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Agronomy
Special Issues
Plant Disease Epidemiology: Changing Perspectives, Emerging Technologies and Prediction Modeling
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Plant Disease Epidemiology: Changing Perspectives, Emerging Technologies and Prediction Modeling

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: closed (31 March 2020) | Viewed by 20706

Special Issue Editors

Dr. Odile Carisse

E-Mail Website
Guest Editor
Centre de recherche et de développement de Saint-Jean-sur-Richelieu, Agriculture et Agroalimentaire Canada, 430 Gouin, St-Jean-sur-Richelieu, QC J3B 3E6, Canada
Interests: plant disease modeling and management decisions; molecular plant pathogen monitoring; fungicide resistance detection and management
Dr. George W. Sundin

E-Mail Website
Guest Editor
Department of Plant, Soil and Microbial Sciences, Center for Integrated Plant Systems, Michigan State University, 578 Wilson Rd., East Lansing, MI 48824, USA
Interests: plant pathology; microbial ecology; environmental microbiology; plant–bacteria interactions; fungal pathogens
Special Issues, Collections and Topics in MDPI journals
Dr. Nathaniel K. Newlands

E-Mail Website
Guest Editor
Summerland Research and Development Centre, Agriculture and Agri-Food Canada, Summerland, BC V0H 1Z0, Canada
Interests: remote sensing applications in agriculture; ecosystem modeling; forecasting in agriculture; predictive analytics; artificial intelligence; machine learning; deep learning; integrated sensing and validation
Special Issues, Collections and Topics in MDPI journals
Dr. Mamadou L. Fall

E-Mail Website
Guest Editor
Centre de Recherche et de Développement de Saint-Jean-sur-Richelieu, Agriculture et Agroalimentaire Canada, 430 Gouin, Saint-Jean-sur-Richelieu, QC J3B 3E6, Canada
Interests: plant virus epidemiology; dynamic simulation modeling; ecogenomic and quantitative epidemiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Plant health is of global importance for sustainable agriculture, food security, and environmental protection. Currently, crop plants are under greater threats than ever before. Depending on the crop species involved, management practices, and environmental conditions, diseases may cause a loss of 20–40% of food crops.

Climate change and variability are putting formidable pressure on agricultural systems and is driving new research in crop protection. Climate change is also enabling pathogens to expand their geographical range, dramatically altering the population dynamics of pathogens, their natural enemies, and host crops. The increasing commercial exchange and movement of plant materials and pathogens are enabling foreign pathogens to establish and thrive as invasive species in new agricultural areas. The intensification of agricultural practices, based on a steady increase in pesticide and fertilizer usage and soil impoverishment, has resulted in increased pesticide resistance, favoring disease development. In the context of food security, disease management is strongly influenced by socio-economic and farm cultural factors outside the concern of biological sciences such as public trust and demographic pressures which cause an increasing demand for high-quality food with the least amount of pesticide residues and higher production ethics. Consequently, the complexity of future requirements for plant disease management may be difficult to address. Nonetheless, a large amount of knowledge on pathogen genetics, biology, and ecology are available, and new crop protection technologies are rapidly emerging.

This Special Issue focuses on how epidemiology can be used to enhance our knowledge of crop disease development in a continuously changing environment, to predict future requirements in disease management, and to design novel crop disease management approaches. We welcome contributions, both research papers and high-quality reviews that present epidemiological approaches to enhance our understanding of pathogen and host population dynamics and discuss novel disease management solutions or alternatives.

