Predicting fat cover in beef cattle to make on-farm management decisions: a review of assessing fat and of modeling fat deposition

Demands of domestic and foreign market specifications of carcass weight and fat cover, of beef cattle, have led to the development of cattle growth models that predict fat cover to assist on-farm managers make management decisions. The objectives of this paper are 4-fold: 1) conduct a brief review of the biological basis of adipose tissue accretion, 2) briefly review live and carcass assessments of beef cattle, and carcass grading systems used to develop quantitative compositional and quality indices, 3) review fat deposition models: Davis growth model (DGM), French National Institute for Agricultural Research growth model (IGM), Cornell Value Discovery System (CVDS), and BeefSpecs drafting tool (BeefSpecsDT), and 4) appraise the process of translating science and practical skills into research/decision support tools that assist the Beef industry improve profitability. The r2 for live and carcass animal assessments, using several techniques across a range of species and traits, ranged from 0.61 to 0.99 and from 0.52 to 0.99, respectively. Model evaluations of DGM and IGM were conducted using Salers heifers (n = 24) and Angus-Hereford steers (n = 15) from an existing publication and model evaluations of CVDS and BeefSpecsDT were conducted using Angus steers (n = 33) from a research trial where steers were grain finished for 101 d in a commercial feedlot. Evaluating the observed and predicted fat mass (FM) is the focus of this review. The FM mean bias for Salers heifers were 7.5 and 1.3 kg and the root mean square error of prediction (RMSEP) were 31.2 and 27.8 kg and for Angus-Hereford steers the mean bias were -4.0 and -10.5 kg and the RMSEP were 9.14 and 21.5 kg for DGM and IGM, respectively. The FM mean bias for Angus steers were -5.61 and -2.93 kg and the RMSEP were 12.3 and 13.4 kg for CVDS and BeefSpecsDT, respectively. The decomposition for bias, slope, and deviance were 21%, 12%, and 68% and 5%, 4%, and 91% for CVDS and BeefSpecsDT, respectively. The modeling efficiencies were 0.38 and 0.27 and the models were within a 20 kg level of tolerance 91% and 88% for CVDS and BeefSpecsDT, respectively. Fat deposition models reported in this review have the potential to assist the beef industry make on-farm management decisions on live cattle before slaughter and improve profitability. Modelers need to continually assess and improve their models but with a caveat of 1) striving to minimize inputs, and 2) choosing on-farm inputs that are readily available.

Modelling and predicting fat deposition rates in various South African sheep crosses using ultrasound technology

Producers require an accurate predictive tool that can determine the optimal point of slaughter based on fat depth. The modelling of fat deposition with a simple mathematical model could supply in this need. Dohne Merino and Merino ewes were crossed with Dorper, Dormer and Ile de France rams or rams of their own breeds to create two purebred (Dohne Merino and Merino) and six crossbred groups (Dohne x Dorper, Dohne x Dormer, Dohne x Ile de France, Merino x Dorper, Merino x Dormer and Merino x Ile de France) of offspring. Fat deposition of four lambs of each sex per genotypic group was monitored from 80 to 360 days using ultrasound, and the data subsequently fitted to various equations and evaluated for goodness of fit. A linear fitting of fat depth to age (R2 > 0.77) and live weight (R2 > 0.56) were deemed to provide the best fit. The slope parameters of the equations indicated that ewes deposited fat faster than rams and that Dorper crosses had the highest fat deposition rate. An attempt was also made to model loin muscle growth, but the model fit was judged to be unsatisfactory. The predictive models developed here are deemed suitable for inclusion in feedlot management systems to aid in the production of optimally classified lamb carcasses.

Processing of beef rumen with ultrasonic waves

The article discusses the main trends in processing animal products, the development of technologies to improve their quality and technologies to preserve the quality indicators of the product over time. A review of the effects of ultrasound treatment on beef rumen is presented, and the main directions of ultrasound application are determined. The advantages of ultrasonic processing and its influence on the characteristics of raw meat were researched. The modes and parameters (frequency, intensity and duration) of ultrasound treatment of muscle tissue were established based on the results. This study evaluated the effect of ultrasound treatment on beef rumen's physical, microstructural and organoleptic characteristics. The physicochemical, mineral, microbiological, vitamin and amino acid composition of beef rumen and reticulum were also studied. Based on the results of the presented review, it can be concluded that the development of technologies for processing beef rumen with ultrasound is of potential interest. The optimal parameters are 400 and 600 W/m2, with a frequency of 40 kHz, for 50-60 minutes.

