Circular Valorization of Pulp and Paper Mill Biosolids for Sustainable Soil Management and Crop Production in Cold-Region Agroecosystems

Circular Valorization of Pulp and Paper Mill Biosolids for Sustainable Soil Management and Crop Production in Cold-Region Agroecosystems | 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 Circular Valorization of Pulp and Paper Mill Biosolids for Sustainable Soil Management and Crop Production in Cold-Region Agroecosystems Emmanuel A. Badewa, Yifan Song, Xinran Duan, Patrick Levasseur, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8232268/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 Sustainable valorization of pulp and paper mill biosolids (PPMB) can improve soil fertility and reduce reliance on synthetic fertilizers in cold-region agriculture. This two-year field study assessed PPMB as a soil amendment for canola ( Brassica napus L.) and wheat ( Triticum aestivum L. ) in Northern Manitoba, Canada. Six treatments; control, urea, mixed PPMB, and three PPMB–urea combinations; were tested in a randomized complete block design. PPMB application reduced soil bulk density by 15-20% compared to urea and increased soil organic carbon by up to 21% under mixed PPMB. Microbial respiration responses were variable, and yield outcomes for both crops were comparable to or higher than urea. Redundancy analysis showed positive links between improved soil attributes and yield. The findings indicated that PPMB can sustain crop production and improve soil health in cold climates, supporting circular bioeconomy applications in northern agriculture. Renewable Resources Agroecology Agronomy Forestry Pulp and paper biosolids Soil health Sustainable soil amendment Circular economy Cold-climate agriculture Biosolid valorization Figures Figure 1 Figure 2 Figure 3 Figure 4 Highlights • Biosolids from pulp mills improved soil health in cold-region agroecosystems. • Combined pulp and paper mill biosolids (PPMB) and urea treatments maintained or increased wheat and canola yields. • Field trial confirms PPMB can reduce inorganic N fertilizer needs by up to 50%. • PPMB improved soil pH, N, and P, with no metal or pathogen buildup detected post-application. • Application of PPMB supports circular economy policies for nutrient recycling and waste valorization in agriculture. 1.0 Introduction Industrial waste disposal and nutrient losses from agricultural systems remain pressing global environmental challenges (Koul et al., 2022 ; Kumar et al., 2025 ). Across multiple sectors, the need to transform waste streams into resources has become central to advancing sustainable development and mitigating pollution (Roy et al., 2023 ; Chenavaz and Dimitrov, 2024 ; Manisha et al., 2025 ). In particular, the pulp and paper industry generates approximately 100 tonnes of organic residuals, including primary and secondary pulp and paper mill biosolids (PPMB), per 550 tonnes of pulp produced as by-products of effluent treatment processes (Haile et al., 2021 ). Historically, concerns over organochlorines and heavy metals limited the reuse potential of PPMB (Koistinen et al., 1994 ). However, technological advances in the late 1980s which use chlorine dioxide rather than elemental chlorine have largely eliminated such contaminants (Turner et al., 2022 ). Modern PPMB now contains partially decomposed organic matter derived from woody biomass, along with essential plant nutrients such as nitrogen (N) and phosphorus (P), but with low concentrations of metals and persistent organic pollutants (Krigstin, 2008 ; Bajpai, 2015 ; Manirakiza et al., 2025 ). Despite this, disposal practices such as landfilling and incineration persist, contributing to greenhouse gas emissions, soil degradation, and escalating operational costs (Bajpai, 2015 ; Sebastian and Louis, 2022 ). Pulp and paper mill biosolids recycling offers a viable route toward resource recovery and supports the principles of a circular economy (Hasan et al., 2025 ). The application of PPMB to agricultural soils can close nutrient loops by substituting inorganic fertilizers, improving soil organic matter, and enhancing nutrient retention (Ziadi et al., 2013 ; Gagnon et al., 2021 ; Tough, 2025 ). Nonetheless, the diversity of both soil properties and biosolid compositions across regions and production systems complicates generalization (Nunes et al., 2008 ; Gagnon et al., 2021 ; Chigbo et al., 2022 ). Primary PPMB, sourced from effluent clarification, typically exhibit high carbon-to-nitrogen (C/N) ratios that may immobilize soil N (Turner et al., 2022 ). Nitrogen immobilization occurs when soil microbes utilize available nitrogen to decompose carbon-rich organic matter, temporarily reducing N availability to plants. In contrast, secondary PPMB from aerobic treatment processes have lower C/N ratios and higher P availability, potentially enhancing crop productivity (Gagnon and Ziadi, 2020 ). Although various trials have demonstrated agronomic benefits from PPMB (e.g., Nunes et al., 2008 ; Gagnon et al., 2010 ; Gagnon and Ziadi, 2021 ), relatively few studies have explicitly assessed PPMB use in combination with reducing inorganic fertilizer rates, a key strategy to lower inorganic fertilizer dependency while maintaining yields. Moreover, an important knowledge gap persists regarding the field-scale evaluation of PPMB amendments in cold-region agroecosystems, such as the subarctic farming zones of northern Canada. Soils in these environments, including Rego Gleysols, are often poorly drained and sensitive to nutrient losses due to short growing seasons and prolonged snow cover (Ehrlich et al., 1960 ; Hopkins and Smith, 1982 ). Limited research has addressed how PPMB perform under these conditions, particularly in terms of soil health outcomes and crop yield responses. The objective of this study was to evaluate the impact of PPMB applications alone and in combination with reduced rates of inorganic N fertilizer on soil health indicators and crop yield performance in canola ( Brassica napus L.) and wheat ( Triticum aestivum L.). We conducted a fully replicated, randomized block field trial in the Carrot River agricultural region near The Pas, Manitoba, using six treatments: a control, inorganic N fertilizer (urea), mixed PPMB (a combination of primary and secondary biosolids), and three additional urea-PPMB blends, each formulated to provide 50:50 N contributions from urea and either primary, secondary, or mixed PPMB sources. Specifically, we aimed to determine whether PPMB based amendments can sustain or enhance crop yields while improving soil physical, chemical, and biological properties compared to conventional inorganic fertilizer practices. We hypothesized that (i) PPMB-based application would improve soil properties, including bulk density, nutrient availability, and microbial activity, relative to unamended and inorganic fertilizer-only controls; and (ii) crop yields under PPMB-based treatments would be comparable to or exceed those of these controls, thereby supporting PPMB use as a partial substitute for conventional nutrient inputs in cold-region cropping systems. 2.0 Materials and Methods 2.1. Experimental study area and design The field trial was conducted during the 2023 and 2024 growing seasons, from late May to mid-September, at Round the Bend Farm, in the Carrot River Valley near The Pas, Manitoba, Canada (53°44′12.2″N, 101°38′54.3″W). The soil at the site is classified as a Rego Gleysol of the Pasquia series, characterized by peaty calcareous properties with modest B horizon development and a silty clay loam texture. The baseline soil pH was 6.9, with a total N content of 0.8% at 0–20 cm depth. Additional baseline soil properties are presented in Table S1. The region experiences a subarctic climate, marked by a short growing season and high soil moisture retention due to low evapotranspiration. The site had been previously maintained under perennial grass cover used for bison grazing. A randomized complete block design (RCBD) with four replicates per treatment was employed. The experimental field (50 × 50 m) was divided into two adjacent sections; each planted with either canola or wheat. Each section contained 24 plots (3 × 9 m) separated by 2 m buffer strips (Fig. 1 ). Six treatments were applied in each crop section: (i) Control (no amendment); (ii) Urea fertilizer; (iii) Secondary PPMB + 50% urea (SecBioUrea); (iv) Mixed PPMB + 50% urea (MixedBioUrea); (v) Primary PPMB + 50% urea (PriBioUrea); and (vi) 100% mixed PPMB (MixBio) (Fig. 1 ). The PPMB application rates were calculated based on crop N requirements and an assumed N efficiency coefficient of 0.25, in compliance with the Tri-Provincial Manure Application Guidelines (2003) to meet metal loading limits (Table S2). 2.2. Biosolids characteristics and crop management The biosolids were sourced from Canadian Kraft Paper (CKP) in The Pas, Manitoba, and included both primary and secondary PPMB streams, blended at specified ratios. Prior to application, PPMB were analyzed for compositional characteristics (Table 1 ). Secondary PPMB contained higher total organic carbon (33.3%) and N (1.22%) than primary PPMB (22.5% and 0.5%), resulting in a lower C:N ratio (27.0 vs. 43.9). Electrical conductivity was also higher in secondary PPMB (2.79 dS/m), compared to primary PPMB (2.22 dS/m). Secondary PPMB had markedly greater concentrations of phosphorus, nitrate-N, and trace elements including Zn, Cd, and Cu, compared to primary PPMB (Table 1 ). All PPMB originated from a composted source (minimum two years) and were routinely screened for pathogens and trace metals to ensure compliance with the Canadian Council of Ministers of the Environment (CCME) guidelines for land application. Application permits were obtained from the Manitoba Environment and Climate Change. Certified crop varieties commonly adopted in northern Manitoba were selected: canola (‘TrueFlex’) and wheat (‘AAC Brandon’). Seeding was performed using a hand-push seeder. The PPMB and urea fertilizers were manually broadcast and incorporated within one hour to a depth of 10 cm using a rototiller. Weed control was implemented using Roundup WeatherMAX (glyphosate) for canola and MCPA Ester 600 herbicide for wheat, following standard agronomic practice. Table 1 Physicochemical properties of pulp and paper mill biosolids (PPMB). Chemical Properties Primary Biosolids Secondary Biosolids pH 7.5 7.1 EC (dS/m) 2.2 2.8 Total organic C (%) 22.5 33.3 Total N (%) 0.5 1.2 C/N ratio 43.9 27.0 Ammonium (mg/kg) 8.7 3.5 Nitrate (mg/kg) 3.5 90.9 Phosphorus (mg/kg) 83.9 101.0 Phosphorus (mg/kg) 811.5 3360.0 Potassium (mg/kg) 196.0 99.0 Magnesium (mg/kg) 188.0 128.0 Arsenic (mg/kg) 0.9 2.0 Cadmium (mg/kg) 0.4 6.0 Cobalt (mg/kg) 2.5 4.0 Chromium (mg/kg) 51.3 43.9 Copper (mg/kg) 11.9 84.8 Lead (mg/kg) 4.7 12.0 Mercury (mg/kg) 0.0 0.1 Molybdenum (mg/kg) 3.5 4.8 Nickel (mg/kg) 31.9 41.9 Selenium (mg/kg) 0.4 0.7 Zinc 60.8 879 2.3. Soil sampling and properties Soil samples were collected at harvest in September 2023 and 2024. Composite samples were collected from depths of 0–10 cm and 10–20 cm. Soil bulk density and porosity were determined using a core sampling method (McKenzie et al., 2002 ). A cylindrical core (inner diameter: 4.5 cm; height: 5.1 cm) was inserted into the soil to extract undisturbed samples. The soil cores were oven-dried at 105°C for 48 hours, and bulk density was calculated as the dry weight divided by the core volume. Porosity was estimated using the bulk density and assuming a particle density of 2.65 g cm − 3 . Gravimetric water content was determined by weighing the cores before and after drying, and volumetric water content (VWC) was obtained by multiplying gravimetric water content by bulk density. Water-filled pore space (WFPS) was calculated as the ratio of VWC to total porosity, expressed as a percentage. Water-stable aggregate (WSA) was assessed using a wet sieving procedure (Kemper and Rosenau, 1986 ). Air-dried soil samples were first sieved to obtain 1–2 mm aggregates, and a 4 g subsample was wet sieved using a wet sieving apparatus (Eijkelkamp, Netherlands). Soil texture was determined using the hydrometer method (Gee and Or, 2002 ). Soil pH was measured using a 1:2 soil to 0.01 M CaCl 2 extraction (McLean, 1982 ; Miller and Kissel, 2010 ). Ammonium (NH 4 + ) and nitrate (NO 3 − ) concentrations were extracted with 2 M KCl and analyzed using colorimetric method (Maynard et al., 2008 ). Plant-available phosphorus (PO 4 − P) was extracted using the Olsen method and analyzed using colorimetric method (Ashworth and Mrazek, 1995 ). Cation exchange capacity (CEC) was determined by ammonium extraction followed by colorimetric quantification (Hendershot et al., 2007 ). Total organic carbon (C), and total N in both plant and soil samples were measured by dry combustion method (Soil Science Society of America, 1996 ; Schumacher, 2002 ). Total elemental concentrations in the soil and plant were determined via inductively coupled plasma optical emission spectrometry (ICP-OES) following HNO₃ digestion and Mehlich-3 extraction (Skoog et al., 2007 ; EPA, 2023). Soil microbial activity was assessed using a 24h in-vitro soil microbial respiration assay (following Noyce et al. 2016 ). 2.4. Crop yield and nitrogen efficiency indicators Plant biomass samples were harvested from a 1 m² area in each treatment replicate plot. Plots were harvested manually by cutting full stems at the soil surface. Grain yield was determined using head/pod count, grain number per head or pod, and 100-grain weight (0.4 g for canola and 3.4 g for wheat) (Agriculture Victoria, 2010 ). Grain yield data were analyzed by treatment, crop, and year. Nitrogen performance indicators were calculated using the following according to Dobermann ( 2007 ): Nitrogen Use Efficiency, NUE (expressed as partial factor productivity of nitrogen, PFP-N); Total yield per unit of N applied; Eq. ( 1 ), Nitrogen Response (NR); Yield gain from N application; Eq. ( 2 ), Agronomic Efficiency (AE) (also called yield-based NUE); Incremental yield per unit N applied; Eq. ( 3 ). $$\:NUE\:(\text{P}\text{F}\text{P}-\text{N})=\:\frac{{Y}_{N}\:}{{N}_{applied}}$$ 1 $$\:NR=\:{Y}_{N}-\:{Y}_{0}$$ 2 $$\:AE=\:\frac{{Y}_{N}-\:{Y}_{0}\:}{{N}_{applied}}$$ 3 Where Y N : Yield with nitrogen application (kg ha − 1 )​, Y 0 : Yield without nitrogen (control) (kg ha − 1 ), N applied : Amount of nitrogen applied (kg ha − 1 ). 