precision nutrient management: grid-sampling basis
DESCRIPTION
Precision Nutrient Management: Grid-Sampling Basis. Hailin Zhang and Gordon Johnson Department of Plant and Soil Sciences. Spatial variability (macro) for agronomic land use. Acquired (use induced). Influence of historical crop production on soil properties. - PowerPoint PPT PresentationTRANSCRIPT
Precision Nutrient Management:
Grid-Sampling Basis
Hailin Zhang and Gordon Johnson
Department of Plant and Soil Sciences
Spatial variability (macro) for agronomic land use.
• Acquired (use induced).• Influence of historical crop production on
soil properties.– Alfalfa vs. wheat for acidification and soil organic
matter. – Fertilizer use and change in soil fertility (Garfield
County).
Soil Test P Variability Among First 50 Free Soil Tests for Garfield County Oklahoma, 1997
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Soil Test P Variability Among First 50 Free Soil Tests for Garfield County Oklahoma, 1997
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C.V. = 54
Acquired spatial variability (macro).Acquired spatial variability (macro).Acquired spatial variability (macro).Acquired spatial variability (macro).
Garfield Co. Farmer’s Use of Soil Testing and FertilizationGarfield Co. Farmer’s Use of Soil Testing and FertilizationGarfield Co. Farmer’s Use of Soil Testing and FertilizationGarfield Co. Farmer’s Use of Soil Testing and Fertilization
PreviousPreviousPreviousPrevious GrainGrainGrainGrain Normal FertilizationNormal FertilizationNormal FertilizationNormal Fertilization Soil Test ResultsSoil Test ResultsSoil Test ResultsSoil Test ResultsAcresAcresAcresAcres Soil TestSoil TestSoil TestSoil Test YieldYieldYieldYield NNNN PPPP2222OOOO5555 KKKK2222OOOO pHpHpHpH NNNN PPPP KKKK
SurSurSurSur SubSubSubSub86*86*86*86* 1981198119811981 35353535 100100100100 46464646 4.54.54.54.5 24242424 54545454 106106106106 445445445445
118*118*118*118* 1981198119811981 25252525 100100100100 46464646 4.94.94.94.9 53535353 108108108108 88888888 41141141141130*30*30*30* 1989198919891989 34343434 100100100100 46464646 5.15.15.15.1 44444444 43434343 75757575 37737737737765*65*65*65* 26262626 100100100100 46464646 4.44.44.44.4 115115115115 118118118118 159159159159 75275275275250505050 1981198119811981 29292929 100100100100 46464646 5.55.55.55.5 0000 70707070 44444444 551551551551
*Savings from no fertilizer to four fields = 299 acres X $24.50/acre, = $7,325*Savings from no fertilizer to four fields = 299 acres X $24.50/acre, = $7,325*Savings from no fertilizer to four fields = 299 acres X $24.50/acre, = $7,325*Savings from no fertilizer to four fields = 299 acres X $24.50/acre, = $7,325
Acquired spatial variability (macro).Acquired spatial variability (macro).Acquired spatial variability (macro).Acquired spatial variability (macro).
Acquired spatial variability (micro).Acquired spatial variability (micro).Acquired spatial variability (micro).Acquired spatial variability (micro).
pH=4.9pH=4.9BI = 6.6BI = 6.6N = 10N = 10P = 93P = 93K = 435K = 435
BottomBottompH=5.2pH=5.2BI = 7.0BI = 7.0N = 13N = 13P = 54P = 54K = 354K = 354
Terrace 1Terrace 1
pH=5.3pH=5.3BI = 6.9BI = 6.9N = 10N = 10P = 44P = 44K = 415K = 415
Terrace 2Terrace 2pH=5.7pH=5.7BI = 6.9BI = 6.9N = 20N = 20P = 23P = 23K = 397K = 397
Terrace 3Terrace 3pH=5.4pH=5.4BI = 6.8BI = 6.8N = 20N = 20P = 31P = 31K = 522K = 522
Terrace 4Terrace 4pH=5.5pH=5.5BI = 6.7BI = 6.7N = 12N = 12P = 32P = 32K = 423K = 423
Terrace 5Terrace 5pH=4.6pH=4.6BI = 6.8BI = 6.8N = 16N = 16P = 65P = 65K = 310K = 310
UplandUpland
pH=7.3pH=7.3BI = --BI = --N = 67N = 67P = 22P = 22K = 343K = 343
““BadBadSpot”Spot”pH=5.2pH=5.2
BI = 6.8BI = 6.8N = 14N = 14P = 49P = 49K = 408K = 408
FieldFieldAverageAverage
pH=4.6-5.7pH=4.6-5.7BI = 6.6-7.0BI = 6.6-7.0N = 10-20N = 10-20P = 23-93P = 23-93K = 310-522K = 310-522
FieldFieldRangeRange
“Cow Pocks” in wheat pasture“Cow Pocks” in wheat pastureAcquired spatial variability (micro).Acquired spatial variability (micro).Acquired spatial variability (micro).Acquired spatial variability (micro).
