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首页> 外文期刊>Acta Horticulturae >Modeling the softening behavior of Chilean 'Hass' avocado to commercially segregate different batches destined for local and distant markets
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Modeling the softening behavior of Chilean 'Hass' avocado to commercially segregate different batches destined for local and distant markets

机译:Modeling the softening behavior of Chilean 'Hass' avocado to commercially segregate different batches destined for local and distant markets

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摘要

Loss of firmness is the most characteristic attribute of 'Hass' avocado ripening process being the result of the coordinated activity of various cell wall modification enzymes. This process is affected by various factors before and after the harvest, which translates into great variability in the postharvest ripening behavior, impacting on fruit quality. The objective of this study was to model the softening of Chilean 'Hass' avocado, destined for local and distant markets, based on biological variation associated with location of cultivation and the harvest seasons. A total of 24 fruit batches were obtained during the 2018-2019 season from different Chilean agro-climatic zones (coast, intermediate and interior) and two harvest stages (according to dry matter content). Fruit softening during air or controlled atmosphere (CA) storage at 5°C followed by shelf life at 20°C was modeled using a simplified mechanistic model. Most of the model parameters for fruit were treated as generic, except for F_0 (firmness at harvest) and E_0 (amount of enzyme complex at harvest). The model was able to describe 87.6 of the observed variation at the batch level and 93.5 of the observed variation at the individual fruit level. It was shown that the firmness of the fruit measured at harvest, by itself, was not able to discriminate between the different batches since all the agroclimatic zones showed similar normal distributions. Monte Carlo simulations revealed that storage temperature is critical in maintaining firmness, having more effect than CA on softening. The segregation of the fruit based on the physiological age (E_0) evaluated by Monte Carlo simulations revealed not only reduction of the ripening heterogeneity but higher storage potential for "premium fruit".

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