2.5. Integrated Soil Health Evaluation Soil health was assessed using a combined approach of multivariate soil analysis and crop performance metrics to evaluate how soil conditions and management treatments influence productivity and plant nutrient status, thereby supporting balanced agronomic decision-making (Toor et al., 2021 ; Badewa et al., 2024 ). Indicators were selected for their responsiveness to short-term management, measurability, and soil ecosystem functional relevance (Bünemann et al., 2018). The soil health evaluation followed a three-step procedure: Step 1: Redundancy Analysis (RDA). Redundancy analysis was performed on standardized soil datasets to identify the principal gradients of soil variability attributable to treatment effects (Souza, 2025 ). Mean RDA scores from the first two canonical axes were calculated for each treatment and used as indicators of treatment-induced soil variability. Step 2: Relationship Between Soil Conditions and Crop Performance . Multiple linear regression models were employed to examine the associations between soil conditions and crop performance, using the RDA scores (axes 1 and 2) as explanatory variables. Crop yield and nutrient concentration served as the response variables in the models (Marcis and Salvatore, 2020 ). Step 3: Soil Health Score (SHS) Calculation and Classification . A Soil Health Score was derived by computing the equally weighted average of the first two RDA scores, standardizing them as z-scores (mean = 0, standard deviation = 1), and transforming the result to a 0-100 scale for interpretability (Zhang et al., 2024 ). Based on fixed z-score thresholds, treatments were categorized into four soil health classes: Very High (Z > 1; SHS > 90), High (0 < Z ≤ 1; SHS ≈ 70), Moderate (− 1 < Z ≤ 0; SHS ≈ 50), and Low (Z ≤ − 1; SHS ≈ 30) (Wu and Congreves, 2021 ). 2.6. Data Analysis All data processing and statistical analyses were performed using R v. 4.4.3 (R Core Team, 2025). Prior to analysis, all soil and crop data were assessed for normality using the Shapiro-Wilk test. Variables that violated the normality assumption were subjected to log or Box-Cox transformations (λ = 0.5) using the MASS package to improve homoscedasticity and model fit. Four-way analysis of variance (ANOVA) was employed to evaluate the effects of treatment, year, depth, and crop type, including their interactions. When significant main or interaction effects were detected (p < 0.05), Tukey’s Honestly Significant Difference (HSD) post-hoc test was used to identify statistically significant pairwise differences among treatments within each depth and crop type. Redundancy Analysis (RDA) was conducted to explore multivariate responses of soil health indicators to treatments and to examine the relationships between soil properties and crop performance. RDA was implemented using the vegan package in R . RDA biplots were generated to visualize the directional influences of treatments and indicator variables. 3.0 Results 3.1. Soil properties 3.1.1. Physical soil properties Bulk density ranged from 0.28 to 1.29 g cm − 3 across treatments and depths (Table S3). Statistically significant effects were observed for crop (F = 21.4, p < 0.001) and depth (F = 67.2, p 0.05). Similarly, total porosity varied between 51.3% and 89.5%, with significant differences by crop and depth ( p < 0.001), but no treatment effects were detected. Volumetric water content and water-filled pore space (WFPS) were significantly influenced by crop (F = 43.5 and 42.8, respectively) and depth (F = 17.7 and 33.6, respectively) ( p < 0.001), with no significant treatment or interaction effects (Table S3). Aggregate stability ranged from 35.1% to 98.5%, with significant effects attributed to crop (F = 8.6, p < 0.01) and depth (F = 30.1, p < 0.001). 3.1.2. Chemical soil properties Soil pH was significantly affected by treatment (F = 4.2, p < 0.01), crop (F = 5.6, p < 0.05), and year (F = 5.7, p < 0.05), with no significant interaction terms (Fig. 2 a-b; Table S3). Nitrate concentrations varied significantly across treatment, crop, and year, and exhibited significant two-way interactions: treatment × crop (F = 3.6, p < 0.01), treatment × year (F = 3.2, p < 0.01), and crop × year (F = 44.3, p < 0.001). In year 1, treatment effects were detected in canola at both 0–10 cm and 10–20 cm depths (Control vs. Urea; PriBioUrea, MixBioUrea vs. Urea), and in wheat at 0–10 cm (MixBio vs. MixBioUrea) and 10–20 cm (MixBio vs. MixBioUrea, Urea) (Fig. 2 c-d; Table S3). Total C showed significant effects of treatment and depth (Fig. 2 e-f; Table S3). In year 2, treatment effects were observed in canola at 0–10 cm (Control, Urea vs. MixBio), while no treatment effect was found in wheat. Calcium (Ca) levels showed significant treatment effects in year 1 for canola at both depths and in wheat at 0–10 cm, with no significant effects at 10–20 cm (Fig. 2 g-h; Table S3; p < 0.05). Ammonium (NH 4 + ) concentrations exhibited a significant three-way interaction between crop, depth, and year (F = 67.5, p 0.05). Available phosphorus (P) concentrations varied significantly with depth (F = 57.7, p < 0.001) and treatment (F = 8.1, p < 0.001), particularly between Control, Urea, and MixBio. Cation exchange capacity (CEC) was significantly influenced by depth (F = 34.8, p 0.05) (Table S3). Iron (Fe) concentrations showed a significant depth × year interaction (F = 46.0, p < 0.001) and a main effect of treatment ( p < 0.05) (Table S3). In year 1, Fe was significantly affected in wheat at 10–20 cm (Control vs. MixBio), with no significant differences observed in canola (Fig. 2 i-j). Manganese (Mn) concentrations varied significantly by treatment, crop, and year, with multiple interaction effects: treatment × crop (F = 3.0, p < 0.05), treatment × depth (F = 2.5, p < 0.05), treatment × year (F = 10.0, p < 0.001), and crop × year (F = 31.0, p < 0.001) (Table S3). Treatment effects on Mn were particularly evident in year 1 in canola at both depths and in wheat at both depths (Fig. 2 k-l). Sodium (Na) showed a significant depth × year interaction (F = 6.0, p < 0.05), with treatment differences at 0–10 cm (Control, Urea vs. PriBioUrea) (Fig. 2 m-n). Zinc (Zn) concentrations exhibited significant interactions: treatment × year (F = 7.8, p < 0.001), crop × year (F = 8.8, p < 0.01), and depth × year (F = 5.1, p < 0.05) (Table S3). In year 1, Zn was significantly influenced by treatment in canola at both depths and in wheat across both depth intervals (Fig. 2 o-p). Nickel concentrations were significantly influenced by interactions between treatment × year (F = 3.3, p < 0.01), crop × year (F = 18.6, p < 0.001), and depth × year (F = 61.1, p < 0.001), alongside main effects of treatment, crop, and depth (Table S3; p < 0.05). Sulphur concentrations varied significantly with treatment (F = 11.7, p < 0.01) and depth (F = 8.1, p < 0.01), while interaction effects were not significant (Table S3). 3.1.3. Soil biological activity Soil microbial respiration was significantly influenced by treatment, crop, and depth, particularly in the 24-hour incubation assay (Table S3). A significant interaction between treatment and crop was detected (F = 3.4, p < 0.01), with a main treatment effect ( p < 0.05). Across both years and depths, MixBio and MixBioUrea treatments consistently showed the highest soil microbial respiration compared to the control (Fig. 2 q-r). In canola, SecBioUrea exhibited the greatest soil microbial respiration at 10–20 cm in both years ( p < 0.05) (Fig. 2 q). In wheat, although not statistically significant, PriBioUrea showed a tendency to enhance microbial activity in year 2 across both depth intervals (Fig. 2 r). 3.2. Crop productivity and nutrient utilization dynamics 3.2.1. Crop yield response Treatment had a statistically significant effect on crop yield across both crop types (F = 5.4, p 0.05). In year 1, canola yields ranged from 1.1 ± 0.2 t ha − 1 in the Control to 3.0 ± 0.5 t ha − 1 under the SecBioUrea treatment, representing a 173% increase over the unfertilized control (Table 2 ). Intermediate yields were observed under MixBioUrea (2.1 ± 0.2 t ha − 1 ) and PriBioUrea (2.3 ± 0.1 t ha − 1 ) (Table 2 ). In year 2, treatment differences in canola yield were not statistically significant ( p > 0.05), with yields ranging from 1.6 ± 0.3 to 3.1 ± 0.4 t ha − 1 (Table 2 ). In wheat, yield responses were generally lower and showed no statistically significant treatment effects in either year ( p > 0.05; Table 2 ). In year 1, the highest mean wheat yield (3.0 ± 0.4 t ha − 1 ) was observed under SecBioUrea, while the Control was 1.7 ± 0.5 t ha − 1 (Table 2 ). However, high variability across treatments and years precluded consistent statistical significance. These results suggest that while canola yield responded positively to treatment, particularly in year 1, wheat yield was less responsive and more variable across years. Table 2 Crop yield (tonnes ha − 1 ) for canola and wheat under different treatments. Values are means ± standard error (n = 4). Treatments sharing the same letter within a depth are not significantly different ( p > 0.05). Treatment Canola (tonnes/ha) Wheat (tonnes/ha) Year 1 Year 2 Year 1 Year 2 Control 1.1 ± 0.2a 1.6 ± 0.3a 1.7 ± 0.5a 1.6 ± 0.1a Urea 1.2 ± 0.2a 2.2 ± 0.5a 2.6 ± 0.5a 1.8 ± 0.2a SecBioUrea 3.0 ± 0.5c 3.1 ± 0.4a 3.0 ± 0.4a 2.1 ± 0.1a MixBioUrea 2.1 ± 0.2bc 2.3 ± 0.4a 3.0 ± 0.5a 1.8 ± 0.1a PriBioUrea 2.3 ± 0.1bc 1.9 ± 0.6a 2.0 ± 0.5a 1.8 ± 0.3a MixBio 1.7 ± 0.0ab 1.9 ± 0.6a 2.3 ± 0.4a 1.7 ± 0.2a 3.2.2. Nitrogen use efficiency indices Nitrogen use efficiency, NR, and AE varied substantially among treatments and between crops (Table 3 ). In canola, NUE ranged from 2.8 ± 0.1 kg grain kg − 1 N under the MixBio treatment to 13.1 ± 0.6 kg grain kg − 1 N under SecBioUrea. SecBioUrea also obtained the highest AE (5.8 ± 1.9 kg grain kg − 1 N), outperforming other PPMB-based treatments including MixBioUrea (2.3 ± 1.8) and PriBioUrea (0.8 ± 3.5) (Table 3 ). Although Urea exhibited a relatively high AE (9.5 ± 8.0), this estimate was accompanied by high variability and lower NR compared to biosolid-urea blends. In wheat, Urea achieved the highest NUE (32 ± 3.5 kg grain kg − 1 N) and AE (6.9 ± 2.5), likely due to the lower N application rate (56.0 kg ha − 1 ). Among PPMB based treatments, SecBioUrea again demonstrated superior efficiency, with an NUE of 15.6 ± 0.4 and AE of 4.2 ± 0.7. MixBioUrea and PriBioUrea yielded moderate AE values of 1.6 ± 0.8 and 1.3 ± 1.8, respectively (Table 3 ). Nitrogen response followed similar trends. In canola, SecBioUrea achieved the highest NR (1,488 kg ha − 1 ), exceeding Urea (639 kg ha − 1 ) and all other treatments. In wheat, MixBioUrea and SecBioUrea observed NR values above 500 kg ha − 1 , suggesting moderate responsiveness to fertilization despite greater inter-treatment variability. Collectively, these findings indicate that co-application of secondary PPMB with urea enhanced N recovery and productivity in canola and provided comparable N efficiency to inorganic N fertilizers in wheat, although with crop-specific and interannual variation. Table 3 Nitrogen use efficiency (NUE), nitrogen response (NR), and agronomic efficiency (AE) of canola and wheat under pulp and paper mill biosolids (PPMB)-based and urea treatments. Values are means ± standard deviation (n = 4). Control plots received no nitrogen input. Canola Wheat Year Treatment Total N Applied (kg/ha) NUE (PFP-N) Nitrogen Response Agronomic Efficiency Total N Applied (kg/ha) NUE (PFP-N) Nitrogen Response Agronomic Efficiency Year 1 MixBio 616.9 2.8 ± 0.1c 593 ± 196ab 1.0 ± 0.3bc 483.3 4.7 ± 0.8c 530 ± 533b 1.1 ± 1.1b MixBioUrea 387.0 5.5 ± 0.6b 1011 ± 97a 2.6 ± 0.3b 303.0 9.9 ± 1.6ab 1246 ± 688ab 4.1 ± 2.3ab PriBioUrea 391.0 5.8 ± 0.1b 1122 ± 187a 2.9 ± 0.5b 306.0 6.4 ± 1.7bc 222 ± 796b 0.7 ± 2.6b SecBioUrea 385.0 7.8 ± 1.2ab 1854 ± 459 4.8 ± 1.2 302.0 9.9 ± 1.5 1258 ± 434 4.2 ± 1.4 Urea 157.0 7.5 ± 1.2ab 51 ± 332b 0.3 ± 2.1c 123.0 21 ± 4.0a 843 ± 305ab 6.9 ± 2.5a Year 2 MixBio 385.1 5.1 ± 1.3b 329 ± 511b 0.5 ± 1.1b 242.0 7.3 ± 1.1bc 153 ± 211b 0.8 ± 0.9b MixBioUrea 234.6 9.5 ± 0.4b 661 ± 459b 2.3 ± 1.8b 138.0 12.9 ± 0.6ab 214 ± 115b 1.6 ± 0.8b PriBioUrea 230.2 8.1 ± 2.3b 324 ± 816b 0.8 ± 3.5b 139.5 12.5 ± 2.2ab 186 ± 249b 1.3 ± 1.8b SecBioUrea 233.4 13.1 ± 0.6a 1488 ± 583a 5.8 ± 1.9a 137.3 15.6 ± 0.4a 573 ± 89a 4.2 ± 0.7a Urea 67.2 33.3 ± 7.6a 639 ± 535b 9.5 ± 8.0a 56.0 32 ± 3.5a 226 ± 181b 4.0 ± 3.2a Abbreviations: NUE (Partial Factor Productivity of N, PFP-N, kg grain kg⁻¹ N applied), NR (Nitrogen Response, kg grain yield increase ha⁻¹ vs. control), AE (Agronomic Efficiency or yield-based NUE, kg grain kg⁻¹ N applied). Control plots = zero N input, hence NUE, NR, and AE are not applicable (N/A). Inorganic N Fertilizer treatment = Urea and Biosolids based treatments: MixBio = mixed PPMB; PriBio = Primary PPMB + urea; SecBio = Secondary PPMB + urea. 3.2.3. Plant tissue nutrient concentration Macronutrient concentration specifically potassium (K), magnesium (Mg), and sulfur (S) was primarily influenced by crop type, with minimal response to treatment or year-by-treatment interactions (Table S4). Potassium accumulation varied significantly by crop (F = 166.4, p < 0.001) and year (F = 89.0, p < 0.001), with a crop × year interaction (F = 6.1, p < 0.05), indicating that seasonal effects modulated concentration efficiency (Table S4). Magnesium concentration followed a similar trend, showing strong main effects of crop (F = 218.1, p < 0.001) and year (F = 47.9, p 0.05) (Table S4). Sulfur concentration was also crop-dependent (F = 185.2, p < 0.001) and varied with year (F = 12.4, p < 0.01), while treatment effects were not significant (Table S4). Micronutrient concentration, including zinc (Zn), copper (Cu), and sodium (Na), also varied strongly by crop. Zinc concentrations were significantly affected by crop (F = 136.4, p < 0.001) and year (F = 6.6, p < 0.05), with a significant treatment × crop interaction (F = 2.7, p < 0.05), indicating that PPMB based amendments may differentially influence Zn concentration depending on crop type (Table S4). Copper and sodium followed similar patterns, with significant crop effects (F = 98.8 and 187.0, respectively; p 0.05) (Table S4). Overall, crop identity and seasonal conditions were the dominant factors influencing nutrient accumulation, rather than N amendment type. 3.3. Integrated soil health assessment 3.3.1. Multivariate Soil and Plant Function Responses Redundancy analysis revealed distinct treatment-driven patterns in soil chemical and biological indicators across crops. In canola systems, the first two RDA axes accounted for 17.3% and 0.1% of the total variance, respectively (Fig. 3 a). Treatments incorporating PPMB particularly MixBioUrea and PriBioUrea were positively associated with indicators such as WFPS, CO 2 respiration, CEC, and micronutrient concentrations (Mn, Zn, Fe) (Fig. 3 a). In contrast, vectors for NO 3 − and aluminium (Al) were negatively correlated with biological properties and oriented away from PPMB treatments, suggesting lower nutrient retention and biological activity under treatments lacking organic inputs (Fig. 3 a). In wheat systems, RDA axes 1 and 2 explained 8.8% and 0.7% of the variance, respectively (Fig. 3 c). PPMB-based treatments (MixBio and SecBioUrea) aligned with biological and chemical properties (e.g., respiration, Zn, NO₃⁻), while Urea clustered near the origin, reflecting minimal association with measured soil properties. The RDA based on plant performance indicators showed lower explanatory power overall, with Axis 1 and Axis 2 explaining 5.6% and 0.8% of variance in wheat (Fig. 3 b, d). Nonetheless, PriBioUrea and SecBioUrea treatments were positively associated with plant nutrient concentration variables (e.g., P, S, Mg), indicating potential alignment between soil nutrient availability and plant demand (Fig. 3 b, d). Model statistics are summarized in Table S5. Adjusted R 2 values ranged from − 0.02 to 0.32 in canola and up to 0.60 for wheat (Mo), indicating moderate explanatory capacity. Significant loadings on RDA Axis 1 included Al, B, K, Mg, and Mo ( p < 0.05), suggesting that these variables contributed substantively to treatment differentiation in the observed ordination structure (Table S5). 