PREDICTION OF LIVE BODY WEIGHTS IN DROMEDARY CAMELS (Camelus dromedarius) FROM MORPHOMETRIC BODY MEASUREMENTS

E. Rotimi, A. Aruwayo, M. Garba, M. Lamido
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Abstract

The study explores the prediction of body weight in dromedary camels (Camelus dromedarius) using morphometric measurements Fifty-one (51) camels, comprising 24 females and 27 males were used for the study. Data were obtained on individual camels, including; estimated body weight (EBW), heart girth (HG), abdominal girth (AG), body length (BL), rump height (RH), shoulder height (SH), face length (FL), foreleg length (FLL), hind leg length (HLL), tail length (TL), neck length (NL), neck circumference (NC), and head length (HL). Data were subjected to statistical analysis. Results obtained showed no-significant (p>0.05) effect of sex on body weight in females and males. The correlation coefficients highlight strong relationships, particularly in HG and AG, emphasizing their significance in predicting body weight. The results show moderate to low VIF values, suggesting acceptable levels of multicollinearity in the models. Prediction equations are gender-specific, with separate models for females and males. For both sexes, HG and AG emerge as crucial predictors, with additional contributions from SH and FLL in certain models. The coefficient of determination (R2) indicates the proportion of variability in body weight explained by the models. For females, a three-variable model achieves an impressive R2 of 99.1%, while the corresponding male model attains 97.6%. Combining sexes, the models reach R2 values of 98.1% and 98.3%, showcasing the efficacy of the proposed regression equations in predicting body weights in dromedary camels. The study provides valuable insights for camel management, offering a practical tool for estimating body weight based on readily measurable morphometric traits.
根据体型测量预测单峰驼的活体重量
本研究探讨了利用形态测量法预测单峰骆驼体重的方法 本研究使用了 51 头骆驼,其中包括 24 头雌性骆驼和 27 头雄性骆驼。获得的骆驼个体数据包括:估计体重 (EBW)、心周 (HG)、腹围 (AG)、体长 (BL)、臀高 (RH)、肩高 (SH)、面长 (FL)、前腿长 (FLL)、后腿长 (HLL)、尾长 (TL)、颈长 (NL)、颈围 (NC) 和头长 (HL)。对数据进行了统计分析。结果表明,性别对雌性和雄性体重的影响不显著(P>0.05)。相关系数突显了强烈的相关性,尤其是在 HG 和 AG 方面,强调了它们在预测体重方面的重要性。结果显示,VIF 值为中低水平,表明模型中的多重共线性水平可以接受。预测方程是按性别划分的,女性和男性有不同的模型。对于两种性别,HG 和 AG 都是关键的预测因子,在某些模型中,SH 和 FLL 也有额外的贡献。判定系数(R2)表示模型所能解释的体重变化比例。对于女性来说,三变量模型的 R2 达到了惊人的 99.1%,而相应的男性模型则为 97.6%。结合性别,模型的 R2 值分别达到 98.1% 和 98.3%,这表明所提出的回归方程在预测单峰骆驼体重方面非常有效。这项研究为骆驼管理提供了宝贵的见解,为根据易于测量的形态特征估计体重提供了实用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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