Abstract:A means to rationalize the use of fungicides for crop protection and to make agriculture friendlier to environment and human health is to develop disease-risk forecasting systems based on the assessment of airborne inoculum abundance. Sclerotinia sclerotiorum, the pandemic agent of white mould disease, is disseminated via the atmosphere in the form of ascospores. These airborne spores are the primary source of inoculum initiating the majority of epidemics. However for witloof chicory (Cichorium intybus var. fo… Show more
“… 1, Fall, Willbur, et al (2018); 2, Willbur, Fall, Bloomingdale, et al (2018); 3, Reich, unpublished; 4, Leyronas et al (2019); 5, Jones et al (2012); 6, Mila et al (2003); 7, Fall, Boyse, et al (2018); 8, Foster et al (2011); 9, Qandah and del Río Mendoza (2011); 10, Bourdôt et al (2001); 11, Mila et al (2004); 12, Workneh and Yang (2000); 13, Reich et al (2017); 14, Matheron and Porchas (2005); 15. Shah et al (2019); 16, Bom and Boland (2000); 17, Ferraz et al (1999); 18, Twengström, Sigvald, et al (1998); 19, Twengström, Köpmans, et al (1998); 20, Grau and Radke (1984); 21, Blad et al (1978); 22, Kader et al (2018); 23, Schwartz and Steadman (1978); 24, Ficke et al (2018).…”
Section: Resultsmentioning
confidence: 98%
“…For ascospores, most studies report no association with 3‐day to 3‐week air temperature summaries (Fall, Willbur, et al, 2018; Foster et al, 2011; Qandah & del Río Mendoza, 2011) or with air temperatures from the same day to 3 days prior to ascospore counts (Bourdôt et al, 2001; Leyronas et al, 2019). However, some studies found significant correlations with air temperature.…”
Section: Resultsmentioning
confidence: 99%
“…However, some studies found significant correlations with air temperature. In witloof chicory, daily ascospore concentration was positively correlated with the minimum air temperature (ρ = 0.2) on the day of and day before ascospore release (Leyronas et al, 2019). In a non‐peer‐reviewed study, hourly and daily air temperature metrics were negatively correlated with ascospore release in dry bean (Archer & Yuan, 2004).…”
Section: Resultsmentioning
confidence: 99%
“…For ascospores, the influence of precipitation was more variable: mean quantities of precipitation at 3-to 7-day intervals were positively associated with days of peak ascospore release in canola (Qandah & del Río Mendoza, 2011), but precipitation was negatively correlated with ascospore release the following day in seed alfalfa fields (Reich et al, 2017). Other summaries of precipitation over periods of zero days to 3 weeks before spore counts found no relationship in carrot (Foster et al, 2011), seed alfalfa (authors' unpublished data) and witloof chicory (Leyronas et al, 2019).…”
Section: Precipitation and Irrigationmentioning
confidence: 94%
“…Pearson r values ranging from 0.26 to 0.52 (Leyronas et al, 2019). In seed alfalfa, daily ascospore levels were strongly associated with changes in RH the day before ascospore collection; furthermore, high RH the day before ascospore collections was associated with lower numbers of ascospores (Reich et al, 2017).…”
Predicting diseases caused by Sclerotinia sclerotiorum in field crops remains difficult, and published literature is largely inconsistent in finding significant relationships with environmental and agronomic factors for various life stages of the fungus. A scoping review was performed to synthesize the current quantitative insights into the role of the environment on the life cycle of S. sclerotiorum and the relationships between various life stages of the fungus and final disease expression under field conditions. For most variables, relationships with stages of the life cycle showed a wide range of responses ranging from closely related (high correlations or r2 values) to not related at all. The effects were often moderated by year, location and/or the presence of another variable such as irrigation, soil type, row spacing or cultivar. Studies that based analysis on a more nuanced understanding of pathogen biology rather than looking only at linear relationships tended to find stronger associations between variables. Yield was consistently negatively associated with disease levels, but cultivar, year, location and planting density were all important determinants of yield. Suggestions for improvement to future research in predictive model development of S. sclerotiorum diseases are discussed.
