This articles intends to contribute to a better understanding of corn variability. Leading to a better understanding of the parameters affected, determine key indicators, measure them, and generate strategies in corn production and processing that minimize such variability.
Understanding corn variability
Corn is the most common feed ingredient used in poultry nutrition worldwide. Consequently, it is the most common physical and biochemical factor affecting the bird’s intestines after drinking water.
Variability in corn composition (understanding what it implies)
In animal nutrition, yellow dent corn tends to be categorized by:
An alternative pathway is establishing a better understanding of the parameters affected for each factor, determine key indicators, measure them, and generate strategies in corn production and processing that minimize the variability.
We intend to contribute to spreading the understanding of corn variability.
This first article on this topic will address recent advances in understanding the:
This information was partially presented at the Arkansas Nutrition Conference in September 2021.
However, the accuracy of estimating those energy values for feed formulation is not always satisfactory due to the:
Variability is part of nature, and there is an inevitable proportion impossible to control. For example, recently, Diego Melo Duran, in his Ph.D. dissertation from the Autonomous University of Barcelona in Spain, concluded that:
“The position of the kernel in the cob cause variation in the nutrient and non-starch polysaccharides (NSP) content of the grain.”
The content of all nutrients or their availability to generate energy could be variable in corn depending on:
In Dr. Melo Duran’s studies, the:
The soluble AX of some maize varieties could be similar to wheat promoting digesta and excreta viscosity issues. On the other hand, some corn varieties have less nutrient and NSP content variability.
Consequently, a long-term goal could be to use corn breeding and genetic selection to minimize this variability in corn nutritional value.
The variation in corn crude protein is close to 5 percentage points from 8 to 13%, but more important is the variation in zein content, the main corn protein.
The starch content variability is around 2%,but the final amylose to amylopectin ratio (AM:AP) may play a bigger role in energy and nutrient availability.
Variability in physico-chemical properties of corn
Maize vitreousness, the ratio of hard to soft endosperm, is related to starch properties and zein content and highly correlated (r = 0.87) with kernel density and, consequently, with corn harvest yields.
However, the zein content and its interactions with starch contribute more to vitreousness properties than starch molecular properties.
Another marker of corn nutritional value is the extractable salt-soluble protein content or protein solubility index (PSI) in 0.5M NaCl.
This test is a laboratory methodology used in France and many parts of the world to evaluate corn quality.
The standard French Promatest method NF-V03-741 (AFNOR, 2008) can be used to determine PSI, and these values can be estimated with NIRS.
Effects of thermal processing in corn variability
Our studies at NC State University have indicated that drying corn at 120 oC can cause more amylose within starch (25.5%) than drying at 35 oC (21.5%) and increases the starch gelatinization linearly without observing significant differences among the drying temperatures evaluated.
The previous observations are just a few of the multiple impacts of drying temperatures in corn of different kernel hardness.
In experiments conducted in my lab, we concluded that:
Hot air-drying at either 80 or 120 oC decreased:
However, when corn kernels with harder endosperm (63.61% vitreousness) were dried, no changes in vitreousness, PSI, and NSPs due to drying temperature were observed.
In the harder endosperm, higher drying temperatures decreased the content of damaged starch and increased the AX compared to drying at 35 oC.
Damaged starch is a valuable parameter for assessing the quality of flours.
We observed interactive effects of corn variety and drying temperature on:
On the other side, the storage time decreased:
Figure 1. Effect of kernel hardness and drying temperature on
particle size (Dgw) in a hammermill at 12-12 screen (4.76 mm)
with 900, 2,400, and 3,600 rpm (NC State University research)
Figure 2. Effect of kernel hardness and drying temperature on standard deviation (Sgw) in hammermill at 12-12 screen (4.76 mm, US mesh 4) at 900, 2,400, and 3,600 rpm (NC State University research).
Figure 3. Effect of corn kernel hardness (average and hard) and drying temperature (35, 80, and 120 oC) on FCR at 40 d. Means not sharing a common superscript (a-c) are significantly different (n=8; P < 0.01) by Tukey’s test (NC State University research)
In the next article, we will discuss in more detail these impacts on energy value for poultry, non-starch polysaccharide content, proposals to determine the best quality corn, and how to control its variability better.
Source: Written by Edgar Orlando Oviedo-Rondón *Prestage Department of Poultry Science, North Carolina State University, Raleigh, NC Corresponding Author: firstname.lastname@example.org
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