TY - JOUR
T1 - Verification and modification of a model to predict bitter pit for 'Honeycrisp' apples
AU - Marini, Richard P.
AU - Baugher, Tara Auxt
AU - Muehlbauer, Megan
AU - Sherif, Sherif
AU - Crassweller, Robert Michael
AU - Schupp, James R.
N1 - Funding Information:
Received for publication 10 July 2020. Accepted for publication 9 Aug. 2020. Published online 22 October 2020. This work is supported by the U.S. Department of Agriculture National Institute of Food and Agriculture and Hatch Appropriations under Project no. 4625 and Accession no. 1006805, and the Pennsylvania Department of Agriculture Research Program. We acknowledge the valuable contributions of Dan and Mark Boyer, Bennett Saunders, and Ben Keim (grower cooperators). R.P.M. is the corresponding author. E-mail: rpm12@psu.edu. This is an open access article distributed under the CC BY-NC-ND license (https://creativecommons. org/licenses/by-nc-nd/4.0/).
PY - 2020/12
Y1 - 2020/12
N2 - '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.
AB - '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.
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U2 - 10.21273/HORTSCI15301-20
DO - 10.21273/HORTSCI15301-20
M3 - Article
AN - SCOPUS:85097230405
VL - 55
SP - 1882
EP - 1887
JO - Hortscience: A Publication of the American Society for Hortcultural Science
JF - Hortscience: A Publication of the American Society for Hortcultural Science
SN - 0018-5345
IS - 12
ER -