Analytical Uncertainty in Animal Feed Laboratories: A Current Evaluation of AAFCO Proficiency Testing Data for Select Analytes

Authors

  • Timothy Herrman Texas AgriLife Research
  • Kyung-min Lee Texas A&M AgriLife Research https://orcid.org/0000-0003-2083-8436
  • Yi-Cheng Hsieh Texas A&M AgriLife Research
  • Sara Williams Texas A&M AgriLife Research

DOI:

https://doi.org/10.21423/JRS-V10I1HERRMAN

Keywords:

analytical variability; animal feed; measurement uncertainty, Association of American Feed Control Officials (AAFCO); proficiency test

Abstract

The animal feed regulatory community utilizes analytical variations (AVs) that account for the normal variability that occurs within and between laboratories.  The AV was created using the Association of American Feed Control Officials (AAFCO) proficiency testing (PT) program results and represent the coefficient of variation times 2 (2 CV). This study was performed to assess the accuracy of the published AVs within the association’s Official Publication (OP) using AAFCO PT data from 2014 to 2020. This study also reevaluated the current AV values by applying the concept of the measurement uncertainties including the expanded uncertainty (U), Horwitz value, and 2 CV for the assessment of the label guarantees. Although greater variations were observed at lower concentrations, the majority of data points from the PT rounds showed an acceptable reproducibility for the select analytical methods except for cobalt, fat, fiber, moisture, and selenium where 2 CV was higher than the current AAFCO AV.  Regression models were developed based on the 95% tolerance interval of expanded uncertainty and 2 CV and were validated using the 2019-2020 AAFCO PT data. The validation data fell within the expanded uncertainty and 2 CV model bounds indicating the new models were fit-for-purpose and accurately characterized current AAFCO PT data.  The study results imply the AAFCO AV and its issues need to be better understood to improve an accuracy and traceability of the laboratory’s measurement and thus regulatory decisions to help animal feed producers and processors lower economic losses.

References

Association of American Feed Control Officials (AAFCO). (2018). GOOD Test Portions: Guidance on Obtaining Defensible Test Portions. AAFCO, Champaign, IL. http://www.aafco.org/Publications/ GOODTestPortions.

AAFCO. (1986). Official publication. Association of American Feed Control Officials.

AAFCO. (2000). Official publication. Association of American Feed Control Officials.

Boyer, K.W., Horwitz, W., & Albert, R. (1985). Interlaboratory variability in trace element analysis. Analytical Chemistry, 57(2), 454-459.

Earnshaw, A, Smith, R. A., & Owen, L. (2009). How proficiency testing can improve the quality of analytical data using vitamin analysis as an example. Food Chemistry, 113(3), 781-783.

Ellison, S. L. R., & Williams, A. (2012). Quantifying uncertainty in analytical measurement. 3rd ed. Eurachem/CITAC guide. http://www.eurachem.org.

Farkas, Z., Slate, A., Whitaker, T. B., Suszter, G., & Ambrus, Á. (2015). Use of combined uncertainty of pesticide residue results for testing compliance with maximum residue limits (MRLs). Journal of Agricultural and Food Chemistry, 63(18), 4418-4428.

Fenton, N., & Neil, M. (2018). Risk assessment and decision analysis with Bayesian networks. Boca Raton, FL: CRC Press.

Fussell, R. J., Hetmanski, M. T., Macarthur, R., Findlay, D., Smith, F., Ambrus, Á., & Brodesser, P. J. (2007). Measurement uncertainty associated with sample processing of oranges and tomatoes for pesticide residue analysis. Journal of Agricultural and Food Chemistry, 55(4), 1062-1070.

Horwitz, W. (1982). Evaluation of analytical methods used for regulation of foods and drugs. Analytical chemistry, 54(1), 67-76.

Horwitz, W. (2003). The certainty of uncertainty. Journal of AOAC International, 86(1), 109-111.

Horwitz, W., Britton, P., & Chirtel, S. J. (1998). A simple method for evaluating data from an interlaboratory study. Journal of AOAC International, 81(6), 1257-1266.

