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A Precision Agriculture Approach for a Crop Rotation Planning Problem with Adjacency Constraints

In: Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry

Author

Listed:
  • Víctor M. Albornoz

    (Universidad Técnica Federico Santa María)

  • Gabriel E. Zamora

    (Universidad Técnica Federico Santa María)

Abstract

This work tackles the management zone delineation and the crop rotation planning problems in an integrated precision agriculture framework. The zoning problem allows to define relatively homogeneous management zones regarding their soil properties and for which specific rates of agricultural inputs are necessary. From a sustainable point of view, cropping of species from different botanic families in adjacent zones at the same time can aid pest control and a reduction in the use of pesticides. More specifically, we propose a novel linear binary integer program for an integrated zoning and crop rotation planning problem with adjacency constraints. In this model, we maximize the incomes of the crop rotation plan subject to zoning constraints and adjacency constraints on crop families. The proposed model is solved using a column generation method with column-dependent rows as an algorithmic strategy. Results from a set of instances show the relevance of the proposed model as well as the need to have an algorithmic technique for solving the proposed model, being able to find acceptable feasible solutions to medium- and large-sized problems that cannot be solved directly by a commercial software.

Suggested Citation

  • Víctor M. Albornoz & Gabriel E. Zamora, 2024. "A Precision Agriculture Approach for a Crop Rotation Planning Problem with Adjacency Constraints," Springer Books, in: Víctor M. Albornoz & Alejandro Mac Cawley & Lluis M. Plà-Aragonés (ed.), Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry, pages 161-178, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-49740-7_7
    DOI: 10.1007/978-3-031-49740-7_7
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