A model estimating the risk of <i>Fusarium</i> head blight on wheat*

Rossi, Vittorio; Giosuè, Simona; Pattori, Elisabetta; Spanna, F.; Vecchio, A. Del

doi:10.1111/j.1365-2338.2003.00667.x

Cited by 72 publications

(57 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…While the window pane methodology (Coakley et al 1982) quantifies important environmental factors and their starting time, our procedure focused on specific growth stages, and identified the associations between DON content in harvested oat grains and environmental factors within each growth stage. This is in agreement with most mechanistic models for FHB development in wheat (Rossi et al 2003;Del Ponte et al 2005) that generally include the dynamics of the host.…”

Section: Association Between Don Content and Weather Conditions At DIsupporting

confidence: 72%

“…Associations between weather conditions during plant development (pre-, around and post-flowering) and DON accumulation in grains are often evaluated in models developed to examine DON in wheat (Hooker et al 2002;De Wolf et al 2003;Klem et al 2007). In prediction models developed for F. graminearum and DON in wheat, only weather conditions pre-and around flowering are included, while weather conditions close to harvest are not (Hooker et al 2002;De Wolf et al 2003;Klem et al 2007), except for the dynamic simulation model for the risk for Fusarium head blight in wheat (Rossi et al 2003). According to the study by Giroux et al (2016) a model developed by De Wolf et al (2003) was best among the nine models evaluated in order to predict DON levels in wheat in Quebec (Canada).…”

Section: Summarizing Comments On the Relationship Between Weather Conmentioning

confidence: 99%

See 1 more Smart Citation

DON content in oat grains in Norway related to weather conditions at different growth stages

et al. 2016

View full text Add to dashboard Cite

High concentrations of the mycotoxin deoxynivalenol (DON), produced by Fusarium graminearum have occurred frequently in Norwegian oats recently. Early prediction of DON levels is important for farmers, authorities and the Cereal Industry. In this study, the main weather factors influencing mycotoxin accumulation were identified and two models to predict the risk of DON in oat grains in Norway were developed: (1) as a warning system for farmers to decide if and when to treat with fungicide, and (2) for authorities and industry to use at harvest to identify potential food safety problems. Oat grain samples from farmers' fields were collected together with weather data (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013).A mathematical model was developed and used to estimate phenology windows of growth stages in oats (tillering, flowering etc.). Weather summarisations were then calculated within these windows, and the Spearman rank correlation factor calculated between DONcontamination in oats at harvest and the weather summarisations for each phenological window. DON contamination was most clearly associated with the weather conditions around flowering and close to harvest. Warm, rainy and humid weather during and around flowering increased the risk of DON accumulation in oats, as did dry periods during germination/seedling growth and tillering. Prior to harvest, warm and humid weather conditions followed by cool and dry conditions were associated with a decreased risk of DON accumulation. A prediction model, including only pre-flowering weather conditions, adequately forecasted risk of DON contamination in oat, and can aid in decisions about fungicide treatments.

show abstract

Section: Association Between Don Content and Weather Conditions At DIsupporting

confidence: 72%

Section: Summarizing Comments On the Relationship Between Weather Conmentioning

confidence: 99%

DON content in oat grains in Norway related to weather conditions at different growth stages

et al. 2016

View full text Add to dashboard Cite

show abstract

“…These equations should enable researchers to estimate the relative amount of F. graminearum inoculum produced based on weather data. The equations could be integrated into, and thus improve, models that describe inoculum production, such as the Brazilian model GIBSIM (49) and the model elaborated in Italy (50), by providing an estimate of the ascosporic inoculum present.…”

Section: Discussionmentioning

confidence: 99%

Effects of Temperature and Moisture on Development of Fusarium graminearum Perithecia in Maize Stalk Residues

