Open AccessA feed is still only as good as its ingredients: An update on the nutritional research strategies for the optimal evaluation of ingredients for aquaculture feeds
Author(s) -
Glencross Brett D.
Publication year - 2020
Publication title -
aquaculture nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.941
H-Index - 79
eISSN - 1365-2095
pISSN - 1353-5773
DOI - 10.1111/anu.13138
Subject(s) - ingredient , quality (philosophy) , risk analysis (engineering) , active ingredient , process (computing) , product (mathematics) , set (abstract data type) , palatability , microbiology and biotechnology , biochemical engineering , order (exchange) , computer science , marketing , business , biology , food science , mathematics , engineering , bioinformatics , philosophy , geometry , epistemology , finance , programming language , operating system
The choice of strategies used to assess ingredients can have a strong impact on the interpretation of their quality. In an attempt to standardize the assessment process, a structured approach using five steps for assessing the quality of ingredients was proposed over a decade ago. Since then, there has been considerable progress in the science of ingredient evaluation, and expectations from the users of those ingredients have also evolved. Two additional steps have emerged that formulators require to make appropriate decisions in the use of ingredients. Accordingly, a series of seven steps (and the order in which they should be done) to develop a comprehensive data set on ingredient quality is proposed; Step 1 Characterization, Step 2 Palatability, Step 3 Digestibility, Step 4 Utilization, Step 5 Immunological, Step 6 Processing Effects and Step 7 Product Quality Influences. Once these seven steps had been achieved, a formulator can make the appropriate choice as to whether to use any particular ingredient, and with what constraints to impose on their use. Without any one of these steps, the risk exposure substantially increases as the formulator needs to make assumptions, and this increases the risk of a feed failing in one or more specifications.