SciELO - Scientific Electronic Library Online

 
vol.28 issueNSPE1Effect of untreated and stabilized dairy effluent applications on soil fertility and associated health risksManagement of dairy heifers in Uruguay: Effects of feeding level and social environment on prepubertal development author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Related links

Share


Agrociencia Uruguay

On-line version ISSN 2730-5066

Abstract

LLANOS, E. et al. OLE! Dairy model: Description and evaluation of the biophysical components of a whole farm simulation model for pastoral-based dairy systems. Agrocienc. Urug. [online]. 2024, vol.28, n.nspe1, e1202.  Epub Sep 20, 2024. ISSN 2730-5066.  https://doi.org/10.31285/agro.28.1202.

The process of intensification of the dairy sector has been characterized in recent decades by the increase in milk production per hectare, the increase in livestock density, the inclusion of more concentrates in the diet, and the improvement of the genetic merit of dairy cows. The use of models has productive, environmental, and economic advantages. The objectives of the study were to describe a new model, “OLE! Dairy model”, to (a) simulate the biophysical performance of a pasture-based dairy production system; (b) evaluate the predictive capacity of the model with a set of statistical parameters, comparing its results with the biophysical performance of experimental studies of dairy farm systems, and (c) calibrate by adjusting the technical coefficient. The experimental design combines two feeding strategies with a different proportion of pasture in the diet and two animal genotypes. We make a description of the biophysical component and the calculations proposed in the “OLE! Dairy model”. Then a variety of parameters was calculated for model testing, including the Mean Squared Error, the Relative Prediction Error, the square root of the MSE, the Concordance Correlation Coefficient, and the Model Efficiency. The model presented a good predictive capacity for stocking rate and concentrate, pasture, and reserve intake. The predictive capacity of the model for individual production and area production improves after performing a rapid calibration, which allows for avoiding overestimations or underestimations that generate erroneous measurements in the planning and management of milk production systems, and can be adjusted to different conditions of production of the region.

Keywords : calibration; milk production; model testing; pasture-based dairy; statistical analysis.

        · abstract in Spanish | Portuguese     · text in English     · English ( pdf )