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Plant resistance inducers (PRIs) are of increasing interest for disease control in sustainable viticulture, but their efficacy in vineyards is still under investigation. We studied the effects of four commercial PRIs, of natural and microbial origin, on the development of powdery mildew (PM) on grapevine leaves over a 3-year period. Disease and sporulation severity were evaluated following the artificial inoculation of PRI-treated leaves with Erysiphe necator conidia at 1, 3, 7 and 12 days after treatment (DAT). Laminarin (LAM) and cos-oga (COS) were the most effective in reducing both disease (57.1% and 49.5%, respectively) and sporulation (85.3% and 90.2%, respectively) severity; the reduction in PM severity provided by cerevisane (CER) was lower (27%), and that of Pythium oligandrum (PYT) was intermediate (44.9%). LAM was effective from 1 DAT, while COS and PYT were more effective when E. necator was inoculated at 7 to 12 DAT. These results open new perspectives on how PRIs are used as single, preventative interventions performed 1 to 3 days before E. necator infection, depending on the product used. The effect of PRIs on the sporulation of E. necator colonies also suggests a broader and longer effect on PM epidemics.PRIs can be used when PM infection risk is considered, and based on preventative treatments applied between 1 to 3 days before Erysiphe necator infection, depending on the product.image

Grape white rot can cause considerable yield losses in viticulture areas worldwide and is principally caused by Coniella diplodiella. The fungus overwinters in berry mummies on the soil surface or on the trellis and produces pycnidia and conidia that serve as primary inoculum. However, little is known about the temporal dynamics and dispersal pattern of C. diplodiella conidia. In this study, we investigated the production and dispersal of C. diplodiella conidia from a primary inoculum source, namely, affected mummified berries that overwintered in two vineyards in northern Italy in 2021 and 2022. Conidia of C. diplodiella were repeatedly produced in berry mummies from the budburst of vines to harvesting, with approximately 50 and 75% of the total conidia in a season being produced before fruit set and véraison, respectively. The production dynamics of C. diplodiella conidia over time were described by a Weibull equation in which the thermal time is the independent variable, with a concordance correlation coefficient of $0.964. A rainfall cutoff of $0.2 mm provided an overall accuracy of $0.86 in predicting conidial dispersal through rain splashes from berry mummies on the soil surface, with the number of dispersed conidia increasing with the amount of rainfall. The dispersal of conidia from mummies on the trellis by washing with rain required at least 6.1 mm of rain. The proposed mathematical equations and rain cutoffs can be used to predict periods with a high dispersal risk of C. diplodiella.

A plant disease model is a simplified representation of the relationships between pathogens, crops, and the environment that cause the development of epidemics over time and/or space. This chapter describes the different modelling approaches, focusing on fundamental (process-based) models for application in crop protection. The development of process-based dynamic models consists of four steps: (i) definition of the intended use of the model; (ii) conceptualization of the system; (iii) development of the mathematical framework; and (iv) model evalua- tion. Plant disease models now have a key role in supporting the decision-making process in integrated pest management (IPM). The advantages of using models in IPM are linked to their ability to process and analyze complex information and to provide outputs supporting decision-making at strategic and tactical levels. In particular, simulation models can support strategic decision-making, and predictive models can assist growers in making tactical decisions. Finally, the chapter briefly considers how different models can be combined with the aim of helping growers to make correct and objective decisions about crop protection.

Plant resistance inducers (PRIs) harbor promising potential for use in downy mildew (DM) control in viticulture. Here, the effects of six commercial PRIs on some epidemiological components of Plasmopara viticola (Pv) on grapevine leaves were studied over 3 years. Disease severity, mycelial colonization of leaf tissue, sporulation severity, production of sporangia on affected leaves, and per unit of DM lesion were evaluated by inoculating the leaves of PRI-treated plants at 1, 3, 6, 12, and 19 days after treatment (DAT). Laminarin, potassium phosphonate (PHO), and fosetyl-aluminium (FOS) were the most effective in reducing disease severity as well as the Pv DNA concentration of DM lesions on leaves treated and inoculated at 1 and 3 DAT; PHO and FOS also showed long-lasting effects on leaves established after treatment (inoculations at 6 to 19 DAT). PRIs also prevented the sporulation of Pv on lesions; all the PRI-treated leaves produced fewer sporangia than the nontreated control, especially in PHO-, FOS-, and cerevisane-treated leaves (>75% reduction). These results illustrate the broader and longer effect of PRIs on DM epidemics. The findings open up new perspectives for using PRIs in a defense program based on single, timely, and preventative field interventions.

This review gives a perspective of selected advances made since the middle of the 20th century in plant disease modelling, and the associated increase in the number of models published during that time frame. This progress can be mainly attributed to advances in (i) sensors and automatic environmental data collection technology, (ii) instrumentation and methods for studying botanical epidemiology, and (iii) data analytics and computer science. We review the evolution of techniques for developing data-based (empirical) models and process-based (mechanistic) models using the wheat rusts as a case study. We also describe the increased importance of knowledge about biological processes for plant disease modeling by using apple scab as a second case study. For both wheat rusts and apple scab, we describe how the models have evolved over the last 50 years by considering certain milestones that have been achieved in disease modeling. Finally, we describe how plant disease models are used as part of a multi-modelling approach to develop decision-making tools in the application of Integrated Pest Management (IPM).

