Completed projects and reports
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Sugar Research Australia, Sugar Research Development Corporation and BSES reports from completed research projects and papers.
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Item Australian sugarcane industry soil health benchmarking in Central Queensland: Increasing profit and transforming soil health practices through cooperative industry research, extension and adoption(2021-12-13) Manatsa, GusActivity 1: Measure changes in soil health under a range of farming practices: potential soil health indicators, benchmarks & measurements recommended to enable grower/ industry demonstration of performance improvement through the implementation of IFS practices (i.e., cover cropping, organic amendments, row spacing, controlled traffic, minimal till). Over two years, ten paired sites were established across the three mill areas of the Central Region to determine the soil health, root health and business impact of transitioning to an Improved Farming System (IFS). Long-term IFS sites, of at least ten years, were matched with nearby sites using conventional farming practices. Physical, chemical, and biological soil parameters were measured, along with root development testing, to determine variation between the sites within each pair and therefore the long-term impact of implementing IFS practices. This work is building the evidence required to assist the industry to determine the best set of soil health indicators for the Central region. Combined results from the Central region indicate that microbial biomass, pH and soil compaction are positively impacted by improved farm management systems. Some measures that seemed to show very strong trends in the first year were more mixed in the second year, notably effective rooting depth. Soil texture emerged as a major influence on results, making it difficult to assess the effects of improved management practices in some cases. Root biomass averaged substantially higher in the IFS treatment, possibly reflecting a combined influence of other soil health factors. Activity 2: Innovative soil health/ IFS extension: regional synthesis of solution-based soil health messages to improve production, profit and sustainability through development, training in and implementation of the SRA Soil Health Toolkit (SHET). This project was an industry partnership of the Central cane growing region of Queensland. Collaboratively, the partners, led by Farmacist and SRA, ground-truthed potential soil health indicators and benchmarks for varying soil types and farming systems of the region. This work was needed so that growers could have increased confidence in soil, plant and root sampling data, to inform their decision making and build a greater understanding of how IFS practices deliver production, profit & sustainability outcomes, in addition to improved resilience to climatic variability and extreme weather. The development of the Soil Health Extension Toolkit (SHET) provided a way for local service providers to build their own knowledge in possible Central region soil health indicators, whilst working alongside “champion” growers keen to trial the tests included in the SHET and use the data to help inform the soil constraints most impacting their yield potential, and importantly, where to progress their investigations through further in-depth testing.Item A Common Approach to Greenhouse-Gas Accounting for Australian Agriculture: Project Overview & Non-Technical Summary(2023-04) Cowie, AnnetteThis document accompanies the Methods and Data Guidance (Sevenster et al., 2023) and Common Terminology (Cowie et al., 2023) documents to provide a non-technical description of the project that led to the development of those documents, and an executive summary of the key technical decisions in the Methods and Data Guidance document. It is intended for industry decision makers without expert knowledge of greenhouse gas (GHG) accounting, and to be read in conjunction with the two technical documents. The need for a common approach to GHG accounting across agricultural sectors was identified in a stakeholder workshop in December 2019 with participants representing most Rural Research and Development Corporations (RDCs), the National Farmers Federation and sector-level peak bodies, federal and state government, AFI, Rabobank and expert consultants. As sector-level reporting was starting to become important (e.g. Mayberry et al. 2018), the lack of clear methodological guidance for this type of GHG accounting was clear. A collaborative project was developed, initially by the Climate Research Strategy for Primary Industries (CRSPI) collaboration and then by Agricultural Innovation Australia (AIA), who commissioned CSIRO and a large team of subcontractors to conduct an interactive, collaborative process to develop such guidance with broad support from both agricultural sectors and technical experts. The scope of the project was to develop a consistent common framework for agriculture GHG baseline accounting at sector level (i.e. a Common Approach). Implementation of the framework was not part of the project and is up to each sector individually. While many stakeholders contributed to the development of the Common Approach there is no obligation or commitment on any party to implement it. The Common Approach is a state-of-the-art, best