Empty Body Chemical Composition Research Articles

Three-dimensional imaging to estimate in vivo body and carcass chemical composition of growing beef-on-dairy crossbred bulls

The dynamics of cattle body chemical composition during growth and fattening periods determine animal performance and beef carcass quality. The aim of this study was to estimate the empty body (EB) and carcass chemical composition of growing beef-on-dairy crossbred bulls (Brown Swiss breed as dam with Angus, Limousin or Simmental as sire) using three-dimensional (3D) imaging. The 3D images of the cattle’s external body shape were recorded in vivo on 48 bulls along growth trajectory (75–520 kg BW and 34–306 kg hot carcass weight [HCW]; set 1) and on 70 bulls at target market slaughter weight, including 18 animals from set 1 (average 517 ± 10 kg BW and 289 ± 10 kg HCW; set 2). The linear, circumference, curve, surface and volume measurements on the 3D body shape were determined. Those predictive variables were used in partial least square regressions, together with the effect of the sire breed whenever significant (P < 0.05), with leave-one-out cross-validation to estimate water, lipid, protein, mineral and energy mass or proportions in the EB and carcass. Mass and proportions were determined directly from postmortem grinding and chemical analyses (set 1) or indirectly using the 11th rib dissection method (set 2). In set 1, bulls’ BW and HCW were estimated via 3D imaging, with root mean square error of prediction (RMSEP) of 12 kg and 6 kg, respectively. The EB and carcass chemical component proportions were estimated with RMSEP from 0.2% for EB minerals (observed mean 3.7 ± 0.2%) to 1.8% for EB lipid (11.6 ± 4.2%), close to the RMSEP found for the carcass. In set 2, the RMSEP for estimation via 3D imaging was 9 kg for BW and 6 kg for HCW. The EB energy and protein proportions were estimated, with RMSEP of 0.5 MJ/kg fresh matter (10.1 ± 0.8 MJ/DM) and 0.2% (18.7 ± 0.7%), respectively. Overall, the estimations of chemical component proportions from 3D imaging were slightly less precise for both sets than the mass estimations. The morphological traits from the 3D images appeared to be precise estimators of BW, HCW as well as EB and carcass chemical component masses and proportions.

Assessment of Equations to Predict Body Weight and Chemical Composition in Growing/Finishing Cattle and Effects of Publication Year, Sex, and Breed Type on the Deviation from Observed Values.

Body weight and chemical composition are important aspects of beef cattle nutrition and management; however, existing equations estimating relationships among empty body and carcass chemical components were developed over 40 years ago using different cattle genetics and production systems. The objective of this analysis was to evaluate existing equations in predicting empty body and carcass chemical composition and determine the effect of sex, breed type, and publication year. A dataset was developed from published literature that contained 388 treatment means from 46 studies published between 1970 and 2020. Two equations relating shrunk body weight (SBW) to empty body weight (EBW), and 8 equations relating EBW and hot carcass weight (HCW) were found in the literature and evaluated using the developed dataset. Three sets of equations relating empty body chemical components, 4 sets of equations relating carcass chemical components, and 2 sets of equations relating carcass with empty body chemical components were found in the literature and evaluated using the dataset. Precision and accuracy of the equations were evaluated by simple linear regression of observed on predicted values, mean bias (MB), and concordance correlation coefficient (CCC). Additionally, the fixed effects of publication year, sex, and breed type on the deviation from observed values were evaluated using a general linear model. Both equations relating SBW to EBW and all equations relating EBW to HCW had high precision, but accuracy varied from -3.22 to -0.11% and -9.35 to -3.73% MB, respectively, and all the equations were affected by sex and breed type with 8 out of the 10 equations affected by publication year. For prediction of empty body chemical composition assuming empty body water is known, the 3 sets of equations varied in precision for protein (0.18 to 0.46), but not for fat (0.88 to 0.96) or ash (0.06 to 0.13) based on CCC, although the precision of prediction of protein and ash were poor. Accuracy of the 3 sets of equations varied for predicting empty body fat, protein, and ash with MB of -19.73 to -3.81, 1.67 to 15.91, and -0.16 to 15.75%, respectively. All 3 sets of equations were affected by publication year and breed type for predicting empty body fat, protein, and ash, and by sex for ash. For prediction of carcass chemical components assuming carcass water is known, the precision was similar among the 4 sets of equations for predicting fat (0.92 to 0.95), protein (0.34 to 0.40), and ash (-0.02 to -0.01) based on CCC, although precision was poor for protein and ash, but accuracy varied for prediction of carcass fat, protein and ash with MB of -11.20 to -2.52, 2.72 to 8.92, and -4.66 to 20.12%, respectively. Publication year and breed type affected the prediction of carcass fat and protein, and publication year, sex, and breed type affected the prediction of carcass ash for all 4 sets of equations. The precision of predicting empty body chemical components assuming carcass chemical components are known was high for water (0.96 and 0.98), fat (0.97 and 0.98), protein (0.97 and 0.97), and ash (0.98 and 0.96) and similar between the 2 sets of equations based on CCC. The accuracy of predicting empty body water (-1.68 and -0.33%), fat (6.38 and 2.70%), protein (0.85 and -0.54%), and ash (-0.65 and -4.54%) was moderate to high, but differed between sets of equations for fat and ash. Publication year influenced the prediction of empty body water for both sets of equations and ash for one of the equations, whereas, breed type influenced the prediction of water, protein, and ash, but not fat for both equations. Overall, existing equations may have major limitations to predicting empty body protein and ash unless carcass protein and ash are known. Additionally, all the equations were affected by some combination of publication year, sex, and breed type for one or more chemical components. Thus, a more robust set of equations should be developed to account for sex, breed type, and more recent cattle genetics and management systems.

