Development of canopy vigour maps using UAV for site-specific management during vineyard spraying process

Abstract

Site-specific management of crops represents an important improvement in terms of efficiency and efficacy of the different labours, and its implementation has experienced a large development in the last decades, especially for field crops. The particular case of the spray application process for what are called “specialty crops” (vineyard, orchard fruits, citrus, olive trees, etc.) represents one of the most controversial and influential actions directly related with economical, technical, and environmental aspects. This study was conducted with the main objective to find possible correlations between data obtained from remote sensing technology and the actual canopy characteristics. The potential correlation will be the starting point to develop a variable rate application technology based on prescription maps previously developed. An unmanned aerial vehicle (UAV) equipped with a multispectral camera was used to obtain data to build a canopy vigour map of an entire parcel. By applying the specific software DOSAVIÑA®, the canopy map was then transformed into a practical prescription map, which was uploaded into the dedicated software embedded in the sprayer. Adding to this information precise georeferenced placement of the sprayer, the system was able to modify the working parameters (pressure) in real time in order to follow the prescription map. The results indicate that site-specific management for spray application in vineyards result in a 45% reduction of application rate when compared with conventional spray application. This fact leads to a equivalent reduction of the amount of pesticide when concentration is maintained constant, showing once more that new technologies can help to achieve the goal of the European legislative network of safe use of pesticides.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

References

  1. Albetis, J., Duthoit, S., Guttler, F., Jacquin, A., Goulard, M., Poilvé, H., et al. (2017). Detection of Flavescence dorée grapevine disease using Unmanned Aerial Vehicle (UAV) multispectral imagery. Remote Sensing, 9, 308.

    Article  Google Scholar 

  2. Ballesteros, R., Ortega, J. F., Hernández, D., & Moreno, M. Á. (2015). Characterization of Vitis vinifera L. canopy using unmanned aerial vehicle-based remote sensing and photogrammetry techniques. American Journal of Enology and Viticulture, 66(2), 120–129.

    Article  Google Scholar 

  3. Balsari, P., Doruchowski, G., Marucco, P., Tamagnone, M., Van de Zande, J., & Wenneker, M. (2008). A system for adjusting the spray application to the target characteristics. Agricultural Engineering International: CIGR Journal, XS, 1–11.

    Google Scholar 

  4. Baluja, J., Diago, M. P., Balda, P., Zorer, R., Meggio, F., Morales, F., et al. (2012). Assessment of vineyard water status variability by thermal and multispectral imagery using an Unmanned Aerial Vehicle (UAV). Irrigation Science, 30, 511–522.

    Article  Google Scholar 

  5. Carvalho, F. P. (2017). Pesticides, environment, and food safety. Food and Energy Security, 6(2), 48–60.

    Article  Google Scholar 

  6. Codis, S., Douzals, J. P., Davy, A., Chapuis, G., Debuisson, S., & Wisniewski, N. (2012). Doses de produits phytos autorisées sur vigne en Europe, vont-elles s’harmoniser? Phytoma, 656, 37–41.

    Google Scholar 

  7. Damalas, C. A., & Eleftherohorinos, I. G. (2011). Pesticide exposure, safety issues, and risk assessment indicators. International Journal of Environmental Research and Public Health, 8(5), 1402–1419.

    CAS  Article  Google Scholar 

  8. de Castro, A. I., Jiménez-Brenes, F. M., Torres-Sánchez, J., Peña, J. M., Borra-Serrano, I., & López-Granados, F. (2018). 3-D characterization of vineyards using a novel UAV imagery-based OBIA procedure for precision viticulture applications. Remote Sensing, 2018(10), 584. https://doi.org/10.3390/rs10040584.

    Article  Google Scholar 

  9. Doruchowski, G., Balsari, P., & Van de Zande, J. C. (2009). Development of a crop adapted spray application system for sustainable plant protection in fruit growing. In Proceedings of international symposium on application of precision agriculture for fruits and vegetables, Orlando, FL, USA.

  10. Dobrowski, S., Ustin, S., & Wolpert, J. (2003). Grapevine dormant pruning weight prediction using remotely sensed data. Australian Journal of Grape and Wine Research, 9, 177–182.

    Article  Google Scholar 

  11. Du, Q., Chang, N. B., Yang, C., & Srilakshmi, K. R. (2008). Combination of multispectral remote sensing, variable rate technology and environmental modeling for citrus pest management. Journal of Environmental Management, 86(1), 14–26.

