Enfoque estadístico para evaluar la heterogeneidad de paltas Hass, sometidas a diferentes estreses abióticos en postcosecha

Translated title of the contribution: A statistical approach for assessing the heterogeneity of Hass avocados subjected to different postharvest abiotic stresses

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Abstract

Hass avocado (Persea americana Mill.) is marketed worldwide. Due to its complex physiology, a wide variability in postharvest ripening can be observed, i.e., heterogeneity in the number of days to reach edible ripeness. There is a need for a simple and objective method for evaluating the efficacy of postharvest treatments in the reduction of this postharvest ripening heterogeneity given the high demand of import countries for consistent quality and product homogeneity. Therefore, the aim of this study was to compare the appropriateness of different statistical methods used to evaluate this ripening heterogeneity. Bartlett’s, Cochran’s, Levene’s homogeneity of variance tests were applied to different treatments. In addition, a multiple comparisons test of squared residuals (parametric and non-parametric) was applied. The classical statistical approaches (Bartlett’s, Cochran’s and Levene’s tests) showed similar results as the multiple comparisons test of squared residuals only when one treatment and large sample sizes (n=100) were evaluated. All statistical methods were able to detect significant differences in ripening heterogeneity from growers and storage conditions. The multiple comparisons test of squared residuals was the most suitable method for multifactorial experiments and small sample sizes (n=30) compared to the classical approaches, which increased the probability of obtaining false positives or a type I error.

Translated title of the contributionA statistical approach for assessing the heterogeneity of Hass avocados subjected to different postharvest abiotic stresses
Original languageSpanish
Pages (from-to)356-365
Number of pages10
JournalCiencia e Investigacion Agraria
Volume43
Issue number3
DOIs
StatePublished - 1 Jan 2016

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