Impact of soil sampling and laboratory analysis on nutrient management

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1 ila.com/blogs/wp- content/uploads/1/7/aggie-turf.tamu_.edu-local-extension- Office-soil-test.j pg Impact of soil sampling and laboratory analysis on nutrient management Robert O. Miller Colorado State University Fort Collins, CO Phoenix, AZ November 7, 18 Background Affiliate Professor Colorado State University. Extension Soil Specialist UC Davis , Ph.D, Montana State University. Twenty-four years coordinating lab proficiency Programs: Agricultural Laboratory Proficiency (ALP) Program; and four other for Compost, Bio-solids, USGA, 36 Yield. Conduct Regional Research in: Soil sampling, Soil fertility, Lab analysis and Soil test calibration. Soil Nutrient Management You can not manage what you can not measure. Tom McGraw, Former owner Midwest Independent Soil Samplers Soil Sample A chain of three components, required for a recommendation. Lab Test Method Calibration Database Accurate and precise measurement tools are required for quality soil fertility management. Soil sampling variability Analysis variability Response & uncertainty Miller, 14 Soil Sampling Field Composite Cyril Hopkins, Univ of Illinois Dept of Agronomy, and James H.Pettit (left), the Morrow Plots,19. Soil sampling has a long history which started with small plots on University research stations. Soil Phosphorus Field Variability Mean and RSD 3 7 Mean Concentration RSD % Field #16, ac No Till yrs N 45 Mean 1.8 Stdev 9.9 RSD % 45 Confidence Interval (CI) ± 6.8 The traditional whole field approach is to collect a composite sample based on -3 individual cores. Number Bray P1 - Field 16 NE

2 Number Bray P 1 (ppm) Bray P1 Field Variability Soil Test Field Variability Wt. Mean Concentration Bray P1 - Field 53 IL 5 5 N 7 Mean 63.5 Stdev 6. RSD % Wt. Mean Concentration 6 5 Bray P1 - Field 345 IL N 31 Mean 54.7 Stdev.7 RSD % Wt. Mean Concentration 5 Bray P1 - Field 47 IA N 6 Mean 53. Stdev 19.1 RSD % 36 Field (N) P ppm K ppm ph Mean RSD % Mean RSD % Mean RSD % #16 NE (45) #53 IL (6) #345 IL (3) #535 IL (4) # WI (18) #57 IA (4) #8557 IL (93) #47 IN (47) Source: R Miller, RIVERLAND FS Inc, United Soils, LGI Labs, and Frontier Labs. Soil Spatial Sampling Sampling Project Scale Zone Grid: Sampling based on GPS collection points. Pattern dependent, acres. Directed: Sampling based on a quantified variable (i.e. soil type, slope, yield, EC,?) Zone: Sampling fields based on Mgt unit, -5 zones per field. 1 Grid Directed (Yield) Seventy-six fields across ten states were selected. At a random grid point, 1 cores were removed in a structured pattern ft radius of center point, individually analyzed in triplicate for ph, Buffer ph, P, K, NO 3 -N, Zn and SOM. 3 6 ft ft J Ellsworth, Wilbur Ellis, 6 Approx scale Field #16 Position Composited? Bray P1 of 1 4 of 1 6 of 1 8 of 1 1 Combinations Min Mean (ppm) Max Mean (ppm) Range RSD % 1 Based on soil core combinations Grid Point - Bray P1 Field #16 - No Till Field, RSD 8% 3 Mean P Concentration Range 5 /1 4/1 6/1 8/1 11/ ft 8 ft Approx scale Selecting 4 cores of 1 results in mean Bray P1 range ppm. 8 of 1 cores results in mean Bray P1 range of ppm. LGI Labs, each sampled analyzed In triplicate. Number of

