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Predicting Yield Potential, 2007Predicting Yield Potential, 2007

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YCan Yield Potential (similar to “yield goals”) be Predicted MID-SEASON?Better than a preplant N decision?

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43 Locations, 1998-2006

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.01

INSEY

Gra

in y

ield

, M

g/h

a

PKNP 1998PKSN 1998TPSN 1998PKNP 1999222 1999301 1999EFAA 1999801 1999502 1999PKNP 2000222 2000301 2000EFAA 2000801 2000502 2000HNAA 2000PKNP 2001222 2001301 2001EFAA 2001801 2001PKNP 2002222 2002301 2002EFAA 2002801 2002HNAA 2002502 2003222 2003EFAA 2003PKNP 2004222 2004301 2004502 200420052006

YP0 = 0.409e258.2 INSEY R2=0.50

YP0 + 1Std Dev = 0.590 e258.2 INSEY

NDVI at F5 INSEY

Days from planting to sensing, GDD>0

Units: biomass, kg/ha/day, where GDD>0

Winter WheatWinter Wheat

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Predicting Yield Potential in Corn NDVI, V8 to V10

INSEY Days from planting to sensing

20 Locations, 2002-2005Hybrid Corn, Mexico, Nebraska, Iowa,

Oklahoma, Virginia, OhioV8-V10 (44 to 69 days)

y = 19583x1.7916

R2 = 0.71

0

2

4

6

8

10

12

14

16

18

20

0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018

INSEY

Gra

in y

ield

, M

g h

a-1

104-day (2003)

107-day (2003)

111-day (2003)

99-day (2004)

113-day (2004)

105-day (2002)

109-day (2002)

113-day (2002)

113-day (OFIT)

108-day (OFIT)

Efaw (2003)

LCB (2003)

Efaw (2004)

LCB 2004

Mexico (2002)

Shelton (2004)

Ames (2004)

OhioCORNCORN

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Exp. 502, 1971-2006

0

10

20

30

40

50

60

70

80

901

97

11

97

21

97

41

97

51

97

61

97

71

97

81

97

91

98

01

98

11

98

21

98

31

98

41

98

51

98

61

98

71

98

81

98

91

99

01

99

11

99

21

99

31

99

41

99

51

99

61

99

71

99

81

99

92

00

02

00

12

00

22

00

32

00

42

00

52

00

6

Gra

in y

ield

, b

u/a

c

0-40-60

100-40-60

Long-Term Winter Wheat Grain Yields, Lahoma, OK

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0

20

40

60

80

100

120

140

1971

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

Op

tim

um

N R

ate,

lb

/ac

Exp. 502, 1971-2006

Optimum N Rate Max YieldAvg. 49 lb N/ac +/- 39 Avg. 43 bu/ac +/- 13

Response to Fertilizer N, Long-Term Winter Wheat Experiment, Lahoma, OK

Response to Fertilizer N, Long-Term Winter Wheat Experiment, Lahoma, OK

“After the FACT” N Rate required for “MAX Yields” Ranged from 0 to 140 lbs N/ac

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Can RI be Predicted in Wheat?.... YES

0.75

1.00

1.25

1.50

1.75

2.00

2.25

2.50

2.75

3.00

3.25

0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75RINDVI

RI H

arve

st

67 Locations, 1998-2004y= -0.70 + 1.69X (x<1.72)y= 1.13 + 0.45X (x>1.72)

R2 = 0.53

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Can RI Be Predicted in Corn?... YES

MullenAgronomy Journal 95:347-351 (2003)Winter Wheat

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Improved Prediction of Yield Potential

SuperPete to the Rescue

Improved Prediction of Yield Potential

SuperPete to the Rescue

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YPMAX

INSEY (NDVI/days from planting to sensing)

Gra

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ield

YP0YPN YPN

RI=2.0RI=2.0

RI=1.5RI=1.5

RI-NFOAYPN=YP0 * RI

Nf = (YP0*RI) – YP0))/Ef

The mechanics of how N rates are computed are really very simple

1. Yield potential is predicted without N

2. The yield achievable with added N is #1 times the RI

3. Grain N uptake for #2 minus #1 = Predicted Additional N Need

4. Fertilizer Rate = #3/ efficiency factor (usually 0.5 to 0.7)

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Problems: Extremely early season prediction of

yield can be overestimated (Feekes 4, wheat) (V6, corn)

