Six new species of Fusarium associated with soil and plant hosts from ecosystems of minimal anthropogenic disturbance in Australia are described. Fusarium coicis from Coix gasteenii, F. goolgardi from Xanthorrhoea glauca, F. mundagurra from soil and Mangifera indica, F. newnesense from soil, F. tjaetaba from Sorghum interjectum and F. tjaynera from soil, Triodia microstachya, Sorghum interjectum and Sorghum intrans. Morphology and phylogenetic analysis of EF-1α, RPB1 and RPB2 sequence data were used to delineate species boundaries. The new species were phylogenetically distributed in the Fusarium sambucinum, F. fujikuroi, and F. chlamydosporum species complexes, and two novel species complexes. These six new species have particular phylogeographic significance as not only do they provide further insight into the geographic patterns of Fusarium evolution but also challenge current phylogeographic hypotheses.

Background: Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison.Results: Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to 0.998 ± 0.003 for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. Conclusions:An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatialspectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

Fusarium species associated with plants as pathogens, saprobes and endophytes in Australia are listed with notes on their pathogenicity and toxicity provided. A list of Fusarium species not known to occur in Australia also is provided and their quarantine significance evaluated.

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Two new species of Fusarium associated with Australian indigenous grasses in natural ecosystems are described as F. lyarnte and F. werrikimbe on the basis of morphology, DNA fingerprinting and phylogenetic analysis of EF-1α and β-tubulin sequence data. Isolates of these species were initially recovered from soil in the McGraths Creek area of central Australia and subsequently recovered from soil and stems of the indigenous grass Sorghum interjectum from Litchfield National Park in the Northern Territory, and from Sorghum leiocladum from Werrikimbe National Park in New South Wales. The common feature of both of these species is the production of large globose microconidia in false heads on polyphialides. Attempts to apply the biological species concept were unsuccessful.