Dr. Odile Carisse
Dr. George W. Sundin
Dr. Nathaniel K. Newlands
Dr. Mamadou L. Fall
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate change and variability
  • crop protection technologies
  • disease modeling
  • novel disease management solutions

Published Papers (4 papers)

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Research

16 pages, 1509 KiB  
Article
Factors Influencing the Occurrence of Onion Downy Mildew (Peronospora destructor) Epidemics: Trends from 31 Years of Observational Data
by Hervé Van der Heyden, Pierre Dutilleul, Jean-Benoît Charron, Guillaume J. Bilodeau and Odile Carisse
Agronomy 2020, 10(5), 738; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy10050738 - 20 May 2020
Cited by 8 | Viewed by 4275
Abstract
Onion downy mildew (ODM) caused by Peronospora destructor has been increasing annually in south-western Québec since the early 2000s, reaching 33% of affected onion fields in 2014. Using observational data collected over a period of 31 consecutive years, this study aimed to investigate [...] Read more.
Onion downy mildew (ODM) caused by Peronospora destructor has been increasing annually in south-western Québec since the early 2000s, reaching 33% of affected onion fields in 2014. Using observational data collected over a period of 31 consecutive years, this study aimed to investigate the variations in ODM incidence and epidemic onset and identify the meteorological variables that influence its polyetic development. A logistic model was fitted to each ODM epidemic to estimate and compare the onset of epidemics on a regional basis. Results of this analysis showed that the first observation date, 10% epidemic onset (b10) and mid-time (b) were, on average, 30.4, 15.1 and 11.3 days earlier in 2007–2017 than in 1987–1996. Results of a principal component analysis suggested that regional disease incidence was mostly influenced by the precipitation regime, the final regional disease incidence the previous year, and warmer temperature during the harvest period the previous fall. Subsequently, the data were divided in three periods of 10, 10 and 11 years, and a discriminant analysis was performed to classify each year in the correct period. Using a sufficient subset of five discriminating variables (temperature and rainfall at harvest the previous fall, winter coldness, solar radiation, and disease incidence the previous year), it was possible to classify 93.5% of the ODM epidemics in the period where they belong. These results suggest that P. destructor may overwinter under northern latitudes and help to highlight the need for more research on overwintering and for the development of molecular-based tools enabling the monitoring of initial and secondary inoculum. Full article
(This article belongs to the Special Issue Plant Disease Epidemiology: Changing Perspectives, Emerging Technologies and Prediction Modeling)
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29 pages, 1870 KiB  
Article
Disease Risk Forecasting with Bayesian Learning Networks: Application to Grape Powdery Mildew (Erysiphe necator) in Vineyards
by Weixun Lu, Nathaniel K. Newlands, Odile Carisse, David E. Atkinson and Alex J. Cannon
Agronomy 2020, 10(5), 622; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy10050622 - 28 Apr 2020
Cited by 19 | Viewed by 4725
Abstract
Powdery mildew (Erysiphe necator) is a fungal disease causing significant loss of grape yield in commercial vineyards. The rate of development of this disease varies annually and is driven by complex interactions between the pathogen, its host, and environmental conditions. The [...] Read more.
Powdery mildew (Erysiphe necator) is a fungal disease causing significant loss of grape yield in commercial vineyards. The rate of development of this disease varies annually and is driven by complex interactions between the pathogen, its host, and environmental conditions. The long term impacts of weather and climate variability on disease development is not well understood, making the development of efficient and durable strategies for disease management challenging, especially under northern conditions. We present a probabilistic, Bayesian learning network model to explore the complex causal interactions between environment, pathogen, and host for three different susceptible northern grape cultivars in Quebec, Canada. This approach combines environmental (weather, climate), pathogen (development stages), and host (crop cultivar-specific susceptibility) factors. The model is evaluated in an operational forecast mode with supervised and algorithm model learning and integrating Global Forecast System (GFS) Ensemble Reforecasts (GEFSR). A model-guided fungicide spray strategy is validated for guiding spray decisions up to 6 days with a 10-day forecast of potential spray efficacy under rain washed off conditions. The model-guided strategy improves fungicide spray decisions; decreasing the number of sprays, and identifying the optimal time to spray to increase spray effectiveness. Full article
(This article belongs to the Special Issue Plant Disease Epidemiology: Changing Perspectives, Emerging Technologies and Prediction Modeling)
