Geospatial analytics for variable rate application of pre emergent herbicides

Geospatial analytics for variable rate application of pre emergent herbicides

Take home message

  • Traditional blanket spraying methods for pre-emergent herbicides fail to consider in-field spatial variability, resulting in inefficiencies
  • Customising pre-emergent herbicide placement and rates based on field zones can enhance performance, crop safety, and return on investment for growers
  • Multi-point, direct injection technology offers a potential solution for variable, multi-product, and multi-rate application of pre-emergent herbicides across a paddock
  • While further research and data analysis is ongoing, the trial work conducted so far has highlighted the potential benefits and value of applying variable rate pre-emergent herbicides.

Approach

Currently pre-emergent herbicide delivery is based on applying a single dose of one or more products in a tank mix. Typically, these are applied as a blanket spray, meaning the whole paddock is treated the same irrespective of soil characteristics or weed seed bank.

An inherent limitation with such an approach is that it locks in the rate and ratio of the individual or tank mixed products and assumes that all parts of the paddock require the same rate. This is not the case as many fields can be extremely heterogenous.

Although some herbicide labels may offer a range of rates that could be variably applied, the potential fit of variable rate pre-emergent herbicides in various systems needs to consider crop safety, plant back requirements and efficacy and the level of precision of application, spray rates and application methods.

This project develops a multifaceted streamlined workflow for precision agriculture technology, focusing on variable rate application of pre-emergent herbicides. It includes:

  • Software for precision mapping
  • Environmental and product interaction analysis
  • Product and hardware integrations.

The success of a defined workflow also brings multiple benefits:

  1. Enhanced adaptability: Growers and agronomists can fine-tune weed management programs using multiple technologies and products.
  2. Targeted product utilisation: Precise application of herbicides optimises resource use and reduces environmental impact
  3. Empowerment through information: Stakeholders provide insights on paddock variability, enriching the knowledge base
  4. Tailored recommendations: Combining diverse data sources and expertise leads to accurate, customized herbicide recommendations.

This approach not only targets pre-emergent herbicide efficiency but also promotes more sustainable and informed agricultural practices.

Paddock characterisation (soil and weed seed bank)

The approach relies on observation and orientation of paddock variability through on-farm-knowledge and feedback to guide the data capture and digital layers for creating a paddock management zone. The zones are simplified to 2 to 3 zones based on diagnosed variability for soil characteristics and weed presence.

Grower/agronomist-led feedback

It is important to start with an open two-way conversation on trial opportunities, and soil and weed challenges. Some key steps for data sharing and knowledge transfer include:

  1. Determine problematic weeds and seedbank locations
  2. Understand herbicide use (programs, rates, tank mix)
  3. Capture rainfall and temperature patterns during fallow periods
  4. Review previous and planned future rotational crops
  5. Discuss strategies and tasks for weed control
  6. Identify products and rates for testing.
  7. Identify paddock hotspots with varying soil type with emphasis on factors that may affect herbicide efficacy or persistence (e.g. organic matter, physical structure, pH, drainage)

With grower adoption of farm management software being slow and fragmented, often there are incomplete views of farm productivity which can complicate decision-making. Equipment manufacturers like John Deere and Case IH may have their own platforms, however these often require extra steps for setup and updates. Additionally, digitisation of farms is often deprioritised in favour of on-farm operational tasks. To boost engagement, the following should be considered.

  • Close and continuous presence and support on the digital platform journey
  • Finding simple solutions with clear benefits to grower and agronomist

Flow diagram illustrating challenges with digital platforms partnering with growers.

Figure 1. Challenges with digital platforms partnering with growers.

Data exploration

After establishing access to farm management systems currently in use, an agreement is then made on what layers can be collected in addition to existing data. The usual recommendation for paddocks where soil is the key driver of weed distribution is Dual EM soil scans followed by strategic soil sampling based on management zones. Additional exploration of satellite data and analysis, fitness to model, and UAV (unmanned aerial vehicles = drones) multispectral paddock assessment of bare paddock when possible. Current examples of data capture and processing steps:

  1. Historic data:
    1. Satellite remote sensing: Capture bare soil layers through different soil colours and vegetation index, identify weed scapes.
    2. Yield maps + as applied weed maps: capture zones of low yield and compare to as applied maps of spot-spraying records.
  2. Dual EM or Veris Soil scanners: Run an EM soil scan across the paddock to identify varying soil texture, salinity (related to soil pH), soil moisture patterns.
  3. Strategic soil sampling: Create a geotagged sampling plan with 1-2 samples per polygon/soil zone to compare soil survey and analysis.
  4. UAV flights: Generate vegetation index/weed density maps by dividing paddocks into 12x12 m plots at 2.6 cm resolution. Post-process RGB and multispectral images into orthomosaic layers and plant health indexes, removing soil reflectance from bare soil assessment.