STP 1996, EFAW
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STP 1996, EFAW
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Acquired spatial variability (micro).Acquired spatial variability (micro).Acquired spatial variability (micro).Acquired spatial variability (micro).
Precision Nutrient ManagementStrategies
1. Grid soil sampling
2. Apparent Electrical Conductivity
3. Yield monitor/mapping
4. Sensing techniques
Purposes of Soil Sampling
1. Measure the nutrient content or availability of the soil
2. Identify nutrient deficiencies
3. Predict crop response to added nutrients
4. Build a nutrient management plan
Recognize Field Nutrient VariabilityRecognize Field Nutrient Variability
Nitrate - Nitrogenlbs/acre
0-30
31-40
41-50
51-60
61-80
>80
(Nitrate-N within a 75’ x 75’ plot)
Limiting Factors for Crop Growth
1. Factors are different for every field, therefore, remediation should be different too
2. Factors change from year to year
3. Factors limiting yield will interact
Considerations for Soil sampling Strategies
1. Locate variability responsive to fertilizer and lime
2. Obtain a sample that accurately represents the area sampled
3. Balance cost of sampling with the value of information
The greatest potentialfor error in soil testingis in taking the sample
Soil Sampling Strategies1. Whole field composites: Composite sample
representing the average nutrient status of the field
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Number of Samplesin a Composite
Nitr
ate-
N (l
b/A
)20 cores are needed to make a representativecomposite sample in order to get reliable soil test results
OSU Cooperative Extension
Soil Probe
Get a Representative Sample
Clean Bucket
Right Depth
15-20 cores
Soil Sampling Strategies
2. Zone composites: Break field based on known or expected source of variability
Soil Sampling Strategies
3. Grid Sampling: Break field based on ordered pattern
1. Grid cell method: similar to whole field
2. Grid center method: point sampling
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Field Soil Sampling, Soil Testing, and Making Fertilizer Recommendations Exercise
1. Random sampling of the entire field ,
25 cores of soil from a 0-6” depth
filling two soil sample bags from the composite mixture
2. Grid-cell sampling
15 cores of soil from a 0-6” depth
3. High resolution
15 cores of soil from a 0-6” depth
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Whole field1 acre gridSub-grid
Whole fieldsample pH:
Team 1: 6.0, 6.1 Team 2: 6.4, 6.4
Whole fieldsample nitrate:
Team 1: 19, 18 Team 2: 28, 28
Soil Test P Variability among 25 1-acre Cells
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Cell Number
Soi
l Tes
t-P
Area STP Point STP
Whole Field Sampling: 114 & 117, 188 & 190
127
Whole Field Sampling: 206 & 196, 186 & 180
Grid Soil Tset K
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Grid Number
Soi
l Tes
t K (l
b/A
)
Area STK Point STK
188
Whole Field Sampling: 5.9 & 5.9, 5.6 & 5.6
4.0
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6.5
7.0
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Grid Number
Soi
l pH
Point pH Area pH
5.6
Why Account for Spatial Variability of Soil Properties
1. Improve performance of ag. practices
2. Either costs go down and/or returns go up
3. Avoid over application that might be environmentally harmful
Analysis Costs of Various Sampling Intensities
Grid Spacing Area/sample Costs*
Feet Acres $/acre
66 0.1 100
104 0.25 40
148 0.5 20
209 1 10
330 2.5 4
467 5 2
660 10 1
Conventional 40 0.25
*at $10/sample
Analysis Costs of Various Sampling Intensities
*at $10/sample; **at $10/hour and collecting 1 to 5 samples per hour
Grid
Spacing
Area/
sample
Analysis Cost*
Sampling Cost**
Total Cost
Feet Acres $/acre $/acre $/acre
66 0.1 100 20 120
104 0.25 40 10 50
148 0.5 20 5 25
209 1 10 2.5 12.5
330 2.5 4 1.25 5.25
467 5 2 0.65 2.65
660 10 1 0.40 1.40Conventional 40 0.25 0.25 0.50
Choosing a Soil Sampling Strategy
• Level of management and the resources to account for variability
• Whole field sampling most appropriate when fertility is high and variability is low
• Zoning/sub-field sampling may be most appropriate when– Location of variation known– Sampling areas are large– Limited resource
• Grid sampling maybe appropriate if location of variation is unknown and variable rate applicator is available, or variable changes slowly with distance