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ARS Home » Southeast Area » Fort Pierce, Florida » U.S. Horticultural Research Laboratory » Citrus and Other Subtropical Products Research » Research » Publications at this Location » Publication #390788
Research Project: Determination of Flavor and Healthful Benefits of Florida-Grown Fruits and Vegetables and Development of Postharvest Treatments to Optimize Shelf Life an Quality for Their Fresh and Processed Products

Location: Citrus and Other Subtropical Products Research

Title: Dynamic prediction of preharvest strawberry quality traits as a function of environmental factors

Author
item HOPF, ALWIN - University Of Florida
item BOOTE, KENNETH - University Of Florida
item Plotto, Anne
item ASSENG, SENTHOLD - University Of Florida
item ZHAO, XIN - University Of Florida
item SHELIA, VAKHTANG - University Of Florida
item HOOGENBOOM, GERRIT - University Of Florida

Submitted to: HortScience
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/18/2022
Publication Date: 9/26/2022
Citation: Hopf, A., Boote, K.J., Plotto, A., Asseng, S., Zhao, X., Shelia, V., Hoogenboom, G. 2022. Dynamic prediction of pre-harvest strawberry quality traits as a function of environmental factors. HortScience. 57/1336-1355. https://doi.org/10.21273/HORTSCI16655-22.
DOI: https://doi.org/10.21273/HORTSCI16655-22

Interpretive Summary: Being able to predict crop quality before harvest can give growers a competitive edge by providing them a tool to choose their market and negotiate prices. In this study, a new crop modeling software was adapted to Florida-grown strawberries. Weather data were correlated with ten years of yield and fruit quality data, including soluble solids content (an indicator of sweetness in strawberries), titratable acidity (sourness) and firmness. This strategic analysis with historical weather data for a subtropical growing region over a 10-year period showed the importance of seasonal climate variability for total strawberry yield, and variation in distribution of fruit production and quality across different harvest months. The prediction model can also be extended to other crop models for which quality traits are important.

Technical Abstract: Strawberry is a high-value horticultural crop with a global market while it also has a strong regional importance in production areas such as Florida. Fruit quality is of increasing importance for consumers but is a complex trait for growers as it is affected by the interactions among environment, genotype, and crop management. Decision support tools, such as dynamic crop simulation models can help optimize strawberry production but require further improvement to predict quality. The goal of this study was to apply the newly developed CROPGRO-Strawberry model in Decision Support System for Agrotechnology Transfer (DSSAT) and develop a module for the dynamic prediction of quality traits for strawberry. Experimental data with quality measurements from multiple harvests were correlated with pre-harvest weather conditions and simulated model parameters during the duration of fruit growth. Two suitable quality relationships based on linear equations were identified and integrated into the model to predict soluble solids content (r2=0.89, d=0.97) and acidity (r2=0.55, d=0.85) based on the pre-harvest 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 total strawberry yield, and variation in distribution of fruit production and quality across different harvest months. This improved CROPGRO-Strawberry model is the first dynamic crop model to predict quality traits across multiple harvests throughout the season and can also be extended to other crop models for which quality traits are important.