Inability to reliably predict yield potential at early stages of growth should be accompanied by more risk averse prediction models (small slope)

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0. 10

0. 75

1. 39

2. 04

ndvi

47

84

121

158

days

yl d

0. 70

22. 59

44. 49

66. 38

NDVI and days from planting to sensing where GDD>0 interact with one another

Model includes > 2800 observations (1996 to present)

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Response Mean 2.427489

Root MSE 1.383095

R-Square 0.5857

Coefficient of Variation 56.9764

Type I Sum

Regression DF of Squares R-Square F Value Pr > F

Linear 2 2148.878927 0.1731 561.67 <.0001

Quadratic 2 5084.614676 0.4095 1329.00 <.0001

Crossproduct 1 37.934739 0.0031 19.83 <.0001

Total Model 5 7271.428342 0.5857 760.23 <.0001

Sum of

Residual DF Squares Mean Square

Total Error 2689 5143.930740 1.912953

Standard from Coded

Parameter DF Estimate Error t Value Pr > |t| Data

Intercept 1 6.841693 0.488513 14.01 <.0001 10.500821

days 1 0.017736 0.007928 2.24 0.0254 -1.395237

ndvi 1 -23.847124 0.819606 -29.10 <.0001 30.358037

days*days 1 -0.000065116 0.000036672 -1.78 0.0759 -0.200572

ndvi*days 1 -0.027534 0.006183 -4.45 <.0001 -1.478405

ndvi*ndvi 1 27.065163 0.524480 51.60 <.0001 25.332527

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47-66 days, GDD>0

Group 1, Mg/ha47 - 66 days, GDD>0

y = 2.2372e0.5494x

R2 = 0.04

0

1

2

3

4

5

6

7

8

0 0.2 0.4 0.6 0.8 1

NDVI

Yie

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Mg

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67-95 days, GDD>0

Group 2, Mg/ha67 - 95 days, GDD>0

y = 1.22e1.5446x

R2 = 0.18

0

1

2

3

4

5

6

7

8

9

10

0.00 0.20 0.40 0.60 0.80 1.00

NDVI

Yie

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Mg

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96-119 days, GDD>0

Group 396 - 119 days, GDD>0

y = 0.8192e2.0179x

R2 = 0.42

0

1

2

3

4

5

6

7

8

0 0.2 0.4 0.6 0.8 1

NDVI

Yie

ld,

Mg

/ha

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120-139 days, GDD>0

Group 4120 - 139 days, GDD>0

y = 0.7067e2.0896x

R2 = 0.46

0

1

2

3

4

5

6

7

8

0 0.2 0.4 0.6 0.8 1

NDVI

Yie

ld,

Mg

/ha

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146-158 days, GDD>0

Group 5146 - 158 days, GDD>0

y = 1.0949e1.5846x

R2 = 0.45

0

1

2

3

4

5

6

7

0 0.2 0.4 0.6 0.8 1

NDVI

Yie

ld,

Mg

/ha

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Yield Prediction Curve Coefficients, kg/ha

y = -0.0003x2 + 0.0816x - 2.7337R2 = 0.99

y = 0.3231x2 - 77.8x + 5405.7R2 = 0.99

0

500

1000

1500

2000

2500

0 20 40 60 80 100 120 140 160 180

GDD

"A"

0

0.5

1

1.5

2

2.5

"B"

"A"

"B"

GDD "A" "B"52 2232 0.59481 1222 1.544

105 819 2.018125 707 2.09154 1094 1.584

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Combined RI = (NDVI-N Rich Strip/NDVI-Farmer Practice) CoefA = (0.323123*Gdd2 - 77.8* Gdd + 5406) CoefB = -0.0003469*Gdd2 + 0.08159*Gdd - 2.73372 YP0 = (CoefA * exp(CoefB * NDVI-FP)) If ((NDVI-N Rich Strip/NDVI-FP)< 1.72) RI = (NDVI-N Rich Strip/NDVI-FP)*1.69 - 0.7 If (RI<1) RI=1 YPN = YP0*RI; NRate = ((YPN-YP0)*0.0239/0.6)

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Variable Rate Technology Treat Temporal and Spatial Variability Returns are higher but require larger investment

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Just remember boys, you can always trust SuperPete!

Just remember boys, you can always trust SuperPete!