Tito Caffi

Dynamics of ascospore maturation and discharge in Erysiphe necator, the causal agent of grape powdery mildew.

Dynamics of ascocarp development, ascospore maturation, and dispersal in Erysiphe necator were studied over a 4-year period, from the time of ascocarp formation to the end of the ascosporic season at the end of June in the following spring. Naturally dispersed chasmothecia were collected from mid-August to late November (when leaf fall was complete); the different collections were used to form three to five cohorts of chasmothecia per year, with each cohort containing ascocarps formed in different periods. Chasmothecia were exposed to natural conditions in a vineyard and periodically sampled. Ascocarps were categorized as containing mature or immature ascospores, or as empty; mature ascospores inside chasmothecia were enumerated starting from late February. Ascospore discharge was determined using silicone-coated slides that were placed 3 to 4 cm from sections of the vine trunk holding the chasmothecia. Before complete leaf fall, 34% of the chasmothecia had mature ascospores, 48% had immature ascospores, and 18% were empty; in the same period, the trapped ascospores represented 56% of the total ascospores trapped in an ascosporic season (i.e., from late summer until the next spring or early summer). The number of viable chasmothecia diminished over time; 11 and 5% of chasmothecia had mature ascospores between complete leaf fall and bud break and after bud break, respectively. These ascocarps discharged ≈2 and 42% of the total ascospores, respectively. All the ascocarp cohorts released ascospores in autumn, survived the winter, and discharged viable ascospores in spring; neither ascospore numbers nor their pattern of temporal release was influenced by the time when chasmothecia were collected and exposed in the vineyard. Abundance of mature ascospores in chasmothecia was expressed as a function of degree-days (DD) (base 10°C) accumulated before and after bud break through a Gompertz equation (R² = 0.92). Based on this equation, 90% of the ascospores were mature when 153 DD (confidence interval, 100 to 210 DD) had accumulated after bud break. Most ascospores were trapped in periods with >2 mm of rain; however, a few ascospores were airborne with <2 mm of rain and, occasionally, in wet periods of ≥3.5 h not initiated by rain.

Modelling Plant Diseases for Decision Making in Crop Protection

A plant disease model is a simplification of the relationships (between a patho-gen, a host plant, and the environment) that determine whether and how an epi-demic develops over time and space. This chapter describes an approach for de-veloping mechanistic, weather-driven, dynamic models which are suitable to be applied in precision crop protection. Model building consists of four steps: (I) defi-nition of the model purpose; (II) conceptualization; (III) development of the mathe-matical relationships; and (IV) model evaluation. Conceptualization is based on systems analysis; it assumes that the state of the pathosystem can be quantitatively determined and that changes in the system can be described by mathematical equations. A conceptual model describes the system (both conceptually and mathematically), and a set of driving models accounts for changes caused by the external variables. Two main types of conceptual models are described: plant- and pathogen-focused models. Model evaluation is the judgement of the overall adequacy of the model, which includes: verification, validation, uncertainty analysis, sensitivity analysis, and judgement of utility. Finally, the chapter briefly considers how models can be used as tools for decision making at different scales of time and space: from warning services to precision agriculture.

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

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.

The Role of Rain in Dispersal of the Primary Inoculum of Plasmopara viticola

Although primary infection of grapevines by Plasmopara viticola requires splash dispersal of inoculum from soil to leaves, little is known about the role of rain in primary inoculum dispersal. Distribution of rain splashes from soil to grapevine canopy was evaluated over 20 rain periods (0.2 to 64.2 mm of rain) with splash samplers placed within the canopy. Samplers at 40, 80, and 140 cm above the soil caught 4.4, 0.03, and 0.003 drops/cm(2) of sampler area, respectively. Drops caught at 40 and 80 cm (1.5 cm in diameter) were larger than drops at 140 cm (1.3 cm). Leaf coverage by splashed drops, total drop number, and drop size increased with an increase in the maximum intensity of rain (mm/h) during any rain period. Any rainfall led to infection in potted grapevines placed outside on leaf litter containing oospores, if the litter contained germinated oospores at the time of rain; infection severity was unrelated to rain amount or intensity. Results from vineyards also indicate that any rain can carry P. viticola inoculum from soil to leaves and should be considered a splash event in disease prediction systems. Sampling for early disease detection should focus on the lower canopy, where the probability of splash impact is greatest.

