ORCID Profile
0000-0002-7671-8292
Current Organisations
CSIRO Queensland Bioscience Precinct
,
CSIRO
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Wiley
Date: 05-2001
Publisher: Elsevier BV
Date: 12-2014
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15400
Abstract: Our capacity to measure performance- and efficiency-related phenotypes in grazing livestock in a timely manner, ideally in real-time without human interference, has been severely limited. Future demands and constraints on grazing livestock production will require a step change beyond our current approaches to obtaining phenotypic data. Animal phenomics is a relatively new term that describes the next generation of animal trait measurement, including methodologies and equipment used to acquire data on traits, and computational approaches required to turn data into phenotypic information. Phenomics offers a range of emerging opportunities to define new traits specific to grazing livestock, including intake and efficiency at pasture, and to measure many traits simultaneously or at a level of detail previously unachievable in the grazing environment. Application of this approach to phenotyping can improve the precision with which nutritional and other management strategies are applied, enable development of predictive biological traits, and accelerate the rate at which genetic gain is achieved for existing and new traits. In the present paper, we briefly outline the potential for livestock phenomics and describe (1) on-animal sensory-based approaches to develop traits diagnostic of productivity and efficiency, as well as resilience, health and welfare and (2) on-farm methods for data collection that drive management solutions to reduce input costs and accelerate genetic gain. The technological and analytical challenges associated with these objectives are also briefly considered, along with a brief overview of a promising field of work in which phenomics will affect animal agriculture, namely efficiency at pasture.
Publisher: Elsevier BV
Date: 08-2021
Publisher: Elsevier BV
Date: 2016
DOI: 10.1016/J.TIBTECH.2015.10.004
Abstract: Radiative forcing of methane (CH4) is significantly higher than carbon dioxide (CO2) and its enteric production by ruminant livestock is one of the major sources of greenhouse gas emissions. CH4 is also an important marker of farming productivity, because it is associated with the conversion of feed to product in livestock. Consequently, measurement of enteric CH4 is emerging as an important research topic. In this review, we briefly describe the conversion of carbohydrate to CH4 by the bacterial community within gut, and highlight some of the key host-microbiome interactions. We then provide a picture of current progress in techniques for measuring enteric CH4, the context in which these technologies are used, and the challenges faced. We also discuss solutions to existing problems and new approaches currently in development.
Publisher: Elsevier BV
Date: 04-2020
Publisher: Informa UK Limited
Date: 1998
Publisher: No publisher found
Date: 2016
Publisher: Elsevier BV
Date: 2010
Publisher: IEEE
Date: 07-2023
Publisher: Elsevier BV
Date: 09-2009
Publisher: MDPI AG
Date: 13-05-2009
DOI: 10.3390/S90503586
Publisher: Elsevier BV
Date: 12-2010
Publisher: Elsevier BV
Date: 10-2016
Publisher: ACM
Date: 06-11-2007
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 1996
Publisher: Elsevier BV
Date: 03-2018
Publisher: ACM
Date: 14-10-2022
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN14368
Abstract: Monitoring and management of grazing livestock production systems can be enhanced with remote monitoring technologies collecting information with high temporal and spatial detail. However, the potential benefits of such technologies have yet to be realised and challenges still exist with hardware, and data analysis and interpretation. The objective of this paper was to propose analytical methods and demonstrate the value of remotely collected liveweight (LW) and behaviour of beef cattle grazing tropical pastures. Three remote weighing systems were set up at the water troughs to capture LW of three groups of 20 animals for 341 days. LW data reflected short-term effects following the first rain event ( mm) at the end of the dry season, which resulted in LW losses of 22 ± 8.8 kg of LW at a rate of –1.54 ± 0.46 kg/day (n = 60). This period was followed by a peak daily LW change (LWC) of +2 kg/day. The remote weighing system also captured longer environmental effects related to seasonal changes in forage quality and quantity with highest LWC during the wet season and weight loss during the dry season. Effects of management on LW and LWC were observed as a result of moving animals to paddocks with more edible forage during the dry season when the negative trend in LWC was reversed after rotating animals. Behavioural monitoring indicated that resting and ruminating took place at c ing sites, and foraging resulted in grazing hotspots. Remotely collected LW data captured both short- and long-term temporal changes associated with environmental and management factors, whereas remote monitoring collars captured the spatial distribution of behaviours in the landscape. Wireless sensor networks have the ability to provide data with sufficient detail in real-time making it possible for increased understanding of animal biology and early management interventions that should result in increased production, animal welfare and environmental stewardship.
