Farming systems in cotton are changing and weed management is again becoming more complex. The rise of herbicide resistance, particularly to glyphosate and the imminent introduction of new herbicide tolerant traits to dicamba and glufosinate has changed the way weeds need to be managed. The project team undertook to pre-empt these changes.

Three new modelling and decision support products were created for industry. The BYGUM decision support tool predicts economic outcomes from summer grass weed management strategies. The tool can be used to create and compare five-year rotations of cotton, grains and fallows, including cover crops, demonstrating the effectiveness, cost and efficiency of herbicide and non-herbicide weed control. BYGUM has been used in workshops and to create extension materials, and has been downloaded by over 300 unique users to date. The Weeds of Australian Cotton ID app allows identification of 50 key weed species in cotton fields. The app uses the Lucid framework and an extensive image library. The app is among the first to include cotyledon shape as a factor for identification, meaning weeds can be identified while still small enough to control effectively. It is free to use and available in Apple and Google app stores for use offline, and via the Identic Lucid Key library for use on desktop and laptop computers.

The Diversity model is a world-first multi-herbicide, multi-species, polygenetic model of herbicide resistance evolution. It determines and quantifies how much diversity is enough, to slow or prevent evolution towards resistance. We used the model to assess the resistance potential of weed management under new triple stack systems, such as Xtendflex® cotton. Our results suggest three key points:

1. That these systems are substantially more diverse than Roundup Ready, and with the right extra tactics can be the basis of long-term effective weed management;

2. Glyphosate, glufosinate and dicamba alone or with minimal extra modes of action are incapable of controlling our existing glyphosate resistant grasses and fleabane—systems are likely to fail due to poorly controlled resistant populations long before new resistances have time to develop;

3. The 2+2+0 strategy is predicted to remain effective, but modelling multiple species at once reminds us that both grasses and broadleaves need multiple effective options in the system.

Genetic exploration of the mechanisms of glyphosate resistance in key weed species led to the discovery of the key role of ploidy and gene copy number in the evolution of glyphosate resistance. Our work on gene expression in fleabane and the genome assembly showed that there are many copies of the target site EPSPS gene in this species. This makes it very hard for fleabane to evolve target site resistance to glyphosate because many copies have to have a mutation, instead, species with many copies of the target site gene have to evolve non-targetsite resistance and this is more difficult for the weed because it usually involves more than one mutation. Feathertop Rhodes grass was found to be diploid with one copy of the EPSPS gene, and this species evolved resistance over 10 times by target site mutations. This understanding explains why it took sowthistle so long to develop resistance to glyphosate, and allows us to make predictions about herbicide resistance evolution in the future. Diploid species with one copy of the target site gene will be more likely to readily evolve resistance to a herbicide than polyploid species or those diploid species with multiple copies of the target site gene.

Work on the population genetics of four key species led to some surprising results. Fleabane is considered a well-dispersed species, but had strong regional genetic structure indicating that wind dispersal may play less of a role than previously expected. Windmill grass and feathertop Rhodes showed very little evidence for outcrossing, but there may have been some admixture in the past. Outcrossing is important because it affects the ability of a weed to develop resistance to multiple modes of action (MOA). Fleabane and sowthistle had evidence for some outcrossing in the genetic data, but we were unable to find experimental evidence for outcrossing in 200 offspring of each species. This highlights how very low levels of outcrossing might still play an important role in the evolution of resistance in species like fleabane that we had previously thought to be only self-pollinating.

In windmill grass and feathertop Rhodes grass, their highly selfing reproductive mode can be used in the fight against herbicide resistance. These species are less able to ‘stack’ resistance to different modes of action.. Our work shows, however, that feathertop has evolved resistance multiple times and how these have spread across the cotton system, and that almost 1/3 of windmill grass populations are now resistant. Each glyphosate resistant individual has the potential to evolve resistance to a second MOA. and our work highlights the importance of controlling glyphosate resistant populations to avoid multiple MOA resistance. Overall, the population genetics work emphasises the importance of the ‘0’ in the 2+2+0 strategy survivor control is essential to prevent the spread of resistance and to avoid multiple MOA resistance.

