Rice leaf chlorophyll carotenoid content ratio remote sensing inversion model and method based on Lars algorithm

Abstract

The invention provides a rice leaf chlorophyll carotenoid content ratio remote sensing inversion model based on a Lars algorithm, the rice leaf chlorophyll carotenoid content ratio remote sensing inversion model based on the Lars algorithm is a Lars regression model of Python language, and model parameters of the Lars regression model are further provided. The invention further provides a rice leaf chlorophyll carotenoid content ratio remote sensing inversion method based on the Lars algorithm. The rice leaf chlorophyll carotenoid content ratio remote sensing inversion model based on the Larsalgorithm can quickly and accurately obtain the rice leaf chlorophyll carotenoid content ratio information, the difficulty that it is difficult to determine the characteristic wave band of the chlorophyll carotenoid content ratio of rice leaves due to the spectral superposition effect caused by complex rice components is overcome, and the precision of the inversion model of the chlorophyll carotenoid content ratio of the rice leaves is greatly improved.

Description

technical field [0001] The invention relates to the technical field of agricultural remote sensing, in particular to the technical field of measuring the chlorophyll-carotenoid content ratio of rice leaves, specifically a Lars algorithm-based remote sensing inversion model and method for the chlorophyll-carotenoid content ratio of rice leaves. Background technique [0002] The chloroplast in rice leaves is the main place for photosynthesis in rice. The pigments that absorb light energy in photosynthesis mainly include chlorophyll and carotenoids, which are the material basis for material exchange and energy conversion between rice and the outside world (Jie Yang. Monitoring research on rice nitrogen and pigment content based on leaf hyperspectral index[D] . Nanjing Agricultural University, 2009). Among them, chlorophyll (including chlorophyll a and chlorophyll b) is the main light-absorbing substance, which directly affects the light energy utilization of rice photosynthesi...

AI Technical Summary

Problems solved by technology

In the process of constructing the inversion model of the ratio of chlorophyll-carotenoid content in rice leaves, the spectral range measured by the full-band spectrometer covers 350nm to 2500nm. It is difficult to determine the characteristic spectrum of carotene content ratio, and the rapid processing of hyperspectral data has become an urgent technical problem to estimate the ratio of chlorophyll-carotenoid content in rice leaves based on hyperspectral data

[0005] Therefore, it is hoped to provide a remote sensing inversion model for the ratio of chlorophyll-carotenoid content in rice leaves, which can quickly and accurately obtain the information of the ratio of chlorophyll-carotenoid content in rice leaves, and overcome the spectral superposition effect caused by complex rice components. It is difficult to determine the characteristic band of the ratio of chlorophyll-carotenoid content in leaves, which greatly improves the accuracy of the inversion model of the ratio of chlorophyll-carotenoid content in rice leaves

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