Fertiliser nitrogen use efficiency in irrigated cotton was assessed on the Darling Downs over 3 years. A total of 47 treatments were examined from 2015/16-2017/18 from 12 locations combining N application rate (farmer’s practice vs 30% reduction), product (urea v DMPP) and irrigation method (furrow vs overhead).

The average yield across all sites and years for the three main fertiliser treatments (DMPP, Urea and Farmer’s Practice) was 9.9 bales ha-1 with the farmer’s average N application rate of 161 kg N ha-1. There was no significant effect of different fertiliser products and reduced rates on lint yield. On average 81 kg N ha-1 was removed in the lint and seed and 138 kg N ha-1 was lost from the system (maximum 260 kg N ha-1) in the form of soil and fertiliser N over the cropping season.

Nitrogen fertiliser use efficiency in irrigated cotton systems was consistently low, with 47% of the applied fertiliser lost over the season. The average rate of N application was only 137 kg N ha-1, well below the industry average of 275 kg N ha-1. We estimate that non-fertiliser derived N losses were 24% of mineralised N.

On average, only 17% of the N taken up by the crop was derived from fertiliser i.e. 83% was soil derived N. Nitrogen fertiliser losses were lower in the overhead irrigated sites (35%) compared to the furrow irrigated sites (51%). At harvest, on average 28% of the applied N was recovered in the soil, with 11% removed in lint and seed and 14% remaining on the field as residual plant material.

The use of the nitrification inhibitor DMPP increased the recovery of N fertiliser in the soil (at harvest) by 21% and reduced overall losses of N fertiliser by 16%, indicating that DMPP could potentially increase fNUE in irrigated cotton systems. More long-term trails on the effect of DMPP in irrigated cotton systems are required to better assess the potential of this product. Ideally, these are done with reduced N rates over multiple years and in N limited systems.

In addition to the N fertiliser, on average 264 kg N ha-1 was supplied from soil mineralisation (169 kg N ha-1) and mineral N in the soil profile at planting (144 kg N ha-1) compared to an average fertiliser application of only 137 kg N ha-1.

Commercial farms have highly elevated levels of available N in the soil, most likely due to excessive N fertiliser applications in previous years. Total crop N uptake averaged 218 kg N ha-1 in the N fertilised treatments, while an average of 194 kg N ha-1 taken up by the crop in the 0N plots. Our results confirm that growers could significantly reduce N fertiliser inputs without any negative impact on lint yield.

Nitrogen fertiliser is not used efficiently under current on-farm management strategies and demonstrates that mineralisation of soil organic N and recycling of N from previous fertilisation events or returned with crop residues is a key source of N in irrigated cotton production systems.

The intercomparison of calculators highlighted the great variability in the N recommendations on offer to the cotton industry. These differences can be attributed to the different methods used to estimate soil N mineralisation, crop residue decomposition and N losses.

The project has shown that remote sensing can provide accurate prediction of yield variability with RDVI being most suitable vegetation index for identification of in-field variability and in field management zones.

For the delineation of management zones it is crucial to have a certain degree of in-field variability and to use multiple years of data to understand whether variable yields are either stable or unstable.

Remotely sensed Vegetation indices could potentially be used in early January to assist in-season N management, but it is essential to evaluate the causes of variability in order to develop N management decisions.

At 31st December 2019, the Agfrontier Regional AgTech Incubator program was at the halfway point in its 14-month long duration. A cohort of ten agricultural innovators was selected from more than 30 applications received from across northern New South Wales and regional Queensland. The cohort is made up of start-ups and spin-offs at all stages of development, from ideation to Series A capital raise. There is a mix of hardware, firmware and software solutions as well as a spread of sectors across cropping (including cotton), livestock, horticulture and bee-keeping.

The program has focussed on creating a bespoke suite of tools to up-skill and equip the cohort with the knowledge, know-how and networks to go global. Key learnings from the program in terms of incubator program design have been:

1. The start-up ecosystem in Australia is still permeated by too much jargon and language that doesn’t lend itself well to the agricultural innovation audience;

2. One-on-one coaching for our cohort is frequently done in the car, in a tractor or out in the middle of a paddock or late at night. This means needing to adapt mainstream tools and techniques to compensate for this, particularly where regional connectivity remains a considerable challenge.

