Can Two Laboratories Test the Same Product and Get Different Results?
One laboratory reports 4.8 parts per billion (ppb) of a contaminant. Another reports 5.3 ppb. Which one should consumers believe?
At first glance, the difference might suggest that one laboratory made a mistake. But laboratory testing is more complex than comparing two numbers.
Both results could be scientifically valid, depending on how the samples were collected, prepared, analyzed, and interpreted.
Understanding these differences matters, particularly when laboratory findings are used to evaluate product quality, substantiate marketing claims, or assess potential exposure to contaminants.
1. A Small Numerical Difference May Not Be a Significant Scientific Difference
Consider these two results:
Laboratory A: 4.8 ppb
Laboratory B: 5.3 ppb
The difference is 0.5 ppb, or approximately 9.9% of the average of the two measurements.
That percentage alone cannot tell us whether the results are scientifically inconsistent.
Every analytical measurement has some degree of uncertainty. The National Institute of Standards and Technology (NIST) explains that measurement uncertainty can be expressed as a range around a reported result.
For example, imagine two laboratories reported:
Laboratory A: 4.8 ± 0.6 ppb
Laboratory B: 5.3 ± 0.7 ppb
These hypothetical uncertainty intervals overlap, suggesting the results may be compatible. However, determining whether two measurements agree requires considering how the uncertainty estimates were calculated, their coverage levels, and whether the measurements are independent.
An important statistic: According to NIST, an expanded uncertainty calculated using a coverage factor of 2 corresponds to approximately 95% confidence under appropriate statistical assumptions.
This is why scientists consider measurement uncertainty rather than treating every decimal-place difference as evidence of an error.
Source: NIST, Expanded Uncertainty and Coverage Factors.
2. The Sample Itself Can Change the Results
Even when laboratories test the same product, they may not be analyzing identical material.
For example, two packages of a plant-based protein powder could contain different concentrations of naturally occurring elements because of variations in:
Agricultural growing conditions
Soil and water composition
Raw material sourcing
Manufacturing and blending processes
Differences between production batches
Even within a single package, contaminants may not be distributed perfectly evenly.
To reduce these differences, laboratories often homogenize samples, meaning they blend or process material to make the portion being tested as representative as possible.
The FDA's Elemental Analysis Manual, Section 2.2, provides specific procedures for food homogenization. Section 3.3 also addresses sampling uncertainty and sample heterogeneity.
Why this matters: Testing one package provides information about the material analyzed. It does not necessarily establish the contaminant concentration in every package, batch, or future production run.
A broader testing program that includes multiple samples and production batches can provide a more representative picture of product consistency.
3. Different Methods Can Produce Different Results
Not all laboratory methods have identical capabilities.
The FDA's Elemental Analysis Manual includes Method 4.7, which uses inductively coupled plasma-mass spectrometry (ICP-MS) to analyze elements such as lead, cadmium, arsenic, and mercury in foods.
This method involves preparing the sample through acid digestion before measuring elemental concentrations.
However, laboratories may use different validated methods, equipment, sample preparation procedures, or reporting criteria.
One especially important distinction is between a method's limit of detection (LOD) and limit of quantitation (LOQ).
LOD: The lowest concentration a method can reliably distinguish from the absence of the analyte under specified conditions.
LOQ: The lowest concentration a method can reliably measure quantitatively while meeting defined performance criteria.
Imagine a product contains a contaminant at 3 ppb.
Laboratory A has a reporting limit of 1 ppb and may report a measurable concentration.
Laboratory B has a reporting limit of 5 ppb and may report the result as below its reporting limit.
Neither finding necessarily contradicts the other.
The key takeaway: A result reported as "not detected" does not establish that the substance is entirely absent. It indicates that the laboratory did not detect it under the conditions and detection capabilities of the method used.
Source: FDA, Elemental Analysis Manual, Sections 3.2 and 4.7.
4. How Much of a Difference Should Raise Questions?
The magnitude of a difference matters, but so does the context.
Consider three hypothetical comparisons:
Laboratory A Laboratory B Difference 4.9 ppb 5.1 ppb 4%5 ppb10 ppb66.7%5 ppb500 ppb196%
Percent differences are calculated relative to the average of the two results.
These examples illustrate why the scale of a discrepancy deserves attention.
A difference between 4.9 and 5.1 ppb may be consistent with normal analytical variation, depending on the method's performance.
A difference between 5 and 500 ppb warrants a much closer investigation into sampling, preparation, analytical procedures, units, contamination, and possible errors.
However, there is no universal percentage difference that automatically proves a laboratory result is correct or incorrect. Acceptable variability depends on the analytical method, contaminant, concentration, sample matrix, and quality-control criteria.
5. How Do Laboratories Know Their Results Are Reliable?
Laboratory quality control is an essential part of the testing process.
Reliable laboratories use procedures designed to identify contamination, evaluate accuracy, and monitor analytical performance.
