In March of this year, the Australian Rural Leadership Foundation (ARLF) 2023 TRAIL cohort of emerging leaders came together to embark on a transformative learning experience, enhancing their leadership skills and amplifying their impact. The program culminated with a graduation ceremony in Canberra on 15 March, where the participants celebrated their growth and accomplishments. Throughout the program, participants were exposed to diverse and challenging environments, which enabled them to adapt, innovate, and experiment with various problem-solving techniques. Additionally, they explored several key themes, including diversity, resilience, building connections within teams, effective decision-making, adapting to change and having conversations that held multiple perspectives that at times created discomfort.

In March this year, our 2022 cohort of emerging leaders assembled beginning a learning path to support their development as they sought to amplify their leadership contributions. The program culminated in Canberra at their graduation on 18 May. During the program, participants were challenged in different environments where they learnt to adapt, innovate and experiment with different problem-solving techniques. They also explored a number of themes such as diversity, resilience, building connection in teams, decision-making, dealing with difficult conversations and coping with change.

Cotton fibre is the most used natural fibre globally. Australia is one of the top exporters of cotton fibres and Australian cotton industry is dedicated to supply the most environmentally and socially responsible cotton to the world. However, the available technologies for tracing Australian cotton fibres are still limited and sometimes it is extremely difficult to track the source of the fibres due to the dispersed supply chain and the lack of transparency.

My award project Traceable Cotton Fibres aims to explore a plant-based technology-option for cotton fibre traceability by using genetic manipulation (GM) cotton germplasms derived from our CSIRO Synthetic Biology (SynBio) FSP: Novel Synthetic Plant Fibres Project (The closure report of the CSIRO Synthetic Biology FSP Project, 2022; related patent PCT number is PCT/AU2023/050436). These cotton germplasms can synthesize foreign proteins which are fluorescent with specific excitation and emission wavelengths of light. The approach was to use different methods to detect the proteins and their fluorescence in various plant tissues including fibres at different developmental stages to assess where it is most stable. Two GM proteins were used: amilGFP and mCherry.

During the progress of this award project, it was found that the fluorescence of the amilGFP protein in the fibre is highly similar to the autofluorescence range of cotton fibre. Therefore, another set of GM cotton germplasm with the mCherry protein was used. mCherry is also fluorescent, and the excitation and emission wavelength are more distinctive in contrast to the high autofluorescence range of cotton fibre. In addition, the Enzyme-Linked Immunosorbent Assay (ELISA) was employed to detect the presence of mCherry protein in fibres as there is a commercially available kit with antibodies which detect mCherry. The results enabled evaluation of the possibility of using such germplasms to develop plant-based techniques for the traceability of cotton fibres across key stages of the value chain.

The concept of soil health is discussed and presented as an integrative property that reflects the capacity of soils, and specifically
of soils used for cotton production, to respond to agricultural intervention, so that it continues to support both agricultural
production and the provision of ecosystem services. Soil health is conceived as being dependent on the maintenance of four major
functions; namely: (i) carbon transformations, (ii) nutrient cycles, (iii) maintenance of soil structure, and (iv) the regulation of pests
and diseases. Measurement of individual soil properties, soil processes, functions or soil biota may not suffice to indicate the
overall state of soil health. Therefore, robust, yet simple, approaches to interpreting and measuring soil health are needed. This
work reviews and compiles a suite of pragmatic soil health indicators that may be applicable to Australian intensive production
systems. This suite of indicators may be used to measure, monitor, and report soil health in a consistent manner using a
combination of standard analytical techniques, quantitative hand-held proximal sensing and qualitative visual assessments, and
potential application of emerging technologies. 
Keywords: Earth observational datasets, Onboard technology, Proximal sensing, Remote sensing, Sensor fusion, Soil processes
and function, Spatial modelling, Soil quality.

This analysis draws on data from a subset of the Cotton Comparative Analysis (CCA) in each of the respective years, along with additional information supplemented from participants’ annual financial statements. The participant dataset includes a sample of irrigated cotton growers operating predominantly in NSW valleys and represent approximately 5% of the annual Australian irrigated cotton bale production. The data is drawn exclusively from the trading entities growing cotton. Related entities are excluded and as a result the data is limited to some extent for example with respect to debt and interest not held in the name of the trading entity. The sample represents a diverse range of grower sizes, from small-scale to large operations. Bale data from our sample and national bale data (Source: Cotton Australia, Australian Cotton Estimate) is used to scale our data to estimate industry-wide irrigated cotton data. The table below shows the number of bales produced by the sample as a percentage of total Australian irrigated cotton production.

