Inferences on the Susceptibility of Wood of Different Tree Species to Heterobasidion annosum Sensu Lato (Fr.) Bref. Primary Infections and on the Range of Pathogen Spores Dispersal

Stumps play a pivotal role in the epidemiology of the fungal forest pathogens Heterobasidion spp. because they are the main courts of primary airborne infections. The aims of this study were (i) to determine the susceptibility of seven tree species (i.e., Larix sibirica, Picea abies, Picea sitchensis, Pinus contorta, Pinus strobus, Pinus sylvestris and Pseudotsuga menziesii) to primary infection by H. annosum and H. parviporum through comparative inoculation experiments of conidia on wood discs in controlled conditions; (ii) to compare the susceptibility of wood discs of the same tree species to natural airborne infections in two Latvian Norway spruce forest stands infested either by H. annosum or H. parviporum; (iii) to explore the rates of infection of wood discs at increasing distances from spore sources in these two forests to make inferences on the range of spores dispersal. Results obtained by spraying wood discs with conidial suspensions in controlled conditions are in agreement with those obtained by exposing wood discs to the natural airborne inoculum in the forests, as clearly supported by the significant correlation (r = 0.79; p < 0.05) between the two sets of data. Susceptibility was highest in Pinus species, followed by P. abies and P. sitchensis. Susceptibility was lowest for L. sibirica and P. menziesii. The area colonized by Heterobasidion spp. in the sapwood of wood discs was much greater than that colonized in the heartwood. A sharp decrease in the rate of infection of wood discs with distance from spore sources (i.e., fruiting bodies) was observed, further confirming the importance of local spore sources in the epidemiology of Heterobasidion spp. Taken together, these findings could help designing tactics to manage these fungal forest pathogens.

Monitoring airborne inoculum for improved plant disease management. A review

Global demand for pesticide-free food products is increasing rapidly. Crops of all types are, however, under constant threat from various plant pathogens. To achieve adequate control with minimal pesticide use, close monitoring is imperative. Many plant pathogens spread through the air, so the atmosphere is composed of a wide variety of plant pathogenic and non-plant pathogenic organisms, in particular in agricultural environments. Aerobiology is the science that studies airborne microorganisms and their distribution, especially as agents of infection. Although this discipline has existed for decades, the development of new molecular technologies is contributing to an increase in the use of aerobiological data for several purposes, from day-to-day monitoring to improving our understanding of pathosystems. Although the importance of knowing the size and composition of plant pathogen populations present in the air is recognized, technical constraints hinder the development of agricultural aerobiology. Here we review the application of spore sampling systems in agriculture and discuss the main considerations underlying the implementation of airborne inoculum monitoring. The results of this literature review confirm that the use of aerobiological data to study the escape of inoculum from a source and its role in the development of diseases is well mastered, but point at a lack of knowledge to proceed with the deployment of these systems at the landscape scale. Thus, we conclude that airborne inoculum surveillance networks are still in their early stages and although more and more initiatives are emerging, research must be conducted primarily to integrate evolving technologies and improve the access, analysis, interpretation and sharing of data. These tools are needed to estimate short- and medium-term risks, identify the most appropriate control measures with the lowest environmental risk, develop indicators to document the effects of climate change, and monitor the evolution of new genotypes at multiple scales.

Comparison of qPCR and Metabarcoding Methods as Tools for the Detection of Airborne Inoculum of Forest Fungal Pathogens

