Airborne fungal phytopathological spore assessment in three European vineyards from different bioclimatic areas

Martínez-Bracero, Moisés; González-Fernández, Estefanía; Wójcik, Magdalena; Alcázar, Pilar; Fernández-González, María; Kasprzyk, Idalia; Rodríguez-Rajo, F. J.; Galán, Carmen Rueda

doi:10.1007/s10453-020-09664-6

Cited by 7 publications

(8 citation statements)

References 35 publications

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“…A myriad of studies, covering various aspects of allergenicity and phytopathogenicity, have highlighted the importance of fungal spore monitoring [10,13,19,53]. Many pollen seasonal calendars have been constructed previously [54].…”

Section: Airborne Fungal Spore Monitoringmentioning

confidence: 99%

“…Other, more "wet weather" spore species, including numerous spores in the Phylum Ascomycota, such as Didimella, Leptosphaeria and Pleospora, have been seen to possess a positive correlation with rainfall [29]. Separately, Botrytis has previously shown a significantly high correlation with humidity, at values exceeding 90%, with storm events resulting in high proliferation of Botrytis infection [53,64,65]. These previous analyses assist in explaining the positive correlation of Ascospores and Botrytis with rainfall in this present study.…”

Section: Meteorololy and Fungal Spore Concentrationsmentioning

confidence: 99%

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First Long-Time Airborne Fungal Spores Study in Dublin, Ireland (1978–1980)

et al. 2022

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Ambient fungal spores within the atmosphere can contribute to a range of negative human, animal and plant health conditions and diseases. However, trends in fungal spore seasonality, species prevalence, and geographical origin have been significantly understudied in Ireland. Previously unpublished data from the late 1970s have recently been collected and analysed to establish historical fungal spore trends/characteristics for Dublin. Historical spore concentrations were largely dominated by Alternaria, Ascospores, Basidiospores, Botrytis, Cladosporium, Erysiphe and Rusts. The main fungal spore season for Dublin commenced in April with the fructification of Scopulariopsis and Ganoderma. However, the vast majority of other spore types did not reach peak spore release until late summer. The correlation between ambient spore concentration, and meteorological parameters was examined using Multivariable Regression Tree (MRT) analysis. The notable correlations found for fungal spore concentrations tended to involve temperature-based parameters. The use of a non-parametric wind regression was also employed to determine the potential geographical origin of ambient fungal spores. The impact of wind direction, and high windspeed on fungal spores was established, ultimately highlighting the importance of studying and monitoring fungal spores within Ireland, rather than attempting to rely on data from other regions, as most fungal spores collected in Dublin appeared to originate from within the island.

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Section: Airborne Fungal Spore Monitoringmentioning

confidence: 99%

Section: Meteorololy and Fungal Spore Concentrationsmentioning

confidence: 99%

First Long-Time Airborne Fungal Spores Study in Dublin, Ireland (1978–1980)

et al. 2022

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“…According to previous research, linear regression models or neural network can predict with success disease behavior such as mycotoxin secretion in crops such as grapevine, rice and wheat or improve the ability of crop-growth monitoring [17,[46][47][48][49][50]. In potato, the publications related with prediction of inoculum of late blight in air using ML algorithms are non-existent.…”

Section: Discussionmentioning

confidence: 99%

Predicting Daily Aerobiological Risk Level of Potato Late Blight Using C5.0 and Random Forest Algorithms under Field Conditions

Meno

Escuredo

Abuley

et al. 2023

Sensors

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Late blight, caused by Phytophthora infestans, is a major disease of the potato crop with a strong negative impact on tuber yield and tuber quality. The control of late blight in conventional potato production systems is often through weekly application of prophylactic fungicides, moving away from a sustainable production system. In support of integrated pest management practices, machine learning algorithms were proposed as tools to forecast aerobiological risk level (ARL) of Phytophthora infestans (>10 sporangia/m3) as inoculum to new infections. For this, meteorological and aerobiological data were monitored during five potato crop seasons in Galicia (northwest Spain). Mild temperatures (T) and high relative humidity (RH) were predominant during the foliar development (FD), coinciding with higher presence of sporangia in this phenological stage. The infection pressure (IP), wind, escape or leaf wetness (LW) of the same day also were significantly correlated with sporangia according to Spearman’s correlation test. ML algorithms such as random forest (RF) and C5.0 decision tree (C5.0) were successfully used to predict daily sporangia levels, with an accuracy of the models of 87% and 85%, respectively. Currently, existing late blight forecasting systems assume a constant presence of critical inoculum. Therefore, ML algorithms offer the possibility of predicting critical levels of Phytophthora infestans concentration. The inclusion of this type of information in forecasting systems would increase the exactitude in the estimation of the sporangia of this potato pathogen.

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“…Similarly to allergenic pollen grains, the presence of fungal spores in the air is a threat to public health (Horner et al, 1995). Moreover, fungal spores are also essential pathogens of crops, fruits, and vegetables, causing significant losses in the agricultural, vineyard, and gardening industries (Dean et al, 2012;Jędryczka, 2014;Martínez-Bracero et al, 2020). In Poland, the most important aeromycological research centers are the Institute of Plant Genetics, the Polish Academy of Science in Poznań, the University of Szczecin, and Jagiellonian University in Kraków.…”

Section: Fungal Spore Concentrations -Variation and Impacts Of Climatementioning

confidence: 99%

Aerobiology in Poland: Achievements and challenges

Grewling,

Myszkowska,

Piotrowska-Weryszko

et al. 2023

Acta Soc Bot Pol

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Aerobiology is a scientific discipline that focuses on investigating biological particles (bioaerosols) passively transported in the atmosphere, mainly fungal spores and pollen grains. Due to the allergic and pathogenic properties of these particles, aerobiological data is widely used in allergology, plant pathology, and agriculture. In addition, the results of aerobiological monitoring have found applications in biogeography, paleoecology, forestry, veterinary medicine, forensic science, and climate change research, as well as in the assessment of threats to the deterioration of cultural heritage. In this review, the contribution of Polish scientists to the development of worldwide aerobiology is presented. The most important results on the atmospheric dispersion of bioaerosols, spatiotemporal modeling, and novel methods used in aerobiological research are described. Moreover, the cooperation at the national and international levels as part of scientific programs and the perspectives for further development of aerobiology in Poland are discussed.

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Airborne fungal phytopathological spore assessment in three European vineyards from different bioclimatic areas

Cited by 7 publications

References 35 publications

First Long-Time Airborne Fungal Spores Study in Dublin, Ireland (1978–1980)

First Long-Time Airborne Fungal Spores Study in Dublin, Ireland (1978–1980)

Predicting Daily Aerobiological Risk Level of Potato Late Blight Using C5.0 and Random Forest Algorithms under Field Conditions

Aerobiology in Poland: Achievements and challenges

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