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Dive into the research topics where Don Menzies is active.

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Featured researches published by Don Menzies.


Electronic Commerce Research and Applications | 2003

Reasons why farmers in Australia adopt the Internet

John Rolfe; Shirley Gregor; Don Menzies

Abstract Landholders in rural Australia are increasing their use of computers and the Internet. In part, this is because of the increased availability of hardware, software and communications infrastructure at reasonable cost. However, it is unclear what all the benefits of adopting a new technology are. It may be that the primary benefits are simply cost reduction; for example, the time saved in financial bookkeeping. Other reasons might include potential gains to production, keeping pace with regulatory and other external changes, or improved marketing opportunities. These issues are explored in relation to the grains and beef industries of the Central Queensland region.


Animal Production Science | 2017

Using temporal associations to determine maternal parentage in extensive beef herds

Don Menzies; Kym P. Patison; N. J. Corbet; Dave Swain

The assignment of maternal parentage, although time-consuming and expensive using traditional methods, is essential for genetic improvement. Within the sheep industry the recording of time-based (temporal) associations without human intervention has been routinely used to derive maternal parentage, however it has not been researched in extensive beef production systems. To determine whether temporal associations could be used to assign maternal parentage, cows and calves had their identity recorded as they walked to water over a 27-day trial. Two methods of association were investigated, being the half-weight index and the time difference between a cow and calf having their identity recorded. The half-weight index, which is a measure of the number of times two individuals are recorded together, correctly assigned greater than 90% of maternal pairs. When investigating the duration of data recording it was shown that 85% of maternal parentage could be achieved within only 21 days. Further work is required to determine the effect of calf age, herd and paddock size; however, the results showed that the half-weight index method of determining maternal associations is a labour-saving and accurate alternative to traditional methods used to identify maternal parentage.


Computers and Electronics in Agriculture | 2016

A scoping study to assess the precision of an automated radiolocation animal tracking system

Don Menzies; Kym P. Patison; David R. Fox; Dave Swain

The mean spatial precision for the ARATS ear tags was ?22m.Signal propagation effects and meteorological parameters affected spatial precision.The time between transmissions showed no effect on the spatial precision. The spatial precision of a new automated radiolocation animal tracking system (ARATS) was studied in a small-scale (~5ha) trial site. Twelve static tags, in a four by three grid, transmitted for 28days. The 12 tags recorded 36,452 transmissions with a mean transmission per tag of 3037. Each transmission included the tag number, date and time and the calculated longitude and latitude. The mean location and then the Euclidean distance from the mean location for each tag were calculated in order to derive location precision per tag. The overall precision for the 12 tags was ?22m with a SD of 49m with the most and least precise tags having precisions of ?8m and ?51m, respectively. As with other geolocation technologies, it would appear that structures in the environment cause signal propagation effects including multipath and non-line-of-sight, which result in errors in the derived locations.The distance from the mean data was log transformed (log10) and summarised in order to present all data over a 24-h period. There was a statistically significant decrease in precision between 11:00 and 17:00h. These data were correlated with meteorological parameters for the period of the trial, again summarised over 24h, with temperature, humidity, wind speed and pressure all having significant correlations with the precision data.The variance between individual tag transmissions were compared to see whether the distance between derived locations increased as time between transmissions increased. The means for each tag showed the same variance as the mean precision values, that is the more precise tags had lower means and the less precise tags had higher means. However, no tags showed a trend towards an increase in the distance between locations as the time between transmissions increased.In order to assess whether there was any spatial variability in the derived locations, the variability in distance between tags was compared for all tag combinations. Tags that were proximal to each other had shorter distances between the mean derived locations and less variance, whereas tags farther apart had large distances and large variance in the mean derived locations.The ARATS assessed in this static evaluation showed a lower level of spatial precision than commercially available global positioning systems. However the system could still have application when used to derive proximal associations between animals in low stocking-rate, extensive grazing situations such as are present in northern Australia.