Prescription mapping with variable rate and product

Paddock diagnosis and zone creation

By stacking layers of topography, soil characteristics, crop, and weed density data into management zones, patterns within paddock’s can be identified. These layers then undergo geospatial analysis to understand their correlations, and then ground-truthing, before being consolidated into management zones.

Once management zones are defined, a prescription is generated using farm management software. This prescription includes a selection of pre-emergent herbicides to control target weed(s). The process is guided by testing a matrix of herbicides suggested by growers and agronomists, with local proposed chemistries providing case studies for regional feasibility on varying rates and application methods.

Testing soil characterisation through mapping zones on herbicide performance

A series of trials were planned from 2023-2025 to gain insight into soil variability by mapping paddocks with available technology and comparison treatments comprising of grower-led indication of a standard herbicide matrix, yet at variable rate or product, based on zones.

In QLD and northern NSW, problematic grass weed patches are often associated with lighter soil zones. This is common knowledge but has been validated/measured through UAV and satellite layers where we are testing products such as Dual Gold®, Valor Eze®, and Terbyne® associated chemistries for control of a range of summer grass and broad-leafed weeds at variable rates associated with label in fallow paddocks followed by crops such as sorghum or chickpeas (as allowed by product labels). Current trials are located in Grassdale, Capella have been deployed in the fallow after sorghum. Herbicide performance and crop safety are evaluated using a combination of digital capture by UAV and ground-truth weed assessments at 6 and 10 weeks after application, and post-planting crop response assessments at 3,6 and 10 weeks after sowing.

In southern Australia, small plot trials targeting annual ryegrass (ARG) in wheat were conducted near Crystal Brook, and Gulnare South Australia, respectively in 2023 and 2024. These trials addressed soil pH as the primary soil variability factor and driver of weed pressure . To select trial locations, pH surveys of paddocks were created using a Veris® soil sensor that scans paddock for pH, organic matter/carbon and EC (electroconductivity).

Two maps showing the preliminary pH Zone Mapping of trials in SA with Veris®.

Figure 2. Preliminary pH Zone Mapping of trials in SA with Veris®.
Survey by Trengrove Consulting.

Seasonal conditions across 2023 and 2024 varied.  2024 was a very dry season with 190mm rainfall average in the growing season versus over 230 mm at Crystal Brook. In 2023, dry conditions severely impacted yield. However, the trials produced comparable results with regards to weed control in both years. In 2024, minimal differences in crop response were observed between herbicides per zone. However, Overwatch® treatments scored an average crop response of 7.95 on a general phytotoxicity scale 1-9 (1 plant dead, 9 healthy plant).

Despite several products demonstrating similar ARG control across different pH zones, significant differences in herbicide performance across products and pH were noted (mainly low and high pH zones).  There was no significant effect on the interaction between product and pH zones for 2024, while some products performed similarly across pH zones (e.g. Boxer Gold® and Sakura®) whereas others did not show consistent control over different pH zones.

Table 1. P-Values Prob > F - General Factorial Anova (LSD) % Weed control.

% Weed controlCrop response rank (1-9)
2023202420232024
pH_Zone0.5672 (ns)0.0059*<0.001***0.2058(ns)
Product<0.0001***0.0016*<0.001***0.0002**
pH_Zone*Product0.7649 (ns)0.9991(ns)0.003**0.6596(ns)
The Factorial Anova with Least Square Differences shows the effect of pH zone and Product. Significant effects observed at α=0.05. Asteriks denote the level of significance, where *=p< 0.05 (significant),**=P<0.01 (highly significant),***=p< 0.001 (highly, very significant), “ns”=denotes not significant effect.

Products did differ significantly in performance on both years for weed control, see Table 1. The interaction between product and pH zone was significant for pH zone and product in 2023 for crop response. While these results on the effect of pH zone on product performance, the variation may be due to seasonality, available soil moisture and other soil characteristics, which need to be further investigated.

