Barley grass (Hordeum murinum subsp. glaucum.) is an annual weed associated with grain revenue loss and sheep carcass damage in southern Australia. Increasing herbicide resistance led to a recent investigation into effective integrated weed management strategies for barley grass in southern Australia. Field studies in Wagga Wagga, New South Wales (NSW) during 2016 and 2017 examined the effect of post-emergent herbicide applications and strategic defoliation by mowing on barley grass survival and seed production in a mixed legume pasture. Statistically significant differences between herbicide-only treatments in both years showed propaquizafop to be more than 98% effective in reducing barley grass survival and seed production. Paraquat was not effective in controlling barley grass (58% efficacy), but led to a 36% and 63.5% decrease in clover and other weed biomass, respectively, after 12 months and increased lucerne biomass by over three-fold after 24 months. A single repeated mowing treatment resulted in a 46% decline in barley grass seedling emergence after 12 months and, when integrated with herbicide applications, reduced other weed biomass after 24 months by 95%. Resistance to acetyl-CoA carboxylase (ACCase)-inhibiting herbicides observed in local barley grass populations led to additional and more focused investigation comparing the efficacy of other pre- and post-emergent herbicides for barley grass management in legume pastures. Haloxyfop-R + simazine or paraquat, applied at early tillering stage, were most efficacious in reducing barley grass survival and fecundity. Impact of defoliation timing and frequency on barley grass seedlings was also evaluated at various population densities, highlighting the efficacy of repeated post-inflorescence defoliations in reducing plant survival and seed production. Results highlight the importance of optimal environmental conditions and application timing in achieving efficacious control of barley grass and improving pasture growth and biomass accumulation.

Seed contamination significantly affects production capacity and animal welfare in Australian sheep flocks and causes considerable financial loss to producers and processors across sheepmeat value chains. Seven grass-weed species contribute to seed contamination in Australia, with barley grass (Hordeum spp.) identified as a key perpetrator. Herbicide resistance and variable dormancy emerging in southern Australian barley grass populations are thought to enhance its capacity for successful pasture invasion, further exacerbating the potential for seed contamination in sheep. The present article reviews the current literature regarding the impact and incidence of seed contamination on sheepmeat production, with particular reference to key grass-weed species prevalence across Australia. Data are presented on a recent incidence of carcass contamination across years, where incidence varied between 11% and 80% from 2009 to 2013, contracting to between 2% and 60% during 2014 and 2015. Key areas requiring future research are defined. Understanding the biology of key grass weeds, historical influences and economic consequences associated with seed contamination in sheep may assist in defining future risks to sheep production and improve weed management. Furthermore, examining more recent data describing the current status of seed contamination across Australia and the associations with causal weed species may aid the development of critical weed-management strategies in highly infested regions, subsequently limiting the extent of future seed contamination.

Hawkweeds (Pilosella spp.) have become a severe and rapidly invading weed in pasture lands and forest meadows of New Zealand. Detection of hawkweed infestations is essential for eradication and resource management at private and government levels. This study explores the potential of machine learning (ML) algorithms for detecting mouse-ear hawkweed (Pilosella officinarum) foliage and flowers from Unmanned Aerial Vehicle (UAV)-acquired multispectral (MS) images at various spatial resolutions. The performances of different ML algorithms, namely eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Random Forest (RF), and K-nearest neighbours (KNN), were analysed in their capacity to detect hawkweed foliage and flowers using MS imagery. The imagery was obtained at numerous spatial resolutions from a highly infested study site located in the McKenzie Region of the South Island of New Zealand in January 2021. The spatial resolution of 0.65 cm/pixel (acquired at a flying height of 15 m above ground level) produced the highest overall testing and validation accuracy of 100% using the RF, KNN, and XGB models for detecting hawkweed flowers. In hawkweed foliage detection at the same resolution, the RF and XGB models achieved highest testing accuracy of 97%, while other models (KNN and SVM) achieved an overall model testing accuracy of 96% and 72%, respectively. The XGB model achieved the highest overall validation accuracy of 98%, while the other models (RF, KNN, and SVM) produced validation accuracies of 97%, 97%, and 80%, respectively. This proposed methodology may facilitate non-invasive detection efforts of mouse-ear hawkweed flowers and foliage in other naturalised areas, enabling land managers to optimise the use of UAV remote sensing technologies for better resource allocation.

Hordeum spp. (barley grass) and Bromus spp. (brome grass) are annual weed species that achieve long-distance seed dispersal via attachment to sheep, but also lead to sheep carcass damage due to the penetration of seeds into animal tissues. Range expansion of invasive weed populations predicted as a consequence of climate change may be associated with an increase in seed contamination incidence glob-ally. An examination of Australian abattoir data (2006)(2007)(2008)(2009)(2010)(2011)(2012), along with recent weed distribution patterns, indicates carcass contamination was associated with rainfall and abundance of key annual grass weeds, primarily Bromus spp. and Hordeum spp., although other factors may play a contributing role. Significant differences in seed contamination in slaughtered sheep were noted between states and regions, with widespread contamination occurring throughout all agro-ecological zones. Abattoir, sheep age and sex significantly influenced incidence, with contamination highest in adult males. Incidence increased with mean monthly rainfall, but declined with mean elevation, and significant interactions were noted between mean monthly temperature and state, and between mean elevation and year. Results show the need for vigilant recording of seed injuries in sheep to enhance weed surveillance efforts and effective integrated weed management of contributing annual grass weeds. K E Y W O R D Sannual grass weeds, Bromus, damage, Hordeum, livestock 222 |

Context. Barley grass (Hordeum spp. L.) is an annual, invasive grass weed of southern Australian crops and pastures, frequently associated with weight loss and carcass damage in sheep due to its sharp seeds. Knowledge gaps exist regarding optimal density thresholds for effective control to reduce impacts on animal production. The value of integrated weed management (IWM) over individual control options for reducing barley grass populations in pasture is also unknown. Aims. We aimed to develop a model for simulating the population dynamics of barley grass within lucerne (Medicago sativa L.) pastures of southern Australia and to test the hypothesis that combining herbicides with mowing will be more effective for removing barley grass seedbanks over time than individual control measures. Methods. The model was developed within Microsoft Excel and adapted from other annual grass models. The model takes a Monte Carlo approach to simulate control impacts on weed seedbanks over 10 years using five weed-control density thresholds. It was parameterised using data from recent experiments and available literature. Key results. The most effective long-term control strategy for barley grass occurred with a density threshold of 5 seedlings m −2 by combining early and late herbicide applications, and by combining early and late herbicides with mowing, reducing the seedbank by 86% and 89%, respectively. Conclusions. Simulation results showed that IWM programs were more effective than individual control options in reducing the barley grass seedbanks over 10 years, particularly at low weed densities (≤50 seedlings m −2 ). Implications. Incorporation of this model into a bioeconomic grazing systems model will be valuable for determining the economic impacts and optimal weed-control strategies for minimising the effects of barley grass seed contamination in lamb production systems.