3. Relationships between cohort members have developed to have a constructive influence on program outcomes with interpersonal coaching, mentoring and business collaborations. This wasn’t an expected outcome in the original program design, however, has been a positive factor.

4. The importance of focussing on founder mental health as a component of the incubator program design has become very clear. Drought and its impact on both direct farming operations and the cohort customer base agribusiness function has brought this into sharp focus. Future program design will put more emphasis on shared knowledge, understanding and managing founder mental health.

Significant success has been achieved by our inaugural cohort, a short summary of key achievements below:

1. SwarmFarm Robotics based in Gindie, Queensland awarded 3rd place at the Global Agripreneurs Summit in Thessaloniki, Greece after winning the national event in Australian in 2018. They were also named as one of the world’s top 5 robotics start-ups by Startus Insights, an international data science company identifying emerging start-ups & technologies to deliver actionable innovation intelligence.

2. DataFarming based in Toowoomba, Queensland accepted in to the TERRA agrifood accelerator program, beating over 500 applicants from more than 30 countries to be the first Australia firm in this prestigious program. They were also named one of the 15 most promising agtech start-ups in the world by Startup City Magazine, an independent platform for decision makers in the United States, for the latest in start-up ecosystem news. Co-founder Tim Neale was also awarded the 2019 Pearcey Queensland Entrepreneur Award in October.

3. Ben Harzer from Thin & Trim Holdings in the Gayndah / Mundubbera district, Queensland successfully won a place in the Austrade Startup Catalyst Mission to Israel in November.

4. Two of our cohort have attracted significant venture capital investment either already in contract or under due diligence (both announcements currently embargoed).

5. A prototype was developed by Broken Plains Pastoral at Rolleston, Queensland from conceptual idea tackling the multi-million-dollar problem of buffalo fly in the beef industry.

6. An initial order for minimum viable product was placed by Big Sky Technologies based in Toowoomba for their exciting regional connectivity solutions. They were also long-listed for the MLA’s Digital Livestock 4.0 project, and;

7. AgFrontier was recognised by Brad Twynham, Incubator Facilitator with the Australian Department of Industry, Innovation and Science as being in the top 30% of all start-up incubators in the Australia (not just agtech focussed). We have fielded several inquiries from agricultural innovators wanting to apply for any future programs as well as organisations wanting to collaborate with us to deliver the program.

Some key numbers for Agfrontier:

• Three intensive face-to-face workshops completed with +85% total attendance;

• Average feedback score from participants was 4.5 (scale 1 low to 5 high);

• ~100 hours one-on-one coaching delivered, and;

• +260 attendees at AgTeCH19 Emerald: Build it. Use it. Profit.

The remaining program content includes for field visits to the six cohort businesses who have successfully been accepted into Stage 2 of our program, the Startup Catalyst AgFrontier Mission to the USA (Denver, Colorado, San Francisco & Silicon Valley, California), AgTeCH20 Mungindi Start-up Alley (1st April 2020) and the finale milestone event and investor pitch in Brisbane mid-2020. We look forward seeing the cohort further develop, garner investment and scale with the remaining program modules and thank our program partners for their support and investment in this worthy program for Australia’s agricultural industry.

A well-managed supply of clean, usable groundwater is vital for the continued success and growth of the Australian Cotton Industry. The ongoing provision of clean groundwater depends on healthy groundwater ecosystems containing microbes and invertebrates (stygofauna). These biota improve water quality and aid water flow. Without the sustainable management of groundwater, it is likely that the health of these ecosystems will decline, with the consequence that growers may be faced with increased costs for groundwater extraction, water treatment and/or declining cotton yields.

In 2006, the cotton industry, through the Cotton Catchment Communities (CCC) CRC, became the first industry in Australia to recognise the importance of groundwater ecosystem health for the supply of sustainable groundwater resources by funding the development of a groundwater ecosystem monitoring program. The CCC CRC began a world first program to develop a toolbox of biological and chemical indicators to measure and monitor groundwater ecosystem health.

Further funding from the CRDC, through the project reported here (2014-2018), enabled the initial toolbox to be refined through additional sampling and research. From this work, the weighted Groundwater Health Index (wGHI; Korbel & Hose 2017) was developed. The new, refined method allows groundwater health to be assessed and monitored using a combination of biological and water chemistry variables. Since the publication of this method, the authors were invited to present the framework to the European Union Groundwater Working Group (April 2017) as a potential framework for adoption in the Groundwater Framework Directive and NSW DPI have been in discussions about including the approach in their monitoring for groundwater dependent ecosystems within NSW.

