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Cover
PG6 | Iowa Soybean Association Watershed Programming
Locations
PG7 | Buttrick Creek watershed project - N evaluation
PG8 | South Fork watershd project - N evaluation
PG9 | Boone River watershed project - N evaluation
PG10 | Pike Run watershed project - N evaluation
A1 - A5 | Location of on-farm and watershed strip
trials
The 2005 ISA On-Farm Network® poster shows the locations of the many programs offered by the On-Farm Network® in 2005. Nitrogen management activity took place in all 99 counties this past year.
Replicated strip testing
Replicated strip testing allows producers to compare yields
from two different management practices. The poster shows
guidelines for establishing followed by the On-Farm Network® protocols.
Late spring soil nitrate test: what can it do?
The late-spring nitrate test is a tool that can be used in
Nitrogen management to estimate the amount of available N
in the soil. This poster addresses where the late-spring nitrate
test should be used and some of the limitations of the test.
End of season stalk nitrate test
The end-of-season stalk nitrate test is another nitrogen management
tool used in post- season assessment of nitrogen. This poster
explains the proper collection and handling of samples.
Guided stalk sampling
Guided stalk nitrate sampling is a relatively new concept
that integrates precision farming technologies with the end-of-season
stalk nitrate test. The poster explains why this approach
is used and how to implement this concept using remote sensing,
GPS, and GIS tools.
B1
- B5 | Impacts of reducing rates
of spring-applied N by 50 pounds per acre
The average yield response for the UAN trials was 9 bu/acre,
whereas the average response for the NH3 trials was only 6
bu/acre.
Summary of Spring N +/- 50 lb N/acre
Most producers who participated in the Spring +/- 50 lb N/acre
could reduce their rates by 50 lb N/acre without reducing
profi ts.
Is 100 lb/acre of fertilizer N enough for corn following
soybean in Iowa?
If applying N after crop emergence for corn after soybean,
100 lb N/acre typically maximizes profits.
An analysis of optimal sidedressing N rates for corn
following soybean
The price of N fertilizer greatly affects the optimal N rate.
For the scenario for $0.20 /lb N and $2.00 corn, the 10% profit
rate was 109 lb N/acre.
Examples of “ultimate” two-treatment response
trials
Better spatial pattern categories are needed to identify areas
that vary in N fertilizer needs.
B6
- B9 | How does fall anhydrous
compare to spring N?
Time of application did not cause a yield response between
the fall-applied anhydrous ammonia and the spring-applied
N, but additional years of data are needed due to growing
season variability.
Are Fall Anhydrous losses less than 50 lbs N/acre?
During the 2005 growing season, the spring and spring –
50 lb N/acre showed a response where as the fall vs. spring
trials did not, but more data is still needed to support this
fi nding.
N-sufficiency levels in cornfi elds with injected
liquid swine manure
1. Measuring yield responses to extra N
Application of fertilizer N after injected liquid swine manure
decrease profits unless it is possible to identify the responsive
sites prior to fertilization. Above average rainfall in the
March through May period is a possible indicator that the
late-spring soil nitrate test should be used.
N-suffi ciency levels in cornfi elds with injected liquid
swine manure
2. Testing cornstalks for nitrate
End-of-season cornstalk testing is a way to check N-sufficiency
levels if a GPS unit and yield monitor are not available.
B10 | N-sufficiency levels in cornfi elds with injected
liquid swine manure
3. Testing soils for nitrate in late spring
The late-spring test for soil nitrate is not needed on fields
with injected liquid swine manure unless a problem is suspected.
C1
- C4 | Nitrogen-sufficiency levels:
A practical and defensible basis for management guidelines
Reducing model bias problem and variability in yield
response when calculating economic optimum N rates
Different models produce systematic errors (model bias) when
calculating economic optimum rates (EORs) of N for corn when
fitting these models to the same set of yield response data.
We found to reduce systematic errors in EOR values, apply,
and analyze only N rates in the near-optimal range.
