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Strategies for the Content Determination of Capsaicin and the Identification of Adulterated Pepper Powder Using a Hand-held Near-infrared Spectrometer by Sijun Wu; Long Wang; Guoming Zhou; Chao Liu; Zhongrui Ji; Zheng Li; Wenlong Li is a Agricultural and Biological Sciences article available to read on EtoBox.
What is Strategies for the Content Determination of Capsaicin and the Identification of Adulterated Pepper Powder Using a Hand-held Near-infrared Spectrometer about?
To achieve the goals of rapid content determination of capsaicin and adulteration detection of pepper powder. The method based on the hand-held near-infrared spectrometer combined with ensemble preprocessing was proposed. DoE-based ensemble preprocessing technique was utilized to develop the partial least squares regression models of red pepper [Capsicum annuum L. var. conoides (Mill.) Irish] powders. The performance of final models was evaluated using coefficient of determination (R 2), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD). Model development using selective ensemble preprocessing gave the best prediction of capsaicin in Yanjiao pepper powder (R 2 = 0.9800, RPD = 7.090, RMSEP = 0.00689) and Tianying pepper powder (R 2 = 0.8935, RPD = 3.017, RMSEP = 0.06154). Moreover, the potential of grey wolf optimizer-support vector machine (GWO-SVM) to detect adulterated pepper powder was investigated. The samples were composed of two authentic products and three different adulterants with different adulteration levels. The results showed that the classification accuracy of GWO-SVM model for Yanjiao peppers was over 90 %, which realized the adulte
Who reads Strategies for the Content Determination of Capsaicin and the Identification of Adulterated Pepper Powder Using a Hand-held Near-infrared Spectrometer?
It is typically read by researchers, students, and practitioners in Agricultural and Biological Sciences.
- Author
- Sijun Wu; Long Wang; Guoming Zhou; Chao Liu; Zhongrui Ji; Zheng Li; Wenlong Li
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Agricultural and Biological Sciences (Life Sciences)
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