Animal Production Science | 2018

Using temporal associations to determine postpartum oestrus in tropical beef cows

N. J. Corbet; Kym P. Patison; Don Menzies; Dave Swain

The radio frequency identification (RFID) technology introduced with the National Livestock Identification System has increased the precision of livestock management. Tag readers incorporated in walk-over-weighing systems have enabled automated collection of daily RFID sequential data as cattle access water. The temporal sequence of individuals accessing a watering point in a rangeland grazing system could potentially provide knowledge of key aspects of animal behaviour. The current study investigated the use of the shortest daily average interval of time from cow to bull (TTB) coming to water over a 29-day period to predict postpartum oestrus events. Fifteen Brahman and 15 Belmont Red cows mated to bulls of the same breed in separate paddocks were fitted with proximity loggers, heat-mount detectors and were ovarian-scanned with ultrasonics to determine the timing of postpartum oestrus. The data collected from these devices were compared with RFID sequence data of the bulls following cows to water to evaluate whether TTB alone could predict oestrus activity. At the start of the experimental period, mean (±s.d.) weight and days postpartum of the Brahman cows were 527 (±43.4) kg and 89 (±18.4) days respectively, and of the Belmont Red cows 513 (±54.1) kg and averaged 66 (±19.6) days postpartum. Six of the 15 Brahman cows and 9 of the 15 Belmont Red cows displayed oestrus activity, as indicated by increased contact with the bull, an activated heat-mount detector and the presence of an ovarian corpus luteum. The sensitivity and specificity of TTB as an indicator of oestrus events across the groups were 0.65 and 0.60 respectively. Temporal sequence data have the potential to contribute to the determination of oestrus and date of conception.


Animal Production Science | 2017

Using Walk-over-Weighing technology for parturition date determination in beef cattle

Don Menzies; Kym P. Patison; N. J. Corbet; Dave Swain

The northern Australian beef industry is dominated by cow-calf operations where reproductive efficiency is a major profit driver. The postpartum anoestrus interval is a major contributor to an animal’s reproductive efficiency and is influenced by genetic selection. The genetic trait that measures an animal’s postpartum anoestrus interval is the days to calving estimated breeding value and a key requirement is knowledge of the cow’s calving date. Traditionally calving date is recorded using laborious and costly methods that are impeding the recording and hence the accuracy of genetic predictions for this trait by the northern Australian seedstock industry. The present experiment used Walk-over-Weighing technology to automatically record animal weights as cattle enter a restricted area where they access water. With the use of a novel method to accurately assess weights, the growth paths of cows were tracked from late gestation to post-calving. The calving date was visualised in the growth paths of most cows (78.3%) and a custom algorithm was able to automatically detect the calving date within 10 days of the observed calving period for 63% of cows. The use of Walk-over-Weighing to record calving date provides the opportunity to increase the recording of the days to calving estimated breeding value in the northern seedstock industry, thereby increasing reproductive efficiency and improving the profitability of northern beef producers.


28th World Buiatrics Congress | 2014

FACTORS AFFECTING THE EFFICIENCY WITH WHICH BEEF COWS BECOME PREGNANT AFTER CALVING IN NORTHERN AUSTRALIA

M. R. McGowan; Kieren McCosker; Geoffry Fordyce; Dave Smith; Nr Perkins; Peter O’Rourke; T. S. Barnes; Louise Marquart; Don Menzies; Tom Newsome; Di Joyner; N. Phillips; B. M. Burns; J. M. Morton; Sandi Jephcott


ITin Regional Areas Conference 2002, Using IT: Make IT Happen | 2002

Influences on Engagement in ECommerce in Agribusiness: An Empirical Study

Shirley Gregor; Don Menzies; John Rolfe


Northern Beef Research Update Conference (NBRUC 2011) | 2011

Cash Cow-exposing northern breeder herd productivity

Kieren McCosker; M. R. McGowan; Peter O'Rourke; David R. Smith; Geoffry Fordyce; B. M. Burns; Di Joyner; N. Phillips; Don Menzies; Tom Newsome; Nr Perkins; J. M. Morton; Sandi Jephcott


Archive | 2018

Remote calving alert for beef cattle – Technology Development (Phase 3)

Cyril Stephen; Scott Norman; David Swain; Don Menzies; Nick Corbett; Kym P. Patison


Archive | 2015

Remote calving alert for beef cattle: Technology development

Scott Norman; David Swain; Kym P. Patison; Cyril Stephen; Katie Asplin; Jaymie Loy; Don Menzies

Collaboration


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B. M. Burns

University of Queensland

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Kym P. Patison

Central Queensland University

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M. R. McGowan

University of Queensland

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Shirley Gregor

Australian National University

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Dave Swain

Central Queensland University

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John Rolfe

Central Queensland University

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N. J. Corbet

Commonwealth Scientific and Industrial Research Organisation

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Peter O'Rourke

QIMR Berghofer Medical Research Institute

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