3.3.2. Soil health scores and composite rankings Composite soil health scoring confirmed the multivariate findings, revealing distinct treatment rankings across crops (Table 4 ). In canola, SecBioUrea achieved the highest yield score (90/100) and a “High” soil health score (SHS = 70/100), followed by MixBioUrea, which scored 70 in both categories. PriBioUrea and Urea were classified as “Moderate” (SHS = 50), with yield scores of 50 and 60, respectively (Table 4 ). The Control ranked lowest in canola, with yield and SHS scores of 30 and 50. In wheat, SecBioUrea again obtained the highest yield score (90), although its SHS remained “Moderate” (50). Urea achieved the highest SHS (90, “Very High”), but lower yield performance reduced its composite rank (score = 2). MixBioUrea and PriBioUrea performed consistently across yield and SHS categories (both 70), reflecting a balance of agronomic and soil health benefits (Table 4 ). The Control again ranked lowest, with a yield score of 30 and SHS of 70. Final composite rankings identified SecBioUrea and MixBioUrea as the top-performing treatments across both crops, driven by their combined contributions to yield, nutrient efficiency, and soil health improvement. Table 4 Effects of integrated pulp and paper mill biosolids (PPMB) and urea treatments on soil health indicators, elemental composition, and agronomic performance of canola and wheat. Canola Wheat Treatment Control MixBio MixBioUrea PriBioUrea SecBioUrea Urea Treatment Control MixBio MixBioUrea PriBioUrea SecBioUrea Urea RDA1 -5.62 10.13 1.68 -3.39 0.42 -3.22 RDA1 1.80 -5.42 0.26 1.60 -2.58 4.34 RDA2 0.33 -0.16 0.59 -0.43 0.00 -0.33 RDA2 -0.73 -0.58 0.31 -1.11 1.34 0.77 Al 8.76 10.61 13.34 16.23 14.95 10.88 Al 10.46 11.02 10.96 15.67 11.77 12.21 B 19.84 23.85 21.92 23.16 24.34 24.36 B 1.07 1.43 1.04 1.99 1.49 1.36 K 20712 20119 24966 19821 24802 21388 K 11144 11379 9785 12474 10677 10680 Mo 2.01 1.97 2.19 2.06 2.12 2.07 Mo 1.98 2.10 1.75 2.09 1.75 1.75 Ni 0.57 0.58 0.63 0.57 0.69 0.66 Fe 50.69 49.58 56.33 56.07 52.18 54.31 Ca 9780 12003 10681 11302 11311 11180 Mn 27.58 33.49 34.09 27.92 32.57 33.73 Cu 2.73 2.60 2.51 47.28 3.00 3.30 Mg 1505 1510 1490 1547 1477 1553 Fe 30.95 31.68 33.90 154.83 40.05 43.99 S 1793 1803 1727 1880 1770 1785 Zn 20.07 22.49 21.47 35.61 25.12 27.46 Zn 48.96 44.80 46.27 44.81 44.85 47.45 Yield 1.37 1.83 2.20 2.09 3.04 1.71 Yield 1.65 2.00 2.38 1.86 2.57 2.19 z-score (0–1) -0.94 1.76 0.40 -0.68 0.07 -0.63 z-score (0–1) 0.29 -1.66 0.16 0.14 -0.34 1.41 SHS (0-100) 50 90 70 50 70 50 SHS (0-100) 70 30 70 70 50 90 SHS Category Moderate Very High High Moderate High Moderate SHS Category High Low High High Moderate Very High NE 3397 3580 3972 3489 4025 3631 NE 1458 1484 1315 1605 1407 1417 Yield (0–1) -1.18 -0.37 0.28 0.09 1.75 -0.57 Yield (0–1) -1.34 -0.33 0.81 -0.74 1.36 0.24 Yield (0-100) 30 50 70 70 90 50 Yield (0-100) 30 50 70 50 90 70 Yield Category Low Moderate High High Very High Moderate Yield Category Low Moderate High Moderate Very High High Yield Rank 6 4 2 3 1 5 Yield Rank 6 4 2 5 1 3 Soil Health Rank 6 1 2 5 3 4 Soil Health Rank 2 6 3 4 5 1 Final Rank 6 2.5 2 4 2 4.5 Final Rank 4 5 2.5 4.5 3 2 Note: Data include redundancy analysis (RDA1 and RDA2), soil attributes influencing crop yield, z-scores, normalized yield metrics, soil health scores (SHS), nutrient efficiency (NE), and composite rankings for yield, soil health, and final rank. Treatments include Control, inorganic N fertilizer (Urea), mixed PPMB (MixBio), mixed PPMB + urea (MixBioUrea), primary PPMB + urea (PriBio), and secondary PPMB + urea (SecBio). 3.3.3. Sustainability impact of PPMB-based soil amendments A diagram was further constructed to illustrate the integrated sustainability impacts associated with the application of pulp and paper mill biosolids (PPMB) as soil amendments (Fig. 4 ). This synthesis was based on (i) the effects of PPMB-based treatments on key soil health properties (Fig. 2 ), elemental composition (Table 4 ), and agronomic performance in canola and wheat (Tables 2 and 3 ), and (ii) the relationships between soil properties and amendment treatments as revealed by redundancy analysis (Fig. 3 ). Specifically, PPMB amendments contributed to nutrient recycling by increasing soil NO₃⁻-N and PO₄³⁻-P levels, and achieving the highest nitrogen use efficiency (NUE) and agronomic efficiency (AE) in the SecBioUrea treatment (Fig. 4 ). Soil health was improved through enhanced soil respiration and maintenance of aggregate stability, with SecBioUrea and MixBioUrea treatments showing the highest integrated soil health scores (Fig. 4 ). Crop yield stability was evident, particularly under cold soil conditions, with canola yields reaching 3.0-3.1 t/ha in SecBioUrea and wheat showing consistent performance across treatments (Fig. 4 ). In addition, circular economy potential was demonstrated through RDA-based shifts in soil and crop responses, supporting nutrient loop closure and achieving top integrated sustainability scores (1.5–2.5). The amendments also improved soil chemical balance by increasing pH and elevating Ca, Na, Zn, and Mn concentrations within safe and regulatory-compliant levels (Fig. 4 ). 4.0 Discussion 4.1. Soil physical and chemical properties in response to PPMB amendments The PPMB and PPMB-urea treatments had minimal effects on soil physical properties such as bulk density, total porosity, and WFPS, suggesting that crop type and soil depth were the primary drivers of variation. Bulk density values remained within acceptable agronomic limits, indicating that short-term amendment did not lead to compaction or excessive soil loosening. This aligns with findings from PPMB application studies where physical soil improvement is often not observed until after several growing seasons (Zibilski et al, 2000; Chow et al., 2003 ; Camberato et al., 2006 ; Price and Voroney, 2007 ). For instance, Zibilski et al (2000) only noticed bulk density change after a 4- and 5-year period and increase soil stability after 3 years of PPMS application. The lack of treatment effect on the soil physical properties in our study may be attributed to the glaciated origin of the study soil that overshadowed small amendment-driven shifts coupled with the short study duration, tillage and crop rooting effects (Ehrlich et al., 1960 ; Hopkins and Smith; 1982 ; Blanco-Canqui and Ruis; 2018 ). In contrast, PPMB-urea blends influenced key chemical properties, including pH, total C, nitrate, phosphorus, and several micronutrients, particularly in the canola plots. The pH increase observed in PPMB treated soils especially MixBio supports prior observations that PPMB amendments can buffer soil acidity and have a liming potential (Nunes et al., 2008 ; Rasa et al., 2021 ). The significant accumulation of total C concentration in MixBio and PriBioUrea treatments indicates enhanced organic matter input and suggests potential for longer-term improvements in nutrient retention and microbial habitat quality (Camberato et al., 2006 ; Gagnon et al., 2010 ). In our study, the treatment-driven shifts in nutrient concentrations, particularly NO 3 − and P, demonstrate that PPMB amendments can alter soil fertility dynamics, though these effects varied by depth, year, and crop. Notably, nitrogen immobilization, a common occurrence in organic amendments, was reduced in treatments blended with urea, likely due to the readily available form of nitrogen provided by urea. This finding aligns with previous research showing that the co-application of PPMB with other nutrient sources can alleviate nitrogen availability constraints (Manirakiza et al., 2019 ; Chen et al., 2023 ). Interestingly, micronutrient concentration was also responsive to treatment. The consistent elevation of Fe, Mn, and Zn concentrations under PPMB-urea treatments (MixBioUrea and SecBioUrea) in canola plots in our study suggests enhanced micronutrient release from organic residues or improved root access to trace elements (Maqueda et al., 2019). This crop-specific response likely reflects differences in rooting depth, rhizosphere chemistry, and nutrient demand between canola and wheat (Rahman and Schoenau, 2021 ). Urea-alone treatments, in contrast, appeared less effective in maintaining micronutrient concentration, which could reflect dilution effects (Gajula et al., 2024 ) or antagonistic nutrient interactions (Abdoli, 2020 ). 4.2. Soil biological activity and functional indicators Soil respiration was consistently elevated PPMB-urea treatments, particularly SecBioUrea and MixBioUrea, indicating greater microbial activity and substrate availability. This supports the hypothesis that co-application of organic and mineral nitrogen sources promotes microbial growth by balancing labile C inputs with nutrient supply (Xia et al., 2024 ). The significant treatment × crop interaction further suggests that biological responses are modulated by crop type, likely due to differences in root exudation and nutrient concentration patterns (Wang et al., 2021 ). Redundancy analysis confirmed the central role of PPMB-urea blends in enhancing soil biological function. In canola systems, these treatments aligned with higher soil microbial respiration, micronutrient concentrations, and cation exchange capacity, reflecting a more active and nutrient-rich soil environment. In contrast, Urea and Control treatments were associated with lower biological activity and higher NO 3 − accumulation, indicating potential nutrient loss and lower system efficiency (Chen et al., 2023 ). These multivariate trends underscore the ecological advantage of integrating organic materials in fertility management. 4.3. Crop yield and nitrogen use efficiency Crop yield responses differed distinctly between canola and wheat. In canola, PPMB-urea treatments, particularly SecBioUrea, significantly increased yield over both the Control and Urea treatments. The 173% increase in year 1 under SecBioUrea demonstrates the agronomic potential of stabilized PPMB when applied in combination with inorganic nitrogen (Amini et al., 2012 ; Gagnon and Ziadi, 2021 ). In contrast, wheat yields were less responsive to treatment and more variable across years, suggesting either lower nutrient demand or greater sensitivity to seasonal variation in soil moisture and temperature (Zörb et al., 2018 ). Nitrogen use efficiency metrics provided additional insights into treatment performance. In canola, SecBioUrea consistently exhibited the highest agronomic efficiency and nitrogen response, outperforming both PPMB-only and inorganic N treatments. These results suggest improved synchrony between nitrogen release and crop demand under combined applications, likely enhancing nitrogen uptake and reducing losses (Gagnon et al., 2021 ). In wheat, although urea achieved the highest NUE, SecBioUrea remained competitive, indicating that PPMB-urea blends can match the efficiency of inorganic fertilizers when applied at rates aligned with crop demand. 4.4. Plant nutrient concentration and crop-specific patterns Nutrient concentration responses were predominantly shaped by crop identity. Concentration of macronutrients such as K, Mg, and S was governed more by crop demand and seasonal effects than by treatment. This suggests that baseline fertility across treatments was sufficient to meet crop requirements or that nutrient availability was buffered by soil reserves (De Oliveira Silva et al., 2021 ). Micronutrient concentration, particularly Zn and Mn, was more responsive to treatment and varied significantly between crops. Canola exhibited higher sensitivity to PPMB amendments, suggesting a greater capacity for micronutrient extraction or enhanced uptake mechanisms under organic fertilization regimes (Gagnon et al., 2010 ; Shaheen and Tsadilas, 2013 ). These differences highlight the need for crop-specific nutrient management strategies when using PPMB, especially where micronutrient sufficiency is a concern (Elwan et al., 2025 ). 4.5. Integrated soil health assessment Composite soil health scores and multivariate analyses demonstrated that PPMB-urea treatments, especially SecBioUrea, offer an effective strategy for enhancing both soil health and crop productivity (Fig. 4 ). In canola, SecBioUrea achieved the highest scores for yield and soil health, indicating strong integration of agronomic and ecological functions. In wheat, although Urea achieved the highest soil health score, this did not translate to the highest yield, suggesting a disconnect between short-term productivity and measured soil health indicators (Wu and Congreves, 2021 ) MixBioUrea performed consistently across both crops, indicating its robustness as a balanced treatment. These results reinforce the importance of selecting amendment strategies that deliver both yield gains and long-term soil improvement (Ziadi et al., 2013 ; Tough, 2025 ). The differential responses across crops emphasize the need for flexible, crop-adapted nutrient management approaches, particularly when integrating PPMB into rotational systems. In addition, our study highlights seven interconnected sustainability themes derived from soil, crop, and system-level analyses that are critical for the sustainable use of PPMB as soil amendment (Fig. 4 ) 4.6. Limitations and future directions This study focused on short-term treatment responses and did not assess leaching losses, trace metal accumulation, or long-term changes in soil organic C pools. Moreover, the observed soil biological benefits may increase over time as PPMB-derived organic matter continues to decompose and interact with soil microbiota (Tough, 2025 ; Manirakiza et al., 2025 ). Future research should explore long-term impacts of repeated PPMB-urea applications under varying moisture and temperature regimes, as well as their implications for nutrient leaching and greenhouse gas emissions. Overall, the results support the use of co-applied PPMB and urea as an effective soil fertility management strategy. With proper formulation and application timing, these treatments can enhance nutrient use efficiency and maintain or improve soil quality, providing both environmental and agronomic benefits in intensive cropping systems. Conclusion Field-based evidence from this study confirms that PPMB are effective and sustainable soil amendments in cold-region agroecosystems. The application of PPMB improved soil physical, chemical, and biological properties while sustaining or enhancing grain yields of canola and wheat relative to inorganic (urea) treatments. These results highlight the potential of industrial PPMB valorization as a circular economy solution that delivers agronomic and environmental co-benefits (Fig. 4 ). The findings have direct relevance for nutrient management policies and soil restoration initiatives in northern cropping systems. Future multi-year trials and expanded assessments including biomass partitioning and long-term ecological monitoring are recommended to fully capture the system-wide impacts of PPMB amendments. Declarations CRediT authorship contribution statement Emmanuel A. Badewa: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing - original draft, Writing - review & editing. Yifan Song: Investigation, Methodology, Writing - review & editing. Xinran Duan: Investigation, Methodology, Writing - review & editing. Patrick Levasseur: Investigation, Methodology, Writing - review & editing. Amanda Diochon: Investigation, Methodology, Writing - review & editing. Shawn Sexsmith: Field support, Data collection, Writing - review & editing. Lisa Jones: Field logistics, Data collection, Writing - review & editing. Leigh Johnston: Field logistics, Resources, Writing - review & editing. Tamsin Patience : Resources, Writing - review & editing. Nathan Basiliko: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing - review & editing. Nikolai DeMartini: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing - review & editing. Declaration of competing Interest The authors declare that there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements We gratefully acknowledge the financial support provided to Emmanuel A. Badewa through the Mitacs Elevate Postdoctoral Fellowship program, in partnership with the University of Toronto and Canadian Kraft Paper. We also thank Lakehead University for providing research infrastructure and institutional support. This work is part of the industrial research consortium project Effective Energy and Chemical Recovery in Pulp and Paper Mills - III at the University of Toronto supported by Andritz, Arauco, Babcock & Wilcox, Canadian Kraft Paper, Cenibra, Clyde Bergemann, CMPC, ERCO Worldwide, FPinnovations, Georgia Pacific, International Paper, Irving Pulp & Paper, Klabin, Mercer, Rayonier, Sappi, Södra, Stora Enso, Suzano, Valmet, WestRock. Data availability Data will be made available on request. Funding information Financial support for this project was provided by Mitacs Elevate through partnership with the University of Toronto and Canadian Kraft Paper. References Abdoli, M., 2020. Effects of micronutrient fertilization on the overall quality of crops. Plant Micronutrients: Deficiency and Toxicity Management, 31-71. Agriculture Victoria, 2010. Estimating crop yields: A brief guide. Victorian Government. 