Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance.

Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

Effect of DNA extraction on ageing success in coral trout (Plectropomus leopardus) otoliths

To maximize the information commonly collected from otoliths, the effect of DNA extraction on the estimation of age with otoliths was evaluated by comparing sagittal otolith samples from common coral trout (Plectropomus leopardus) for clarity and ageing discrepancies in DNA-extracted and untreated control otoliths. The DNA extraction process had no significant effect, indicating that archived otoliths can be used as a source of DNA while retaining their utility for age estimation.

Spelling strategies for recovery of pasture condition

This work will progess and extend recommendations and guidelines for use of integrated wet season spelling in Queenslands savannahs and woodlands. The research will generate a greater ecological and pasture production understanding of pastures and soils that exist in C land condition areas (major landtypes), and their recovery. Practical, cost-effective spelling regimes will be developed. Research will be conducted on-property with small plot exclosures and plots with controlled utilisation levels, examining ecological responses to different spelling regimes. This information will improve bio-economic modelling capacity. Industry consultations with producers and field staff will drive implementation of the recommendations arising.

Developing and communicating strategies for controlling virus diseases in vegetable cucurbit crops

Virus diseases cause serious yield and quality losses in field grown cucurbit crops worldwide. In Australia, the main viruses of cucurbits are Papaya ringspot virus (PRSV), Squash mosaic virus (SqMV), Watermelon mosaic virus (WMV) and Zucchini yellow mosaic virus (ZYMV). Plants infected early have severely distorted fruit. High infection incidences, of ZYMV and PRSV in crops cause losses of marketable fruit of up to 100% and infected crops are often abandoned. Two new alternative hosts of ZYMV were identified, the native cucurbit Cucumis maderaspatanus and wild legume Rhyncosia minima. No new alternative hosts of PRSV, SqMV or WMV were found in Western Australia or Queensland. Seed transmission of ZYMV (0.7%) was found in seedlings grown from ZYMV-infected fruit of zucchini but not of pumpkin. None was detected with PRSV or SqMV in zucchini or pumpkin seedlings, respectively. ZYMV spread to pumpkins by aphids was greater downwind than upwind of a virus source. Delaying sowing by 2 weeks decreased ZYMV spread. Millet non-host barriers between pumpkin plantings slowed ZYMV infection. Host resistance gene (zym) in cucumber cultivars was effective against ZYMV. Pumpkin cultivars with resistance gene (Zym) became infected under high virus pressure but leaf symptoms were milder and infected plants higher yielding with more market-acceptable fruit than those without Zym. Most zucchini cultivars with Zym developed severe leaf and fruit symptoms. ZYMV, PRSV, WMV and SqMV spread readily from infected to healthy cucurbit plants by direct leaf contact. ZYMV survives and remains infective on diverse surfaces for up to 6 hours but can be inactivated by some disinfectants. Phylogenetic analysis indicates at least three separate introductions of ZYMV into Australia, with new introductions rarely occurring. ZYMV isolates clustered into three groups according to collection location i) Kununurra, ii) Northern Territory and iii) Carnarvon, Qld and Vic. A multiplex Real-Time PCR was developed which distinguished between the three groups of Australian isolates. Integrated disease management (IDM) strategies for virus diseases of vegetable cucurbit crops grown in the field were improved incorporating the new information gathered. These strategies are aimed at causing using minimal extra expense, labour demands and disruption to normal practices.

Maximising profitability with limited water in cotton farming systems

Diminishing water supply, changing weather patterns and pressure to enhance environmental flows are making it imperative to optimise water use efficiency (WUE) on cotton/grain farming systems. Growers are looking for better strategies to make the best use of limited water, but it is still not clear how to best use the available water at farm and field scale. This research project investigated the impact of management strategies to deal with limited water supplies on the yield and quality of irrigated cotton and wheat. The objectives were: (1) to develop irrigation management guidelines for the main irrigated crops on the Darling Downs for full- and deficitirrigation scenarios, taking into account the critical factors that affect irrigation decisions at the local level, (2) to quantify the evapotranspiration (ET) of Bollgard II cotton and wheat and its relationship to yield and quality under full- and deficit-irrigation scenarios, and (3) to increase industry awareness and education of farming systems practises for optimised economic water use efficiency.Objective (1) was addressed by (A) collaborating with ASPRU to develop the APSFarm model within APSIM to be able to perform multi-paddock simulations. APSFarm was then tested by conducting a case study at a farm near Dalby, and (B) conducting semi-structured interviews with individual farmers and crop consultants on the Darling Downs to document the strategies they are using to deal with limited water. Objective (2) was addressed by (A) building and installing 12 large (1 m x 1m x 1.5 m) weighing lysimeters to measure crop evapotranspiration. The lysimeters were installed at the Agri-Science Queensland research station at Kingsthorpe in November 2008, (B) conducting field experiments to measure crop evapotranspiration and crop development under four irrigation treatments, including dryland, deficit-irrigation, and full irrigation. Field experiments were conducted with cotton in 2007-08 and 2008-09, and with wheat in 2008 and 2009, and (C) collaborating with USQ on a PhD thesis to quantify the impact of crop stress on crop evapotranspiration and canopy temperature. Glasshouse experiments were conducted with wheat in 2008 and with cotton in 2008-09. Objective (3) was addressed by (A) conducting a field day at Kingsthorpe in 2009, which was attended by 80 participants, (B) presenting information in conferences in Australia and overseas, (D) presenting information at farmers meeting, (E) making presentations to crop consultants, and (F) preparing extension publications.As part of this project we contributed to the development of APSfarm, which has been successfully applied to evaluate the feasibility of practices at the whole-farm scale. From growers and crop consultants interviews we learned that there is a great variety of strategies, at different scales, that they are using to deal with limited water situation. These strategies will be summarised in the "e;Limited Water Guidelines for the Darling Downs"e; that we are currently preparing. As a result of this project, we now have a state-of-the-art lysimeter research facility (23 large weighing lysimeters) to be able to conduct replicated experiments to investigate daily water use of a variety of crops under different irrigation regimes and under different environments. Under this project, a series of field and glasshouse experiments were conducted with cotton and wheat, investigating aspects like: (A) quantification of daily and seasonal crop water use under nonstressed and stressed conditions, (B) impact of row configuration on crop water use, (C) impact of water stress on yield, evapotranspiration, crop vegetative and reproductive development, soil water extraction pattern, yield and yield quality. The information obtained from this project is now being used to develop web-based tools to help growers make planning and day-to-day irrigation decisions.

