Fusion of three spectroscopic techniques for prediction of fatty acid in processed lamb

The application of individual spectroscopic techniques for meat analysis has been widely explored. Attempts to fuse data from multiple spectroscopic instruments for meat analysis are still lacking. Comparative assessment of the performance of mid infrared (MIR), near infrared (NIR) and Raman spectroscopy to estimate fatty acid (FA) composition in processed lamb was investigated. The acquired data from these individual techniques were then utilised in estimating similar parameters using a multi-block partial least square data fusion approach. Model performance was assessed with respect to the determination coefficient and ratio of predictive deviation upon cross-validation of the model. The fused data had slight improvements for the prediction of four FA parameters including MUFA, C18:0, C18:1 c9 and C9, t11-CLA), suggesting possible information enhancement with use of multiple instruments. However, MIR offered better predictability (RPD values) across the FA parameters considered.

Automated summary

The study compared the performance of mid infrared (MIR), near infrared (NIR) and Raman spectroscopy in estimating fatty acid (FA) composition in processed lamb and explored the potential improvement by fusing data from multiple instruments. The results showed that data fusion had slight improvements in predicting certain FA parameters, but MIR spectroscopy outperformed the other techniques in estimating these parameters.