The reliability of supply of feed grains in the northern region

Reliability of supply of feed grain has become a high priority issue for industry in the northern region. Expansion by major intensive livestock and industrial users of grain, combined with high inter-annual variability in seasonal conditions, has generated concern in the industry about reliability of supply. This paper reports on a modelling study undertaken to analyse the reliability of supply of feed grain in the northern region. Feed grain demand was calculated for major industries (cattle feedlots, pigs, poultry, dairy) based on their current size and rate of grain usage. Current demand was estimated to be 2.8Mt. With the development of new industrial users (ethanol) and by projecting the current growth rate of the various intensive livestock industries, it was estimated that demand would grow to 3.6Mt in three years time. Feed grain supply was estimated using shire scale yield prediction models for wheat and sorghum that had been calibrated against recent ABS production data. Other crops that contribute to a lesser extent to the total feed grain pool (barley, maize) were included by considering their production relative to the major winter and summer grains, with estimates based on available production records. This modelling approach allowed simulation of a 101-year time series of yield that showed the extent of the impact of inter-annual climate variability on yield levels. Production estimates were developed from this yield time series by including planted crop area. Area planted data were obtained from ABS and ABARE records. Total production amounts were adjusted to allow for any export and end uses that were not feed grain (flour, malt etc). The median feed grain supply for an average area planted was about 3.1Mt, but this varied greatly from year to year depending on seasonal conditions and area planted. These estimates indicated that supply would not meet current demand in about 30% of years if a median area crop were planted. Two thirds of the years with a supply shortfall were El Nino years. This proportion of years was halved (i.e. 15%) if the area planted increased to that associated with the best 10% of years. Should demand grow as projected in this study, there would be few years where it could be met if a median crop area was planted. With area planted similar to the best 10% of years, there would still be a shortfall in nearly 50% of all years (and 80% of El Nino years). The implications of these results on supply/demand and risk management and investment in research and development are briefly discussed.

Plant hosts of the phytoplasmas and rickettsia-like-organisms associated with strawberry lethal yellows and green petal diseases

Candidatus Phytoplasma australiense (Ca. P. australiense) is associated with the plant diseases strawberry lethal yellows (SLY), strawberry green petal (SGP), papaya dieback (PDB), Australian grapevine yellows (AGY) and Phormium yellow leaf (PYL; New Zealand). Strawberry lethal yellows disease is also associated with a rickettsia-like-organism (RLO) or infrequently with the tomato big bud (TBB) phytoplasma, the latter being associated with a wide range of plant diseases throughout Australia. In contrast, the RLO has been identified only in association with SLY disease, and Ca. P. australiense has been detected only in a limited number of plant host species. The aim of this study was to identify plant hosts that are possible reservoirs of Ca. P. australiense and the SLY RLO. Thirty-one plant species from south-east Queensland were observed with disease between 2001 and 2003 and, of these, 18 species tested positive using phytoplasma-specific primers. The RLO was detected in diseased Jacksonia scoparia and Modiola caroliniana samples collected at Stanthorpe. The TBB phytoplasma was detected in 16 different plant species and Ca. P. australiense Australian grapevine yellows strain was detected in six species. The TBB phytoplasma was detected in plants collected at Nambour, Stanthorpe, Warwick and Brisbane. Ca. P. australiense was detected in plants collected at Nambour, Stanthorpe, Gatton and Allora. All four phytoplasmas were detected in diseased Gomphocarpus physocarpus plants collected at Toowoomba, Allora, Nambour and Gatton. These results indicated that the vector(s) of Ca. P. australiense are distributed throughout south-east Queensland and the diversity of phytoplasmas detected in G. physocarpus suggests it is a feeding source for phytoplasma insect vectors or it has a broad susceptibility to a range of phytoplasmas.

Tools to manage climate risk in cropping (Australia).

