Akademik Veri Yönetim Sistemi
EUROPEAN FOOD RESEARCH AND TECHNOLOGY, cilt.242, sa.2, ss.271-277, 2016 (SCI-Expanded)
A rapid and nondestructive method for determination of green pea adulteration in pistachio nut granules was demonstrated using Raman hyperspectral imaging combined with principal component analysis and partial least squares regression (PLSR). Pistachio nut granule samples were adulterated with green pea granules at different concentrations ranging from 20 to 80 % (w/w). Hyperspectral Raman images were acquired in the wavenumber range of 200-3700 cm(-1) by using a 1064-nm laser. PLSR model was developed for predicting the content of the green pea adulteration in pistachio nut granules. Based on the whole spectral data, good prediction model was obtained with a coefficient of determination (R (2)) value of 0.99 and root-mean-square error of prediction value of 0.048. The results showed that hyperspectral imaging is beneficial for determining the adulteration of pistachio nuts with a time-saving and nondestructive method, which is important to confirm food quality and safety.