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.
Interfacing crop models to standard software for greenhouse climate control
Abstract The use of models for the control of greenhouse climate and plant growth has been possible for several years through the introduction of the climate computer. However, only a few commercial facilities currently employ this promising technique. Scientific models are normally not developed for implementation on commercially available systems. To aid in overcoming this problem an open system architecture is proposed, which does not infringe upon copyrights or source code security for the manufacturer. By using a set of simple conventions, a model interface structure is described that enables scientists to develop and validate models in a commercial software environment. Models developed with this interface can be distributed to growers for calibration to their own actual greenhouses and crops. The interface was tested by integrating two linked models with a standard climate computer system. In addition a model shell to handle the task of time and data management necessary for running the models is described. The model shell decreases significantly the amount of programming necessary to produce and implement new models.
Spatial distribution of root lesion nematodes (Pratylenchus spp.) in a long-term no-till cropping system and their relationship with soil and landscape properties
The Cook Agronomy Farm of Washington State University is a long-term precision agriculture study site. Since 2000, the farm has been in various three-year no-till rotations with winter wheat, spring wheat, and various rotation crops such as barley, canola, peas, lentils, and chickpea. The spatial distribution of root lesion nematodes (Pratylenchus spp.) and their relationships with soil and terrain variables were studied by collecting soil samples at 127 and 124 geo-referenced points in two 12-ha fields during the spring of 2010 and 2011, respectively. Pratylenchus spp. were detected in more than 85% of the sampled locations in both fields. Nematode densities spatially mapped using ArcGIS software occurred in an aggregated pattern. Previous rotation crops had no effect on the spatial distribution. Classification and regression tree analysis (CART) using soil and terrain variables, and nematode density, explained 61 and 34% of the variability associated with nematode density in 2010 and 2011, respectively. Soil edaphic factors, such as organic matter, were stronger predictors of nematode populations than rotation effects.