Two line graphs illustrating the main effects plot on percent Annual Ryegrass (ARG) Control for 2023 (42 days after application,  DAA) and 2024 (55 days after application, DAA). This plot shows the mean percentage weed control of each treatment, with the impact of pH Zone displayed on the left, and the impact of different herbicide products on the right.

Figure 3. Main effects plot on percent Annual Ryegrass (ARG) Control for 2023 (42 days after application,  DAA) and 2024 (55 days after application, DAA). This plot shows the mean percentage weed control of each treatment, with the impact of pH Zone displayed on the left, and the impact of different herbicide products on the right.

Whilst the soil pH screening with Veris Equipment was the preliminary driver of mapping management zones, in both years, the allocation of trial zones (low, mid and high) smoothed the pH variability within the paddock. Differences between soil analysis results and Veris could be due to timing of Veris Screening and growers practice on liming. Sampling could have introduced another source of variation in the results, as many samples collected at 0-10 cm depth were composited. Sampling occurred prior to trial and post liming.  However, low pH zones, weed pressure was consistently higher, and control was lowest, for these observations reflect the zone variability found in the Veris screening.

Additionally, 2024 soil results indicated differences in low and mid pH in the Cation Exchange Capacity, PBI (phosphorus buffering capacity) and DGT-P, which measures plant available phosphorus. In the mid pH soil in 2024 with higher PBI values, may bind phosphorus tightly, and with a lower DGT-P (69) than the low pH soil (97) may be reducing phosphorus availability and potentially limiting ARG growth. Conversely, lower PBI soils retain more available phosphorus, supporting ryegrass proliferation. This correlation with different pH sites becomes less evident when examining some of the trial results across the two seasons, specifically when assessing ARG pressure and control per treatment in low and high pH zones across years. This is particularly true for Avadex Xtra® and in combination with Overwatch® treatments over both years as seen in Table 2.

Table 2. Pre-sowing results - Soil Physico-chemical analysis by APAL.

Sample Name

2023
Crystal Brooks
Low pH
2023
Crystal Brooks
Mid pH
2023
Crystal Brooks
High pH
2024
Gulnare
Low pH
2024
Gulnare
Mid pH
2024
Gulnare
High pH
Organic carbon (W&B)% (40°C)0.991.671.611.942.291.96
MIR – Aus Soil Texture Sandy loamClay loamLoamLoamSilty loamClay loam
Colwell Phosphorusmg/kg406230645628
PBI + Col P 55711056374111
DGT-P(μg/L)758026976914
KCI Suphur (S)mg/kg6.69.1643436
Calcium (Ca) – AmmAccmol/kg4.989.9126.36.810.137.5
Magnesium (Mg) – AmmAccmol/kg1.264.22.282.43.23.4
Potassium (K) – AmmAccmol/kg0.8632.42.4511.82.3
Sodium (Na) – AmmAccmol/kg0.0970.2270.1420.40.30.3
Exchangeable aluminiumcmol/kg<0.02<0.02<0.02<0.02<0.02<0.02
ECECcmol/kg7.216.731.210.715.443.4
Sodium%1.41.40.53.92.000.60
Salinity EC 1:5dS/m0.130.160.210.260.230.21
EcedS/m1.81.422.472.192

Table 3. Mean percent weed control on multiple products in Small Plot Trials in SA, 2023 and 2024.

Average of % control ARG 40-60DAA (days after application)
20232024
TreatmentsHigh pHMid pHLow pHHigh pHMid pHLow pH
Avadex Xtra®47.6574.6851.6571.6365.382.64
Boxer Gold®76.0759.0747.6861.5463.4619.42
Boxer Gold + Avadex Xtra85.2884.8179.7550.9672.1253.96
Luximax®79.1477.2269.6286.0676.9273.38
Luximax®+ Voraxor54.4087.3482.03   
Mateno Complete®81.6077.2250.7266.3563.9466.19
Overwatch®45.8182.2866.3386.5484.1350.84
Overwatch + Avadex Xtra91.4187.3481.2790.8781.2560.43
Overwatch fb  Boxer Gold **   87.5071.1562.59
Overwatch fb Mateno Complete**82.8275.9551.7381.7378.8556.12
Sakura59.5148.1077.2266.3564.4255.40
Sakura + Avadex Xtra88.3477.2292.1580.2960.1035.97
Sakura + Overwatch82.8284.8185.8293.7584.1363.31
Trifluralin76.0778.4871.1455.7738.4653.72
Trifluralin + Avadex Xtra79.1469.6280.2563.9462.5030.94
**At the time of assessment, Boxer Gold and Mateno Complete had not yet been applied.

