2825	47	8	values	value	NOUN
cana-2825	47	9	,	,	PUNCT
cana-2825	47	10	grain	grain	NOUN
cana-2825	47	11	nitrogen	nitrogen	NOUN
cana-2825	47	12	concentration	concentration	NOUN
cana-2825	47	13	,	,	PUNCT
cana-2825	47	14	grain	grain	NOUN
cana-2825	47	15	yield	yield	NOUN
cana-2825	47	16	,	,	PUNCT
cana-2825	47	17	plant	plant	NOUN
cana-2825	47	18	nitrogen	nitrogen	NOUN
cana-2825	47	19	,	,	PUNCT
cana-2825	47	20	and	and	CCONJ
cana-2825	47	21	biomass	biomass	NOUN
cana-2825	47	22	by	by	ADP
cana-2825	47	23	applying	apply	VERB
cana-2825	47	24	the	the	DET
cana-2825	47	25	reg	reg	NOUN
cana-2825	47	26	process	process	NOUN
cana-2825	47	27	in	in	ADP
cana-2825	47	28	sas	sas	PROPN
cana-2825	47	29	to	to	ADP
cana-2825	47	30	the	the	DET
cana-2825	47	31	stored	store	VERB
cana-2825	47	32	data	datum	NOUN
cana-2825	47	33	.	.	PUNCT
cana-2825	48	1	to	to	ADP
cana-2825	48	2	what	what	DET
cana-2825	48	3	extent	extent	NOUN
cana-2825	48	4	anns	anns	NOUN
cana-2825	48	5	outperform	outperform	NOUN
cana-2825	48	6	smlr	smlr	NOUN
cana-2825	48	7	is	be	AUX
cana-2825	48	8	something	something	PRON
cana-2825	48	9	they	they	PRON
cana-2825	48	10	investigate	investigate	VERB
cana-2825	48	11	.	.	PUNCT
cana-2825	49	1	the	the	DET
cana-2825	49	2	authors	author	NOUN
cana-2825	49	3	identify	identify	VERB
cana-2825	49	4	three	three	NUM
cana-2825	49	5	significant	significant	ADJ
cana-2825	49	6	disadvantages	disadvantage	NOUN
cana-2825	49	7	associated	associate	VERB
cana-2825	49	8	with	with	ADP
cana-2825	49	9	the	the	DET
cana-2825	49	10	use	use	NOUN
cana-2825	49	11	of	of	ADP
cana-2825	49	12	smlr	smlr	NOUN
cana-2825	49	13	.	.	PUNCT
cana-2825	50	1	initially	initially	ADV
cana-2825	50	2	,	,	PUNCT
cana-2825	50	3	the	the	DET
cana-2825	50	4	foundation	foundation	NOUN
cana-2825	50	5	of	of	ADP
cana-2825	50	6	support	support	NOUN
cana-2825	50	7	vector	vector	NOUN
cana-2825	50	8	load	load	NOUN
cana-2825	50	9	regression	regression	NOUN
cana-2825	50	10	(	(	PUNCT
cana-2825	50	11	smlr	smlr	PROPN
cana-2825	50	12	)	)	PUNCT
cana-2825	50	13	is	be	AUX
cana-2825	50	14	the	the	DET
cana-2825	50	15	assumption	assumption	NOUN
cana-2825	50	16	that	that	SCONJ
cana-2825	50	17	the	the	DET
cana-2825	50	18	response	response	NOUN
cana-2825	50	19	and	and	CCONJ
cana-2825	50	20	input	input	NOUN
cana-2825	50	21	variables	variable	NOUN
cana-2825	50	22	are	be	AUX
cana-2825	50	23	linearly	linearly	ADV
cana-2825	50	24	related	relate	VERB
cana-2825	50	25	.	.	PUNCT
cana-2825	51	1	secondly	secondly	ADV
cana-2825	51	2	,	,	PUNCT
cana-2825	51	3	it	it	PRON
cana-2825	51	4	is	be	AUX
cana-2825	51	5	assumed	assume	VERB
cana-2825	51	6	that	that	SCONJ
cana-2825	51	7	the	the	DET
cana-2825	51	8	noise	noise	NOUN
cana-2825	51	9	included	include	VERB
cana-2825	51	10	in	in	ADP
cana-2825	51	11	the	the	DET
cana-2825	51	12	samples	sample	NOUN
cana-2825	51	13	has	have	VERB
cana-2825	51	14	a	a	DET
cana-2825	51	15	normal	normal	ADJ
cana-2825	51	16	distribution	distribution	NOUN
cana-2825	51	17	.	.	PUNCT
cana-2825	52	1	lastly	lastly	ADV
cana-2825	52	2	,	,	PUNCT
cana-2825	52	3	there	there	PRON
cana-2825	52	4	are	be	VERB
cana-2825	52	5	instances	instance	NOUN
cana-2825	52	6	when	when	SCONJ
cana-2825	52	7	the	the	DET
cana-2825	52	8	model	model	NOUN
cana-2825	52	9	overfits	overfit	NOUN
cana-2825	52	10	,	,	PUNCT
cana-2825	52	11	which	which	PRON
cana-2825	52	12	diminishes	diminish	VERB
cana-2825	52	13	its	its	PRON
cana-2825	52	14	capacity	capacity	NOUN
cana-2825	52	15	to	to	PART
cana-2825	52	16	apply	apply	VERB
cana-2825	52	17	to	to	ADP
cana-2825	52	18	unobserved	unobserved	ADJ
cana-2825	52	19	data	datum	NOUN
cana-2825	52	20	.	.	PUNCT
cana-2825	53	1	nonetheless	nonetheless	ADV
cana-2825	53	2	,	,	PUNCT
cana-2825	53	3	their	their	PRON
cana-2825	53	4	findings	finding	NOUN
cana-2825	53	5	indicate	indicate	VERB
cana-2825	53	6	that	that	SCONJ
cana-2825	53	7	anns	ann	NOUN
cana-2825	53	8	and	and	CCONJ
cana-2825	53	9	smlr	smlr	NOUN
cana-2825	53	10	exhibit	exhibit	VERB
cana-2825	53	11	comparable	comparable	ADJ
cana-2825	53	12	performance	performance	NOUN
cana-2825	53	13	.	.	PUNCT
cana-2825	54	1	due	due	ADP
cana-2825	54	2	to	to	ADP
cana-2825	54	3	their	their	PRON
cana-2825	54	4	ambiguous	ambiguous	ADJ
cana-2825	54	5	findings	finding	NOUN
cana-2825	54	6	,	,	PUNCT
cana-2825	54	7	the	the	DET
cana-2825	54	8	authors	author	NOUN
cana-2825	54	9	stress	stress	VERB
cana-2825	54	10	the	the	DET
cana-2825	54	11	need	need	NOUN
cana-2825	54	12	for	for	ADP
cana-2825	54	13	more	more	ADJ
cana-2825	54	14	studies	study	NOUN
cana-2825	54	15	utilising	utilise	VERB
cana-2825	54	16	both	both	DET
cana-2825	54	17	methods	method	NOUN
cana-2825	54	18	.	.	PUNCT
cana-2825	55	1	2.2	2.2	NUM
cana-2825	55	2	machine	machine	NOUN
cana-2825	55	3	learning	learn	VERB
cana-2825	55	4	machine	machine	NOUN
cana-2825	55	5	learning	learning	NOUN
cana-2825	55	6	has	have	AUX
cana-2825	55	7	facilitated	facilitate	VERB
cana-2825	55	8	comprehensive	comprehensive	ADJ
cana-2825	55	9	study	study	NOUN
cana-2825	55	10	across	across	ADP
cana-2825	55	11	several	several	ADJ
cana-2825	55	12	disciplines	discipline	NOUN
cana-2825	55	13	.	.	PUNCT
cana-2825	56	1	training	train	VERB
cana-2825	56	2	artificial	artificial	ADJ
cana-2825	56	3	neural	neural	ADJ
cana-2825	56	4	networks	network	NOUN
cana-2825	56	5	is	be	AUX
cana-2825	56	6	a	a	DET
cana-2825	56	7	prevalent	prevalent	ADJ
cana-2825	56	8	method	method	NOUN
cana-2825	56	9	in	in	ADP
cana-2825	56	10	machine	machine	NOUN
cana-2825	56	11	learning	learning	NOUN
cana-2825	56	12	and	and	CCONJ
cana-2825	56	13	has	have	AUX
cana-2825	56	14	been	be	AUX
cana-2825	56	15	used	use	VERB
cana-2825	56	16	for	for	ADP
cana-2825	56	17	many	many	ADJ
cana-2825	56	18	biological	biological	ADJ
cana-2825	56	19	and	and	CCONJ
cana-2825	56	20	communications	communication	NOUN
cana-2825	56	21	on	on	ADP
cana-2825	56	22	applied	apply	VERB
cana-2825	56	23	nonlinear	nonlinear	ADJ
cana-2825	56	24	analysis	analysis	NOUN
cana-2825	56	25	issn	issn	NOUN
cana-2825	56	26	:	:	PUNCT
cana-2825	56	27	1074	1074	NUM
cana-2825	56	28	-	-	PUNCT
cana-2825	56	29	133x	133x	NUM
cana-2825	56	30	vol	vol	NOUN
cana-2825	56	31	32	32	NUM
cana-2825	56	32	no	no	NOUN
cana-2825	56	33	.	.	PUNCT
cana-2825	57	1	4s	4s	NUM
cana-2825	57	2	(	(	PUNCT
cana-2825	57	3	2025	2025	NUM
cana-2825	57	4	)	)	PUNCT
cana-2825	57	5	346	346	NUM
cana-2825	57	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	57	7	agricultural	agricultural	ADJ
cana-2825	57	8	challenges	challenge	NOUN
cana-2825	57	9	.	.	PUNCT
cana-2825	58	1	an	an	DET
cana-2825	58	2	intriguing	intriguing	ADJ
cana-2825	58	3	and	and	CCONJ
cana-2825	58	4	beneficial	beneficial	ADJ
cana-2825	58	5	characteristic	characteristic	NOUN
cana-2825	58	6	of	of	ADP
cana-2825	58	7	artificial	artificial	ADJ
cana-2825	58	8	neural	neural	ADJ
cana-2825	58	9	networks	network	NOUN
cana-2825	58	10	(	(	PUNCT
cana-2825	58	11	anns	anns	PROPN
cana-2825	58	12	)	)	PUNCT
cana-2825	58	13	is	be	AUX
cana-2825	58	14	their	their	PRON
cana-2825	58	15	capacity	capacity	NOUN
cana-2825	58	16	to	to	PART
cana-2825	58	17	identify	identify	VERB
cana-2825	58	18	complex	complex	ADJ
cana-2825	58	19	relationships	relationship	NOUN
cana-2825	58	20	among	among	ADP
cana-2825	58	21	input	input	NOUN
cana-2825	58	22	and	and	CCONJ
cana-2825	58	23	response	response	NOUN
cana-2825	58	24	variables	variable	NOUN
cana-2825	58	25	,	,	PUNCT
cana-2825	58	26	without	without	ADP
cana-2825	58	27	the	the	DET
cana-2825	58	28	need	need	NOUN
cana-2825	58	29	of	of	ADP
cana-2825	58	30	pre	pre	ADJ
cana-2825	58	31	-	-	ADJ
cana-2825	58	32	establishing	establishing	ADJ
cana-2825	58	33	limitations	limitation	NOUN
cana-2825	58	34	for	for	ADP
cana-2825	58	35	the	the	DET
cana-2825	58	36	distribution	distribution	NOUN
cana-2825	58	37	of	of	ADP
cana-2825	58	38	samples	sample	NOUN
cana-2825	58	39	of	of	ADP
cana-2825	58	40	information	information	NOUN
cana-2825	58	41	.	.	PUNCT
cana-2825	59	1	this	this	PRON
cana-2825	59	2	facilitates	facilitate	VERB
cana-2825	59	3	the	the	DET
cana-2825	59	4	characterisation	characterisation	NOUN
cana-2825	59	5	of	of	ADP
cana-2825	59	6	intricate	intricate	ADJ
cana-2825	59	7	non	non	ADJ
cana-2825	59	8	-	-	ADJ
cana-2825	59	9	linear	linear	ADJ
cana-2825	59	10	interactions	interaction	NOUN
cana-2825	59	11	often	often	ADV
cana-2825	59	12	seen	see	VERB
cana-2825	59	13	in	in	ADP
cana-2825	59	14	areas	area	NOUN
cana-2825	59	15	like	like	ADP
cana-2825	59	16	pa	pa	PROPN
cana-2825	59	17	,	,	PUNCT
cana-2825	59	18	arising	arise	VERB
cana-2825	59	19	from	from	ADP
cana-2825	59	20	diverse	diverse	ADJ
cana-2825	59	21	crop	crop	NOUN
cana-2825	59	22	conditions	condition	NOUN
cana-2825	59	23	and	and	CCONJ
cana-2825	59	24	several	several	ADJ
cana-2825	59	25	impacting	impact	VERB
cana-2825	59	26	variables	variable	NOUN
cana-2825	59	27	.	.	PUNCT
cana-2825	60	1	research	research	NOUN
cana-2825	60	2	on	on	ADP
cana-2825	60	3	the	the	DET
cana-2825	60	4	application	application	NOUN
cana-2825	60	5	of	of	ADP
cana-2825	60	6	anns	anns	NOUN
cana-2825	60	7	in	in	ADP
cana-2825	60	8	agriculture	agriculture	NOUN
cana-2825	60	9	,	,	PUNCT
cana-2825	60	10	particularly	particularly	ADV
cana-2825	60	11	in	in	ADP
cana-2825	60	12	the	the	DET
cana-2825	60	13	areas	area	NOUN
cana-2825	60	14	of	of	ADP
cana-2825	60	15	yield	yield	NOUN
cana-2825	60	16	prediction	prediction	NOUN
cana-2825	60	17	and	and	CCONJ
cana-2825	60	18	fertilisation	fertilisation	NOUN
cana-2825	60	19	optimisation	optimisation	NOUN
cana-2825	60	20	,	,	PUNCT
cana-2825	60	21	is	be	AUX
cana-2825	60	22	the	the	DET
cana-2825	60	23	primary	primary	ADJ
cana-2825	60	24	emphasis	emphasis	NOUN
cana-2825	60	25	of	of	ADP
cana-2825	60	26	this	this	DET
cana-2825	60	27	section	section	NOUN
cana-2825	60	28	.	.	PUNCT
cana-2825	61	1	summarise	summarise	VERB
cana-2825	61	2	studies	study	NOUN
cana-2825	61	3	that	that	PRON
cana-2825	61	4	have	have	AUX
cana-2825	61	5	effectively	effectively	ADV
cana-2825	61	6	used	use	VERB
cana-2825	61	7	anns	anns	NOUN
cana-2825	61	8	in	in	ADP
cana-2825	61	9	the	the	DET
cana-2825	61	10	field	field	NOUN
cana-2825	61	11	of	of	ADP
cana-2825	61	12	biology	biology	NOUN
cana-2825	61	13	and	and	CCONJ
cana-2825	61	14	agriculture	agriculture	NOUN
cana-2825	61	15	to	to	PART
cana-2825	61	16	get	get	VERB
cana-2825	61	17	a	a	DET
cana-2825	61	18	broader	broad	ADJ
cana-2825	61	19	picture	picture	NOUN
cana-2825	61	20	of	of	ADP
cana-2825	61	21	their	their	PRON
cana-2825	61	22	potential	potential	ADJ
cana-2825	61	23	uses	use	NOUN
cana-2825	61	24	.	.	PUNCT
cana-2825	62	1	to	to	PART
cana-2825	62	2	forecast	forecast	VERB
cana-2825	62	3	yield	yield	NOUN
cana-2825	62	4	,	,	PUNCT
cana-2825	62	5	they	they	PRON
cana-2825	62	6	train	train	VERB
cana-2825	62	7	artificial	artificial	ADJ
cana-2825	62	8	neural	neural	ADJ
cana-2825	62	9	networks	network	NOUN
cana-2825	62	10	in	in	ADP
cana-2825	62	11	various	various	ADJ
cana-2825	62	12	ways	way	NOUN
cana-2825	62	13	using	use	VERB
cana-2825	62	14	the	the	DET
cana-2825	62	15	same	same	ADJ
cana-2825	62	16	dataset	dataset	NOUN
cana-2825	62	17	.	.	PUNCT
cana-2825	63	1	to	to	PART
cana-2825	63	2	find	find	VERB
cana-2825	63	3	the	the	DET
cana-2825	63	4	best	good	ADJ
cana-2825	63	5	approach	approach	NOUN
cana-2825	63	6	,	,	PUNCT
cana-2825	63	7	they	they	PRON
cana-2825	63	8	prioritise	prioritise	VERB
cana-2825	63	9	features	feature	VERB
cana-2825	63	10	such	such	ADJ
cana-2825	63	11	as	as	ADP
cana-2825	63	12	outlier	outlier	NOUN
cana-2825	63	13	rejection	rejection	NOUN
cana-2825	63	14	,	,	PUNCT
cana-2825	63	15	test	test	NOUN
cana-2825	63	16	set	set	NOUN
cana-2825	63	17	generalisability	generalisability	NOUN
cana-2825	63	18	,	,	PUNCT
cana-2825	63	19	and	and	CCONJ
cana-2825	63	20	training	training	NOUN
cana-2825	63	21	accuracy	accuracy	NOUN
cana-2825	63	22	.	.	PUNCT
cana-2825	64	1	for	for	ADP
cana-2825	64	2	their	their	PRON
cana-2825	64	3	training	training	NOUN
cana-2825	64	4	strategies	strategy	NOUN
cana-2825	64	5	,	,	PUNCT
cana-2825	64	6	the	the	DET
cana-2825	64	7	authors	author	NOUN
cana-2825	64	8	considered	consider	VERB
cana-2825	64	9	backpropagation	backpropagation	NOUN
cana-2825	64	10	as	as	ADV
cana-2825	64	11	well	well	ADV
cana-2825	64	12	as	as	ADP
cana-2825	64	13	without	without	ADP
cana-2825	64	14	weight	weight	NOUN
cana-2825	64	15	decay	decay	NOUN
cana-2825	64	16	,	,	PUNCT
cana-2825	64	17	in	in	ADP
cana-2825	64	18	addition	addition	NOUN
cana-2825	64	19	to	to	ADP
cana-2825	64	20	quick	quick	ADJ
cana-2825	64	21	prop	prop	NOUN
cana-2825	64	22	and	and	CCONJ
cana-2825	64	23	r	r	NOUN
cana-2825	64	24	prop	prop	NOUN
cana-2825	64	25	.	.	PUNCT
cana-2825	65	1	the	the	DET
cana-2825	65	2	results	result	NOUN
cana-2825	65	3	showed	show	VERB
cana-2825	65	4	that	that	SCONJ
cana-2825	65	5	r	r	NOUN
cana-2825	65	6	prop	prop	NOUN
cana-2825	65	7	,	,	PUNCT
cana-2825	65	8	as	as	ADP
cana-2825	65	9	a	a	DET
cana-2825	65	10	learning	learning	NOUN
cana-2825	65	11	strategy	strategy	NOUN
cana-2825	65	12	,	,	PUNCT
cana-2825	65	13	was	be	AUX
cana-2825	65	14	marginally	marginally	ADV
cana-2825	65	15	more	more	ADV
cana-2825	65	16	effective	effective	ADJ
cana-2825	65	17	than	than	ADP
cana-2825	65	18	backpropagation	backpropagation	NOUN
cana-2825	65	19	,	,	PUNCT
cana-2825	65	20	and	and	CCONJ
cana-2825	65	21	that	that	SCONJ
cana-2825	65	22	any	any	DET
cana-2825	65	23	kind	kind	NOUN
cana-2825	65	24	of	of	ADP
cana-2825	65	25	training	training	NOUN
cana-2825	65	26	and	and	CCONJ
cana-2825	65	27	learning	learning	NOUN
cana-2825	65	28	beat	beat	VERB
cana-2825	65	29	the	the	DET
cana-2825	65	30	linear	linear	ADJ
cana-2825	65	31	method	method	NOUN
cana-2825	65	32	.	.	PUNCT
cana-2825	66	1	in	in	ADP
cana-2825	66	2	fertilisation	fertilisation	NOUN
cana-2825	66	3	models	model	NOUN
cana-2825	66	4	,	,	PUNCT
cana-2825	66	5	they	they	PRON
cana-2825	66	6	added	add	VERB
cana-2825	66	7	a	a	DET
cana-2825	66	8	group	group	NOUN
cana-2825	66	9	of	of	ADP
cana-2825	66	10	feedforward	feedforward	NOUN
cana-2825	66	11	anns	ann	NOUN
cana-2825	66	12	.	.	PUNCT
cana-2825	67	1	they	they	PRON
cana-2825	67	2	assert	assert	VERB
cana-2825	67	3	that	that	SCONJ
cana-2825	67	4	while	while	SCONJ
cana-2825	67	5	utilising	utilise	VERB
cana-2825	67	6	a	a	DET
cana-2825	67	7	single	single	ADJ
cana-2825	67	8	feed	feed	NOUN
cana-2825	67	9	-	-	PUNCT
cana-2825	67	10	forward	forward	NOUN
cana-2825	67	11	network	network	NOUN
cana-2825	67	12	in	in	ADP
cana-2825	67	13	this	this	DET
cana-2825	67	14	scenario	scenario	NOUN
cana-2825	67	15	,	,	PUNCT
cana-2825	67	16	there	there	PRON
cana-2825	67	17	are	be	VERB
cana-2825	67	18	two	two	NUM
cana-2825	67	19	typical	typical	ADJ
cana-2825	67	20	problems	problem	NOUN
cana-2825	67	21	.	.	PUNCT
cana-2825	68	1	initially	initially	ADV
cana-2825	68	2	,	,	PUNCT
cana-2825	68	3	they	they	PRON
cana-2825	68	4	discovered	discover	VERB
cana-2825	68	5	that	that	SCONJ
cana-2825	68	6	if	if	SCONJ
cana-2825	68	7	a	a	DET
cana-2825	68	8	maximum	maximum	ADJ
cana-2825	68	9	goal	goal	NOUN
cana-2825	68	10	yield	yield	NOUN
cana-2825	68	11	is	be	AUX
cana-2825	68	12	assigned	assign	VERB
cana-2825	68	13	before	before	ADP
cana-2825	68	14	to	to	PART
cana-2825	68	15	computation	computation	VERB
cana-2825	68	16	,	,	PUNCT
cana-2825	68	17	there	there	PRON
cana-2825	68	18	would	would	AUX
cana-2825	68	19	be	be	AUX
cana-2825	68	20	a	a	DET
cana-2825	68	21	significant	significant	ADJ
cana-2825	68	22	mistake	mistake	NOUN
cana-2825	68	23	in	in	ADP
cana-2825	68	24	the	the	DET
cana-2825	68	25	fertilisation	fertilisation	NOUN
cana-2825	68	26	rate	rate	NOUN
cana-2825	68	27	calculations	calculation	NOUN
cana-2825	68	28	.	.	PUNCT
cana-2825	69	1	secondly	secondly	ADV
cana-2825	69	2	,	,	PUNCT
cana-2825	69	3	they	they	PRON
cana-2825	69	4	think	think	VERB
cana-2825	69	5	that	that	SCONJ
cana-2825	69	6	their	their	PRON
cana-2825	69	7	model	model	NOUN
cana-2825	69	8	's	's	PART
cana-2825	69	9	predicting	predict	VERB
cana-2825	69	10	accuracy	accuracy	NOUN
cana-2825	69	11	and	and	CCONJ
cana-2825	69	12	generalisation	generalisation	NOUN
cana-2825	69	13	ability	ability	NOUN
cana-2825	69	14	are	be	AUX
cana-2825	69	15	constrained	constrain	VERB
cana-2825	69	16	when	when	SCONJ
cana-2825	69	17	it	it	PRON
cana-2825	69	18	uses	use	VERB
cana-2825	69	19	a	a	DET
cana-2825	69	20	single	single	ADJ
cana-2825	69	21	ann	ann	PROPN
cana-2825	69	22	.	.	PUNCT
cana-2825	70	1	the	the	DET
cana-2825	70	2	researchers	researcher	NOUN
cana-2825	70	3	suggested	suggest	VERB
cana-2825	70	4	employing	employ	VERB
cana-2825	70	5	an	an	DET
cana-2825	70	6	ann	ann	NOUN
cana-2825	70	7	with	with	ADP
cana-2825	70	8	yield	yield	NOUN
cana-2825	70	9	as	as	ADP
cana-2825	70	10	the	the	DET
cana-2825	70	11	output	output	NOUN
cana-2825	70	12	and	and	CCONJ
cana-2825	70	13	nutrient	nutrient	NOUN
cana-2825	70	14	concentration	concentration	NOUN
cana-2825	70	15	and	and	CCONJ
cana-2825	70	16	fertilisation	fertilisation	NOUN
cana-2825	70	17	rate	rate	NOUN
cana-2825	70	18	as	as	ADP
cana-2825	70	19	the	the	DET
cana-2825	70	20	input	input	NOUN
cana-2825	70	21	.	.	PUNCT
cana-2825	71	1	using	use	VERB
cana-2825	71	2	a	a	DET
cana-2825	71	3	bagging	bagging	NOUN
cana-2825	71	4	approach	approach	NOUN
cana-2825	71	5	,	,	PUNCT
cana-2825	71	6	they	they	PRON
cana-2825	71	7	trained	train	VERB
cana-2825	71	8	multiple	multiple	ADJ
cana-2825	71	9	neural	neural	ADJ
cana-2825	71	10	networks	network	NOUN
cana-2825	71	11	using	use	VERB
cana-2825	71	12	backpropagation	backpropagation	NOUN
cana-2825	71	13	.	.	PUNCT
cana-2825	72	1	then	then	ADV
cana-2825	72	2	,	,	PUNCT
cana-2825	72	3	they	they	PRON
cana-2825	72	4	clustered	cluster	VERB
cana-2825	72	5	the	the	DET
cana-2825	72	6	networks	network	NOUN
cana-2825	72	7	using	use	VERB
cana-2825	72	8	k	k	NOUN
cana-2825	72	9	-	-	PUNCT
cana-2825	72	10	means	means	NOUN
cana-2825	72	11	.	.	PUNCT
cana-2825	73	1	the	the	DET
cana-2825	73	2	next	next	ADJ
cana-2825	73	3	step	step	NOUN
cana-2825	73	4	in	in	ADP
cana-2825	73	5	assembling	assemble	VERB
cana-2825	73	6	a	a	DET
cana-2825	73	7	group	group	NOUN
cana-2825	73	8	of	of	ADP
cana-2825	73	9	anns	anns	NOUN
cana-2825	73	10	was	be	AUX
cana-2825	73	11	to	to	PART
cana-2825	73	12	choose	choose	VERB
cana-2825	73	13	a	a	DET
cana-2825	73	14	single	single	ADJ
cana-2825	73	15	network	network	NOUN
cana-2825	73	16	that	that	PRON
cana-2825	73	17	exemplified	exemplify	VERB
cana-2825	73	18	each	each	DET
cana-2825	73	19	cluster	cluster	NOUN
cana-2825	73	20	.	.	PUNCT
cana-2825	74	1	using	use	VERB
cana-2825	74	2	the	the	DET
cana-2825	74	3	lagrange	lagrange	NOUN
cana-2825	74	4	multiplier	multipli	ADJ
cana-2825	74	5	approach	approach	NOUN
cana-2825	74	6	,	,	PUNCT
cana-2825	74	7	which	which	PRON
cana-2825	74	8	is	be	AUX
cana-2825	74	9	connected	connect	VERB
cana-2825	74	10	with	with	ADP
cana-2825	74	11	constraints	constraint	NOUN
cana-2825	74	12	that	that	PRON
cana-2825	74	13	require	require	VERB
cana-2825	74	14	the	the	DET
cana-2825	74	15	weights	weight	NOUN
cana-2825	74	16	to	to	PART
cana-2825	74	17	add	add	VERB
cana-2825	74	18	to	to	ADP
cana-2825	74	19	one	one	NUM
cana-2825	74	20	,	,	PUNCT
cana-2825	74	21	they	they	PRON
cana-2825	74	22	calculated	calculate	VERB
cana-2825	74	23	the	the	DET
cana-2825	74	24	ensemble	ensemble	NOUN
cana-2825	74	25	's	's	PART
cana-2825	74	26	combining	combine	VERB
cana-2825	74	27	weights	weight	NOUN
cana-2825	74	28	.	.	PUNCT
cana-2825	75	1	then	then	ADV
cana-2825	75	2	,	,	PUNCT
cana-2825	75	3	using	use	VERB
cana-2825	75	4	the	the	DET
cana-2825	75	5	ensemble	ensemble	NOUN
cana-2825	75	6	's	's	PART
cana-2825	75	7	output	output	NOUN
cana-2825	75	8	as	as	ADP
cana-2825	75	9	a	a	DET
cana-2825	75	10	basis	basis	NOUN
cana-2825	75	11	,	,	PUNCT
cana-2825	75	12	they	they	PRON
cana-2825	75	13	defined	define	VERB
cana-2825	75	14	a	a	DET
cana-2825	75	15	nonlinear	nonlinear	ADJ
cana-2825	75	16	objective	objective	ADJ
cana-2825	75	17	function	function	NOUN
cana-2825	75	18	and	and	CCONJ
cana-2825	75	19	used	use	VERB
cana-2825	75	20	nonlinear	nonlinear	ADJ
cana-2825	75	21	programming	programming	NOUN
cana-2825	75	22	to	to	PART
cana-2825	75	23	optimise	optimise	VERB
cana-2825	75	24	the	the	DET
cana-2825	75	25	rates	rate	NOUN
cana-2825	75	26	of	of	ADP
cana-2825	75	27	fertiliser	fertiliser	NOUN
cana-2825	75	28	delivery	delivery	NOUN
cana-2825	75	29	.	.	PUNCT
cana-2825	76	1	improvements	improvement	NOUN
cana-2825	76	2	in	in	ADP
cana-2825	76	3	using	use	VERB
cana-2825	76	4	anns	ann	NOUN
cana-2825	76	5	for	for	ADP
cana-2825	76	6	pa	pa	PROPN
cana-2825	76	7	have	have	AUX
cana-2825	76	8	been	be	AUX
cana-2825	76	9	substantial	substantial	ADJ
cana-2825	76	10	since	since	SCONJ
cana-2825	76	11	the	the	DET
cana-2825	76	12	aforementioned	aforementioned	ADJ
cana-2825	76	13	studies	study	NOUN
cana-2825	76	14	.	.	PUNCT
cana-2825	77	1	to	to	PART
cana-2825	77	2	determine	determine	VERB
cana-2825	77	3	the	the	DET
cana-2825	77	4	optimal	optimal	ADJ
cana-2825	77	5	crop	crop	NOUN
cana-2825	77	6	for	for	ADP
cana-2825	77	7	a	a	DET
cana-2825	77	8	given	give	VERB
cana-2825	77	9	field	field	NOUN
cana-2825	77	10	given	give	VERB
cana-2825	77	11	a	a	DET
cana-2825	77	12	variety	variety	NOUN
cana-2825	77	13	of	of	ADP
cana-2825	77	14	soil	soil	NOUN
cana-2825	77	15	and	and	CCONJ
cana-2825	77	16	atmospheric	atmospheric	ADJ
cana-2825	77	17	conditions	condition	NOUN
cana-2825	77	18	,	,	PUNCT
cana-2825	77	19	they	they	PRON
cana-2825	77	20	used	use	VERB
cana-2825	77	21	a	a	DET
cana-2825	77	22	feed	feed	NOUN
cana-2825	77	23	-	-	PUNCT
cana-2825	77	24	forward	forward	NOUN
cana-2825	77	25	neural	neural	ADJ
cana-2825	77	26	network	network	NOUN
cana-2825	77	27	trained	train	VERB
cana-2825	77	28	using	use	VERB
cana-2825	77	29	backpropagation	backpropagation	NOUN
cana-2825	77	30	.	.	PUNCT
cana-2825	78	1	temperature	temperature	NOUN
cana-2825	78	2	,	,	PUNCT
cana-2825	78	3	precipitation	precipitation	NOUN
cana-2825	78	4	,	,	PUNCT
cana-2825	78	5	ph	ph	NOUN
cana-2825	78	6	,	,	PUNCT
cana-2825	78	7	nitrogen	nitrogen	NOUN
cana-2825	78	8	,	,	PUNCT
cana-2825	78	9	and	and	CCONJ
cana-2825	78	10	potassium	potassium	NOUN
cana-2825	78	11	levels	level	NOUN
cana-2825	78	12	were	be	AUX
cana-2825	78	13	among	among	ADP
cana-2825	78	14	the	the	DET
cana-2825	78	15	input	input	NOUN
cana-2825	78	16	characteristics	characteristic	NOUN
cana-2825	78	17	they	they	PRON
cana-2825	78	18	used	use	VERB
cana-2825	78	19	.	.	PUNCT
cana-2825	79	1	in	in	ADP
cana-2825	79	2	addition	addition	NOUN
cana-2825	79	3	,	,	PUNCT
cana-2825	79	4	they	they	PRON
cana-2825	79	5	foretold	foretell	VERB
cana-2825	79	6	the	the	DET
cana-2825	79	7	optimal	optimal	ADJ
cana-2825	79	8	fertiliser	fertiliser	NOUN
cana-2825	79	9	rate	rate	NOUN
cana-2825	79	10	that	that	PRON
cana-2825	79	11	would	would	AUX
cana-2825	79	12	benefit	benefit	VERB
cana-2825	79	13	the	the	DET
cana-2825	79	14	harvest	harvest	NOUN
cana-2825	79	15	.	.	PUNCT
cana-2825	80	1	for	for	ADP
cana-2825	80	2	farmers	farmer	NOUN
cana-2825	80	3	without	without	ADP
cana-2825	80	4	access	access	NOUN
cana-2825	80	5	to	to	ADP
cana-2825	80	6	costly	costly	ADJ
cana-2825	80	7	soil	soil	NOUN
cana-2825	80	8	testing	testing	NOUN
cana-2825	80	9	equipment	equipment	NOUN
cana-2825	80	10	,	,	PUNCT
cana-2825	80	11	their	their	PRON
cana-2825	80	12	projections	projection	NOUN
cana-2825	80	13	were	be	AUX
cana-2825	80	14	a	a	DET
cana-2825	80	15	lifesaver	lifesaver	NOUN
cana-2825	80	16	.	.	PUNCT
cana-2825	81	1	the	the	DET
cana-2825	81	2	findings	finding	NOUN
cana-2825	81	3	revealed	reveal	VERB
cana-2825	81	4	quite	quite	ADV
cana-2825	81	5	accurate	accurate	ADJ
cana-2825	81	6	forecasts	forecast	NOUN
cana-2825	81	7	,	,	PUNCT
cana-2825	81	8	which	which	PRON
cana-2825	81	9	might	might	AUX
cana-2825	81	10	be	be	AUX
cana-2825	81	11	of	of	ADP
cana-2825	81	12	great	great	ADJ
cana-2825	81	13	assistance	assistance	NOUN
cana-2825	81	14	to	to	ADP
cana-2825	81	15	these	these	DET
cana-2825	81	16	farmers	farmer	NOUN
cana-2825	81	17	.	.	PUNCT
cana-2825	82	1	the	the	DET
cana-2825	82	2	ndvi	ndvi	NOUN
cana-2825	82	3	,	,	PUNCT
cana-2825	82	4	water	water	NOUN
cana-2825	82	5	stress	stress	PROPN
cana-2825	82	6	index	index	PROPN
cana-2825	82	7	,	,	PUNCT
cana-2825	82	8	canopy	canopy	NOUN
