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This Guide provides you with a comprehensive summary of the key cotton crop protection issues, and is brought to you by CRDC and the Australian cotton industry's joint extension program, CottonInfo.
In 2014 the Central Highlands Cotton Growers and Irrigators Association (CHCG&IA) partnered with Biosecurity Qld and the Cotton Research and Development Corporation (CRDC) to purchase and install 9 weather stations in key locations within the Emerald cotton growing and irrigation area. The weather station data is broadcast via the OzForecast website with data retained by the CHCG&IA. The CHCG&IA engaged Pat Menkens from Menkin’s Irrigation a professional weather and water technology provider to locate the stations in a strategic manner to gain the best coverage for users. The network has been a valued asset by growers, industry support organisations and community across the Emerald cotton growing Area. The grass roots/on the ground value this network provides members of the CHCG&IA is ongoingly noted. Our members share feedback on the networks functioning and clear reiteration for the maintenance and expansion of the network to be a key objective of the CHCG&IA via formal email notices and verbal feedback in members meetings. Furthermore, our members request that the weather station network to be improved with fixing and replacing parts of the stations which have naturally expired/degraded over time. This it to ensure the network continues to operate in its entirety and foster a greater range of people across our industry who gain value from it.
Northern growers and agronomists visited Emerald in May 2024 to observe & learn how the CQ Farming system (particularly Long Season Cotton ie 2 flowering periods) has adapted and changed to climatic conditions. This was an extremely successful exchange of learnings, lessons, discussions and ideas between growers & agros. In return, 6 x growers, 1 x Agronomist and 2 x Industry Reps all from the CH Region travelled to the NT & WA in April 2025 to build on discussions from the May 2024 visit and learn of the North's adaptations to their farming system, particularly in areas of crop destruction, crop management in the long season cotton farming system, biosecurity, RMP, cover cropping and irrigation systems. It was a very successful tour as you will see below.
The present study investigated the effect of Gibberellin (GA) and Salicylic acid (SA) on cotton during germination at high temperatures. Extreme temperatures have made the cotton seed germination and overall crop production challengeable, particularly in heat-prone regions like the Northern Territory (NT). Seed germination is a major developmental stage which is sensitive to heat stress, and enhancing thermal tolerance via priming treatment has proven to be an efficient approach. In the present study, cotton seeds were pretreated for 24 hours with GA and SA 100 ppm solutions and a control (water). Primed seeds were allowed for germination under laboratory conditions with oven temperatures set at 25°C, 30°C, 35°C, 40°C, and 45°C. Seed germination percentage, days taken for root and shoot emergence (first,50% and final), and root and shoot lengths were recorded. The ANOVA results revealed statistically significant temperature and treatment interaction (p<0.05) on final root emergence days, all shoot emergence days, and root length. Even though, germination percentage, days taken for first and 50% root emergence, and shoot length were not statistically significant, some trends were observed. Overall, GA primed seeds resulted in the fastest root and shoot emergence across all temperatures. However, GA priming exhibited a reduction in germination percentage and root and shoot lengths at elevated temperatures. Seeds primed with SA resulted reduced germination parameters at all temperatures, which might be due to the concentration-dependent hormonal imbalances. In contrast, control outperformed both hormonal treatments. It resulted in the highest seed germination percentage, highest root and shoot lengths, and facilitated root and shoot emergence days, particularly at elevated temperatures (40-45°C). These findings concluded that hydropriming is a potential and cost-effective method to promote heat tolerance during cotton seed germination. It is recommended to conduct further research, including field-based trials with the consideration of other growth stages, to validate the results of GA and SA priming on cotton seed germination at elevated temperatures.
This project was to develop insight into the future of rainfed cotton systems by developing an understanding of soil carbon and water use efficiency across a number of current rotation options.
The project included:
There is an appetite for understanding more about soil organic carbon and the benefits of managing a rainfed cropping system to accumulate soil carbon.
Rainfed cotton growers still indicate that they don’t understand how soil organic carbon fits into their farming system and are unsure of how to make evidence based, on-farm decisions specifically around soil organic carbon. Likewise, despite the uptake of technology to monitor soil moisture growers and their advisors are unsure how to use the data to make on-farm decisions. This project was to look at the interaction of soil organic carbon and water use efficiency so this constraint to adoption needs to be addressed.
The rainfed cotton industry could benefit from further investigation in to:
This project, while a good start, requires further investment to realise the full value of the work already completed.
As technology improves and research learnings are ground truth in commercial systems the development of simple to use tools will be critical to facilitate integration of these profitability and sustainability concepts into current rainfed cotton cropping systems.
Aligned with the principles of the Community Trust in Rural Industries (CTRI) program of research, Voconiq has worked to deliver a longitudinal social licence research program focused explicitly on the cotton industry from 2020 to 2023.
