Establishing a maturity prediction model for respiratory fruits via ethylene-regulated physiology: A case investigation of avocado

Abstract

In addressing the severe waste issue in the Chinese avocado market due to uncontrollable storage temperatures and quality deterioration, this study investigated avocados under three distinct temperature conditions (20, 12, and 4 °C, with 80% ± 5% relative humidity), analyzing fruit respiration rate, ethylene release rate, peel color, flesh hardness, rheological properties, and sensory quality to explore the intrinsic changes during the ripening process. The study revealed significant differences in ripening rates among the different storage temperatures, albeit with relatively consistent physicochemical changes. Among the temperatures investigated, 12 °C was found to be the most suitable condition, effectively delaying fruit ripening, extending the shelf life, and yielding similar sensory quality to that of room temperature ripening. Subsequently, a ripeness prediction model based on respiratory and ethylene data changes was developed using LASSO regression analysis, achieving accuracy rates of 87%, 72%, and 91% at 20, 12, and 4 °C, respectively. This model demonstrates a high degree of fitting and can be used to predict the ripening stage of avocados. The study sets a direction for future data-driven strategies to optimize storage of climacteric fruits, contributing to reducing carbon emissions in the food cold chain and food waste.