Wheat variety scab comprehensive resistance identification method based on hyperspectral images

Abstract

The invention discloses a wheat variety scab comprehensive resistance identification method based on hyperspectral images, which takes wheat ears of different varieties infected by scab germs as research objects and comprehensively utilizes the knowledge in the fields of hyperspectral imaging technology, spectroscopy, time sequence analysis, deep learning and the like. The invention provides a resistance identification method for wheat varieties in an infection non-morbidity period, a resistance identification method for wheat varieties after morbidity, and a wheat variety scab comprehensive resistance identification method. The wheat variety scab comprehensive resistance identification method based on hyperspectral images overcomes the defects of difficult detection of resistance in an infection period, low speed and precision in manual identification operation, complex program and high cost in a chemical method, provides a quicker and more accurate method for identifying the resistance of wheat scab, and can identify the resistance of wheat varieties in a wheat scab infection non-morbidity period.

Description

Technical field [0001] The invention relates to the fields of wheat head blight detection and resistance identification, hyperspectral imaging technology, time series analysis and deep learning algorithms, and specifically to a method for comprehensive resistance identification of wheat head blight based on hyperspectral images. Background technique [0002] As one of the three major foods in the world, wheat diseases have become the focus of attention. Among them, Fusarium graminearum is a high-incidence fungal disease that poses the greatest threat to wheat production. This disease is also known as red wheat head, red head malaria, rotten wheat head, and wheat ear blight. Wheat grains infected with Fusarium head blight will be affected during the infection process. Produce deoxynivalenol-based mycotoxins (Xu Fei; the influence of different infection periods on the occurrence of wheat head blight and the accumulation of DON in the grain), which will cause serious yield loss and ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the invention is to address the problems existing in the prior art, and propose a method for comprehensive resistance identification of wheat varieties scab based on hyperspectral images; As well as defects such as slow speed, low precision, and complex procedures and high costs in the manual resistance identification operation after the onset of the disease, it covers the detection of the initial onset time and the difference analysis of spectra and image features in the non-onset period of wheat scab infection and post-onset Level automatic grading detection, comprehensively considering the initial onset time of the non-onset period of infection and the average severity of the disease after onset, can comprehensively, quickly and accurately realize the comprehensive resistance identification of wheat varieties scab

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