Rheological property for nutrients prediction of Korla pear

Abstract

Abstract This study aimed to investigate the feasibility of predicting nutrients of Korla pear using stress relaxation and creep parameters. Creep-recovery test and stress relaxation test were performed on the pear using a TA-XT plus Texture Analyzer. Creep and stress relaxation properties of pear were characterized by a generalized Kelvin-Voigt model (six elements) and Maxwell model (seven elements), with coefficients of determination R2 of 0.992 and 0.998, respectively. The partial rheological parameters of the two models were significantly correlated with total soluble solid (TSS), titratable acidity (TA) and solid acid ratio (RTT) of pear(p < 0.05). Hence, the constructed stepwise multiple linear regression models can effectively predict three nutrients (correlation coefficient r of prediction model > 0.7). The RMSE value of each nutrients prediction model based on the creep parameters was smaller than that of the prediction models based on the stress relaxation parameters. Therefore, the models constructed using creep parameters are more stable and reliable for predicting the nutrients of Korla pear.