Benchmarking crop performance following soil profile re-engineering: four-year field studies in an Arenosol and a Kurosol of Western Australia

Benchmarking crop performance following soil profile re-engineering: four-year field studies in an Arenosol and a Kurosol of Western Australia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Benchmarking crop performance following soil profile re-engineering: four-year field studies in an Arenosol and a Kurosol of Western Australia Gaus Azam, Kanch Wickramarachchi, Hasinur Rahman, Md Shahinur Rahman, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8297071/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Context Soil constraints, including subsoil acidity, compaction, and low fertility, limit crop productivity and water-use efficiency (WUE) in Western Australia (WA) and around the world. Conventional amelioration offers slow or short-lived benefits. Soil profile re-engineering (SPR), involving deep mixing with amendments to 80 cm depth, may address multiple constraints, but the longevity of its productivity benefits and economic outcomes remain poorly understood. Aim This study assessed the persistence of soil improvements and crop responses to soil re-engineering across four cropping seasons under variable rainfall. Methods Eight treatments, including an untreated control, shallow surface amendments, and four re-engineering approaches, were evaluated in a partially randomised block design on two contrasting soils: an Arenosol and a Kurosol in the central wheatbelt of WA. Measurements included soil physicochemical properties, grain yield, WUE, and N and K uptake. Key results All SPR treatments involving soil loosening and incorporation of lime substantially increased pH Ca and cation exchange capacity (CEC) and reduced soil strength, while clay addition enhanced volumetric water content, and addition of compost increased soil organic carbon (SOC) throughout the profile. Grain yield increased by up to 432% and WUE by up to 9.8 kg mm⁻¹ relative to the control, whereas shallow incorporation treatments produced no or minimal yield and WUE gains depending on the soil types, amendments, and crop types. Yield responses to SPR were consistent across seasons, crops, and soil types. N and K uptake increased proportionally with yield. Regression tree analysis identified changes in CEC, SOC, and soil strength as the dominant predictors of yield improvement (explaining up to 80.4% of variance) across both soils. Clay addition was the primary driver of yield gains in the Arenosol, whereas increases in pH Ca were more influential in the Kurosol. Benefits from SPR persisted for at least four cropping seasons and are expected to continue for several years. Conclusions and i mplications Although soil profile re-engineering may not be economically scalable at present, it provides a valuable benchmark for designing targeted, cost-effective amelioration strategies to enhance the resilience and productivity of rainfed cropping system in semi-arid environments in WA. Agricultural Engineering Subsoil acidity soil compaction soil strength water use efficiency dryland cropping water-limited yield potential Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Soil physical, chemical and biological constraints frequently limit crop performance and the sustainability of agricultural productivity. In the grainbelt of Western Australia (WA), a complex suite of limitations reduces grain yield and water-use efficiency (WUE) despite decades of soil management and agronomic innovations (Gazey et al. 2019 ; Roper et al. 2015 ; van Gool 2016 ; Davies et al. 2024 ; Lawes et al. 2021 ; Harries et al. 2022 ; Kirkegaard et al. 2011 ; Schmittmann et al. 2021 ; Schneider et al. 2017 ; Aziz et al. 2017 ). Frequently found soil constraints include subsoil acidity, compaction, low fertility, and low water-holding capacity, which often co-occur (van Gool 2016 ) and interact to restrict roots to shallower depths in the soil profile (Azam et al. 2025 ). As a result, crops fail to make use of resources from deeper in the soil profile, and remain vulnerable to terminal drought, and typically fall short of water-limited yield potential (Sadras and Angus 2006 ; Harries et al. 2022 ; Barrett-Lennard et al. 2024 ; Lawes et al. 2021 ). Subsoil acidity is widespread across Australian cropping soils, driven by ammonium-based fertiliser use, removal of alkaline products, increased legume rotations, and reduced tillage (Gazey et al. 2019 ; Li et al. 2019 ). Low pH increases aluminium and manganese toxicity, which creates hostile conditions for root growth and reduces the availability of phosphorus, calcium and magnesium (Rengel 2003 ; Bell and de Oliveira 2022 ; Anderson et al. 2021 ). Subsoil compaction arises from the traffic of heavy machinery, livestock grazing, and natural soil consolidation during dry periods (Busscher et al. 2002 ; Hall et al. 2020 ). Compaction commonly occurs below the top 20 cm of the soil profile, where root penetration is impeded and porosity is limited (Bengough et al. 2011 ; Unkovich et al. 2023 ; Azam and Gazey 2019; Azam et al. 2024b ; Wickramarachchi et al. 2025b ), and is a major cause of the persistent yield gap (the difference between water-limited yield potential and the actual yield). There are additional constraints that interact with subsoil acidity and compaction. Low fertility is an inherent characteristic of WA’s ancient, weathered soils, which are typically deficient in N, P, K, S and micronutrients and have poor cation exchange capacity, making them prone to N and S leaching (Bell and de Oliveira 2022 ; Azam 2025 ; Anderson et al. 1998 ). In coarse-textured sands, these constraints reduce fertiliser use efficiency and pose environmental risks such as off-farm P pollution (Weaver et al. 2005 ), N leaching (Anderson et al. 1998 ) or emission of nitrous oxide (Barton et al. 2013 ). Low water-holding capacity, typical of sandy and sandy-duplex soils, further limits resilience to variable rainfall, as plant-available water is minimal and rapidly depleted (Sadras and Angus 2006 ; Bruun et al. 2014 ). The combination of these soil constraints restricts rainfall capture and use, leaving WUE consistently below the theoretical potential despite advances in genetic potential and agronomic management (Lawes et al. 2021 ; Aziz et al. 2017 ). A range of strategies to address theabove mentioned soil constraints have been developed by researchers and adopted by farmers, in Australia and internationally, but each has limitations. The surface-application of lime is the primary approach to acidity management, however, due to the very slow downward movement of alkali from surface applied lime, amelioration of subsoil acidity takes decades (Azam and Gazey 2021 ; Li et al. 2019 ). Deep ripping to 50 cm depth is widely used to alleviate compaction, but the benefits are partial and temporary as soils recompact (Damon et al. 2022 ; Unkovich et al. 2023 ). Clay addition can increase water infiltration and storage, but incorporation is difficult and results are inconsistent, especially when poorer-quality clay is used at low ratesand incorporated to shallow depth (Hall et al. 2010 ; Roper et al. 2015 ). The addition of organic amendments can improve soil fertility and structure; however, it might take decades before cropping becomes profitable on soils amended with organic amendments (Hall and Edwards 2025 ; Lauricella et al. 2020 ). These interventions are typically targeted at single constraints, act slowly, or provide uneven benefits, underscoring the need for integrated approaches capable of addressing multiple soil limitations simultaneously (Isbister et al. 2024 ; Azam et al. 2023 ; Davies et al. 2019 ; Unkovich et al. 2023 ). Soil profile re-engineering (SPR) is a recently developed experimental approach, which involves excavating individual soil horizons (often in 10 cm increments) to a depth of 80 cm followed by thorough mixing to incorporate various soil amendments such as lime, clay and organic materials and then replacing each layer back into the pit in its original sequence, resulting in a reengineered soil profile (Azam et al. 2025 ; Azam 2025 ). Unlike incremental soil management strategies such as deep ripping or surface liming, SPR rapidly eliminates or alleviates subsoil constraints — including acidity, compaction and nutrient deficiencies (e.g. phosphorus, calcium and magnesium) — to create a more uniform and productive soil profile (Azam and Gazey 2019; Azam et al. 2022 ; Azam et al. 2025 ; Wickramarachchi et al. 2025b ; Wickramarachchi and Azam 2025 ). While this approach seems to be not scalable or economically viable at the farm level for now, it provides a benchmark for the maximum grain yield and WUE achievable if multiple constraints are simultaneously removed (Azam et al. 2025 ). This benchmark is critical for the development of next-generation soil amelioration technologies for large-scale adoption with improved return on investment. Evidence from a similar study by Wickramarachchi et al. ( 2025b ), together with findings from previous research using similar approaches (Gahoonia et al. 2007 ; Azam et al. 2024b ), suggests that SPR can markedly improve rooting depth and root density, enabling crops to better exploit subsoil resources (Wasson et al. 2012 ). It also enhances nutrient uptake efficiency—particularly nitrogen recovery—by reducing leaching losses (Angus and Grace 2017 ; Aziz et al. 2017 ; Wickramarachchi et al. 2025b ). By simultaneously alleviating acidity, compaction and other constraints, re-engineered soils support better crop establishment, higher yields, and improved WUE (Azam et al. 2024a ). However, little is known about how long these benefits persist under field conditions, how they interact with variable seasonal rainfall, or how different cereal crops respond, all of which influence the economics of adopting part or all of the technique This study reports on data from two sites from Western Australia (WA), Bolgart and Meenar, to evaluate the impacts of soil profile re-engineering on crop performance in the last four years (2021–2024). The main research question was: to what extent can SPR, through loosening and incorporation of lime, clay, inorganic nutrients and organic matter at 10 cm increments to 80 cm depth, overcome the combined constraints of acidity, compaction, low fertility and low water-holding capacity, and thereby improve root growth, grain yield, and water-use efficiency across multiple cropping seasons in contrasting Western Australian soils (Arenosol and Kurosol). To answer the above question, we conducted two SPR field experiments and assessed the persistence of soil chemical and physical improvements, quantified effects on root development, yield and WUE over four years under variable seasonal conditions on the two soils. We expect results from this study will inform the development of scalable soil amelioration technologies, enable economic assessment of the technique and contribute to future sustainable soil management strategies for constrained agricultural landscapes. Methods and materials Study sites In May 2021, we established two SPR field experiments in the central grain growing regions of WA. Experiment 1 was conducted at Bolgart (Latitude: -31.3162; Longitude: 116.5831; Elevation 260.2 m above mean sea level, AMSL; about 130 km northeast of Perth), while Experiment 2 was conducted at Meenar (Latitude: -31.6450; Longitude 116.8940; Elevation 241.8 AMSL; about 120 km east of Perth). The soil at Bolgart is classified as Yellow Arenosol, while the soil at Meenar was classified as Brown Kurosol (Isbell 2021 ). Both of the experimental sites were located in a hot, semi-arid temperate region, corresponding to the Csa category in the Köppen–Geiger climate classification (Peel et al. 2007 ). Under the rainfall zone classification for southwestern West Australia, both sites (Bolgart = 366 mm and Meenar = 429 mm per year) fell within the medium rainfall zone (Islam and Salim 2012 ). The paddock at Bolgart had been in a cereal-canola-cereal-cereal-lupin rotation, while the paddock at Meenar had been in a cereal-canola-cereal-canola rotation. Both paddocks were cropped under no till systems since mid 1990s until 2020. Both paddocks were surface limed with 4 t ha − 1 limesand (hereafter lime), but the lime was never incorporated. Both experimental sites had multiple soil constraints, including subsoil acidity, compaction, low inherent fertility (low soil organic carbon, SOC and cation exchange capacity, CEC), and limited water-holding capacity. The soil at Bolgart consisted of a coarse-textured, moderately acidic sand throughout the profile, i.e., an Arenosol, while the Meenar site had a coarse-textured sand at 0–40 cm and a sandy clay at 40–80 cm, with a very low pH throughout the profile, i.e., a Kurosol (Isbell 2021 ). More details on sites and soil specific characteristics are provided in Table 1 . Table 1 Location, rainfall, soil types and soil constraints at two experimental sites. Parameters Bolgart Meenar Coordinates (Lat, Long) -31.3162, 116.5831 -31.6450, 116.8940 Elevation (above mean seas level, m) 260.2 241.8 Long-term annual rainfall (mm) 366 429 Long-term growing season (April-October) rainfall (mm) 291 355 Australian soil classification (Isbell 2021 ) Yellow Arenosol Brown Kurosol Soil textural class (sand, silt and clay, %) Coarse sand: 0–10 cm: (96.8, 1.3, 1.9) Coase sand: 10–40 cm: (96.9, 0, 3.1) Coarse sand: 40–80 cm: (96.7, 0, 3.6) Coarse sand: 0–10 cm: (90.8, 2.3, 6.9) Loamy sand: 10–40 cm: (84.2, 2.6, 13.2) Sandy clay: 40–80 cm: (60.0, 3.3, 36.7) Soil organic carbon (SOC, %) 0–10 cm: 0.38; 10–40 cm: 0.15 and 40–80 cm: 0.10 0–10 cm: 1.29; 10–40 cm: 0.43 and 40–80 cm: 0.23 pH Ca 0–10 cm: 5.4; 10–40 cm: 4.6 and 40–80 cm: 4.6 0–10 cm: 4.5; 10–40 cm: 4.2 and 40–80 cm: 4.0 Cation exchange capacity (CEC, cmol kg -1 ) 0–10 cm: 0.77; 10–40 cm: 0.21 and 40–80 cm: 0.20 0–10 cm: 1.26; 10–40 cm: 0.39 and 40–80 cm: 0.72 Experimental setup Eight treatments were evaluated: an untreated control (T1), three shallow soil-amelioration (SSA) treatments (T2–T4), and four SPR treatments (T5–T8) (Table 2 ). Treatments were arranged in a partially randomized block design, with T1–T4 and T5–T8 allocated to two separate blocks within each of the three replicates. Treatments were applied once before sowing in May 2021. Plots measured 5 × 4 m with 1 m buffer zones between treatments. The soil profile re-engineering treatments (T5–T8) followed the general approach previously outlined by Azam ( 2025 ), where the soil horizons were removed, amended, and replaced. For these treatments soil layers (0–10, 10–40, and 40–80 cm) were excavated using a 20-ton excavator (Komatsu PC200) and stockpiled separately by layer. Each layer was returned in 10 cm increments using a front-end loader (Volvo L90F) and lightly cultivated with a rotary hoe (Red Roo RH918) after spreading and incorporation of the amendments as described in Table 2 . For T2, T3 and T4, all amendments (Table 2 ) were placed on the surface followed by incorporation to 10 cm depth using the same rotary hoe. The liming material was limesand, with a neutralising value of 94.9% relative to analytical CaCO₃, and contained 99% particles < 0.5 mm; this was applied to all treatments except T1 (Table 2 ). Clay was sourced either from a nearby pit at Bolgart (sand 28.8%, silt 0.7%, clay 70.5%) or the B horizon (40–80 cm) of the experimental soil at Meenar (sand 60.0%, silt 3.3%, clay 36.7%). Compost was obtained from a commercial supplier and contained 40% organic C, 2.5% N, 1.0% P, 1.7% K, 5.4% Ca, 0.5% Mg, 1.7% S, and 0.4% Na; this was applied in T4 and T8 (Table 2 ). In addition, inorganic fertiliser containing N, P and K was applied (in T3 and T4, see Table 2 ) at rates calculated to supplement the proportion of nutrients expected to be mineralised from the compost (approximately 16% per year) (Horrocks et al. 2016 ). This inorganic fertiliser treatment with matching nutrient content was included to distinguish the nutrient contribution of the organic amendment (i.e., improved soil fertility) from its non-nutrient effects, such as those arising from its carbon and biological components (e.g. improved soil structure, increased microbial activity and increased water-holding capacity). Table 2 Description of the soil re-engineering experiments. Treatments Description Bolgart Meenar Control (T1)* No tillage or amendment was applied. No tillage or amendment was applied. Surface liming and claying to 10 cm depth (T2) Loosening of soil and incorporation of 1.5 t ha − 1 lime, and 110 t ha − 1 clay to 0–10 cm depth. Loosening of soil and incorporation of 1.7 t ha − 1 lime, and 110 t ha − 1 clay to 0–10 cm depth. Surface liming, claying and adding N, P and K to 10 cm depth (T3) Loosening of soil and incorporation of 1.5 t ha − 1 lime, 110 t ha − 1 clay, and 61, 24 and 42 kg ha − 1 inorganic N, P and K, respectively to 0–10 cm depth. Loosening of soil and incorporation of 1.7 t ha − 1 lime, 110 t ha − 1 clay, and 57, 23 and 39 kg ha − 1 inorganic N, P and K, respectively to 0–10 cm depth. Surface liming, claying and adding compost to 10 cm depth (T4) Loosening of soil and incorporation of 1.5 t ha − 1 lime, 110 t ha − 1 clay, and 42 t ha − 1 compost to 0–10 cm depth. Loosening of soil and incorporation of 1.7 t ha − 1 lime, 110 t ha − 1 clay, and 31 t ha − 1 compost to 0–10 cm depth. Loosening and liming to 80 cm depth (T5) Loosening of soil and incorporation of 6.0 t ha − 1 lime to 0–80 cm depth. Loosening of soil and incorporation of 6.8 t ha − 1 lime to 0–80 cm depth. Loosening, liming and claying to 80 cm depth (T6) Loosening of soil and incorporation of 6.8 t ha − 1 lime, and 1,337 t ha − 1 clay to 0–80 cm depth. Loosening of soil and incorporation of 6.8 t ha − 1 lime to 0–80 cm depth and 329 t ha − 1 clay to 0–40 cm depth. Loosening, liming, claying and adding compost to 80 cm depth (T7) Loosening of soil and incorporation of 6.8 t ha − 1 lime, 1,337 t ha − 1 clay, and 245, 98 and 166 kg ha − 1 inorganic N, P and K, respectively to 0–80 cm depth. Loosening of soil and incorporation of 6.8 t ha − 1 lime to 0–80 cm depth; 329 t ha − 1 clay to 0–40 cm depth and 226, 90 and 154 kg ha − 1 inorganic N, P and K, respectively to 2–80 cm depth. Loosening, liming, claying and adding compost to 80 cm depth (T8) Loosening of soil and incorporation of 6.8 t ha − 1 lime, 1,337 t ha − 1 clay, and 167 t ha − 1 compost to 0–80 cm depth. Loosening of soil and incorporation of 6.8 t ha − 1 lime to 0–80 cm depth; 329 t ha − 1 clay to 0–40 cm depth and incorporation of 125 t ha − 1 compost to 20–80 cm depth. Notes: all rates of amendments were calculated on a w/w basis. The untreated control received a surface application 4 t ha − 1 lime as a standard agronomic practice in the last ten years organised by the host farmers. Crop management The experiments were established within farmer’s existing controlled traffic farming (CTF) system at both sites. This allowed the host growers to run the cropping program according to their commercial plan, i.e., seeding, fertilisation, weed control, pest and disease control sprays were carried out by the farmers. This operation within the CTF system helped prevent additional machinery-induced compaction in the already loosened, re-engineered soil profiles. Details of the key operations, including crop details, are provided in Table 3 . At the start of the experiment, the Bolgart soil (0–10 cm) contained 15 mg Colwell P kg⁻¹ and 3.8 mg KCl-40 S kg⁻¹, while Colwell K was below the detection limit. In contrast, the Meenar soil (0–10 cm) had 22 mg Colwell P kg⁻¹, 51 mg Colwell K kg⁻¹, and 4.8 mg KCl 40 S kg⁻¹. Based on established critical soil test values, P supply was adequate at both sites (Bell et al. 2013 )d supply was adequate for cereals but not sufficient for canola (Anderson et al. 2013 ). Thefrefore, growers at both sites did not apply S fertiliser to cereals, but both sites were fertilised by 25 kg S ha⁻¹ in seasons when canola was grown. Potassium supply was adequate at Meenar, but inadequate at Bolgart (Brennan and Bell 2013 ). Other baseline nutrient application rates differed between the two sites according to seasonal forecasts and crop choice. At Bolgart, basal applications included 12.5–18 kg P ha⁻¹, 8–40 kg K ha⁻¹, and 65–115 kg N ha⁻¹. At Meenar, basal rates were 20 kg P ha⁻¹, 20 kg K ha⁻¹, and 60–100 kg N ha⁻¹. These N rates reflect typical grower practice for achieving cereal yields of approximately 2–3 t ha⁻¹ (Scanlan et al. 2022 ). Table 3 Bolgart and Meenar sites (Western Australia) seeding, N, P, and K rate (kg ha − 1 ), annual rainfall during 2021–2024 and potential yield (determined using method of Oliver et al. 2029). Year Site Crop type Seeding rate (kg ha − 1 ) Fertiliser applications (kg ha − 1 ) Annual rainfall (mm) Oliver et al. ( 2009 ) potential yield (t ha − 1 ) 2021 Bolgart Wheat, var Scepter 65 N, P and K = 65, 12.5 and 15 496 3.14 Meenar Canola 3 N, P and K = 60, 20 and 20 566 4.22 2022 Bolgart Canola 3 N, P and K = 95, 12.5 and 15 472 3.71 