<p><strong>Background.</strong> In terms of animal management, the measurement of body weight (BW) is important in the design of nutrition and health programs. <strong>Objective.</strong> The objective of the present study was to evaluate the relationship between body volume (BV) and BW in Pelibuey ewe lambs and ewes. <strong>Methodology. </strong>For the model development, the BW and body volume (BV) were recorded in 406 Pelibuey ewe lambs and ewes ranging from two months to one years in age. All animals were clinically healthy, with a BW = 37.62 ± 10.63 kg. The BV was calculated using the heart girt (HG) and the body length (BL). BV was calculated according to the mathematical formulas for calculating the volume of a cylinder, considering biometric measurements in the calculation. The relationship between BV and BW was assessed by linear (Eq. 1), quadratic (Eq. 2) and allometric equation (Eq. 3). The goodness of fit of the regression models was assessed by the Akaike information criterion (AIC), Bayesian information criterion (BIC), coefficient of determination (R<sup>2</sup>), mean square error (MSE) and root mean square error (RMSE). <strong>Results. </strong>The correlation coefficient (r) between BW and BV was 0.89 (<em>P</em> < 0.001). The quadratic model had the higher value of coefficient of determination (R<sup>2</sup>= 0.81, and the lower MSE (4.17), RMSE (2.04), AIC (1163.64) and BIC (1175.66) values. The predictive ability of the three live weight prediction models was evaluated using <em>k</em>-folds validation (<em>k</em> = 10). <strong>Implications.</strong> The quadratic model had the higher coefficient of determination and lowest values were found for the mean square error (MSE) and mean absolute error (MAE). This model is practical and predicts with high accuracy the BW of the animals. <strong>Conclusion.</strong> Based on the evaluation approaches used in the present study and the close relationship between BW and BV in Pelibuey ewe lambs and adult ewes, the quadratic model was the mathematical model that had the best performance according to the goodness-of-fit evaluation.</p>
Appropriate supplementation of trace minerals is fundamental to enhance the metabolic status of growing animals and promote an adequate expression of genetic potential. Zinc (Zn) is an essential mineral fundamental in many biological processes that are related to growth, energy balance and immunity. The aim of the present study was to analyse the effect of Zn supplementation on growth parameters in small ruminants by using a meta-analytic approach. Sources of heterogeneity were explored using a meta-regression analysis. The final database was integrated from a total of 53 trials. Only indexed articles that provided an effect size measure, variability measure, sample size and randomisation of the procedure were considered. The dependent variables considered for the study were average daily gain (ADG), dry-matter intake (DMI), feed conversion ratio (FCR), final bodyweight, and glucose blood concentration. The exploratory variables included species (sheep and goat), breed, production level, Zn source and dosage. The ‘meta’ package in R statistical software was used to conduct the meta-analyses. For response variables that showed substantial heterogeneity (I2 > 50%), mixed-effect models (meta-regression analysis) were constructed to explore the sources of heterogeneity using the ‘Metafor’ package. DMI was higher in animals supplemented with Zn (>21.08 g/day, P = 0.0001). Breed, species, production level, and dosage reduced heterogeneity of DMI response from I2 = 84.8 to I2 = 48.1%. Zn-supplemented animals showed higher ADG (17.39 g/day, P = 0.001), which was affected by species, breed dosage and Zn-source. Zn supplementation improved feed efficiency, with lower values of FCR (–1.56 g/g, P < 0.0001). There was a positive relationship between the dosage and effect size in all outcome variables (P < 0.05). Zn-proteinate showed the best response in both species to ADG, FCR and final body weight. Our findings of the systematic review concluded that dietary Zn supplementation improves growth performance in small ruminants and their level of response is influenced mainly by species, production level, and Zn-source and dosage.
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