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Application method of Fourier Transform Infrared (FTIR) combined with chemometrics for analysis of rat meat (Rattus Diardi) in meatballs beef
Counterfeit food products are starting to become a new problem around the people of Indonesia. Problems that are getting special attention especially the concern of contamination of food products by non-halal meat . For example rat meat on meatballs. This research is expected to be one of the basis...
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Published in: | Pharmaciana 2017-12, Vol.7 (2), p.133-140 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | Counterfeit food products are starting to become a new problem around the people of Indonesia. Problems that are getting special attention especially the concern of contamination of food products by non-halal meat . For example rat meat on meatballs. This research is expected to be one of the basis for the guarantee of non-halal meatballs products. The study of Fourier Transform Infrared spectrophotometry (FTIR) combined with chemometrics can be used to identify the presence of rat meat in meatballs qualitatively and quantitatively. Samples of meatballs are made by preparing pure rat and pure beef meat. The calibration samples were prepared by making meatballs containing beef - rat with variations of 0%, 25%, 35%, 65%, 75%, and 100% rat meat in dough meatballs. Validation samples were prepared from a number of meatballs prepared in the laboratory containing rat meat in a certain concentration and 5 samples of meatballs in the market. Cow and rat fat contained in meatballs were extracted with Soxhlet at ≤ 70oC for 7 hours with n-hexane solvent. Quantitative analysis was performed on wave number 750 - 1600 cm-1 using multivariate partial least square (PLS) and qualitative analysis with principal component analysis (PCA). Result of calibration model with y = 0.9720x + 1.580, coefficient of determination (R2) = 0.9941, and root mean square error of calibration (RMSEC) value equal to 1.63%. The validation model with the root mean square error of cross validation (RMSECV) is 1.79%, and the root mean square error of prediction (RMSEP) is 2.60%. By using PCA, the grouping of cow and rat fat in the meatball successfully done. |
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ISSN: | 2088-4559 2477-0256 |
DOI: | 10.12928/pharmaciana.v7i2.4247 |