‘Honeycrisp’ is a popular apple cultivar, but it is susceptible to several postharvest disorders, including bitter pit (Al Shoffe et al., 2016; DeEll et al., 2016; Watkins et al., 2004). Several studies showed that bitter pit development is likely due to an imbalance of K, Mg, P, Ca, and N in the fruit (Cheng, 2016; Ferguson, 2001; Ferguson and Watkins, 1989). The severity of bitter pit varies considerably among years, orchards, and trees within orchards. During some years, 100% of the fruit on a tree may develop bitter pit after storage; often, more than 30% of the fruit develop bitter pit (Baugher et al., 2017). To avoid storing, packing, and shipping fruit that is likely to develop bitter pit, apple producers must be able to identify blocks of trees with high potential for bitter pit so they can sell the fruit immediately. We recently reported a bitter pit prediction model for ‘Honeycrisp’ based on the average shoot length (SL) and ratio of N to Ca in the peel of apples sampled 3 weeks before commercial harvest from individual trees with varying crop densities at six commercial orchards in Adams County, PA, over 3 years (Baugher et al., 2017). The model was validated using three different statistical methods that provided supporting evidence that the selected model included the most important variables that were evaluated. However, the model tended to underpredict bitter pit for trees with higher levels of observed bitter pit. The objective of this study was to obtain ‘Honeycrisp’ apples from blocks of trees, rather than individual trees, in a larger geographical region to verify the model.
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