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Open AccessArticle

Application of Logistic Regression Models for the Marketability of Cucumber Cultivars

Department of Engineering, University of Almería, Agrifood Campus of International Excellence (CeiA3), La Cañada de San Urbano, 04120 Almería, Spain
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Agronomy 2019, 9(1), 17; https://doi.org/10.3390/agronomy9010017
Received: 15 November 2018 / Revised: 8 December 2018 / Accepted: 27 December 2018 / Published: 3 January 2019
The aim of this study is to establish a binary logistic regression method to evaluate and select cucumber cultivars (Cucumis sativus L.) with a longer postharvest shelf life. Each sample was evaluated for commercial quality (fruit aging, weight loss, wilting, yellowing, chilling injury, and rotting) every 7 days of storage. Simple and multiple binary logistic regression models were applied in which the dependent variable was the probability of marketability and the independent variables were the days of storage, cultivars, fruit weight loss, and months of evaluation. The results showed that cucumber cultivars with a longer shelf life can be selected by a simple and multiple binary logistic regression analysis. Storage time was the main determinant of fruit marketability. Fruit weight loss strongly influenced the probability of marketability. The logistic model allowed us to determine the cucumber weight loss percentage over which a fruit would be rejected in the market. View Full-Text
Keywords: cucumber; cultivar; quality; days of storage; logistic regression; probability of marketability cucumber; cultivar; quality; days of storage; logistic regression; probability of marketability
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MDPI and ACS Style

Díaz-Pérez, M.; Carreño-Ortega, Á.; Salinas-Andújar, J.-A.; Callejón-Ferre, Á.-J. Application of Logistic Regression Models for the Marketability of Cucumber Cultivars. Agronomy 2019, 9, 17.

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