Li Qi, Hu Guiping, Jubery Talukder Zaki, Ganapathysubramanian Baskar
Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, United States of America.
Department of Mechanical Engineering, Iowa State University, Ames, Iowa, United States of America.
PLoS One. 2017 Mar 27;12(3):e0174680. doi: 10.1371/journal.pone.0174680. eCollection 2017.
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.
农田管理涉及多项规划和决策任务，包括种子选择和灌溉管理。本研究提出了一种基于混合整数线性规划的农场级精准农田管理模型。针对作物季前规划和灌溉用水分配设计了最优决策。该模型考虑了决策规模的大小和形状以及特殊灌溉模式的影响。作者通过对美国加利福尼亚州一个农场的案例研究对该模型进行了说明，并表明该模型能够捕捉精准农场管理对盈利能力的影响。结果表明，通过精心选择灌溉方式和种子，农民的年净利润可提高两倍。虽然农民仅对种子或灌溉应用精准管理就能增加利润，但如果同时对种子和灌溉应用精准管理，利润增长会更显著。所提出的模型还可以作为面临季节性灌溉用水限制的农民的风险分析工具，以及探索精准农业影响的定量工具。
