A decision-support system for real-time management of Easter lily (Lilium longiflorum Thunb.) scheduling and height--I. System description
Abstract A decision-support system was developed for recommending night and day temperature settings to control the timing and height of Easter lily ( Lilium longiflorum Thunb.). Existing biological models and qualitative rules were combined into an overall model of the response of plant development rate to temperature. A process control algorithm was used to determine appropriate height control actions based on a graphical control chart of plant height over time. A knowledge-based system checked the feasibility of output from the development and height control models and generated a text report. This model was implemented on a personal computer in a program called “The Greenhouse CARE System” and has been linked directly with an environmental computer to control greenhouse temperatures. A companion article describes validation of this model.
Variability in flower development of Easter lily (Lilium longiflorum Thunb.): model and decision-support system.
Abstract A model to predict the distribution of harvest dates in an Easter lily crop was validated using data from several locations. Plants were individually harvested (i.e. removed from the greenhouse for shipping) when flowers on a plant reached a minimum flower bud length. A computer decision-support system called LilyDate was developed to allow the model to be used to optimize greenhouse temperature settings to ensure that the majority of a crop is ready to harvest by a target date. To implement LilyDate, the user measures the length of the largest flower bud per plant on a sample of plants in the greenhouse, and enters the frequency of plants at each flower bud length (to the nearest cm) into the program. Based on the expected temperature and sample growth data, the software predicts a cumulative and daily distribution of when plants will be in flower. Model predictions were not biased, and the model predicted the number of days until 50 or 95% of plants were in flower with a precision of ±2 and ±3 days, respectively. The general approach to the computer system could be adapted to predict the harvest distribution for other crop species that require a consistent quantity of thermal time to harvest, and that are grown for a target harvest date.
Transpiration of greenhouse crops : an aid to climate management
In this book some physical aspects of greenhouse climate are analyzed to show the direct interrelation between microclimate and crop transpiration. The energy balance of a greenhouse crop is shown to provide a sound physical framework to quantify the impact of microclimate on transpiration and to identify the constraints set on climate management by the termodynamic behaviour of the canopy. Before the relationship among microclimate, canopy temperature and transpiration is rendered in mathematical terms, a good deal of experimental work is necessary to establish sub-models for the heat transfer of the foliage, for the radiative transfer within the canopy and for the canopy resistance to vapour transfer. The sub-models are merged in a combination-type equation to obtain the temperature of a greenhouse crop and its transpiration. The resulting estimates are shown to reproduce accurately the temperature and transpiration of a greenhouse tomato crop, as measured at time intervals of a few minutes. To illustrate the practical application of the model thus developed a number of examples are presented. In particular, it is shown that defining the transpiration rate as the criterion for the control of air humidity within a greenhouse would deliver a quantitative framework for that control. That would largely enhance the efficiency of the (expensive) procedures applied at present for the control of humidity in greenhouses.