Verification and modification of a model to predict bitter pit for 'Honeycrisp' apples

Richard P. Marini, Tara Auxt Baugher, Megan Muehlbauer, Sherif Sherif, Robert Crassweller, James R. Schupp

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


'Honeycrisp' (Malus 3domestica) apples were harvested from a total of 17 mid-Atlantic orchards during 2018 and 2019 to verify a previously published bitter pit prediction model. As in the previous study, bitter pit incidence was associated with low calcium (Ca) levels and high ratios of nitrogen (N), potassium (K), and/or magnesium (Mg) to Ca in the fruit peel and excessive terminal shoot growth. The best two-variable model for predicting bitter pit developed with the 2018-19 data set contained boron (B) and the ratio of Mg to Ca (R2 = 0.83), which is different from previous models developed with data from three individual years (2015-17). When used to predict the bitter pit incidence of the 2018-19 data, our previous best model containing the average shoot length (SL) and the ratio of N to Ca underestimated the incidence of bitter pit. The model is probably biased because one or more important variables related to bitter pit have not yet been identified. However, the model is accurate enough to identify orchards with a low incidence of bitter pit.

Original languageEnglish (US)
Pages (from-to)1882-1887
Number of pages6
Issue number12
StatePublished - Dec 2020

All Science Journal Classification (ASJC) codes

  • Horticulture


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