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The 5895 nucleotide long single-stranded RNA genome of Sugarcane yellow leaf virus Florida isolate (SCYLV-F) includes six major ORFs. All but the first of these are homologous to genes of known function encoded by viruses of the three newly defined genera in the Luteoviridae (' luteovirids '), i.e. poleroviruses, luteoviruses and the enamoviruses. SCYLV-F ORFs 1 and 2 are most closely related to their polerovirus counterparts, whereas SCYLV-F ORFs 3 and 4 are most closely related to counterparts in luteovirus genomes, and SCYLV-F ORF5 is most closely related to the read-through protein gene of the only known enamovirus. These differences in affinity result from inter-species recombination. Two recombination sites in the genome of SCYLV-F map to the same genomic locations as previously described recombinations involving other luteovirids. A fourth type of luteovirid, Soybean dwarf virus, has already been described. Our analyses indicate that SCYLV-F represents a distinct fifth type.

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The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests. This paper proposes a framework that consolidates site-based insights and remote sensing capabilities to detect and segment deteriorations by fungal pathogens in natural and plantation forests. This approach is illustrated with an experimentation case of myrtle rust (Austropuccinia psidii) on paperbark tea trees (Melaleuca quinquenervia) in New South Wales (NSW), Australia. The method integrates unmanned aerial vehicles (UAVs), hyperspectral image sensors, and data processing algorithms using machine learning. Imagery is acquired using a Headwall Nano-Hyperspec® camera, orthorectified in Headwall SpectralView®, and processed in Python programming language using eXtreme Gradient Boosting (XGBoost), Geospatial Data Abstraction Library (GDAL), and Scikit-learn third-party libraries. In total, 11,385 samples were extracted and labelled into five classes: two classes for deterioration status and three classes for background objects. Insights reveal individual detection rates of 95% for healthy trees, 97% for deteriorated trees, and a global multiclass detection rate of 97%. The methodology is versatile to be applied to additional datasets taken with different image sensors, and the processing of large datasets with freeware tools.

The genetic diversity of sugarcane yellow leaf virus (SCYLV) was analyzed with 43 virus isolates from Réunion Island and 17 isolates from world-wide locations. We attempted to amplify by reverse-transcription polymerase chain reaction (RT-PCR), clone, and sequence four different fragments covering 72% of the genome of these virus isolates. The number of amplified isolates and useful sequence information varied according to each fragment, whereas an amplicon was obtained with diagnostic primers for 59 out of 60 isolates (98%). Phylogenetic analyses of the sequences determined here and additional sequences of 11 other SCYLV isolates available from GenBank showed that SCYLV isolates were distributed in different phylogenetic groups or belonged to single genotypes. The majority of isolates from Réunion Island were grouped in phylogenetic clusters that did not contain any isolates from other origins. The complete six ORFs (5612 bp) of five SCYLV isolates (two from Réunion Island, one from Brazil, one from China, and one from Peru) were amplified, cloned, and sequenced. The existence of at least three distinct genotypes of SCYLV was shown by phylogenetic analysis of the sequences of these isolates and additional published sequences of three SCYLV isolates (GenBank accessions). The biological significance of these genotypes and of the origin of the distinct lineage of SCYLV in Réunion Island remains to be determined.