3 Bray P1 Grid Point Variability Conv Till No Till Wt. Mean Conc Wt. Mean Conc Strip Till Wt. Mean Conc 1 Phosphorus Grid Point RSD 76 Sites, Across Ten States 8 ft Approx scale 3 IL - Field # IN - West # IA - Field # Field Mgt No-Till Min-Till Conv. Manured # Sites Range Median N 1 N 1 N 1 1 Based on 76 sites, A&L Great Lakes, USI, Spectrum and LGI November, 6-. Mean 34.1 Mean 3. Mean 14.4 Stdev 6.1 Stdev 14.1 Stdev. RSD % 18 RSD % 47 RSD % 71 How many? n = (Z x S ) / D n : Z : Z-statistic for Desired Confidence S : Standard Deviation D : Width of Confidence Interval (Accuracy) Confidence Level 8% 9% 95% Z Uncertainty Calculation n = (Z x S ) / D n : Z : Z-statistic for Desired Confidence S : Standard Deviation D : Width of Confidence Interval RSD = % ± D (%) RSD = 5% ± D (%) RSD = % ± D (%) Confidence Level 8% 9% 95% Confidence Level 8% 9% 95% Confidence Level 8% 9% 95% Soil Sampling Uncertainty How good are 4 cores? No-Till Field Bray P1 Mean = 3 ppm RSD = 5% 9% Confidence Level D = ((Z x S ) / n).5 3 ± 13 ppm What Management Value is Grid Sampling? acre field,.5 ac grid Soil Sampling Observations Grid Sampling Grid point soil test variability (RSD) generally follows: STP > Soil NO 3 -N > STK > SOM > ph. Decreased tillage stratifies crop residue at the surface resulting in high concentration of nutrients. Transitions to No and Strip-Till has increased Bray P heterogeneity, resulting in grid point RSDs 3-5%. For 1 cores 3 ± 7ppm / Miller, 16 3

4 Number of Manage your Soil Sampling Soil Nutrient Management With decreased tillage, increase the number of cores, to improve accuracy and precision. Adjust intensity with tillage system and field test history. Soil Sample Soil sampling variability A chain of three components, required for a recommendation. Lab Test Method Analysis variability Calibration Database Response & uncertainty Conventional No Till Decreased Tillage Miller, 14 Lab Analysis: A Process Types of Soil Tests 1 or 5, Samples / Day A series of steps. Starting with Login... Drying and Grinding Extraction. Analysis Reporting Quantitative Electrical Conductivity NO 3 -N, Cl SOM, TOC, TN CEC Sand, Silt Clay Semi-Quantitative Phos (Bray, Olsen, Mehlich 3) K, Ca, Mg, Na, SO4 Generally soil fertility methods are semi-quantitative, an index of plant nutrient availability. Micronutrients (Zn, B, Cu, Fe) Soil Analysis Measurement Uncertainty Every measurement has associated with it, an uncertainty limit Uncertainty and Management With agricultural management we must always assess the measurement uncertainty in the decision. ±.5 volts This is true for any measurement Example soil EC ds/m Field 1.5 ± 1. Field 3.5 ±.3 M:&ved=CAUQjRw&url=http%3A%F%Fwww.bluesea.com%Fproducts%F5B%FVoltmeter%5-16%5Volts&ei=_lAyUe6HKZCFyQG_7IHgAQ&bvm=bv ,d.aWc&psig=AFQjCNH373nb9BVk_iCvO- 4UKVlvMjkjw&ust= ph, EC, P, K, yield monitor, speedometer, sprayer output, temperature, etc. Example, there is no difference in soil EC for the two fields 4

