Skip to main content
SpringerLink
Log in

Planning and scheduling of selective harvest with management zones delineation

  • S.I. : CLAIO 2018
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

This paper considers an integrated approach to two common problems in a precision agriculture framework: management zone delineation and selective harvest scheduling. Our model minimizes the total costs of harvest operations, establishing planning and scheduling for selective harvest of each selected management zone. Therefore, this tool provides important information for decision making of farmers in the field. Our integrated model is contrasted with the hierarchical approach commonly used in the literature for these cases, where the result of zoning problem is an input to schedule the harvest problem. Both problems were solved through a complete enumeration of all the potential management zones and demonstrated the advantages of our proposed model over the hierarchical approach. Our model reached an average reduction of 10% in harvest operations costs for different instances in a case study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Source: www.efficientvineyard.com

Fig. 2

Similar content being viewed by others

References

  • Albornoz, V. M., & Ñanco, L. J. (2016). An empirical design of a column generation algorithm applied to a management zone delineation problem. In R. Fonseca, G. W. Weber & J. Telhada (Eds.), Computational management science (pp. 201–208). Springer.

  • Albornoz, V. M., & Zamora, G. E. (2021). Decomposition-based heuristic for the zoning and crop planning problem with adjacency constraints. TOP, 29, 248–265.

    Article  Google Scholar 

  • Albornoz, V. M., Ñanco, L. J., & Sáez, J. L. (2019). Delineating robust rectangular management zones based on column generation algorithm. Computers and Electronics in Agriculture, 161, 194–201.

    Article  Google Scholar 

  • Ampatzidis, Y. G., Vougioukas, S. G., Whiting, M. D., & Zhang, Q. (2014). Applying the machine repair model to improve efficiency of harvesting fruit. Biosystems Engineering, 120, 25–33.

    Article  Google Scholar 

  • Arab, S. T., Noguchi, R., Matsushita, S., & Ahamed, T. (2021). Prediction of grape yields from time-series vegetation indices using satellite remote sensing and a machine-learning approach. Remote Sensing Applications: Society and Environment, 22, 100485.

    Article  Google Scholar 

  • Arnaout, J. P. M., & Maatouk, M. (2010). Optimization of quality and operational costs through improved scheduling of harvest operations. International Transactions in Operational Research, 17(5), 595–605.

    Article  Google Scholar 

  • Bhatti, A., Mulla, D., & Frazier, B. (1991). Estimation of soil properties and wheat yields on complex eroded hills using geostatistics and thematic mapper images. Remote Sensing of Environment, 37(3), 181–191.

    Article  Google Scholar 

  • Blackmore, S. (2000). The interpretation of trends from multiple yield maps. Computers and Electronics in Agriculture, 26(1), 37–51.

    Article  Google Scholar 

  • Bohle, C., Maturana, S., & Vera, J. (2010). A robust optimization approach to wine grape harvesting scheduling. European Journal of Operational Research, 200(1), 245–252.

    Article  Google Scholar 

  • Caixeta-Filho, J. V. (2006). Orange harvesting scheduling management: A case study. Journal of the Operational Research Society, 57(6), 637–642.

    Article  Google Scholar 

  • Carr, P., Carlson, G., Jacobsen, J., Nielsen, G., & Skogley, E. (1991). Farming soils, not fields: A strategy for increasing fertilizer profitability. Journal of Production Agriculture, 4(1), 57–61.

    Article  Google Scholar 

  • Cid-Garcia, N. M., Albornoz, V., Rios-Solis, Y. A., & Ortega, R. (2013). Rectangular shape management zone delineation using integer linear programming. Computers and Electronics in Agriculture, 93, 1–9.

    Article  Google Scholar 

  • Diker, K., Heermann, D., & Brodahl, M. (2004). Frequency analysis of yield for delineating yield response zones. Precision Agriculture, 5(5), 435–444.

    Article  Google Scholar 

  • Escallón-Barrios, M., Castillo-Gómez, D., Leal, J., & Medaglia, A. L. (2020). Improving harvesting operations in an oil palm plantation. Annals of Operations Research,. https://doi.org/10.1007/s10479-020-03686-6.

