TY - JOUR
T1 - Modeling the effects of the environment and the host plant on the ripe rot of grapes, caused by the Colletotrichum species
AU - Ji, Tao
AU - Salotti, Irene
AU - Dong, C.
AU - Li, M.
AU - Rossi, V.
PY - 2021
Y1 - 2021
N2 - Ripe rot caused by Colletotrichum spp. is a serious threat in many vineyards, and its control relies mainly on the repeated use of fungicides. A mechanistic, dynamic model for the prediction of grape ripe rot epidemics was developed by using information and data from a systematic literature review. The model accounts for i) the production and maturation of the primary inoculum; ii) the infection caused by the primary inoculum; iii) the production of a secondary inoculum; and iv) the infection caused by the secondary inoculum. The model was validated in 19 epidemics (vineyard × year combinations) between 1980 and 2014 in China, Japan, and the USA. The observed disease incidence was correlated with the number of infection events predicted by the model and their severity (ρ = 0.878 and 0.533, respectively, n=37, P≤ 0.001). The model also accurately predicted the disease severity progress during the season, with a concordance correlation coefficient of 0.975 between the observed and predicted data. Overall, the model provided an accurate description of the grape ripe rot system, as well as reliable predictions of infection events and of disease progress during the season. The model increases our understanding of ripe rot epidemics in vineyards and will help guide disease control. By using the model, growers can schedule fungicides based on the risk of infection rather than on a seasonal spray calendar.
AB - Ripe rot caused by Colletotrichum spp. is a serious threat in many vineyards, and its control relies mainly on the repeated use of fungicides. A mechanistic, dynamic model for the prediction of grape ripe rot epidemics was developed by using information and data from a systematic literature review. The model accounts for i) the production and maturation of the primary inoculum; ii) the infection caused by the primary inoculum; iii) the production of a secondary inoculum; and iv) the infection caused by the secondary inoculum. The model was validated in 19 epidemics (vineyard × year combinations) between 1980 and 2014 in China, Japan, and the USA. The observed disease incidence was correlated with the number of infection events predicted by the model and their severity (ρ = 0.878 and 0.533, respectively, n=37, P≤ 0.001). The model also accurately predicted the disease severity progress during the season, with a concordance correlation coefficient of 0.975 between the observed and predicted data. Overall, the model provided an accurate description of the grape ripe rot system, as well as reliable predictions of infection events and of disease progress during the season. The model increases our understanding of ripe rot epidemics in vineyards and will help guide disease control. By using the model, growers can schedule fungicides based on the risk of infection rather than on a seasonal spray calendar.
KW - Disease modeling
KW - Epidemiology
KW - Life cycle
KW - Model validation
KW - Disease modeling
KW - Epidemiology
KW - Life cycle
KW - Model validation
UR - https://publicatt.unicatt.it/handle/10807/188385
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85117610833&origin=inward
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85117610833&origin=inward
U2 - 10.3390/plants10112288
DO - 10.3390/plants10112288
M3 - Article
SN - 2223-7747
VL - 10
SP - 2288-N/A
JO - Plants
JF - Plants
IS - 11
ER -