Production and release of asexual sporangia in Plasmopara viticola

To study the influence of environmental conditions on sporulation of Plasmopara viticola lesions under vineyards conditions, unsprayed vines were inspected every second or third day and the numbers of sporulating and nonsporulating lesions were counted in two North Italy vineyards in 2008 to 2010. Infected leaves were removed so that only fresh lesions were assessed at each field assessment. Sporulation was studied at two scales, across field assessments and across the seasonal population of lesions. Frequencies of sporulating lesions were positively correlated with the numbers of moist hours in the preceding dark period (i.e., the number of hours between 8:00 p.m. and 7:00 a.m. with relative humidity ≥80%, rainfall >0 mm, or wetness duration >30 min). In a receiver operating characteristic analysis, predicted sporulation based on the occurrence of ≥3 moist hours at night provided overall accuracy of 0.85. To study the time course of sporulation on lesions which were not washed by rainfall, numbers of sporangia produced per square millimeter of lesion were estimated on individual cohorts of lesions over the whole infectious period. The numbers of sporangia per square millimeter of lesion increased rapidly during the first 4 days after the beginning of sporulation and then tapered off prior to a halt; the time course of cumulative sporangia production by a lesion followed a monomolecular growth model (R(2) = 0.97). The total number of sporangia produced by a square millimeter of lesion increased as the maximum temperature decreased and moist hours in the dark increased. To study the release pattern of the sporangia, spore samplers were placed near grapevines with sporulating lesions. Airborne sporangia were caught in 91.2% of the days over a wide range of weather conditions, including rainless periods. The results of this study provide quantitative information on production of P. viticola sporangia that may help refine epidemiological models used as decision aids in grape disease management programs.

Contribution of molecular studies to botanical epidemiology and disease modelling: grapevine downy mildew as a case-study

After being accidentally introduced from the USA at the end of the 19th century, downy mildew caused by Plasmopara viticola (Berk. et Curt.) Berlese et De Toni became one of the most damaging diseases affecting Vitis vinifera in Europe. Downy mildew causes both direct and indirect losses and can lead to severe reduction of yield. Our understanding of the life cycle and epidemiology of P. viticola has been recently altered by molecular studies that revealed that the overwintering inoculum (i.e., the oospores) does more than initiate disease, as was previously thought. A mechanistic model was developed for predicting the entire chain of processes leading to primary infections, and this primary infection model was linked to other models of secondary infection cycles. The model for primary infections defines the length of the primary inoculum season and a seasonal oospore dose consisting of several cohorts of oospores that progressively mature. The model was evaluated by means of Bayesian analysis in both Italy and eastern Canada, and showed high sensitivity, specificity, and accuracy both for potted plants and vineyards. Fungicide applications are necessary to control downy mildew because preventive agronomic practices are not very effective, including host resistance. The use of warning systems based on weather-driven models leads to a reduction in the use and cost of chemicals and a reduction in their environmental impact.

