| Autor: |
Castilhos AM; Department of Breeding and Animal Nutrition, São Paulo State University (UNESP), School of Veterinary Medicine and Animal Science (FMVZ), Botucatu, SP, Brazil., Francisco CL; Department of Animal Production, São Paulo State University (UNESP), School of Veterinary Medicine and Animal Science (FMVZ), Botucatu, SP, Brazil., Branco RH; Centro APTA Bovinos de Corte - Instituto de Zootecnia - Secretaria de Agricultura e Abastecimento do Estado de São Paulo, Sertãozinho, SP, Brazil., Bonilha SFM; Centro APTA Bovinos de Corte - Instituto de Zootecnia - Secretaria de Agricultura e Abastecimento do Estado de São Paulo, Sertãozinho, SP, Brazil., Mercadante MEZ; Centro APTA Bovinos de Corte - Instituto de Zootecnia - Secretaria de Agricultura e Abastecimento do Estado de São Paulo, Sertãozinho, SP, Brazil., Meirelles PRL; Department of Breeding and Animal Nutrition, São Paulo State University (UNESP), School of Veterinary Medicine and Animal Science (FMVZ), Botucatu, SP, Brazil., Pariz CM; Department of Breeding and Animal Nutrition, São Paulo State University (UNESP), School of Veterinary Medicine and Animal Science (FMVZ), Botucatu, SP, Brazil., Jorge AM; Department of Animal Production, São Paulo State University (UNESP), School of Veterinary Medicine and Animal Science (FMVZ), Botucatu, SP, Brazil. |
| Abstrakt: |
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. |
