Prediction of Nutritional Compositions of Korla Pear Flesh Based on Rheological Properties
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Abstract:
To achieve efficient and accurate detection of various nutritional composition indexes of Korla pear flesh, creep-recovery and stress relaxation tests were performed on pear flesh with using a TA-XT plus Texture Analyzer. Rheological models which were the fittest for describing Korla pear flesh’s creep-recovery and stress relaxation properties were determined, and the rheological parameters of Korla pear flesh were obtained with the models. Then, the correlations between the rheological parameters and soluble solid content (SSC), titratable acidity (TA), solid acid ratio (RTT) of pear flesh were analyzed, and the three nutritional composition indexes were predicted through stepwise multi-linear regression analyses. The results showed that creep-recovery and stress relaxation properties of Korla pear flesh can be best characterized by a generalized Kelvin-Voigt model with six elements and a generalized Maxwell model with five elements respectively, and the coefficients of determination R2 were higher than 0.95. Partial rheological parameters of the two models were significantly correlated with the SSC, TA and RTT (p<0.05), hence, the constructed stepwise multi-linear regression models could also effectively predict the three nutritional composition indexes. The correlation coefficient r of the prediction models were higher than 0.7, and there was no significant difference between the measured values and the predicted values. The RMSE values of the models for predicating the three nutritional compositions based on creep parameters were smaller than those of the models based on stress-relaxation parameters. Therefore, the models constructed on the basis of creep parameters were more stable and reliable for predicting nutritional compositions of Korla pear flesh.
