Diet formulation: Constraints, strategy and additivity of


FEED ADDITIVES By Rob ten Doeschate, Technical Director EMEA, AB Vista


The principles of diet formulation are simple and straightforward: we assume we know exactly what the nutrient requirements of a given group of animals are, we know the nutrients each potential ingredient can deliver, we assume all nutrients are additive and linear, we know the cost of the materials, we apply any production constraints and we then combine all that knowledge in our linear programming software so we can get the lowest cost solution to meet the nutrient requirement given the available raw materials. With regards to feed additives, defined as low inclusion products that have an impact on nutrient availability of the diet, there are many opportunities to be confused when applying these in feed formulations. The main reason for this is confusion about matrix values, how best to apply them and how to combine matrix values from different types of additives. This paper is meant to clarify some of these issues and give food for thought to get to the best strategies for applying feed additives in formulations. Enzymes are one of the major categories of additives with matrix values but several other product categories use the same approach and in principle should be considered together. The problem is that most of the ‘we know’ phrases in the


previous paragraph are really more accurately described as ‘we think we know’. And some of the assumptions are incorrect, especially when we look at matrix values for additives: These are unlikely to be linear and nor are they additive. For instance, if we look at an enzyme like phytase the dose response is normally described as logarithmic, which in effect means that a doubling of the dose will give 30% more nutrient release. It is possible to deal with this in the formulation system, either through specific enzyme modules in the software or by having different versions of the same material for different inclusion levels. Similarly, nutrient requirements are normally based on a dose-response curve, with the target value set based on the economic situation as well as the biological response. This means that supplying more nutrients than targeted may well have some positive impact on performance but supplying less nutrients than targeted will have a relatively bigger negative impact.


PAGE 36 JULY/AUGUST 2021 FEED COMPOUNDER Additivity means, in fact, that there is no interaction between


any of the ingredients in the formulation, which is much less likely than them having some sort of interaction. This could of course be both negative (resulting in sub-additivity) or positive (synergy). In the case of most additives it is probably fair to assume some level of sub-additivity, simply because each subsequent additive has less opportunity to improve the availability of nutrients as availability can’t get better than 100%! A simple rule of thumb would be to assume that a combination of two additives that affect the same nutrient would deliver 80% of the combined nutrient release, which is based on typical diet compositions reviewed and responses observed, rather than the 100% expected with full additivity. This approach effectively deals with the expected sub-additivity of additives whilst still opening up substantial opportunity to save diet costs. A formulation exercise using a broiler grower diet as an example


nicely shows the potential benefits of using (and combining) full recommended matrix values of phytase at various dosing levels combined with an NSP enzyme using the 80% concept (Figure 1). It can be seen that whilst the common strategy of just using mineral release values for the phytase gives worthwhile cost reductions from increasing the dose up to 2000 FTU/kg, much greater cost benefits result from taking all nutrients into account using the full matrix. While not taking account of the matrix values offers a way to improve performance, provided the extra nutrients can be utilised by the animal, one caveat would be the fact that we may be unbalancing the diet and thus not extracting the ideal cost-benefit. Reformulating the diet in order to take account of the expected nutrient release is the most cost-effective approach as nutrient balance would be maintained and nutrient requirements will be met exactly, provided they were met in the original diet of course. Next, we need to consider whether there is room in the diet to


apply the provided matrix values. There are several factors to consider, such as the level of substrate in the diet, whether it is possible to reduce nutrient levels and whether expected nutrient release values


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