A method and system for detecting physiological indicators of rice leaf adversity

Abstract

The invention relates to a method and system for detecting physiological indicators of rice leaf adversity. The method includes: obtaining a rice leaf sample; determining the hyperspectral information of the rice leaf sample; performing smoothing, denoising and dimension reduction processing on the hyperspectral information; obtaining the The real content value of the adversity physiological index of the rice leaf sample; the feature band of the hyperspectral information after smoothing, denoising and dimension reduction processing with the highest correlation with the real content value obtained by using the feature variable screening method; the feature band is m rows A spectral matrix of n columns, wherein n columns of spectra represent n characteristic variables highly correlated with rice leaf sample ascorbic acid content; based on the true content value and the eigenvector to establish a test set of rice leaf hyperspectral information-stress physiological index content A regression model; determining the stress physiological index of the rice leaf sample based on the regression model. The above-mentioned method in the present invention has high precise measurement precision and fast calculation.

Description

technical field [0001] The invention relates to the field of heavy metal detection, in particular to a method and system for detecting physiological indicators of rice leaf adversity. Background technique [0002] With modern industry and human activities, such as industrial waste and domestic sewage discharge, heavy metals are widely present in the plant growth environment. Among them, the heavy metal cadmium (Cadmium, Cd) is a non-essential toxic element for plants, animals and humans. The accumulation of Cd will not only cause the yield and quality loss of crops, but also enter through the food chain and endanger human health. [0003] Rice (Oryza sativa L.) is an important food crop in the world, and its consumption reaches more than 60% of the global population. At the same time, rice is also a crop sensitive to the heavy metal Cd in the environment. When rice is polluted by heavy metals, it will promote the increase of harmful reactive oxygen species (ROIs) in rice ...

AI Technical Summary

Problems solved by technology

[0004] The traditional detection methods of physiological indicators in adversity mostly use laboratory chemical detection, and sample pretreatment requires a low-temperature multi-reagent environment, which has large human error, high cost, and low efficiency, and cannot realize large-scale real-time monitoring

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