Testing and modelling the effects of climate on the incidence of the emergent nut rot agent of chestnut Gnomoniopsis castanea

摘要: Gnomoniopsis castanea is an emerging fungal pathogen causing nut rot of sweet chestnut, Castanea sativa. This study was aimed at testing and modelling the effects climate on disease incidence. Up to 120 ripe nuts were collected in 2011 from trees each 12 sites located northwest Italy. The incidence G. site expressed as number infected out total sampled (%), determined by combining results morphological identification isolates obtained nuts, their typing through a newly developed taxon-specific molecular assay. Disease ranged 20 93%, depending site. Geostatistical analyses revealed that, despite clustering (P   0·05). finding suggests that influenced site-dependent factors whose scale (c. 7·5–15·6 km) consistent with variability throughout sampling region. Multivariate maximum, mean minimum temperatures rainfall showed warmer associated higher levels months before harvesting selected predictors for partial least squares regression (PLSR) models (GnoMods) External validation data either or years not used model fitting good predictive abilities GnoMods (Spearman's ρobs/pred > 0·72, P < 0·05). above findings support relationship between castanea, providing statistical tools forecast level.