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...

Full description

Bibliographic Details
Main Authors: Manuel Díaz-Pérez, Ángel Carreño-Ortega, Marta Gómez-Galán, Ángel-Jesús Callejón-Ferre
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Agronomy
Subjects:
Online Access:http://www.mdpi.com/2073-4395/8/9/176
id doaj-d07c7e27e0044d86bf2e2854224d770a
record_format Article
spelling 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
work_keys_str_mv AT manueldiazperez marketabilityprobabilitystudyofcherrytomatocultivarsbasedonlogisticregressionmodels
AT angelcarrenoortega marketabilityprobabilitystudyofcherrytomatocultivarsbasedonlogisticregressionmodels
AT martagomezgalan marketabilityprobabilitystudyofcherrytomatocultivarsbasedonlogisticregressionmodels
AT angeljesuscallejonferre marketabilityprobabilitystudyofcherrytomatocultivarsbasedonlogisticregressionmodels
_version_ 1721553279855362048