Studies on the growth and development of awnless barnyard grass, feathertop Rhodes grass, windmill grass, fleabane and sowthistle were conducted. In general, with the summer grasses, plants that emerged at the start of summer grew larger and produced more seed than those emerging later. This is where the focus of control should be for the greatest impact. However, it is important to note that plants emerging later still produce seed and need to be controlled. Sowthistle now has the ability to emerge and grow well throughout the year. Fleabane also appears to be adapting to warmer temperatures, readily producing seed throughout spring, summer and autumn.

The addition of glufosinate and dicamba has the potential to improve control, particularly on the five key species tested. When glufosinate was used, as a double knock partner, effective control was achieved in both glyphosate-resistant and susceptible populations tested. The glufosinate double knock should prove an effective option in Xtendflex® cotton.

Research on cover crops was hampered with dry conditions, and as the result the effects on weed emergence were limited. However, growers have shown cover crops to be an effective option provided they start with a clean crop and ensure that the cover provided is adequate and evenly spread.

The 2+2 and 0 was shown to be an effective management strategy for long-term resistance management. Research also concluded that additional options will provide more effective control in years with more rainfall events and subsequent emergences.

This project aimed to provide ecological information on an important pest species to underpin strategies for resistance management in Bt cotton. The cotton industry relies on Bt, now in Bollgard III® varieties, which provide security to growers, enable new farming systems and reduce pesticide use, ensuring continued social license to farm. At the time the project began, these benefits were threatened by rising frequencies of alleles giving resistance to Bt, especially to the Cry2Ab toxin in H. punctigera. Current resistance management plans were designed for H. armigera, but now they also had to consider H. punctigera. Updating our understanding of H. punctigera was therefore crucial. We needed to revisit key questions such as immigration from the remote inland, which was previously thought to be extensive and a valuable asset for resistance management, because it brought genes from unselected populations into cropping areas, thus diluting resistance.

For the previous three years, we had studied the ecology of H. punctigera in western Queensland, and compared results to the work we and others did in the 1980s and 90s. We had found that many remote inland areas still regularly produced many H. punctigera, but there was evidence of decreasing immigration to cropping areas. We speculated that the Millennium Drought of 2001 -2009 may have changed the distribution and abundance of key host plants, especially in mulga regions of western Queensland which act as a bridge to enable migration from the floodplains and sandy deserts of central Australia to cropping regions. However, in such a variable environment as inland Australia, we needed more data. This project aimed to provide better understanding of long term changes in H. punctigera populations that might affect pest impacts on cotton and other crops, and management of resistance to Bt in cotton.

We established ten pheromone trapping sites, six in western Queensland and four in non-cropping regions of South Australia, to monitor moth populations. Results showed fewer moths than before the Millennium Drought in parts of western Queensland, but substantial numbers in some South Australian sites, suggesting alternative migration routes from the inland. Eleven survey trips were made to inland regions, during which larval populations were sampled by sweep netting, and vegetation conditions and the presence of host plants were recorded. These results indicated a depletion of good host plants in the mulga regions since the drought, which probably contributed to reduced migration. We also studied diapause induction and termination and the timing of spring emergence in inland populations, and the potential for host plants with the C4 photosynthetic pathway to contribute to inland populations.

We added results from this project to data from earlier projects in a geographic information system which provides a long-term record that is unique in the study of insect pest ecology in Australia. The information will be crucial for the development of pest forecasting systems for a range of crops affected by H. punctigera. For cotton it has provided a long-term perspective of changes in resistance to Bt which indicates that increases in the frequency of resistance alleles in H. punctigera may occur from time to time due to prolonged droughts. However such increases are unlikely to be sustained, and the greatest resistance risk continues to be posed by Helicoverpa armigera rather than H. punctigera, because this species does not develop large populations in the inland.

Development of a land use indicator set for the Australian cotton industry to demonstrate the sustainability impacts on soil health:

May we recommend that the follow criteria be considered when developing an indicator set for the Australian cotton industry:

General:

• Land use will probably be one of a number of environmental impact categories being assessed by an LCA practitioner as part of a sustainability assessment, each with their respective metrics, and therefore the number of land use metrics need to be practical and manageable from this perspective

• Apart from meeting specific industry requirements, the cotton industry should also use this framework and initiative to communicate its own sustainability achievements as part of regular reporting.