Because of the variable and changing environment, advisors and farmers are seeking systems that provide risk management support at a number of time scales. The Agricultural Production Systems Research Unit, Toowoomba, Australia has developed a suite of tools to assist advisors and farmers to better manage risk in cropping. These tools range from simple rainfall analysis tools (Rainman, HowWet, HowOften) through crop simulation tools (WhopperCropper and YieldProphet) to the most complex, APSFarm, a whole-farm analysis tool. Most are derivatives of the APSIM crop model. These tools encompass a range of complexity and potential benefit to both the farming community and for government policy. This paper describes, the development and usage of two specific products; WhopperCropper and APSFarm. WhopperCropper facilitates simulation-aided discussion of growers' exposure to risk when comparing alternative crop input options. The user can readily generate 'what-if' scenarios that separate the major influences whilst holding other factors constant. Interactions of the major inputs can also be tested. A manager can examine the effects of input levels (and Southern Oscillation Index phase) to broadly determine input levels that match their attitude to risk. APSFarm has been used to demonstrate that management changes can have different effects in short and long time periods. It can be used to test local advisors and farmers' knowledge and experience of their desired rotation system. This study has shown that crop type has a larger influence than more conservative minimum soil water triggers in the long term. However, in short term dry periods, minimum soil water triggers and maximum area of the various crops can give significant financial gains.

Cotton root systems and recovery of applied P and K fertilisers

With potential to accumulate substantial amounts of above-ground biomass, at maturity an irrigated cotton crop can have taken up more than 20 kg/ha phosphorus and often more than 200 kg/ha of potassium. Despite the size of plant accumulation of P and K, recovery of applied P and K fertilisers by the crop in our field experiment program has poor. Processing large amounts of mature cotton plant material to provide a representative sample for chemical analysis has not been without its challenges, but the questions regarding mechanism of where, how and when the plant is acquiring immobile nutrients remain. Dry matter measured early in the growing season (squaring, first white flower) have demonstrated a 50% increase in crop biomass to applied P (in particular), but it represents only 20% of the total P accumulation by the plant. By first open boll (and onwards), no response in dry matter or P concentration could be detected to P application. A glasshouse study indicated P recovery was greater (to FOB) where it was completely mixed through a profile as opposed to a banded application method suggesting cotton prefers a more diffuse distribution. The relative effects of root morphology, mycorrhizal fungi infection, seasonal growth patterns and how irrigation is applied are areas for future investigation on how, when and where cotton acquires immobile nutrients.

Winter sowing for more reliable boll filling in Central Queensland

The Central Highlands region has a unique climate that presents both challenges and novel farming systems opportunities for cotton production. We have been re-examining the Emerald climate in a bid to identify opportunities that might enable the production of more consistent cotton yields and quality in what can be a highly variable climate. A detailed climatic analysis identified that spring and early summer is the most optimal period for boll growth and maturation. However, to unlock this potential requires unseasonal winter sowing that is 4 to 6 weeks earlier than the traditional mid-September sowing. Our experiments have sought answers to two questions: i) how much earlier can cotton be sown for reliable crop establishment and high yield; ii) can degradable plastic film mulches minimise the impact of potentially cold temperatures on crop establishment and early vigour. Initial data suggests August sowing offers the potential to grow a high yield at a time of year with reduced risk of cloud and high night temperatures during boll growth. For the past two seasons late winter sowing (with and without film) has resulted in a compact plant with high retention that physiologically matures by the beginning of January. Even with the spectre of replanting cotton in some seasons due to frost in August, early sowing would appear to offer the opportunity for more efficient crop input usage, simplified agronomic management and new crop rotation options during late summer and autumn. This talk will present an overview of results to date.

What influences fungal communities in cotton soils

Soilborne diseases such as Fusarium wilt, Black root rot and Verticillium wilt have significant impact on cotton production. Fungi are an important component of soil biota with capacity to affect pathogen inoculum levels and their disease causing potential. Very little is known about the soil fungal community structure and management effects in Australian cotton soils. We analysed surface soils from ongoing field experiments monitoring cotton performance and disease incidence in three cotton growing regions, collected prior to 2013 planting, for the genetic diversity and abundance as influenced by soil type, environment and management practices and link it with disease incidence and suppression. Results from the 28S LSU rRNA sequencing based analysis indicated a total of 370 fungal genera in all the cotton soils and the top 25 genera in abundance accounted for the major portion of total fungal community. There were significant differences in the composition and genetic diversity of soil fungi between the different field sites from the three cotton growing regions. Results for diversity indices showed significantly greater diversity in the long-term crop rotation experiment at Narrabri (F6E) and experiments at Cowan and Goondiwindi compared to the Biofumigation and D1 field experiments at ACRI, Narrabri. Diversity was lowest in the soils under brassica crop rotation in Biofumigation experiment. Overall, the diversity and abundance of soil fungal community varied significantly in the three cotton growing regions indicating soil type and environmental effects. These results suggest that changes in soil fungal community may play a notable role in soilborne disease incidence in cotton.

