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2020 PSA notes #2!  

On Monday, as usual, PSA held the famous Informal Nutrition Symposium. This year, the topic was Ingredient Quality Assessment for Old and New Ingredients.

Why this topic? Because ingredient assessment is the cornerstone for accurate formulation. To achieve precision nutrition, we need to reduce the impact of (incorrect) assumptions, and quantify & understand variation in ingredients in a rapid, accurate, and precise manner. How do we do that? These 5 intriguing talks from this symposium may bring you some practical ideas to think about.

Here are my notes from the symposium...Happy Reading! :)



We want to have consistent feed, and this is achieved by controlling the natural variability from ingredient, processing, and analysis...Among them, analytical variability can bring in a lot of uncertainty depending on the method used, sampling representativeness, and the nature of the testing material.

So what is the right analytical method? It is the method that is providing a meaningful information. Remember:  "An analytical result is always an information, rarely a response, never a solution."

Sometimes we might be tempted to go down the "math rabbit hole" to see how much saving a analytical result difference can bring. But where do we stop on the math? The answer is analytical viability, because if we go too low on the "delta", it might already be out of the analytical range and it would make no practical sense. (Credit: Stercoli @ 2020 PSA)

We need to balance Accuracy (costs and time) vs. Representativeness (sampling, monitoring, mindset). If a test is more rapid —> we can run more testing —> Possibly more representative.

So that's where NIR comes into play...It allows for a rapid testing of incoming ingredients and finished feeds.

Credit: Stercoli @ 2020 PSA

The key to properly utilize NIR is to build a strong quality program. There are 4 components of a good quality system:

a). Define benchmarks — Good lab practice (have a reference system like ISO) & regular comparison with recognized reference.

b). Standardize and verify methods — Standardized SOPs (especially if you have multiple labs) & Continuous verification of methods.

c). Monitoring results — Routinely check if data are consistent & realign wet chemistry and NIR whenever needed.  

d). Act to improve — Focusing on improving process by regularly check performance reports and collect user feedback.  

Dr. Stercoli then talked about other novel methods, including Fingerprinting, Inline NIR, and Portable NIR...all of them could serve as useful tools to minimize analytical variability.  

Inline NIR pros and cons (Credit: Stercoli @ 2020 PSA)

Take-Home Message

Compared to wet chemistry, NIR allows for rapid testing and possibly more representativeness, but make sure to build a strong quality program  for obtaining meaningful information (and this requires continuing work, cannot be a one-time effort).


(Baiada Poultry, Australia)

Peter is a commercial nutritionist, and he has been using the Evonik NIR tools — When an ingredient comes in, NIR will return 32 nutrient values within 10 minutes (20 amino acids, proximates, starch, sugar, ADF, NDF, P & phytate), and provide Standardized Ileal Digestible values (from Lemme, 2014) and AMEn (calculated based on WPSA 1989).

Credit: Chrystal @2020 PSA

So...a lot of data are generated from this approach. Just within the past year, 2976 raw material analyses were performed, times 32 = 95,232 data points! Within these data, there are a lot of variation.

First, there might be huge variation for a single nutrient from different batches of ingredients — for instance, Lys content from 27 SBM samples can vary with a CV of 3.4% ,while from 25 MBM samples can vary with a CV of  16.5%; similar CVs are true for Lys digestibility as well.

Also, variation comes from feed mill batching as well. Peter's Rule of thumb: For a feed ingredient quantity to be less than 10% variation, the weighed quantity needs to be greater than 4% of the scale capacity! e.g. The minimum weight on a 3000 kg batch scale = 120 kg.

So...the question is — with all the NIR data, What is the best way to use these data...What value to use for formulation? (Average? Average - 50% of SD? How many data points do you take - last week, last month, last year? What about outliers in there?)

Peter's suggestion (and his practice for many years) is:

Look for patterns in the NIRs nutrient analyses and take the NIR data to create multiple regression equations per raw material by geographical region and season...then drive the matrix values off a few nutrients (e.g. energy, crude protein)
Predicting SID Lys levels by crude protein level and process damage index (Credit: Chrystal @ 2020 PSA)

Also, each source of the same ingredient (for instant, canola meal) requires its own specific nutrient matrix (as it's impacted by processing conditions, expeller/solvent product, and agronomic conditions)

It is important to generate your own data and use your own data because analyzed values & book values are often different. (AMINOdat = book values; AMINOnir = analyzed values; Credit: Chrystal @ 2020 PSA)


  • For "nutrition process", Peter thinks that 3 levels exist: The formulated feed | The actual feed produced | The actual feed delivered. They can all be vastly different, and controlling viability is key.
  • No (analytical/matrix) system is perfect, what's important is to stick with one system and be consistent (so that overtime, you know how your birds will respond when formulation changes are made).