Meenar Barley, var Maximus 80 N, P and K = 60, 20 and 20 443 5.95 2023 Bolgart Triticale var 80 N, P and K = 115, 12.5 and 40 307 2.41 Meenar Canola 3 N, P and K = 100, 20 and 20 240 1.42 2024 Bolgart Barley, var Commodus 65 N, P and K = 87, 18 and 8 333 3.36 Meenar Wheat, var Scepter 80 N, P and K = 60, 20 and 20 352 3.60 Soil sampling, in situ measurements and analyses Soil profile samples were collected each July from 2021 to 2024, when soil moisture conditions were suitable for core sampling using a 40 mm inner-diameter stainless-steel tube. Data from the 2021 sampling are reported in Azam ( 2025 ), while the 2022 and 2023 data are not presented. This paper reports the July 2024 results. Samples were taken at 10-cm depth increments to a maximum of 100 cm, although the final depth varied depending on subsoil conditions (e.g. soil hardness or excess moisture). Within each plot, four sampling points were selected. Soil collected at the same depth from these four points was combined to form a composite sample. From each composite sample, a 100-g subsample was used to determine the gravimetric water content. The remaining material was dried at 40°C, passed through a 2 mm sieve, and analysed for soil pH Ca (Method 4B2), CEC (Method 15E1), and SOC (Method 6A1) (Rayment and Lyons 2011 ). Soil strength (penetration resistance) was also measured in July each year, using a handheld electronic cone penetrometer (CP40II, Rimik Pty Ltd, Toowoomba, Queensland), but this paper reports the July 2024 results. Soil pH Ca , soil strength, CEC, and SOC were assessed as indicators of soil acidity, compaction, water-holding and nutrient-retention capacity, and overall soil health to evaluate the effects of soil re-engineering treatments (Anderson et al. 2020 ; Bengough et al. 2011 ; Hall et al. 2010 ; Hoyle et al. 2013 ; Riaz and Marschner 2020 ). In situ root images were recorded annually at crop anthesis (Z65 for cereals; 10% flowering for canola) from treatments T1, T5, T6, T7 and T8 using a 360° root scanner (CI-600, CID Bio-Science, Camas, WA, USA) and 130-cm mini-rhizotron tubes installed in the soil. This approach has been shown to effectively distinguish treatment-related differences in root development in previous work (Uddin et al. 2018 ; Azam et al. 2024b ). Image processing, root tracing and root analysis followed the procedures described in Azam et al. ( 2025 ). Three shoot samples (each collected from a pre-determined sampling zone by cutting two adjacent rows each 1m in length) were collected and composited for each plot. Cereal shoots were sampled at growth stage Z65 (Zadoks et al. 1974 ), while canola shoots were collected at approximately 10% flowering (Smith and Scarisbrick 1990 ). All samples were oven-dried at 60°C for seven days before determining dry biomass. Tissue nitrogen (N) was measured using the Rayment and Lyons ( 2011 , method 7A5 modified) and tissue potassium (K) was measured using the method of McQuaker (1979). Total N and K uptake were calculated by multiplying tissue nutrient concentrations by the corresponding biomass yields to express the results in units of kg ha − 1 . Yield and WUE measurements From each plot, crop was hand-harvested at physiological maturity from a 4 x 2 m area to calculate grain yields (t ha − 1 ). The WUE (kg mm − 1 ) of cereals and canola was calculated using models calibrated in this region by Oliver et al. ( 2009 ) as shownbelow:. $$\:WUE=\frac{\text{Y}}{\text{A}\text{S}\text{W}}$$ where WUE is water use efficiency (kg mm − 1 ), potential grain yield (PY) is grain yield (kg ha − 1 ) and ASW is available soil water (mm), which is calculated as below: ASW = SW + GSR – I where SW is stored soil water at sowing (mm), GSR is growing season (April to October) rainfall (mm), and I is the threshold rainfall (mm) required before a crop will yield. In our work here, it was assumed that SW is equal to 30% of the pre-season (January to March) rainfall (mm), and also has an upper limit equal to the plant available water capacity (PAWC) of the soil (SW ≤ PAWC). The PAWC of the Bolgart and Meenar soils were 40 and 100 mm respectively (Oliver et al. 2009 ). GSR also has an upper limit related to the PAWC of the soil; the upper limit of the GSR for Bolgart and Meenar sites were 240 and 290 mm, respectively (Oliver et al. 2009 ). I was 130 mm for all seasons as the both sites had > 180 mm GSR (Oliver et al. 2009 ). The calculated PY for the two sites for the four experimental yields are presented in Table 3 . Monthly rainfall measures are presented in the Supplemental Materials (Table S1). Statistical analyses Crop yield, nutrient uptake, and soil properties were analysed using separate linear mixed models (LMMs) for each variable, implemented in AsREML-R package (Butler et al. 2018 ) within the R statistical environment (R-Core-Team 2025 ). For yield data, treatment was treated as a fixed effect, and models were fitted independently for each year. The random effects for the experimental design were accounted for with a structure where plots were nested within replications and years were nested within plots. Variance components were estimated for each year using restricted maximum likelihood (REML), and model adequacy was evaluated by inspecting residual distributions. Predicted means for each treatment–year combination were generated, and within-year differences were tested using Fisher’s protected least significant difference (LSD) method. Soil properties were analysed using a similar framework, with treatment included as a fixed effect and models were fitted separately for each sampling time and soil depth. The random structure reflected sampling time nested within plots and plots were nested within replications. To explore the relationship between crop performance and nutrient uptake, linear regressions were conducted between total N and K uptake and grain yield for each season and site. The coefficient of determination (r²) was used to quantify the strength of these relationships, and significance was determined at P ≤ 0.05. Regression tree analysis was applied to identify the relative influence of five key soil physicochemical properties from all sampling depths on grain yield across seasons at both sites. For each regression tree model, the residual mean square error and the proportion of variance explained were reported, providing insight into the primary soil factors governing yield responses. Results Improvement in yield and water-use efficiency Soil profole re-engineering produced consistent, statistically significant increases in grain yield and water-use efficiency (WUE) across all crop species and four contrasting growing seasons at both the Bolgart (Arenosol) and Meenar (Kurosol) sites (Figs. 1–2). In contrast, treatments involving shallow incorporation of amendments (T2–T4) showed minimal or no gains relative to the control (T1) at both sites. On the Arenosol at Bolgart, grain yield (Fig. 1a–d) and WUE (Fig. 1e–h) increased markedly in all four crops in the SPR treatments and in the shallow incorporation of compost treatment (T4) compared to the control. In 2021, wheat grain yield and WUE increased by up to 147% relative to the untreated control, exceeding the least significant difference (LSD for yield = 0.24 t ha⁻¹, LSD for WUE = 2.11 kg mm − 1 , P < 0.05). However, significant improvements in yield and WUE were recorded in only in T4 (surface incorporation) and T8 (incorporation to 80 bm depth) that involved incorporation of lime, clay and compost either in the surface or up to 80 cm depth (Fig. 1a and 1e). In 2022, canola yield and WUE rose by 432% (LSD for yield = 0.74 t ha⁻¹, LSD for WUE = 2.58 kg mm − 1 , P < 0.05) (Fig. 1b and 1f). Canola yield was significantly higher in T4–T8, with the highest difference in yield being 2.14 t ha − 1 in T8 (limed, clayed and composted) compared to T1. Triticale and barley yields were 300% and 277% greater in 2023 and 2024, respectively (LSD = 0.29 t ha⁻¹ and 0.46 t ha⁻¹) (Fig. 1c and 1d). Triticale and barley WUE rose at the same magnitude as with the yields, with the highest improvement of 5.06 kg mm − 1 and 9.81 kg mm − 1 in T8, respectively (LSD = 1.35 kg mm − 1 and 1.92 kg mm − 1 ) (Fig. 1g and 1h). Yield responses were consistent across replicate plots, with all re-engineered treatments (T5–T8) significantly outperforming the untreated control in all years except 2021 (the trial establishment year). At the Meenar site (Kurosol), grain yield (Fig. 2a–d) and WUE (Fig. 2e–h) increased markedly, although treatment effects differed from those at Bolgart (Arenosol). Shallow incorporation of clay and lime (T2) had no effect, while shallow incorporation of nutrients (T3) or compost (T4) had inconsistent effects across years. In 2021, canola yield and WUE increased by up to 106% relative to the control, exceeding the LSD (yield = 0.23 t ha⁻¹, WUE = 0.71 kg mm⁻¹, P < 0.05), primarily in the re-engineering treatments (T5–T8), with the largest gain of 1.57 t ha⁻¹ in T7 (re-engineered with added lime, clay and nutrients to 80 cm depth). In 2022, barley yield and WUE increased by ~ 150% (LSD yield = 0.66 t ha⁻¹, WUE = 2.45 kg mm⁻¹, P < 0.05) in all re-engineering treatments, with the highest gains of 2.62 t ha⁻¹ and 9.68 kg mm⁻¹ in T7 compared to T1. Differences between re-engineering treatments were generally not significant. Canola and wheat yields were 148% and 118% higher in 2023 and 2024, respectively (LSD = 0.53 t ha⁻¹ and 0.47 t ha⁻¹) (Fig. 2c and 2d). In 2023, the maximum canola yield and WUE increased by 1.06 t ha⁻¹ and 5.65 kg mm − 1 in T7, respectively (Fig. 2c and 2g). Similar to canola in 2023, wheat yield and WUE in 2024, rose by 1.23 t ha⁻¹ and 7.50 kg mm − 1 in T7, respectively (Fig. 2d and 2h). Figure 2 near here Improvement in N and K uptakes Re-engineering treatments also resulted in substantial increases in shoot nitrogen (N) and potassium (K) uptakes across all crops and growing seasons at both sites (Fig. 3 and Fig. 4). At Bolgart, total shoot N uptake at anthesis increased substatially in all four seasons (Fig. 3a–d). In 2021, N uptake by wheat shoots grown in the re-engineered treatments (T5–T8) increased by up to 252% relative to the untreated control, exceeding the least significant difference (LSD = 48.2 kg ha⁻¹, P < 0.05). However, the improvement in N uptake was observed only in T4 (surface limed, clayed and composted) and T8 (re-engineering with added lime, clay and compost) (Fig. 3a). In 2022, N uptake in canola shoot increased by approximately 490% with the maximum improvement of 147.8 kg ha⁻¹ in T8 compared to T1 (LSD = 63.1 kg ha⁻¹, P < 0.05) (Fig. 3b). Triticale (2023) and barley (2024) N uptakes in shoot in T8 were 46.9 kg ha⁻¹ and 71.0 kg ha⁻¹ higher than T1, respectively (LSD = 14.1 kg ha⁻¹ and 14.0 kg ha⁻¹) (Fig. 3c and 3d). At Bolgart, total K uptake also increased substantially in all four seasons (Fig. 3e–h). In 2021, K uptake by wheat shoot lifted by up to 336% (92.9 kg ha⁻¹) compared to the untreated control (LSD = 46.8 kg ha⁻¹, P < 0.05), however, the improvement in K uptake was only observed in T4 and T8 (K applied as organic matter) in this first year of the experiment (Fig. 3e). In 2022, K uptake in canola shoot rose approximately by 11-fold with the maximum improvement of 138.6 kg ha⁻¹ in T8 compared to T1 (LSD = 34.6 kg ha⁻¹, P < 0.05) (Fig. 3f). Triticale and barley K uptakes in shoot were 55.0 kg ha⁻¹ and 163.8 kg ha⁻¹ higher in 2023 and 2024, respectively (LSD = 14.4 kg ha⁻¹ and 23.3 kg ha⁻¹) (Fig. 3g and 3h). Figure 3 near here At Meenar, total N and K uptakes in shoots at anthesis increased significantly in all four seasons (Fig. 4). In 2021, N uptake in canola shoot increased by up to 446%, while K uptake was higher by more than 6-fold compared to the untreated control (Fig. 4a and 4e). This was equivalent of an increase in N uptake of 292.5 kg ha⁻¹ and in K uptake of 290.6 kg ha⁻¹ relative to the untreated control (LSD for N uptake = 48.2 kg ha⁻¹, LSD for K uptake = 48.2 kg ha⁻¹, P < 0.05). In 2022, N and K uptakes in barley increased by 328% and 551%, respectively. This equates to a maximum improvement of 187.4 and 194.4 kg ha⁻¹ N and K uptakes, respectively, in T8 compared to T1 (LSD = 63.1 kg ha⁻¹, P < 0.05) (Fig. 4b and 4f). Canola and wheat N uptakes in the shoot were 154.2 kg ha⁻¹ and 176.3 kg ha⁻¹ higher in 2023 and 2024, respectively (LSD = 72.4 kg ha⁻¹ and 41.3 kg ha⁻¹) (Fig. 4c and 4d). Similarly, canola and wheat K uptakes increased by 102.0 kg ha⁻¹ and 254.9 kg ha⁻¹ in 2023 and 2024, respectively (LSD = 36.3 kg ha⁻¹ and 52.1 kg ha⁻¹) (Fig. 4c and 4d). Figure 4 near here Root architecture of wheat and canola A clear visual improvement in root development was observed for both wheat at Bolgart and canola at Meenar in all soil re-engineering treatments (T5–T8) relative to the untreated control (T1) (Fig. 5). Root distribution on the Rhizotron tube surfaces was not uniform across samples, reflecting natural variation in plant spacing and root–tube contact. In the control treatment, maximum rooting depth was limited to approximately 50 cm in the Arenosol at Bolgart (Fig. 5a) and around 35 cm in the Kurosol at Meenar (Fig. 5b). In contrast, plants in all re-engineering treatments had roots that extended to at least the depth of soil re-engineering (≈ 80 cm). Among the re-engineering treatments, T8 consistently produced the most extensive and well-developed root systems for both crops, while T6 (re-engineered with added lime and clay) and T7 (re-engineered with added lime, clay and compost) produced a greater root density than T5 (re-engineered with added lime), particularly in canola. Figure 5 near here Longevity of the improvement in soil properties Previously soil re-engineering was shown to improve soil strength, soil water holding capacity (i.e., volumetric water content, pH Ca , SOC and CEC almost immediately after the experiments were established in 2021 (Azam 2025 ). The improvements in these key soil physicochemical properties persisted for at least four cropping seasons following treatment application (Fig. 6). Figure 6 near here At Bolgart (Arenosol), all soil re-engineering treatments (T5–T8) had a significantly lower soil strength than the untreated control (T1) (Fig. 6a). Among the re-engineering treatments, T8 had lower soil strength than T6 and T7 at 30–60 cm depth, although no significant difference was observed between T5 and T8. In addition, all soil re-engineering treatments had a higher volumetric water content at 0–20 cm depth compared with the control, but no significant differences were detected at greater depths (Fig. 6b). All re-engineered soils had significantly higher pH Ca at 10–80 cm depth than the control and other surface treatments (Fig. 6c). The re-engineering treatment incorporating compost (T8) had significantly greater SOC at 20–90 cm depth compared with all other treatments (Fig. 6d). Similarly, all re-engineering treatments showed higher CEC at 20–90 cm depth than the control and other surface treatments, with T8 having significantly greater CEC than the other re-engineering treatments (T5–T7) (Fig. 6e). At Meenar (Kurosol), greater variation in soil strength was observed among treatments than at Bolgart (Fig. 6f). All soil re-engineering treatments (T5–T8) had significantly lower soil strength than the untreated control, with T5 and T8 showing the lowest values, particularly at 10–80 cm depth. Volumetric water content was lower in T5 than in T1 and T7 at 40–70 cm depth, but no other significant differences were observed among the other treatments (Fig. 6g). All re-engineered treatments had significantly higher pH Ca at 10–70 cm depth compared with the control and surface treatments (Fig. 6h). Similarly, all soil re-engineering treatments had higher SOC at 10–30 cm depth relative to the control and surface treatments, with T8 also having having higher SOC at 30–60 cm depth than all other treatments (Fig. 6i). CEC was also significantly higher under all re-engineering treatments at 20–70 cm depth compared with the control and surface treatments, and among these, T8 had the highest CEC between 30 and 70 cm depth (Fig. 6j). Relationships between N and K uptakes and yield In most cases, positive significant relationships were observed between total shoot N and K uptakes and grain yield across both sites (Fig. 7). In general, at Bolgart (Arenosol), yield increased proportionally with total shoot N and K uptake across all crops, with coefficients of determination (r²) ranging from 0.87 to 0.95 for N uptake and K uptake (Fig. 7a–d). For this site, the yield response to N uptake was linear in all four seasons (Fig. 7a–d), while the yield response to K uptake was linear only in the first two seasons (Fig. 7a and 7b). For the last two seasons the yield response to total shoot uptake of K was logarithmic (Fig. 7c and 7d). Figure 7 near here At Meenar (Kurosol), positive significant relationships were observed between total shoot K uptake and grain yield across all seasons (Fig. 7e–h), however, the relationships between total shoot N uptake and grain yield were weaker in 2023 (Fig. 7g) and not significant in 2024 (Fig. 7h). The r² values ranged from 0.43 to 0.90 for N uptake and from 0.72 to 0.88 for K uptake. Determinants of yield improvement Regression tree analyses identified the key soil variables determining yield responses to re-engineering treatments (Fig. 8). At Bolgart, cation exchange capacity (CEC), soil strength (SS), soil organic carbon (SOC) and clay content were the dominant predictors of yield variation (Fig. 8a). The first split occurred at the CEC threshold of 0.99 cmol kg − 1 (average for the soil profile) and benchmarked the grain yield at 1.13 t ha⁻¹. The second split also occurred in favour of CEC at a threshold of 2.07 cmol kg − 1 (average for the soil profile), which generated a maximum yield of 3.38 t ha⁻¹. Treatments with higher CEC and a SS threshold of < 1.64 MPa had the highest grain yield of 3.75 t ha⁻¹. SOC appeared at three splits with a threshold range of 0.11–0.15% (average for the soil profile). Clay content appeared at the last split with a threshold value of 3.89% (average for the soil profile), separating the low-yield ( 2.79 t ha⁻¹) groups. Notably, soil pH Ca did not appear in any of the splits at this site. The model accounted for 64.5% of total variance, with a residual mean square error of 0.51 t ha⁻¹. Figure 8 near here At Meenar, CEC, SS, pH Ca , and SOC were the main determinants of yield, while clay content did not affect the yield outcome (Fig. 8b). Soil CEC appeared at three splits with threshold values of 0.83, 1.97 and 2.33 cmol kg − 1 (average for the soil profile). Where CEC had a lower threshold value, SOC and SS had the greatest influence on improving yield from 1.70 t ha − 1 to 4.19 t ha − 1 . Soil pH Ca also appeared at three splits with threshold values in the range of 4.91–5.35 (average for the soil profile), whereas SS and SOC appeared at two splits each. The regression tree explained 80.4% of yield variance, with a residual mean square error of 0.67 t ha⁻¹. Discussion Benchmarking yield and WUE gains through soil profile re-engineering This four-year field evaluation across two contrasting sites has demonstrated that soil profile re-engineering can substantially close the yield gap in water-limited environments by simultaneously alleviating multiple constraints, including subsoil acidity, compaction, and low fertility. Yield improvements of up to 432% for canola, 300% for triticale, 277% for barley and 147% for wheat, coupled with WUE gains exceeding 9 kg mm⁻¹, indicate that integrated deep amelioration can approach theoretical water-limited yield potential benchmarks for Western Australian and southern Australian cropping systems (Sadras and Angus 2006 ; Harries et al. 2022 ; Barrett-Lennard et al. 2024 ; Oliver et al. 2009 ). These results confirm earlier short-term (first year following amelioration) findings that 45–80 cm deep incorporation of lime and other amendments enhances rooting depth and resource capture (Azam and Gazey 2019; Wickramarachchi and Azam 2024 ), but extend the evidence by demonstrating persistence of the benefits over multiple and contrasting growing seasons. Unlike surface liming, ripping or claying, which act slowly or provide inconsistent benefits or aggravate evaporative water loss (Li et al. 2019 ; Damon et al. 2022 ; Hall et al. 2010 ; Wickramarachchi et al. 2025a ), soil re-engineering has delivered immediate (Azam 2025 ) and durable improvements in soil physical and chemical properties, evidenced by sustained soil strength, pH Ca , CEC, and SOC gains over four seasons. This persistence suggests that soil profile re-engineering can serve as a benchmark for designing scalable amelioration strategies (Davies et al. 2024 ; Musei et al. 2024 ). Importantly, the magnitude of the yield responses observed here and in other deep soil amelioration research (Azam et al. 2025 ) can exceed the theoretical water-limited yield boundary for WA and southern Australia (Barrett-Lennard et al. 2024 ), highlighting the potential of integrated interventions to overcome