Estimation Model of Cotton Leaf Phosphorus Content Based on Hyperspectral Reflectance

doi:10.11924/j.issn.1000-6850.casb2021-1212

Abstract

Abstract:

The changes of chlorophyll content in cotton leaves under different phosphorus application rates were studied, aiming to establish an estimation model of leaf phosphorus content based on hyperspectrum to realize the rapid monitoring of phosphorus content in cotton leaves. Pot experiments were conducted, the chlorophyll content and phosphorus content of cotton functional leaves were determined under different phosphorus application rates, and the spectral variables of phosphorus content were constructed by using the correlation between vegetation index and chlorophyll content, thus achieving the quantitative monitoring of phosphorus content in cotton leaves by using hyperspectrum. The following results were obtained. (1) About 100 days after sowing, leaf phosphorus content and chlorophyll content has a significant relationship (R²=0.96). (2) The spectral variables of phosphorus content in the first leaf, the second leaf, the third leaf and the fourth leaf from the top are constructed by the correlation between vegetation index (X) and chlorophyll content (I). Each blade of the optimal model is shown as follows: for the first leaf from the top (L₁): I₁=2.6131X_RENDVI-0.4275, the X_RENDVI represents red edge normalized difference vegetation index, R²and root mean square error (RMSE) reach 0.71 and 0.20, respectively; for the second leaf from the top (L₂): I₅ =0.0142X_TVI+0.3274, the X_TVI represents triangular vegetation index, R² and RMSE reach 0.76 and 0.09, respectively; for the third leaf from the top (L₃): I₉=-0.3445X_ARI+0.4996, the X_ARI represents anthocyanin reflectance index, R² and RMSE reach 0.47 and 0.15, respectively; and for the fourth leaf from the top (L₄): I₁₀=-0.5082X_ARI+0.3484, R² and RMSE reach 0.82 and 0.10, respectively. (3) The inversion model of leaf phosphorus content of cotton is constructed based on spectral variables, and the R² and RMSE reach 0.75 and 0.04, respectively. Therefore, the leaf phosphorus content of cotton can be effectively monitored based on the correlation between leaf vegetation index and chlorophyll content at different leaf positions, and the liner relationship between chlorophyll content and leaf phosphorus content.

Key words: cotton, hyperspectrum, leaf position, chlorophyll, leaf phosphorus content

MA Yuanhua, YIN Caixia, WANG Hongyu, LIU Yuxuan, LIU Qiantong, ZHANG Ze. Estimation Model of Cotton Leaf Phosphorus Content Based on Hyperspectral Reflectance[J]. Chinese Agricultural Science Bulletin, 2023, 39(1): 123-132.

Figures/Tables 11

References 46

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营养元素	盐类	相对分子质量	母液浓度/ (mmol/L)	母液浓度/ (g/L)	每升最终营养液中母液用量/ mL	营养元素	营养液中元素最终浓度/ (μmol/L)
大量营养元素	KNO₃	101.1	1000	101.1	6	N、K	16000
	Ca(NO₃)₂·4H₂O	236.16	1000	236.16	4	Ca	6000
	NH₄H₂PO₄	115.08	1000	115.08	2	P	4000
	MgSO₄·7H₂O	246.48	1000	246.48	1	S、Mg	2000
						S	1000
						Mg	1000
微量营养元素	KCl^*	74.55	25	1.864	2	Cl	50
	H₃BO₃	61.83	12.5	0.7773	2	B	25
	MnSO₄·H₂O	169.01	1	0.169	2	Mn	2
	ZnSO₄·H₂O	287.54	1	0.288	2	Zn	2
	CuSO₄·5H₂O	249.68	0.25	0.062	2	Cu	0.5
	H₂MoO₄	161.97	0.25	0.04	2	Mo	0.5
	NaFeDTPA	558.5	64	30	0.3~1.0	Fe	16~53
	NiSO₄·6H₂O^*	262.86	0.25	0.066	2	Ni	0.5
	NaSiO₃·9H₂O^*	284.20	1000	284.2	1	Si	1000