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Prod., 469, 143211. https://doi.org/10.1016/j.jclepro.2024.143211 Xu, X., He, P., Wei, J., Cui, R., Sun, J., Qiu, S., Zhao, S., Zhou, W., 2021. Use of controlled-release urea to improve yield, nitrogen utilization, and economic return and reduce nitrogen loss in wheat-maize crop rotations. Agronomy, 11(4), 723. https://doi.org/10.3390/agronomy11040723 Zhang, J., Dyck, M., Quideau, S.A., Norris, C.E., 2024. Assessment of soil health and identification of key soil health indicators for five long-term crop rotations with varying fertility management. Geoderma, 443, 116836. https://doi.org/10.1016/j.geoderma.2024.116836 Ziadi, N., Gagnon, B., Nyiraneza, J., 2013. Crop yield and soil fertility as affected by papermill biosolids and liming by-products. Can. J. Soil Sci., 93(3), 319-328. Zibilske, L.M., Clapham, W.M., Rourke, R.V., 2000. Multiple applications of paper mill sludge in an agricultural system: soil effects. Agron. J., 92(6), 1227-1234. Zörb, C., Ludewig, U., Hawkesford, M.J., 2018. Perspective on wheat yield and quality with reduced nitrogen supply. Trends Plant Sci., 23(11), 1029-1037. https://doi.org/10.1016/j.tplants.2018.08.012 Additional Declarations The authors declare potential competing interests as follows: Some authors are employed by the company that supplied the pulp and paper mill biosolids used in this study. Several industry partners provided financial support for the broader research consortium. These relationships did not influence the study design, data collection, analysis, or interpretation. Supplementary Files SupplementaryMaterialsFileRCRBadewaetal.docx Circular Valorization of Pulp and Paper Mill Biosolids for Sustainable Soil Management and Crop Production in Cold-Region Agroecosystems GraphicalAbstract.docx 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. 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10:16:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":244084,"visible":true,"origin":"","legend":"\u003cp\u003eSoil properties significantly affected by treatments containing pulp and paper mill biosolids (PPMB) and urea. Bars represent mean ± standard error (n = 4). Treatments sharing the same letter within a depth are not significantly different (\u003cem\u003ep \u003c/em\u003e\u0026gt; 0.05).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8232268/v1/480135e13780085abbc03b57.jpg"},{"id":97235140,"identity":"4a7cc217-2919-4385-b24e-854ae3b2a3a6","added_by":"auto","created_at":"2025-12-02 10:16:35","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89971,"visible":true,"origin":"","legend":"\u003cp\u003eRedundancy analysis (RDA) ordination plots (scaling = 1) illustrating the relationships between soil properties and different soil amendment treatments containing pulp and paper mill biosolids (PPMB) and urea. Panels (A-C) show treatment distributions based on soil variables while Panels (B-D) show treatment distributions based on plant performance variables. Axes percentages indicate the proportion of explained variance. Vectors represent the directional influence of soil or plant performance variables.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8232268/v1/9e29975228c6b4e678a9e82f.jpg"},{"id":97251341,"identity":"6fcddc31-3789-48d7-8ef0-6ed3aa2a429a","added_by":"auto","created_at":"2025-12-02 13:16:49","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":100998,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated sustainability impact diagram for pulp and paper mill biosolid amendments.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8232268/v1/80ab1cf0590ed370ecbf4e99.jpg"},{"id":97366836,"identity":"b95324d5-85c8-444a-86c4-ddcc306fefb2","added_by":"auto","created_at":"2025-12-03 16:08:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2262347,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8232268/v1/25c57580-6176-4aab-8bd1-dcd95259b8de.pdf"},{"id":97235136,"identity":"4508dcf7-5fbc-4031-ab93-6a1176a33658","added_by":"auto","created_at":"2025-12-02 10:16:35","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":109043,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCircular Valorization of Pulp and Paper Mill Biosolids for Sustainable Soil Management and Crop Production in Cold-Region Agroecosystems\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryMaterialsFileRCRBadewaetal.docx","url":"https://assets-eu.researchsquare.com/files/rs-8232268/v1/59290115d625425393bd8aed.docx"},{"id":97235138,"identity":"8c22c9d8-91bd-4b72-bbf9-7623fb6d23dd","added_by":"auto","created_at":"2025-12-02 10:16:35","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":468171,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-8232268/v1/4637c96162ad6dc4f7a59b80.docx"}],"financialInterests":"The authors declare potential competing interests as follows: Some authors are employed by the company that supplied the pulp and paper mill biosolids used in this study. Several industry partners provided financial support for the broader research consortium. These relationships did not influence the study design, data collection, analysis, or interpretation.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eCircular Valorization of Pulp and Paper Mill Biosolids for Sustainable Soil Management and Crop Production in Cold-Region Agroecosystems\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; Biosolids from pulp mills improved soil health in cold-region agroecosystems.\u003c/p\u003e\u003cp\u003e\u0026bull; Combined pulp and paper mill biosolids (PPMB) and urea treatments maintained or increased wheat and canola yields.\u003c/p\u003e\u003cp\u003e\u0026bull; Field trial confirms PPMB can reduce inorganic N fertilizer needs by up to 50%.\u003c/p\u003e\u003cp\u003e\u0026bull; PPMB improved soil pH, N, and P, with no metal or pathogen buildup detected post-application.\u003c/p\u003e\u003cp\u003e\u0026bull; Application of PPMB supports circular economy policies for nutrient recycling and waste valorization in agriculture.\u003c/p\u003e"},{"header":"1.0 Introduction","content":"\u003cp\u003eIndustrial waste disposal and nutrient losses from agricultural systems remain pressing global environmental challenges (Koul et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kumar et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Across multiple sectors, the need to transform waste streams into resources has become central to advancing sustainable development and mitigating pollution (Roy et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chenavaz and Dimitrov, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Manisha et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In particular, the pulp and paper industry generates approximately 100 tonnes of organic residuals, including primary and secondary pulp and paper mill biosolids (PPMB), per 550 tonnes of pulp produced as by-products of effluent treatment processes (Haile et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Historically, concerns over organochlorines and heavy metals limited the reuse potential of PPMB (Koistinen et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). However, technological advances in the late 1980s which use chlorine dioxide rather than elemental chlorine have largely eliminated such contaminants (Turner et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Modern PPMB now contains partially decomposed organic matter derived from woody biomass, along with essential plant nutrients such as nitrogen (N) and phosphorus (P), but with low concentrations of metals and persistent organic pollutants (Krigstin, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Bajpai, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Manirakiza et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Despite this, disposal practices such as landfilling and incineration persist, contributing to greenhouse gas emissions, soil degradation, and escalating operational costs (Bajpai, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sebastian and Louis, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePulp and paper mill biosolids recycling offers a viable route toward resource recovery and supports the principles of a circular economy (Hasan et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The application of PPMB to agricultural soils can close nutrient loops by substituting inorganic fertilizers, improving soil organic matter, and enhancing nutrient retention (Ziadi et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gagnon et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tough, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Nonetheless, the diversity of both soil properties and biosolid compositions across regions and production systems complicates generalization (Nunes et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gagnon et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chigbo et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Primary PPMB, sourced from effluent clarification, typically exhibit high carbon-to-nitrogen (C/N) ratios that may immobilize soil N (Turner et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nitrogen immobilization occurs when soil microbes utilize available nitrogen to decompose carbon-rich organic matter, temporarily reducing N availability to plants. In contrast, secondary PPMB from aerobic treatment processes have lower C/N ratios and higher P availability, potentially enhancing crop productivity (Gagnon and Ziadi, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Although various trials have demonstrated agronomic benefits from PPMB (e.g., Nunes et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gagnon et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Gagnon and Ziadi, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), relatively few studies have explicitly assessed PPMB use in combination with reducing inorganic fertilizer rates, a key strategy to lower inorganic fertilizer dependency while maintaining yields.\u003c/p\u003e\u003cp\u003eMoreover, an important knowledge gap persists regarding the field-scale evaluation of PPMB amendments in cold-region agroecosystems, such as the subarctic farming zones of northern Canada. Soils in these environments, including Rego Gleysols, are often poorly drained and sensitive to nutrient losses due to short growing seasons and prolonged snow cover (Ehrlich et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1960\u003c/span\u003e; Hopkins and Smith, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Limited research has addressed how PPMB perform under these conditions, particularly in terms of soil health outcomes and crop yield responses. The objective of this study was to evaluate the impact of PPMB applications alone and in combination with reduced rates of inorganic N fertilizer on soil health indicators and crop yield performance in canola (\u003cem\u003eBrassica napus\u003c/em\u003e L.) and wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L.). We conducted a fully replicated, randomized block field trial in the Carrot River agricultural region near The Pas, Manitoba, using six treatments: a control, inorganic N fertilizer (urea), mixed PPMB (a combination of primary and secondary biosolids), and three additional urea-PPMB blends, each formulated to provide 50:50 N contributions from urea and either primary, secondary, or mixed PPMB sources.\u003c/p\u003e\u003cp\u003eSpecifically, we aimed to determine whether PPMB based amendments can sustain or enhance crop yields while improving soil physical, chemical, and biological properties compared to conventional inorganic fertilizer practices. We hypothesized that (i) PPMB-based application would improve soil properties, including bulk density, nutrient availability, and microbial activity, relative to unamended and inorganic fertilizer-only controls; and (ii) crop yields under PPMB-based treatments would be comparable to or exceed those of these controls, thereby supporting PPMB use as a partial substitute for conventional nutrient inputs in cold-region cropping systems.