multiple interacting soil constraints in semi-arid and rainfed cropping systems. Nutrient uptake and soil functional improvements as drivers of productivity The strong positive relationships between N and K uptake and grain yield (r² up to 0.95, P ≤ 0.001 ) underscore the role of improved nutrient acquisition in driving productivity gains. For sandy soils with the typical distribution of rainfall at our sites, nitrate leaching is a significant nutrient loss process (Anderson et al. 1998 ). Hence, enhanced rooting depth and reduced nitrate leaching losses likely contributed to higher nitrogen recovery, consistent with previous reports on deep ameliorated soils (Angus and Grace 2017 ; Lynch 2019 ; Wickramarachchi et al. 2025b ). Treatments incorporating compost (T8) delivered the greatest SOC and CEC improvements, which are critical for nutrient retention in coarse-textured sandy soils (Bell and de Oliveira 2022 ; Hoyle et al. 2013 ). Regression tree analysis further highlighted CEC, SOC and soil strength as dominant predictors of yield at both soil types, while yield improvement was also related to claying at Bolgart (moderately acidic Arenosol) and soil pH Ca at Meenar (very acidic Kurosol). These reinforce the importance of physical–chemical–biological synergy in soil management (Bell and de Oliveira 2022 ; Azam et al. 2023 ). Our findings are consistent with the global evidence that integrated amendments—lime, clay, and organic matter—enhance soil buffering capacity and nutrient cycling, thereby sustaining crop performance under variable rainfall (Lauricella et al. 2020 ). The observed logarithmic yield response to K uptake in later seasons suggests diminishing returns once structural constraints are alleviated, pointing to the need for balanced nutrient strategies in ameliorated soils. Recent work by Wickramarachchi and Azam ( 2024 ) on fertiliser strategies for re-engineered soils supports this, showing that surface-applied N at higher rates can maintain yield gains without deep fertiliser incorporation. Deeper root systems and soil water storage: a critical mechanism One of the most striking outcomes of soil profile re-engineering is the development of deeper and more continuous root systems, which significantly enhance access to subsoil water and nutrients. Our results align with rhizotron-based studies showing that removal of subsoil strength and acidity promotes root elongation and proliferation, increasing planar root length density and water uptake (Azam et al. 2024b ; Gregory 2006 ; Uddin et al. 2018 ). This holistic improvement effectively increases the soil plant available water holding capacity. Hence buffering crops against terminal drought—a key limitation in Mediterranean-type climates (Sadras and Angus 2006 ; Harries et al. 2022 ; Wickramarachchi et al. 2025b ). The importance of rooting depth is further emphasised by global research on subsoil constraints. Bell and de Oliveira ( 2022 ) note that crops may acquire up to 75% of N and 70% of K from subsoil layers if root growth is unrestricted. Conversely, compaction and acidity severely limit this potential, confining roots to shallow horizons and exacerbating yield variability (Unkovich et al. 2023 ; Cui et al. 2022 ). Our findings demonstrate that re-engineering not only removes these barriers but also creates conditions for sustained root development across seasons, a prerequisite for resilience under climate variability. Longevity and practical implications for semi-arid cropping systems A critical outcome of this study is the durability of soil improvements. Four years post-treatment, re-engineered profiles maintained lower soil strength and higher pH Ca , SOC, and CEC compared to controls, even across contrasting soil types (Arenosol and Kurosol). This contrasts with the rapid decline in benefits often observed after deep ripping to a depth of up to 50 cm alone (Busscher et al. 2002 ; Unkovich et al. 2023 ). While the economic and logistical constraints of full-profile re-engineering currently preclude farm-scale adoption, our results provide a benchmark for next-generation technologies such as targeted deep placement of amendments or hybrid mechanical–biological approaches (Schmittmann et al. 2021 ; Davies et al. 2024 ). Future research should explore cost-effective strategies that mimic the functional outcomes of re-engineering—particularly improved rooting depth and nutrient retention—while minimising repeated soil disturbance and carbon loss. Integrating soil microbiome management with physiochemical amelioration may offer synergistic gains in resilience and sustainability (Wu et al. 2024 ). In addition, long-term monitoring of carbon dynamics and economic analyses will be essential to evaluate the feasibility of scaled-down interventions that deliver similar benefits. Conclusions This four-year field study provides compelling evidence that soil profile re-engineering can substantially improve crop productivity, N and K use efficiencies, and WUE in water-limited environments by simultaneously addressing multiple interacting soil constraints. Across two contrasting soil types—an Arenosol and a Kurosol— spanning the four-year time scale of this work, re-engineering treatments consistently delivered large and persistent gains in grain yield, WUE, and N and K uptake compared with conventional surface amelioration strategies. These improvements were underpinned by enhanced soil physicochemical properties (pH Ca , CEC, SOC, and reduced soil strength) and the development of deeper, more continuous root systems that increased access to subsoil water, N and K. The durability of these benefits over four cropping seasons highlights the potential of integrated deep amelioration as a benchmark for next-generation soil management technologies. While full-profile re-engineering is currenty not economically feasible at farm scale, the insights gained here can inform the design of scalable interventions—such as targeted deep placement of amendments or hybrid mechanical–biological approaches—that mimic the functional outcomes of re-engineering. Future research should focus on continuous assessment of SPR benefits, optimising these strategies for cost-effectiveness, assessing long-term carbon dynamics, and integrating biological enhancements to further improve resilience and sustainability in semi-arid cropping systems. Declarations Acknowledgements The authors gratefully acknowledge the Department of Primary Industries and Regional Development (DPIRD) and the Grains Research and Development Corporation (GRDC) for funding support through projects DAW1902_003RTX and SWAN DAW2407-001SPX. We thank the Syme and Fulwood families for providing field sites and for their ongoing cooperation throughout the experiments. We also acknowledge the valuable technical assistance of DPIRD staff, including Jenni Clausen, Dr Shahab Pathan, Alistair Hall, Shelley Hall, Joanne Walker, Dr Bidhyut Banik, Steve Rossi, and Trey Beeson. Guidance on experimental design and statistical analysis from Dr Andrew van Burgel is gratefully acknowledged. We further thank Chris Gazey, Dr Stephen Davies, and Tim Boyes (AgVivo) for their practical advice during the initial phase of the project. Finally, we appreciate the constructive internal review provided by Dr Ed Barrett-Lennard, Dr Geoff Anderson, and Sue Bestow before submission. Conflict of Interest The authors declare no conflicts of interest. Data availability The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. Author’s contribution Gaus Azam: Fund sourcing, trial design, execution, data analysis and manuscript preparation. Kanchana Wickramarachchi: data collection, data analysis and manuscript preparation. Hasinur Rahman: data collection, data analysis and manuscript preparation. Md Shahinur Rahman: data collection and manuscript preparation. Chad Reynolds: trial establishment and manuscript preparation. References Anderson GC, Fillery IRP, Dolling PJ, Asseng S (1998) Nitrogen and water flows under pasture-wheat and lupin-wheat rotations in deep sands in Western Australia. 1. Nitrogen fixation in legumes, net N mineralisation,and utilisation of soil-derived nitrogen. Aust J Agric Res 49(3):329–344. https://doi.org/10.1071/A97141 Anderson GC, Pathan S, Easton J, Hall DJM, Sharma R (2020) Short- and Long-Term Effects of Lime and Gypsum Applications on Acid Soils in a Water-Limited Environment: 1. Grain Yield Response and Nutrient Concentration. Agronomy 10(8):1213 Anderson GC, Pathan S, Hall DJM, Sharma R, Easton J (2021) Short- and Long-Term Effects of Lime and Gypsum Applications on Acid Soils in a Water-Limited Environment: 3. Soil Solut Chem Agron 11(5):826 Anderson GC, Peverill KI, Brennan RF (2013) Soil sulfur—crop response calibration relationships and criteria for field crops grown in Australia. Crop Pasture Sci 64(5):523–530 Angus JF, Grace PR (2017) Nitrogen balance in Australia and nitrogen use efficiency on Australian farms. Soil Res 55(6):435–450. https://doi.org/10.1071/SR16325 Azam G (2025) A method to re-engineer soils for quick amelioration of physical and chemical constraints - examples from an Arenosol and a Kurosol in Western Australia. Soil Research (under review) Azam G, Gazey C Re-engineering soil pH profiles to boost water use efficiency by wheat Paper presented at the Agronomy Australia Conference, Wagga W (2019) 25–29 August 2019 Azam G, Gazey C (2021) Slow movement of alkali from surface-applied lime warrants the introduction of strategic tillage for rapid amelioration of subsurface acidity in south-western Australia. Soil Res 59(1):97–106. https://doi.org/10.1071/SR19329 Azam G, Gazey C, Davies S, Scanlan C (2022) Mind the depth of soil amelioration to surpass the yield gap in western Australia. Paper presented at the Australian Agronomy Conference, Toowoomba, Queensland, Australia, 18–22 September 2022 Azam G, Rahman MS, Scanlan C, Rahman MH, Gazey R, Barrett-Lennard EG, Wickramarachchi K, Nixon B, Gazey C (2025) Deep Amelioration of Compaction and Acidity Doubled the Water Use Efficiency of Cereal Crops on a Sandy Soil in a Long-term Experiment in a Water-Limited Environment. Geoderma (under review) Azam G, Rahman MS, Scanlan C, Rahman MH, Gazey R, Gazey C (2024a) Soil Profile Re-engineering Doubled the Yield and Water Use Efficiency of Crops over Six Years on Acidic and Compacted Sand in a Water-limited Environment. https://doi.org/10.21203/rs.3.rs-4710141/v1 . Scientific Reports Azam G, Rahman MS, Wickramarachchi K (2023) Strategic Tillage for Sustaining the Productivity of Broadacre Cropping in the Arid and Semi-Arid Regions of Southern Australia. In: Dr. Rodrigo De S (ed) Strategic Tillage and Soil Management - New Perspectives. IntechOpen, Rijeka, p Ch. 3. 10.5772/intechopen.112875 Azam G, Wickramarachchi K, Scanlan C, Chen Y (2024b) Deep and continuous root development in ameliorated soil improves water and nutrient uptakes and wheat yield in water-limited conditions. Plant Soil 512:1405–1420. 10.1007/s11104-024-07153-0 Aziz M, Palta J, Siddique K, Sadras V (2017) Five decades of selection for yield reduced root length density and increased nitrogen uptake per unit root length in Australian wheat varieties. Plant Soil 413. 10.1007/s11104-016-3059-y Barrett-Lennard EG, George N, D’Antuono M, Holmes KW, Ward PR (2024) Rain and potential evapotranspiration are the main drivers of yield for wheat and barley in southern Australia: insights from 12 years of National Variety Trials. Crop Pasture Sci 75(6):–. https://doi.org/10.1071/CP23320 Barton L, Gleeson DB, Maccarone LD, Zúñiga LP, Murphy DV (2013) Is liming soil a strategy for mitigating nitrous oxide emissions from semi-arid soils? Soil Biol Biochem 62:28–35. https://doi.org/10.1016/j.soilbio.2013.02.014 Bell R, Reuter D, Scott B, Sparrow L, Strong W, Chen tlW (2013) Soil phosphorus–crop response calibration relationships and criteria for winter cereal crops grown in Australia. Crop Pasture Sci 64(5):480–498. 10.1071/cp13016 Bell RW, de Oliveira TS (2022) Subsoil Constraints for Crop Production: Recent Advances, New Technologies, and Priorities for Further Research. Subsoil Constraints for Crop Production:397–422 Bengough AG, McKenzie BM, Hallett PD, Valentine TA (2011) Root elongation, water stress, and mechanical impedance: a review of limiting stresses and beneficial root tip traits. J Exp Bot 62(1):59–68. 10.1093/jxb/erq350 Brennan RF, Bell MJ (2013) Soil potassium—crop response calibration relationships and criteria for field crops grown in Australia. Crop Pasture Sci 64(5):514–522 Bruun EW, Petersen CT, Hansen E, Holm JK, Hauggaard-Nielsen H (2014) Biochar amendment to coarse sandy subsoil improves root growth and increases water retention. Soil Use Manag 30(1):109–118. 10.1111/sum.12102 Busscher WJ, Bauer PJ, Frederick JR (2002) Recompaction of a coastal loamy sand after deep tillage as a function of subsequent cumulative rainfall. Soil Tillage Res 68(1):49–57. https://doi.org/10.1016/S0167-1987(02)00083-1 Butler DG, Cullis BR, Gilmour A, Gogel R B, J (2018) ASReml-R 4 reference manual: mixed models for S language environments. Queensland Department of Primary Industries and Fisheries Cui Z, Yan B, Gao Y, Wu B, Wang Y, Xie Y, Xu P, Wang H, Wen M, Wang Y, Ma X (2022) Crop yield and water use efficiency in response to long-term diversified crop rotations. Front Plant Sci Volume 13–2022. 10.3389/fpls.2022.1024898 Damon PM, Azam G, Gazey C, Scanlan CA, Rengel Z (2022) Response of wheat to the geometry and proximity of lime slotting in an acidic soil profile. Soil Tillage Res 217:105269. https://doi.org/10.1016/j.still.2021.105269 Davies S, Betti G, Edwards T, McDonald G, Hall D, Anderson G, Scanlan C, Reynolds C, Walker J, Poulish G, Ward P (2019) Ten years of managing water repellent soils research in Western Australia–a review of current progress and future opportunities. In: Proceedings of the 2019 GRDC Research Update, Perth, WA, pp 25–26 Davies S, Parker W, Azam G, Hall D, Edwards T, Mwenda G, Reynolds C, McDonald G, Isbister B, Butler A, Scanlan C, Blake A, Newman P, Sands R, Ryan K, Curtis B, Bunny H, Gazey C (2024) Soil amelioration in Western Australian cropping systems: a review of thebenefits, adoption, and value. Paper presented at the Australian Agronomy Conference, Albany, Western Australia, 21–24 October 2024 Gahoonia T, Ali R, Malhotra R, Jahoor A, Rahman M (2007) Variation in Root Morphological and Physiological Traits and Nutrient Uptake of Chickpea Genotypes. J Plant Nutr 30:829–841. 10.1080/15226510701373213 Gazey C, Azam G, Clausen J, Rengel Z (2019) Soil Quality: 4 Soil Acidity. Perth, WA Gregory P (2006) Roots, rhizosphere and soil: The route to a better understanding of soil science? Eur J Soil Sci 57:2–12. 10.1111/j.1365-2389.2005.00778.x Hall DJM, Davies SL, Bell RW, Edwards TJ (2020) Soil Management Systems to Overcome Multiple Constraints for Dryland Crops on Deep Sands in a Water Limited Environment on the South Coast of Western Australia. Agronomy 10(12):1881 Hall DJM, Edwards TJ (2025) Trenching and compost sustain grain yield increases over nine years on deep sands but at a cost. Soil Res 63(3):–. https://doi.org/10.1071/SR24221 Hall DJM, Jones HR, Crabtree WL, Daniels TL (2010) Claying and deep ripping can increase crop yields and profits on water repellent sands with marginal fertility in southern Western Australia. Soil Res 48(2):178–187. https://doi.org/10.1071/SR09078 Harries M, Flower KC, Renton M, Anderson GC (2022) Water use efficiency in Western Australian cropping systems. Crop Pasture Sci 73(10):1097–1117. https://doi.org/10.1071/CP21745 Horrocks A, Curtin D, Tregurtha C, Meenken E (2016) Municipal Compost as a Nutrient Source for Organic Crop Production in New Zealand. Agronomy 6(2):35 Hoyle FC, D'Antuono M, Overheu T, Murphy DV (2013) Capacity for increasing soil organic carbon stocks in dryland agricultural systems. Soil Res 51(8):657–667. https://doi.org/10.1071/SR12373 Isbell RF (2021) The Australian Soil Classification, 3 edn. CSIRO Publishing, Melbourne Isbister B, Rahman H, Azam G, Walker J, Kupsch M, Wilkins R (2024) To rip on or off the old rip line: a paddock-scale study on deep ripping and topsoil inclusion in a dry season. Paper presented at the GRDC Research Updates, Perth Islam N, Salim R (2012) Can R&D Investment Offset the Negative Impact. of Climate Change on Agricultural Productivity? Kirkegaard JA, Peoples MB, Angus JF, Unkovich MJ (2011) Diversity and Evolution of Rainfed Farming Systems in Southern Australia. In: Tow P, Cooper I, Partridge I, Birch C (eds) Rainfed Farming Systems. Springer Netherlands, Dordrecht, pp 715–754. doi: 10.1007/978-1-4020-9132-2_26 Lauricella D, Butterly CR, Clark GJ, Sale PWG, Li G, Tang C (2020) Effectiveness of innovative organic amendments in acid soils depends on their ability to supply P and alleviate Al and Mn toxicity in plants. J Soils Sediments 20(11):3951–3962. 10.1007/s11368-020-02721-0 Lawes R, Chen C, Whish J, Meier E, Ouzman J, Gobbett D, Vadakattu G, Ota N, van Rees H (2021) Applying more nitrogen is not always sufficient to address dryland wheat yield gaps in Australia. Field Crops Res 262:108033. https://doi.org/10.1016/j.fcr.2020.108033 Li GD, Conyers MK, Helyar KR, Lisle CJ, Poile GJ, Cullis BR (2019) Long-term surface application of lime ameliorates subsurface soil acidity in the mixed farming zone of south-eastern Australia. Geoderma 338:236–246. 10.1016/j.geoderma.2018.12.003 Lynch JP (2019) Root phenotypes for improved nutrient capture: an underexploited opportunity for global agriculture. New Phytol 223(2):548–564. 10.1111/nph.15738 McQuaker NR, Brown DF, Kluckner PD (1979) Digestion of environmental materials for analysis by inductively coupled plasma-atomic emission spectrometry. Anal Chem 51:1082–1084 Musei SK, Kuyah S, Nyawira S, Ng’ang’a SK, Karugu WN, Smucker A, Nkurunziza L (2024) Sandy soil reclamation technologies to improve crop productivity and soil health: a review. Front Soil Sci Volume 4–2024. 10.3389/fsoil.2024.1345895 Oliver YM, Robertson MJ, Stone PJ, Whitbread A (2009) Improving estimates of water-limited yield of wheat by accounting for soil type and within-season rainfall. Crop Pasture Sci 60(12):1137–1146. https://doi.org/10.1071/CP09122 Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci 11(5):1633–1644. 10.5194/hess-11-1633-2007 R-Core-Team (2025) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria Rayment GE, Lyons DJ (2011) Soil chemical methods: Australasia. CSIRO Publishing, Collingwood, Australia Rengel Z (2003) Handbook of Soil Acidity. Marcel Dekker, New York, USA Riaz M, Marschner P (2020) Sandy Soil Amended with Clay Soil: Effect of Clay Soil Properties on Soil Respiration, Microbial Biomass, and Water Extractable Organic C. J Soil Sci Plant Nutr 20(4):2465–2470. 10.1007/s42729-020-00312-z Roper MM, Davies SL, Blackwell PS, Hall DJM, Bakker DM, Jongepier R, Ward PR (2015) Management options for water-repellent soils in Australian dryland agriculture. Soil Res 53(7):786–806. https://doi.org/10.1071/SR14330 Sadras VO, Angus JF (2006) Benchmarking water-use efficiency of rainfed wheat in dry environments. Aust J Agric Res 57(8):847–856. https://doi.org/10.1071/AR05359 Scanlan C, Malik R, Easton J, Gherardi M, Rengel Z, Bell R, Boitt G, Ma Q (2022) Optimising fertiliser application – what level of precision can we achieve? Paper presented at the Grain Research and Development Corporation - Updates, Perth Schmittmann O, Christ A, Schulze Lammers P (2021) Subsoil Melioration with Organic Material—Principle, Technology and Yield Effects. Agronomy 11(10):1970 Schneider F, Don A, Hennings I, Schmittmann O, Seidel SJ (2017) The effect of deep tillage on crop yield – What do we really know? Soil Tillage Res 174:193–204. https://doi.org/10.1016/j.still.2017.07.005 Smith LJ, Scarisbrick DH (1990) Reproductive Development in Oilseed Rape (Brassica napus cv. Bienvenu). Ann Botany 65(2):205–212 Uddin S, Löw M, Parvin S, Fitzgerald G, Bahrami H, Tausz-Posch S, Armstrong R, O’Leary G, Tausz M (2018) Water use and growth responses of dryland wheat grown under elevated [CO2] are associated with root length in deeper, but not upper soil layer. Field Crops Res 224:170–181. https://doi.org/10.1016/j.fcr.2018.05.014 Unkovich M, McKenzie D, Parker W (2023) New insights into high soil strength and crop plants; implications for grain crop production in the Australian environment. Plant Soil 486(1):183–208. 10.1007/s11104-022-05862-y van Gool D (2016) Identifying soil constraints that limit wheat yield in South-West Western Australia. Perth Wasson AP, Richards RA, Chatrath R, Misra SC, Prasad SVS, Rebetzke GJ, Kirkegaard JA, Christopher J, Watt M (2012) Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops. J Exp Bot 63(9):3485–3498. 10.1093/jxb/ers111 Weaver DM, Neville S, Deeley DM (2005) Addressing off-site nutrient pollution through conventional management actions: a modelling case study. Australasian J Water Resour 8(2):165–177. 