Handheld near-infrared spectrometer allows on-line prediction of beef quality traits. (February 2022)

• Record Type: Journal Article
• Authors: Goi, Arianna; Hocquette, Jean-François; Pellattiero, Erika; De Marchi, Massimo
• Is Part Of: Meat science. Volume 184(2022)
• Publication Date: 2022-02
• Subjects: Meat -- Fatty acids -- Minerals -- Technological traits -- Portable NIR instrument; 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.2021.108694
• Languages: English
• ISSNs: 0309-1740

Abstract

Abstract: The aim of this study was to evaluate the ability of a miniaturized near-infrared spectrometer to predict chemical parameters, technological and quality traits, fatty acids and minerals in intact Longissimus thoracis and Trapezius obtained from the ribs of 40 Charolais cattle. Modified partial least squares regression analysis to correlate spectra information to reference values, and several scatter correction and mathematical treatments have been tested. Leave-one-out cross-validation results showed that the handheld instrument could be used to obtain a good prediction of moisture and an approximate quantitative prediction of fat or protein contents, a*, b*, shear force and purge loss with coefficients of determination above 0.66. Moreover, prediction models were satisfactory for proportions of MUFA, PUFA, oleic and palmitic acids, for Fe and Cu contents. Overall, results exhibited the usefulness of the on-line miniaturized tool to predict some beef quality traits and the possibility to use it with commercial cuts without sampling, carcass deterioration nor grinding and consequent meat products' loss. Highlights: Miniaturized handheld NIR spectrometer allows satisfactory prediction of MUFA, PUFA, Cu and Fe in intact beef muscles. Technological and quality traits of beef can be predicted using a handheld NIR device. Calibration models' accuracy do not allow on-line prediction of major minerals in beef muscles.