The national community research initiative within the Australian cotton industry sought to develop an in-depth understanding of community perspectives regarding the sector. Its primary objectives are to monitor and compare key indicators related to community attitudes, trust, and acceptance of the Australian cotton industry over time. Additionally, the program aims to explore emerging issues, such as perceptions concerning water usage.
The More Profit from Nitrogen Program (MPfN) has been a five-year partnership, commencing in 2016, between Australia’s four most intensive users of nitrogenous fertilisers: cotton, dairy, sugar and horticulture. Comprehensive research and development was conducted to increase nitrogen use efficiency (NUE) across the four sectors whilst improving profitable and sustainable use. By better understanding the influence of contributing factors upon NUE in farming systems, MPfN has generated greater knowledge and understanding of:
Research and extension activities were supported by $5.889 million funding from the Australian Government Department of Agriculture, Fisheries and Forestry (then Department of Agriculture, Water and the Environment) as a part of its Rural R&D for Profit program, with a further $9.757 million cash and in-kind contribution from the partnering RDCs, research organisations and collaborating partners.
MPfN was managed by CRDC, in partnership with Dairy Australia, SRA and Hort Innovation. The eleven research projects were delivered by nine lead research organisations:
Activities were supported by a further 24 collaborating partners, overall encompassing 93 interacting research, technical and PhD candidate positions.
Forty-five field sites were used in the research effort, from Darwin in the north to Hobart in the south, supported by laboratory experimentation, analysis and systems modelling. The research has delivered or informed new N fertiliser formulations, application and measurement technologies, decision support tools and best management practice guidelines.
MPfN continuously produced progressive outputs that were embedded into industry programs, reducing lag time between research and adoption by cotton, sugar, horticultural and dairy producers. Over the Program’s duration, 173 extension activities were conducted that engaged with over 16,000 farmers, service providers and commercial advisors, as well as national and international researchers. These included industry and science conferences, field days, training workshops and webinars. 165 communication campaigns reached 478,000 people, through industry articles, videos, podcasts, websites and social media. Project materials developed included peer reviewed journal articles, industry best management practice (BMP) guidelines, economic case studies and decision trees/calculators totaling 84 outputs. Importantly, the teams of the MPfN Program conducted or participated in 77 collaboration activities with over 1500 other industry, research and commercial stakeholders, to ensure relevance, efficient delivery and consideration of aligned research.
In June 2021, the MPfN Program delivered the final technologies and decision support resources that will significantly contribute to increased industry NUE in coming years. As the outputs and outcomes of the research effort are extended through industry programs, it is anticipated that farmer uptake and adoption of recommendations and guidelines will gain momentum.
The MPfN Program legacy promises to be a significant reduction in environmental impact from nitrogenous fertiliser use whilst delivering greater sustainability and profitability outcomes for Australian farming businesses.
Weeds reduce agricultural productivity by competing for resources, and weed management is one of the largest costs faced by crop growers. Weeds are constantly evolving, and changes in weed types and their characteristics require ongoing adaptation of management. Farming systems also evolve, introducing new weed management challenges and opportunities. This dynamic nature of weed management often leads to shifting demands for research, development and extension specific to weeds and local farming systems. This study, funded by the Grains Research and Development Corporation (GRDC) and Cotton Research and Development Corporation (CRDC), aims to inform R&D investment priorities and industry at a broader scale. Given the wide range of weeds, agroecological zones (AEZs), impacts and management demands across variable seasons, it is not simple to identify where and in what form the largest costs are incurred. The last major study of the distribution and economic impact of weeds in Australian cropping systems (Llewellyn et al., 2016) began more than a decade ago and drew upon data from the period 2010 to 2014. The study focused only on grain production, and the overall cost of weeds to Australian grain growers was estimated to be $3300 million. The results of this new study represent the most comprehensive national analysis of the cost of weeds to Australian broadacre crop production. The study covers the 14 major GRDC-defined agroecological zones across the western, southern and northern regions, and the major crop types of wheat, barley, oats, canola, pulses, grain sorghum and – new to this study – cotton. This report outlines the study methods and then presents the results for the cost of weeds in grain crops, cotton crops and, finally, the cost for grain and cotton crops combined. The analysis is based on a modified, broadened and updated version of the national weed impact model used in the 2016 study. It includes the costs of yield loss due to in-crop weeds, water and nutrient use by fallow weeds, weed contamination, off-target herbicide impacts and weed control. Weed control costs, such as herbicide and non-herbicide practices, include seed technology costs attributable to weed control. Inputs used to represent cropping and farms in each AEZ have been informed by newly available data sources, including the GRDC Farm Practice Survey results; national herbicide resistance paddock survey data, including weed presence and density assessments; proprietary Kynetec annual herbicide farmer panel data; Australian Bureau of Statistics (ABS) production data; GRDC National Variety Trial yield results; Australian Pesticides and Veterinary Medicines Authority (APVMA) herbicide sales values; regional crop planning guides; and a panel of regional agronomy and weed management advisers, including cotton weed management experts.
