Dalphy O C Harteveld, Michael R Grant, Jay W Pscheidt, Tobin L Peever

Mummy berry, caused by Monilinia vaccinii-corymbosi, causes economic losses of highbush blueberry in the US Pacific Northwest (PNW). Apothecia develop from mummified berries overwintering on soil surfaces and produce ascospores that infect tissue emerging from floral and vegetative buds. Disease control currently relies on fungicides applied on a calendar-basis rather than inoculum availability. To establish a prediction model for ascospore release, apothecial development was tracked in three fields, one in western OR and two in northwestern WA in 2015 and 2016. Air and soil temperature, precipitation, soil moisture, leaf wetness, relative humidity and solar radiation were monitored using in-field weather stations and WSU's AgWeatherNet stations. Four modeling approaches were compared: logistic regression, multivariate adaptive regression splines, artificial neural networks and random forest. A supervised learning approach was used to train the models on two data sets: training (70%) and testing (30%). The importance of environmental factors was calculated for each model separately. Soil temperature, soil moisture, and solar radiation were identified as the most important factors influencing ascospore release. Random forest models, with 78% accuracy, showed the best performance compared to the other models. Results of this research helps PNW blueberry growers to optimize fungicide use and reduce production costs.