10.1080/13241583.2005.11465253 Wickramarachchi K, Azam G (2024) Fertiliser strategies to boost crop yield in re-engineered soil profiles. Paper presented at the Australian Agronomy Conference, Albanry, Western Australia, October 2024 Wickramarachchi K, Azam G (2025) Improving Barley (Hordeum vulgare L.) Yield through Deeper Root Architecture Impacted by Nitrogen Management in a Reengineered Kurosol. Soil Research (under review) Wickramarachchi K, Betti G, Azam G (2025a) Effect of Clay Amendment and Strategic Deep Tillage on Soil Water Dynamics and Plant Growth Under Controlled Environments. Plants (Basel) 14(5). 10.3390/plants14050799 Wickramarachchi K, Chen Y, Azam G (2025b) Reengineering a compacted acidic coarse sand enhanced the root architecture and yield of triticale (x Triticosecale) – A. Soil Columns Study Plant and Soil (accepted) Wu M, Chen L, Chen S, Chen Y, Ma J, Zhang Y, Pang D, Li X (2024) Soil microbial carbon and nitrogen limitation constraints soil organic carbon stability in arid and semi-arid grasslands. J Environ Manage 373. 10.1016/j.jenvman.2024.123675 Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14(6):415–421. https://doi.org/10.1111/j.1365-3180.1974.tb01084.x Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8297071","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":556347844,"identity":"a4b1d8e9-fe49-4132-9662-2a1390b63fd7","order_by":0,"name":"Gaus Azam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYFAD9gYDhgQGZlK08BwgWYtEggGQJEKLvPsZ4w8MNXXyujMfb3vwcI81g8HxA8wvPrYxyBscwK7F8EyOmQTDMTbDbbfTyg0SnqUzGJxJYLOc2cZguAGXloYcMwYGNh7GbbeBehMOHGYwO5DAZsxzhoERp5b+N0CH/ZOw33bzDFTL+QdgLfa4tMhL5BhIMLYZJG67wQPVciOB+TFPBUMiLi0GEs/KJBL7EpK3nQH55UA6j/2Nh22MMyokkmfisqU/efOHD9/qbLcdP7zt4Y8D1nKS/cmHP3wwsLHtw2ULSDwBwmYDETwMDIxtEsBowq4eZEsDgs0GYzB/wKl+FIyCUTAKRiIAAIbnXurUfTdEAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Primary Industries and Regional Development, Western Australia","correspondingAuthor":true,"prefix":"","firstName":"Gaus","middleName":"","lastName":"Azam","suffix":""},{"id":556349168,"identity":"115d8e3c-81ee-4640-b247-e944d79dd888","order_by":1,"name":"Kanch Wickramarachchi","email":"","orcid":"","institution":"Department of Primary Industries and Regional Development, Western Australia","correspondingAuthor":false,"prefix":"","firstName":"Kanch","middleName":"","lastName":"Wickramarachchi","suffix":""},{"id":556349169,"identity":"a2c89de1-03b4-41c0-9a0b-22945289f833","order_by":2,"name":"Hasinur Rahman","email":"","orcid":"","institution":"Department of Primary Industries and Regional Development, Western Australia","correspondingAuthor":false,"prefix":"","firstName":"Hasinur","middleName":"","lastName":"Rahman","suffix":""},{"id":556349170,"identity":"d552a671-32fb-48a7-886b-c18d263922bf","order_by":3,"name":"Md Shahinur Rahman","email":"","orcid":"","institution":"Department of Primary Industries and Regional Development, Western Australia","correspondingAuthor":false,"prefix":"","firstName":"Md","middleName":"Shahinur","lastName":"Rahman","suffix":""},{"id":556349171,"identity":"e7e66e4b-d6cc-4129-b49d-979660283a0f","order_by":4,"name":"Chad Reynolds","email":"","orcid":"","institution":"Department of Primary Industries and Regional Development, Western Australia","correspondingAuthor":false,"prefix":"","firstName":"Chad","middleName":"","lastName":"Reynolds","suffix":""}],"badges":[],"createdAt":"2025-12-06 23:25:43","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8297071/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8297071/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97778182,"identity":"04e76b8b-fc04-43c2-adde-121a4cbc691b","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":166800,"visible":true,"origin":"","legend":"","description":"","filename":"Maintextreengineeringsoilsfull.docx","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/f16443978d3973416748dc7d.docx"},{"id":97778173,"identity":"2fc13fa7-ba9c-446c-8d77-f09bc9569161","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs8297071.json","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/a3330c993c74b7d06713d0ca.json"},{"id":97896744,"identity":"bdd57104-97ad-4e80-81de-b46216ca61ad","added_by":"auto","created_at":"2025-12-10 15:36:59","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171861,"visible":true,"origin":"","legend":"","description":"","filename":"rs82970710enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/3369831218e1f227c73c9def.xml"},{"id":97896734,"identity":"bd592ad0-a171-45a2-8c70-b18991eb961c","added_by":"auto","created_at":"2025-12-10 15:36:58","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":169365,"visible":true,"origin":"","legend":"","description":"","filename":"rs82970710structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/b8de66919b38c4d10118d31d.xml"},{"id":97778181,"identity":"9ddef4e5-db58-4bb3-a9b9-ef277ee6a570","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":175560,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/c4666ebf2bc84c1b972ed05e.html"},{"id":97778174,"identity":"353461e1-a6ae-4228-9f77-6c704f8af562","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":183073,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of soil re-engineering on (a-d) grain yield and (e-f) water-use efficiency (WUE) of (a and e) wheat, (b and f) canola, (c and g) triticale, and (d and h) barley grown on an Arenosol at Bolgart, Western Australia. Eight treatments were: T1 = untreated control; T2 = clay (110 t ha⁻¹) incorporated to 0–10 cm; T3 = T2 plus additional N, P and K at 0–10 cm; T4 = T2 plus compost (42 t ha⁻¹) at 0–10 cm; T5 = lime (6 t ha⁻¹) incorporated to 0–80 cm; T6 = T5 plus clay (1,337 t ha⁻¹) at 0–80 cm; T7 = T6 plus additional N, P and K at 0–80 cm; and T8 = T6 plus compost (160 t ha⁻¹) at 0–80 cm. Error bars represent the standard error of the mean. Different letters indicate significant differences according to Fisher’s protected LSD test (P \u0026lt; 0.05). LSD values for grain yield and WUE were 0.24 and 2.11, 0.74 and 2.58, 0.29 and 1.35, and 0.46 and 1.92 for wheat, canola, triticale, and barley, respectively. GSR = growing season (Apr–Oct) rainfall.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/0a63fdfd96c1ad8dcaab7710.png"},{"id":97778176,"identity":"acdc09c9-6d80-4feb-b4ca-2410ad64d160","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":183992,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of soil re-engineering on (a-d) grain yield and (e-h) water-use efficiency (WUE) of (a and e) canola, (b and f) barley, (c and g) canola, and (d and h) wheat grown on a Kurosol at Meenar, Western Australia. Eight treatments were: T1 = untreated control; T2 = clay (110 t ha⁻¹) incorporated to 0–10 cm; T3 = T2 plus additional N, P and K at 0–10 cm; T4 = T2 plus compost (31 t ha⁻¹) at 0–10 cm; T5 = lime (6.8 t ha⁻¹) incorporated to 0–80 cm; T6 = T5 plus clay (329 t ha⁻¹) at 0–40 cm; T7 = T6 plus additional N, P and K at 0–80 cm; and T8 = T6 plus compost (125 t ha⁻¹) at 0–80 cm. Error bars represent the standard error of the mean. Different letters indicate significant differences according to Fisher’s protected LSD test (P \u0026lt; 0.05). LSD values for grain yield and WUE were 0.23 and 0.71, 0.66 and 2.45, 0.53 and 4.85, and 0.47 and 2.86 for canola, barley, canola and wheat, respectively. GSR = growing season (Apr–Oct) rainfall.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/bfdaf011698563033516a765.png"},{"id":97778172,"identity":"e20e0cc5-5d44-4818-bb08-af0af3d1f0a1","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":151231,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of soil re-engineering on (a-d) shoot N and (e-f) shoot K uptakes of (a and e) wheat (2021), (b and f) canola (2022), (c and g) triticale (2023), and (d and h) barley (2024) grown on an Arenosol at Bolgart, Western Australia. Eight treatments were established: T1 = untreated control; T2 = clay (110 t ha⁻¹) incorporated to 0–10 cm; T3 = T2 plus additional N, P and K at 0–10 cm; T4 = T2 plus compost (42 t ha⁻¹) at 0–10 cm; T5 = lime (6 t ha⁻¹) incorporated to 0–80 cm; T6 = T5 plus clay (1,337 t ha⁻¹) at 0–80 cm; T7 = T6 plus additional N, P and K at 0–80 cm; and T8 = T6 plus compost (160 t ha⁻¹) at 0–80 cm. Error bars represent the standard error of the mean. Different letters indicate significant differences according to Fisher’s protected LSD test (P \u0026lt; 0.05). LSD values for shoot N and shoot K uptakes were 48.2 and 46.8, 63.1 and 34.6, 14.1 and 14.4, and 14.0 and 23.3 for wheat, canola, triticale, and barley, respectively.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/781c25e6df0523a2aadc301a.png"},{"id":97778178,"identity":"7856072e-846b-4109-b889-ecc1befe4c18","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":160029,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of soil re-engineering on (a-d) shoot N and (e-f) shoot K uptakes of (a and e) canola (2021), (b and f) barley (2022), (c and g) canola (2023), and (d and h) wheat (2024) grown on a Kurosol at Meenar, Western Australia. Eight treatments were established: T1 = untreated control; T2 = clay (110 t ha⁻¹) incorporated to 0–10 cm; T3 = T2 plus additional N, P and K at 0–10 cm; T4 = T2 plus compost (31 t ha⁻¹) at 0–10 cm; T5 = lime (6.8 t ha⁻¹) incorporated to 0–80 cm; T6 = T5 plus clay (329 t ha⁻¹) at 0–40 cm; T7 = T6 plus additional N, P and K at 0–80 cm; and T8 = T6 plus compost (125 t ha⁻¹) at 0–80 cm. Error bars represent the standard error of the mean. Different letters indicate significant differences according to Fisher’s protected LSD test (P \u0026lt; 0.05). LSD values for shoot N and shoot K uptakes were 45.3 and 28.9, 51.7 and 70.1, 72.4 and 36.3, and 41.3 and 52.1 for canola, barley, canola and wheat, respectively.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/16b5b6a10ef1f3679aeb2bd9.png"},{"id":97778179,"identity":"b75e19e4-fb0c-4b2d-95bb-e708d5c75bb0","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1560812,"visible":true,"origin":"","legend":"\u003cp\u003eRoot profile images of (a) wheat and (b) canola collected from treatments T1, T5, T6, T7 and T8 at growth stage Z65 for wheat and 10% flowering for canola during the 2021 growing season. Wheat was grown at Bolgart, and canola at Meenar, Western Australia.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/a80b86a88f13fdf45e43466b.png"},{"id":97778175,"identity":"f8c61e11-de92-4dcf-813a-f246ec8a3782","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":327459,"visible":true,"origin":"","legend":"\u003cp\u003eImprovement and lasting effect (measure in July 2024) of soil re-engineering treatments (80 cm depth) in soil constraints in an Arenosol at Bolgart, WA (a–e) and a Kurosol at Meenar, WA (f–j). Treatments were applied only once in May 2021. Treatments include: T1 = untreated control, T2 = loosening and lime incorporation, T3 = loosening, lime and clay incorporation, and T4 = loosening, lime, clay and organic matter incorporation. Soil pH measured in 0.01 M ClCl\u003csub\u003e2\u003c/sub\u003e extract, VWC = volumetric water content, SOC = soil organic carbon, and CEC = cation exchange capacity. Depth of soil measurements varies between sites due to the difference in the depth of the B Horizon of the soil profiles or the capacity of the equipment used (e.g. soil strength). Soil strength and VWC were measured only from selected five treatments. Horizontal error bars represent standard errors of the mean values.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/2f86c17cc529d1b416223113.png"},{"id":97778184,"identity":"1fa9a839-3374-4a58-98c8-fdec93943547","added_by":"auto","created_at":"2025-12-09 09:15:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":301670,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between total nitrogen and potassium uptakes with yield of various grain crops on a re-engineered Arenosol at Bolgart, WA (a–d) and a re-engineered Kurosol at Meenar, WA (e–h).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/9377b8b73be608e0d1806db3.png"},{"id":97895338,"identity":"af6458ee-8462-4a66-8706-18afb417d019","added_by":"auto","created_at":"2025-12-10 15:34:01","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":165816,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/c7bc7e1f0b8b68381edd286f.png"},{"id":97902590,"identity":"daf5bb3c-6edc-41b8-ba84-9196a5ece410","added_by":"auto","created_at":"2025-12-10 15:53:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3469104,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8297071/v1/1dfde3fc-640f-4ac4-834b-e5c24faa2933.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eBenchmarking crop performance following soil profile re-engineering: four-year field studies in an Arenosol and a Kurosol of Western Australia\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSoil physical, chemical and biological constraints frequently limit crop performance and the sustainability of agricultural productivity. In the grainbelt of Western Australia (WA), a complex suite of limitations reduces grain yield and water-use efficiency (WUE) despite decades of soil management and agronomic innovations (Gazey et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Roper et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; van Gool \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Davies et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lawes et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Harries et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kirkegaard et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Schmittmann et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Schneider et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Aziz et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Frequently found soil constraints include subsoil acidity, compaction, low fertility, and low water-holding capacity, which often co-occur (van Gool \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and interact to restrict roots to shallower depths in the soil profile (Azam et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). As a result, crops fail to make use of resources from deeper in the soil profile, and remain vulnerable to terminal drought, and typically fall short of water-limited yield potential (Sadras and Angus \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Harries et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Barrett-Lennard et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lawes et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSubsoil acidity is widespread across Australian cropping soils, driven by ammonium-based fertiliser use, removal of alkaline products, increased legume rotations, and reduced tillage (Gazey et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Low pH increases aluminium and manganese toxicity, which creates hostile conditions for root growth and reduces the availability of phosphorus, calcium and magnesium (Rengel \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Bell and de Oliveira \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Anderson et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Subsoil compaction arises from the traffic of heavy machinery, livestock grazing, and natural soil consolidation during dry periods (Busscher et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Hall et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Compaction commonly occurs below the top 20 cm of the soil profile, where root penetration is impeded and porosity is limited (Bengough et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Unkovich et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Azam and Gazey 2019; Azam et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e; Wickramarachchi et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e), and is a major cause of the persistent yield gap (the difference between water-limited yield potential and the actual yield). There are additional constraints that interact with subsoil acidity and compaction. Low fertility is an inherent characteristic of WA’s ancient, weathered soils, which are typically deficient in N, P, K, S and micronutrients and have poor cation exchange capacity, making them prone to N and S leaching (Bell and de Oliveira \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Azam \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Anderson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). In coarse-textured sands, these constraints reduce fertiliser use efficiency and pose environmental risks such as off-farm P pollution (Weaver et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), N leaching (Anderson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) or emission of nitrous oxide (Barton et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Low water-holding capacity, typical of sandy and sandy-duplex soils, further limits resilience to variable rainfall, as plant-available water is minimal and rapidly depleted (Sadras and Angus \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Bruun et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The combination of these soil constraints restricts rainfall capture and use, leaving WUE consistently below the theoretical potential despite advances in genetic potential and agronomic management (Lawes et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Aziz et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA range of strategies to address theabove mentioned soil constraints have been developed by researchers and adopted by farmers, in Australia and internationally, but each has limitations. The surface-application of lime is the primary approach to acidity management, however, due to the very slow downward movement of alkali from surface applied lime, amelioration of subsoil acidity takes decades (Azam and Gazey \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Deep ripping to 50 cm depth is widely used to alleviate compaction, but the benefits are partial and temporary as soils recompact (Damon et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Unkovich et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Clay addition can increase water infiltration and storage, but incorporation is difficult and results are inconsistent, especially when poorer-quality clay is used at low ratesand incorporated to shallow depth (Hall et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Roper et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The addition of organic amendments can improve soil fertility and structure; however, it might take decades before cropping becomes profitable on soils amended with organic amendments (Hall and Edwards \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Lauricella et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These interventions are typically targeted at single constraints, act slowly, or provide uneven benefits, underscoring the need for integrated approaches capable of addressing multiple soil limitations simultaneously (Isbister et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Azam et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Davies et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Unkovich et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSoil profile re-engineering (SPR) is a recently developed experimental approach, which involves excavating individual soil horizons (often in 10 cm increments) to a depth of 80 cm followed by thorough mixing to incorporate various soil amendments such as lime, clay and organic materials and then replacing each layer back into the pit in its original sequence, resulting in a reengineered soil profile (Azam et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Azam \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Unlike incremental soil management strategies such as deep ripping or surface liming, SPR rapidly eliminates or alleviates subsoil constraints — including acidity, compaction and nutrient deficiencies (e.g. phosphorus, calcium and magnesium) — to create a more uniform and productive soil profile (Azam and Gazey 2019; Azam et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Azam et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Wickramarachchi et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e; Wickramarachchi and Azam \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). While this approach seems to be not scalable or economically viable at the farm level for now, it provides a benchmark for the maximum grain yield and WUE achievable if multiple constraints are simultaneously removed (Azam et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This benchmark is critical for the development of next-generation soil amelioration technologies for large-scale adoption with improved return on investment.