Statistical associations identified in historical datasets
A geospatial database was developed and three years of field assessed cotton pathology data and management practices were collected. Multivariate analyses of survey data were performed to test for any effect of previous crop and cotton trash present on early and late season diseases. Further correlation network analyses were performed on the data to identify relationships between diseases and yield and diseases themselves in the whole data set and in each state.
Key findings include the impact of previous cropping on disease in the subsequent cotton crop. For example, Verticillium wilt was significantly higher following winter cereal crops than cotton. Seed rot was significantly lower following a fallow or winter cereals, boll rot was significantly higher following summer grains, and tight-lock was significantly lower following fallow and winter cereals, than cotton. Tight-lock had the strongest negative relationship with yield in the data set, providing statistical support of anecdotal findings. The amount of cotton trash present in the field did not have any significantly detectable effect on disease in the analyses performed on these data. Given the impact of previous crop on disease incidence, an estimation of crop residues other than cotton may provide insight to how other crops influence disease, such as maintaining inoculum levels through asymptomatic colonisation or providing a suitable carbon source for saprophytic growth. Hence, these findings provide direction for research to investigate cropping rotations that potentially will decrease/increase disease incidence of important diseases of cotton. The groundwork achieved in this project has provided the foundation knowledge and critical directions to improve the collection and storage of data, and to build on the analyses already conducted.
Disease suppression potential of cotton soils from different cotton growing regions
Composition and abundance of microbial communities were analysed for soils collected from different regions with different cropping histories and varying disease incidences. Results from the long-term experiments indicate that (i) the diversity and abundance of soil fungal communities varied significantly by crop management history and (ii) fungal communities in suppressive cotton soils were characterized by higher diversity and higher connectedness. The high level of organization along with higher diversity in the soil fungal community in the suppressive soils would provide the cotton plant with a stable microbial reservoir across varied seasonal environmental conditions.
Changes in the microbial diversity and activity in the short-term rotation experiment clearly indicated the significant and important contribution of soil microbiome (bacteria and fungi) for the suppression of Verticillium disease in cotton. The influence of rotation crops such as sorghum and corn could be attributed to (i) increased microbial catabolic diversity and activity (ii) higher diversity of bacteria and fungi, (iii) increased abundances of specific groups of microorganisms involved in antibiosis, antifungal (cell-wall degradation) and plant growth promoting capabilities, and (iv) lower pathogen levels. These changes would have contributed to the suppression of the pathogen, disease incidence and impact. Whereas the fallow treatment caused a significant decline in the total microbial activity and catabolic diversity, genetic diversity of bacteria and fungi resulting in lower pathogen suppression capacity. Although the lower pathogen levels would help in the reduction of disease incidence, long-term adoption of such management practices would not benefit in maintaining or improving the overall soil biological health. The traditional continuous cotton system seems to promote the growth of pathogenic fungi such as V. dahliae and result in lower microbial diversity and abundances of beneficial microorganisms.
A laboratory based pathogen suppression potential assay was developed which provides a quantitative measure of a cotton soils ability to support or inhibit soil-borne fungal pathogens such as V. dahliae.
Results from this study clearly indicate the presence of a genetically diverse fungal community in cotton soils and distinct variation in the community composition and diversity between fields in different cotton regions. Actinobacteria were the most dominant bacteria in cotton soils and bacterial community composition was significantly different in fields from some regions e.g. Darling Downs vs. Lochlan and Namoi vs. Theodore.
Verticillium wilt research
The management of Verticillium wilt requires an integrated approach that ultimately reduces soil inoculum levels with deleterious effects on overall soil biological health. The field trials conducted in this project have shown that rotation can reduce disease but needs to be longer than one year out of cotton where Verticillium levels are high. Two years of rotation to either non-hosts (sorghum and corn) or a bare fallow significantly reduced Verticillium levels compared to growing three years of continuous cotton. One year of rotation (corn, sorghum or fallow) on the other hand was not long enough to significantly lower disease levels. The assessment of microbial changes in the soil under the different rotations sequences suggest that management of this disease through cropping to other non-host crops that may also promote disease suppressive microorganisms may be a better option than fallow as they reduce disease incidence but also maintain overall soil biological health. A decline in overall microbial populations in the long term could potentially make soils more conducive to soil borne diseases.
