Application of Ultrasound Images Texture Analysis for the Estimation of Intramuscular Fat Content in the Longissimus Thoracis Muscle of Beef Cattle after Slaughter: A Methodological Study.

Giorgia Fabbri,Luigi Gallo,Matteo Gianesella,Michele Muraro,Massimo Morgante,Matteo Boso,Enrico Fiore,Barbara Contiero

doi:10.3390/ani11041117

Giorgia Fabbri, Luigi Gallo + Show 6 more

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https://doi.org/10.3390/ani11041117

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Abstract

Simple SummaryFat content in the muscle mass (IMF) is one of the most important characteristics influencing the aroma, tenderness, and juiciness of the meat and therefore has high importance for both commercialization purposes and consumers. However, IMF determination currently relies on visual inspection, which is a subjective and inconsistent technique. The aim of the present study is the elaboration of a procedure capable of predicting IMF% in beef carcasses using ultrasound imaging texture analysis. Ultrasound images taken on meat samples were compared to meat composition measured by chemical extraction. Determination coefficient between the two techniques was R2 = 0.76, while Receiver Operating Characteristic analysis showed a sensitivity of 88% and a specificity of 90%. The results therefore suggest that the described procedure is expected to determine IMF% in muscle with good accuracy. Ultrasound imaging could be applied in routine beef grading practices. This may help to solve the issues related to subjectivity and leave to the operator only imaging acquisition. Better consistency in beef products could enhance consumers’ satisfaction and commercial standardization programs.Intramuscular fat (IMF) is a major trait in the evaluation of beef meat, but its determination is subjective and inconsistent and still relies on visual inspection. This research objective was a method to predict IMF% from beef meat using ultrasound (US) imaging texture analysis. US images were performed on the longissimus thoracis muscle of 27 Charolaise heifers. Cuts from the 12th to 13th ribs were scanned. The lipid content of the muscle samples was determined with the petrol ether (Randall) extraction method. A stepwise linear discriminant analysis was used to screen US texture parameters. IMF% measured by chemical extraction (IMFqa) was the dependent variable and the results of the texture analysis were the explanatory variables. The model highlighted seven parameters, as a predictive and a multiple regression equation was created. Prediction of IMF content (IMFpred) was then validated using IMFqa as ground truth. Determination coefficient between IMFqa and IMFpred was R2 = 0.76, while the ROC analysis showing a sensitivity of 88% and a specificity of 90%. Bland-Altman plot upper and lower limit were +1.34 and −1.42, respectively (±1.96 SD), with a mean of −0.04. The results from the present study therefore suggest that prediction of IMF content in muscle mass by US texture analysis is possible.

Highlights

While modern trends and fashions in the food market could suggest a decrease in meat consumption, favoring vegetable-based alternatives, many studies have indicated that meat demand has increased globally and is likely to continue in the future [1].One of the main challenges in the market of beef, along with ensuring food safety, is the commercialization of a product that is both homogeneous and enjoyable
The results from the present study suggest that prediction of Intramuscular fat (IMF) content in muscle mass by US texture analysis is possible
S(2,2)InvDfMom, S(3,−3)Contrast, and S(4,−4)DifEntrp pertain to the Co-occurrence matrix category. These parameters provide a description of homogeneity in the region of interest (ROI) by analyzing the changes in pixel intensity at increasing pixel distances. 45dgr_ShrtREmp is part of the Run-length matrix category and provides a numerical description of the homogeneity of the signal intensity in specific directions of the ROI [22]. These seven variables were combined into a model that resulted in the following regression equation: IMFpred = 281.89031 + (−208.07129 * S(2,2)InvDfMom) + (0.14783 * S(3,−3)Contrast)

Summary

Introduction

One of the main challenges in the market of beef, along with ensuring food safety, is the commercialization of a product that is both homogeneous and enjoyable. Lipid content in the muscle (commonly referred as Intramuscular Fat, IMF) directly influences palatability traits, and the profits, since it is often considered as directly affecting consumers’ consumption decisions [4]. Chemical analysis is still the most precise method to determine carcass composition and IMF content. It can be performed either by ether-extraction or with other fat extraction methods such as chloroform/methanol. The preferred method to determine IMF content is marbling scoring, and the grading carcasses still relays on the visual appraisal by trained evaluators [6]. Visual grading is an imprecise technique: it’s inconsistent and subject to the bias of the inspector (human factor) [7,8]

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