title: Determination of carcass and body fat compositions of grazing crossbred bulls using body measurements.
abstract: The objectives of this study were to analyze body measurements of 40 crossbred bulls grazing low quality forage with different supplementation strategies, to estimate interrelationships among those measurements and carcass and body compositions, and to develop systems of equations to predict body fat using body and carcass measurements. Eight animals were slaughtered at the beginning of the experiment, and the remaining animals were slaughtered at 90 or 220 d. The biometric measures (BM) were obtained the day before the slaughter and included hook width, pin width, pelvic girdle length, rump depth, rump height, abdomen width, body length, height at withers, rib depth, girth, and body diagonal length. Other measurements included full, shrunk, and empty BW; internal physical and chemical fats; body volume; body area; carcass weight; 9th- to 11th-rib section weight and composition; fat thickness; subcutaneous fat; intermuscular fat; carcass chemical fat; and empty body physical and chemical fats. The relationships between BM and body components were evaluated, and equations to predict body area, body volume, subcutaneous fat, and carcass and body physical and chemical fat were developed. Biological interpretations of the parameter estimates of equations were similar to those found in the literature such as a ratio of 1 kg of subcutaneous fat to 1.6 kg of intermuscular fat and a deposit of 72 to 76% of body fat in the carcass. The first system used to predict carcass and empty body physical and chemical fat was devised using in vivo information, whereas the second system used BW and the 9th- to 11th-rib fat weight. Our results indicated the combination of BW, carcass traits, and BM was precise and accurate in estimating carcass and body fat composition of backgrounding bulls. The second system had better adequacy statistics [r(2) > 0.92, concordance correlation coefficient (CCC) > 0.957, and root mean square error (RMSE) < 14.4% of the average observed value] compared with the first system. The first system had acceptable adequacy statistics (r(2) > 0.767, CCC > 0.866, and RMSE varying from 15.8 to 22.3% of the average observed value). For both systems, the simultaneous F-test of the linear regression of observed on model-predicted values indicated intercepts were equal to zero, and slopes were equal to 1 (P > 0.246). We concluded that BM can improve the accuracy and precision of the predictions of body composition of grazing animals.
authors.affiliation: State University of Mato Grosso do Sul, Aquidauana, Mato Grosso do Sul, Brazil 79200-000. henrique@uems.br
authors.forename: H J
authors.initials: HJ
authors.lastname: Fernandes
authors.forename: L O
authors.initials: LO
authors.lastname: Tedeschi
authors.forename: M F
authors.initials: MF
authors.lastname: Paulino
authors.forename: L M
authors.initials: LM
authors.lastname: Paiva
mesh_terms: D000273:Adipose Tissue / Q000033:anatomy & histology*; D000821:Animal Feed; D000822:Animal Husbandry; D000818:Animals; D001823:Body Composition / Q000502:physiology; D001835:Body Weight; D002417:Cattle / Q000033:anatomy & histology* / Q000502:physiology; D008297:Male; D008460:Meat / Q000592:standards; D012016:Reference Values