Nutrient content prediction and geographical origin identification of red raspberry fruits by combining hyperspectral imaging with chemometrics

• DOI: 10.3389/fnut.2022.980095
• Publication Date: 2022-10-17T04:51:45Z
• Authors: Youyou Wang; Yue Zhang; Yuwei Yuan; Yuyang Zhao; Jing Nie; Tiegui Nan; Luqi Huang; Jian Yang
• Keywords: Blowing a raspberry; Chemometrics

The geographical origin and the important nutrient contents greatly affect quality of red raspberry (RRB, Rubus idaeus L.), a popular fruit with various health benefits. In this study, chemometrics-assisted hyperspectral imaging (HSI) method was developed for predicting contents, including pectin polysaccharides (PPS), reducing sugars (RS), total flavonoids (TF) phenolics (TP), identifying RRB fruits. results showed that these in fruits had significant differences between regions ( P < 0.05) could be well predicted based on HSI full or effective wavelengths selected through competitive adaptive reweighted sampling (CARS) variable iterative space shrinkage approach (VISSA). best prediction PPS, RS, TF, TP were achieved highest residual predictive deviation (RPD) values 3.66, 3.95, 2.85, 4.85, respectively. from multi-regions China effectively distinguished by using first derivative-partial least squares discriminant analysis (DER-PLSDA) model, an accuracy above 97%. Meanwhile, three protected indication (PGI) successfully classified orthogonal partial discrimination (OPLSDA) 98%. study indicate assisted chemometrics is promising