These may include:
Method blanks: Samples without the product material that help identify contamination introduced during preparation or analysis.
Reference materials: Materials with known or certified concentrations used to evaluate whether a method produces accurate results.
Duplicate analyses: Repeated testing used to assess precision and identify unexpected variation.
Calibration verification: Checks that instruments continue to measure accurately throughout an analytical sequence.
Recovery studies: Evaluations of how effectively a method measures an analyte added to a sample.
The FDA's Elemental Analysis Manual dedicates sections to reference materials, instrument performance, and analytical quality control.
Importantly, accreditation under standards such as ISO/IEC 17025 provides evidence that a laboratory has demonstrated technical competence for activities within its accredited scope. It does not guarantee that every individual result is error-free.
Source: FDA, Elemental Analysis Manual, Sections 3.5 and 3.6.
6. Why the Difference Matters Even More Near a Regulatory Threshold
Consider a hypothetical regulatory limit of 5 ppb.
One laboratory reports 4.8 ppb, while another reports 5.3 ppb.
Although the numerical difference is small, the results fall on opposite sides of the hypothetical threshold.
Does that automatically establish that one product passes and the other fails?
Not necessarily.
Regulatory determinations may depend on the applicable legal standard, the required sampling protocol, analytical uncertainty, and the decision rules used to evaluate compliance.
A concentration reported slightly below a threshold is not necessarily proof that the underlying concentration is below it with high confidence. Likewise, a result slightly above a threshold may require additional context before a compliance determination can be made.
This distinction becomes especially important when testing results are used in product labeling, enforcement, or consumer protection.
It is also important to distinguish concentration-based limits from exposure-based standards. For example, California Proposition 65's safe harbor levels are often expressed as daily exposure amounts rather than concentrations in ppb.
7. Why One Test May Not Tell the Whole Story
A laboratory result represents a particular sample analyzed at a particular time.
If a manufacturer changes suppliers, reformulates a product, or introduces a new production batch, contaminant concentrations may also change.
This is why repeated testing can be valuable.
A well-designed testing program may evaluate multiple batches, monitor changes over time, and investigate unusual results rather than relying exclusively on one measurement.
For example, if several batches consistently produce results near 5 ppb but a later batch measures 50 ppb, that change may indicate a meaningful difference in the product or testing process that warrants investigation.
Repeated measurements are also useful for distinguishing isolated observations from patterns.
The goal is not simply to generate more numbers. It is to produce reliable, representative data that can support meaningful decisions.
8. What Should Consumers Look for When Comparing Results?
Before concluding that two laboratories disagree, consider several questions:
Were the samples from the same production batch or package?
Were the same contaminants and chemical forms measured?
Were the results reported in the same units?
Were the analytical methods appropriate for the product?
What were the detection and reporting limits?
Did the laboratories report measurement uncertainty?
Were the results supported by appropriate quality-control procedures?
Were the laboratories accredited for the relevant testing activities?
A laboratory report becomes much more informative when the methodology and limitations are understood alongside the numerical results.
The Bottom Line
Two laboratories can analyze the same product and report different contaminant concentrations without either laboratory necessarily being wrong.
Differences may reflect sample variability, analytical methods, detection capabilities, or measurement uncertainty. At the same time, substantial discrepancies should not be dismissed without investigation.
Scientific reliability is not determined by whether two numbers match perfectly. It depends on whether the testing methods are appropriate, the results are supported by quality control, and the findings are interpreted within their limitations.
For manufacturers, consistent testing and transparent reporting can help identify potential quality concerns and evaluate changes over time.
For consumers, understanding how laboratory measurements work provides a stronger foundation for interpreting product claims, evaluating reported findings, and making informed purchasing decisions.
Ultimately, trustworthy product testing requires more than a single number. It requires reliable methods, meaningful context, and accountability for the information being reported.
Sources and Further Reading
U.S. Food and Drug Administration (FDA). Elemental Analysis Manual for Food and Related Products. Sections 2.2 (Food Homogenization), 3.2 (Terminology), 3.3 (Measurement Uncertainty), 3.5 (Reference Materials), 3.6 (Performance), and 4.7 (ICP-MS Method).
https://www.fda.gov/food/laboratory-methods-food/elemental-analysis-manual-eam-food-and-related-productsNational Institute of Standards and Technology (NIST). Expanded Uncertainty and Coverage Factors.
https://physics.nist.gov/cuu/Uncertainty/coverage.htmlNIST. Uncertainty of Measurement Results.
https://physics.nist.gov/cuu/Uncertainty/Kacker, R. N., Datla, R. U., & Parr, A. C. (2002). Combined Result and the Associated Uncertainty from Interlaboratory Evaluations Based on the ISO Guide. Metrologia, 39(3).
https://www.nist.gov/publications/combined-result-and-associated-uncertainty-interlaboratory-evaluations-based-iso-0International Organization for Standardization (ISO). ISO/IEC 17025:2017 — General Requirements for the Competence of Testing and Calibration Laboratories.