Silverleaf whitefly resistance management

Silverleaf whitefly (SLW) is a major late season pest of cotton due to its potential to contaminate cotton lint with honeydew. To prevent this, management is often reliant on the use of insecticides to control SLW populations. With selection pressure SLW develop resistance to insecticides they are exposed to, resulting in spray failures. Our lab tests resistance levels in SLW populations collected from across the cotton industry. In this presentation I will provide an update of emerging SLW resistance issues the cotton industry is facing.

Growth and development of three key summer grasses in Australian cotton systems

Awnless barnyard grass, feathertop Rhodes grass, and windmill grass are important weeds in Australian cotton systems. In October 2014, an experiment was established to investigate the phenological plasticity of these species. Seed of these species were planted in a glasshouse every four weeks and each cohort grown for 6 months. A developmental response to day length was observed in barnyard grass but not in the other species. Days to maturity increased with each planting for feathertop Rhodes and windmill grass for the first six cohorts. Barnyard grass showed a similar pattern in growth for seeds planted from October to December with an increase in the onset of maturity from 51 to 58 days. However, the onset of maturity for cohorts planted between January and March decreased to between 50 and 52 days. All species had a decrease in the total number of panicles produced from the first four plantings. Feathertop Rhodes grass planted in October produced 41 panicles compared to those planted at the end of December producing 30 panicles, barnyard grass had a decrease from 99 to 47 panicles and windmill grass 37 to 15 panicles on average. By comparing the development of these key weed species over 12 months, detailed information on the phenological plasticity of these species will be obtained. This information will contribute to more informed management decisions by improving our understanding of appropriate weed control timings or herbicide rates depending on weed emergence and development.

Is Australia ready for triple gene herbicide stack technology?

Integration of multiple herbicide-resistant genes (trait stacking) into crop plants would allow over the top application of herbicides that are otherwise fatal to crops. The US has just approved Bollgard II® XtendFlex™ cotton which has dicamba, glyphosate and glufosinate resistance traits stacked. The pace of glyphosate resistance evolution is expected to be slowed by this technology. In addition, over the top application of two more herbicides may help to manage hard to kill weeds in cotton such as flax leaf fleabane and milk thistle. However, there are some issues that need to be considered prior to the adoption of this technology. Wherever herbicide tolerant technology is adopted, volunteer crops can emerge as a weed problem, as can herbicide resistant weeds. For cotton, seed movement is the most likely way for resistant traits to move around. Management of multiple stack volunteers may add additional complexity to volunteer management in cotton fields and along roadsides. This paper attempts to evaluate the pros and cons of trait stacking technology by analysing the available literature in other crop growing regions across the world. The efficacy of dicamba and glufosinate on common weeds of the Australian cotton system, herbicide resistance evolution, synergy and antagonisms due to herbicide mixtures, drift hazards and the evolution of herbicide resistance to glyphosate, glufosinate and dicamba were analysed based on the available literature.

