塔里木大学学报2025，Vol.37Issue(1)：83-92,10.DOI:10.3969/j.issn.1009-0568.2025.01.010
可见光图像识别开花期苹果叶片SPAD含量估测研究
Visible light image recognition for estimation of SPAD content in apple leaves at flowering stage
摘要
Abstract
Obtaining timely and accurate information on the chlorophyll content in the canopy of fruit trees is a matter of significant concern in the field of production.This study focuses on the canopy leaves of apple trees,a significant economic crop in the South-ern Xinjiang region,as the subject of research.By obtaining the actual SPAD values of apple canopy leaves during the flowering pe-riod,combined with the visible light image data of the canopy leaves,different channel combinations of color characteristics were explored.The study investigated the correlations between 16 different combinations of color features—B,R,G/B,(G-B)/R,(G-B)/(G+B),(G-B)/(R+G+B),G-B,R-B,R/B,R/(G+B),B/(G+R),(R-B)/G,(R-B)/(R+B),(G-B)/(G-R),(R-B)/(R+G+B),and(G-R)/(G+R-B)—and the SPAD values.The study selected four different algorithms to construct predictive models:Backpropagation neural network(BPNN),Particle swarm optimization backpropagation neural network(PSO-BP),Support vec-tor regression(SVR),and Convolutional neural network(CNN).Each of these algorithms was utilized to develop models aimed at forecasting based on the data collected.The results show that the CNN has the highest accuracy,and the training set R2 can reach 0.968 with an RMSE of 1.996 9;the test set R2 can reach 0.943 with an RMSE of 2.815 4.Upon comprehensive analysis,it is con-cluded that the combination of visible light imagery with a Convolutional neural network(CNN)model can effectively monitor the chlorophyll content in apple tree canopy leaves during the blooming period.This approach provides a reference for achieving non-destructive monitoring of chlorophyll content in fruit tree leaves.关键词
苹果叶片/SPAD/可见光图像/颜色特征/BP神经网络/卷积神经网络Key words
apple leaves/SPAD/visible light image/color feature/BP neural network/convolutional neural network分类
农业工程引用本文复制引用
候凯耀,李旭,石子琰,邬竞明..可见光图像识别开花期苹果叶片SPAD含量估测研究[J].塔里木大学学报,2025,37(1):83-92,10.基金项目
塔里木大学校长基金创新团队项目(TDZKCX202306) （TDZKCX202306）
中国农业大学-塔里木大学联合基金项目(ZNLH202402) （ZNLH202402）
