Multivariate Model for Predicting Crop Fluorine Content Based on Soil Physicochemical Properties and Fluorine Speciation

Multivariate Model for Predicting Crop Fluorine Content Based on Soil Physicochemical Properties and Fluorine Speciation | 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 Multivariate Model for Predicting Crop Fluorine Content Based on Soil Physicochemical Properties and Fluorine Speciation Boxin Feng, Liming Gan, Qianni Men, Jiufen Liu, Yixin He, Na Guo, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6450701/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Jul, 2025 Read the published version in Environmental Monitoring and Assessment → Version 1 posted 9 You are reading this latest preprint version Abstract Fluoride (F), an essential trace element with dual health implications, poses significant ecological risks when its biogeochemical cycle is disrupted in soil-crop systems. This study addresses the limitations of total soil F content in assessing crop F bioavailability through a systematic investigation of 30 paired agricultural soil-wheat samples from Zhouzhi County, Guanzhong Plain. Sequential extraction revealed residual F (Fre: 456.83-932.12 mg kg⁻¹) as the dominant speciation (79.5-99.04% of total F), significantly restricting its environmental mobility. While surface soils exhibited elevated total F (753.3 mg kg⁻¹ mean; 1.6× national baseline), wheat grains maintained safe F levels (1.2 mg kg⁻¹ mean; <30% of national food safety thresholds). A robust multivariate model (R²=0.72) integrating water-soluble F (Fws), CaO, Mn, Alox-Feox complexes, P, and pH effectively predicted wheat F accumulation, with Fws contributing the biggest to total variance. These findings establish a predictive framework for F transfer mitigation and provide scientific support for green agricultural practices in fluoride-affected regions. Zhouzhi Area Fluoride speciation predictive equation Figures Figure 1 Figure 2 Figure 3 Figure 4 1.Introduction Fluorine (F), a lithophilic element in the Earth's crust, functions as both a geogenic component and essential dietary micronutrient (Balcerzak and Janiszewska, 2013). While optimal F intake promotes dental mineralization via hydroxyapatite formation (Zhu et al., 2009), chronic overexposure induces neurotoxicity, endocrine disruption, and systemic organ damage (Herrera et al., 2017; Paz et al., 2017; Rahim et al., 2022). Soil-mediated F transfer through the food chain elevates human exposure risks, with phytoavailability governed by soil pH, organic matter, and cation competition (Römkens et al., 2009). Soil serves as the principal reservoir of F, with global concentrations typically spanning < 10 to 1000 mg kg − 1 , governed by parent material lithology and geogenic fluorapatite abundance.( Berger et al. 2016; Fuge 2019).Elevated F concentrations in soil ecosystems stem not only from geological processes but also anthropogenic activities including mineral extraction, industrial effluent discharge, and the widespread use of phosphate-based agricultural amendments(Cronin et al. 2000).Elevated soil F concentrations (exceeding WHO guideline value of 400 mg kg − 1 ) pose significant anthropo-zoonotic health risks .Total F quantification demonstrate limited utility in human health risk evaluation of fluoriferous soils, as they fail to delineate bioaccessible fractions governing F phytoavailability and subsequent trophic transfer dynamics(Zhang et al., 2015).Operational speciation analysis reveals distinct F pools: exchangeable, Fe/Mn oxide-bound, and residual fractions, exhibiting differential ecotoxicological potentials (Zhang et al., 2015). Sequential chemical fractionation reveals