    Article  Google Scholar 

  12. EFSA (European Food Safety Authority). (2018). The 2016 European Union report on pesticide residues in food. EFSA Journal, 16(7), 5348. https://doi.org/10.2903/j.efsa.2018.5348.

    CAS  Article  Google Scholar 

  13. EPPO (European Plant Protection Organization). (2012). Dose expression for plant protection products. Bulletin OEPP/EPPO Bulletin, 42(3), 409–415. https://doi.org/10.1111/epp.12000.

    Article  Google Scholar 

  14. EPPO (European Plant Protection Organization). (2016). Conclusions and recommendations. Plenary session. Workshop on harmonized dose expression for the zonal evaluation of plant protection products in high growing crops. Vienna. Retrieved from https://www.eppo.int/media/uploaded_images/MEETINGS/Conferences_2016/dose_expression/Conclusions_and_recommendations.pdf

  15. Escolà, A., Rosell-Polo, J. R., Planas, S., Gil, E., Pomar, J., Camp, F., et al. (2013). Variable rate sprayer Part 1—Orchard prototype: design, implementation and validation. Computers and Electronics in Agriculture, 95, 122–135. https://doi.org/10.1016/j.compag.2013.02.004.

    Article  Google Scholar 

  16. EU. (2009). Directive 2009/128/EC of the European Parliament and of the Council of 21 October 2009 Establishing a Framework for Community Action to Achieve the Sustainable Use of Pesticides; 2009/128/EC (p. 2009). Bruxelles, Belgium: European Parliament.

    Google Scholar 

  17. Garcerá, C., Fonte, A., Moltó, E., & Chueca, P. (2017). Sustainable use of pesticide applications in citrus: A support tool for volume rate adjustment. International Journal of Environmental Research and Public Health, 14(7), 715.

    Article  Google Scholar 

  18. Gil, E., Arnó, J., Llorens, J., Sanz, R., Llop, J., Rosell-Polo, J. R., et al. (2014a). Advanced technologies for the improvement of spray application techniques in Spanish viticulture: An overview. Sensors, 14(1), 691–708. https://doi.org/10.3390/s120100691.

    Article  PubMed  Google Scholar 

  19. Gil, E., & Escolà, A. (2009). Design of a decision support method to determine volume rate for vineyard spraying. Applied Engineering in Agriculture, 25(2), 145–151.

    Article  Google Scholar 

  20. Gil, E., Escolà, A., Rosell, J. R., Planas, S., & Val, L. (2007). Variable rate application of plant protection products in vineyard using ultrasonic sensors. Crop Protection, 26, 1287–1297.

    Article  Google Scholar 

  21. Gil, E., Gallart, M., Llorens, J., Llop, J., Bayer, T., & Carvalho, C. (2014b). Spray adjustments based on LWA concept in vineyard. Relationship between canopy and coverage for different application settings (pp. 25–32). Oxford, UK: International Advances in Pesticide Applications.

    Google Scholar 

  22. Gil, E., Llop, J., Gallart, M., Valera, M., Llorens, J. (2015). Design and evaluation of a manual device for air flow rate adjustment in spray application in vineyards. A: Workshop on spray application techniques in fruit growing. In: Proceedings of the Suprofruit 2015—13th Workshop on Spray Application in Fruit Growing. Linday: p. 8-9.

  23. Gil, E., Llorens, J., Landers, A., Llop, J., & Giralt, L. (2011). Field validation of DOSAVIÑA, a decision support system to determine the optimal volume rate for pesticide application in vineyards. European Journal of Agronomy, 35(1), 33–46. https://doi.org/10.1016/j.eja.2011.03.005.

    Article  Google Scholar 

  24. Gil, E., Llorens, J., Llop, J., Escolà, A., & Rosell-Polo, J. R. (2013). Variable rate sprayer. Part 2—Vineyard 1 prototype: Design, implementation and validation. Computers and Electronics in Agriculture, 95, 136–150. https://doi.org/10.1016/j.compag.2013.02.010.

    Article  Google Scholar 

  25. Hall, A., Lamb, D. W., Holzapfel, B., & Louis, J. (2002). Optical remote sensing applications in viticulture—A review. Australian Journal of Grape and Wine Research, 8, 36–47.

