Boosting leaf trait estimation from reflectance spectra by elucidating the transferability of PLSR models

Leaf spectroscopy, combined with partial least squares regression (PLSR), is recognized as an efficient and precise tool for measuring plant leaf traits. However, the feasibility of developing a generalizable model remains unclear, primarily due to limited understanding of PLSR model transferability. Here, we provided the datasets and codes for investigating this issue using 1,967 samples of 349 tree species in eight forest sites across China.Researchers utilizing these datasets and codes should cite the following paper:Jiatong Wang, Xiaoqiang Liu, Xiaotian Qi, Xiaoyong Wu, Yilin Long,Yuhao Feng, Qi Dong, Jiabo Yan, Liwen Huang, Yue Luo, Mengqi Cao, Kai Xu, Changming Zhao, Yang Wang, Tianyu Hu, Jin Wu, Lingli Liu, Yanjun Su (2025) . Boosting leaf trait estimation from reflectance spectra by elucidating the transferability of PLSR models. Plant Phenomics. Accepted.