214 Assessment of Equations Relating Empty Body Chemical Components in Growing/Finishing Cattle

Abstract Existing equations to estimate empty body chemical composition were developed over 40 years ago using different cattle genetics. The objective of this analysis was to evaluate existing equations using cattle genetics from then to today. A literature search was performed to identify experiments measuring empty body chemical composition by proximate analysis resulting in 198 treatment means from 25 experiments since 1976. Three sets of equations were used to compute empty body chemical composition assuming empty body water was known: 1) Garrett and Hinman (1969; 10.2527/jas1969.2811), 2) Gil et al. (1970: 10.2527/jas1970.313459x), and 3) Ferrell et al. (1976; 10.2527/jas1976.4251158x). Mean (SD) empty body water, fat and protein were 59.91 (6.32), 17.58 (7.89), and 18.24 (2.02) % of EBW, respectively. For all equations, simultaneous testing of intercept equal to zero and slope equal to 1 indicated that the intercept and slope for fat, protein, ash and energy were different than zero and one, respectively. The concordance correlation coefficient (CCC) was high (&amp;gt; 0.85) for fat and energy, but low (&amp;lt; 0.50) for protein and ash for all equations. Mean bias for fat, protein, ash, and energy ranged from -19.58 to -3.50%, 1.62 to 15.84%, -2.22 to 14.15%, and -6.09 to -0.63%, respectively, with Eq. 1 having the MB closest to 0 for protein, and Eq. 3 having the MB closest to 0 for fat, ash, and energy. Publication year as a continuous variable was a significant predictor of the difference between observed and predicted values for all components. Fat and energy had greater overpredicted whereas, protein and ash had greater underprediction in more recent publications. In conclusion, existing equations provide similar precision, but differ in accuracy to predict empty body chemical composition. The trend for greater bias in more recent publication years indicates the need to reevaluate relationships among empty body chemical components using current cattle genetics.

216 Assessment of Equations Relating Carcass with Empty Body Chemical Components in Growing/Finishing Cattle

Abstract Existing equations to estimate empty body chemical composition from carcass chemical composition developed over 40 years ago using different cattle genetics. The objective of this analysis was to evaluate existing equations using cattle genetics from then to today. A literature search was performed to identify experiments measuring carcass and offal chemical composition by proximate analysis resulting in 88 treatment means from 11 experiments since 1982. Two sets of equations 1) Garrett and Hinman (1969; 10.2527/jas1969.2811) and 2) Ferrell et al. (1976; 10.2527/jas1976.4251158x) were used to compute empty body chemical components from carcass chemical components. Mean (SD) carcass fat and protein were 18.86 (8.37) and 18.18 (2.94) % of HCW, respectively, and empty body fat and protein were 18.25 (7.85) and 18.69 (2.32) % of EBW, respectively. Carcass chemical components were strongly correlated (≥ 0.98) with empty body chemical components. For Eq. 1, simultaneous testing of intercept equal to 0 and slope equal to 1 indicated that the intercept and slope for water, fat, ash, and energy were different than 0 and 1, but were not different for protein, whereas the intercept and slope were different for all components when using Eq. 2. Mean bias for chemical components ranged from -2.43 to 7.94% for Eq. 1, and -2.41 to 3.56% for Eq. 2. The mean bias was closer to 0 for water, fat and energy when using Eq. 2, but were closer to 0 for protein and ash when using Eq. 1. Offal chemical composition was a significant (P &amp;lt; 0.05) predictor of the difference between observed and predicted empty body components. Publication year was a significant (P &amp;lt; 0.05) predictor of the difference for protein and ash using either set of equations. In conclusion, both sets of equations were highly precise for all chemical components, and moderately to highly accurate, although later publication years had greater overprediction for protein.

Estimation of empty body and carcass chemical composition of lactating and growing cattle: comparison of imaging, adipose cellularity, and rib dissection methods.