practice guidance for sector-level GHG accounting and can be seen as aspirational; guiding improvements in data collection and GHG reporting over time across Australia’s agricultural sectors.Item A Common Approach to Greenhouse-Gas Accounting for Australian Agriculture: Methods and Data Guidance(2023-04) Cowie, AnnetteA common approach for GHG accounting across agricultural sectors is essential to enhance consistency, transparency and confidence in sector-level GHG reporting. Internationally, there are approaches and tools that influence Australian farmers via market access criteria or product labelling, which do not always adequately reflect the reality of Australian farming. A common approach to GHG accounting will allow Australian agriculture to control the representation and communication of climate impacts and mitigation. This Methods and Data Guidance provides a common framework for greenhouse gas (GHG)accounting of Australian agricultural activities at the sector level. The process that was followed to develop this framework is described in the Project Overview and Non-Technical Summary (Sevenster et al., 2023). It describes how GHG accounting can be conducted to generate a transparent and trusted inventory of GHG emissions based on: - a consistent set of principles - a modular approach to account for differences between agricultural sectors - general guidance on data - consistent terminology and language. Agricultural sectors, in the context of this document, refer to individual commodities (or commodity groups such as “grains”), as distinguished by the system of levies applied to primary production. They include forestry and fisheries. No existing standards or protocols exist for this context, which is the reason this guidance document was generated. Nevertheless, where possible and appropriate, the approaches and method choices recommended in this framework draw on relevant guidance from the following frameworks primarily: - Australian National Greenhouse Gas Inventory (NGGI) - ISO 14044:2006 Environmental management — Life cycle assessment — Requirements and guidelines (ISO, 2006) - ISO 14067:2018 Greenhouse gases — Carbon footprint of products — Requirements and guidelines for quantification (ISO, 2018) - guidance provided by the Livestock Environmental Assessment and Performance (LEAP) Partnership (FAO, 2016) - sector-specific guidance for product or corporate accounting, such as IDF (2022). In addition, guidance for corporate accounting provided by the Greenhouse Gas Protocol (GHG-P)(GHG-P, 2015), guidance for product accounting provided by GHG-P(GHG-P, 2011), the Product Environmental Footprint (PEF) scheme (EU, 2021), and guidance from the ILCD Handbook (ILCD, 2010) is referenced for some aspects of the goal and scope principles (2.1).Item A Common Approach to Greenhouse-Gas Accounting for Australian Agriculture: Common Terminology for GHG Accounting(2023-04) Cowie, AnnetteThis document is an extended glossary of terms used in or relevant to the project A Common Approach to Sector-Level GHG Accounting for Australian Agriculture, including abbreviations. It accompanies the Methods and Data Guidance (Sevenster et al., 2023a) and Project Overview and Non-Technical Summary (Sevenster et al., 2023b) reports. Definitions have been sourced from authoritative literature, particularly the Intergovernmental Panel on Climate Change (IPCC) glossary, International Organization for Standardization (ISO) standards, and specific policies and schemes, such as the Emissions Reduction Fund (ERF) and the United Nations Framework Convention on Climate Change (UNFCCC). Abbreviations are included where in common use. Additional relevant information is included in the glossary entries to aid comprehension and to indicate relevance for Australian agricultural systems.Item Seeing is believing: managing soil variability, improve crop yield, and minimising off site impacts using digital soil mapping(2020-12-31) Triantafilis, Honorary Associate Professor JohnOver 70 % of sugarcane industry operates next to the Great Barrier Reef (GBR). Farmers are under pressure to improve practices to minimise off-farm pollution, while at the same time improve fertiliser (e.g. lime) and amelioration (e.g. gypsum) efficiency to minimise yield variation. While the biggest driver of variation is rainfall, differences in soil condition affect yield and farmers need to know its variation. For example, knowledge about soil cation exchange capacity (CEC – cmol(+)/kg) is important because it is a measure of how many exchangeable (exch.) cations (i.e. calcium [Ca], magnesium [Mg]) can be retained on soil surfaces and because it influences soil stability, nutrient availability, pH and reaction to fertilisers. If no action is taken to map soil and manage different soil condition, opportunities to sustainably improve application of fertilisers and ameliorants in a cost-effective way will be foregone as well as an opportunity to make a meaningful, economically viable contribution to reducing impacts of sugarcane growing on the GBR. The six-easy-steps (6ES) nutrient and ameliorant guidelines were developed to minimise in-field variation and reduce losses of inputs to the GBR. However, there was and is no practical way for farmers to apply the 6ES guidelines given there is no in-field data to enable its application. This project aimed to undertake case studies in four