山东农业科学2024，Vol.56Issue(9)：133-141,9.DOI:10.14083/j.issn.1001-4942.2024.09.018
基于卷积神经网络和叶绿素荧光成像的绿豆叶斑病识别研究
Identification of Mung Bean Leaf Spot Disease Based on Convolutional Neural Network and Chlorophyll Fluorescence Imaging
摘要
Abstract
In order to solve the problem of confusion among different disease levels of mung bean leaf spot,a Multi-Module Sequential Convolutional Neural Network(MMS-Net)model was proposed based on chlorophyll fluorescence imaging of mung bean leaves infected by the disease.The model was mainly composed of the Sub modules and Wave modules proposed in this article,and the Convolutional Block Attention Module(CBAM)was added into each Sub module and at the end of each Wave module,which could detect similar disease spot features in more detail and reduce the mixing of non-leaf spot features at the same time,thereby improved the accuracy rate of disease recognition.Under the same conditions,compared with several classic convolutional neural network models(VGG16,GoogLeNet,ResNet50)and popular lightweight convolutional neural network models(MobileNetV2,MobileNeXt,MobileNetv3,ShuffleNetV2),the parameter size of the MMS-Net model was only 11.43 M and the test accuracy was 91.25％,which were higher than those in the other models,so it showed the best classification effect.By analyzing evaluation indicators such as precision,recall rate and Fl-score,it was concluded that the MMS-Net model exhibited better robustness and generaliza-tion ability,which could provide new ideas for screening disease-resistant germplasm resources of mung bean and other crops.关键词
绿豆叶斑病/病害等级/卷积神经网络/叶绿素荧光成像/注意力机制Key words
Mung bean leaf spot/Disease degree/Convolutional neural network/Chlorophyll fluores-cence imaging/Attention mechanism分类
农业科技引用本文复制引用
张浩淼,高尚兵,蒋东山,李洁,袁星星,陈新,刘金洋..基于卷积神经网络和叶绿素荧光成像的绿豆叶斑病识别研究[J].山东农业科学,2024,56(9):133-141,9.基金项目
国家自然科学基金面上项目(62076107) （62076107）
科技部重点研发政府间国际合作项目"抗黄花叶病毒病绿豆新品种选育与示范推广"(2019YFE0109100) （2019YFE0109100）
江苏省一带一路国际合作项目"抗黄花叶病毒病绿豆新品种及绿色增产增效技术合作研发及海外应用示范"(BZ2022005) （BZ2022005）
江苏省种业揭榜挂帅项目"双抗杂交绿豆新种质创制及关键基因挖掘利用"(JBGS[2021]004) （JBGS[2021]004）
江苏省研究生科研与实践创新计划项目(SJCX24_2145) （SJCX24_2145）
