FluroSense crop analytics and decision support platform has been enhanced with work-ready nutrient mapping and recommendation workflows, accessible for cotton grower via data integrations with major farm management systems.

The nutrient recommendations combine the science from widely accepted in Australian cotton industry tool NutriLOGIC/CottAssist with remote sensing imagery and sampling data from grower’s won fields. The growers’ data is used for additional calibration of the nitrogen recommendation to achieve higher accuracy through model localisation. The workflows for generation of management zones, suggested sampling points and derivation of the machinery-ready shape file with nitrogen recommendations are near-real-time, and are highly automated providing growers with the timely, tailored decision support, that has not been available to date.

The evident benefits for the growers and advisors are in the easy of use, shorter turnaround for generation of recommendations and savings on inputs from early detection and crop stress mitigation.

The case studies with progressive Australian cotton growers and agronomists demonstrate the willingness of the industry to adopt science based decision support tools, such as FluroSense, and the benefit that can be achieved from variable rate input application and improved yield through more accurate timely management.

Research summary:

In the course of the study aerial and satellite image collection campaigns were conducted covering around 17.000 ha of cotton in the Narrabri/Moree area with revisits during the season. The multispectral and hyperspectral imagery collected in the study was utilised to map the nitrogen levels of cotton crop in periods of in-season nitrogen application and later to monitor the impact of the fertilisation strategy on yield. Correlations were established between the remote sensing imagery and the cotton canopy nitrogen content. Using the remote sensing estimate of canopy chlorophyll content index (CCCI), several management zones were defined in each of the research and commercial fields taking part in the study. The tissue sampling point selection was based on the management zones and was performed in a novel way that ensures robust results with minimal testing points.

The accuracy of the nitrogen map generated by the model has been defined through a correlation coefficient of R2= 0.81. The accuracy and the practicality of the method for automatic nitrogen map generation using an online software tool were validated for in-season nitrogen management to improve the Nitrogen Use Efficiency.

Main outcomes and industry benefits:

The developed research models linking remote sensing imagery and tissue sampling results have been incorporated into an online platform, FluroSense. The online platform is designed for crop management using remote sensing imagery, and incorporates the learnings from the trials in the form of the link between the remote sensing imagery and plant tissue sampling through the management zone definition, smart sampling and scouting tools, and ultimately crop canopy nitrogen map generation tool.

The FluroSense platform has been launched with the free trial access for cotton growers in recognition of the CRDC and grower community support.

The service consisting aerial and satellite imagery in combination with the online decision support platform are now offered to cotton growers in Australia. The service allows agronomists and growers to access the remote sensing imagery, the insights from the crop health analysis, guidance on ground-truthing the crop performance with tissue testing as well as tools for generation of the management zones and application maps for in-field use. Alongside the nitrogen management tools the platform allows the users to monitor the performance of their crops across the season and perform the analysis of the yield and electrical conductivity layers, which combined with the remote sensing imagery provide a comprehensive view of the field variability and the strategies for its potential improvement.

Contact details:

Anastasia Volkova

CEO, FluroSat

anastasia@flurosat.com

A capacity to accurately assess economically important insects and their impact on crop physiology is pivotal to making informed and cost-effective decisions within an Integrated Pest Management (IPM) framework. The use of transgenic cotton provides a strong platform for IPM in the management of Helicoverpa spp. However, sucking pests such as Creontiades dilutus (green mirid) and Nezara viridula (green vegetable bug) are not controlled by the Bt toxin produced by transgenic cotton. Traditional sampling techniques can underestimate abundance of green mirid and green vegetable bug populations in cropping areas because these pests are easily dispersed and their distribution is often not uniform in cotton fields. Therefore, there is an urgent need to develop an effective surveillance system to measure peak activity of these pests throughout the growing season and to provide a predictive tool for identifying quantitative shifts in population abundance that would optimise the timing of control measures.

