Abstract
In order to solve the problems of many kinds of crop diseases and pests, fast diffusion speed, and long time of manual identification of diseases and pests, a crop disease and pest identification model based on deep learning from the perspective of ecological and environmental protection is proposed. Firstly, crop images are collected by field sampling to collect data set, and image preprocessing is completed by using nearest neighbor interpolation. Then, the network structure of the AlexNet model is improved. By optimizing the full connection layer, different neuron nodes and experimental parameters are set. Finally, the improved AlexNet model is used to identify crop diseases and pests. The experimental analysis of the proposed model based on the constructed data set shows that the average recognition accuracy and recognition time of fragrant pear diseases and insect pests are 96.26% and 321 ms, respectively, which are better than other comparison models. And, the recognition accuracy of this method on other data sets is not less than 91%, which has good portability.
Highlights
With the continuous advancement of agricultural reform, modern technology is closely related to the development of agriculture. e sustainable development of modern agriculture is no longer limited to the use of natural resources and includes the understanding and control of information resources [1]
Frequent outbreaks of crop diseases and insect pests directly affect the quantity and quality of agricultural products, resulting in economic losses [4]. erefore, it is necessary to study the control of crop diseases and insect pests to avoid unnecessary losses
Pest control was usually carried out by manual statistics and analysis, and the relevant technical personnel or agricultural experts relied on experience to determine the type of pest through tedious and repetitive inspection, measurement, and statistical calculation [7, 8]
Summary
With the continuous advancement of agricultural reform, modern technology is closely related to the development of agriculture. e sustainable development of modern agriculture is no longer limited to the use of natural resources and includes the understanding and control of information resources [1]. Reference [10] deeply analyzed the identification methods of different crop diseases and explored their control technologies, which provided technical guidance for effectively solving the problems of diseases and pests in the strawberry growth process. Reference [19] proposed a video detection architecture based on deep learning to achieve precise detection of plant diseases and insect pests, but the identification efficiency of a variety of plant diseases and insect pests needs to be improved. In order to solve the aforementioned problems of complex data preprocessing and low recognition accuracy, a recognition model of crop diseases and insect pests based on deep learning is proposed from the perspective of ecological environment protection.
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