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

Chima Robert; Wendy E Bain; Cameron Craigie; Talia M Hicks; Mark Loeffen; Sara J Fraser-Miller; Keith C Gordon

doi:10.1016/j.meatsci.2022.109005

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

Meat Sci. 2023 Jan:195:109005. doi: 10.1016/j.meatsci.2022.109005. Epub 2022 Oct 14.

Authors

Chima Robert¹, Wendy E Bain², Cameron Craigie³, Talia M Hicks⁴, Mark Loeffen⁵, Sara J Fraser-Miller⁶, Keith C Gordon⁷

Affiliations

¹ Dodd Walls Centre for Photonics and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin, New Zealand.
² AgResearch, Invermay Research Centre, Private Bag 50034, Mosgiel 9053, New Zealand.
³ AgResearch, Lincoln Research Centre, Private Bag 4749, Christchurch 8140, New Zealand.
⁴ AgResearch, Grasslands Research Centre, Te Ohu Rangahau Kai, Palmerston North 4410, New Zealand.
⁵ Delytics Ltd, Waikato Innovation Centre, Hamilton East, Hamilton 3216, New Zealand.
⁶ Dodd Walls Centre for Photonics and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin, New Zealand. Electronic address: sara.miller@otago.ac.nz.
⁷ Dodd Walls Centre for Photonics and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin, New Zealand. Electronic address: keith.gordon@otago.ac.nz.

PMID: 36272312
DOI: 10.1016/j.meatsci.2022.109005

Abstract

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.

Keywords: Chemometrics; Data fusion; Fatty acid; Infrared; Meat; Raman; Spectroscopy.

MeSH terms

Animals
Fatty Acids* / analysis
Least-Squares Analysis
Meat / analysis
Red Meat* / analysis
Sheep
Spectrum Analysis, Raman

Substances

Fatty Acids