Managing the risk of glyphosate resistance in Australian glyphosate-resistant cotton production systems

BACKGROUND: Glyphosate-resistant cotton varieties are an important tool for weed control in Australian cotton production systems. To increase the sustainability of this technology and to minimise the likelihood of resistance evolving through its use, weed scientists, together with herbicide regulators, industry representatives and the technology owners, have developed a framework that guides the use of the technology. Central to this framework is a crop management plan (CMP) and grower accreditation course. A simulation model that takes into account the characteristics of the weed species, initial gene frequencies and any associated fitness penalties was developed to ensure that the CMP was sufficiently robust to minimise resistance risks. RESULTS: The simulations showed that, when a combination of weed control options was employed in addition to glyphosate, resistance did not evolve over the 30 year period of the simulation. CONCLUSION: These simulations underline the importance of maintaining an integrated system for weed management to prevent the evolution of glyphosate resistance, prolonging the use of glyphosate-resistant cotton.

Long-term trends in fertility of soils under continuous cultivation and cereal cropping in southern Queensland. IX. Simulation of soil carbon and nitrogen pools using CENTURY model

Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.

Simulating the effects of saline and sodic subsoils on wheat crops growing on Vertosols

Soils with high levels of chloride and/or sodium in their subsurface layers are often referred to as having subsoil constraints (SSCs). There is growing evidence that SSCs affect wheat yields by increasing the lower limit of a crop's available soil water (CLL) and thus reducing the soil's plant-available water capacity (PAWC). This proposal was tested by simulation of 33 farmers' paddocks in south-western Queensland and north-western New South Wales. The simulated results accounted for 79% of observed variation in grain yield, with a root mean squared deviation (RMSD) of 0.50 t/ha. This result was as close as any achieved from sites without SSCs, thus providing strong support for the proposed mechanism that SSCs affect wheat yields by increasing the CLL and thus reducing the soil's PAWC. In order to reduce the need to measure CLL of every paddock or management zone, two additional approaches to simulating the effects of SSCs were tested. In the first approach the CLL of soils was predicted from the 0.3-0.5 m soil layer, which was taken as the reference CLL of a soil regardless of its level of SSCs, while the CLL values of soil layers below 0.5 m depth were calculated as a function of these soils' 0.3-0.5 m CLL values as well as of soil depth plus one of the SSC indices EC, Cl, ESP, or Na. The best estimates of subsoil CLL values were obtained when the effects of SSCs were described by an ESP-dependent function. In the second approach, depth-dependent CLL values were also derived from the CLL values of the 0.3-0.5 m soil layer. However, instead of using SSC indices to further modify CLL, the default values of the water-extraction coefficient (kl) of each depth layer were modified as a function of the SSC indices. The strength of this approach was evaluated on the basis of correlation of observed and simulated grain yields. In this approach the best estimates were obtained when the default kl values were multiplied by a Cl-determined function. The kl approach was also evaluated with respect to simulated soil moisture at anthesis and at grain maturity. Results using this approach were highly correlated with soil moisture results obtained from simulations based on the measured CLL values. This research provides strong evidence that the effects of SSCs on wheat yields are accounted for by the effects of these constraints on wheat CLL values. The study also produced two satisfactory methods for simulating the effects of SSCs on CLL and on grain yield. While Cl and ESP proved to be effective indices of SSCs, EC was not effective due to the confounding effect of the presence of gypsum in some of these soils. This study provides the tools necessary for investigating the effects of SSCs on wheat crop yields and natural resource management (NRM) issues such as runoff, recharge, and nutrient loss through simulation studies. It also facilitates investigation of suggested agronomic adaptations to SSCs.

Row spacing and planting density effects on the growth and yield of sugarcane. 2. Strategies for the adoption of controlled traffic.

