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AfriLAB: Regional Soil Laboratory Network for Africa | First meeting. 21 - 24 May 2019 | Nairobi, Kenya

Transcrição

  1. 1. © NERC All rights reserved Reference Materials- at the heart of reliable analysis Prepared by Dr Charles Gowing Sample Handling Manager, Inorganic Geochemistry Presented by Dr Michael Watts, Head of Inorganic Geochemistry
  2. 2. © NERC All rights reserved Dr Charles Gowing • UKAS Quality Manager • Sample Handling Manager • Reference Material Production • Radiometics Lab Manager • HH-XRFS • Radiation Protection • Internal Auditor • Proficiency Testing • Capacity Building
  3. 3. © NERC All rights reserved Why are RMs important? Quality management principles: process approach – a coherent system achieves consistent and predictable results If the method provides expected data for the RM when all steps in the method sequence are used, there is confidence that it will provide representative data for unknown samples. • Analysis of a well characterised sample provides the ultimate check of analytical method Reference materials are important tools for the transfer of measurement accuracy between laboratories especially when it is important to ensure that chemical interferences and matrix effects are adequately addressed .
  4. 4. © NERC All rights reserved ISO/IEC 17025:2005 4. Management requirements 4.1. Organization 4.2. Management system 4.3. Document control 4.4. Review of requests, tenders, contracts 4.5. Subcontracting of tests 4.6. Purchasing services and supplies 4.7. Service to the customer 4.8. Complaints 4.9. Control of non-conforming work 4.10. Improvement 4.11. Corrective actions 4.12. Preventive actions 4.13. Control of quality records 4.14. Internal audits 4.15. Management review 5. Technical requirements 5.1. General 5.2. Personnel 5.3. Accommodation & environmental conditions 5.4. Test methods and validation 5.5. Equipment 5.6. Measurement traceability 5.7. Sampling 5.8. Handling of Test items 5.9. Assuring the quality of test results 5.10. Reporting the results Quality system Technical competency ISO 17025
  5. 5. © NERC All rights reserved Technical requirements
  6. 6. © NERC All rights reserved Identifying a material Key question: for what QA purpose is the RM needed? • What type of soil? • Which horizon? • Which analysis do you want to support? • Do you want to include the “strange patches”?
  7. 7. © NERC All rights reserved
  8. 8. © NERC All rights reserved
  9. 9. © NERC All rights reserved Particle size Useable particle size: • sieved to <2 mm – widely accepted size fraction, ensuring removal of foreign objects from soil, e.g. grass, stones • sieved to <250 μm – identified as the particle size fraction that is most likely to be ingested from handling vegetables • milled to <53 μm – breakdown of soil particles allowing for increased sample homogeneity • milled to <32 μm – additional milling if solid sample analysis is undertaken where minimising particle size effects is important, e.g. aiding uptake during leaching or digestion
  10. 10. © NERC All rights reserved Sampling from the field • Select location make use of existing geochemical data and other prior information • Identify method for sampling target material e.g. topsoil, subsoil • Identify a clean area of appropriate soil type • Assess amount required coarse/fine/representivity
  11. 11. © NERC All rights reserved Sampling and storage
  12. 12. © NERC All rights reserved Transportation • Clear labelling • Secure transit • Protect package during transit • Minimise amount - pre-preparation
  13. 13. © NERC All rights reserved Drying • Stabilise the soil, prevents rotting • Outside – slow • Oven – overheating, briquetting • Freeze assisted – can help if fine grained
  14. 14. © NERC All rights reserved Initial storage • Appropriate container • Sub-divide to prepare second source • Stable environment to avoid deterioration
  15. 15. © NERC All rights reserved Initial sample division plan
  16. 16. © NERC All rights reserved Disaggregation • Lumps will not be uniformly distributed throughout material • Material might generate a product that is not representative of the original material • Disaggregation can reduce the chance of this happening • Beware potential source of contamination
  17. 17. © NERC All rights reserved Sieving • Required if certain particle size fractions are desired. • Unwanted dilution and inhomogeneity • <2 mm, <250 μm • Removal of foreign objects from soil, e.g. aggregates, grass, stones.