    Article  Google Scholar 

  • Ferrer, J. C., Mac Cawley, A., Maturana, S., Toloza, S., & Vera, J. (2008). An optimization approach for scheduling wine grape harvest operations. International Journal of Production Economics, 112(2), 985–999.

    Article  Google Scholar 

  • Fraisse, C., Sudduth, K., & Kitchen, N. (2001). Delineation of site-specific management zones by unsupervised classification of topographic attributes and soil electrical conductivity. Transactions of the ASAE, 44(1), 155.

    Article  Google Scholar 

  • Franzen, D., & Nanna, T. (2002). Management zone delineation methods. In Proceedings of 6th international conference on precision agriculture, Minneapolis, MN [CD-ROM], (Vol. 1417, p. 363377).

  • González-Araya, M. C., Soto-Silva, W. E., & Espejo, L. G. A. (2015). Harvest planning in apple orchards using an optimization model. In L. M. Plá-Aragonés (Ed.), Handbook of operations research in agriculture and the agri-food industry (pp. 79–105). Springer.

  • Haghverdi, A., Leib, B. G., Washington-Allen, R. A., Ayers, P. D., & Buschermohle, M. J. (2015). Perspectives on delineating management zones for variable rate irrigation. Computers and Electronics in Agriculture, 117, 154–167.

    Article  Google Scholar 

  • Herrera-Cáceres, C., Pérez-Galarce, F., Álvarez-Miranda, E., & Candia-Véjar, A. (2017). Optimization of the harvest planning in the olive oil production: A case study in Chile. Computers and Electronics in Agriculture, 141, 147–159.

    Article  Google Scholar 

  • Hornung, A., Khosla, R., Reich, R., Inman, D., & Westfall, D. (2006). Comparison of site-specific management zones. Agronomy Journal, 98(2), 407–415.

    Article  Google Scholar 

  • Hornung, A., Khosla, R., Reich, R., & Westfall, D. (2003). Evaluation of site-specific management zones: Grain yield and nitrogen use efficiency. In Proceeding of European conference on precision agriculture (pp. 297–302). 4th. Wageningen Academic Publ., Wageningen, the Netherlands.

  • Jena, S. D., & Poggi, M. (2013). Harvest planning in the brazilian sugar cane industry via mixed integer programming. European Journal of Operational Research, 230, 374–384.

    Article  Google Scholar 

  • Jiang, Q., Fu, Q., & Wang, Z. (2010). Study on delineation of irrigation management zones based on management zone analyst software. In International conference on computer and computing technologies in agriculture (pp. 419–427). Springer.

  • Johnson, C. K., Mortensen, D. A., Wienhold, B. J., Shanahan, J. F., & Doran, J. W. (2003). Site-specific management zones based on soil electrical conductivity in a semiarid cropping system. Agronomy Journal, 95(2), 303–315.

    Article  Google Scholar 

  • Junqueira, R., & Morabito, R. (2019). Modeling and solving a sugarcane harvest front scheduling problem. International Journal of Production Economics, 213, 150–160.

    Article  Google Scholar 

  • Kotsaki, E., Reynolds, A. G., Brown, R., Jollineau, M., Lee, H., & Aubie, E. (2020). Proximal sensing and relationships to soil and vine water status, yield, and berry composition in Ontario vineyards. American Journal of Enology and Viticulture, 71, 114–131.

    Article  Google Scholar 

  • Kusumastuti, R. D., van Donk, D. P., & Teunter, R. (2016). Crop-related harvesting and processing planning: A review. International Journal of Production Economics, 174, 76–92.

    Article  Google Scholar 

  • Mulla, D. (1991). Using geostatistics and GIS to manage spatial patterns in soil fertility. In Automated agriculture for the 21st century. ASAE.

  • Ortega, J., Foster, W., & Ortega, R. (2002). Definicion de sub-rodales para una silvicultura de precision: Una aplicacion del metodo fuzzy k-means. Ciencia e Investigacion Agraria v, 29(1), 35–44.

    Article  Google Scholar 

  • Ortega, R. A., & Santibáñez, O. A. (2007). Determination of management zones in corn (zea mays l.) based on soil fertility. Computers and Electronics in Agriculture, 58(1), 49–59.

