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Increased sensitivity central to successful soybean processing

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Jae Kim, Technical Manager ASPAC and William Greenwood, Sales and Technical Services Manager EMEA

The production of soybean meal requires several processes including the application of a range of grinding, pressures and temperatures to extract the required oils, remove anti-nutrients (e.g. trypsin inhibitors) and increase digestibility. This can impact the quality of the soybean meal and its nutritive value, reducing animal performance and producer profits.

It is essential that feed producers are able to identify undercooked and overcooked soybean meals so that they can identify low quality soybean meals and optimise animal feed. The American Soybean Meal Association conducted a study on the ileal digestibility of amino acids in raw soybean flake, correctly cooked soybean meal and over-cooked soybean meal in caecectomised roosters. The study demonstrated that the ileal digestibility of all amino acids is compromised when soybean meals are inappropriately cooked.

Traditionally, feed producers looking to optimise their feed formula have concentrated on ascertaining the content of soybean meal at a macro-nutrient level, for example, the moisture, protein, oil, crude fibre and ash content.

Advancing knowledge and understanding

As technology advances, producers are now increasingly able to check more advanced nutritional parameters, including amino acids, non-starch polysaccharide (NSP) content and phytate-P. They can also assess additional protein quality indicators and use them to check the impact of processing on soybean meal quality.

5 common tests for checking soybean meal quality:

  1. Potassium Hydroxide (KOH) solubility​ – Measuring the nitrogen solubility in 0.2% KOH solution detects over-cooked soybean meal. The optimum quality lies between 78% (overcooked) and 84% (undercooked); raw soybean meal is 100% soluble.
  2. Protein dispersibility index (PDI)​ – This test assesses the volume of soybean meal protein dissolved in water after blending a sample in a high-speed blender. The optimum quality is a PDI value between 40 and 45%.
  3. Reactive lysine​ – The toasting process reduces the total and reactive amino acid content and digestibility levels. The lysine is unusable by livestock if the free amino group on its sidechain is exposed as it reacts readily with sugars and fats if the temperature and moisture allow.  Lysine is therefore a sensitive marker of overprocessing. The reactive lysine content is a measure of the free amino groups remaining and thus the availability of the lysine for protein synthesis. Optimum values are above 90% reactive: total lysine ratio.
  4. Trypsin inhibitor activity (TIA)​ – TIA is destroyed during the desolventising-toasting (D-T) operation and this is strongly linked to the destruction of urease activity and can be used to detect under-processed material.
  5. Urease activity (UA)​ – This test involves analysing the change in pH values resulting from the existence of urease and is the most common method of detecting under-processed soybean meal. When soybean meal is under-processed, there should be more urease enzyme present meaning a greater pH rise. This is an indirect method commonly used in the industry to roughly estimate the TIA, as detection of the TIA is difficult and expensive. UA correlates with TIA as both enzymes are similarly deactivated at a range of dry and wet heat treatments. Typically, UA is quoted in urease index units (U), and industry expectation is 0.05-0.3U, depending on the species and physiological stage of the animal.

Take a closer look

Recent advancements in near-infrared reflectance (NIR) technology, and the rapid analysis it involves, mean it is a cost-effective alternative to traditional chemical testing to check ingredient and feed nutritional composition and that more accurate analysis than ever before is available.

Concerns over the reliability and sensitivity of the KOH and PDI tests – including from studies by Batal et al. (2000) and the US Soybean Export Council (USSEC) – led us to select reactive lysine and UA as the optimal soybean meal quality indicators for our web-based NIR prediction service, the Feed Quality Service.

During soybean meal production, the reducing (carbonyl) sugars can react with the amino group of lysine in the D-T process. This can produce a combination of poorly characterised Maillard products. The lysine can also react with other nutrients including fats, polyphenols, vitamins and other food additives, creating unspecified compounds.

One issue with this process is that part of lysine detected as total lysine in high-performance liquid chromatography (HPLC) analysis are not bioavailable for lean tissue anabolism – the biochemical reaction that constructs molecules – or for other biological functions, as the heat damaged lysine is excreted through urine even if they are digested and absorbed in the small intestine.

Using data from our global soybean meal database, we predict that approximately 15% of all soybean meal samples could be considered to be over-toasted (reactive:total lysine ratio <90%). We, therefore, recommend that feed producers consider supplementing feed containing soybean meal with additional amino acids. This will help them to ensure the feed contains the correct amino acid levels.

We also predict the standardised ileal digestible (SID) amino acid content in soybean meals. These results can be used in combination with the total and reactive lysine content to create conversion factors so that producers can adjust the expected SID AA content in the feed formulation system.

A deeper understanding essential for the optimisation

Soybean meal production has an impact on the quality of the material. Popular current methods to check the impact of soybean meal processing on quality may not be sensitive enough in practical situations. Research shows urease activity and reactive lysine are the most appropriate methods to detect under and over-processed soybean meal, respectively.

Given the volatility in soybean meal prices, and growing sustainability pressures, feed producers need to have a thorough understanding of its nutritional composition. Only then can they accurately compare different suppliers and optimise their inclusion in animal feed.

NIR technology is a rapid, non-destructive and cost-effective alternative to traditional wet chemistry analysis. Urease index and reactive lysine protein quality indicators are available for AB Vista clients using our web-based NIR prediction Feed Quality Service.

https://www.abvista.com/feed-quality-service

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