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Grain & Feed Milling Technology is published six times a year by Perendale Publishers Ltd of the United Kingdom. All data is published in good faith, based on information received, and while every care is taken to prevent inaccuracies, the publishers accept no liability for any errors or omissions or for the consequences of action taken on the basis of information published. ©Copyright 2010 Perendale Publishers Ltd. All rights reserved. No part of this publication may be reproduced in any form or by any means without prior permission of the copyright owner. Printed by Perendale Publishers Ltd. ISSN: 1466-3872 Digital Re-print - March | April 2012 Assessing cereal quality parameters www.gfmt.co.uk

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Grain & Feed Milling Technology is published six times a year by Perendale Publishers Ltd of the United Kingdom.All data is published in good faith, based on information received, and while every care is taken to prevent inaccuracies, the publishers accept no liability for any errors or omissions or for the consequences of action taken on the basis of information published. ©Copyright 2010 Perendale Publishers Ltd. All rights reserved. No part of this publication may be reproduced in any form or by any means without prior permission of the copyright owner. Printed by Perendale Publishers Ltd. ISSN: 1466-3872

Digital Re-print - March | April 2012 Assessing cereal quality parameters

www.gfmt.co.uk

Page 2: Assessing cereal quality parameters

Animal feed is the second largest consuming industry of cereals across the globe; their use is due

primarily to the high starch concentra-tion of these ingredients, which will usually account for more than 60 percent of the energy of the final feed.

The three cereals most routinely used in animal nutrition are maize, wheat and sorghum.

While the use of wheat and sorghum is specific to geographical regions (wheat being used in Europe, Canada and Australia and sorghum in Mexico, Australia and Central West Brazil), maize is used more globally.

The increase in use of maize by the bio-fuel industry has increased its cost, which has resulted in the more commonplace use of alternate cereals. The quality of cereals is of greatest concern to the nutritionist due to their high inclusion rates in animal feeds.

One of the most important determinants of cereal quality is their content of non-starch (fibre) polysaccharides (NSP), the concentration and functionality of which varies from sample to sample. They are countered with the use of dietary exogenous NSP-degrading enzymes, and evidently the response obtained depends very much upon initial cereal quality.

Understanding those factors that affect cereal quality will aid in ensuring more con-sistent animal performance.

Nutrient contribution of the dietCereals such as wheat, maize and sorghum

are high starch, low protein ingredients that makes them important energy sources for animals.

Considering the poor quality of the pro-tein due to the low concentration of essential amino acids (mainly lysine), the influence of these ingredients on dietary amino acid con-centration is not great.

Considering an average 65 percent inclu-sion in the diet and a diet formulation with 3150kcal/kg, 1.00 percent digestible lysine (dLys) and 0.75 percent digestible sulphur amino acids (dSAA), the main cereal will contribute approximately 65-70 percent of the energy, 10 to 15 percent of dLys and 25 to 30 percent dSAA.

This clearly shows their importance as an energy contributing ingredient and highlights the importance of having an accurate meas-urement of energy content.

Ingredient energy content is usually meas-ured using an Apparent Metabolisable Energy (AME) chick bioassay. In this bioassay, ingre-dients are fed to animals and the amount of energy absorbed is calculated as the difference between the gross energy of the feed and the energy of the excreta (poultry) or faeces plus urine (swine); gross energy is measured using bomb calorimetry.

Higher digestibilityIt is clear that an ingredient with a high

AME will have higher digestibility of the major

nutrients, that is, starch, protein and fat, than a similar ingredient with a low AME.

Thus, it is not surprising that most of the equations for energy determination of ingredi-ents or diets for broilers and swine are based on values of nutrient concentration (starch, protein, fat), multiplied by their respective digestibility coefficients (which are determined as an average for the ingredient). These equa-tions work well when comparing different ingredients (for example, wheat versus maize) that have different nutrient composition and nutrient digestibility.

However, such equations are less accurate when applied to individual ingredients as, in most cases, nutrient content varies less than digestibility between samples. In the case of wheat, although AME and starch digestibility are reported to be correlated, this does not account for all the variation found between different varieties, as a result of different grow-ing environment and year of production to name a few variables of interest.

The ability to identify all parameters involved in determining the nutritive value of a cereal is an ultimate goal of any nutritionist as this will enable more accurate formula-tions and, as a result, more consistent animal performance.

Quality of cereals could be summarised as the concentration of nutrients and physi-cochemical factors that may affect the digest-ibility of these nutrients.