  18. 18. © NERC All rights reserved Homogenising a bulk • Prior operations inherently cause the material to partition. • It is important to ensure that: each split is representative of the whole; and each portion taken is representative of the subsample used.
  19. 19. © NERC All rights reserved
  20. 20. © NERC All rights reserved
  21. 21. © NERC All rights reserved Nugget effect Discrete high density particles: frequent occurrence (a); rare occurrence (b); absence(c).
  22. 22. © NERC All rights reserved Considerations for barrel • No more than half full • Rotating barrel - internal vanes • Reinforcement? • Ideally end over end, or angled
  23. 23. © NERC All rights reserved Designing a subsampling tree • Split a bulk down representatively • Generate manageable portions • Identify unique subsample identifiers A B AC AD B1 B2 ACE ACF ADG ADH B13 B14 B25 B26
  24. 24. © NERC All rights reserved Representative subsampling • Sampling plan to address controlling factors • Based on appropriate statistical methods • Record client requested deviations for reporting • Procedures for recording sampling data
  25. 25. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  26. 26. © NERC All rights reserved
  27. 27. © NERC All rights reserved
  28. 28. © NERC All rights reserved
  29. 29. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  30. 30. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  31. 31. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  32. 32. © NERC All rights reserved Temporary packaging • If required • Store labelled portions securely awaiting further dividing
  33. 33. © NERC All rights reserved Homogeneity testing • We think we have a homogenous material – but we need to test this • Random sampling to identify splits for analysis • Element selection… Sample Ni Cu Zn … ppm ppm ppm … ADF4-3 19.9 11.9 78.1 … B135-3 19.2 11.8 78.2 … B137-2 21.1 12.0 78.0 … ADE4-1 20.5 11.3 80.2 … B262-2 19.8 12.0 78.0 … B264-3 20.0 11.5 79.5 … B251-3 20.1 11.7 77.5 … ADE5-1 20.1 11.8 78.9 … B251-1 19.6 10.8 76.1 … ADF1-1 20.4 12.8 78.7 … ACG7-1 20.7 12.2 81.6 … B142-3 21.1 12.1 77.8 … B137-3 19.8 11.1 77.9 … B261-2 19.8 11.6 79.4 … ADE5-2 20.5 11.8 78.3 … … … … … … A B AC AD B1 B2 ACE ACF ADG ADH B13 B14 B25 B26
  34. 34. © NERC All rights reserved Acceptance criteria • Between-sample variability is not significantly greater than within-sample variability • F< defined value, Fcritical • Confidence limits: 95% 𝐹 = 𝐵𝑒𝑡𝑤𝑒𝑒𝑛 𝑠𝑎𝑚𝑝𝑙𝑒 𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒 𝑊𝑖𝑡ℎ𝑖𝑛 𝑠𝑎𝑚𝑝𝑙𝑒 𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒
  35. 35. © NERC All rights reserved Data analysis • Identify statistical outliers • Test for normality • ANOVA - Analysis of Variance Source of Variation SS df MS F P-value F crit Between Groups 945.8 23 41.1 1.1 0.4 2.0 Within Groups 883.5 24 36.8 Total 1829.3 47
  36. 36. © NERC All rights reserved Final splitting • If required – • use appropriate methodology as before
  37. 37. © NERC All rights reserved Storage options • Container type • Consider how this will be used, portion size etc. • Susceptibility to change in air – sealing, inert gas? • Susceptibility to settling?