cana-2825	82	9	surface	surface	NOUN
cana-2825	82	10	temperature	temperature	NOUN
cana-2825	82	11	,	,	PUNCT
cana-2825	82	12	and	and	CCONJ
cana-2825	82	13	absorbed	absorb	VERB
cana-2825	82	14	photosynthetically	photosynthetically	ADV
cana-2825	82	15	active	active	ADJ
cana-2825	82	16	radiation	radiation	NOUN
cana-2825	82	17	are	be	AUX
cana-2825	82	18	the	the	DET
cana-2825	82	19	inputs	input	NOUN
cana-2825	82	20	used	use	VERB
cana-2825	82	21	by	by	ADP
cana-2825	82	22	their	their	PRON
cana-2825	82	23	support	support	NOUN
cana-2825	82	24	vector	vector	NOUN
cana-2825	82	25	regressor	regressor	NOUN
cana-2825	82	26	and	and	CCONJ
cana-2825	82	27	dnn	dnn	PROPN
cana-2825	82	28	.	.	PUNCT
cana-2825	83	1	there	there	PRON
cana-2825	83	2	has	have	AUX
cana-2825	83	3	been	be	AUX
cana-2825	83	4	the	the	DET
cana-2825	83	5	application	application	NOUN
cana-2825	83	6	of	of	ADP
cana-2825	83	7	a	a	DET
cana-2825	83	8	deep	deep	ADJ
cana-2825	83	9	neural	neural	ADJ
cana-2825	83	10	net	net	NOUN
cana-2825	83	11	.	.	PUNCT
cana-2825	84	1	their	their	PRON
cana-2825	84	2	dnn	dnn	PROPN
cana-2825	84	3	and	and	CCONJ
cana-2825	84	4	svr	svr	PROPN
cana-2825	84	5	are	be	AUX
cana-2825	84	6	fed	feed	VERB
cana-2825	84	7	data	datum	NOUN
cana-2825	84	8	on	on	ADP
cana-2825	84	9	water	water	NOUN
cana-2825	84	10	stress	stress	PROPN
cana-2825	84	11	index	index	PROPN
cana-2825	84	12	,	,	PUNCT
cana-2825	84	13	canopy	canopy	NOUN
cana-2825	84	14	surface	surface	NOUN
cana-2825	84	15	temperature	temperature	NOUN
cana-2825	84	16	,	,	PUNCT
cana-2825	84	17	absorption	absorption	NOUN
cana-2825	84	18	photosynthetically	photosynthetically	ADV
cana-2825	84	19	active	active	ADJ
cana-2825	84	20	radiation	radiation	NOUN
cana-2825	84	21	,	,	PUNCT
cana-2825	84	22	and	and	CCONJ
cana-2825	84	23	normalised	normalise	VERB
cana-2825	84	24	difference	difference	NOUN
cana-2825	84	25	vegetation	vegetation	NOUN
cana-2825	84	26	index	index	NOUN
cana-2825	84	27	(	(	PUNCT
cana-2825	84	28	ndvi	ndvi	NOUN
cana-2825	84	29	)	)	PUNCT
cana-2825	84	30	.	.	PUNCT
cana-2825	85	1	by	by	ADP
cana-2825	85	2	using	use	VERB
cana-2825	85	3	a	a	DET
cana-2825	85	4	cnn	cnn	NOUN
cana-2825	85	5	and	and	CCONJ
cana-2825	85	6	a	a	DET
cana-2825	85	7	long	long	ADJ
cana-2825	85	8	-	-	PUNCT
cana-2825	85	9	short	short	ADJ
cana-2825	85	10	term	term	NOUN
cana-2825	85	11	memory	memory	NOUN
cana-2825	85	12	net	net	NOUN
cana-2825	85	13	for	for	ADP
cana-2825	85	14	the	the	DET
cana-2825	85	15	sorting	sorting	NOUN
cana-2825	85	16	of	of	ADP
cana-2825	85	17	histograms	histogram	NOUN
cana-2825	85	18	formed	form	VERB
cana-2825	85	19	from	from	ADP
cana-2825	85	20	rarely	rarely	ADV
cana-2825	85	21	sensed	sense	VERB
cana-2825	85	22	pictures	picture	NOUN
cana-2825	85	23	,	,	PUNCT
cana-2825	85	24	the	the	DET
cana-2825	85	25	dnn	dnn	PROPN
cana-2825	85	26	can	can	AUX
cana-2825	85	27	attain	attain	VERB
cana-2825	85	28	rmse	rmse	ADJ
cana-2825	85	29	values	value	NOUN
cana-2825	85	30	of	of	ADP
cana-2825	85	31	about	about	ADP
cana-2825	85	32	for	for	ADP
cana-2825	85	33	maize	maize	NOUN
cana-2825	85	34	yield	yield	NOUN
cana-2825	85	35	prediction	prediction	NOUN
cana-2825	85	36	,	,	PUNCT
cana-2825	85	37	while	while	SCONJ
cana-2825	85	38	the	the	DET
cana-2825	85	39	svr	svr	PROPN
cana-2825	85	40	does	do	VERB
cana-2825	85	41	not	not	PART
cana-2825	85	42	.	.	PUNCT
cana-2825	86	1	in	in	ADP
cana-2825	86	2	terms	term	NOUN
cana-2825	86	3	of	of	ADP
cana-2825	86	4	total	total	ADJ
cana-2825	86	5	rmse	rmse	ADJ
cana-2825	86	6	values	value	NOUN
cana-2825	86	7	,	,	PUNCT
cana-2825	86	8	the	the	DET
cana-2825	86	9	cnn	cnn	PROPN
cana-2825	86	10	performs	perform	VERB
cana-2825	86	11	the	the	DET
cana-2825	86	12	best	good	ADJ
cana-2825	86	13	.	.	PUNCT
cana-2825	87	1	communications	communication	NOUN
cana-2825	87	2	on	on	ADP
cana-2825	87	3	applied	apply	VERB
cana-2825	87	4	nonlinear	nonlinear	ADJ
cana-2825	87	5	analysis	analysis	NOUN
cana-2825	87	6	issn	issn	NOUN
cana-2825	87	7	:	:	PUNCT
cana-2825	87	8	1074	1074	NUM
cana-2825	87	9	-	-	PUNCT
cana-2825	87	10	133x	133x	NUM
cana-2825	87	11	vol	vol	NOUN
cana-2825	87	12	32	32	NUM
cana-2825	87	13	no	no	NOUN
cana-2825	87	14	.	.	PUNCT
cana-2825	88	1	4s	4s	NUM
cana-2825	88	2	(	(	PUNCT
cana-2825	88	3	2025	2025	NUM
cana-2825	88	4	)	)	PUNCT
cana-2825	88	5	347	347	NUM
cana-2825	88	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	88	7	to	to	PART
cana-2825	88	8	evaluate	evaluate	VERB
cana-2825	88	9	measurement	measurement	NOUN
cana-2825	88	10	data	datum	NOUN
cana-2825	88	11	,	,	PUNCT
cana-2825	88	12	examine	examine	VERB
cana-2825	88	13	sensor	sensor	NOUN
cana-2825	88	14	information	information	NOUN
cana-2825	88	15	,	,	PUNCT
cana-2825	88	16	and	and	CCONJ
cana-2825	88	17	update	update	VERB
cana-2825	88	18	basic	basic	ADJ
cana-2825	88	19	knowledge	knowledge	NOUN
cana-2825	88	20	,	,	PUNCT
cana-2825	88	21	data	data	NOUN
cana-2825	88	22	mining	mining	NOUN
cana-2825	88	23	—	—	PUNCT
cana-2825	88	24	a	a	DET
cana-2825	88	25	distinct	distinct	ADJ
cana-2825	88	26	area	area	NOUN
cana-2825	88	27	of	of	ADP
cana-2825	88	28	study	study	NOUN
cana-2825	88	29	—	—	PUNCT
cana-2825	88	30	often	often	ADV
cana-2825	88	31	employs	employ	VERB
cana-2825	88	32	methods	method	NOUN
cana-2825	88	33	based	base	VERB
cana-2825	88	34	on	on	ADP
cana-2825	88	35	supervised	supervised	ADJ
cana-2825	88	36	self	self	NOUN
cana-2825	88	37	-	-	PUNCT
cana-2825	88	38	organising	organise	VERB
cana-2825	88	39	maps	map	NOUN
cana-2825	88	40	.	.	PUNCT
cana-2825	89	1	the	the	DET
cana-2825	89	2	model	model	NOUN
cana-2825	89	3	's	's	PART
cana-2825	89	4	input	input	NOUN
cana-2825	89	5	nodes	node	NOUN
cana-2825	89	6	,	,	PUNCT
cana-2825	89	7	according	accord	VERB
cana-2825	89	8	to	to	ADP
cana-2825	89	9	their	their	PRON
cana-2825	89	10	proposal	proposal	NOUN
cana-2825	89	11	,	,	PUNCT
cana-2825	89	12	would	would	AUX
cana-2825	89	13	represent	represent	VERB
cana-2825	89	14	the	the	DET
cana-2825	89	15	primary	primary	ADJ
cana-2825	89	16	components	component	NOUN
cana-2825	89	17	of	of	ADP
cana-2825	89	18	grain	grain	NOUN
cana-2825	89	19	crop	crop	NOUN
cana-2825	89	20	production	production	NOUN
cana-2825	89	21	.	.	PUNCT
cana-2825	90	1	using	use	VERB
cana-2825	90	2	neural	neural	ADJ
cana-2825	90	3	networks	network	NOUN
cana-2825	90	4	to	to	PART
cana-2825	90	5	forecast	forecast	VERB
cana-2825	90	6	wheat	wheat	NOUN
cana-2825	90	7	yield	yield	NOUN
cana-2825	90	8	using	use	VERB
cana-2825	90	9	publicly	publicly	ADV
cana-2825	90	10	accessible	accessible	ADJ
cana-2825	90	11	,	,	PUNCT
cana-2825	90	12	but	but	CCONJ
cana-2825	90	13	often	often	ADV
cana-2825	90	14	of	of	ADP
cana-2825	90	15	poor	poor	ADJ
cana-2825	90	16	quality	quality	NOUN
cana-2825	90	17	,	,	PUNCT
cana-2825	90	18	in	in	ADP
cana-2825	90	19	-	-	PUNCT
cana-2825	90	20	season	season	NOUN
cana-2825	90	21	data	datum	NOUN
cana-2825	90	22	,	,	PUNCT
cana-2825	90	23	the	the	DET
cana-2825	90	24	model	model	NOUN
cana-2825	90	25	categorised	categorise	VERB
cana-2825	90	26	the	the	DET
cana-2825	90	27	data	datum	NOUN
cana-2825	90	28	to	to	PART
cana-2825	90	29	forecast	forecast	VERB
cana-2825	90	30	productivity	productivity	NOUN
cana-2825	90	31	and	and	CCONJ
cana-2825	90	32	wheat	wheat	NOUN
cana-2825	90	33	output	output	NOUN
cana-2825	90	34	.	.	PUNCT
cana-2825	91	1	to	to	PART
cana-2825	91	2	maximise	maximise	VERB
cana-2825	91	3	the	the	DET
cana-2825	91	4	effectiveness	effectiveness	NOUN
cana-2825	91	5	of	of	ADP
cana-2825	91	6	fertiliser	fertiliser	NOUN
cana-2825	91	7	,	,	PUNCT
cana-2825	91	8	the	the	DET
cana-2825	91	9	writers	writer	NOUN
cana-2825	91	10	also	also	ADV
cana-2825	91	11	used	use	VERB
cana-2825	91	12	data	datum	NOUN
cana-2825	91	13	mining	mining	NOUN
cana-2825	91	14	techniques	technique	NOUN
cana-2825	91	15	including	include	VERB
cana-2825	91	16	neural	neural	ADJ
cana-2825	91	17	networks	network	NOUN
cana-2825	91	18	.	.	PUNCT
cana-2825	92	1	various	various	ADJ
cana-2825	92	2	networks	network	NOUN
cana-2825	92	3	were	be	AUX
cana-2825	92	4	constructed	construct	VERB
cana-2825	92	5	and	and	CCONJ
cana-2825	92	6	tested	test	VERB
cana-2825	92	7	;	;	PUNCT
cana-2825	92	8	the	the	DET
cana-2825	92	9	results	result	NOUN
cana-2825	92	10	showed	show	VERB
cana-2825	92	11	that	that	SCONJ
cana-2825	92	12	,	,	PUNCT
cana-2825	92	13	as	as	SCONJ
cana-2825	92	14	more	more	ADJ
cana-2825	92	15	data	datum	NOUN
cana-2825	92	16	became	become	VERB
cana-2825	92	17	accessible	accessible	ADJ
cana-2825	92	18	,	,	PUNCT
cana-2825	92	19	the	the	DET
cana-2825	92	20	networks	network	NOUN
cana-2825	92	21	'	'	PART
cana-2825	92	22	prediction	prediction	NOUN
cana-2825	92	23	accuracy	accuracy	NOUN
cana-2825	92	24	improved	improve	VERB
cana-2825	92	25	.	.	PUNCT
cana-2825	93	1	3	3	X
cana-2825	93	2	.	.	X
cana-2825	93	3	background	background	NOUN
cana-2825	93	4	an	an	DET
cana-2825	93	5	overview	overview	NOUN
cana-2825	93	6	of	of	ADP
cana-2825	93	7	precision	precision	NOUN
cana-2825	93	8	agriculture	agriculture	NOUN
cana-2825	93	9	will	will	AUX
cana-2825	93	10	be	be	AUX
cana-2825	93	11	provided	provide	VERB
cana-2825	93	12	before	before	ADP
cana-2825	93	13	delving	delve	VERB
cana-2825	93	14	into	into	ADP
cana-2825	93	15	the	the	DET
cana-2825	93	16	specifics	specific	NOUN
cana-2825	93	17	of	of	ADP
cana-2825	93	18	the	the	DET
cana-2825	93	19	methodology	methodology	NOUN
cana-2825	93	20	suggested	suggest	VERB
cana-2825	93	21	in	in	ADP
cana-2825	93	22	this	this	DET
cana-2825	93	23	article	article	NOUN
cana-2825	93	24	.	.	PUNCT
cana-2825	94	1	3.1	3.1	NUM
cana-2825	94	2	agricultural	agricultural	ADJ
cana-2825	94	3	expertise	expertise	NOUN
cana-2825	94	4	the	the	DET
cana-2825	94	5	goal	goal	NOUN
cana-2825	94	6	of	of	ADP
cana-2825	94	7	precision	precision	NOUN
cana-2825	94	8	agriculture	agriculture	NOUN
cana-2825	94	9	(	(	PUNCT
cana-2825	94	10	pa	pa	PROPN
cana-2825	94	11	)	)	PUNCT
cana-2825	94	12	is	be	AUX
cana-2825	94	13	to	to	PART
cana-2825	94	14	enhance	enhance	VERB
cana-2825	94	15	crop	crop	NOUN
cana-2825	94	16	yields	yield	NOUN
cana-2825	94	17	via	via	ADP
cana-2825	94	18	the	the	DET
cana-2825	94	19	strategic	strategic	ADJ
cana-2825	94	20	use	use	NOUN
cana-2825	94	21	of	of	ADP
cana-2825	94	22	different	different	ADJ
cana-2825	94	23	technological	technological	ADJ
cana-2825	94	24	tools	tool	NOUN
cana-2825	94	25	.	.	PUNCT
cana-2825	95	1	the	the	DET
cana-2825	95	2	area	area	NOUN
cana-2825	95	3	began	begin	VERB
cana-2825	95	4	with	with	ADP
cana-2825	95	5	the	the	DET
cana-2825	95	6	invention	invention	NOUN
cana-2825	95	7	of	of	ADP
cana-2825	95	8	the	the	DET
cana-2825	95	9	global	global	ADJ
cana-2825	95	10	positioning	positioning	NOUN
cana-2825	95	11	system	system	NOUN
cana-2825	95	12	,	,	PUNCT
cana-2825	95	13	which	which	PRON
cana-2825	95	14	allowed	allow	VERB
cana-2825	95	15	robots	robot	NOUN
cana-2825	95	16	to	to	PART
cana-2825	95	17	manage	manage	VERB
cana-2825	95	18	remedies	remedy	NOUN
cana-2825	95	19	with	with	ADP
cana-2825	95	20	localised	localised	ADJ
cana-2825	95	21	needs	need	NOUN
cana-2825	95	22	for	for	ADP
cana-2825	95	23	each	each	DET
cana-2825	95	24	field	field	NOUN
cana-2825	95	25	by	by	ADP
cana-2825	95	26	determining	determine	VERB
cana-2825	95	27	coordinates	coordinate	NOUN
cana-2825	95	28	anywhere	anywhere	ADV
cana-2825	95	29	on	on	ADP
cana-2825	95	30	earth	earth	NOUN
cana-2825	95	31	.	.	PUNCT
cana-2825	96	1	several	several	ADJ
cana-2825	96	2	fields	field	NOUN
cana-2825	96	3	of	of	ADP
cana-2825	96	4	engineering	engineering	NOUN
cana-2825	96	5	and	and	CCONJ
cana-2825	96	6	computer	computer	NOUN
cana-2825	96	7	science	science	NOUN
cana-2825	96	8	have	have	AUX
cana-2825	96	9	recently	recently	ADV
cana-2825	96	10	seen	see	VERB
cana-2825	96	11	significant	significant	ADJ
cana-2825	96	12	growth	growth	NOUN
cana-2825	96	13	the	the	DET
cana-2825	96	14	next	next	ADJ
cana-2825	96	15	sections	section	NOUN
cana-2825	96	16	will	will	AUX
cana-2825	96	17	discuss	discuss	VERB
cana-2825	96	18	the	the	DET
cana-2825	96	19	subfields	subfield	NOUN
cana-2825	96	20	of	of	ADP
cana-2825	96	21	pa	pa	PROPN
cana-2825	96	22	that	that	PRON
cana-2825	96	23	have	have	AUX
cana-2825	96	24	been	be	AUX
cana-2825	96	25	studied	study	VERB
cana-2825	96	26	,	,	PUNCT
cana-2825	96	27	namely	namely	ADV
cana-2825	96	28	yield	yield	VERB
cana-2825	96	29	mapping	mapping	NOUN
cana-2825	96	30	and	and	CCONJ
cana-2825	96	31	fertilisation	fertilisation	NOUN
cana-2825	96	32	optimisation	optimisation	NOUN
cana-2825	96	33	.	.	PUNCT
cana-2825	97	1	3.1.1	3.1.1	NUM
cana-2825	97	2	mapping	mapping	NOUN
cana-2825	97	3	yields	yield	VERB
cana-2825	97	4	the	the	DET
cana-2825	97	5	process	process	NOUN
cana-2825	97	6	of	of	ADP
cana-2825	97	7	yield	yield	NOUN
cana-2825	97	8	mapping	mapping	NOUN
cana-2825	97	9	entails	entail	VERB
cana-2825	97	10	visualising	visualise	VERB
cana-2825	97	11	agricultural	agricultural	ADJ
cana-2825	97	12	output	output	NOUN
cana-2825	97	13	for	for	ADP
cana-2825	97	14	a	a	DET
cana-2825	97	15	certain	certain	ADJ
cana-2825	97	16	region	region	NOUN
cana-2825	97	17	about	about	ADP
cana-2825	97	18	a	a	DET
cana-2825	97	19	given	give	VERB
cana-2825	97	20	geographic	geographic	ADJ
cana-2825	97	21	location	location	NOUN
cana-2825	97	22	.	.	PUNCT
cana-2825	98	1	physical	physical	ADJ
cana-2825	98	2	observations	observation	NOUN
cana-2825	98	3	or	or	CCONJ
cana-2825	98	4	yield	yield	NOUN
cana-2825	98	5	estimates	estimate	NOUN
cana-2825	98	6	derived	derive	VERB
cana-2825	98	7	from	from	ADP
cana-2825	98	8	computer	computer	NOUN
cana-2825	98	9	models	model	NOUN
cana-2825	98	10	may	may	AUX
cana-2825	98	11	form	form	VERB
cana-2825	98	12	the	the	DET
cana-2825	98	13	basis	basis	NOUN
cana-2825	98	14	of	of	ADP
cana-2825	98	15	these	these	DET
cana-2825	98	16	maps	map	NOUN
cana-2825	98	17	.	.	PUNCT
cana-2825	99	1	the	the	DET
cana-2825	99	2	four	four	NUM
cana-2825	99	3	main	main	ADJ
cana-2825	99	4	types	type	NOUN
cana-2825	99	5	of	of	ADP
cana-2825	99	6	yield	yield	NOUN
cana-2825	99	7	maps	map	NOUN
cana-2825	99	8	are	be	AUX
cana-2825	99	9	inference	inference	NOUN
cana-2825	99	10	,	,	PUNCT
cana-2825	99	11	prediction	prediction	NOUN
cana-2825	99	12	,	,	PUNCT
cana-2825	99	13	interpolation	interpolation	NOUN
cana-2825	99	14	,	,	PUNCT
cana-2825	99	15	and	and	CCONJ
cana-2825	99	16	aggregation	aggregation	NOUN
cana-2825	99	17	.	.	PUNCT
cana-2825	100	1	when	when	SCONJ
cana-2825	100	2	establishing	establish	VERB
cana-2825	100	3	a	a	DET
cana-2825	100	4	target	target	NOUN
cana-2825	100	5	yield	yield	NOUN
cana-2825	100	6	,	,	PUNCT
cana-2825	100	7	for	for	ADP
cana-2825	100	8	instance	instance	NOUN
cana-2825	100	9	,	,	PUNCT
cana-2825	100	10	this	this	PRON
cana-2825	100	11	is	be	AUX
cana-2825	100	12	helpful	helpful	ADJ
cana-2825	100	13	when	when	SCONJ
cana-2825	100	14	working	work	VERB
cana-2825	100	15	with	with	ADP
cana-2825	100	16	a	a	DET
cana-2825	100	17	soil	soil	NOUN
cana-2825	100	18	map	map	NOUN
cana-2825	100	19	.	.	PUNCT
cana-2825	101	1	on	on	ADP
cana-2825	101	2	the	the	DET
cana-2825	101	3	prediction	prediction	NOUN
cana-2825	101	4	map	map	NOUN
cana-2825	101	5	,	,	PUNCT
cana-2825	101	6	any	any	DET
cana-2825	101	7	value	value	NOUN
cana-2825	101	8	where	where	SCONJ
cana-2825	101	9	the	the	DET
cana-2825	101	10	yielding	yield	VERB
cana-2825	101	11	element	element	NOUN
cana-2825	101	12	is	be	AUX
cana-2825	101	13	expected	expect	VERB
cana-2825	101	14	to	to	PART
cana-2825	101	15	be	be	AUX
cana-2825	101	16	substantially	substantially	ADV
cana-2825	101	17	quantifiable	quantifiable	ADJ
cana-2825	101	18	is	be	AUX
cana-2825	101	19	filled	fill	VERB
cana-2825	101	20	up	up	ADP
cana-2825	101	21	.	.	PUNCT
cana-2825	102	1	produced	produce	VERB
cana-2825	102	2	by	by	ADP
cana-2825	102	3	measuring	measure	VERB
cana-2825	102	4	yield	yield	NOUN
cana-2825	102	5	at	at	ADP
cana-2825	102	6	discrete	discrete	ADJ
cana-2825	102	7	points	point	NOUN
cana-2825	102	8	within	within	ADP
cana-2825	102	9	a	a	DET
cana-2825	102	10	predefined	predefine	VERB
cana-2825	102	11	region	region	NOUN
cana-2825	102	12	,	,	PUNCT
cana-2825	102	13	interpolation	interpolation	NOUN
cana-2825	102	14	maps	map	NOUN
cana-2825	102	15	are	be	AUX
cana-2825	102	16	more	more	ADV
cana-2825	102	17	coarsely	coarsely	ADV
cana-2825	102	18	detailed	detailed	ADJ
cana-2825	102	19	than	than	ADP
cana-2825	102	20	prediction	prediction	NOUN
cana-2825	102	21	maps	map	NOUN
cana-2825	102	22	.	.	PUNCT
cana-2825	103	1	afterwards	afterwards	ADV
cana-2825	103	2	,	,	PUNCT
cana-2825	103	3	a	a	DET
cana-2825	103	4	local	local	ADJ
cana-2825	103	5	estimation	estimation	NOUN
cana-2825	103	6	technique	technique	NOUN
cana-2825	103	7	is	be	AUX
cana-2825	103	8	used	use	VERB
cana-2825	103	9	to	to	PART
cana-2825	103	10	estimate	estimate	VERB
cana-2825	103	11	the	the	DET
cana-2825	103	12	yield	yield	NOUN
cana-2825	103	13	values	value	NOUN
cana-2825	103	14	among	among	ADP
cana-2825	103	15	data	datum	NOUN
cana-2825	103	16	points	point	NOUN
cana-2825	103	17	.	.	PUNCT
cana-2825	104	1	ultimately	ultimately	ADV
cana-2825	104	2	,	,	PUNCT
cana-2825	104	3	by	by	ADP
cana-2825	104	4	measuring	measure	VERB
cana-2825	104	5	or	or	CCONJ
cana-2825	104	6	predicting	predict	VERB
cana-2825	104	7	the	the	DET
cana-2825	104	8	source	source	NOUN
cana-2825	104	9	data	data	NOUN
cana-2825	104	10	,	,	PUNCT
cana-2825	104	11	aggregation	aggregation	NOUN
cana-2825	104	12	maps	map	NOUN
cana-2825	104	13	provide	provide	VERB
cana-2825	104	14	aggregated	aggregated	ADJ
cana-2825	104	15	statistics	statistic	NOUN
cana-2825	104	16	.	.	PUNCT
cana-2825	105	1	in	in	ADP
cana-2825	105	2	pa	pa	PROPN
cana-2825	105	3	,	,	PUNCT
cana-2825	105	4	data	datum	NOUN
cana-2825	105	5	aggregation	aggregation	NOUN
cana-2825	105	6	and	and	CCONJ
cana-2825	105	7	prediction	prediction	NOUN
cana-2825	105	8	are	be	AUX
cana-2825	105	9	the	the	PRON
cana-2825	105	10	most	most	ADV
cana-2825	105	11	often	often	ADV
cana-2825	105	12	used	use	VERB
cana-2825	105	13	yield	yield	NOUN
cana-2825	105	14	mapping	mapping	NOUN
cana-2825	105	15	techniques	technique	NOUN
cana-2825	105	16	out	out	ADP
cana-2825	105	17	of	of	ADP
cana-2825	105	18	the	the	DET
cana-2825	105	19	four	four	NUM
cana-2825	105	20	.	.	PUNCT
cana-2825	106	1	the	the	DET
cana-2825	106	2	three	three	NUM
cana-2825	106	3	measurements	measurement	NOUN
cana-2825	106	4	needed	need	VERB
cana-2825	106	5	for	for	ADP
cana-2825	106	6	yield	yield	NOUN
cana-2825	106	7	mapping	mapping	NOUN
cana-2825	106	8	—	—	PUNCT
cana-2825	106	9	the	the	DET
cana-2825	106	10	yield	yield	NOUN
cana-2825	106	11	measurement	measurement	NOUN
cana-2825	106	12	,	,	PUNCT
cana-2825	106	13	an	an	DET
cana-2825	106	14	area	area	NOUN
cana-2825	106	15	of	of	ADP
cana-2825	106	16	measurement	measurement	NOUN
cana-2825	106	17	,	,	PUNCT
cana-2825	106	18	as	as	ADV
cana-2825	106	19	well	well	ADV
cana-2825	106	20	as	as	ADP
cana-2825	106	21	the	the	DET
cana-2825	106	22	precise	precise	ADJ
cana-2825	106	23	location	location	NOUN
cana-2825	106	24	of	of	ADP
cana-2825	106	25	measurements	measurement	NOUN
cana-2825	106	26	within	within	ADP
cana-2825	106	27	this	this	DET
cana-2825	106	28	area	area	NOUN
cana-2825	106	29	—	—	PUNCT
cana-2825	106	30	allow	allow	VERB
cana-2825	106	31	for	for	ADP
cana-2825	106	32	the	the	DET
cana-2825	106	33	quantification	quantification	NOUN
cana-2825	106	34	of	of	ADP
cana-2825	106	35	grain	grain	NOUN
cana-2825	106	36	,	,	PUNCT
cana-2825	106	37	harvested	harvest	VERB
cana-2825	106	38	crop	crop	NOUN
cana-2825	106	39	volume	volume	NOUN
cana-2825	106	40	or	or	CCONJ
cana-2825	106	41	mass	mass	NOUN
cana-2825	106	42	according	accord	VERB
cana-2825	106	43	to	to	ADP
cana-2825	106	44	position	position	NOUN
cana-2825	106	45	within	within	ADP
cana-2825	106	46	a	a	DET
cana-2825	106	47	specified	specified	ADJ
cana-2825	106	48	field	field	NOUN
cana-2825	106	49	.	.	PUNCT
cana-2825	107	1	yield	yield	NOUN
cana-2825	107	2	mapping	mapping	NOUN
cana-2825	107	3	is	be	AUX
cana-2825	107	4	intrinsically	intrinsically	ADV
cana-2825	107	5	linked	link	VERB
cana-2825	107	6	to	to	ADP
cana-2825	107	7	our	our	PRON
cana-2825	107	8	goal	goal	NOUN
cana-2825	107	9	of	of	ADP
cana-2825	107	10	optimising	optimise	VERB
cana-2825	107	11	fertilisation	fertilisation	NOUN
cana-2825	107	12	since	since	SCONJ
cana-2825	107	13	it	it	PRON
cana-2825	107	14	often	often	ADV
cana-2825	107	15	serves	serve	VERB
cana-2825	107	16	as	as	ADP
cana-2825	107	17	a	a	DET
cana-2825	107	18	foundation	foundation	NOUN
cana-2825	107	19	for	for	ADP
cana-2825	107	20	determining	determine	VERB
cana-2825	107	21	the	the	DET
cana-2825	107	22	optimal	optimal	ADJ
cana-2825	107	23	fertilisation	fertilisation	NOUN
cana-2825	107	24	rate	rate	NOUN
cana-2825	107	25	for	for	ADP
cana-2825	107	26	fields	field	NOUN
cana-2825	107	27	.	.	PUNCT
cana-2825	108	1	3.1.2	3.1.2	NUM
cana-2825	108	2	optimisation	optimisation	NOUN
cana-2825	108	3	of	of	ADP
cana-2825	108	4	fertilisation	fertilisation	NOUN
cana-2825	108	5	over	over	ADP
cana-2825	108	6	the	the	DET
cana-2825	108	7	last	last	ADJ
cana-2825	108	8	50	50	NUM
cana-2825	108	9	years	year	NOUN
cana-2825	108	10	,	,	PUNCT
cana-2825	108	11	the	the	DET
cana-2825	108	12	rise	rise	NOUN
cana-2825	108	13	in	in	ADP
cana-2825	108	14	agricultural	agricultural	ADJ
cana-2825	108	15	productivity	productivity	NOUN
cana-2825	108	16	has	have	AUX
cana-2825	108	17	led	lead	VERB
cana-2825	108	18	to	to	ADP
cana-2825	108	19	a	a	DET
cana-2825	108	20	substantial	substantial	ADJ
cana-2825	108	21	increase	increase	NOUN
cana-2825	108	22	in	in	ADP
cana-2825	108	23	fertiliser	fertiliser	NOUN
cana-2825	108	24	application	application	NOUN
cana-2825	108	25	.	.	PUNCT
cana-2825	109	1	the	the	DET
cana-2825	109	2	increase	increase	NOUN
cana-2825	109	3	in	in	ADP
cana-2825	109	4	fertilisation	fertilisation	NOUN
cana-2825	109	5	leads	lead	VERB
cana-2825	109	6	to	to	ADP
cana-2825	109	7	heightened	heightened	ADJ
cana-2825	109	8	output	output	NOUN
cana-2825	109	9	;	;	PUNCT
cana-2825	109	10	nevertheless	nevertheless	ADV
cana-2825	109	11	,	,	PUNCT
cana-2825	109	12	similarly	similarly	ADV
cana-2825	109	13	escalates	escalate	VERB
cana-2825	109	14	agricultural	agricultural	ADJ
cana-2825	109	15	emissions	emission	NOUN
cana-2825	109	16	,	,	PUNCT
cana-2825	109	17	particularly	particularly	ADV
cana-2825	109	18	nitrogen	nitrogen	NOUN
cana-2825	109	19	emissions	emission	NOUN
cana-2825	109	20	,	,	PUNCT
cana-2825	109	21	in	in	ADP
cana-2825	109	22	both	both	PRON
cana-2825	109	23	groundwater	groundwater	NOUN
cana-2825	109	24	and	and	CCONJ
cana-2825	109	25	surface	surface	NOUN
cana-2825	109	26	water	water	NOUN
cana-2825	109	27	.	.	PUNCT
cana-2825	110	1	the	the	DET
cana-2825	110	2	problem	problem	NOUN
cana-2825	110	3	,	,	PUNCT
cana-2825	110	4	along	along	ADP
cana-2825	110	5	with	with	ADP
cana-2825	110	6	enhancing	enhance	VERB
cana-2825	110	7	nitrogen	nitrogen	NOUN
cana-2825	110	8	application	application	NOUN
cana-2825	110	9	to	to	PART
cana-2825	110	10	boost	boost	VERB
cana-2825	110	11	yield	yield	NOUN
cana-2825	110	12	and	and	CCONJ
cana-2825	110	13	therefore	therefore	ADV
cana-2825	110	14	profit	profit	NOUN
cana-2825	110	15	,	,	PUNCT
cana-2825	110	16	prompted	prompt	VERB
cana-2825	110	17	communications	communication	NOUN
cana-2825	110	18	on	on	ADP
cana-2825	110	19	applied	apply	VERB
cana-2825	110	20	nonlinear	nonlinear	ADJ
cana-2825	110	21	analysis	analysis	NOUN
cana-2825	110	22	issn	issn	NOUN
cana-2825	110	23	:	:	PUNCT
cana-2825	110	24	1074	1074	NUM
cana-2825	110	25	-	-	PUNCT
cana-2825	110	26	133x	133x	NUM
cana-2825	110	27	vol	vol	NOUN
cana-2825	110	28	32	32	NUM
cana-2825	110	29	no	no	NOUN
cana-2825	110	30	.	.	PUNCT
cana-2825	111	1	4s	4s	NUM
cana-2825	111	2	(	(	PUNCT
cana-2825	111	3	2025	2025	NUM
cana-2825	111	4	)	)	PUNCT
cana-2825	111	5	348	348	NUM
cana-2825	111	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	111	7	a	a	DET
cana-2825	111	8	study	study	NOUN
cana-2825	111	9	in	in	ADP
cana-2825	111	10	fertilisation	fertilisation	NOUN
cana-2825	111	11	optimisation	optimisation	NOUN
cana-2825	111	12	.	.	PUNCT
cana-2825	112	1	the	the	DET
cana-2825	112	2	predominant	predominant	ADJ
cana-2825	112	3	technique	technique	NOUN
cana-2825	112	4	for	for	ADP
cana-2825	112	5	enhancing	enhance	VERB