Nutrient concentration can be analysed by proximate analysis while physiochemical

by Tiago Tedeschi dos Santos and Helen Masey O’Neill, AB Vista, UK

ASSESSING CEREAL QUALITY PARAMETERS

Grain&feed millinG technoloGy10 | march - april 2012

FEATURE

factors that may affect digestibility, like protein solubility index, vitreousness and viscosity parameters can also be analysed by their own specific methods.

The high volume of use of these ingre-dients and the cost of each specific analysis may be a limitation of controlling the qual-ity of these cereals, as to do so it would be necessary to have a constant evaluation of the quality of these ingredients, remembering that they compose on average 60-65 percent of the feed provided to animals.

One alternative for this challenge is to evaluate these parameters through NIR analy-sis; if well adjusted with wet chemistry analysis and constantly updated, NIR can give a reli-able, accurate and fast analysis.

At the same time, the lower cost of NIR compared to the analysis of all proximate and physiochemical parameters allows the nutritionist to expand the volume of samples, also giving a more accurate picture of the real quality of these ingredients.

Proximate analysisThe region of production affects the proxi-

mate analysis of maize (see Table 1) and sor-ghum (see Table 2).

Obviously, within these large regions the quality of cereal may also change.

In addition to the region, the time of the year of the harvest (summer or winter) also influences the nutritional value of maize.

Fewer sorghum samples were collected but nevertheless it was possible to observe regional effects between samples harvested in Australia, Mexico and South America.

It is known that cereals vary considerably in composition with environment, growth region, agronomic inputs and variety. Starch can vary from around 550g/kg to 750g/kg in cereals.

A study in the USA in 1999 showed crude protein (CP) in maize across 16 states varied between 73.1 and 90.6g/kg and a separate study of 23 UK wheat samples showed vari-ability between 85 and 151g/kg.

Environment is most likely to be the cause of variation in chemical composition; elevated temperatures during grain filling may decrease starch content and increase protein.

Within the starch, amylose to amylopectin ratio may also be affected; across 15 countries, total starch in wheat varied between 65 and 70 percent and the amylopectin content of that starch varied between 73 and 83 percent.

In broilers, ileal starch digestibility can be upwards of 90 percent Starch content (and protein, which is correlated to starch) are clearly important and because anti-nutritional factors such as NSP detract from the overall quality of the cereal, it is important to have accurate knowledge of the proximate com-position.

After harvest, cereal handling may vary considerably before being fed to animals.

One of the most detrimental procedures is drying, where moisture content is reduced in order to prevent germination and spoilage during storage. Maize harvested at a high moisture level needs more rigorous drying, which will change the characteristic of the grain and the availability of nutrients.

Heat treatmentThe Protein Solubility Index (PSI) is an

indicator of the severity of heat treatment on the maize sample and has a high correla-tion with the starch extraction in bioethanol production. Research has already shown a good relationship between PSI and animal performance of birds fed maize with similar proximate analysis, showing that nutrient con-tent alone cannot explain the nutritive value of the maize.

However, other researchers have shown that broilers fed maize with similar proximate analysis and PSI still differed in performance, suggesting that other factors also play a role in defining maize quality.

Higher drying temperature increases starch granule size and rigidity, reduces starch viscos-ity and increases the temperature necessary for subsequent gelatinisation, but is depend-ent on moisture content.

Interestingly, the hydration capacity of the grain is negatively correlated with the AME of wheat and triticale for broilers but positively correlated with that of sorghum.

Grain&feed millinG technoloGy march - april 2012 | 11

FEATURE

Page 3: Assessing cereal quality parameters

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Operations ManagerJAMES VALLEY GRAIN, LLCOakes, North Dakota, U.S.A.

*Grain Journal, Country Journal Publishing Co., Inc., Decatur, Illinois, U.S.A. The color blue, when used in connection with elevator buckets, is a U.S. registered trademark owned by Tapco Inc. © 2012 Tapco Inc.® All rights reserved.

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When James Valley Grain installed Tapco buckets in theirnew facility in 2001, nobody expected them to last this long.

A lot of commodities of differentdensity variations – like wheat, cornand soybeans – have run through the

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“We went from five million bushels the first year to around 30 million the last four years,” Jamie Mattson, OperationsManager, James Valley Grain, says. “In fact, I just looked it up and

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Page 4: Assessing cereal quality parameters

So, similarly to PSI, the value of a vitreous-ness measure may be in contributing to a more complex equation.

