Data-based modeling of the spatiotemporal temperature distribution in a reach-in plant growth chamber

The spatiotemporal temperature distribution in the imperfectly mixed airspace around plants has a considerable effect on the physiological plant processes. In a fully instrumented climate chamber, eight identification experiments were carried out to model the spatiodynamic temperature response around plants to variations in the supply air temperature and the sensible heat, produced by the lamps (directly related to the light intensity), as control inputs. From the experimental data, a minimally parameterized, linear, discrete–time transfer function matrix (TFM) model was identified, capturing the dominant model behavior of the dynamic process. Based on statistical considerations, a first–order TFM model came out as the best model structure. The first–order model provided a good compromise between goodness of fit (minimum Rt2 i of 0.91) and parametric efficiency (standard error), characterized the airflow behavior very well, and formed an adequate basis for model–based process control.