Abstract
Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews’s correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%–100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.
Highlights
Nowadays, processed meat products are widely consumed all over the world
The Raman spectra obtained for the three different types of frankfurters are given in Figure 1 and the main vibrational bands are listed in Table 1, with their respective tentative assignments based on comparisons with previously published data
partial least square discriminant analysis (PLS-DA) was applied for classification purposes; for construction of the PLS-DA models, it is necessary a matrix X that contains the Raman spectra and a Y matrix, that is related to the interest property, in this case the classes of samples
Summary
Nowadays, processed meat products are widely consumed all over the world. Among them, the most widely accepted by consumers are bologna, salami and frankfurters. Several analytical techniques have been suggested for the identification of meat species, including different protein-based methods, such as high-performance liquid chromatography, electrophoretic techniques and enzyme-linked immunosorbent assays [4]. These techniques use expensive instruments, are destructive, time-consuming and generate toxic by-products. Raman spectroscopy was used to discriminate frankfurters from different sources; this technique provides molecular-specific information, is not destructive, does not require sample preparation ( saving on time and reagents), can determine more than one component at a time, and is free from water interference in the analysis [14,15]. The performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency, and Matthews’s correlation coefficient for both a training and validation set
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