Using Mathematical Modeling Techniques for Optimized Dairy Herd Management and Decision Making

Using Mathematical Modeling Techniques for Optimized Dairy Herd Management and Decision Making
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ISBN-10 : OCLC:970663976
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Book Synopsis Using Mathematical Modeling Techniques for Optimized Dairy Herd Management and Decision Making by : Afshin Samia Kalantari

Download or read book Using Mathematical Modeling Techniques for Optimized Dairy Herd Management and Decision Making written by Afshin Samia Kalantari and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dairy farm is a complex business enterprise with several uncertain and interacting factors (e.g., biology, environment, market conditions). To become and remain viable in such environment, dairy farm decision makers need to make better-informed decisions. Appreciation of these facts has resulted in extensive on-farm data gathering. However, to obtain useful information for decision-making, data need to be processed. For this purpose, mathematical modeling techniques can be used to develop decision support systems. This thesis applies different mathematical modeling methods- dynamic programming, Markov chain, and Monte Carlo- to evaluate and quantify the economic impact of optimal replacement decisions, reproductive management, and nutritional grouping on dairy herd's profitability. Some of these models were also transformed into decision support systems that can further assist decision-making at the farm level. Dynamic programming optimization and Markov chain simulation were compared to find the optimal replacement decisions in dairy cows. The results showed that although dynamic programming remains the best algorithm for replacement decisions, the simulation method had comparable results. The effect of reproductive management on the herd value was quantified by integrating daily dynamic programming and Markov chain models. The results showed that there is an economic opportunity to differentiate reproductive management strategies according to cows' relative milk productivity. Also, a robust Markov chain was introduced and used for stochastic evaluation of reproductive performance. The study confirmed greater profitability with increased reproductive performance, but a great variation among farms at a given level of reproductive performance was also observed. Finally, a dynamic, finite, stochastic Monte Carlo simulation was developed and used to evaluate the economic impact of nutritional grouping of lactating cows. The results indicated that there was an economic opportunity when grouping homogeneous cows based on both their protein and energy concentration requirements. Regardless of herd size, a maximum relative gain could be achieved by having three nutritional groups beyond the fresh cow group.


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