The aim of present study was to compare in vivo and post mortem methods for estimating the empty body (EB) and carcass chemical compositions of Simmental lactating and growing cattle. Indirect methods were calibrated against the direct post mortem reference determination of chemical compositions of EB and carcass, determined after grinding and analyzing the water, lipid, protein, mineral masses, and energy content. The indirect methods applied to 12 lactating cows and 10 of their offspring were ultrasound (US), half-carcass and 11th rib dual-energy X-ray absorptiometry (DXA) scans, subcutaneous and perirenal adipose cell size (ACS), and dissection of the 11th rib. Additionally, three-dimensional (3D) images were captured for 8 cows. Multiple linear regressions with leave-one-out-cross-validations were tested between predictive variables derived from the methods tested, and the EB and carcass chemical compositions. Partial least square regressions were used to estimate body composition with morphological traits measured on 3D images. Body weight (BW) alone estimated the EB and carcass composition masses with a root mean squared error of prediction (RMSEP) for the EB from 1 kg for minerals to 12.4 kg for lipids, and for carcass from 0.9 kg for minerals to 7.8 kg for water. Subcutaneous adipose tissue thickness measured by US was the most accurate in vivo predictor when associated with BW to estimate chemical composition, with the EB lipid mass RMSEP = 11 kg and R2 = 0.75; carcass water mass RMSEP = 6 kg and R2 = 0.98; and carcass energy content RMSEP = 236 MJ and R2 = 0.91. Post mortem, carcass lipid mass was best estimated by half-carcass DXA scan (RMSEP = 2 kg, R2 = 0.98), 11th rib DXA scan (RMSEP = 3 kg, R2 = 0.96), 11th rib dissection (RMSEP = 4 kg, R2 = 0.92), and perirenal ACS (RMSEP = 6 kg, R2 = 0.79) in this respective order. The results obtained by 11th rib DXA scan were accurate and close to the half-carcass DXA scan with a reduction in scan time. Morphological traits from 3D images delivered promising estimations of the cow EB and carcass chemical component masses with an error less than 13 kg for the EB lipid mass and than 740 MJ for the EB energy. Future research is required to test the 3D imaging method on a larger number of animals to confirm and quantify its interest in estimating body composition in living animals.

Empty body chemical composition of Nellore steers estimated by indirect methods

Thirty-six Nellore steers at 20 months of age on average and initial body weight of 360 kg were fed ad libitum for 78 days and two levels of feed restriction for 58 days and posterior ad libitum feeding for 78 days were used to estimate body composition using the methods of indirect deuterium oxide or the 9th-10th-11th ribs cut. The body water content was calculated with equations established for Nellore steers. The chemical body composition was different for the ether extract content. The animals subjected to feed restriction presented higher body fat content when estimated by deuterium than by the rib cut. The deuterium oxide or 9th-10th-11th ribs cut methods used for body composition determination were effective to estimate body contents for animals fed ad libitum, however, not for animals on feed restriction. Comparatively, the indirect method of deuterium oxide was better than the 9th-10th-11th ribs cut method to estimate body composition in Nellore steers submitted to feed restriction; however, both methods were similar in animals fed ad libitum.

223 Evaluation of dietary characteristics and empty body chemical components affecting the relationship between heat production and metabolizable energy intake in growing beef cattle

Abstract Metabolizable energy required for maintenance varies with diet and empty body chemical composition. The objective was to quantify the relationships of dietary characteristics and empty body chemical composition with heat production. A literature search was performed to compile data (31 studies, 214 treatment means) on metabolizable energy intake (MEI) and composition of empty body gain in growing steers and heifers. Data analysis were performed using R statistical package for mixed models with study as random variable. Nonlinear regression of energy gain (EG) on MEI indicated the relationship was not curvilinear in this data set, likely due to lack of negative values of EG. Further analyses were conducted using a linear model. Dietary characteristics of roughage level (0–100% of diet DM) and CP (10–25% diet DM), metabolizable energy concentration (1.3–3.3 Mcal/kg DM), and roughage type were evaluated in the model. Roughage sources were categorized into no roughage, silage, hay, pellets, silage + pellets, and hay + pellets. Of the empty body chemical components, proportion of fat in the empty body (EBFp) and in the gain (EBFgp) had a significant (P &amp;lt; 0.001) interaction with MEI on HP. Of the dietary characteristics, roughage level and type had a significant (P &amp;lt; 0.001) interaction with MEI on HP; however, when both were included in the model, roughage type was not significant (P &amp;gt; 0.10). The final model was 47.01 ± 12.54 + 0.630 ± 0.05*MEI – 132.3 ± 64.7*EBFp + 0.0007 ± 0.0001*MEI*Roughage level + 0.753 ± 0.24*MEI*EBFp – 0.268 ± 0.032*MEI*EBFgp with an R2 of 0.919 and an AIC of 1614 compared with 0.867 and 1695 for the simple linear regression model of HP on MEI. In conclusion, greater empty body fat decreased the intercept, and greater empty body fat proportion and levels of roughage in the diet increased the slope between HP and MEI, whereas greater percentage of fat in the empty body gain decreased the slope between HP and MEI.

