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Utilizing Malaysian local ingredients in developing low-cost goat formulation: a modeling approach
Author(s):
1. Rosshairy Abd. Rahman: School of Quantitative Sciences University Utara Malaysia Kuala Lumpur, Kedah, Malaysia; Institute of Strategic Industrial Decision Modelling, Universiti Utara Malaysia, 06010, Sintok, Kedah, Malaysia
2. Razamin Ramli: School of Quantitative Sciences University Utara Malaysia Kuala Lumpur,Kedah,Malaysia
3. Nurul Najwa Zainal Abidin: School of Quantitative Sciences University Utara Malaysia Kuala Lumpur,Kedah,Malaysia
4. Siti Noor Asyikin Mohd Razali: Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia,Pagoh Education Hub, 84600 Pagoh, Johor,Malaysia
Abstract:
Expensive feed prices for ruminants farming is one of the main factors that slash the farmers' profit margin. The main reason is due to most pallets are imported from abroad. However, many local ingredients can also be used to produce cheaper pallets complete with the required nutrients, simultaneously the ability to use the sources of local plants. Hence, this study proposes a diet mix for ruminants that consists of the best combination of ingredients with specific quantities that fulfil nutritional needs using the mathematical modeling approach known as Linear Programming (LP). The ruminant that is the focus of this study is goat since this type of ruminant has a high market demand in Malaysia. As a result, the LP model generated an optimal solution at a minimum cost compared to the existing feed in the market. Only two ingredients have been chosen by the LP model which fulfils all nutritional needs at a very low-cost. This solution may be used by practitioners to assist in generating low-cost quality ruminant diets which able to increase profit margins among local farmers.
Page(s): 1-5
Published: Journal: Journal of Global Innovations in Agricultural Sciences, Volume: 11, Issue: 1, Year: 2023
Keywords:
Nutrients , optimization , goat , goat , Linear programming , cost minimization , feed mix
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