Editorial: Integrative biophysical models to uncover fundamental processes in plant growth, development, and physiology

our knowledge of plant biology and improving agricultural practices. However, traditional wetlaboratory approaches often fail to capture the dynamic and integrative nature of these processes.The application of biophysical models provides a powerful framework for bridging gaps in understanding and knowledge and enables us to explore how physical and chemical forces, molecular mechanisms, and environmental factors interact to govern plant behavior. In fact, in the last years, biophysical modeling has become an increasingly important tool for deciphering fundamental processes in plants at various organizational levels. From the molecular dynamics of individual membrane proteins to water and substance transport throughout the entire organism, mathematical and physically based models enable a quantitative understanding of biological mechanisms.To highlight the broad applicability of such modeling approaches, we have compiled a collection of research and review articles on the topic of "integrative biophysical models" that address key questions in plant biology. A total of 13 articles by 74 authors from 10 different countries cover a broad spectrum of the topic. They address, for example, (i) a broad spectrum of modeling approaches for predicting plant growth and development, including the effects of thinning on growth and yield of forest trees, spatiotemporal water demand, variations in branch growth, wheat growth, fruit nutritional status, leaf phenotype, leaf vein patterns, and secondary metabolites; (ii) challenges in modeling the effects of abiotic stress factors, such as frost, heat stress and water flow stress, on plant development and yield, (iii) the use of models to mitigate the emission of greenhouse gases from agriculture, as well as (iii) the application of modeling in modern agricultural technology for food production, particularly smart irrigation management techniques.The article by Zhao et al. (2025b) Secondary metabolites in plants are crucial for survival, defense, signaling, and responses to environmental stresses (Jan et al., 2021). In their article, Devadze et al. (2025) successfully predicted the content of secondary metabolites using data-driven methods by integrating and analyzing time-series data from greenhouse measurements. The content of secondary metabolites in hydroponically grown greenhouse tomatoes was forecasted, taking into account all climatic changes as well as photosynthesis and transpiration rates throughout the entire growing season.They demonstrated that the optimal accumulation of individual phenolic compounds and carotenoids in tomatoes depends on environmental factors such as radiation, temperature, relative humidity, and CO2 concentration, as well as plant transpiration and photosynthesis during the growing season. Another objective was to achieve the maximum content of secondary metabolites in tomatoes in order to obtain an optimal amount of health-promoting phytochemicals for the benefit of human health. detect key points and extract skeletons according to plant morphology. Therefore, it can be effectively used for accurate phenotypic extraction in leafy plants with complex morphologies.In addition, we have a research article by Yu et al. (2025) on the total phosphorus content of the leaves. The nutrient status of the fruit depends mainly on the phosphorus content of the leaves (Bai et al., 2021). On this base, Yu et al. systematically predicted the total phosphorus content (LTP) of Korla fragrant pear leaves using near-infrared spectroscopy. This model prediction, based on the specificity of the growth stage, also significantly improved the accuracy and applicability of the model.Finally, we would like to draw attention to a review article by Dusfour-Castan et al. (2026) on wheat growth models that take into account physiological trade-offs between growth, defense, and reproduction, as well as hormonal signaling and gene regulatory networks. Such methods can improve and support experimental design for physiological questions such as plant growth and resistance.Increasing frost and heat stress due to the uncertainty of climate change are key limiting factors for plant growth and development and ultimately affect crop yield (Rezaei et al., 2023). The review article by Richetti et al. (2025) focuses on the effectiveness of yield simulation models for the yield of cool-season annual cereal crops. The authors argue that modeling approaches are inadequate due to six major challenges and that model predictions can be improved through the refined use of Climate change due to rising greenhouse gas emissions from Agriculture, Forestry, and Other Land-Use sectors (AFOLU) is one of the most significant global environmental challenges (Bumyut et al., 2026). Within the Research Topic, Kwak et al. (2025) Overall, this Research Topic brings together research and review articles from various perspectives that explore integrative modeling approaches aimed at understanding complex physiological, biochemical, anatomical, regulatory, and environmental stress responses using a variety of predictive tools.