Method for predicting bacterial blight of rice by utilizing miRNA169h genes

Abstract

The invention discloses a method for predicting bacterial blight of rice by utilizing miRNA 169h genes, belonging to the technical field of biology. The method comprises the following steps: selecting rice to be detected and control rice, wherein the selected control rice is not infected with the bacterial blight but is cultivated with the rice to be detected under the same conditions; respectively separating total miRNA genes in the rice to be detected and the control rice; respectively detecting the expression quantities of the miRNA169h genes in the total miRNA genes in the rice to be detected and the control rice, wherein the sequences of the miRNA169h genes are shown in SEQ ID NO:1 in a sequence table; and judging whether the experiments are successful according to the expression quantities of the miRNA169h genes in the rice to be detected and the control rice and further judging whether a plant to be detected is infected with the bacterial blight if the experiments are successful. The prediction method disclosed by the invention achieves success, can achieve accurate prediction a few days before the bacterial blight of rice appears and has the effects of gaining time for early prevention and treatment and reducing the rice loss caused by the bacterial blight.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular to a method for predicting rice bacterial blight with miRNA169h gene. Background technique [0002] Rice is the main food crop in my country. Bacterial blight is one of the two major diseases of rice. It is a worldwide disease, especially in Asian rice regions. The incidence of bacterial blight is high and the infection is fast, and the rice fields with the disease will reduce production by 20-30%, or even 50%. Like most diseases, the early control effect of bacterial blight is better. In the middle and late stages of the disease, the pathogens have multiplied in large numbers, causing damage to the rice, and the control effect is poor. It can be seen that early forecasting is the key to the prevention of rice bacterial blight. [0003] The traditional rice bacterial blight forecast is mainly based on climate, weather, variety resistance, nitrogen fertilizer application, and disease ...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the shortcomings of untimely and inaccurate prediction of rice bacterial blight in the prior art, the embodiment of the present invention provides a method for predicting rice bacterial blight with miRNA169h gene

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