Estimation of cattle weight gain under the influence of meteorological and nutritional variables by applying a multiple linear regression model in Sabanalarga, Colombia (2023)
The present investigation arose from the current problem in the entire territory of the Department of Atlántico in the Republic of Colombia, in which the livestock sector currently lacks a reliable modernization that contributes to the planning and profitability of meat production, translated into weight gain. The main focus of the study gravitated around the ignorance of the real effect exerted by meteorological and nutritional factors on the weight gain of cattle. As a possible solution, it was proposed to carry out a statistical analysis by means of a multiple linear regression model where cattle weight gain was the dependent variable to study under the influence of the following independent variables: accumulated precipitation for two weeks (mm), average daily precipitation for two weeks (mm), average daily forage height consumed for two weeks (cm), percentage daily average of forage consumed during two weeks (%), average protein percentage of forage consumed during two weeks (%), the average maximum temperature recorded during two weeks (°C), the average minimum temperature recorded during two weeks (°C), average daily temperature variation recorded for two weeks (°C) and average relative humidity recorded for two weeks (%). All independent data values were collected in the field. Once the analysis was carried out, it was concluded that there was statistical evidence to affirm that only the independent variables "accumulated precipitation", "average precipitation", "average minimum temperature" and "relative humidity" significantly influenced the changes observed in profit of cattle weight, being formulated a multiple linear regression model that contained only the mentioned variables, the rest were discarded. On the other hand, for the constructed linear regression model, the coefficient of determination R2 = 89.3691% was obtained, that is, for the significance level α = 0.05 (95% confidence level), this determined that the model of Multiple linear regression (A) explained the behavior of the average monthly cattle weight gain by 89.3691%. It was concluded, therefore, that the present work gives veracity to the determination of previous investigations where it is also concluded that the meteorological variables directly affect the changes associated with the weight of cattle for meat production.