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A risk management system for meteorological disasters of solar greenhouse vegetables
- Li, Ming, Chen, Sining, Liu, Fang, Zhao, Li, Xue, Qingyu, Wang, Hui, Chen, Meixiang, Lei, Peng, Wen, Dongmei, Sanchez-Molina, Jorge Antonio, Bienvenido, Jose Fernando, Li, Zhenfa, Yang, Xinting
- Precision agriculture 2017 v.18 no.6 pp. 997-1010
- Internet, data collection, decision making, disasters, downy mildew, farmers, greenhouses, mildews, models, powdery mildew, precision agriculture, risk management, solar radiation, temperature, vegetables, winter, China
- Solar greenhouses are well-established and very popular in the north of China as a way of meeting the demand for fresh local winter vegetables. Nonetheless, they are more susceptible to meteorological disasters, such as fog, haze and cold temperatures. A meteorological risk management system that includes disaster forecasting and control is a useful tool to efficiently capture long-term and up-to-the-minute environmental fluctuations inside greenhouses. Based on the concept of the meteorological disaster warning model, this study has developed a meteorological risk management system built upon a browser/server framework and mobile internet to provide precision agriculture (PA) services with large-scale, long-term, scalable and real-time data collection capabilities for solar greenhouse vegetables. Early warning indicators were established for the main meteorological hazards to winter-spring vegetables in solar greenhouses, including low temperature and sparse sunlight, downy mildew, grey mildew and powdery mildew induced by unfavorable meteorological conditions. The system could provide a valuable framework for farmers and agrometeorological officials in analyzing the relationships between vegetable damage dynamics and meteorological events. Having been applied in Beijing and Tianjin, the system has correctly forecast meteorological disaster and diseases caused by long-term fog and haze from November 2015. Based on the analysis carried out, improved meteorological risk management and a more accurate decision-making strategy can be developed to assist PA in combating meteorological disaster.