cana-2825	112	6	fertilisation	fertilisation	NOUN
cana-2825	112	7	application	application	NOUN
cana-2825	112	8	is	be	AUX
cana-2825	112	9	the	the	DET
cana-2825	112	10	use	use	NOUN
cana-2825	112	11	of	of	ADP
cana-2825	112	12	variable	variable	ADJ
cana-2825	112	13	rate	rate	NOUN
cana-2825	112	14	technology	technology	NOUN
cana-2825	112	15	.	.	PUNCT
cana-2825	113	1	their	their	PRON
cana-2825	113	2	summary	summary	NOUN
cana-2825	113	3	provides	provide	VERB
cana-2825	113	4	a	a	DET
cana-2825	113	5	synopsis	synopsis	NOUN
cana-2825	113	6	of	of	ADP
cana-2825	113	7	the	the	DET
cana-2825	113	8	many	many	ADJ
cana-2825	113	9	precision	precision	NOUN
cana-2825	113	10	agriculture	agriculture	NOUN
cana-2825	113	11	fertilisation	fertilisation	NOUN
cana-2825	113	12	experiments	experiment	NOUN
cana-2825	113	13	.	.	PUNCT
cana-2825	114	1	nutritional	nutritional	ADJ
cana-2825	114	2	management	management	NOUN
cana-2825	114	3	study	study	NOUN
cana-2825	114	4	examining	examine	VERB
cana-2825	114	5	the	the	DET
cana-2825	114	6	effects	effect	NOUN
cana-2825	114	7	of	of	ADP
cana-2825	114	8	fertilisation	fertilisation	NOUN
cana-2825	114	9	on	on	ADP
cana-2825	114	10	crop	crop	NOUN
cana-2825	114	11	yields	yield	NOUN
cana-2825	114	12	is	be	AUX
cana-2825	114	13	the	the	DET
cana-2825	114	14	subject	subject	NOUN
cana-2825	114	15	of	of	ADP
cana-2825	114	16	their	their	PRON
cana-2825	114	17	first	first	ADJ
cana-2825	114	18	literature	literature	PROPN
cana-2825	114	19	review	review	NOUN
cana-2825	114	20	.	.	PUNCT
cana-2825	115	1	when	when	SCONJ
cana-2825	115	2	it	it	PRON
cana-2825	115	3	comes	come	VERB
cana-2825	115	4	to	to	ADP
cana-2825	115	5	site	site	NOUN
cana-2825	115	6	-	-	PUNCT
cana-2825	115	7	specific	specific	ADJ
cana-2825	115	8	management	management	NOUN
cana-2825	115	9	,	,	PUNCT
cana-2825	115	10	the	the	DET
cana-2825	115	11	authors	author	NOUN
cana-2825	115	12	discovered	discover	VERB
cana-2825	115	13	that	that	SCONJ
cana-2825	115	14	the	the	DET
cana-2825	115	15	majority	majority	NOUN
cana-2825	115	16	of	of	ADP
cana-2825	115	17	studies	study	NOUN
cana-2825	115	18	support	support	VERB
cana-2825	115	19	the	the	DET
cana-2825	115	20	idea	idea	NOUN
cana-2825	115	21	that	that	SCONJ
cana-2825	115	22	applying	apply	VERB
cana-2825	115	23	at	at	ADP
cana-2825	115	24	different	different	ADJ
cana-2825	115	25	rates	rate	NOUN
cana-2825	115	26	yields	yield	VERB
cana-2825	115	27	better	well	ADJ
cana-2825	115	28	results	result	NOUN
cana-2825	115	29	than	than	ADP
cana-2825	115	30	employing	employ	VERB
cana-2825	115	31	a	a	DET
cana-2825	115	32	uniform	uniform	ADJ
cana-2825	115	33	rate	rate	NOUN
cana-2825	115	34	.	.	PUNCT
cana-2825	116	1	to	to	PART
cana-2825	116	2	find	find	VERB
cana-2825	116	3	out	out	ADP
cana-2825	116	4	how	how	SCONJ
cana-2825	116	5	much	much	ADJ
cana-2825	116	6	nitrogen	nitrogen	NOUN
cana-2825	116	7	to	to	PART
cana-2825	116	8	apply	apply	VERB
cana-2825	116	9	to	to	ADP
cana-2825	116	10	specific	specific	ADJ
cana-2825	116	11	areas	area	NOUN
cana-2825	116	12	of	of	ADP
cana-2825	116	13	a	a	DET
cana-2825	116	14	field	field	NOUN
cana-2825	116	15	,	,	PUNCT
cana-2825	116	16	variable	variable	ADJ
cana-2825	116	17	rate	rate	NOUN
cana-2825	116	18	technology	technology	NOUN
cana-2825	116	19	uses	use	VERB
cana-2825	116	20	several	several	ADJ
cana-2825	116	21	optimisation	optimisation	NOUN
cana-2825	116	22	models	model	NOUN
cana-2825	116	23	.	.	PUNCT
cana-2825	117	1	instead	instead	ADV
cana-2825	117	2	of	of	ADP
cana-2825	117	3	applying	apply	VERB
cana-2825	117	4	a	a	DET
cana-2825	117	5	uniform	uniform	ADJ
cana-2825	117	6	rate	rate	NOUN
cana-2825	117	7	to	to	ADP
cana-2825	117	8	the	the	DET
cana-2825	117	9	whole	whole	ADJ
cana-2825	117	10	field	field	NOUN
cana-2825	117	11	,	,	PUNCT
cana-2825	117	12	it	it	PRON
cana-2825	117	13	determines	determine	VERB
cana-2825	117	14	the	the	DET
cana-2825	117	15	optimal	optimal	ADJ
cana-2825	117	16	nitrogen	nitrogen	NOUN
cana-2825	117	17	rates	rate	NOUN
cana-2825	117	18	for	for	ADP
cana-2825	117	19	every	every	DET
cana-2825	117	20	plot	plot	NOUN
cana-2825	117	21	and	and	CCONJ
cana-2825	117	22	utilises	utilise	VERB
cana-2825	117	23	them	they	PRON
cana-2825	117	24	as	as	ADP
cana-2825	117	25	a	a	DET
cana-2825	117	26	foundation	foundation	NOUN
cana-2825	117	27	for	for	ADP
cana-2825	117	28	return	return	NOUN
cana-2825	117	29	prediction	prediction	NOUN
cana-2825	117	30	.	.	PUNCT
cana-2825	118	1	the	the	DET
cana-2825	118	2	mechanics	mechanic	NOUN
cana-2825	118	3	of	of	ADP
cana-2825	118	4	sprayers	sprayer	NOUN
cana-2825	118	5	as	as	ADV
cana-2825	118	6	well	well	ADV
cana-2825	118	7	as	as	ADP
cana-2825	118	8	spreaders	spreader	NOUN
cana-2825	118	9	that	that	PRON
cana-2825	118	10	can	can	AUX
cana-2825	118	11	apply	apply	VERB
cana-2825	118	12	these	these	DET
cana-2825	118	13	various	various	ADJ
cana-2825	118	14	rates	rate	NOUN
cana-2825	118	15	,	,	PUNCT
cana-2825	118	16	however	however	ADV
cana-2825	118	17	,	,	PUNCT
cana-2825	118	18	suffer	suffer	VERB
cana-2825	118	19	more	more	ADV
cana-2825	118	20	when	when	SCONJ
cana-2825	118	21	rates	rate	NOUN
cana-2825	118	22	are	be	AUX
cana-2825	118	23	altered	alter	VERB
cana-2825	118	24	often	often	ADV
cana-2825	118	25	or	or	CCONJ
cana-2825	118	26	if	if	SCONJ
cana-2825	118	27	variations	variation	NOUN
cana-2825	118	28	entail	entail	VERB
cana-2825	118	29	very	very	ADV
cana-2825	118	30	big	big	ADJ
cana-2825	118	31	changes	change	NOUN
cana-2825	118	32	.	.	PUNCT
cana-2825	119	1	these	these	DET
cana-2825	119	2	devices	device	NOUN
cana-2825	119	3	are	be	AUX
cana-2825	119	4	also	also	ADV
cana-2825	119	5	more	more	ADV
cana-2825	119	6	costly	costly	ADJ
cana-2825	119	7	.	.	PUNCT
cana-2825	120	1	the	the	DET
cana-2825	120	2	fact	fact	NOUN
cana-2825	120	3	that	that	SCONJ
cana-2825	120	4	the	the	DET
cana-2825	120	5	authors	author	NOUN
cana-2825	120	6	provide	provide	VERB
cana-2825	120	7	two	two	NUM
cana-2825	120	8	trials	trial	NOUN
cana-2825	120	9	with	with	ADP
cana-2825	120	10	uniform	uniform	ADJ
cana-2825	120	11	rate	rate	NOUN
cana-2825	120	12	application	application	NOUN
cana-2825	120	13	yielding	yield	VERB
cana-2825	120	14	larger	large	ADJ
cana-2825	120	15	profits	profit	NOUN
cana-2825	120	16	is	be	AUX
cana-2825	120	17	thus	thus	ADV
cana-2825	120	18	not	not	PART
cana-2825	120	19	surprising	surprising	ADJ
cana-2825	120	20	,	,	PUNCT
cana-2825	120	21	especially	especially	ADV
cana-2825	120	22	considering	consider	VERB
cana-2825	120	23	that	that	SCONJ
cana-2825	120	24	these	these	DET
cana-2825	120	25	researchers	researcher	NOUN
cana-2825	120	26	were	be	AUX
cana-2825	120	27	directed	direct	VERB
cana-2825	120	28	when	when	SCONJ
cana-2825	120	29	the	the	DET
cana-2825	120	30	device	device	NOUN
cana-2825	120	31	was	be	AUX
cana-2825	120	32	less	less	ADV
cana-2825	120	33	comfortable	comfortable	ADJ
cana-2825	120	34	.	.	PUNCT
cana-2825	121	1	3.2	3.2	NUM
cana-2825	121	2	regression	regression	NOUN
cana-2825	121	3	:	:	PUNCT
cana-2825	121	4	linear	linear	ADJ
cana-2825	121	5	and	and	CCONJ
cana-2825	121	6	non	non	ADJ
cana-2825	121	7	-	-	ADJ
cana-2825	121	8	linear	linear	ADJ
cana-2825	121	9	one	one	NUM
cana-2825	121	10	way	way	NOUN
cana-2825	121	11	to	to	PART
cana-2825	121	12	define	define	VERB
cana-2825	121	13	potential	potential	ADJ
cana-2825	121	14	correlations	correlation	NOUN
cana-2825	121	15	between	between	ADP
cana-2825	121	16	variables	variable	NOUN
cana-2825	121	17	in	in	ADP
cana-2825	121	18	statistical	statistical	ADJ
cana-2825	121	19	analysis	analysis	NOUN
cana-2825	121	20	is	be	AUX
cana-2825	121	21	multiple	multiple	ADJ
cana-2825	121	22	regression	regression	NOUN
cana-2825	121	23	,	,	PUNCT
cana-2825	121	24	which	which	PRON
cana-2825	121	25	employs	employ	VERB
cana-2825	121	26	mathematical	mathematical	ADJ
cana-2825	121	27	procedures	procedure	NOUN
cana-2825	121	28	.	.	PUNCT
cana-2825	122	1	in	in	ADP
cana-2825	122	2	linear	linear	PROPN
cana-2825	122	3	regression	regression	NOUN
cana-2825	122	4	,	,	PUNCT
cana-2825	122	5	the	the	DET
cana-2825	122	6	response	response	NOUN
cana-2825	122	7	values	value	NOUN
cana-2825	122	8	are	be	AUX
cana-2825	122	9	best	well	ADV
cana-2825	122	10	predicted	predict	VERB
cana-2825	122	11	by	by	ADP
cana-2825	122	12	fitting	fit	VERB
cana-2825	122	13	a	a	DET
cana-2825	122	14	straight	straight	ADJ
cana-2825	122	15	line	line	NOUN
cana-2825	122	16	across	across	ADP
cana-2825	122	17	the	the	DET
cana-2825	122	18	data	datum	NOUN
cana-2825	122	19	.	.	PUNCT
cana-2825	123	1	in	in	ADP
cana-2825	123	2	addition	addition	NOUN
cana-2825	123	3	to	to	ADP
cana-2825	123	4	helping	help	VERB
cana-2825	123	5	explain	explain	VERB
cana-2825	123	6	or	or	CCONJ
cana-2825	123	7	evaluate	evaluate	VERB
cana-2825	123	8	a	a	DET
cana-2825	123	9	scientific	scientific	ADJ
cana-2825	123	10	theory	theory	NOUN
cana-2825	123	11	,	,	PUNCT
cana-2825	123	12	this	this	DET
cana-2825	123	13	approach	approach	NOUN
cana-2825	123	14	is	be	AUX
cana-2825	123	15	often	often	ADV
cana-2825	123	16	used	use	VERB
cana-2825	123	17	for	for	ADP
cana-2825	123	18	making	make	VERB
cana-2825	123	19	predictions	prediction	NOUN
cana-2825	123	20	about	about	ADP
cana-2825	123	21	the	the	DET
cana-2825	123	22	values	value	NOUN
cana-2825	123	23	of	of	ADP
cana-2825	123	24	one	one	NUM
cana-2825	123	25	variable	variable	NOUN
cana-2825	123	26	given	give	VERB
cana-2825	123	27	another	another	PRON
cana-2825	123	28	.	.	PUNCT
cana-2825	124	1	similar	similar	ADJ
cana-2825	124	2	to	to	ADP
cana-2825	124	3	linear	linear	PROPN
cana-2825	124	4	regression	regression	NOUN
cana-2825	124	5	,	,	PUNCT
cana-2825	124	6	nonlinear	nonlinear	ADJ
cana-2825	124	7	regression	regression	NOUN
cana-2825	124	8	uses	use	VERB
cana-2825	124	9	non	non	ADJ
cana-2825	124	10	-	-	ADJ
cana-2825	124	11	linear	linear	ADJ
cana-2825	124	12	surface	surface	NOUN
cana-2825	124	13	forms	form	NOUN
cana-2825	124	14	instead	instead	ADV
cana-2825	124	15	of	of	ADP
cana-2825	124	16	a	a	DET
cana-2825	124	17	linear	linear	ADJ
cana-2825	124	18	one	one	NUM
cana-2825	124	19	.	.	PUNCT
cana-2825	125	1	the	the	DET
cana-2825	125	2	form	form	NOUN
cana-2825	125	3	might	might	AUX
cana-2825	125	4	vary	vary	VERB
cana-2825	125	5	substantially	substantially	ADV
cana-2825	125	6	since	since	SCONJ
cana-2825	125	7	it	it	PRON
cana-2825	125	8	is	be	AUX
cana-2825	125	9	governed	govern	VERB
cana-2825	125	10	by	by	ADP
cana-2825	125	11	the	the	DET
cana-2825	125	12	general	general	ADJ
cana-2825	125	13	dispersion	dispersion	NOUN
cana-2825	125	14	of	of	ADP
cana-2825	125	15	the	the	DET
cana-2825	125	16	data	datum	NOUN
cana-2825	125	17	.	.	PUNCT
cana-2825	126	1	this	this	DET
cana-2825	126	2	study	study	NOUN
cana-2825	126	3	's	's	PART
cana-2825	126	4	non	non	ADJ
cana-2825	126	5	-	-	ADJ
cana-2825	126	6	linear	linear	ADJ
cana-2825	126	7	model	model	NOUN
cana-2825	126	8	estimates	estimate	NOUN
cana-2825	126	9	yield	yield	VERB
cana-2825	126	10	as	as	ADV
cana-2825	126	11	well	well	ADV
cana-2825	126	12	as	as	ADP
cana-2825	126	13	protein	protein	NOUN
cana-2825	126	14	values	value	NOUN
cana-2825	126	15	using	use	VERB
cana-2825	126	16	a	a	DET
cana-2825	126	17	hyperbolic	hyperbolic	ADJ
cana-2825	126	18	function	function	NOUN
cana-2825	126	19	.	.	PUNCT
cana-2825	127	1	3.3	3.3	NUM
cana-2825	127	2	networks	network	NOUN
cana-2825	127	3	of	of	ADP
cana-2825	127	4	neutrals	neutral	NOUN
cana-2825	127	5	an	an	DET
cana-2825	127	6	architecture	architecture	NOUN
cana-2825	127	7	for	for	ADP
cana-2825	127	8	distributed	distribute	VERB
cana-2825	127	9	and	and	CCONJ
cana-2825	127	10	parallel	parallel	ADJ
cana-2825	127	11	computing	computing	NOUN
cana-2825	127	12	called	call	VERB
cana-2825	127	13	an	an	DET
cana-2825	127	14	artificial	artificial	ADJ
cana-2825	127	15	neural	neural	ADJ
cana-2825	127	16	network	network	NOUN
cana-2825	127	17	mimics	mimic	VERB
cana-2825	127	18	the	the	DET
cana-2825	127	19	brain	brain	NOUN
cana-2825	127	20	's	's	PART
cana-2825	127	21	natural	natural	ADJ
cana-2825	127	22	operation	operation	NOUN
cana-2825	127	23	.	.	PUNCT
cana-2825	128	1	the	the	DET
cana-2825	128	2	building	building	NOUN
cana-2825	128	3	's	's	PART
cana-2825	128	4	processing	processing	NOUN
cana-2825	128	5	components	component	NOUN
cana-2825	128	6	are	be	AUX
cana-2825	128	7	linked	link	VERB
cana-2825	128	8	via	via	ADP
cana-2825	128	9	bidirectional	bidirectional	ADJ
cana-2825	128	10	or	or	CCONJ
cana-2825	128	11	unidirectional	unidirectional	ADJ
cana-2825	128	12	signal	signal	NOUN
cana-2825	128	13	stations	station	NOUN
cana-2825	128	14	.	.	PUNCT
cana-2825	129	1	all	all	PRON
cana-2825	129	2	of	of	ADP
cana-2825	129	3	the	the	DET
cana-2825	129	4	processing	processing	NOUN
cana-2825	129	5	parts	part	NOUN
cana-2825	129	6	have	have	VERB
cana-2825	129	7	their	their	PRON
cana-2825	129	8	local	local	ADJ
cana-2825	129	9	memory	memory	NOUN
cana-2825	129	10	,	,	PUNCT
cana-2825	129	11	so	so	SCONJ
cana-2825	129	12	they	they	PRON
cana-2825	129	13	can	can	AUX
cana-2825	129	14	only	only	ADV
cana-2825	129	15	process	process	VERB
cana-2825	129	16	data	datum	NOUN
cana-2825	129	17	that	that	PRON
cana-2825	129	18	is	be	AUX
cana-2825	129	19	local	local	ADJ
cana-2825	129	20	to	to	ADP
cana-2825	129	21	them	they	PRON
cana-2825	129	22	.	.	PUNCT
cana-2825	130	1	the	the	DET
cana-2825	130	2	present	present	ADJ
cana-2825	130	3	status	status	NOUN
cana-2825	130	4	of	of	ADP
cana-2825	130	5	the	the	DET
cana-2825	130	6	input	input	NOUN
cana-2825	130	7	signal	signal	NOUN
cana-2825	130	8	and	and	CCONJ
cana-2825	130	9	the	the	DET
cana-2825	130	10	stored	store	VERB
cana-2825	130	11	values	value	NOUN
cana-2825	130	12	in	in	ADP
cana-2825	130	13	this	this	DET
cana-2825	130	14	reminiscence	reminiscence	NOUN
cana-2825	130	15	are	be	AUX
cana-2825	130	16	the	the	DET
cana-2825	130	17	only	only	ADJ
cana-2825	130	18	inputs	input	NOUN
cana-2825	130	19	that	that	PRON
cana-2825	130	20	an	an	DET
cana-2825	130	21	element	element	NOUN
cana-2825	130	22	takes	take	VERB
cana-2825	130	23	into	into	ADP
cana-2825	130	24	consideration	consideration	NOUN
cana-2825	130	25	during	during	ADP
cana-2825	130	26	processing	processing	NOUN
cana-2825	130	27	.	.	PUNCT
cana-2825	131	1	all	all	DET
cana-2825	131	2	the	the	DET
cana-2825	131	3	components	component	NOUN
cana-2825	131	4	have	have	VERB
cana-2825	131	5	one	one	NUM
cana-2825	131	6	output	output	NOUN
cana-2825	131	7	,	,	PUNCT
cana-2825	131	8	which	which	PRON
cana-2825	131	9	may	may	AUX
cana-2825	131	10	be	be	AUX
cana-2825	131	11	any	any	DET
cana-2825	131	12	mathematical	mathematical	ADJ
cana-2825	131	13	signal	signal	NOUN
cana-2825	131	14	,	,	PUNCT
cana-2825	131	15	and	and	CCONJ
cana-2825	131	16	as	as	ADP
cana-2825	131	17	many	many	ADJ
cana-2825	131	18	collateral	collateral	ADJ
cana-2825	131	19	connections	connection	NOUN
cana-2825	131	20	as	as	SCONJ
cana-2825	131	21	are	be	AUX
cana-2825	131	22	needed	need	VERB
cana-2825	131	23	.	.	PUNCT
cana-2825	132	1	here	here	ADV
cana-2825	132	2	,	,	PUNCT
cana-2825	132	3	go	go	VERB
cana-2825	132	4	into	into	ADP
cana-2825	132	5	more	more	ADJ
cana-2825	132	6	depth	depth	NOUN
cana-2825	132	7	about	about	ADP
cana-2825	132	8	the	the	DET
cana-2825	132	9	feed	feed	NOUN
cana-2825	132	10	-	-	PUNCT
cana-2825	132	11	forward	forward	NOUN
cana-2825	132	12	method	method	NOUN
cana-2825	132	13	and	and	CCONJ
cana-2825	132	14	present	present	VERB
cana-2825	132	15	the	the	DET
cana-2825	132	16	idea	idea	NOUN
cana-2825	132	17	of	of	ADP
cana-2825	132	18	a	a	DET
cana-2825	132	19	stacked	stack	VERB
cana-2825	132	20	autoencoder	autoencoder	NOUN
cana-2825	132	21	,	,	PUNCT
cana-2825	132	22	a	a	DET
cana-2825	132	23	deep	deep	ADJ
cana-2825	132	24	approach	approach	NOUN
cana-2825	132	25	that	that	PRON
cana-2825	132	26	is	be	AUX
cana-2825	132	27	not	not	PART
cana-2825	132	28	used	use	VERB
cana-2825	132	29	for	for	ADP
cana-2825	132	30	pa	pa	PROPN
cana-2825	132	31	.	.	PROPN
cana-2825	133	1	3.3.1	3.3.1	NUM
cana-2825	133	2	the	the	DET
cana-2825	133	3	feed	feed	NOUN
cana-2825	133	4	-	-	PUNCT
cana-2825	133	5	forward	forward	NOUN
cana-2825	133	6	neural	neural	ADJ
cana-2825	133	7	network	network	NOUN
cana-2825	133	8	every	every	DET
cana-2825	133	9	node	node	NOUN
cana-2825	133	10	in	in	ADP
cana-2825	133	11	a	a	DET
cana-2825	133	12	feed	feed	NOUN
cana-2825	133	13	-	-	PUNCT
cana-2825	133	14	forward	forward	NOUN
cana-2825	133	15	ann	ann	PROPN
cana-2825	133	16	contributes	contribute	VERB
cana-2825	133	17	data	datum	NOUN
cana-2825	133	18	to	to	ADP
cana-2825	133	19	the	the	DET
cana-2825	133	20	final	final	ADJ
cana-2825	133	21	output	output	NOUN
cana-2825	133	22	layer	layer	NOUN
cana-2825	133	23	by	by	ADP
cana-2825	133	24	passing	pass	VERB
cana-2825	133	25	it	it	PRON
cana-2825	133	26	forward	forward	ADV
cana-2825	133	27	via	via	ADP
cana-2825	133	28	each	each	DET
cana-2825	133	29	following	follow	VERB
cana-2825	133	30	layer	layer	NOUN
cana-2825	133	31	.	.	PUNCT
cana-2825	134	1	to	to	PART
cana-2825	134	2	find	find	VERB
cana-2825	134	3	a	a	DET
cana-2825	134	4	node	node	NOUN
cana-2825	134	5	's	's	PART
cana-2825	134	6	output	output	NOUN
cana-2825	134	7	in	in	ADP
cana-2825	134	8	a	a	DET
cana-2825	134	9	network	network	NOUN
cana-2825	134	10	,	,	PUNCT
cana-2825	134	11	utilise	utilise	VERB
cana-2825	134	12	the	the	DET
cana-2825	134	13	following	follow	VERB
cana-2825	134	14	approach	approach	NOUN
cana-2825	134	15	:	:	PUNCT
cana-2825	134	16	𝑦	𝑦	NOUN
cana-2825	134	17	=	=	SYM
cana-2825	134	18	𝑓	𝑓	X
cana-2825	134	19	(	(	PUNCT
cana-2825	134	20	𝑤0	𝑤0	NOUN
cana-2825	134	21	+	+	NOUN
cana-2825	134	22	∑	∑	PROPN
cana-2825	134	23	𝑤𝑖	𝑤𝑖	PRON
cana-2825	134	24	𝑥𝑖	𝑥𝑖	ADP
cana-2825	134	25	𝑛	𝑛	PRON
cana-2825	134	26	𝑖=1	𝑖=1	PUNCT
cana-2825	134	27	)	)	PUNCT
cana-2825	134	28	where	where	SCONJ
cana-2825	134	29	f	f	X
cana-2825	134	30	(	(	PUNCT
cana-2825	134	31	.	.	PUNCT
cana-2825	134	32	)	)	PUNCT
cana-2825	134	33	is	be	AUX
cana-2825	134	34	often	often	ADV
cana-2825	134	35	referred	refer	VERB
cana-2825	134	36	to	to	ADP
cana-2825	134	37	as	as	ADP
cana-2825	134	38	an	an	DET
cana-2825	134	39	“	"	PUNCT
cana-2825	134	40	activation	activation	NOUN
cana-2825	134	41	function	function	NOUN
cana-2825	134	42	”	"	PUNCT
cana-2825	134	43	.	.	PUNCT
cana-2825	135	1	given	give	VERB
cana-2825	135	2	z=	z=	PROPN
cana-2825	135	3	𝑤0	𝑤0	PROPN
cana-2825	135	4	+	+	CCONJ
cana-2825	135	5	∑	∑	PROPN
cana-2825	135	6	𝑤𝑖	𝑤𝑖	PRON
cana-2825	135	7	𝑥𝑖	𝑥𝑖	ADP
cana-2825	135	8	𝑛	𝑛	PRON
cana-2825	135	9	𝑖=1	𝑖=1	PUNCT
cana-2825	135	10	,	,	PUNCT
cana-2825	135	11	these	these	DET
cana-2825	135	12	activation	activation	NOUN
cana-2825	135	13	functions	function	NOUN
cana-2825	135	14	may	may	AUX
cana-2825	135	15	be	be	AUX
cana-2825	135	16	linear	linear	ADJ
cana-2825	135	17	(	(	PUNCT
cana-2825	135	18	f(z	f(z	PROPN
cana-2825	135	19	)	)	PUNCT
cana-2825	135	20	=	=	SYM
cana-2825	136	1	z	z	NOUN
cana-2825	136	2	)	)	PUNCT
cana-2825	136	3	,	,	PUNCT
cana-2825	136	4	rectified	rectify	VERB
cana-2825	136	5	linear	linear	NOUN
cana-2825	136	6	(	(	PUNCT
cana-2825	136	7	f(z	f(z	PROPN
cana-2825	136	8	)	)	PUNCT
cana-2825	136	9	=	=	SYM
cana-2825	136	10	max	max	PROPN
cana-2825	136	11	,	,	PUNCT
cana-2825	136	12	z	z	NOUN
cana-2825	136	13	)	)	PUNCT
cana-2825	136	14	,	,	PUNCT
cana-2825	136	15	logistic	logistic	ADJ
cana-2825	136	16	(	(	PUNCT
cana-2825	136	17	f(z	f(z	PROPN
cana-2825	136	18	)	)	PUNCT
cana-2825	136	19	=	=	SYM
cana-2825	137	1	1/(1+exp	1/(1+exp	PROPN
cana-2825	137	2	(	(	PUNCT
cana-2825	137	3	-z	-z	NOUN
cana-2825	137	4	)	)	PUNCT
cana-2825	137	5	)	)	PUNCT
cana-2825	137	6	,	,	PUNCT
cana-2825	137	7	hyperbolic	hyperbolic	ADJ
cana-2825	137	8	tangent	tangent	NOUN
cana-2825	137	9	(	(	PUNCT
cana-2825	137	10	f(z	f(z	PROPN
cana-2825	137	11	)	)	PUNCT
cana-2825	137	12	=	=	PUNCT
cana-2825	137	13	tanh	tanh	PROPN
cana-2825	137	14	z	z	PROPN
cana-2825	137	15	)	)	PUNCT
cana-2825	137	16	,	,	PUNCT
cana-2825	137	17	or	or	CCONJ
cana-2825	137	18	radial	radial	ADJ
cana-2825	137	19	(	(	PUNCT
cana-2825	137	20	f(x	f(x	PROPN
cana-2825	137	21	)	)	PUNCT
cana-2825	137	22	=	=	SYM
cana-2825	138	1	exp(||x	exp(||x	PROPN
cana-2825	138	2	c||/σ	c||/σ	PROPN
cana-2825	138	3	)	)	PUNCT
cana-2825	138	4	)	)	PUNCT
cana-2825	138	5	.	.	PUNCT
cana-2825	139	1	communications	communication	NOUN
cana-2825	139	2	on	on	ADP
cana-2825	139	3	applied	apply	VERB
cana-2825	139	4	nonlinear	nonlinear	ADJ
cana-2825	139	5	analysis	analysis	NOUN
cana-2825	139	6	issn	issn	NOUN
cana-2825	139	7	:	:	PUNCT
cana-2825	139	8	1074	1074	NUM
cana-2825	139	9	-	-	PUNCT
cana-2825	139	10	133x	133x	NUM
cana-2825	139	11	vol	vol	NOUN
cana-2825	139	12	32	32	NUM
cana-2825	139	13	no	no	NOUN
cana-2825	139	14	.	.	PUNCT
cana-2825	140	1	4s	4s	NUM
cana-2825	140	2	(	(	PUNCT
cana-2825	140	3	2025	2025	NUM
cana-2825	140	4	)	)	PUNCT
cana-2825	140	5	349	349	NUM
cana-2825	140	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	140	7	the	the	DET
cana-2825	140	8	modifications	modification	NOUN
cana-2825	140	9	to	to	ADP
cana-2825	140	10	the	the	DET
cana-2825	140	11	weights	weight	NOUN
cana-2825	140	12	inside	inside	ADP
cana-2825	140	13	the	the	DET
cana-2825	140	14	network	network	NOUN
cana-2825	140	15	's	's	PART
cana-2825	140	16	interior	interior	NOUN
cana-2825	140	17	are	be	AUX
cana-2825	140	18	determined	determine	VERB
cana-2825	140	19	by	by	ADP
cana-2825	140	20	the	the	DET
cana-2825	140	21	backpropagation	backpropagation	NOUN
cana-2825	140	22	(	(	PUNCT
cana-2825	140	23	bp	bp	PROPN
cana-2825	140	24	)	)	PUNCT
cana-2825	140	25	method	method	NOUN
cana-2825	140	26	.	.	PUNCT
cana-2825	141	1	figure	figure	NOUN
cana-2825	141	2	1	1	NUM
cana-2825	141	3	is	be	AUX
cana-2825	141	4	an	an	DET
cana-2825	141	5	example	example	NOUN
cana-2825	141	6	of	of	ADP
cana-2825	141	7	a	a	DET
cana-2825	141	8	feed	feed	NOUN
cana-2825	141	9	-	-	PUNCT
cana-2825	141	10	forward	forward	ADV
cana-2825	141	11	artificial	artificial	ADJ
cana-2825	141	12	neural	neural	ADJ
cana-2825	141	13	network	network	NOUN
cana-2825	141	14	demonstrating	demonstrate	VERB
cana-2825	141	15	the	the	DET
cana-2825	141	16	backpropagation	backpropagation	NOUN
cana-2825	141	17	process	process	NOUN
cana-2825	141	18	.	.	PUNCT
cana-2825	142	1	backpropagation	backpropagation	NOUN
cana-2825	142	2	is	be	AUX
cana-2825	142	3	a	a	DET
cana-2825	142	4	widely	widely	ADV
cana-2825	142	5	used	use	VERB
cana-2825	142	6	method	method	NOUN
cana-2825	142	7	for	for	ADP
cana-2825	142	8	training	train	VERB
cana-2825	142	9	neural	neural	ADJ
cana-2825	142	10	networks	network	NOUN
cana-2825	142	11	.	.	PUNCT
cana-2825	143	1	the	the	DET
cana-2825	143	2	parallel	parallel	ADJ
cana-2825	143	3	distributed	distribute	VERB
cana-2825	143	4	processing	processing	NOUN
cana-2825	143	5	(	(	PUNCT
cana-2825	143	6	pdp	pdp	PROPN
cana-2825	143	7	)	)	PUNCT
cana-2825	143	8	grouping	grouping	NOUN
cana-2825	143	9	at	at	ADP
cana-2825	143	10	stanford	stanford	PROPN
cana-2825	143	11	presented	present	VERB
cana-2825	143	12	it	it	PRON
cana-2825	143	13	to	to	ADP
cana-2825	143	14	a	a	DET
cana-2825	143	15	broad	broad	ADJ
cana-2825	143	16	audience	audience	NOUN
cana-2825	143	17	.	.	PUNCT
cana-2825	144	1	although	although	SCONJ
cana-2825	144	2	other	other	ADJ
cana-2825	144	3	researchers	researcher	NOUN
cana-2825	144	4	found	find	VERB
cana-2825	144	5	bp	bp	PROPN
cana-2825	144	6	earlier	early	ADV
cana-2825	144	7	,	,	PUNCT
cana-2825	144	8	the	the	DET
cana-2825	144	9	pdp	pdp	PROPN
cana-2825	144	10	lab	lab	NOUN
cana-2825	144	11	is	be	AUX
cana-2825	144	12	often	often	ADV
cana-2825	144	13	credited	credit	VERB
cana-2825	144	14	with	with	ADP
cana-2825	144	15	developing	develop	VERB
cana-2825	144	16	the	the	DET
cana-2825	144	17	first	first	ADJ
cana-2825	144	18	practical	practical	ADJ
cana-2825	144	19	way	way	NOUN
cana-2825	144	20	to	to	PART
cana-2825	144	21	use	use	VERB
cana-2825	144	22	backpropagation	backpropagation	NOUN
cana-2825	144	23	,	,	PUNCT
cana-2825	144	24	which	which	PRON
cana-2825	144	25	is	be	AUX
cana-2825	144	26	why	why	SCONJ
cana-2825	144	27	they	they	PRON
cana-2825	144	28	are	be	AUX
cana-2825	144	29	seen	see	VERB
cana-2825	144	30	as	as	ADP
cana-2825	144	31	the	the	DET
cana-2825	144	32	ones	one	NOUN
cana-2825	144	33	responsible	responsible	ADJ
cana-2825	144	34	for	for	ADP
cana-2825	144	35	the	the	DET
cana-2825	144	36	present	present	ADJ