Horwitz, W., Kamps, L. V. R., & Boyer, K. W. (1980). Quality assurance in the analysis of foods for trace constituents. Journal of the Association of Official Analytical Chemists, 63(6), 1344-1354.

International Organization for Standardization. (2005). ISO 13528:2005 Statistical method for use in proficiency testing by interlaboratory comparison. ISO, Geneva.

International Organization for Standardization. (2010). ISO 17043:2010 Conformity assessment-general requirements for proficiency testing. ISO, Geneva.

International Organization for Standardization. (2017). ISO/IEC 17025 General requirements for the competence of testing and calibration laboratories. ISO, Geneva.

International Organization for Standardization. (1997). ISO/IEC Guide 43–1 Proficiency testing by interlaboratory comparisons—Part 1: Development and operation of proficiency testing schemes. 2nd ed. ISO, Geneva.

JCGM. (2012). Evaluation of measurement data–the role of measurement uncertainty in conformity assessment. JCGM 106.

Johnson, R. L., Latimer Jr., G. W., & Spiegelman, C. (1994). Use of trimmed duplicates derived from laboratory data to estimate standard deviation. Journal of AOAC International, 77(6), 1660-1663.

Omeroglu, P. Y., Ámbrus, Á., Boyacioglu, D., & Majzik, E. S. (2013). Uncertainty of the sample size reduction step in pesticide residue analysis of large-sized crops. Food Additives & Contaminants: Part A, 30(1), 116-126.

Regan, H. M., Colyvan, M., & Burgman, M. A. (2002). A taxonomy and treatment of uncertainty for ecology and conservation biology. Ecological Applications, 12(2), 618-628.

Taverniers, I., De Loose, M., & Bockstaele, Van E. (2004). Trends in quality in the analytical laboratory. I. Traceability and measurement uncertainty of analytical results. TrAC Trends in Analytical Chemistry, 23(7), 480-490.

Thompson, M. & Lowthian, P. J. (1996). Statistical aspects of proficiency testing in analytical laboratories. Part 1. Ranking of participants on scores is misleading. Analyst, 121(11), 1589-1592.

Thompson, M. & Lowthian, P. J. (1997). The Horwitz function revisited. Journal of AOAC International, 80(3), 676-680.

Thompson, M., & Wood, R. (1993). The international harmonized protocol for the proficiency testing of (chemical) analytical laboratories (Technical Report). Pure Appl Chem, 65(9), 2123-2144.

Thompson, M. (2012). The characteristic function, a method-specific alternative to the Horwitz function. Journal of AOAC International, 95(6), 1803-1806.

Thompson, M., Ellison, S. L., & Wood, R. (2006). The International Harmonized Protocol for the proficiency testing of analytical chemistry laboratories (IUPAC Technical Report). Pure and Applied Chemistry, 78(1), 145-196.

Trucksess, M. W., Whitaker, T. B., Weaver, C. M., Slate, A., Giesbrecht, F. G., Rader, J. I., & Betz, J. M. (2009). Sampling and analytical variability associated with the determination of total aflatoxins and ochratoxin A in powdered ginger sold as a dietary supplement in capsules. Journal of Agricultural and Food Chemistry, 57(2), 321-325.

Uusitalo, L., Lehikoinen, A., Helle, I., & Myrberg, K. (2015). An overview of methods to evaluate uncertainty of deterministic models in decision support. Environmental Modelling & Software, 63, 24-31.

Wallace, J. (2010). Ten methods for calculating the uncertainty of measurement. Science & Justice, 50(4), 182-186.

Whitaker, T.B., Hagler, W. M., Giesbrecht, F. G., & Johansson, A. S. (2000). Sampling, sample preparation, and analytical variability associated with testing wheat for deoxynivalenol. Journal of AOAC International, 83(5), 1285-1292.

Williams, A. (2008). Principles of the EURACHEM/CITAC guide “Use of uncertainty information in compliance assessment”. Accreditation and Quality Assurance, 13(11), 633-638.

Downloads

Published

2022-05-11 — Updated on 2022-05-26

Versions

Issue

Section

Scientific Articles

Most read articles by the same author(s)