The Business Case for Conservation

Cost-Benefit Analysis of Conservation Practices

WATCH A FARMDOC WEBINAR ON TILLAGE NITROGEN USE, & COVER CROP IMPACTS OF CORN AND SOYBEAN RETURNS

 

IL Corn developed Precision Conservation Management (PCM) to meet the management needs of farmers by making possible the integration of agronomic information with financial and environmental analytics.

PCM helps farmers address water quality through the voluntary adoption of conservation practices, the developing confidence in those practices, and the understanding of economic impacts of those practices.

 

Through an online Farmer Portal, farmers can access the economics of their farming practices or systems based on the financial averages/standard costs derived from Farm Business Farm Management (FBFM) data and University of Illinois Ag Economics Department.  Users can also enter their own financial numbers in place of the standard costs in order to get a more individualized assessment of their own on-farm economics. 

 

The farmer’s individual information is protected in this system* and is not shared unless the individual farmer grants permission.  In this case, data anonymous and aggregated before it is shared with researchers.  Through this system – either with standardized or individualized data – the farmer has access to the agronomic data on each field for his or her farm to see how well the conservation practices may be working.

 

PCM relies on an extensive set of team members including U of I, FBFM, and Heartland Science and Technology to aggregate, assess, and compare each of these data sets.  Now, in its fourth year working with Illinois farmers, PCM is prepared to make some recommendations to help farmers accomplish both their economic and their conservation goals.

 

The PCM program is focused on the following Illinois counties: Champaign, Douglas, Edgar, Ford, Coles, Vermilion, Piatt, DeWitt, Macon, Christian, Macoupin, Sangamon, Tazewell, Woodford, Livingston and McLean.  The program is also offered in Kentucky.

 

 2020 PCM Data Summa ry

 

Visit the PCM Website

Tillage Analysis, 2015-2019

Tillage Data and Recommendations download printable version here   In our last analysis, strip-till and 1-pass light tillage were the most profitable tillage systems among PCM farmers regardless of soil productivity range. The new 2018 and 2019 data changed these trends. High SPR corn fields that adopted a 2-pass light tillage system had the highest average net return; 1-pass light tillage...

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Nitrogen Analysis 2015-2019

Nitrogen Data and Recommendations download printable version here   PCM nitrogen fertilizer management analysis on high SPR soils shows that corn fields receiving more than 40 percent of the total nitrogen application in the fall demonstrated a Nitrogen Use Efficiency (NUE) >1.0, higher nitrogen fertilizer application rates and higher total costs than most in-season nitrogen fertilizer...

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Low SRP Soils in Central Illinois

Low Soil Productivity Rating Soils Data & Recommendations   download printable version here     Low soil productivity rating (SPR) soils in central Illinois continue to indicate 1-pass tillage as the most profitable system.  The table below shows an increase of $39 per acre for soybeans grown in low SPR soils when farmers forgo additional tillage passes.    This is a case where farmers...

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Cover Crop Analysis 2015-2019

Cover Crop Data and Recommendations download print friendly version here   Precision Conservation Management (PCM) data continues to be limited by a lack of farmers in the program planting cover crops.  As you review the data presented below, be aware that 1,500 – 2,000 fields in our program did not plant cover crops, while only 150-275 fields in our program did.   Also, the extremely wet...

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Historical Data

  In June 2019, IL Corn published the first PCM data summary, including recommendations for farmers based on four years of PCM farmer data.  Our experts analyzed data and made several recommendations for farmers to increase profitability - which does not always equal increasing production!  Dive into the data sets and the resulting recommendations below.  These can help you understand what...

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