Chemometric analysis of fingerprinting derivative spectrophotometry for authentication of shallots
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Abstract
The Bima Brebes, variety of shallots, was in high demand, which led to mixing with other varieties. Derivative spectrophotometric fingerprinting combined with chemometrics was used to distinguish between authentic and adulterated shallot varieties. The objective of this study was to identify the original spectra and their derivative spectrophotometric fingerprinting, as well as classify and differentiate between shallot varieties using chemometrics. UV-Visible (UV-Vis) spectrophotometry was used to test essential oil samples from three shallot varieties and their mixtures, followed by spectral derivatization. The spectral data revealed distinct patterns for each sample, including individual varieties and mixtures, and was then analyzed using Principal Component Analysis (PCA) and Partial Least Square-Discriminant Analysis (PLS-DA). The original spectra and their derivatives showed similarities across the samples. PCA and PLS-DA results indicated that the second-order derivative data provided the greatest separation, with a total Principal Component 1 (PC1) and Principal Component 2 (PC2) value of 62.2%, a total component 1 and 2 value of 60.1%, and the highest Variable Importance in the Projection (VIP) score wavelength of 225 nm. The PLS-DA results were validated to ensure that the model was not overfit, as evidenced by a satisfactory cross-validation quality (Q2/R2) value of 0.693 and a significant permutation test. The combination of derivative spectrophotometry fingerprinting and a chemometric approach effectively classified different samples, allowing for the determination of the authenticity of a specific shallot variety.
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