Publisher: Elsevier BV
Date: 03-2023
Publisher: Springer Science and Business Media LLC
Date: 08-2021
DOI: 10.1186/S40317-021-00248-W
Abstract: Agriculture is becoming increasingly reliant upon accurate data from sensor arrays, with localization an emerging application in the livestock industry. Ground-based time difference of arrival (TDoA) radio location methods have the advantage of being lightweight and exhibit higher energy efficiency than methods reliant upon Global Navigation Satellite Systems (GNSS). Such methods can employ small primary battery cells, rather than rechargeable cells, and still deliver a multi-year deployment. In this paper, we present a novel deep learning algorithm adapted from a one-dimensional implementing a convolutional neural network (CNN) model, originally developed for the task of semantic segmentation. The presented model () both converts TDoA sequences directly to positions and reduces positional errors introduced by sources such as multipathing. We have evaluated the model using simulated animal movements in the form of TDoA position sequences in combination with real-world distributions of TDoA error. These animal tracks were simulated at various step intervals to mimic potential TDoA transmission intervals. We compare to a Kalman filter to evaluate the performance of our algorithm to a more traditional noise reduction approach. On average, for simulated tracks having added noise with a standard deviation of 50 m, the described approach was able to reduce localization error by between 66.3% and 73.6%. The Kalman filter only achieved a reduction of between 8.0% and 22.5%. For a scenario with larger added noise having a standard deviation of 100 m, the described approach was able to reduce average localization error by between 76.2% and 81.9%. The Kalman filter only achieved a reduction of between 31.0% and 39.1%. Results indicate that this novel 1D CNN like encoder/decoder for TDoA location error correction outperforms the Kalman filter. It is able to reduce average localization errors to between 16 and 34 m across all simulated experimental treatments while the uncorrected average TDoA error ranged from 55 to 188 m.
Publisher: Wiley
Date: 05-2013
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 2019
Publisher: IEEE
Date: 11-2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2007
DOI: 10.1109/MPRV.2007.47
Publisher: Elsevier BV
Date: 03-2007
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/CP16383
Abstract: Practical and reliable measurement of pasture intake by in idual animals will enable improved precision in livestock and pasture management, provide input data for prediction and simulation models, and allow animals to be ranked on grazing efficiency for genetic improvement. In this study, we assessed whether pasture intake of in idual grazing cattle could be estimated from time spent exhibiting behaviours as determined from data generated by on-animal sensor devices. Variation in pasture intake was created by providing Angus steers (n = 10, mean ± s.d. liveweight 650 ± 77 kg) with differing amounts of concentrate supplementation during grazing within in idual ryegrass plots (≤0.22 ha). Pasture dry matter intake (DMI) for the steers was estimated from the slope (kg DM day–1) of the regression of total pasture DM per plot on intake over an 11-day period. Pasture DM in each plot, commencing with ≤2 t DM ha–1, was determined by using repeatedly calibrated pasture height and electronic rising plate meters. The amounts of time spent grazing, ruminating, walking and resting were determined for the 10 steers by using data from collar-mounted, inertial measurement units and a previously developed, highly accurate, behaviour classification model. An initial pasture intake algorithm was established for time spent grazing: pasture DMI (kg day–1) = –4.13 + 2.325 × hours spent grazing (P = 0.010, r2 = 0.53, RSD = 1.65 kg DM day–1). Intake algorithms require further development, validation and refinement under varying pasture conditions by using sensor devices to determine specific pasture intake behaviours coupled with established methods for measuring pasture characteristics and grazing intake and selectivity.
