Numerical estimation of chlorophyll in pepper leaves based on optimized vegetation index combination

doi:10.3969/j.issn.1004-1524.20221456

Acta Agriculturae Zhejiangensis ›› 2023, Vol. 35 ›› Issue (9): 2109-2120.DOI: 10.3969/j.issn.1004-1524.20221456

• Horticultural Science • Previous Articles Next Articles

Numerical estimation of chlorophyll in pepper leaves based on optimized vegetation index combination

WANG Yu¹(), WANG Hong¹^,^*(), XIAO Jiujun²^,³, LI Kexiang²^,³, XING Dan⁴, ZHANG Yongliang¹, CHEN Yang²^,³, ZHANG Lanyue²^,³

1. Mining College, Guizhou University, Guiyang 550025, China
2. Institute of Mountain Resources of Guizhou, Guizhou Academy of Sciences, Guiyang 550001, China
3. Engineering Research Center for Land Green Consolidation of Guizhou, Guiyang 550001, China
4. Pepper Research Institute, Guizhou Academy of Agricultural Sciences, Guiyang 550009, China

Received:2022-10-11 Online:2023-09-25 Published:2023-10-09

Abstract

Abstract:

Leaf chlorophyll is closely related to vegetation growth, and it is an important parameter that directly affects vegetation growth and health status. SPAD value can reflect the chlorophyll content of crop leaves. The larger the SPAD value, the higher the chlorophyll content, and the smaller the SPAD value, the lower the chlorophyll content. The shape and physiological and ecological parameters of different varieties of pepper are significantly different, so it is of great significance to accurately and quickly estimate the SPAD value. The SPAD values of 4 different varieties of peppers, Qianjiao 8, Hongla 18, Layan 101, and Red Globe, were measured. The reciprocal, logarithm, reciprocal logarithm, first-order differential and second-order differential transformation of the original spectrum were performed. The vegetation index was optimized by replacing the original spectrum with the transformed spectrum, and the difference between the optimized vegetation index and the classical vegetation index was compared. Finally, the relationship between SPAD values and hyperspectral of different varieties of peppers was obtained, and the optimal inversion model of SPAD values was found. The results showed that there were differences in canopy spectral characteristics of different pepper varieties. SPAD values of modeling set, validation set and full sample of pepper leaves showed that the change trend of line pepper was greater than that of Chao tian pepper. The correlation coefficients of vegetation indices based on reciprocal logarithmic spectral optimization were higher than classical vegetation indices except CI_{red edge}. The random forest model based on lg1/R-VI had good accuracy in both the modeling set and the validation set, which was suitable for the estimation of SPAD values of different varieties of pepper leaves. The coefficient of determination (R²) of full sample model test set was 0.83, mean absolute deviation (MAD) was 1.90, and R²of validation set was 0.45, MAD was 1.26.

Key words: pepper, SPAD, canopy hyperspectral, optimizing vegetation index, random forest model

CLC Number:

S641.3

WANG Yu, WANG Hong, XIAO Jiujun, LI Kexiang, XING Dan, ZHANG Yongliang, CHEN Yang, ZHANG Lanyue. Numerical estimation of chlorophyll in pepper leaves based on optimized vegetation index combination[J]. Acta Agriculturae Zhejiangensis, 2023, 35(9): 2109-2120.

Figures/Tables 6

Table 1 Statistical analysis of SPAD value of pepper

统计参数 Statistical parameter	辣研101号 Layan 101		红全球 Red global		黔椒8号 Qianjiao No.8		红辣18号 Red Hot 18		全样本 Whole sample
统计参数 Statistical parameter	建模集 Modeling set	验证集 Validation set	建模集 Modeling set	验证集 Validation set	建模集 Modeling set	验证集 Validation set	建模集 Modeling set	验证集 Validation set	建模集 Modeling set	验证集 Validation set
最小值Minimum value	29.4	31.2	34.5	35.9	40.9	46.1	45.1	52.1	29.4	31.2
最大值Maximum value	78.2	68.3	77.8	72	79.9	71.5	73.5	70.5	79.9	74.9
平均值Mean value	53.46	58.32	55.84	51.38	58.09	60.65	57.74	59.72	57.04	55.28
标准差Standard deviation	12.32	10.45	11.93	12.82	10.17	7.97	7.88	5.08	10.45	11.41
变异系数	0.23	0.18	0.21	0.25	0.18	0.13	0.14	0.09	0.18	0.21
Coefficient of variation

Fig.1 Spectral reflectance of different pepper varieties A represents Qianjiao No.8, B represents Hongla 18, C represents Layan 101, D represents Red Global. FRrepresents the original spectral reflectance, F1/R represents the reciprocal spectral reflectance, FlgR represents the logarithmic spectral reflectance, Flg(1/R) represents the reciprocal logarithmic spectral reflectance, FR' represents the first-order differential spectral reflectance, FR″ represents the second-order spectral reflectance.

Fig.2 Heat map of correlation analysis between SPAD and vegetation index CARI, Chlorophyll absorption ratio index; MCARI, Modified chlorophyll absorption ratio index; MTCI, MERIS terrestrial chlorophyll index; NDVI, Normalized difference vegetation index; TCARI, Transformed chlorophyll absorption in reflectance index; OSVAI, Optimized soil-adjusted vegetation index; C I r e d ? e d g e, Red edge chlorophyll index.

