Sub-regional identification of peanuts from Shandong Province of China based on Fourier transform infrared (FT-IR) spectroscopy

ABSTRACT The objective of this study was to select infrared spectra closely related to sub-region and less influenced by variety to distinguish the sub-regions of peanuts combined with chemometrics. Based on field experiments in Shandong Province of China, a total of 90 peanut samples of 10 different varieties from three different cities were measured by Fourier transform infrared (FT-IR) spectroscopy. And the obtained spectra data were analyzed by principal component analysis (PCA), multi-way analysis of variance (ANOVA), stepwise linear discriminant analysis (SLDA), k-nearest neighbor (k-NN), and support vector machines (SVM). PCA showed the gathering trends for samples from three different cities. The results of multi-way ANOVA showed that sub-region, variety, and their interaction influenced infrared spectra of peanut significantly, and the wavenumbers 2923 cm-1, 2851 cm-1, 1742 cm-1, 1162 cm-1, and 1051 cm-1 were mainly associated with the sub-region and less affected by variety. The recognition rates of peanut samples from different sub-regions achieved 94.2%, 82.6%, and 76.8% for training sets and 85.7%, 76.2%, and 71.4% for validation sets by SLDA, k-NN, and SVM, respectively. It could be concluded that it was feasible to identify the sub-regions of peanut by infrared spectra closely related to sub-region and less influenced by variety combined with SLDA.