(United Animal Health)

Mike started of by providing two definitions:

Applying results = Validate that the nutrient values that are applied to each feed ingredient are accurate.

Accurate delivery = Are the feed ingredients being accurately dosed, mixed and delivered to the bird?

So first, how do we validate nutrients? Things to pay attention to:

  • Correct unit for each nutrient! (kcal/kg vs. kcal/lb; ppm vs. %; mg/kg or mg/lb...)
  • Make sure the correct value is assigned to the respective nutrient in the formulation software (do occasional random self-audit to double check).
  • Make sure the equations used in formulation software are accurate. (e.g. digestible values, Ca:P ratio...)
  • Correctly assign nutrient values to an additive/premix based on its inclusion level ( e.g. Enzymes' matrix values for ME, Ca, P, etc.)
  • NIR vs. Wet chemistry — Suggest submit 20-30% of feed ingredient samples for wet chemistry to validate NIR at start-up, and then 10-20% for ongoing monitoring. It also depends on nutrient — e.g. NIR values might work well for proximates and amino acids, but not for minerals. So focus on the key nutrients.
  • A dedicated person to commit 100% to NIR is necessary...

After feed is formulated, it is equally important to make sure that it is produced and delivered properly. So on the feed mill end, things to consider include:

  • Necessary to accept or reject ingredients and validate suppliers based on real time analytical values (upon validation per historical values)
  • Keep historical data rolling for 4-wk averages for feed ingredients and adjust the values for variation (to do that, we must know the standard deviation, range of values, and CV)
  • Logistics...# of ingredient bins and finished feed bins we have vs. how many different diets we are trying to make.
  • Ingredient scaling — understand the nearest scaling at the feed mill. E.g. on the feed formulation, we can be as precise as 6 decimal points, but at the mill, it can only be weighed to the nearest 0.1, 2, or 5 lbs (for micro, minor, or macro scales, respectively). The rounding will affect final values in the diet!
  • Feed mixing — Conduct the mixer profile quarterly to assess scaling, dry & liquid mix times, and total mix time after liquids are added; Pay attention not only to the CV of 10 samples, but also the actual/theoretical percentage.


"You can mix an accurately formulated feed really bad Or mix an inaccurately formulated feed really good! " 🤣



(University of Saskatchewan)

Dr. Newkirk talked about the steps to assess and commercialize new ingredients, and things to consider. There are several stages of assessment required by the industry & the regulators:

  • Nutritional/anti-nutritional profile — Required by both regulators and industry — at least 3 samples from different sources/locations, need to understand variability in samples. For anti-nutritional factors, industry is concerned about the level and risk & ways to control, while regulators will be more concerned on liability (e.g. the potential of transferring to human foods).
  • Economic modeling — conduct modeling/formulation per species & phases of focus.
  • Digestibility/Performance studies
  • Registration
  • Commercial trials, data sharing, training...

Sometimes, there are intrinsic differences between the interest of the industry vs. the regulators. For example, regulators give very strict definitions of a new ingredient in terms of its manufacturing method, species to use, and stages that can be used, whereas industry would like more flexibility and depend more on practical experiences.

Rex suggest that we do as much as front work as possible, so that if we want to expand the use to another stage, species, or inclusion rate, we won't have to redo the whole process all over again...

A practical example of a new ingredient — Camelina...Huge amount of work involved to get registration. (Credit: Newkirk @ 2020 PSA)


(EnviroFlight LLC)

Why insect protein? Because it can be fed to virtually all animals, and it has very high yields relative to other protein sources per acre of land. Also, it requires much less feed and water compared to other livestock animals.

Credit: Koutsos @ 2020 PSA
Credit: Koutsos @ 2020 PSA

Black soldier fly has a rapid lifecycle (20 - 40 days) compared to other insects of interest (e.g. cricket: 60-90 days; mealworm: 60-80 days), it provides a very good nutrient profile, and has also been shown to have mycotoxin detoxification trait.

Nutrient composition of insect protein (Credit: Koutsos @ 2020 PSA)

In animal nutrition, the use of insect derived ingredients have generated a lot interest, first in aquaculture (as a replacement of fishmeal), and more recently on poultry and swine. Major concerns for their application though include chitin content, heavy metals (from flies), pathogens (species specific), and feedstock (safety, approval - e.g. in the U.S., the insects must be fed AAFCO-approved ingredients themselves...).

There are some novel, potentially beneficial attributes of insects, such as lauric acid and anti-microbial peptides.

Currently, BSFL meal is approved in the U.S. for broilers and layers. However, the volume is still limited for the industry, so at this point it would be more for niche markets (backyard flock, free-range flocks, etc.). In the future, there might be opportunity to explore its use at low inclusion rates  (<3%) for gut health benefits. (For insect meals to be competitive with SBM? It would be quite a long way...)

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