The project has succeeded in providing

• Documentation of the extent and condition of subterranean GDEs in 4 subcatchments of the MDB

• Provision of baseline data on groundwater biodiversity

• Enhancing knowledge of GW ecosystems

• Improve groundwater ecosystem sampling methodologies

• Development of GHI to be used on farms with potential incorporation into MyBMP

The outcomes from this work are an improved groundwater management program, shifting from the current approach of managing water quality and quantity to an approach that considers groundwater biodiversity and the maintenance of ecosystem function and services. It will allow for future assessment of potential groundwater health decline due to competing industries. The results of this report will be implemented through the cotton industry My BMP program, promoting ecological sustainability and natural resource stewardship, while concurrently improving the capacity for the future management of this resource.

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. This year, for the first time, we have also partnered with our fellow key industry organisation, Crop Consultants Australia (CCA), on the development of the Guide.

CRDC sponsored ASDS to enable an international Verticillium speaker to present. As part of this sponsorship, CRDC has been provided with complementary registration for one participant. Brendon Warnock is taking this registration. It was also determined that it would be beneficial to have a Southern perspective at this event, and as such an invitation was extended to Todd Peach

As farming systems become more complex and the administrative burden grows, cotton farmers are not spending the time (and sometimes do not have the skills) to undertake high level climate, investment or business analysis for their cotton enterprises. Independent reviews and feasibility research are essential for growers and advisors considering practice change or capital investments in cotton farming businesses. Equipment suppliers often develop in-house feasibility with limited transparency on calculations / assumptions for a willing and sometimes unsuspecting consumer. Comprehensive peer review (including CottonInfo) of documentation and analysis underpins all outputs.

To make informed decisions, these analyses are essential. From 2017-2020, the following tasks were undertaken by CottonInfo’s Jon Welsh, in partnership with economist Janine Powell:

• Regular climate risk analysis via CottonInfo e-news, webinars and workshops to improve climate literacy of growers and advisors – allowing better management decisions to reduce climate risk and build industry resilience;

• Improved climate literacy was achieved by regular climate e-news including feature editions at winter and summer cropping decision points as well as webinars, face-to-face extension, presentations to industry and CCA and other novel approaches to messaging such as podcasts;

• Gross margin analysis of dry-land and irrigated cotton was broadened to include contracted operations and overhead irrigation scenarios. Key input analysis within the gross margins was also reported and extended. Industry budgets and analysis give current and new cotton growers a starting point to create their own budgets which can potentially lead to more informed cropping and input choices and a more profitable enterprise, business and industry.

• Energy efficiency extension for irrigators to build knowledge in what works and when. Improved energy literacy results in informed decision making for cotton growers. 5 large solar investments have been installed as a direct result of project extension material. These investments have improved energy efficiency and farm profitability through lower cost of energy. And also improved farm sustainability through lowered emissions.

• Resource efficiency analysis; limited irrigation water scenarios, incorporating renewables and energy technologies into irrigation systems, robotics in agriculture and, measuring practice change scenarios through dynamic gross margin analysis. The in-depth and targeted analysis conducted within the project were extended to the industry to inform cotton growers of the feasibility drivers for various new technologies and practice changes. Building this business knowledge in our industry can improve the return on investment capital creating a more profitable and sustainable cotton industry.

The summer edition of CRDC's magazine, Spotlight, focuses on research results and science-based best practices to help cotton growers successfully produce their 2018-19 crop, and contribute to sustaining the responsible production of Australian cotton.

In this edition, we feature technology and blue-sky approaches to solving recalcitrant issues, such as disease, spray drift, weed and insect pest resistance, with CRDC focused on seeking more efficient and effective solutions to these challenges.

This edition also includes articles on the CottonInfo team, the Australian Rural Leadership Program participants, our Nuffield scholars and the Rural Womens' Award recipients: showcasing the talented people of cotton. We also feature CRDC's major achievements and impacts from the 2018-19 year, highlighted in the Annual Report summary. And we extend a fond farewell to outgoing CRDC Executive Director, Bruce Finney, who steps down from his position after 14 years at the helm.