Publisher: Wiley
Date: 16-11-2016
DOI: 10.1111/JPN.12640
Abstract: This study used a systematic literature review methodology to determine whether there is evidence that drinking frequency has effects on cattle performance, what performance responses to drinking frequency are documented and how performance responses vary according to environmental and animal factors. Electronic databases were searched for English language articles with original data on at least one performance attribute (e.g. water intake, feed intake, live weight) of cattle in response to voluntary drinking frequency or controlled access periods to water. Sixteen experiments on dairy cows and 12 experiments on beef cattle were retrieved from the literature. For beef cattle, all experiments reported reduced water and feed intake with access to water once every second and/or third day compared with once-daily access. Median reductions of 15% and 25% in water intake and 16% and 9% in feed intake were found across experiments respectively. Live weight responses of beef cattle to access to water were limited and yielded positive, negative and no effects. For dairy cows, most experiments reported reduced water intake, milk yield and milk fat content with access to water twice or once daily compared with controls (ad libitum or ad libitum except at the dairy). Median reductions of 13% and 12% in water intake, 2% and 1% in milk yield and 1% and 2% in milk fat content were found across experiments respectively. Water availability effects on feed intake and live weight were very limited for dairy cows and yielded positive, neutral and negative effects. Season, climate, experiment conditions, animal class and animal genotype were identified to potentially influence intake responses of cattle. The review highlights a number of important gaps in the literature where future work is required to better understand the optimum drinking frequency of cattle and implications of water availability on health, welfare and performance.
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15581
Abstract: An intra-rumen (IR) gas-sensing system incorporating commercially available gas sensors [methane (CH4), carbon dioxide (CO2) and hydrogen (H2)] and a wireless sensor network was developed to measure rumen gas concentrations of grazing animals in real-time. The IR gas-sensing devices also measure temperature and pressure near the sensors and the design isolates the electronics and battery from exposure to gases. Membranes were developed that allow the desired gases to diffuse through to the sensors while excluding corrosive hydrogen sulfide (H2S). Performance of the prototype IR devices was tested in cattle and sheep fed once a day as a proof-of-concept. Concentrations of expired gases from respiration chambers were compared with the concentrations obtained by the IR gas-sensing device within the rumen digesta. Direct measurements of rumen gas cap s les demonstrate a similar gas profile to that observed with the IR gas-sensing device with the ratio of CO2 : CH4 peaking shortly after feeding and CO2 levels nearly 2.5 times greater than those of CH4. The gas ratio then declines over time to a point when at 23 h post-feeding the concentration of CH4 exceeds that of CO2. The H2 gas concentration in the rumen varied throughout the day reaching maximum levels of 2500 ppm after feeding and declining to 250 ppm over the day. Although the IR device was able to detect H2 in the rumen throughout the entire day, expired H2 was often below the limits of detection in the respiration chamber. Current work is focussed on extending the longevity of the devices in the rumen so that replicated trials can be performed on the accuracy and precision of the measurements.
Publisher: Springer Science and Business Media LLC
Date: 25-10-2005
Publisher: Wiley
Date: 2015
Abstract: Enteric methane (CH) emission from cattle is a source of greenhouse gas and is an energy loss that contributes to production inefficiency for cattle. Direct measurements of enteric CH emissions are useful to quantify the magnitude and variation and to evaluate mitigation of this important greenhouse gas source. The objectives of this study were to evaluate the impact of stocking density of cattle and source configuration (i.e., point source vs. area source and elevation of area source) on CH emissions from grazing beef cattle in Queensland, Australia. This was accomplished using nonintrusive atmospheric measurements and a gas dispersion model. The average measured CH emission for the point and area source was between 240 and 250 g animal d over the entire study. There was no difference ( > 0.05) in emission when using an elevated area source (0.5 m) or a ground area source (0 m). For the point-source configuration, there was a difference in CH emission due to stocking density likewise, some differences existed for the area-source emissions. This study demonstrates the flexibility of the area-source configuration of the dispersion model to estimate CH emissions even at a low stocking density.