Predictability of carcass traits in live Tan sheep by real-time ultrasound technology with least-squares support vector machines

This study aimed to investigate the performance of least-squares support vector machines to predict carcass characteristics in Tan sheep using noninvasive in vivo measurements. A total of 80 six-month-old Tan sheep (37 rams and 43 ewes) were examined. Back fat thickness and eye muscle area between the 12th and 13th ribs were measured using real-time ultrasound in live Tan sheep. All carcasses were dissected to hind leg, longissimus dorsi muscle, lean meat, fat, and bone to determine carcass composition. Multiple linear regression (MLR), partial least squares regression (PLSR), and least-squares support vector machines (LSSVM) were applied to correlate the live Tan sheep characteristics with carcass composition. The results showed that the LSSVM model had a better efficacy for estimating carcass weight, longissimus dorsi muscle weight, lean meat weight, fat weight, lean meat, and fat percentage in live lambs (R = 0.94, RMSE = 0.62; R = 0.73, RMSE = 0.02; R = 0.86, RMSE = 0.47; R = 0.78, RMSE = 0.63; R = 0.73, RMSE = 0.02; R = 0.65, RMSE = 0.03, respectively). LSSVM algorithm was a potential alternative to the conventional MLR method. The results demonstrated that LSSVM model might have great potential to be applied to the evaluation of sheep with superior carcass traits by combining with real-time ultrasound technology.

Prediction of carcass composition and meat and fat quality using sensing technologies: A review

Consumer demand for high-quality healthy food is increasing,  thus meat processors require the means toassess these rapidly, accurately, and inexpensively. Traditional methods forquality assessments are time-consuming, expensive, invasive, and have potentialto negatively impact the environment. Consequently, emphasis has been put onfinding non-destructive, fast, and accurate technologies for productcomposition and quality evaluation. Research in this area is advancing rapidlythrough recent developments in the areas of portability, accuracy, and machinelearning. The present review, therefore, critically evaluates and summarizes developmentsof popular non-invasive technologies (i.e., from imaging to spectroscopicsensing technologies) for estimating beef, pork, and lamb composition andquality, which will hopefully assist in the implementation of thesetechnologies for rapid evaluation/real-timegrading of livestock products in the nearfuture.

Advances in Sheep and Goat Meat Products Research

The main goal of this chapter was to review the state of the art in the recent advances in sheep and goat meat products research. Research and innovation have been playing an important role in sheep and goat meat production and meat processing as well as food safety. Special emphasis will be placed on the imaging and spectroscopic methods for predicting body composition, carcass and meat quality. The physicochemical and sensory quality as well as food safety will be referenced to the new sheep and goat meat products. Finally, the future trends in sheep and goat meat products research will be pointed out.

The use of ultrasound to measure muscle depth and area in postmortem Holstein dairy calves

Monitoring growth of neonatal dairy calves is a useful management tool to assist producers in achieving goals for reproduction and performance. The goal of this study was to examine ultrasound as an in vivo tool to quantify longissimus dorsi muscle (ribeye) linear depth and extensor carpi radialis (ECR) and semitendinosus (ST) muscle cross-sectional areas in postmortem preweaned Holstein calves. Postmortem preweaned calves (n = 137, age 13.1 d ± 15.5 SD, body weight 36.5 kg ± 7.2 SD) were obtained from two California calf ranches between April and July 2013. Two operators collected ultrasound images of the ribeye, ECR, and ST muscles using an Aloka 500V equipped with a 5-cm 7.5-MHz linear transducer. Ultrasound ribeye linear depth and ECR and ST cross-sectional areas were calculated using the Ultrasound Image Capture System. Ultrasound measurements were compared to dissected (carcass) measures. Carcass ribeye linear depth was estimated using a ruler. Dissected ECR and ST muscle cross-sectional areas were estimated by tracing muscle cross sections onto transparency paper and then photocopying, cutting out, and weighing individual paper muscle tracings. Weights of the tracings were then converted to areas using the known area of a standard 8.5 × 11 inch paper. Data were analyzed by regressing carcass estimates on observed ultrasound measurements. The coefficient of determination (R²) indicated that ultrasound measurements were most closely associated with carcass measurements for the ST muscle (R² = 0.60, 0.62 for operator 1 and 2, respectively) when compared to the ribeye and ECR muscles (R² = 0.27, 0.41 for ribeye and 0.43, 0.32 for ECR for operator 1 and 2, respectively). The mean bias showed consistent underestimation by the ultrasound measurements when predicting carcass measurements for all three muscles and for both operators (ribeye bias = 0.15, 0.40; ECR bias = 0.95, 1.15; and ST bias = 0.73, 0.27 for operator 1 and 2, respectively). Operator contributed significantly in explaining a proportion of the variation in the regression equation for the ST muscle only, whereas calf body weight contributed significantly in explaining a proportion of the variation in the regression equation for all three muscles. The results of this study demonstrated that ultrasound measurements of the ST were the most accurate for quantifying the cross-sectional area when compared to both the ECR and ribeye in postmortem Holstein calves.

