Near Infrared Spectroscopy and Hyperspectral Imaging for Prediction and Visualisation of Fat and Fatty Acid Content in Intact Raw Beef Cuts

Abstract

The meat quality grade of a beef carcass is greatly affected by its visible fat content. In premium beef from Japanese Black (Wagyu) cattle, a high fat content is greatly valued. However, the fatty acid composition, which is linked to the properties of the fat, is not considered in grading. In this paper, we describe the feasibility of an evaluation method based on food composition and its distribution. An intact raw beef cut from Wagyu cattle was used as an evaluation target. A total of 90 samples from various parts of three Wagyu cattle were measured by near infrared (NIR) hyperspectral imaging at wavelengths of 1000–2300 nm at a spatial resolution of 380 urn pixel⁻¹ and were also analysed by conventional physical and chemical methods. The fat and fatty acid content were selected as the objective content, including the proportions of total saturated fatty acid (SFA), total unsaturated fatty acid (UFA) and the main fatty acids: myristic [C14:0, where Cx:y indicates the number of carbon atoms (x) and the number of double bonds (y)], palmitic (C16:0), stearic (C18:0), myristoleic (C14:1), palmitoleic (C16:1), oleic (C18:1) and linoleic (C18:2). The mean spectrum from an area extracted from the hyperspectral image to fit the area analysed by physical and chemical methods was used to develop partial least squares regression models for prediction of fat and fatty acid content. The prediction of total fat, SFA and UFA were satisfactory with r², standard error of prediction (SEP) and ratio of prediction to deviation (RPD) values of 0.90, 0.87 and 0.89, 4.81%, 1.69% and 3.41% and 2.84, 2.43 and 2.84, respectively. For individual fatty acids, the r² and RPD values ranged from 0.68 to 0.89 and 1.69 to 2.85, respectively. Prediction of fat content for each pixel of the hyperspectral image made using these prediction models yielded spatially distributed visualisations of the content. These results showed the feasibility of a beef evaluation method based on fat content evaluated by NIR hyperspectral imaging.