Circular Feed Innovation: Biotechnological Upgrading of Rice Straw and Agro-Wastes into High-Value Silage Using Fungal Enzymes

Abstract

Agricultural activities in Malaysia generate large volumes of lignocellulosic biomass, particularly rice straw and oil palm residues, which are often burned or discarded, contributing to air pollution, greenhouse gas emissions, and nutrient loss. Current research indicates that biotechnological upgrading of these wastes into silage can improve feed availability while supporting sustainable environmental management. This study aims to determine whether agricultural wastes, especially rice straw, can be transformed into high-value ruminant feed through microbial fermentation combined with fungal enzyme extraction. Controlled ensiling trials were conducted using lactic acid bacteria inoculants and enzymes derived from cellulolytic fungi to enhance fiber degradation and improve silage quality. General parameters evaluated included pH reduction, crude protein enhancement, neutral detergent fiber (NDF) reduction, aerobic stability, and preliminary intake response in ruminants. The results demonstrated that rice straw treated with fungal enzymes showed significantly improved fermentative quality, lower lignocellulose content, and higher digestibility compared to untreated materials. Oil palm biomass silage also showed higher metabolic energy potential and reduced spoilage under microbial inoculation. Overall, biotechnological treatments reduced the reliance on conventional forage by up to 30–50%, improved dry matter utilization, and supported better rumen fermentation efficiency. Environmentally, this approach diverted agricultural residues from open burning and landfill, contributing to lower methane emissions and improved natural resource conservation. In conclusion, upgrading rice straw and other agro-wastes via enzymatic and microbial silage technology offers a practical circular feed strategy that enhances feed security, decreases production cost, and aligns with sustainable natural resource and environmental management goals. Further exploration of enzyme optimization and scalable application models is recommended.