A Web-based Decision Support System for Managing Durum Wheat Crops

One important goal in agricultural crop production is to develop less intensive and integrated farming systems with lower inputs of fertilizers and pesticides, and with restricted use of the natural resources (water, soil, energy, etc.). The main objectives of these systems are to maintain crop production in both quantitative and qualitative terms, maintain or preferably improve farm income, and at the same time reduce negative environmental impacts as much as possible. Achieving all of these objectives is a prerequisite for sustainable agriculture (Geng et al., 1990; Jordan & Hutcheon, 1996). Integrated Production (IP) (Boller et al., 2004) and Integrated Farming (IF) (EISA, 2001) have been developed as holistic concepts that involve all crop and farming activities and that shape these activities according to the individual site and farm. The Thematic Strategy on the Sustainable Use of Pesticides adopted in 2006 by the European Commission aims to establish minimum rules for the use of pesticides in the Community so as to reduce risks to human health and the environment from the use of pesticides. A key component of this Strategy is implementation of Integrated Pest Management (IPM), which will become mandatory as of 2014. In the context of IPM, the EU will develop crop-specific standards, the implementation of which would be voluntary. According to ENDURE (2009), IPM creates synergies by integrating complementary methods drawing from a diverse array of approaches that include biocontrol agents, plant genetics, cultural and mechanical methods, biotechnologies, and information technologies, together with some pesticides that are still needed to control the most problematic pests and to manage critical situations. Concepts of IPM, IP, and IF are based on dynamic processes and require careful and detailed organisation and management of farm activities at both strategic and tactical levels. This means that time must be invested in management, business planning, data collection and detailed record keeping, and identification of required skills and provision for appropriate training to ensure safe farm operation. In IPM, IP, and IF, farm managers must also know where to obtain expert advice, and they must be willing to accept scientific and technical advances that benefit the environment, food quality, and economic performance, and that therefore can be integrated into the crop management as soon as they are reliable (EISA, 2001).

Use of systems analysis to develop plant disease models based on literature data: grape black-rot as a case-study

The available knowledge on black-rot of grape was retrieved from literature, analyzed, and synthesized to develop a mechanistic model of the life cycle of the pathogen (Guignardia bidwelii) based on the systems analysis. Three life-cycle compartments were defined: (i) production and maturation of inoculum in overwintered sources (i.e., ascospores from pseudothecia and conidia from pycnidia in berry mummies and cane lesions); (ii) infection caused by ascospores and conidia; and (iii) disease onset and production of secondary inoculum. An analysis of published, quantitative information was conducted to develop a mechanistic model driven by weather and vine phenology; equations were developed for ascospore and conidial maturation in overwintered fruiting bodies, spore release and survival, infection occurrence and severity, incubation and latency periods, onset of lesions, production of pycnidia, and infectious periods. The model was then evaluated for its ability to represent the real system and its usefulness for understanding black-rot epidemics by using three typical epidemics. Finally, weaknesses in our knowledge are discussed. Additional research is needed concerning the influence of wetness duration and temperature on infection by ascospores, production dynamics of pycnidia and conidia in black-rot lesions, and the dynamics of conidia exudation from pycnidia.

Evaluation of a Dynamic Model for Primary Infections Caused by Plasmopara viticola on Grapevine in Quebec