The Zappa trap was previously tested in proof-of-concept trials over a three year period from 2015 to 2018. Results of these trials demonstrated the potential of the Zappa trap as a sentinel tool for providing growers with an early warning of pest presence, particularly green mirids and green vegetable bugs, which are otherwise difficult to quantify under field conditions. The Zappa trap could also have a direct pest management application as an “attract and kill” strategy, potentially offering growers an alternative method to reduce pest numbers while mitigating risk to non-target species and enhancing the IPM potential in cotton.

The aim of this one year project was to further test the potential of the Zappa trap in field trials located in different cotton growing regions and under intensive sampling regimes. The results provided additional evidence that Zappa trap sampling could be a useful biological indicator for predicting the timing of mirid nymph activity in cotton because temporal synchrony was consistently observed between adult mirids recorded from Zappa trap and total mirid numbers samples recorded during in-field insect checks. Notwithstanding the possibility that Zappa trap sampling could be confounded by environmental factors such as the speed and direction of prevailing winds, the information could nevertheless provide an early warning for the presence of populations in the vicinity of cotton fields and heighten grower awareness to the need for vigilant assessment of pest abundance to optimise the timing of spray applications.

The study of trap placement on the distribution of mirids within cotton indicated that mirid nymph abundance may be influenced by distance from the trap location. Results from the assessment of crop damage generally support the insect abundance and distribution data and there was a trend toward higher levels of insect damage to bolls and lower yield potential at increasing distances away from traps, suggesting that the placement of traps in strategic locations around cotton fields could have a positive influence on yield outcome.

The predictive capability of the Zappa trap could provide the opportunity to manage populations in a timely manner and minimise the damage to fruiting structures of plants while optimising the cost of effectively and sustainably managing green mirids and green vegetable bugs on cotton. An additional benefit could be an increased understanding by growers of pest phenology and behaviour of these problematic species which could reduce reliance on chemical control measures and reduce the risk of flaring end-of season-pests in cotton such as silver leaf whitefly.

This project has conducted a nation-wide survey to better understand Australian producers’ needs and issues in relation to agricultural data. The survey included multiple industries and regions, to increase the researchers understanding of the range of issues facing different kinds of Australian producers in relation to agricultural data and identify the key factors, attitudes and perceptions that are likely to influence levels and trends in adoption of digital technologies in Australia agriculture.

The objective of this survey was to enhance the understanding of effective data technology adoption pathways, which take into account producers’ needs, perceived risks and benefits, and expectations across a wide range of agricultural industries.

To achieve the goals of the research project, the survey was designed to collect data toward the following objectives:

• To benchmark the current state of agricultural data systems, which include telecommunication infrastructure, the types of data collected and how they were stored, and the software used to manage the data;

• To examine how producers perceive the usefulness of the data in supporting farm management, their concerns over the ownership and privacy of the data they have collected, and the potential uses of aggregated agricultural data; and

• To explore producers’ willingness to share various types of data with different actors, which include other farmers, agricultural industry-based organisations, technology and service provider businesses, research institutes, and the Australian Bureau of Statistics.

Background The project ‘Feasibility study of managed aquifer recharge [MAR] for improved water productivity for Australian cotton production’ is investigating the potential to implement MAR at a regional scale in key irrigated cotton growing regions of Australia. The first focus region was the Murrumbidgee River system, with particular focus on Coleambally Irrigation Area of Operations (CIAO). This case study aimed to evaluate whether MAR could be feasible for irrigated cotton production in the Murrumbidgee region, and if so, make recommendations on further work to evaluate local hydrogeological conditions, plan the necessary site-specific infrastructure, and establish the legal, social and organisational conditions for its implementation. The broad approach taken was to draw on evidence from a holistic feasibility assessment to scope the most promising opportunities (“scenarios”) for MAR, and to test and refine these scenarios with the local stakeholder working group.

Project aims: (i) to investigate the spatial and temporal patterns of Heliothis adult and larval abundance, mortality and host use by each species and their dispersal from other crops into cotton. (ii) to investigate the oviposition behaviour of Heliothis within

The cotton industry is rapidly expanding in southern NSW. The purchase of a cotton trial picker will significantly enhance the ability of NSW DPI Plant Systems Branch, and other research organisations, to deliver accurate results from existing cotton research projects in the southern connected systems. There is no other equipment of this type available in southern NSW, and equipment that is available across the broader industry is fully committed with no opportunity to share with the owners of the equipment.