• Through this initiative, the Australian cotton industry should aim to stay at the forefront in this space

• This is a new sustainability space and industry is only applying a single indicator / metric for land use at present. The Australian cotton industry may therefore be afforded the leniency of adopting a conservative and phased approach whereby a limited and suitable number of indicators are implemented at first, with the intention of increasing this as practical data structures become available or put in place.

• Importantly the programme should be of direct benefit to growers to address their concerns about the state of the soil that they will be passing on the next generations

Therefore, specific recommendations:

1) Use 2 sources of data: firstly grower surveys to assess land use intensity and input intensity, and secondly soil test data for another 6 metric outcomes

2) Indicators from soil tests: soil organic carbon, ph., phosphorous, potassium, nitrogen (total, nitrates and ammonia), CEC and % sodium.

3) Soil compaction is a major concern for growers and therefore an additional ‘wet sieving’ test will give an indication of soil structure and stability – it appears that Nutrient Advantage is not able to do this but EAL Laboratory can for $60, and separate samples will have to be sent there but it is probably justified.

4) All results received form Nutrient Advantage lab and therefore provides a common methodology and able to utilise historical grower data for the database and trending – growers that we have consulted is agreeable to this.

5) Form the “soil sustainability awareness group’ SSAG with a pilot group of concerned growers to ‘test’ the programme to assess how it could be rolled out on a regional and national scale.

6) Growers are required to take soil test at those specific sites including a ‘native’ sample each year, according to a standardised procedure.

7) Results will be expressed as a % relative to the native soil, which can be benchmarked, aggregated as a single farm score, and scaled / aggregated to a regional and national level accordingly.

8) Results will be treated anonymously although will receive their specific results evaluations, along with their normal results via their agronomist / consultant.

9) CRDC / Cotton Australia or a funded project may have to cover the costs of the additional native soil test, the wet sieving test and potentially the assessments.

It is unfortunate that the above indicators will not assess soil biology / microbial life, but this is an expensive, time consuming procedure. Fortunately soil carbon is a strong driver of soil biology, and perhaps a suitable proxy indicator could be introduced for this in the future.

We have had discussions with a number of growers, who have been very supportive of the idea, and keen to join such an initiative and are willing to provide their historical soil test data. We have also consulted with relevant scientists for their views and recommendations which have been taken into consideration.

A weed control threshold for cotton production was first released to the Australian industry in 2008. It has been widely used as a guide to the level of weed pressure that can be tolerated in fields without economic damage occurring. However, the model behind the threshold was based on a limited data set, derived using the ‘mimic weeds’ (common sunflower, mungbeans and Japanese millet), based on the assumption that the level of competition from these ‘mimic weeds’ could be readily related to real competition levels from real weeds.

Project DAN1601 focused on testing the underlying assumption that the competition results from mimic weeds could be related to real weeds, and, assuming the approach was valid, using a much larger data set to derive a more accurate threshold.

Data from 3 years was used to test the validity of using mimic weeds to define competition in irrigated cotton. Competition levels were compared between differing population densities of: fierce thornapple vs. common sunflower; bladder ketmia vs. mungbean; and, awnless barnyard grass vs. Japanese millet. Many similarities and differences were found between the mimic and real weeds, but an underlying relationship was derived that showed that as far as the cotton was concerned, the only real differences between the six ‘weeds’ were related to weed height and biomass – in other words, bigger weeds are more competitive! So, competition experiments using mimic weeds are valid, and a lot easier to conduct than experiments using real weeds. Also, the findings of this work showed that it is possible to extrapolate the results from a few mimic weeds to a wide range of real weeds.

Based on this finding, data from field experiments between 2002 and 2015 was collated and analysed to develop much more accurate relationships between the three mimic weeds weeds’ (common sunflower, mungbeans and Japanese millet) and irrigated cotton. Three papers were developed, one for each weed type, developing dynamic weed control thresholds for these weed types. The first of these papers has been accepted for publication and the second paper has been submitted to the publishing journal. The final paper will be submitted when the third paper is accepted.

Results from the first paper showed that for a large weed (eg. fierce thornapple, Noogoora burr, sesbania), densities of 1 per m of row caused more than 5% yield loss if present in the crop between 43 and 615 GDD. Higher densities caused higher levels of damage. Where the weed can be controlled with glyphosate, a 1% yield loss threshold is more realistic, extending the critical period for weed control for 1 weed per m row to between planting and 836 GDD.

