Understanding Laboratory Variation: Why the Same Feed Sample Can Produce Different Results ​

Both results may be correct within analytical tolerance. 

Small differences between laboratories can arise from: 

• analytical method differences 

• calibration standards 

• sample preparation procedures 

• technician handling variation 

These factors are common in analytical testing and do not necessarily indicate a problem with ingredient quality or formulation accuracy. 

Natural Ingredient Variation Comes First

Before analytical variation is considered, it is important to recognize that feed ingredients themselves are not uniform. 

Agricultural ingredients such as corn and soybean meal vary naturally due to environmental and genetic factors. 

A cooperative research study evaluating nutrient composition of corn and soybean meal across multiple regions of the United States demonstrated substantial variation among ingredient sources. Selenium concentrations in corn ranged from 0.02 to 0.29 mg/kg, while soybean meal ranged from 0.08 to 0.95 mg/kg, depending largely on geographic location and soil mineral content. 

Crude protein and amino acid concentrations also varied between sources. 

These differences arise from factors including: 

• soil fertility and mineral composition 

• crop genetics and hybrid selection 

• climate and rainfall patterns 

• agronomic management practices 

• processing differences in ingredient production 

Because of these influences, even well-established feed ingredients cannot be assumed to have identical nutrient profiles across suppliers or regions. 

For nutritionists and feed manufacturers, this means that some variation observed in laboratory reports reflects real biological differences in ingredients, not analytical error. 

Analytical Variation Between Laboratories

Even when identical samples are analyzed, laboratories may produce slightly different results, which is a key challenge when understanding feed test results. 

Differences in instrumentation, calibration standards, sample preparation procedures, and technician handling can all influence analytical results. 

In a multi-laboratory study analyzing identical corn and soybean meal samples, researchers found that analytical variability between laboratories was sometimes as large as the variation observed among ingredient sources themselves. 

Several factors contribute to inter-laboratory variation: 

• analytical instrumentation 

• calibration standards and reference materials 

• extraction procedures 

• technician experience 

• interpretation of analytical protocols 

To help interpret these differences, it is useful to understand typical levels of analytical variability. 

Table 1. Typical Analytical Variation in Feed Testing 

CV = Coefficient of Variation 

These ranges vary depending on analytical method, laboratory proficiency, and sample preparation procedures. Understanding expected analytical variation helps nutritionists interpret laboratory results more realistically. 

Manufacturing Variation Can Influence Analytical Results

Laboratory variation is only one component of the analytical chain. Nutrient distribution within feed manufacturing systems can also introduce variability before samples are collected. 

A cooperative study involving 25 research feed mills evaluated the consistency of diet mixing using a common formula. Despite identical formulations, measured nutrient concentrations varied substantially among mixed diets. 

For example, zinc concentrations ranged from 71 ppm to 182 ppm, even though the targeted inclusion level was 125 ppm. 

Manufacturing factors contributing to variation include: 

• mixer efficiency and mixing time 

• ingredient particle size differences 

• density differences between ingredients 

• segregation during conveying or discharge 

• micro-ingredient inclusion accuracy 

These findings demonstrate that laboratory results often reflect the combined effects of formulation, manufacturing, sampling, and analytical measurement.