Abstract:

Soluble solids content, dry matter, peel color and firmness of cherry ‘Rainier’, ‘Brooks’, ‘Regina’, ‘Tieton’ were measured with no damage by near-infrared spectroscopy (NIR) in the experiment. Predictive NIR regression model was developed to measure four quality indicators using the ‘Rainier’ cherry fruit from beginning of coloration to fully maturity. The result showed that the coefficients of determination (R²) of soluble solids content, dry matter, peel color and firmness were 0.87, 0.97, 0.77 and 0.76, respectively. The closer the model linearity (R²) of the model gets to 1, the better the fitting effect and the higher the fitting degree of the model. The R² values were all greater than 0.7, indicating that the model could achieve the performance expectations. The accuracy of the soluble solids model and dry matter model was higher than that of models of peel color and firmness. The soluble solid and dry matter gradually increased, skin color gradually deepened and hardness gradually decreased during the ripening of cherry fruit. The model established in this study can be applied in predicting four quality indexes for other cultivars, providing the intuitive reference for exploring changes on endogenous substances in the fruit ripening stage.

Key words: cherry, spectroscopy, model building, prediction, fruit quality