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.