  38. 38. © NERC All rights reserved
  39. 39. © NERC All rights reserved Documentation • Measurand including analyte • Measurement range (concentration) • Matrix match and potential interferences • Sample size • Homogeneity and stability • Measurement uncertainty • Value assignment procedures (measurement and statistical)
  40. 40. © NERC All rights reserved WHEN AND WHY TO USE A REFERENCE MATERIAL
  41. 41. © NERC All rights reserved Assuring the quality of test results • Quality Control (QC) procedures • Record results - to view trends • Statistical evaluation of QC data • Plan and review monitoring of QC data • CRMs, secondary standards • Proficiency Testing schemes - EPTIS • Replicates and repeats • Predefined acceptance criteria • Shewhart chart – Westgard rules • Planned action to correct and prevent
  42. 42. © NERC All rights reserved Shewhart QC chart 90 100 110 120 130 140 150 160 0 5 10 15 20 25 30 35 Concentration(mg/kg) Index As As Mean +2sd +3sd -2sd -3sd Expected
  43. 43. © NERC All rights reserved ENHANCING DATA QUALITY
  44. 44. © NERC All rights reserved Sources of error • Systematic error • Can occur… • Will be minimised by careful planning • Aim to remove entirely • Random error • Will occur • Can be quantified
  45. 45. © NERC All rights reserved Characterising Uncertainty • Analysis gives one data value • Each time a sample is analysed it will be slightly different • Many sources of random error • Combine to give a method uncertainty • Normal distribution – bell curve • Allows calculation of 95% confidence limits • Use error bars on graphs • allows meaningful data interpretation Total uncertainty
  46. 46. © NERC All rights reserved Soil-type and Se supply in Malawi: Evidence of widespread deficiency Chilimba et al. (2011) Hurst et al. (2013)
  47. 47. © NERC All rights reserved Se application (g Se ha-1 ) 0 10 20 30 GrainSe(mgSekg -1 ) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Alleviation strategies: agronomy Liquid drench y = 0.019x + 0.061 CAN+Se (granular) y = 0.015x + 0.085 NPK+Se (granular) y = 0.022x + 0.056 15-22 µg Se kg-1 grain . g-1 Se ha-1 Chilimba et al., 2012

Descrição

AfriLAB: Regional Soil Laboratory Network for Africa | First meeting. 21 - 24 May 2019 | Nairobi, Kenya

Transcrição

  1. 1. © NERC All rights reserved Reference Materials- at the heart of reliable analysis Prepared by Dr Charles Gowing Sample Handling Manager, Inorganic Geochemistry Presented by Dr Michael Watts, Head of Inorganic Geochemistry
  2. 2. © NERC All rights reserved Dr Charles Gowing • UKAS Quality Manager • Sample Handling Manager • Reference Material Production • Radiometics Lab Manager • HH-XRFS • Radiation Protection • Internal Auditor • Proficiency Testing • Capacity Building
  3. 3. © NERC All rights reserved Why are RMs important? Quality management principles: process approach – a coherent system achieves consistent and predictable results If the method provides expected data for the RM when all steps in the method sequence are used, there is confidence that it will provide representative data for unknown samples. • Analysis of a well characterised sample provides the ultimate check of analytical method Reference materials are important tools for the transfer of measurement accuracy between laboratories especially when it is important to ensure that chemical interferences and matrix effects are adequately addressed .
  4. 4. © NERC All rights reserved ISO/IEC 17025:2005 4. Management requirements 4.1. Organization 4.2. Management system 4.3. Document control 4.4. Review of requests, tenders, contracts 4.5. Subcontracting of tests 4.6. Purchasing services and supplies 4.7. Service to the customer 4.8. Complaints 4.9. Control of non-conforming work 4.10. Improvement 4.11. Corrective actions 4.12. Preventive actions 4.13. Control of quality records 4.14. Internal audits 4.15. Management review 5. Technical requirements 5.1. General 5.2. Personnel 5.3. Accommodation & environmental conditions 5.4. Test methods and validation 5.5. Equipment 5.6. Measurement traceability 5.7. Sampling 5.8. Handling of Test items 5.9. Assuring the quality of test results 5.10. Reporting the results Quality system Technical competency ISO 17025
  5. 5. © NERC All rights reserved Technical requirements
  6. 6. © NERC All rights reserved Identifying a material Key question: for what QA purpose is the RM needed? • What type of soil? • Which horizon? • Which analysis do you want to support? • Do you want to include the “strange patches”?
