Modeling Mathematical Relationship with Weight Loss and Texture on Table Grapes of ‘Red Globe’ and ‘Wink’ during Cold and Ambient Temperature Storage

Abstract

Weight loss associated with fruit texture during storage has received numerous reports; however, no research has been conducted on the mathematical relationships between weight loss and textural traits of table grapes stored at cold and ambient temperatures. In this study, it was found that the weight loss of ‘Red Globe’ was in the range of 0 to 0.0487, 0 to 0.0284 and 0 to 0.0199 compared to 0 to 0.0661, 0 to 0.0301 and 0 to 0.028 of ‘Wink’ at 13 °C, 3 °C, and 0 °C of storage for 13 days. Stored for 13 days at 13 °C, 3 °C, and 0 °C, the range of the textural traits of failure force, strain and penetration work in ‘Red Globe’ were 6.274 to 3.765, 6.441 to 3.867, 6.321 to 4.014; 51.931 to 11.114, 51.876 to 13.002, 51.576 to 20.892; 21.524 to 13.225, 21.432 to 14.234, 21.321 to 15.198 in contrast to in ‘Wink’ of 4.4202 to 2.2292, 4.4197 to 2.653, 4.4371 to 2.8199 and 15.674 to 2.7881, 15.776 to 4.1431, 15.704 to 5.702 and 12.922 to 7.754, 12.909 to 8.021, 12.915 to 8.407. Meanwhile, the weight loss and textural traits of two table grapes were examined using time-dependent and weight loss-dependent modeling at 13 °C, 3 °C, and 0 °C of storage. The Logistic, ExpDec1, and ExpDec2 models, as well as the Boltzmann model, were identified as the best fit for the obtained data. The equations proved to be more effective in characterizing the change in weight loss and texture of ‘Red Globe’ and ‘Wink,’ with the best equations suited to the weight loss and textural parameters having an average mean standard error of 2.89%. The viability of the established models was evaluated, and parametric confidence intervals of the equations were proposed to fit different grape cultivars. According to the findings, the weight loss and texture of the two grape cultivars could be accurately predicted by the established models; additionally, the results showed that cold storage is better for the quality of table grapes and that weight loss can predict the textural quality of table grapes. This study provides a theoretical framework for optimum storage temperature together with a significantly convenient and quick approach to measure the texture of grapes for fruit dealers and enterprises.