\u003c/p\u003e\u003cp\u003eEvidence from a similar study by Wickramarachchi et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e), together with findings from previous research using similar approaches (Gahoonia et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Azam et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e), suggests that SPR can markedly improve rooting depth and root density, enabling crops to better exploit subsoil resources (Wasson et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). It also enhances nutrient uptake efficiency—particularly nitrogen recovery—by reducing leaching losses (Angus and Grace \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Aziz et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wickramarachchi et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e). By simultaneously alleviating acidity, compaction and other constraints, re-engineered soils support better crop establishment, higher yields, and improved WUE (Azam et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e). However, little is known about how long these benefits persist under field conditions, how they interact with variable seasonal rainfall, or how different cereal crops respond, all of which influence the economics of adopting part or all of the technique\u003c/p\u003e\u003cp\u003eThis study reports on data from two sites from Western Australia (WA), Bolgart and Meenar, to evaluate the impacts of soil profile re-engineering on crop performance in the last four years (2021–2024). The main research question was: to what extent can SPR, through loosening and incorporation of lime, clay, inorganic nutrients and organic matter at 10 cm increments to 80 cm depth, overcome the combined constraints of acidity, compaction, low fertility and low water-holding capacity, and thereby improve root growth, grain yield, and water-use efficiency across multiple cropping seasons in contrasting Western Australian soils (Arenosol and Kurosol). To answer the above question, we conducted two SPR field experiments and assessed the persistence of soil chemical and physical improvements, quantified effects on root development, yield and WUE over four years under variable seasonal conditions on the two soils. We expect results from this study will inform the development of scalable soil amelioration technologies, enable economic assessment of the technique and contribute to future sustainable soil management strategies for constrained agricultural landscapes.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003ch4\u003eStudy sites\u003c/h4\u003e\n\u003cp\u003eIn May 2021, we established two SPR field experiments in the central grain growing regions of WA. Experiment 1 was conducted at Bolgart (Latitude: -31.3162; Longitude: 116.5831; Elevation 260.2 m above mean sea level, AMSL; about 130 km northeast of Perth), while Experiment 2 was conducted at Meenar (Latitude: -31.6450; Longitude 116.8940; Elevation 241.8 AMSL; about 120 km east of Perth). The soil at Bolgart is classified as Yellow Arenosol, while the soil at Meenar was classified as Brown Kurosol (Isbell \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Both of the experimental sites were located in a hot, semi-arid temperate region, corresponding to the Csa category in the K\u0026ouml;ppen\u0026ndash;Geiger climate classification (Peel et al. \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e). Under the rainfall zone classification for southwestern West Australia, both sites (Bolgart\u0026thinsp;=\u0026thinsp;366 mm and Meenar\u0026thinsp;=\u0026thinsp;429 mm per year) fell within the medium rainfall zone (Islam and Salim \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe paddock at Bolgart had been in a cereal-canola-cereal-cereal-lupin rotation, while the paddock at Meenar had been in a cereal-canola-cereal-canola rotation. Both paddocks were cropped under no till systems since mid 1990s until 2020. Both paddocks were surface limed with 4 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e limesand (hereafter lime), but the lime was never incorporated. Both experimental sites had multiple soil constraints, including subsoil acidity, compaction, low inherent fertility (low soil organic carbon, SOC and cation exchange capacity, CEC), and limited water-holding capacity. The soil at Bolgart consisted of a coarse-textured, moderately acidic sand throughout the profile, i.e., an Arenosol, while the Meenar site had a coarse-textured sand at 0\u0026ndash;40 cm and a sandy clay at 40\u0026ndash;80 cm, with a very low pH throughout the profile, i.e., a Kurosol (Isbell \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). More details on sites and soil specific characteristics are provided in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eLocation, rainfall, soil types and soil constraints at two experimental sites.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eParameters\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBolgart\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMeenar\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoordinates (Lat, Long)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-31.3162, 116.5831\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-31.6450, 116.8940\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElevation (above mean seas level, m)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e260.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e241.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLong-term annual rainfall (mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e366\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e429\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLong-term growing season (April-October) rainfall (mm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e291\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e355\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAustralian soil classification (Isbell \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYellow Arenosol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBrown Kurosol\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSoil textural class (sand, silt and clay, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoarse sand: 0\u0026ndash;10 cm: (96.8, 1.3, 1.9)\u003c/p\u003e\n\u003cp\u003eCoase sand: 10\u0026ndash;40 cm: (96.9, 0, 3.1)\u003c/p\u003e\n\u003cp\u003eCoarse sand: 40\u0026ndash;80 cm: (96.7, 0, 3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoarse sand: 0\u0026ndash;10 cm: (90.8, 2.3, 6.9)\u003c/p\u003e\n\u003cp\u003eLoamy sand: 10\u0026ndash;40 cm: (84.2, 2.6, 13.2)\u003c/p\u003e\n\u003cp\u003eSandy clay: 40\u0026ndash;80 cm: (60.0, 3.3, 36.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSoil organic carbon (SOC, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;10 cm: 0.38; 10\u0026ndash;40 cm: 0.15 and 40\u0026ndash;80 cm: 0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;10 cm: 1.29; 10\u0026ndash;40 cm: 0.43 and 40\u0026ndash;80 cm: 0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003epH\u003csub\u003eCa\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;10 cm: 5.4; 10\u0026ndash;40 cm: 4.6 and 40\u0026ndash;80 cm: 4.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;10 cm: 4.5; 10\u0026ndash;40 cm: 4.2 and 40\u0026ndash;80 cm: 4.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCation exchange capacity (CEC, cmol kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;10 cm: 0.77; 10\u0026ndash;40 cm: 0.21 and 40\u0026ndash;80 cm: 0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u0026ndash;10 cm: 1.26; 10\u0026ndash;40 cm: 0.39 and 40\u0026ndash;80 cm: 0.72\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eExperimental setup\u003c/h2\u003e\n\u003cp\u003eEight treatments were evaluated: an untreated control (T1), three shallow soil-amelioration (SSA) treatments (T2\u0026ndash;T4), and four SPR treatments (T5\u0026ndash;T8) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Treatments were arranged in a partially randomized block design, with T1\u0026ndash;T4 and T5\u0026ndash;T8 allocated to two separate blocks within each of the three replicates. Treatments were applied once before sowing in May 2021. Plots measured 5 \u0026times; 4 m with 1 m buffer zones between treatments.\u003c/p\u003e\n\u003cp\u003eThe soil profile re-engineering treatments (T5\u0026ndash;T8) followed the general approach previously outlined by Azam (\u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), where the soil horizons were removed, amended, and replaced. For these treatments soil layers (0\u0026ndash;10, 10\u0026ndash;40, and 40\u0026ndash;80 cm) were excavated using a 20-ton excavator (Komatsu PC200) and stockpiled separately by layer. Each layer was returned in 10 cm increments using a front-end loader (Volvo L90F) and lightly cultivated with a rotary hoe (Red Roo RH918) after spreading and incorporation of the amendments as described in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. For T2, T3 and T4, all amendments (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) were placed on the surface followed by incorporation to 10 cm depth using the same rotary hoe.\u003c/p\u003e\n\u003cp\u003eThe liming material was limesand, with a neutralising value of 94.9% relative to analytical CaCO₃, and contained 99% particles\u0026thinsp;\u0026lt;\u0026thinsp;0.5 mm; this was applied to all treatments except T1 (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Clay was sourced either from a nearby pit at Bolgart (sand 28.8%, silt 0.7%, clay 70.5%) or the B horizon (40\u0026ndash;80 cm) of the experimental soil at Meenar (sand 60.0%, silt 3.3%, clay 36.7%). Compost was obtained from a commercial supplier and contained 40% organic C, 2.5% N, 1.0% P, 1.7% K, 5.4% Ca, 0.5% Mg, 1.7% S, and 0.4% Na; this was applied in T4 and T8 (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, inorganic fertiliser containing N, P and K was applied (in T3 and T4, see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) at rates calculated to supplement the proportion of nutrients expected to be mineralised from the compost (approximately 16% per year) (Horrocks et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). This inorganic fertiliser treatment with matching nutrient content was included to distinguish the nutrient contribution of the organic amendment (i.e., improved soil fertility) from its non-nutrient effects, such as those arising from its carbon and biological components (e.g. improved soil structure, increased microbial activity and increased water-holding capacity).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eDescription of the soil re-engineering experiments.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eTreatments\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDescription\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBolgart\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMeenar\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eControl (T1)*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo tillage or amendment was applied.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo tillage or amendment was applied.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSurface liming and claying to 10 cm depth (T2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 1.5 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, and 110 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay to 0\u0026ndash;10 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 1.7 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, and 110 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay to 0\u0026ndash;10 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSurface liming, claying and adding N, P and K to 10 cm depth (T3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 1.5 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, 110 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay, and 61, 24 and 42 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e inorganic N, P and K, respectively to 0\u0026ndash;10 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 1.7 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, 110 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay, and 57, 23 and 39 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e inorganic N, P and K, respectively to 0\u0026ndash;10 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSurface liming, claying and adding compost to 10 cm depth (T4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 1.5 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, 110 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay, and 42 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e compost to 0\u0026ndash;10 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 1.7 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, 110 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay, and 31 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e compost to 0\u0026ndash;10 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening and liming to 80 cm depth (T5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.0 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime to 0\u0026ndash;80 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime to 0\u0026ndash;80 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening, liming and claying to 80 cm depth (T6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, and 1,337 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay to 0\u0026ndash;80 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime to 0\u0026ndash;80 cm depth and 329 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay to 0\u0026ndash;40 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening, liming, claying and adding compost to 80 cm depth (T7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, 1,337 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay, and 245, 98 and 166 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e inorganic N, P and K, respectively to 0\u0026ndash;80 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime to 0\u0026ndash;80 cm depth; 329 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay to 0\u0026ndash;40 cm depth and 226, 90 and 154 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e inorganic N, P and K, respectively to 2\u0026ndash;80 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening, liming, claying and adding compost to 80 cm depth (T8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime, 1,337 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay, and 167 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e compost to 0\u0026ndash;80 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoosening of soil and incorporation of 6.8 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e lime to 0\u0026ndash;80 cm depth; 329 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e clay to 0\u0026ndash;40 cm depth and incorporation of 125 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e compost to 20\u0026ndash;80 cm depth.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\"\u003e\u003cem\u003eNotes: all rates of amendments were calculated on a w/w basis. The untreated control received a surface application 4 t ha\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;\u0026thinsp;1\u003c/em\u003e\u003c/sup\u003e \u003cem\u003elime as a standard agronomic practice in the last ten years organised by the host farmers.\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eCrop management\u003c/h3\u003e\n\u003cp\u003eThe experiments were established within farmer\u0026rsquo;s existing controlled traffic farming (CTF) system at both sites. This allowed the host growers to run the cropping program according to their commercial plan, i.e., seeding, fertilisation, weed control, pest and disease control sprays were carried out by the farmers. This operation within the CTF system helped prevent additional machinery-induced compaction in the already loosened, re-engineered soil profiles. Details of the key operations, including crop details, are provided in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eAt the start of the experiment, the Bolgart soil (0\u0026ndash;10 cm) contained 15 mg Colwell P kg⁻\u0026sup1; and 3.8 mg KCl-40 S kg⁻\u0026sup1;, while Colwell K was below the detection limit. In contrast, the Meenar soil (0\u0026ndash;10 cm) had 22 mg Colwell P kg⁻\u0026sup1;, 51 mg Colwell K kg⁻\u0026sup1;, and 4.8 mg KCl\u003csub\u003e40\u003c/sub\u003e S kg⁻\u0026sup1;. Based on established critical soil test values, P supply was adequate at both sites (Bell et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e)d supply was adequate for cereals but not sufficient for canola (Anderson et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Thefrefore, growers at both sites did not apply S fertiliser to cereals, but both sites were fertilised by 25 kg S ha⁻\u0026sup1; in seasons when canola was grown. Potassium supply was adequate at Meenar, but inadequate at Bolgart (Brennan and Bell \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Other baseline nutrient application rates differed between the two sites according to seasonal forecasts and crop choice. At Bolgart, basal applications included 12.5\u0026ndash;18 kg P ha⁻\u0026sup1;, 8\u0026ndash;40 kg K ha⁻\u0026sup1;, and 65\u0026ndash;115 kg N ha⁻\u0026sup1;. At Meenar, basal rates were 20 kg P ha⁻\u0026sup1;, 20 kg K ha⁻\u0026sup1;, and 60\u0026ndash;100 kg N ha⁻\u0026sup1;. These N rates reflect typical grower practice for achieving cereal yields of approximately 2\u0026ndash;3 t ha⁻\u0026sup1; (Scanlan et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBolgart and Meenar sites (Western Australia) seeding, N, P, and K rate (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), annual rainfall during 2021\u0026ndash;2024 and potential yield (determined using method of Oliver et al. 2029).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eYear\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSite\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCrop type\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSeeding rate\u003c/p\u003e\n\u003cp\u003e(kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFertiliser applications\u003c/p\u003e\n\u003cp\u003e(kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAnnual rainfall (mm)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOliver et al. (\u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e) potential yield\u003c/p\u003e\n\u003cp\u003e(t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBolgart\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWheat, var Scepter\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;65, 12.5 and 15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e496\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.14\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMeenar\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCanola\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;60, 20 and 20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e566\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.22\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBolgart\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCanola\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;95, 12.5 and 15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e472\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.71\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMeenar\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBarley, var Maximus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;60, 20 and 20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e443\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBolgart\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTriticale var\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;115, 12.5 and 40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e307\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.41\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMeenar\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCanola\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;100, 20 and 20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e240\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.42\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2024\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBolgart\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBarley, var Commodus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;87, 18 and 8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.36\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMeenar\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWheat, var Scepter\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN, P and K\u0026thinsp;=\u0026thinsp;60, 20 and 20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e352\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.60\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003eSoil sampling, in situ measurements and analyses\u003c/h3\u003e\n\u003cp\u003eSoil profile samples were collected each July from 2021 to 2024, when soil moisture conditions were suitable for core sampling using a 40 mm inner-diameter stainless-steel tube. Data from the 2021 sampling are reported in Azam (\u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), while the 2022 and 2023 data are not presented. This paper reports the July 2024 results.