Forest diseases caused by invasive fungal pathogens are becoming more common, sometimes with dramatic consequences to forest ecosystems. The development of early detection systems is necessary for efficient surveillance and to mitigate the impact of invasive pathogens. Windborne spores are an important pathway for introduction of fungal pathogens into new areas; the design of spore trapping devices adapted to forests, capable of collecting different types of spores, and aligned with development of efficient molecular methods for detection of the pathogen, should help forest managers anticipate new disease outbreaks. Two types of Rotorod samplers were evaluated for the collection of airborne inoculum of forest fungal pathogens with a range of spore sizes in five forest types. Detection was by specific quantitative PCR (qPCR) and by high-throughput sequencing (HTS) of amplified internal transcribed spacer sequences using a new bioinformatic pipeline, FungiSearch, developed for diagnostic purposes. Validation of the pipeline was conducted on mock communities of 10 fungal species belonging to different taxa. Although the sensitivity of the new HTS pipeline was lower than the specific qPCR, it was able to detect a wide variety of fungal pathogens. FungiSearch is easy to use, and the reference database is updatable, making the tool suitable for rapid identification of new pathogens. This new approach combining spore trapping and HTS detection is promising as a diagnostic tool for invasive fungal pathogens.

Decision Trees to Forecast Risks of Strawberry Powdery Mildew Caused by Podosphaera aphanis

Powdery mildew (Podosphaera aphanis) is a major disease in day-neutral strawberry. Up to 30% yield losses have been observed in Eastern Canada. Currently, management of powdery mildew is mostly based on fungicide applications without consideration of risk. The objective of this study is to use P. aphanis inoculum, host ontogenic resistance, and weather predictors to forecast the risk of strawberry powdery mildew using CART models (classification trees). The data used to build the trees were collected in 2006, 2007, and 2008 at one experimental farm and six commercial farms located in two main strawberry-production areas, while external validation data were collected at the same experimental farm in 2015, 2016, and 2018. Data on proportion of leaf area diseased (PLAD) were grouped into four severity classes (1: PLAD = 0; 2: PLAD > 0 and <5%; 3: >5% and <15%; and 4: PLAD > 15%) for a total of 681 and 136 cases for training and external validation, respectively. From the initial 92 weather variables, 21 were selected following clustering. The tree with the best balance between the number of predictors and highest accuracy was built with: airborne inoculum concentration and number of susceptible leaves on the day of sampling, and mean relative humidity, mean daily number of hours at temperature between 18 and 30 °C, and mean daily number of hours at saturation vapor pressure between 10 and 25 mmHg during the previous 6 days. For training, internal validation, and external validation datasets, the sensitivity, specificity, and accuracy ranged from 0.70 to 0.90, 0.87 to 0.98, and 0.82 to 0.97, respectively. The classification rules to estimate strawberry powdery mildew risk can be easily implemented into disease decision support systems and used to treat only when necessary and thus avoid preventable yield losses and unnecessary treatments.

Characterization of Pathogen Airborne Inoculum Density by Information Theoretic Analysis of Spore Trap Time Series Data

In a previous study, air sampling using vortex air samplers combined with species-specific amplification of pathogen DNA was carried out over two years in four or five locations in the Salinas Valley of California. The resulting time series data for the abundance of pathogen DNA trapped per day displayed complex dynamics with features of both deterministic (chaotic) and stochastic uncertainty. Methods of nonlinear time series analysis developed for the reconstruction of low dimensional attractors provided new insights into the complexity of pathogen abundance data. In particular, the analyses suggested that the length of time series data that it is practical or cost-effective to collect may limit the ability to definitively classify the uncertainty in the data. Over the two years of the study, five location/year combinations were classified as having stochastic linear dynamics and four were not. Calculation of entropy values for either the number of pathogen DNA copies or for a binary string indicating whether the pathogen abundance data were increasing revealed (1) some robust differences in the dynamics between seasons that were not obvious in the time series data themselves and (2) that the series were almost all at their theoretical maximum entropy value when considered from the simple perspective of whether instantaneous change along the sequence was positive.