Nutrient requirements and evaluation of equations to predict chemical body composition of dairy crossbred steers.

ObjectiveObjectives were to estimate energy and protein requirements of dairy crossbred steers, as well as to evaluate equations previously described in the literature (HH46 and CS16) to predict the carcass and empty body chemical composition of crossbred dairy cattle.MethodsThirty-three Holstein×Zebu steers, aged 19±1 months old, with an initial shrunk body weight (BW) of 324±7.7 kg, were randomly divided into three groups: reference group (n = 5), maintenance level (1.17% BW; n = 4), and the remaining 24 steers were randomly allocated to 1 of 4 treatments. Treatments were: intake restricted to 85% of ad libitum feed intake for either 0, 28, 42, or 84 d of an 84-d finishing period.ResultsThe net energy and the metabolizable protein requirements for maintenance were 0.083 Mcal/EBW0.75/d and 4.40 g/EBW0.75, respectively. The net energy (NEG) and protein (NPG) requirements for growth can be estimated with the following equations: NEG (Mcal/kg EBG) = 0.2973(±0.1212) ×EBW0.4336(±0.1002) and NPG (g/d) = 183.6(±22.5333)×EBG−2.0693(±4.7254)×RE, where EBW, empty BW; EBG, empty body gain; and RE, retained energy. Crude protein (CP) and ether extract (EE) chemical contents in carcass, and all the chemical components in the empty body were precisely and accurately estimated by CS16 equations. However, water content in carcass was better predicted by HH46 equation.ConclusionThe equations proposed in this study can be used for estimating the energy and protein requirements of crossbred dairy steers. The CS16 equations were the best estimator for CP and EE chemical contents in carcass, and all chemical components in the empty body of crossbred dairy steers, whereas water in carcass was better estimated using the HH46 equations.

In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle.

Evaluation of the body chemical composition of beef cattle can only be measured postmortem and those data cannot be used in real production scenarios to adjust nutritional plans. The objective of this study was to develop multiple linear regression equations from in vivo measurements, such as ultrasound parameters [backfat thickness (uBFT, mm), rump fat thickness (uRF, mm), and ribeye area (uLMA, cm2)], shrunk body weight (SBW, kg), age (AG, d), hip height (HH, m), as well as from postmortem measurements (composition of the 9th to 11th rib section) to predict the empty body and carcass chemical composition for Nellore cattle. Thirty-three young bulls were used (339 ± 36.15 kg and 448 ± 17.78 d for initial weight and age, respectively). Empty body chemical composition (protein, fat, water, and ash in kg) was obtained by combining noncarcass and carcass components. Data were analyzed using the PROC REG procedure of SAS software. Mallows' Cp values were close to the ideal value of number of independent variables in the prediction equations plus one. Equations to predict chemical components of both empty body and carcass using in vivo measurements presented higher R2 values than those determined by postmortem measurements. Chemical composition of the empty body using in vivo measurements was predicted with R2 > 0.73. Equations to predict chemical composition of the carcass from in vivo measurements showed R2 lower (R2< 0.68) than observed for empty body, except for the water (R2 = 0.84). The independent variables SBW, uRF, and AG were sufficient to predict the fat, water, energy components of the empty body, whereas for estimation of protein content the uRF, HH, and SBW were satisfactory. For the calculation of the ash, the SBW variable in the equation was sufficient. Chemical compounds from components of the empty body of Nellore cattle can be calculated by the following equations: protein (kg) = 47.92 + 0.18 × SBW - 1.46 × uRF - 30.72 × HH (R2 = 0.94, RMSPE = 1.79); fat (kg) = 11.33 + 0.16 × SBW + 2.09 × uRF - 0.06 × AG (R2 = 0.74, RMSPE = 4.18); water (kg) = - 34.00 + 0.55 × SBW + 0.10 × AG - 2.34 × uRF (R2 = 0.96, RMSPE = 5.47). In conclusion, the coefficients of determination (for determining the chemical composition of the empty body) of the equations derived from in vivo measures were higher than those of the equations obtained from rib section measurements taken postmortem, and better than coefficients of determination of the equations to predict the chemical composition of the carcass.

Assessment of body fat composition in crossbred Angus × Nellore using biometric measurements.

