Understanding Soil Productivity Ratings

One of the most important components of farmland value is soil productivity, but most of the information available about how productivity metrics work is overly technical, conflicting, or buried in long reports. These sources are not particularly helpful when trying to understand the potential of farmland to produce food, fuel, or fiber. Add to that the complexity of translating a soil productivity rating into actual crop yields, and it’s no wonder so many feel overwhelmed by the topic.

At AcreValue, we compile public data sources such as land ownership, records of land transactions, crop histories, precipitation, and soil information from local, state and federal government agencies, private entities, foundations, and universities. We then synthesize this data into the most comprehensive land database available and make it easy for users to analyze the value and productive capacity of their farms. Though we provide a wealth of soil information on AcreValue, the challenge comes in interpreting it. Do not despair, however, we are here to help!

What soils information does AcreValue provide?

If you identify your farm on AcreValue and explore the soils information provided in the report, you will note that we provide a wide variety of data, including:

  • Soil map
  • List of soils present, with slope and erosion information
  • Acreage and percentage (%) of each soil type
  • Soil rating (PI, CPI, CSR2, or NCCPI) for each soil
  • Average soil productivity rating for the farm
  • County average soil productivity rating (great for comparing!)
  • A “heat map” of the farm, showing more productive soils in darker colors and less productive soils in lighter colors. This offers a quick visualization of a farm’s range in productivity, even if you’re not familiar with specific soil types
  • List of soil classes, which is another illustration of productivity. They range from 1 to 8, with Class 1 being the highest productivity

Depending on your use case, the soil analysis can be completed based on parcel boundaries, CLUs (i.e., USDA FSA tillable boundaries), or any custom boundary that you choose to draw.

You can compare the productive potential of farms by comparing their weighted average soil productivity rating (best done on the soils present on only the tillable/cropland acreage).

Where does soil productivity information come from? Like others in agriculture, we rely on the Soil Survey Geographic Database (SSURGO), which refers to digital soils data from the Natural Resources Conservation Service (NRCS), for our soils information. These data include the productive capacity of the soil, however, how productivity is expressed varies by state or geographic region:

Corn Suitability Rating 2 (CSR2) State: Iowa

CSR2 rates a soil’s potential to produce row crops, and is the standard productivity index used in Iowa. Iowa State University replaced CSR with CSR2 in 2012 toward the goal of greater transparency and consistency, as the original CSR came out of an obscure 1971 paper. CSR2 ranges from 5 (least productive) to 100 (most productive). CSR2 lets farmers and landowners easily compare productivity across farms. For example, a farm with an average CSR2 of 85 is significantly more productive than one with an average CSR2 of 60. Additionally, land brokers and appraisers often analyze markets based on how much land is selling for by “dollars per CSR2 point” — larger numbers mean a stronger land market or a “seller’s market.” For more information on CSR2, check out these resources available through Iowa State University.

Productivity Index (PI) State: Illinois

Productivity Index or PI, published by the University of Illinois (see Bulletin 811), is used to measure the yield potential of soils in Illinois. PIs range from 47 to 147, and higher PIs are generally associated with higher corn and soybean yields under optimal management. The more productive a farm’s individual soils, the higher it’s weighted average PI.

In Illinois, land market participants often talk in terms of “prime agricultural land classes,” though classes are no longer published in Bulletin 811. Soil types with optimum PIs ranging from 133-147 are Class A, from 117-132 are Class B, and from 100-116 are Class C. (Soil types with PI’s of 99 or below are not considered prime agricultural land.)

Crop Productivity Index (CPI) State: Minnesota

In order to measure soil productivity in Minnesota, the state NRCS office created the “Crop Productivity Index” or CPI, which ranges from 0 to 100. Higher numbers indicate higher productive potential. The Minnesota NRCS did not take into account climatic factors like growing degree days or precipitation in creating the index, so if the same soil type existed on the border with Iowa and the border with Canada, it would have the same rating despite having a very different yield potential in those two places.

Productivity Index (PI) State: North Dakota

North Dakota uses the same term as Illinois – “Productivity Index” – but the indices are different and are not interchangeable. Like Minnesota’s CPI, North Dakota’s PI ranges from 0 to 100. The Productivity Index for North Dakota came from the NRCS.

National Commodity Crop Productivity Index (NCCPI) States: All Others

The NCCPI is a national (continental US) interpretation that’s not intended to replace other crop production models developed by individual states — it’s considered less reliable than the more locally-produced measures. For a deeper dive into the NCCPI, here is the 2012 User Guide.

So in summary, here is a visual of the various soil rating systems, the specific state(s) they apply to, and the ranges for each rating. In all cases, a higher rating is better.

Soil RatingState(s)Range
CSR2Iowa5 – 100
PIIllinois47 – 147
CPIMinnesota0 – 100
PINorth Dakota0 – 100
NCCPIAll other states0 – 100

How do soil ratings translate to actual crop yields?

Now, how do these ratings translate into actual crop yields? Let’s look at a couple of examples. In Iowa, there is a published formulaic relationship: Estimated corn yield = (1.6 x CSR2) + 80. So given this relationship, a farm with a CSR2 of 100 should achieve a corn yield of 240 bushels per acre under a high level of management.

In Illinois, Amended Table S2 of Bulletin 811 provides a corresponding yield for several common regional crops, including corn and soybeans, for each soil type. For example, Muscatune silt loam has a PI of 147 and can achieve a corn yield of 200 bushels per acre under an optimal level of management.

While the ratings stay the same over time, actual yields can increase (e.g., improved genetics) so keep in mind that the relationship between the two will vary over time.

In Summary

Soils remain fundamentally important to the productivity, income potential, and market value of your farm. But making sense of soil productivity ratings and how they relate to actual yields can be somewhat of a challenge. We hope that the information provided above will serve as a valuable resource.

photo of Chris Seifert
About Chris Seifert

Chris leads the data science team at Granular. Previously, Chris held roles at Google and NASA and has worked on geospatial analysis projects in conjunction with collaborators ranging from the International Maize and Wheat Improvement Center to the Qatari government. He was also the first ag-tech hire at The Climate Corporation, where he helped pioneer the use of weather and soil information for index-based insurance as well as agricultural decision support at scale. Chris holds a BS, MS and PhD in Earth Systems from Stanford University.

photo of LeeAnn Moss
About LeeAnn Moss

LeeAnn directs industry marketing for AcreValue. Previously, she co-owned a real estate brokerage, valuation, and consulting company specializing in farm real estate across the Midwest. She has held various roles with national agricultural asset management and valuation firms and organizations. She has written extensively on farmland valuation, leasing, and agribusiness management. LeeAnn holds a BSc in Animal Science from the University of Guelph, and a PhD in Agricultural Economics from the University of Illinois.

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