Ginseng foliar diseases are typically controlled by spray application using periodic schedules. Few disease warning systems have been used for effective control of ginseng foliar diseases because ginseng is grown under shade nettings, which makes it difficult to obtain weather data for operation of the disease warning system. Using weather data measured outside the shade as inputs to an empirical leaf wetness duration (LWD) model, LWD was estimated to examine if operation of a disease warning system would be feasible for control of ginseng foliar diseases. An empirical model based on a fuzzy logic system (fuzzy model) was used to estimate LWD at two commercial ginseng fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012. Accuracy of LWD estimates was assessed in terms of mean error (ME) and mean absolute error (MAE). The fuzzy model tended to overestimate LWD during dew eligible days whereas it tended to underestimate LWD during rainfall eligible days. Still, daily disease risk ratings of the TOM-CAST disease warning system, which are derived from estimates of wetness duration and temperature, had a tendency to coincide with that derived from measurements of weather variables. As a result, spray advisory dates for the TOM-CAST disease warning system were predicted within ±3 days for about 78% of time windows during which the action threshold for spray application was reached. This result suggested that estimates of LWD using an empirical model would be helpful in control of a foliar disease in a ginseng field. It was also found that a spray application time model using meteorological observations may prove successful without the requirement of leaf wetness sensors within the field. Development of empirical correction schemes to the fuzzy model and a physical model for LWD estimation in a ginseng field could improve accuracy of LWD estimates and, as a result, spray advisory date prediction, which merits further studies.

Sclerotinia white rot disease was observed on 5 and 6-year-old ginseng (Panax ginseng) roots in Hongchun, Cheorwon, and Yanggu, Gangwon Province, Korea from 2006 to 2010. Symptoms included a brownish watery soft rot of the roots, and black sclerotia were often found on the rotten roots. The causal agent of the disease was identified as Sclerotinia nivalis based on cultural characteristics and sequence analyses of the internal transcribed spacer region of rDNA and β-tubulin gene with 100% sequence similarity. Pathogenicity tests were performed on 2-year-old ginseng roots with mycelium plugs without wounds. A watery soft rot of the roots and black sclerotia were observed 10 days after inoculation. These symptoms were identical to those observed on naturally infected roots. The same fungus was re-isolated from the lesions induced by artificial inoculation. This is the first report of sclerotinia white rot caused by S. nivalis on P. ginseng in Korea.

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BackgroundKnowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production.MethodsWeather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model.ResultsAir temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between 8°C and 27°C, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%.ConclusionWeather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.