cana-2825	144	37	approach	approach	NOUN
cana-2825	144	38	to	to	ADP
cana-2825	144	39	bp	bp	PROPN
cana-2825	144	40	.	.	PUNCT
cana-2825	145	1	in	in	ADP
cana-2825	145	2	bp	bp	PROPN
cana-2825	145	3	,	,	PUNCT
cana-2825	145	4	the	the	DET
cana-2825	145	5	goal	goal	NOUN
cana-2825	145	6	is	be	AUX
cana-2825	145	7	to	to	PART
cana-2825	145	8	minimise	minimise	VERB
cana-2825	145	9	the	the	DET
cana-2825	145	10	network	network	NOUN
cana-2825	145	11	's	's	PART
cana-2825	145	12	mean	mean	ADJ
cana-2825	145	13	squared	square	VERB
cana-2825	145	14	error	error	NOUN
cana-2825	145	15	as	as	ADP
cana-2825	145	16	a	a	DET
cana-2825	145	17	loss	loss	NOUN
cana-2825	145	18	function	function	NOUN
cana-2825	145	19	,	,	PUNCT
cana-2825	145	20	and	and	CCONJ
cana-2825	145	21	the	the	DET
cana-2825	145	22	updates	update	NOUN
cana-2825	145	23	are	be	AUX
cana-2825	145	24	related	relate	VERB
cana-2825	145	25	to	to	ADP
cana-2825	145	26	:	:	PUNCT
cana-2825	145	27	∆	∆	PROPN
cana-2825	145	28	𝑤𝑖𝑗	𝑤𝑖𝑗	PROPN
cana-2825	145	29	=	=	SYM
cana-2825	145	30	𝜕𝐸𝑟𝑟(𝑥	𝜕𝐸𝑟𝑟(𝑥	NOUN
cana-2825	145	31	)	)	PUNCT
cana-2825	145	32	𝑤𝑖𝑗	𝑤𝑖𝑗	NOUN
cana-2825	145	33	=	=	SYM
cana-2825	145	34	𝜂𝛿𝑖𝑥𝑗𝑖	𝜂𝛿𝑖𝑥𝑗𝑖	ADJ
cana-2825	145	35	figure	figure	NOUN
cana-2825	145	36	.	.	PUNCT
cana-2825	146	1	1	1	NUM
cana-2825	146	2	backpropagation	backpropagation	NOUN
cana-2825	146	3	is	be	AUX
cana-2825	146	4	used	use	VERB
cana-2825	146	5	to	to	PART
cana-2825	146	6	train	train	VERB
cana-2825	146	7	a	a	DET
cana-2825	146	8	feed	feed	NOUN
cana-2825	146	9	-	-	PUNCT
cana-2825	146	10	forward	forward	ADV
cana-2825	146	11	neural	neural	ADJ
cana-2825	146	12	network	network	NOUN
cana-2825	146	13	.	.	PUNCT
cana-2825	147	1	where	where	SCONJ
cana-2825	147	2	at	at	ADP
cana-2825	147	3	the	the	DET
cana-2825	147	4	output	output	NOUN
cana-2825	147	5	layer	layer	NOUN
cana-2825	147	6	,	,	PUNCT
cana-2825	147	7	𝛿𝑗	𝛿𝑗	PROPN
cana-2825	147	8	=	=	X
cana-2825	147	9	(	(	PUNCT
cana-2825	147	10	𝑟𝑗	𝑟𝑗	ADP
cana-2825	147	11	−	−	PROPN
cana-2825	147	12	𝑦𝑗)𝑦𝑗(1	𝑦𝑗)𝑦𝑗(1	ADJ
cana-2825	147	13	−	−	PROPN
cana-2825	147	14	𝑦𝑗	𝑦𝑗	NOUN
cana-2825	147	15	)	)	PUNCT
cana-2825	147	16	where	where	SCONJ
cana-2825	147	17	an	an	DET
cana-2825	147	18	input	input	NOUN
cana-2825	147	19	from	from	ADP
cana-2825	147	20	the	the	DET
cana-2825	147	21	𝑖𝑡ℎ	𝑖𝑡ℎ	NOUN
cana-2825	147	22	nodes	node	NOUN
cana-2825	147	23	to	to	ADP
cana-2825	147	24	the	the	DET
cana-2825	147	25	𝑗𝑡ℎ	𝑗𝑡ℎ	PROPN
cana-2825	147	26	node	node	PROPN
cana-2825	147	27	is	be	AUX
cana-2825	147	28	𝑥𝑖𝑗	𝑥𝑖𝑗	PROPN
cana-2825	147	29	,	,	PUNCT
cana-2825	147	30	the	the	DET
cana-2825	147	31	intended	intend	VERB
cana-2825	147	32	response	response	NOUN
cana-2825	147	33	value	value	NOUN
cana-2825	147	34	is	be	AUX
cana-2825	147	35	𝑟𝑗.	𝑟𝑗.	PROPN
cana-2825	147	36	the	the	DET
cana-2825	147	37	inner	inner	ADJ
cana-2825	147	38	layers	layer	NOUN
cana-2825	147	39	𝛿𝑗	𝛿𝑗	PROPN
cana-2825	148	1	=	=	X
cana-2825	148	2	𝑜𝑗	𝑜𝑗	X
cana-2825	148	3	(	(	PUNCT
cana-2825	148	4	1	1	NUM
cana-2825	148	5	−	−	PROPN
cana-2825	148	6	𝑜𝑗	𝑜𝑗	NUM
cana-2825	148	7	)	)	PUNCT
cana-2825	148	8	∑	∑	ADP
cana-2825	148	9	𝛿𝑘	𝛿𝑘	ADP
cana-2825	148	10	𝑊𝑘𝑗	𝑊𝑘𝑗	PROPN
cana-2825	148	11	𝑘∈𝑑𝑜𝑤𝑛𝑠𝑡𝑟𝑒𝑎𝑚(𝑗	𝑘∈𝑑𝑜𝑤𝑛𝑠𝑡𝑟𝑒𝑎𝑚(𝑗	PROPN
cana-2825	148	12	)	)	PUNCT
cana-2825	148	13	and	and	CCONJ
cana-2825	148	14	𝑜𝑗	𝑜𝑗	ADP
cana-2825	148	15	the	the	DET
cana-2825	148	16	output	output	NOUN
cana-2825	148	17	produced	produce	VERB
cana-2825	148	18	by	by	ADP
cana-2825	148	19	the	the	DET
cana-2825	148	20	𝑗𝑡ℎnodes	𝑗𝑡ℎnode	NOUN
cana-2825	148	21	are	be	AUX
cana-2825	148	22	represented	represent	VERB
cana-2825	148	23	.	.	PUNCT
cana-2825	149	1	this	this	DET
cana-2825	149	2	update	update	NOUN
cana-2825	149	3	rule	rule	NOUN
cana-2825	149	4	is	be	AUX
cana-2825	149	5	predicated	predicate	VERB
cana-2825	149	6	on	on	ADP
cana-2825	149	7	a	a	DET
cana-2825	149	8	logistic	logistic	ADJ
cana-2825	149	9	activation	activation	NOUN
cana-2825	149	10	function	function	NOUN
cana-2825	149	11	,	,	PUNCT
cana-2825	149	12	so	so	ADV
cana-2825	149	13	keep	keep	VERB
cana-2825	149	14	that	that	PRON
cana-2825	149	15	in	in	ADP
cana-2825	149	16	mind	mind	NOUN
cana-2825	149	17	.	.	PUNCT
cana-2825	150	1	the	the	DET
cana-2825	150	2	updating	update	VERB
cana-2825	150	3	rule	rule	NOUN
cana-2825	150	4	will	will	AUX
cana-2825	150	5	be	be	AUX
cana-2825	150	6	somewhat	somewhat	ADV
cana-2825	150	7	modified	modify	VERB
cana-2825	150	8	by	by	ADP
cana-2825	150	9	other	other	ADJ
cana-2825	150	10	activation	activation	NOUN
cana-2825	150	11	functions	function	NOUN
cana-2825	150	12	due	due	ADP
cana-2825	150	13	to	to	ADP
cana-2825	150	14	the	the	DET
cana-2825	150	15	varied	varied	ADJ
cana-2825	150	16	derivatives	derivative	NOUN
cana-2825	150	17	being	be	AUX
cana-2825	150	18	computed	compute	VERB
cana-2825	150	19	.	.	PUNCT
cana-2825	151	1	3.3.2	3.3.2	NUM
cana-2825	151	2	automatic	automatic	ADJ
cana-2825	151	3	stacked	stack	VERB
cana-2825	151	4	encoder	encoder	NOUN
cana-2825	151	5	this	this	DET
cana-2825	151	6	paper	paper	NOUN
cana-2825	151	7	's	's	PART
cana-2825	151	8	study	study	NOUN
cana-2825	151	9	makes	make	VERB
cana-2825	151	10	use	use	NOUN
cana-2825	151	11	of	of	ADP
cana-2825	151	12	a	a	DET
cana-2825	151	13	stacked	stack	VERB
cana-2825	151	14	autoencoder	autoencoder	NOUN
cana-2825	151	15	(	(	PUNCT
cana-2825	151	16	sae	sae	PROPN
cana-2825	151	17	)	)	PUNCT
cana-2825	151	18	,	,	PUNCT
cana-2825	151	19	a	a	DET
cana-2825	151	20	distinct	distinct	ADJ
cana-2825	151	21	kind	kind	NOUN
cana-2825	151	22	of	of	ADP
cana-2825	151	23	ann	ann	PROPN
cana-2825	151	24	that	that	PRON
cana-2825	151	25	employs	employ	VERB
cana-2825	151	26	deep	deep	ADJ
cana-2825	151	27	learning	learning	NOUN
cana-2825	151	28	for	for	ADP
cana-2825	151	29	yield	yield	NOUN
cana-2825	151	30	prediction	prediction	NOUN
cana-2825	151	31	.	.	PUNCT
cana-2825	152	1	the	the	DET
cana-2825	152	2	idea	idea	NOUN
cana-2825	152	3	of	of	ADP
cana-2825	152	4	deep	deep	ADJ
cana-2825	152	5	learning	learning	NOUN
cana-2825	152	6	originated	originate	VERB
cana-2825	152	7	from	from	ADP
cana-2825	152	8	the	the	DET
cana-2825	152	9	belief	belief	NOUN
cana-2825	152	10	that	that	SCONJ
cana-2825	152	11	improved	improved	ADJ
cana-2825	152	12	generalisations	generalisation	NOUN
cana-2825	152	13	on	on	ADP
cana-2825	152	14	complicated	complicated	ADJ
cana-2825	152	15	recognition	recognition	NOUN
cana-2825	152	16	tasks	task	NOUN
cana-2825	152	17	may	may	AUX
cana-2825	152	18	be	be	AUX
cana-2825	152	19	achieved	achieve	VERB
cana-2825	152	20	by	by	ADP
cana-2825	152	21	increasing	increase	VERB
cana-2825	152	22	the	the	DET
cana-2825	152	23	modelling	modelling	NOUN
cana-2825	152	24	of	of	ADP
cana-2825	152	25	very	very	ADV
cana-2825	152	26	nonlinear	nonlinear	ADJ
cana-2825	152	27	interactions	interaction	NOUN
cana-2825	152	28	among	among	ADP
cana-2825	152	29	the	the	DET
cana-2825	152	30	variables	variable	NOUN
cana-2825	152	31	.	.	PUNCT
cana-2825	153	1	this	this	PRON
cana-2825	153	2	would	would	AUX
cana-2825	153	3	need	need	VERB
cana-2825	153	4	multiple	multiple	ADJ
cana-2825	153	5	layers	layer	NOUN
cana-2825	153	6	of	of	ADP
cana-2825	153	7	abstractions	abstraction	NOUN
cana-2825	153	8	in	in	ADP
cana-2825	153	9	feature	feature	NOUN
cana-2825	153	10	space	space	NOUN
cana-2825	153	11	.	.	PUNCT
cana-2825	154	1	one	one	NUM
cana-2825	154	2	artificial	artificial	ADJ
cana-2825	154	3	neural	neural	ADJ
cana-2825	154	4	network	network	NOUN
cana-2825	154	5	(	(	PUNCT
cana-2825	154	6	ann	ann	PROPN
cana-2825	154	7	)	)	PUNCT
cana-2825	154	8	that	that	PRON
cana-2825	154	9	aims	aim	VERB
cana-2825	154	10	to	to	PART
cana-2825	154	11	replicate	replicate	VERB
cana-2825	154	12	input	input	NOUN
cana-2825	154	13	-	-	PUNCT
cana-2825	154	14	to	to	ADP
cana-2825	154	15	-	-	PUNCT
cana-2825	154	16	output	output	NOUN
cana-2825	154	17	mapping	mapping	NOUN
cana-2825	154	18	using	use	VERB
cana-2825	154	19	a	a	DET
cana-2825	154	20	communications	communication	NOUN
cana-2825	154	21	on	on	ADP
cana-2825	154	22	applied	apply	VERB
cana-2825	154	23	nonlinear	nonlinear	ADJ
cana-2825	154	24	analysis	analysis	NOUN
cana-2825	154	25	issn	issn	NOUN
cana-2825	154	26	:	:	PUNCT
cana-2825	154	27	1074	1074	NUM
cana-2825	154	28	-	-	PUNCT
cana-2825	154	29	133x	133x	NUM
cana-2825	154	30	vol	vol	NOUN
cana-2825	154	31	32	32	NUM
cana-2825	154	32	no	no	NOUN
cana-2825	154	33	.	.	PUNCT
cana-2825	155	1	4s	4s	NUM
cana-2825	155	2	(	(	PUNCT
cana-2825	155	3	2025	2025	NUM
cana-2825	155	4	)	)	PUNCT
cana-2825	155	5	350	350	NUM
cana-2825	155	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-2825	155	7	hidden	hide	VERB
cana-2825	155	8	layer	layer	NOUN
cana-2825	155	9	to	to	PART
cana-2825	155	10	encode	encode	VERB
cana-2825	155	11	input	input	NOUN
cana-2825	155	12	is	be	AUX
cana-2825	155	13	the	the	DET
cana-2825	155	14	autoencoder	autoencoder	NOUN
cana-2825	155	15	.	.	PUNCT
cana-2825	156	1	the	the	DET
cana-2825	156	2	first	first	ADJ
cana-2825	156	3	step	step	NOUN
cana-2825	156	4	of	of	ADP
cana-2825	156	5	an	an	DET
cana-2825	156	6	autoencoder	autoencoder	NOUN
cana-2825	156	7	is	be	AUX
cana-2825	156	8	to	to	PART
cana-2825	156	9	encode	encode	VERB
cana-2825	156	10	the	the	DET
cana-2825	156	11	input	input	NOUN
cana-2825	156	12	with	with	ADP
cana-2825	156	13	the	the	DET
cana-2825	156	14	hidden	hide	VERB
cana-2825	156	15	layer	layer	NOUN
cana-2825	156	16	;	;	PUNCT
cana-2825	156	17	the	the	DET
cana-2825	156	18	second	second	NOUN
cana-2825	156	19	is	be	AUX
cana-2825	156	20	to	to	PART
cana-2825	156	21	decode	decode	VERB
cana-2825	156	22	the	the	DET
cana-2825	156	23	encoded	encode	VERB
cana-2825	156	24	values	value	NOUN
cana-2825	156	25	and	and	CCONJ
cana-2825	156	26	use	use	VERB
cana-2825	156	27	them	they	PRON
cana-2825	156	28	to	to	PART
cana-2825	156	29	rebuild	rebuild	VERB
cana-2825	156	30	the	the	DET
cana-2825	156	31	input	input	NOUN
cana-2825	156	32	.	.	PUNCT
cana-2825	157	1	the	the	DET
cana-2825	157	2	autoencoder	autoencoder	NOUN
cana-2825	157	3	model	model	NOUN
cana-2825	157	4	learns	learn	VERB
cana-2825	157	5	valuable	valuable	ADJ
cana-2825	157	6	data	datum	NOUN
cana-2825	157	7	characteristics	characteristic	NOUN
cana-2825	157	8	since	since	SCONJ
cana-2825	157	9	it	it	PRON
cana-2825	157	10	is	be	AUX
cana-2825	157	11	designed	design	VERB
cana-2825	157	12	to	to	PART
cana-2825	157	13	prioritise	prioritise	VERB
cana-2825	157	14	specific	specific	ADJ
cana-2825	157	15	input	input	NOUN
cana-2825	157	16	qualities	quality	NOUN
cana-2825	157	17	to	to	PART
cana-2825	157	18	be	be	AUX
cana-2825	157	19	duplicated	duplicate	VERB
cana-2825	157	20	.	.	PUNCT
cana-2825	158	1	this	this	PRON
cana-2825	158	2	is	be	AUX
cana-2825	158	3	the	the	DET
cana-2825	158	4	first	first	ADJ
cana-2825	158	5	step	step	NOUN
cana-2825	158	6	in	in	ADP
cana-2825	158	7	creating	create	VERB
cana-2825	158	8	a	a	DET
cana-2825	158	9	stacked	stacked	ADJ
cana-2825	158	10	autoencoder	autoencoder	NOUN
cana-2825	158	11	.	.	PUNCT
cana-2825	159	1	firstly	firstly	ADV
cana-2825	159	2	,	,	PUNCT
cana-2825	159	3	train	train	VERB
cana-2825	159	4	the	the	DET
cana-2825	159	5	only	only	ADJ
cana-2825	159	6	autoencoder	autoencoder	NOUN
cana-2825	159	7	using	use	VERB
cana-2825	159	8	backpropagation	backpropagation	NOUN
cana-2825	159	9	,	,	PUNCT
cana-2825	159	10	using	use	VERB
cana-2825	159	11	the	the	DET
cana-2825	159	12	inputs	input	NOUN
cana-2825	159	13	as	as	ADP
cana-2825	159	14	both	both	CCONJ
cana-2825	159	15	the	the	DET
cana-2825	159	16	goal	goal	NOUN
cana-2825	159	17	values	value	NOUN
cana-2825	159	18	and	and	CCONJ
cana-2825	159	19	the	the	DET
cana-2825	159	20	training	training	NOUN
cana-2825	159	21	set	set	NOUN
cana-2825	159	22	.	.	PUNCT
cana-2825	160	1	in	in	ADP
cana-2825	160	2	the	the	DET
cana-2825	160	3	second	second	ADJ
cana-2825	160	4	phase	phase	NOUN
cana-2825	160	5	,	,	PUNCT
cana-2825	160	6	an	an	DET
cana-2825	160	7	additional	additional	ADJ
cana-2825	160	8	hidden	hide	VERB
cana-2825	160	9	-	-	PUNCT
cana-2825	160	10	layer	layer	NOUN
cana-2825	160	11	net	net	NOUN
cana-2825	160	12	is	be	AUX
cana-2825	160	13	superimposed	superimpose	VERB
cana-2825	160	14	on	on	ADP
cana-2825	160	15	top	top	NOUN
cana-2825	160	16	of	of	ADP
cana-2825	160	17	the	the	DET
cana-2825	160	18	current	current	ADJ
cana-2825	160	19	autoencoder	autoencoder	NOUN
cana-2825	160	20	.	.	PUNCT
cana-2825	161	1	this	this	DET
cana-2825	161	2	network	network	NOUN
cana-2825	161	3	strives	strive	VERB
cana-2825	161	4	to	to	PART
cana-2825	161	5	recover	recover	VERB
cana-2825	161	6	the	the	DET
cana-2825	161	7	hidden	hidden	ADJ
cana-2825	161	8	values	value	NOUN
cana-2825	161	9	that	that	PRON
cana-2825	161	10	were	be	AUX
cana-2825	161	11	created	create	VERB
cana-2825	161	12	by	by	ADP
cana-2825	161	13	the	the	DET
cana-2825	161	14	previous	previous	ADJ
cana-2825	161	15	autoencoder	autoencoder	NOUN
cana-2825	161	16	's	's	PART
cana-2825	161	17	hidden	hide	VERB
cana-2825	161	18	layer	layer	NOUN
cana-2825	161	19	.	.	PUNCT
cana-2825	162	1	the	the	DET
cana-2825	162	2	input	input	NOUN
cana-2825	162	3	layer	layer	NOUN
cana-2825	162	4	of	of	ADP
cana-2825	162	5	the	the	DET
cana-2825	162	6	new	new	ADJ
cana-2825	162	7	network	network	NOUN
cana-2825	162	8	is	be	AUX
cana-2825	162	9	mapped	map	VERB
cana-2825	162	10	to	to	ADP
cana-2825	162	11	those	those	DET
cana-2825	162	12	values	value	NOUN
cana-2825	162	13	.	.	PUNCT
cana-2825	163	1	a	a	DET
cana-2825	163	2	"	"	PUNCT
cana-2825	163	3	stacked	stack	VERB
cana-2825	163	4	"	"	PUNCT
cana-2825	163	5	autoencoder	autoencoder	NOUN
cana-2825	163	6	is	be	AUX
cana-2825	163	7	the	the	DET
cana-2825	163	8	product	product	NOUN
cana-2825	163	9	of	of	ADP
cana-2825	163	10	this	this	DET
cana-2825	163	11	procedure	procedure	NOUN
cana-2825	163	12	repeated	repeat	VERB
cana-2825	163	13	while	while	SCONJ
cana-2825	163	14	linking	link	VERB
cana-2825	163	15	the	the	DET
cana-2825	163	16	learnt	learnt	ADJ
cana-2825	163	17	autoencoders	autoencoder	NOUN
cana-2825	163	18	(	(	PUNCT
cana-2825	163	19	figure	figure	NOUN
cana-2825	163	20	2	2	NUM
cana-2825	163	21	)	)	PUNCT
cana-2825	163	22	.	.	PUNCT
cana-2825	164	1	figure	figure	NOUN
cana-2825	164	2	.	.	PUNCT
cana-2825	165	1	2	2	NUM
cana-2825	165	2	a	a	DET
cana-2825	165	3	softmax	softmax	NOUN
cana-2825	165	4	classifier	classifier	NOUN
cana-2825	165	5	combined	combine	VERB
cana-2825	165	6	with	with	ADP
cana-2825	165	7	a	a	DET
cana-2825	165	8	stacked	stack	VERB
cana-2825	165	9	autoencoder	autoencoder	NOUN
cana-2825	165	10	the	the	DET
cana-2825	165	11	idea	idea	NOUN
cana-2825	165	12	behind	behind	ADP
cana-2825	165	13	stacking	stack	VERB
cana-2825	165	14	autoencoders	autoencoder	NOUN
cana-2825	165	15	is	be	AUX
cana-2825	165	16	that	that	SCONJ
cana-2825	165	17	it	it	PRON
cana-2825	165	18	creates	create	VERB
cana-2825	165	19	a	a	DET
cana-2825	165	20	hierarchical	hierarchical	ADJ
cana-2825	165	21	abstraction	abstraction	NOUN
cana-2825	165	22	of	of	ADP
cana-2825	165	23	characteristics	characteristic	NOUN
cana-2825	165	24	for	for	ADP
cana-2825	165	25	the	the	DET
cana-2825	165	26	data	datum	NOUN
cana-2825	165	27	under	under	ADP
cana-2825	165	28	analysis	analysis	NOUN
cana-2825	165	29	,	,	PUNCT
cana-2825	165	30	as	as	SCONJ
cana-2825	165	31	each	each	DET
cana-2825	165	32	hidden	hide	VERB
cana-2825	165	33	layer	layer	NOUN
cana-2825	165	34	corresponds	correspond	VERB
cana-2825	165	35	to	to	ADP
cana-2825	165	36	a	a	DET
cana-2825	165	37	set	set	NOUN
cana-2825	165	38	of	of	ADP
cana-2825	165	39	detectors	detector	NOUN
cana-2825	165	40	for	for	ADP
cana-2825	165	41	features	feature	NOUN
cana-2825	165	42	that	that	PRON
cana-2825	165	43	target	target	VERB
cana-2825	165	44	the	the	DET
cana-2825	165	45	signals	signal	NOUN
cana-2825	165	46	of	of	ADP
cana-2825	165	47	the	the	DET
cana-2825	165	48	preceding	precede	VERB
cana-2825	165	49	layer	layer	NOUN
cana-2825	165	50	.	.	PUNCT
cana-2825	166	1	the	the	DET
cana-2825	166	2	last	last	ADJ
cana-2825	166	3	stage	stage	NOUN
cana-2825	166	4	in	in	ADP
cana-2825	166	5	stacking	stack	VERB
cana-2825	166	6	autoencoders	autoencoder	NOUN
cana-2825	166	7	for	for	ADP
cana-2825	166	8	training	training	NOUN
cana-2825	166	9	is	be	AUX
cana-2825	166	10	to	to	PART
cana-2825	166	11	put	put	VERB
cana-2825	166	12	another	another	DET
cana-2825	166	13	learning	learning	NOUN
cana-2825	166	14	-	-	PUNCT
cana-2825	166	15	focused	focus	VERB
cana-2825	166	16	network	network	NOUN
cana-2825	166	17	on	on	ADP
cana-2825	166	18	top	top	NOUN
cana-2825	166	19	.	.	PUNCT
cana-2825	167	1	after	after	SCONJ
cana-2825	167	2	this	this	PRON
cana-2825	167	3	is	be	AUX
cana-2825	167	4	complete	complete	ADJ
cana-2825	167	5	,	,	PUNCT
cana-2825	167	6	by	by	ADP
cana-2825	167	7	training	train	VERB
cana-2825	167	8	the	the	DET
cana-2825	167	9	weights	weight	NOUN
cana-2825	167	10	collectively	collectively	ADV
cana-2825	167	11	,	,	PUNCT
cana-2825	167	12	the	the	DET
cana-2825	167	13	ideal	ideal	ADJ
cana-2825	167	14	mapping	mapping	NOUN
cana-2825	167	15	between	between	ADP
cana-2825	167	16	the	the	DET
cana-2825	167	17	initial	initial	ADJ
cana-2825	167	18	set	set	NOUN
cana-2825	167	19	of	of	ADP
cana-2825	167	20	inputs	input	NOUN
cana-2825	167	21	and	and	CCONJ
cana-2825	167	22	the	the	DET
cana-2825	167	23	desired	desire	VERB
cana-2825	167	24	yield	yield	NOUN
cana-2825	167	25	/	/	SYM
cana-2825	167	26	protein	protein	NOUN
cana-2825	167	27	levels	level	NOUN
cana-2825	167	28	might	might	AUX
cana-2825	167	29	be	be	AUX
cana-2825	167	30	discovered	discover	VERB
cana-2825	167	31	.	.	PUNCT
cana-2825	168	1	3.4	3.4	NUM
cana-2825	168	2	geographic	geographic	ADJ
cana-2825	168	3	sample	sample	NOUN
cana-2825	168	4	the	the	DET
cana-2825	168	5	technique	technique	NOUN
cana-2825	168	6	known	know	VERB
cana-2825	168	7	as	as	ADP
cana-2825	168	8	"	"	PUNCT
cana-2825	168	9	spatial	spatial	ADJ
cana-2825	168	10	sampling	sampling	NOUN
cana-2825	168	11	"	"	PUNCT
cana-2825	168	12	involves	involve	VERB
cana-2825	168	13	gathering	gather	VERB
cana-2825	168	14	data	datum	NOUN
cana-2825	168	15	in	in	ADP
cana-2825	168	16	a	a	DET
cana-2825	168	17	two	two	NUM
cana-2825	168	18	-	-	PUNCT
cana-2825	168	19	dimensional	dimensional	ADJ
cana-2825	168	20	area	area	NOUN
cana-2825	168	21	.	.	PUNCT
cana-2825	169	1	as	as	SCONJ
cana-2825	169	2	many	many	ADJ
cana-2825	169	3	geographical	geographical	ADJ
cana-2825	169	4	variations	variation	NOUN
cana-2825	169	5	of	of	ADP
cana-2825	169	6	the	the	DET
cana-2825	169	7	study	study	NOUN
cana-2825	169	8	variables	variable	NOUN
cana-2825	169	9	as	as	ADP
cana-2825	169	10	possible	possible	ADJ
cana-2825	169	11	are	be	AUX
cana-2825	169	12	often	often	ADV
cana-2825	169	13	accounted	account	VERB
cana-2825	169	14	for	for	ADP
cana-2825	169	15	in	in	ADP
cana-2825	169	16	the	the	DET
cana-2825	169	17	sampling	sample	VERB
cana-2825	169	18	strategy	strategy	NOUN
cana-2825	169	19	.	.	PUNCT
cana-2825	170	1	additional	additional	ADJ
cana-2825	170	2	measurements	measurement	NOUN
cana-2825	170	3	may	may	AUX
cana-2825	170	4	be	be	AUX
cana-2825	170	5	taken	take	VERB
cana-2825	170	6	after	after	SCONJ
cana-2825	170	7	the	the	DET
cana-2825	170	8	first	first	ADJ
cana-2825	170	9	data	datum	NOUN
cana-2825	170	10	has	have	AUX
cana-2825	170	11	been	be	AUX
cana-2825	170	12	collected	collect	VERB
cana-2825	170	13	and	and	CCONJ
cana-2825	170	14	recorded	record	VERB
cana-2825	170	15	,	,	PUNCT
cana-2825	170	16	depending	depend	VERB
cana-2825	170	17	on	on	ADP
cana-2825	170	18	the	the	DET
cana-2825	170	19	data	datum	NOUN
cana-2825	170	20	's	's	PART
cana-2825	170	21	fluctuations	fluctuation	NOUN
cana-2825	170	22	.	.	PUNCT
cana-2825	171	1	criteria	criterion	NOUN
cana-2825	171	2	to	to	PART
cana-2825	171	3	optimise	optimise	VERB
cana-2825	171	4	the	the	DET
cana-2825	171	5	data	datum	NOUN
cana-2825	171	6	often	often	ADV
cana-2825	171	7	inform	inform	VERB
cana-2825	171	8	these	these	DET
cana-2825	171	9	further	further	ADJ
cana-2825	171	10	measures	measure	NOUN
cana-2825	171	11	.	.	PUNCT
cana-2825	172	1	because	because	SCONJ
cana-2825	172	2	certain	certain	ADJ
cana-2825	172	3	factors	factor	NOUN
cana-2825	172	4	are	be	AUX
cana-2825	172	5	more	more	ADV
cana-2825	172	6	important	important	ADJ
cana-2825	172	7	in	in	ADP
cana-2825	172	8	some	some	DET
cana-2825	172	9	regions	region	NOUN
cana-2825	172	10	than	than	ADP
cana-2825	172	11	others	other	NOUN
cana-2825	172	12	,	,	PUNCT
cana-2825	172	13	or	or	CCONJ
cana-2825	172	14	because	because	SCONJ
cana-2825	172	15	of	of	ADP
cana-2825	172	16	differences	difference	NOUN
cana-2825	172	17	in	in	ADP
cana-2825	172	18	topography	topography	NOUN
cana-2825	172	19	,	,	PUNCT
cana-2825	172	20	the	the	DET
cana-2825	172	21	final	final	ADJ
cana-2825	172	22	data	datum	NOUN
cana-2825	172	23	obtained	obtain	VERB
cana-2825	172	24	may	may	AUX
cana-2825	172	25	be	be	AUX
cana-2825	172	26	skewed	skew	VERB
cana-2825	172	27	.	.	PUNCT
cana-2825	173	1	in	in	SCONJ
cana-2825	173	2	comparison	comparison	NOUN
cana-2825	173	3	to	to	ADP
cana-2825	173	4	data	datum	NOUN
cana-2825	173	5	that	that	PRON
cana-2825	173	6	is	be	AUX
cana-2825	173	7	evenly	evenly	ADV
cana-2825	173	8	spaced	space	VERB
cana-2825	173	9	,	,	PUNCT
cana-2825	173	10	this	this	DET
cana-2825	173	11	data	data	NOUN
cana-2825	173	12	is	be	AUX
cana-2825	173	13	far	far	ADV
cana-2825	173	14	more	more	ADV
cana-2825	173	15	difficult	difficult	ADJ
cana-2825	173	16	to	to	PART
cana-2825	173	17	analyse	analyse	VERB
cana-2825	173	18	due	due	ADP
cana-2825	173	19	to	to	ADP
cana-2825	173	20	its	its	PRON
cana-2825	173	21	uneven	uneven	ADJ
cana-2825	173	22	spacing	spacing	NOUN
cana-2825	173	23	.	.	PUNCT
cana-2825	174	1	thus	thus	ADV
cana-2825	174	2	,	,	PUNCT
cana-2825	174	3	it	it	PRON
cana-2825	174	4	is	be	AUX
cana-2825	174	5	crucial	crucial	ADJ
cana-2825	174	6	to	to	PART
cana-2825	174	7	handle	handle	VERB
cana-2825	174	8	these	these	DET
cana-2825	174	9	anomalies	anomaly	NOUN
cana-2825	174	10	to	to	PART
cana-2825	174	11	conduct	conduct	VERB
cana-2825	174	12	the	the	DET
cana-2825	174	13	dataset	dataset	NOUN
cana-2825	174	14	analyses	analyse	VERB
cana-2825	174	15	more	more	ADV
cana-2825	174	16	effectively	effectively	ADV
cana-2825	174	17	.	.	PUNCT
cana-2825	175	1	because	because	SCONJ
cana-2825	175	2	the	the	DET
cana-2825	175	3	fields	field	NOUN
cana-2825	175	4	researched	research	VERB
cana-2825	175	5	&	&	CCONJ
cana-2825	175	6	the	the	DET
cana-2825	175	7	prescription	prescription	NOUN
cana-2825	175	8	maps	map	NOUN
cana-2825	175	9	generated	generate	VERB
cana-2825	175	10	for	for	ADP
cana-2825	175	11	them	they	PRON
cana-2825	175	12	are	be	AUX
cana-2825	175	13	grid	grid	NOUN
cana-2825	175	14	-	-	PUNCT
cana-2825	175	15	based	base	VERB
cana-2825	175	16	,	,	PUNCT
cana-2825	175	17	a	a	DET
cana-2825	175	18	kind	kind	NOUN
cana-2825	175	19	of	of	ADP
cana-2825	175	20	spatial	spatial	ADJ
cana-2825	175	21	sampling	sampling	NOUN
cana-2825	175	22	is	be	AUX
cana-2825	175	23	inherent	inherent	ADJ
cana-2825	175	24	to	to	ADP
cana-2825	175	25	this	this	DET
cana-2825	175	26	study	study	NOUN
cana-2825	175	27	because	because	SCONJ
cana-2825	175	28	of	of	ADP
cana-2825	175	29	the	the	DET
cana-2825	175	30	grid	grid	NOUN
cana-2825	175	31	-	-	PUNCT
cana-2825	175	32	based	base	VERB
cana-2825	175	33	layout	layout	NOUN
cana-2825	175	34	of	of	ADP
cana-2825	175	35	the	the	DET
cana-2825	175	36	fields	field	NOUN
cana-2825	175	37	.	.	PUNCT
cana-2825	176	1	since	since	SCONJ
cana-2825	176	2	each	each	DET
cana-2825	176	3	grid	grid	NOUN
cana-2825	176	4	cell	cell	NOUN
cana-2825	176	5	contains	contain	VERB
cana-2825	176	6	data	datum	NOUN
cana-2825	176	7	points	point	NOUN
cana-2825	176	8	,	,	PUNCT
cana-2825	176	9	it	it	PRON
cana-2825	176	10	is	be	AUX
cana-2825	176	11	reasonable	reasonable	ADJ
cana-2825	176	12	to	to	ADP
cana-2825	176	13	sample	sample	NOUN
cana-2825	176	14	from	from	ADP
cana-2825	176	15	both	both	CCONJ
cana-2825	176	16	the	the	DET
cana-2825	176	17	target	target	NOUN
cana-2825	176	18	cell	cell	NOUN
cana-2825	176	19	and	and	CCONJ
cana-2825	176	20	its	its	PRON
cana-2825	176	21	nearby	nearby	ADJ
cana-2825	176	22	neighbours	neighbour	NOUN
cana-2825	176	23	.	.	PUNCT
cana-2825	177	1	both	both	CCONJ
cana-2825	177	2	the	the	DET
cana-2825	177	3	von	von	PROPN
cana-2825	177	4	neumann	neumann	PROPN
cana-2825	177	5	and	and	CCONJ