Evidence for differences in the temporal progress of Plasmopara viticola clades riparia and aestivalis airborne inoculum monitored in vineyards in eastern Canada using a specific multiplex qPCR assay

Four clades of Plasmopara viticola isolated from wild and cultivated Vitis species have recently been described. Currently, only P. viticola clades riparia and aestivalis had been detected in eastern Canada. In order to increase our understanding of the epidemiology of these clades of P. viticola, airborne sporangia were monitored with spore samplers at two experimental vineyards from 2015 to 2018, and at 11, 14, and 15 commercial vineyards in 2016, 2017, and 2018, respectively. At each vineyard and in each year, airborne sporangia were assessed three times weekly from grapevine budbreak to harvest. To accurately monitor airborne inoculum, a specific and sensitive qPCR assay for simultaneous quantification of P. viticola clades riparia and aestivalis was developed. At the experimental site, in the vineyard planted with the hybrid grape variety Chancellor, mostly P. viticola clade riparia was detected. In vineyards planted with multiple grape varieties, airborne sporangia of P. viticola clade riparia were prevalent at the beginning of the season, while P. viticola clade aestivalis was mostly detected from mid-season to harvest. At the commercial sites, airborne sporangia of P. viticola clade riparia were more prevalent in 2016, while P. viticola clade aestivalis was more prevalent in 2017 and 2018. The only significant difference between the inoculum progress curves was the time at which 50% of the seasonal inoculum was reached, with an average for the three years of 100.8 and 117.9 days since May 1 for P. viticola clade riparia and clade aestivalis, respectively. When airborne sporangium concentrations were expressed as the proportion of the two clades, in general, the proportion of clade aestivalis to that of riparia was low at the beginning of the season and increased to reach around 0.9 to 1.0 at the end of the season. These results suggest that both clades of P. viticola coexist, but that clade aestivalis is predominant and that downy mildew epidemics caused by P. viticola clade riparia occur 2-3 weeks before those caused by clade aestivalis.

Early Detection of Airborne Inoculum of Nothopassalora personata in Spore Trap Samples from Peanut Fields Using Quantitative PCR

A quantitative PCR (qPCR)-assay was developed to detect airborne inoculum of Nothopassalora personata, causal agent of late leaf spot (LLS) on peanut, collected with a modified impaction spore trap. The qPCR assay was able to consistently detect as few as 10 spores with purified DNA and 25 spores based on crude DNA extraction from rods. In 2019, two spore traps were placed in two peanut fields with a history of LLS. Sampling units were replaced every 2 to 4 days and tested with the developed qPCR assay, while plots were monitored for symptom development. The system detected inoculum 35 to 56 days before visual symptoms developed in the field, with detection related to environmental parameters affecting pathogen life-cycle and disease development. This study develops the framework of the qPCR spore trap system and represents the initial steps towards validation of the performance of the system for use as a decision support tool to complement integrated management of LLS.

Temporal Dispersal Patterns of Phaeomoniella chlamydospora, Causal Agent of Petri Disease and Esca, in Vineyards

Although the fungus Phaeomoniella chlamydospora is the most commonly detected causal agent of Petri disease and esca, two important fungal grapevine trunk diseases, little is known about the dispersal patterns of P. chlamydospora inoculum. In this work, we studied the dispersal of P. chlamydospora airborne inoculum from 2016 to 2018 in two viticultural areas of eastern (Ontinyent) and northern (Logroño) Spain. The vineyards were monitored weekly from November to April using microscope slide traps, and P. chlamydospora was detected and quantified by a specific real-time quantitative (qPCR) method set up in this work. The method was found to be sensitive, and a good correlation was observed between numbers of P. chlamydospora conidia (counted by microscope) and DNA copy numbers (quantified by qPCR). We consistently detected DNA of P. chlamydospora at both locations and in all seasons but in different quantities. In most cases, DNA was first detected in the last half of November, and most of the DNA was detected from December to early April. When rain was used as a predictor of P. chlamydospora DNA detection in traps, false-negative detections were observed, but these involved only 4% of the total. The dispersal pattern of P. chlamydospora DNA over time was best described (R2 = 0.765 and concordance correlation coefficient = 0.870) by a Gompertz equation, with time expressed as hydrothermal time (a physiological time accounting for the effects of temperature and rain). This equation could be used to predict periods with a high risk of dispersal of P. chlamydospora.