\u003c/p\u003e"},{"header":"2.0 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Experimental study area and design\u003c/h2\u003e\u003cp\u003eThe field trial was conducted during the 2023 and 2024 growing seasons, from late May to mid-September, at Round the Bend Farm, in the Carrot River Valley near The Pas, Manitoba, Canada (53\u0026deg;44\u0026prime;12.2\u0026Prime;N, 101\u0026deg;38\u0026prime;54.3\u0026Prime;W). The soil at the site is classified as a Rego Gleysol of the Pasquia series, characterized by peaty calcareous properties with modest B horizon development and a silty clay loam texture. The baseline soil pH was 6.9, with a total N content of 0.8% at 0\u0026ndash;20 cm depth. Additional baseline soil properties are presented in Table S1. The region experiences a subarctic climate, marked by a short growing season and high soil moisture retention due to low evapotranspiration. The site had been previously maintained under perennial grass cover used for bison grazing. A randomized complete block design (RCBD) with four replicates per treatment was employed. The experimental field (50 \u0026times; 50 m) was divided into two adjacent sections; each planted with either canola or wheat. Each section contained 24 plots (3 \u0026times; 9 m) separated by 2 m buffer strips (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Six treatments were applied in each crop section: (i) Control (no amendment); (ii) Urea fertilizer; (iii) Secondary PPMB\u0026thinsp;+\u0026thinsp;50% urea (SecBioUrea); (iv) Mixed PPMB\u0026thinsp;+\u0026thinsp;50% urea (MixedBioUrea); (v) Primary PPMB\u0026thinsp;+\u0026thinsp;50% urea (PriBioUrea); and (vi) 100% mixed PPMB (MixBio) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The PPMB application rates were calculated based on crop N requirements and an assumed N efficiency coefficient of 0.25, in compliance with the Tri-Provincial Manure Application Guidelines (2003) to meet metal loading limits (Table S2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Biosolids characteristics and crop management\u003c/h2\u003e\u003cp\u003eThe biosolids were sourced from Canadian Kraft Paper (CKP) in The Pas, Manitoba, and included both primary and secondary PPMB streams, blended at specified ratios. Prior to application, PPMB were analyzed for compositional characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Secondary PPMB contained higher total organic carbon (33.3%) and N (1.22%) than primary PPMB (22.5% and 0.5%), resulting in a lower C:N ratio (27.0 vs. 43.9). Electrical conductivity was also higher in secondary PPMB (2.79 dS/m), compared to primary PPMB (2.22 dS/m). Secondary PPMB had markedly greater concentrations of phosphorus, nitrate-N, and trace elements including Zn, Cd, and Cu, compared to primary PPMB (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All PPMB originated from a composted source (minimum two years) and were routinely screened for pathogens and trace metals to ensure compliance with the Canadian Council of Ministers of the Environment (CCME) guidelines for land application. Application permits were obtained from the Manitoba Environment and Climate Change. Certified crop varieties commonly adopted in northern Manitoba were selected: canola (\u0026lsquo;TrueFlex\u0026rsquo;) and wheat (\u0026lsquo;AAC Brandon\u0026rsquo;). Seeding was performed using a hand-push seeder. The PPMB and urea fertilizers were manually broadcast and incorporated within one hour to a depth of 10 cm using a rototiller. Weed control was implemented using Roundup WeatherMAX (glyphosate) for canola and MCPA Ester 600 herbicide for wheat, following standard agronomic practice.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical properties of pulp and paper mill biosolids (PPMB).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChemical Properties\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary Biosolids\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSecondary Biosolids\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC (dS/m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal organic C (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC/N ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmmonium (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNitrate (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhosphorus (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e83.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhosphorus (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e811.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3360.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePotassium (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e196.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMagnesium (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e188.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArsenic (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCadmium (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCobalt (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChromium (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCopper (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLead (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMercury (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolybdenum (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNickel (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelenium (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZinc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e879\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Soil sampling and properties\u003c/h2\u003e\u003cp\u003eSoil samples were collected at harvest in September 2023 and 2024. Composite samples were collected from depths of 0\u0026ndash;10 cm and 10\u0026ndash;20 cm. Soil bulk density and porosity were determined using a core sampling method (McKenzie et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). A cylindrical core (inner diameter: 4.5 cm; height: 5.1 cm) was inserted into the soil to extract undisturbed samples. The soil cores were oven-dried at 105\u0026deg;C for 48 hours, and bulk density was calculated as the dry weight divided by the core volume. Porosity was estimated using the bulk density and assuming a particle density of 2.65 g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. Gravimetric water content was determined by weighing the cores before and after drying, and volumetric water content (VWC) was obtained by multiplying gravimetric water content by bulk density. Water-filled pore space (WFPS) was calculated as the ratio of VWC to total porosity, expressed as a percentage. Water-stable aggregate (WSA) was assessed using a wet sieving procedure (Kemper and Rosenau, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). Air-dried soil samples were first sieved to obtain 1\u0026ndash;2 mm aggregates, and a 4 g subsample was wet sieved using a wet sieving apparatus (Eijkelkamp, Netherlands). Soil texture was determined using the hydrometer method (Gee and Or, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Soil pH was measured using a 1:2 soil to 0.01 M CaCl\u003csub\u003e2\u003c/sub\u003e extraction (McLean, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Miller and Kissel, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Ammonium (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e) and nitrate (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e) concentrations were extracted with 2 M KCl and analyzed using colorimetric method (Maynard et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Plant-available phosphorus (PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003eP) was extracted using the Olsen method and analyzed using colorimetric method (Ashworth and Mrazek, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Cation exchange capacity (CEC) was determined by ammonium extraction followed by colorimetric quantification (Hendershot et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Total organic carbon (C), and total N in both plant and soil samples were measured by dry combustion method (Soil Science Society of America, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Schumacher, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Total elemental concentrations in the soil and plant were determined via inductively coupled plasma optical emission spectrometry (ICP-OES) following HNO₃ digestion and Mehlich-3 extraction (Skoog et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; EPA, 2023). Soil microbial activity was assessed using a 24h in-vitro soil microbial respiration assay (following Noyce et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Crop yield and nitrogen efficiency indicators\u003c/h2\u003e\u003cp\u003ePlant biomass samples were harvested from a 1 m\u0026sup2; area in each treatment replicate plot. Plots were harvested manually by cutting full stems at the soil surface. Grain yield was determined using head/pod count, grain number per head or pod, and 100-grain weight (0.4 g for canola and 3.4 g for wheat) (Agriculture Victoria, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Grain yield data were analyzed by treatment, crop, and year. Nitrogen performance indicators were calculated using the following according to Dobermann (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2007\u003c/span\u003e): Nitrogen Use Efficiency, NUE (expressed as partial factor productivity of nitrogen, PFP-N); Total yield per unit of N applied; Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), Nitrogen Response (NR); Yield gain from N application; Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), Agronomic Efficiency (AE) (also called yield-based NUE); Incremental yield per unit N applied; Eq.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:NUE\\:(\\text{P}\\text{F}\\text{P}-\\text{N})=\\:\\frac{{Y}_{N}\\:}{{N}_{applied}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:NR=\\:{Y}_{N}-\\:{Y}_{0}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:AE=\\:\\frac{{Y}_{N}-\\:{Y}_{0}\\:}{{N}_{applied}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere Y\u003csub\u003eN\u003c/sub\u003e: Yield with nitrogen application (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)​, Y\u003csub\u003e0\u003c/sub\u003e: Yield without nitrogen (control) (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), N \u003csub\u003eapplied\u003c/sub\u003e: Amount of nitrogen applied (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Integrated Soil Health Evaluation\u003c/h2\u003e\u003cp\u003eSoil health was assessed using a combined approach of multivariate soil analysis and crop performance metrics to evaluate how soil conditions and management treatments influence productivity and plant nutrient status, thereby supporting balanced agronomic decision-making (Toor et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Badewa et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Indicators were selected for their responsiveness to short-term management, measurability, and soil ecosystem functional relevance (B\u0026uuml;nemann et al., 2018). The soil health evaluation followed a three-step procedure: Step 1: \u003cem\u003eRedundancy Analysis (RDA).\u003c/em\u003e Redundancy analysis was performed on standardized soil datasets to identify the principal gradients of soil variability attributable to treatment effects (Souza, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Mean RDA scores from the first two canonical axes were calculated for each treatment and used as indicators of treatment-induced soil variability. Step 2: \u003cem\u003eRelationship Between Soil Conditions and Crop Performance\u003c/em\u003e. Multiple linear regression models were employed to examine the associations between soil conditions and crop performance, using the RDA scores (axes 1 and 2) as explanatory variables. Crop yield and nutrient concentration served as the response variables in the models (Marcis and Salvatore, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Step 3: \u003cem\u003eSoil Health Score (SHS) Calculation and Classification\u003c/em\u003e. A Soil Health Score was derived by computing the equally weighted average of the first two RDA scores, standardizing them as z-scores (mean\u0026thinsp;=\u0026thinsp;0, standard deviation\u0026thinsp;=\u0026thinsp;1), and transforming the result to a 0-100 scale for interpretability (Zhang et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Based on fixed z-score thresholds, treatments were categorized into four soil health classes: Very High (Z\u0026thinsp;\u0026gt;\u0026thinsp;1; SHS\u0026thinsp;\u0026gt;\u0026thinsp;90), High (0\u0026thinsp;\u0026lt;\u0026thinsp;Z\u0026thinsp;\u0026le;\u0026thinsp;1; SHS\u0026thinsp;\u0026asymp;\u0026thinsp;70), Moderate (\u0026minus;\u0026thinsp;1\u0026thinsp;\u0026lt;\u0026thinsp;Z\u0026thinsp;\u0026le;\u0026thinsp;0; SHS\u0026thinsp;\u0026asymp;\u0026thinsp;50), and Low (Z\u0026thinsp;\u0026le;\u0026thinsp;\u0026minus;\u0026thinsp;1; SHS\u0026thinsp;\u0026asymp;\u0026thinsp;30) (Wu and Congreves, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Data Analysis\u003c/h2\u003e\u003cp\u003eAll data processing and statistical analyses were performed using \u003cem\u003eR v.\u003c/em\u003e4.4.3 (R Core Team, 2025). Prior to analysis, all soil and crop data were assessed for normality using the Shapiro-Wilk test. Variables that violated the normality assumption were subjected to log or Box-Cox transformations (λ\u0026thinsp;=\u0026thinsp;0.5) using the MASS package to improve homoscedasticity and model fit. Four-way analysis of variance (ANOVA) was employed to evaluate the effects of treatment, year, depth, and crop type, including their interactions. When significant main or interaction effects were detected (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), Tukey\u0026rsquo;s Honestly Significant Difference (HSD) post-hoc test was used to identify statistically significant pairwise differences among treatments within each depth and crop type. Redundancy Analysis (RDA) was conducted to explore multivariate responses of soil health indicators to treatments and to examine the relationships between soil properties and crop performance. RDA was implemented using the vegan package in \u003cem\u003eR\u003c/em\u003e. RDA biplots were generated to visualize the directional influences of treatments and indicator variables.\u003c/p\u003e\u003c/div\u003e"},{"header":"3.0 Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Soil properties\u003c/h2\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.1. Physical soil properties\u003c/h2\u003e\n \u003cp\u003eBulk density ranged from 0.28 to 1.29 g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e across treatments and depths (Table S3). Statistically significant effects were observed for crop (F\u0026thinsp;=\u0026thinsp;21.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and depth (F\u0026thinsp;=\u0026thinsp;67.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas treatment effects were not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Similarly, total porosity varied between 51.3% and 89.5%, with significant differences by crop and depth (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but no treatment effects were detected. Volumetric water content and water-filled pore space (WFPS) were significantly influenced by crop (F\u0026thinsp;=\u0026thinsp;43.5 and 42.8, respectively) and depth (F\u0026thinsp;=\u0026thinsp;17.7 and 33.6, respectively) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with no significant treatment or interaction effects (Table S3). Aggregate stability ranged from 35.1% to 98.5%, with significant effects attributed to crop (F\u0026thinsp;=\u0026thinsp;8.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and depth (F\u0026thinsp;=\u0026thinsp;30.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.2. Chemical soil properties\u003c/h2\u003e\n \u003cp\u003eSoil pH was significantly affected by treatment (F\u0026thinsp;=\u0026thinsp;4.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), crop (F\u0026thinsp;=\u0026thinsp;5.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and year (F\u0026thinsp;=\u0026thinsp;5.