5 Uncertainty ± P (ppm) Un certainty ± NO 3 -N (ppm) Increasing Trueness Lab Quality Uncertainty is part of the measurement Precision Lab Proficiency Setting the Standard of Analysis Soil testing labs may participate in the ALP or the NAPT proficiency programs, but are not certified. Proficiency is based on periodic assessment of lab performance, and is required by 7 states. Measurement, variance Accuracy of the Only Minnesota Dept of Ag and Illinois Soil Testing Association conduct certification for soil testing labs. Measurement, bias ALP is the only accredited proficiency provider in North America and evaluates both lab bias and precision. Increasing Precision ALP Program Accredited Proficiency Provider Lab NO 3 -N Uncertainty Sample SRS-11, NO 3 -N 7.4 ppm Program Operation: Five PT soils three cycles per year. Labs select from 18 test methods, each perform in triplicate. Data evaluated by a statistician, and reports provided on analytical performance, bias and precision. 1 labs enrolled. PT Soils: Collected 3 soils from 57 US states and Canadian provinces, representing 11 USDA textures, ph range , and SOM %. Samples are: dried; pulverized; blended; homogeneity tested. Soil Collection Maine 14 Across labs NO 3 -N uncertainty ranges from ±. to ± 14.7 ppm, with a median of ± 3. ppm, for soil SRS % of labs provided results for uncertainty < ± 4. ppm. Five labs had uncertainties much higher than the median of participants Median. Soil NO 3 -N: 7.4 ppm. 3 Lab Number Miller 16, within lab uncertainty, Data from ALP Program 1 ALP data based on within lab precision (stdev), 3 labs, uncertainty 95% level. Lab Olsen-P Uncertainty Sample SRS-11, Olsen-P.4 ppm Across labs Olsen-P uncertainty ranges from ±.3 to ± 11. ppm, with a median of ±. ppm, for soil SRS % of labs provided results for uncertainty < ± 4. ppm. Seven labs had uncertainties much higher than the median of ALP participants. Miller 16, within lab uncertainty, Data from ALP Program Median Bicarb-P:.4 ppm. 3 Lab Number 1 ALP data based on within lab precision (stdev), 33 labs. Soil Methods Performance Ranking Low to High Relative Uncertainty 1 5 % 5 % % 5 % 5 35 % Soil Analysis Methods (Ranked low to high) ph, Buffer ph, Saturated Paste %, Bray-K, M1-Mg M1-Ca, M1-K, NO 3 N-CTA, M1-Mn, M1-Zn, M3-Al, TOC, M1-P, M3-Ca, M3-Mn M3-K, X-Ca, M3-Mg, X-K, NO 3 N-Cd, EC, SOM-LOI, X-Mg, M3-Cu, M3-P ICP, Bray-P CEC, TKN, M3-Zn, Clay %, Bicarb-P, DTPA-Zn, M3-S, Cl, DTPA-Cu M3-Na, Hot W-B, Extr. SO 4 -S, M3-B, SAR, NH 4 -N 1 Based on 5 ALP soils 9-, soil P values < ppm, ph < 7.5, removed Calculated based on three replicates and 95% confidence limits. 5

6 ± NREC (lbs ac -1 ) Relative Uncertainty (%) Relative Uncertainty (%) Relative Uncertainty (%) Uncertainty Soil Nitrate Uncertainty Mehlich 3 P and K For the Cd reduction method, absolute uncertainty increases with soil NO 3 -N concentration. Whereas, relative uncertainty for NO 3 -N is the highest at low concentrations. Increasing relative uncertainty as function of decreasing concentration is fundamental to lab analysis. Miller 16, within lab uncertainty, Data from ALP Program Soil ID Median (ppm) Uncert (ppm) SRS ± 1. SRS ±.7 SRS ± 3. SRS ± 4.6 SRS ± 6.8 Data based on within lab stdev, average of 3 Labs, uncertainty 95% confidence limits. M3 Phosphorus (ppm) 3 5 ±.8 ± 4. ± 6. M3 Potassium (ppm) ± 1 ± 16 ± 4 Miller 16, within lab uncertainty, Data from ALP Program 1 Data based on within lab stdev, 48 Labs, uncertainty 95% level. ± % ± 1% Analysis Uncertainty 9 M3-Ca Lab Analysis Observations Function of Concentration NO 3 -N M3-P ICP y = 37.1x -.51 R² = y = x R² = Soil M3-Ca (ppm) Measurement uncertainty is associated with all lab analysis and is a function of the method, instrument and lab technician. Lab uncertainty (precision) varies by soil method. EC < NO 3 -N < Mehlich 3 P < SOM < CEC < Hot Water B. 5 3 y = 3.71x R² = Soil NO 3-N (ppm) 6 8 Soil M3-P ICP (ppm) Data: ALP Program, 8 Soils 6-1 Uncertainty based on 95% CL, three replicates each soil, 48 laboratories. Analysis precision is a function concentration Low concentrations has the highest uncertainty (poorest precision). Example NO 3 -N < ppm. Miller, 16 Combining Lab Precision with Nitrogen Recommendation 1 Algorithm For Corn UNL Nitrogen Algorithm for Corn: NREC = E(Y) - 8 (NO 3 -N) -.14 E(Y) OM - Cw E(Y): 18 bu ac -1 NO 3 -N: - feet OM = 3.% Cw = Water Credit lbs ac -1 1 Hergert, G.W., R. Ferguson and C. Shapiro (1995). NO 3 -N Precision is function of: - Concentration, exponential - Method - Laboratory Combine nitrogen algorithm with equation describing precision as a function of soil NO 3 -N Concentration. Impact of Lab Precision on Nebraska Nitrogen Algorithm 1 for Corn As soil NO 3 -N concentration increases, NREC precision follows an exponential function. Thus YG=18 bu/ac, RSD of 5% and mg kg -1 NO 3 -N, the precision of the recommendation of 95 lbs ac -1 nitrogen is: ± 7 lbs ac -1, at % ± 14 lbs ac -1 Precision has impact on the Nitrogen recommendation. 1 Hergert, G.W., R. Ferguson and C. Shapiro (1995). NREC Precision as a function of soil NO 3 -N Concentration 5 5 y = 5.1(x.47 ) y =.7(x.47 ) 5 Soil NO 3 -N (mg kg -1 ), -4 in Intra-Lab RSD % Intra-Lab RSD 5 % 6

