Identification of the Geographic Origin of Peanut Kernels by Raman Spectroscopy Fingerprinting with Chemometrics

Abstract

This study aimed to investigate the feasibility of identifying the geographical origin of peanuts by combining Raman spectroscopy with chemometrics. A total of 161 peanut samples were collected from Jilin, Jiangsu, and Shandong provinces in China, and their Raman spectra were collected. One-way analysis of variance (ANOVA) was used to analyze the difference in characteristic Raman spectra of peanuts from these locations. Raman spectroscopy combined with principal component analysis (PCA), k-nearest neighbor (k-NN), stepwise linear discriminant analysis (SLDA), and support vector machines (SVM) were used to classify the peanuts by province and Jilin Province city. One-way ANOVA indicated that the peak intensities at 2900, 1660, 1440, 1077, and 848 cm⁻¹ had significant differences. The peaks at 2900, 1660, 1440, 1300, and 1077 cm⁻¹ had significant differences in the Jilin Province city. The correct identification rates were highest for k-NN. This study demonstrates the identification of the origin of peanuts by Raman spectroscopy with chemometrics and may provide technical support for the traceability of other agricultural products.

Keywords:

• k-nearest neighbor (k-NN)
• peanut kernels
• Raman spectroscopy
• stepwise linear discriminant analysis (SLDA)
• support vector machine (SVM)

Disclosure statement

The authors declare no conflicts of interest.

Additional information

Funding

This work was supported by the Natural Science Foundation of Shandong Province (No. ZR2019BC033) and Key Laboratory of Agro-Products Processing, Ministry of Agriculture and Rural Affairs (No. S2021KFKT-07).