ArticlePhotosynthesis research2025
PhoTorch: a robust and generalized biochemical photosynthesis model fitting package based on PyTorch.
Article in Photosynthesis research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Leaf gas exchange measurement for steady-state stomatal conductance model calibration.The New phytologist · 2026Article
- AI-driven multiscale virtual plant cell modeling: from molecular mechanisms to tissue functions.Planta · 2026Review
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Authors and funding
3 authors.
Funding
Abstract
Advancements in artificial intelligence (AI) have greatly benefited plant phenotyping and predictive modeling. However, unrealized opportunities exist in leveraging AI advancements in model parameter optimization for parameter fitting in complex biophysical models. This work developed novel software, PhoTorch, for fitting parameters of the Farquhar, von Caemmerer, and Berry (FvCB) biochemical photosynthesis model based on the parameter optimization components of the popular AI framework PyTorch. The primary novelty of the software lies in its computational efficiency, robustness of parameter estimation, and flexibility in handling different types of response curves and sub-model functional forms. PhoTorch can fit both steady-state and non-steady-state gas exchange data with high efficiency and accuracy. Its flexibility allows for optional fitting of temperature and light response parameters, and can simultaneously fit light response curves and standard
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