SUSTAINABILITY FEED & ADDITIVE MAGAZINE August 2025 101 of the assessment and the importance to the commercial industry. While LCA is highly valuable for providing a broad environmental overview, its reliance on large amounts of secondary data may limit the ability to capture farm-specific variations. As a result, it may not always offer a comprehensive representation of on-the-ground conditions necessary for reporting to government authorities, processors, and consumers. CHALLENGES ASSOCIATED WITH LCA APPLICATION Due to the perceived lack of robust scientific data and reliability of modelled data, LCA faces scepticism from nutrition researchers.4 Predicting the biological responses of poultry, for instance, can be tricky. Many experiments lack replication under controlled conditions and are influenced by external factors like temperature and pH, leading to significant margins for error. Moreover, the results of an LCA can vary widely depending on the choice of database and methodology used, making comparisons between studies challenging and unreliable.5 The standardised LCA methodologies may not accommodate emerging feed innovations, new sourcing strategies, or novel processing techniques that lack established impact data. This can result in overly conservative assessments that discourage experimentation with alternative feed ingredients due to gaps or uncertainties in LCA databases. Additionally, LCA requires detailed and reliable supply chain data, which can be difficult to obtain in global feed systems. When ingredient availability fluctuates, or new suppliers enter the market, the time and resources needed to update LCA models can slow down decision-making and discourage agile adaptation to new, more sustainable options. Regulatory bodies and retailers often use LCA-based certifications and sustainability benchmarks to assess suppliers6, meaning that innovations with unproven LCA data may struggle to gain market acceptance, despite their potential benefits. To gain a competitive advantage from a low carbon innovation in animal production, theoretical modelling isn’t sufficient. It’s therefore essential to provide a robust and transparent calculation that shows the innovation, or intervention which has led to measurable improvements. CURRENT LCI TYPE APPLICATIONS TO CONTROLLED FEEDING INVESTIGATIONS Nottingham Trent University (NTU) has developed an in-house system for doing this, but the number of factors not measured and unaccounted for are enormous. This means NTU can precisely quantify the impact of a feed change but it is not possible to generate the accurate data that can be used as part of larger LCA models to create more meaningful insight on a macro scale. Emily Burton Professor in Sustainable Food Production in NTU’s School of Animal, Rural and Environmental Sciences, said, “We had to develop a system to apply in our research unit, that allowed us to quantify the impact of diet change, but it seems such a waste of generating such precise raw data not to end up with something that can contribute to a more widely used LCA system.” ShutterStock | 133220729
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