Abstract
A multi-faceted whole farm planning model is developed to compare conventional and autonomous machinery for grain crop production under various benefit, farm size, suitable field day risk aversion, and grain price scenarios. Results suggest that autonomous machinery can be an economically viable alternative to conventional manned machinery if the establishment of intelligent controls is cost effective. An increase in net returns of 24% over operating with conventional machinery is found when including both input savings and a yield increase due to reduced compaction. This study also identifies the break-even investment price for intelligent controls for the safe and reliable commercialization of autonomous machinery. Results indicate that the break-even investment price is highly variable depending on the financial benefits resulting from the deployment of autonomous machinery, farm size, suitable field day risk aversion, and grain prices. The maximum break-even investment price for intelligent, autonomous controls is nearly US$500 000 for the median days suitable for fieldwork when including both input savings and a yield increase due to reduced compaction.
Document Type
Article
Publication Date
2-2-2019
Digital Object Identifier (DOI)
https://doi.org/10.1007/s11119-019-09638-w
Funding Information
This research was partially funded by a USDA-CSREES Grant titled “Precision Agriculture: Development and Assessment of Integrated Practices for Kentucky Producers.”
Repository Citation
Shockley, Jordan Murphy; Dillon, Carl R.; and Shearer, Scott A., "An Economic Feasibility Assessment of Autonomous Field Machinery in Grain Crop Production" (2019). Agricultural Economics Faculty Publications. 15.
https://uknowledge.uky.edu/agecon_facpub/15
Notes/Citation Information
To be published in Precision Agriculture, p. 1-18.
© Springer Science+Business Media, LLC, part of Springer Nature 2019
This is a post-peer-review, pre-copyedit version of an article published in Precision Agriculture. The final authenticated version is available online at: https://doi.org/10.1007/s11119-019-09638-w.
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