Prediction of the intramuscular connective tissue components of fresh and freeze-dried samples by near infrared spectroscopy. (September 2021)

• Record Type: Journal Article
• Authors: Andueza, D.; Picard, F.; Hocquette, J.F.; Listrat, A.
• Is Part Of: Meat science. Volume 179(2021)
• Publication Date: 2021-09
• Subjects: Hydroxyproline -- Collagen -- Proteoglycans -- Cross-links -- NIR -- Beef; Meat -- Periodicals; Meat industry and trade -- Periodicals; Viande -- Périodiques; Viande -- Industrie -- Périodiques; Meat; Meat industry and trade; Periodicals; 641.36
• DOI: 10.1016/j.meatsci.2021.108537
• Languages: English
• ISSNs: 0309-1740

Abstract

Abstract: This study compared the performance of near-infrared spectroscopy (NIRS) models on fresh and freeze-dried beef muscle samples to predict intramuscular connective tissue (IMCT) components and to determine whether the accuracy of the models differed among different muscles from beef cattle. The hypothesis was that the water content of muscle samples would negatively influence the accuracy of the models, which would differ among muscles. Fresh and freeze-dried samples ( n = 171) of four muscles were used to develop NIRS models to predict the contents IMCT. For the total collagen content, the standard error of cross validation (SECV) for model using freeze-dried samples (0.75 mg OH-prol/g DM) was lower than that for model using fresh samples (0.84 mg OH-prol/g DM). For cross-links and proteoglycans, the SECV for models using fresh sample spectra was lower than that for models using freeze-dried sample spectra. The accuracy of the prediction of the models also differed among predicted muscle types.