Maybe you have seen some tweets and pictures about manure
application uniformity testing over the past years, or hopefully seen some
information about upcoming field
days where uniformity is going to be a key topic. You might be wondering
why we are making a big deal about this, but when it comes to using manure as a
fertilizer effectively, understanding how uncertainty impacts your decisions is
critical for making the best management decision.
So why should we worry about manure application uniformity?
Nitrogen for crop growth can come from multiple sources, the soil organic
matter can mineralize and in doing so release mineral nitrogen for the plant. The
remaining nitrogen needed to support crop growth comes from applied fertilizer.
Years of research have gone into characterizing how crops would respond. If you take a look at the Nitrogen Rate Calculator it will give
you an idea of how a corn crop (in this case corn following soybeans) responds
to the addition of nitrogen. What this graph (figure 1) shows is how the
addition of nitrogen causes corn to respond. What the figure demonstrates is
that we want to apply somewhere around 150 lb N/acre, if we are less than this
the yield goes down, if we apply more than this we see minimal yield
improvement.
Figure 1. Corn
response to added nitrogen for Iowa conditions for a corn crop following
soybean.
So what does this all have to do with manure application
uniformity? When we are trying to hit 150 lb N/acre does that mean we just need
to average that for the field? Probably not, it’s about getting a condition
where it’s uniform over the whole field (yes, there might be some soil
variations and every field has a bit different response to nitrogen, and
weather conditions matter so some year’s crop response to nitrogen is much more
drastic than others, but for the sake of argument, let’s work with this curve
to see what it means).
For fun as we think about the math behind this problem,
let’s assume we have corn planted on 30-inch spacing, our manure toolbar also
has 30-inch spacing, and that corn roots only get their nitrogen from the
manure application band that was placed next to that corn row. Then let’s
figure we applied 150 lb N/acre from liquid swine manure that tested 50 lb
available N/1000 gallons, so we were applying 3000 gallons an acre.
Now think about two pieces of equipment, one has a
knife-to-knife coefficient of variation of 35% at this application rate, the
other has a coefficient of variation of 10%. In both cases let’s figure an
8-knife setup. To give you an idea what this looks like in terms of nitrogen
application rates achieved by the different knives and the impact different
levels of uniformity have on crop yield let’s run through an example. Both of
the tools in this example hit the right application rate on average, but how
they do it, in terms of evenness across the toolbar is very different. What I
want you to start thinking about is what would this mean for your crop yield
from row-to-row and nitrogen leaching.
Table 1. Nitrogen and
manure application rates for two pieces of application equipment that that
achieve different levels of manure application uniformity.
Knife #
|
N Application
(lb N/acre) |
N Application
(lb N/acre) |
Application Rate
(gallons/acre) |
Application Rate
(gallons/acre) |
% of
Desired Rate |
% of
Desired Rate |
1
|
100
|
150
|
2000
|
3000
|
67
|
100
|
2
|
135
|
160
|
2700
|
3200
|
90
|
107
|
3
|
165
|
170
|
3300
|
3400
|
110
|
113
|
4
|
210
|
160
|
4200
|
3200
|
140
|
107
|
5
|
220
|
150
|
4400
|
3000
|
147
|
100
|
6
|
180
|
140
|
3600
|
2800
|
120
|
93
|
7
|
120
|
120
|
2400
|
2400
|
80
|
80
|
8
|
70
|
150
|
1400
|
3000
|
47
|
100
|
Average
|
150
|
150
|
3000
|
3000
|
100
|
100
|
St. Dev.
|
53
|
15
|
1060
|
302
|
35
|
10
|
COV
|
35
|
10
|
35
|
10
|
35
|
10
|
So let’s do a nitrogen example, using figure 1 (the nitrogen
response curve) you can make an estimate of the corn yield that would be
achieved from each of the knives (and if you assume a maximum yield of around
200 bushels an acre) can figure out what the field level yields would be.
So if you work through this math, you can find a few interesting results (table
2). Even though we were putting on the same amount of nitrogen on in both
cases, because of variation from knife-to-knife we get different average yields
per acre. In the case of corn following soybean, yields increased by 2 extra
bushels per acre yield from the improved distribution and in the case of
continuous corn about 4 extra bushels per acre. But there are other things to
notice, the coefficient of variation in corn yield is always much lower than
that in the nitrogen application rate. The soil supplies some of the nitrogen
and this dampens out the response making everything a bit more uniform, but one
thing to keep in mind is that early in the growing season the response might be
more visually drastic than what final yields end up showing. Overall I think
this asks an interesting question -how good is uniform enough, how does
application uniformity uncertainty compare with other uncertainties in crop
production, and how does this information help us make better manure decisions?
Table 2. Impact of
nitrogen application uniformity on crop yield in corn-soybean (CS) and
continuous corn (CC) rotations for machines with coefficients of variation in
their application of 35% (left) and 10% (right)
Knife #
|
Corn Yield (CS)
(bu/acre) |
Corn Yield (CS)
(bu/acre) |
|
Corn Yield (CC)
(bu/acre) |
Corn Yield (CC)
(bu/acre) |
1
|
187
|
194
|
162
|
179
|
|
2
|
193
|
195
|
175
|
182
|
|
3
|
196
|
196
|
183
|
184
|
|
4
|
198
|
195
|
190
|
182
|
|
5
|
198
|
194
|
191
|
179
|
|
6
|
197
|
193
|
186
|
177
|
|
7
|
191
|
191
|
170
|
170
|
|
8
|
178
|
194
|
|
146
|
179
|
Average
|
192
|
194
|
175
|
179
|
|
St. Dev.
|
7
|
2
|
16
|
4
|
|
COV
|
4
|
1
|
|
9
|
2
|
To learn more about this topic and how you can get the most
benefit from your manure make sure you register for one of our four field days, get a
free lunch, get your manure questions answered, and learn how to set yourself
up to maximize the benefit of manure on your farm this fall.
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