Australian cotton and grain growers are world-renowned for producing high-yielding, high quality fibre and grains. However, there is still considerable variation in both yield and quality within and between fields, farms, and seasons. Grain quality, namely the grain protein content (GPC), and cotton fibre quality, including length and micronaire (a composite measurement of fibre fineness [diameter] and maturity), are key determinants of the prices that growers receive due to the introduction of a premium and discount system for Australian growers.
Thus, there is an onus on growers to manage for both quality and quantity to attain premium prices. Site-specific crop management (SSCM) is the practical application of precision agriculture (PA) principles, and involves the allocation of resources and agronomic practices to match spatiotemporal variability in the crop growing environment. However, uncertainty regarding the amount of within-field variation necessary to justify investment in PA technologies, and a lack of understanding regarding the drivers of this variation to support improved decision making, is a considerable limitation to the adoption of PA for growers and advisors. Today, more data is being collected on farms and by the industry than ever before (e.g. yield data, variable-rate inputs), and there is also an enormous amount of public data that is free to access (e.g. remote sensing imagery) which can be used to describe or represent variability in GPC and cotton fibre quality. By understanding how and why cotton fibre and grain quality varies within-fields, growers and advisors can be equipped with the necessary information and tools to make better management decisions for more profitable and environmentally sustainable production systems.
This thesis explores the application of on-farm and publicly-available spatial data layers for the description, characterisation, and quantification of within-field variability in cotton yield and fibre quality (length and micronaire) and GPC, and to understand the drivers of this variability within fields. Chapter 1 provides an overview and background of the Australian cotton and grains industries and the current role of PA in understanding and managing for variability in cotton fibre and grain quality. Chapter 2 presents a generalised geostatistical approach using area-to-point kriging to map and downscale areal observations of crop production data,
which is illustrated using cotton yield and fibre quality (length and micronaire) data which is measured as a module (areal/block) average. Chapter 3 demonstrates how a combination of readily-available yield, agronomic, and publicly-available data layers can be used to create a model to predict GPC within-fields to fill-in gaps in the absence of a protein sensor. Chapter 4 investigates the relationship between wheat grain yield and GPC and applies interpretive machine learning approaches using existing spatial data layers to understand the drivers of spatial variability in GPC within-fields. In Chapter 5, the opportunities for SSCM for wheat grain yield and GPC are compared by quantifying the magnitude and spatial structure of within-field variability using the Opportunity Index (OI).

While the interpretation and application of the growing plethora of spatial data layers for decision-making is a challenge for growers and advisors, this research demonstrates the how a PA approach can use these data layers to better understand the nature and drivers of within-field variability in cotton fibre and grain quality to make better management decisions for more profitable and environmentally sustainable production systems that optimise both yield and quality.

Indicators for sustainable pesticide use are essential for the cotton industry to assess, manage and demonstrate commitment to environmentally responsible cotton production. Improved pesticide management not only protects overall ecological and human health on cotton farms and in cotton catchments, but it also generates social license, facilitates market access and potentially increases the value of cotton produced.

