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Livestock Production
Tuesday, July 19, 2016 8:08:25 PM
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Is it possible to predict broiler performance through NIR?

 

Usama Aftab, AB Vista Asia Pte Ltd.

 

 

Corn serves as the major cereal for the most poultry and swine diets. Contributing about 60-65% of the dietary energy (AME), a minor variance in the quality of the corn could have a significant effect on the energy supply and hence the growth performance of the animal. Direct assessment of the feed ingredient AME is a specialized and expensive process and therefore it is not performed as part of routine QC in the feed mill operation. As an easy alternative, nutritionists often rely on the simple parameters like Dry Matter (DM) as the basis for 'correcting' the ME content and use this information for segregating different batches of incoming corn for storage and subsequent usage. Although the DM content is an important determinant, the true nutritional (energy) value of the corn would likely be influenced by several other variables, including starch (both type and the content), fat, protein and fiber as well as the conditions applied during the process of grain drying. This drives research to develop equations to predict the AME content of feed ingredients, taking into account a range of potential variables. The worth of these predictions would depend on how closely these reflect the performance of animals fed diets formulated on these predicted values. In the absence of this assessment, the predicted AME may have no biological sense.

 

Researchers at AB Vista developed a NIR-enabled prediction model for assessing the quality of the corn for broilers. These predictions were developed taking into account factors known to affect the feeding value of corn. So in addition to the DM and nutrient contents, other key variables such as vitreousness (starch-type and starch-protein interactions) and a specific protein solubility index (which measures the degree of grain drying, mild to harsh) were included. As part of the assessment of the biological significance of this prediction model, a broiler growth study was conducted involving six corn samples collected from different states in the USA. Each of these samples was fed to broilers as part of a common basal diet (Table1) and the growth performance was recorded from 1-41 days posthatch. The objective of the study was to assess, 1) if the growth performance of the broilers was affected by different corn samples, and 2) if the variance in growth performance can be accounted for by the predicted AME of the source corn. Table 2 summarized the data on the NIR-predicted AME of the test corns and the effect on growth performance of broilers. A fitted regression line (Figure 1) revealed that 79% of the variability in the broiler FCR was explained by the NIR predicted AME of the test corns. Ileal Digestible Energy (IDE), measurements at 17 or 41 day for the same set of corn samples, was shown to explain 60% or 17%, respectively, of the variance in 41-day-FCR (data not shown).    

 

Summary
 

NIR is a common tool in modern feed mill QC labs. Recent advances in the NIR technology make the energy predictions of corn, and other feedstuffs, possible on day to day basis. High correlation with animal performance supports the robust nature of the NIR-enabled AME predictions within the AB Vista Corn Quality Service.       

 

Table 1. Composition of the trial diets

 

Ingredient/Nutrient

Starter (0-18 d)

Grower (19-33 d)

Finisher (34-41 d)

Corn

61.60

65.00

70.00

SBM

32.60

29.70

24.00

Limestone

1.58

1.46

1.36

Biofos

1.57

1.40

1.29

Fat (blended)

1.50

1.30

1.10

Salt

0.46

0.40

0.18

DL-Methionine

0.26

0.23

0.23

Vitamins

0.25

0.25

0.25

Lysine HCl

0.17

0.14

0.21

Minerals

0.05

0.05

0.05

Coban 90

0.05

0.05

0.05

L-Threonine

0.02

-

0.03

Sodium bicarbonate

-

0.09

0.31

Calculated nutrients

 

 

 

ME (kCal/kg)

3000

3025

3075

Crude Protein

21.30

20.20

18.00

SID Lysine

1.13

1.04

0.95

Calcium

0.95

0.87

0.80

Av. Phosphorous

0.45

0.41

0.38

 

Table 2. Predicted corn ME and growth performance, 1-41 days


Corn source

NIR-predicted ME,

Gain, g

FCR, 

Kcal per kg

bw corrected

Iowa

3266

2806

1.681

Minnesota 

3213

2734

1.743

Nebraska 

3238

2734

1.721

North Dakota 

3257

2732

1.708

South Dakota 

3243

2782

1.676

Texas 

3317

2799

1.643

 

Figure 1.  Body weight corrected FCR vs. NIR-predicted ME of corn

 

 

   

For more of the article, please click here.

 

Article made possible through the contribution of Usama Aftab and AB Vista Asia Pte Ltd.

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