Source of model bias problem when calculating optimal N rates
Model bias problem occur because different models give different
slopes (yield response per a pound of N applied) or marginal
products in the near-optimal range. Slopes of the models were
found to be nearly linear related to N rates in the near-optimal
range.
Discrete marginal analysis method for estimating optimal N
rates
A new method, discrete marginal analysis, was tested for calculating
optimal N rates for corn without using models. We found that
discrete marginal products were almost linear related to N
rates in the near-optimal range as result greatly simplifying
calculations of optimal N rates.
C5
- C15 | Estimating
N optimal rates with the desired rates of profi t by using
discrete marginal analysis
Economic optimum rates of N fertilization are calculated
with the assumption that producers have unlimited amount capital
and, therefore, yield responses on the last units of N applied
just pay for the cost this N. A new method, discrete marginal
analysis, was used to calculate optimal N rates that give
the desired rates of profi t on the last units of N applied.
“N calculator” for estimating N
optimal rates for two-treatment N response precision farming
trials
An Excel program was created to estimate N optimal
rates for two-treatment N response precision farming trials
by using slopes of the relationship between discrete marginal
products and rates of N fertilization observed in a sample
of trials collected in the past.
Use of cumulative distribution functions of
yield responses to estimate optimal N rates on the scale of
farms
Cumulative distribution functions were used to calculate
probabilities of getting given yield responses to N fertilizer
applied, estimate optimal rates of N fertilization, and reduce
effects of errors and extreme observations in yield responses
on values of optimal N rates estimated on the scale of the
farms.
A multi-step procedure for estimating optimal
rates of N fertilization in on-farm N response trials
A general procedure was outlined for conducting yield
response trials, collecting and analyzing yield response observations,
and calculating reliable optimal rates of N fertilization
in on-farm N response trials.
Spring rainfall leaches N before the corn can grow
Spring rainfall amounts affect the amount of N available
to a corn crop.
Reliability of manure guidelines is questioned
More than 200 replicated trials by ISU show the current
guidelines in Iowa State publication Pm-1811 have little accuracy
in predicting the optimal amount of N for corn on manured
soils.
Effects of carbon in manure on supplies of N for corn
growth
Higher levels of carbon can decrease N availability
for a corn crop.
Equivalency of N supplied in liquid
swine manure
Equivalency of N applied in liquid swine manure compared
to N applied as urea ammonium nitrate solution was estimated
at four locations in 2004 and showed the estimated availability
to be less than 60%.
Equivalency of N supplied in liquid swine manure
Equivalency of N applied in liquid swine manure compared
to N applied as urea ammonium nitrate solution was estimated
below 70% at two sites of corn after soybean in 2005.
Interpreting the results from “guided”
stalk nitrate samples #1
This sheet gives an example of how to interpret the
multiple samples for a single field interpretation.
Interpreting the results from “guided”
stalk nitrate samples #2
This sheet gives an example of how to interpret the
weather effect on the field classification.
E1 | Soil pH and buffer pH: what’s the
difference?
Overview of differences between pH and buffer pH.
How they relate to buffering capacity of the soil and lime
recommendations.
E2 | High soil pH promotes loses of fall applied N
Overview of studies assessing the importance of soil pH as
a factor affecting nitrification rates and losses of fall
applied N.
E3 | Remote sensing of soybean canopy confi
rms the importance of soil pH on losses of fall applied anhydrous
ammonia
Aerial images of corn canopy showing complex spatial patterns
of fall N loss showed good correlations with spatial patterns
of soybean that exhibited symptoms of iron deficiency chlorosis
on high-pH soils.
E4 | How do calcareous soils form?
Geological processes that led to calcareous soils in the Iowa
landscape include formatoin of prairie potholes where calcite
laden groundwater collects and evaporates, leaving behind
rings of calcitic soil.
E5 | Progression of iron defi ciency chlorosis in soybean
with time
Poster captures time series of pictures that show progression
of visual symptoms of iron deficiency chlorosis.
