Method for predicting occurrence risk of wheat scab

Abstract

The invention discloses a method for predicting the occurrence risk of wheat scab. The method comprises the steps: wheat planting areas are divided according to wheat variety types and ecological climates of different production areas; according to actual production and a scab pathogen infection rule, the wheat scab infection expansion period is about 10 days before flowering to 30 days after flowering, so that the scab is divided: the infection period is the first ten days and the middle ten days of April, and the expansion period is from late April to early and middle May; an infection riskcoefficient (IRC) in an infection period is calculated; an expansion risk coefficient (ERC) of an expansion period is calculated; a total risk coefficient (TRC) of scab is calculated according to theinfection period risk coefficient and the expansion period risk coefficient; and whether the scab occurs or not is judged according to the obtained scab occurrence total risk coefficient. The method can accurately predict the risk of scab of wheat, so that the wheat can be prevented and treated in time according to the risk of scab of wheat, and popularization and application are facilitated.

Description

technical field [0001] The invention relates to the technical field of predicting wheat scab, in particular to a method for predicting the occurrence risk of wheat scab. Background technique [0002] Scab is a typical "meteorological" disease. The high incidence period is around the wheat flowering and heading period (late April to early May), during which wet and rainy and warm climate conditions (that is, the temperature in spring is higher than 12 ℃, the humidity is higher than 50 %), it is very easy to cause the epidemic of scab fungal pathogen. According to the epidemiological theory of plant diseases and insect pests, the occurrence of plant diseases and insect pests is comprehensively affected by three factors: pathogen, host and environment, and its development reflects the biological process of pathogen reproduction and amplification, as well as the spatiotemporal process of transmission and diffusion. Therefore, the overall performance is as follows: A complex and...

AI Technical Summary

Problems solved by technology

However, in the actual forecasting process, the year when the head blight occurs is often predicted in the early stage, and the head blight epidemic did not occur in the later period because of low rainfall and unsuitable temperature.