Downy mildew is major grape disease in several areas of the world. Recently, a dynamic model for primary infections of grapes by Plasmopara viticola, forecasting time of primary lesions emergence, was developed in Italy. The model simulates the development of predicted oospore cohorts during the primary infection period. The efficacy of this disease-cycle-based model was evaluated in eastern Canada by comparing the time of lesion emergence predicted by the model with field observations in 20 and 23 vineyards in 2008 and 2009, respectively. For each vineyard, one to 20 simulation runs were performed depending on the number of oospore cohorts expected to form, for a total of 545 simulations. The model evaluation was based on the true positive proportion (lesion emergence was predicted and observed) and the true negative proportion (lesion emergence was not predicted and not observed) which were 0.996, and 0.907, respectively. A total of 313 simulations resulted in no infection among which 284 corresponded to no lesion emergence. In only one situation, lesions were observed and not predicted by the model. On the contrary, in 29 simulations run, lesion emergence was predicted but not observed in the field. Further validation of this model is required, but the results of this study are encouraging and this model may be used to improve timing of fungicide sprays against P. viticola. Introduction In eastern Canada, as well as in several viticultural areas, downy mildew, caused by Plasmopara viticola (Berk et Curt.) Berlese et de Toni, represents one of the most important grapevine (Vitis vinifera L.) diseases. The warm and wet spring with abundant rainfall generally occurring in the spring favor disease development (13). The pathogen, native to North America, infects most species of Vitis with vinifera cultivars being highly susceptible and wild species relatively resistant. The pathogen attacks all aerial parts of the vines, causing indirect losses (leaf, shoot, and tendrils infections, Fig 1A) or direct losses (berry infections, Fig. 1B). In addition, the quality of wine produced from infected grapes is reduced (21). Grape downy mildew epidemics can progress rapidly and can cause economic losses up to 100%; hence, growers attempt to limit this threat by managing their fungicide program as though a disease risk is always present. However, increasing fungicide, fuel, and labor costs make routine use of fungicides costly. This strategy has several disadvantages, not only from an economic point of view but also with regard to the environmental impact of fungicides. In this context, the use of decision-support systems and of simulation models that predict “real risk” represents a valid alternative to calendar-based fungicide spray program. 26 January 2011 Plant Health Progress Like most polycyclic diseases, epidemics of grape downy mildew entail a sequence of events initiated by the production and dispersal of initial inoculum, followed by primary infections, production and dispersal of secondary inoculum, and completed by survival of P. viticola. Recent molecular studies showed the preponderant effect of primary infections on the epidemic (8,9,24). Gobbin et al. (8,9) analyzed more than 10,000 isolates of P. viticola from 39 vineyards using microsatellite markers and found numerous infections originating from primary inoculum from May to August. Furthermore, they reported that genotypes identified once throughout the sampling period always constituted the dominant class (71% of all genotypes) regardless of the sampling date. Only one or two genotypes per epidemic developed into secondary cycles and generated a high number of progenies. In other words, epidemics of grape downy mildew are strongly influenced by primary inoculum and hence controlling them is crucial for adequate management of the disease. The relationship of temperature and relative humidity to downy mildew development and P. viticola reproduction serve as the basis for most prediction systems. Grape downy mildew prediction models have been proposed for identifying the periods of high risk (i.e. conditions are favorable for disease development) and for scheduling fungicide applications (16,23). Some of these models are based on the simulation of primary infection development such as the POM (26), EPI (25), SIMPO (10), DMCAST (20), and UCSC (23) models. While other models predict the development of secondary infections through a simulation of one or more stages of P. viticola biological cycle (3,6,15,18,19). Despite the availability of warning systems for management of grape downy mildew, Quebec’s growers generally apply fungicides in a preventative manner starting soon after the green tip phenological stage or based on the 3-10 rule (2). This rule is based on the concurrent occurrence of: (i) air temperature equal to or greater than 10°C; (ii) vine shoots at least 10 cm long; (iii) a minimum of 10 mm of rainfall in the past 24 to 48 h. Considering the frequent spring to early summer occurrence of temperatures above 10°C and rainfall, this rule basically relies on the phonological criteria (vine shoots at least 10 cm long) and does not accounts for the development of the pathogen. The objective of this study was to evaluate under the conditions of eastern Canada, the potential of a new dynamic model for predicting P. viticola development during the initial phase of the disease development (23) for predicting the emergence of the primary lesions. Model Description The model was previously described in detail (23). Briefly, it is a dynamic model developed following a mechanistic approach according to principles of systems analysis (22). The model simulates, with a time step of one hour, the entire process of downy mildew primary infection: oospore maturation and 26 January 2011 Plant Health Progress germination, then zoospore ejection and dispersal, and finally infection establishment and disease symptom onset. This process was separated into different stages: the pathogen changes from one stage to another at different rates, depending on environmental conditions (Fig. 2). Pathogen stages are considered as state variables and their changes are regulated by rate variables; weather conditions influence rates acting as parameters or intermediate variables. Hourly temperature (T), relative humidity (RH), and rainfall (R) from 1 January were used as input data in the model. A simulation was initiated by each rainfall wetting the leaf litter and triggering the oospore germination process. In this model, it is assumed that oospores are present. At this time, the oospores which have broken dormancy form a cohort which develops in a similar way. An assumption of the model is that the germination process is temperature dependent when humidity of the leaf litter is not a limiting factor. The model simulates all the primary infection cycle of P. viticola (23). After germination, sporangia present on the leaf litter release zoospore in the presence of water; otherwise sporangia can survive for a few days and then die, depending on temperature and relative humidity. Zoospores are splashed by rain droplets and aerosols to grape leaves, but if the litter surface dries before rainfall zoospores do not survive. Infection establishment is caused by deposited zoospores when wetness duration and the corresponding temperature are favorable. If the leaf litter surface dries the zoospores dry out and die. The length of incubation period is influenced by temperature and relative humidity. At the end of the incubation period lesions develop at the infection sites. 26 January 2011 Plant Health Progress Field Observations The field observations used to evaluate the model were collected by government and private grape specialists and scouts in 20 and 23 vineyards in 2008 and 2009, respectively, located in the south of the province of Quebec, near the US border, and the north of the province (L’Ile d’Orleans) (Fig. 3). Vineyards were selected based on availability of scouting data and the presence of susceptible cultivars. The vineyards selected for this evaluation are 26 January 2011 Plant Health Progress representative of the different grapevine-growing areas, for soil type, varieties, training systems and cropping regimes. They also represent a range of dose of overwintering inoculum because of different fungicide spray programs, environmental conditions and geographical locations. Starting from bud burst, each vineyard was inspected at a 3 or 4 day-interval, to detect the emergence of the first lesions expressed as “oil spots” on leaves. At each assessment, all leaves on 50 to 100 vines, depending on vineyard size, were assessed for the presence of downy mildew lesions. Since the oil spots could have been appeared on each single day between the last negative and the first positive scouting, the actual symptoms onset was expressed as an “onset window” (Fig. 4). 26 January 2011 Plant Health Progress Hourly temperature (°C), relative humidity (%) and rainfall (mm) were obtained from the nearest (not more than 15 km) automatic weather station operated by Environment Canada available. The model was used to simulate, for each year and each vineyard, the progress of downy mildew for each predicted oospore cohort from 1 January to the emergence of the lesions (23). For a small number of vineyards located near to each other data from the same weather station were used. Methods for Model Evaluation For each vineyard, one to 20 simulations were performed depending on the number of oospore cohorts expected to be formed (presence of rain), for a total of 545 simulations. All simulations were divided into two groups based on observed lesion emergence; the cases and the controls were defined as the simulation with lesion emergence observed (O+) or not observed (O-), respectively. Within each group, simulations were further divided into two groups based on positive (P+) and negative (P-) prediction