    Article  Google Scholar 

  26. Jeon, H. Y., Zhu, H., Derksen, R., Ozkan, E., & Krause, C. (2011). Evaluation of ultrasonic sensor for variable—Rate spray applications. Computers and Electronics in Agriculture, 75(2011), 213–221.

    Article  Google Scholar 

  27. Johnson, L. (2003). Temporal stability of an NDVI-LAI relationship in a Napa Valley vineyard. Australian Journal of Grape and Wine Research, 9, 96–101. https://doi.org/10.1111/j.1755-0238.2003.tb00258.x.

    Article  Google Scholar 

  28. Johnson, L., Bosch, D., Williams, D., & Lobitz, B. (2001). Remote sensing of vineyard management zones: Implications for wine quality. Applied Engineering in Agriculture, 17, 557–560. https://doi.org/10.13031/2013.6454.

    Article  Google Scholar 

  29. Johnson, L. F., Roczen, D. E., Youkhana, S. K., Nemani, R. R., & Bosch, D. F. (2003). Mapping Vineyard leaf area with multispectral satellite imagery. Computers and Electronics in Agriculture, 38, 37–48.

    Article  Google Scholar 

  30. Le Maire, G., François, C., Soudani, K., Berveiller, D., Pontailler, J., Bréda, N., et al. (2008). Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass. Remote Sensing of Environment, 112, 3846–3864.

    Article  Google Scholar 

  31. Lee, K., & Ehsani, R. (2008). A laser-scanning system for quantification of tree-geometric characteristics (p. 083980). St. Joseph, MI, ASABE Paper No: ASABE.

    Google Scholar 

  32. Llorens, J., Gil, E., Llop, J., & Escolà, A. (2011). Ultrasonic and LIDAR sensors for electronic canopy characterization in vineyards: advances to improve pesticide application methods. Sensors, 11(2), 2177–2194. https://doi.org/10.3390/s110202177.

    Article  PubMed  Google Scholar 

  33. Matese, A., Toscano, P., Di Gennaro, S., Genesio, L., Vaccari, F., Primicerio, J., et al. (2015). Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture. Remote Sensing, 7(3), 2971–2990.

    Article  Google Scholar 

  34. Mathews, A. J., & Jensen, J. L. R. (2013). Visualizing and quantifying vineyard canopy LAI using an Unmanned Aerial Vehicle (UAV) collected high density structure from motion point cloud. Remote Sensing, 5, 2164–2183.

    Article  Google Scholar 

  35. Meier, U. (1997). BBCH-Monograph. Growth stages of plants - Entwicklungsstadien von Pflanzen - Estadios de las plantas - Développement des Plantes. Blackwell Wissenschaftsverlag, Berlin und Wien. 622 p

  36. Miranda-Fuentes, A., Llorens, J., Rodriguez-Lizana, A., Cuenca, A., Gil, E., Blanco-Roldán, G. L., et al. (2016). Assessing the optimal liquid volume to be sprayed on isolated olive trees according to their canopy volumes. Science of the Total Environment, 568(2016), 269–305.

    Google Scholar 

  37. Mõttus, M., Sulev, M., & Lang, M. (2006). Estimation of crown volume for a geometric radiation model from detailed measurements of tree structure. Ecological Modelling, 198, 506–514.

    Article  Google Scholar 

  38. Palleja, T., Landers, A. (2015). Precision fruit spraying: measuring canopy density and volume for air and liquid control. SuproFruit 2015 – 13th workshop on spray application in fruit growing, Lindau, Germany, 15–18 July 2015. Julius-Kühn-Archiv, 448.

  39. Patrick, A., & Changying, L. (2017). High throughput phenotyping of blueberry bush morphological traits using Unmanned Aerial Systems. Remote Sensing, 2017(9), 1250. https://doi.org/10.3390/rs9121250.

    Article  Google Scholar 

  40. Pergher, G., Petris. R. (2008). Pesticide Dose Adjustment in Vineyard Spraying and Potential for Dose Reduction. Agricultural Engineering International: The CIGR Ejournal. Manuscript ALNARP 08 011. Vol. X.

  41. Poblete-Echeverría, C., Olmedo, G. F., Ingram, B., & Bardeen, M. (2017). Detection and segmentation of vine canopy in ultra-high spatial resolution rgb imagery obtained from Unmanned Aerial Vehicle (UAV): A case study in a commercial vineyard. Remote Sens., 9, 268.

