4.4 Article

Quantification of the relationship between the environment and Fusarium head blight, Fusarium pathogen density, and mycotoxins in winter wheat in Europe

期刊

EUROPEAN JOURNAL OF PLANT PATHOLOGY
卷 133, 期 4, 页码 975-993

出版社

SPRINGER
DOI: 10.1007/s10658-012-9968-6

关键词

Disease forecasting; Gibberella zeae; Multiple testing; Nonparametric correlations; Wheat scab; Window-pane

资金

  1. European Commission, Quality of Life and Management of Living Resources Programme (QOL), Key Action 5 on Sustainable Agriculture [QLK5-CT-2000-01517 (RAMFIC)]
  2. USDA [2010-34493-21087]
  3. Biotechnology and Biological Sciences Research Council [BBS/E/J/00000606, BBS/E/J/000CA310] Funding Source: researchfish
  4. BBSRC [BBS/E/J/000CA310] Funding Source: UKRI

向作者/读者索取更多资源

Measurements of local environmental conditions, intensity of Fusarium head blight (FHB) in wheat spikes, biomass of Fusarium graminearum, F. culmorum, and F. poae (pathogens causing FHB) and concentration of the mycotoxins deoxynivalenol (DON) and nivalenol (NIV) in harvested wheat grain were obtained in a total of 150 location-years, originating in three European countries (Hungary, Ireland, United Kingdom) from 2001 to 2004. Through window-pane methodology, the length and starting time of temporal windows where the environmental variables were significantly associated with the biological variables were identified. Window lengths of 5 to 30 days were evaluated, with starting times from 18 days before anthesis to harvest. Associations were quantified with nonparametric Spearman correlation coefficients. All biological variables were significantly associated with at least one evaluated environmental variable (P a parts per thousand currency signaEuro parts per thousand 0.05). Moisture-related variables (e.g., average relative humidity, hours of relative humidity above 80%) had the highest positive correlations with the biological variables, but there also was a significant negative correlation between average temperature and several biological variables. When significant correlations were found, they were generally for all window lengths, but for a limited number of window start times (generally before anthesis for disease index and after anthesis for the toxins and late-season fungal biomasses). Semi-partial Spearman correlation coefficients were used to evaluate the relationship between the environmental variables and the concentration of DON and NIV after the effects of FHB intensity and fungal biomass on the mycotoxins were removed. Significant semi-partial correlations were found between relative humidity variables and DON, and between temperature and relative humidity variables and NIV for time windows that started after anthesis (and not for any earlier time windows). Results confirm that the environment influences disease, fungal biomass, and mycotoxin production, and help refine the time windows where the association is greatest. However, variability in the relationships was high, indicating that no single environmental variable is sufficient for prediction of disease or mycotoxin contamination.

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