Non-destructive Raman spectroscopy as a tool for measuring ASTA color values and Sudan I content in paprika powder
The aim of this study was developing a non-destructive method for the determination of color in paprika powder as well as for detecting possible adulteration with Sudan I. Non-destructive Raman spectroscopy was applied directly to paprika powder employing a laser excitation of 785 nm for the first t...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad Nacional de Educación a Distancia |
| Repositorio: | e-spacio. Repositorio Institucional de la UNED |
| Idioma: | inglés |
| OAI Identifier: | oai:e-spacio.uned.es:20.500.14468/11559 |
| Acceso en línea: | https://hdl.handle.net/20.500.14468/11559 |
| Access Level: | acceso abierto |
| Palabra clave: | ASTA values Sudan I Partial least-squares regression Partial least-squares discriminant-analysis U-PLS/RBL |
| Sumario: | The aim of this study was developing a non-destructive method for the determination of color in paprika powder as well as for detecting possible adulteration with Sudan I. Non-destructive Raman spectroscopy was applied directly to paprika powder employing a laser excitation of 785 nm for the first time. The fluorescence background was estimated, by fitting a polynomial to each spectrum, and then subtracted. After preprocessing the spectra, some peaks were clearly identified as characteristic from pigments present in paprika. The preprocessed Raman spectra were correlated with the ASTA color values of paprika by partial least squares regression (PLSR). Twenty-five paprika samples were adulterated with Sudan I at different levels and the PLSR model was also obtained. The coefficients of determination (R2) were 0.945 and 0.982 for ASTA and Sudan I concentration, respectively, and the root mean square errors of prediction (RMSEP) were 8.8 ASTA values and 0.91 mg/g, respectively. Finally, different approaches were applied to discriminate between adulterated and non-adulterated samples. Best results were obtained for partial least squares – discriminant analysis (PLS-DA), allowing a good discrimination when the adulteration with Sudan I was higher than 0.5%. |
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