It is hoped that the next two scientific papers will be accepted for publication later this year, and then the results from the work can be extended to the Australian industry, giving growers a firm threshold for controlling weeds in irrigated cotton.

In addition to this core work, the project has continued to support the cotton industry through articles, meeting and input into the weeds sub-committee of the TIMS panel, as well as in other areas.

Work on a pupae busting experiment has continued, preliminary results indicating that pupae busting does deliver additional benefits through improved weed control.

A study into 2,4-D damage, prompted by the heavy damage experienced in the Walgett area in the 2017/18 season, highlighted the very low levels of 2,4-D that could cause damage to cotton. A series of tissue tests determined that damage at ACRI observed in this same season was caused by 2,4-D concentrations below the level of detection by instruments.

At the request of the CottonInfo team, all main articles in WEEDpak have been updated, and short (4-page) CottonInfo sheets developed from the longer articles.

This project has also had a large input, as lead, of a parallel project, DAN1805, the “Biological control and taxonomic advancement for management in the Noogoora burr complex”, which also finished in June 2019. The project involved a number of different facets and was exceptionally successful in achieving its objectives in spite of many issues. A final report on this project has separately been submitted to CRDC. Outcomes included: re-evaluating the taxonomy and distribution of the Noogoora burr complex, showing that based on genetics, there appears to be only two groups of burrs (species), with many hybrids occurring; successfully developing a bioherbicide which is effective across all the Noogoora burr species; and determining that all plants in the Noogoora burr complex are hosts of the Verticillium wilt pathogen, with multiple defoliating and non-defoliating strains of the pathogen isolated from the burrs, often with more than one strain present in a single burr. Four scientific papers are currently being developed from this project.

Following the success of the technology developed around the bioherbicide for Noogoora burr, steps towards commercialisation of a bioherbicide for Bathurst burr have been commenced.

The AgFutures – Innovation and Investment Conference was held on the 22-23 November 2016 at the Brisbane Convention and Exhibition Centre. AgFutures was the first Queensland conference focusing on future technology in agriculture and agricultural investment opportunities. Internationally-renowned researchers and innovators demonstrated the latest agri-tech developments and applications, including digital and data platforms, robotics, satellites, and bio-technologies.

Experts from the business and investment community also discussed emerging trends, business opportunities and capital models from the farm gate to agribusiness, agri-tech, processing and research.

As part of the conference, the Peter Kenny Medal and Minister’s Emerging Leaders Award were presented at the AgFutures Conference Dinner.

The project UNE1403, Prodessor of Soil Systems Biology, was established between UNE and CRDC in 2014. Dr Oliver Knox was recruited from Scotland’s Rural College (SRUC) to the post marking his return to Australia and the cotton industry. In the first few months of the project the Cotton Hub at UNE was established and the remit of this aggregation of academics established. Over the past five years the Cotton Hub, under Oliver’s coordination, has been privileged to host the CRDC board twice at UNE, to develop a network of no fewer than 25 academics across five of UNE’s nine schools, support several PhD candidates and foster more collaborative responses to funding calls, both within UNE and in collaboration with other research partners. The Cotton Hub has also generated several Spotlight and Cottongrower articles to increase the industry awareness of research activities associated with the hub as well as developing a growing social media presence via both an on-line blog and the Twitter handle @CottonHubUNE.

The research conducted under this project has also resulted in a modified and improved method for the passive recovery of free living soil nematodes from heavy clay soils, such as the grey and brown vertosols that much of the industry relies on. The method represents a saving in sample processing time as well as a reduction in potential sample size, in theory making more rapid nematode recovery and analysis possible.

In addition to this, the work has used capacitance probe data sets to establish the extent of the industry where cotton is being grown in just the top 60 cm of the profile. The analysis conducted over three seasons from 2015 to 2018, showed that approximately 25% of fields suffer from sub soil constraints that prevent root exploration below 60 cm during peak vegetative growth. These numbers are similar to physical studies conducted through the McIntyre in the 1980’s, but have allowed areas from all of the cotton growing valleys to be studied across most years. The work has gone on to look at the nature of the constraints likely to be reducing root exploration and also observed that where an awareness of the constraint is known and appropriate management is put in place, profit margins remain good. Potential remedial management to alleviate some of these constraints is now being undertaken in other projects.

