A Mechanistic Model of Botrytis cinerea on Grapevines That Includes Weather, Vine Growth Stage, and the Main Infection Pathways

Abstract

A mechanistic model for Botrytis cinerea on grapevine was developed. The model, which accounts for conidia production on various inoculum sources and for multiple infection pathways, considers two infection periods. During the first period (“inflorescences clearly visible” to “berries groat-sized”), the model calculates: i) infection severity on inflorescences and young clusters caused by conidia (SEV1). During the second period (“majority of berries touching” to “berries ripe for harvest”), the model calculates: ii) infection severity of ripening berries by conidia (SEV2); and iii) severity of berry-to-berry infection caused by mycelium (SEV3). The model was validated in 21 epidemics (vineyard × year combinations) between 2009 and 2014 in Italy and France. A discriminant function analysis (DFA) was used to: i) evaluate the ability of the model to predict mild, intermediate, and severe epidemics; and ii) assess how SEV1, SEV2, and SEV3 contribute to epidemics. The model correctly classified the severity of 17 of 21 epidemics. Results from DFA were also used to calculate the daily probabilities that an ongoing epidemic would be mild, intermediate, or severe. SEV1 was the most influential variable in discriminating between mild and intermediate epidemics, whereas SEV2 and SEV3 were relevant for discriminating between intermediate and severe epidemics. The model represents an improvement of previous B. cinerea models in viticulture and could be useful for making decisions about Botrytis bunch rot control.

Meteorological Conditions: Influence on Yield, Sanitary Status and Grape Composition

“…In both periods, rainfall and relative humidity were strongly correlated with bunch rot incidence, in accordance with Fermaud et al [9] and González-Domínguez et al [29].…”

“…Maximum temperature of January was negatively related with bunch rot incidence since it surpassed the threshold for being favorable to fungus development [9,29]. However, the minimum temperatures of the same month and those of the maturation period were positively correlated with bunch rot incidence and they were between the intervals reported as favorable by the same authors (Table 3).…”

Climate warming effects on grape and grapevine moth (Lobesia botrana) in thePalearcticregion

“…A mechanistic model for B. cinerea on grapevine was recently reported by González-Domínguez et al (2015) that accounts for conidia production on various inoculum sources and for multiple infection pathways. Using discriminant function analysis, the ability of the model to predict mild, intermediate and severe epidemics of B. cinerea was evaluated.…”

“…Using discriminant function analysis, the ability of the model to predict mild, intermediate and severe epidemics of B. cinerea was evaluated. The effects of Botrytis are not included in the model, although the model of González-Domínguez et al (2015) can be added to our grapevine system model. Important bottom-up plant effects on L. botrana include the phenology and abundance of fruit stages and their effects on larval-pupal developmental rates and on adult fecundity and longevity (see below).…”

Gray mold caused by Botrytis cinerea limits grape production in Chile

“…Forecasting systems allow the reduction of unnecessary fungicide applications, restricting them to periods that are conducive to disease development. Models to predict conditions for B. cinerea infection in grapes, which are based on environmental conditions (Broome et al, 1995;González-Domínguez et. al., 2015;Kim et al, 2007;Nair and Allen, 1993;Shtienberg, 2004;Shtienberg and Elad, 1997) and inoculum concentration and their dynamics (Carisse et al, 2014;Fernández-González et al, 2012), have been developed and proposed to predict the risk of GM infection.…”