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with no significant interaction terms (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea-b; Table S3). Nitrate concentrations varied significantly across treatment, crop, and year, and exhibited significant two-way interactions: treatment \u0026times; crop (F\u0026thinsp;=\u0026thinsp;3.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), treatment \u0026times; year (F\u0026thinsp;=\u0026thinsp;3.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and crop \u0026times; year (F\u0026thinsp;=\u0026thinsp;44.3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In year 1, treatment effects were detected in canola at both 0\u0026ndash;10 cm and 10\u0026ndash;20 cm depths (Control vs. Urea; PriBioUrea, MixBioUrea vs. Urea), and in wheat at 0\u0026ndash;10 cm (MixBio vs. MixBioUrea) and 10\u0026ndash;20 cm (MixBio vs. MixBioUrea, Urea) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec-d; Table S3). Total C showed significant effects of treatment and depth (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ee-f; Table S3). In year 2, treatment effects were observed in canola at 0\u0026ndash;10 cm (Control, Urea vs. MixBio), while no treatment effect was found in wheat. Calcium (Ca) levels showed significant treatment effects in year 1 for canola at both depths and in wheat at 0\u0026ndash;10 cm, with no significant effects at 10\u0026ndash;20 cm (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eg-h; Table S3; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Ammonium (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e) concentrations exhibited a significant three-way interaction between crop, depth, and year (F\u0026thinsp;=\u0026thinsp;67.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), although treatment effects were not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Available phosphorus (P) concentrations varied significantly with depth (F\u0026thinsp;=\u0026thinsp;57.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and treatment (F\u0026thinsp;=\u0026thinsp;8.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), particularly between Control, Urea, and MixBio. Cation exchange capacity (CEC) was significantly influenced by depth (F\u0026thinsp;=\u0026thinsp;34.8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while no significant treatment effects were observed (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table S3).\u003c/p\u003e\n \u003cp\u003eIron (Fe) concentrations showed a significant depth \u0026times; year interaction (F\u0026thinsp;=\u0026thinsp;46.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a main effect of treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table S3). In year 1, Fe was significantly affected in wheat at 10\u0026ndash;20 cm (Control vs. MixBio), with no significant differences observed in canola (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ei-j). Manganese (Mn) concentrations varied significantly by treatment, crop, and year, with multiple interaction effects: treatment \u0026times; crop (F\u0026thinsp;=\u0026thinsp;3.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), treatment \u0026times; depth (F\u0026thinsp;=\u0026thinsp;2.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), treatment \u0026times; year (F\u0026thinsp;=\u0026thinsp;10.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and crop \u0026times; year (F\u0026thinsp;=\u0026thinsp;31.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table S3). Treatment effects on Mn were particularly evident in year 1 in canola at both depths and in wheat at both depths (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ek-l). Sodium (Na) showed a significant depth \u0026times; year interaction (F\u0026thinsp;=\u0026thinsp;6.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with treatment differences at 0\u0026ndash;10 cm (Control, Urea vs. PriBioUrea) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003em-n). Zinc (Zn) concentrations exhibited significant interactions: treatment \u0026times; year (F\u0026thinsp;=\u0026thinsp;7.8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), crop \u0026times; year (F\u0026thinsp;=\u0026thinsp;8.8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and depth \u0026times; year (F\u0026thinsp;=\u0026thinsp;5.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table S3). In year 1, Zn was significantly influenced by treatment in canola at both depths and in wheat across both depth intervals (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eo-p). Nickel concentrations were significantly influenced by interactions between treatment \u0026times; year (F\u0026thinsp;=\u0026thinsp;3.3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), crop \u0026times; year (F\u0026thinsp;=\u0026thinsp;18.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and depth \u0026times; year (F\u0026thinsp;=\u0026thinsp;61.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), alongside main effects of treatment, crop, and depth (Table S3; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Sulphur concentrations varied significantly with treatment (F\u0026thinsp;=\u0026thinsp;11.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and depth (F\u0026thinsp;=\u0026thinsp;8.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while interaction effects were not significant (Table S3).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.3. Soil biological activity\u003c/h2\u003e\n \u003cp\u003eSoil microbial respiration was significantly influenced by treatment, crop, and depth, particularly in the 24-hour incubation assay (Table S3). A significant interaction between treatment and crop was detected (F\u0026thinsp;=\u0026thinsp;3.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with a main treatment effect (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Across both years and depths, MixBio and MixBioUrea treatments consistently showed the highest soil microbial respiration compared to the control (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eq-r). In canola, SecBioUrea exhibited the greatest soil microbial respiration at 10\u0026ndash;20 cm in both years (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eq). In wheat, although not statistically significant, PriBioUrea showed a tendency to enhance microbial activity in year 2 across both depth intervals (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003er).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Crop productivity and nutrient utilization dynamics\u003c/h2\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.1. Crop yield response\u003c/h2\u003e\n \u003cp\u003eTreatment had a statistically significant effect on crop yield across both crop types (F\u0026thinsp;=\u0026thinsp;5.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Table S4), whereas crop and year effects were not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In year 1, canola yields ranged from 1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in the Control to 3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e under the SecBioUrea treatment, representing a 173% increase over the unfertilized control (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Intermediate yields were observed under MixBioUrea (2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and PriBioUrea (2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In year 2, treatment differences in canola yield were not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), with yields ranging from 1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 to 3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In wheat, yield responses were generally lower and showed no statistically significant treatment effects in either year (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In year 1, the highest mean wheat yield (3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was observed under SecBioUrea, while the Control was 1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). However, high variability across treatments and years precluded consistent statistical significance. These results suggest that while canola yield responded positively to treatment, particularly in year 1, wheat yield was less responsive and more variable across years.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCrop yield (tonnes ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) for canola and wheat under different treatments. Values are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (n\u0026thinsp;=\u0026thinsp;4). Treatments sharing the same letter within a depth are not significantly different (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCanola (tonnes/ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eWheat (tonnes/ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear 2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear 2\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\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePriBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixBio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.2. Nitrogen use efficiency indices\u003c/h2\u003e\n \u003cp\u003eNitrogen use efficiency, NR, and AE varied substantially among treatments and between crops (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In canola, NUE ranged from 2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 kg grain kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e N under the MixBio treatment to 13.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 kg grain kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e N under SecBioUrea. SecBioUrea also obtained the highest AE (5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 kg grain kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e N), outperforming other PPMB-based treatments including MixBioUrea (2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8) and PriBioUrea (0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5) (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Although Urea exhibited a relatively high AE (9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0), this estimate was accompanied by high variability and lower NR compared to biosolid-urea blends. In wheat, Urea achieved the highest NUE (32\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 kg grain kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e N) and AE (6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5), likely due to the lower N application rate (56.0 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Among PPMB based treatments, SecBioUrea again demonstrated superior efficiency, with an NUE of 15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 and AE of 4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7. MixBioUrea and PriBioUrea yielded moderate AE values of 1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 and 1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8, respectively (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Nitrogen response followed similar trends. In canola, SecBioUrea achieved the highest NR (1,488 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), exceeding Urea (639 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and all other treatments. In wheat, MixBioUrea and SecBioUrea observed NR values above 500 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, suggesting moderate responsiveness to fertilization despite greater inter-treatment variability. Collectively, these findings indicate that co-application of secondary PPMB with urea enhanced N recovery and productivity in canola and provided comparable N efficiency to inorganic N fertilizers in wheat, although with crop-specific and interannual variation.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eNitrogen use efficiency (NUE), nitrogen response (NR), and agronomic efficiency (AE) of canola and wheat under pulp and paper mill biosolids (PPMB)-based and urea treatments. Values are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (n\u0026thinsp;=\u0026thinsp;4). Control plots received no nitrogen input.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCanola\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eWheat\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\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\u003eTreatment\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal N Applied (kg/ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNUE\u003c/p\u003e\n \u003cp\u003e(PFP-N)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNitrogen Response\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAgronomic Efficiency\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal N Applied (kg/ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNUE\u0026nbsp;(PFP-N)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNitrogen Response\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAgronomic Efficiency\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\u003eYear 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixBio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e616.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e593\u0026thinsp;\u0026plusmn;\u0026thinsp;196ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e483.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e530\u0026thinsp;\u0026plusmn;\u0026thinsp;533b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1b\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\u003eMixBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e387.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1011\u0026thinsp;\u0026plusmn;\u0026thinsp;97a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e303.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1246\u0026thinsp;\u0026plusmn;\u0026thinsp;688ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3ab\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\u003ePriBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e391.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1122\u0026thinsp;\u0026plusmn;\u0026thinsp;187a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e306.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e222\u0026thinsp;\u0026plusmn;\u0026thinsp;796b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6b\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\u003eSecBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e385.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1854\u0026thinsp;\u0026plusmn;\u0026thinsp;459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e302.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1258\u0026thinsp;\u0026plusmn;\u0026thinsp;434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\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\u003eUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e157.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;332b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e123.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e843\u0026thinsp;\u0026plusmn;\u0026thinsp;305ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYear 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixBio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e385.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e329\u0026thinsp;\u0026plusmn;\u0026thinsp;511b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e242.