Border cells were again investigated under this project. Whilst newer cotton varieties have more than those that were commercially available 10 years ago there remains no link with the resistance to wilts or black root rot. Exogenous DNA (exDNA) from these cells was also quantified and appeared to have little effect on these pathogens, but it was also noted that cotton appears to produce less exDNA than peas and maize.

Finally, the project took on the delivery of the Cotton Production Course. The units continue to deliver a scientific approach to aspects of cotton production, protection, system development and position in the wider environment and to attract the majority of their students from industry.

EXECUTIVE SUMMARY

Spray drift, the off-target movement of herbicides and pesticides, negatively impacts agricultural production across Australia. The problem is particularly acute in mixed cropping regions where a diverse range of chemicals may be applied at any given time. Although industry organisations have developed and implemented an impressive set of technologies, education programs and workshops aimed at improving spray solutions across multiple agriculture sectors, the problem persists.

This project used theory and methods from the behavioural sciences to:

1) Identify the main drivers and barriers to engagement in best-practice spray application at three time points: Before spraying, during spraying and after spraying.

2) Identify the number and nature of grower segments based on their current practices before, during, and after spraying.

3) Identify the main leverage points to initiate and sustain behaviour changes to reduce spray drift.

4) Recommend targeted engagement strategies for segments that are not engaged in best-practice spraying.

Using interviews of key industry stakeholders, and an online grower survey we identified seven behaviours that, if adopted, would produce the greatest reduction in spray drift:

1) Before spraying:

a. Using online mapping tools to register crop locations

b. Checking online sources for sensitive areas

c. Discussing spray plans with neighbours.

2) During spraying:

a. Driving at recommended speed

b. Spraying when conditions (Delta-T, low risk of surface inversion, wind speed) were suitable.

3) After spraying:

a. Decontaminating spray equipment appropriately

b. Keeping accurate records.

Audience segmentation analyses identified 3 grower segments for the before-spraying behaviours (Disengaged, Partially engaged and Engaged), 3 grower segments for the during-spray behaviours (Disengaged, Partially engaged and Occasional speeders) and 2 grower segments for the after-spraying behaviours (Disengaged and Engaged). Discriminant analysis identified the primary barriers (classified as capabilities, opportunities and motivations) for each of the behavioural segments that were not engaged in best-practice spray behaviours:

1) Before spraying (Not registering or checking online mapping tools):

a. Not being aware of the mapping tools (capability)

b. Not having the time to check the online sources (opportunity)

c. Not knowing anyone else who used the mapping tool (motivation).

2) Before spraying (Not discussing spray plans with neighbours):

a. Bad relationships between neighbours (capability and motivation)

b. Growers saw no need to discuss plans (motivation).

3) During spraying (Not driving at recommended speed):

a. Not enough time when conditions are suitable (opportunity)

b. Not aware of the link between speed and spray drift (capability)

c. Need to complete job (motivation)

d. Field conditions (opportunity)

e. Perception of reduced efficiency at slower speeds (motivation).

4) During spraying (Not spraying when conditions were suitable):

a. No flexibility with the contractors /staff resulting in spraying when somebody was available to do so regardless of conditions (opportunity)

b. Beliefs that their crop production took precedence, getting the job completed was the priority and spray drift was not an important issue (motivation)

c. Perception that everyone cuts corners and sprays in less than ideal conditions so it was acceptable for them to do so as well (motivation)

d. Knowledge about when conditions were suitable to spray (capability)

e. Perception that no-one would know anyway if they did spray in less than ideal conditions (motivation).

5) After spraying (decontaminating spray equipment):

a. Awareness of the need to decontaminate (capability)

b. Having the time to perform decontamination (opportunity)

c. Having a suitable location to decontaminate (opportunity)

d. Perceiving decontamination as important (motivation).

6) After spraying (keeping accurate records):

a. Awareness of the need to keep records (capability)

b. Forgetfulness (capability)

c. Perception that no-one was going to check anyway (motivation)

d. Not knowing anyone else who kept records (motivation).