E6 | Mapping nigh-pH soils on the field scale
Poster describes the potential of remote sensing of soybean
canopy to identify and map calcareous soils on the fi eld
scale. Aerial images are superior to grid sampling in addressing
the complex spatial variability that occurs in the field.
E7 | Remote sensing to characterize stresses on soybean
in fi elds with high-pH soils
Poster describes the procedure of development of soil stress
alkalinity index, which combines the effect of pH and carbonates.
Alkalinity index was superior to pH or carbonates alone in
describing yield variability on the field scale.
E8 | Summary of liming trial
A Central Iowa liming trial, begun in 2001, raises agronomic
and economic questions about current liming recommendations.
F1 | Ammonia volatilization from surface-applied urea
fertilizer
If urea is applied to a wet soil and not incorporated, N losses
can be expected.
F2 | Losses of N from fertilizer solutions sprayed on
soils
There are several issues with urea ammonium nitrate solutions
that can lead to N loss if mismanaged.
F3 | Will improvements in the effi ciency of N fertilization
deplete soil organic matter?
Fertilizing to optimal N rates will not deplete soil organic
matter over the long term.
F4 | Benefi ts of nitrifi cation inhibitors as assessed
by producers using precision farming technologies
Despite the fact that N-Serve did appear to reduce N losses
in fall-applied anhydrous ammonia, the value of N loss was
not as high as the cost of the product. In short, N-Serve
was not profitable.
F5 | Does mid-season application of nitrogen increase
corn yields?
Mid season N application was profi table but it may have been
because of dry weather.
F6 | Comparison of dribbled and injected fertilizer-N
solutions sidedressed for corn
There was a trade off between the cost and benefits of the
sidedressed applications.
F7 | Evaluation of polymer-coated urea as a fertilizer
for corn
The polymer-coated urea did not show consistent benefi ts.
F8 | Spring rainfall summaries for 2000
F9 | Spring rainfall summaries for 2001
F10 | Spring rainfall summaries for 2002
F11 | Spring rainfall summaries for 2003
F12 | Spring rainfall summaries for 2004
F13 | Spring rainfall summaries for 2005
F14 | Iowa’s two-treatment trials with
precision farming technologies
1. A general introduction focusing on N-response trials
This trial allows growers to make the types of comparisons
that benefi t them.
F15 | Iowa’s two-treatment trials with precision
farming technologies
2. The “ultimate” N-response trials
It’s suggested that producers use these ‘ultimate’
trials once they’ve conducted initial N management trials
for a fi nal fine-tuning of N management.
F16 | Iowa’s two-treatment response trials with
precision farming technologies
3. Current methods for establishing N-response trials
Attention to details in establishing and harvesting trials
can make them run better.
F17 | Iowa’s two-treatment trials with precision
farming technologies
4. Should non-fertilized controls be included
in N-response trials?
Zero N rates should only be used if it’s likely that
yields can be optimal with no applied N.
F18 | Iowa’s two-treatment trials with precision
farming technologies
5. Defining “optimal” rates of N fertilization
Defining the true ‘optimal’ rate is diffi cult
and people disagree on how to calculate it.
F19 | Iowa’s two-treatment trials with precision
farming technologies
6. How much would have another 50 pounds of N
increased yields?
There is a simple formula that can be used to guess how much
yield response would occur with more fertilizer than applied
in the treatments tested.
F20 | Temporal
patterns in chlorophyll meter readings
Studies showed that chlorophyll meters were effective to diagnose
severe N deficiencies early in the season but performed poorly
in the near-optimal range of N sufficiency.
F21 | Temporal patterns in symptoms of nitrogen defi ciency
as revealed by
remote sensing of corn Remote sensing of canopy reflectance
was proved useful for diagnosing N deficiencies, but had limited
sensitivity when it was used early in the season to predict
yield response.
F22 | Calibrating remote sensing to yield response by
using cumulative distribution
Cumulative distribution functions (CDF) of canopy refl ectance
and yield responses were compared for their pattern and consistency
in diagnosing N deficiencies. CDFs provide a simple way to
address variability in these two measurements.