Controlled traffic (matching wheel and row spacing) is being promoted as a means to manage soil compaction in the Australian sugar industry. However, machinery limitations dictate that wider row spacings than the standard 1.5-m single row will need to be adopted to incorporate controlled traffic and many growers are reluctant to widen row spacing for fear of yield penalties. To address these concerns, contrasting row configuration and planting density combinations were investigated for their effect on cane and sugar yield in large-scale experiments in the Gordonvale, Tully, Ingham, Mackay, and Bingera (near Bundaberg) sugarcane-growing regions of Queensland, Australia. The results showed that sugarcane possesses a capacity to compensate for different row configurations and planting densities through variation in stalk number and individual stalk weight. Row configurations ranging from 1.5-m single rows (the current industry standard) to 1.8-m dual rows (50 cm between duals), 2.1-m dual (80 cm between duals) and triple ( 65 cm between triples) rows, and 2.3-m triple rows (65 cm between triples) produced similar yields. Four rows (50 cm apart) on a 2.1-m configuration (quad rows) produced lower yields largely due to crop lodging, while a 1.8-m single row configuration produced lower yields in the plant crop, probably due to inadequate resource availability (water stress/limited radiation interception). The results suggest that controlled traffic can be adopted in the Australian sugar industry by changing from a 1.5-m single row to 1.8-m dual row configuration without yield penalty. Further, the similar yields obtained with wider row configurations (2 m or greater with multiple rows) in these experiments emphasise the physiological and environmental plasticity that exists in sugarcane. Controlled traffic can be implemented with these wider row configurations (>2 m), although it will be necessary to carry out expensive modifications to the current harvester and haul-out equipment. There were indications from this research that not all cultivars were suited to configurations involving multiple rows. The results suggest that consideration be given to assessing clones with different growth habits under a range of row configurations to find the most suitable plant types for controlled traffic cropping systems.

Australia takes prickly acacia biocontrol search to India

A project co-funded by Meat & Livestock Australia and the Queensland Government is putting new life into the search for biocontrol agents for prickly acacia (Acacia nilotica), a Weed of National Significance in Australia.

Integrated Cotton Farming Systems for Central Queensland

This project has delivered outcomes that address major agronomic and crop protection issues closely linked to the profitability and sustainability of cotton production enterprises in CQ. From an agronomic perspective, the CQ environment was always though to support economically viable cotton production in a wide sowing window from the middle of September to early January prior to this research. The ideal positioning of Bollgard II varieties in the CQ planting window was, therefore, critical to the future of the local cotton industry because growers needed baseline information to determine how best to take advantage of the higher yield potential offered by the Bt cotton technology, optimise irrigation water use and fibre characteristics. The project’s outputs include a number of key agronomic findings. Over three growing seasons, Bollgard II crop planted in the traditional sowing window from the middle of September to the end of October consistently produced the highest yields. The project delivers a clear and quantitative assessment of the impacts of planting outside the traditional cropping window - a yield penalty of between 1-4 bales/ha for November and December planted cotton. Whilst yield penalties associated with December-planted crops are clearly linked to declining heat units in the second half of the crop and a cool finish, those associated with November-planted cotton are not consistent with the theoretical yield potential for this sowing date. Further research to understand and minimize the physiological constraints on November-planted cotton would give CQ cotton growers far greater flexibility to develop mixed/double/rotation cropping farming systems that are relevant to the rapidly evolving nature of Agricultural production in Australia. The equivalence of cultivar types with clearly distinguishable, genetically based growth habits, demonstrated in this project, gives growers important information for making varietal choices. The entomological outcomes of this project represent strategic and tactical tools that are highly relevant to the viability and profitability of the cotton industry in Australia. The future of the cotton industry is inextricably linked to the survival and efficacy of GM cotton. Research done in the Callide irrigation area demonstrates the unquestionable potential for development of alternative and highly effective resistance management strategies for Bollgard II using novel technologies and strategies based on products such as Magnet®. Magnet® and similar technologies will be increasingly important in strategies to preserve the shelf life and efficacy of current and future generations of GM technology. However, more research will be required to address logistical and operational issues related to these new technologies before they can be fully exploited in commercial production systems. From an economic perspective, SLW is the sleeping giant in terms of insect nemeses of cotton, particularly from the standpoint of climate change and an increasingly warmer production environment. An effective sampling and management strategy for SLW which has been delivered by this project will go a long way towards minimising production costs in an environment characterised by rapidly rising input costs. SLW has the potential to permanently debilitate the national cotton industry by influencing market sentiment and quality perceptions. Field validation of the SLW population sampling models and management options in the Dawson irrigation area cotton and southern Queensland during 2006-07 documents the robustness of the entomological research outcomes achieved through this project.

The role of tillage, fertiliser and forage species in sustaining dairying based on crops in southern Queensland 1. Winter-dominant forage systems.

