农业机械学报2026，Vol.57Issue(18)：93-105,13.DOI:10.6041/j.issn.1000-1298.2026.18.009
基于ABC-CatBoost和光谱指数的黄瓜霜霉病叶部病斑SPAD值反演与严重度估计
SPAD Value Inversion and Severity Estimation for Cucumber Downy Mildew Leaf Lesions Based on ABC-CatBoost and Spectral Indices
摘要
Abstract
Accurate inversion and estimation of SPAD content and severity of cucumber downy mildew are of great significance for the management of the disease.Current research predominantly focused on overall leaf analysis,overlooking the inversion and estimation of SPAD content and severity of individual lesions.Moreover,traditional methods for SPAD inversion and severity estimation were time-consuming and labor-intensive.Therefore,it was aimed to investigate the SPAD inversion and severity estimation of individual cucumber downy mildew lesions based on ABC-CatBoost and spectral indices.By acquiring Fv/Fm images of infected leaves,the severity of different lesions was classified.Corresponding SPAD values and hyperspectral data of the lesions were also collected.To enhance the correlation between spectral data and SPAD content and severity,and reduce the impact of noise on modeling accuracy,MMS and Detrend data preprocessing methods were utilized.Optimal spectral feature bands were extracted from raw,MMS,and Detrend preprocessed data based on constructed one-dimensional,two-dimensional,and three-dimensional spectral indices.Using these features,the ABC-CatBoost model was employed to achieve SPAD inversion and severity estimation of cucumber downy mildew lesions.The results showed that the CatBoost algorithm,optimized by the artificial bee colony(ABC)algorithm,significantly improved the accuracy of SPAD inversion and severity estimation.Compared with one-dimensional spectral indices,two-dimensional and three-dimensional spectral indices,with their ability to integrate multidimensional information,demonstrated superior performance.Specifically,after Detrend preprocessing,the coefficients of determination between the two-dimensional and three-dimensional spectral indices and SPAD reached 0.927.In severity estimation,the accuracy between the Detrend-preprocessed two-dimensional spectral indices and the MMS-preprocessed three-dimensional spectral indices and the severity reached 90.90％,further demonstrating that Detrend preprocessing was superior to MMS.The research result can not only provide a reliable scientific basis for managing downy mildew but also have significant implications for improving the yield and quality of cucumber production.关键词
黄瓜霜霉病/最大光化学效率/严重度/人工蜂群算法/CatBoostKey words
cucumber downy mildew/Fv/Fm/severity/artificial bee colony algorithm/CatBoost分类
信息技术与安全科学引用本文复制引用
乔琛,刘源,姚坤宇,韩宗桓,李宜滨,张一丁,张领先..基于ABC-CatBoost和光谱指数的黄瓜霜霉病叶部病斑SPAD值反演与严重度估计[J].农业机械学报,2026,57(18):93-105,13.基金项目
国家自然科学基金项目(62376272、62176261) （62376272、62176261）
