A few years
ago, I became interested in the value of manure sampling and how obtaining good
information helped us make better nutrient management decisions. I tried to use
the theory of value of data to determine how much a manure sample was worth.
Read a summary here.
Many factors cause
variations in manure's average nutrient concentration: diet, housing type,
manure storage type, environmental conditions, management techniques, and
treatment practices. Just as critically, our ability to agitate and create a
uniform, homogeneous mixture is often limited by our ability to stir manure
storages.
A repeated
sampling at five manure storages was used to assess the average, standard
deviation, and coefficient of variability. The data were summarized as averages
across the sampling data set to determine the variability in manure
concentrations from each manure application event. Average manure nutrient
concentrations were 28, 16, and 21 pounds of N, P, and K, respectively, per 1,000
gallons with standard deviations of 4, 7, and 3.
In
determining the manure test's value, it is essential to understand how a farmer
can use the information gained from the test results, i.e., how having this
information alters the farmer's nutrient management and affects the farm
profit. This is a complex topic, as almost limitless possibilities exist. This
evaluation assumed the manure application method would be either injection or
immediate incorporation to maximize N utilization. Additionally, we assumed
best management practices for manure application timing were followed. As a
result, the yield response to available N (defined here as the sum of ammonia N
and organic N expected to mineralize in the first growing season) would be the
same as the yield response to mineral N fertilizer. Finally, we limited crop
rotation choices to continuous corn and corn-soybean rotations, as these
represent the dominant rotations in the upper Midwestern U.S.
Our
methodology was to estimate the profit that would have been made if the manure
was assumed to have a "typical" nutrient composition and then to
compare this to the profit generated if the actual nutrient composition was
known. To make this evaluation, an economic model was developed as an Excel
spreadsheet. The model compared the costs and revenue of corn production. Corn
yield was calculated as the product of maximum yield and the estimated percent
yield that was achieved.
For a
corn-soybean rotation where the manure is going to corn, this means that the
real-time nutrient correction for manure would be worth approximately $3.13 per
acre. However, in a continuous corn rotation, which is more sensitive to
nitrogen application in terms of crop response, it would be worth around $4.29 per acre. However, understanding just how big this variability is from
load-to-load or pass-to-pass is critical for putting value to this technology.
