LAUSR

Abstract Mango physicochemical quality can potentially affect fruit cooling time. In that case, an efficient cooling time should take into account fruit quality parameters. The objective of this study was to develop models that can be used to predict ‘Tommy Atkins’ mango cooling time based on fruit physicochemical quality. The prediction models were developed using 150 fruit harvested at maturity stages ranging from 2 to 4. Two thermocouples were fixed in each fruit, one immediately below the epidermis and the other close to the endocarp. From the total number of fruit, 83 were subjected to hydrothermal treatment and 67 were maintained at room temperature (25 °C). The hydrothermal treatment was applied by keeping the mangoes in water bath at 46 °C for 75 min. This treatment is commercially used as a phytosanitary method for mangoes exported to North America and Asian countries. After hydrothermal treatment, treated and non-treated fruit were kept in a cold room to determine the cooling time of the flesh immediately below the epidermis and close to the endocarp, until reaching 12 °C. After reaching storage temperature, each fruit was evaluated for physicochemical characteristics, which were used to obtain the cooling time prediction models. Quality attributes presenting the highest to the lowest influence on fruit cooling time were fruit weight, flesh and skin color (Chroma, Hue angle and Lightness), soluble solids, dry matter, fruit diameter, fruit length, flesh thickness and seed thickness. Cooling time prediction models were generated with these variables by multiple linear regression (MLR) and exhibited high prediction accuracy for fruit without hydrothermal treatment (R²SEC = 88% RMSEC 42.1% R²SEP = 85.5% RMSEP = 52.2%) and with hydrothermal treatment (R²SEC = 72.2% RMSEC 42.4% R²SEP = 73.6% RMSEP = 47.2%). According to the results, the models developed based on physicochemical parameters can predict with relatively high accuracy the cooling time of ‘Tommy Atkins’ mangoes. These models can be used in the mango industry to determine the most effective cooling time required to maintain fruit quality.