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Sensors 2012, 12(11), 15244-15266;

Virtual Sensors for Designing Irrigation Controllers in Greenhouses

Ingeniería de Sistemas y Automática, Departamento de Lenguajes y Computación, The Agrifood Campus of International Excellence (ceiA3), Universidad de Almería, Ctra de la Playa s/n.,Almería 04120, Spain
Departamento de Ingeniería de Sistemas y Automática, Escuela Superior de Ingenieros, Universidadde Sevilla, Camino de los Descubrimientos s/n, Sevilla 41092, Spain
Author to whom correspondence should be addressed.
Received: 3 August 2012 / Revised: 19 October 2012 / Accepted: 22 October 2012 / Published: 8 November 2012
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [650 KB, uploaded 21 June 2014]


Monitoring the greenhouse transpiration for control purposes is currently a difficult task. The absence of affordable sensors that provide continuous transpiration measurements motivates the use of estimators. In the case of tomato crops, the availability of estimators allows the design of automatic fertirrigation (irrigation + fertilization) schemes in greenhouses, minimizing the dispensed water while fulfilling crop needs. This paper shows how system identification techniques can be applied to obtain nonlinear virtual sensors for estimating transpiration. The greenhouse used for this study is equipped with a microlysimeter, which allows one to continuously sample the transpiration values. While the microlysimeter is an advantageous piece of equipment for research, it is also expensive and requires maintenance. This paper presents the design and development of a virtual sensor to model the crop transpiration, hence avoiding the use of this kind of expensive sensor. The resulting virtual sensor is obtained by dynamical system identification techniques based on regressors taken from variables typically found in a greenhouse, such as global radiation and vapor pressure deficit. The virtual sensor is thus based on empirical data. In this paper, some effort has been made to eliminate some problems associated with grey-box models: advance phenomenon and overestimation. The results are tested with real data and compared with other approaches. Better results are obtained with the use of nonlinear Black-box virtual sensors. This sensor is based on global radiation and vapor pressure deficit (VPD) measurements. Predictive results for the three models are developed for comparative purposes. View Full-Text
Keywords: virtual sensor; transpiration; nonlinear model; micro-lysimeter virtual sensor; transpiration; nonlinear model; micro-lysimeter
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Sánchez, J.A.; Rodríguez, F.; Guzmán, J.L.; Arahal, M.R. Virtual Sensors for Designing Irrigation Controllers in Greenhouses. Sensors 2012, 12, 15244-15266.

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