Spectral Preprocessing Combined with Deep Transfer Learning to Evaluate Chlorophyll Content in Cotton Leaves

作     者：Qinlin Xiao Wentan Tang Chu Zhang Lei Zhou Lei Feng Jianxun Shen Tianying Yan Pan Gao Yong He Na Wu Qinlin Xiao;Wentan Tang;Chu Zhang;Lei Zhou;Lei Feng;Jianxun Shen;Tianying Yan;Pan Gao;Yong He;Na Wu

作者机构：College of Biosystems Engineering and Food ScienceZhejiang UniversityHangzhou 310058China Key Laboratory of Spectroscopy SensingMinistry of Agriculture and Rural AffairsHangzhou 310058China School of Information EngineeringHuzhou UniversityHuzhou 313000China College of Mechanical and Electronic EngineeringNanjing Forestry UniversityNanjing 210037China Hangzhou Raw Seed Growing FarmHangzhou 311115China College of Information Science and TechnologyShihezi UniversityShihezi 832000China 

出 版 物：《Plant Phenomics》 (植物表型组学（英文）)

年 卷 期：2022年第4卷第1期

页      面：127-141页

核心收录：

学科分类：0710[理学-生物学] 071001[理学-植物学] 07[理学] 

基　　金：This research was supported by XPCC Science and Technol-ogy Projects of Key Areas(2020AB005) 

主　　题：equipped batch content 

摘      要：Rapid determination of chlorophyll content is significant for evaluating cotton’s nutritional and physiological *** technology equipped with multivariate analysis methods has been widely used for chlorophyll content ***,the model developed on one batch or variety cannot produce the same effect for another due to variations,such as samples and measurement conditions.