Relationships between body condition score and ultrasound skin-associated subcutaneous fat depth in equids

Background

In equids, health and welfare depend on body composition. A growing number of equids are now used as leisure and companion animals, and often found overfeed. The need for a close monitoring of body fatness led to the search for tools allowing a rapid and non-invasive estimation of fatness. This study intends to assess real-time ultrasonography (RTU) usefulness in establishing a relationship between ultrasound measures of subcutaneous fat–plus–skin thickness (SF-Skin) and body condition score (BCS) in horses and donkeys. Forty-three healthy animals (16 donkeys and 27 horses) were used in this study to generate 95 records (RTU and BCS pairs), in multiple RTU sessions for 2 years. Using visual appraisal and palpation, BCS was graded in a 1–9 points scale. Real-time ultrasonography images were taken using a 7.5 MHz linear transducer, placed perpendicular to the backbone, over the 3rd lumbar vertebra. ImageJ was used to measure the SF-Skin on RTU images. The relation between BCS and SF-Skin measurements was tested by linear and polynomial regression analysis.

Results

The BCS values were similar in horses (5.50; from 3 to 8 points) and donkeys (5.14; from 3 to 7 points). The SF-Skin measures show a similar trend (a mean of 7.1 and 7.7 mm in horses and donkeys, respectively). A polynomial regression among BCS and SF-Skin explained 92 and 77 % of the variation in donkeys and horses respectively. The coefficient of determination was considerably higher for the regression developed for donkeys compared with that of horses (R2 = 0.92 vs. 0.77, respectively), which reduced the accuracy of the method in horses. Both the linear and polynomial models tested show a strong relationship among BCS and SF-Skin for donkeys (R2 > 0.91; P < 0.01) and horses (R2 > 0.74; P < 0.01), despite that the extremes for BCS did not existed in our sample.

Conclusions

Our results showed the potential RTU usefulness to monitor body fat in equids. Using a high-frequency transducer and RTU together with image analysis allowed the identification of small SF-skin variations. This report will support further studies on the relationships between SF-Skin and BCS, particularly in extreme BCS scores.

Bayesian inference of genetic parameters for ultrasound scanning traits of Kivircik lambs

Ultrasound scanning traits have been adapted in selection programs in many countries to improve carcass traits for lean meat production. As the genetic parameters of the traits interested are important for breeding programs, the estimation of these parameters was aimed at the present investigation. The estimated parameters were direct and maternal heritability as well as genetic correlations between the studied traits. The traits were backfat thickness (BFT), skin+backfat thickness (SBFT), eye muscle depth (MD) and live weights at the day of scanning (LW). The breed investigated was Kivircik, which has a high quality of meat. Six different multi-trait animal models were fitted to determine the most suitable model for the data using Bayesian approach. Based on deviance information criterion, a model that includes direct additive genetic effects, maternal additive genetic effects, direct maternal genetic covariance and maternal permanent environmental effects revealed to be the most appropriate for the data, and therefore, inferences were built on the results of that model. The direct heritability estimates for BFT, SBFT, MD and LW were 0.26, 0.26, 0.23 and 0.09, whereas the maternal heritability estimates were 0.27, 0.27, 0.24 and 0.20, respectively. Negative genetic correlations were obtained between direct and maternal effects for BFT, SBFT and MD. Both direct and maternal genetic correlations between traits were favorable, whereas BFT-MD and SBFT-MD had negligible direct genetic correlation. The highest direct and maternal genetic correlations were between BFT and SBFT (0.39) and between MD and LW (0.48), respectively. Our results, in general, indicated that maternal effects should be accounted for in estimation of genetic parameters of ultrasound scanning traits in Kivircik lambs, and SBFT can be used as a selection criterion to improve BFT.