This study was conducted to assess the body and empty body fat physical and chemical composition through biometric measurements (BM) as well as postmortem measurements taken in 40 F Angus × Nellore bulls and steers. The animals used were 12.5 ± 0.51 mo of age, with an average shrunk BW of 233 ± 23.5 and 238 ± 24.6 kg for bulls and steers, respectively. Animals were fed 60:40 ratio of corn silage to concentrate diets. Eight animals (4 bulls and 4 steers) were slaughtered at the beginning of the trial, and the remaining animals were randomly assigned to a 1 + 2 × 3 factorial arrangement (1 reference group, 2 sexes, and 3 slaughter weights). The remaining animals were slaughtered when the average BW of the group reached 380 ± 19.5 (6 bulls and 5 steers), 440 ± 19.2 (6 bulls and 5 steers), and 500 ± 19.5 kg (5 bulls and 5 steers). Before the slaughter, the animals were led through a squeeze chute in which BM were taken, including hook bone width (HBW), pin bone width, abdomen width (AW), body length (BL), rump height, height at the withers, pelvic girdle length (PGL), rib depth (RD), girth circumference (GC), rump depth, body diagonal length (BDL), and thorax width. Additionally, the following postmortem measurements were obtained: total body surface (TBS), body volume (BV), subcutaneous fat (SF), internal physical fat (InF), intermuscular fat, carcass physical fat (CF), empty body physically separable fat (EBF), carcass chemical fat (CFch), empty body chemical fat (EBFch), fat thickness in the 12th rib, and 9th to 11th rib section fat. The equations were developed using a stepwise procedure to select the variables that should enter into the model. The and root mean square error (RMSE) were used to account for precision and accuracy. The ranges for and RMSE were 0.852 to 0.946 and 0.0625 to 0.103 m, respectively for TBS; 0.942 to 0.998 and 0.004 to 0.022 m, respectively, for BV; 0.767 to 0.967 and 2.70 to 3.24 kg, respectively, for SF; 0.816 to 0.900 and 3.04 to 4.12 kg, respectively, for InF; 0.830 to 0.988 and 3.44 to 8.39 kg, respectively, for CF; 0.861 to 0.998 and 1.51 to 10.98 kg, respectively, for EBF; 0.825 to 0.985 and 5.96 to 8.46 kg, respectively, for CFch; and 0.862 to 0.992 and 5.54 to 12.19 kg, respectively, for EBFch. Our results indicated that BM that could accurately and precisely be used as alternatives to predict different fat depots of F Angus × Nellore bulls and steers are AW, GC, or PGL for CF estimation; HBW and RD for CFch estimation; and body lengths such as BL and BDL for InF and SF estimation, respectively.

Ewe whole body composition predicted in vivo by real-time ultrasonography and image analysis

The relationship between ultrasound measurements and the empty body chemical composition of mature ewes was studied in two breeds. The breeds were a milk-producing breed Churra da Terra Quente—CTQ (n=33; live weight 42.0±7.3kg, mean±SD), and a meat breed Ile de France—IF (n=23; live weight 60.7±9.1kg, mean±SD). Fat and muscle depths were measured in the live animals by real-time ultrasound scanning (RTU; 7.5MHz probe) over the 13th thoracic, and between the 3rd and 4th lumbar vertebrae, and total tissue depth over the 11th rib. Following slaughter, the carcass and non-carcass components of the empty body were combined and subjected to chemical analysis and assessment of energy value. Data obtained by RTU after image analysis was used to develop simple and multiple regression models for each breed. The traits most accurately estimated from single RTU measurements were the absolute values for fat content and energy value of the empty body. The respective coefficients of determination (R2) for IF and CTQ ewes using subcutaneous fat depth over the 13th thoracic vertebra were 0.768 and 0.908 for fat, 0.821 and 0.900 for energy; and for measurements between the 3rd and 4th lumbar vertebrae were 0.845 and 0.911 for fat, 0.852 and 0.906 for energy. All these coefficients were significant (P<0.01). The best prediction models included one to three RTU measurements and were better for CTQ ewes, where adjusted R2 values ranged from 0.923 (P<0.001) for water to 0.969 (P<0.001) for protein, than for IF ewes, where the range was 0.394 (P<0.01) for protein to 0.940 (P<0.001) for fat. The results revealed good estimates of the fat and energy content of the empty body of both breeds and also good estimates of protein content for CTQ ewes, but poor estimates of protein content for IF ewes, with the best prediction models for each body component being different from each breed. Consequently, it is concluded that predictive models that are specific to the breed and circumstances of the study in which they are to be used will have to be established to have a practical application.

Evaluation of predictive equations developed to assess body composition of F1 Nellore × Angus bulls and steers

