The Impact of Precision Agriculture Techniques on Kentucky Grain Farmers' Carbon Footprint

This study estimates the carbon footprint of a Henderson County, Kentucky grain farmer under different production strategies; traditional farming and precision agriculture technologies. Four constrained optimization, whole farm analysis models were formulated under no-till conditions. One of the models was optimized without utilizing any precision agriculture techniques and was used as a base model to compare the other three models which incorporated precision agriculture technologies (PAT). The three technologies investigated include sub-meter auto-steer, RTK auto-steer and automatic section control (ASC). These models are used to analyze the different production systems to determine if said technologies increase expected net returns and enhance the carbon input:output ratio. Given the levels of anthropogenic greenhouse gases released by the agricultural sector, quantifying the potential reduction in these gases due to the adoption of PAT is essential in seeing exactly how PAT can alter the impacts to the environment. The results show that all precision agriculture techniques produce a Pareto improvement over the base model. Specifically, automatic section control gave the greatest improvement with a mean net return that was 0.59% over the base. RTK provided the most significant enhancement in the carbon ratio with an improvement of 2.42% over the base model. All of these improvements over the base scenario can to the adoption of precision agriculture technology.


Issue Date:
2012
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/119802
Total Pages:
17




 Record created 2017-04-01, last modified 2017-08-22

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