sugarcane growing areas to enable precision agriculture via the use of a digital soil map (DSM). A DSM requires collection of digital data, such as proximally sensed electromagnetic (EM) induction and gamma-ray spectrometry (ϒ-ray) and coupling this to soil data via mathematical models. The study areas, where a DSM approach was taken, include Mossman, Herbert, Burdekin and Proserpine. The results show that a DSM approach is valid with the potential to implement the 6ES nutrient and ameliorant guidelines to enable precise application of lime, gypsum and other fertilisers demonstrated via various case studies. They are provided here in brief and in summarised form in Section 5. All published papers or submitted manuscripts are provided in the same order and appear in the Appendices. In the Mossman area (see Section 5.1), a DSM approach was used to characterise soil condition in terms of topsoil (0-0.3 m) soil organic carbon (SOC, %) variation, with the DSM able to be used to apply the 6ES nutrient management guidelines (Schroeder et al., 2010) with varying N application rates for different levels of SOC to achieve a district yield potential of 120 t/ha after a bare fallow (Wang et al., 2021). In various areas (see Section 5.2), the DSM approach could be used to predict topsoil (0-0.3 m) clay content across any of six study sites in the Mossman, Herbert, Burdekin, and Proserpine districts. The site-specific approach to making DSM of topsoil clay was optimal, however site-independent (universal calibration) and a spiking approach give almost as good prediction agreement and accuracy (Arshad et al., 2021). In the Herbert (see Section 5.3), a DSM approach was used to characterise soil condition in terms of topsoil (0–0.3 m) and subsoil (0.6–0.9 m) CEC (cmol(+)/kg) variation, with the topsoil DSM able to be used to apply the 6ES nutrient management guidelines (Sugar Research Australia, 2013) with varying lime application rates for different levels of CEC (Li et al., 2018). In the Herbert (see Section 5.4), a DSM approach was used to identify zones by clustering digital data (i.e. EM and -ray data). The DSM was more accurate in predicting topsoil (0-0.3 m) and subsoil (0.6–0.9 m) chemical (e.g. CEC, exch. Ca and Mg and ESP) properties. The 6ES guidelines of Schroeder et al. (2009) were applicable to ameliorate topsoil ESP; the latter shown to influence yield percentage (Dennerley et al., 2018). In the Herbert (see Section 5.5), a wavelet transform of the digital data (i.e. EM and -ray data) was used to enable prediction of topsoil (0-0.3 m) ESP. The DSM, using all the wavelet transformed digital data (i.e. elevation, EM and -ray data) gave the most accurate predictions. The 6ES guidelines of Schroeder et al. (2006) to manage ESP through variable rates of gypsum was also demonstrated (Li et al., 2021a). Sugar Research Australia Final Report 2017/014 4 In the Herbert (see Section 5.6), a DSM approach was again used to identify zones by clustering digital data (i.e. EM and -ray data). The DSM was more accurate in predicting topsoil (0-0.3 m) and subsoil (0.6–0.9 m) chemical (e.g. CEC, exch. Ca and Mg) properties than a traditional texture map or field delineations. The 6ES guidelines of Schroeder et al. (2009) were applicable for these properties (Arshad et al., 2019). In the Burdekin (see Section 5.7), a DSM approach was used to predict topsoil (0-0.3 m) exch. Ca and Mg. The DSM was more accurate than a traditional map (Li et al., 2019a) and useful for applying lime and magnesium, respectively, using 6ES guidelines (Schroeder et al., 2009). In terms of calibration, 30 samples were enough to predict exch. Ca with 40 for exch. Mg (Li et al., 2019b). In Proserpine (see Section 5.8), a DSM was developed to predict topsoil (0-0.3 m) ESP. A map generated using ordinary kriging of 120 soil samples was satisfactory, but, a minimum of 100 samples was required. When digital data was used to value add to soil data, Cubist-RK outperformed OK with only 60 samples required. The 6ES guidelines of Schroeder et al. (2009) were applicable to ameliorate topsoil ESP (Li et al., 2021b). In Proserpine (see Section 5.9), a DSM was developed to predict topsoil (0-0.3 m) and subsoil (0.9-1.2 m) CEC. Topsoil prediction required 80 calibration samples whereas for subsoil only 30 were needed. Using both digital gave best results although -ray used alone slightly better than EM. Small transect spacing (i.e. 5 m) was recommended for topsoil, but larger spacing OK for subsoil (i.e. 5 – 60 m). The 6ES guidelines of Proserpine (Calcino et al., 2010) were applicable to ameliorate topsoil CEC (Zhao et al., 2020). Given the results presented in this Final Report and the published research, it can be concluded that the DSM approach can be applied to map various topsoil and subsoil physical (e.g. clay, silt and sand) and chemical (i.e. CEC, Exch. Ca, Exch. Mg and ESP) properties at the field and multi-field scale in different sugarcane growing districts. The final DSM can be used to apply the 6ES nutrient and ameliorant guidelines in the four sugarcane growing areas investigated and including Mossman, Herbert, Burdekin, and Proserpine. In terms of operational aspects, the following key conclusions can be made; i) Various soil physical (e.g. clay, silt and sand) and chemical (i.e. CEC, Exch. Ca, Exch. Mg and ESP) properties can be mapped using a DSM approach, but regardless