Based on these results, we recommended which behaviour change techniques would be most suitable to remove and circumvent these barriers to achieve maximum on-ground impact. Further research is needed to implement and evaluate behaviour change interventions based on the results from the current research. This implementation and evaluation lies outside of the scope of the present project.

Diseases of cotton are of a significant constraint to cotton production and have been identified as key areas for investment by the cotton industry. Sustainability of the Australian cotton industry remains dependent on the continued development and adoption of cultivars that are highly resistant against major soilborne pathogens such as Thielaviopsis basicola, Fusarium oxysporum f. sp. vasinfestum and Verticillium dahliae, and a re-emerging Alternaria leaf spot (ALS) pathogen, Alternaria alternata. Incorporating high yielding traits with disease resistance is a difficult long-term process; and with limited resources, it is not always possible to develop a complete resistant cultivar to all diseases. Therefore, effective management of cotton diseases relies on an integrated approach. a key focus of this project was to identify non-cotton fungicides, novel chemistries and biocontrol agents, which can be integrated into management strategies of major diseases in cotton production systems.

This project has identified a number potential candidates/approaches. Several pathological research gaps that could be further investigated for their efficacy and insights into pathogen biology. These are as follows:

• Non-cotton fungicides A-16148-F and Fungicide 2, and a novel plant extract PlantY provided a potential black root rot (BRR) control, but there was a lack of control consistency and required further assessments;

• In response to the leaf spot outbreak on seedlings in 2017/18 season in southern NSW, Alternaria alternata was a predominant pathogen responsible for the outbreak;

• Mancozeb and Tebuconazole have been granted an emergency application permit on both seedling and mature cotton in the event of a future outbreak;

• Incorporation of a brassica crop could provide a potential alternative practice to suppress the V. dahliae population, but this requires a long-term field assessment for inclusive recommendations;

• BRR and Verticillium wilt pathogens are now widely distributed in NSW, but insights of their biology and diversity are largely unknown. Such knowledge is essential for developing an accurate and rapid detection approach, as well as management strategies;

• Assessing for disinfestation efficacy against BRR and Verticillium wilt pathogens of Farmcleanse-alternative products will be vital for farm hygiene practices;

• Studies focused etiology and epidemiology of a sporadic but important boll rot disease should also be a priority.

State-based agencies such as NSW DPI have historically played an important role in providing responses to industry needs and delivering leadership in cotton pathology. This project built and enhanced research capacity by the appointment of an additional cotton pathologist based at NSW DPI Narrabri. The aim was to retain grower confidence in the cotton industry to provide support and leadership of cotton pathology issues. The appointed team including Dr Duy Le and Aphrika Gregson has collaborated with Queensland cotton pathology team, southern NSW Cotton Crop Protection specialist based at Yanco Agricultural Institute and CottonInfo team. Such collaboration allowed us to investigate into a broad array of plant pathology research activities such as disease surveillance, management and diagnostics.

The autumn edition of CRDC's magazine, Spotlight, takes a look at two innovative new initiatives underway: the research and development corporation collaboration Agricultural Innovation Australia, and the Federal Government’s Business Research and Innovation Initiative. CRDC is excited to be a part of both these initiatives.

Also in this edition, we include several articles on innovative technologies that CRDC is investing in as they come to the field. These exciting developments include a new pest detection app, which will change the way we monitor insects, and new yield prediction software. CRDC has not only supported the development of the software, it has supported much of the foundational research which drives the technology. We were also pleased to collaborate with CSIRO’s Data61 on the On Farm Experiment app, using data through a CRDC Grassroots Grant. Once released, this will be a game changer for growers wanting to do on-farm trials.

These applications are reflective of two of our key focuses for 2021 – increased commercialisation and digital transformation. CRDC and our research partners are currently seeking partners to take these technologies to the commercialisation phase: the next step towards ensuring real, tangible benefits for growers and industry.

