Pingping Li

Integration of an environment information acquisition system with a greenhouse management expert system

Abstract A real‐time environment information acquisition system is essential if models and vegetable‐crop information are to be integrated with a greenhouse management expert system for good decision making. Our greenhouse management expert system has four functional modules: (1) cultivation techniques, (2) pest and disease diagnosis and prevention, (3) nutrient deficiency diagnosis and fertilisation, and (4) environment control. The hardware and software of the environment information acquisition system are incorporated into the expert system, which also offers a multi‐interface for sensors and is easily extended and maintained. Implementation was accomplished with the whole system to ensure its reliability and applicability for expert system, on‐line decision making. The results show that a dynamic integration of a greenhouse management system and an environment information acquisition system can supply sufficient information for good control strategies and for decision‐support.

Studies on Photosynthesis Model of Mini-Cucumber Leaf in Greenhouse

Photosynthesis (Pn) is the most important parameters in greenhouse climate control system based on model. Temperature and radiation are important climate factors affecting crop photosynthesis rate. The purpose of this study is to quantitatively investigate the effects of both temperature and photosynthetically active radiation (PAR) on the cucumber Photosynthesis rate. Experiments with different weather were conducted in greenhouse of Jingkou Institute of Vegetable. The results show that under the fine and cloudy weather, the curve of photosynthesis had two peaks, with an obvious midday depression at 11:00am–12:00am. But under the rainy weather, there is no depression. Based on experimental data, the relationship between photo-temperature and photosynthesis were established. The coefficient of determination (R 2) of the model is 0.953. And when temperature was 28.7°C, PAR was 1311μmolm-2s-1, the photosynthesis would reach to a maximum value of 20.13 CO2μmolm−2s−1. The model developed in this study can predict photosynthesis with different temperature and radiation. And it also can give the optimum parameters of greenhouse climate control.

Decision Support System for Greenhouse Environment Control Based on Model

Greenhouse environment control and manage mainly emphasize on the growth of crop, and seldom take into account the cost of control. In this research, the decision support system (DSS) of greenhouse environment control based on model is put forward. In this system, models included greenhouse crop growth model, greenhouse control effect model and control cost model. Then knowledge-base, model-base and database are established including the aspects of crop growth, environment control in greenhouse. Based on those, the software of greenhouse environment control decision support system (GHMDS) is developed. With consideration to both crop growth and economic profits, the system combined the advantages of “Model Based Reason (MBR)” and “Knowledge Based Reason (KBR)”. By this system, the optimized dynamic parameters of environment control under different weather conditions and crop growth stage can be given. And it also can forecast market period, growth stage. Connected with greenhouse controller, it can realize intelligent control. The simple man-machine interface of GHMDSS makes the user more convenience and more applicable in greenhouse crop and climate management practices.