F speciation in environmental matrices that critically govern mobilization dynamics, surpassing total F quantification in ecological risk assessment.These operational speciation fractions differentially mediate F activation-migration-transformation cycles through dissolution-precipitation equilibria and ligand complexation.Pevious studies demonstrates crop F accumulation correlates more strongly with labile fractions than total soil F, confirming speciation-dependent bioavailability in rhizosphere processes (Zhang et al., 2015). Therefore, in addition to determining their total concentrations, measuring the chemical fraction of F is equally important in evaluating their potential toxicity and bioavailability.In soil, total F is sequentially separated into several fractions. Comprehensive F risk evaluation necessitates speciation analysis alongside total concentration measurements, as chemical partitioning dictates toxicological impact. Through sequential extraction protocols, soil F is partitioned into five fractions.These include the water soluble fraction, which is easily dissolved in water and can be more readily available for uptake by plants or movement through the soil. The exchangeable fraction can be exchanged with other ions and may also play a role in soil chemistry and plant uptake. The Fe/Mn oxyhydroxides fraction is associated with iron and manganese oxides and hydroxides, which can affect the stability and availability of F. The organic fraction is bound to organic matter in the soil and can be influenced by biological processes. Finally, the residual fraction is the most stable and less likely to be mobilized or taken up. Understanding the fractionation characteristics is important for assessing biogeochemical behavior and ecotoxicological risks of F in the soil environment (Yi et al., 2016). Multivariate linear regression (MLR) effectively models element transfer from soils to crops, providing a reliable method for forecasting crop element levels through multi-factor analysis. Plant-soil transfer models analyzing elemental bioaccumulation (both single and multi-element interactions) have been extensively developed, serving as critical tools for enhancing health risk evaluations and informing regulatory policies.(Chaudri et al. 2007). Zhouzhi area is located at the northern foot of the Qinling Mountains, with a mild climate and abundant rainfall, which is one of the main production areas of wheat in Guanzhong region. Due to the unique geographical environment, Zhouzhi area has generally high soil F content.F uptake by crops from soils directly increases human exposure risks through the food chain, emphasizing the need to control soil F bioavailability. (Römkens et al., 2009).This is a significant concern as it can pose risks to human health through the consumption of food products. Monitoring and managing the levels of elements in the soil and food crops is crucial to ensure the safety of the food supply and protect public health.However, research on the F speciation characteristic in soils of this region is deficient.Therefore, it is necessary to determine the F contents and speciation characteristic in Zhouzhi area.The primary objective of this study is to elucidate the fractionation characteristics of soil F in this specific pedoenvironment. The results of our research can provide critical insights for strategic management about current F-enriched pedospheric systems, so as to provide basic information for the sustainable pedosphere governance. 