    Article  Google Scholar 

  42. Primicerio, I., Di Gennaro, S. F., Fiorillo, E., Genesio, L., Lugato, E., Matese, A., et al. (2012). A flexible unmanned aerial vehicle for precision agriculture. Precision Agriculture, 13(4), 517–523.

    Article  Google Scholar 

  43. Rosell, J. R., & Sanz, R. (2012). A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Computers and electronics in agriculture, 81, 124–141.

    Article  Google Scholar 

  44. Rouse, J. W., R. H. Haas, J. A. Schell, and D. W. Deering. (1973). Monitoring vegetation systems in the Great Plains with ERTS, Third ERTS Symposium, NASA SP-351 I, 309-317.

  45. Salcedo, R., Garcerá, C., Granell, R., Molto, E., & Chueca, P. (2015). Description of the airflow produced by an air-assisted sprayer during pesticide applications to citrus. Spanish Journal of Agricultural Research, 2, 4.

    Google Scholar 

  46. Solanelles, F., Planas, S., Escolà, A., & Rosell, J. R. (2002). Spray application efficiency of an electronic control system for proportional application to the canopy volume. International advances in pesticide application 2002. Aspects of Applied Biology, 66, 139–146.

    Google Scholar 

  47. Solanelles, F., Planas, S., Rosell, J. R., Camp, F., & Gràcia, F. (2006). An electronic control system for pesticide application proportional to the canopy width of tree crops. Biosystems Engineering, 95(4), 473–481.

    Article  Google Scholar 

  48. Toews, B., & Friessleben, R. (2012). Dose rate expression—Need for harmonization and consequences of the Leaf Wall Area approach. Aspects of Applied Biology, 114, 2012. https://doi.org/10.1007/s10341-012-016-z.

    Article  Google Scholar 

  49. UMA-UPC. (2018). DOSAVIÑA®. Decision Support System for determining the optimal volume rate in vineyard. Retrieved August 2018, from https://dosavina.upc.edu.

  50. USGS (2018). NDVI, the Foundation for Remote Sensing Phenology. Retrieved August 2018, from https://phenology.cr.usgs.gov/ndvi_foundation.php.

  51. Walklate, P., & Cross, J. (2012). An examination of leaf-wall-area dose expression. Crop Protection, 35, 132–134.

    Article  Google Scholar 

  52. Wei, J., & Salyani, M. (2005). Development of a laser scanner for measuring tree canopy characteristics: Phase 2. Foliage density measurement. Transactions of ASAE, 48(4), 1595–1601.

    Article  Google Scholar 

  53. Weiss, M., & Baret, F. (2017). Using 3D point clouds derived from UAV RGB imagery to describe vineyard 3D macro-structure. Remote Sensing, 9, 111.

    Article  Google Scholar 

  54. Xiongkui, H., Bonds, J., Herbst, A., & Langenakens, J. (2017). Recent development of unmanned aerial vehicle for plant protection in East Asia. International Journal of Agricultural and Biological Engineering, 10(3), 18–30.

    Google Scholar 

Download references

Acknowledgements

The authors sincerely wish to thank Andreu Piñol, Topcon Positioning Spain S.L.U., Ilemo-Hardi, S.A.U., and AgriArgo Ibérica, S.A.

Funding

This research was partially funded by the “Ajuts a les activitats de demostració (operació 01.02.01 de Transferència Tecnològica del Programa de desenvolupament rural de Catalunya 20142020)” and an FI-DGR Grant from Generalitat de Catalunya (2018 FI_B1 00083). Research and improvement of Dosaviña have been developed under LIFE PERFECT project: Pesticide Reduction using Friendly and Environmentally Controlled Technologies (LIFE17 ENV/ES/000205).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Emilio Gil.

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

Verify currency and authenticity via CrossMark

Cite this article

Campos, J., Llop, J., Gallart, M. et al. Development of canopy vigour maps using UAV for site-specific management during vineyard spraying process. Precision Agric 20, 1136–1156 (2019). https://doi.org/10.1007/s11119-019-09643-z

Download citation

Keywords

  • Unmanned aerial vehicle (UAV)
  • Canopy map
  • Variable rate application
  • DOSAVIÑA
  • Spray map