1. “Normalization” of Foliar Nutrient Data

2. l Differences in laboratory methodology may affect analytical results

3. Relationship between foliar N analytical methodologies dry combustion vs. wet digestion

4. Relationship between foliar S analytical methodologies dry combustion vs. wet digestion

5. “Normalization” of Foliar Nutrient Data l Differences in laboratory methodology may affect analytical results l Inter-laboratory differences may be large enough to affect interpretation

6. “Normalization” of Foliar Nutrient Data l Differences in laboratory methodology may affect analytical results l Inter-laboratory differences may be large enough to affect interpretation l Nutrient interpretative criteria do not account for differences in methodology

7. “Normalization” of Foliar Nutrient Data l Differences in laboratory methodology may affect analytical results l Inter-laboratory differences may be large enough to affect interpretation l Nutrient interpretative criteria do not account for differences in methodology l Known differences in laboratory analytical results can be used to “normalize” foliar data prior to interpretation

8. “Normalization” of Foliar Nutrient Data l Differences in laboratory methodology may affect analytical results l Inter-laboratory differences may be large enough to affect interpretation l Nutrient interpretative criteria do not account for differences in methodology l Known differences in laboratory analytical results can be used to “normalize” foliar data prior to interpretation l “Normalization” requires inter-laboratory comparisons

9. “Normalization” of Foliar Nutrient Data l Differences in laboratory methodology may affect analytical results l Inter-laboratory differences may be large enough to affect interpretation l Nutrient interpretative criteria do not account for differences in methodology l Known differences in laboratory analytical results can be used to “normalize” foliar data prior to interpretation l “Normalization” requires inter-laboratory comparisons l The “normalization” process does not make inferences about the quality of foliar nutrient data

10. Laboratory foliar N comparison (2012) PSAI vs. MoE

11. Laboratory foliar S comparison (2012) PSAI vs. MoE

12. “Normalization” spreadsheet (2012)

14. = 0.561x + 0.052 = 0.677x + 0.019 = 0.720x + 0.026 = 0.840x + 0.036

15. “Normalization” spreadsheet (2012) = 0.786x + 0.134 = 1.004x + 0.007 = 1.057x – 8.03 = 0.903x + 1.73

16. Inter-laboratory comparison Pacific Soil Analysis vs. Ministry of Environment l The 2012 inter-laboratory comparison was repeated in early 2013 following analytical equipment upgrade at the MoE lab

17. Inter-laboratory comparison Pacific Soil Analysis vs. Ministry of Environment l The 2012 inter-laboratory comparison was repeated in early 2013 following analytical equipment upgrade at the MoE lab l 50 previously analyzed foliage samples were used

18. Inter-laboratory comparison Pacific Soil Analysis vs. Ministry of Environment l The 2012 inter-laboratory comparison was repeated in early 2013 following analytical equipment upgrade at the MoE lab l 50 previously analyzed foliage samples were used l Samples were selected to cover a broader range of species and foliar nutrient levels than used in the 2012 comparison

19. Inter-laboratory comparison Pacific Soil Analysis vs. Ministry of Environment l The 2012 inter-laboratory comparison was repeated in early 2013 following analytical equipment upgrade at the MoE lab l 50 previously analyzed foliage samples were used l Samples were selected to cover a broader range of species and foliar nutrient levels than used in the 2012 comparison l Each sample was thoroughly mixed and split into two sub-samples

20. Inter-laboratory comparison Pacific Soil Analysis vs. Ministry of Environment l The 2012 inter-laboratory comparison was repeated in early 2013 following analytical equipment upgrade at the MoE lab l 50 previously analyzed foliage samples were used l Samples were selected to cover a broader range of species and foliar nutrient levels than used in the 2012 comparison l Each sample was thoroughly mixed and split into two sub-samples l One sub-sample was shipped to each lab

21. Inter-laboratory comparison Pacific Soil Analysis vs. Ministry of Environment l The 2012 inter-laboratory comparison was repeated in early 2013 following analytical equipment upgrade at the MoE lab l 50 previously analyzed foliage samples were used l Samples were selected to cover a broader range of species and foliar nutrient levels than used in the 2012 comparison l Each sample was thoroughly mixed and split into two sub-samples l One sub-sample was shipped to each lab l For each nutrient, laboratory results were subjected to regression analysis

22. Inter-laboratory comparison Pacific Soil Analysis vs. Ministry of Environment l The 2012 inter-laboratory comparison was repeated in early 2013 following analytical equipment upgrade at the MoE lab l 50 previously analyzed foliage samples were used l Samples were selected to cover a broader range of species and foliar nutrient levels than used in the 2012 comparison l Each sample was thoroughly mixed and split into two sub-samples l One sub-sample was shipped to each lab l For each nutrient, laboratory results were subjected to regression analysis l The new equations were used to revise the 2012 “normalization” spreadsheet

23. Laboratory foliar N comparison PSAI vs. MoE

24. Laboratory foliar S comparison PSAI vs. MoE

25. Laboratory foliar P comparison PSAI vs. MoE

26. Laboratory foliar K comparison PSAI vs. MoE

27. Laboratory foliar Ca comparison PSAI vs. MoE

28. Laboratory foliar Mg comparison PSAI vs. MoE

29. Laboratory foliar B comparison PSAI vs. MoE

30. “Normalization” of laboratory foliar nutrient data

34. = 0.9492x = (0.3592x 2 ) + (0.7346x) = 1.0249x = (0.1714x 2 ) + (0.8504x)

35. Normalization of laboratory foliar nutrient data

36. “Normalization” of laboratory foliar nutrient data

39. = 0.9584x = (0.9558x) – (0.6267x 2 ) = (1.4164x) – (0.0008x 2 ) = (0.8732x) – (0.0012x 2 )

40. “Normalization” of laboratory foliar nutrient data