The Inversion of Rice Leaf Pigment Content: Using the Absorption Spectrum to Optimize the Vegetation Index

Longfei Ma, Yuanjin Li, Ningge Yuan, Xiaojuan Liu, Yuyan Yan, Chaoran Zhang, Shenghui Fang and Yan Gong ()
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Longfei Ma: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Yuanjin Li: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Ningge Yuan: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Xiaojuan Liu: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Yuyan Yan: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Chaoran Zhang: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Shenghui Fang: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Yan Gong: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China

Agriculture, 2024, vol. 14, issue 12, 1-18

Abstract: The pigment content of rice leaves plays an important role in the growth and development of rice. The accurate and rapid assessment of the pigment content of leaves is of great significance for monitoring the growth status of rice. This study used the Analytical Spectra Device (ASD) FieldSpec 4 spectrometer to measure the leaf reflectance spectra of 4 rice varieties during the entire growth period under 4 nitrogen application rates and simultaneously measured the leaf pigment content. The leaf’s absorption spectra were calculated based on the physical process of spectral transmission. An examination was conducted on the variations in pigment composition among distinct rice cultivars, alongside a thorough dissection of the interrelations and distinctions between leaf reflectance spectra and absorption spectra. Based on the vegetation index proposed by previous researchers in order to invert pigment content, the absorption spectrum was used to replace the original reflectance data to optimize the vegetation index. The results showed that the chlorophyll and carotenoid contents of different rice varieties showed regular changes during the whole growth period, and that the leaf absorption spectra of different rice varieties showed more obvious differences than reflectance spectra. After replacing the reflectance of pigment absorptivity-sensitive bands (400 nm, 550 nm, 680 nm, and red-edge bands) with absorptivities that would optimize the vegetation index, the correlation between the vegetation index, which combines absorptivity and reflectivity, and the chlorophyll and carotenoid contents of 4 rice varieties during the whole growth period was significantly improved. The model’s validation results indicate that the pigment inversion model, based on the improved vegetation index using absorption spectra, outperforms the traditional vegetation index-based pigment inversion model. The results of this study demonstrate the potential application of absorption spectroscopy in the quantitative inversion of crop phenotypes.

Keywords: pigment content; absorption spectrum; reflection spectrum; vegetation index; rice (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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