Soil and Environmental Monitoring on a Vineyard in the Guadalupe Valley as a Tool for Processes of Precision Viticulture Based on ZigBee Technology to Improve the E-Agriculture

  • J. A. López-LeyvaEmail author
  • A. Talamantes-Álvarez
  • E. Sanabia-Vincent
  • L. Aguilera-Silva
  • G. Gastelum-Rodríguez
  • O. Meza-Arballo
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1154)


This paper presents the design and field tests of a system to remotely monitor environmental variables in a vineyard in the Guadalupe Valley, Mexico. In particular, the environmental variables are temperature, humidity, and luminosity, some of them monitored in the subsoil. These variables affect the quality of the grapes, and these quality parameters are also different according to each grape variety according to the different stages of the crop. The presented prototype is based on the ZigBee technology and is part of the E-Agriculture process, particularly related to Precision Agriculture concept. In addition, measurements were made with the early-adopters in order to determine the performance of the prototype and consider the feedback to improve the overall performance. Finally, the prototype shows an adequate performance with respect to the measurements of the environmental variables, the reliability of the interconnection, the storage and presentation of the data. Also, there are some findings that could improve the performance and installation of the prototype to enhance the E-Agriculture process and the widespread use in the Guadalupe Valley through a sectorization process according to the grape variety crops.