    Article  Google Scholar 

  • Pastonchi, L., Di Gennaro, S. F., Toscano, P., & Matese, A. (2020). Comparison between satellite and ground data with UAV-based information to analyse vineyard spatio-temporal variability. Oeno One, 54(4), 919–934.

    Article  Google Scholar 

  • Pedroso, M., Taylor, J., Tisseyre, B., Charnomordic, B., & Guillaume, S. (2010). A segmentation algorithm for the delineation of agricultural management zones. Computers and Electronics in Agriculture, 70(1), 199–208.

    Article  Google Scholar 

  • Rey, D., & Neuhauser, M. (2011). Wilcoxon-signed-rank test. In M. Lovric (Ed.), International encyclopedia of statistical science. Berlin: Springer.

    Google Scholar 

  • Risyahadi, S. T. (2015). Scheduling model in strawberry harvesting by considering product decay during storage. Procedia Manufacturing, 4, 487–495.

    Article  Google Scholar 

  • Roudier, P., Tisseyre, B., Poilvé, H., & Roger, J. M. (2008). Management zone delineation using a modified watershed algorithm. Precision Agriculture, 9(5), 233.

    Article  Google Scholar 

  • Schepers, A. R., Shanahan, J. F., Liebig, M. A., Schepers, J. S., Johnson, S. H., & Luchiari, A. (2004). Appropriateness of management zones for characterizing spatial variability of soil properties and irrigated corn yields across years. Agronomy Journal, 96(1), 195–203.

    Article  Google Scholar 

  • Sun, L., Gao, F., Anderson, M. C., Kustas, W. P., Alsina, M. M., Sanchez, L., et al. (2017). Daily mapping of 30 m LAI and NDVI for grape yield prediction in California vineyard. Remote Sensing, 9, 317.

    Article  Google Scholar 

  • Vélez, S., Rubio, J. A., Andrés, M. I., & Barajas, E. (2019). Agronomic classification between vineyards (‘Verdejo’) using NDVI and Sentinel-2 and evaluation of their wines. Vitis - Journal of Grapevine Research, 58, 33–38.

    Google Scholar 

  • Whelan, B., Cupitt, J., & McBratney, A. (2002). Practical definition and interpretation of potential management zones in Australian dryland cropping. In P. C. Robert (Ed.), Proceedings of the 6th international conference on precision agriculture. Madison, WI: ASA-CSSA-SSSA.

    Google Scholar 

  • Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming—A review. Agricultural Systems, 153, 69–80.

    Article  Google Scholar 

  • Zhang, Q., & Pierce, F. J. (2016). Agricultural automation: Fundamentals and practices. Boca Raton: CRC Press.

    Book  Google Scholar 

  • Zhang, X., Jiang, L., Qiu, X., Qiu, J., Wang, J., & Zhu, Y. (2016). An improved method of delineating rectangular management zones using a semivariogram-based technique. Computers and Electronics in Agriculture, 121, 74–83.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions on earlier version of this paper. We also appreciate the work performed by research assistant Daniela Navarro. This research was partially supported by DGIIP from Universidad Técnica Federico Santa María (Grant PIM 172). The authors also wish to acknowledge the Ibero-American Program for Science and Technology for Development (CYTED 516RT0513).

Author information

Authors and Affiliations

  1. Departamento de Industrias, Campus Santiago Vitacura, Universidad Técnica Federico Santa María, Avenida Santa María, 6400, Vitacura, Santiago, Chile

    Víctor M. Albornoz

  2. Departamento de Industrias, Universidad Técnica Federico Santa María, Avenida Santa Marí, 6400, Vitacura, Santiago, Chile

    Lia C. Araneda

  3. Departamento de Ingeniería Comercial, Universidad Técnica Federico Santa María, Avenida Santa Marí, 6400, Vitacura, Santiago, Chile

    Rodrigo Ortega

Authors
  1. Víctor M. Albornoz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lia C. Araneda
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rodrigo Ortega
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Víctor M. Albornoz.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Albornoz, V.M., Araneda, L.C. & Ortega, R. Planning and scheduling of selective harvest with management zones delineation. Ann Oper Res 316, 873–890 (2022). https://doi.org/10.1007/s10479-021-04112-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-021-04112-1

Keywords

Search

Navigation