عنوان مقاله [English]
During the last few decades, there has been an increase in the development of mathematical models, as both research tools and management tools that can integrate our current knowledge of reproductive events and then would be helpful in predicting the reproductive efficiency of farm animals. This paper presents a conceptualized mathematical modeling of hormonal and metabolites interactions over non-estrous and negative energy balance phase in dairy cow. Anestrus occurs annually and after each calving. The anestrus period in high milk-producing cows due to the negative balance of energy produced by high milk production in the first few days after parturition is a constant challenge in the modern world of dairy cow worldwide. For this reason, many scientific efforts have been made to explore the biological aspects of this phase. Due to the complexity of the existing relationships between effective parameters, descriptive-analytical biological analyses have not succeeded in elucidating this biological system. In this research, it was attempted to look at the elaborating factors playing in this phase, at same time, it was tired to pinpoint and explore this phase from biological system perspective.
Material and Methods: In the present study, first diverse information on the various aspects of the factors affecting on the postpartum negative balance of energy and reproduction performance of dairy cows were initially collected. Then, this information was converted to their sound mathematical equations. Efforts have been made to simplify the long and unprocessed equations from well-known factors including liver glucose, blood glucose, pancreatic insulin and blood insulin, IGF-1 liver and blood, and hypothalamic GnRH affecting on this biological phase to be simplified using ordinary differential equations. In other part of this study,
Findings: By using the data published in the scientific articles and expanding them by using Curve Expert software, the computer simulation process was performed by MATLAB software (Version 9.1) and the predictive models were developed for some system parameters.
Conclusion: The results showed that the system of ordinary differential equations was able to predict good blood glucose (AARD = 0.388) and insulin (AARD% = 0.638), but they were not able to provide accurate predictions for pancreatic insulin and blood IGF-1.
The present model was a starting point to reach a comprehensive model which should be completed gradually. In this model, it was tried to use empirical data from reliable sources in simulation model, a matter that was more or less successful in this research.