Title: Measurement and modelling of the water requirement of some greenhouse crops with artificial neural networks and genetic algorithm

Authors: Saeid Eslamian; Jahangir Abedi-Koupai; Mohammad Javad Zareian

Addresses: Department of Water Engineering, Collage of Agriculture, Isfahan University of Technology, Isfahan, 8415683111, Iran. ' Department of Water Engineering, Collage of Agriculture, Isfahan University of Technology, Isfahan, 8415683111, Iran. ' Department of Water Engineering, Collage of Agriculture, Isfahan University of Technology, Isfahan, 8415683111, Iran

Abstract: Crop evapotranspiration is the most important parameter for management of irrigation systems in greenhouses. This study was conducted to determine the evapotranspiration of cucumber, tomato and peppers, using micro-lysimeter during seven months in a greenhouse located in central region of Iran. Reference evapotranspiration estimated using drainage lysimeters and the water balance of soil micro-lysimeters was determined using the gravimetric method. To find the relationship between meteorological data and crops height with crops evapotranspiration, artificial neural networks (ANNs) and genetic algorithms-ANNs (GA-ANNs) were used. The results indicated that both models had a quite good agreement with the actual evapotranspiration of crops, but the GA-ANNs model will respond better than the ANNs model.

Keywords: greenhouses; crop evapotranspiration; cucumbers; tomatos; peppers; artificial neural networks; ANNs; genetic algorithms; GAs; micro-lysimeters; irrigation management; Iran; drainage lysimeters; water balance; greenhouse crops.

DOI: 10.1504/IJHST.2012.049185

International Journal of Hydrology Science and Technology, 2012 Vol.2 No.3, pp.237 - 251

Available online: 22 Sep 2012 *

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