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e153\u0026thinsp;\u0026plusmn;\u0026thinsp;211b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9b\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\u003eMixBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e234.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e661\u0026thinsp;\u0026plusmn;\u0026thinsp;459b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e138.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214\u0026thinsp;\u0026plusmn;\u0026thinsp;115b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8b\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\u003ePriBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e230.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e324\u0026thinsp;\u0026plusmn;\u0026thinsp;816b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e139.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e186\u0026thinsp;\u0026plusmn;\u0026thinsp;249b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8b\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\u003eSecBioUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e233.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1488\u0026thinsp;\u0026plusmn;\u0026thinsp;583a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e137.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e573\u0026thinsp;\u0026plusmn;\u0026thinsp;89a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7a\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\u003eUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e639\u0026thinsp;\u0026plusmn;\u0026thinsp;535b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e226\u0026thinsp;\u0026plusmn;\u0026thinsp;181b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\n \u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e NUE (Partial Factor Productivity of N, PFP-N, kg grain kg⁻\u0026sup1; N applied), NR (Nitrogen Response, kg grain yield increase ha⁻\u0026sup1; vs. control), AE (Agronomic Efficiency or yield-based NUE, kg grain kg⁻\u0026sup1; N applied).\u003cbr\u003eControl plots = zero N input, hence NUE, NR, and AE are not applicable (N/A). Inorganic N Fertilizer treatment = Urea and Biosolids based treatments: MixBio = mixed PPMB; PriBio = Primary PPMB + urea; SecBio = Secondary PPMB + urea.\u003c/p\u003e\n \u003ch2\u003e3.2.3. Plant tissue nutrient concentration\u003c/h2\u003e\n \u003cp\u003eMacronutrient concentration specifically potassium (K), magnesium (Mg), and sulfur (S) was primarily influenced by crop type, with minimal response to treatment or year-by-treatment interactions (Table S4). Potassium accumulation varied significantly by crop (F\u0026thinsp;=\u0026thinsp;166.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and year (F\u0026thinsp;=\u0026thinsp;89.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a crop \u0026times; year interaction (F\u0026thinsp;=\u0026thinsp;6.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that seasonal effects modulated concentration efficiency (Table S4). Magnesium concentration followed a similar trend, showing strong main effects of crop (F\u0026thinsp;=\u0026thinsp;218.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and year (F\u0026thinsp;=\u0026thinsp;47.9, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but no treatment or interaction effects (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table S4). Sulfur concentration was also crop-dependent (F\u0026thinsp;=\u0026thinsp;185.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and varied with year (F\u0026thinsp;=\u0026thinsp;12.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while treatment effects were not significant (Table S4). Micronutrient concentration, including zinc (Zn), copper (Cu), and sodium (Na), also varied strongly by crop. Zinc concentrations were significantly affected by crop (F\u0026thinsp;=\u0026thinsp;136.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and year (F\u0026thinsp;=\u0026thinsp;6.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with a significant treatment \u0026times; crop interaction (F\u0026thinsp;=\u0026thinsp;2.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that PPMB based amendments may differentially influence Zn concentration depending on crop type (Table S4). Copper and sodium followed similar patterns, with significant crop effects (F\u0026thinsp;=\u0026thinsp;98.8 and 187.0, respectively; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and non-significant treatment and interaction terms (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table S4). Overall, crop identity and seasonal conditions were the dominant factors influencing nutrient accumulation, rather than N amendment type.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Integrated soil health assessment\u003c/h2\u003e\n \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.1. Multivariate Soil and Plant Function Responses\u003c/h2\u003e\n \u003cp\u003eRedundancy analysis revealed distinct treatment-driven patterns in soil chemical and biological indicators across crops. In canola systems, the first two RDA axes accounted for 17.3% and 0.1% of the total variance, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). Treatments incorporating PPMB particularly MixBioUrea and PriBioUrea were positively associated with indicators such as WFPS, CO\u003csub\u003e2\u003c/sub\u003e respiration, CEC, and micronutrient concentrations (Mn, Zn, Fe) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). In contrast, vectors for NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e and aluminium (Al) were negatively correlated with biological properties and oriented away from PPMB treatments, suggesting lower nutrient retention and biological activity under treatments lacking organic inputs (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). In wheat systems, RDA axes 1 and 2 explained 8.8% and 0.7% of the variance, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec). PPMB-based treatments (MixBio and SecBioUrea) aligned with biological and chemical properties (e.g., respiration, Zn, NO₃⁻), while Urea clustered near the origin, reflecting minimal association with measured soil properties. The RDA based on plant performance indicators showed lower explanatory power overall, with Axis 1 and Axis 2 explaining 5.6% and 0.8% of variance in wheat (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb, d). Nonetheless, PriBioUrea and SecBioUrea treatments were positively associated with plant nutrient concentration variables (e.g., P, S, Mg), indicating potential alignment between soil nutrient availability and plant demand (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb, d). Model statistics are summarized in Table S5. Adjusted R\u003csup\u003e2\u003c/sup\u003e values ranged from \u0026minus;\u0026thinsp;0.02 to 0.32 in canola and up to 0.60 for wheat (Mo), indicating moderate explanatory capacity. Significant loadings on RDA Axis 1 included Al, B, K, Mg, and Mo (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that these variables contributed substantively to treatment differentiation in the observed ordination structure (Table S5).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.2. Soil health scores and composite rankings\u003c/h2\u003e\n \u003cp\u003eComposite soil health scoring confirmed the multivariate findings, revealing distinct treatment rankings across crops (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). In canola, SecBioUrea achieved the highest yield score (90/100) and a \u0026ldquo;High\u0026rdquo; soil health score (SHS\u0026thinsp;=\u0026thinsp;70/100), followed by MixBioUrea, which scored 70 in both categories. PriBioUrea and Urea were classified as \u0026ldquo;Moderate\u0026rdquo; (SHS\u0026thinsp;=\u0026thinsp;50), with yield scores of 50 and 60, respectively (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The Control ranked lowest in canola, with yield and SHS scores of 30 and 50. In wheat, SecBioUrea again obtained the highest yield score (90), although its SHS remained \u0026ldquo;Moderate\u0026rdquo; (50). Urea achieved the highest SHS (90, \u0026ldquo;Very High\u0026rdquo;), but lower yield performance reduced its composite rank (score\u0026thinsp;=\u0026thinsp;2). MixBioUrea and PriBioUrea performed consistently across yield and SHS categories (both 70), reflecting a balance of agronomic and soil health benefits (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The Control again ranked lowest, with a yield score of 30 and SHS of 70. Final composite rankings identified SecBioUrea and MixBioUrea as the top-performing treatments across both crops, driven by their combined contributions to yield, nutrient efficiency, and soil health improvement.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of integrated pulp and paper mill biosolids (PPMB) and urea treatments on soil health indicators, elemental composition, and agronomic performance of canola and wheat.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eCanola\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eWheat\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMixBio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMixBioUrea\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePriBioUrea\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSecBioUrea\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUrea\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMixBio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMixBioUrea\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePriBioUrea\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSecBioUrea\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUrea\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\u003e\u003cstrong\u003eRDA1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDA1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDA2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDA2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1553\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1785\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ez-score (0\u0026ndash;1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ez-score (0\u0026ndash;1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSHS (0-100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSHS (0-100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSHS Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSHS Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery High\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1417\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield (0\u0026ndash;1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield (0\u0026ndash;1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield (0-100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield (0-100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoil Health Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoil Health Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinal Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinal Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eNote: Data include redundancy analysis (RDA1 and RDA2), soil attributes influencing crop yield, z-scores, normalized yield metrics, soil health scores (SHS), nutrient efficiency (NE), and composite rankings for yield, soil health, and final rank. Treatments include Control, inorganic N fertilizer (Urea), mixed PPMB (MixBio), mixed PPMB\u0026thinsp;+\u0026thinsp;urea (MixBioUrea), primary PPMB\u0026thinsp;+\u0026thinsp;urea (PriBio), and secondary PPMB\u0026thinsp;+\u0026thinsp;urea (SecBio).\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.3. Sustainability impact of PPMB-based soil amendments\u003c/h2\u003e\n \u003cp\u003eA diagram was further constructed to illustrate the integrated sustainability impacts associated with the application of pulp and paper mill biosolids (PPMB) as soil amendments (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). This synthesis was based on (i) the effects of PPMB-based treatments on key soil health properties (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), elemental composition (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e), and agronomic performance in canola and wheat (Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), and (ii) the relationships between soil properties and amendment treatments as revealed by redundancy analysis (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Specifically, PPMB amendments contributed to nutrient recycling by increasing soil NO₃⁻-N and PO₄\u0026sup3;⁻-P levels, and achieving the highest nitrogen use efficiency (NUE) and agronomic efficiency (AE) in the SecBioUrea treatment (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Soil health was improved through enhanced soil respiration and maintenance of aggregate stability, with SecBioUrea and MixBioUrea treatments showing the highest integrated soil health scores (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Crop yield stability was evident, particularly under cold soil conditions, with canola yields reaching 3.0-3.1 t/ha in SecBioUrea and wheat showing consistent performance across treatments (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). In addition, circular economy potential was demonstrated through RDA-based shifts in soil and crop responses, supporting nutrient loop closure and achieving top integrated sustainability scores (1.5\u0026ndash;2.5). The amendments also improved soil chemical balance by increasing pH and elevating Ca, Na, Zn, and Mn concentrations within safe and regulatory-compliant levels (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4.0 Discussion","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Soil physical and chemical properties in response to PPMB amendments\u003c/h2\u003e\u003cp\u003eThe PPMB and PPMB-urea treatments had minimal effects on soil physical properties such as bulk density, total porosity, and WFPS, suggesting that crop type and soil depth were the primary drivers of variation. Bulk density values remained within acceptable agronomic limits, indicating that short-term amendment did not lead to compaction or excessive soil loosening. This aligns with findings from PPMB application studies where physical soil improvement is often not observed until after several growing seasons (Zibilski et al, 2000; Chow et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Camberato et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Price and Voroney, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). For instance, Zibilski et al (2000) only noticed bulk density change after a 4- and 5-year period and increase soil stability after 3 years of PPMS application. The lack of treatment effect on the soil physical properties in our study may be attributed to the glaciated origin of the study soil that overshadowed small amendment-driven shifts coupled with the short study duration, tillage and crop rooting effects (Ehrlich et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1960\u003c/span\u003e; Hopkins and Smith; \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Blanco-Canqui and Ruis; \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, PPMB-urea blends influenced key chemical properties, including pH, total C, nitrate, phosphorus, and several micronutrients, particularly in the canola plots. The pH increase observed in PPMB treated soils especially MixBio supports prior observations that PPMB amendments can buffer soil acidity and have a liming potential (Nunes et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Rasa et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The significant accumulation of total C concentration in MixBio and PriBioUrea treatments indicates enhanced organic matter input and suggests potential for longer-term improvements in nutrient retention and microbial habitat quality (Camberato et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Gagnon et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In our study, the treatment-driven shifts in nutrient concentrations, particularly NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e and P, demonstrate that PPMB amendments can alter soil fertility dynamics, though these effects varied by depth, year, and crop.