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

Thumbnail Image
Date
2017-03-27
Authors
Hu, Guiping
Jubery, Talukder
Ganapathysubramanian, Baskar
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Is Version Of
Versions
Series
Department
Mechanical EngineeringIndustrial and Manufacturing Systems Engineering
Abstract

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.

Comments

This article is from PLoS ONE 12 (2017): e0174680, doi:10.1371/journal.pone.0174680. Posted with permission.

Description
Keywords
Citation
DOI
Copyright
Sun Jan 01 00:00:00 UTC 2017
Collections