Publisher: CSIRO Publishing
Date: 2018
DOI: 10.1071/RJ17092
Abstract: The distance travelled by an animal, when determined by using global positioning system (GPS) coordinates, is usually calculated assuming linear movement between the recorded coordinates. When using long s le intervals, some movement may be overlooked if linear movement between each recorded position is assumed, because of the tendency of livestock to move in meandering paths. Conversely, overestimation of the true distance travelled could occur with short s le intervals because of the accumulation of extra distance due to GPS measurement error. Data from 10 experiments were used to explore the effect of paddock size and GPS s ling rate on the calculation of distance travelled by free-ranging cattle. Shortening the s le interval increased apparent distance travelled according to a power function. As paddock size increased from ha to ha, distance travelled increased according to a logarithmic relationship however, other variation between experiments could have affected these results. It was concluded that selecting an optimal GPS s ling interval is critical to accurately determining the distance travelled by free-ranging cattle.
Publisher: Elsevier BV
Date: 06-2003
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier BV
Date: 05-2015
Publisher: CSIRO Publishing
Date: 2011
DOI: 10.1071/AN10255
Abstract: Since the late 1980s, satellite-based global positioning systems (GPS) have provided unique and novel data that have been used to track animal movement. Tracking animals with GPS can provide useful information, but the cost of the technology often limits experimental replication. Limitations on the number of devices available to monitor the behaviour of animals, in combination with technical constraints, can weaken the statistical power of experiments and create significant experimental design challenges. The present paper provides a review and synthesis of using GPS for livestock-based studies and suggests some future research directions. Wildlife ecologists working in extensive landscapes have pioneered the use of GPS-based devices for tracking animals. Wildlife researchers have focussed efforts on quantifying and addressing issues associated with technology limitations, including spatial accuracy, rate of data collection, battery life and environmental factors causing loss of data. It is therefore not surprising that there has been a significant number of methodological papers published in the literature that have considered technical developments of GPS-based animal tracking. Livestock scientists have used GPS data to inform them about behavioural differences in free-grazing experiments. With a shift in focus from the environment to the animal comes the challenge of ensuring independence of the experimental unit. Social facilitation challenges independence of the in idual in a group. The use of spatial modelling methods to process GPS data provides an opportunity to determine the degree of independence of data collected from an in idual animal within behavioural-based studies. By using location and movement information derived from GPS data, researchers have been able to determine the environmental impact of grazing animals as well as assessing animal responses to management activities or environmental perturbations. Combining satellite-derived remote-sensing data with GPS-derived landscape preference indices provides a further opportunity to identify landscape avoidance and selection behaviours. As spatial livestock monitoring tools become more widely used, there will be a greater need to ensure the data and associated processing methods are able to answer a broader range of questions. Experimental design and analytical techniques need to be given more attention if GPS technology is to provide answers to questions associated with free-grazing animals.
Publisher: Elsevier BV
Date: 12-2016
Publisher: Elsevier BV
Date: 1996
Publisher: Copernicus GmbH
Date: 22-08-2016
Abstract: Abstract. Timely and accurate monitoring of pasture biomass and ground cover is necessary in livestock production systems to ensure productive and sustainable management. Interest in the use of proximal sensors for monitoring pasture status in grazing systems has increased, since data can be returned in near real time. Proximal sensors have the potential for deployment on large properties where remote sensing may not be suitable due to issues such as spatial scale or cloud cover. There are unresolved challenges in gathering reliable sensor data and in calibrating raw sensor data to values such as pasture biomass or vegetation ground cover, which allow meaningful interpretation of sensor data by livestock producers. Our goal was to assess whether a combination of proximal sensors could be reliably deployed to monitor tropical pasture status in an operational beef production system, as a precursor to designing a full sensor deployment. We use this pilot project to (1) illustrate practical issues around sensor deployment, (2) develop the methods necessary for the quality control of the sensor data, and (3) assess the strength of the relationships between vegetation indices derived from the proximal sensors and field observations across the wet and dry seasons. Proximal sensors were deployed at two sites in a tropical pasture on a beef production property near Townsville, Australia. Each site was monitored by a Skye SKR-four-band multispectral sensor (every 1 min), a digital camera (every 30 min), and a soil moisture sensor (every 1 min), each of which were operated over 18 months. Raw data from each sensor was processed