Abstract: Research on meteorological grade prediction for rice false smut is critical to the prevention of rice disease. Based on the meteorological data from 71 basic weather stations and 2259 regional automatic stations in Zhejiang Province, Optimized Consensus Forecast fine grid numerical prediction products, as well as field investigation of rice false smut, the diseasepromoting meteorological index model and dynamic forecast method for rice false smut grade were established by GIS and weighted index sum method. Results showed that the disease-promoting meteorological index model performed well, with a validation accuracy rate of 87.5%. The meteorological grade of rice false smut could be predicted eight days in advance, with resolution at township. The forecast result of 21 August, 2018 was consistent with the actual situation, with a test accuracy rate of 90.9% in 11 cities across the province. Our results provide scientific meteorological technique support for fine and quantitative monitoring and forecasting services of crop disease.

Key words: middleaged Pinus tabuliformis plantation, canopy density, tree form quality, AHP, the Loess Plateau.