We evaluated and compared empirical equations used for assessing beef cattle body composition, developed in 2010 (M10), 2012 (M12), 2006 (V06) and 1946 (HH46). Forty-eight F1 Nellore × Angus bulls and steers, aged 12.5 ± 0.51 months old, with initial shrunk bodyweight of 233 ± 23.5 kg and 238 ± 24.6 kg, respectively, were used in this experiment. The trial was a randomised factorial arrangement of treatments (two genders and five slaughter weights). The animals were randomly assigned to five slaughter-weight-based groups: baseline, maintenance, and 380, 440 and 500 kg. The diet comprised maize silage and concentrate (60 : 40). After slaughter, the 9th–11th rib section cut was dissected into muscle, fat and bone. The remaining carcass was similarly dissected. Other variables evaluated as partial predictors of body composition included empty bodyweight, dressing percentage, visceral fat percentage, and organ and viscera percentage. The values estimated with predictive equations were compared with observed values. For the physically separable carcass composition, only the M12 equation estimated precisely and accurately the amount of muscle (r2 = 0.98, root-mean-square error (RMSE) = 5.64 kg, concordance correlation coefficient (CCC) = 0.96) and fat (r2 = 0.94, RMSE = 4.91 kg, CCC = 0.96) tissue present in the carcass. The V06 and M10 equations estimated precisely and accurately the amount of carcass chemical components; HH46 could explain only the amount of crude protein (r2 = 0.84, RMSE = 4.71 kg, CCC = 0.90) content in the carcass. The equations used to predict empty body chemical composition failed to estimate correctly the amount of chemical contents present in the empty bodyweight. However, V06 can be used to estimate the crude protein (r2 = 0.91, RMSE = 5.97 kg, CCC = 0.93) content in the empty bodyweight. Furthermore, M10 could be used to estimate ether extract (r2 = 0.94, RMSE = 8.13 kg, CCC = 0.84) content, although this had to be analysed by gender, because such variables (i.e. ether extract) presented a pronounced effect, especially for steers, on total chemical fat.

Consumo, avaliação do modelo Small Ruminant Nutrition System e predição da composição corporal de cordeiros Santa Inês alimentados com rações contendo diferentes níveis de energia

The objective of this study was to evaluate the nutrient intake and suitability test of the SRNS nutritional model for dry matter intake (DMI) and average daily gain (ADG), and Hankins and Howe equations to estimate the carcass and empty body chemical composition of 35 Santa Ines lambs, non-castrated, with initial body weight of 14.77 ± 1.26 kg and two months old. After 10 days of adaptation, five animals were slaughtered serving as reference group for estimates of empty body weight (EBW) and initial body composition. The remaining animals were distributed in randomized block design with five treatments with different levels of metabolizable energy (1.13, 1.40, 1.73, 2.22 and 2.60 Mcal/kg DM). Quadratic effect was observed for DMI, expressed in g/d, % BW and g/BW0.75, with maximum DM intake of 867.25 g/d. Non fiber carbohydrates (NFC) and total digestible nutrients (TDN) intakes, expressed in g/d, increased with increases in ME levels and the intakes of neutral detergent fiber (NDF), acid detergent fiber (ADF) and fibrous carbohydrates (FC), expressed in g/d, presented decreasing linear effect. The DMI and ADG observed and predicted by SRNS model showed a Pearson correlation coefficient of 0.68 and 0.98, respectively. Comparing the chemical composition of the carcass and HH section, observed that HH section estimated satisfactorily the protein and ether extract of carcass of animals, with Pearson correlation coefficient of 0.77 and 0.92, respectively, while the water content was underestimated with Pearson correlation coefficient of 0.42. The rib section also satisfactorily estimated to ether extract and protein in the empty body (r = 0.96 and 0.86, respectively).

Body chemical composition, tissue deposition rates and gain composition of young Nellore cattle selected for postweaning weight

Empty body and carcass chemical composition were determined in 67 Nellore bulls from Selection Nellore (NeS) and Control Nellore (NeC) herds of an animal breeding program for growth, slaughtered at 570 days of average age, after 100 days of feedlot. Selection Nellore animals had, respectively, 360 and 430 kg of initial and slaughter body weight, and NeC animals had 318 and 373 kg for the same traits. Animals were slaughtered and empty body composition was determined by chemical analysis of the components blood, hide, head and feet, viscera and carcass. Tissue deposition rates and gain chemical composition were also determined based on gains estimated by comparative slaughter technique. Significant differences were detected between NeS and NeC animals for slaughter body weight, empty body weight, empty body gain rate, and contents of water, protein, ash and retained energy in empty body, showing that selected animals had greater body sizes and growth rates. There were no significant differences in fat contents in empty body and carcass, suggesting that selected animals had higher growth rates as compared with the control, and were slaughtered with good body and carcass fat contents in the same feedlot time. Control Nellore animals showed a 10% higher gain in fat percentage than NeS in the period. This shows that the growth of bone and muscle ceased earlier and NeC group accumulated more fat. Animals selected for growth have heavier carcasses and greater tissue deposition rates with proportional composition similar to unselected animals.