Sorghum samples also show a correlation between vitreousness and protein content. In sorghum, high protein content is related with a higher quantity of kafirin, which is a prolamin storage protein in sorghum as zein is in maize. When there is a high temperature drought, kafirin may be further cross-linked with disul-phide bridges, further decreasing its solubility and affecting starch solubility.

This process occurs to a greater extent in kafirn than with zein, which suggests that drying and pelleting temperatures may be of greater significance with sorghum than with maize.

ConclusionEven examples of wheat where overall

quality is low (as measured by AME), the starch, when extracted and fed to an animal, is extremely well digested.

So it is likely that a combination of factors and the interactions between components contribute to nutritional value for the animal, not simply the starch itself.

This further suggests that a combination of factors is necessary to predict quality of cereals. As these factors change depending on harvest time or sample origin, constant monitoring of cereal quality, as made possible by NIR analysis, is advisable,

A recent animal study in China comparing five different maize samples confirmed that no one value can predict performance.

Thus, knowledge of the composition and factors affecting digestibility of the grain is cru-cial for predicting quality and also for making informed decisions on whether this prediction should be used in feed formulation.

Dietary xylanase, when used in maize-based poultry diets, is well-known to reduce performance variation both within and between flocks; xylanase is more efficacious in improving nutrient digestibility in diets with low quality cereals.

Southeast samples had higher PSI while Northern samples, known to be harvested in a more humid environment, have a lower PSI value, closer to values found with Canadian samples.

For sorghum samples, on the other hand, the harvest is usually conducted during a much drier period and as a result drying is usually not necessary, and consequently the differences between Brazilian and Mexican samples are low.

Vitreousness (hardness) is a measure of the amount of vitreous endosperm present in

the kernel and is related to evolution of the grain to protect against digestion and weather. USA/Canadian maize tends to have lower vit-reousness than South American (see Table 3).

Prolamin proteins, such as zeins, tend to be more concentrated in vitreous maize, which is confirmed in our data that shows a high correlation between protein content and vitreousness. Furthermore there is a positive relationship between NSPs and vitreousness in maize (data not shown).

There is little information in the literature relating maize vitreousness (as an isolated value) to bird performance.

However, it seems that when a large range of wheat hardness scores are investigated, a positive correlation is found between starch digestibility and hardness. On the other hand, authors investigating a small range of scores in the middle of the scale failed to find any relationship between hardness and starch digestibility.

Authors comparing six maize variants that appeared to be quite similar in hardness char-acteristics did report significant broiler per-formance differences between the samples.

However, the differences were small and only seen between weeks 0-2 and 4-6 of the bird experiment. When two maize samples similar in composition but differing in hardness and kernel size were compared, they were found not to be different in broiler perform-ance response (feed efficiency) between day 0 and 42 in two separate studies.

In the case of sorghum, this is likely due to increased drying temperature changing the structure of the starch such that it hydrates more slowly which would clearly reduce AME.

With wheat and triticale this effect of drying temperature on starch is overwhelmed by that on NSP. In this case higher drying temperatures disrupt the NSP structure, mak-ing it more soluble (i.e. more rapidly hydrated) and viscous, which clearly negatively influences AME. The effect of drying temperature on starch structure is indicated by decreased PSI.

Starch and protein within the kernel are closely associated but their relationship is affected by heat treatment. Maize that has been dried at high temperatures due to weather conditions at harvest has a decreased protein solubility, which appears to be linearly related to the initial moisture content and drying temperature employed.

The PSI value is calculated by determining solubility of protein in an alkali solution, as a percentage of an albumin standard. It has been shown that this value alone can indicate decreased nutritional value for an animal. However, it also may provide a useful correc-tion factor within a multi-factorial prediction equation for nutritional value.

Regional effect on PSIFrom our own internal data for maize

(see Table 3) and sorghum (see Table 4), it is possible to see that there is also a regional effect on PSI, but as the regions differ in their post-harvest treatment, it is not clear whether it is regions per se having such an effect on this parameter in the same way that it seems to on vitreousness.

It is interesting to see that the season when the maize is harvested also influences the PSI result, which is likely related to the moisture content at harvest and subsequent drying.

In confirmation of this observation, when separating US maize by region (North and Southeast - data not shown), it is possible to see

Grain&feed millinG technoloGy12 | march - april 2012

The three cereals most routinely

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maize,wheat

and sorghum

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