营养元素	盐类	相对分子质量	母液浓度/ (mmol/L)	母液浓度/ (g/L)	每升最终营养液中母液用量/ mL	营养元素	营养液中元素最终浓度/ (μmol/L)
大量营养元素	KNO₃	101.1	1000	101.1	6	N、K	16000
	Ca(NO₃)₂·4H₂O	236.16	1000	236.16	4	Ca	6000
	NH₄H₂PO₄	115.08	1000	115.08	2	P	4000
	MgSO₄·7H₂O	246.48	1000	246.48	1	S、Mg	2000
						S	1000
						Mg	1000
微量营养元素	KCl^*	74.55	25	1.864	2	Cl	50
	H₃BO₃	61.83	12.5	0.7773	2	B	25
	MnSO₄·H₂O	169.01	1	0.169	2	Mn	2
	ZnSO₄·H₂O	287.54	1	0.288	2	Zn	2
	CuSO₄·5H₂O	249.68	0.25	0.062	2	Cu	0.5
	H₂MoO₄	161.97	0.25	0.04	2	Mo	0.5
	NaFeDTPA	558.5	64	30	0.3~1.0	Fe	16~53
	NiSO₄·6H₂O^*	262.86	0.25	0.066	2	Ni	0.5
	NaSiO₃·9H₂O^*	284.20	1000	284.2	1	Si	1000

植被指数	定义或计算公式	文献
比值植被指数1(RVI)	R₇₆₅/R₇₂₀	[20]
归一化植被指数(NDVI)	(R₈₀₀-R₆₇₀)/(R₈₀₀+R₆₇₀)	[21]
大气阻抗植被指数(ARVI)	(R₈₀₀-R₆₇₀)/(R₈₀₀+R₆₇₀-R₄₅₀)	[22]
红边归一化植被指数(RENDVI)	(R₇₅₀-R₇₀₅)/(R₇₅₀+R₇₀₅).	[23]
绿色归一化植被指数(GNDVI)	(R₈₀₁-R₅₅₀)/(R₈₀₁+R₅₅₀)	[24]
简单比值植被指数(GRVI)	R₈₀₀/R₅₅₀	[24]
色素吸收比值植被指数(MRESR)	(R₇₅₀-R₄₄₅)/(R₇₀₅+R₄₄₅)	[25]
花青素反射指数(ARI)	(1/R₅₅₀)-(l/R₇₀₀)	[26]
比值植被指数2(MACI)	R_NIR/R_green
比值植被指数3(ACI)	R_green/R_NIR
三角植被指数(TVI)	60×(R₈₀₀-R₅₅₀)-100×(R₆₇₀-R₅₅₀)	[27]
MERIS陆地叶绿素指数(MTCI)	(R₇₅₄-R₇₀₉)/(R₇₀₉-R₆₈₁)	[28]

植被指数	定义或计算公式	文献
比值植被指数1(RVI)	R₇₆₅/R₇₂₀	[20]
归一化植被指数(NDVI)	(R₈₀₀-R₆₇₀)/(R₈₀₀+R₆₇₀)	[21]
大气阻抗植被指数(ARVI)	(R₈₀₀-R₆₇₀)/(R₈₀₀+R₆₇₀-R₄₅₀)	[22]
红边归一化植被指数(RENDVI)	(R₇₅₀-R₇₀₅)/(R₇₅₀+R₇₀₅).	[23]
绿色归一化植被指数(GNDVI)	(R₈₀₁-R₅₅₀)/(R₈₀₁+R₅₅₀)	[24]
简单比值植被指数(GRVI)	R₈₀₀/R₅₅₀	[24]
色素吸收比值植被指数(MRESR)	(R₇₅₀-R₄₄₅)/(R₇₀₅+R₄₄₅)	[25]
花青素反射指数(ARI)	(1/R₅₅₀)-(l/R₇₀₀)	[26]
比值植被指数2(MACI)	R_NIR/R_green
比值植被指数3(ACI)	R_green/R_NIR
三角植被指数(TVI)	60×(R₈₀₀-R₅₅₀)-100×(R₆₇₀-R₅₅₀)	[27]
MERIS陆地叶绿素指数(MTCI)	(R₇₅₄-R₇₀₉)/(R₇₀₉-R₆₈₁)	[28]

植被指数	倒一叶(L₁)	倒二叶(L₂)	倒三叶(L₃)	倒四叶(L₄)
RVI	0.43^*	0.38^*	0.26	0.34
NDVI	0.37^*	0.23	-0.02	0.39^*
ARVI	0.33	0.16	-0.01	0.41^*
RENDVI	0.50^**	0.38^*	0.26	0.45^*
GNDVI	0.49^**	0.33	0.18	0.36
MRESR	0.46^*	0.39^*	0.17	0.41^*
ARI	-0.37^*	-0.34	-0.27	-0.75^**
MACI	0.47^**	0.39^*	0.19	0.35
GRVI	0.47^**	0.39^*	0.19	0.35
TVI	0.29	0.39^*	0.27	0.14
ACI	-0.49^**	-0.32	-0.18	-0.36
MTCI	0.47^**	0.41^*	0.32	0.38^*