Table 4. 2024 ANOVA - ARG counts per meter square 55 DAA means comparison with LSD test.

Trt #HerbicideRate (g/ha or mL/ha)ARG per m2
Low pHMid pHHigh pH
1Nil031ab4.6ab3.9a
2Avadex® Xtra2000#43a1.6cd1.3bcd
3Boxer Gold®250025abc1.7abc1.8abc
4Sakura®11814bc1.6abc1.6abc
5Luximax®5008c1.1cd0.6de
6Overwatch125017bc0.7d0.6def
7Mateno® Complete100010c1.7abc1.6abc
8Boxer Gold + Avadex Xtra2500 + 2000#14bc1.3abcd2.3a
9Sakura + Avadex Xtra118 + 2000#20bc1.8abc0.9bcd
10Sakura + Overwatch118 + 125011c0.7cd0.3f
11Overwatch fb  BoxerGold **1250 fb 250012c1.3cd0.6def
12Overwatch + Avadex Xtra1250 + 2000#12c0.9cd0.4ef
13Overwatch fb Mateno Complete**1250 fb 100013bc1.0bcd0.8cd
14Trifluralin480200022bc2.8a2.0ab
15Trifluralin + Avadex Xtra2000 + 2000#22bc1.7abc1.7abc
Pr(>F)0.0490.044<0.001
# Note: Label rates for standalone use of Avadex Xtra are 1.6L/ha when used alone in full disturbance systems, or 3.2L used as an IBS treatment in no/min till systems. Label rates in mixes with trifluralin or s-metolachlor as an IBS treatment in no/min till systems are 1.6-2.4L/ha. Always check product labels and use at registered use rates.**At the time of assessment, Boxer Gold and Mateno Complete had not yet been applied.

In Western Australia trials were conducted for canola-wheat rotation in both 2023 and 2024 to assess the impact of soil type on product efficacy and crop safety. The trials targeted volunteer canola and wild radish in wheat, across three different soil types: white sand, yellow sand, and gravel. While the results from the 2024 trials are still being analysed, the 2023 results showed significant differences in herbicide efficacy by soil zone. White sand enabled the best weed control for most herbicides, but the inverse was true for crop health (see Figure 4 and 5 below).

Line graph illustrating herbicide efficacy (% control) on wild radish 85 days after application (DAA) in a small plot pre-emergent trial at Walkaway, WA 2023. Products: Callisto® @ 100/150/200 mL/ha; Diuron 900 @ 275/550 g/ha; Voraxor® @ 150/200 mL/ha; Terrain® Flow @ 125 mL/ha; Brodal® Options @ 200 mL/ha.

Figure 4. Herbicide efficacy (% control) on wild radish 85 days after application (DAA) in a small plot pre-emergent trial at Walkaway, WA 2023. Products: Callisto® @ 100/150/200 mL/ha; Diuron 900 @ 275/550 g/ha; Voraxor® @ 150/200 mL/ha; Terrain® Flow @ 125 mL/ha; Brodal® Options @ 200 mL/ha.

Line graph showing wheat crop emergence 31 days after planting (DAP) in a small plot pre-emergent trial at Walkaway, WA 2023.

Figure 5. Wheat crop emergence 31 days after planting (DAP) in a small plot pre-emergent trial at Walkaway, WA 2023.

Currently, 2024 trial data is still being analysed, we will continue to evaluate the potential drivers in soil and weed pressure behind observed variations in herbicide performance as part of variable application of products and rates across different soil zones. Although the project does not aim to evaluate all interactions between crop, weed, herbicide, and environment, the current findings highlight that paddock variability found in soil can affect herbicide performance. This emphasizes the importance of tailoring prescriptions with products and rates for pre-emergent herbicide strategies for a more efficient weed control and crop safety.