Manstretta

Rossi

2016

Appl Environ Microbiol

View full text Add to dashboard Cite

Fusarium graminearum is the predominant component of the Fusarium head blight complex of wheat. F. graminearum ascospores, which initiate head infection, mature in perithecia on crop residues and become airborne. The effects of temperature (T) and moisture on perithecium production and maturation and on ascospore production on maize stalk residues were determined. In the laboratory, perithecia were produced at temperatures between 5 and 30°C (the optimum was 21.7°C) but matured only at 20 and 25°C. Perithecia were produced when relative humidity (RH) was >75% but matured only when RH was >85%; perithecium production and maturation increased with RH. Equations describing perithecium production and maturation over time as a function of T and RH (R 2 > 0.96) were developed. Maize stalks were also placed outdoors on three substrates: a grass lawn exposed to rain; a constantly wet, spongelike foam exposed to rain; and a grass lawn protected from rain. No perithecia were produced on stalks protected from rain. Perithecium production and maturation were significantly higher on the constantly wet foam than on the intermittently wet lawn (both exposed to rain). Ascospore numbers but not their dispersal patterns were also affected by the substrate. Fusarium head blight (FHB) is one of the most widespread and dangerous diseases of wheat and other small-grain cereals (1, 2). Up to 17 species belonging to the genera Fusarium and Microdochium have been recognized as responsible for FHB (3). Fusarium graminearum has been considered the predominant species in most cereal-growing areas of the world (4, 5, 6). Symptoms of the disease include premature bleaching of spikes or spikelets, sterile florets, poorly filled grains, and grains that are shriveled and discolored (white to pale pink) (7). The disease reduces yield, grain quality, including contamination by mycotoxins, and seed quality (3).Wheat spikes are receptive to infection from flowering to the soft-dough stage (8). Ascospores and macroconidia are the main inocula (3,7,9) and are typically produced on the residues of the previous crop (4, 7). The fungus can survive as a saprophyte on the previous crop's residue for 2 or more years (10,11,12). Although both ascospores and conidia can be detected in cereal crops, ascospores are more prevalent than conidia in many areas (3,4,7,13). Macroconidia are produced in sporodochia and are dispersed for short distances by splashing rain (14,15,16). Ascospores mature in perithecia and are forcibly discharged into the air; they are then airborne and can travel meters to kilometers (9,17,18,19).The main factors influencing production of perithecia and ascospores are light, temperature, and moisture. Light with wavelengths between 300 and 320 nm is essential for the induction of perithecium (20). Paulitz (21) observed more perithecia on the side of debris exposed to direct light; perithecia were also found on grains buried at 5 to 10 cm, but they did not produce ascospores (10).Perithecia and ascospores are formed under warm and moist co...

show abstract

“…Research in plant pathology over the past decade has produced models for risk prediction based on climate information (Rossi et al (2003), Hooker et al (2002), De Wolf et al (2003). …”

Section: Introductionmentioning

confidence: 99%

Estimating the Risk of a Crop Epidemic From Coincident Spatio-temporal Processes

Haran

Bhat

Molineros

et al. 2010

JABES

View full text Add to dashboard Cite

Fusarium Head Blight (FHB) or 'scab' is a very destructive disease that affects wheat crops. Recent research has resulted in accurate weather-driven models that estimate the probability of an FHB epidemic based on experiments. However, these predictions ignore two crucial aspects of FHB epidemics: (1) An epidemic is very unlikely to occur unless the plants are flowering, and (2) FHB spreads by its spores, resulting in spatial and temporal dependence in risk. We develop a new approach that combines existing weather-based probabilities with information on flowering dates from survey data, while simultaneously accounting for spatial and temporal dependence. Our model combines two space-time processes, one associated with pure weather-based FHB risks and the other associated with flowering date probabilities. To allow for scalability, we model spatiotemporal dependence via a process convolutions approach. Our sample based approach produces a realistic assessment of areas that are persistently at high risk (the probability of an epidemic is elevated for extended time periods), along with associated estimates of uncertainty. We conclude with the application of our approach to a case study from North Dakota.

show abstract

A model estimating the risk of Fusarium head blight on wheat*

Cited by 72 publications

References 3 publications

DON content in oat grains in Norway related to weather conditions at different growth stages

DON content in oat grains in Norway related to weather conditions at different growth stages

Effects of Temperature and Moisture on Development of Fusarium graminearum Perithecia in Maize Stalk Residues

Estimating the Risk of a Crop Epidemic From Coincident Spatio-temporal Processes

Contact Info

Product

Resources

About