Monitoring Precision viticulture Prototype 


  1. 1.
    Walls, H., Baker, P., Chirwa, E., Hawkins, B.: Food security, food safety & healthy nutrition: are they compatible?. Global Food Security (2019). (In Press)Google Scholar
  2. 2.
    Barrett, C.B., Palm, C.: Meeting the global food security challenge: obstacles and opportunities ahead. Global Food Secur. 11, 1–4 (2016)Google Scholar
  3. 3.
    Kasturi, P.: Technology and food security. Humanomics 25(2), 163–168 (2009)Google Scholar
  4. 4.
    Bongiovanni, R., Lowenberg-Deboer, J.: Precision agriculture and sustainability. Precision Agric. 5(4), 359–387 (2004)Google Scholar
  5. 5.
    McBratney, A., Whelan, B., Ancev, T., Bouma, J.: Future directions of precision agriculture. Precision Agric. 6(1), 7–23 (2005)Google Scholar
  6. 6.
    Santesteban, L.G.: Precision viticulture and advanced analytics. Short Rev. Food Chem. 279, 58–62 (2019)Google Scholar
  7. 7.
    Newson, D.N., Ratcliff, A.R., Freckleton, J.C.: Practical applications of precision viticulture in Australia. Acta Hort. 978, 37–46 (2013)Google Scholar
  8. 8.
    Zhu, Q., Lin, H.S., Doolittle, J.A.: Functional soil mapping for site-specific soil moisture and crop yield management. Geoderma 200–201, 45–54 (2013)Google Scholar
  9. 9.
    Gili, A., Álvarez, C., Bagnato, R., Noellemeyer, E.: Comparison of three methods for delineating management zones for site-specific crop management. Comput. Electron. Agric. 139, 213–223 (2017)Google Scholar
  10. 10.
    Braga, R.P., Jones, J.W.: Using optimization to estimate soil inputs of crop models for use in site-specific management. Trans. ASAE 47(5), 1821–1831 (2004)Google Scholar
  11. 11.
    Schramm, H.: On Farm Tools for Site Specific Crop Management. SAE Technical Paper Series (1995)Google Scholar
  12. 12.
    Zhang, Q.: Precision Agriculture Technology for Crop Farming. CRC Press, Boca Raton (2015)Google Scholar
  13. 13.
    Pedersen, S.M., Lind, K.M.: Progress in Precision Agriculture. Springer, Cham (2017).
  14. 14.
    Cao, F., Wu, D., He, Y.: Soluble solids content and pH prediction and varieties discrimination of grapes based on visible–near infrared spectroscopy. Comput. Electron. Agric. 71, S15–S18 (2010)Google Scholar
  15. 15.
    D’Agata, I.: Native Wine Grapes of Italy. University of California Press, Berkeley (2019)Google Scholar
  16. 16.
    Pedersen, S.M., Lind, K.M. (eds.): Precision Agriculture: Technology and Economic Perspectives. PPA. Springer, Cham (2017). Scholar
  17. 17.
    Adamchuk, V.I., Morgan, M.T., Lowenberg-Deboer, J.M.: A model for agro-economic analysis of soil ph mapping. Precision Agric. 5(2), 111–129 (2004)Google Scholar
  18. 18.
    Li, Daoliang, Zhao, Chunjiang (eds.): CCTA 2008. IAICT, vol. 293. Springer, Boston, MA (2009). Scholar
  19. 19.
    Kondawar, D.G.: Information and communication technology in agriculture. J. Commer. Manag. Thought 9(4), 509 (2018)Google Scholar
  20. 20.
    Demiryürek, K.: Information systems and communication networks for agriculture and rural people. Agric. Econ. 56(5), 209–214 (2010)Google Scholar
  21. 21.
    Zhang, N., Taylor, R.K.: Applications of a Field Level Geographic Information System (FIS) in Precision Agriculture. Appl. Eng. Agric. 17(6), 885–892 (2001)Google Scholar
  22. 22.
    Rahmadian, R., Widyartono, M.: Machine vision and global positioning system for autonomous robotic navigation in agriculture: a review. J. Inf. Eng. Educ. Technol. 1(1), 46–54 (2017)Google Scholar
  23. 23.
    Fernandez, G.: Applications of statistical data mining methods. In: Conference on Applied Statistics in Agriculture, pp. 1–16 (2004)Google Scholar
  24. 24.
    Georg, R.: Computational Intelligence in Intelligent Data Analysis. Springer, Berlin (2013). Scholar
  25. 25.
    Mašík, I.: Reliability of ZigBee transmission in agriculture production. Res. Agric. Eng. 59(4), 153–159 (2013)Google Scholar
  26. 26.
    Lin, Y.G.: An intelligent monitoring system for agriculture based on ZigBee wireless sensor networks. Adv. Mater. Res. 383–390, 4358–4364 (2011)Google Scholar
  27. 27.
    Bakó, K.I.: ZigBee technology in precision agriculture. Acta Agraria Debreceniensis 47, 15–17 (2012)Google Scholar
  28. 28.
    Planinić, M.: Influence of temperature and drying time on extraction yield of phenolic compounds from grape pomace variety ‘Portogizac’. Chem. Biochem. Eng. Q. 29(3), 343–350 (2015)Google Scholar
  29. 29.
    Lante, A.L.: Characterization of esterase activity in the Bianchetta trevigiana grape variety under reducing conditions. Int. J. Wine Res. 2012(4), 45 (2012)Google Scholar
  30. 30.
    Pradel, E., Pieri, P.: Influence of a grass layer on vineyard soil temperature. Aust. J. Grape Wine Res. 6(1), 59–67 (2000)Google Scholar
  31. 31.
    Smit, J.L., Sithole, G., Strever, A.E.: Vine signal extraction – an application of remote sensing in precision viticulture. S. Afr. J. Enol. Vitic. 31(2), 65–74 (2016)Google Scholar
  32. 32.
    Morais, R., Fernandes, M.A., Matos, S.G., Serôdio, C., Ferreira, P.J.S.G., Reis, M.J.C.S.: A ZigBee multi-powered wireless acquisition device for remote sensing applications in precision viticulture. Comput. Electron. Agric. 62(2), 94–106 (2008)Google Scholar
  33. 33.
    Matese, A., Di Gennaro, S.F.: Technology in precision viticulture: a state of the art review. Int. J. Wine Res. 7, 69–81 (2015)Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.CETyS Universidad, Centro de Innovación y DiseñoEnsenadaMexico

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