Deep learning-based Candidatus Liberibacter spp detection method, device and system

Abstract

The invention relates to a deep learning-based Candidatus Liberibacter spp detection method, device and system. The method comprises the steps: acquiring image data of citrus leaves to be identified;Inputting the image data into a neural network model of Candidatus Liberibacter spp detection of a mobile terminal; And determining a detection result corresponding to the image data. The detection method is simple and convenient to operate, lossless, low in cost and popular with citrus producers; Moreover, the diagnosis process is simplified, the diagnosis cost is reduced, fruit farmers can be helped to detect and discover diseases as soon as possible, rapid, real-time, accurate and non-destructive diagnosis on citrus fruit trees in orchards is realized, reference can be provided for fertilization and production of the fruit farmers, great help is provided for the fruit tree yield, and a positive role is played in promoting accurate agriculture and agricultural informatization.

Description

technical field [0001] The invention relates to the technical field of intelligent identification of citrus huanglongbing, in particular to a method, device and system for detecting citrus huanglongbing based on deep learning. Background technique [0002] Citrus is one of the fruits with the largest production volume in the world, and it is also one of the largest fruit varieties planted in southern my country. It plays a very important role in the agricultural economy. And citrus Huanglongbing (HLB) is destructive to the production of citrus. The disease causes citrus trees to show symptoms such as mottled leaves, yellow leaves, weak tree vigor, red-nosed fruit or green fruit that does not turn color, etc., and has the potential to spread. The characteristics of fast speed and great harm. Once the citrus trees are infected with the disease, the light ones will seriously affect the fruit yield and quality, and the severe ones will cause the citrus plants to die, resulting ...

AI Technical Summary

Problems solved by technology

At present, the most reliable detection method for HLB is PCR detection technology, but the detection process of this method is cumbersome, the cycle is long, the detection cost is high, and the detection environment and operation requirements are high, which limits the application of this method in actual production.

In addition, methods such as graft diagnosis, serological diagnosis, field diagnosis, and DNA probe hybridization are difficult to promote in actual production due to low diagnostic accuracy, long time-consuming, high cost, and cumbersome processes.

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