Soil is an invaluable finite resource, and there is considerable interest in monitoring the status of soil, as well as the direction and degree of any changes in soil attributes. Land use change and agricultural management have the capacity to alter the properties of soil considerably over relatively short time scales, however, it is less clear how recent climatic shifts observed throughout the globe will influence changes in soil condition. In the semi-arid regions of eastern Australia, there has been an expansion of irrigated cotton production, which is considered to be a very intensive land use with vigorous management practices. These regions have also been exposed to significant fluctuations in rainfall patterns in the last decade or so. While these semi-arid areas are agriculturally important, they often possess distinct soil characteristics, such as high levels of alkalinity, salinity, sodicity, inorganic carbon, and low levels of organic carbon. This body of work focuses on monitoring the change in soil condition in the semi-arid irrigated cotton-growing district of Hillston in the lower Lachlan River valley catchment in south-west, New South Wales (NSW), Australia. Data from soil cores extracted to 1.5 m depth from two soil surveys performed in 2002 and 2015 were used to monitor the change in several important soil properties – pH, electrical conductivity, exchangeable sodium percentage, organic carbon, and inorganic carbon. It is anticipated that the significant shifts in land use and rainfall patterns could have altered the condition of soil during this period.

Rather than using traditional digital soil mapping techniques, such as regression kriging or machine learning approaches, this study focuses on using linear mixed models, which are particularly advantageous for monitoring changes in soil properties as they can account for correlation in space and time. In this work, the focus is on using bivariate linear mixed models (BLMMs) and multivariate linear mixed models (MLMMs) to create digital maps of the various soil properties. In the BLMM approach, one model is used to predict a soil property from both time points at a single depth, which results in improved soil maps that have a logical connection through time. The MLMM approach is similar to the BLMM approach, but multiple depths are also be modelled simultaneously in addition, which results in more coherent connections between the different sampling depths. Another strong advantage of using these approaches to monitor soil is that the correlation between the monitoring periods is used to improve the sensitivity of the model to detect statistically significant changes. Traditional laboratory methods of measuring certain soil properties can be expensive and laborious. This study used visible near infrared (VisNIR) spectroscopic techniques to rapidly predict soil exchangeable sodium percentage (ESP), soil organic carbon (SOC) content, and soil inorganic carbon (SIC) content to overcome this.

The role of public-sector agricultural research, development and extension (R,D&E) investment as a starting point for innovation and productivity growth in agriculture is well understood, with numerous international studies highlighting the linkages between long-term publicly-funded agricultural R,D&E investment and agricultural productivity growth. Less well understood, however, are the linkages between private-sector agricultural R,D&E investment and agricultural productivity growth. This arises in part because of the shorter history of private-sector agricultural R,D&E investment, but also due to the lack of clarity surrounding the motivations for, and the nature and extent of private-sector investment. Further complicating this lack of clarity is the multinational nature of much private-sector agricultural R,D&E investment, with many of the investment decisions made in the context of global market opportunities, rather than national agriculture sector priorities.

For a relatively small and agriculturally unique market such as Australia, the engagement of the private sector in agricultural R,D&E investment is essential in order to maximise national agricultural R,D&E efforts, but also challenging due to the lack of information about such investment. The research reported here had the objective of developing a better information base about private-sector agricultural R,D&E investment in Australia, in order to find ways to incentivise such investment, with the longer-term goal of optimising national agricultural productivity growth.he research reported here aimed to obtain a better understanding of role of the private sector in agricultural research, development and extension (R,D&E) in Australia, with a particular focus on those factors or policies that are likely to enhance the role of the private sector in agricultural R,D&E.

The Australian Farm Institute previously conducted research into private-sector investment in agricultural R,D&E in Australia in 2011. The focus of the previous research was on quantifying investment by the private sector, and obtaining a better understanding of the nature of that investment.

Understanding where and how investment in agricultural R,D&E is occurring, from both public and private sources, is important for the formation of good public policy and for strategy development for private entities. This data is needed to ensure that critical capacity is retained in vital research areas and that appropriate collaborative efforts are identified to maximise the effectiveness of research and development (R&D) investment. The opaque nature of R&D classifications for statistical purposes and the poorly defined boundaries between food processing (and other industrial processes) and production within the food and agriculture supply chain continue to frustrate efforts to understand investment trends and potential areas requiring additional investment.