V. dahliae has one of the widest host ranges of any fungal pathogen, including over 400 susceptible crop and weed hosts. It may cause classic characteristic symptoms but also has the ability to develop asymptomatic, endophytic infections. The susceptibility of some rotation crops commonly grown in the Australian cotton farming system has been largely unknown to date. Our studies have shown that grain sorghum is a non-host (previous study) and that faba bean (previous study) and cultivars of chickpea, mungbean, wheat and barley are all susceptible symptomatic hosts with some differential cultivar and strain reactions observed in some of these crops. While the susceptibility of these crops has not been proven under natural field conditions there is clearly the potential for infection to occur and close monitoring of field plants of these alternative hosts should be carefully monitored and assessed when grown in fields known to have a history of Verticillium.
To conclude, these analyses of laboratory and field based research, have provided a wealth of knowledge to address systems questions on disease management. Research to understand management strategies that promote microbial diversity, increase specific groups of beneficial microorganisms, and reduce pathogen capability to cause disease, is required.
Agriculture is on the brink of an upgrade. An increasing number of producers are becoming skilled at deploying precision agriculture technologies and the amount of data generated on farm is increasing
exponentially. Farm machinery, sensors and digital technologies are now generating large volumes of data about the status of soil, water, crops, animals and pasture. This growth in data, currently stored on and off farm on laptops, in spreadsheets, with consultants, in machinery and in supply chain data centres means that agriculture is well placed to benefit from what is commonly described as Big Data, or more precisely Big Data Analytics.
Big Data analytics promises significant productivity and profit benefits for Australian producers and the emerging “AgTech” industry is pushing producers to do more with the data they generate on farm. Unfortunately, this has resulted in many competing products and conflicting messages to producers leading to confusion and paralysis, and this is exacerbated by the noise in the market place as vendors compete to gain market share of their products and producers worry about making an expensive mistake.
Through Precision to Decision project research, it has been observed that there is a clear digital skills and capability gap within the Research Development Corporations (RDCs) and in the early stages of the industry value chains. RDCs and producer consultants have, to date, failed to develop the key skills in Data Science and Technology that are required for the digitisation of their industries and to take full advantage of Big Data.
Additionally, this skills gap has resulted in a visible vacuum of digital leadership across the Australian agricultural industries. Historically, producers and value chain organisations have leant heavily on their industry bodies and consultants for advice and direction on key industry topics. For digital, the usual sources of advice are currently coming up short.
The result is that producer businesses lack the key digital skills and capabilities required to benefit from Big Data. Worse, based on the findings from eight producer workshops, a cross industry survey of 1000 producers and individual producer interviews it is clear that they also don’t know where to start or where to invest to take advantage of the benefits of Big Data and other profit building Digital technologies. The RDCs, industry bodies and value chain participants are not communicating a common “north star” value proposition for Big Data to their producers.
RDCs must quickly address this lack of digital leadership within their industries as machinery, sensor and technology providers – both existing and new to agriculture – are moving the sector towards digitisation regardless of RDC policy. In the absence of cohesive industry digital strategies, RDCs risk being locked out of future market decisions and unable to influence the digital enablement of their industry as the commercial market consolidates and industry leaders emerge.
There is an opportunity for RDCs to accelerate the creation of industry digital strategies by collaborating on the core components of digital enablement. Particularly through co-investing in and sharing knowledge on common platforms, capability, change process and language. Without a cross industry whole-of-Agriculture digital strategy it will be difficult for RDCs to clearly communicate the benefits of digital enablement. This is currently seen in the number of levy payers missing out on co-investment opportunities that span industries, particularly those with mixed production systems.
Competitors in international markets may also leapfrog Australian Agricultural industries as they execute established digital strategies. While not affecting the Australian domestic market, this has particular implications for Australian Agricultural export activities.
Finally, inevitable, ad-hoc digital and Big Data projects both current and future will be delivered into value chains by the RDCs. As these products and services become established it will become harder for the participating RDCs to collaborate on common platforms to optimise value for their industries and levy payers.
The BDRA provides a framework to assist RDC projects with needs in Big Data collection, storage and analysis. To achieve this, the BDRA guides solution architectures by assisting with requirements definitions and identifying appropriate strategies and design patterns for Agricultural Big Data challenges.
It is important to note that a Reference Architecture for Big Data provides just one of the elements that is required to successfully transform Australian Agriculture into a data driven industry. Other elements such as Strategy, Culture, Governance and importantly the change management of each of these have been found to be equally important.
The reference architecture can facilitate collaboration between RDCs by creating a common language and approach when addressing Big Data challenges.
Research undertaken for the project, has surfaced a number of potential initiatives that can be adopted by the agricultural sector in Australia. These initiatives facilitate collaboration between the RDCs to define digital strategy and increase the velocity of adoption of agriculture decision support tools based on Big Data. These are detailed in the following recommendations arising from this research.
