Black rot is a fungal disease of grapevine that, in the last few years, has had a recrudescence in some areas. The knowledge on the life cycle of Guignardia bidwellii was retrieved through a systematic literature review and used to draw a mechanistic model able to simulate the fungus life cycle as influenced by weather and grapevine phenology. A meta-analysis was carried out on literature data to develop the mathematical equations describing the system both quantitatively and dynamically. Due to the lack of sufficient information, assumptions were introduced derived from similar systems. The model was then evaluated for its ability to describe the black rot epidemics in three representative cases. The model accurately represented the real system and has proven to be a useful tool for understanding the dynamics of epidemics. Further research will be necessary to acquire additional knowledge on some biological processes, to further validate the model and verify its use as a predictive tool for the disease
Onesti, G., Caffi, T., Legler, S. E., Rossi, V., Un nuovo modello per il black rot della vite, in Atti Giornate Fitopatologiche, (Chianciano Terme, 18-21 March 2014), Clueb, Bologna 2014: 501-508 [http://hdl.handle.net/10807/70729]
Un nuovo modello per il black rot della vite
Onesti, Giovanni;Caffi, Tito;Legler, Sara Elisabetta;Rossi, Vittorio
2014
Abstract
Black rot is a fungal disease of grapevine that, in the last few years, has had a recrudescence in some areas. The knowledge on the life cycle of Guignardia bidwellii was retrieved through a systematic literature review and used to draw a mechanistic model able to simulate the fungus life cycle as influenced by weather and grapevine phenology. A meta-analysis was carried out on literature data to develop the mathematical equations describing the system both quantitatively and dynamically. Due to the lack of sufficient information, assumptions were introduced derived from similar systems. The model was then evaluated for its ability to describe the black rot epidemics in three representative cases. The model accurately represented the real system and has proven to be a useful tool for understanding the dynamics of epidemics. Further research will be necessary to acquire additional knowledge on some biological processes, to further validate the model and verify its use as a predictive tool for the diseaseI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.