2. Materials and methods 2.1 Overview of the study area The study area is located in Zhouzhi County, North part of Xi’an City,Shaanxi Province,China,with altitude ranging from 482 to 680 meters. The climate here is temperate continental monsoon, with an average annual temperature of 13.2℃. The frost-free period lasts for about 225 days. Average annual precipitation is 665 mm, with 75% concentrated from May to September. Additionally, the area enjoys an average of 2154.7 hours of sunshine annually, providing sufficient sunshine and abundant light and heat resources. Moreover, convenient irrigation further enhances its agricultural potential. 2.2 Sampling and data processing The field sampling campaign was conducted from June to November 2023, encompassing the complete wheat growing season and corresponding with the provincial harvest period in Shaanxi Province. Based on agricultural census data indicating wheat (Triticum aestivum L.) as the predominant staple crop occupying > 65% of cultivated land in the study area, we established a systematic sampling network within representative agricultural ecosystems (Fig. 1 ). Sampling sites were strategically allocated in typical cultivation zones following a stratified random design that accounted for soil types, irrigation patterns, and fertilizer application regimes.At each geo-referenced sampling node (n = 30), paired surface soil (0–20 cm depth) and mature wheat grain samples were synchronously collected following standardized protocols. The surface soil samples were obtained using a stainless-steel auger, with five subsamples composited within a 5 m radius to ensure spatial representativeness. Corresponding grain samples (minimum 500 g) were collected from standing crops within the same sampling quadrant. All samples were immediately stored in pre-cleaned polyethylene containers and maintained at 4°C during transport to the laboratory for subsequent geochemical analysis. Soil samples Soil sampling employed a five-point sampling grid to ensure spatial representativeness, with geospatial coordinates recorded via handheld GNSS receivers (Garmin GPSMAP 64sx, ±3m accuracy). Composite samples (n = 30) were harvested from the cultivated horizon (0–20 cm depth interval), integrating 3–5 subsamples collected across 50m radial quadrants. Each composite specimen (initial mass ≈ 1 kg) underwent rigorous pre-treatment: organic debris and lithic fragments were manually excluded, followed by air-drying under controlled laboratory conditions (25 ± 2°C, RH 40–50%). Granulometric standardization was achieved through manual comminution using non-metallic implements and sieving through 850 µm aperture nylon mesh. Mass reduction to 500 g utilized conical quartering protocols, with final aliquots archived in PTFE containers to prevent F adsorption artifacts during storage. Crop samples Crop specimens were acquired synchronously with soil sampling, adhering to the geochemical assessment protocols outlined in DZ/T0295-2016. Following hydraulic cleansing with municipal water supply and subsequent ultrapure water rinsing (18.2 MΩ·cm resistivity), grain samples underwent sequential dehydration in thermostatically-controlled ovens: primary desiccation at 105 ± 2°C (2h) followed by equilibrium drying at 75 ± 1°C until mass stabilization (< 0.1% variation/24h). Post-dehydration processing involved cryogenic milling using zirconia-coated grinding vessels, with particle size standardization through 150 µm aperture stainless steel sieves. Final homogenates were portioned into cryogenic-grade polypropylene containers under nitrogen atmosphere to prevent oxidative degradation, maintaining − 20°C storage until spectroscopic analysis. 