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History of Predicting Yield Potential. TEAM VRT Oklahoma State University. Outline. Yield Goals and Potential Yield Soil Test vs. Sensor Based Sufficiency: Mobile vs. Immobile Nutrients Bray’s mobility concept How to generate nutrient recommendations What should we learn from soil testing

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history of predicting yield potential

History of Predicting Yield Potential

TEAM VRT

Oklahoma State University

outline
Outline
  • Yield Goals and Potential Yield
  • Soil Test vs. Sensor Based
  • Sufficiency: Mobile vs. Immobile Nutrients
  • Bray’s mobility concept
  • How to generate nutrient recommendations
  • What should we learn from soil testing
  • Subsoil nutrient availability
  • Soil Testing: Correlation/Calibration/Recommendation
  • Models for Interpretation of Response
  • Interfering agronomic factors
yield goal potential yield
Yield Goal/Potential Yield
  • Yield Goal: yield per acre you hope to grow (Dahnke et al., 1988)
  • Potential yield: highest possible yield obtainable with ideal management, FOR specific soil and weather conditions
  • Maximum Yield: grain yield achievable when all manageable growth factors (nutrients, insects, disease, and weeds) are nonlimiting and the environment is ideal
yield goals in the literature
Yield Goals in the Literature
  • Yield per acre you hope to grow (Dahnke et al. (1988).
  • Highest yield attained in the last 4-5 years and that is usually 30-33% higher than avg. yield (J. Goos, 1998).
  • Aim for a 10-20% increase over the recent average (Rehm and Schmitt, 1989).
  • Yield goal should be based on how much water is available (stored soil water to 1.5m, Black and Bauer, 1988).
  • When Yield Goals are used it explicitly places the risk of predicting the environment (good or bad) on the producer.
slide5

Value of Using Yield Goals

  • Nutrient removal can be reliably estimated for a given yield level in specific crops.
  • Selected Yield Goal defines the risk the producer is willing to take.
    • Yield Goal can define the limits in terms of economic inputs when considering herbicides, insecticides, etc.
importance of predicting potential yield
Importance of Predicting Potential Yield
  • Seasonal N need directly related to observed yield.
  • NUE decreases with increasing N rate.
  • Known Potential Yield = Known N Input = Highest NUE.
slide7

YieldGoal

Yield Goal

+30%

Grain yield

Average Yield

Bound by Environment and Management

Max Yield YPMAX

PotentialYieldYP0

Potential Yield with N, YPN

slide8

Predicting N Needs

  • Use of Yield Goals.
    • Based on past season yields.
    • May take into account current-year preplant conditions of available moisture and residual N.
    • Seldom is adjusted for midseason conditions to alter N inputs.
  • Use of Potential Yield.
    • Reliability of predicting final yield (and N requirement) from existing soil and crop conditions should increase as harvest approaches.
spatial variability and yield potential
Spatial Variability and Yield Potential
  • Significant soil variability at distances less than 30 m apart (Lengnick, 1997)
  • In order to describe the variability encountered in field experiments, soil, plant and indirect measures should be made at the 1m or submeter resolution
  • Significant differences in soil test P, organic C, and pH were found at distances <0.30m (OSU)
crop response models to predict yield n need
Crop Response/Models to Predict Yield (N need)
  • CERES (Crop-Environment Resource Synthesis) crop response model was not useful in predicting wheat grain yield (Moulin and Beckie, 1993)
    • Complicated.
  • Total N uptake at Feekes growth stage 5 was found to be a good predictor of yield (Reeves et al., 1993)
    • Worked some, but not all years.
slide11

Growth Stages in Cereals

Stem Extension

Ripening

Stage

Heading

Tillering

slide12

100 lb N/ac

45 bu/ac, 2.5% N in the grain

75 lb N/ac

N uptake, lb/ac

50 lb N /ac

days with GDD>0?