Real-Time PCR and LAMP Assays for the Detection of Spores of Alternaria solani and Sporangia of Phytophthora infestans to Inform Disease Risk Forecasting

Real-time loop-mediated isothermal amplification (LAMP) assays for the detection of sporangia of the causal pathogen of late blight, Phytophthora infestans, and spores of the main causal pathogen of early blight, Alternaria solani, were developed to facilitate the in-field detection of airborne inoculum to improve disease forecasting. These assays were compared with an existing real-time PCR assay for P. infestans and a newly developed real-time PCR assay for A. solani. Primers were designed for real-time LAMP of P. infestans and A. solani. The specificity of the P. infestans real-time LAMP assay was similar to that of an existing real-time PCR assay: DNA of P. infestans was consistently amplified as was DNA of the taxonomically closely related species Phytophthora mirabilis, Phytophthora phaseoli, and Phytophthora ipomoea; no amplification of DNA from the potato pathogens Phytophthora erythroseptica or Phytophthora nicotianae occurred. Real-time LAMP and PCR assays were developed for A. solani, and the specificity was compared with an existing conventional PCR assay. Importantly, the A. solani real-time LAMP and PCR assays did not amplify the species Alternaria alternata. However, cross-reactivity with Alternaria dauci was observed with the real-time PCR assay and Alternaria brassicae with the real-time LAMP assay. The sensitivity of all assays for the detection of DNA extracted from sporangia/spores of the target pathogens was evaluated. The P. infestans real-time LAMP assay reliably detected 5 pg of DNA, equivalent to ∼1 sporangia per reaction. By comparison, 20 fg of DNA was detectable with the existing real-time PCR assay. In the case of A. solani, real-time LAMP detected 4.4 pg of DNA, equivalent to ∼1 spore per reaction, and real-time PCR detected 200 fg of DNA. In-field air samplers were deployed in two trial plots planted with potato: one infected with P. infestans, and the other infected with A. solani. Four additional samplers were located in commercial potato fields. Air samples were taken through the season, and detection of airborne inoculum of P. infestans and A. solani with both real-time PCR and LAMP was assessed.

Spatiotemporal dynamics and modelling support the case for area-wide management of citrus greasy spot in a Brazilian smallholder farming region

Citrus greasy spot (CGS), caused byZasmidium citri, induces premature defoliation and yield loss inCitrusspp. CGS epidemiology is well understood in areas of high humidity such as Florida (USA), but remains unaddressed in Brazil, despite differing climatic conditions and disease management practices. We characterize the spatiotemporal dynamics of CGS in the Recôncavo of Bahia, Brazil, focusing on four hierarchical levels (quadrant, plant, grove and region). A survey conducted in 19 municipalities showed that disease is found throughout the entire region with a prevalence (i.e. proportion of affected sampling units) of 100% in groves and plants, and never lower than 70% on leaves. Index of dispersion (D) values suggest the spatial pattern of symptomatic units lies somewhere between random and regular. This was confirmed by the parameters of the binary power law for plants and their quadrants (log(A)<0 andb<1). Variability in disease severity at different plant heights (0.7 m, 1.3 m and 2.0 m) was tested, but no consistent differences were observed. We introduce a simple compartmental model synthesising the epidemiology of the disease, in order to motivate and guide further research. The data we have collected allow such a model to be parameterised, albeit with some ambiguity over the proportion of new infections that result from inoculum produced within the grovevs.external sources of infection. By extending our model to include two populations of growers – those who control and those who do not – coupled by the spread of airborne inoculum, we investigate likely performance of the type of cultural controls that would be accessible to citrus growers in Northeastern Brazil. Our model shows that control via removal of the key source of inoculum – i.e. fallen leaves – can be very effective. However, successful control is likely to require area-wide strategies, in which a large proportion of growers actively manage disease.