The fungal genus Colletotrichum includes plant pathogens that cause substantial economic damage to horticultural, ornamental, and fruit tree crops worldwide. Here, we conducted a systematic literature review to retrieve and analyze the metadata on the influence of temperature on four biological processes: (i) mycelial growth, (ii) conidial germination, (iii) infection by conidia, and (iv) sporulation. The literature review considered 118 papers (selected from a total of 1,641 papers found with the literature search), 19 Colletotrichum species belonging to eight clades (acutatum, graminicola, destructivum, coccodes, dematium, gloeosporioides, and orbiculare), and 27 host plants (alfalfa, almond, apple, azalea, banana, barley, bathurst burr, blueberry, celery, chilli, coffee, corn, cotton, cowpea, grape, guava, jointvetch, lentil, lupin, olive, onion, snap bean, spinach, strawberry, tomato, watermelon, and white bean). We used the metadata to develop temperature-dependent equations representing the effect of temperature on the biological processes for the different clades and species. Inter- and intra-clades similarities and differences are analyzed and discussed. A multi-factor cluster analysis identified four groups of clades with similar temperature dependencies. The results should facilitate further research on the biology and epidemiology of Colletotrichum species and should also contribute to the development of models for the management of anthracnose diseases.

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.

IntroductionPruning wounds are the main entry points for fungi causing grapevine trunk diseases (GTDs). Several studies identified factors influencing the temporal dynamics of wound susceptibility, which include the fungal species and inoculum dose, weather conditions, grape variety, pruning date, and so forth. Here, we conducted a quantitative analysis of literature data to synthesise outcomes across studies and to identify the factors that most affect the length of pruning wound susceptibility.MethodsWe extracted data on the frequency at which the inoculated wounds showed GTD symptoms or an inoculated pathogen was reisolated following artificial inoculation at the time of pruning or in the following days. A negative exponential model was fit to these data to describe changes in wound susceptibility as a function of time since pruning, in which the rate parameter changed depending on specific factors.Results and DiscussionThe results show that wound susceptibility is high at the time of pruning, and they remain susceptible to invasion by GTD fungi for months after pruning. Infection incidence on wounds was higher for fungi associated with Botryosphaeria dieback than those associated with Eutypa dieback or Esca complex, and wound susceptibility decreased faster for Eutypa dieback than for other GTD agents. Grapevine variety and pruning season also affected the wound susceptibility period. Sauvignon Blanc remains susceptible to GTDs longer than other varieties. We also found that the time of pruning can affect infection dynamics, especially for more susceptible varieties. The results increase our understanding of GTD epidemiology and should help growers control infections.

Resistance to downy mildew (DM) and powdery mildew (PM) contributes to sustainable vineyard management by reducing the diseases and the need for fungicide applications. Resistant varieties vary in their degree of resistance to DM and PM, and in their susceptibility to other diseases. As a consequence, fungicide use may differ among varieties depending on their “resistance patterns” (i.e., the resistance level of a variety toward all of the diseases in the vineyard). The resistance patterns of 16 grapevine varieties to DM, PM, black rot (BR), and gray mold (GM) were evaluated over a 4-year period under field conditions. Disease severity was assessed on leaves and bunches, and the AUDPC (Area Under Disease Progress Curve) was calculated to represent the epidemic progress. GM was found only on bunches and only at very low levels, irrespective of the year or variety, and was therefore excluded from further analyses. The varieties were then grouped into four resistance patterns: i) low resistance to DM and PM, intermediate resistance to BR; ii) high resistance to DM, intermediate resistance to PM, low resistance to BR; iii) intermediate resistance to DM and BR, low resistance to PM; and iv) high resistance to DM, PM, and BR. AUDPC values on leaves were positively correlated with AUDPC values on bunches for susceptible varieties but not for resistant ones, with the exception of PM. Therefore, bioassays with leaves can be used to predict the resistance of bunches to DM and BR for susceptible varieties but not for resistant ones. These results may facilitate both strategic and tactical decisions for the sustainable management of grapevine diseases.

Stem rust (or black rust) of wheat, caused by Puccinia graminis f. sp. tritici (Pgt), is a re-emerging, major threat to wheat production worldwide. Here, we retrieved, analyzed, and synthetized the available information about Pgt to develop a mechanistic, weather-driven model for predicting stem rust epidemics caused by uredospores. The ability of the model to predict the first infections in a season was evaluated using field data collected in three wheat-growing areas of Italy (Emilia-Romagna, Apulia, and Sardinia) from 2016 to 2021. The model showed good accuracy, with a posterior probability to correctly predict infections of 0.78 and a probability that there was no infection when not predicted of 0.96. The model’s ability to predict disease progress during the growing season was also evaluated by using published data obtained from trials in Minnesota, United States, in 1968, 1978, and 1979, and in Pennsylvania, United States, in 1986. Comparison of observed versus predicted data generated a concordance correlation coefficient of 0.96 and an average distance between real data and the fitted line of 0.09. The model could therefore be considered accurate and reliable for predicting epidemics of wheat stem rust and could be tested for its ability to support risk-based control of the disease.