In collaboration with Paul Neiffer.
Farm Accounting has not changed much over the last several decades. Some farmers are simply content to know how much the farm operation made on a cash basis each year. Others go a step further to be able to determine how much each crop made, or even how much each field generated in contribution margin to the farming operation.
But I believe the next step in farm accounting is to determine how much contribution margin is generated by each soil type on the farm. A field can contain many different soil types, and the return to the farm can vary dramatically by each. Simply knowing the yield by type is not sufficient since a bump in yield may not offset the increased input costs that are incurred. By having data available that shows the expected return for each of these soil types, a farmer can make an informed decision as to how much inputs he should allocate for each type. Collecting and analyzing this data is not an easy task, but it can pay off big time.
How do you know if accounting by soil type is worth it? It depends largely on where you are. If your operation is blessed with entirely flat, black, well drained ground, with minimal variation in yield, it may not be worth thinking this way. However, if, for example, you had a 1000 acre operation in Wisconsin with a 50-50 split between high yield potential soils and sandy soils with yields of 180 and 130 respectively, $4 corn, and the same crop plan, input budget, and rent for each soil type, you could be making $25,000 on the good soil and losing $75,000 on the other half. In this situation, analyzing by soil might be for you. Taking the example further, looking at the marginal benefit for N inputs you could improve your outcome by $6,600 using economically optimal N application on the land, even in spite of lower yield potential.
Average within-field coefficient of variation in soil quality from >10 million CLUs in Granular’s AcreValue system.
This example might sound extreme, but how common is extreme variation in soil quality within fields? We analyzed over 10 million farm fields (CLUs) from AcreValue to look at how within-field soil variability changes around the US. The Dakotas and Appalachia are hotspots for within-field soil variability, while the Des Moines Lobe in Iowa, Loess of Illinois and Lake Plain of Ohio are home to very low variability. However, for those of you in the corn belt, seeing that the most uniform soils in the US according to the NCCPI index are on the coastal plains of North Carolina might come as a bit of a surprise.
So what does this mean for the prospect of accounting by soil type? If you are in the red zones, it may be time to give it a try this winter while putting together your plans for 2016. For a grower, looking at this map should be able to help him or her judge where they land in comparison with peers in other regions as it relates to this important metric. If you are an farm advisor, farm accountant or other member of a grower’s trusted network, discussing this type of analysis in an area with more variable soils is more likely to hit home.
 Iowa State Nitrogen Rate Calculator http://extension.agron.iastate.edu/soilfertility/nrate.aspx $13.33 comes from the .37/lb N * 36 lbs comparison assumes $600 ammonia and continuous corn.
 Within-field soil variability is defined as the area-weighted standard deviation of NCCPI within a CLU (field), an aggregated to the county level and divided by the mean.