Method using miRNA166 b gene for prediction of bacterial leaf blight of rice

Abstract

The invention discloses a method using miRNA166 b gene for prediction of bacterial leaf blight of rice, and belongs to the field of biotechnology. The method comprises the following steps: rice to be measured and control rice are selected, the selected the control rice is not infected with the bacterial leaf blight and is cultivated in the same condition with the rice to be measured; total miRNA genes in the rice to be measured and the control rice are separated respectively; the expression amounts of the miRNA166 b gene in the total miRNA genes in the rice to be measured and the control rice are detected respectively; the miRNA166 b gene sequence is as shown in SEQ ID NO:1 in a sequence table; and according to the expression amounts of the miRNA166 b gene in the total miRNA genes in the rice to be measured and the control rice, whether the experiment is successful is judged, and if the experiment is successful, whether the plant to be measured is infected with the bacterial leaf blight is further determined. The prediction method achieves a success, can accurately predict a few days before the bacterial leaf blight of rice, wins time for the early prevention and treatment, and reduces the loss caused by the bacterial leaf blight of rice.

Description

Technical field [0001] The present invention relates to the field of biotechnology, in particular to a method for forecasting rice bacterial blight using miRNA166b gene. Background technique [0002] Rice is the main food crop in my country. Bacterial blight is one of the two main diseases of rice. It is a worldwide disease, especially in Asian rice regions. Bacterial blight has a high incidence and rapid transmission, and the yield of the diseased rice field is reduced by 20-30%, even 50%. Like most diseases, the early control effect of bacterial blight is better. In the middle and late stages of the disease, the bacteria have multiplied in large numbers and have caused damage to the rice. The control effect is poor. This shows that early prediction is the key to the prevention of rice bacterial blight. [0003] Traditional rice bacterial blight forecasting is mainly based on the climate, weather, variety resistance, nitrogen fertilizer application, and disease history. It can ...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the shortcomings of untimely and inaccurate forecasting of rice bacterial blight in the prior art, the embodiment of the present invention provides a method of using miRNA166b gene to predict rice bacterial blight

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