Method for monitoring wheat plant water content under different plant nitrogen content levels

Abstract

The invention belongs to the field of crop growth monitoring, and discloses a method for monitoring the wheat plant water content (PWC) under different plant nitrogen content (PNC) levels. The method comprises the following steps: combining wheat canopy blade reflectance spectroscopic data with PWC data, carrying out classification according to different PNC size levels, determining a core waveband common region under different PNC levels, constructing an optimum spectral index based on the core waveband common region, and establishing a general monitoring model of the wheat plant water content on the basis of the optimum spectral index. According to the invention, the influence of low, medium and high nitrogen nutrition conditions to PWC monitoring is fully considered, the selected optimal spectral index is suitable for wheat PWC high-spectrum monitoring under multiple kinds of nitrogen nutritions, and the wheat PWC under different water nitrogen conditions can be rapidly and accurately estimated without loss. The method provides important technical support for high-spectrum monitoring on the wheat plant water content under different nitrogen nutrition conditions in the precision agriculture.

Description

technical field [0001] The invention belongs to the field of crop growth monitoring, and relates to a method for monitoring moisture content of wheat plants at different plant nitrogen content levels, in particular to a method based on hyperspectral technology to determine the maximum common area of ​​the core band of wheat plant moisture content at different plant nitrogen content levels. The optimal spectral index and the method of establishing a wheat PWC monitoring model based on the optimal spectral index are especially suitable for hyperspectral monitoring research of wheat plant moisture content under different nitrogen nutrition levels. Background technique [0002] Based on hyperspectral remote sensing technology, real-time monitoring and rapid diagnosis of crop water status can be realized, which is of great significance for improving crop irrigation management level and water use efficiency. [0003] Plant water content (PWC) can fully reflect the water demand inf...

AI Technical Summary

Problems solved by technology

In recent years, scholars at home and abroad have done a lot of research on the sensitive bands and characteristic spectral parameters of crop PWC, and proposed various moisture spectral indexes, but these spectral indexes often only consider the single moisture influence.

Studies have shown that there is a strong correlation between biochemical components in crops, in which nitrogen (N) is indirectly related to crop moisture through chlorophyll, lignin, and cellulose. Therefore, different plant nitrogen content (PNC) levels will inevitably affect crops. Growth and development, thus indirectly affecting crop PWC monitoring

Since different nitrogen application levels are often involved in actual field production, the existing moisture spectral indices seldom consider the influence of different nitrogen nutrition levels, and although some spectral indices have high accuracy for the overall PWC monitoring research, they are not effective at certain PNC levels. The monitoring precision to PWC is then lower, and error is larger, therefore, urgently needs a kind of technology and the method that determine the PWC spectral index applicable to different PNC level conditions

Images