to calculate multispectral vegetation indices. The data capture from the digital cameras was more reliable than the multispectral sensors, which had up to 67 % of data discarded after data cleaning and quality control for technical issues related to the sensor design, as well as environmental issues such as water incursion and insect infestations. We recommend having a system with both sensor types to aid in data interpretation and troubleshooting technical issues. Non-destructive observations of pasture characteristics, including above-ground standing biomass and fractional ground cover, were made every 2 weeks. This simplified data collection was designed for multiple years of s ling at the remote site, but had the disadvantage of high measurement uncertainty. A bootstrapping method was used to explore the strength of the relationships between sensor and pasture observations. Due to the uncertainty in the field observations, the relationships between sensor and field data are not confirmational and should be used only to inform the design of future work. We found the strongest relationships occurred during the wet season period of maximum pasture growth (January to April), with generally poor relationships outside of this period. Strong relationships were found with multispectral indices that were sensitive to the green and dry components of the vegetation, such as those containing the band in the lower shortwave infrared (SWIR) region of the electromagnetic spectrum. During the wet season the bias-adjusted bootstrap point estimate of the R2 between above-ground biomass and the normalized ratio between the SWIR and red bands (NVI-SR) was 0.72 (95 % CI of 0.28 to 0.98), while that for the percentage of green vegetation observed in three dimensions and a simple ratio between the near infrared and SWIR bands (RatioNS34) was 0.81 (95 % CI of 0.53 to 1.00). Relationships between field data and the vegetation index derived from the digital camera images were generally weaker than from the multispectral sensor data, except for green vegetation observations in two and three dimensions. Our successful pilot of multiple proximal sensors supports the design of future deployments in tropical pastures and their potential for operational use. The stringent rules we developed for data cleaning can be more broadly applied to other sensor projects to ensure quality data. Although proximal sensors observe only a small area of the pasture, they deliver continual and timely pasture measurements to inform timely on-farm decision-making.
Publisher: Wiley
Date: 07-2003
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2009
DOI: 10.1109/MPRV.2009.15
Publisher: Elsevier BV
Date: 2018
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/AN17052
Abstract: Accelerometers have been used to record many cattle postures and behaviours including standing, lying, walking, grazing and ruminating but not cattle drinking behaviour. This study explores whether neck-mounted triaxial accelerometers can identify drinking and whether head-neck position and activity can be used to record drinking. Over three consecutive days, data were collected from 12 yearling Brahman cattle each fitted with a collar containing an accelerometer. Each day the cattle were herded into a small yard containing a water trough and allowed 5 min to drink. Drinking, standing (head up), walking and standing (head down) were recorded. Examination of the accelerometer data showed that drinking events were characterised by a unique signature compared with the other behaviours. A linear mixed-effects model identified two variables that reflected differences in head-neck position and activity between drinking and the other behaviours: mean of the z- (front-to-back) axis and variance of the x- (vertical) axis (P & 0.05). Threshold values, derived from Kernel density plots, were applied to classify drinking from the other behaviours using these two variables. The method accurately classified drinking from standing (head up) with 100% accuracy, from walking with 92% accuracy and from standing (head down) with 79% accuracy. The study shows that accelerometers have the potential to record cattle drinking behaviour. Further development of a classification method for drinking is required to allow accelerometer-derived data to be used to improve our understanding of cattle drinking behaviour and ensure that their water intake needs are met.
Publisher: Elsevier BV
Date: 04-2023
Publisher: IEEE
Date: 11-2015
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 02-2015
Publisher: Elsevier BV
Date: 2007
Publisher: FapUNIFESP (SciELO)
Date: 12-2010
DOI: 10.1590/S1415-43662010001200012
Abstract: Objetivou-se, com este trabalho, analisar os efeitos ambientais sobre o desempenho produtivo de frangos de corte comerciais, criados em dois aviários, localizados na região semiárida paraibana, em condições de verão, sendo um com cobertura de telha de cerâmica e outro coberto com telha de fibrocimento. Não houve diferença significativa entre os galpões (P 0,05) para temperatura e umidade relativa do ar, índice de temperatura de globo negro e umidade, carga térmica de radiação e a velocidade do vento e os galpões proporcionaram, nos horários considerados mais quentes do dia (10 às 16 h), valores médios considerados acima da zona de conforto, causando situação de desconforto para as aves, mas não influenciaram no seu desempenho produtivo. A temperatura da água nos dois galpões foi superior à recomendada, mas também não influenciou no desempenho produtivo. O nível de pressão sonora dentro dos aviários não causou desconforto às aves nem aos trabalhadores.