The Australian cotton industry is committed to improving on-farm sustainability; however, as the raw material travels through the ‘value adding’ stages in the globalised fashion and textile industries, it is uncertain how its ‘sustainable value’ is transferred into the final product. The central aim of this research is to analyse how the Australian cotton industry can understand where value is created, as well as opportunities to create sustainable value along its supply chain. To explore this question, a tailored tool was developed that combines value chain analysis methods with value mapping interview techniques. This involved ‘walking’ the chain from fibre to finished fashion product to disposal. A total of 21 stakeholders were interviewed across two Australian cotton value chains from growers to retailers through to actors that collect discarded garments. Participants identified what sustainable value is, how it is created, who it benefits both in and beyond the chain (including local communities, the environment and consumers) and where future opportunities to create further value may lie. This study delivers three original contributions to the knowledge surrounding how sustainability is valued within the fashion value chain. First, the development of a method and approach which proposes another way of understanding sustainable value through ‘asking’ actors specifically what they value and why, and converging these insights to better understand the entire chain. Second, through mapping the Australian cotton value chain, it identifies actors’ experiences and perceptions of sustainability which have previously been unexamined, noting where these perceptions converge and diverge. It pinpoints the complexities that face the Australian cotton industry’s transfer of sustainable value within global value chains, such as the separation between raw material producers and retailers, as well as locked-in practices (i.e. blending fibres) which inhibit traceability and circularity. The results demonstrate a need to create a shared understanding of ‘on-farm’ sustainability. The study identifies elements to best do this through substantive (LCA data) and symbolic (storytelling) sustainability messages – and proposes how these can be co-created with stakeholders. From this, the study offers a third contribution by extending understandings around sustainability and its value within the context of fashion and textile value chains, and identifies practices that can be taken up more broadly to further sustainability within the industry.

Textile waste is a growing global issue with no effective methods of disposal currently 
available. In Australia, 85% of new clothing purchased annually ends up in landfill, which 
represents a waste of water and energy to produce these textiles. Escalating this issue, is the 
synthetic composition of these textile materials which represent 60% of current clothing 
textiles globally. To minimise the environmental impacts and relieve waste management from 
existing facilities, the concept of utilising recycled cotton fibres as reinforcement in cement 
mortar has been proposed. While most engineering practices typically use synthetic fibre 
reinforcement to obtain specific mechanical improvements, the processing and development of 
these fibres is unsustainable and environmentally damaging. 
Recent studies have found effective uses for natural fibre reinforcement in cement-based 
products. Results demonstrated comparable mechanical improvements, while minimising 
environmental impacts and costs to manufacture. In this study, cotton bed sheets obtained from 
a textile-waste recycling facility were repurposed to a fibrous state to assess the physical, 
mechanical, and microstructural interaction with a cement-mortar. A total of 7 different mix 
designs were prepared with various quantities and lengths of cotton fibres, to evaluate the 
influence of fibre content and fibre length on cement composites. 
To observe the physical properties, flow table tests were performed for each mix to determine 
the workability of fresh mix. It was observed that the increase in fibre content decreased the 
workability, and superplasticiser had minimal effect on higher quantities of fibres. Hardened 
properties were measured using compressive and flexural tests at 7, 28 and 56 day curing ages. 
The compressive strength for samples with increasing cotton fibre content demonstrated a 
decrease in compressive properties. However, flexural properties indicated a significant 
improvement in flexural toughness, and confirmed that the presence of cotton fibres was 
influencing a fibre bridging mechanism. This was supported through microstructural imaging, 
which indicated a strong correlation between fibre dispersion and the cohesion with cement 
bonding. 
Cotton fibres display promising flexural improvements in cement composites, however 
additional research should focus on the chemical pre-treatment of fibres, to enhance the 
dispersion and bonding between cement particles.

Soil is a finite and irreplaceable resource that underpins agricultural systems, regulates water cycles and presents opportunities for climate change mitigation. Consequently, the sustainable management of soil is essential for guarding the security of agricultural production and ecosystems. For this to occur, however, an accurate understanding of inherent soil properties and how they vary spatially, is required. Within the lower Murrumbidgee valley of southern NSW, Australia, there is a paucity of available data and land managers require more information on both the chemical and physical properties of their soils and the presence of potential constraints to agricultural production. While the development of novel approaches and ‘blue-sky’ research is important, the targeted application of developed methods is essential in filling knowledge gaps and allowing benefits to reach the end user, in this instance, farmers and land managers. Within the lower Murrumbidgee valley farmers are a key stakeholder of the soil resource. Thus, they should be a key consideration when designing, undertaking and communicating projects to ensure their outcomes are tangible. Therefore, rather than seeking to develop novel approaches to digital soil mapping (DSM) and digital soil assessment (DSA), this thesis utilises various methods recognised in literature to develop outputs targeted to the cotton industry in southern NSW. Using a collected dataset of 153 soil cores to 1 m depth from across the region, soil profiles are morphologically described, soil properties are modelled and mapped at the within-field and regional scales, before a regionally specific classification is developed.