Understanding Precision Farming and Soil Morphology

Understanding Precision Farming and Soil Morphology

The USDA Soil Conservation Service, now Natural Resources Conservation Service, has been charged with creating the country’s soil survey. This survey was designed for broad land use planning. My career was spent mapping soils across the country and that process included identifying soil components within a soil mapping unit. Years were spent digging 30 to 40 holes a day describing soils and developing landscape models for predicting where the soils formed on the landform. The information gathered was then used to create the historical soil survey manuscripts.


Then in 2004, the hard copy manuscripts were entered into USDA NRCS NASIS database and published to the Soil Data Mart (SDM) database. The SDM database contains the soil mapping units, their components, and the component properties for the entire country. Many precision farming web sites and professionals reference the Soil Data Mart soils map, but incorrectly refer to the map unit as a soil type. Using the dominant soil as a soil type is appropriate in broad land use planning, however in precision farming applications, understanding all the soils within the map unit is necessary to correctly identify and understand management zones.

The base image presented below is a SoilWeb soils map displaying a specific field in the lower right hand corner. Inset into this base image are three analyses of that same field, used to identify the various (gross) soil components. The lower right hand corner is the base field soils map presenting two map units: 3401 and 3402. Map unit 3401 is the Longford silt loam, with 1% to 3% slopes. Map unit 3402 is the Longford silt loam, with 3% to 7% slopes. The red X is in map unit 3402 and the focus of this article.


When a polygon is chosen in SoilWeb, the Map Unit Composition is displayed. In this case, map unit 3402 contains seven identified components. The dominant component is the Longford series, however the minor components are listed to identify the expected landform position. The estimated composition percentage is an amalgamation of all the 3402 polygons, not the specific polygon. The SCS soil survey was created using maps varying from scales of 1:15,840 (4 inch to the mile) to 1:24,000 (2.64 inch to the mile). The NRCS has standardized the mapping scales to 1:12,000 and 1:24,000. Precision farming mapping uses much smaller scales of 1:2,400 (26 inches to the mile), or greater.

Although the mapping scales and precision farming scales are significantly dissimilar, information can be gleaned from the soils database to aid in precision farming prescriptions. In a very simple analysis, this field used the Veris Technologies mapper to intensively map the soils using electrical conductivity (EC). EC mapping is a common method of mapping the differences of the soils within the field. Analysis of the Veris mapper data can help predict changes in the soils across the field.

The lower left image is the Veris surface-to-subsoil ratio combined with the five-year crop yield data. The red dots being the lowest values (less variation, highest yields) and the purple dots being the highest values (greatest variation, lowest yields). The soil morphology is homogenous in the red areas and dissimilar in the purple areas. These are clues used to differentiate the various components within the field or within the map unit.

The upper left image is a Veris analysis of only the surface-to-subsoil readings ratio. The red are those with a low EC ratio and green being the high EC ratio. Using the stoplight legend allows for grouping of similar EC points. These various analysis of EC mapping, yield mapping, along with information gleaned from the NRCS soils map database, contains enough information to sufficiently separate the various soil components. The computer analysis provided clues for areas to ground truth the soil type.

The upper right hand image is the gross soil type or soil component map. That map was created to identify field sample sites. Visiting the site to dig holes is needed to understand the soil morphology. This is as important as collecting samples for soil fertility in the upper 6 inches. The soil profile provides clues both in the history of the soil and the answers as to plant productivity.


Understanding the soil morphology is necessary to determine the cause and effects of crop selection and production. The soil morphology explains potential troublesome soil properties. In the soil photos above, the range in the EC readings can be used to identify the natural Longford, the eroded Longford, the higher clay content Crete soil, the toeslope Longford with its higher organic matter and clay content, and the Hobbs soil with its increased organic matter and homogenous silt loam profile.

There are many stories that can be gleaned from understanding the soil morphology. For example, this field has been in no-till for eight years, however the morphological evidence shows the scars still exist from the many decades of tillage. Take the time to use the NRCS soils database to identify the clues used in prescriptive farming.

For more information on analysis of the SSURGO database for precision farming, contact Paul R. Finnell at [email protected] or visit prairiehillssoilsconsulting.com or LinkedIn.

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