Agronomic crops have their yield potential assessed once per growing season at harvest time. In contrast, horticultural crops such as blueberries (Vaccinium spp.) require prolonged harvest periods, spanning 6 to 8 weeks of recurrent mechanical- or hand-picking. Collected data throughout the harvest period offer a comprehensive source of information to estimate production curves (cumulative harvest). These capture the yield dynamics of each cultivar under specific environmental conditions and treatments. For blueberry growers in Florida, desirable production curves should exhibit: 1) accumulation at the beginning of the harvest season (earliness), and 2) reduced harvest periods (concentration). This pattern is advantageous as it could significantly enhance productivity and profitability while simultaneously cutting down labor costs linked to harvest operations. Thus, pinpointing cultivars displaying these beneficial traits is paramount. In this study, we considered the Weibull distribution to model the production curves for each genotype-in-environment combination. Phenotypic and genomic information were combined for model calibration to predict the corresponding parameters of the distribution besides yield performance in a multi-trait framework. To our knowledge, there are no methods in the current literature that address the identification of cultivars that both ripen early and/or are suited for concentrated harvesting. In this study, we employ a novel analytical approach designed to fill this gap, aiming to systematically identify cultivars aligning with these ideal production characteristics.
