The implementation of innovative and efficient irrigation techniques is among the greatest challenges facing agriculture. In this regard, a linear programming model is presented in order to optimize water use. The idea behind this model is to assess the effectiveness or ineffectiveness of precipitation to determine the amount of irrigation water required to optimize water use. To achieve this idea, the "knapsack" problem decisional form was used, and the combination of the linear programming and the above-mentioned form proved satisfactory. Field experiments were conducted in Algeria. Based on calculated budgets a model using linear programming was developed. A comparison between the model results and the field findings suggests that the model could reduce water consumption by 28.5%.
Abstract.While thermal structures such as greenhouses are complex to model under transient conditions because of coupled heat and mass (H 2 O and CO 2 ) exchanges between their different parts, systems theory allows a simple analysis of the input/output behaviour of the model. In particular, parameters of the reduced dynamic models can be derived from in-situ measurements on these systems. This paper describes an application of the systems approach to a greenhouse climate model which incorporates CO 2 balance, crop transpiration and photosynthesis and the effects of heating, CO 2 enrichment, natural ventilation and evaporative cooling. In a first stage, system parameters such as the equivalent thermal mass, the wind dependent coefficient of natural ventilation and the various heat exchange coefficients were identified in situ from sequences of input-output data concerning the heat and water vapour balance, recorded over the crop production period from December to July. Good agreement between measured and computed values of air temperature, air humidity was observed. In a second stage, we have considered simultaneously the sensible heat, water vapour and CO 2 exchanges and tested the model against experimental data measured using a commercial greenhouse climate control computer. The identified values of the physical and physiological parameters are close the theoretical values and the accuracy of temperature, humidity and CO 2 content is rather good.
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