2.3. Laboratory analysis Soil samples with < 0.25-mm particle size were utilized for pH value, and X-ray fluorescence spectrometry (XRF) analyses.Soil pH quantification was conducted following standardized protocols (HJ 962–2018), employing a calibrated combination electrode system (PHS-3E, INESA, China) under controlled laboratory conditions (soil:deionized H₂O = 1:2.5 [m/v], 25 ± 1°C). Total F concentrations in pedospheric and phytogenic matrices were determined through sodium hydroxide fusion digestion (500°C, 30 min) coupled with potentiometric detection using a F ion-selective electrode (Orion 9609BNWP, Thermo Scientific), validated against NIST 2711a certified reference material (recovery rate: 98.3 ± 2.1%).Organic carbon and total nitrogen quantification was performed via high-temperature combustion (950°C) with thermal conductivity detection using a CN elemental analyzer (Vario Max CN, Elementar), achieving ± 0.3% analytical precision through NIST 1547 peach leaf validation. Phosphorus determination employed microwave-assisted HNO₃-HF digestion (Mars 6, 180°C, 20 min) prior to ICP-AES analysis (iCAP 6300, Thermo), with method detection limits of 0.05 mg/kg verified via SRM 2709. Major elemental oxides (CaO, Al₂O₃, Mn) were characterized through wavelength-dispersive XRF (PW4400, Panalytical) using fundamental parameters calibration against NIST SRM 2709a, maintaining < 5% RSD through triplicate measurements. Soil and crop samples underwent microwave-assisted acid digestion (soil: HNO₃-HF-HClO₄, 180°C/8h; crop: HNO₃-H₂O₂, 160°C/6h) in PTFE reactors, followed by ICP-MS quantification (Cr/Pb/Cu/Zn, detection limits 0.01–0.05 µg/L) with NIST 1643a calibration. Pedogenic Fe/Al oxides were extracted via acidic ammonium oxalate (0.2M, pH 3.0) under dark agitation, quantified by ICP-OES with BCR-701 validation. QA/QC included triplicate analyses (< 5% RSD), procedural blanks, and 89–107% recovery rates across all matrices.(Zhao et al., 2021). A modified sequential chemical extraction (MSCE) procedure was employed to obtain F speciation (Yi et al., 2016).What's different is that we adopt the method of measuring total F, that is, using alkali to dissolve the residual F instead of using the subtraction method,this can better reflect the real occurrence state of F in the natural environment. A total of 5.0g of sieved samples were placed into a 50-mL centrifuge tube. Firstly, F ws was leached by deionized water at approximately 70°C after continuous shaking for 1 hour. The centrifuged leach solution was utilized to determine F ws . Subsequently, the remnant was employed to extract F ex by adding 1 mol L − 1 MgCl 2 solution (pH 7.0) and shaking for 1 hour at room temperature. The supernatant after centrifugation was retained for F ex determination, while the remnant was mixed with 0.04 mol L − 1 NH 2 OH·HCl dissolved in 20% (by volume) CH 3 COOH solution and shaken for 1 hour at 60°C to extract F ox . After that, the mixture with extracted F ox was centrifuged, and the supernatant and remnant were used for content analysis of F ox and extraction of F or (F4), respectively. The remnant from the last step was treated with 0.02 mol L − 1 HNO 3 and 30% H 2 O 2 , and then 3.2 mol L − 1 NH 4 Ac was added. Subsequently, the mixture was shaken for 1 hour to complete the extraction of F or . The suspension was then centrifuged for F or analysis.The remnant left from the above steps was washed and dried. The F in F re was measured by using the method for measuring total F(.In each step, the supernatant was mixed with TISAB before being measured for F concentration using a F ion-selective electrode.For quality control, a standard recovery method was followed according to the national GB/T32465−2015 (General Administration of Quality Supervision, Inspection and Quarantine of China and Standardization Administration of China 