Applying effect of three forecasting methods for the occurrence trend of Alternaria alternata (Fries) Keissler

Rainfall (mm) of the second month after transplanting, average temperature (°C) at the same period and rainfall days of the first month after transplanting, Rainfall (mm) of June, the daily average temperature of June and rainfall days of June were selected using anomalous sign method from 39 factors from 9 continuous years data at Ningyuan county. Using data of spore trap for 11 continuous years at Chenzhou county. The occurrence trend of Alternaria alternata (Fries) Keissler was studied with the grade-statistics method. and correlation coefficient. Results showed that the back forecasting was in line with the actual value. The accurate percent of forecasting for Alternaria alternata (Fries) Keissle at Yongzhou for 10 years was 90%, the accurate percent of forecasting for Alternaria alternata (Fries) Keissle at different counties for 2009 was 75% with the forecasting model during the early growing stage of tabacco, the accurate percent of forecasting for Alternaria alternata (Fries) Keissle at Yongzhou for 10 years was 80% with the forecasting model during the late growing stage of tabacco; the accurate percent of forecasting for Alternaria alternata (Fries) Keissle at Yongzhou for 10 years was 90% with the both forecasting models and relied on the contributing percent; at different counties was 83.3% for 2009; the number of trapped spore at peak was used as x, the end disease index was used as y, the forecasting model is y=−0.5951+0.04x (r=0.8985∗∗ n=11), the span from spore peak to end were 2 d at least, 22 d at most, the average was 8.3 d, so the model can be used as the forecasting of the disease for short period. Both models of the early and the late growing stage can be used to forecast occurrence trend of Alternaria alternata (Fries) Keissler for short-to medium-term.