\u003c/p\u003e\n\u003cp\u003eSamples were taken at 10-cm depth increments to a maximum of 100 cm, although the final depth varied depending on subsoil conditions (e.g. soil hardness or excess moisture). Within each plot, four sampling points were selected. Soil collected at the same depth from these four points was combined to form a composite sample. From each composite sample, a 100-g subsample was used to determine the gravimetric water content. The remaining material was dried at 40\u0026deg;C, passed through a 2 mm sieve, and analysed for soil pH\u003csub\u003eCa\u003c/sub\u003e (Method 4B2), CEC (Method 15E1), and SOC (Method 6A1) (Rayment and Lyons \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). Soil strength (penetration resistance) was also measured in July each year, using a handheld electronic cone penetrometer (CP40II, Rimik Pty Ltd, Toowoomba, Queensland), but this paper reports the July 2024 results.\u003c/p\u003e\n\u003cp\u003eSoil pH\u003csub\u003eCa\u003c/sub\u003e, soil strength, CEC, and SOC were assessed as indicators of soil acidity, compaction, water-holding and nutrient-retention capacity, and overall soil health to evaluate the effects of soil re-engineering treatments (Anderson et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bengough et al. \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hall et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hoyle et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Riaz and Marschner \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn situ\u003c/em\u003e root images were recorded annually at crop anthesis (Z65 for cereals; 10% flowering for canola) from treatments T1, T5, T6, T7 and T8 using a 360\u0026deg; root scanner (CI-600, CID Bio-Science, Camas, WA, USA) and 130-cm mini-rhizotron tubes installed in the soil. This approach has been shown to effectively distinguish treatment-related differences in root development in previous work (Uddin et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Azam et al. \u003cspan class=\"CitationRef\"\u003e2024b\u003c/span\u003e). Image processing, root tracing and root analysis followed the procedures described in Azam et al. (\u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThree shoot samples (each collected from a pre-determined sampling zone by cutting two adjacent rows each 1m in length) were collected and composited for each plot. Cereal shoots were sampled at growth stage Z65 (Zadoks et al. \u003cspan class=\"CitationRef\"\u003e1974\u003c/span\u003e), while canola shoots were collected at approximately 10% flowering (Smith and Scarisbrick \u003cspan class=\"CitationRef\"\u003e1990\u003c/span\u003e). All samples were oven-dried at 60\u0026deg;C for seven days before determining dry biomass. Tissue nitrogen (N) was measured using the Rayment and Lyons (\u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e, method 7A5 modified) and tissue potassium (K) was measured using the method of McQuaker (1979). Total N and K uptake were calculated by multiplying tissue nutrient concentrations by the corresponding biomass yields to express the results in units of kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eYield and WUE measurements\u003c/h3\u003e\n\u003cp\u003eFrom each plot, crop was hand-harvested at physiological maturity from a 4 x 2 m area to calculate grain yields (t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003eThe WUE (kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) of cereals and canola was calculated using models calibrated in this region by Oliver et al. (\u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e) as shownbelow:.\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$\\:WUE=\\frac{\\text{Y}}{\\text{A}\\text{S}\\text{W}}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003ewhere WUE is water use efficiency (kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), potential grain yield (PY) is grain yield (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and ASW is available soil water (mm), which is calculated as below:\u003c/p\u003e\n\u003cp\u003eASW\u0026thinsp;=\u0026thinsp;SW\u0026thinsp;+\u0026thinsp;GSR \u0026ndash; I\u003c/p\u003e\n\u003cp\u003ewhere SW is stored soil water at sowing (mm), GSR is growing season (April to October) rainfall (mm), and I is the threshold rainfall (mm) required before a crop will yield. In our work here, it was assumed that SW is equal to 30% of the pre-season (January to March) rainfall (mm), and also has an upper limit equal to the plant available water capacity (PAWC) of the soil (SW\u0026thinsp;\u0026le;\u0026thinsp;PAWC). The PAWC of the Bolgart and Meenar soils were 40 and 100 mm respectively (Oliver et al. \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). GSR also has an upper limit related to the PAWC of the soil; the upper limit of the GSR for Bolgart and Meenar sites were 240 and 290 mm, respectively (Oliver et al. \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). I was 130 mm for all seasons as the both sites had\u0026thinsp;\u0026gt;\u0026thinsp;180 mm GSR (Oliver et al. \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe calculated PY for the two sites for the four experimental yields are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Monthly rainfall measures are presented in the Supplemental Materials (Table S1).\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical analyses\u003c/h2\u003e\n\u003cp\u003eCrop yield, nutrient uptake, and soil properties were analysed using separate linear mixed models (LMMs) for each variable, implemented in AsREML-R package (Butler et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) within the R statistical environment (R-Core-Team \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). For yield data, treatment was treated as a fixed effect, and models were fitted independently for each year. The random effects for the experimental design were accounted for with a structure where plots were nested within replications and years were nested within plots. Variance components were estimated for each year using restricted maximum likelihood (REML), and model adequacy was evaluated by inspecting residual distributions. Predicted means for each treatment\u0026ndash;year combination were generated, and within-year differences were tested using Fisher\u0026rsquo;s protected least significant difference (LSD) method.\u003c/p\u003e\n\u003cp\u003eSoil properties were analysed using a similar framework, with treatment included as a fixed effect and models were fitted separately for each sampling time and soil depth. The random structure reflected sampling time nested within plots and plots were nested within replications. To explore the relationship between crop performance and nutrient uptake, linear regressions were conducted between total N and K uptake and grain yield for each season and site. The coefficient of determination (r\u0026sup2;) was used to quantify the strength of these relationships, and significance was determined at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e\n\u003cp\u003eRegression tree analysis was applied to identify the relative influence of five key soil physicochemical properties from all sampling depths on grain yield across seasons at both sites. For each regression tree model, the residual mean square error and the proportion of variance explained were reported, providing insight into the primary soil factors governing yield responses.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eImprovement in yield and water-use efficiency\u003c/h2\u003e\u003cp\u003eSoil profole re-engineering produced consistent, statistically significant increases in grain yield and water-use efficiency (WUE) across all crop species and four contrasting growing seasons at both the Bolgart (Arenosol) and Meenar (Kurosol) sites (Figs.\u0026nbsp;1\u0026ndash;2). In contrast, treatments involving shallow incorporation of amendments (T2\u0026ndash;T4) showed minimal or no gains relative to the control (T1) at both sites.\u003c/p\u003e\u003cp\u003eOn the Arenosol at Bolgart, grain yield (Fig.\u0026nbsp;1a\u0026ndash;d) and WUE (Fig.\u0026nbsp;1e\u0026ndash;h) increased markedly in all four crops in the SPR treatments and in the shallow incorporation of compost treatment (T4) compared to the control. In 2021, wheat grain yield and WUE increased by up to 147% relative to the untreated control, exceeding the least significant difference (LSD for yield\u0026thinsp;=\u0026thinsp;0.24 t ha⁻\u0026sup1;, LSD for WUE\u0026thinsp;=\u0026thinsp;2.11 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, significant improvements in yield and WUE were recorded in only in T4 (surface incorporation) and T8 (incorporation to 80 bm depth) that involved incorporation of lime, clay and compost either in the surface or up to 80 cm depth (Fig.\u0026nbsp;1a and 1e). In 2022, canola yield and WUE rose by 432% (LSD for yield\u0026thinsp;=\u0026thinsp;0.74 t ha⁻\u0026sup1;, LSD for WUE\u0026thinsp;=\u0026thinsp;2.58 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1b and 1f). Canola yield was significantly higher in T4\u0026ndash;T8, with the highest difference in yield being 2.14 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in T8 (limed, clayed and composted) compared to T1.\u003c/p\u003e\u003cp\u003eTriticale and barley yields were 300% and 277% greater in 2023 and 2024, respectively (LSD\u0026thinsp;=\u0026thinsp;0.29 t ha⁻\u0026sup1; and 0.46 t ha⁻\u0026sup1;) (Fig.\u0026nbsp;1c and 1d). Triticale and barley WUE rose at the same magnitude as with the yields, with the highest improvement of 5.06 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 9.81 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in T8, respectively (LSD\u0026thinsp;=\u0026thinsp;1.35 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eand 1.92 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;1g and 1h). Yield responses were consistent across replicate plots, with all re-engineered treatments (T5\u0026ndash;T8) significantly outperforming the untreated control in all years except 2021 (the trial establishment year).\u003c/p\u003e\u003cp\u003eAt the Meenar site (Kurosol), grain yield (Fig.\u0026nbsp;2a\u0026ndash;d) and WUE (Fig.\u0026nbsp;2e\u0026ndash;h) increased markedly, although treatment effects differed from those at Bolgart (Arenosol). Shallow incorporation of clay and lime (T2) had no effect, while shallow incorporation of nutrients (T3) or compost (T4) had inconsistent effects across years.\u003c/p\u003e\u003cp\u003eIn 2021, canola yield and WUE increased by up to 106% relative to the control, exceeding the LSD (yield\u0026thinsp;=\u0026thinsp;0.23 t ha⁻\u0026sup1;, WUE\u0026thinsp;=\u0026thinsp;0.71 kg mm⁻\u0026sup1;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), primarily in the re-engineering treatments (T5\u0026ndash;T8), with the largest gain of 1.57 t ha⁻\u0026sup1; in T7 (re-engineered with added lime, clay and nutrients to 80 cm depth). In 2022, barley yield and WUE increased by ~\u0026thinsp;150% (LSD yield\u0026thinsp;=\u0026thinsp;0.66 t ha⁻\u0026sup1;, WUE\u0026thinsp;=\u0026thinsp;2.45 kg mm⁻\u0026sup1;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in all re-engineering treatments, with the highest gains of 2.62 t ha⁻\u0026sup1; and 9.68 kg mm⁻\u0026sup1; in T7 compared to T1. Differences between re-engineering treatments were generally not significant.\u003c/p\u003e\u003cp\u003eCanola and wheat yields were 148% and 118% higher in 2023 and 2024, respectively (LSD\u0026thinsp;=\u0026thinsp;0.53 t ha⁻\u0026sup1; and 0.47 t ha⁻\u0026sup1;) (Fig.\u0026nbsp;2c and 2d). In 2023, the maximum canola yield and WUE increased by 1.06 t ha⁻\u0026sup1; and 5.65 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in T7, respectively (Fig.\u0026nbsp;2c and 2g). Similar to canola in 2023, wheat yield and WUE in 2024, rose by 1.23 t ha⁻\u0026sup1; and 7.50 kg mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in T7, respectively (Fig.\u0026nbsp;2d and 2h).\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 2 near here\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eImprovement in N and K uptakes\u003c/h2\u003e\u003cp\u003eRe-engineering treatments also resulted in substantial increases in shoot nitrogen (N) and potassium (K) uptakes across all crops and growing seasons at both sites (Fig.\u0026nbsp;3 and Fig.\u0026nbsp;4).\u003c/p\u003e\u003cp\u003eAt Bolgart, total shoot N uptake at anthesis increased substatially in all four seasons (Fig.\u0026nbsp;3a\u0026ndash;d). In 2021, N uptake by wheat shoots grown in the re-engineered treatments (T5\u0026ndash;T8) increased by up to 252% relative to the untreated control, exceeding the least significant difference (LSD\u0026thinsp;=\u0026thinsp;48.2 kg ha⁻\u0026sup1;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, the improvement in N uptake was observed only in T4 (surface limed, clayed and composted) and T8 (re-engineering with added lime, clay and compost) (Fig.\u0026nbsp;3a). In 2022, N uptake in canola shoot increased by approximately 490% with the maximum improvement of 147.8 kg ha⁻\u0026sup1; in T8 compared to T1 (LSD\u0026thinsp;=\u0026thinsp;63.1 kg ha⁻\u0026sup1;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;3b). Triticale (2023) and barley (2024) N uptakes in shoot in T8 were 46.9 kg ha⁻\u0026sup1; and 71.0 kg ha⁻\u0026sup1; higher than T1, respectively (LSD\u0026thinsp;=\u0026thinsp;14.1 kg ha⁻\u0026sup1; and 14.0 kg ha⁻\u0026sup1;) (Fig.\u0026nbsp;3c and 3d).\u003c/p\u003e\u003cp\u003eAt Bolgart, total K uptake also increased substantially in all four seasons (Fig.\u0026nbsp;3e\u0026ndash;h). In 2021, K uptake by wheat shoot lifted by up to 336% (92.9 kg ha⁻\u0026sup1;) compared to the untreated control (LSD\u0026thinsp;=\u0026thinsp;46.8 kg ha⁻\u0026sup1;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), however, the improvement in K uptake was only observed in T4 and T8 (K applied as organic matter) in this first year of the experiment (Fig.\u0026nbsp;3e). In 2022, K uptake in canola shoot rose approximately by 11-fold with the maximum improvement of 138.6 kg ha⁻\u0026sup1; in T8 compared to T1 (LSD\u0026thinsp;=\u0026thinsp;34.6 kg ha⁻\u0026sup1;, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;3f). Triticale and barley K uptakes in shoot were 55.0 kg ha⁻\u0026sup1; and 163.8 kg ha⁻\u0026sup1; higher in 2023 and 2024, respectively (LSD\u0026thinsp;=\u0026thinsp;14.4 kg ha⁻\u0026sup1; and 23.3 kg ha⁻\u0026sup1;) (Fig.\u0026nbsp;3g and 3h).\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 3 near here\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAt Meenar, total N and K uptakes in shoots at anthesis increased significantly in all four seasons (Fig.\u0026nbsp;4). In 2021, N uptake in canola shoot increased by up to 446%, while K uptake was higher by more than 6-fold compared to the untreated control (Fig.\u0026nbsp;4a and 4e). This was equivalent of an increase in N uptake of 292.5 kg ha⁻\u0026sup1; and in K uptake of 290.6 kg ha⁻\u0026sup1; relative to the untreated control (LSD for N uptake\u0026thinsp;=\u0026thinsp;48.2 kg ha⁻\u0026sup1;, LSD for K uptake\u0026thinsp;=\u0026thinsp;48.2 kg ha⁻\u0026sup1;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In 2022, N and K uptakes in barley increased by 328% and 551%, respectively. This equates to a maximum improvement of 187.4 and 194.4 kg ha⁻\u0026sup1; N and K uptakes, respectively, in T8 compared to T1 (LSD\u0026thinsp;=\u0026thinsp;63.1 kg ha⁻\u0026sup1;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;4b and 4f). Canola and wheat N uptakes in the shoot were 154.2 kg ha⁻\u0026sup1; and 176.3 kg ha⁻\u0026sup1; higher in 2023 and 2024, respectively (LSD\u0026thinsp;=\u0026thinsp;72.4 kg ha⁻\u0026sup1; and 41.3 kg ha⁻\u0026sup1;) (Fig.\u0026nbsp;4c and 4d). Similarly, canola and wheat K uptakes increased by 102.0 kg ha⁻\u0026sup1; and 254.9 kg ha⁻\u0026sup1; in 2023 and 2024, respectively (LSD\u0026thinsp;=\u0026thinsp;36.3 kg ha⁻\u0026sup1; and 52.1 kg ha⁻\u0026sup1;) (Fig.\u0026nbsp;4c and 4d).\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 4 near here\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eRoot architecture of wheat and canola\u003c/h2\u003e\u003cp\u003eA clear visual improvement in root development was observed for both wheat at Bolgart and canola at Meenar in all soil re-engineering treatments (T5\u0026ndash;T8) relative to the untreated control (T1) (Fig.\u0026nbsp;5). Root distribution on the Rhizotron tube surfaces was not uniform across samples, reflecting natural variation in plant spacing and root\u0026ndash;tube contact. In the control treatment, maximum rooting depth was limited to approximately 50 cm in the Arenosol at Bolgart (Fig.\u0026nbsp;5a) and around 35 cm in the Kurosol at Meenar (Fig.\u0026nbsp;5b). In contrast, plants in all re-engineering treatments had roots that extended to at least the depth of soil re-engineering (\u0026asymp;\u0026thinsp;80 cm). Among the re-engineering treatments, T8 consistently produced the most extensive and well-developed root systems for both crops, while T6 (re-engineered with added lime and clay) and T7 (re-engineered with added lime, clay and compost) produced a greater root density than T5 (re-engineered with added lime), particularly in canola.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 5 near here\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eLongevity of the improvement in soil properties\u003c/h2\u003e\u003cp\u003ePreviously soil re-engineering was shown to improve soil strength, soil water holding capacity (i.e., volumetric water content, pH\u003csub\u003eCa\u003c/sub\u003e, SOC and CEC almost immediately after the experiments were established in 2021 (Azam \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The improvements in these key soil physicochemical properties persisted for at least four cropping seasons following treatment application (Fig.\u0026nbsp;6).\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 6 near here\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAt Bolgart (Arenosol), all soil re-engineering treatments (T5\u0026ndash;T8) had a significantly lower soil strength than the untreated control (T1) (Fig.\u0026nbsp;6a). Among the re-engineering treatments, T8 had lower soil strength than T6 and T7 at 30\u0026ndash;60 cm depth, although no significant difference was observed between T5 and T8. In addition, all soil re-engineering treatments had a higher volumetric water content at 0\u0026ndash;20 cm depth compared with the control, but no significant differences were detected at greater depths (Fig.\u0026nbsp;6b).\u003c/p\u003e\u003cp\u003eAll re-engineered soils had significantly higher pH\u003csub\u003eCa\u003c/sub\u003e at 10\u0026ndash;80 cm depth than the control and other surface treatments (Fig.\u0026nbsp;6c). The re-engineering treatment incorporating compost (T8) had significantly greater SOC at 20\u0026ndash;90 cm depth compared with all other treatments (Fig.\u0026nbsp;6d). Similarly, all re-engineering treatments showed higher CEC at 20\u0026ndash;90 cm depth than the control and other surface treatments, with T8 having significantly greater CEC than the other re-engineering treatments (T5\u0026ndash;T7) (Fig.\u0026nbsp;6e).\u003c/p\u003e\u003cp\u003eAt Meenar (Kurosol), greater variation in soil strength was observed among treatments than at Bolgart (Fig.\u0026nbsp;6f). All soil re-engineering treatments (T5\u0026ndash;T8) had significantly lower soil strength than the untreated control, with T5 and T8 showing the lowest values, particularly at 10\u0026ndash;80 cm depth. Volumetric water content was lower in T5 than in T1 and T7 at 40\u0026ndash;70 cm depth, but no other significant differences were observed among the other treatments (Fig.\u0026nbsp;6g).\u003c/p\u003e\u003cp\u003eAll re-engineered treatments had significantly higher pH\u003csub\u003eCa\u003c/sub\u003e at 10\u0026ndash;70 cm depth compared with the control and surface treatments (Fig.\u0026nbsp;6h). Similarly, all soil re-engineering treatments had higher SOC at 10\u0026ndash;30 cm depth relative to the control and surface treatments, with T8 also having having higher SOC at 30\u0026ndash;60 cm depth than all other treatments (Fig.\u0026nbsp;6i). CEC was also significantly higher under all re-engineering treatments at 20\u0026ndash;70 cm depth compared with the control and surface treatments, and among these, T8 had the highest CEC between 30 and 70 cm depth (Fig.\u0026nbsp;6j).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eRelationships between N and K uptakes and yield\u003c/h2\u003e\u003cp\u003eIn most cases, positive significant relationships were observed between total shoot N and K uptakes and grain yield across both sites (Fig.\u0026nbsp;7). In general, at Bolgart (Arenosol), yield increased proportionally with total shoot N and K uptake across all crops, with coefficients of determination (r\u0026sup2;) ranging from 0.87 to 0.95 for N uptake and K uptake (Fig.