CottonInfo Extending Research

There are many ways in which research messages and findings can be extended to the expansive cotton community. As everyone learns differently it is crucial that information is delivered in a variety of ways to meet the various learning needs of the CottonInfo team’s broad audience. In addition different cotton production areas often require targeted information to address specific challenges. Successful implementation of innovative research outcomes typically relies on a history of cultivated communication between the researcher and the end-user, the grower. The CottonInfo team, supported by a joint venture between Cotton Seed Distributors, Cotton Research Development Corporation, Cotton Australia and other collaborative partners, represents a unique model of extension in Australian agriculture. Industry research is extended via regionally based Regional Development Officers backed by support from Technical Specialists. The 2015 Cotton Irrigation Technology Tour is one example of a successful CottonInfo capacity building activity. This tour took seven CRDC funded irrigation-specific researchers to Emerald, Moree and Nevertire to showcase their research and technologies. These events provided irrigators and consultants with the opportunity to hear first-hand from researchers about their technologies and how they could be applied onfarm. This tour was an example of how the CottonInfo team can connect growers and researchers, not only to provide an avenue for growers to learn about the latest irrigation research, but for researchers to receive feedback about their current and future irrigation research.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

Response of irrigated cotton to applied nitrogen

Like all high yielding farming systems nitrogen (N) is a key component to their productivity and profitability and Australian irrigated cotton growers are tending to apply more N than is required for the level of lint yield that is being achieved. This suggests either over application of N or inefficient systems limiting the response of cotton to N inputs. To investigate this four replicated trials were established in commercial fields during the 2014/15 season. The trials were aiming to measure the difference in response of irrigated cotton to the application of N under flood and overhead irrigation systems. The application treatments utilized eight upfront rates of applied N, ranging from 0 N kg/ha to a maximum of 410 kg N/ha, with three of the fours trials receiving a growerdetermined in-crop application of N in the irrigation water. The two flood irrigation systems had lower lint yields from similar levels of N input compared to one of the overhead irrigated sites; the result from the second overhead site was impacted by disease. This paper discusses the response of plant N uptake, lint yield and fertilizer N recovery to N application..

The importance of cotton disease surveys in Queensland for monitoring endemic diseases and detecting new pathogens and pests

The cotton industry in Australia funds biannual disease surveys conducted by plant pathologists. The objective of these surveys is to monitor the distribution and importance of key endemic pests and record the presence or absence of new or exotic diseases. Surveys have been conducted in Queensland since 2002/03, with surveillance undertaken by experienced plant pathologists. Monitoring of endemic diseases indicates the impact of farming practices on disease incidence and severity. The information collected gives direction to cotton disease research. Routine diagnostics has provided early detection of new disease problems which include 1) the identification of Nematospora coryli, a pathogenic yeast associated with seed and internal boll rot; and 2) Rotylenchulus reniformis, a plant-parasitic nematode. This finding established the need for an intensive survey of the Theodore district revealing that reniform was prevalent across the district at populations causing up to 30% yield loss. Surveys have identified an exotic defoliating strain (VCG 1A) and non-defoliating strains of Verticillium dahliae, which cause Verticillium wilt. An intensive study of the diversity of V. dahliae and the impact these strains have on cotton are underway. Results demonstrate the necessity of general multi-pest surveillance systems in broad acre agriculture in providing (1) an ongoing evaluation of current integrated disease management practices and (2) early detection for a suite of exotic pests and previously unknown pests.

BYGUM – a new tool for BarnYard Grass Understanding and Management

Weed management has become increasingly challenging for cotton growers in Australia in the last decade. Glyphosate, the cornerstone of weed management in the industry, is waning in effectiveness as a result of the evolution of resistance in several species. One of these, awnless barnyard grass, is very common in Australian cotton fields, and is a prime example of the new difficulties facing growers in choosing effective and affordable management strategies. RIM (Ryegrass Integrated Management) is a computer-based decision support tool developed for the south-western Australian grains industry. It is commonly used there as a tool for grower engagement in weed management thinking and strategy development. We used RIM as the basis for a new tool that can fulfil the same types of functions for subtropical Australian cotton-grains farming systems. The new tool, BYGUM, provides growers with a robust means to evaluate five-year rotations including testing the economic value of fallows and fallow weed management, winter and summer cropping, cover crops, tillage, different herbicide options, herbicide resistance management, and more. The new model includes several northernregion- specific enhancements: winter and summer fallows, subtropical crop choices, barnyard grass seed bank, competition, and ecology parameters, and more freedom in weed control applications. We anticipate that BYGUM will become a key tool for teaching and driving the changes that will be needed to maintain sound weed management in cotton in the near future.