Ruiz-Ramos Jorge, Torres-Chable Oswaldo M, Peralta-Torres Jorge A, Ojeda-Robertos Nadia F, Luna-Palomera Carlos, Portillo-Salgado Rodrigo, Tyasi Thobela Louis, Gurgel Antonio Leandro Chaves, Ítavo Luís Carlos Vinhas, Chay-Canul Alfonso J
División Académica de Ciencias Agropecuarias, Universidad Juárez Autónoma de Tabasco, Villahermosa, Tabasco, México.
Department of Agricultural Economics and Animal Production, University of Limpopo, Limpopo, South Africa.
Trop Anim Health Prod. 2023 Mar 30;55(2):137. doi: 10.1007/s11250-023-03549-9.
Buffalo farming is an important livestock activity in Mexico. However, the low technological level of the farms makes it difficult to monitor the growth rates of the animals. The objectives of this study were to analyse the body measurements of 107 adult female Murrah buffaloes, to estimate the interrelationships between those measurements and body weight, and to develop equations to predict body weight (BW) using body measurements including withers at height (WH), rump height (RH), body height (BH), heart girth (HG), abdominal girth (AG), pelvic girth (PG), body length (BL), girth circumference (GC), diagonal body length (DBL), pelvic circumference (PC), and abdomen circumference (AC). The study was conducted on two commercial farms in southern Mexico. Pearson correlation and stepwise regression techniques were used for the data analysis. To find out the best regression models, we used model quality criteria such as coefficient of determination (R), adjusted R (Adj.R), root mean square error (RMSE), Mallow's Cp, Akaike's information criteria (AIC), Bayesian information criteria (BIC), and coefficient of variation (CV). Correlation results indicated that BW had a positive high correlation (P < 0.01) of all the measured traits. Model 4 (-780.56 + 311.76GC + 383.51DBL + 51.82PC + 47.65AC-106.78BL) was the best regression model with a higher R (0.87), Adj. R (0.86) smaller Cp (4.24), AIC (749.19), BIC (752.16), and RMSE (36.91). The current study suggests that GC, DBL, PC, AC, and BL might be used in combination to estimate BW of adult female Murrah buffaloes.
水牛养殖是墨西哥一项重要的畜牧活动。然而,养殖场的技术水平较低,难以监测动物的生长速度。本研究的目的是分析107头成年雌性摩拉水牛的体尺,估计这些体尺与体重之间的相互关系,并建立利用体尺预测体重(BW)的方程,这些体尺包括鬐甲高(WH)、臀高(RH)、体高(BH)、胸围(HG)、腹围(AG)、骨盆围(PG)、体长(BL)、围周长(GC)、体斜长(DBL)、骨盆周长(PC)和腹围(AC)。该研究在墨西哥南部的两个商业养殖场进行。数据分析采用Pearson相关性和逐步回归技术。为了找出最佳回归模型,我们使用了模型质量标准,如决定系数(R)、调整后的R(Adj.R)、均方根误差(RMSE)、马洛斯Cp统计量、赤池信息准则(AIC)、贝叶斯信息准则(BIC)和变异系数(CV)。相关性结果表明,BW与所有测量性状均呈高度正相关(P < 0.01)。模型4(-780.56 + 311.76GC + 383.51DBL + 51.82PC + 47.65AC - 106.78BL)是最佳回归模型,其R值较高(0.87),Adj. R值为(0.86),Cp值较小(4.24),AIC值为(749.19),BIC值为(752.16),RMSE值为(36.91)。当前研究表明,GC、DBL、PC、AC和BL可联合用于估计成年雌性摩拉水牛的BW。