7 ± PREC (P O5 lbs ac -1 ) Impact of Lab Precision on LGU Phosphorus Algorithm 1 for Corn Bray P1 PREC = (.7-.35(STP))YG As soil Bray P1 concentration increases, PREC precision follows an exponential function. Thus an intra-lab RSD of % and Bray P1 level of mg kg -1 in the soil, the precision of the recommendation of 3 lbs ac -1 P O 5 is ± 14 lbs ac-1. 1 Dahnke and Fanning (199) NDSU PREC Precision as a Function of Soil Bray P1 Concentration, YG = 18 bu ac -1 Olson P vs 5% y = 6.(x.56 ) y = 3.1(x.56 ) Intra-Lab RSD % Intra-Lab RSD % 5 Bray P1 Soil P (mg kg -1 ) -6 in Concluding Remarks Soil Sampling: Sampling for precision nutrient management requires a understanding of sampling uncertainty and tillage systems. Decreased tillage > emphasis on sampling strategy. Lab Analysis: Measurement uncertainty impacts all soil test results, varies by method, and increases for low nutrient concentrations. Specific methods (i.e. M3-B, M3-S ) have relative uncertainties > 3%. Take Home Acknowledgements With reduced tillage, -1 cores optimum, (- foot radius). Strip till 1/3 /3 rule. Realize P and K have highest variation. Lab analysis: ph +/-. units; NO3-N 6-%; P and K tests 8-% (concentration dependent); and micros -%. Specific labs maybe better. Realize that uncertainties associated with sampling and lab analysis are multiplicative, which impact the accuracy of the recommendation. Mallarino et al., 3 Better Crops Tom McGraw, Midwest Samplers, MN Craig Struve, Soil View, IA Chris Nelson, Midwest Samplers, IA Mike Lindaman, LGI Laboratory, IA Tim Smith, Cropsmith, IL Bill Urbanowicz, OH Randy Busch, Rock River Labs, WI Kess Berg, A&L Great Lakes, IN John Grandin, Riverland FS, IL Richard Finstead, Frontier Labs, IA David Taylor, Harvest Land Co-op, IL Greg Ikins, United Soils Lab, IL David Green, Servi-Tech, CO For more Information contact: rmiller@colostate.edu Standard Reference Soils Available Miller et al., 16 Thank You for Your Time and Attention Miller, 6 7

8 Can More Improve Precision for No Till Lab Analysis 3 No Till Wt Mean Conc NE - Field # Increasing the number of samples beyond 1 cores at a highly variable site, does not significantly improve the estimate of the mean or reduce the variance for P. N 4 Mean 14.1 Stdev 8.7 RSD % 58 You can not manage what you cannot measure. Tom McGraw Modern Lab Miller, 7 8