Commercial sugarcane, belonging to the genus Saccharum (Poaceae), is an important industrial crop accounting for nearly 70% of sugar produced worldwide. Compared to other major crops, efforts to improve sugarcane are limited and relatively recent, with the first introduction of interspecific hybrids about 80 yr ago. Progress in traditional breeding of sugareane, a highly polyploid and frequently aneuploid plant, is impeded by its narrow gene pool, complex genome, poor fertility, and the long breeding/selection cycle. These constraints, however, make sugarcane a good candidate for molecular breeding. In the past decade considerable progress has been made in understanding and manipulating the sugarcane genome using various biotechnological and cell biological approaches. Notable among them are the creation of transgenic plants with improved agronomic or other important traits, advances in genomics and molecular markers, and progress in understanding the molecular aspects of sucrose transport and accumulation. More recently, substantial effort has been directed towards developing sugarcane as a biofactory for high-value products. While these achievements are commendable, a greater understanding of the sugarcane genome, and cell and whole plant physiology, will accelerate the implementation of commercially significant biotechnology outcomes. We anticipate that the rapid advancements in molecular biology and emerging biotechnology innovations would play a significant role in the future sugarcane crop improvement programs and offer many new opportunities to develop it as a new-generation industrial crop.

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 ${}^{\circledR }$ camera, orthorectified in Headwall SpectralView ${}^{\circledR }$ , 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 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, luccccteoviruses 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.

Austropuccinia psidii, originating in South America, is a globally invasive fungal plant pathogen that causes rust disease on Myrtaceae. Several biotypes are recognized, with the most widely distributed pandemic biotype spreading throughout the Asia-Pacific and Oceania regions over the last decade. Austropuccinia psidii has a broad host range with more than 480 myrtaceous species. Since first detected in Australia in 2010, the pathogen has caused the near extinction of at least three species and negatively affected commercial production of several Myrtaceae. To enable molecular and evolutionary studies into A. psidii pathogenicity, we assembled a highly contiguous genome for the pandemic biotype. With an estimated haploid genome size of just over 1 Gb (gigabases), it is the largest assembled fungal genome to date. The genome has undergone massive expansion via distinct transposable element (TE) bursts. Over 90% of the genome is covered by TEs predominantly belonging to the Gypsy superfamily. These TE bursts have likely been followed by deamination events of methylated cytosines to silence the repetitive elements. This in turn led to the depletion of CpG sites in TEs and a very low overall GC content of 33.8%. Compared to other Pucciniales, the intergenic distances are increased by an order of magnitude indicating a general insertion of TEs between genes. Overall, we show how TEs shaped the genome evolution of A. psidii and provide a greatly needed resource for strategic approaches to combat disease spread.