Precision application technology

Direct injection technology is one way herbicide rates could be changed on the go in the paddock in response to a variable rate map.  Direct injection technology is not new; however, the main challenge has been managing the chevron effect, a v-shaped application pattern based on the distribution of the product across the spray boom against travel time along the spray pass (see Figure 6). It is primarily caused by the time delay between product injected into the spray line to when it reaches the nozzles. This variation in product concentration is influenced by travel speed, the product viscosity, solubility, length of spray boom, flow rate of carrier, and injection point location.

The severity increases with direct injection systems since it relies on a single injection point. By injecting herbicides at multiple locations across a boom, the delay until it reaches the nozzle is reduced.  A multi-point system, injected at the boom, has been developed to help reduce the chevron effect, as illustrated in Figure 6 below.

Annotated diagram showing a visual representation of single- and multi-point injection spray in movement forward (upward) illustrating the chevron effect.

Figure 6. Visual representation of single- and multi-point injection spray in movement forward (upward) illustrating the chevron effect.

Although there are isolated instances of sprayers fitted with direct injection, for greater consistency where trialling locations will vary, Syngenta engaged in the development of a Multi-Point Direct Injection Sprayer (MPDIS) led by RDO® Equipment in Toowoomba. Trailer specifications are in Table 5.

Table 5. Multi point direct injection sprayer (MPDIS) specifications.

FeaturesSpecification
RTK SystemSF RTK G5
Main carrier tank capacity1200 L
Direct injection (DI) tank capacity70 L each (2 tanks)
Swath width12 m
Sections5 sections
Section width2.4 m each
DI locationAt the boom
Friction tubes1.8mm tubes to stabilize pressure and flow rate
Application capabilityMultiple pre-emergent products in a single pass at varying rates according to designed zones

With the development of the MPDIS sprayer in early 2024, a pilot large-scale trial was conducted in a commercial farming system at Grassdale, QLD. This was the first in a series of trials to test variable rate application using multiple technologies based on geospatial data layers. The trial design was carried out in collaboration with a local agronomist, identifying problematic weeds such as feathertop Rhodes grass, fleabane, and other summer grasses in the lighter soil areas.

Two maps demonstrating UAV data collected by Airborn Insight® with multispectral drone, post processed to remove soil reflectance. In Orthomosaic red-orange colours indicate higher weed abundance.

Figure 7. UAV data collected by Airborn Insight® with multispectral drone, post processed to remove soil reflectance. In Orthomosaic red-orange colours indicate higher weed abundance.

In the figure above, a UAV was used initially to map out soil texture in fallow (bare) paddock, using differences in soil reflectance and colour patterns correlating to soil texture.  Zones were subsequently assessed by ground-truth observations  and soil sampling. Sandy areas typically have higher reflectance (NDVI values) and different patterns due to quicker drainage. Additionally, clay-rich and dark organic soils present lower values due to absorbing light across the spectra. Additional indices were used to confirm the soil x vegetation differentiation, such as satellite OSAVI, RGBI and others.

The paddock characterisation followed on from a comparison against satellite imagery, soil EM scanning and strategic soil sampling, where 21 out of 22 soils matched the exact soil texture results derived from laboratory soil analysis results.

Four maps showing management zones created post paddock soil texture characterisation. Top left: A combination of satellite layers was compared against UAV. Top right: strategic sampling points mapped the soil variation across different zones. Bottom left strip trial designed overlayed on soil Dual EM @ 50cm. Bottom right: management zones created with trial design overlay.

Figure 8. Management zones created post paddock soil texture characterisation. Top left: A combination of satellite layers was compared against UAV. Top right: strategic sampling points mapped the soil variation across different zones. Bottom left strip trial designed overlayed on soil Dual EM @ 50cm. Bottom right:  management zones created with trial design overlay.

The zones were derived from the measured layers of soil scanning.  A matrix of herbicide treatments was developed to spray multiple products per strip at varying rates, where the lighter soil texture had 4 treatments (Table 6).

Table 6. Pre-emergent herbicide treatments applied in trial strips in different soil zones.

Light soil*Heavy soil*All zones
Valor® @ 280 g/haDual Gold® @ 1 L/haTerbyne® @ 1 kg/ha
Valor® Eze™ @ 220 mL/ha + Dual Gold® @ 1 L/ha
Dual Gold® @ 2 L/ha
Dual Gold® @ 1 L/ha
*Light soil included sampled regions as sandy loam and sandy clay. Heavy soil included zones with clay.

