EQUATIONS FOR BODY WEIGHT ADJUSTMENTS IN BLACK BELLY EWE LAMBS

Q3 Agricultural and Biological Sciences
Samuel Vázquez-Jiménez, Daniel Vidal-Ramírez, R. Salazar-Cuytun, Ignacio Vázquez-Martínez, Enrique Camacho-Pérez, Antonio Leandro Chaves Gurgel, G. Muñoz-Osorio, A. J. Chay Canul
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引用次数: 0

Abstract

Background. As body weight (BW) is rarely determined on fasted animals in most production systems, the need to develop accurate mathematical models for adjusting BW has been identified. Objective. To evaluate models for estimating shrunk body weight (SBW) and empty body weight (EBW) in Black Belly growing ewe lambs raised in tropical conditions. Methodology. Data of sixty Black Belly ewe lambs, between four to eight months of age with a mean BW of 26.55± 3.92 kg (± SD) were used. The SBW was estimated based on the BW without fasting (fed) and the EBW based on SBW through three models: 1. Linear; 2.-Linear without intercept and 3.- Exponential. The predictive capacity of the models was evaluated by cross-validation. Results. The correlation coefficients between BW and SBW and SB and EBW were high (r = 0.94; <0.0001). The coefficients of determination (r2) for the equations between BW and SBW were 0.89 (P<0.001); and 0.86 (P<0.001) for the relationship between SBW and EBW. Based on the AIC (26.81) Eq. 2 described the relationship between BW and SBW better than Eq. 1, (AIC = 28.44) and Eq. 3 (AIC =28.35). The final model to estimate SBW as a function of BW was: SBW (kg): 0.96 (±0.001***) × BW. With respect to the SBW and EBW ratio, Equation 5, was better than the linear Eq. 4, (AIC = 33.01) and Eq. 6 (AIC = 33.35). The following model was: EBW (kg): 0.81 (± 0.06***) × SBW. The cross-validation of the equation of the relationship between BW and SBW showed that Eq. 1 had a higher r2 (0.87), and lower RMSEP and MAE than Eq. 2 and Eq. 3. Also, the equation of the relationship between SBW and EBW the cross-validation revealed that Eqs. 4 and 6 had the higher r2 (0.82), and lower RMSEP and MAE and tended to be more accurate than Eq. 5. Implications. The results obtained in present study contributes to the development of mathematical models for more accurate body weight adjustments in tropical sheep. Conclusion. The equations developed and evaluated in the present study revealed that the linear relationship between BW and SBW, and the linear and exponential relationship between SBW and EBW can be used to body weight adjustments in growing Black Belly ewe lambs. It's worth noting that this confirms that the SBW can be calculated using an adjustment factor of 0.96 FBW.
黑腹母羊羔羊体重调整方程
背景。由于在大多数生产系统中很少对空腹动物的体重(BW)进行测定,因此需要开发精确的数学模型来调整体重。目的评估在热带条件下饲养的黑腹生长母羔羊的收缩体重(SBW)和空腹体重(EBW)估算模型。方法。使用 60 只黑腹生长母羔羊的数据,这些羔羊年龄在 4 到 8 个月之间,平均体重为 26.55± 3.92 千克(± SD)。根据未禁食(喂养)的体重估算 SBW,并通过三种模型根据 SBW 估算 EBW:1.1.线性模型;2.无截距线性模型;3.指数模型。通过交叉验证评估了模型的预测能力。结果如下体重(BW)与腹围(SBW)、腹围(SB)与体重(EBW)之间的相关系数很高(r = 0.94;<0.0001)。体重和 SBW 之间方程的决定系数 (r2) 为 0.89 (P<0.001);SBW 和 EBW 之间关系的决定系数 (r2) 为 0.86 (P<0.001)。根据 AIC(26.81),公式 2 比公式 1(AIC = 28.44)和公式 3(AIC = 28.35)更好地描述了体重和 SBW 之间的关系。估计 SBW 与体重关系的最终模型是SBW(千克):0.96 (±0.001***) × 体重。在 SBW 和 EBW 比值方面,公式 5 优于线性公式 4(AIC = 33.01)和公式 6(AIC = 33.35)。模型如下EBW (kg):0.81 (± 0.06***) × sbw。对体重和 SBW 关系式的交叉验证表明,公式 1 的 r2(0.87)比公式 2 和公式 3 高,RMSEP 和 MAE 比公式 2 和公式 3 低。另外,SBW 和 EBW 关系方程的交叉验证显示,公式 4 和 6 的 r2(0.82)较高,RMSEP 和 MAE 较低,且往往比公式 5 更准确。启示本研究获得的结果有助于建立更准确的热带绵羊体重调整数学模型。结论。本研究中开发和评估的方程表明,体重和SBW之间的线性关系以及SBW和EBW之间的线性和指数关系可用于调整生长黑腹滨母羊羔羊的体重。值得注意的是,这证实了可以使用 0.96 FBW 的调整系数来计算 SBW。
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来源期刊
Tropical and Subtropical Agroecosystems
Tropical and Subtropical Agroecosystems Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
CiteScore
1.00
自引率
0.00%
发文量
49
审稿时长
24 weeks
期刊介绍: The journal is an international peer-reviewed publication devoted to disseminate original information contributing to the understanding and development of agroecosystems in tropical and subtropical areas. The Journal recognizes the multidisciplinary nature of its scope and encourages the submission of original manuscripts from all of the disciplines involved in this area. Original contributions are welcomed in relation to the study of particular components of the agroecosystems (i.e. plant, animal, soil) as well as the resulting interactions and their relationship/impact on society and environment. The journal does not received manuscripts based solely on economic acpects o food technology.
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