\u003c/p\u003e\u003cp\u003eNotably, nitrogen immobilization, a common occurrence in organic amendments, was reduced in treatments blended with urea, likely due to the readily available form of nitrogen provided by urea. This finding aligns with previous research showing that the co-application of PPMB with other nutrient sources can alleviate nitrogen availability constraints (Manirakiza et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Interestingly, micronutrient concentration was also responsive to treatment. The consistent elevation of Fe, Mn, and Zn concentrations under PPMB-urea treatments (MixBioUrea and SecBioUrea) in canola plots in our study suggests enhanced micronutrient release from organic residues or improved root access to trace elements (Maqueda et al., 2019). This crop-specific response likely reflects differences in rooting depth, rhizosphere chemistry, and nutrient demand between canola and wheat (Rahman and Schoenau, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Urea-alone treatments, in contrast, appeared less effective in maintaining micronutrient concentration, which could reflect dilution effects (Gajula et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) or antagonistic nutrient interactions (Abdoli, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Soil biological activity and functional indicators\u003c/h2\u003e\u003cp\u003eSoil respiration was consistently elevated PPMB-urea treatments, particularly SecBioUrea and MixBioUrea, indicating greater microbial activity and substrate availability. This supports the hypothesis that co-application of organic and mineral nitrogen sources promotes microbial growth by balancing labile C inputs with nutrient supply (Xia et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The significant treatment \u0026times; crop interaction further suggests that biological responses are modulated by crop type, likely due to differences in root exudation and nutrient concentration patterns (Wang et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Redundancy analysis confirmed the central role of PPMB-urea blends in enhancing soil biological function. In canola systems, these treatments aligned with higher soil microbial respiration, micronutrient concentrations, and cation exchange capacity, reflecting a more active and nutrient-rich soil environment. In contrast, Urea and Control treatments were associated with lower biological activity and higher NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e accumulation, indicating potential nutrient loss and lower system efficiency (Chen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These multivariate trends underscore the ecological advantage of integrating organic materials in fertility management.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Crop yield and nitrogen use efficiency\u003c/h2\u003e\u003cp\u003eCrop yield responses differed distinctly between canola and wheat. In canola, PPMB-urea treatments, particularly SecBioUrea, significantly increased yield over both the Control and Urea treatments. The 173% increase in year 1 under SecBioUrea demonstrates the agronomic potential of stabilized PPMB when applied in combination with inorganic nitrogen (Amini et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Gagnon and Ziadi, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In contrast, wheat yields were less responsive to treatment and more variable across years, suggesting either lower nutrient demand or greater sensitivity to seasonal variation in soil moisture and temperature (Z\u0026ouml;rb et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Nitrogen use efficiency metrics provided additional insights into treatment performance. In canola, SecBioUrea consistently exhibited the highest agronomic efficiency and nitrogen response, outperforming both PPMB-only and inorganic N treatments. These results suggest improved synchrony between nitrogen release and crop demand under combined applications, likely enhancing nitrogen uptake and reducing losses (Gagnon et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In wheat, although urea achieved the highest NUE, SecBioUrea remained competitive, indicating that PPMB-urea blends can match the efficiency of inorganic fertilizers when applied at rates aligned with crop demand.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Plant nutrient concentration and crop-specific patterns\u003c/h2\u003e\u003cp\u003eNutrient concentration responses were predominantly shaped by crop identity. Concentration of macronutrients such as K, Mg, and S was governed more by crop demand and seasonal effects than by treatment. This suggests that baseline fertility across treatments was sufficient to meet crop requirements or that nutrient availability was buffered by soil reserves (De Oliveira Silva et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Micronutrient concentration, particularly Zn and Mn, was more responsive to treatment and varied significantly between crops. Canola exhibited higher sensitivity to PPMB amendments, suggesting a greater capacity for micronutrient extraction or enhanced uptake mechanisms under organic fertilization regimes (Gagnon et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Shaheen and Tsadilas, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These differences highlight the need for crop-specific nutrient management strategies when using PPMB, especially where micronutrient sufficiency is a concern (Elwan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e4.5. Integrated soil health assessment\u003c/h2\u003e\u003cp\u003eComposite soil health scores and multivariate analyses demonstrated that PPMB-urea treatments, especially SecBioUrea, offer an effective strategy for enhancing both soil health and crop productivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In canola, SecBioUrea achieved the highest scores for yield and soil health, indicating strong integration of agronomic and ecological functions. In wheat, although Urea achieved the highest soil health score, this did not translate to the highest yield, suggesting a disconnect between short-term productivity and measured soil health indicators (Wu and Congreves, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) MixBioUrea performed consistently across both crops, indicating its robustness as a balanced treatment. These results reinforce the importance of selecting amendment strategies that deliver both yield gains and long-term soil improvement (Ziadi et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Tough, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The differential responses across crops emphasize the need for flexible, crop-adapted nutrient management approaches, particularly when integrating PPMB into rotational systems. In addition, our study highlights seven interconnected sustainability themes derived from soil, crop, and system-level analyses that are critical for the sustainable use of PPMB as soil amendment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003e4.6. Limitations and future directions\u003c/h2\u003e\u003cp\u003eThis study focused on short-term treatment responses and did not assess leaching losses, trace metal accumulation, or long-term changes in soil organic C pools. Moreover, the observed soil biological benefits may increase over time as PPMB-derived organic matter continues to decompose and interact with soil microbiota (Tough, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Manirakiza et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Future research should explore long-term impacts of repeated PPMB-urea applications under varying moisture and temperature regimes, as well as their implications for nutrient leaching and greenhouse gas emissions. Overall, the results support the use of co-applied PPMB and urea as an effective soil fertility management strategy. With proper formulation and application timing, these treatments can enhance nutrient use efficiency and maintain or improve soil quality, providing both environmental and agronomic benefits in intensive cropping systems.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eField-based evidence from this study confirms that PPMB are effective and sustainable soil amendments in cold-region agroecosystems. The application of PPMB improved soil physical, chemical, and biological properties while sustaining or enhancing grain yields of canola and wheat relative to inorganic (urea) treatments. These results highlight the potential of industrial PPMB valorization as a circular economy solution that delivers agronomic and environmental co-benefits (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The findings have direct relevance for nutrient management policies and soil restoration initiatives in northern cropping systems. Future multi-year trials and expanded assessments including biomass partitioning and long-term ecological monitoring are recommended to fully capture the system-wide impacts of PPMB amendments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eCRediT authorship contribution statement\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEmmanuel A. Badewa:\u003c/strong\u003e Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing - original draft, Writing - review \u0026amp; editing. \u003cstrong\u003eYifan Song:\u003c/strong\u003e Investigation, Methodology, Writing - review \u0026amp; editing. \u003cstrong\u003eXinran Duan:\u003c/strong\u003e Investigation, Methodology, Writing - review \u0026amp; editing. \u003cstrong\u003ePatrick Levasseur:\u003c/strong\u003e Investigation, Methodology, Writing - review \u0026amp; editing. \u003cstrong\u003eAmanda Diochon:\u003c/strong\u003e Investigation, Methodology, Writing - review \u0026amp; editing. \u003cstrong\u003eShawn Sexsmith:\u003c/strong\u003e Field support, Data collection, Writing - review \u0026amp; editing. \u003cstrong\u003eLisa Jones:\u003c/strong\u003e Field logistics, Data collection, Writing - review \u0026amp; editing. \u003cstrong\u003eLeigh Johnston:\u003c/strong\u003e Field logistics, Resources, Writing - review \u0026amp; editing. \u003cstrong\u003eTamsin Patience\u003c/strong\u003e: Resources, Writing - review \u0026amp; editing. \u003cstrong\u003eNathan Basiliko:\u003c/strong\u003e Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing - review \u0026amp; editing. \u003cstrong\u003eNikolai DeMartini:\u003c/strong\u003e Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing - review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eDeclaration of competing Interest\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge the financial support provided to Emmanuel A. Badewa through the Mitacs Elevate Postdoctoral Fellowship program, in partnership with the University of Toronto and Canadian Kraft Paper. We also thank Lakehead University for providing research infrastructure and institutional support. This work is part of the industrial research consortium project Effective Energy and Chemical Recovery in Pulp and Paper Mills - \u0026nbsp;III at the University of Toronto supported by Andritz, Arauco, Babcock \u0026amp; Wilcox, Canadian Kraft Paper, Cenibra, Clyde Bergemann, CMPC, ERCO Worldwide, FPinnovations, Georgia Pacific, International Paper, Irving Pulp \u0026amp; Paper, Klabin, Mercer, Rayonier, Sappi, S\u0026ouml;dra, Stora Enso, Suzano, Valmet, WestRock.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003eFunding information\u003c/p\u003e\n\u003cp\u003eFinancial support for this project was provided by Mitacs Elevate through partnership with the University of Toronto and Canadian Kraft Paper. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdoli, M., 2020. Effects of micronutrient fertilization on the overall quality of crops. 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Trends Plant Sci., 23(11), 1029-1037. https://doi.org/10.1016/j.tplants.2018.08.012\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Toronto","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":"Pulp and paper biosolids, Soil health, Sustainable soil amendment, Circular economy, Cold-climate agriculture, Biosolid valorization","lastPublishedDoi":"10.21203/rs.3.rs-8232268/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8232268/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSustainable valorization of pulp and paper mill biosolids (PPMB) can improve soil fertility and reduce reliance on synthetic fertilizers in cold-region agriculture. This two-year field study assessed PPMB as a soil amendment for canola (\u003cem\u003eBrassica napus L.)\u003c/em\u003e and wheat (\u003cem\u003eTriticum aestivum L.\u003c/em\u003e) in Northern Manitoba, Canada. Six treatments; control, urea, mixed PPMB, and three PPMB–urea combinations; were tested in a randomized complete block design. PPMB application reduced soil bulk density by 15-20% compared to urea and increased soil organic carbon by up to 21% under mixed PPMB. Microbial respiration responses were variable, and yield outcomes for both crops were comparable to or higher than urea. Redundancy analysis showed positive links between improved soil attributes and yield. The findings indicated that PPMB can sustain crop production and improve soil health in cold climates, supporting circular bioeconomy applications in northern agriculture.\u003c/p\u003e","manuscriptTitle":"Circular Valorization of Pulp and Paper Mill Biosolids for Sustainable Soil Management and Crop Production in Cold-Region Agroecosystems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 10:16:30","doi":"10.21203/rs.3.rs-8232268/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":"20528c0e-faa6-48d3-a507-197316850dfb","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58790528,"name":"Renewable Resources"},{"id":58790529,"name":"Agroecology"},{"id":58790530,"name":"Agronomy"},{"id":58790531,"name":"Forestry"}],"tags":[],"updatedAt":"2026-03-01T09:05:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 10:16:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8232268","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8232268","identity":"rs-8232268","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}