Prediction of texture on two cultivars’ table grapes based on weight loss during ambient storage

Abstract

Texture is an important indicator to evaluate the quality of table grapes. However, there is no convenient and fast method to estimate the texture on grapes. Hence, this study evaluated the texture of two table grapes (cvs. Red Globe and Wink) through weight loss-dependent modeling under ambient storage. The weight loss and textural properties of the Polynomial, Boltzmann, and ExpDec2 models were found to better fit the obtained data. The equations were proved to be more efficient in describing the change in weight loss and texture of 'Red Globe' and 'Wink', with the best equations fitted to the weight loss and textural parameters having an average mean standard error of 3.78%. The feasibility of the established models was evaluated, and parametric confidence intervals of the equations were proposed to fit the different varieties of grapes. According to our findings, the textural quality of table grapes can be predicted by weight loss. The results may offer a critically convenient and fast method to estimate the texture on grapes for industry.