As a first-of-its-kind trial, we were reminded that "you do not learn anything if nothing goes wrong," facing many issues on site from software to hardware.

Software for precision mapping

  1. Two AB lines were defined in the field however neither aligned with current tramlines, requiring a shift in the entire trial map and prescription (Rx), which was done by the PCT Agcloud local support team due to connectivity issues.
  2. The prescription generated a map in 2 m pixels, causing a zig-zag effect on the main controller monitor and shifting treatments sideways by a meter to align the pixels. Pushing the Rx into QGIS resolved the effect of pixelation by smoothing polygons.

Environment and product

The application of pre-emergent herbicides requires consideration of mixing different formulations, dilutions, and the required volume of water for activation or incorporation. Their solubility and adsorption influence tank allocation and mixing.

Hardware

Preparing tanks with granular products for direct injection (DI) application, adjusting rates based on tank water capacity and required spray volume presented challenges. Dual Gold® placed neat into the first DI tank increased in viscosity due to temperatures below 20°C, rupturing the pump tube twice. This was resolved by swapping tubes and distributing the product into two DIs after applying Valor® Eze™. Syngenta's team in Basel, Switzerland is investigating the formulation's impact on product flow.

Continued research with the MPDIS sprayer will explore the adaptability of various products and equipment, focusing on precision application adjustments like flow-volume, pump pressure, and application speed versus accuracy.

Conclusion

With the onset of small plot trials, we were able to validate the soil paddock variability and response to weed control and crop response. Some products perform better at different pHs, and soil type/texture highlighting the need for paddock characterisation and adjusting herbicide program to match the variability.

Digital mapping of soil can be improved by understanding constraints from farmer knowledge and ground-truthing digital capture with strategic soil sampling.

The technical difficulties with software compatibility, hardware fitness and chemistry delivery highlight the need to evaluate and address current workflow challenges. This underscores the importance of converging efforts between precision technology development and the crop protection industry to further innovate and support growers. Note: Some use patterns were included for experimental purposes only. Always read and follow label directions.

Table 7. Products used in these trials and their active ingredients.

ProductActive
Avadex® Xtra500 g/L tri-allate
Boxer Gold®800 g/L prosulfocarb + 120 g/L s-metolachlor
Brodal® Options500 g/L diflufenican
Callisto®480 g/L mesotrione
Diuron 900900 g/kg diuron
Dual Gold®960 g/L S-metolachlor
Luximax®750 g/L cinmethylin
Mateno® Complete400 g/L aclonifen + 100 g/L pyroxasulfone+ 66 g/L diflufenican
Overwatch®400 g/L bixlozone
Sakura®850 g/kg pyroxasulfone
Terbyne®750 g/kg terbuthylazine
Terrain® Flow480 g/L flumioxazin
Trifluralin 480480 g/L trifluralin
Valor Eze®480 g/L flumioxazin
Voraxor®250 g/L saflufenacil + 125 g/L trifludimoxazin

Acknowledgements

The research undertaken as part of this project is made possible by the significant contributions GRDC, support of growers, agronomists through trial cooperation, we would like to thank all for their continued support.

Data provided by trials and remote sensing data of the following farm management platforms:
Cropwise Operations, DataFarming, FarmLab, JD Ops, PCT AgCloud, SwarmFarm Robotics.

Additional data collection by contractors and team: Airborn Insight, Agrarian Management, CGS, Eurofins APAL, Kalyx, Metagen Pty Ltd, PairTree Technologies, RDO Equipment Pty Ltd, Single Ag, SurePoint Ag Systems, Trengrove Consulting & Veris Technology (Trengrove).

We also acknowledge the contributions of AAGI team at Curtin University, AHRI Team at UWA Perth, Patrick Filippi with the National Soil Mapping Project and team at Sydney University.

This research utilises open-source libraries including ArcGIS online, QGIS, SSURGO.

Contact details

Lara Vallejo Roosdorp
Rob Battaglia  
Syngenta Australia
Level 1, 2-4 Lyonpark Rd
Macquarie Park, NSW 2113 
lara.vallejo_roosdorp@syngenta.com
rob.battaglia@syngenta.com

Date published
February 2025

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GRDC Project Code: SYA2304-001RTX,

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