Publisher: Elsevier BV
Date: 04-2008
Publisher: Elsevier BV
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 22-06-2015
DOI: 10.1038/SREP11515
Abstract: Unique in vivo tests were conducted through the use of a fistulated ruminant, providing an ideal environment with a erse and vibrant microbial community. Utilizing such a procedure can be especially invaluable for investigating the performance of antimicrobial materials related to human and animal related infections. In this pilot study, it is shown that the rumen of a fistulated animal provides an excellent live laboratory for assessing the properties of antimicrobial materials. We investigate microbial colonization onto model nanocomposites based on silver (Ag) nanoparticles at different concentrations into polydimethylsiloxane (PDMS). With implantable devices posing a major risk for hospital-acquired infections, the present study provides a viable solution to understand microbial colonization with the potential to reduce the incidence of infection through the introduction of Ag nanoparticles at the optimum concentrations. In vitro measurements were also conducted to show the validity of the approach. An optimal loading of 0.25 wt % Ag is found to show the greatest antimicrobial activity and observed through the in vivo tests to reduce the microbial ersity colonizing the surface.
Publisher: ACM
Date: 06-12-2016
Publisher: Elsevier BV
Date: 07-2015
Publisher: Wiley
Date: 05-2003
Publisher: Elsevier BV
Date: 2020
Publisher: Elsevier BV
Date: 05-2011
Publisher: CSIRO Publishing
Date: 2009
DOI: 10.1071/RJ07070
Abstract: With the commercial development of the global positioning system (GPS), it is now possible to monitor the distribution of free ranging cattle and derive measures to describe landscape use. Animal GPS data can be integrated with a geographic information system (GIS) detailing topography, vegetation, soil type and other landscape features. Combining GPS and GIS information is useful for understanding how animals respond to spatial variability. This study quantified land-type preferences for Brahman cross steers over three time periods, from October 2004 to March 2006 in a replicated trial, under heavy (4 ha/AE animal equivalent of ~450 kg steer) and light (8 ha/AE) stocking in four, ~105 ha paddocks of subtropical semi-arid savanna near Charters Towers, Queensland, Australia. The grazing trail was conducted at a scale much less than would be found in commercial situations. Consequently, the spatial pattern of cattle reported here may not represent what occurs at a commercial scale and implications are discussed. Results were analysed in terms of the spatial distribution of steers fitted with GPS devices in each of the four paddocks and for each stocking rate to provide insight into cattle distribution and land-type preferences. Steers walked in excess of 6 km per day, regardless of stocking rate, and exhibited diurnal patterns of movement, with peak activity around dawn (0500–0700 hours) and dusk (1800–2000 hours). The spatial distribution of the collared steers was not uniform and appeared to be strongly influenced by the prevailing drought conditions and location of water points within each paddock. A hierarchy of drivers for distribution was identified. With the exception of drinking water location, land subtype based on soil-vegetation associations influenced animal distribution. Preference indices (ŵi) indicated that steers selected sites associated with heavy clay and texture contrast soils dominated by Eucalyptus coolabah Blakely & Jacobs (ŵi = 5.33) and Eucalyptus brownii Maiden & Cambage (ŵi = 3.27), respectively, and avoiding Eucalyptus melanophloia F.Muell. ridges (ŵi = 0.26) and Eucalyptus cambageana Maiden (ŵi = 0.12) on sodosols. The results suggest that spatial variation in cattle distribution within a paddock may be more critical than overall stocking rate in influencing the pattern of biomass utilisation. However, to quantifying the effects of different grazing land management practices on animal distribution on a commercial scale, additional studies in extensive paddocks are required.
Publisher: CSIRO Publishing
Date: 2023
DOI: 10.1071/AN23045
Publisher: Elsevier BV
Date: 10-2010
Location: Australia
No related grants have been discovered for Gregory Bishop-Hurley.