The responsiveness and clinical utility of the Australian therapy outcome measure for indigenous clients.

Introduction: The Australian Therapy Outcome Measure for Indigenous Clients (ATOMIC) is a goal-setting tool designed to measure therapy outcomes with First Australians. It was originally developed and validated for use with First Australian children as a culturally responsive alternative to traditional western outcome measures. This research explored the applicability, responsiveness and clinical utility of the ATOMIC when used with First Australian adults attending an urban health service.

Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location.

Background: This study explores the use of Unmanned Aerial Vehicles (UAVs) for estimating wheat biomass, focusing on the impact of phenotyping and analytical protocols in the context of late-stage variety selection programs. It emphasizes the importance of variable selection, model specificity, and sampling location within the experimental plot in predicting biomass, aiming to refine UAV-based estimation techniques for enhanced selection accuracy and throughput in variety testing programs.

Results: The research uncovered that integrating geometric and spectral traits led to an increase in prediction accuracy, whilst a recursive feature elimination (RFE) based variable selection workflowled to slight reductions in accuracy with the benefit of increased interpretability.

Mapping quantitative trait loci for seminal root angle in a selected durum wheat population.

Seminal root angle (SRA) is an important root architectural trait associated with drought adaptation in cereal crops. To date, all attempts to dissect the genetic architecture of SRA in durum wheat (Triticum durum Desf.) have used large association panels or structured mapping populations.

From Prototype to Inference: A Pipeline to Apply Deep Learning in Sorghum Panicle Detection.

Head (panicle) density is a major component in understanding crop yield, especially in crops that produce variable numbers of tillers such as sorghum and wheat. Use of panicle density both in plant breeding and in the agronomy scouting of commercial crops typically relies on manual counts observation, which is an inefficient and tedious process. Because of the easy availability of red-green-blue images, machine learning approaches have been applied to replacing manual counting.

Challenges and opportunities in remote sensing-based crop monitoring: a review.

Building a more resilient food system for sustainable development and reducing uncertainty in global food markets both require concurrent and near-real-time and reliable crop information for decision making. Satellite-driven crop monitoring has become a main method to derive crop information at local, regional, and global scales by revealing the spatial and temporal dimensions of crop growth status and production. However, there is a lack of quantitative, objective, and robust methods to ensure the reliability of crop information, which reduces the applicability of crop monitoring and leads to uncertain and undesirable consequences.

A cross-scale analysis to understand and quantify the effects of photosynthetic enhancement on crop growth and yield across environments.

Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of individual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state-of-the-art cross-scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme-limited (A ) and electron transport-limited (A ) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear-by-location crop growth simulations.

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency.

Leaf width was correlated with plant-level transpiration efficiency and associated with 19 QTL in sorghum, suggesting it could be a surrogate for transpiration efficiency in large breeding program. Enhancing plant transpiration efficiency (TE) by reducing transpiration without compromising photosynthesis and yield is a desirable selection target in crop improvement programs. While narrow individual leaf width has been correlated with greater intrinsic water use efficiency in C species, the extent to which this translates to greater plant TE has not been investigated.

Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum.

Sorghum, a genetically diverse C cereal, is an ideal model to study natural variation in photosynthetic capacity. Specific leaf nitrogen (SLN) and leaf mass per leaf area (LMA), as well as, maximal rates of Rubisco carboxylation ( ), phosphoenolpyruvate (PEP) carboxylation ( ), and electron transport ( ), quantified using a C photosynthesis model, were evaluated in two field-grown training sets ( = 169 plots including 124 genotypes) in 2019 and 2020. Partial least square regression (PLSR) was used to predict ( = 0.

The association between weather and crime in a township setting in South Africa.

The association between various meteorological parameters and crime is well-established in developed contexts. In contrast in this study, we investigated the association between three weather parameters (temperature, relative humidity and rainfall) and three categories of crime in the developing township of Khayelitsha, in the Western Cape Province of South Africa. Distributed lag non-linear modelling was used to identify temporal relationships between temperature, relative humidity and rainfall, and violent, property and sexual crime over a 10-year period (2006-2016).

Modelling Representative Population Mobility for COVID-19 Spatial Transmission in South Africa.

The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. To understand the spread, a comprehension of human mobility patterns is needed.

Genetic control of leaf angle in sorghum and its effect on light interception.

Developing sorghum genotypes adapted to different light environments requires understanding of a plant's ability to capture light, determined through leaf angle specifically. This study dissected the genetic basis of leaf angle in 3 year field trials at two sites, using a sorghum diversity panel (729 accessions). A wide range of variation in leaf angle with medium heritability was observed.

Genetic Characterisation of South African and Mozambican Bovine Rotaviruses Reveals a Typical Bovine-like Artiodactyl Constellation Derived through Multiple Reassortment Events.

This study presents whole genomes of seven bovine rotavirus strains from South Africa and Mozambique. Double-stranded RNA, extracted from stool samples without prior adaptation to cell culture, was used to synthesise cDNA using a self-annealing anchor primer ligated to dsRNA and random hexamers. The cDNA was subsequently sequenced using an Illumina MiSeq platform without prior genome amplification.

Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery.

In plant breeding, unmanned aerial vehicles (UAVs) carrying multispectral cameras have demonstrated increasing utility for high-throughput phenotyping (HTP) to aid the interpretation of genotype and environment effects on morphological, biochemical, and physiological traits. A key constraint remains the reduced resolution and quality extracted from "stitched" mosaics generated from UAV missions across large areas. This can be addressed by generating high-quality reflectance data from a single nadir image per plot.

Scaling up high-throughput phenotyping for abiotic stress selection in the field.

High-throughput phenotyping (HTP) is in its infancy for deployment in large-scale breeding programmes. With the ability to measure correlated traits associated with physiological ideotypes, in-field phenotyping methods are available for screening of abiotic stress responses. As cropping environments become more hostile and unpredictable due to the effects of climate change, the need to characterise variability across spatial and temporal scales will become increasingly important.

African horse sickness virus NS4 protein is an important virulence factor and interferes with JAK-STAT signaling during viral infection.

African horse sickness virus (AHSV) non-structural protein NS4 is a nucleocytoplasmic protein that is expressed in the heart, lung, and spleen of infected horses, binds dsDNA, and colocalizes with promyelocytic leukemia nuclear bodies (PML-NBs). The aim of this study was to investigate the role of AHSV NS4 in viral replication, virulence and the host immune response. Using a reverse genetics-derived virulent strain of AHSV-5 and NS4 deletion mutants, we showed that knockdown of NS4 expression has no impact in cell culture, but results in virus attenuation in infected horses.

High-Throughput Phenotyping of Dynamic Canopy Traits Associated with Stay-Green in Grain Sorghum.

Drought is a recurring phenomenon that puts crop yields at risk and threatens the livelihoods of many people around the globe. Stay-green is a drought adaption phenotype found in sorghum and other cereals. Plants expressing this phenotype show less drought-induced senescence and maintain functional green leaves for longer when water limitation occurs during grain fill, conferring benefits in both yield and harvestability.

Genetic characterisation of novel G29P[14] and G10P[11] rotavirus strains from African buffalo.

We report the first description of rotavirus A strains in African buffalo (Syncerus caffer). Following RNA extraction from stool samples, cDNA was prepared, followed either by sequence-independent amplification and 454 pyrosequencing or direct sequencing on an Illumina MiSeq platform. RVA/Buffalo-wt/ZAF/4426/2002/G29P[14] exhibited a novel G29P[14] combination and an artiodactyl backbone: I2-R2-C2-M2-A11-N2-T6-E2-H3.

African horse sickness virus NS4 is a nucleocytoplasmic protein that localizes to PML nuclear bodies.

African horse sickness virus (AHSV) is the causative agent of the often fatal disease African horse sickness in equids. The non-structural protein NS4 is the only AHSV protein that localizes to the nucleus. Here we report that all AHSV reference and representative field strains express one of the two forms of NS4, i.

Metabolic surgery in South Africa: an initial academic hospital experience.

Background: In South Africa, 42.0% of adult females and 13.5% of adult males are classified as obese, the highest recorded numbers in Sub-Saharan Africa.

A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting.

The yield of cereal crops such as sorghum ( L. Moench) depends on the distribution of crop-heads in varying branching arrangements. Therefore, counting the head number per unit area is critical for plant breeders to correlate with the genotypic variation in a specific breeding field.

Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops.

Plant phenotyping forms the core of crop breeding, allowing breeders to build on physiological traits and mechanistic science to inform their selection of material for crossing and genetic gain. Recent rapid progress in high-throughput techniques based on machine vision, robotics, and computing (plant phenomics) enables crop physiologists and breeders to quantitatively measure complex and previously intractable traits. By combining these techniques with affordable genomic sequencing and genotyping, machine learning, and genome selection approaches, breeders have an opportunity to make rapid genetic progress.

Quantitative RT-PCR assays for identification and typing of the Equine encephalosis virus.

Equine encephalosis (EE) is an acute, arthropod-borne, noncontagious, febrile disease of equids. The clinical signs of EE are similar to milder forms of African horse sickness (AHS) and the two diseases can be easily confused. The Equine encephalosis virus (EEV) is a distinct virus species within the genus Orbivirus, family Reoviridae, with ten linear segments of dsRNA genome.

Aerial Imagery Analysis - Quantifying Appearance and Number of Sorghum Heads for Applications in Breeding and Agronomy.

Sorghum ( L. Moench) is a C4 tropical grass that plays an essential role in providing nutrition to humans and livestock, particularly in marginal rainfall environments. The timing of head development and the number of heads per unit area are key adaptation traits to consider in agronomy and breeding but are time consuming and labor intensive to measure.

Multi-Spectral Imaging from an Unmanned Aerial Vehicle Enables the Assessment of Seasonal Leaf Area Dynamics of Sorghum Breeding Lines.

Genetic improvement in sorghum breeding programs requires the assessment of adaptation traits in small-plot breeding trials across multiple environments. Many of these phenotypic assessments are made by manual measurement or visual scoring, both of which are time consuming and expensive. This limits trial size and the potential for genetic gain.