This equipment will allow greater scientific rigour to current research trials and eliminates the risk of compromised experimental results that arise as a result of the current need for hand picking of cotton trials. Hand picking leads to reduced ability to measure treatment impacts and less confidence in research outcomes. The ultimate impact of this is a lower industry confidence in, and adoption of, best management practice identified within research, and reduced potential for farmers to realise productivity and profitability outcomes.

The pest status of A. gossypii in Australian cotton has steadily increased since the 1990’s when it was considered a late season secondary pest suppressed by insecticides used against other insect species (Wilson 1996). The introduction of Bt-transgenic cotton into Australia in the 1990’s, which contains a toxin deadly to the primary cotton insect pest Helicoverpa spp., significantly reduced the number of insecticide sprays required for their control (Fitt 2003). These sprays were inadvertently controlling secondary pest populations including A. gossypii, which consequently increased (Wilson 1996). In the late 1990s significant damage from A. gossypii via the transmission of the poleovirus Cotton Bunchy Top (CBT) disease (Reddall et al. 2004) led to reduced aphid tolerance by growers, and an increase in the number of targeted sprays against them. These sprays led to resistance in pest populations of A. gossypii that have caused the chemical control to fail. Spray failures against aphids can permanently tarnish Australia’s reputation for producing high quality lint if failures lead to ‘sticky cotton’. Failures also increase grower costs and the likely hood of unforeseen environmental consequences.

The aim of this study was to investigate insecticide resistance mechanisms associated with neonicotinoid resistant A. gossypii from Australian cotton. In the present de novo assembly, a total of 132,159,760 clean reads from the pooled transcriptomes of thiamethoxam resistant and susceptible A. gossypii strains were generated resulting in a dramatically increased repertoire of resistance-related genes in A. gossypii under thiamethoxam stress. Clean reads were assembled into 37,167 contigs and from this 31,042 unigenes were assembled of which 23,372 matched known genes. Therefore, this study has generated a comprehensive transcriptome resource for A. gossypii that has characterized the expression of numerous important transcripts encoding proteins involved in insecticide resistance. Consequently, this study will contribute to future research relating to molecular characterization of insecticide resistance mechanisms of A. gossypii and other insect pests.

This project was initially developed in response to the shift in the Australian agriculture industry to a new stage of transformation: the rise of digital agriculture. Reports on the future of the industry described potential scenarios and the current research has attempted to explore what this may mean for the workforce capacity and capability requirements of the Australian cotton industry. Building capacity in the cotton industry workforce involves equipping people to proactively drive change and innovation within the industry and on–farm, ensuring the Australian cotton industry maintains a competitive advantage in the future. The research presented in this report examines how people at the forefront of change are successfully adapting as individuals and as businesses to survive and thrive into the future and identify what these changes may mean more broadly for the future of work in the cotton industry.

A key tactic within the CRDC’s 2012-12 Annual Operating Plan is ‘Assuring industry capacity to manage the stewardship of biotechnologies and crop protection products’. Refuges are key to maintaining the viability of Bt cotton by delaying resistance development in Helicoverpa to Bt toxin. However, to ensure the best resistant management strategies are in place for Bollgard III, refuge assumptions need to be confirmed.

In a previous summer Scholarship (CRC 5.10.03.31 SS) refuge assumptions were tested, finding 1) no difference on commercial farms in the number of eggs laid on pigeon pea and cotton refuges; and 2) that more moths were produced from cotton refuges. Because these results are controversial, , the researcher proposes to repeat the study, but include additional measurements of nitrogen and moisture content of the refuge crop, as laboratory results indicate that these parameters affect refuge attractiveness and productivity. The aim of this project is to clarify the findings of relative attractiveness and productivity of commercially grown cotton and pigeon pea refuges. This information will enable us to quantify refuge productivity.

This project will involve sampling refuges on approximately 20 farms. The direct involvement of growers with this project will increase their ownership and acceptance of the results.