F23 | Diagnosing deficiencies of N during vegetative growth
of
1. Effects of anhydrous ammonia bands on young plants
F24 | Diagnosing deficiencies of N during vegetative
growth of corn
2. Measuring height to leaf collars to characterize growth
F25 | Diagnosing
deficiencies of N during vegetative growth of corn
3. Fertilizer-induced advances in growth stage
F26 | Diagnosing
deficiencies of N during vegetative growth of corn
4. The leaf-change problem when chlorophyll meters are used
F27 | Diagnosing
deficiencies of N during vegetative growth of corn
5. Leaf-change errors with chlorophyll meters
F27A | The leaf-change
problem associated with chlorophyll measurements near silking
to diagnose deficiencies of N
Discontinuity in chlorophyll meter readings
due to the measurement switching from the uppermost fully
developed leaf to the ear leaf made the diagnoses of N deficiency
more diffi cult when plants are not at the same growth stage.
F28 | Diagnosing deficiencies of N during vegetative growth
of corn
6. Visual rating versus chlorophyll meters
Visual ratings may be more reliable than chlorophyll meters.
F29 | Testing the assumption that nitrogen fertilizer
needs are proportional to yields of corn Fertilizer needs
are not proportional to yield goals
F30 | Are recommendations for variable rate application
of N reliable?
Current guidelines for variable rate application
are not adequate.
BACK
COVER
E1 | Soil pH and buffer pH: what’s the
difference?
Overview of differences between pH and buffer pH.
How they relate to buffering capacity of the soil and lime
recommendations.
E2 | High soil pH promotes loses of fall applied N
Overview of studies assessing the importance of soil pH as
a factor affecting nitrification rates and losses of fall
applied N.
E3 | Remote sensing of soybean canopy confi
rms the importance of soil pH on losses of fall applied anhydrous
ammonia
Aerial images of corn canopy showing complex spatial patterns
of fall N loss showed good correlations with spatial patterns
of soybean that exhibited symptoms of iron deficiency chlorosis
on high-pH soils.
E4 | How do calcareous soils form?
Geological processes that led to calcareous soils in the Iowa
landscape include formatoin of prairie potholes where calcite
laden groundwater collects and evaporates, leaving behind
rings of calcitic soil.
E5 | Progression of iron defi ciency chlorosis in soybean
with time
Poster captures time series of pictures that show progression
of visual symptoms of iron deficiency chlorosis.
E6 | Mapping nigh-pH soils on the field scale
Poster describes the potential of remote sensing of soybean
canopy to identify and map calcareous soils on the fi eld
scale. Aerial images are superior to grid sampling in addressing
the complex spatial variability that occurs in the field.
E7 | Remote sensing to characterize stresses on soybean
in fi elds with high-pH soils
Poster describes the procedure of development of soil stress
alkalinity index, which combines the effect of pH and carbonates.
Alkalinity index was superior to pH or carbonates alone in
describing yield variability on the field scale.
E8 | Summary of liming trial
A Central Iowa liming trial, begun in 2001, raises agronomic
and economic questions about current liming recommendations.
F1 | Ammonia volatilization from surface-applied urea
fertilizer
If urea is applied to a wet soil and not incorporated, N losses
can be expected.
F2 | Losses of N from fertilizer solutions sprayed on
soils
There are several issues with urea ammonium nitrate solutions
that can lead to N loss if mismanaged.
F3 | Will improvements in the effi ciency of N fertilization
deplete soil organic matter?
Fertilizing to optimal N rates will not deplete soil organic
matter over the long term.
F4 | Benefi ts of nitrifi cation inhibitors as assessed
by producers using precision farming technologies
Despite the fact that N-Serve did appear to reduce N losses
in fall-applied anhydrous ammonia, the value of N loss was
not as high as the cost of the product. In short, N-Serve
was not profitable.
F5 | Does mid-season application of nitrogen increase
corn yields?
