基于热成像处理技术的生菜水分胁迫检测模型研究  

Study on water stress detection model of lettuce based on thermal imaging technology

作　　者：杨玉超 籍颖[1] 李敬蕊[2] 宫彬彬[2] 高洪波[2] Yang Yuchao;Ji Ying;Li Jingrui;Gong Binbin;Gao Hongbo(College of Information Science and Technology,Hebei Agricultural University,Baoding,071000,China;College of Horticulture,Hebei Agricultural University,Baoding,071000,China)

机构地区：[1]河北农业大学信息科学与技术学院,河北保定071000 [2]河北农业大学园艺学院,河北保定071000

出　　处：《中国农机化学报》2025年第1期131-137,共7页Journal of Chinese Agricultural Mechanization

基　　金：河北省重点研发计划——农业节水科技创新专项(21326903D)。

摘　　要：在生菜生长阶段对生菜植株进行受水分胁迫检测,在不影响品质的同时,可以有效节约水资源。以140棵生菜1901和耶罗为试验对象,在生菜生长阶段进行不同灌水量处理。采用热成像技术获取生菜冠层温度信息,以植株冠层温度信息为基础,提取其最大值、最小值、均值、方差、标准差、熵值、变异系数和不同温度宽度频率值作为特征值,建立支持向量机(SVM)、随机森林(RF)、鲸鱼算法优化支持向量机(WOA-SVM)和基于主成分分析的WOA-SVM的生菜受水分胁迫程度检测模型,进行识别准确性比较。试验结果,RF对耶罗和1901检测准确率为94.76%、92.37%;SVM对耶罗和1901检测准确率为91.64%、85.35%,WOA-SVM对耶罗和1901检测准确率为98.77%、94.76%,PCA-WOA-SVM模型对耶罗和1901检测准确率为98.94%、95.71%,PCA-WOA-SVM识别准确率高且稳定。During the growth stage of lettuce,water stress detection on lettuce plants can effectively save water resources without affecting the quality.In this study,140 lettuces 1901 and Yeluo were used as experimental subjects,and different irrigation amounts were applied during the growth stage of lettuce.Thermal imaging technology was used to obtain lettuce canopy temperature information,and the maximum value,minimum value,mean value,variance,standard deviation,entropy value,coefficient of variation and frequency values of different temperature widths based on the plant canopy temperature information were used as characteristic values.Support vector machine(SVM),Random Forest(RF),Whale Algorithm Optimized Support Vector Machine(WOA-SVM)and WOA-SVM based on principal component analysis were established to detect the water stress degree of lettuce,and the accuracy was compared.Experimental results show that RF has an accuracy of 94.76%and 92.37%for Yeluo and 1901.SVM has an accuracy of 91.64%and 85.35%for Yeluo and 1901.WOA-SVM has an accuracy of 98.77%and 94.76%for Yeluo and 1901.The PCA-WOA-SVM model has an accuracy of 98.94%and 95.71%for Yeluo and 1901.The PCA-WOA-SVM recognition accuracy is high and stable.

关 键 词：生菜 支持向量机 机器学习 热成像技术 水分胁迫检测 

分 类 号：S636.2[农业科学—蔬菜学] TP393[农业科学—园艺学]