Application of Infrared Spectroscopy with Multivariate Analysis and Soft Indepen dent Modelling of Class Analogies (Simca) for the Detection of Meat Species - Devatkal, Suresh k; Jaiswal, Praneeta; Anurag, Rahul; Jatoth, Kalyani; Yadagiri, Chandana (Journal of Meat Science, 2026)
Meat speciation is currently monitored using various chemical and biological  methods that rely on proteins, DNA, and RNA. However, these approaches are  slow, costly, and difficult for automation. Infrared spectroscopy presents itself  as a convenient analytical tool for monitoring food quality. This study aimed  to evaluate the potential of FTIR spectroscopy and multivariate analyses in  identifying meat species. Dried powders were prepared from defatted goat meat,  chicken and pork. Initially, powders from single meat species were subjected  to spectral scanning in the range of 400-400 cm-1. Subsequently, mixtures of  chicken and goat, pork and goat, and chicken and pork in a 50:50 ratio were  prepared and analysed using FTIR spectroscopy. Chemometric analyses,  employing multivariate analysis, were conducted for each sample. Spectral  signatures of 16-18 samples for each type of mixed powder were acquired.  Results of Principal component analysis showed clear clustering of samples  with sum of PC1 and PC2 described 98% variance. Further, SIMCA correctly  classified the chicken, goat and pig powder into their respective classes with  an accuracy of 93.75%, 88.88% and 93.75% respectively. In conclusion, NIR  spectral analysis proves to be a novel, rapid, and cost-effective technique for  identifying meat species in various meat and meat products. Experiments were  carried out in ICAR-CIPHET, Ludhiana.
Keywords: FTIR spectroscopy; chemometric analysis; SIMCA; meat adulteration