of modelling technique, the number of soil samples required to make a calibration was approximately the same (i.e. 1 sample per hectare) regardless of the soil property (i.e. topsoil Exch. Ca and Mg and ESP) or study area. ii) Mathematical methods such as LMM are useful when digital data are correlated with soil data, with hybrid methods of machine learning (i.e. Cubist) and regression kriging (Cubist-RK) useful when correlations were statistically significant but not as strong and if residuals were spatially auto-correlated. Alternatively, wavelet analysis can also be useful to predict soil properties (i.e. topsoil ESP) where there was no direct relationship with digital data but a relationship with scale specific variation in digital data (i.e. ϒ-ray, EM and DEM). Moreover, fuzzy k-means or k-means clustering can be used to make management zones from -ray and EM data when the digital data is not directly correlated to the soil data of interest and produce superior predictions than traditional soil texture maps and or using field delineations to predict soil properties. iii) Digital data of elevation, ϒ-ray and EM were best used in combination rather than alone, regardless of which modelling technique was considered (e.g. LMM, Cubist-RK and wavelet analysis). In terms of the density of digital data transect spacing, the smaller the spacing the better (i.e. transect every 7.5 m) with a maximum transect spacing of 30 m allowing large areas to be measured in a day (~ 400 ha).Item Item Understanding the mechanisms that control the release of a soluble crystalline agrichemical extruded with polymers(2020) Levett, Ian ChristopherNitrogen (N) is an essential element to sustain all life on Earth, yet it also wreaks havoc when in excess. The production of synthetic N fertilisers through the Haber-Bosch process began in the early 1900s and initiated the ‘green revolution’, seeing agricultural productivity soar. These productivity gains support roughly half of the current global population. Yet while heavy application of synthetic N fertilisers ensures crop success, it also leads to harmful environmental losses of 50-70% of the N applied. Such losses damage fresh and coastal aquatic ecosystems through eutrophication and biodiversity loss, reduce air quality, accelerate climate change and lead to numerous human health implications. The human race has doubled the cycling of N through the environment leading to a global challenge. To reduce these environmental nutrient losses, enhanced efficiency fertilisers were developed, including slow- and controlled-release fertilisers and stabilised N fertilisers. These products aim to increase the proportion of N taken up by the crop relative to the amount added, meaning that less fertiliser is required. Slow- and controlled-release products specifically aim to deliver N at a rate to match the crop N uptake curve, while N stabilisers are chemical additives that inhibit urease and nitrification in the soil, reducing leaching of highly mobile nitrate-N and lowering denitrification to gaseous nitrogen oxides (NOx) and nitrous oxide (N2O) - a potent greenhouse gas. Dicyandiamide (DCD) is a commercial nitrification inhibitor that effectively reduces N losses and can improve crop productivity in temperate climates. However, in tropical soils, microbial metabolism of this molecule results in limited efficacy. This project aimed to improve the efficacy of DCD for tropical agriculture through encapsulation and controlled-release of this soluble, crystalline agrichemical using biodegradable and environmentally friendly polymers. The principle is to protect the DCD from degradation and extend the duration of effective concentration in the soil. Controlled-release DCD pellets were produced through extrusion processing, as a simple, cost-effective, commercially relevant fabrication technique. The polymers tested include thermo-plastic wheat starch (TPS), the bacterial polyester poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and synthetic polycaprolactone (PCL) as well as blends of PHBV with PCL. DCD was distributed in these polymers through extrusion melt compounding to produce ~3×3 mm cylindrical pellets. The release kinetics were studied and, importantly, the underlying mechanisms that control release were identified and modelled. Much of the mechanistic understanding was developed through advanced imaging of the materials before and after release, using scanning electron microscopy (SEM), mapping with Raman spectroscopy, and high-resolution X-ray micro-computed tomography (μ-CT). The release kinetics were modelled using empirical and mechanistic models. From the outcomes of these studies, this thesis builds an understanding of the key material design parameters, including: (1) Polymer(s) selection. The physical and chemical properties of the polymer determined the time for release, ranging from 1 day (for TPS) to 6+ months (for PHBV), and the mechanisms controlling release. Release from TPS occurred by rapid diffusion through and swelling of the hydrophilic polymer matrix. By contrast, PHBV shows promise for long-term release profiles (6+ months), but diffusion through this polymer is so slow that release occurs via other mechanisms. Initially, the release was rapid via the dissolution of surface exposed DCD crystals, confirmed through SEM, resulting in ~20 wt.