Predicting the moisture content and textural characteristics of roasted pistachio kernels using Vis/NIR reflectance spectroscopy and PLSR analysis

The objective of this study is to develop calibration models in order to predict the moisture content and textural characteristics (including fracture force, hardness, apparent modulus of elasticity, and compressive energy) of pistachio kernels roasted at different temperatures (90, 120 and 150 °C), times (20, 35 and 50 min), and air velocities (0.5, 1.5 and 2.5 m/s) by using visible/near infrared spectroscopy and PLSR. The effects of different pre-processing methods and spectra treatments such as normalization, multiplicative scatter correction (MSC), standard normal variate transformation, median filter, Savitzky–Golay, wavelet, and differentiation (first derivative (D1) and second derivative (D2)) were analyzed. High correlation between Vis/NIR measurements with fracture force and apparent modulus of elasticity were obtained with the combination of SNV, wavelet, and D1. NIR measurements correlated well with hardness and compressive energy. Meanwhile, moisture content had correlation with SNV, median filter, D1; SNV, Savitzky–Golay, D1 and MSC, median filter, D1 respectively.

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