Reflectance Vis/NIR spectroscopy for nondestructive taste characterization of Valencia oranges

The feasibility of reflectance Vis/NIR spectroscopy was investigated for taste characterization of Valencia oranges based on taste attributes including soluble solids content (SSC) and titratable acidity (TA), as well as taste indices including SSC to TA ratio (SSC/TA) and BrimA. The robustness of multivariate analysis in terms of prediction was also assessed. Several combinations of various preprocessing techniques with moving average and Savitzky–Golay smoothing filters, standard normal variate (SNV) and multiplicative scatter correction (MSC) were used before calibration and the models were developed based on both partial least squares (PLS) and principle component regression (PCR) methods. The best models obtained with PLS method had root mean square errors of prediction (RMSEP) of 0.33 °Brix, 0.07%, 1.03 and 0.37, and prediction correlation coefficients (rp) of 0.96, 0.86, 0.87 and 0.92 for SSC, TA, SSC/TA, and BrimA, respectively. It was concluded that Vis/NIR spectroscopy combined with chemometrics could be an accurate and fast method for nondestructive prediction of taste attributes and indices of Valencia oranges. Moreover, the application of this technique was suggested for taste characterization, directly based on BrimA which is the best index related to fruit flavor rather than determination of SSC or TA alone.

► Feasibility of using Vis/NIRS for taste characterization of oranges was investigated.
► Different chemometrics to predict taste attributes and indices were assessed.
► The developed models have the potential to estimate taste characteristics.
► Vis/NIRS is capable of predicting BrimA index directly and nondestructively.
► Preprocessing methods have a pronounced influence on the prediction results.