cana-2825	177	6	moore	moore	PROPN
cana-2825	177	7	communications	communication	NOUN
cana-2825	177	8	on	on	ADP
cana-2825	177	9	applied	apply	VERB
cana-2825	177	10	nonlinear	nonlinear	ADJ
cana-2825	177	11	analysis	analysis	NOUN
cana-2825	177	12	issn	issn	NOUN
cana-2825	177	13	:	:	PUNCT
cana-2825	177	14	1074	1074	NUM
cana-2825	177	15	-	-	PUNCT
cana-2825	177	16	133x	133x	NUM
cana-2825	177	17	vol	vol	NOUN
cana-2825	177	18	32	32	NUM
cana-2825	177	19	no	no	NOUN
cana-2825	177	20	.	.	PUNCT
cana-2825	178	1	4s	4s	NUM
cana-2825	178	2	(	(	PUNCT
cana-2825	178	3	2025	2025	NUM
cana-2825	178	4	)	)	PUNCT
cana-2825	178	5	351	351	NUM
cana-2825	178	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	178	7	neighbourhoods	neighbourhood	NOUN
cana-2825	178	8	are	be	AUX
cana-2825	178	9	typical	typical	ADJ
cana-2825	178	10	for	for	ADP
cana-2825	178	11	this	this	DET
cana-2825	178	12	kind	kind	NOUN
cana-2825	178	13	of	of	ADP
cana-2825	178	14	sample	sample	NOUN
cana-2825	178	15	(	(	PUNCT
cana-2825	178	16	figure	figure	NOUN
cana-2825	178	17	3	3	NUM
cana-2825	178	18	left	left	ADJ
cana-2825	178	19	and	and	CCONJ
cana-2825	178	20	3	3	NUM
cana-2825	178	21	right	right	ADJ
cana-2825	178	22	,	,	PUNCT
cana-2825	178	23	respectively	respectively	ADV
cana-2825	178	24	)	)	PUNCT
cana-2825	178	25	.	.	PUNCT
cana-2825	179	1	our	our	PRON
cana-2825	179	2	spatial	spatial	ADJ
cana-2825	179	3	sampling	sampling	NOUN
cana-2825	179	4	method	method	NOUN
cana-2825	179	5	relies	rely	VERB
cana-2825	179	6	on	on	ADP
cana-2825	179	7	the	the	DET
cana-2825	179	8	moore	moore	PROPN
cana-2825	179	9	neighbourhood	neighbourhood	NOUN
cana-2825	179	10	because	because	SCONJ
cana-2825	179	11	it	it	PRON
cana-2825	179	12	gives	give	VERB
cana-2825	179	13	a	a	DET
cana-2825	179	14	more	more	ADV
cana-2825	179	15	complete	complete	ADJ
cana-2825	179	16	picture	picture	NOUN
cana-2825	179	17	of	of	ADP
cana-2825	179	18	the	the	DET
cana-2825	179	19	surrounding	surround	VERB
cana-2825	179	20	samples	sample	NOUN
cana-2825	179	21	.	.	PUNCT
cana-2825	180	1	for	for	ADP
cana-2825	180	2	each	each	DET
cana-2825	180	3	given	give	VERB
cana-2825	180	4	cell	cell	NOUN
cana-2825	180	5	,	,	PUNCT
cana-2825	180	6	we	we	PRON
cana-2825	180	7	averaged	average	VERB
cana-2825	180	8	the	the	DET
cana-2825	180	9	values	value	NOUN
cana-2825	180	10	of	of	ADP
cana-2825	180	11	all	all	DET
cana-2825	180	12	the	the	DET
cana-2825	180	13	points	point	NOUN
cana-2825	180	14	within	within	ADV
cana-2825	180	15	.	.	PUNCT
cana-2825	181	1	the	the	DET
cana-2825	181	2	location	location	NOUN
cana-2825	181	3	information	information	NOUN
cana-2825	181	4	for	for	ADP
cana-2825	181	5	every	every	DET
cana-2825	181	6	point	point	NOUN
cana-2825	181	7	of	of	ADP
cana-2825	181	8	data	datum	NOUN
cana-2825	181	9	is	be	AUX
cana-2825	181	10	derived	derive	VERB
cana-2825	181	11	from	from	ADP
cana-2825	181	12	the	the	DET
cana-2825	181	13	mean	mean	ADJ
cana-2825	181	14	values	value	NOUN
cana-2825	181	15	of	of	ADP
cana-2825	181	16	the	the	DET
cana-2825	181	17	eight	eight	NUM
cana-2825	181	18	cells	cell	NOUN
cana-2825	181	19	immediately	immediately	ADV
cana-2825	181	20	around	around	ADP
cana-2825	181	21	it	it	PRON
cana-2825	181	22	.	.	PUNCT
cana-2825	182	1	two	two	NUM
cana-2825	182	2	data	datum	NOUN
cana-2825	182	3	adjustments	adjustment	NOUN
cana-2825	182	4	were	be	AUX
cana-2825	182	5	used	use	VERB
cana-2825	182	6	to	to	PART
cana-2825	182	7	reduce	reduce	VERB
cana-2825	182	8	noise	noise	NOUN
cana-2825	182	9	and	and	CCONJ
cana-2825	182	10	smooth	smooth	VERB
cana-2825	182	11	the	the	DET
cana-2825	182	12	information	information	NOUN
cana-2825	182	13	for	for	ADP
cana-2825	182	14	more	more	ADV
cana-2825	182	15	consistent	consistent	ADJ
cana-2825	182	16	spatial	spatial	ADJ
cana-2825	182	17	information	information	NOUN
cana-2825	182	18	.	.	PUNCT
cana-2825	183	1	one	one	NUM
cana-2825	183	2	was	be	AUX
cana-2825	183	3	to	to	PART
cana-2825	183	4	use	use	VERB
cana-2825	183	5	the	the	DET
cana-2825	183	6	average	average	ADJ
cana-2825	183	7	method	method	NOUN
cana-2825	183	8	already	already	ADV
cana-2825	183	9	discussed	discuss	VERB
cana-2825	183	10	,	,	PUNCT
cana-2825	183	11	and	and	CCONJ
cana-2825	183	12	the	the	DET
cana-2825	183	13	other	other	ADJ
cana-2825	183	14	was	be	AUX
cana-2825	183	15	to	to	PART
cana-2825	183	16	make	make	VERB
cana-2825	183	17	the	the	DET
cana-2825	183	18	grid	grid	NOUN
cana-2825	183	19	cells	cell	NOUN
cana-2825	183	20	larger	large	ADJ
cana-2825	183	21	so	so	SCONJ
cana-2825	183	22	that	that	SCONJ
cana-2825	183	23	more	more	ADJ
cana-2825	183	24	points	point	NOUN
cana-2825	183	25	could	could	AUX
cana-2825	183	26	fit	fit	VERB
cana-2825	183	27	into	into	ADP
cana-2825	183	28	each	each	DET
cana-2825	183	29	cell	cell	NOUN
cana-2825	183	30	.	.	PUNCT
cana-2825	184	1	figure	figure	NOUN
cana-2825	184	2	.	.	PUNCT
cana-2825	185	1	3	3	NUM
cana-2825	185	2	sample	sample	NOUN
cana-2825	185	3	settings	setting	NOUN
cana-2825	185	4	for	for	ADP
cana-2825	185	5	neighbourhoods	neighbourhood	NOUN
cana-2825	185	6	.	.	PUNCT
cana-2825	186	1	"	"	PUNCT
cana-2825	186	2	c	c	X
cana-2825	186	3	"	"	PUNCT
cana-2825	186	4	is	be	AUX
cana-2825	186	5	the	the	DET
cana-2825	186	6	symbol	symbol	NOUN
cana-2825	186	7	for	for	ADP
cana-2825	186	8	the	the	DET
cana-2825	186	9	centre	centre	NOUN
cana-2825	186	10	cell	cell	NOUN
cana-2825	186	11	.	.	PUNCT
cana-2825	187	1	the	the	DET
cana-2825	187	2	neighbourhoods	neighbourhood	NOUN
cana-2825	187	3	of	of	ADP
cana-2825	187	4	von	von	PROPN
cana-2825	187	5	neuman	neuman	PROPN
cana-2825	187	6	and	and	CCONJ
cana-2825	187	7	moore	moore	PROPN
cana-2825	187	8	appear	appear	VERB
cana-2825	187	9	on	on	ADP
cana-2825	187	10	the	the	DET
cana-2825	187	11	left	left	NOUN
cana-2825	187	12	and	and	CCONJ
cana-2825	187	13	right	right	ADJ
cana-2825	187	14	,	,	PUNCT
cana-2825	187	15	respectively	respectively	ADV
cana-2825	187	16	.	.	PUNCT
cana-2825	188	1	4	4	X
cana-2825	188	2	.	.	X
cana-2825	188	3	experiments	experiment	NOUN
cana-2825	188	4	section	section	VERB
cana-2825	188	5	4.1	4.1	NUM
cana-2825	188	6	,	,	PUNCT
cana-2825	188	7	covers	cover	VERB
cana-2825	188	8	the	the	DET
cana-2825	188	9	specifics	specific	NOUN
cana-2825	188	10	of	of	ADP
cana-2825	188	11	evaluating	evaluate	VERB
cana-2825	188	12	several	several	ADJ
cana-2825	188	13	ml	ml	NOUN
cana-2825	188	14	and	and	CCONJ
cana-2825	188	15	ss	ss	NOUN
cana-2825	188	16	methods	method	NOUN
cana-2825	188	17	.	.	PUNCT
cana-2825	189	1	section	section	NOUN
cana-2825	189	2	4.2	4.2	NUM
cana-2825	189	3	displays	display	NOUN
cana-2825	189	4	and	and	CCONJ
cana-2825	189	5	compares	compare	VERB
cana-2825	189	6	the	the	DET
cana-2825	189	7	results	result	NOUN
cana-2825	189	8	of	of	ADP
cana-2825	189	9	the	the	DET
cana-2825	189	10	four	four	NUM
cana-2825	189	11	well	well	ADV
cana-2825	189	12	-	-	PUNCT
cana-2825	189	13	established	establish	VERB
cana-2825	189	14	methods	method	NOUN
cana-2825	189	15	:	:	PUNCT
cana-2825	189	16	artificial	artificial	ADJ
cana-2825	189	17	neural	neural	ADJ
cana-2825	189	18	networks	network	NOUN
cana-2825	189	19	(	(	PUNCT
cana-2825	189	20	ann	ann	PROPN
cana-2825	189	21	)	)	PUNCT
cana-2825	189	22	,	,	PUNCT
cana-2825	189	23	support	support	VERB
cana-2825	189	24	vector	vector	NOUN
cana-2825	189	25	machines	machine	NOUN
cana-2825	189	26	(	(	PUNCT
cana-2825	189	27	sse	sse	PROPN
cana-2825	189	28	)	)	PUNCT
cana-2825	189	29	,	,	PUNCT
cana-2825	189	30	not	not	PART
cana-2825	189	31	linear	linear	ADJ
cana-2825	189	32	regression	regression	NOUN
cana-2825	189	33	,	,	PUNCT
cana-2825	189	34	however	however	ADV
cana-2825	189	35	,	,	PUNCT
cana-2825	189	36	and	and	CCONJ
cana-2825	189	37	line	line	NOUN
cana-2825	189	38	regression	regression	NOUN
cana-2825	189	39	.	.	PUNCT
cana-2825	190	1	the	the	DET
cana-2825	190	2	next	next	ADJ
cana-2825	190	3	stage	stage	NOUN
cana-2825	190	4	is	be	AUX
cana-2825	190	5	to	to	PART
cana-2825	190	6	compare	compare	VERB
cana-2825	190	7	the	the	DET
cana-2825	190	8	k	k	NOUN
cana-2825	190	9	-	-	PUNCT
cana-2825	190	10	nearest	near	ADJ
cana-2825	190	11	neighbour	neighbour	ADJ
cana-2825	190	12	algorithm	algorithm	NOUN
cana-2825	190	13	-	-	PUNCT
cana-2825	190	14	sampled	sample	VERB
cana-2825	190	15	data	datum	NOUN
cana-2825	190	16	with	with	ADP
cana-2825	190	17	non	non	ADJ
cana-2825	190	18	-	-	ADJ
cana-2825	190	19	sampled	sample	VERB
cana-2825	190	20	data	datum	NOUN
cana-2825	190	21	about	about	ADP
cana-2825	190	22	its	its	PRON
cana-2825	190	23	geographic	geographic	ADJ
cana-2825	190	24	distribution	distribution	NOUN
cana-2825	190	25	.	.	PUNCT
cana-2825	191	1	these	these	DET
cana-2825	191	2	results	result	NOUN
cana-2825	191	3	are	be	AUX
cana-2825	191	4	discussed	discuss	VERB
cana-2825	191	5	and	and	CCONJ
cana-2825	191	6	explained	explain	VERB
cana-2825	191	7	in	in	ADP
cana-2825	191	8	section	section	NOUN
cana-2825	191	9	4.3	4.3	NUM
cana-2825	191	10	,	,	PUNCT
cana-2825	191	11	which	which	PRON
cana-2825	191	12	is	be	AUX
cana-2825	191	13	the	the	DET
cana-2825	191	14	last	last	ADJ
cana-2825	191	15	section	section	NOUN
cana-2825	191	16	.	.	PUNCT
cana-2825	192	1	4.1	4.1	NUM
cana-2825	192	2	the	the	DET
cana-2825	192	3	approach	approach	NOUN
cana-2825	192	4	utilising	utilise	VERB
cana-2825	192	5	the	the	DET
cana-2825	192	6	fertiliser	fertiliser	NOUN
cana-2825	192	7	rate	rate	NOUN
cana-2825	192	8	as	as	ADP
cana-2825	192	9	a	a	DET
cana-2825	192	10	variable	variable	NOUN
cana-2825	192	11	,	,	PUNCT
cana-2825	192	12	a	a	DET
cana-2825	192	13	basic	basic	ADJ
cana-2825	192	14	linear	linear	ADJ
cana-2825	192	15	regression	regression	NOUN
cana-2825	192	16	across	across	ADP
cana-2825	192	17	the	the	DET
cana-2825	192	18	protein	protein	NOUN
cana-2825	192	19	&	&	CCONJ
cana-2825	192	20	yield	yield	NOUN
cana-2825	192	21	points	point	NOUN
cana-2825	192	22	is	be	AUX
cana-2825	192	23	utilised	utilise	VERB
cana-2825	192	24	.	.	PUNCT
cana-2825	193	1	a	a	DET
cana-2825	193	2	hyperbolic	hyperbolic	ADJ
cana-2825	193	3	curve	curve	NOUN
cana-2825	193	4	was	be	AUX
cana-2825	193	5	fitted	fit	VERB
cana-2825	193	6	across	across	ADP
cana-2825	193	7	the	the	DET
cana-2825	193	8	data	datum	NOUN
cana-2825	193	9	using	use	VERB
cana-2825	193	10	the	the	DET
cana-2825	193	11	nonlinear	nonlinear	ADJ
cana-2825	193	12	model	model	NOUN
cana-2825	193	13	.	.	PUNCT
cana-2825	194	1	because	because	SCONJ
cana-2825	194	2	there	there	PRON
cana-2825	194	3	is	be	VERB
cana-2825	194	4	a	a	DET
cana-2825	194	5	saturation	saturation	NOUN
cana-2825	194	6	threshold	threshold	NOUN
cana-2825	194	7	for	for	ADP
cana-2825	194	8	fertiliser	fertiliser	NOUN
cana-2825	194	9	rates	rate	NOUN
cana-2825	194	10	beyond	beyond	ADP
cana-2825	194	11	which	which	DET
cana-2825	194	12	yield	yield	NOUN
cana-2825	194	13	&	&	CCONJ
cana-2825	194	14	protein	protein	NOUN
cana-2825	194	15	values	value	NOUN
cana-2825	194	16	stop	stop	VERB
cana-2825	194	17	increasing	increase	VERB
cana-2825	194	18	,	,	PUNCT
cana-2825	194	19	a	a	DET
cana-2825	194	20	hyperbolic	hyperbolic	ADJ
cana-2825	194	21	fit	fit	NOUN
cana-2825	194	22	is	be	AUX
cana-2825	194	23	used	use	VERB
cana-2825	194	24	.	.	PUNCT
cana-2825	195	1	create	create	VERB
cana-2825	195	2	a	a	DET
cana-2825	195	3	total	total	NOUN
cana-2825	195	4	of	of	ADP
cana-2825	195	5	6	6	NUM
cana-2825	195	6	models	model	NOUN
cana-2825	195	7	by	by	ADP
cana-2825	195	8	implementing	implement	VERB
cana-2825	195	9	and	and	CCONJ
cana-2825	195	10	evaluating	evaluate	VERB
cana-2825	195	11	both	both	CCONJ
cana-2825	195	12	spatial	spatial	ADJ
cana-2825	195	13	and	and	CCONJ
cana-2825	195	14	nonspatial	nonspatial	ADJ
cana-2825	195	15	versions	version	NOUN
cana-2825	195	16	of	of	ADP
cana-2825	195	17	the	the	DET
cana-2825	195	18	ann	ann	PROPN
cana-2825	195	19	as	as	ADV
cana-2825	195	20	well	well	ADV
cana-2825	195	21	as	as	ADP
cana-2825	195	22	the	the	DET
cana-2825	195	23	sae	sae	PROPN
cana-2825	195	24	.	.	PUNCT
cana-2825	196	1	it	it	PRON
cana-2825	196	2	was	be	AUX
cana-2825	196	3	determined	determine	VERB
cana-2825	196	4	which	which	DET
cana-2825	196	5	design	design	NOUN
cana-2825	196	6	yielded	yield	VERB
cana-2825	196	7	the	the	DET
cana-2825	196	8	greatest	great	ADJ
cana-2825	196	9	results	result	NOUN
cana-2825	196	10	by	by	ADP
cana-2825	196	11	experimenting	experiment	VERB
cana-2825	196	12	with	with	ADP
cana-2825	196	13	various	various	ADJ
cana-2825	196	14	settings	setting	NOUN
cana-2825	196	15	.	.	PUNCT
cana-2825	197	1	a	a	DET
cana-2825	197	2	few	few	ADJ
cana-2825	197	3	examples	example	NOUN
cana-2825	197	4	of	of	ADP
cana-2825	197	5	these	these	DET
cana-2825	197	6	parameters	parameter	NOUN
cana-2825	197	7	include	include	VERB
cana-2825	197	8	the	the	DET
cana-2825	197	9	total	total	ADJ
cana-2825	197	10	number	number	NOUN
cana-2825	197	11	of	of	ADP
cana-2825	197	12	ann	ann	PROPN
cana-2825	197	13	and	and	CCONJ
cana-2825	197	14	sae	sae	PROPN
cana-2825	197	15	epochs	epoch	NOUN
cana-2825	197	16	,	,	PUNCT
cana-2825	197	17	the	the	DET
cana-2825	197	18	total	total	ADJ
cana-2825	197	19	number	number	NOUN
cana-2825	197	20	of	of	ADP
cana-2825	197	21	layers	layer	NOUN
cana-2825	197	22	that	that	PRON
cana-2825	197	23	are	be	AUX
cana-2825	197	24	hidden	hide	VERB
cana-2825	197	25	,	,	PUNCT
cana-2825	197	26	and	and	CCONJ
cana-2825	197	27	the	the	DET
cana-2825	197	28	total	total	ADJ
cana-2825	197	29	number	number	NOUN
cana-2825	197	30	of	of	ADP
cana-2825	197	31	nodes	node	NOUN
cana-2825	197	32	that	that	PRON
cana-2825	197	33	are	be	AUX
cana-2825	197	34	hidden	hide	VERB
cana-2825	197	35	within	within	ADP
cana-2825	197	36	each	each	DET
cana-2825	197	37	layer	layer	NOUN
cana-2825	197	38	.	.	PUNCT
cana-2825	198	1	depending	depend	VERB
cana-2825	198	2	on	on	ADP
cana-2825	198	3	the	the	DET
cana-2825	198	4	field	field	NOUN
cana-2825	198	5	's	's	PART
cana-2825	198	6	accessible	accessible	ADJ
cana-2825	198	7	features	feature	NOUN
cana-2825	198	8	,	,	PUNCT
cana-2825	198	9	the	the	DET
cana-2825	198	10	ann	ann	PROPN
cana-2825	198	11	's	's	PART
cana-2825	198	12	optimum	optimum	ADJ
cana-2825	198	13	performance	performance	NOUN
cana-2825	198	14	was	be	AUX
cana-2825	198	15	attained	attain	VERB
cana-2825	198	16	with	with	ADP
cana-2825	198	17	just	just	ADV
cana-2825	198	18	one	one	NUM
cana-2825	198	19	hidden	hide	VERB
cana-2825	198	20	layer	layer	NOUN
cana-2825	198	21	containing	contain	VERB
cana-2825	198	22	15	15	NUM
cana-2825	198	23	–	–	SYM
cana-2825	198	24	100	100	NUM
cana-2825	198	25	hidden	hide	VERB
cana-2825	198	26	nodes	node	NOUN
cana-2825	198	27	;	;	PUNCT
cana-2825	198	28	however	however	ADV
cana-2825	198	29	,	,	PUNCT
cana-2825	198	30	these	these	DET
cana-2825	198	31	values	value	NOUN
cana-2825	198	32	were	be	AUX
cana-2825	198	33	changed	change	VERB
cana-2825	198	34	for	for	ADP
cana-2825	198	35	each	each	DET
cana-2825	198	36	dataset	dataset	NOUN
cana-2825	198	37	.	.	PUNCT
cana-2825	199	1	for	for	ADP
cana-2825	199	2	non	non	ADJ
cana-2825	199	3	-	-	ADJ
cana-2825	199	4	spatial	spatial	ADJ
cana-2825	199	5	data	datum	NOUN
cana-2825	199	6	,	,	PUNCT
cana-2825	199	7	the	the	DET
cana-2825	199	8	sae	sae	PROPN
cana-2825	199	9	uses	use	VERB
cana-2825	199	10	two	two	NUM
cana-2825	199	11	hidden	hidden	ADJ
cana-2825	199	12	layers	layer	NOUN
cana-2825	199	13	;	;	PUNCT
cana-2825	199	14	for	for	ADP
cana-2825	199	15	spatial	spatial	ADJ
cana-2825	199	16	data	datum	NOUN
cana-2825	199	17	,	,	PUNCT
cana-2825	199	18	it	it	PRON
cana-2825	199	19	uses	use	VERB
cana-2825	199	20	three	three	NUM
cana-2825	199	21	,	,	PUNCT
cana-2825	199	22	with	with	ADP
cana-2825	199	23	the	the	DET
cana-2825	199	24	number	number	NOUN
cana-2825	199	25	of	of	ADP
cana-2825	199	26	hidden	hide	VERB
cana-2825	199	27	nodes	node	NOUN
cana-2825	199	28	decreasing	decrease	VERB
cana-2825	199	29	with	with	ADP
cana-2825	199	30	each	each	DET
cana-2825	199	31	successive	successive	ADJ
cana-2825	199	32	layer	layer	NOUN
cana-2825	199	33	.	.	PUNCT
cana-2825	200	1	starting	start	VERB
cana-2825	200	2	with	with	ADP
cana-2825	200	3	the	the	DET
cana-2825	200	4	top	top	ADJ
cana-2825	200	5	layer	layer	NOUN
cana-2825	200	6	and	and	CCONJ
cana-2825	200	7	working	work	VERB
cana-2825	200	8	down	down	ADP
cana-2825	200	9	the	the	DET
cana-2825	200	10	way	way	NOUN
cana-2825	200	11	,	,	PUNCT
cana-2825	200	12	utilise	utilise	VERB
cana-2825	200	13	500	500	NUM
cana-2825	200	14	,	,	PUNCT
cana-2825	200	15	250	250	NUM
cana-2825	200	16	,	,	PUNCT
cana-2825	200	17	and	and	CCONJ
cana-2825	200	18	125	125	NUM
cana-2825	200	19	concealed	conceal	VERB
cana-2825	200	20	nodes	node	NOUN
cana-2825	200	21	for	for	ADP
cana-2825	200	22	the	the	DET
cana-2825	200	23	spatial	spatial	ADJ
cana-2825	200	24	information	information	NOUN
cana-2825	200	25	,	,	PUNCT
cana-2825	200	26	respectively	respectively	ADV
cana-2825	200	27	.	.	PUNCT
cana-2825	201	1	the	the	DET
cana-2825	201	2	consistency	consistency	NOUN
cana-2825	201	3	of	of	ADP
cana-2825	201	4	the	the	DET
cana-2825	201	5	number	number	NOUN
cana-2825	201	6	of	of	ADP
cana-2825	201	7	concealed	conceal	VERB
cana-2825	201	8	nodes	node	NOUN
cana-2825	201	9	for	for	ADP
cana-2825	201	10	nonspatial	nonspatial	ADJ
cana-2825	201	11	information	information	NOUN
cana-2825	201	12	varied	varied	ADJ
cana-2825	201	13	with	with	ADP
cana-2825	201	14	the	the	DET
cana-2825	201	15	available	available	ADJ
cana-2825	201	16	data	data	NOUN
cana-2825	201	17	points	point	NOUN
cana-2825	201	18	.	.	PUNCT
cana-2825	202	1	two	two	NUM
cana-2825	202	2	distinct	distinct	ADJ
cana-2825	202	3	metrics	metric	NOUN
cana-2825	202	4	,	,	PUNCT
cana-2825	202	5	the	the	DET
cana-2825	202	6	root	root	NOUN
cana-2825	202	7	mean	mean	VERB
cana-2825	202	8	squared	square	VERB
cana-2825	202	9	communications	communication	NOUN
cana-2825	202	10	on	on	ADP
cana-2825	202	11	applied	apply	VERB
cana-2825	202	12	nonlinear	nonlinear	ADJ
cana-2825	202	13	analysis	analysis	NOUN
cana-2825	202	14	issn	issn	NOUN
cana-2825	202	15	:	:	PUNCT
cana-2825	202	16	1074	1074	NUM
cana-2825	202	17	-	-	PUNCT
cana-2825	202	18	133x	133x	NUM
cana-2825	202	19	vol	vol	NOUN
cana-2825	202	20	32	32	NUM
cana-2825	202	21	no	no	NOUN
cana-2825	202	22	.	.	PUNCT
cana-2825	203	1	4s	4s	NUM
cana-2825	203	2	(	(	PUNCT
cana-2825	203	3	2025	2025	NUM
cana-2825	203	4	)	)	PUNCT
cana-2825	203	5	352	352	NUM
cana-2825	203	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	203	7	error	error	NOUN
cana-2825	203	8	and	and	CCONJ
cana-2825	203	9	the	the	DET
cana-2825	203	10	coefficient	coefficient	NOUN
cana-2825	203	11	of	of	ADP
cana-2825	203	12	determination	determination	NOUN
cana-2825	203	13	(	(	PUNCT
cana-2825	203	14	r²	r²	PROPN
cana-2825	203	15	)	)	PUNCT
cana-2825	203	16	,	,	PUNCT
cana-2825	203	17	were	be	AUX
cana-2825	203	18	utilised	utilise	VERB
cana-2825	203	19	to	to	PART
cana-2825	203	20	assess	assess	VERB
cana-2825	203	21	each	each	DET
cana-2825	203	22	model	model	NOUN
cana-2825	203	23	.	.	PUNCT
cana-2825	204	1	utilise	utilise	VERB
cana-2825	204	2	the	the	DET
cana-2825	204	3	10	10	NUM
cana-2825	204	4	-	-	ADJ
cana-2825	204	5	fold	fold	ADJ
cana-2825	204	6	cross	cross	NOUN
cana-2825	204	7	-	-	NOUN
cana-2825	204	8	validation	validation	NOUN
cana-2825	204	9	to	to	PART
cana-2825	204	10	determine	determine	VERB
cana-2825	204	11	each	each	PRON
cana-2825	204	12	of	of	ADP
cana-2825	204	13	these	these	PRON
cana-2825	204	14	,	,	PUNCT
cana-2825	204	15	and	and	CCONJ
cana-2825	204	16	then	then	ADV
cana-2825	204	17	average	average	VERB
cana-2825	204	18	the	the	DET
cana-2825	204	19	findings	finding	NOUN
cana-2825	204	20	over	over	ADP
cana-2825	204	21	all	all	PRON
cana-2825	204	22	of	of	ADP
cana-2825	204	23	the	the	DET
cana-2825	204	24	folds	fold	NOUN
cana-2825	204	25	.	.	PUNCT
cana-2825	205	1	researchers	researcher	NOUN
cana-2825	205	2	performed	perform	VERB
cana-2825	205	3	a	a	DET
cana-2825	205	4	paired	pair	VERB
cana-2825	205	5	student	student	NOUN
cana-2825	205	6	t	t	PROPN
cana-2825	205	7	-	-	PUNCT
cana-2825	205	8	test	test	NOUN
cana-2825	205	9	with	with	ADP
cana-2825	205	10	bonferroni	bonferroni	NOUN
cana-2825	205	11	alteration	alteration	NOUN
cana-2825	205	12	to	to	PART
cana-2825	205	13	look	look	VERB
cana-2825	205	14	at	at	ADP
cana-2825	205	15	the	the	DET
cana-2825	205	16	difference	difference	NOUN
cana-2825	205	17	in	in	ADP
cana-2825	205	18	means	mean	NOUN
cana-2825	205	19	.	.	PUNCT
cana-2825	206	1	utilising	utilise	VERB
cana-2825	206	2	the	the	DET
cana-2825	206	3	information	information	NOUN
cana-2825	206	4	gathered	gather	VERB
cana-2825	206	5	from	from	ADP
cana-2825	206	6	four	four	NUM
cana-2825	206	7	separate	separate	ADJ
cana-2825	206	8	fields	field	NOUN
cana-2825	206	9	,	,	PUNCT
cana-2825	206	10	all	all	PRON
cana-2825	206	11	of	of	ADP
cana-2825	206	12	which	which	PRON
cana-2825	206	13	belonged	belong	VERB
cana-2825	206	14	to	to	PART
cana-2825	206	15	separate	separate	VERB
cana-2825	206	16	farmers	farmer	NOUN
cana-2825	206	17	.	.	PUNCT
cana-2825	207	1	produce	produce	VERB
cana-2825	207	2	and	and	CCONJ
cana-2825	207	3	protein	protein	NOUN
cana-2825	207	4	levels	level	NOUN
cana-2825	207	5	for	for	ADP
cana-2825	207	6	a	a	DET
cana-2825	207	7	given	give	VERB
cana-2825	207	8	spot	spot	NOUN
cana-2825	207	9	on	on	ADP
cana-2825	207	10	the	the	DET
cana-2825	207	11	field	field	NOUN
cana-2825	207	12	,	,	PUNCT
cana-2825	207	13	together	together	ADV
cana-2825	207	14	with	with	ADP
cana-2825	207	15	details	detail	NOUN
cana-2825	207	16	about	about	ADP
cana-2825	207	17	that	that	DET
cana-2825	207	18	spot	spot	NOUN
cana-2825	207	19	's	's	PART
cana-2825	207	20	location	location	NOUN
cana-2825	207	21	and	and	CCONJ
cana-2825	207	22	slope	slope	NOUN
cana-2825	207	23	,	,	PUNCT
cana-2825	207	24	nitrogen	nitrogen	NOUN
cana-2825	207	25	application	application	NOUN
cana-2825	207	26	rates	rate	NOUN
cana-2825	207	27	,	,	PUNCT
cana-2825	207	28	observed	observed	ADJ
cana-2825	207	29	precipitation	precipitation	NOUN
cana-2825	207	30	,	,	PUNCT
cana-2825	207	31	and	and	CCONJ
cana-2825	207	32	normalised	normalise	VERB
cana-2825	207	33	difference	difference	NOUN
cana-2825	207	34	vegetation	vegetation	NOUN
cana-2825	207	35	index	index	NOUN
cana-2825	207	36	(	(	PUNCT
cana-2825	207	37	ndvi	ndvi	PROPN
cana-2825	207	38	)	)	PUNCT
cana-2825	207	39	from	from	ADP
cana-2825	207	40	prior	prior	ADJ
cana-2825	207	41	years	year	NOUN
cana-2825	207	42	make	make	VERB
cana-2825	207	43	up	up	ADP
cana-2825	207	44	the	the	DET
cana-2825	207	45	data	datum	NOUN
cana-2825	207	46	.	.	PUNCT
cana-2825	208	1	based	base	VERB
cana-2825	208	2	on	on	ADP
cana-2825	208	3	the	the	DET
cana-2825	208	4	additional	additional	ADJ
cana-2825	208	5	data	datum	NOUN
cana-2825	208	6	that	that	PRON
cana-2825	208	7	is	be	AUX
cana-2825	208	8	given	give	VERB
cana-2825	208	9	,	,	PUNCT
cana-2825	208	10	the	the	DET
cana-2825	208	11	models	model	NOUN
cana-2825	208	12	that	that	PRON
cana-2825	208	13	have	have	AUX
cana-2825	208	14	been	be	AUX
cana-2825	208	15	put	put	VERB
cana-2825	208	16	into	into	ADP
cana-2825	208	17	place	place	NOUN
cana-2825	208	18	are	be	AUX
cana-2825	208	19	attempting	attempt	VERB
cana-2825	208	20	to	to	PART
cana-2825	208	21	forecast	forecast	VERB
cana-2825	208	22	yields	yield	NOUN
cana-2825	208	23	and	and	CCONJ
cana-2825	208	24	protein	protein	NOUN
cana-2825	208	25	levels	level	NOUN
cana-2825	208	26	.	.	PUNCT
cana-2825	209	1	both	both	CCONJ
cana-2825	209	2	the	the	DET
cana-2825	209	3	yield	yield	NOUN
cana-2825	209	4	and	and	CCONJ
cana-2825	209	5	the	the	DET
cana-2825	209	6	protein	protein	NOUN
cana-2825	209	7	values	value	NOUN
cana-2825	209	8	were	be	AUX
cana-2825	209	9	from	from	ADP
cana-2825	209	10	already	already	ADV
cana-2825	209	11	-	-	PUNCT
cana-2825	209	12	harvested	harvest	VERB
cana-2825	209	13	fields	field	NOUN
cana-2825	209	14	as	as	SCONJ
cana-2825	209	15	the	the	DET
cana-2825	209	16	recommended	recommend	VERB
cana-2825	209	17	map	map	NOUN
cana-2825	209	18	was	be	AUX
cana-2825	209	19	made	make	VERB
cana-2825	209	20	using	use	VERB
cana-2825	209	21	information	information	NOUN
cana-2825	209	22	from	from	ADP
cana-2825	209	23	previous	previous	ADJ
cana-2825	209	24	harvest	harvest	NOUN
cana-2825	209	25	bins.the	bins.the	DET
cana-2825	209	26	cell	cell	NOUN
cana-2825	209	27	densities	density	NOUN
cana-2825	209	28	in	in	ADP
