Incorporation of Milk Yield, Dry Matter Intake and Phosphorous Excretion Predictive Functions in the Development of a Multi-Objective Dairy Feed Formulation Software Program

S M Mutua, B O Bebe, A K Kahi, A Y Guliye

Abstract


Predictive functions for milk yield, dry matter intake, and phosphorous-manure derived from the National Research Council 2001 and the present study were incorporated in the development of a multiple objective dairy feed formulation software program (MoF-Dairy Edition-2010); that attempted to optimise feed cost, milk yield and profits while minimising Phosphorous-excretion in manure. Important objects in the feed milling industry considered in the program development were feed millers, dairy farmers, and government feed policy regulatory guidelines. The multi-objective formulation approach comprises hierarchical design levels which include data, model, tools, and output layers. Program database objects are manipulated using VB.NET programming language within a Microsoft .NET Framework Environment. Users interact with the program by providing individual details after which a customer system instance is created. Program formulation inputs are entered through VB forms linked to the core simulation model layer (Microsoft SQL Server Database) to automatically calculate and generate nutrient requirements in accordance with NRC, 2001 for the particular cow or cow production groups under specified production performance parameters. The final solution is obtained by allowing the program to solve for the most feasible combination of available ingredients under the imposed formulation, ingredient as well as nutrient constraints. Program outputs include tailor-made reports on feed formulae; and the accompanying physical nutrient compositions and nutrient deviation analysis; potential unit and gross P-manure environmental pollution, and business economic analysis; detailing concentrate supplementation rates per cow per milking as well as the corresponding projected daily milk profit margins.


Full Text: PDF DOI: 10.5539/jas.v5n11p208

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This work is licensed under a Creative Commons Attribution 3.0 License.

Journal of Agricultural Science ISSN 1916-9752 (Print) ISSN 1916-9760 (Online)

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