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QA/QC Programs

QA/QC Programs. Agricultural and Environmental Services Laboratories (AESL). Leticia Sonon University of Georgia. AESL Director. Soil Lab Coordinator. Feeds Lab Coordinator. Pesticides Lab Coordinator. Trace Lab Coordinator. QA/QC Officer. Objectives. Produce accurate and precise data.

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QA/QC Programs

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  1. QA/QC Programs Agricultural and Environmental Services Laboratories (AESL) Leticia Sonon University of Georgia

  2. AESL Director Soil Lab Coordinator Feeds Lab Coordinator Pesticides Lab Coordinator Trace Lab Coordinator QA/QC Officer

  3. Objectives • Produce accurate and precise data. • Minimize analyst and procedural errors. • Assess the quality of the analytical data. • Document decisions and quality measures.

  4. Assessment Implementation Corrective Action Planning

  5. What the director/coordinators see: • Summaries • Lab Monitor • EPD Parameters Analyzed • Extension Specialist Samples • Yearly Summary • Water • Drinking Water Standards • Water Chemistry Balances • Miscellaneous • Error Tracking • Employee Contact Information • County Program Usage • Proficiency Tests • Projects Page • International Samples Animal Waste Animal Waste QC Sulfur: ICP vs. ICP Yearly Litter Samples Litter Averages Plant Ranges Sulfur: ICP vs. CNS Soil pH vs. Mehlich weight Swapped Sets Model Scale Direct Client Submission SPW Accounting SPW Auditor Yearly Invoices Ages Receivables

  6. UPS Bar Code Check

  7. Check soil

  8. B 20R 10R 20 10 Check Mehlich I Set “Community work” 1 check 2 duplicates 1 blank

  9. 9/19 B Mehlich Redips Technician 2 20R 10R 20 10 19 Check 9

  10. B 20R 10R 9 20 10 19 Check 9/19 Mehlich Redips

  11. Today's checks and 9/19s. (Exceptions for short sets or small samples). Good to go!

  12. 10/04 B Re-extract re-analyze

  13. Soil pH Set 20R 2 checks 2 duplicates 10R 20 10 Check Check

  14. Swapped Sets Model (Rick Hitchcock) Why needed: • On few occasions, we discovered that a technician had run two or more pH sets out of order. Client questioned the results. • Two groups of three sets had been swapped. Correct Order: G-H-I and J-K-L Actual order: J-L-K and G-H-I • This resulted in incorrect pH results and lime recommendations for 216 samples, affecting 28 clients in 14 counties.

  15. New Model (Rick Hitchcock – Programmer) How many times have we seen this combination of pH, Mehlich, and soil province before? Group analytical parameters into categories of Very Low, Low, Medium, High, and Very High. These categories are relative depending on parameter, so I've calculated them by creating five equal-sized partitions of three years' worth of data. Here are the ranges per parameter (Mehlich is in lbs/acre): Simply counting the number of times we've seen a combination wouldn't be useful, because some sets will have unusual data. But if we compared the count with that of other sets after substituting their pH data into the Mehlich set, we could determine which pH set best matches the data. The assumption is that an unusual set will produce a higher count than a random set. The program normalizes the count to produce a score.

  16. Below is the model on the day that the technician ran pH sets out of order. A green score means that the pH set matches the corresponding Mehlich set. It will always be the highest score within its row. Yellow, orange, and red indicate the relative likelihood of errors. The Hits column lists the pH set that best matches the Mehlich set. In this case, the model correctly predicted the order in which pH was analyzed.

  17. Below is the model after correcting for the technician’s error. All sets are green, because each pH set now matches the corresponding Mehlich set.

  18. Research Soil Samples – Weights Comparison • pH (20 g) and Mehlich I (5 grams) samples • Average ratio of pH:Mehlich weights is 4.75 (5248 samples) • Criteria of Acceptance (CoA) of ± 0.75 g, giving an acceptable range of 4.00-5.5 g. This is equivalent to ± 16%. • When weights are outside our CoA, sets are rerun. Last fiscal year, only 4.25% of research soils were flagged. • Occasional exceptions, due to the material of the soil or the amount of soil submitted. • A Criteria of Acceptance (CoA) is established and adhered to before any data are reported back to the client.

  19. Water Testing

  20. External Audits of Our Work • Assoc. of American Feed Control Officials (AAFCO): Feeds • Env. Resource Associates (ERA): Fecal coliform and E. coli in water • MN Dept. of Agriculture Manure Analysis Proficiency (MAP): Manure • National Forage Testing Association (NFTA): Forage and hays • Agriculture Agricultural Laboratory ProficiencyProgram (ALP): Soil and plant • NSI Solutions, Inc.: Water • State of Georgia EPD (EPD): Drinking water microbiology • United States Geological Survey (USGS): Water

  21. QA/QC Officer • Proficiency Programs • ALP (soil + plant) • MAP (manure) • USGS (Water)

  22. Soil Test Handbook For Georgia Agricultural and Environmental Services Laboratories Cooperative Extension, College of Agriculture and Environmental Sciences The University of Georgia

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