A simple empirical growing degree day model for predicting winter cover crop biomass in sandy soils

Abstract The ecosystem services provided by cover crops (CCs) are related to their biomass production. The objective of this study was to develop a simple empirical model to enable farmers to predict CC biomass yields based on planting and termination timing, thereby improving the assessment of CC benefits. A field experiment was conducted over 3 years on sandy soils using two common winter CCs, cereal rye ( Secale cereale ) and hairy vetch ( Vicia villosa ), grown as monocultures and in mixture following local management guidelines. Aboveground biomass was collected periodically from establishment to termination during each growing season, and cumulative growing degree days (GDDs) were calculated. A quadratic model was developed using GDD as the independent variable and the natural logarithm of biomass yield as the dependent variable. Model's performance was significant across all treatments, with coefficients of determination ( R 2 ) ranging from 0.59 to 0.74. The models were further validated with data from adjacent fields under similar management, showing strong agreement between predicted and observed values for cereal rye ( R 2 = 0.82) and hairy vetch ( R 2 = 0.87). The validated model was then used to simulate CC production under 15 growth duration scenarios. Results suggest that the model is a reliable and practical tool for optimizing CC management to achieve desired agronomic and environmental outcomes. However, model performance is constrained by limited data inputs and could be improved with additional observations across a broader range of climatic conditions.