Project details: CRDC project ID: MLAB1901

CRDC goal: Click here to select a Goal

CRDC key focus area: Click here to select a KFA

Principal researcher: Dr Maria Manjarrez, Research and Development

Organisation: Microbiology Laboratories Australia

Start date: July 2018

End date: June 2020

Objectives • To verify if the ready to use Test is robust enough to recover infective T. basicola propagules in different soils or farms

• To correlate the levels of T. basicola from field soils or “naturally” infected soils against plant symptoms or disease in cotton

• To determine what other fungi are predominantly involved in causing BRR, if any

Background From the CRDC project 1624 it was concluded that a “ready to use test” selected in that project for quantification of BRR needed to be fine-tuned using “artificially” infected soils. The initial development of the test used one soil type with or without black root rot. The initial quantification using the ready to use test was merely based on the contrasting levels without taking into account what was happening with the plant (disease incidence).

To verify those results, soils with different levels of BRR and with different properties needed to be tested. If the test was robust enough, the end result will be a tool to help reduce the risk associated with the disease.

The test needed also to be adjusted to test for the interaction with other plant pathogens causing root rot as previous results showed that black root rot may be the result of different fungal species acting together to produce the disease. The results may be used to design a multi-species detection test.

Research activities Our team worked with ±50 soil samples with different BRR histories, from different cotton producing regions (Whitton, Hay, Hillston, Griffith, Macquarie, Lachlan, Canargo, etc). Soil samples were used to establish 4 experiments under controlled conditions. In Experiment 1 and 2, trap plants such as green beans, soybean and pansy were used to facilitate and speed up quantification of T. basicola. However, the trap plants used gave variable, unrepeatable results, which made detection of the pathogen unreliable. After adjusting the methodology and by following advice from the CRDC research team, experiments 3 and 4 were setup using Sicot 620 cotton seeds supplied by Cotton Seed Distributors (CSD). Both experiments gave repeatable results when using the ready to use test with some statistically significant data. Statistical correlations were achieved between BRR levels and reduction of cotton seedlings biomass under controlled conditions. The test was also detecting other pathogenic fungi such as Fusarium and Verticillium.

Outputs From the total number of soil samples, results showed that 8 samples had below detectable level or zero colonies, 6 sites had less than 10 BRR/g soil, 8 had 10-30 BRR/g soil, 11 samples had 30-100 colonies and 9 samples had more than 100 colonies (up to 2000)/g soil after the soils were planted with cotton for 6-10 weeks under controlled conditions. T. basicola also varied depending on the “dilution” of the original soil (from 20% to 50%) for each site. The sometimes very high variability between the soil dilutions during the testing made correlations not always significant. However, some important results were obtained.

Our project concluded that the ready to use test can achieve with reasonable accuracy, quantification of T. basicola at very low, intermediate and very high levels in soils from different farms or sites, which have different chemical and physical properties. This conclusion came after results showed statistical correlations (and or linear regressions) between shoot dry weights and BRR levels (P= 0.0003). These mathematical models may be used to help reduce the risks associated with the disease.

In addition, results showed that plant biomass started decreasing at just 30 BRR colonies/g of soil, which is new information that could be used to correlate better with what is happening in the plant. There was not big difference in biomass reduction after 100 BRR colonies/g soil, however some soils showed up to 1500 BRR colonies/g of soil after planting cotton under controlled conditions.

Another important result was the detection of other pathogenic fungi such as Fusarium and Verticillium using the ready to use test. Although there were no significant correlations between the levels of these fungi and the reduction in cotton seedling biomass, results can be used to better manage seedling diseases in such a cases as fungicide management.

Impacts As results showed a mathematical correlation between BRR levels with biomass reduction (and root “quality”), the ready to use test could be used to reduce the risks associated with the disease (at least partially as other factors may be involved in this complex production system). In discussing the results, we see an opportunity for new cutting-edge data analytics to be paired with the mathematical model so it can “learn” to predict the disease incidence better in the near future so farmers can fully take advantage of this tool.

Key publications 1.Participation at Australian Soil Science conference (suspended for 2020) but will be attending in 2021

2.FUSCOM 2020 presentations- Farmers (October) and Scientific (November, 2020)

3.Twitter

4.Honours Project: “Can Trichoderma and Bacillus be used as biocontrol agents against T. Basicola (BRR) in cotton?” An in-vitro study. Fabiel Hernandez-Espinosa. International Student. 2020. He will be presenting at FUSCOM 2020, scientific program.

Appendix 1

Example of Report generated after soil samples were tested using the Ready to use test. One report per soil sample.