Research on the pathogen components involved in Fusarium head blight (FHB) along with the effects of their interactions on disease development and mycotoxin accumulation is reviewed. The fungal components within the FHB complex differ significantly in different environments. Individual species may respond differently to, and be differentially influenced by, particular disease control measures. Almost all published co-inoculation studies on wheat spikes or grains show that competitive interactions among FHB pathogens are the rule when fungal/disease development is considered. However, the fungi with the competitive advantage do not usually gain any advantage from the presence of other weaker competing fungi. Total mycotoxin production in mixed inoculations may decrease, increase, or remain unchanged compared with single-isolate inoculations, depending on the fungal species concerned and environmental conditions. A few recent studies, where each individual fungal component was quantified using molecular methods, suggest that mycotoxin productivity in mixed inoculations generally increases.

Effective use of biological control agents (BCAs) is a potentially important component of sustainable agriculture. Recently, there has been an increasing interest among researchers in using combinations of BCAs to exploit potential synergistic effects among them. The methodology for investigating such synergistic effects was reviewed first and published results were then assessed for available evidence for synergy. Correct formulation of hypotheses based on the theoretical definition of independence (Bliss independence or Loewe additivity) and the subsequent and statistical testing for the independence–synergistic–antagonistic interactions have rarely been carried out thus far in studies on biocontrol of plant diseases. Thus, caution must be taken when interpreting reported “synergistic” effects without assessing the original publications. Recent theoretical modeling work suggested that disease suppression from combined use of two BCAs was, in general, very similar to that achieved by the more efficacious one, indicating no synergistic but more likely antagonistic interactions. Only in 2% of the total 465 published treatments was there evidence for synergistic effects among BCAs. In the majority of the cases, antagonistic interactions among BCAs were indicated. Thus, both theoretical and experimental studies suggest that, in combined use of BCAs, antagonistic interactions among BCAs are more likely to occur than synergistic interactions. Several research strategies, including formulation of synergy hypotheses in relation to biocontrol mechanisms, are outlined to exploit microbial mixtures for uses in biocontrol of plant diseases.

Over 4 years, the environmental conditions and the causal agents of Fusarium head blight (FHB) disease of wheat were determined in field sites in four European countries: Hungary, Ireland, Italy, and the United Kingdom. Polymerase chain reaction-based methods were used to detect each species causing FHB and quantify its DNA (as a measurement of fungal abundance) in the samples. Canonical correspondence analysis (CCA) was used to determine the relationship of the incidence and abundance of each species with weather variables. CCA indicated that little variability in the species prevalence data was explained by the weather variables. In contrast, a greater proportion of variability in abundance data was accounted for by the weather variables. Most samples contained two or more species and statistical analysis suggested that these species tended to coexist at field sites. CCA also indicated that there were differences in the relationships of the prevalence and abundance of the six FHB species with environmental variables. Fusarium poae was associated with relatively drier and warmer conditions, whereas F. graminearum was associated with warmer/humid conditions. F. avenaceum and F. culmorum were both associated with niches of cooler/wet/humid conditions. Two Microdochium species were associated with regions of relatively cool/moderate temperatures and frequent rainfalls of short duration. The results also suggested that environmental conditions differentially affect the infection and colonization processes, and the comparative abundance of the six species.

Agriculture is facing severe challenges from crop stresses, threatening its sustainable development and food security. This work exploits aerial visual perception for yellow rust disease monitoring, which seamlessly integrates state-of-the-art techniques and algorithms including UAV sensing, multispectral imaging, vegetation segmentation and deep learning U-Net. A field experiment is designed by infecting winter wheat with yellow rust inoculum, on top of which multispectral aerial images are captured by DJI Matrice 100 equipped with RedEdge camera. After image calibration and stitching, multispectral orthomosaic is labelled for system evaluation by inspecting high-resolution RGB images taken by Parrot Anafi Drone. The merits of the developed framework drawing spectral-spatial information concurrently are demonstrated by showing improved performance over purely spectral based classifier by the classical random forest algorithm. Moreover, various network input band combinations are tested including three RGB bands and five selected spectral vegetation indices by Sequential Forward Selection strategy of Wrapper algorithm.