Dynamic Prediction of Preharvest Strawberry Quality Traits as a Function of Environmental Factors

Abstract

Fruit quality is of increasing importance for consumers but is a complex trait for growers, as it is affected by environment, genotype, and crop management interactions. Decision support tools, such as computer models that simulate crop growth and development can help optimize production but require further improvement to simulate quality aspects. The goal of this study was to apply the newly developed CROPGRO-Strawberry model in the Decision Support System for Agrotechnology Transfer (DSSAT) model framework and develop a module for the dynamic prediction of quality traits for strawberry. Experimental data from Florida with quality measurements from multiple harvests were correlated with indices based on preharvest weather conditions (temperature, radiation, rainfall) and simulated model parameters (evapotranspiration) during fruit development. Two quality relationships based on linear equations were identified and integrated into the model to simulate strawberry fruit soluble solids content (r2 = 0.89, d = 0.97) and titratable acidity (r2 = 0.55, d = 0.85) based on preharvest temperature. A strategic analysis with historical weather data for a subtropical growing region over a 10-year period showed the importance of seasonal climate variability for simulated strawberry yield and fruit quality across different harvest months. The improved CROPGRO-Strawberry model is the first process-based crop model to predict selected quality traits across multiple harvests throughout the season and can be extended to other crop models for which quality traits are important.