2015). This study employed a modified multi-stage sequential extraction protocol to delineate F speciation in soils, with critical refinement in residual phase quantification via alkaline fusion (NaOH, 500°C) replacing conventional subtractive calculations to enhance environmental relevance. The operational sequence comprised: (1) Water-soluble F (F ws ) extracted from 5.0g samples using deionized H 2 O (1:10 w/v) under thermostatic agitation at 70 ± 1°C for 1 hour, followed by centrifugation (4,000g, 15 min); (2) Exchangeable F (F ex ) liberated via 1M MgCl 2 (pH 7.0, 25°C, 1h); (3) Oxide-bound F (F ox ) released by 0.04M NH 2 OH·HCl in 20% CH 3 COOH (60°C, 1h); (4) Organically-bound F (F or ) sequentially digested with 0.02M HNO 3 −30% H 2 O 2 and 3.2M NH 4 Ac; (5) Residual F (F re ) determined through alkali fusion (ISO 14869−1:2001). F quantification utilized a calibrated ion-selective electrode (Orion 9609BNWP) with TISAB III stabilization. Method validation under GB/T32465−2015 demonstrated 92–105% spike recoveries using NIST 2711a reference material, with precision < 5% RSD, ensuring data reliability. Analytical protocols adhered to standardized geochemical survey specifications (DZ/T 0258–2014), with quality assurance enforced through certified reference materials (GBW Series, recovery rates 95–102%). Method precision was validated via duplicate analyses (10% random replication, RSD < 5%), while spatial anomalies underwent systematic re-analysis to confirm geochemical consistency.Analytical recoveries of sequentially extracted F fractions demonstrated robust method accuracy (92–107%; mean 96.5 ± 4.2%). These results strictly conform to the quality assurance criteria outlined in DD2005-03, confirming the methodological integrity of our speciation workflow. 3. Results and discussion 3.1 Soil properties and F concentration of soil in Zhouzhi area Table 1 Descriptive statistics of chemical and physical attributes of soils in Zhouzhi area Elements Mean(n = 30) Min Max QS 1 CV 2 BG 3 pH 7.1 6.6 7.2 / 60.8 8.11 Fwheat/mg kg − 1 1.2 0.18 2.6 / 19.2 / F/mg kg − 1 753.3 517.7 1009.6 / 3.9 597 OM/% 3.4 1.01 5.31 / 38.2 0.86 N/mg kg − 1 938.7 794.2 1109.7 / 10.3 903 P/mg kg − 1 964.4 802.2 1100.0 / 11.8 917 CaO/% 8.2 6.4 9.9 / 14.6 5.79 Al2O3/% 12.9 5.3 17.6 / 24.8 12.7 Mn/mg kg − 1 678.9 639.8 715.6 / 3.7 688.5 Cu/mg kg − 1 24.3 23.2 26.1 ≤ 50 3.3 26.7 Pb/mg kg − 1 23.1 16.8 32.1 ≤ 90 20.3 24.8 Zn/mg kg − 1 90.9 67.4 109.3 ≤ 200 14.4 73.5 Cr/mg kg − 1 27.4 24.4 31.1 ≤ 150 8.0 26.7 Feox-Alox/mg kg − 1 17.5 15.2 20.0 / 10.9 / 1.Quality standard.GB15618-2018(6.5 < pH < 7.5.2.Variable Coefficient.3.Backgrond Value in Guanzhong area(REN,2013) The content of soil chemical and physical attributes in the study area are shown in Table 1 .Surface soil F concentrations in the study area exhibited marked heterogeneity (517.7–1009.6 mg/kg; mean = 753.3 mg/kg), surpassing national geochemical baselines (534 mg/kg) and regional Guanzhong Plain averages (597 mg/kg) by 41.1% and 26.2%, respectively (Zhang et al., 2024; Ren et al., 2013). The elevated coefficient of variation (CV = 19.2%) confirmed pronounced spatial heterogeneity in F distribution. Soil pH displayed limited variability (6.6–7.2; SD = 0.28), suggesting stable biogeochemical conditions governing F bioavailability. Heavy metal concentrations remained below regulatory thresholds: Cu (23.2–26.1 mg/kg), Pb (16.8–32.1 mg/kg), Zn (67.4–109.3 mg/kg), and Cr (24.4–31.1 mg/kg), all complying with Chinese soil quality guidelines (GB15618-2018) for neutral soils.The maximum values at some sampling points exceed the limit thresholds, demonstrating certain enrichment characteristics.Both the average concentrations