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23 pages, 3507 KiB  
Article
A General Model for the Effect of Crop Management on Plant Disease Epidemics at Different Scales of Complexity
by Elisa González-Domínguez, Giorgia Fedele, Francesca Salinari and Vittorio Rossi
Agronomy 2020, 10(4), 462; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy10040462 - 26 Mar 2020
Cited by 7 | Viewed by 5529
Abstract
A general and flexible model was developed to simulate progress over time of the epidemics caused by a generic polycyclic pathogen on aerial plant parts. The model includes all of the epidemiological parameters involved in the pathogen life cycle: between-season survival, production of [...] Read more.
A general and flexible model was developed to simulate progress over time of the epidemics caused by a generic polycyclic pathogen on aerial plant parts. The model includes all of the epidemiological parameters involved in the pathogen life cycle: between-season survival, production of primary inoculum, occurrence of primary infections, production and dispersal of secondary inoculum both inside and outside the crop, and concatenation of secondary infection cycles during the host’s growing season. The model was designed to include the effect of the main crop management actions that affect disease levels in the crop. Policy-oriented, strategic, and tactical actions were considered at the different levels of complexity (from the agro-ecosystem to the farming and cropping system). All effects due to disease management actions were translated into variations in the epidemiological components of the model, and the model quantitatively simulates the effect of these actions on epidemic development, expressed as changes in final disease and in the area under the disease progress curve. The model can help researchers, students and policy makers understand how management decisions (especially those commonly recommended as part of Integrated Pest Management programs) will affect plant disease epidemics at different scales of complexity. Full article
(This article belongs to the Special Issue Plant Disease Epidemiology: Changing Perspectives, Emerging Technologies and Prediction Modeling)
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16 pages, 2944 KiB  
Article
Susceptibility of Winter Wheat and Triticale to Yellow Rust Influenced by Complex Interactions between Vernalisation, Temperature, Plant Growth Stage and Pathogen Race
by Julian Rodriguez-Algaba, Chris K. Sørensen, Rodrigo Labouriau, Annemarie F. Justesen and Mogens S. Hovmøller
Agronomy 2020, 10(1), 13; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy10010013 - 20 Dec 2019
Cited by 12 | Viewed by 4735
Abstract
Environmental factors influence the disease susceptibility of crop plants. In this study, we established an experimental system to investigate the effects of vernalisation, temperature and plant growth stage on the susceptibility of winter wheat and winter triticale to Puccinia striiformis, the causal [...] Read more.
Environmental factors influence the disease susceptibility of crop plants. In this study, we established an experimental system to investigate the effects of vernalisation, temperature and plant growth stage on the susceptibility of winter wheat and winter triticale to Puccinia striiformis, the causal agent of yellow (stripe) rust. Two temperature regimes: standard (18 °C day/12 °C night) and low (12 °C day/6 °C night), vernalised and non-vernalised seedlings, vernalised adult plants and two pathogen races were investigated. At low temperatures, vernalisation reduced the susceptibility of seedlings exposed to the ‘Warrior’ race, while this was only the case for five out of eight varieties exposed to the ‘Kranich’ race. Changing from standard to low temperature resulted in increased susceptibility of non-vernalised seedlings of seven varieties inoculated with the ‘Warrior’ race and five varieties inoculated with the ‘Kranich’ race. Increased susceptibility at low temperature was also detected for several varieties at the adult plant growth stage. Comparisons between vernalised seedlings and adult plants revealed an effect of plant growth stage on disease susceptibility (e.g., Adult Plant Resistance) in five varieties at standard temperature for the ‘Warrior’ race and in five and four varieties at standard and low temperature respectively, for the ‘Kranich’ race. The complex and unpredictable interactions between environment and pathogen influencing yellow rust susceptibility of individual varieties stress the importance of phenotyping for disease resistance under different environmental conditions and pathogen populations. The environmental impact on rust susceptibility should also be taken into account in early-warning systems targeting wheat and triticale breeding programmes and growers. Full article
(This article belongs to the Special Issue Plant Disease Epidemiology: Changing Perspectives, Emerging Technologies and Prediction Modeling)
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