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Application of texture analysis of b-mode ultrasound images for the quantification and prediction of intramuscular fat in living beef cattle: a methodological study
Fabbri, G., Gianesella, M., Gallo...
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Objectives
Intramuscular fat (IMF) plays a key role in determination of beef meat quality, because it contributes significantly to the aroma and tenderness of the meat. However, methods to determine fat % in muscle mass rely on visual inspection or on fat extraction from meat samples, and therefore require the animals’ to be slaughtered. IMF determination in vivo could permit early meat quality estimation, and thus lead to changes in the animals’ management to influence meat composition and better meet market requests. The aim of this methodological study was the elaboration of a formula capable of IMF% prediction from real-time ultrasound (RTU) images live beef cattle.
Material and methods
26 Charolaise heifers were enrolled in the study and their longissimus dorsi (LD) muscle was investigated. Ultrasound images were scanned on the animals’ right side between the 12th and 13th rib with a portable ultrasound scanner (MyLabOne™, Esaote S.p.a., Genoa, Italy) equipped with a multi-frequency convex probe (SC3421, Esaote S.p.a., Genoa, Italy; 2.5 – 6.6 MHz). All scans had 4.3 MHz frequency, 15 cm depth, and 100% gain. Texture analysis of the collected scans was performed by means of a free purpose-specific software (MaZda v4.6; Technical University of Lodz, Institute of Electronics, Poland).
One week after the in vivo examination, the animals were slaughtered and the whole cut of the 12th rib was collected. The cut was dissected into muscles, fat and bones. The sample of LD was analyzed with centesimal extraction: IMF% was determined by extraction with petrol ether (Randall) method.
Animals were divided in 3 groups depending on their mean lipid content percentage in 100g meat, and thresholds where chosen using IMF mean ± ½SD (Group 1 included animals with IMF below 4.24 g; Group 2 included between 4.25 g and 5.75 g; and, Group 3 included animals with IMF higher than 5.76 g).
Texture parameters were screened with a stepwise linear discriminant analysis using IMF measured by chemical extraction (IMFqa) as the dependent variable, and the results of the texture analysis as explanatory variables, to identify the best combinations of high-quality variables. The aim was a parsimonious model with as few parameters as possible, to enhance stability during validation.
The differentiation efficiency of IMFqa was tested by means of the receiver operating characteristic (ROC) curves. Bland-Altman analysis was performed to validate the method and to assess the agreement between IMFqa and IMFpred.
Results
Each scan generated approximately 300 texture parameters. Among these, 6 variables were identified as predictive by the stepwise analysis and were molded into a multiple regression equation.
IMF in the samples was then predicted by means of the formula (Predicted IMF, or IMFpred), and compared to the quantified IMF (IMFqa).
Among all samples, the mean IMFqa extracted from the meat was 5.08 ±1.47 g, while the mean IMFpred was 5.07±1.35 g.
A high linear correlation between IMFqa and IMFpred was found (r²=0.85) and results from the ROC analysis showed an Area Under the Curve (AUC) of 92%, with a sensitivity of 80% and a specificity of 93.7%, while results from the Bland-Altman plot were ± 1.96 (±1.11SD).
Conclusions
In the present study, IMF% from beef cattle LD muscle was estimated successfully and with high accuracy, using RTU, one week prior slaughter.
Application of this technology on wide-scale breeding could lead to important economic impacts. A good accuracy in IMF% prediction could permit screening of the animals that are going to be slaughtered, and see whether their fattening is optimal for the market requirements, maximizing the profits.
This technology could also permit monitoring of fattening cycles, leading to rapid estimation in vivo of adequacy of the diets fed to the animals. Lastly, it could be used for genetic selection, bypassing lengthy genetic progeny testing and therefore saving large amounts of time.
Further studies to validate the method both on a wider sample and on different sex and breeds are encouraged, but such technology could be a powerful heard selection tool as well as assist farmers in fattening practices.
Ethical Standards
All animals were slaughtered according to EU regulations (Council Regulation (EC) No 1099/2009 of 24 September 2009 on the protection of animals at the time of killing).
Keywords: Beef Cattle, Fat Prediction, Intramuscular Fat, Texture Analysis, Ultrasonography.
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