Method and system for detecting rice panicle blast based on deep convolutional neural network

Abstract

The invention discloses a method and a system for detecting rice panicle blast based on a deep convolutional neural network. The method comprises the following steps: acquiring a hyperspectral image of outdoor rice panicles and performing panicle blast disease calibration; performing data preprocessing and data enhancement on the hyperspectral image of the rice panicles; establishing a deep convolutional neural network model and optimizing model parameters with a stochastic gradient descent algorithm; detecting the hyperspectral image of the rice panicles to be tested with the trained deep convolutional neural network model, and judging whether the rice panicles are infected by the panicle blast disease or not. The system comprises a hyperspectral camera, a computer, a tripod and a reflection board, wherein the rice panicles are hung on the reflection board; the hyperspectral camera is fixed on the tripod, is connected with the computer, and has a lens aiming at the rice panicles on the reflection board. The method and the system provided by the invention can provide technical support for predicting the outdoor rice panicle blast disease and can also play an instructive role in rational and precise application and management of water and fertilizer, pesticide or other agricultural resources in a production process.

Description

technical field [0001] The invention relates to a rice blast blast detection method and system, in particular to a rice blast blast detection method and system based on a deep convolutional neural network, belonging to the technical field of intelligent detection of rice blast blast. Background technique [0002] Rice is the most important food crop in my country. my country's rice planting area reaches 30 million hectares, and its output accounts for 40% of the total grain output. Rice production is responsible for ensuring my country's food security. However, rice is often attacked by diseases and insect pests during its growth process, which affects the yield and quality. Rice blast is a fungal disease in the world, and it is one of the most serious rice diseases in the northern and southern rice-growing regions of my country. Rice blast occurs in all major rice areas in my country, with an average annual area of ​​more than 3.8 million hectares, and the annual loss of ...

AI Technical Summary

Problems solved by technology

The research work is limited to a sample size of hundreds of orders, and is limited to the hyperspectral image acquisition process operated by a laboratory light box under the condition of a fixed light source, which is still far from the actual production application.

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