生态学杂志2024，Vol.43Issue(3)：733-740,8.DOI:10.13292/j.1000-4890.202403.003
受渍冬小麦不同叶位叶片的SPAD高光谱估算
Hyperspectral estimation of SPAD in different leaf positions of waterlogged winter wheat
摘要
Abstract
Real-time and accurate acquisition of chlorophyll content information is of great significance for timely understanding crop damage degree,guiding agricultural production,and estimating yield.To explore the optimal es-timation model for the soil and plant analyzer development(SPAD)in different leaf positions of waterlogged winter wheat,a plot experiment with a waterlogging stress gradient in winter wheat field under controlled drainage and irri-gation was established.The correlation between 15 commonly used hyperspectral indices and SPAD was analyzed.The SPAD estimation results of waterlogged winter wheat leaves were compared using hyperspectral indices com-bined with the multiple linear regression,support vector machine,BP neural network,decision tree,and random forest models.The results showed that compared with normal winter wheat,there was no significant difference for SPAD and the value of hyperspectral reflectance under short-term waterlogging(less than 3d).The SPAD was sig-nificantly decreased after more than 9 d waterlogging,and the value was close to 0 in the later growth period.The 15 hyperspectral indices were all correlated with the SPAD(P＜0.05),with the correlations between SPAD and the four indices(Ctr2,Dy,NDVI and SIPI)being the highest with the absolute correlation coefficient of 0.880,0.868,0.868 and 0.833,respectively.Compared with the SPAD estimation of the L1,L2,and L3 leaves,the results of average SPAD were the best,with the R2 of 0.719.The SPAD estimation models constructed with random forest model was the best for different leaf positions,with R2,RMSE and RE of 0.824,4.359 and 2.96％,respec-tively.Therefore,the average SPAD value could be used to estimate the SPAD of waterlogged winter wheat based on hyperspectral technology,and the random forest estimation model was best.关键词
高光谱特征指数/SPAD/冬小麦/渍害/随机森林模型Key words
hyperspectral characteristic index/SPAD/winter wheat/waterlogging/random forest model引用本文复制引用
高小梅,李燕丽,熊勤学,徐乐,李继福,李新竹,王晓军..受渍冬小麦不同叶位叶片的SPAD高光谱估算[J].生态学杂志,2024,43(3):733-740,8.基金项目
湖北省教育厅科学研究计划项目(B2020037)、湿地生态与农业利用教育部工程研究中心开放基金项目(KF202016)和国家自然科学基金项目(31871516)资助. （B2020037）
