The characterization of the nutritive value of aquaculture feed ingredients typically relies on a combination of proximate composition analysis (crude protein, crude lipids, crude fiber), near-infrared spectroscopy (NIRS), and in vitro assays such as pepsin HCl and ELISA. While these methods offer useful insights and are practical for routine evaluation, they each have limitations in their ability to fully capture the true nutrient content and biological value of ingredients. As a result, there is a risk that feeds formulated using these data may not fully meet the nutritional requirements of the animal, leading to reduced performance and economic inefficiencies.
Amino acid composition is a critical element of protein quality, but values are highly variable across — and even within — ingredient types. Analytical procedures are complex, costly, and subject to technical errors. In vivo digestibility assays, particularly when combined with in vivo bioavailability measurements, are the most reliable methods available when properly designed and executed. However, these trials are time-consuming, expensive, and not practical for routine ingredient screening. There is a pressing need for rapid, reliable, and cost-effective assays to estimate the digestibility of proteins and amino acids. In our experience, more than 90% of the digestibility results we have audited contain significant errors or biases, often due to issues with experimental design, marker recovery, or analytical inconsistencies.
Discrepancies of 10–15% in digestible amino acid levels between ingredient batches are not uncommon. These differences can significantly affect feed formulation and cost. In shrimp feed simulations, a 30% reduction in protein digestibility of fish meal resulted in an increased feed cost of USD $43 per tonne. As ingredient markets become more volatile and sustainability targets more demanding, improving the precision of ingredient evaluation becomes increasingly important.
Our efforts to model and measure the impact of ingredient quality on feed performance across key aquaculture species — including shrimp, tilapia, and salmonids — in diverse global production systems have consistently demonstrated the value of improved characterization of protein ingredients. Approaches such as nitrogen mass balance, amino acid data auditing, and well-designed in vivo digestibility trials have proven essential in identifying meaningful differences in ingredient nutritive value. These tools enable more accurate feed formulation, reduce variability in animal performance, and contribute to more cost-effective and sustainable aquafeed production.
Our efforts to model and measure the impact of ingredient quality on feed performance across key aquaculture species — including shrimp, tilapia, and salmonids — in diverse global production systems have consistently demonstrated the value of better understanding the principles that underpin ingredient nutritive value. Concepts such as nitrogen mass balance, auditing of amino acid composition, and the distinction between digestibility and bioavailability have proven essential in identifying meaningful differences between ingredients. Applying these principles enables more accurate feed formulation, reduces variability in animal performance, and contributes to more cost-effective and sustainable aquafeed production.