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Hardware and Software System for Hydric Estimation and Crop Irrigation Scheduling

  • Karen Daza
  • Jorge Hernandez
  • Hector FlorezEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11623)

Abstract

In hydroponic crops located in underdeveloped countries, the hydric estimation is usually done manually and empirically; however, based on tropical climate, the ideal factors regarding temperature and humidity for each plant can be different. Thus, hydric estimation must be different depending on the plants because it depends on the plants species, type of soil, variety in the diameter of the roots, among others. Therefore, the hydric estimation must be done plant by plant in order to achieve a right development of every plant in a desired crop. In this paper, we present an approach based on software and hardware components integration, which is able to calculate the crops evapotranspiration and to make hydric estimation based on the ideal factors of each plant and the experimental data collected from each species in order to minimize the use of water in irrigation processes and to ensure the right development of plans.

Keywords

Hydric estimation Crop irrigation Hardware and software 

References

  1. 1.
    Adams, S., Cockshull, K., Cave, C.: Effect of temperature on the growth and development of tomato fruits. Ann. Bot. 88(5), 869–877 (2001)CrossRefGoogle Scholar
  2. 2.
    Allen, R., Pereira, L., Raes, D., Smith, M.: Guidelines for computing crop water requirements. Geophysics 156, 178 (1998)Google Scholar
  3. 3.
    Bradley, P., Marulanda, C.: Simplified hydroponics to reduce global hunger. In: World Congress on Soilless Culture: Agriculture in the Coming Millennium, vol. 554, pp. 289–296 (2000)Google Scholar
  4. 4.
    Camp, C.: Subsurface drip irrigation: a review. Trans. ASAE 41(5), 1353 (1998)CrossRefGoogle Scholar
  5. 5.
    Everhart, C.: The complete guide to growing tomatoes: a complete step-by-step guide including heirloom tomatoes (back-to-basics gardening) (2010)Google Scholar
  6. 6.
    Hoogenboom, G., et al.: Decision support system for agrotechnology transfer version 4.0. University of Hawaii, Honolulu, HI (2004). (CD-ROM)Google Scholar
  7. 7.
    Irmak, S., Haman, D.Z.: Evapotranspiration: potential or reference. IFAS Extension, ABE 343, 1–3 (2003)Google Scholar
  8. 8.
    Joe Stevens, B.K.: Trends and outlook: agricultural water management in Southern Africa country report South Africa, pp. 10–18. International Water Management Institute (2015)Google Scholar
  9. 9.
    Machado, R.M., Maria do Rosàrio, G.O.: Tomato root distribution, yield and fruit quality under different subsurface drip irrigation regimes and depths. Irrig. Sci. 24(1), 15–24 (2005)CrossRefGoogle Scholar
  10. 10.
    Ritchie, J.: Soil water balance and plant water stress. In: Tsuji, G.Y., Hoogenboom, G., Thornton, P.K. (eds.) Understanding Options for Agricultural Production, vol. 7, pp. 41–54. Springer, Dordrecht (1998).  https://doi.org/10.1007/978-94-017-3624-4_3CrossRefGoogle Scholar
  11. 11.
    Shah, N., Das, I.: Precision irrigation sensor network based irrigation. In: Problems, Perspectives and Challenges of Agricultural Water Management, pp. 217–232. InTech, Rijeka (2012)Google Scholar
  12. 12.
    Shamshirband, S., et al.: Estimation of reference evapotranspiration using neural networks and cuckoo search algorithm. Am. Soc. Civ. Eng. 142(2), 1–12 (2015)Google Scholar
  13. 13.
    Umair, S.M., Usman, R.: Automation of irrigation system using ANN based controller. Int. J. Electr. Comput. Sci. IJECS-IJENS 10(02), 41–47 (2010)Google Scholar
  14. 14.
    Zhang, S., Wang, M., Shi, W., Zheng, W.: Construction of intelligent water saving irrigation control system based on water balance. IFAC-PapersOnLine 51(17), 466–471 (2018)CrossRefGoogle Scholar
  15. 15.
    Zheng, Q., Zhu, F., Mao, C., Lv, X.: A smart irrigation decision support system based on cloud, pp. 1–10. Undergraduate, Hohai University, Nanjing, China (2014)Google Scholar
  16. 16.
    Zotarelli, L., Dukes, M.D., Romero, C.C., Migliaccio, K.W., Morgan, K.T.: Step by step calculation of the penman-monteith evapotranspiration (fao-56 method). Institute of Food and Agricultural Sciences, University of Florida (2010)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universidad Distrital Francisco Jose de CaldasBogotáColombia

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