Application of Hyperspectral imaging to predict the pH, intramuscular fatty acid content and composition of lamb M. longissimus lumborum at 24h post mortem

Abstract

Cost-effective, rapid and objective measurement of lamb quality on a routine basis is an important step for lamb value chains wishing to manage lamb product quality. Hyperspectral imaging (HSI) technology has shown promise as a solution for objective non-invasive prediction of meat quality. The performance of HSI applied 24h post mortem to lamb M. longissimus lumborum (LL) within a processing plant environment was assessed over two sampling years to evaluate its suitability for an objective lamb meat quality assurance tool. Calibration and validation steps were undertaken to evaluate HSI prediction performance for predicting fatty acid content and composition (n=1020 lambs) and pH (n=2406 lambs). Practical considerations of reference meat quality data quality and validation strategies are discussed. HSI can be used to predict meat quality parameters of lamb LL with varying accuracy levels, but ongoing calibration and validation across seasons is required to improve robustness of HSI for objective non-invasive assessment of lamb meat quality.

Keywords: Chemometrics; Fatty acid composition; Hyperspectral image analysis; Intramuscular fat; Lamb.