Prediction the Spatial Air Temperature Distribution of an Experimental Greenhouse Using Geostatistical Methods

Concerning the greenhouse environment, the ultimate goal of an investigation would be to determine the climatic parameters for all locations in the study area. Objective of the present study is to analyse the distribution of air temperature and air velocity of an experimental greenhouse with tomato crop, equipped with fan and pad evaporative cooling system, using geostatistical methods. The main aspects of geostatistics in terms 4 theoretical background for understanding spatial correlation models and kriging applications are presented. The most common variogram models were fitted to the experimental data sets obtained during summer period from an experimental greenhouse equipped with fan and pad evaporative cooling system. The Kriging approach was applied using the semivariograms corresponded to these data sets. Finally, the prediction maps of air temperature and air velocity were produced in different height levels inside the tomato crop canopy showing a great variability. Geostatistic analysis may be applied to determine not just optimal spatial predictions but also probabilities associated with risk-based analysis in order to improve the suitability and efficiency of climatic controls systems in greenhouses.