% release within the first 5 h. Between 5 h and 8 weeks, a further 25 wt.% of the DCD was mobilized as water accessed connected DCD crystals or entered via micro-cracks in the matrix, as determined through high-resolution μ-CT and Raman mapping. A large portion (~50%) of the agrichemical remained encapsulated until the PHBV matrix degraded in soil environments. To increase the rate of matrix diffusion, blending with a more hydrophilic polymer, PCL, were studied. However, the higher affinity between DCD and PCL counter-intuitively resulted in less interconnected DCD crystals, which lead to slower release with increasing PCL content in the blend. (2) The DCD loading. This determined the degree of percolation within the matrix, with a threshold at between 200 and 400 g.kg-1 for DCD-PHBV. Below the percolation threshold, this parameter controls the thickness of the polymer between agrichemical crystals. (3) DCD crystal size. Below the percolation threshold, the fractional release from the surface of the pellet was modulated through the grind size of the agrichemical. (4) DCD pellet size. As identified through mathematical modelling, this parameter can control the fractional release rate and has important consequences on the distribution of pellets within the soil. Understanding these key parameters and the mechanisms that control release allows cost-effective, environmentally friendly material design to increase the effectiveness of nitrogen stabilisers in tropical climates and reduce N pollution. Moreover, the knowledge gained here is relevant for the controlled-release of any soluble, crystalline agrichemical and could be applied for the design of controlled-release fertilisers, herbicides and pesticides.Item Scoping Study for CaneMAPPS Development(2022-04-22) Radanielson, Dr A.M.; Lai, Y.R.; Dekeyser, S; Mougouei, D; Pembleton, K.G.This project scopes the development requirements of CaneMAPPS: a digital platform to facilitate growers’ adoption and implementation of sustainable farming practices in sugarcane production. Consultations with SRA staff and selected industry experts were conducted via videoconference, focusing on the data use, the constraints in data use, and the type of tools available to support productivity improvement in the sugar industry. The status and needs of current SRA activities were used as a source of information for CaneMAPPS requirements. Information was cross-validated with inputs from one-to-one conversations with selected actors in the industry including growers, third-service providers and government body representatives. Data in the industry are available for a range of different purposes and in different formats. They are in separate locations and managed by different stakeholders with varying rights to access, use and sharing. These constraints reflect a lack of consistency in data collection, management and use in the industry. Recommendations for the development of CaneMAPPS are suggested to account for these constraints to enable data stewardship and governance and ensure relevance and successful engagement of different stakeholders in the industry. With the adoption of these recommendations, the core module for CaneMAPPS, which sets up the infrastructure foundation of the platform, and its first decision-support component, a nutrient management and budgeting analysis service, may be developed within a three-year project. The implementation of an agile development pipeline is a prerequisite for CaneMAPPS development to clearly articulate its scope and benefits for the industry. This will require a multidisciplinary team with expertise in human-centred software engineering, end-user engagement and sugarcane production.Item Australian Sugar Industry Training – Development of factory training modules – Phase 2(2022-05-04) Moller, DavidThe Australian Sugar Industry Training Learning Management System (ASIT LMS) provides a valuable training resource for the Australian Sugar Industry. As a single location for the milling training programs that have been developed for the last 30 years this provides a great reference resource for operators seeking to solve operating issues during the crushing season. New on-line operator training programs that have been mapped to the national competencies provide a minimum industry level of knowledge training and assessment for all the raw sugar making processes from juice to sugar storage. Included in the training programs are suitable skills competency assessment checklists that can be undertaken on site by a suitably qualified assessor. The ASIT LMS also provides a system whereby groups can develop their own internal training courses and use them for internal knowledge assessment activities. This feature is being used by several sugar milling companies to undertake knowledge competency training in areas other than sugar milling operations. The LMS has been designed to cover all training for the sugar industry. To date there has been limited adoption from the non-milling sector despite the Chief Investigator having made repeated attempts to interest the non-milling sector in using this training platform as the basis of the training for the Australian sugar industry. The on-line nature of the LMS and the ease of use, combined with its extensive learner tracking and assistance capabilities have provided the Australia Sugar Industry with a knowledge training platform to be used into the future.