Body chemical composition of Nellore bulls with different residual feed intakes1

Empty body and carcass chemical compositions, expressed as content of water, ether extract, protein, minerals, and energy, were evaluated in Nellore bulls with different residual feed intakes (RFI). Forty-nine not castrated males, with 343 kg of average initial BW and 398 kg of average slaughter BW, were studied. Animals were divided in two subgroups: reference group (RG) and ad libitum feeding group. At the end of the adaptation period, animals of subgroup RG were slaughtered and the other animals were finished in individual pens for approximately 100 d, until they reached a subcutaneous fat thickness over the LM of 4 mm, and were slaughtered at an average age of 540 d. Body composition was obtained after grinding, homogenizing, sampling, analyzing, and combining blood, hide, head + feet, viscera, and carcass. Tissue deposition rates and chemical composition of gain were also measured based on gains estimated by comparative slaughter technique. No significant differences in slaughter BW (P = 0.8639), empty BW (P = 0.7288), HCW (P = 0.6563), or empty body and carcass rates of gain were observed between RFI groups, demonstrating that the low (-0.331 kg DM/d) and high (+0.325 kg DM/d) RFI animals presented similar body sizes and growth rates. No significant differences in empty body or carcass content of water, ether extract, protein, minerals, and energy were observed between the low and high RFI animals. And also there were no significant differences in empty BW or carcass gain, demonstrating that low and high RFI animals had a similar growth potential. More efficient animals (low RFI) consumed less feed than less efficient animals (high RFI) but presented similar body sizes, growth rates, and empty body and carcass chemical composition.

Interspecies differences in the empty body chemical composition of domestic animals

Domestication of animals has resulted in phenotypic changes by means of natural and human-directed selection. Body composition is important for farm animals because it reflects the status of energy reserves. Thus, there is the possibility that farm animals as providers of food have been more affected by human-directed selection for body composition than laboratory animals. In this study, an analysis was conducted to determine what similarities and differences in body composition occur between farm and laboratory animals using literature data obtained from seven comparative slaughter studies (n = 136 observations). Farm animals from four species (cattle, goats, pigs and sheep) were all castrated males, whereas laboratory animals from three species (dogs, mice and rats) comprised males and/or females. All animals were fed ad libitum. The allometric equation, Y = aXb, was used to determine the influence of species on the accretion rates of chemical components (Y, kg) relative to the growth of the empty body, fat-free empty body or protein weights (X, kg). There were differences between farm and laboratory animals in terms of the allometric growth coefficients for chemical components relative to the empty BW and fat-free empty BW (P < 0.01); farm animals had more rapid accretion rates of fat (P < 0.01) but laboratory animals had more rapid accretion rates of protein, water and ash (P < 0.01). In contrast, there was no difference in terms of the allometric growth coefficients for protein and water within farm animals (P > 0.2). The allometric growth coefficients for ash weight relative to protein weight for six species except sheep were not different from a value of 1 (P > 0.1), whereas that of sheep was smaller than 1 (P < 0.01). When compared at the same fat content of the empty body, the rate of change in water content (%) per unit change in fat content (%) was not different (P > 0.05) across farm animal species and similar ash-to-protein ratios were obtained except for dogs. The fraction of empty body energy gain retained as fat increased in a curvilinear manner, and there was little variation among farm animals at the same fat content of the empty body. These findings may provide the opportunity to develop a general model to predict empty body composition across farm animal species. In contrast, there were considerable differences of chemical body composition between farm and laboratory animals.

Evaluation of equations to predict body composition in Nellore bulls

The equations developed by Hankins and Howe (1946, HH), Marcondes et al. (2010, M10), Marcondes et al. (in press, M11) and Valadares Filho et al. (2006, V6) were evaluated to predict the body composition from the 9–10–11th rib cut in Nellore bulls. The evaluated equations estimated the physical and the carcass chemical composition, the empty body chemical composition and the noncarcass chemical composition. Thirty-seven Nellore bulls (14±1 months old initially) with shrunk body weight of 259±24.9kg were used in this experiment. The bulls were randomly divided into three groups: five bulls to the reference group, four bulls were fed at maintenance level and twenty-eight bulls were fed ad libitum. The bulls fed ad libitum were separated into four groups, one of which was slaughtered every 42 days. The diet was composed of corn silage and concentrate (55:45). After slaughter, the 9–10–11th rib cut was dissected into muscle, fat and bone fractions. The remaining carcass was similarly dissected. The others parameters that were evaluated as partial predictors included the empty body weight, the dressing percentage, the visceral fat percentage, the organ and viscera percentage and the composition of the noncarcass components. The values estimated with prediction equations were compared to the observed values. The equations obtained by M11 predicted correctly the carcass physical composition. However, the muscle and fat tissues were under- and overestimated, respectively, by HH. Some constituents of the noncarcass components can be predicted from equations developed by M10. The equations obtained by M10 predicted correctly the carcass and empty body chemical composition. The carcass water was underestimated by HH. The equations by V6 did not predict the carcass or empty body chemical composition. The carcass physical and chemical composition and empty body chemical composition can be predicted from the composition of 9–10–11th rib cut by equations obtained by Marcondes et al. (2010, in press) while the composition of these components cannot be predicted by Hankins and Howe (1946) and Valadares Filho et al. (2006) in Nellore bulls.