“… 1, Fall, Willbur, et al (2018); 2, Willbur, Fall, Bloomingdale, et al (2018); 3, Reich, unpublished; 4, Leyronas et al (2019); 5, Jones et al (2012); 6, Mila et al (2003); 7, Fall, Boyse, et al (2018); 8, Foster et al (2011); 9, Qandah and del Río Mendoza (2011); 10, Bourdôt et al (2001); 11, Mila et al (2004); 12, Workneh and Yang (2000); 13, Reich et al (2017); 14, Matheron and Porchas (2005); 15. Shah et al (2019); 16, Bom and Boland (2000); 17, Ferraz et al (1999); 18, Twengström, Sigvald, et al (1998); 19, Twengström, Köpmans, et al (1998); 20, Grau and Radke (1984); 21, Blad et al (1978); 22, Kader et al (2018); 23, Schwartz and Steadman (1978); 24, Ficke et al (2018).…”
Section: Resultsmentioning
confidence: 98%
“…For ascospores, most studies report no association with 3‐day to 3‐week air temperature summaries (Fall, Willbur, et al, 2018; Foster et al, 2011; Qandah & del Río Mendoza, 2011) or with air temperatures from the same day to 3 days prior to ascospore counts (Bourdôt et al, 2001; Leyronas et al, 2019). However, some studies found significant correlations with air temperature.…”
Section: Resultsmentioning
confidence: 99%
“…However, some studies found significant correlations with air temperature. In witloof chicory, daily ascospore concentration was positively correlated with the minimum air temperature (ρ = 0.2) on the day of and day before ascospore release (Leyronas et al, 2019). In a non‐peer‐reviewed study, hourly and daily air temperature metrics were negatively correlated with ascospore release in dry bean (Archer & Yuan, 2004).…”
Section: Resultsmentioning
confidence: 99%
“…For ascospores, the influence of precipitation was more variable: mean quantities of precipitation at 3-to 7-day intervals were positively associated with days of peak ascospore release in canola (Qandah & del Río Mendoza, 2011), but precipitation was negatively correlated with ascospore release the following day in seed alfalfa fields (Reich et al, 2017). Other summaries of precipitation over periods of zero days to 3 weeks before spore counts found no relationship in carrot (Foster et al, 2011), seed alfalfa (authors' unpublished data) and witloof chicory (Leyronas et al, 2019).…”
Section: Precipitation and Irrigationmentioning
confidence: 94%
“…Pearson r values ranging from 0.26 to 0.52 (Leyronas et al, 2019). In seed alfalfa, daily ascospore levels were strongly associated with changes in RH the day before ascospore collection; furthermore, high RH the day before ascospore collections was associated with lower numbers of ascospores (Reich et al, 2017).…”
Predicting diseases caused by Sclerotinia sclerotiorum in field crops remains difficult, and published literature is largely inconsistent in finding significant relationships with environmental and agronomic factors for various life stages of the fungus. A scoping review was performed to synthesize the current quantitative insights into the role of the environment on the life cycle of S. sclerotiorum and the relationships between various life stages of the fungus and final disease expression under field conditions. For most variables, relationships with stages of the life cycle showed a wide range of responses ranging from closely related (high correlations or r2 values) to not related at all. The effects were often moderated by year, location and/or the presence of another variable such as irrigation, soil type, row spacing or cultivar. Studies that based analysis on a more nuanced understanding of pathogen biology rather than looking only at linear relationships tended to find stronger associations between variables. Yield was consistently negatively associated with disease levels, but cultivar, year, location and planting density were all important determinants of yield. Suggestions for improvement to future research in predictive model development of S. sclerotiorum diseases are discussed.
Identifying the sources of fungal inoculum that induces epidemics is instrumental to managing crop health in a more efficient way by implementing prophylactic methods and by using better targeted biocontrol and fungicide applications. For some phytopathogenic fungi, this identification is hampered by the multiplicity of inoculum types. This is the case for Sclerotinia sclerotiorum, the agent of white mould, which can produce ascospores disseminated via the atmosphere, sclerotia stored in the soil and mycelium in plant debris of a large variety of hosts. The present study aims to assess the relative importance of airborne and soilborne inocula in white mould disease development and its persistence across two crop seasons. S. sclerotiorum isolates were collected from air, soil and carrot plants during two crop seasons in south‐western France and genotyped with 16 microsatellite markers. Among the 490 isolates, 162 clonal lineages were identified. The genetic characteristics did not differ significantly among isolates collected from air, soil and carrots. The epidemics of white mould on carrots were initiated either by airborne inoculum or by soilborne inoculum. It also appears that some isolates from airborne inoculum persisted from year to year.
A main biological constraint of dry bean (Phaseolus vulgaris) production in Canada is white mould, caused by the fungal pathogen Sclerotinia sclerotiorum. The primary infectious propagules of S. sclerotiorum are airborne ascospores and monitoring the air for inoculum levels could help predict the severity of white mould in bean fields. Daily air samples were collected in commercial dry bean fields in Alberta, Manitoba and Ontario and ascospores were quantified using quantitative PCR. Daily weather data was obtained from in‐field weather stations. The number of ascospores on a given day was modelled using 63 different environmental variables and several modelling methods, both regression and classification approaches, were implemented with machine learning (ML) (random forests, logistic regression and support vector machines) and statistical (generalized linear models) approaches. Across all years and provinces, ascospores were most highly correlated with ascospore release from the previous day (r ranged from 0.15 to 0.6). This variable was also the only variable included in all models and had the greatest weight in all models. Models without this variable had much poorer performance than those with it. Correlations of ascospores with other environmental variables varied by province and sometimes by year. A comparison of ML and statistical models revealed that they both performed similarly, but that the statistical models were easier to interpret. However, the precise relationship between airborne ascospore levels and in‐field disease severity remains unclear, and spore sampling methods will require further development before they can be deployed as a disease management tool.
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