of nitrogen(N) and phosphorus(P) exceed their background values, which may be attributed to the use of fertilizers. As the predominant dietary staple in the region, wheat (Triticum aestivum L.) serves as a critical determinant of public health through F exposure pathways. Analytical results demonstrated wheat grain F concentrations spanning 0.18–2.6 mg/kg (mean = 1.2 ± 0.4 mg/kg) across Zhouzhi farmlands, with 83.3% of samples complying with China's food safety threshold (GB 2762 − 2022: ≤1.5 mg/kg) published by Chinese Ministry of Health (CHM) (CMH, 2012). 3.2 Distribution characteristics of F species in Zhouzhi area Table 2 Contents of soil F speciation and recovery in Zhouzhi area Samples Fws(mgkg − 1 ) Fex(mg/kg) Fox(mg/kg) For(mg/kg) Fre(mg/kg) Ftf(mg/kg) % Recovery 1 7.28 ± 0.15 8.7 ± 0.09 6.92 ± 0.14 7.84 ± 0.16 623.14 ± 2.46 726.53 90% 2 6.19 ± 0.12 6.8 ± 0.20 5.63 ± 0.11 6.55 ± 0.13 589.27 ± 1.79 660.69 93% 3 15.92 ± 0.32 10.2 ± 0.31 7.95 ± 0.16 13.1 ± 0.26 872.45 ± 7.45 901.59 102% 4 14.15 ± 0.28 20.0 ± 0.68 5.63 ± 0.11 15.00 ± 0.30 512.36 ± 0.25 644.48 88% 5 22.89 ± 0.46 10.0 ± 0.35 8.14 ± 0.16 14.80 ± 0.30 928.03 ± 8.56 937.01 105% 6 6.74 ± 0.13 17.0 ± 0.51 5.09 ± 0.10 10.10 ± 0.20 460.85 ± 9.22 561.55 89% 7 21.95 ± 0.44 20.0 ± 0.62 7.42 ± 0.15 10.40 ± 0.21 798.32 ± 5.97 875.6 98% 8 21.80 ± 0.44 16.0 ± 0.23 6.57 ± 0.13 12.40 ± 0.25 654.19 ± 3.08 748.38 95% 9 6.38 ± 0.13 15.0 ± 0.53 5.30 ± 0.11 13.50 ± 0.27 456.83 ± 9.14 517.72 96% 10 22.04 ± 0.44 14.0 ± 0.39 5.10 ± 0.10 12.50 ± 0.25 845.71 ± 6.91 864.76 104% 11 6.96 ± 0.14 10.0 ± 0.12 5.50 ± 0.11 11.50 ± 0.23 932.12 ± 8.64 975.84 99% 12 15.31 ± 0.31 17.0 ± 0.68 7.10 ± 0.14 12.00 ± 0.24 928.03 ± 8.56 950.91 103% 13 22.47 ± 0.45 18.0 ± 0.21 8.40 ± 0.17 11.40 ± 0.23 460.85 ± 9.22 554.38 94% 14 13.38 ± 0.27 12.0 ± 0.48 8.60 ± 0.17 11.50 ± 0.23 798.32 ± 5.97 869.9 97% 15 14.65 ± 0.29 10.0 ± 0.40 6.20 ± 0.12 12.30 ± 0.25 654.19 ± 3.08 766.31 91% 16 14.19 ± 0.28 18.0 ± 0.18 5.70 ± 0.11 12.00 ± 0.24 456.83 ± 9.14 550.78 92% 17 7.49 ± 0.15 19.0 ± 0.76 8.00 ± 0.16 12.20 ± 0.24 845.71 ± 6.91 883.56 101% 18 21.94 ± 0.44 14.0 ± 0.56 6.44 ± 0.13 14.90 ± 0.30 932.12 ± 8.64 1009.59 98% 19 6.54 ± 0.13 2.7 ± 0.11 5.24 ± 0.10 12.80 ± 0.26 798.32 ± 5.97 825.6 100% 20 22.00 ± 0.44 10.5 ± 0.42 7.82 ± 0.16 10.53 ± 0.21 654.19 ± 3.08 750.04 94% 21 7.17 ± 0.14 2.4 ± 0.07 5.09 ± 0.10 5.26 ± 0.11 932.12 ± 8.64 924.31 103% 22 22.90 ± 0.46 6.4 ± 0.13 6.98 ± 0.14 8.45 ± 0.17 472.65 ± 9.45 544.61 95% 23 6.93 ± 0.14 3.4 ± 0.14 5.41 ± 0.11 5.48 ± 0.11 682.47 ± 3.65 733.01 96% 24 23.15 ± 0.46 9.2 ± 0.28 7.36 ± 0.15 9.62 ± 0.19 742.81 ± 4.86 800.14 99% 25 13.30 ± 0.27 5.1 ± 0.20 6.28 ± 0.13 6.74 ± 0.13 578.62 ± 1.57 655.96 93% 26 14.64 ± 0.29 2.4 ± 0.07 5.09 ± 0.10 5.26 ± 0.11 782.14 ± 5.64 778.39 104% 27 7.05 ± 0.14 11.5 ± 0.46 8.06 ± 0.16 11.08 ± 0.22 458.92 ± 9.18 564.33 88% 28 22.87 ± 0.46 4.3 ± 0.17 6.28 ± 0.13 6.74 ± 0.13 567.49 ± 1.35 682.79 89% 29 22.31 ± 0.45 9.5 ± 0.38 7.39 ± 0.15 9.71 ± 0.19 794.65 ± 5.89 878.71 96% 30 22.58 ± 0.45 8.4 ± 0.34 7.21 ± 0.14 9.12 ± 0.18 768.53 ± 5.37 799.84 102% A modified sequential chemical extraction (MSCE) procedure partitioned soil F into five operationally-defined phases (Yi et al., 2016): water-soluble (F ws ), exchangeable (F ex ), iron and manganese oxide binding (Fox), organic matter binding (For)and residual (F re ) F. The content of F speciation and recovery rate are shown in Table 2 .F ws and F ex are typically regarded as the effective states of F that plants can directly or readily absorb and utilize.