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Discrimination of climacteric and non‐climacteric melon fruit at harvest or at the senescence stage by quality traits
Author(s) -
ObandoUlloa Javier M,
Jowkar MohammadMahdi,
Moreno Eduard,
Souri M Kazem,
Martínez Juan A,
Bueso María C,
Monforte Antonio J,
FernándezTrujillo J Pablo
Publication year - 2009
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.3651
Subject(s) - climacteric , postharvest , biology , horticulture , melon , principal component analysis , ripening , botany , mathematics , statistics , genetics , menopause
BACKGROUND: This paper characterizes the quality traits at harvest and the changes associated with fruit senescence based on fruit physiological behaviour (climacteric or non‐climacteric) found in a collection of near‐isogenic lines (NILs) of melon ( Cucumis melo L.). Data from both stages of postharvest development were analyzed by univariate and multivariate statistical analysis. RESULTS: The principal components and random forest analyses of the fruit quality traits allowed the best classification of the NILs by time (harvest, senescence), or by climacteric behaviour at harvest, but not at the senescent stage. The overall quality profile of the non‐climacteric senescent melons was, in general, very different from that of the climacteric ones, and was in accord with a longer storage life. Most of the taste quality traits (individual sugars or sucrose equivalents, titratable acidity and the citric, oxalacetic, glutamic and succinic acids) and the traits related to skin, flesh and juice colour parameters (chroma, hue angle) helped to distinguish the climacteric NILs from the non‐climacteric ones independently of the time considered. CONCLUSIONS: The time had a stronger effect on quality than the physiological behaviour. The discrimination by climacteric or non‐climacteric behaviour was usually better at harvest than at the senescent stage irrespective of the methodology used. Principal component analysis was the best multivariate method to discriminate by time and physiological behaviour followed by random forest and linear discriminant analysis. Copyright © 2009 Society of Chemical Industry