Predicting the chemical composition of the body and the carcass of 3/4Boer × 1/4Saanen kids using body components

The determination of the chemical composition of body and carcass is important in nutritional and growth regulation studies. The purpose of this study was to develop equations to predict the chemical composition of body and carcass using chemical composition of body components. Twenty 3/4Boer × 1/4Saanen crossbred male kids, weighing from 20 to 35 kg, were used in this study. The empty body chemical composition was measured by grinding all body components and sampling for chemical analyses. The body components used to estimate body and carcass composition were: neck, fore leg, ribs, loin, hind leg, 9–11th rib section, non-carcass components (head plus feet, organs plus blood, and hide), visceral fat, and kidney fat. The chemical composition of organs plus blood and 9–11th rib section had the highest precision to estimate percentage of fat, protein, and water in the body ( r 2 of 0.94, 0.82, and 0.90, respectively). For carcass composition, the chemical composition of ribs was the best component to predict all carcass chemical components; however, the equations to estimate the percentages of protein and ash showed a low precision ( r 2 = 0.48, 0.44, respectively). The 9–11th rib section was accurate and precise to estimate carcass fat percentage. We concluded the chemical composition of the body of 3/4Boer × 1/4Saanen crossbred male kids was highly correlated with the composition of body parts, specifically organs plus blood and 9–11th rib section. Further studies should focus on evaluating these body parts for different breeds and genders under different production scenarios.

Estimation in vivo of the body and carcass chemical composition of growing lambs by real-time ultrasonography1

The relationship between ultrasound measurements and empty body and carcass chemical composition was investigated. A 500-V real-time ultrasound with a 7.5-MHz probe combined with image analysis was used to make in vivo measurements to predict the empty body and carcass chemical composition of 31 female lambs of two genotypes, ranging in BW from 18.2 to 48.9 kg. Eleven ultrasound measurements of s.c. fat, muscle, and tissue depth were taken at four different sites (over the 13th thoracic vertebra, between the 3rd and 4th lumbar vertebrae, at the 3rd sternebra of the sternum, and over the 11th rib, 16 cm from the dorsal midline). The single best predictor of empty body fat quantity and energy value was the s.c. fat depth over the 13th thoracic vertebra (r(2) = 0.904 and 0.912; P <0.01, respectively). Body weight was used with ultrasound measurements in multiple regression equations to establish the best independent variables combination for predicting chemical composition. Results showed that BW and two of the three ultrasound measurements (s.c. fat depth over the 13th thoracic vertebra, between the 3rd and 4th lumbar vertebrae, and tissue depth over the 11th rib, 16 cm from the dorsal midline), explained 94.7 to 98.7% (P < 0.01) of the quantity of water and fat and the energy value variation in the empty body and carcass. Body weight per se was the best predictor of the quantity of protein, accounting for 97.5 and 96.8% (P < 0.01) of the variation observed in the empty body and carcass, respectively. The results of this study suggest that BW and some ultrasound measurements combined with image analysis, particularly subcutaneous fat depth over the 13th thoracic vertebra, allow accurate prediction of empty body and carcass chemical composition in lambs.

Validação das equações desenvolvidas por Hankins e Howe para predição da composição da carcaça de zebuínos e desenvolvimento de equações para estimativa da composição corporal

Validaram-se as equações desenvolvidas por Hankins e Howe (1946) para fins de predição da composição física e química da carcaça e desenvolveram-se equações a partir de corte da costela para se estimar a composição química do corpo vazio. Foram utilizados 19 novilhos anelorados, com peso vivo médio inicial de 270 kg e 24 meses de idade, castrados - quatro pertencentes ao grupo referência, três ao grupo mantença e 12 distribuídos uniformemente em três grupos, com diferentes níveis de concentrado na dieta (5, 35 e 65% na base da matéria seca total). Como volumoso, foi utilizado pré-secado de capim-braquiária (Brachiaria brizantha) e de capim-tifton 85 (Cynodon sp.). As dietas foram isoprotéicas e os alimentos foram fornecidos permitindo-se cerca de 5% de sobras. Os animais do grupo mantença e dos tratamentos com 5, 35 e 65% de concentrado foram alimentados por um período de, respectivamente, 84, 109, 104 e 102 dias, após o qual foram abatidos, apresentando peso vivo médio de 340,25; 360,55 e 374,50 kg, respectivamente. Após o abate, procedeu-se à dissecação completa da carcaça direita e do corte das 9-10-11ª costelas, retirado da carcaça esquerda. O corte das 9-10-11ª costelas estimou satisfatoriamente a composição física da carcaça dos animais e estimou adequadamente os conteúdos de proteína, água e minerais da carcaça, enquanto o teor de extrato etéreo foi superestimado em 7,8%. Foi desenvolvida uma equação para estimar a porcentagem de extrato etéreo na carcaça a partir da porcentagem desse componente no corte das 9-10-11ª costelas: % EE na carcaça = 1,0709 + 0,7854 * % EE no corte das 9-10-11ª costelas, r² = 0,97. A composição química do corpo vazio pode ser estimada satisfatoriamente a partir da composição química do corte das 9-10-11ª costelas, entretanto, mais informações devem ser geradas para que se possa obter equações mais abrangentes e aplicáveis de forma confiável.