  7. 7. © NERC All rights reserved
  8. 8. © NERC All rights reserved
  9. 9. © NERC All rights reserved Particle size Useable particle size: • sieved to <2 mm – widely accepted size fraction, ensuring removal of foreign objects from soil, e.g. grass, stones • sieved to <250 μm – identified as the particle size fraction that is most likely to be ingested from handling vegetables • milled to <53 μm – breakdown of soil particles allowing for increased sample homogeneity • milled to <32 μm – additional milling if solid sample analysis is undertaken where minimising particle size effects is important, e.g. aiding uptake during leaching or digestion
  10. 10. © NERC All rights reserved Sampling from the field • Select location make use of existing geochemical data and other prior information • Identify method for sampling target material e.g. topsoil, subsoil • Identify a clean area of appropriate soil type • Assess amount required coarse/fine/representivity
  11. 11. © NERC All rights reserved Sampling and storage
  12. 12. © NERC All rights reserved Transportation • Clear labelling • Secure transit • Protect package during transit • Minimise amount - pre-preparation
  13. 13. © NERC All rights reserved Drying • Stabilise the soil, prevents rotting • Outside – slow • Oven – overheating, briquetting • Freeze assisted – can help if fine grained
  14. 14. © NERC All rights reserved Initial storage • Appropriate container • Sub-divide to prepare second source • Stable environment to avoid deterioration
  15. 15. © NERC All rights reserved Initial sample division plan
  16. 16. © NERC All rights reserved Disaggregation • Lumps will not be uniformly distributed throughout material • Material might generate a product that is not representative of the original material • Disaggregation can reduce the chance of this happening • Beware potential source of contamination
  17. 17. © NERC All rights reserved Sieving • Required if certain particle size fractions are desired. • Unwanted dilution and inhomogeneity • <2 mm, <250 μm • Removal of foreign objects from soil, e.g. aggregates, grass, stones.
  18. 18. © NERC All rights reserved Homogenising a bulk • Prior operations inherently cause the material to partition. • It is important to ensure that: each split is representative of the whole; and each portion taken is representative of the subsample used.
  19. 19. © NERC All rights reserved
  20. 20. © NERC All rights reserved
  21. 21. © NERC All rights reserved Nugget effect Discrete high density particles: frequent occurrence (a); rare occurrence (b); absence(c).
  22. 22. © NERC All rights reserved Considerations for barrel • No more than half full • Rotating barrel - internal vanes • Reinforcement? • Ideally end over end, or angled
  23. 23. © NERC All rights reserved Designing a subsampling tree • Split a bulk down representatively • Generate manageable portions • Identify unique subsample identifiers A B AC AD B1 B2 ACE ACF ADG ADH B13 B14 B25 B26
  24. 24. © NERC All rights reserved Representative subsampling • Sampling plan to address controlling factors • Based on appropriate statistical methods • Record client requested deviations for reporting • Procedures for recording sampling data
  25. 25. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  26. 26. © NERC All rights reserved
  27. 27. © NERC All rights reserved
  28. 28. © NERC All rights reserved
  29. 29. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  30. 30. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  31. 31. © NERC All rights reserved Representative subsampling • Cone quartering • Riffle splitting • Rotary divider
  32. 32. © NERC All rights reserved Temporary packaging • If required • Store labelled portions securely awaiting further dividing