Mid season N application was profi table but it may have been
because of dry weather.
F6 | Comparison of dribbled and injected fertilizer-N
solutions sidedressed for corn
There was a trade off between the cost and benefits of the
sidedressed applications.
F7 | Evaluation of polymer-coated urea as a fertilizer
for corn
The polymer-coated urea did not show consistent benefi ts.
F8 | Spring rainfall summaries for 2000
F9 | Spring rainfall summaries for 2001
F10 | Spring rainfall summaries for 2002
F11 | Spring rainfall summaries for 2003
F12 | Spring rainfall summaries for 2004
F13 | Spring rainfall summaries for 2005
F14 | Iowa’s two-treatment trials with
precision farming technologies
1. A general introduction focusing on N-response trials
This trial allows growers to make the types of comparisons
that benefi t them.
F15 | Iowa’s two-treatment trials with precision
farming technologies
2. The “ultimate” N-response trials
It’s suggested that producers use these ‘ultimate’
trials once they’ve conducted initial N management trials
for a fi nal fine-tuning of N management.
F16 | Iowa’s two-treatment response trials with
precision farming technologies
3. Current methods for establishing N-response trials
Attention to details in establishing and harvesting trials
can make them run better.
F17 | Iowa’s two-treatment trials with precision
farming technologies
4. Should non-fertilized controls be included
in N-response trials?
Zero N rates should only be used if it’s likely that
yields can be optimal with no applied N.
F18 | Iowa’s two-treatment trials with precision
farming technologies
5. Defining “optimal” rates of N fertilization
Defining the true ‘optimal’ rate is diffi cult
and people disagree on how to calculate it.
F19 | Iowa’s two-treatment trials with precision
farming technologies
6. How much would have another 50 pounds of N
increased yields?
There is a simple formula that can be used to guess how much
yield response would occur with more fertilizer than applied
in the treatments tested.
F20 | Temporal
patterns in chlorophyll meter readings
Studies showed that chlorophyll meters were effective to diagnose
severe N deficiencies early in the season but performed poorly
in the near-optimal range of N sufficiency.
F21 | Temporal patterns in symptoms of nitrogen defi ciency
as revealed by
remote sensing of corn Remote sensing of canopy reflectance
was proved useful for diagnosing N deficiencies, but had limited
sensitivity when it was used early in the season to predict
yield response.
F22 | Calibrating remote sensing to yield response by
using cumulative distribution
Cumulative distribution functions (CDF) of canopy refl ectance
and yield responses were compared for their pattern and consistency
in diagnosing N deficiencies. CDFs provide a simple way to
address variability in these two measurements.
F23 | Diagnosing deficiencies of N during vegetative growth
of
1. Effects of anhydrous ammonia bands on young plants
F24 | Diagnosing deficiencies of N during vegetative
growth of corn
2. Measuring height to leaf collars to characterize growth
F25 | Diagnosing
deficiencies of N during vegetative growth of corn
3. Fertilizer-induced advances in growth stage
F26 | Diagnosing
deficiencies of N during vegetative growth of corn
4. The leaf-change problem when chlorophyll meters are used
F27 | Diagnosing
deficiencies of N during vegetative growth of corn
5. Leaf-change errors with chlorophyll meters
F27A | The leaf-change
problem associated with chlorophyll measurements near silking
to diagnose deficiencies of N
Discontinuity in chlorophyll meter readings
due to the measurement switching from the uppermost fully
developed leaf to the ear leaf made the diagnoses of N deficiency
more diffi cult when plants are not at the same growth stage.
F28 | Diagnosing deficiencies of N during vegetative growth
of corn
6. Visual rating versus chlorophyll meters
Visual ratings may be more reliable than chlorophyll meters.
F29 | Testing the assumption that nitrogen fertilizer
needs are proportional to yields of corn Fertilizer needs
are not proportional to yield goals
F30 | Are recommendations for variable rate application
of N reliable?
Current guidelines for variable rate application
are not adequate.
BACK
COVER
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