Table 2 Correlation analysis between whole sample optimized vegetation index and SPAD value

经典植被指数 Classical vegetation index		优化植被指数 Optimize vegetation index
R-VI	r	1/R-VI	r	lgR-VI	r	lg1/R-VI	r	R'-VI	r	R″-VI	r
CARI	0.02	CARI	0.18^*	CARI	0.09	CARI	-0.03	CARI	-0.01	CARI	-0.02
MCRAI	0.06	MCARI	0.01	MCARI	-0.12	MCARI	0.14^*	MCARI	0.03	MCARI	0.03
MTCI	-0.08	MTCI	-0.01	MTCI	0.11	MTCI	-0.20^**	MTCI	-0.04	MTCI	0.03
NDVI	0.13	NDVI	0.004	NDVI	0.001	NDVI	-0.16^*	NDVI	0.09	NDVI	0.04
TCARI	0.06	TCARI	-0.06	TCARI	-0.08	TCARI	0.20^**	TCARI	-0.05	TCARI	-0.04
OSVAI	0.09	OSVAI	-0.07	OSVAI	-0.08	OSVAI	0.22^**	OSVAI	-0.11	OSVAI	-0.02
T/O	0.04	T/O	0.03	T/O	0.04	T/O	0.18^*	T/O	0.03	T/O	-0.03
$C I r e d ? e d g e$	0.19^**	$C I r e d ? e d g e$	-0.11	$C I r e d ? e d g e$	-0.15^*	$C I r e d ? e d g e$	-0.02	$C I r e d ? e d g e$	0.07	$C I r e d ? e d g e$	0.06

Table 2 Correlation analysis between whole sample optimized vegetation index and SPAD value

经典植被指数 Classical vegetation index		优化植被指数 Optimize vegetation index
R-VI	r	1/R-VI	r	lgR-VI	r	lg1/R-VI	r	R'-VI	r	R″-VI	r
CARI	0.02	CARI	0.18^*	CARI	0.09	CARI	-0.03	CARI	-0.01	CARI	-0.02
MCRAI	0.06	MCARI	0.01	MCARI	-0.12	MCARI	0.14^*	MCARI	0.03	MCARI	0.03
MTCI	-0.08	MTCI	-0.01	MTCI	0.11	MTCI	-0.20^**	MTCI	-0.04	MTCI	0.03
NDVI	0.13	NDVI	0.004	NDVI	0.001	NDVI	-0.16^*	NDVI	0.09	NDVI	0.04
TCARI	0.06	TCARI	-0.06	TCARI	-0.08	TCARI	0.20^**	TCARI	-0.05	TCARI	-0.04
OSVAI	0.09	OSVAI	-0.07	OSVAI	-0.08	OSVAI	0.22^**	OSVAI	-0.11	OSVAI	-0.02
T/O	0.04	T/O	0.03	T/O	0.04	T/O	0.18^*	T/O	0.03	T/O	-0.03
$C I r e d ? e d g e$	0.19^**	$C I r e d ? e d g e$	-0.11	$C I r e d ? e d g e$	-0.15^*	$C I r e d ? e d g e$	-0.02	$C I r e d ? e d g e$	0.07	$C I r e d ? e d g e$	0.06

Table 3 RF model results of SPAD value estimated by optimizing vegetation index combination

品种 Variety	优化植被指数组合 Optimize vegetation	建模集 Modeling set		验证集 Validation set		品种 Variety	优化植被指数组合 Optimize vegetation	建模集 Modeling set		验证集 Validation set
品种 Variety	优化植被指数组合 Optimize vegetation	R²	MAD	R²	MAD	品种 Variety	优化植被指数组合 Optimize vegetation	R²	MAD	R²	MAD
辣研101号	F_R-VI	0.90	2.33	0.80	1.74	黔椒8号	F_R-VI	0.86	1.96	0.80	1.61
Layan 101	F_lgR-VI	0.87	2.29	0.64	1.67	Qianjiao	F_lgR-VI	0.87	2.10	0.65	1.38
	F_1/R-VI	0.90	2.42	0.90	2.45	No.8	F_1/R-VI	0.85	2.01	0.72	1.66
	F_lg1/R-VI	0.87	2.22	0.79	2.03		F_lg1/R-VI	0.87	2.24	0.83	2.07
	F_R'-VI	0.88	2.43	0.61	1.44		F_R'-VI	0.80	1.61	0.42	1.13
	F_R″-VI	0.84	2.05	0.51	1.37		F_R″-VI	0.85	1.64	0.46	1.25
红全球	F_R-VI	0.80	1.81	0.83	1.55	红辣18号	F_R-VI	0.83	1.95	0.63	1.26
Red global	F_lgR-VI	0.85	1.74	0.95	1.31	Red Hot 18	F_lgR-VI	0.79	1.83	0.66	1.40
	F_1/R-VI	0.83	1.84	0.56	1.28		F_1/R-VI	0.80	1.84	0.63	1.35
	F_lg1/R-VI	0.85	1.81	0.94	1.58		F_lg1/R-VI	0.76	1.74	0.51	1.22
	F_R'-VI	0.84	1.71	0.49	1.12		F_R'-VI	0.81	1.84	0.30	1.10
	F_R″-VI	0.83	1.69	0.71	0.86		F_R″-VI	0.84	1.83	0.30	0.71
全样本	F_R-VI	0.80	1.84	0.39	1.22
Whole	F_lgR-VI	0.82	1.91	0.42	1.27
sample	F_1/R-VI	0.80	1.80	0.42	1.25
	F_lg1/R-VI	0.83	1.90	0.45	1.26
	F_R'-VI	0.79	1.84	0.41	1.23
	F_R″-VI	0.79	1.83	0.40	1.22

Fig.3 Relationship between the measured value and the predicted value of SPAD optimal estimation model of different varieties of pepper

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Numerical estimation of chlorophyll in pepper leaves based on optimized vegetation index combination

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