cana-2825	209	29	prescription	prescription	NOUN
cana-2825	209	30	charts	chart	NOUN
cana-2825	209	31	might	might	AUX
cana-2825	209	32	vary	vary	VERB
cana-2825	209	33	according	accord	VERB
cana-2825	209	34	to	to	ADP
cana-2825	209	35	the	the	DET
cana-2825	209	36	field	field	NOUN
cana-2825	209	37	and	and	CCONJ
cana-2825	209	38	grid	grid	NOUN
cana-2825	209	39	size	size	NOUN
cana-2825	209	40	.	.	PUNCT
cana-2825	210	1	table	table	NOUN
cana-2825	210	2	1	1	NUM
cana-2825	210	3	shows	show	VERB
cana-2825	210	4	that	that	SCONJ
cana-2825	210	5	there	there	PRON
cana-2825	210	6	is	be	VERB
cana-2825	210	7	a	a	DET
cana-2825	210	8	lot	lot	NOUN
cana-2825	210	9	of	of	ADP
cana-2825	210	10	variation	variation	NOUN
cana-2825	210	11	in	in	ADP
cana-2825	210	12	the	the	DET
cana-2825	210	13	data	datum	NOUN
cana-2825	210	14	about	about	ADP
cana-2825	210	15	protein	protein	NOUN
cana-2825	210	16	and	and	CCONJ
cana-2825	210	17	yield	yield	VERB
cana-2825	210	18	points	point	NOUN
cana-2825	210	19	for	for	ADP
cana-2825	210	20	each	each	DET
cana-2825	210	21	location	location	NOUN
cana-2825	210	22	.	.	PUNCT
cana-2825	211	1	since	since	SCONJ
cana-2825	211	2	only	only	ADJ
cana-2825	211	3	locations	location	NOUN
cana-2825	211	4	with	with	ADP
cana-2825	211	5	eight	eight	NUM
cana-2825	211	6	neighbouring	neighbouring	ADJ
cana-2825	211	7	cells	cell	NOUN
cana-2825	211	8	containing	contain	VERB
cana-2825	211	9	data	datum	NOUN
cana-2825	211	10	are	be	AUX
cana-2825	211	11	taken	take	VERB
cana-2825	211	12	into	into	ADP
cana-2825	211	13	account	account	NOUN
cana-2825	211	14	throughout	throughout	ADP
cana-2825	211	15	the	the	DET
cana-2825	211	16	spatial	spatial	ADJ
cana-2825	211	17	sampling	sampling	NOUN
cana-2825	211	18	method	method	NOUN
cana-2825	211	19	,	,	PUNCT
cana-2825	211	20	the	the	DET
cana-2825	211	21	amount	amount	NOUN
cana-2825	211	22	of	of	ADP
cana-2825	211	23	information	information	NOUN
cana-2825	211	24	gradually	gradually	ADV
cana-2825	211	25	decreases	decrease	VERB
cana-2825	211	26	.	.	PUNCT
cana-2825	212	1	table.1	table.1	VERB
cana-2825	212	2	data	data	NOUN
cana-2825	212	3	quantity	quantity	NOUN
cana-2825	212	4	for	for	ADP
cana-2825	212	5	every	every	DET
cana-2825	212	6	field	field	NOUN
cana-2825	212	7	.	.	PUNCT
cana-2825	213	1	sec35mid	sec35mid	PROPN
cana-2825	213	2	sre1314	sre1314	ADJ
cana-2825	213	3	davidson	davidson	PROPN
cana-2825	213	4	mw	mw	PROPN
cana-2825	213	5	carlin	carlin	PROPN
cana-2825	213	6	w	w	PROPN
cana-2825	213	7	protein	protein	NOUN
cana-2825	213	8	points	point	VERB
cana-2825	213	9	1020	1020	NUM
cana-2825	213	10	2999	2999	NUM
cana-2825	213	11	561	561	NUM
cana-2825	213	12	656	656	NUM
cana-2825	213	13	yield	yield	NOUN
cana-2825	213	14	points	point	NOUN
cana-2825	213	15	17874	17874	NUM
cana-2825	213	16	24647	24647	NUM
cana-2825	213	17	11803	11803	NUM
cana-2825	213	18	15622	15622	NUM
cana-2825	213	19	4.2	4.2	NUM
cana-2825	213	20	result	result	NOUN
cana-2825	213	21	table	table	NOUN
cana-2825	213	22	2	2	NUM
cana-2825	213	23	displays	display	VERB
cana-2825	213	24	the	the	DET
cana-2825	213	25	root	root	NOUN
cana-2825	213	26	-	-	PUNCT
cana-2825	213	27	mean	mean	ADJ
cana-2825	213	28	-	-	PUNCT
cana-2825	213	29	squared	square	VERB
cana-2825	213	30	error	error	NOUN
cana-2825	213	31	(	(	PUNCT
cana-2825	213	32	rmse	rmse	NOUN
cana-2825	213	33	)	)	PUNCT
cana-2825	213	34	for	for	ADP
cana-2825	213	35	yield	yield	NOUN
cana-2825	213	36	predictions	prediction	NOUN
cana-2825	213	37	,	,	PUNCT
cana-2825	213	38	whereas	whereas	SCONJ
cana-2825	213	39	table	table	NOUN
cana-2825	213	40	2displays	2displays	NUM
cana-2825	213	41	the	the	DET
cana-2825	213	42	results	result	NOUN
cana-2825	213	43	for	for	ADP
cana-2825	213	44	protein	protein	NOUN
cana-2825	213	45	predictions	prediction	NOUN
cana-2825	213	46	.	.	PUNCT
cana-2825	214	1	table	table	NOUN
cana-2825	214	2	3	3	NUM
cana-2825	214	3	shows	show	VERB
cana-2825	214	4	that	that	SCONJ
cana-2825	214	5	the	the	DET
cana-2825	214	6	non	non	ADJ
cana-2825	214	7	-	-	ADJ
cana-2825	214	8	linear	linear	ADJ
cana-2825	214	9	system	system	NOUN
cana-2825	214	10	did	do	AUX
cana-2825	214	11	not	not	PART
cana-2825	214	12	offer	offer	VERB
cana-2825	214	13	any	any	DET
cana-2825	214	14	outcomes	outcome	NOUN
cana-2825	214	15	for	for	ADP
cana-2825	214	16	protein	protein	NOUN
cana-2825	214	17	prediction	prediction	NOUN
cana-2825	214	18	.	.	PUNCT
cana-2825	215	1	the	the	DET
cana-2825	215	2	boldface	boldface	NOUN
cana-2825	215	3	indicates	indicate	VERB
cana-2825	215	4	statistically	statistically	ADV
cana-2825	215	5	significant	significant	ADJ
cana-2825	215	6	differences	difference	NOUN
cana-2825	215	7	in	in	ADP
cana-2825	215	8	rmse	rmse	ADJ
cana-2825	215	9	values	value	NOUN
cana-2825	215	10	.	.	PUNCT
cana-2825	216	1	field	field	NOUN
cana-2825	216	2	measure	measure	NOUN
cana-2825	216	3	linear	linear	PROPN
cana-2825	216	4	non	non	PROPN
cana-2825	216	5	-	-	PROPN
cana-2825	216	6	lin	lin	PROPN
cana-2825	216	7	ann	ann	PROPN
cana-2825	216	8	ann	ann	PROPN
cana-2825	216	9	sp	sp	ADP
cana-2825	216	10	sae	sae	PROPN
cana-2825	216	11	sae	sae	PROPN
cana-2825	217	1	sp	sp	ADP
cana-2825	217	2	sec35mid	sec35mid	PROPN
cana-2825	217	3	rmse	rmse	NOUN
cana-2825	217	4	10.17	10.17	NUM
cana-2825	217	5	10.02	10.02	NUM
cana-2825	217	6	10.65	10.65	NUM
cana-2825	217	7	8.98	8.98	NUM
cana-2825	217	8	10.08	10.08	NUM
cana-2825	217	9	8.96	8.96	NUM
cana-2825	217	10	𝑅2	𝑅2	NOUN
cana-2825	217	11	30.04	30.04	NUM
cana-2825	217	12	52.67	52.67	NUM
cana-2825	217	13	24.08	24.08	NUM
cana-2825	217	14	45.16	45.16	NUM
cana-2825	217	15	53.96	53.96	NUM
cana-2825	217	16	65.79	65.79	NUM
cana-2825	217	17	sre1314	sre1314	ADJ
cana-2825	217	18	rmse	rmse	PROPN
cana-2825	217	19	11.24	11.24	NUM
cana-2825	217	20	11.26	11.26	NUM
cana-2825	217	21	11.52	11.52	NUM
cana-2825	217	22	11.06	11.06	NUM
cana-2825	217	23	10.88	10.88	NUM
cana-2825	217	24	10.16	10.16	NUM
cana-2825	217	25	𝑅2	𝑅2	NOUN
cana-2825	217	26	1.38	1.38	NUM
cana-2825	217	27	14.79	14.79	NUM
cana-2825	217	28	9.17	9.17	NUM
cana-2825	217	29	20.68	20.68	NUM
cana-2825	217	30	17.68	17.68	NUM
cana-2825	217	31	32.68	32.68	NUM
cana-2825	217	32	david	david	PROPN
cana-2825	217	33	rmse	rmse	PROPN
cana-2825	217	34	15.26	15.26	NUM
cana-2825	217	35	15.93	15.93	NUM
cana-2825	217	36	16.37	16.37	NUM
cana-2825	217	37	12.48	12.48	NUM
cana-2825	217	38	16.04	16.04	NUM
cana-2825	217	39	12.07	12.07	NUM
cana-2825	217	40	𝑅2	𝑅2	NOUN
cana-2825	217	41	38.95	38.95	NUM
cana-2825	217	42	36.94	36.94	NUM
cana-2825	217	43	30.47	30.47	NUM
cana-2825	217	44	50.65	50.65	NUM
cana-2825	217	45	35.17	35.17	NUM
cana-2825	217	46	59.36	59.36	NUM
cana-2825	217	47	carlin	carlin	PROPN
cana-2825	217	48	rmse	rmse	PROPN
cana-2825	217	49	12.08	12.08	NUM
cana-2825	217	50	10.21	10.21	NUM
cana-2825	217	51	10.24	10.24	NUM
cana-2825	217	52	8.07	8.07	NUM
cana-2825	217	53	9.94	9.94	NUM
cana-2825	217	54	9.16	9.16	NUM
cana-2825	217	55	𝑅2	𝑅2	NOUN
cana-2825	217	56	1.46	1.46	NUM
cana-2825	217	57	6.78	6.78	NUM
cana-2825	217	58	-4.31	-4.31	NUM
cana-2825	217	59	16.18	16.18	NUM
cana-2825	217	60	11.48	11.48	NUM
cana-2825	217	61	9.69	9.69	NUM
cana-2825	217	62	table	table	NOUN
cana-2825	217	63	.	.	PUNCT
cana-2825	218	1	2	2	NUM
cana-2825	218	2	forecasted	forecast	VERB
cana-2825	218	3	yields	yield	NOUN
cana-2825	218	4	per	per	ADP
cana-2825	218	5	field	field	NOUN
cana-2825	218	6	.	.	PUNCT
cana-2825	219	1	emphasised	emphasise	VERB
cana-2825	219	2	are	be	AUX
cana-2825	219	3	the	the	DET
cana-2825	219	4	notable	notable	ADJ
cana-2825	219	5	variations	variation	NOUN
cana-2825	219	6	.	.	PUNCT
cana-2825	220	1	for	for	ADP
cana-2825	220	2	geographic	geographic	ADJ
cana-2825	220	3	data	datum	NOUN
cana-2825	220	4	,	,	PUNCT
cana-2825	220	5	the	the	DET
cana-2825	220	6	sign	sign	NOUN
cana-2825	220	7	"	"	PUNCT
cana-2825	220	8	sp	sp	NOUN
cana-2825	220	9	"	"	PUNCT
cana-2825	220	10	is	be	AUX
cana-2825	220	11	equivalent	equivalent	ADJ
cana-2825	220	12	.	.	PUNCT
cana-2825	221	1	pitch	pitch	NOUN
cana-2825	221	2	measure	measure	NOUN
cana-2825	221	3	linear	linear	PROPN
cana-2825	221	4	non	non	PROPN
cana-2825	221	5	-	-	PROPN
cana-2825	221	6	lin	lin	PROPN
cana-2825	221	7	ann	ann	PROPN
cana-2825	221	8	ann	ann	PROPN
cana-2825	221	9	sp	sp	ADP
cana-2825	221	10	sae	sae	PROPN
cana-2825	221	11	sae	sae	PROPN
cana-2825	221	12	sp	sp	ADP
cana-2825	221	13	sec35mid	sec35mid	PROPN
cana-2825	221	14	rmse	rmse	NOUN
cana-2825	221	15	1.41	1.41	NUM
cana-2825	221	16	n	n	CCONJ
cana-2825	221	17	-	-	PUNCT
cana-2825	221	18	a	a	PRON
cana-2825	221	19	1.45	1.45	NUM
cana-2825	221	20	1.23	1.23	NUM
cana-2825	221	21	1.98	1.98	NUM
cana-2825	221	22	1.97	1.97	NUM
cana-2825	221	23	𝑅2	𝑅2	NOUN
cana-2825	221	24	24.61	24.61	NUM
cana-2825	221	25	n	n	CCONJ
cana-2825	221	26	-	-	PUNCT
cana-2825	221	27	a	a	DET
cana-2825	221	28	23.14	23.14	NUM
cana-2825	221	29	49.73	49.73	NUM
cana-2825	221	30	0.79	0.79	NUM
cana-2825	221	31	17.42	17.42	NUM
cana-2825	221	32	sre1314	sre1314	NOUN
cana-2825	221	33	rmse	rmse	PROPN
cana-2825	221	34	1.23	1.23	NUM
cana-2825	221	35	n	n	CCONJ
cana-2825	221	36	-	-	PUNCT
cana-2825	221	37	a	a	PRON
cana-2825	221	38	1.17	1.17	NUM
cana-2825	221	39	0.91	0.91	NUM
cana-2825	221	40	1.16	1.16	NUM
cana-2825	221	41	1.14	1.14	NUM
cana-2825	221	42	𝑅2	𝑅2	NOUN
cana-2825	221	43	-56.97	-56.97	PROPN
cana-2825	221	44	n	n	CCONJ
cana-2825	221	45	-	-	PUNCT
cana-2825	221	46	a	a	DET
cana-2825	221	47	-41.38	-41.38	PROPN
cana-2825	221	48	11.65	11.65	NUM
cana-2825	221	49	0.42	0.42	NUM
cana-2825	221	50	5.71	5.71	NUM
cana-2825	221	51	communications	communication	NOUN
cana-2825	221	52	on	on	ADP
cana-2825	221	53	applied	apply	VERB
cana-2825	221	54	nonlinear	nonlinear	ADJ
cana-2825	221	55	analysis	analysis	NOUN
cana-2825	221	56	issn	issn	NOUN
cana-2825	221	57	:	:	PUNCT
cana-2825	221	58	1074	1074	NUM
cana-2825	221	59	-	-	PUNCT
cana-2825	221	60	133x	133x	NUM
cana-2825	221	61	vol	vol	NOUN
cana-2825	221	62	32	32	NUM
cana-2825	221	63	no	no	NOUN
cana-2825	221	64	.	.	PUNCT
cana-2825	222	1	4s	4s	NUM
cana-2825	222	2	(	(	PUNCT
cana-2825	222	3	2025	2025	NUM
cana-2825	222	4	)	)	PUNCT
cana-2825	222	5	353	353	NUM
cana-2825	222	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	222	7	david	david	PROPN
cana-2825	222	8	rmse	rmse	PROPN
cana-2825	222	9	1.69	1.69	NUM
cana-2825	222	10	n	n	CCONJ
cana-2825	222	11	-	-	PUNCT
cana-2825	222	12	a	a	DET
cana-2825	222	13	1.61	1.61	NUM
cana-2825	222	14	1.48	1.48	NUM
cana-2825	222	15	1.68	1.68	NUM
cana-2825	222	16	1.62	1.62	NUM
cana-2825	222	17	𝑅2	𝑅2	NOUN
cana-2825	222	18	-32.21	-32.21	PROPN
cana-2825	222	19	n	n	CCONJ
cana-2825	222	20	-	-	PUNCT
cana-2825	222	21	a	a	DET
cana-2825	222	22	-15.69	-15.69	NOUN
cana-2825	222	23	-9.61	-9.61	NOUN
cana-2825	222	24	0.06	0.06	NUM
cana-2825	222	25	0.06	0.06	NUM
cana-2825	222	26	carlin	carlin	PROPN
cana-2825	222	27	rmse	rmse	PROPN
cana-2825	222	28	1.18	1.18	NUM
cana-2825	222	29	n	n	CCONJ
cana-2825	222	30	-	-	PUNCT
cana-2825	222	31	a	a	PRON
cana-2825	222	32	1.19	1.19	NUM
cana-2825	222	33	1.14	1.14	NUM
cana-2825	222	34	1.38	1.38	NUM
cana-2825	222	35	1.28	1.28	NUM
cana-2825	222	36	𝑅2	𝑅2	NOUN
cana-2825	222	37	11.16	11.16	NUM
cana-2825	222	38	n	n	CCONJ
cana-2825	222	39	-	-	PUNCT
cana-2825	222	40	a	a	DET
cana-2825	222	41	11.13	11.13	NUM
cana-2825	222	42	16.46	16.46	NUM
cana-2825	222	43	4.83	4.83	NUM
cana-2825	222	44	0.49	0.49	NUM
cana-2825	222	45	table	table	NOUN
cana-2825	222	46	.	.	PUNCT
cana-2825	223	1	3	3	NUM
cana-2825	223	2	protein	protein	NOUN
cana-2825	223	3	prediction	prediction	NOUN
cana-2825	223	4	for	for	ADP
cana-2825	223	5	all	all	DET
cana-2825	223	6	areas	area	NOUN
cana-2825	223	7	.	.	PUNCT
cana-2825	224	1	bold	bold	ADJ
cana-2825	224	2	text	text	NOUN
cana-2825	224	3	indicates	indicate	VERB
cana-2825	224	4	statistically	statistically	ADV
cana-2825	224	5	significant	significant	ADJ
cana-2825	224	6	differences	difference	NOUN
cana-2825	224	7	.	.	PUNCT
cana-2825	225	1	"	"	PUNCT
cana-2825	225	2	sp	sp	NOUN
cana-2825	225	3	"	"	PUNCT
cana-2825	225	4	represents	represent	VERB
cana-2825	225	5	spatial	spatial	ADJ
cana-2825	225	6	data	datum	NOUN
cana-2825	225	7	.	.	PUNCT
cana-2825	226	1	4.3	4.3	NUM
cana-2825	226	2	discussion	discussion	NOUN
cana-2825	226	3	the	the	DET
cana-2825	226	4	results	result	NOUN
cana-2825	226	5	of	of	ADP
cana-2825	226	6	this	this	DET
cana-2825	226	7	study	study	NOUN
cana-2825	226	8	on	on	ADP
cana-2825	226	9	yield	yield	NOUN
cana-2825	226	10	prediction	prediction	NOUN
cana-2825	226	11	indicate	indicate	VERB
cana-2825	226	12	that	that	SCONJ
cana-2825	226	13	geographical	geographical	ADJ
cana-2825	226	14	data	datum	NOUN
cana-2825	226	15	often	often	ADV
cana-2825	226	16	enhances	enhance	VERB
cana-2825	226	17	a	a	DET
cana-2825	226	18	model	model	NOUN
cana-2825	226	19	's	's	PART
cana-2825	226	20	precision	precision	NOUN
cana-2825	226	21	.	.	PUNCT
cana-2825	227	1	aside	aside	ADV
cana-2825	227	2	from	from	ADP
cana-2825	227	3	one	one	NUM
cana-2825	227	4	area	area	NOUN
cana-2825	227	5	,	,	PUNCT
cana-2825	227	6	the	the	DET
cana-2825	227	7	spatial	spatial	PROPN
cana-2825	227	8	ann	ann	PROPN
cana-2825	227	9	&	&	CCONJ
cana-2825	227	10	spatial	spatial	PROPN
cana-2825	227	11	sae	sae	PROPN
cana-2825	227	12	exhibit	exhibit	VERB
cana-2825	227	13	much	much	ADJ
cana-2825	227	14	superior	superior	ADJ
cana-2825	227	15	performance	performance	NOUN
cana-2825	227	16	compared	compare	VERB
cana-2825	227	17	to	to	ADP
cana-2825	227	18	the	the	DET
cana-2825	227	19	other	other	ADJ
cana-2825	227	20	models	model	NOUN
cana-2825	227	21	.	.	PUNCT
cana-2825	228	1	the	the	DET
cana-2825	228	2	absence	absence	NOUN
cana-2825	228	3	of	of	ADP
cana-2825	228	4	advancement	advancement	NOUN
cana-2825	228	5	in	in	ADP
cana-2825	228	6	this	this	DET
cana-2825	228	7	area	area	NOUN
cana-2825	228	8	may	may	AUX
cana-2825	228	9	result	result	VERB
cana-2825	228	10	from	from	ADP
cana-2825	228	11	the	the	DET
cana-2825	228	12	distribution	distribution	NOUN
cana-2825	228	13	of	of	ADP
cana-2825	228	14	yield	yield	NOUN
cana-2825	228	15	sites	site	NOUN
cana-2825	228	16	;	;	PUNCT
cana-2825	228	17	these	these	DET
cana-2825	228	18	spots	spot	NOUN
cana-2825	228	19	are	be	AUX
cana-2825	228	20	densely	densely	ADV
cana-2825	228	21	clustered	clustered	ADJ
cana-2825	228	22	along	along	ADP
cana-2825	228	23	the	the	DET
cana-2825	228	24	field	field	NOUN
cana-2825	228	25	's	's	PART
cana-2825	228	26	length	length	NOUN
cana-2825	228	27	but	but	CCONJ
cana-2825	228	28	are	be	AUX
cana-2825	228	29	much	much	ADV
cana-2825	228	30	more	more	ADV
cana-2825	228	31	dispersed	disperse	VERB
cana-2825	228	32	throughout	throughout	ADP
cana-2825	228	33	its	its	PRON
cana-2825	228	34	breadth	breadth	NOUN
cana-2825	228	35	compared	compare	VERB
cana-2825	228	36	to	to	ADP
cana-2825	228	37	other	other	ADJ
cana-2825	228	38	fields	field	NOUN
cana-2825	228	39	.	.	PUNCT
cana-2825	229	1	this	this	PRON
cana-2825	229	2	successfully	successfully	ADV
cana-2825	229	3	augments	augment	VERB
cana-2825	229	4	the	the	DET
cana-2825	229	5	point	point	NOUN
cana-2825	229	6	density	density	NOUN
cana-2825	229	7	inside	inside	ADP
cana-2825	229	8	a	a	DET
cana-2825	229	9	single	single	ADJ
cana-2825	229	10	grid	grid	NOUN
cana-2825	229	11	cell	cell	NOUN
cana-2825	229	12	while	while	SCONJ
cana-2825	229	13	reducing	reduce	VERB
cana-2825	229	14	the	the	DET
cana-2825	229	15	overall	overall	ADJ
cana-2825	229	16	number	number	NOUN
cana-2825	229	17	of	of	ADP
cana-2825	229	18	cells	cell	NOUN
cana-2825	229	19	considered	consider	VERB
cana-2825	229	20	for	for	ADP
cana-2825	229	21	the	the	DET
cana-2825	229	22	spatial	spatial	ADJ
cana-2825	229	23	information	information	NOUN
cana-2825	229	24	.	.	PUNCT
cana-2825	230	1	in	in	ADP
cana-2825	230	2	general	general	ADJ
cana-2825	230	3	,	,	PUNCT
cana-2825	230	4	the	the	DET
cana-2825	230	5	application	application	NOUN
cana-2825	230	6	of	of	ADP
cana-2825	230	7	machine	machine	NOUN
cana-2825	230	8	learning	learn	VERB
cana-2825	230	9	methods	method	NOUN
cana-2825	230	10	to	to	ADP
cana-2825	230	11	spatial	spatial	ADJ
cana-2825	230	12	information	information	NOUN
cana-2825	230	13	surpasses	surpass	VERB
cana-2825	230	14	conventional	conventional	ADJ
cana-2825	230	15	methods	method	NOUN
cana-2825	230	16	in	in	ADP
cana-2825	230	17	generating	generate	VERB
cana-2825	230	18	predictions	prediction	NOUN
cana-2825	230	19	.	.	PUNCT
cana-2825	231	1	further	further	ADJ
cana-2825	231	2	investigation	investigation	NOUN
cana-2825	231	3	into	into	ADP
cana-2825	231	4	both	both	PRON
cana-2825	231	5	regression	regression	NOUN
cana-2825	231	6	algorithms	algorithm	NOUN
cana-2825	231	7	and	and	CCONJ
cana-2825	231	8	geographical	geographical	ADJ
cana-2825	231	9	sampling	sampling	NOUN
cana-2825	231	10	methods	method	NOUN
cana-2825	231	11	may	may	AUX
cana-2825	231	12	give	give	VERB
cana-2825	231	13	valuable	valuable	ADJ
cana-2825	231	14	insights	insight	NOUN
cana-2825	231	15	into	into	ADP
cana-2825	231	16	yield	yield	NOUN
cana-2825	231	17	prediction	prediction	NOUN
cana-2825	231	18	as	as	ADV
cana-2825	231	19	well	well	ADV
cana-2825	231	20	as	as	ADP
cana-2825	231	21	improve	improve	VERB
cana-2825	231	22	precision	precision	NOUN
cana-2825	231	23	.	.	PUNCT
cana-2825	232	1	the	the	DET
cana-2825	232	2	findings	finding	NOUN
cana-2825	232	3	for	for	ADP
cana-2825	232	4	protein	protein	NOUN
cana-2825	232	5	prediction	prediction	NOUN
cana-2825	232	6	provide	provide	VERB
cana-2825	232	7	a	a	DET
cana-2825	232	8	contrasting	contrast	VERB
cana-2825	232	9	narrative	narrative	NOUN
cana-2825	232	10	.	.	PUNCT
cana-2825	233	1	while	while	SCONJ
cana-2825	233	2	enhancements	enhancement	NOUN
cana-2825	233	3	are	be	AUX
cana-2825	233	4	consistently	consistently	ADV
cana-2825	233	5	seen	see	VERB
cana-2825	233	6	in	in	ADP
cana-2825	233	7	the	the	DET
cana-2825	233	8	outcomes	outcome	NOUN
cana-2825	233	9	for	for	ADP
cana-2825	233	10	the	the	DET
cana-2825	233	11	same	same	ADJ
cana-2825	233	12	models	model	NOUN
cana-2825	233	13	using	use	VERB
cana-2825	233	14	geographical	geographical	ADJ
cana-2825	233	15	data	datum	NOUN
cana-2825	233	16	,	,	PUNCT
cana-2825	233	17	the	the	DET
cana-2825	233	18	findings	finding	NOUN
cana-2825	233	19	do	do	AUX
cana-2825	233	20	not	not	PART
cana-2825	233	21	exhibit	exhibit	VERB
cana-2825	233	22	substantial	substantial	ADJ
cana-2825	233	23	differences	difference	NOUN
cana-2825	233	24	from	from	ADP
cana-2825	233	25	one	one	NUM
cana-2825	233	26	another	another	DET
cana-2825	233	27	.	.	PUNCT
cana-2825	234	1	nonetheless	nonetheless	ADV
cana-2825	234	2	,	,	PUNCT
cana-2825	234	3	the	the	DET
cana-2825	234	4	anns	anns	NOUN
cana-2825	234	5	exhibited	exhibit	VERB
cana-2825	234	6	markedly	markedly	ADV
cana-2825	234	7	superior	superior	ADJ
cana-2825	234	8	performance	performance	NOUN
cana-2825	234	9	compared	compare	VERB
cana-2825	234	10	to	to	ADP
cana-2825	234	11	the	the	DET
cana-2825	234	12	other	other	ADJ
cana-2825	234	13	models	model	NOUN
cana-2825	234	14	in	in	ADP
cana-2825	234	15	two	two	NUM
cana-2825	234	16	of	of	ADP
cana-2825	234	17	the	the	DET
cana-2825	234	18	domains	domain	NOUN
cana-2825	234	19	.	.	PUNCT
cana-2825	235	1	notably	notably	ADV
cana-2825	235	2	,	,	PUNCT
cana-2825	235	3	the	the	DET
cana-2825	235	4	two	two	NUM
cana-2825	235	5	fields	field	NOUN
cana-2825	235	6	have	have	VERB
cana-2825	235	7	the	the	DET
cana-2825	235	8	largest	large	ADJ
cana-2825	235	9	and	and	CCONJ
cana-2825	235	10	lowest	low	ADJ
cana-2825	235	11	quantities	quantity	NOUN
cana-2825	235	12	of	of	ADP
cana-2825	235	13	protein	protein	NOUN
cana-2825	235	14	points	point	NOUN
cana-2825	235	15	.	.	PUNCT
cana-2825	236	1	a	a	DET
cana-2825	236	2	thorough	thorough	ADJ
cana-2825	236	3	examination	examination	NOUN
cana-2825	236	4	of	of	ADP
cana-2825	236	5	the	the	DET
cana-2825	236	6	information	information	NOUN
cana-2825	236	7	could	could	AUX
cana-2825	236	8	give	give	VERB
cana-2825	236	9	more	more	ADJ
cana-2825	236	10	understanding	understanding	NOUN
cana-2825	236	11	of	of	ADP
cana-2825	236	12	the	the	DET
cana-2825	236	13	source	source	NOUN
cana-2825	236	14	of	of	ADP
cana-2825	236	15	this	this	DET
cana-2825	236	16	phenomenon	phenomenon	NOUN
cana-2825	236	17	.	.	PUNCT
cana-2825	237	1	also	also	ADV
cana-2825	237	2	,	,	PUNCT
cana-2825	237	3	the	the	DET
cana-2825	237	4	sae	sae	PROPN
cana-2825	237	5	is	be	AUX
cana-2825	237	6	n't	not	PART
cana-2825	237	7	very	very	ADV
cana-2825	237	8	good	good	ADJ
cana-2825	237	9	at	at	ADP
cana-2825	237	10	this	this	PRON
cana-2825	237	11	,	,	PUNCT
cana-2825	237	12	particularly	particularly	ADV
cana-2825	237	13	when	when	SCONJ
cana-2825	237	14	contrasted	contrast	VERB
cana-2825	237	15	with	with	ADP
cana-2825	237	16	how	how	SCONJ
cana-2825	237	17	well	well	ADV
cana-2825	237	18	it	it	PRON
cana-2825	237	19	does	do	AUX
cana-2825	237	20	with	with	ADP
cana-2825	237	21	yield	yield	NOUN
cana-2825	237	22	prediction	prediction	NOUN
cana-2825	237	23	.	.	PUNCT
cana-2825	238	1	since	since	SCONJ
cana-2825	238	2	saes	sae	NOUN
cana-2825	238	3	do	do	VERB
cana-2825	238	4	better	well	ADV
cana-2825	238	5	with	with	ADP
cana-2825	238	6	a	a	DET
cana-2825	238	7	large	large	ADJ
cana-2825	238	8	amount	amount	NOUN
cana-2825	238	9	of	of	ADP
cana-2825	238	10	data	datum	NOUN
cana-2825	238	11	,	,	PUNCT
cana-2825	238	12	the	the	DET
cana-2825	238	13	most	most	ADV
cana-2825	238	14	reasonable	reasonable	ADJ
cana-2825	238	15	explanation	explanation	NOUN
cana-2825	238	16	is	be	AUX
cana-2825	238	17	that	that	SCONJ
cana-2825	238	18	there	there	PRON
cana-2825	238	19	are	be	VERB
cana-2825	238	20	n't	not	PART
cana-2825	238	21	enough	enough	ADJ
cana-2825	238	22	data	datum	NOUN
cana-2825	238	23	points	point	NOUN
cana-2825	238	24	to	to	PART
cana-2825	238	25	train	train	VERB
cana-2825	238	26	the	the	DET
cana-2825	238	27	protein	protein	NOUN
cana-2825	238	28	models	model	NOUN
cana-2825	238	29	,	,	PUNCT
cana-2825	238	30	which	which	PRON
cana-2825	238	31	means	mean	VERB
cana-2825	238	32	they	they	PRON
cana-2825	238	33	ca	can	AUX
cana-2825	238	34	n't	not	PART
cana-2825	238	35	learn	learn	VERB
cana-2825	238	36	very	very	ADV
cana-2825	238	37	well	well	ADV
cana-2825	238	38	.	.	PUNCT
cana-2825	239	1	on	on	ADP
cana-2825	239	2	the	the	DET
cana-2825	239	3	other	other	ADJ
cana-2825	239	4	hand	hand	NOUN
cana-2825	239	5	,	,	PUNCT
cana-2825	239	6	when	when	SCONJ
cana-2825	239	7	we	we	PRON
cana-2825	239	8	examine	examine	VERB
cana-2825	239	9	the	the	DET
cana-2825	239	10	rmse	rmse	ADJ
cana-2825	239	11	values	value	NOUN
cana-2825	239	12	,	,	PUNCT
cana-2825	239	13	we	we	PRON
cana-2825	239	14	can	can	AUX
cana-2825	239	15	see	see	VERB
cana-2825	239	16	that	that	SCONJ
cana-2825	239	17	the	the	DET
cana-2825	239	18	predictions	prediction	NOUN
cana-2825	239	19	made	make	VERB
cana-2825	239	20	by	by	ADP
cana-2825	239	21	each	each	DET
cana-2825	239	22	model	model	NOUN
cana-2825	239	23	are	be	AUX
cana-2825	239	24	quite	quite	ADV
cana-2825	239	25	accurate	accurate	ADJ
cana-2825	239	26	.	.	PUNCT
cana-2825	240	1	it	it	PRON
cana-2825	240	2	seems	seem	VERB
cana-2825	240	3	from	from	ADP
cana-2825	240	4	the	the	DET
cana-2825	240	5	data	datum	NOUN
cana-2825	240	6	that	that	PRON
cana-2825	240	7	protein	protein	NOUN
cana-2825	240	8	values	value	NOUN
cana-2825	240	9	are	be	AUX
cana-2825	240	10	not	not	PART
cana-2825	240	11	significantly	significantly	ADV
cana-2825	240	12	different	different	ADJ
cana-2825	240	13	from	from	ADP
cana-2825	240	14	yield	yield	NOUN
cana-2825	240	15	values	value	NOUN
cana-2825	240	16	,	,	PUNCT
cana-2825	240	17	which	which	PRON
cana-2825	240	18	might	might	AUX
cana-2825	240	19	make	make	VERB
cana-2825	240	20	it	it	PRON
cana-2825	240	21	simpler	simple	ADJ
cana-2825	240	22	to	to	PART
cana-2825	240	23	anticipate	anticipate	VERB
cana-2825	240	24	the	the	DET
cana-2825	240	25	right	right	ADJ
cana-2825	240	26	protein	protein	NOUN
cana-2825	240	27	values	value	NOUN
cana-2825	240	28	and	and	CCONJ
cana-2825	240	29	ultimately	ultimately	ADV
cana-2825	240	30	lead	lead	VERB
cana-2825	240	31	to	to	PART
cana-2825	240	32	decreased	decrease	VERB
cana-2825	240	33	rmse	rmse	ADJ
cana-2825	240	34	values	value	NOUN
cana-2825	240	35	.	.	PUNCT
cana-2825	241	1	5	5	X
cana-2825	241	2	.	.	X
cana-2825	241	3	conclusion	conclusion	NOUN