  33. 33. © NERC All rights reserved Homogeneity testing • We think we have a homogenous material – but we need to test this • Random sampling to identify splits for analysis • Element selection… Sample Ni Cu Zn … ppm ppm ppm … ADF4-3 19.9 11.9 78.1 … B135-3 19.2 11.8 78.2 … B137-2 21.1 12.0 78.0 … ADE4-1 20.5 11.3 80.2 … B262-2 19.8 12.0 78.0 … B264-3 20.0 11.5 79.5 … B251-3 20.1 11.7 77.5 … ADE5-1 20.1 11.8 78.9 … B251-1 19.6 10.8 76.1 … ADF1-1 20.4 12.8 78.7 … ACG7-1 20.7 12.2 81.6 … B142-3 21.1 12.1 77.8 … B137-3 19.8 11.1 77.9 … B261-2 19.8 11.6 79.4 … ADE5-2 20.5 11.8 78.3 … … … … … … A B AC AD B1 B2 ACE ACF ADG ADH B13 B14 B25 B26
  34. 34. © NERC All rights reserved Acceptance criteria • Between-sample variability is not significantly greater than within-sample variability • F< defined value, Fcritical • Confidence limits: 95% 𝐹 = 𝐵𝑒𝑡𝑤𝑒𝑒𝑛 𝑠𝑎𝑚𝑝𝑙𝑒 𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒 𝑊𝑖𝑡ℎ𝑖𝑛 𝑠𝑎𝑚𝑝𝑙𝑒 𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒
  35. 35. © NERC All rights reserved Data analysis • Identify statistical outliers • Test for normality • ANOVA - Analysis of Variance Source of Variation SS df MS F P-value F crit Between Groups 945.8 23 41.1 1.1 0.4 2.0 Within Groups 883.5 24 36.8 Total 1829.3 47
  36. 36. © NERC All rights reserved Final splitting • If required – • use appropriate methodology as before
  37. 37. © NERC All rights reserved Storage options • Container type • Consider how this will be used, portion size etc. • Susceptibility to change in air – sealing, inert gas? • Susceptibility to settling?
  38. 38. © NERC All rights reserved
  39. 39. © NERC All rights reserved Documentation • Measurand including analyte • Measurement range (concentration) • Matrix match and potential interferences • Sample size • Homogeneity and stability • Measurement uncertainty • Value assignment procedures (measurement and statistical)
  40. 40. © NERC All rights reserved WHEN AND WHY TO USE A REFERENCE MATERIAL
  41. 41. © NERC All rights reserved Assuring the quality of test results • Quality Control (QC) procedures • Record results - to view trends • Statistical evaluation of QC data • Plan and review monitoring of QC data • CRMs, secondary standards • Proficiency Testing schemes - EPTIS • Replicates and repeats • Predefined acceptance criteria • Shewhart chart – Westgard rules • Planned action to correct and prevent
  42. 42. © NERC All rights reserved Shewhart QC chart 90 100 110 120 130 140 150 160 0 5 10 15 20 25 30 35 Concentration(mg/kg) Index As As Mean +2sd +3sd -2sd -3sd Expected
  43. 43. © NERC All rights reserved ENHANCING DATA QUALITY
  44. 44. © NERC All rights reserved Sources of error • Systematic error • Can occur… • Will be minimised by careful planning • Aim to remove entirely • Random error • Will occur • Can be quantified
  45. 45. © NERC All rights reserved Characterising Uncertainty • Analysis gives one data value • Each time a sample is analysed it will be slightly different • Many sources of random error • Combine to give a method uncertainty • Normal distribution – bell curve • Allows calculation of 95% confidence limits • Use error bars on graphs • allows meaningful data interpretation Total uncertainty
  46. 46. © NERC All rights reserved Soil-type and Se supply in Malawi: Evidence of widespread deficiency Chilimba et al. (2011) Hurst et al. (2013)
  47. 47. © NERC All rights reserved Se application (g Se ha-1 ) 0 10 20 30 GrainSe(mgSekg -1 ) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Alleviation strategies: agronomy Liquid drench y = 0.019x + 0.061 CAN+Se (granular) y = 0.015x + 0.085 NPK+Se (granular) y = 0.022x + 0.056 15-22 µg Se kg-1 grain . g-1 Se ha-1 Chilimba et al., 2012

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