The Quantitative Study on Chlorophyll Content of Hylocereus polyrhizus Based on Hyperspectral Analysis

Li-jie LI; Yan-bin YUE; Yan-cang WANG; Ze-ying ZHAO; Rui-jun LI; Ke-yan NIE; Ling YUAN

doi:10.3964/j.issn.1000-0593(2021)11-3538-07

Journals >Spectroscopy and Spectral Analysis >Volume 41 >Issue 11 >Page 3538 > Article

Spectroscopy and Spectral Analysis
Vol. 41, Issue 11, 3538 (2021)

The Quantitative Study on Chlorophyll Content of Hylocereus polyrhizus Based on Hyperspectral Analysis

Li-jie LI^1,*, Yan-bin YUE^2,2;, Yan-cang WANG^3,3;, Ze-ying ZHAO^2,2;..., Rui-jun LI^2,2;, Ke-yan NIE^2,2; and Ling YUAN^{1,1; *;}|Show fewer author(s)

Author Affiliations

¹1. College of Resource and Environment, Southwest University, Chongqing 400716, China

²2. Institute of Science and Technology Information, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China

³3. North China Institute of Aerospace Engineering, Langfang 065000, China

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DOI: 10.3964/j.issn.1000-0593(2021)11-3538-07 Cite this Article

Li-jie LI, Yan-bin YUE, Yan-cang WANG, Ze-ying ZHAO, Rui-jun LI, Ke-yan NIE, Ling YUAN. The Quantitative Study on Chlorophyll Content of Hylocereus polyrhizus Based on Hyperspectral Analysis[J]. Spectroscopy and Spectral Analysis, 2021, 41(11): 3538 Copy Citation Text

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Fig. 1. Spectral measurement of Hylocereus polyrhizus branch

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Fig. 2. Reflectance spectra (a) and absorption peak depth (b) of stems of Hylocereus polyrhizus under different nitrogen levels

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Fig. 3. Matrix of determination coefficient of spectrum and chlorophyll content

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Fig. 4. Scatter plot of measured and predicted values based on first order differential transformation

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Fig. 5. Scatter plot of measured and predicted values based on continuous wavelet transform

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Statistic	Number	Minimum	Maximum	Mean	Standard deviation
CHL/%	96	0.041	0.359	0.161	0.060

Table 1. The statistical description of chlorophyll contents of Hylocereus polyrhizus branches

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变换形式	波段	模型	建模		验证
变换形式	波段	模型	$R_{建模}^{2}$	RMSE	$R_{验证}^{2}$	RMSE	RPD
R	969, 1 000	Y=0.079+7.046X₉₆₉-6.560X_{1 000}	0.509	0.4	0.382	0.052	1.074
R'	735, 1 645	Y=2 572.400X₇₃₅+74 903.5X_{1 645}	0.609	0.036	0.625	0.048	1.238
Log(R)	969, 1 000	Y=0.094+4.204X₉₆₉-4.134X_{1 000}	0.491	0.041	0.383	0.054	1.033
Log(R)'	673, 756, 996	Y=0.300+1 342.700X₆₇₃+5 344.200X₇₅₆-12 163.4X₉₉₆	0.601	0.036	0.630	0.07	0.874
1/R	969, 1 000	Y=0.230-0.023X₉₆₉+0.023X_{1 000}	0.455	0.042	0.272	0.057	0.98
(1/R)'	996, 1 074	Y=0.320+31.427X₉₉₆-96.869X_{1 074}	0.445	0.043	0.269	0.058	0.989

Table 2. The list of estimation models for chlorophyll content of Hylocereus polyrhizus stem based on mathematical transformation

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变换形式	波段	模型	建模		验证
变换形式	波段	模型	$R_{建模}^{2}$	RMSE	$R_{验证}^{2}$	RMSE	RPD
R	969, 1 000	Y=0.079+7.046X₉₆₉-6.560X_{1 000}	0.509	0.40	0.382	0.052	1.074
H₁	740, 830	Y=0.098+21.110X₇₄₀-123.046X₈₃₀	0.654	0.034	0.626	0.056	0.991
H₂	742, 1 312	Y=-0.059+4.001X₇₄₂+31.806X_{1 312}	0.657	0.034	0.639	0.040	1.336
H₃	761, 1 311	Y=-0.012+1.883X₇₆₁+5.434X_{1 311}	0.629	0.035	0.628	0.040	1.317
H₄	761, 1 134	Y= -0.026+0.353X₇₆₁+0.975X_{1 134}	0.621	0.035	0.609	0.041	1.284
H₅	702, 1 131	Y=-0.047-0.118 0X₇₀₂+0.656X_{1 131}	0.590	0.037	0.579	0.043	1.237
H₆	587, 1 561	Y=-0.059-0.122X₅₈₇-1.847X_{1 561}	0.584	0.037	0.624	0.041	1.300
H₇	688, 1 595	Y=-0.017-0.116X₆₈₈-0.168X_{1 595}	0.609	0.036	0.677	0.038	1.409
H₈	568, 1 206	Y=-0.006-0.052X₅₆₈+0.035X_{1 206}	0.529	0.039	0.691	0.038	1.392
H₉	358, 1 198	Y=-0.038-0.091X₃₅₈+0.011X_{1 198}	0.479	0.041	0.609	0.042	1.254
H₁₀	1 594, 1 742	Y=-0.092+0.019X_{1 594}+0.031X_{1 742}	0.336	0.047	0.202	0.060	0.887
ALL	L₁-740, L₁-1 347, L₄-698	Y=-0.075+58.988 $X_{L_{1} ⁃ 740}$ -243.373 $X_{L_{1} - 1 347}$ + 0.596 $X_{L_{4} - 698}$	0.752	0.029	0.678	0.037	1.652

Table 3. The estimation model list of chlorophyll content in Hylocereus polyrhizus stem based on binary wavelet

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