cana-2825	241	4	precision	precision	NOUN
cana-2825	241	5	agriculture	agriculture	NOUN
cana-2825	241	6	may	may	AUX
cana-2825	241	7	significantly	significantly	ADV
cana-2825	241	8	enhance	enhance	VERB
cana-2825	241	9	agricultural	agricultural	ADJ
cana-2825	241	10	yields	yield	NOUN
cana-2825	241	11	by	by	ADP
cana-2825	241	12	using	use	VERB
cana-2825	241	13	several	several	ADJ
cana-2825	241	14	mathematical	mathematical	ADJ
cana-2825	241	15	methods	method	NOUN
cana-2825	241	16	&	&	CCONJ
cana-2825	241	17	experimental	experimental	ADJ
cana-2825	241	18	methodologies	methodology	NOUN
cana-2825	241	19	.	.	PUNCT
cana-2825	242	1	this	this	DET
cana-2825	242	2	field	field	NOUN
cana-2825	242	3	of	of	ADP
cana-2825	242	4	study	study	NOUN
cana-2825	242	5	has	have	AUX
cana-2825	242	6	realized	realize	VERB
cana-2825	242	7	a	a	DET
cana-2825	242	8	rise	rise	NOUN
cana-2825	242	9	in	in	ADP
cana-2825	242	10	computational	computational	ADJ
cana-2825	242	11	investigation	investigation	NOUN
cana-2825	242	12	,	,	PUNCT
cana-2825	242	13	particularly	particularly	ADV
cana-2825	242	14	in	in	ADP
cana-2825	242	15	machine	machine	NOUN
cana-2825	242	16	learning	learning	NOUN
cana-2825	242	17	.	.	PUNCT
cana-2825	243	1	utilising	utilise	VERB
cana-2825	243	2	machine	machine	NOUN
cana-2825	243	3	learning	learn	VERB
cana-2825	243	4	to	to	PART
cana-2825	243	5	develop	develop	VERB
cana-2825	243	6	predictive	predictive	ADJ
cana-2825	243	7	models	model	NOUN
cana-2825	243	8	may	may	AUX
cana-2825	243	9	enhance	enhance	VERB
cana-2825	243	10	the	the	DET
cana-2825	243	11	accuracy	accuracy	NOUN
cana-2825	243	12	of	of	ADP
cana-2825	243	13	fertilisation	fertilisation	NOUN
cana-2825	243	14	prescription	prescription	NOUN
cana-2825	243	15	maps	map	NOUN
cana-2825	243	16	and	and	CCONJ
cana-2825	243	17	yield	yield	NOUN
cana-2825	243	18	/	/	SYM
cana-2825	243	19	protein	protein	NOUN
cana-2825	243	20	forecasts	forecast	NOUN
cana-2825	243	21	,	,	PUNCT
cana-2825	243	22	hence	hence	ADV
cana-2825	243	23	improving	improve	VERB
cana-2825	243	24	production	production	NOUN
cana-2825	243	25	.	.	PUNCT
cana-2825	244	1	this	this	PRON
cana-2825	244	2	notwithstanding	notwithstanding	ADP
cana-2825	244	3	the	the	DET
cana-2825	244	4	extensive	extensive	ADJ
cana-2825	244	5	prior	prior	ADJ
cana-2825	244	6	study	study	NOUN
cana-2825	244	7	on	on	ADP
cana-2825	244	8	machine	machine	NOUN
cana-2825	244	9	learning	learning	NOUN
cana-2825	244	10	,	,	PUNCT
cana-2825	244	11	there	there	PRON
cana-2825	244	12	has	have	AUX
cana-2825	244	13	been	be	AUX
cana-2825	244	14	less	less	ADJ
cana-2825	244	15	investigation	investigation	NOUN
cana-2825	244	16	into	into	ADP
cana-2825	244	17	the	the	DET
cana-2825	244	18	use	use	NOUN
cana-2825	244	19	of	of	ADP
cana-2825	244	20	deep	deep	ADJ
cana-2825	244	21	learning	learning	NOUN
cana-2825	244	22	methodologies	methodology	NOUN
cana-2825	244	23	in	in	ADP
cana-2825	244	24	precision	precision	NOUN
cana-2825	244	25	agriculture	agriculture	NOUN
cana-2825	244	26	.	.	PUNCT
cana-2825	245	1	to	to	PART
cana-2825	245	2	create	create	VERB
cana-2825	245	3	productivity	productivity	NOUN
cana-2825	245	4	and	and	CCONJ
cana-2825	245	5	protein	protein	NOUN
cana-2825	245	6	prediction	prediction	NOUN
cana-2825	245	7	techniques	technique	NOUN
cana-2825	245	8	,	,	PUNCT
cana-2825	245	9	this	this	DET
cana-2825	245	10	study	study	NOUN
cana-2825	245	11	examines	examine	VERB
cana-2825	245	12	multiple	multiple	ADJ
cana-2825	245	13	regression	regression	NOUN
cana-2825	245	14	,	,	PUNCT
cana-2825	245	15	a	a	DET
cana-2825	245	16	shallow	shallow	ADJ
cana-2825	245	17	feedback	feedback	NOUN
cana-2825	245	18	net	net	NOUN
cana-2825	245	19	,	,	PUNCT
cana-2825	245	20	and	and	CCONJ
cana-2825	245	21	stacking	stack	VERB
cana-2825	245	22	automatic	automatic	ADJ
cana-2825	245	23	encoders	encoder	NOUN
cana-2825	245	24	in	in	ADP
cana-2825	245	25	geographic	geographic	ADJ
cana-2825	245	26	and	and	CCONJ
cana-2825	245	27	non	non	ADJ
cana-2825	245	28	-	-	ADJ
cana-2825	245	29	spatial	spatial	ADJ
cana-2825	245	30	situations	situation	NOUN
cana-2825	245	31	.	.	PUNCT
cana-2825	246	1	compared	compare	VERB
cana-2825	246	2	to	to	ADP
cana-2825	246	3	the	the	DET
cana-2825	246	4	other	other	ADJ
cana-2825	246	5	methods	method	NOUN
cana-2825	246	6	tested	test	VERB
cana-2825	246	7	,	,	PUNCT
cana-2825	246	8	our	our	PRON
cana-2825	246	9	results	result	NOUN
cana-2825	246	10	show	show	VERB
cana-2825	246	11	that	that	SCONJ
cana-2825	246	12	feed	feed	NOUN
cana-2825	246	13	-	-	PUNCT
cana-2825	246	14	forward	forward	NOUN
cana-2825	246	15	net	net	ADJ
cana-2825	246	16	and	and	CCONJ
cana-2825	246	17	spatial	spatial	ADJ
cana-2825	246	18	stacked	stack	VERB
cana-2825	246	19	autoencoders	autoencoder	NOUN
cana-2825	246	20	provide	provide	VERB
cana-2825	246	21	much	much	ADV
cana-2825	246	22	better	well	ADJ
cana-2825	246	23	accuracy	accuracy	NOUN
cana-2825	246	24	in	in	ADP
cana-2825	246	25	the	the	DET
cana-2825	246	26	studied	study	VERB
cana-2825	246	27	domains	domain	NOUN
cana-2825	246	28	.	.	PUNCT
cana-2825	247	1	6	6	NUM
cana-2825	247	2	.	.	X
cana-2825	247	3	future	future	ADJ
cana-2825	247	4	work	work	NOUN
cana-2825	247	5	communications	communication	NOUN
cana-2825	247	6	on	on	ADP
cana-2825	247	7	applied	apply	VERB
cana-2825	247	8	nonlinear	nonlinear	ADJ
cana-2825	247	9	analysis	analysis	NOUN
cana-2825	247	10	issn	issn	NOUN
cana-2825	247	11	:	:	PUNCT
cana-2825	247	12	1074	1074	NUM
cana-2825	247	13	-	-	PUNCT
cana-2825	247	14	133x	133x	NUM
cana-2825	247	15	vol	vol	NOUN
cana-2825	247	16	32	32	NUM
cana-2825	247	17	no	no	NOUN
cana-2825	247	18	.	.	PUNCT
cana-2825	248	1	4s	4s	NUM
cana-2825	248	2	(	(	PUNCT
cana-2825	248	3	2025	2025	NUM
cana-2825	248	4	)	)	PUNCT
cana-2825	248	5	354	354	NUM
cana-2825	248	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	248	7	equal	equal	ADJ
cana-2825	248	8	distance	distance	NOUN
cana-2825	248	9	&	&	CCONJ
cana-2825	248	10	random	random	ADJ
cana-2825	248	11	selection	selection	NOUN
cana-2825	248	12	are	be	AUX
cana-2825	248	13	two	two	NUM
cana-2825	248	14	more	more	ADJ
cana-2825	248	15	techniques	technique	NOUN
cana-2825	248	16	of	of	ADP
cana-2825	248	17	sample	sample	NOUN
cana-2825	248	18	spatial	spatial	ADJ
cana-2825	248	19	framework	framework	NOUN
cana-2825	248	20	that	that	PRON
cana-2825	248	21	are	be	AUX
cana-2825	248	22	not	not	PART
cana-2825	248	23	covered	cover	VERB
cana-2825	248	24	in	in	ADP
cana-2825	248	25	this	this	DET
cana-2825	248	26	book	book	NOUN
cana-2825	248	27	but	but	CCONJ
cana-2825	248	28	are	be	AUX
cana-2825	248	29	certainly	certainly	ADV
cana-2825	248	30	worthy	worthy	ADJ
cana-2825	248	31	of	of	ADP
cana-2825	248	32	investigation	investigation	NOUN
cana-2825	248	33	.	.	PUNCT
cana-2825	249	1	they	they	PRON
cana-2825	249	2	are	be	AUX
cana-2825	249	3	interested	interested	ADJ
cana-2825	249	4	in	in	ADP
cana-2825	249	5	determining	determine	VERB
cana-2825	249	6	how	how	SCONJ
cana-2825	249	7	well	well	ADV
cana-2825	249	8	various	various	ADJ
cana-2825	249	9	forms	form	NOUN
cana-2825	249	10	of	of	ADP
cana-2825	249	11	spatial	spatial	ADJ
cana-2825	249	12	context	context	NOUN
cana-2825	249	13	perform	perform	NOUN
cana-2825	249	14	when	when	SCONJ
cana-2825	249	15	included	include	VERB
cana-2825	249	16	.	.	PUNCT
cana-2825	250	1	given	give	VERB
cana-2825	250	2	that	that	SCONJ
cana-2825	250	3	the	the	DET
cana-2825	250	4	ann	ann	PROPN
cana-2825	250	5	and	and	CCONJ
cana-2825	250	6	sae	sae	PROPN
cana-2825	250	7	performed	perform	VERB
cana-2825	250	8	similarly	similarly	ADV
cana-2825	250	9	,	,	PUNCT
cana-2825	250	10	more	more	ADJ
cana-2825	250	11	research	research	NOUN
cana-2825	250	12	into	into	ADP
cana-2825	250	13	their	their	PRON
cana-2825	250	14	inner	inner	ADJ
cana-2825	250	15	workings	working	NOUN
cana-2825	250	16	is	be	AUX
cana-2825	250	17	necessary	necessary	ADJ
cana-2825	250	18	.	.	PUNCT
cana-2825	251	1	it	it	PRON
cana-2825	251	2	could	could	AUX
cana-2825	251	3	be	be	AUX
cana-2825	251	4	helpful	helpful	ADJ
cana-2825	251	5	to	to	PART
cana-2825	251	6	examine	examine	VERB
cana-2825	251	7	whether	whether	SCONJ
cana-2825	251	8	an	an	DET
cana-2825	251	9	autoencoder	autoencoder	NOUN
cana-2825	251	10	can	can	AUX
cana-2825	251	11	be	be	AUX
cana-2825	251	12	adjusted	adjust	VERB
cana-2825	251	13	to	to	PART
cana-2825	251	14	better	well	ADV
cana-2825	251	15	fit	fit	VERB
cana-2825	251	16	this	this	DET
cana-2825	251	17	particular	particular	ADJ
cana-2825	251	18	challenge	challenge	NOUN
cana-2825	251	19	as	as	SCONJ
cana-2825	251	20	the	the	DET
cana-2825	251	21	presently	presently	ADV
cana-2825	251	22	used	use	VERB
cana-2825	251	23	stacked	stack	VERB
cana-2825	251	24	autoencoder	autoencoder	NOUN
cana-2825	251	25	was	be	AUX
cana-2825	251	26	first	first	ADV
cana-2825	251	27	developed	develop	VERB
cana-2825	251	28	for	for	ADP
cana-2825	251	29	another	another	DET
cana-2825	251	30	study	study	NOUN
cana-2825	251	31	.	.	PUNCT
cana-2825	252	1	the	the	DET
cana-2825	252	2	data	datum	NOUN
cana-2825	252	3	being	be	AUX
cana-2825	252	4	analysed	analyse	VERB
cana-2825	252	5	determines	determine	VERB
cana-2825	252	6	how	how	SCONJ
cana-2825	252	7	the	the	DET
cana-2825	252	8	ann	ann	PROPN
cana-2825	252	9	and	and	CCONJ
cana-2825	252	10	sae	sae	PROPN
cana-2825	252	11	structures	structure	NOUN
cana-2825	252	12	are	be	AUX
cana-2825	252	13	modified	modify	VERB
cana-2825	252	14	.	.	PUNCT
cana-2825	253	1	stated	state	VERB
cana-2825	253	2	differently	differently	ADV
cana-2825	253	3	,	,	PUNCT
cana-2825	253	4	distinct	distinct	ADJ
cana-2825	253	5	models	model	NOUN
cana-2825	253	6	are	be	AUX
cana-2825	253	7	established	establish	VERB
cana-2825	253	8	for	for	ADP
cana-2825	253	9	every	every	DET
cana-2825	253	10	distinct	distinct	ADJ
cana-2825	253	11	area	area	NOUN
cana-2825	253	12	.	.	PUNCT
cana-2825	254	1	"	"	PUNCT
cana-2825	254	2	transfer	transfer	NOUN
cana-2825	254	3	learning	learning	NOUN
cana-2825	254	4	,	,	PUNCT
cana-2825	254	5	"	"	PUNCT
cana-2825	254	6	or	or	CCONJ
cana-2825	254	7	the	the	DET
cana-2825	254	8	application	application	NOUN
cana-2825	254	9	of	of	ADP
cana-2825	254	10	information	information	NOUN
cana-2825	254	11	acquired	acquire	VERB
cana-2825	254	12	in	in	ADP
cana-2825	254	13	one	one	NUM
cana-2825	254	14	discipline	discipline	NOUN
cana-2825	254	15	to	to	ADP
cana-2825	254	16	another	another	PRON
cana-2825	254	17	,	,	PUNCT
cana-2825	254	18	is	be	AUX
cana-2825	254	19	a	a	DET
cana-2825	254	20	topic	topic	NOUN
cana-2825	254	21	of	of	ADP
cana-2825	254	22	study	study	NOUN
cana-2825	254	23	that	that	PRON
cana-2825	254	24	is	be	AUX
cana-2825	254	25	now	now	ADV
cana-2825	254	26	getting	get	VERB
cana-2825	254	27	attention	attention	NOUN
cana-2825	254	28	.	.	PUNCT
cana-2825	255	1	investigating	investigate	VERB
cana-2825	255	2	how	how	SCONJ
cana-2825	255	3	this	this	PRON
cana-2825	255	4	could	could	AUX
cana-2825	255	5	reduce	reduce	VERB
cana-2825	255	6	training	training	NOUN
cana-2825	255	7	complexity	complexity	NOUN
cana-2825	255	8	or	or	CCONJ
cana-2825	255	9	perhaps	perhaps	ADV
cana-2825	255	10	raise	raise	VERB
cana-2825	255	11	overall	overall	ADJ
cana-2825	255	12	exactness	exactness	NOUN
cana-2825	255	13	would	would	AUX
cana-2825	255	14	be	be	AUX
cana-2825	255	15	intriguing	intriguing	ADJ
cana-2825	255	16	.	.	PUNCT
cana-2825	256	1	the	the	DET
cana-2825	256	2	data	datum	NOUN
cana-2825	256	3	utilised	utilise	VERB
cana-2825	256	4	to	to	PART
cana-2825	256	5	forecast	forecast	VERB
cana-2825	256	6	the	the	DET
cana-2825	256	7	yield	yield	NOUN
cana-2825	256	8	&	&	CCONJ
cana-2825	256	9	protein	protein	NOUN
cana-2825	256	10	levels	level	NOUN
cana-2825	256	11	is	be	AUX
cana-2825	256	12	another	another	DET
cana-2825	256	13	factor	factor	NOUN
cana-2825	256	14	to	to	PART
cana-2825	256	15	take	take	VERB
cana-2825	256	16	into	into	ADP
cana-2825	256	17	account	account	NOUN
cana-2825	256	18	for	for	ADP
cana-2825	256	19	further	further	ADJ
cana-2825	256	20	research	research	NOUN
cana-2825	256	21	.	.	PUNCT
cana-2825	257	1	it	it	PRON
cana-2825	257	2	may	may	AUX
cana-2825	257	3	be	be	AUX
cana-2825	257	4	useful	useful	ADJ
cana-2825	257	5	to	to	PART
cana-2825	257	6	look	look	VERB
cana-2825	257	7	at	at	ADP
cana-2825	257	8	which	which	PRON
cana-2825	257	9	values	value	NOUN
cana-2825	257	10	have	have	VERB
cana-2825	257	11	the	the	DET
cana-2825	257	12	most	most	ADJ
cana-2825	257	13	effects	effect	NOUN
cana-2825	257	14	on	on	ADP
cana-2825	257	15	exact	exact	ADJ
cana-2825	257	16	forecast	forecast	NOUN
cana-2825	257	17	whereas	whereas	SCONJ
cana-2825	257	18	others	other	NOUN
cana-2825	257	19	have	have	VERB
cana-2825	257	20	little	little	ADJ
cana-2825	257	21	to	to	ADP
cana-2825	257	22	no	no	DET
cana-2825	257	23	effect	effect	NOUN
cana-2825	257	24	.	.	PUNCT
cana-2825	258	1	further	further	ADJ
cana-2825	258	2	understanding	understanding	NOUN
cana-2825	258	3	of	of	ADP
cana-2825	258	4	the	the	DET
cana-2825	258	5	systems	system	NOUN
cana-2825	258	6	and	and	CCONJ
cana-2825	258	7	how	how	SCONJ
cana-2825	258	8	they	they	PRON
cana-2825	258	9	forecast	forecast	VERB
cana-2825	258	10	the	the	DET
cana-2825	258	11	yield	yield	NOUN
cana-2825	258	12	,	,	PUNCT
cana-2825	258	13	as	as	ADV
cana-2825	258	14	well	well	ADV
cana-2825	258	15	as	as	ADP
cana-2825	258	16	protein	protein	NOUN
cana-2825	258	17	values	value	NOUN
cana-2825	258	18	,	,	PUNCT
cana-2825	258	19	may	may	AUX
cana-2825	258	20	be	be	AUX
cana-2825	258	21	gained	gain	VERB
cana-2825	258	22	by	by	ADP
cana-2825	258	23	examining	examine	VERB
cana-2825	258	24	how	how	SCONJ
cana-2825	258	25	particular	particular	ADJ
cana-2825	258	26	values	value	NOUN
cana-2825	258	27	affect	affect	VERB
cana-2825	258	28	the	the	DET
cana-2825	258	29	various	various	ADJ
cana-2825	258	30	system	system	NOUN
cana-2825	258	31	types	type	NOUN
cana-2825	258	32	and	and	CCONJ
cana-2825	258	33	contrasting	contrast	VERB
cana-2825	258	34	the	the	DET
cana-2825	258	35	variations	variation	NOUN
cana-2825	258	36	in	in	ADP
cana-2825	258	37	the	the	DET
cana-2825	258	38	effect	effect	NOUN
cana-2825	258	39	of	of	ADP
cana-2825	258	40	those	those	DET
cana-2825	258	41	values	value	NOUN
cana-2825	258	42	for	for	ADP
cana-2825	258	43	individual	individual	ADJ
cana-2825	258	44	types	type	NOUN
cana-2825	258	45	.	.	PUNCT
cana-2825	259	1	this	this	DET
cana-2825	259	2	research	research	NOUN
cana-2825	259	3	only	only	ADV
cana-2825	259	4	focuses	focus	VERB
cana-2825	259	5	on	on	ADP
cana-2825	259	6	predicting	predict	VERB
cana-2825	259	7	protein	protein	NOUN
cana-2825	259	8	and	and	CCONJ
cana-2825	259	9	yield	yield	NOUN
cana-2825	259	10	,	,	PUNCT
cana-2825	259	11	particularly	particularly	ADV
cana-2825	259	12	in	in	ADP
cana-2825	259	13	connection	connection	NOUN
cana-2825	259	14	to	to	ADP
cana-2825	259	15	fertiliser	fertiliser	NOUN
cana-2825	259	16	application	application	NOUN
cana-2825	259	17	.	.	PUNCT
cana-2825	260	1	as	as	SCONJ
cana-2825	260	2	before	before	ADV
cana-2825	260	3	said	say	VERB
cana-2825	260	4	,	,	PUNCT
cana-2825	260	5	forecasting	forecast	VERB
cana-2825	260	6	the	the	DET
cana-2825	260	7	ideal	ideal	ADJ
cana-2825	260	8	fertilisation	fertilisation	NOUN
cana-2825	260	9	rate	rate	NOUN
cana-2825	260	10	is	be	AUX
cana-2825	260	11	a	a	DET
cana-2825	260	12	crucial	crucial	ADJ
cana-2825	260	13	component	component	NOUN
cana-2825	260	14	of	of	ADP
cana-2825	260	15	our	our	PRON
cana-2825	260	16	research	research	NOUN
cana-2825	260	17	,	,	PUNCT
cana-2825	260	18	and	and	CCONJ
cana-2825	260	19	examine	examine	VERB
cana-2825	260	20	the	the	DET
cana-2825	260	21	degree	degree	NOUN
cana-2825	260	22	to	to	PART
cana-2825	260	23	which	which	PRON
cana-2825	260	24	may	may	AUX
cana-2825	260	25	utilise	utilise	VERB
cana-2825	260	26	these	these	DET
cana-2825	260	27	models	model	NOUN
cana-2825	260	28	to	to	PART
cana-2825	260	29	provide	provide	VERB
cana-2825	260	30	optimised	optimise	VERB
cana-2825	260	31	fertilisation	fertilisation	NOUN
cana-2825	260	32	prescriptions	prescription	NOUN
cana-2825	260	33	.	.	PUNCT
cana-2825	261	1	references	reference	NOUN
cana-2825	261	2	[	[	X
cana-2825	261	3	1	1	NUM
cana-2825	261	4	]	]	X
cana-2825	261	5	awad	awad	PROPN
cana-2825	261	6	,	,	PUNCT
cana-2825	261	7	mohamad	mohamad	PROPN
cana-2825	261	8	m.	m.	NOUN
cana-2825	261	9	"	"	PUNCT
cana-2825	261	10	toward	toward	ADP
cana-2825	261	11	precision	precision	NOUN
cana-2825	261	12	in	in	ADP
cana-2825	261	13	crop	crop	NOUN
cana-2825	261	14	yield	yield	NOUN
cana-2825	261	15	estimation	estimation	NOUN
cana-2825	261	16	using	use	VERB
cana-2825	261	17	remote	remote	ADJ
cana-2825	261	18	sensing	sensing	NOUN
cana-2825	261	19	and	and	CCONJ
cana-2825	261	20	optimization	optimization	NOUN
cana-2825	261	21	techniques	technique	NOUN
cana-2825	261	22	.	.	PUNCT
cana-2825	261	23	"	"	PUNCT
cana-2825	262	1	agriculture	agriculture	NOUN
cana-2825	262	2	9.3	9.3	NUM
cana-2825	262	3	(	(	PUNCT
cana-2825	262	4	2019	2019	NUM
cana-2825	262	5	):	):	PUNCT
cana-2825	262	6	54	54	NUM
cana-2825	262	7	.	.	PUNCT
cana-2825	263	1	[	[	X
cana-2825	263	2	2	2	X
cana-2825	263	3	]	]	PUNCT
cana-2825	263	4	rama	rama	PROPN
cana-2825	263	5	devi	devi	PROPN
cana-2825	263	6	,	,	PUNCT
cana-2825	263	7	o.	o.	PROPN
cana-2825	263	8	,	,	PUNCT
cana-2825	263	9	et	et	PROPN
cana-2825	263	10	al	al	PROPN
cana-2825	263	11	.	.	PUNCT
cana-2825	264	1	"	"	PUNCT
cana-2825	264	2	optimizing	optimize	VERB
cana-2825	264	3	crop	crop	NOUN
cana-2825	264	4	yield	yield	NOUN
cana-2825	264	5	prediction	prediction	NOUN
cana-2825	264	6	in	in	ADP
cana-2825	264	7	precision	precision	NOUN
cana-2825	264	8	agriculture	agriculture	NOUN
cana-2825	264	9	with	with	ADP
cana-2825	264	10	hyperspectral	hyperspectral	ADJ
cana-2825	264	11	imagingunmixing	imagingunmixing	NOUN
cana-2825	264	12	and	and	CCONJ
cana-2825	264	13	deep	deep	ADJ
cana-2825	264	14	learning	learning	NOUN
cana-2825	264	15	.	.	PUNCT
cana-2825	264	16	"	"	PUNCT
cana-2825	265	1	international	international	ADJ
cana-2825	265	2	journal	journal	NOUN
cana-2825	265	3	of	of	ADP
cana-2825	265	4	advanced	advanced	ADJ
cana-2825	265	5	computer	computer	NOUN
cana-2825	265	6	science	science	NOUN
cana-2825	265	7	&	&	CCONJ
cana-2825	265	8	applications	application	NOUN
cana-2825	265	9	14.12	14.12	NUM
cana-2825	265	10	(	(	PUNCT
cana-2825	265	11	2023	2023	NUM
cana-2825	265	12	)	)	PUNCT
cana-2825	265	13	.	.	PUNCT
cana-2825	266	1	[	[	X
cana-2825	266	2	3	3	NUM
cana-2825	266	3	]	]	PUNCT
cana-2825	266	4	aworka	aworka	NOUN
cana-2825	266	5	,	,	PUNCT
cana-2825	266	6	rubby	rubby	PROPN
cana-2825	266	7	,	,	PUNCT
cana-2825	266	8	et	et	PROPN
cana-2825	266	9	al	al	PROPN
cana-2825	266	10	.	.	PUNCT
cana-2825	267	1	"	"	PUNCT
cana-2825	267	2	agricultural	agricultural	ADJ
cana-2825	267	3	decision	decision	NOUN
cana-2825	267	4	system	system	NOUN
cana-2825	267	5	based	base	VERB
cana-2825	267	6	on	on	ADP
cana-2825	267	7	advanced	advanced	ADJ
cana-2825	267	8	machine	machine	NOUN
cana-2825	267	9	learning	learning	NOUN
cana-2825	267	10	models	model	NOUN
cana-2825	267	11	for	for	ADP
cana-2825	267	12	yield	yield	NOUN
cana-2825	267	13	prediction	prediction	NOUN
cana-2825	267	14	:	:	PUNCT
cana-2825	267	15	case	case	NOUN
cana-2825	267	16	of	of	ADP
cana-2825	267	17	east	east	ADJ
cana-2825	267	18	african	african	ADJ
cana-2825	267	19	countries	country	NOUN
cana-2825	267	20	.	.	PUNCT
cana-2825	267	21	"	"	PUNCT
cana-2825	268	1	smart	smart	ADJ
cana-2825	268	2	agricultural	agricultural	ADJ
cana-2825	268	3	technology	technology	NOUN
cana-2825	268	4	2	2	NUM
cana-2825	268	5	(	(	PUNCT
cana-2825	268	6	2022	2022	NUM
cana-2825	268	7	):	):	PUNCT
cana-2825	268	8	100048	100048	NUM
cana-2825	268	9	.	.	PUNCT
cana-2825	269	1	[	[	X
cana-2825	269	2	4	4	NUM
cana-2825	269	3	]	]	SYM
cana-2825	269	4	kuradusenge	kuradusenge	NOUN
cana-2825	269	5	,	,	PUNCT
cana-2825	269	6	martin	martin	PROPN
cana-2825	269	7	,	,	PUNCT
cana-2825	269	8	et	et	PROPN
cana-2825	269	9	al	al	PROPN
cana-2825	269	10	.	.	PUNCT
cana-2825	270	1	"	"	PUNCT
cana-2825	270	2	crop	crop	NOUN
cana-2825	270	3	yield	yield	NOUN
cana-2825	270	4	prediction	prediction	NOUN
cana-2825	270	5	using	use	VERB
cana-2825	270	6	machine	machine	NOUN
cana-2825	270	7	learning	learning	NOUN
cana-2825	270	8	models	model	NOUN
cana-2825	270	9	:	:	PUNCT
cana-2825	270	10	case	case	NOUN
cana-2825	270	11	of	of	ADP
cana-2825	270	12	irish	irish	ADJ
cana-2825	270	13	potato	potato	NOUN
cana-2825	270	14	and	and	CCONJ
cana-2825	270	15	maize	maize	NOUN
cana-2825	270	16	.	.	PUNCT
cana-2825	270	17	"	"	PUNCT
cana-2825	271	1	agriculture	agriculture	NOUN
cana-2825	271	2	13.1	13.1	NUM
cana-2825	271	3	(	(	PUNCT
cana-2825	271	4	2023	2023	NUM
cana-2825	271	5	):	):	PUNCT
cana-2825	271	6	225	225	NUM
cana-2825	271	7	.	.	PUNCT
cana-2825	272	1	[	[	X
cana-2825	272	2	5	5	NUM
cana-2825	272	3	]	]	SYM
cana-2825	272	4	rao	rao	PROPN
cana-2825	272	5	,	,	PUNCT
cana-2825	272	6	m.	m.	NOUN
cana-2825	272	7	venkateswara	venkateswara	PROPN
cana-2825	272	8	,	,	PUNCT
cana-2825	272	9	et	et	PROPN
cana-2825	272	10	al	al	PROPN
cana-2825	272	11	.	.	PUNCT
cana-2825	272	12	"	"	PUNCT
cana-2825	272	13	brinjal	brinjal	ADJ
cana-2825	272	14	crop	crop	NOUN
cana-2825	272	15	yield	yield	NOUN
cana-2825	272	16	prediction	prediction	NOUN
cana-2825	272	17	using	use	VERB
cana-2825	272	18	shuffled	shuffle	VERB
cana-2825	272	19	shepherd	shepherd	ADJ
cana-2825	272	20	optimization	optimization	NOUN
cana-2825	272	21	algorithm	algorithm	PROPN
cana-2825	272	22	based	base	VERB
cana-2825	272	23	acnn	acnn	PROPN
cana-2825	272	24	-	-	PUNCT
cana-2825	272	25	obdlstm	obdlstm	PROPN
cana-2825	272	26	model	model	NOUN
cana-2825	272	27	in	in	ADP
cana-2825	272	28	smart	smart	ADJ
cana-2825	272	29	agriculture	agriculture	NOUN
cana-2825	272	30	.	.	PUNCT
cana-2825	272	31	"	"	PUNCT
cana-2825	273	1	journal	journal	NOUN
cana-2825	273	2	of	of	ADP
cana-2825	273	3	integrated	integrate	VERB
cana-2825	273	4	science	science	NOUN
cana-2825	273	5	and	and	CCONJ
cana-2825	273	6	technology	technology	NOUN
cana-2825	273	7	12.1	12.1	NUM
cana-2825	273	8	(	(	PUNCT
cana-2825	273	9	2024	2024	NUM
cana-2825	273	10	):	):	PUNCT
cana-2825	273	11	710710	710710	NUM
cana-2825	273	12	.	.	PUNCT
cana-2825	274	1	[	[	X
cana-2825	274	2	6	6	NUM
cana-2825	274	3	]	]	PUNCT
cana-2825	274	4	abbas	abbas	PROPN
cana-2825	274	5	,	,	PUNCT
cana-2825	274	6	farhat	farhat	PROPN
cana-2825	274	7	,	,	PUNCT
cana-2825	274	8	et	et	PROPN
cana-2825	274	9	al	al	PROPN
cana-2825	274	10	.	.	PUNCT
cana-2825	275	1	"	"	PUNCT
cana-2825	275	2	crop	crop	NOUN
cana-2825	275	3	yield	yield	NOUN
cana-2825	275	4	prediction	prediction	NOUN
cana-2825	275	5	through	through	ADP
cana-2825	275	6	proximal	proximal	ADJ
cana-2825	275	7	sensing	sensing	NOUN
cana-2825	275	8	and	and	CCONJ
cana-2825	275	9	machine	machine	NOUN
cana-2825	275	10	learning	learning	NOUN
cana-2825	275	11	algorithms	algorithm	NOUN
cana-2825	275	12	.	.	PUNCT
cana-2825	275	13	"	"	PUNCT
cana-2825	276	1	agronomy	agronomy	NOUN
cana-2825	276	2	10.7	10.7	NUM
cana-2825	276	3	(	(	PUNCT
cana-2825	276	4	2020	2020	NUM
cana-2825	276	5	):	):	PUNCT
cana-2825	276	6	1046	1046	NUM
cana-2825	276	7	.	.	PUNCT
cana-2825	277	1	[	[	X
cana-2825	277	2	7	7	NUM
cana-2825	277	3	]	]	X
cana-2825	277	4	wei	wei	PROPN
cana-2825	277	5	,	,	PUNCT
cana-2825	277	6	marcelo	marcelo	PROPN
cana-2825	277	7	chan	chan	PROPN
cana-2825	277	8	fu	fu	PROPN
cana-2825	277	9	,	,	PUNCT
cana-2825	277	10	et	et	PROPN
cana-2825	277	11	al	al	PROPN
cana-2825	277	12	.	.	PUNCT
cana-2825	278	1	"	"	PUNCT
cana-2825	278	2	carrot	carrot	NOUN
cana-2825	278	3	yield	yield	NOUN
cana-2825	278	4	mapping	mapping	NOUN
cana-2825	278	5	:	:	PUNCT
cana-2825	278	6	a	a	DET
cana-2825	278	7	precision	precision	NOUN
cana-2825	278	8	agriculture	agriculture	NOUN
cana-2825	278	9	approach	approach	NOUN
cana-2825	278	10	based	base	VERB
cana-2825	278	11	on	on	ADP
cana-2825	278	12	machine	machine	NOUN
cana-2825	278	13	learning	learning	NOUN
cana-2825	278	14	.	.	PUNCT
cana-2825	278	15	"	"	PUNCT
cana-2825	278	16	ai	ai	VERB
cana-2825	278	17	1.2	1.2	NUM
cana-2825	278	18	(	(	PUNCT
cana-2825	278	19	2020	2020	NUM
cana-2825	278	20	):	):	PUNCT
cana-2825	278	21	229	229	NUM
cana-2825	278	22	-	-	SYM
cana-2825	278	23	241	241	NUM
cana-2825	278	24	.	.	PUNCT
cana-2825	279	1	[	[	X
cana-2825	279	2	8	8	NUM
cana-2825	279	3	]	]	PUNCT