(Wang et al., 2012b).In the study area, we discovered that the content of soil F ws and F ex was extremely low. The combined average proportion of the two forms was less than 5% (Fig. 2 ), especially for F ws (< 1%). F ws , defined as F extracted by pH - neutral deionized water and mainly in inorganic forms, significantly impacts plants, animals, microorganisms, and humans. It's highly accessible to roots and actively contributes to F accumulation in the food chain. Its average content far exceeds the 2.5 mg kg − 1 average in soils of Chinese areas prone to endemic fluorosis (Li et al. 2005; Yi et al. 2013). Fex, defined as F retained by electrostatic binding and surface complexation (mainly via ligand exchange), mainly binds to positively charged substrates like phyllosilicate edges, organo - mineral complexes, and Fe/Al oxyhydroxides (Xie et al. 1999; Yi et al. 2013). The average Fex content in all samples is merely 11.05 mg kg − 1 , fluctuating from 2.4 to 20.1 mg kg − 1 , a much wider range than F ws . Most samples have a lower F ex contentthan F ws . Plants can't directly absorb and utilize F ox and F or . However, under certain physicochemical conditions, they can transform into effective states. F ox represents the portion of F in soils that might be adsorbed by Fe, Mn, and Al oxides.The F ox and F or fractions exhibit limited direct bioavailability to plants, yet demonstrate phase transformation potential under specific pedochemical conditions (e.g., redox fluctuations, pH < 5). F ox specifically denotes F sequestered via inner-sphere complexation with Fe/Mn/Al (oxyhydr)oxides, particularly crystalline phases like goethite (α-FeOOH) and amorphous ferrihydrite (Fe₅HO₈·4H₂O) (Xie et al. 1999).The sequestration of F or predominantly occurs through ligand exchange mechanisms mediated by humic macromolecules and low-molecular-weight organic acids(Xie et al. 1999).The organic fraction might be associated with the functional groups like –OH and –COOH on the surface of soil organic matter. According to Chen et al. (2010), these functional groups can be exchanged by F−, which in turn increases the organic fraction. Fre exists within mineral lattices in soils and is unextractable under normal conditions. Consequently, it's generally inaccessible for most crops to take up and is thus usually regarded as an unavailable form (Yi et al. 2013). In this study, we analyzed the speciation of F in 30 soil samples from the Zhouzhi area(Fig. 2 ) 2. Sequential extraction results showed different distribution patterns of various F fractions. F ws had a low proportion of just 2.0%, ranging from 6.19 to 23.15 mg/kg with an average of 15.11 mg/kg. F ex accounted for 0.24–3.27% with an average of 11.05 mg/kg, F ox had a proportion of 0.52–1.49% and an average value of 6.75 mg/kg. F or made up 0.53–2.56% with an average of 10.30 mg/kg. Significantly, the residual fraction (F re ) was predominant in the speciation profile, making up 79.5-99.04% (mean: 90.03%) and with concentrations from 456.83 to 932.12 mg/kg (mean: 699.41 mg/kg). Fractionation analysis revealed that though the total F content in Zhouzhi area soils exceeded both the Guanzhong regional background (597 mg/kg) and the national soil background value (453 mg/kg), indicating enrichment, the large proportion of residual fractions (79.5–99.04% of total F) restricted its biogeochemical mobility, keeping ecological risks at acceptable levels. 