Grapevine white rot, caused by Coniella diplodiella, can severely damage berries during ripening. The effects of temperature and wetness duration on the infection severity of C. diplodiella were investigated by artificially inoculating grape berries through via infection pathways (uninjured and injured berries, and through pedicels). The effect of temperature on incubation was also studied, as was that of inoculum dose. Injured berries were affected sooner than uninjured berries, even though 100% of the berries inoculated with C. diplodiella conidia became rotted whether injured or not; infection through pedicels was less severe. On injured berries, the disease increased as the inoculum dose increased. Irrespective of the infection pathway, 1 h of wetness was sufficient to cause infection at any temperature tested (10–35 °C); with the optimal temperature being 23.8 °C. The length of incubation was shorter for injured berries than for uninjured ones, and was shorter at 25–35 °C than at lower temperatures; the shortest incubation period was 14 h for injured berries at 30 °C. Mathematical equations were developed that fit the data, with R² = 0.93 for infection through any infection pathway, and R² = 0.98 for incubation on injured berries, which could be used to predict infection period and, therefore, to schedule fungicide applications.

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.

Grapevine anthracnose caused by Elsinoë ampelina is a serious threat in many vineyards, and its control requires repeated application of fungicides, usually on a calendar basis. A better understanding of the pathogen life cycle would help growers manage anthracnose more safely and effectively. After conducting a systematic literature search of grape anthracnose, we used the retrieved information and data to develop a mechanistic model based on systems analysis. The model simulates production and maturation of primary inoculum, infection caused by both primary and secondary conidia, and lesion formation and production of secondary inoculum. The model was validated for its ability to predict first seasonal onset of anthracnose lesions by using 8 years of data collected at Auckland, New Zealand, and disease progress during the season by using 3 years of data collected at Frelighsburg, Canada. Overall, the model provided accurate predictions of infection occurrence, with 0.96 accuracy, 0.91 sensitivity, and 0.97 specificity. The model also showed good accuracy for predicting disease progress, with a concordance correlation coefficient between observed and predicted disease severities of 0.92, a root mean square error of 0.14, and a coefficient of residual mass of 0.06. Although the model failed to predict 10 of 110 real infection periods, these missed infections led to only mild disease symptoms. We therefore conclude that the model is reliable and can be used to reduce the costs of anthracnose management by improving the timing of fungicide applications.

Grapevine trunk diseases are caused by a complex of fungi that belong to different taxa, which produce different spore types and have different spore dispersal mechanisms. It is commonly accepted that rainfall plays a key role in spore dispersal, but there is conflicting information in the literature on the relationship between rain and spore trapping in aerobiology studies. We conducted a systematic literature review, extracted quantitative data from published papers, and used the pooled data for Bayesian analysis of the effect of rain on spore trapping. We selected 17 papers covering 95 studies and 8,778 trapping periods, concerning a total of 26 fungal taxa causing Botryosphaeria dieback (BD), Esca complex (EC), and Eutypa dieback (ED). Results confirmed the role of rain in the spore dispersal of these fungi but revealed differences among the different fungi. Rain was a good predictor of spore trapping for ED (AUROC = 0.820) and BD (0.766) but not for the ascomycetes involved in EC (0.569) and not for the only basidiomycetes, Fomitiporella viticola, studied as for spore discharge (AUROC not significant). Prediction of spore trapping was more accurate for negative prognosis than for positive prognosis; a rain cutoff of ≥0.2 mm provided an overall accuracy of ≥0.61 for correct prognoses. Spores trapped in rainless periods accounted for only <10% of the total spores. Our analysis had some drawbacks, which were mainly caused by knowledge gaps and limited data availability; these drawbacks are discussed to facilitate further research.

Grapevine trunk diseases (GTDs) are serious threats in all viticultural areas of the world, and their management is always complex and usually inadequate. Fragmented and inconsistent information on the epidemiology and environmental requirements of the causal fungi is among the reasons for poor disease control. Therefore, we conducted a quantitative analysis of literature data to determine the effects of temperature on mycelial growth and the effects of temperature and moisture duration on spore germination. Using the collected information, we then developed mathematical equations describing the response of mycelial growth to temperature, and the response of spore germination to temperature and moisture for the different species and disease syndromes. We considered 27 articles (selected from a total of 207 articles found through a systematic literature search) and 116 cases; these involved 43 fungal species belonging to three disease syndromes. The mycelial growth of the fungi causing Botryosphaeria dieback (BD) and the esca complex (EC) responded similarly to temperature, and preferred higher temperatures than those causing Eutypa dieback (ED) (with optimal temperature of 25.3, 26.5, and 23.3°C, respectively). At any temperature, the minimal duration of the moist period required for 50% spore germination was shorter for BD (3.0 h) than for EC (17.2 h) or ED (15.5 h). Mathematical equations were developed accounting for temperature–moisture relationships of GTD fungi, which showed concordance correlation coefficients ≥0.888; such equations should be useful for reducing the risk of infection.

Grapevine trunk diseases (GTDs) are serious threats worldwide and are difficult to control, in part because the environmental requirements for epidemiological processes of the causal fungi are poorly understood. Therefore, we investigated the effects of temperature and moisture duration on spore germination of four fungi associated with two GTDs (esca complex and Eutypa dieback): Phaeomoniella chlamydospora, Phaeoacremonium minimum, Cadophora luteo-olivacea, and Eutypa lata. Conidia of Phaeomoniella chlamydospora, Phaeoacremonium minimum, and C. luteo-olivacea were similar: conidia of these fungi germinated profusely (>90%) between 20 and 30°C; Phaeomoniella chlamydospora and Phaeoacremonium minimum tended to germinate at higher temperatures (up to 40°C for P. minimum), and C. luteo-olivacea at lower temperatures (as low as 5°C). E. lata ascospores germinated between 10 and 30°C. The required duration of moist periods for germination was shortest for C. luteo-olivacea (about 6 h), followed by P. minimum and E. lata (about 12 h) and Phaeomoniella chlamydospora (about 24 h). Further research on the environmental requirements of GTD fungi may increase our ability to predict infection periods and, thereby, improve disease control.