ArticleFrontiers in plant science2026
Using Biomod2 and spatial quality modeling for comprehensive production zoning of
Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Methods: This study constructed a comprehensive production zoning system by integrating ecological suitability modeling and spatial quality prediction. We utilized the Biomod2 platform to predict the distribution of ecological suitability and identify environmental factors affecting growth. Subsequently, a Principal Component Analysis - Multiple Linear Regression - Spatial Prediction framework was applied to evaluate spatial quality. Results: (1) The ensemble model constructed using the biomod2 platform (TSS = 0.851, AUC = 0.980) was employed to evaluate ecological suitability. The results indicated that the ecological suitability was higher in northern regions than in southern regions, with precipitation (Bio13, Bio17) and temperature (Bio6, Bio3, Bio2) were identified as the major driving factors. (2) Climatic factors (Bio15, Bio17) and soil factor (tp05) significantly affected saikosaponin content, while topographic factors exerted only a weak influence. Based on a regression model constructed via PCA-MLR-PC (R Discussion: The comprehensive framework that integrated both ecology and quality, representing the synergistic advantage between ecological suitability and medicinal quality. These findings distinguished different grades of production zones, providing a reference for prioritizing the development of high production zones and implementing differentiated cultivation strategies across various production zones.
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