Multilayer information monitoring early warning method of early diseases of crops

Abstract

The invention discloses a multilayer information monitoring early warning method of early diseases of crops. The objective is to provide a lossless monitoring method of early diseases of crops. The method comprises steps of shooting the whole crop to obtain an object infrared image; calculating the average temperature of a monitoring object pixel point, the average temperature of a low-temperature pixel point and the average temperature of a high-temperature pixel point, and calculating the temperature difference between the average temperature of the low-temperature pixel point and the average temperature of the high-temperature pixel point; comparing the temperature difference with a monitoring threshold value and taking the temperature difference as the basis for determining whether the crops are infected with diseases; using a visible light-near infrared high spectral imaging device to monitor the crops suffering the diseases to obtain characteristic images; using a microscopy imaging device to monitor disease speckles in the characteristic images,= to obtain microscopy images; and according to a microscopy image gray scale histogram, estimating the early disease degree of the crops by combining the characteristic images. According to the invention, multilayer information of temperatures, pigments and textures of the crops is monitored; and disease detection and precise analysis in the incubation period and at the disease early stage are achieved.

Description

technical field [0001] The invention relates to a monitoring and early warning method for early crop diseases, in particular to a method for comprehensively utilizing infrared thermal imaging technology, visible light-near-infrared hyperspectral imaging technology and microscopic imaging technology to monitor the temperature, pigment, structure and texture of early crop diseases. A method for monitoring and early warning of early diseases with multi-level information. Background technique [0002] Crop disease management is a management method that replaces simple extensive and large-scale untargeted spraying. The key to realizing this management method is to use advanced detection methods to detect disease infection in time, and to carry out effective prevention and control according to the type and degree of disease. Disease stress detection research usually includes chemical analysis methods such as PCR detection, serological detection, and DNA array, which not only invo...

AI Technical Summary

Problems solved by technology

Disease stress detection and research usually include chemical analysis methods such as PCR detection, serological detection, and DNA array, which not only involve expensive instruments, but also require operators to have high professionalism; it takes a long time and costs a lot

[0003] In recent years, although non-destructive testing methods represented by spectral analysis and imaging technology have received more and more attention in crop disease monitoring, currently only visible light-near-infrared hyperspectral imaging or infrared imaging is used to monitor crop infection diseases. After a single level of biological information, it is difficult to monitor and warn early diseases that have not been discovered by the human eye

This is because infrared thermal imaging technology can monitor the difference in crop surface temperature when the disease is infected in the early stage, and has strong sensitivity and early warning. It can reveal the opening and closing of the stomatal heterogeneity of the crop after the disease is stressed, and reflect the early characteristics of the crop after the disease is infected; However, further research is still needed on the monitoring threshold of early crop disease and the evaluation of infection degree.

However, the visible-near-infrared hyperspectral imaging technology reflects the image texture features in the visible-near-infrared range, and the timeliness and early warning of the disease degree of the diseased crops are poor, and it is difficult to monitor and early warning of early crop infection.

Images