Plant resistance inducers (PRIs) are potential alternatives for controlling grapevine downy (DM) and powdery (PM) mildews in vineyards. In a 3-year field study, we evaluated the field efficacy of six commercial PRIs of chemical and natural origin against DM and PM diseases when applied at designated vine growth stages in a mixture with low doses of copper and sulfur, and only when advised by weather-driven disease models. The disease severity and incidence were evaluated for each season at key growth stages (i.e., the end of flowering, berries pea-sized, veraison, and pre-harvest), and areas under the disease progress curves (AUDPC) were calculated and compared with those of nontreated vines. These risk-based applications resulted in a 41% and 61% reduction of interventions against DM and PM, respectively, compared to the official advice for integrated pest management in the growing area. These applications provided a disease control efficacy of 88% for DM and 93% for PM; the disease severity on bunches never exceeded 5%. Overall, when the disease severity was expressed as AUDPC, we observed higher efficacy of all the PRIs for PM, and of laminarin and cerevisane for DM. We also found that potassium phosphonate and fosetyl-Al (commonly used against DM) were effective against PM, and cos-oga (used against PM) was effective against DM. These results broaden the application and integration of PRIs in viticulture.

The growth of four commercial biocontrol agents (BCAs: Bacillus amyloliquefaciens (BAD), Aureobasidium pullulans (APD), Metschnikowia fructicola (MFN), and Trichoderma atroviride (TAS)) was evaluated using turbidimetric assays on artificial substrates mimicking the chemical berry composition at four stages: pea-sized berries, veraison, softening, and ripe berries. The response of BCA growth differed among BCAs. Subsequently, the BCAs’ population size was assessed after 1 to 13 days of incubation on the substrate mimicking ripe berries at 15 to 35 °C. The population size of BAD increased with temperatures, while that of MFN decreased; the population sizes of APD and TAS showed bell-shaped patterns with lower growth at 15 or 35 °C. Finally, the BCAs were applied to ripe berries and then incubated at 15 to 30 °C. After 1 to 13 days, the berries were inoculated with B. cinerea and incubated for 7 days, after which the BCA control efficacy was assessed. The highest control was observed at 25 °C for BAD and APD, at 15 to 20 °C for MFN, and at 25 to 30 °C for TAS. The results confirm that the plant substrates and temperature affect the population size of the BCA following application; temperature also affects the preventative efficacy of BCA against B. cinerea.

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.

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.

The use of biocontrol agents (BCAs) represents a promising alternative to conventional methods for the management of gray mold in vineyards during the berry ripening stage. The main advantages of BCAs are the short preharvest interval and lack of chemical fungicide residues in wine. In this study, eight commercial BCAs (based on different Bacillus or Trichoderma species and strains, Aureobasidium pullulans, Metschnikowia fructicola, and Pythium oligandrum) and a reference fungicide (boscalid) were applied to a vineyard during berry ripening over three seasons to evaluate the dynamics over time in terms of their relative efficacies in gray mold control. At 1-13 days after application of BCAs to the berry surfaces in field conditions, the berries were collected and artificially inoculated with conidia of Botrytis cinerea under controlled laboratory conditions, and gray mold severity was observed after 7 days of incubation. Significant differences were observed in gray mold severity among years, according to the number of days the BCAs grew on the berry surface before B. cinerea inoculation, and the season by day interaction (altogether accounting for >80% of the experimental variance). The variability in BCA efficacy was closely related to the environmental conditions at the time of application and in the following days. Overall, the BCA efficacy increased with the degree days accumulated between BCA application in the vineyard and B. cinerea inoculation in the dry (no rain) periods (r = 0.914, P = 0.001). Rainfall and the associated drop in temperature caused a relevant reduction of BCA efficacy. These results demonstrate that BCAs are an effective alternative to conventional chemicals for the preharvest control of gray mold in vineyards. However, environmental conditions can considerably affect the BCA efficacy.

Fungi in the genus Colletotrichum cause serious pre- and post-harvest losses to several agricultural crops worldwide. Through a systematic literature review, we retrieved the published information on Colletotrichum anthracnose diseases on different host plants and developed a mechanistic model incorporating the main stages of the pathogen's life cycle and the effect of weather. The model predicts anthracnose progress during the growing season on the aerial organs of different crops, and was parameterized for seven Colletotrichum clades (acutatum, dematium, destructivum, gloeosporioides, graminicola, and orbiculare) and the singleton species, C. coccodes. The model was evaluated for the anthracnose diseases caused by fungi belonging to five clades on six hosts by using data from 17 epidemics that occurred in Italy, the USA, Canada, and Japan. A comparison of observed versus predicted data showed a concordance correlation coefficient of 0.928 and an average distance between real data and the fitted line of 0.044. After further validation, the model could be used to support decision-making for crop protection.

The fungus Sclerotinia sclerotiorum causes serious losses to several agricultural crops worldwide. By using systems analysis, we retrieved the available knowledge concerning S. sclerotiorum from the literature and then analyzed and synthesized the data to develop a mechanistic, dynamic, weather-driven model for the prediction of epidemics on different crops. The model accounts for i) the production and survival of apothecia; ii) the production, dispersal, and survival of ascospores; iii) infection by ascospores; and iv) lesion onset. The ability of the model to predict the occurrence of apothecia was evaluated for epidemics observed with different climates, soil types, and host crops (soybean, white bean, and carrot) using independent data obtained from trials conducted in Ontario (Canada) in 1981, 1982, and from 1999 to 2002; in Michigan (U.S.A.) in 2015 and 2016; and in Wisconsin (U.S.A.) in 2016. The model showed 0.82 accuracy and 0.73 specificity in predicting the presence of apothecia, with a posterior probability of correctly predicting apothecia to be present or absent of 0.804 and 0.876, respectively. The model was also validated for its ability to predict disease progress on soybean and sunflower in Ontario in 1981 and 1982, in Manitoba (Canada) in 2001 and 2002, and in Michigan in 2015 and 2016. Comparison of model output with observations showed a concordance correlation coefficient of 0.948, and a root mean square error of 0.122. The model represents an improvement of previous S. sclerotiorum models and could be useful for making decisions on disease control.

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.