\u0026nbsp;7a\u0026ndash;d). For this site, the yield response to N uptake was linear in all four seasons (Fig.\u0026nbsp;7a\u0026ndash;d), while the yield response to K uptake was linear only in the first two seasons (Fig.\u0026nbsp;7a and 7b). For the last two seasons the yield response to total shoot uptake of K was logarithmic (Fig.\u0026nbsp;7c and 7d).\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 7 near here\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAt Meenar (Kurosol), positive significant relationships were observed between total shoot K uptake and grain yield across all seasons (Fig.\u0026nbsp;7e\u0026ndash;h), however, the relationships between total shoot N uptake and grain yield were weaker in 2023 (Fig.\u0026nbsp;7g) and not significant in 2024 (Fig.\u0026nbsp;7h). The r\u0026sup2; values ranged from 0.43 to 0.90 for N uptake and from 0.72 to 0.88 for K uptake.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eDeterminants of yield improvement\u003c/h2\u003e\u003cp\u003eRegression tree analyses identified the key soil variables determining yield responses to re-engineering treatments (Fig.\u0026nbsp;8). At Bolgart, cation exchange capacity (CEC), soil strength (SS), soil organic carbon (SOC) and clay content were the dominant predictors of yield variation (Fig.\u0026nbsp;8a). The first split occurred at the CEC threshold of 0.99 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (average for the soil profile) and benchmarked the grain yield at 1.13 t ha⁻\u0026sup1;. The second split also occurred in favour of CEC at a threshold of 2.07 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (average for the soil profile), which generated a maximum yield of 3.38 t ha⁻\u0026sup1;. Treatments with higher CEC and a SS threshold of \u0026lt;\u0026thinsp;1.64 MPa had the highest grain yield of 3.75 t ha⁻\u0026sup1;. SOC appeared at three splits with a threshold range of 0.11\u0026ndash;0.15% (average for the soil profile). Clay content appeared at the last split with a threshold value of 3.89% (average for the soil profile), separating the low-yield (\u0026lt;\u0026thinsp;1.18 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and high-yield (\u0026gt;\u0026thinsp;2.79 t ha⁻\u0026sup1;) groups. Notably, soil pH\u003csub\u003eCa\u003c/sub\u003e did not appear in any of the splits at this site. The model accounted for 64.5% of total variance, with a residual mean square error of 0.51 t ha⁻\u0026sup1;.\u003c/p\u003e\u003cp\u003e\u003cem\u003eFigure 8 near here\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAt Meenar, CEC, SS, pH\u003csub\u003eCa\u003c/sub\u003e, and SOC were the main determinants of yield, while clay content did not affect the yield outcome (Fig.\u0026nbsp;8b). Soil CEC appeared at three splits with threshold values of 0.83, 1.97 and 2.33 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (average for the soil profile). Where CEC had a lower threshold value, SOC and SS had the greatest influence on improving yield from 1.70 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 4.19 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Soil pH\u003csub\u003eCa\u003c/sub\u003e also appeared at three splits with threshold values in the range of 4.91\u0026ndash;5.35 (average for the soil profile), whereas SS and SOC appeared at two splits each. The regression tree explained 80.4% of yield variance, with a residual mean square error of 0.67 t ha⁻\u0026sup1;.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eBenchmarking yield and WUE gains through soil profile re-engineering\u003c/h2\u003e\u003cp\u003eThis four-year field evaluation across two contrasting sites has demonstrated that soil profile re-engineering can substantially close the yield gap in water-limited environments by simultaneously alleviating multiple constraints, including subsoil acidity, compaction, and low fertility. Yield improvements of up to 432% for canola, 300% for triticale, 277% for barley and 147% for wheat, coupled with WUE gains exceeding 9 kg mm⁻\u0026sup1;, indicate that integrated deep amelioration can approach theoretical water-limited yield potential benchmarks for Western Australian and southern Australian cropping systems (Sadras and Angus \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Harries et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Barrett-Lennard et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Oliver et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). These results confirm earlier short-term (first year following amelioration) findings that 45\u0026ndash;80 cm deep incorporation of lime and other amendments enhances rooting depth and resource capture (Azam and Gazey 2019; Wickramarachchi and Azam \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), but extend the evidence by demonstrating persistence of the benefits over multiple and contrasting growing seasons.\u003c/p\u003e\u003cp\u003eUnlike surface liming, ripping or claying, which act slowly or provide inconsistent benefits or aggravate evaporative water loss (Li et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Damon et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hall et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wickramarachchi et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e), soil re-engineering has delivered immediate (Azam \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and durable improvements in soil physical and chemical properties, evidenced by sustained soil strength, pH\u003csub\u003eCa\u003c/sub\u003e, CEC, and SOC gains over four seasons. This persistence suggests that soil profile re-engineering can serve as a benchmark for designing scalable amelioration strategies (Davies et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Musei et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Importantly, the magnitude of the yield responses observed here and in other deep soil amelioration research (Azam et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) can exceed the theoretical water-limited yield boundary for WA and southern Australia (Barrett-Lennard et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), highlighting the potential of integrated interventions to overcome multiple interacting soil constraints in semi-arid and rainfed cropping systems.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eNutrient uptake and soil functional improvements as drivers of productivity\u003c/h2\u003e\u003cp\u003eThe strong positive relationships between N and K uptake and grain yield (r\u0026sup2; up to 0.95, \u003cem\u003eP\u0026thinsp;\u0026le;\u0026thinsp;0.001\u003c/em\u003e) underscore the role of improved nutrient acquisition in driving productivity gains. For sandy soils with the typical distribution of rainfall at our sites, nitrate leaching is a significant nutrient loss process (Anderson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Hence, enhanced rooting depth and reduced nitrate leaching losses likely contributed to higher nitrogen recovery, consistent with previous reports on deep ameliorated soils (Angus and Grace \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lynch \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wickramarachchi et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e). Treatments incorporating compost (T8) delivered the greatest SOC and CEC improvements, which are critical for nutrient retention in coarse-textured sandy soils (Bell and de Oliveira \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hoyle et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Regression tree analysis further highlighted CEC, SOC and soil strength as dominant predictors of yield at both soil types, while yield improvement was also related to claying at Bolgart (moderately acidic Arenosol) and soil pH\u003csub\u003eCa\u003c/sub\u003e at Meenar (very acidic Kurosol). These reinforce the importance of physical\u0026ndash;chemical\u0026ndash;biological synergy in soil management (Bell and de Oliveira \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Azam et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur findings are consistent with the global evidence that integrated amendments\u0026mdash;lime, clay, and organic matter\u0026mdash;enhance soil buffering capacity and nutrient cycling, thereby sustaining crop performance under variable rainfall (Lauricella et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The observed logarithmic yield response to K uptake in later seasons suggests diminishing returns once structural constraints are alleviated, pointing to the need for balanced nutrient strategies in ameliorated soils. Recent work by Wickramarachchi and Azam (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) on fertiliser strategies for re-engineered soils supports this, showing that surface-applied N at higher rates can maintain yield gains without deep fertiliser incorporation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eDeeper root systems and soil water storage: a critical mechanism\u003c/h2\u003e\u003cp\u003eOne of the most striking outcomes of soil profile re-engineering is the development of deeper and more continuous root systems, which significantly enhance access to subsoil water and nutrients. Our results align with rhizotron-based studies showing that removal of subsoil strength and acidity promotes root elongation and proliferation, increasing planar root length density and water uptake (Azam et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e; Gregory \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Uddin et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This holistic improvement effectively increases the soil plant available water holding capacity. Hence buffering crops against terminal drought\u0026mdash;a key limitation in Mediterranean-type climates (Sadras and Angus \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Harries et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wickramarachchi et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe importance of rooting depth is further emphasised by global research on subsoil constraints. Bell and de Oliveira (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) note that crops may acquire up to 75% of N and 70% of K from subsoil layers if root growth is unrestricted. Conversely, compaction and acidity severely limit this potential, confining roots to shallow horizons and exacerbating yield variability (Unkovich et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cui et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Our findings demonstrate that re-engineering not only removes these barriers but also creates conditions for sustained root development across seasons, a prerequisite for resilience under climate variability.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eLongevity and practical implications for semi-arid cropping systems\u003c/h2\u003e\u003cp\u003eA critical outcome of this study is the durability of soil improvements. Four years post-treatment, re-engineered profiles maintained lower soil strength and higher pH\u003csub\u003eCa\u003c/sub\u003e, SOC, and CEC compared to controls, even across contrasting soil types (Arenosol and Kurosol). This contrasts with the rapid decline in benefits often observed after deep ripping to a depth of up to 50 cm alone (Busscher et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Unkovich et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While the economic and logistical constraints of full-profile re-engineering currently preclude farm-scale adoption, our results provide a benchmark for next-generation technologies such as targeted deep placement of amendments or hybrid mechanical\u0026ndash;biological approaches (Schmittmann et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Davies et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFuture research should explore cost-effective strategies that mimic the functional outcomes of re-engineering\u0026mdash;particularly improved rooting depth and nutrient retention\u0026mdash;while minimising repeated soil disturbance and carbon loss. Integrating soil microbiome management with physiochemical amelioration may offer synergistic gains in resilience and sustainability (Wu et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In addition, long-term monitoring of carbon dynamics and economic analyses will be essential to evaluate the feasibility of scaled-down interventions that deliver similar benefits.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis four-year field study provides compelling evidence that soil profile re-engineering can substantially improve crop productivity, N and K use efficiencies, and WUE in water-limited environments by simultaneously addressing multiple interacting soil constraints. Across two contrasting soil types\u0026mdash;an Arenosol and a Kurosol\u0026mdash; spanning the four-year time scale of this work, re-engineering treatments consistently delivered large and persistent gains in grain yield, WUE, and N and K uptake compared with conventional surface amelioration strategies. These improvements were underpinned by enhanced soil physicochemical properties (pH\u003csub\u003eCa\u003c/sub\u003e, CEC, SOC, and reduced soil strength) and the development of deeper, more continuous root systems that increased access to subsoil water, N and K.\u003c/p\u003e\u003cp\u003eThe durability of these benefits over four cropping seasons highlights the potential of integrated deep amelioration as a benchmark for next-generation soil management technologies. While full-profile re-engineering is currenty not economically feasible at farm scale, the insights gained here can inform the design of scalable interventions\u0026mdash;such as targeted deep placement of amendments or hybrid mechanical\u0026ndash;biological approaches\u0026mdash;that mimic the functional outcomes of re-engineering. Future research should focus on continuous assessment of SPR benefits, optimising these strategies for cost-effectiveness, assessing long-term carbon dynamics, and integrating biological enhancements to further improve resilience and sustainability in semi-arid cropping systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch4\u003eAcknowledgements\u003c/h4\u003e\n\u003cp\u003eThe authors gratefully acknowledge the Department of Primary Industries and Regional Development (DPIRD) and the Grains Research and Development Corporation (GRDC) for funding support through projects DAW1902_003RTX and SWAN DAW2407-001SPX. We thank the Syme and Fulwood families for providing field sites and for their ongoing cooperation throughout the experiments. We also acknowledge the valuable technical assistance of DPIRD staff, including Jenni Clausen, Dr Shahab Pathan, Alistair Hall, Shelley Hall, Joanne Walker, Dr Bidhyut Banik, Steve Rossi, and Trey Beeson. Guidance on experimental design and statistical analysis from Dr Andrew van Burgel is gratefully acknowledged. We further thank Chris Gazey, Dr Stephen Davies, and Tim Boyes (AgVivo) for their practical advice during the initial phase of the project. Finally, we appreciate the constructive internal review provided by Dr Ed Barrett-Lennard, Dr Geoff Anderson, and Sue Bestow before submission.\u003c/p\u003e\n\u003ch4\u003eConflict of Interest\u0026nbsp;\u003c/h4\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003ch4\u003eData availability\u003c/h4\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch4\u003eAuthor’s contribution\u003c/h4\u003e\n\u003cp\u003eGaus Azam: Fund sourcing, trial design, execution, data analysis and manuscript preparation.\u003c/p\u003e\n\u003cp\u003eKanchana Wickramarachchi: data collection, data analysis and manuscript preparation.\u003c/p\u003e\n\u003cp\u003eHasinur Rahman: data collection, data analysis and manuscript preparation.\u003c/p\u003e\n\u003cp\u003eMd Shahinur Rahman: data collection and manuscript preparation.\u003c/p\u003e\n\u003cp\u003eChad Reynolds: trial establishment and manuscript preparation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnderson GC, Fillery IRP, Dolling PJ, Asseng S (1998) Nitrogen and water flows under pasture-wheat and lupin-wheat rotations in deep sands in Western Australia. 1. Nitrogen fixation in legumes, net N mineralisation,and utilisation of soil-derived nitrogen. Aust J Agric Res 49(3):329\u0026ndash;344. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/A97141\u003c/span\u003e\u003cspan address=\"10.1071/A97141\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnderson GC, Pathan S, Easton J, Hall DJM, Sharma R (2020) Short- and Long-Term Effects of Lime and Gypsum Applications on Acid Soils in a Water-Limited Environment: 1. Grain Yield Response and Nutrient Concentration. Agronomy 10(8):1213\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnderson GC, Pathan S, Hall DJM, Sharma R, Easton J (2021) Short- and Long-Term Effects of Lime and Gypsum Applications on Acid Soils in a Water-Limited Environment: 3. Soil Solut Chem Agron 11(5):826\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnderson GC, Peverill KI, Brennan RF (2013) Soil sulfur\u0026mdash;crop response calibration relationships and criteria for field crops grown in Australia. Crop Pasture Sci 64(5):523\u0026ndash;530\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAngus JF, Grace PR (2017) Nitrogen balance in Australia and nitrogen use efficiency on Australian farms. Soil Res 55(6):435\u0026ndash;450. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/SR16325\u003c/span\u003e\u003cspan address=\"10.1071/SR16325\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G (2025) A method to re-engineer soils for quick amelioration of physical and chemical constraints - examples from an Arenosol and a Kurosol in Western Australia. Soil Research (under review)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G, Gazey C Re-engineering soil pH profiles to boost water use efficiency by wheat Paper presented at the Agronomy Australia Conference, Wagga W (2019) 25\u0026ndash;29 August 2019\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G, Gazey C (2021) Slow movement of alkali from surface-applied lime warrants the introduction of strategic tillage for rapid amelioration of subsurface acidity in south-western Australia. Soil Res 59(1):97\u0026ndash;106. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/SR19329\u003c/span\u003e\u003cspan address=\"10.1071/SR19329\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G, Gazey C, Davies S, Scanlan C (2022) Mind the depth of soil amelioration to surpass the yield gap in western Australia. Paper presented at the Australian Agronomy Conference, Toowoomba, Queensland, Australia, 18\u0026ndash;22 September 2022\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G, Rahman MS, Scanlan C, Rahman MH, Gazey R, Barrett-Lennard EG, Wickramarachchi K, Nixon B, Gazey C (2025) Deep Amelioration of Compaction and Acidity Doubled the Water Use Efficiency of Cereal Crops on a Sandy Soil in a Long-term Experiment in a Water-Limited Environment. Geoderma (under review)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G, Rahman MS, Scanlan C, Rahman MH, Gazey R, Gazey C (2024a) Soil Profile Re-engineering Doubled the Yield and Water Use Efficiency of Crops over Six Years on Acidic and Compacted Sand in a Water-limited Environment. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21203/rs.3.rs-4710141/v1\u003c/span\u003e\u003cspan address=\"10.21203/rs.3.rs-4710141/v1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Scientific Reports\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G, Rahman MS, Wickramarachchi K (2023) Strategic Tillage for Sustaining the Productivity of Broadacre Cropping in the Arid and Semi-Arid Regions of Southern Australia. In: Dr. Rodrigo De S (ed) Strategic Tillage and Soil Management - New Perspectives. IntechOpen, Rijeka, p Ch. 3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5772/intechopen.112875\u003c/span\u003e\u003cspan address=\"10.5772/intechopen.112875\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzam G, Wickramarachchi K, Scanlan C, Chen Y (2024b) Deep and continuous root development in ameliorated soil improves water and nutrient uptakes and wheat yield in water-limited conditions. Plant Soil 512:1405\u0026ndash;1420. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11104-024-07153-0\u003c/span\u003e\u003cspan address=\"10.1007/s11104-024-07153-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAziz M, Palta J, Siddique K, Sadras V (2017) Five decades of selection for yield reduced root length density and increased nitrogen uptake per unit root length in Australian wheat varieties. Plant Soil 413. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11104-016-3059-y\u003c/span\u003e\u003cspan address=\"10.1007/s11104-016-3059-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarrett-Lennard EG, George N, D\u0026rsquo;Antuono M, Holmes KW, Ward PR (2024) Rain and potential evapotranspiration are the main drivers of yield for wheat and barley in southern Australia: insights from 12 years of National Variety Trials. Crop Pasture Sci 75(6):\u0026ndash;. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/CP23320\u003c/span\u003e\u003cspan address=\"10.1071/CP23320\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarton L, Gleeson DB, Maccarone LD, Z\u0026uacute;\u0026ntilde;iga LP, Murphy DV (2013) Is liming soil a strategy for mitigating nitrous oxide emissions from semi-arid soils? Soil Biol Biochem 62:28\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2013.02.014\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2013.02.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBell R, Reuter D, Scott B, Sparrow L, Strong W, Chen tlW (2013) Soil phosphorus\u0026ndash;crop response calibration relationships and criteria for winter cereal crops grown in Australia. Crop Pasture Sci 64(5):480\u0026ndash;498. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1071/cp13016\u003c/span\u003e\u003cspan address=\"10.1071/cp13016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBell RW, de Oliveira TS (2022) Subsoil Constraints for Crop Production: Recent Advances, New Technologies, and Priorities for Further Research. Subsoil Constraints for Crop Production:397\u0026ndash;422\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBengough AG, McKenzie BM, Hallett PD, Valentine TA (2011) Root elongation, water stress, and mechanical impedance: a review of limiting stresses and beneficial root tip traits. J Exp Bot 62(1):59\u0026ndash;68. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jxb/erq350\u003c/span\u003e\u003cspan address=\"10.1093/jxb/erq350\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrennan RF, Bell MJ (2013) Soil potassium\u0026mdash;crop response calibration relationships and criteria for field crops grown in Australia. Crop Pasture Sci 64(5):514\u0026ndash;522\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBruun EW, Petersen CT, Hansen E, Holm JK, Hauggaard-Nielsen H (2014) Biochar amendment to coarse sandy subsoil improves root growth and increases water retention. Soil Use Manag 30(1):109\u0026ndash;118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/sum.12102\u003c/span\u003e\u003cspan address=\"10.1111/sum.12102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBusscher WJ, Bauer PJ, Frederick JR (2002) Recompaction of a coastal loamy sand after deep tillage as a function of subsequent cumulative rainfall. Soil Tillage Res 68(1):49\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0167-1987(02)00083-1\u003c/span\u003e\u003cspan address=\"10.1016/S0167-1987(02)00083-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eButler DG, Cullis BR, Gilmour A, Gogel R B, J (2018) ASReml-R 4 reference manual: mixed models for S language environments. Queensland Department of Primary Industries and Fisheries\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCui Z, Yan B, Gao Y, Wu B, Wang Y, Xie Y, Xu P, Wang H, Wen M, Wang Y, Ma X (2022) Crop yield and water use efficiency in response to long-term diversified crop rotations. Front Plant Sci Volume 13\u0026ndash;2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2022.1024898\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2022.1024898\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDamon PM, Azam G, Gazey C, Scanlan CA, Rengel Z (2022) Response of wheat to the geometry and proximity of lime slotting in an acidic soil profile. Soil Tillage Res 217:105269. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.still.2021.105269\u003c/span\u003e\u003cspan address=\"10.1016/j.still.2021.105269\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavies S, Betti G, Edwards T, McDonald G, Hall D, Anderson G, Scanlan C, Reynolds C, Walker J, Poulish G, Ward P (2019) Ten years of managing water repellent soils research in Western Australia\u0026ndash;a review of current progress and future opportunities. In: Proceedings of the 2019 GRDC Research Update, Perth, WA, pp 25\u0026ndash;26\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavies S, Parker W, Azam G, Hall D, Edwards T, Mwenda G, Reynolds C, McDonald G, Isbister B, Butler A, Scanlan C, Blake A, Newman P, Sands R, Ryan K, Curtis B, Bunny H, Gazey C (2024) Soil amelioration in Western Australian cropping systems: a review of thebenefits, adoption, and value. Paper presented at the Australian Agronomy Conference, Albany, Western Australia, 21\u0026ndash;24 October 2024\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGahoonia T, Ali R, Malhotra R, Jahoor A, Rahman M (2007) Variation in Root Morphological and Physiological Traits and Nutrient Uptake of Chickpea Genotypes. J Plant Nutr 30:829\u0026ndash;841. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/15226510701373213\u003c/span\u003e\u003cspan address=\"10.1080/15226510701373213\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGazey C, Azam G, Clausen J, Rengel Z (2019) Soil Quality: 4 Soil Acidity. Perth, WA\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGregory P (2006) Roots, rhizosphere and soil: The route to a better understanding of soil science? Eur J Soil Sci 57:2\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1365-2389.2005.00778.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2389.2005.00778.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHall DJM, Davies SL, Bell RW, Edwards TJ (2020) Soil Management Systems to Overcome Multiple Constraints for Dryland Crops on Deep Sands in a Water Limited Environment on the South Coast of Western Australia. Agronomy 10(12):1881\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHall DJM, Edwards TJ (2025) Trenching and compost sustain grain yield increases over nine years on deep sands but at a cost. Soil Res 63(3):\u0026ndash;. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/SR24221\u003c/span\u003e\u003cspan address=\"10.1071/SR24221\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHall DJM, Jones HR, Crabtree WL, Daniels TL (2010) Claying and deep ripping can increase crop yields and profits on water repellent sands with marginal fertility in southern Western Australia. Soil Res 48(2):178\u0026ndash;187. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/SR09078\u003c/span\u003e\u003cspan address=\"10.1071/SR09078\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarries M, Flower KC, Renton M, Anderson GC (2022) Water use efficiency in Western Australian cropping systems. Crop Pasture Sci 73(10):1097\u0026ndash;1117. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/CP21745\u003c/span\u003e\u003cspan address=\"10.1071/CP21745\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHorrocks A, Curtin D, Tregurtha C, Meenken E (2016) Municipal Compost as a Nutrient Source for Organic Crop Production in New Zealand. Agronomy 6(2):35\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoyle FC, D'Antuono M, Overheu T, Murphy DV (2013) Capacity for increasing soil organic carbon stocks in dryland agricultural systems. Soil Res 51(8):657\u0026ndash;667. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/SR12373\u003c/span\u003e\u003cspan address=\"10.1071/SR12373\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIsbell RF (2021) The Australian Soil Classification, 3 edn. CSIRO Publishing, Melbourne\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIsbister B, Rahman H, Azam G, Walker J, Kupsch M, Wilkins R (2024) To rip on or off the old rip line: a paddock-scale study on deep ripping and topsoil inclusion in a dry season. Paper presented at the GRDC Research Updates, Perth\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIslam N, Salim R (2012) Can R\u0026amp;D Investment Offset the Negative Impact. of Climate Change on Agricultural Productivity?\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKirkegaard JA, Peoples MB, Angus JF, Unkovich MJ (2011) Diversity and Evolution of Rainfed Farming Systems in Southern Australia. In: Tow P, Cooper I, Partridge I, Birch C (eds) Rainfed Farming Systems. Springer Netherlands, Dordrecht, pp 715\u0026ndash;754. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-1-4020-9132-2_26\u003c/span\u003e\u003cspan address=\"10.1007/978-1-4020-9132-2_26\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLauricella D, Butterly CR, Clark GJ, Sale PWG, Li G, Tang C (2020) Effectiveness of innovative organic amendments in acid soils depends on their ability to supply P and alleviate Al and Mn toxicity in plants. J Soils Sediments 20(11):3951\u0026ndash;3962. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11368-020-02721-0\u003c/span\u003e\u003cspan address=\"10.1007/s11368-020-02721-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLawes R, Chen C, Whish J, Meier E, Ouzman J, Gobbett D, Vadakattu G, Ota N, van Rees H (2021) Applying more nitrogen is not always sufficient to address dryland wheat yield gaps in Australia. Field Crops Res 262:108033. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fcr.2020.108033\u003c/span\u003e\u003cspan address=\"10.1016/j.fcr.2020.108033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi GD, Conyers MK, Helyar KR, Lisle CJ, Poile GJ, Cullis BR (2019) Long-term surface application of lime ameliorates subsurface soil acidity in the mixed farming zone of south-eastern Australia. Geoderma 338:236\u0026ndash;246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.geoderma.2018.12.003\u003c/span\u003e\u003cspan address=\"10.1016/j.geoderma.2018.12.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLynch JP (2019) Root phenotypes for improved nutrient capture: an underexploited opportunity for global agriculture. New Phytol 223(2):548\u0026ndash;564. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/nph.15738\u003c/span\u003e\u003cspan address=\"10.1111/nph.15738\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcQuaker NR, Brown DF, Kluckner PD (1979) Digestion of environmental materials for analysis by inductively coupled plasma-atomic emission spectrometry. Anal Chem 51:1082\u0026ndash;1084\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMusei SK, Kuyah S, Nyawira S, Ng\u0026rsquo;ang\u0026rsquo;a SK, Karugu WN, Smucker A, Nkurunziza L (2024) Sandy soil reclamation technologies to improve crop productivity and soil health: a review. Front Soil Sci Volume 4\u0026ndash;2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fsoil.2024.1345895\u003c/span\u003e\u003cspan address=\"10.3389/fsoil.2024.1345895\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOliver YM, Robertson MJ, Stone PJ, Whitbread A (2009) Improving estimates of water-limited yield of wheat by accounting for soil type and within-season rainfall. Crop Pasture Sci 60(12):1137\u0026ndash;1146. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/CP09122\u003c/span\u003e\u003cspan address=\"10.1071/CP09122\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePeel MC, Finlayson BL, McMahon TA (2007) Updated world map of the K\u0026ouml;ppen-Geiger climate classification. Hydrol Earth Syst Sci 11(5):1633\u0026ndash;1644. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5194/hess-11-1633-2007\u003c/span\u003e\u003cspan address=\"10.5194/hess-11-1633-2007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR-Core-Team (2025) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRayment GE, Lyons DJ (2011) Soil chemical methods: Australasia. CSIRO Publishing, Collingwood, Australia\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRengel Z (2003) Handbook of Soil Acidity. Marcel Dekker, New York, USA\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRiaz M, Marschner P (2020) Sandy Soil Amended with Clay Soil: Effect of Clay Soil Properties on Soil Respiration, Microbial Biomass, and Water Extractable Organic C. J Soil Sci Plant Nutr 20(4):2465\u0026ndash;2470. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s42729-020-00312-z\u003c/span\u003e\u003cspan address=\"10.1007/s42729-020-00312-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoper MM, Davies SL, Blackwell PS, Hall DJM, Bakker DM, Jongepier R, Ward PR (2015) Management options for water-repellent soils in Australian dryland agriculture. Soil Res 53(7):786\u0026ndash;806. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/SR14330\u003c/span\u003e\u003cspan address=\"10.1071/SR14330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSadras VO, Angus JF (2006) Benchmarking water-use efficiency of rainfed wheat in dry environments. Aust J Agric Res 57(8):847\u0026ndash;856. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/AR05359\u003c/span\u003e\u003cspan address=\"10.1071/AR05359\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScanlan C, Malik R, Easton J, Gherardi M, Rengel Z, Bell R, Boitt G, Ma Q (2022) Optimising fertiliser application \u0026ndash; what level of precision can we achieve? Paper presented at the Grain Research and Development Corporation - Updates, Perth\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchmittmann O, Christ A, Schulze Lammers P (2021) Subsoil Melioration with Organic Material\u0026mdash;Principle, Technology and Yield Effects. Agronomy 11(10):1970\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchneider F, Don A, Hennings I, Schmittmann O, Seidel SJ (2017) The effect of deep tillage on crop yield \u0026ndash; What do we really know? Soil Tillage Res 174:193\u0026ndash;204. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.still.2017.07.005\u003c/span\u003e\u003cspan address=\"10.1016/j.still.2017.07.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith LJ, Scarisbrick DH (1990) Reproductive Development in Oilseed Rape (Brassica napus cv. Bienvenu). Ann Botany 65(2):205\u0026ndash;212\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUddin S, L\u0026ouml;w M, Parvin S, Fitzgerald G, Bahrami H, Tausz-Posch S, Armstrong R, O\u0026rsquo;Leary G, Tausz M (2018) Water use and growth responses of dryland wheat grown under elevated [CO2] are associated with root length in deeper, but not upper soil layer. Field Crops Res 224:170\u0026ndash;181. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fcr.2018.05.014\u003c/span\u003e\u003cspan address=\"10.1016/j.fcr.2018.05.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnkovich M, McKenzie D, Parker W (2023) New insights into high soil strength and crop plants; implications for grain crop production in the Australian environment. Plant Soil 486(1):183\u0026ndash;208. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11104-022-05862-y\u003c/span\u003e\u003cspan address=\"10.1007/s11104-022-05862-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Gool D (2016) Identifying soil constraints that limit wheat yield in South-West Western Australia. Perth\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWasson AP, Richards RA, Chatrath R, Misra SC, Prasad SVS, Rebetzke GJ, Kirkegaard JA, Christopher J, Watt M (2012) Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops. J Exp Bot 63(9):3485\u0026ndash;3498. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jxb/ers111\u003c/span\u003e\u003cspan address=\"10.1093/jxb/ers111\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWeaver DM, Neville S, Deeley DM (2005) Addressing off-site nutrient pollution through conventional management actions: a modelling case study. Australasian J Water Resour 8(2):165\u0026ndash;177. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13241583.2005.11465253\u003c/span\u003e\u003cspan address=\"10.1080/13241583.2005.11465253\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickramarachchi K, Azam G (2024) Fertiliser strategies to boost crop yield in re-engineered soil profiles. Paper presented at the Australian Agronomy Conference, Albanry, Western Australia, October 2024\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickramarachchi K, Azam G (2025) Improving Barley (Hordeum vulgare L.) Yield through Deeper Root Architecture Impacted by Nitrogen Management in a Reengineered Kurosol. Soil Research (under review)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickramarachchi K, Betti G, Azam G (2025a) Effect of Clay Amendment and Strategic Deep Tillage on Soil Water Dynamics and Plant Growth Under Controlled Environments. Plants (Basel) 14(5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/plants14050799\u003c/span\u003e\u003cspan address=\"10.3390/plants14050799\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickramarachchi K, Chen Y, Azam G (2025b) Reengineering a compacted acidic coarse sand enhanced the root architecture and yield of triticale (x Triticosecale) \u0026ndash; A. Soil Columns Study Plant and Soil (accepted)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu M, Chen L, Chen S, Chen Y, Ma J, Zhang Y, Pang D, Li X (2024) Soil microbial carbon and nitrogen limitation constraints soil organic carbon stability in arid and semi-arid grasslands. J Environ Manage 373. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jenvman.2024.123675\u003c/span\u003e\u003cspan address=\"10.1016/j.jenvman.2024.123675\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14(6):415\u0026ndash;421. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-3180.1974.tb01084.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3180.1974.tb01084.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Grains Research and Development Corporation","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Subsoil acidity, soil compaction, soil strength, water use efficiency, dryland cropping, water-limited yield potential","lastPublishedDoi":"10.21203/rs.3.rs-8297071/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8297071/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eContext\u003c/p\u003e\u003cp\u003eSoil constraints, including subsoil acidity, compaction, and low fertility, limit crop productivity and water-use efficiency (WUE) in Western Australia (WA) and around the world. Conventional amelioration offers slow or short-lived benefits. Soil profile re-engineering (SPR), involving deep mixing with amendments to 80 cm depth, may address multiple constraints, but the longevity of its productivity benefits and economic outcomes remain poorly understood.\u003c/p\u003e\u003cp\u003eAim\u003c/p\u003e\u003cp\u003eThis study assessed the persistence of soil improvements and crop responses to soil re-engineering across four cropping seasons under variable rainfall.\u003c/p\u003e\u003cp\u003eMethods\u003c/p\u003e\u003cp\u003eEight treatments, including an untreated control, shallow surface amendments, and four re-engineering approaches, were evaluated in a partially randomised block design on two contrasting soils: an Arenosol and a Kurosol in the central wheatbelt of WA. Measurements included soil physicochemical properties, grain yield, WUE, and N and K uptake.\u003c/p\u003e\u003cp\u003eKey results\u003c/p\u003e\u003cp\u003eAll SPR treatments involving soil loosening and incorporation of lime substantially increased pH\u003csub\u003eCa\u003c/sub\u003e and cation exchange capacity (CEC) and reduced soil strength, while clay addition enhanced volumetric water content, and addition of compost increased soil organic carbon (SOC) throughout the profile. Grain yield increased by up to 432% and WUE by up to 9.8 kg mm⁻\u0026sup1; relative to the control, whereas shallow incorporation treatments produced no or minimal yield and WUE gains depending on the soil types, amendments, and crop types. Yield responses to SPR were consistent across seasons, crops, and soil types. N and K uptake increased proportionally with yield. Regression tree analysis identified changes in CEC, SOC, and soil strength as the dominant predictors of yield improvement (explaining up to 80.4% of variance) across both soils. Clay addition was the primary driver of yield gains in the Arenosol, whereas increases in pH\u003csub\u003eCa\u003c/sub\u003e were more influential in the Kurosol. Benefits from SPR persisted for at least four cropping seasons and are expected to continue for several years.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions and\u003c/b\u003e i\u003cb\u003emplications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAlthough soil profile re-engineering may not be economically scalable at present, it provides a valuable benchmark for designing targeted, cost-effective amelioration strategies to enhance the resilience and productivity of rainfed cropping system in semi-arid environments in WA.\u003c/p\u003e","manuscriptTitle":"Benchmarking crop performance following soil profile re-engineering: four-year field studies in an Arenosol and a Kurosol of Western Australia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-09 09:15:42","doi":"10.21203/rs.3.rs-8297071/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e6cced30-6f38-4cfe-b593-ceed49520216","owner":[],"postedDate":"December 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59215198,"name":"Agricultural Engineering"}],"tags":[],"updatedAt":"2025-12-09T09:15:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-09 09:15:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8297071","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8297071","identity":"rs-8297071","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}