Weed management strategies for farming systems with herbicide tolerant cotton.

The introduction of glyphosate tolerant cotton has significantly improved the flexibility and management of a number of problem weeds in cotton systems. However, reliance on glyphosate poses risks to the industry in term of glyphosate resistance and species shift. The aims of this project were to identify these risks, and determine strategies to prevent and mitigate the potential for resistance evolution. Field surveys identified fleabane as the most common weed now in both irrigated and dryland system. Sowthistle has also increased in prevalence, and bladder ketmia and peachvine remained common. The continued reliance on glyphosate has favoured small seeded, and glyphosate tolerant species. Fleabane is both of these, with populations confirmed resistant in grains systems in Queensland and NSW. When species were assessed for their resistance risk, fleabane, liverseed grass, feathertop Rhodes grass, sowthistle and barnyard grass were determined to have high risk ratings. Management practices were also determined to rely heavily on glyphosate and therefore be high risk in summer fallows, and dryland glyphosate tolerant and conventional cotton. Situations were these high risk species are present in high risk cropping phases need particular attention. The confirmation of a glyphosate resistance barnyard grass population in a dryland glyphosate tolerant cotton system means resistance is now a reality for the cotton industry. However, experiments have shown that resistant populations can be managed with other herbicide options currently available. However, the options for fleabane management in cotton are still limited. Although some selective residual herbicides are showing promise, the majority of fleabane control tactics can only be used in other phases of the cotton rotation. An online glyphosate resistance tool has been developed. This tool allows growers to assess their individual glyphosate resistance risks, and how they can adjust their practices to reduce their risks. It also provides researchers with current information on weed species present and practices used across the industry. This tool will be extremely useful in tailoring future research and extension efforts. Simulations from the expanded glyphosate resistance model have shown that glyphosate resistance can be prevented and managed in glyphosate-tolerant cotton farming systems. However, for strategies to be successful, some effort is required. Simulations have shown the importance of controlling survivors of glyphosate applications, using effective glyphosate alternatives in fallows, and combining several effective glyphosate alternatives in crop, and these are the key to the prevention and management of glyphosate resistance.

Integrating sorghum whole genome sequence information with a compendium of sorghum QTL studies reveals uneven distribution of QTL and of gene-rich regions with significant implications for crop improvement.

A comprehensive analysis was conducted using 48 sorghum QTL studies published from 1995 to 2010 to make information from historical sorghum QTL experiments available in a form that could be more readily used by sorghum researchers and plant breeders. In total, 771 QTL relating to 161 unique traits from 44 studies were projected onto a sorghum consensus map. Confidence intervals (CI) of QTL were estimated so that valid comparisons could be made between studies. The method accounted for the number of lines used and the phenotypic variation explained by individual QTL from each study. In addition, estimated centimorgan (cM) locations were calculated for the predicted sorghum gene models identified in Phytozome (JGI GeneModels SBI v1.4) and compared with QTL distribution genome-wide, both on genetic linkage (cM) and physical (base-pair/bp) map scales. QTL and genes were distributed unevenly across the genome. Heterochromatic enrichment for QTL was observed, with approximately 22% of QTL either entirely or partially located in the heterochromatic regions. Heterochromatic gene enrichment was also observed based on their predicted cM locations on the sorghum consensus map, due to suppressed recombination in heterochromatic regions, in contrast to the euchromatic gene enrichment observed on the physical, sequence-based map. The finding of high gene density in recombination-poor regions, coupled with the association with increased QTL density, has implications for the development of more efficient breeding systems in sorghum to better exploit heterosis. The projected QTL information described, combined with the physical locations of sorghum sequence-based markers and predicted gene models, provides sorghum researchers with a useful resource for more detailed analysis of traits and development of efficient marker-assisted breeding strategies.

Networks of stored grain diseases and pests: Strategies for sampling and mitigation

Pathogens and pests of stored grains move through complex dynamic networks linking fields, farms, and bulk storage facilities. Human transport and other forms of dispersal link the components of this network. A network model for pathogen and pest movement through stored grain systems is a first step toward new sampling and mitigation strategies that utilize information about the network structure. An understanding of network structure can be applied to identifying the key network components for pathogen or pest movement through the system. For example, it may be useful to identify a network node, such as a local grain storage facility, through which grain from a large number of fields will be accumulated and move through the network. This node may be particularly important for sampling and mitigation. In some cases more detailed information about network structure can identify key nodes that link two large sections of the network, such that management at the key nodes will greatly reduce the risk of spread between the two sections. In addition to the spread of particular species of pathogens and pests, we also evaluate the spread of problematic subpopulations, such as subpopulations with pesticide resistance. We present an analysis of stored grain pathogen and pest networks for Australia and the United States.