Sporulation rate in culture and mycoparasitic activity, but not mycohost specificity, are the key factors for selecting Ampelomyces strains for biocontrol of grapevine powdery mildew (Erysiphe necator)

To develop a new biofungicide product against grapevine powdery mildew, caused by Erysiphe necator, cultural characteristics and mycoparasitic activities of pre-selected strains of Ampelomyces spp. were compared in laboratory tests to the commercial strain AQ10. Then, a 2-year experiment was performed in five vineyards with a selected strain, RS1-a, and the AQ10 strain. This consisted of autumn sprays in vineyards as the goal was to reduce the number of chasmothecia of E. necator, and, thus, the amount of overwintering inocula, instead of targeting the conidial stage of the pathogen during spring and summer. This is a yet little explored strategy to manage E. necator in vineyards. Laboratory tests compared the growth and sporulation of colonies of a total of 33 strains in culture; among these, eight strains with superior characteristics were compared to the commercial product AQ10 Biofungicide® in terms of their intra-hyphal spread, pycnidial production, and reduction of both asexual and sexual reproduction in E. necator colonies. Mycoparasitic activities of the eight strains isolated from six different powdery mildew species, including E. necator, did not depend on their mycohost species of origin. Strain RS1-a, isolated from rose powdery mildew, showed, together with three strains from E. necator, the highest rate of parasitism of E. necator chasmothecia. In field experiments, each strain, AQ10 and RS1-a, applied twice in autumn, significantly delayed and reduced early-season development of grapevine powdery mildew in the next year. Therefore, instead of mycohost specificity of Ampelomyces presumed in some works, but not confirmed by this study, the high sporulation rate in culture and the mycoparasitic patterns became the key factors for proposing strain RS1-a for further development as a biocontrol agent of E. necator.