Field studies were conducted over 5 years on two dairy farms in southern Queensland to evaluate the impacts of zero-tillage, nitrogen (N) fertiliser and legumes on a winter-dominant forage system based on raingrown oats. Oats was able to be successfully established using zero-tillage methods, with no yield penalties and potential benefits in stubble retention over the summer fallow. N fertiliser, applied at above industry-standard rates (140 vs. 55 kg/ha.crop) in the first 3 years, increased forage N concentration significantly and had residual effects on soil nitrate-N at both sites. At one site, crop yield was increased by 10 kg DM/ha. kg fertiliser N applied above industry-standard rates. The difference between sites in fertiliser response reflected contrasting soil and fertiliser history. There was no evidence that modifications to oats cropping practices (zero-tillage and increased N fertiliser) increased surface soil organic carbon (0-10 cm) in the time frame of the present study. When oats was substituted with annual legumes, there were benefits in improved forage N content of the oat crop immediately following, but legume yield was significantly inferior to oats. In contrast, the perennial legume Medicago sativa was competitive in biomass production and forage quality with oats at both sites and increased soil nitrate-N levels following termination. However, its contribution to winter forage was low at 10% of total production, compared with 40% for oats, and soil water reserves were significantly reduced at one site, which had an impact on the following oat production. The study demonstrated that productive grazed oat crops can be grown using zero tillage and that increased N fertiliser is more consistent in its effect on N concentration than on forage yield. A lucerne ley provides a strategy for raising soil nitrate-N concentration and increasing overall forage productivity, although winter forage production is reduced.

Evaluating the performance of weed containment programmes

Aim: To develop approaches to the evaluation of programmes whose strategic objectives are to halt or slow weed spread. Location: Australia. Methods: Key aspects in the evaluation of weed containment programmes are considered. These include the relevance of models that predict the effects of management intervention on spread, the detection of spread, evidence for containment failure and metrics for absolute or partial containment. Case studies documenting either near-absolute (Orobanche ramosa L., branched broomrape) or partial (Parthenium hysterophorus (L.) King and Robinson, parthenium) containment are presented. Results: While useful for informing containment strategies, predictive models cannot be employed in containment programme evaluation owing to the highly stochastic nature of realized weed spread. The quality of observations is critical to the timely detection of weed spread. Effectiveness of surveillance and monitoring activities will be improved by utilizing information on habitat suitability and identification of sites from which spread could most compromise containment. Proof of containment failure may be difficult to obtain. The default option of assuming that a new detection represents containment failure could lead to an underestimate of containment success, the magnitude of which will depend on how often this assumption is made. Main conclusions: Evaluation of weed containment programmes will be relatively straightforward if containment is either absolute or near-absolute and may be based on total containment area and direct measures of containment failure, for example, levels of dispersal, establishment and reproduction beyond (but proximal to) the containment line. Where containment is only partial, other measures of containment effectiveness will be required. These may include changes in the rates of detection of new infestations following the institution of interventions designed to reduce dispersal, the degree of compliance with such interventions, and the effectiveness of tactics intended to reduce fecundity or other demographic drivers of spread. © 2012 Blackwell Publishing Ltd.

Harvesting, packing, postharvest technology, transport and processing

This chapter provides updated information on avocado fruit quality parameters, sensory perception and maturity, production and postharvest factors affecting quality defects, disinfestation and storage (including pre-conditioning), predicting outturn quality and processing.

Good science for improving policy: greenhouse gas emissions from agricultural manures

Australia’s and New Zealand’s major agricultural manure management emission sources are reported to be, in descending order of magnitude: (1) methane (CH4) from dairy farms in both countries; (2) CH4 from pig farms in Australia; and nitrous oxide (N2O) from (3) beef feedlots and (4) poultry sheds in Australia. We used literature to critically review these inventory estimates. Alarmingly for dairy farm CH4 (1), our review revealed assumptions and omissions that when addressed could dramatically increase this emission estimate. The estimate of CH4 from Australian pig farms (2) appears to be accurate, according to industry data and field measurements. The N2O emission estimates for beef feedlots (3) and poultry sheds (4) are based on northern hemisphere default factors whose appropriateness for Australia is questionable and unverified. Therefore, most of Australasia’s key livestock manure management greenhouse gas (GHG) emission profiles are either questionable or are unsubstantiated by region-specific research. Encouragingly, GHG from dairy shed manure are relatively easy to mitigate because they are a point source which can be managed by several ‘close-to-market’ abatement solutions. Reducing these manure emissions therefore constitutes an opportunity for meaningful action sooner compared with the more difficult-to-implement and long-term strategies that currently dominate agricultural GHG mitigation research. At an international level, our review highlights the critical need to carefully reassess GHG emission profiles, particularly if such assessments have not been made since the compilation of original inventories. Failure to act in this regard presents the very real risk of missing the ‘low hanging fruit’ in the rush towards a meaningful response to climate change