cana-2825	279	4	sishodia	sishodia	NOUN
cana-2825	279	5	,	,	PUNCT
cana-2825	279	6	rajendra	rajendra	PROPN
cana-2825	279	7	p.	p.	PROPN
cana-2825	279	8	,	,	PUNCT
cana-2825	279	9	ram	ram	PROPN
cana-2825	279	10	l.	l.	PROPN
cana-2825	279	11	ray	ray	PROPN
cana-2825	279	12	,	,	PUNCT
cana-2825	279	13	and	and	CCONJ
cana-2825	279	14	sudhir	sudhir	PROPN
cana-2825	279	15	k.	k.	PROPN
cana-2825	279	16	singh	singh	PROPN
cana-2825	279	17	.	.	PUNCT
cana-2825	280	1	"	"	PUNCT
cana-2825	280	2	applications	application	NOUN
cana-2825	280	3	of	of	ADP
cana-2825	280	4	remote	remote	ADJ
cana-2825	280	5	sensing	sensing	NOUN
cana-2825	280	6	in	in	ADP
cana-2825	280	7	precision	precision	NOUN
cana-2825	280	8	agriculture	agriculture	NOUN
cana-2825	280	9	:	:	PUNCT
cana-2825	280	10	a	a	DET
cana-2825	280	11	review	review	NOUN
cana-2825	280	12	.	.	PUNCT
cana-2825	280	13	"	"	PUNCT
cana-2825	281	1	remote	remote	ADJ
cana-2825	281	2	sensing	sense	VERB
cana-2825	281	3	12.19	12.19	NUM
cana-2825	281	4	(	(	PUNCT
cana-2825	281	5	2020	2020	NUM
cana-2825	281	6	):	):	PUNCT
cana-2825	281	7	3136	3136	NUM
cana-2825	281	8	.	.	PUNCT
cana-2825	282	1	[	[	X
cana-2825	282	2	9	9	NUM
cana-2825	282	3	]	]	PUNCT
cana-2825	282	4	akhter	akhter	NOUN
cana-2825	282	5	,	,	PUNCT
cana-2825	282	6	ravesa	ravesa	NOUN
cana-2825	282	7	,	,	PUNCT
cana-2825	282	8	and	and	CCONJ
cana-2825	282	9	shabir	shabir	PROPN
cana-2825	282	10	ahmad	ahmad	PROPN
cana-2825	282	11	sofi	sofi	PROPN
cana-2825	282	12	.	.	PUNCT
cana-2825	283	1	"	"	PUNCT
cana-2825	283	2	precision	precision	NOUN
cana-2825	283	3	agriculture	agriculture	NOUN
cana-2825	283	4	using	use	VERB
cana-2825	283	5	iot	iot	PROPN
cana-2825	283	6	data	datum	NOUN
cana-2825	283	7	analytics	analytic	NOUN
cana-2825	283	8	and	and	CCONJ
cana-2825	283	9	machine	machine	NOUN
cana-2825	283	10	learning	learning	NOUN
cana-2825	283	11	.	.	PUNCT
cana-2825	283	12	"	"	PUNCT
cana-2825	284	1	journal	journal	NOUN
cana-2825	284	2	of	of	ADP
cana-2825	284	3	king	king	PROPN
cana-2825	284	4	saud	saud	PROPN
cana-2825	284	5	university	university	PROPN
cana-2825	284	6	-	-	PUNCT
cana-2825	284	7	computer	computer	NOUN
cana-2825	284	8	and	and	CCONJ
cana-2825	284	9	information	information	NOUN
cana-2825	284	10	sciences	science	NOUN
cana-2825	284	11	34.8	34.8	NUM
cana-2825	284	12	(	(	PUNCT
cana-2825	284	13	2022	2022	NUM
cana-2825	284	14	):	):	PUNCT
cana-2825	284	15	5602	5602	NUM
cana-2825	284	16	-	-	SYM
cana-2825	284	17	5618	5618	NUM
cana-2825	284	18	.	.	PUNCT
cana-2825	285	1	[	[	X
cana-2825	285	2	10	10	NUM
cana-2825	285	3	]	]	X
cana-2825	285	4	agarwal	agarwal	PROPN
cana-2825	285	5	,	,	PUNCT
cana-2825	285	6	sonal	sonal	NOUN
cana-2825	285	7	,	,	PUNCT
cana-2825	285	8	and	and	CCONJ
cana-2825	285	9	sandhya	sandhya	PROPN
cana-2825	285	10	tarar	tarar	NOUN
cana-2825	285	11	.	.	PUNCT
cana-2825	286	1	"	"	PUNCT
cana-2825	286	2	a	a	DET
cana-2825	286	3	hybrid	hybrid	ADJ
cana-2825	286	4	approach	approach	NOUN
cana-2825	286	5	for	for	ADP
cana-2825	286	6	crop	crop	NOUN
cana-2825	286	7	yield	yield	NOUN
cana-2825	286	8	prediction	prediction	NOUN
cana-2825	286	9	using	use	VERB
cana-2825	286	10	machine	machine	NOUN
cana-2825	286	11	learning	learning	NOUN
cana-2825	286	12	and	and	CCONJ
cana-2825	286	13	deep	deep	ADJ
cana-2825	286	14	learning	learning	NOUN
cana-2825	286	15	algorithms	algorithm	NOUN
cana-2825	286	16	.	.	PUNCT
cana-2825	286	17	"	"	PUNCT
cana-2825	287	1	journal	journal	PROPN
cana-2825	287	2	of	of	ADP
cana-2825	287	3	physics	physics	PROPN
cana-2825	287	4	:	:	PUNCT
cana-2825	287	5	conference	conference	NOUN
cana-2825	287	6	series	series	NOUN
cana-2825	287	7	.	.	PUNCT
cana-2825	288	1	vol	vol	NOUN
cana-2825	288	2	.	.	PUNCT
cana-2825	288	3	1714	1714	NUM
cana-2825	288	4	.	.	PUNCT
cana-2825	289	1	no	no	INTJ
cana-2825	289	2	.	.	NOUN
cana-2825	290	1	1	1	X
cana-2825	290	2	.	.	X
cana-2825	290	3	iop	iop	NOUN
cana-2825	290	4	publishing	publishing	NOUN
cana-2825	290	5	,	,	PUNCT
cana-2825	290	6	2021	2021	NUM
cana-2825	290	7	.	.	PUNCT
cana-2825	291	1	[	[	X
cana-2825	291	2	11	11	NUM
cana-2825	291	3	]	]	PUNCT
cana-2825	291	4	gopal	gopal	NOUN
cana-2825	291	5	,	,	PUNCT
cana-2825	291	6	ps	ps	PROPN
cana-2825	291	7	maya	maya	PROPN
cana-2825	291	8	,	,	PUNCT
cana-2825	291	9	and	and	CCONJ
cana-2825	291	10	r.	r.	PROPN
cana-2825	291	11	bhargavi	bhargavi	PROPN
cana-2825	291	12	.	.	PUNCT
cana-2825	292	1	"	"	PUNCT
cana-2825	292	2	a	a	DET
cana-2825	292	3	novel	novel	ADJ
cana-2825	292	4	approach	approach	NOUN
cana-2825	292	5	for	for	ADP
cana-2825	292	6	efficient	efficient	ADJ
cana-2825	292	7	crop	crop	NOUN
cana-2825	292	8	yield	yield	NOUN
cana-2825	292	9	prediction	prediction	NOUN
cana-2825	292	10	.	.	PUNCT
cana-2825	292	11	"	"	PUNCT
cana-2825	293	1	computers	computer	NOUN
cana-2825	293	2	and	and	CCONJ
cana-2825	293	3	electronics	electronic	NOUN
cana-2825	293	4	in	in	ADP
cana-2825	293	5	agriculture	agriculture	NOUN
cana-2825	293	6	165	165	NUM
cana-2825	293	7	(	(	PUNCT
cana-2825	293	8	2019	2019	NUM
cana-2825	293	9	):	):	PUNCT
cana-2825	293	10	104968	104968	NUM
cana-2825	293	11	.	.	PUNCT
cana-2825	294	1	[	[	X
cana-2825	294	2	12	12	NUM
cana-2825	294	3	]	]	PUNCT
cana-2825	294	4	gómez	gómez	NOUN
cana-2825	294	5	,	,	PUNCT
cana-2825	294	6	diego	diego	PROPN
cana-2825	294	7	,	,	PUNCT
cana-2825	294	8	et	et	PROPN
cana-2825	294	9	al	al	PROPN
cana-2825	294	10	.	.	PUNCT
cana-2825	295	1	"	"	PUNCT
cana-2825	295	2	potato	potato	NOUN
cana-2825	295	3	yield	yield	NOUN
cana-2825	295	4	prediction	prediction	NOUN
cana-2825	295	5	using	use	VERB
cana-2825	295	6	machine	machine	NOUN
cana-2825	295	7	learning	learn	VERB
cana-2825	295	8	techniques	technique	NOUN
cana-2825	295	9	and	and	CCONJ
cana-2825	295	10	sentinel	sentinel	ADJ
cana-2825	295	11	2	2	NUM
cana-2825	295	12	data	datum	NOUN
cana-2825	295	13	.	.	PUNCT
cana-2825	295	14	"	"	PUNCT
cana-2825	296	1	remote	remote	ADJ
cana-2825	296	2	sensing	sense	VERB
cana-2825	296	3	11.15	11.15	NUM
cana-2825	296	4	(	(	PUNCT
cana-2825	296	5	2019	2019	NUM
cana-2825	296	6	):	):	PUNCT
cana-2825	296	7	1745	1745	NUM
cana-2825	296	8	.	.	PUNCT
cana-2825	297	1	[	[	X
cana-2825	297	2	13	13	NUM
cana-2825	297	3	]	]	SYM
cana-2825	297	4	medar	medar	NOUN
cana-2825	297	5	,	,	PUNCT
cana-2825	297	6	ramesh	ramesh	PROPN
cana-2825	297	7	,	,	PUNCT
cana-2825	297	8	vijay	vijay	PROPN
cana-2825	297	9	s.	s.	PROPN
cana-2825	297	10	rajpurohit	rajpurohit	PROPN
cana-2825	297	11	,	,	PUNCT
cana-2825	297	12	and	and	CCONJ
cana-2825	297	13	shweta	shweta	PROPN
cana-2825	297	14	shweta	shweta	PROPN
cana-2825	297	15	.	.	PUNCT
cana-2825	298	1	"	"	PUNCT
cana-2825	298	2	crop	crop	NOUN
cana-2825	298	3	yield	yield	NOUN
cana-2825	298	4	prediction	prediction	NOUN
cana-2825	298	5	using	use	VERB
cana-2825	298	6	machine	machine	NOUN
cana-2825	298	7	learning	learn	VERB
cana-2825	298	8	techniques	technique	NOUN
cana-2825	298	9	.	.	PUNCT
cana-2825	298	10	"	"	PUNCT
cana-2825	299	1	2019	2019	NUM
cana-2825	299	2	ieee	ieee	NOUN
cana-2825	299	3	5th	5th	ADJ
cana-2825	299	4	international	international	ADJ
cana-2825	299	5	conference	conference	NOUN
cana-2825	299	6	for	for	ADP
cana-2825	299	7	convergence	convergence	NOUN
cana-2825	299	8	in	in	ADP
cana-2825	299	9	technology	technology	NOUN
cana-2825	299	10	(	(	PUNCT
cana-2825	299	11	i2ct	i2ct	NOUN
cana-2825	299	12	)	)	PUNCT
cana-2825	299	13	.	.	PUNCT
cana-2825	300	1	ieee	ieee	PROPN
cana-2825	300	2	,	,	PUNCT
cana-2825	300	3	2019	2019	NUM
cana-2825	300	4	.	.	PUNCT
cana-2825	301	1	communications	communication	NOUN
cana-2825	301	2	on	on	ADP
cana-2825	301	3	applied	apply	VERB
cana-2825	301	4	nonlinear	nonlinear	ADJ
cana-2825	301	5	analysis	analysis	NOUN
cana-2825	301	6	issn	issn	NOUN
cana-2825	301	7	:	:	PUNCT
cana-2825	301	8	1074	1074	NUM
cana-2825	301	9	-	-	PUNCT
cana-2825	301	10	133x	133x	NUM
cana-2825	301	11	vol	vol	NOUN
cana-2825	301	12	32	32	NUM
cana-2825	301	13	no	no	NOUN
cana-2825	301	14	.	.	PUNCT
cana-2825	302	1	4s	4s	NUM
cana-2825	302	2	(	(	PUNCT
cana-2825	302	3	2025	2025	NUM
cana-2825	302	4	)	)	PUNCT
cana-2825	302	5	355	355	NUM
cana-2825	302	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2825	303	1	[	[	X
cana-2825	303	2	14	14	NUM
cana-2825	303	3	]	]	SYM
cana-2825	303	4	ju	ju	PROPN
cana-2825	303	5	,	,	PUNCT
cana-2825	303	6	sungha	sungha	PROPN
cana-2825	303	7	,	,	PUNCT
cana-2825	303	8	et	et	PROPN
cana-2825	303	9	al	al	PROPN
cana-2825	303	10	.	.	PUNCT
cana-2825	304	1	"	"	PUNCT
cana-2825	304	2	optimal	optimal	ADJ
cana-2825	304	3	county	county	NOUN
cana-2825	304	4	-	-	PUNCT
cana-2825	304	5	level	level	NOUN
cana-2825	304	6	crop	crop	NOUN
cana-2825	304	7	yield	yield	NOUN
cana-2825	304	8	prediction	prediction	NOUN
cana-2825	304	9	using	use	VERB
cana-2825	304	10	modis	modis	PROPN
cana-2825	304	11	-	-	PUNCT
cana-2825	304	12	based	base	VERB
cana-2825	304	13	variables	variable	NOUN
cana-2825	304	14	and	and	CCONJ
cana-2825	304	15	weather	weather	NOUN
cana-2825	304	16	data	datum	NOUN
cana-2825	304	17	:	:	PUNCT
cana-2825	304	18	a	a	DET
cana-2825	304	19	comparative	comparative	ADJ
cana-2825	304	20	study	study	NOUN
cana-2825	304	21	on	on	ADP
cana-2825	304	22	machine	machine	NOUN
cana-2825	304	23	learning	learning	NOUN
cana-2825	304	24	models	model	NOUN
cana-2825	304	25	.	.	PUNCT
cana-2825	304	26	"	"	PUNCT
cana-2825	305	1	agricultural	agricultural	ADJ
cana-2825	305	2	and	and	CCONJ
cana-2825	305	3	forest	forest	NOUN
cana-2825	305	4	meteorology	meteorology	NOUN
cana-2825	305	5	307	307	NUM
cana-2825	305	6	(	(	PUNCT
cana-2825	305	7	2021	2021	NUM
cana-2825	305	8	):	):	PUNCT
cana-2825	305	9	108530	108530	NUM
cana-2825	305	10	.	.	PUNCT
cana-2825	306	1	[	[	X
cana-2825	306	2	15	15	NUM
cana-2825	306	3	]	]	X
cana-2825	306	4	coulibaly	coulibaly	NOUN
cana-2825	306	5	,	,	PUNCT
cana-2825	306	6	solemane	solemane	PROPN
cana-2825	306	7	,	,	PUNCT
cana-2825	306	8	et	et	PROPN
cana-2825	306	9	al	al	PROPN
cana-2825	306	10	.	.	PUNCT
cana-2825	307	1	"	"	PUNCT
cana-2825	307	2	deep	deep	ADJ
cana-2825	307	3	learning	learning	NOUN
cana-2825	307	4	for	for	ADP
cana-2825	307	5	precision	precision	NOUN
cana-2825	307	6	agriculture	agriculture	NOUN
cana-2825	307	7	:	:	PUNCT
cana-2825	307	8	a	a	DET
cana-2825	307	9	bibliometric	bibliometric	ADJ
cana-2825	307	10	analysis	analysis	NOUN
cana-2825	307	11	.	.	PUNCT
cana-2825	307	12	"	"	PUNCT
cana-2825	308	1	intelligent	intelligent	ADJ
cana-2825	308	2	systems	system	NOUN
cana-2825	308	3	with	with	ADP
cana-2825	308	4	applications	application	NOUN
cana-2825	308	5	16	16	NUM
cana-2825	308	6	(	(	PUNCT
cana-2825	308	7	2022	2022	NUM
cana-2825	308	8	):	):	PUNCT
cana-2825	308	9	200102	200102	NUM
cana-2825	308	10	.	.	PUNCT
cana-2825	309	1	[	[	X
cana-2825	309	2	16	16	NUM
cana-2825	309	3	]	]	X
cana-2825	309	4	sunitha	sunitha	PROPN
cana-2825	309	5	,	,	PUNCT
cana-2825	309	6	gurram	gurram	PROPN
cana-2825	309	7	,	,	PUNCT
cana-2825	309	8	et	et	PROPN
cana-2825	309	9	al	al	PROPN
cana-2825	309	10	.	.	PUNCT
cana-2825	310	1	"	"	PUNCT
cana-2825	310	2	modeling	modeling	NOUN
cana-2825	310	3	of	of	ADP
cana-2825	310	4	chaotic	chaotic	ADJ
cana-2825	310	5	political	political	ADJ
cana-2825	310	6	optimizer	optimizer	NOUN
cana-2825	310	7	for	for	ADP
cana-2825	310	8	crop	crop	NOUN
cana-2825	310	9	yield	yield	NOUN
cana-2825	310	10	prediction	prediction	NOUN
cana-2825	310	11	.	.	PUNCT
cana-2825	310	12	"	"	PUNCT
cana-2825	310	13	intelligent	intelligent	ADJ
cana-2825	310	14	automation	automation	NOUN
cana-2825	310	15	and	and	CCONJ
cana-2825	310	16	soft	soft	ADJ
cana-2825	310	17	computing	computing	NOUN
cana-2825	310	18	34.1	34.1	NUM
cana-2825	310	19	(	(	PUNCT
cana-2825	310	20	2022	2022	NUM
cana-2825	310	21	):	):	PUNCT
cana-2825	310	22	423	423	NUM
cana-2825	310	23	-	-	SYM
cana-2825	310	24	437	437	NUM
cana-2825	310	25	.	.	PUNCT
cana-2825	311	1	[	[	X
cana-2825	311	2	17	17	NUM
cana-2825	311	3	]	]	X
cana-2825	311	4	kumar	kumar	PROPN
cana-2825	311	5	,	,	PUNCT
cana-2825	311	6	y.	y.	PROPN
cana-2825	311	7	jeevan	jeevan	PROPN
cana-2825	311	8	nagendra	nagendra	PROPN
cana-2825	311	9	,	,	PUNCT
cana-2825	311	10	et	et	PROPN
cana-2825	311	11	al	al	PROPN
cana-2825	311	12	.	.	PUNCT
cana-2825	312	1	"	"	PUNCT
cana-2825	312	2	supervised	supervised	ADJ
cana-2825	312	3	machine	machine	NOUN
cana-2825	312	4	learning	learn	VERB
cana-2825	312	5	approach	approach	NOUN
cana-2825	312	6	for	for	ADP
cana-2825	312	7	crop	crop	NOUN
cana-2825	312	8	yield	yield	NOUN
cana-2825	312	9	prediction	prediction	NOUN
cana-2825	312	10	in	in	ADP
cana-2825	312	11	the	the	DET
cana-2825	312	12	agriculture	agriculture	NOUN
cana-2825	312	13	sector	sector	NOUN
cana-2825	312	14	.	.	PUNCT
cana-2825	312	15	"	"	PUNCT
cana-2825	313	1	2020	2020	NUM
cana-2825	313	2	5th	5th	ADJ
cana-2825	313	3	international	international	ADJ
cana-2825	313	4	conference	conference	NOUN
cana-2825	313	5	on	on	ADP
cana-2825	313	6	communication	communication	NOUN
cana-2825	313	7	and	and	CCONJ
cana-2825	313	8	electronics	electronic	NOUN
cana-2825	313	9	systems	system	NOUN
cana-2825	313	10	(	(	PUNCT
cana-2825	313	11	icces	icce	NOUN
cana-2825	313	12	)	)	PUNCT
cana-2825	313	13	.	.	PUNCT
cana-2825	314	1	ieee	ieee	PROPN
cana-2825	314	2	,	,	PUNCT
cana-2825	314	3	2020	2020	NUM
cana-2825	314	4	.	.	PUNCT
cana-2825	315	1	[	[	X
cana-2825	315	2	18	18	NUM
cana-2825	315	3	]	]	PUNCT
cana-2825	315	4	radočaj	radočaj	NOUN
cana-2825	315	5	,	,	PUNCT
cana-2825	315	6	dorijan	dorijan	VERB
cana-2825	315	7	,	,	PUNCT
cana-2825	315	8	mladen	mladen	PROPN
cana-2825	315	9	jurišić	jurišić	PROPN
cana-2825	315	10	,	,	PUNCT
cana-2825	315	11	and	and	CCONJ
cana-2825	315	12	mateo	mateo	PROPN
cana-2825	315	13	gašparović	gašparović	ADJ
cana-2825	315	14	.	.	PUNCT
cana-2825	316	1	"	"	PUNCT
cana-2825	316	2	the	the	DET
cana-2825	316	3	role	role	NOUN
cana-2825	316	4	of	of	ADP
cana-2825	316	5	remote	remote	ADJ
cana-2825	316	6	sensing	sense	VERB
cana-2825	316	7	data	datum	NOUN
cana-2825	316	8	and	and	CCONJ
cana-2825	316	9	methods	method	NOUN
cana-2825	316	10	in	in	ADP
cana-2825	316	11	a	a	DET
cana-2825	316	12	modern	modern	ADJ
cana-2825	316	13	approach	approach	NOUN
cana-2825	316	14	to	to	ADP
cana-2825	316	15	fertilization	fertilization	NOUN
cana-2825	316	16	in	in	ADP
cana-2825	316	17	precision	precision	NOUN
cana-2825	316	18	agriculture	agriculture	NOUN
cana-2825	316	19	.	.	PUNCT
cana-2825	316	20	"	"	PUNCT
cana-2825	317	1	remote	remote	ADJ
cana-2825	317	2	sensing	sense	VERB
cana-2825	317	3	14.3	14.3	NUM
cana-2825	317	4	(	(	PUNCT
cana-2825	317	5	2022	2022	NUM
cana-2825	317	6	):	):	PUNCT
cana-2825	317	7	778	778	NUM
cana-2825	317	8	.	.	PUNCT
cana-2825	318	1	[	[	X
cana-2825	318	2	19	19	NUM
cana-2825	318	3	]	]	X
cana-2825	318	4	abdel	abdel	PROPN
cana-2825	318	5	-	-	PUNCT
cana-2825	318	6	salam	salam	PROPN
cana-2825	318	7	,	,	PUNCT
cana-2825	318	8	mahmoud	mahmoud	PROPN
cana-2825	318	9	,	,	PUNCT
cana-2825	318	10	neeraj	neeraj	PROPN
cana-2825	318	11	kumar	kumar	PROPN
cana-2825	318	12	,	,	PUNCT
cana-2825	318	13	and	and	CCONJ
cana-2825	318	14	shubham	shubham	PROPN
cana-2825	318	15	mahajan	mahajan	PROPN
cana-2825	318	16	.	.	PUNCT
cana-2825	319	1	"	"	PUNCT
cana-2825	319	2	a	a	DET
cana-2825	319	3	proposed	propose	VERB
cana-2825	319	4	framework	framework	NOUN
cana-2825	319	5	for	for	ADP
cana-2825	319	6	crop	crop	NOUN
cana-2825	319	7	yield	yield	NOUN
cana-2825	319	8	prediction	prediction	NOUN
cana-2825	319	9	using	use	VERB
cana-2825	319	10	hybrid	hybrid	ADJ
cana-2825	319	11	feature	feature	NOUN
cana-2825	319	12	selection	selection	NOUN
cana-2825	319	13	approach	approach	NOUN
cana-2825	319	14	and	and	CCONJ
cana-2825	319	15	optimized	optimize	VERB
cana-2825	319	16	machine	machine	NOUN
cana-2825	319	17	learning	learning	NOUN
cana-2825	319	18	.	.	PUNCT
cana-2825	319	19	"	"	PUNCT
cana-2825	319	20	neural	neural	ADJ
cana-2825	319	21	computing	computing	NOUN
cana-2825	319	22	and	and	CCONJ
cana-2825	319	23	applications	application	NOUN
cana-2825	319	24	(	(	PUNCT
cana-2825	319	25	2024	2024	NUM
cana-2825	319	26	):	):	PUNCT
cana-2825	319	27	1	1	NUM
cana-2825	319	28	-	-	SYM
cana-2825	319	29	28	28	NUM
cana-2825	319	30	.	.	PUNCT
cana-2825	320	1	[	[	X
cana-2825	320	2	20	20	NUM
cana-2825	320	3	]	]	X
cana-2825	320	4	elavarasan	elavarasan	ADJ
cana-2825	320	5	,	,	PUNCT
cana-2825	320	6	dhivya	dhivya	NOUN
cana-2825	320	7	,	,	PUNCT
cana-2825	320	8	and	and	CCONJ
cana-2825	320	9	p.	p.	NOUN
cana-2825	320	10	m.	m.	NOUN
cana-2825	320	11	durai	durai	PROPN
cana-2825	320	12	raj	raj	PROPN
cana-2825	320	13	vincent	vincent	PROPN
cana-2825	320	14	.	.	PUNCT
cana-2825	321	1	"	"	PUNCT
cana-2825	321	2	fuzzy	fuzzy	ADJ
cana-2825	321	3	deep	deep	ADJ
cana-2825	321	4	learning	learning	NOUN
cana-2825	321	5	-	-	PUNCT
cana-2825	321	6	based	base	VERB
cana-2825	321	7	crop	crop	NOUN
cana-2825	321	8	yield	yield	NOUN
cana-2825	321	9	prediction	prediction	NOUN
cana-2825	321	10	model	model	NOUN
cana-2825	321	11	for	for	ADP
cana-2825	321	12	sustainable	sustainable	ADJ
cana-2825	321	13	agronomical	agronomical	ADJ
cana-2825	321	14	frameworks	framework	NOUN
cana-2825	321	15	.	.	PUNCT
cana-2825	321	16	"	"	PUNCT
cana-2825	321	17	neural	neural	ADJ
cana-2825	321	18	computing	computing	NOUN
cana-2825	321	19	and	and	CCONJ
cana-2825	321	20	applications	application	NOUN
cana-2825	321	21	33.20	33.20	NUM
cana-2825	321	22	(	(	PUNCT
cana-2825	321	23	2021	2021	NUM
cana-2825	321	24	):	):	PUNCT
cana-2825	321	25	13205	13205	NUM
cana-2825	321	26	-	-	SYM
cana-2825	321	27	13224	13224	NUM
cana-2825	321	28	.	.	PUNCT
cana-2825	322	1	[	[	X
cana-2825	322	2	21	21	NUM
cana-2825	322	3	]	]	X
cana-2825	322	4	wang	wang	PROPN
cana-2825	322	5	,	,	PUNCT
cana-2825	322	6	xinlei	xinlei	PROPN
cana-2825	322	7	,	,	PUNCT
cana-2825	322	8	et	et	PROPN
cana-2825	322	9	al	al	PROPN
cana-2825	322	10	.	.	PUNCT
cana-2825	323	1	"	"	PUNCT
cana-2825	323	2	winter	winter	NOUN
cana-2825	323	3	wheat	wheat	NOUN
cana-2825	323	4	yield	yield	NOUN
cana-2825	323	5	prediction	prediction	NOUN
cana-2825	323	6	at	at	ADP
cana-2825	323	7	county	county	NOUN
cana-2825	323	8	level	level	NOUN
cana-2825	323	9	and	and	CCONJ
cana-2825	323	10	uncertainty	uncertainty	NOUN
cana-2825	323	11	analysis	analysis	NOUN
cana-2825	323	12	in	in	ADP
cana-2825	323	13	main	main	ADJ
cana-2825	323	14	wheat	wheat	NOUN
cana-2825	323	15	-	-	PUNCT
cana-2825	323	16	producing	produce	VERB
cana-2825	323	17	regions	region	NOUN
cana-2825	323	18	of	of	ADP
cana-2825	323	19	china	china	PROPN
cana-2825	323	20	with	with	ADP
cana-2825	323	21	deep	deep	ADJ
cana-2825	323	22	learning	learning	NOUN
cana-2825	323	23	approaches	approach	NOUN
cana-2825	323	24	.	.	PUNCT
cana-2825	323	25	"	"	PUNCT
cana-2825	324	1	remote	remote	ADJ
cana-2825	324	2	sensing	sense	VERB
cana-2825	324	3	12.11	12.11	NUM
cana-2825	324	4	(	(	PUNCT
cana-2825	324	5	2020	2020	NUM
cana-2825	324	6	):	):	PUNCT
cana-2825	324	7	1744	1744	NUM
cana-2825	324	8	.	.	PUNCT
cana-2825	325	1	[	[	X
cana-2825	325	2	22	22	NUM
cana-2825	325	3	]	]	PUNCT
cana-2825	325	4	patro	patro	NOUN
cana-2825	325	5	,	,	PUNCT
cana-2825	325	6	pramoda	pramoda	PROPN
cana-2825	325	7	,	,	PUNCT
cana-2825	325	8	et	et	PROPN
cana-2825	325	9	al	al	PROPN
cana-2825	325	10	.	.	PUNCT
cana-2825	326	1	"	"	PUNCT
cana-2825	326	2	a	a	DET
cana-2825	326	3	hybrid	hybrid	ADJ
cana-2825	326	4	approach	approach	NOUN
cana-2825	326	5	estimates	estimate	VERB
cana-2825	326	6	the	the	DET
cana-2825	326	7	real	real	ADJ
cana-2825	326	8	-	-	PUNCT
cana-2825	326	9	time	time	NOUN
cana-2825	326	10	health	health	NOUN
cana-2825	326	11	state	state	NOUN
cana-2825	326	12	of	of	ADP
cana-2825	326	13	a	a	DET
cana-2825	326	14	bearing	bearing	NOUN
cana-2825	326	15	by	by	ADP
cana-2825	326	16	accelerated	accelerate	VERB
cana-2825	326	17	degradation	degradation	NOUN
cana-2825	326	18	tests	test	NOUN
cana-2825	326	19	,	,	PUNCT
cana-2825	326	20	machine	machine	NOUN
cana-2825	326	21	learning	learning	NOUN
cana-2825	326	22	.	.	PUNCT
cana-2825	326	23	"	"	PUNCT
cana-2825	327	1	2021	2021	NUM
cana-2825	327	2	second	second	ADJ
cana-2825	327	3	international	international	ADJ
cana-2825	327	4	conference	conference	NOUN
cana-2825	327	5	on	on	ADP
cana-2825	327	6	smart	smart	ADJ
cana-2825	327	7	technologies	technology	NOUN
cana-2825	327	8	in	in	ADP
cana-2825	327	9	computing	computing	NOUN
cana-2825	327	10	,	,	PUNCT
cana-2825	327	11	electrical	electrical	ADJ
cana-2825	327	12	and	and	CCONJ
cana-2825	327	13	electronics	electronics	NOUN
cana-2825	327	14	(	(	PUNCT
cana-2825	327	15	icstcee	icstcee	NOUN
cana-2825	327	16	)	)	PUNCT
cana-2825	327	17	.	.	PUNCT
cana-2825	328	1	ieee	ieee	NOUN
cana-2825	328	2	,	,	PUNCT
cana-2825	328	3	2021	2021	NUM
cana-2825	328	4	.	.	PUNCT
cana-2825	329	1	[	[	X
cana-2825	329	2	23	23	NUM
cana-2825	329	3	]	]	X
cana-2825	329	4	gopi	gopi	PROPN
cana-2825	329	5	,	,	PUNCT
cana-2825	329	6	p.	p.	PROPN
cana-2825	329	7	s.	s.	PROPN
cana-2825	329	8	s.	s.	PROPN
cana-2825	329	9	,	,	PUNCT
cana-2825	329	10	and	and	CCONJ
cana-2825	329	11	m.	m.	PROPN
cana-2825	329	12	karthikeyan	karthikeyan	PROPN
cana-2825	329	13	.	.	PUNCT
cana-2825	330	1	"	"	PUNCT
cana-2825	330	2	multimodal	multimodal	ADJ
cana-2825	330	3	machine	machine	NOUN
cana-2825	330	4	learning	learning	NOUN
cana-2825	330	5	based	base	VERB
cana-2825	330	6	crop	crop	NOUN
cana-2825	330	7	recommendation	recommendation	NOUN
cana-2825	330	8	and	and	CCONJ
cana-2825	330	9	yield	yield	NOUN
cana-2825	330	10	prediction	prediction	NOUN
cana-2825	330	11	model	model	NOUN
cana-2825	330	12	.	.	PUNCT
cana-2825	330	13	"	"	PUNCT
cana-2825	331	1	intell	intell	PROPN
cana-2825	331	2	autom	autom	PROPN
cana-2825	331	3	soft	soft	ADJ
cana-2825	331	4	comput	comput	NOUN
cana-2825	331	5	36.1	36.1	NUM
cana-2825	331	6	(	(	PUNCT
cana-2825	331	7	2023	2023	NUM
cana-2825	331	8	):	):	PUNCT
cana-2825	331	9	313	313	NUM
cana-2825	331	10	-	-	SYM
cana-2825	331	11	326	326	NUM
cana-2825	331	12	.	.	PUNCT
cana-2825	332	1	[	[	X
cana-2825	332	2	24	24	NUM
cana-2825	332	3	]	]	X
cana-2825	332	4	richetti	richetti	PROPN
cana-2825	332	5	,	,	PUNCT
cana-2825	332	6	jonathan	jonathan	PROPN
cana-2825	332	7	,	,	PUNCT
cana-2825	332	8	et	et	PROPN
cana-2825	332	9	al	al	PROPN
cana-2825	332	10	.	.	PUNCT
cana-2825	333	1	"	"	PUNCT
cana-2825	333	2	a	a	DET
cana-2825	333	3	methods	method	NOUN
cana-2825	333	4	guideline	guideline	NOUN
cana-2825	333	5	for	for	ADP
cana-2825	333	6	deep	deep	ADJ
cana-2825	333	7	learning	learning	NOUN
cana-2825	333	8	for	for	ADP
cana-2825	333	9	tabular	tabular	PROPN
cana-2825	333	10	data	datum	NOUN
cana-2825	333	11	in	in	ADP
cana-2825	333	12	agriculture	agriculture	NOUN
cana-2825	333	13	with	with	ADP
cana-2825	333	14	a	a	DET
cana-2825	333	15	case	case	NOUN
cana-2825	333	16	study	study	NOUN
cana-2825	333	17	to	to	PART
cana-2825	333	18	forecast	forecast	VERB
cana-2825	333	19	cereal	cereal	NOUN
cana-2825	333	20	yield	yield	NOUN
cana-2825	333	21	.	.	PUNCT
cana-2825	333	22	"	"	PUNCT
cana-2825	334	1	computers	computer	NOUN
cana-2825	334	2	and	and	CCONJ
cana-2825	334	3	electronics	electronic	NOUN
cana-2825	334	4	in	in	ADP
cana-2825	334	5	agriculture	agriculture	NOUN
cana-2825	334	6	205	205	NUM
cana-2825	334	7	(	(	PUNCT
cana-2825	334	8	2023	2023	NUM
cana-2825	334	9	):	):	PUNCT
cana-2825	334	10	107642	107642	NUM
cana-2825	334	11	.	.	PUNCT
cana-2825	335	1	[	[	X
cana-2825	335	2	25	25	NUM
cana-2825	335	3	]	]	X
cana-2825	335	4	kok	kok	PROPN
cana-2825	335	5	,	,	PUNCT
cana-2825	335	6	zhi	zhi	PROPN
cana-2825	335	7	hong	hong	PROPN
cana-2825	335	8	,	,	PUNCT
cana-2825	335	9	et	et	PROPN
cana-2825	335	10	al	al	PROPN
cana-2825	335	11	.	.	PUNCT
cana-2825	335	12	"	"	PUNCT
cana-2825	335	13	support	support	NOUN
cana-2825	335	14	vector	vector	NOUN
cana-2825	335	15	machine	machine	NOUN
cana-2825	335	16	in	in	ADP
cana-2825	335	17	precision	precision	NOUN
cana-2825	335	18	agriculture	agriculture	NOUN
cana-2825	335	19	:	:	PUNCT
cana-2825	335	20	a	a	DET
cana-2825	335	21	review	review	NOUN
cana-2825	335	22	.	.	PUNCT
cana-2825	335	23	"	"	PUNCT
cana-2825	335	24	computers	computer	NOUN
cana-2825	335	25	and	and	CCONJ
cana-2825	335	26	electronics	electronic	NOUN
cana-2825	335	27	in	in	ADP
cana-2825	335	28	agriculture	agriculture	NOUN
cana-2825	335	29	191	191	NUM
cana-2825	335	30	(	(	PUNCT
cana-2825	335	31	2021	2021	NUM
cana-2825	335	32	):	):	PUNCT
cana-2825	335	33	106546	106546	NUM
cana-2825	335	34	.	.	PUNCT