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A report issued by the U.S. Department of Agriculture’s Economic Research Service, looked at adoption rates for precision agriculture (PA) to investigate PA adoption and its impact on profitability.
November 10, 2016

A report issued by the U.S. Department of Agriculture’s Economic Research Service, looked at adoption rates for precision agriculture (PA) to investigate PA adoption and its impact on profitability. Three types of PA technologies were examined:

  • GPS-based mapping systems (including yield monitors and soil/yield mapping)
  • guidance or auto-steer systems
  • variable-rate technology (VRT) for applying inputs.1
The report found that utilizing PA technologies increased net profitability on the average U.S. farm but that adoption rates varied significantly across technology and farm size.

  • All three technologies have positive impacts on both net returns and operating profits for average size US corn farms2:

    GPS mapping increases the operating profit of corn farms by 2.8% with an increase in net return of 1.8%. Guidance Systems raise operating profit on corn farms by 2.5% and net returns by 1.5%. Variable-rate technology (VRT) raises both operating profit and net return on corn farms by 1.1%.

  • Adoption rates vary significantly across PA technologies3:

    Yield monitors that produce the data for GPS-based mapping are the most widely adopted and are used on about half of all corn and soybean farms. Auto-steer systems are used on about a third of farms that use yield monitors, while GPS-based yield mapping can be found on a quarter of those farms. Soil mapping using GPS coordinates and VRT are used on 16 -26% of yield monitoring farms.

  • The largest corn farms, over 2,900 acres, have double the PA adoption rates of all farms4:

    70-80% of large farms use mapping, about 80% use guidance systems, and 30-40% use variable rate technology. The share of all corn and soybean acres on which PA technologies are used tends to be higher than the share of farms, implying that larger farms are more likely to adopt these technologies. Yield mapping is used on about 40% of US corn and soybean acres, GPS soil maps on about 30%, guidance over 50%, and VRT on 28-34% of acres.5

  • PA technology adoption and farm size both influence production costs on corn farms6:

    Hired labor costs are 60-70% lower with any of the three PA technologies on smaller corn farms but higher on large farms that need to hire personnel for information management as well as field operation specialists. Larger farms tend to have expenses for other inputs that these specialists can help control using PA that falls out of the capabilities of farm management.7

  • Statistical analysis finds that several production inputs and practices are associated, both positively and negatively, with adoption of PA technology on corn farms8:

    Non-GPS-based soil testing increases the adoption of all PA technology. Higher levels of unpaid labor and higher yield goals have a negative effect on PA adoption. Unpaid labor, unpaid hours provided by farm household members or partners, is a large fixed overhead that reduced flexibility to adopt new technology. Farms do not factor these hours into marginal cost of production analysis that plays a part in PA technology adoption decisions. Higher yield goals, harvesting more crop per unit of land area, may be an indication that a farmer may already be close to the production potential for their land.


RubinBrown has a dedicated Life Sciences and Technology Services Group that works with local, national and international companies to provide advisory, assurance and tax services for entities participating in or supporting life sciences and technology industries.

We will continue to monitor the levels and trends in ag-tech, including precision agriculture technology and what they mean for life sciences and technology related industries and the overall economy. Advisory Services can assist in decision analysis and modeling to help determine if investing in precision agriculture technologies is a value-creating proposition for production operations.

 

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Sources:

1    Schimmelpfennig, David. Farm Profits and Adoption of Precision Agriculture, ERR-217, U.S. Department of Agriculture, Economic Research Service, October 2016.  Page 5

2    Ibid. Page 35

3    Ibid. Page 5

4    Ibid. Page 5

5    Ibid. Page 6

6    Ibid. Page 6

7    Ibid. Page 6

8    Ibid. Page 6


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