October February June 0 120 240 days

INSEY: Rate of N uptake over 120 days, > ½ of the total growing days

and should be a good predictor of grain yield

slide13

Adjusting Yield Potential

October 1

Benchmark Planting Date

Planting Date

F5 Date

F4 Date

Adj. Index

42+20=62

29+6=35

Perkins

42

20 143 185

Tipton

29

6 116 145

slide14

SF45 = (NDVI4 + NDVI5)/days from F4 to F5

 growth

YIELD POTENTIAL

NDVI

 growth

NDVI min

F4 F5 Maturity

Feekes growth stage

slide15

Total N Uptake

40 20

50 50

Feekes 4 Feekes 5 Grain Yield

slide16

INSEY

= (NDVI

+ NDVI

)/GDD T1 to T2

INSEY

= (NDVI

+ NDVI

)/GDD T1 to T2

T1

T2

T1

T2

14

14

12

12

10

10

8

8

Above ground dry

Above ground dry

S

S

NDVI

NDVI

6

6

T1 T2

T1 T2

4

4

weight

weight

GDD

GDD

2

2

0

500

1000

1500

2000

2500

0

500

1000

1500

2000

2500

0

0

Cumulative growing degree days

Cumulative growing degree days

Rickman, R.W., Sue E. Waldman and Betty Klepper. 1996.

Rickman, R.W., Sue E. Waldman and Betty Klepper. 1996.

MODWht3: A development

-

driven wheat growth simulation.

MODWht3: A development

-

driven wheat growth simulation.

Agron J. 88:176

-

185.

Agron J. 88:176

-

185.

slide18

Normalized Difference Vegetation Index (NDVI)

= NIR ref – red ref / NIR ref + red ref

(up – down)

excellent predictor of plant N uptake

Units:

N uptake, kg ha-1

slide19

Normalized Difference Vegetation Index (NDVI)

Reasonably good predictor of final grain yield

slide20

T1

+

NDVI

NDVIT2

EstimatedYield (EY)

=

GDD from T1 to T2

+Good predictor of final grain yield- Requires two sensor readings +GDD

y = 0.4554e344.12x

R2 = 0.62

slide21

NDVI at F5

In-SeasonEstimatedYield (INSEY)1

=

days from planting to F5

+Good predictor of final grain yield+Requires only one sensor reading

Units:

N uptake, kg ha-1 day-1

slide22

NDVI at F5

In-SeasonEstimatedYield (INSEY)1

=

days from planting to F5

Hard Red Winter Wheat (Oklahoma)Soft White Winter Wheat (Virginia)

slide23

In-SeasonEstimatedYield (INSEY)2

NDVI at F5

=

days from planting to F5, GDD>0

GDD = ((Tmin + Tmax)/2)-4.4°C

Units:

N uptake, kg ha-1 day-1 where GDD>0

need for gdd
Need for GDD
  • Is growth possible on all days (October to May)?
  • Days where average temp did not exceed 4.4°C (40°F)
  • Count only those days where growth was possible
  • What if GDD was high, but moisture was limiting?
  • Under irrigation, use cumulative GDD
slide25
Oklahoma Mesonet

Discuss Mission I.

slide26

In-SeasonEstimatedYield (INSEY)2

NDVI at F5

=

days from planting to F5, GDD>0

+Good predictor of final grain yield+Requires only one sensor reading+Appears to work over different regions

Units:

N uptake, kg ha-1 day-1 where GDD>0

slide27

In-SeasonEstimatedYield (INSEY)2

NDVI at F5

=

days from planting to F5, GDD>0

Hard Red Winter Wheat (Oklahoma)Soft White Winter Wheat (Virginia)

slide28

Winter Wheat24 locations in Oklahoma1998-2001

Spring Wheat4 locations in Ciudad Obregon, MX2001

Soft White Winter Wheat7 locations in Virginia, 2001

slide30

Can We Predict Yield with No Additional N Applied?

YP0

  • Can We Predict The Yield Increase If We Apply N in a Given Year?

YPN

  • Can We Predict if Harvested Yield will be Less than Predicted Yield?

YP?

slide31

Post-maturity yield loss

12

10

8

6

4

2

0

Above ground dry weight

Harvest

Cumulative growing degree days

slide32

VEGETATIVE

REPRODUCTIVE

R-NH2

NO3

NH4

R-NH2

Total N

moistureheat

Total N

NH3

Safetyvalve

amino

NH

NO

NO

3

3

2

acids

nitrate reductase

nitrite reductase

  • NO3- + 2e (nitrate reductase) NO2- + 6e (nitrite reductase) NH4+
slide33

12

10

8

6

4

2

0

RainfallDiseaseFrost

Above ground dry weight

Harvest

Cumulative growing degree days

slide34

NEXT Section…… ????

Predicting the Increase in Yield due to Applied N

N uptake, lb/ac

40 N

0 N

October February June