Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression Models
The purpose of this study was to demonstrate interest in applying simple and multiple logistic regression analyses to the marketability probability of commercial tomato (Solanum lycopersicum L.) cultivars when the tomatoes are harvested as loose fruit. A fruit’s firmness and commercial quality (soft...
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doaj-d07c7e27e0044d86bf2e2854224d770a2021-04-02T17:49:14ZengMDPI AGAgronomy2073-43952018-09-018917610.3390/agronomy8090176agronomy8090176Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression ModelsManuel Díaz-Pérez0Ángel Carreño-Ortega1Marta Gómez-Galán2Ángel-Jesús Callejón-Ferre3Department of Engineering, University of Almería, Agrifood Campus of International Excellence (CeiA3), 04120 La Cañada de San Urbano, Almería, SpainDepartment of Engineering, University of Almería, Agrifood Campus of International Excellence (CeiA3), 04120 La Cañada de San Urbano, Almería, SpainDepartment of Engineering, University of Almería, Agrifood Campus of International Excellence (CeiA3), 04120 La Cañada de San Urbano, Almería, SpainDepartment of Engineering, University of Almería, Agrifood Campus of International Excellence (CeiA3), 04120 La Cañada de San Urbano, Almería, SpainThe purpose of this study was to demonstrate interest in applying simple and multiple logistic regression analyses to the marketability probability of commercial tomato (Solanum lycopersicum L.) cultivars when the tomatoes are harvested as loose fruit. A fruit’s firmness and commercial quality (softening or over-ripe fruit, cracking, cold damage, and rotting) were determined at 0, 7, 14, and 21 days of storage. The storage test simulated typical conditions from harvest to purchase-consumption by the consumer. The combined simple and multiple analyses of the primary continuous and categorical variables with the greatest influence on the commercial quality of postharvest fruit allowed for a more detailed understanding of the behavior of different tomato cultivars and identified the cultivars with greater marketability probability. The odds ratios allowed us to determine the increase or decrease in the marketability probability when we substituted one cultivar with a reference one. Thus, for example, the marketability probability was approximately 2.59 times greater for ‘Santyplum’ than for ‘Angelle’. Overall, of the studied cultivars, ‘Santyplum’, followed by ‘Dolchettini’, showed greater marketability probability than ‘Angelle’ and ‘Genio’. In conclusion, the logistic regression model is useful for studying and identifying tomato cultivars with good postharvest marketability characteristics.http://www.mdpi.com/2073-4395/8/9/176cherry tomatocultivarqualitydays of storagelogistic regressionprobability of marketability |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Manuel Díaz-Pérez Ángel Carreño-Ortega Marta Gómez-Galán Ángel-Jesús Callejón-Ferre |
spellingShingle |
Manuel Díaz-Pérez Ángel Carreño-Ortega Marta Gómez-Galán Ángel-Jesús Callejón-Ferre Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression Models Agronomy cherry tomato cultivar quality days of storage logistic regression probability of marketability |
author_facet |
Manuel Díaz-Pérez Ángel Carreño-Ortega Marta Gómez-Galán Ángel-Jesús Callejón-Ferre |
author_sort |
Manuel Díaz-Pérez |
title |
Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression Models |
title_short |
Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression Models |
title_full |
Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression Models |
title_fullStr |
Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression Models |
title_full_unstemmed |
Marketability Probability Study of Cherry Tomato Cultivars Based on Logistic Regression Models |
title_sort |
marketability probability study of cherry tomato cultivars based on logistic regression models |
publisher |
MDPI AG |
series |
Agronomy |
issn |
2073-4395 |
publishDate |
2018-09-01 |
description |
The purpose of this study was to demonstrate interest in applying simple and multiple logistic regression analyses to the marketability probability of commercial tomato (Solanum lycopersicum L.) cultivars when the tomatoes are harvested as loose fruit. A fruit’s firmness and commercial quality (softening or over-ripe fruit, cracking, cold damage, and rotting) were determined at 0, 7, 14, and 21 days of storage. The storage test simulated typical conditions from harvest to purchase-consumption by the consumer. The combined simple and multiple analyses of the primary continuous and categorical variables with the greatest influence on the commercial quality of postharvest fruit allowed for a more detailed understanding of the behavior of different tomato cultivars and identified the cultivars with greater marketability probability. The odds ratios allowed us to determine the increase or decrease in the marketability probability when we substituted one cultivar with a reference one. Thus, for example, the marketability probability was approximately 2.59 times greater for ‘Santyplum’ than for ‘Angelle’. Overall, of the studied cultivars, ‘Santyplum’, followed by ‘Dolchettini’, showed greater marketability probability than ‘Angelle’ and ‘Genio’. In conclusion, the logistic regression model is useful for studying and identifying tomato cultivars with good postharvest marketability characteristics. |
topic |
cherry tomato cultivar quality days of storage logistic regression probability of marketability |
url |
http://www.mdpi.com/2073-4395/8/9/176 |
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