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ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Technical Advances in Plant Science
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1547832
Estimating photosynthetic characteristics of forage rape by fusing the sensitive spectral bands to combined stresses of nitrogen and salt
Provisionally accepted- College of Agriculture, Shihezi University, Shihezi, China
Leaf gas exchange and chlorophyll fluorescence parameters (PGE-CFPs), which respond significantly and quickly to environmental stresses, have been used to assess the early responses of crop physiology to stresses. Most spectral estimations only focus on crop photosynthetic characteristics under a single environmental stress. Thus, the methods proposed previously are not suitable for the estimations under combined stresses (i.e., nitrogen and salt). In this research, the leaf spectral features of forage rape (Brassica napus L.) under nitrogen stress (NSpe) and salt stress (SSpe) were fused to increase the accuracy of the spectral estimation of photosynthetic characteristics of forage rape under combined stresses in arid region of Xinjiang, China. The results showed that PGE-CFPs’ spectral features were extracted with SPA (successive projections algorithm) after preprocessing. Among the SSpe- and NSpe-based models, the RF (random forest) models had higher estimation accuracy than the PLSR (partial least squares regression) and BPNN (backpropagation neural network) models. Specifically, the RF models had a PGE-CFPs estimation accuracy of 0.597–0.712, 0.640–0.715, and 0.377–0.461 under nitrogen stress (NS), salt stress (SS), and NS*SS, respectively. After fusing NSpe and SSpe, the accuracy in estimating PGE-CFPs of forage rape under NS, SS, and NS*SS were 0.729–0.755, 0.667–0.768, and 0.621–0.689, respectively. Then, the constructed models were further validated using field data, and the accuracy obtained was in the range of 0.585–0.711. Therefore, the feature fusion modeling method proposed has strong transferability and applicability. This research will offer a technical reference for crop photosynthesis monitoring at the early stage of environmental stresses.
Keywords: Hyperspectral technology, Feature fusion, Combined stresses, photosynthetic systems, continuous wavelet transform
Received: 18 Dec 2024; Accepted: 11 Mar 2025.
Copyright: © 2025 Wang, Wang, Lv, Cui, Shi, Song, Li and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Haijiang Wang, College of Agriculture, Shihezi University, Shihezi, China
Xin Lv, College of Agriculture, Shihezi University, Shihezi, China
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