ISSUE FOCUS 44 FEED & ADDITIVE MAGAZINE January 2025 Parametric analysis involves adjusting key variables— such as ingredient inclusion rates or production emissions factors—and observing how these changes affect the overall environmental outcomes of a formulation. By systematically varying inputs, formulators can identify thresholds where an ingredient substitution substantially improves sustainability metrics. TECHNOLOGICAL INNOVATIONS Technology plays a pivotal role in overcoming data challenges and integrating environmental metrics. Advanced formulation software can incorporate LCA databases, parametric analysis tools, and user-friendly interfaces that help nutritionists experiment with various scenarios. Real-time modeling allows formulators to quickly test the environmental and nutritional outcomes of substituting one ingredient for another. Emerging digital technologies, such as the blockchain, can enhance traceability by recording each transaction in a tamper-proof ledger. This approach can build trust in data quality, reduce the risk of misinformation, and streamline verification processes. As these tools mature, formulators will be able to make faster, more reliable decisions that align with both environmental and economic goals. ADAPTING TO FUTURE CHALLENGES The environmental dimensions of feed formulation will only grow in importance as global challenges like climate change, population growth, and resource scarcity intensify. Future feed systems may rely on entirely new categories of ingredients—such as insect meals, cultured proteins, or algae-based feeds—with their own unique environmental profiles. Keeping pace with these innovations demands flexibility, openness to experimentation, and willingness to update LCA methodologies accordingly. As data collection technologies improve—using sensors, remote sensing tools, or satellite imagery— environmental metrics will become more accurate and readily available. This enhanced precision will further empower formulators to make data-driven decisions that reflect current realities rather than outdated assumptions. In this evolving landscape, the ability to adapt will be as important as the ability to measure. CONCLUSION The journey towards environmentally responsible feed formulation is complex, but it is also filled with opportunities. By embracing life-cycle assessment methodologies, improving data quality, leveraging analytical tools, and fostering transparency throughout the supply chain, feed formulators can integrate ecological considerations without losing sight of nutritional and economic objectives. Overcoming the data challenge is a central theme. Without reliable, comprehensive, and comparable environmental data, it remains difficult to make confident choices that truly reduce footprints. Yet, as the industry invests in research, collaborations, technology, and education, the quality of environmental metrics will improve. Eventually, sustainable feed formulation will become the norm, and the industry will be recognized as a key driver of positive change. In this pursuit, innovation and adaptation are constant companions. The sector’s collective efforts to refine data, methodologies, and strategies will create a more resilient, competitive, and forward-looking industry. By making environmentally informed decisions, feed formulators help ensure that animal agriculture can continue to meet global nutritional needs while safeguarding the planet’s resources. About Ricardo Amaral Ricardo Amaral is currently Chief Executive Officer (CEO) at Optimal. With an MBA in Corporate Finance and specialization in Agribusiness Management and Governance, Amaral has been working with technology companies with an emphasis on mathematical optimization methods and data analysis for the past 15 years. His focus as the CEO at Optimal is to create tools for laboratory information management and formulation optimization, allowing business to craft the ideal strategies to optimize feed efficiency, improve animal performance and maximize profit from the whole system.
RkJQdWJsaXNoZXIy MTUxNjkxNQ==