Deoxynivalenol accumulation and other scab symptoms in six romanian wheat genotypes inoculated withFusarium graminearum

Reaction of winter wheat (Triticum aestivum L.) cultivars to infection with Fusarium spp.: mycotoxin contamination in grain and chaff

This study compares the susceptibility of winter wheat (Triticum aestivum L.) cultivars to Fusarium head blight (FHB) and accumulation of mycotoxins in kernels and chaff under different climatic conditions in two locations-Cerekwica near Poznan (Central West Poland) and Sitaniec, near Zamosc, Lublin region (South East Poland). Very high variations were found in the concentrations of mycotoxins (zearalenone, ZEA; nivalenol, NIV; deoxynivalenol, DON; moniliformin, MON) in examined fractions: Fusarium-damaged kernels (FDK) and healthy looking kernels (HLK) and in chaff for individual cultivars in both locations. In most cases, significantly higher concentrations of investigated toxins were recorded in wheat from the area of Lublin than from Poznan (p < 0.05). The highest Fusarium infection rates and mycotoxin biosynthesis levels were observed in the Lublin location, with the percentage of the FDK fraction ranging 8.1-81.6. In this region, ZEA concentration (microg g(-1)) after inoculation with F. culmorum and F. graminearum ranged from 0.02-0.48 and 0.32-1.04, respectively. In the Poznan area, the toxin concentrations were considerably lower, ranging 0.01-0.10 and 0.03-0.13 microg g(-1) for both isolates, respectively. The concentration of DON was significantly higher than ZEA or NIV levels. The levels of MON accumulation (microg g(-1)) in the FDK fraction were between 0.14 and 1.73 (Poznan area) and ND (not detected) to 2.51 (Lublin area). F. avenaceum infection rate ranged 7-35% in samples where the toxin was detected.

Occurrence of deoxynivalenol in Czech grain

A survey of deoxynivalenol (DON) content in cereals intended for human consumption was carried out in the Czech Republic (CR) over a seven-year period (2000-2006). Wheat, barley and rye samples of harvested cereals were collected directly from farmers where the selection was based on sample origin. In wheat, randomly sampled spikes and risk samples selected on the basis of visually scabby kernels (VSK) were also analysed. An immunochemical method, ELISA, was used for analysis. The maximum limit, according to Commission Regulation (EC) No. 1881/2006, for DON content (1,250 µg/kg) in unprocessed cereals for human nutrition was exceeded in random samples of wheat in 3.5% out of 345 analysed samples, of barley in 1.6% out of 498 analysed samples, and there were no samples of rye (out of 113) exceeding this limit. The analysis of spike samples and the samples that were selected based on VSK occurrence revealed much higher levels of DON content. Highly significant effects of the year, sample origin, and preceding crop on the DON content were found.

Analysis of disease progress as a basis for evaluating disease management practices

The relationship between epidemiology and disease management is long-standing but sometimes tenuous. It may seem self-evident that improved understanding of epidemic processes will lead to more effective control practices but this remains a testable proposition rather than demonstrated reality. A wide range of models differing in mathematical sophistication and computational complexity has been proposed as a means of achieving a greater understanding of epidemiology and carrying this through to improved management. The potential exists to align these modeling approaches to evaluation of control practices and prediction of the consequent epidemic outcomes, but these have yet to make a major impact on practical disease management. For the immediate future simpler pragmatic approaches for analysis of disease progress, using nonlinear growth functions and/or integrated measures such as area under disease progress curves, will play a key role in informing tactical and strategic decisions on control treatments. These approaches have proved useful in describing control effectiveness and, in some cases, optimizing or changing control practices.