Development of new fruit quality indices through aggregation of fruit quality parameters and their predictions using near-infrared spectroscopy

This study introduces a flexible approach to aggregate several quality-related parameters to provide new fruit quality indices (FQIs) with the aim of evaluating the overall quality of fruits. The calculations were based on the aggregation of selected fruit quality parameters, such as total soluble solids (TSS), titratable acidity (TA), pH, firmness, dry matter (DM), and lipid content. The fruit quality index 1 (FQI1) and fruit quality index 2 (FQI2) were calculated, respectively, as geometric and weighted arithmetic means of the scaled fruit quality parameters. Both calculations resulted in numerical scores corresponding to a quality rank ranging from 0 to 100. For rapid and non-destructive detection, near-infrared (NIR) spectra were calibrated for predictions of the developed indices using partial least squares (PLS). The predictive performance was evaluated based on several metrics, including root mean square errors of calibration (RMSEC) and prediction (RMSEP), coefficients of determination for calibration (R2) and prediction (Q2), the ratio of RMSEP and RMSEC (RP/C) and the ratio of prediction to deviation (RPD). Mango, tangerine, and avocado were used in the demonstration. The FQI evaluations offer flexibility in the number of aggregate parameters, making them applicable to various types of fruits. With the NIR detection, the developed indices resulted in a significant reduction in the measurements of quality-related parameters but still provided the overall quality of the fruit samples.