Variation of main cereal byproducts used in poultry diets

Price increases of classical protein ingredients like soybean meal have prompted poultry producers to seriously consider use of more alternative ingredients, such as corn DDGS.

LIHONG ZHANG and KEVIN LIU* present survey findings for a large number of corn DDGS, rice bran and wheat bran samples received from feed producers in southeast Asia for NIR assessment, for proximate, total and digestible amino acids, and metabolizable energy (AME for DDGS) and their coefficient of variation.

Cereal byproducts for poultry diets

Poultry producers in southeast Asia are facing challenges by the supply shortage and price hike of classical feed ingredients like soybean meal, which prompts more serious consideration of using the alternative ingredients such as rice bran, distillers dried grains with soluble (DDGS) and wheat bran, at higher inclusion levels in their formulations. Indeed, full fat or de-oiled rice bran, DDGS and wheat bran are often classified as “alternative ingredients” with limited dietary inclusion in this region due mainly to their high variability in terms of contents of nutrients and their digestibility plus inconsistent supply. Quality variation and consistency have been a real concern when using these ingredients for high-performing poultry flocks. 

Some producers employ Near Infrared Reflectance Spectroscopy (NIRs) to monitor quality variation, but mostly for proximate constituents only. There are enormous challenges to develop reliable and robust NIR database and calibrations for the advanced parameters such as digestible energy and amino acids. With decades of effort, Adisseo has developed NIRs to predict total and digestible amino acids (TAA, DAA) as well as apparent metabolizable energy (AME) and nitrogen-corrected AME (AMEn) in common feedstuffs. This NIRs is based on reliable wet chemistry and in vivo tests on standardized ileal digestibility of amino acid (SID AA) using adult cecaectomized rooster as well as AME using 3-week-old male broilers. These NIRs models have been validated as the most updated and robust tool to monitor quality variation of cereal byproducts on proximate, total amino acids as well as digestible nutrients. With a few exceptions, well-established NIRs calibrations can explain 80-97% of the variability of TAA, DAA and AME. For instance, our NIR calibration developed for SID of Lys corn DDGS reaches a correlation of 85% to the in vivo results. 

Mapping the nutrient variation by NIRs

From July 2020 to June 2021, in total 2,077 full fat and de-oiled rice bran, 413 wheat bran and 2,305 corn DDGS samples were scanned on Adisseo standardized and validated NIR instruments at feed mill level. These samples were predicted for their proximate (PROX), namely dry matter (DM), crude protein (CP), ash (Ash), crude fiber (CF) and fats (Fat), total and digestible amino acids (TAA, SID AA, DAA), AME and AMEn using database derived from in vivo tests.

Rice bran

The two main byproducts obtained from rice milling are the hulls and rice meal. Bran is the coarse outer covering on grains separated during processing. NIRs predicted results showed the average full fat rice bran contains: CP 13.81%, Ash 8.13%, Fat 20.18%, CF 9.52%. Ash and CF have the highest coefficient of variation (CV) at 27.9% and 23.2%, respectively. Fat ranges from 7.65 to 30.12% with CV at 10.9%. The average values are close to Brazilian table values except for the fat content (20.18% by Adisseo NIR v.s 14.2% from Brazilian Table 2017). Higher variation was observed for de-oiled rice bran proximate (Table 1) with CV above 10%. This reflects the substantial diversity of rice bran suppliers in rice-producing areas. Fat of de-oiled rice bran has the highest variation ranging from 0.59 to 5.41% with CV at 46.5%. 

Table 1: Proximate for de-oiled rice bran by NIR prediction.

NIR analyzed average values for total amino acids are close to Brazilian table values. Variability level differs from one AA to the other: the lowest CV% is for total Thr (8.1%) and the highest for total Met (13.9%). Coefficient of variation for DAA ranges from 8.1 to 14.0%. Large variation of digestible amino acids is amino acid digestibility, suggesting a real need to monitor this variability by screening each batch of rice bran, in order to capture its true value, which can be done by NIR system only.

Wheat bran

Wheat bran is the outer layer combined with small amount of endosperm of wheat kernel. The proximate average of wheat bran contains: CP 15.97%, Ash 4.93%, Fat 4.72%, CF 9.02%. The protein is of better quality than that of corn. The high fiber content in wheat bran has laxative effect that may benefit gut health. Coefficient of variation is 17.2% for CF, 16.1% for Fat, 13.4% for Ash and 6.2% for CP. Essential TAA has CV ranging from 7.1 to 10.3%. Coefficient of variation for DAA ranges from 7.5 to 12.5%. AMEn, as calculated by World Poultry Sciences Association (WPSA) equations, ranges from 774 kcal/kg to 2,723 kcal/kg with CV 13.7%.  


The high interest in clean energy through ethanol from plant source, has led to rapid increases in corn processing and the production of DDGS as a byproduct. During the past 10 years, we’ve seen evolutions in the ethanol industry and new technologies used in order to improve ethanol yield and profitability. These changes may not necessarily improve the quality and consistency of DDGS. Thus, it is important to determine the value and monitor the variation of DDGS of each batch, in a rapid yet reliable manner, for procurement and optimum usage in formulation. Our NIR prediction on 2,305 corn DDGS samples reveals substantial variations for all nutrition parameters. From the usual proximate parameters, the average corn DDGS contains: CP 29.55%, Ash 4.36%, Fat 8.31%, CF 7.41%. Coefficient of variation is 14.0% for Fat, 9.2% for Ash, 7.4% for CF and 5.8% for CP. Essential TAA has CV ranging from 4.7% to 7.1%. Standardized ileal digestibility of AAs has CV from 3.4% for SID Met and SID Leu to 12.6% for SID Cys. DLys, DCys and DTrp have CV above 10%. Corn DDGS can be a source of protein and energy in poultry diet. Mean value of AME for these corn DDGS samples is 2,344 kcal/kg with a minimum 1640 and maximum 2,915 kcal/kg. Nitrogen corrected AME (AMEn) was from 1,554 to 2,718 kcal/kg with a standard deviation 189 kcal/kg. Phytic phosphorous (Phytic P), and available phosphorous (Ava. P) in corn DDGS are also highly variable, with CV at 22.9% and 17.1%, respectively.

Table 2: Proximate, total and digestible amino acids, AMEn and AME, phytic P and available P for cereal byproducts (NIR prediction).


Cereal byproducts can be of valuable ingredients for poultry diets, but their variations remain a real concern. NIR predictions, especially the advanced models based on reliable wet chemistry data and in vivo determination, appear to be the best strategy to monitor their quality variation, enabling rapid assessment on their proximate, TAA, as well as digestible nutrients like DAA, AME and digestible phosphorus. 

Results from a large number of cereal byproducts collected from southeast Asia revealed that wide variation not only exists for proximate but also availability of nutrients. Essential DAA has CV from 8.1 to 14% for rice bran, 7.3 to 14.7% for corn DDGS, and 7.5 to 12.5% for wheat bran.Mean AME value of corn DDGS was 2,344 kcal/kg, with a large range from 1,640 to 2,915 kcal/kg (CV 8.4%). These findings confirm the substantial diversity among the cereal byproducts currently used in southeast Asia, and only advanced NIR technology allows rapid and precise assessment, which enables informed procurement and the formulation by using “true” value to achieve expected performance results.

*Lihong Zhang ([email protected]) is NIR & Analytical Services Manager and Kevin Liu is Vice President. Both are with Adisseo Asia Pacific Pte Ltd. 

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Based and working in the region.