A farm-level precision land management framework based on integer programming

dc.contributor.author Ganapathysubramanian, Baskar
dc.contributor.author Li, Qi
dc.contributor.author Hu, Guiping
dc.contributor.author Jubery, Talukder
dc.contributor.author Ganapathysubramanian, Baskar
dc.contributor.author Hu, Guiping
dc.contributor.department Mechanical Engineering
dc.contributor.department Industrial and Manufacturing Systems Engineering
dc.date 2018-02-18T12:52:14.000
dc.date.accessioned 2020-06-30T06:03:53Z
dc.date.available 2020-06-30T06:03:53Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.issued 2017-03-27
dc.description.abstract <p>Farmland management involves several planning and decision making tasks including seed selection and irrigation management. A farm-level precision farmland management model based on mixed integer linear programming is proposed in this study. Optimal decisions are designed for pre-season planning of crops and irrigation water allocation. The model captures the effect of size and shape of decision scale as well as special irrigation patterns. The authors illustrate the model with a case study on a farm in the state of California in the U.S. and show the model can capture the impact of precision farm management on profitability. The results show that threefold increase of annual net profit for farmers could be achieved by carefully choosing irrigation and seed selection. Although farmers could increase profits by applying precision management to seed or irrigation alone, profit increase is more significant if farmers apply precision management on seed and irrigation simultaneously. The proposed model can also serve as a risk analysis tool for farmers facing seasonal irrigation water limits as well as a quantitative tool to explore the impact of precision agriculture.</p>
dc.description.comments <p>This article is from <em>PLoS ONE </em>12 (2017): e0174680, doi:<a href="http://dx.doi.org/10.1371/journal.pone.0174680" target="_blank">10.1371/journal.pone.0174680</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/me_pubs/206/
dc.identifier.articleid 1210
dc.identifier.contextkey 10233287
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath me_pubs/206
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/55062
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/me_pubs/206/2017_Ganapathysubramanian_FarmLevel.pdf|||Fri Jan 14 22:26:26 UTC 2022
dc.source.uri 10.1371/journal.pone.0174680
dc.subject.disciplines Agricultural Science
dc.subject.disciplines Applied Mechanics
dc.subject.disciplines Mechanical Engineering
dc.subject.disciplines Plant Breeding and Genetics
dc.title A farm-level precision land management framework based on integer programming
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication da41682a-ff6f-466a-b99c-703b9d7a78ef
relation.isAuthorOfPublication a9a9fb1b-4a43-4d73-9db6-8f93f1551c44
relation.isOrgUnitOfPublication 6d38ab0f-8cc2-4ad3-90b1-67a60c5a6f59
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
File
Original bundle
Now showing 1 - 1 of 1
Name:
2017_Ganapathysubramanian_FarmLevel.pdf
Size:
1.82 MB
Format:
Adobe Portable Document Format
Description:
Collections