The optimization of ruminant feed with local ingredients using linear programming

Abstract

The high cost of feed is a major factor that reduces profit margins in ruminant farming, primarily due to the reliance on imported feed pellets. However, various locally available ingredients present cost–effective alternatives that can still meet the nutritional requirements of ruminants. This study aims to create a cost–effective goat feed using local ingredients through Linear Programming (LP). The objective is to find the cheapest feed mix that still meets all the nutritional requirements. Eleven local ingredients from Kedah and Perlis were chosen for their availability, cost–effective, and nutritional value. Using Excel Solver, a LP model was formulated and solved to meet key nutrient needs for ruminants, specifically dry matter, crude protein, calcium, and phosphorus. Nutrient composition data for each ingredient were collected from The Malaysian Agricultural Research and Development Institute (MARDI). The results show that a balanced feed can be formulated using local ingredients, reducing reliance on imported feed and supporting sustainable farming in Kedah and Perlis. The LP model found an optimal solution using just two local ingredients, petai belalang and napier grass, that fully meet all nutritional needs. This approach resulted in a 72% reduction in feed costs compared to current commercial options. This research offers a practical solution for local farmers, enabling the production of ruminant feed at a lower cost and thereby enhancing profit margins. As a result, this contributes to improved food security, economic resilience in rural communities, and a more sustainable livestock industry