Quality properties of pre- and post-rigor beef muscle after interventions with high frequency ultrasound

The delivery of a consistent quality product to the consumer is vitally important for the food industry. The aim of this study was to investigate the potential for using high frequency ultrasound applied to pre- and post-rigor beef muscle on the metabolism and subsequent quality. High frequency ultrasound (600kHz at 48kPa and 65kPa acoustic pressure) applied to post-rigor beef striploin steaks resulted in no significant effect on the texture (peak force value) of cooked steaks as measured by a Tenderometer. There was no added benefit of ultrasound treatment above that of the normal ageing process after ageing of the steaks for 7days at 4°C. Ultrasound treatment of post-rigor beef steaks resulted in a darkening of fresh steaks but after ageing for 7days at 4°C, the ultrasound-treated steaks were similar in colour to that of the aged, untreated steaks. High frequency ultrasound (2MHz at 48kPa acoustic pressure) applied to pre-rigor beef neck muscle had no effect on the pH, but the calculated exhaustion factor suggested that there was some effect on metabolism and actin-myosin interaction. However, the resultant texture of cooked, ultrasound-treated muscle was lower in tenderness compared to the control sample. After ageing for 3weeks at 0°C, the ultrasound-treated samples had the same peak force value as the control. High frequency ultrasound had no significant effect on the colour parameters of pre-rigor beef neck muscle. This proof-of-concept study showed no effect of ultrasound on quality but did indicate that the application of high frequency ultrasound to pre-rigor beef muscle shows potential for modifying ATP turnover and further investigation is warranted.

Backfat thickness and longissimus dorsi real-time ultrasound measurements in light lambs

The aim of this study was to assess the accuracy of ultrasound measurements for predicting carcass traits in 124 Spanish pascual-type lambs (13 to 16 kg carcass weight). Ultrasound images were taken transversal and longitudinal to the vertebral column and at thoracic (TV; between 12th and 13th ribs) and lumbar (LV; between first and second lumbar vertebrae) locations. Skin thickness, subcutaneous backfat thickness (BFT), and depth (DLD), width (WLD), and area (ALD) of longissimus dorsi were obtained with ImageJ 1.42q software. After slaughter, BFT (TV, 2.30 ± 0.06 mm; LV, 2.46 ± 0.06 mm), DLD (TV, 2.47 ± 0.03 cm; LV, 2.48 ± 0.03 cm), WLD (TV, 4.50 ± 0.04 cm; LV, 4.60 ± 0.04 cm), and ALD (TV, 9.96 ± 0.12 cm(2); LV, 10.19 ± 0.13 cm(2)) were directly measured on the lamb carcass. Correlations between ultrasound and direct carcass measurements were greater than 0.61 for DLD, WLD, and ALD (P < 0.05) whereas they fluctuated between 0.32 and 0.60 for BFT (P < 0.05); moreover, correlations were significantly (P < 0.05) greater for transversal than for longitudinal views. In a similar way, linear regression analyses suggested a moderate underestimation for BFT and lumbar DLD when using real-time ultrasound technologies whereas WLD, ALD, and thoracic DLD suffered from under- and overestimation for small and large values of carcass traits, respectively. After decomposing the mean square prediction error (MSPE) for the different ultrasound measurements, we found that the error due to disturbance contributed most to the MSPE followed by the error of central tendency and the error due to regression. The SE of prediction (SEP) was also calculated as an additional precision indicator, obtaining estimates less than that in previous studies with larger lambs. In conclusion, transversal ultrasound measurements at the thoracic and lumbar levels could be a useful tool for predicting DLD, WLD, and ALD in light lambs, perhaps suffering from worse prediction properties when focusing on BFT. This information could be of special relevance for light lamb producers worldwide, with a special emphasis in the Mediterranean basin where this kind of production system accounts for a large percentage of the sheep industry.

Mapping Quantitative Trait Loci (QTL) in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL

An (Awassi × Merino) × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL) for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1) and 3.5 (cohort 2) years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3), 15 significant (LOD ≥ 2), and 11 suggestive QTL (1.7 ≤ LOD < 2) were detected on eleven chromosomes. Regression analysis confirmed 28 of these QTL and an additional 17 suggestive (P < 0.1) and two significant (P < 0.05) QTL were identified using this method. QTL with pleiotropic effects for two or more tissues were identified on chromosomes 1, 6, 10, 14, 16 and 23. No tissue-specific QTL were identified.A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.