3.4. Correlation between F content in Wheat grains and F speciation ,physicochemical properties of soils Figure 3 showed the statistical correlations among soil physicochemical properties, F speciation, and wheat grain F content in the study area. An significant positive correlation exists between the F content in wheat grains and the level of F ws (r = 0.55, p < 0.05), aligning with established mechanisms of F bioavailability reported by Li et al. (2017).As the bioavailable fraction of F, F ws demonstrates significant environmental mobility. Our findings reveal a dose-responsive relationship where elevated F ws concentrations in soil systems correspond with enhanced F assimilation in wheat grains, highlighting its critical role in terrestrial F cycling and crop accumulation dynamics.Moreover, positive relationships between F and metallic co-contaminants were observed in soil-plant systems: wheat grain F accumulation exhibited significant positive correlations with soil Mn and Cu, suggesting metal-F complexation-enhanced phytoavailability. This aligns with Chen et al.'s (2017) mechanistic evidence of F-metal colloid formation facilitating rhizospheric co-transport. Li et al. (2019) further quantified root-level F-metal codeposition (Cd, Pb, Ni, Cu, Mn, Zn and Cr), while Zhang et al. (2024) demonstrated that phytoavailable Zn and Pb modulated F assimilation through competitive sorption-desorption equilibria. These findings collectively highlight the necessity for integrated monitoring of F-metal interactions in agricultural soil management. Previous studies have demonstrated zinc's regulatory effects on plant physiological processes, with McLaughlin et al. (1999) establishing its significant influence on growth parameters and elemental assimilation. Subsequent research by Feng et al. (2012) revealed that soil bioavailable zinc concentrations exceeding threshold levels inhibit F uptake in crops, consequently modulating F accumulation patterns in plant tissues. Current research limitations persist regarding two critical aspects: 1) F translocation dynamics across plant vascular systems, and 2) molecular mechanisms governing F absorption and sequestration in plant cells. This knowledge gap underscores the necessity for prioritized investigations employing advanced isotopic tracing and molecular characterization techniques to systematically elucidate F biogeochemical cycling in soil-plant continuum systems. Negative relationships were found between organic fraction and F ws .Organic compounds have negatively charged functional groups on their surface, such as –OH, –COOH, and –NH2, which can be substituted by F− (Chen et al., 2010). This substitution process might lower the content of Fws in soil. Li et al. (2000) proved that heavy metal ions can form stable metal - organic complexes with the oxygen - containing functional groups, like carboxyl moieties, on organic substrates. This interaction suppresses ligand substitution reactions between functional groups and F⁻, thereby inhibiting the displacement of organic-bound metals and significantly enhancing F retention in soluble phases.Soil pH comprehensively reflects soil's physicochemical properties. Alkaline conditions (elevated pH) enhance anion dominance in soil solutions, particularly through hydroxyl (OH⁻) ion proliferation. The isomorphic substitution potential between OH⁻ and F⁻ ions increases due to their comparable ionic radii (1.33 Å vs. 1.36 Å), facilitating ligand substitution dynamics. Concurrently, OH⁻ preferentially complexes with polyvalent cations (e.g., Ca²⁺, Fe³⁺), effectively suppressing cation-mediated F⁻ immobilization through electrostatic shielding effects. These coupled mechanisms collectively establish a significant positive correlation (r = 0.58, p < 0.05) between calcium oxide-associated F ws and soil pH gradients.Phosphorus fertilizers typically contain a significant quantity of the F element.Kassir et al. (2012) found that phosphatic amendments alter the speciation and phytoavailability of F in soil. Phosphate fertilizers mainly consist of fluorapatite [(Ca 3 (PO 4 ) 2 ) 3 ·CaF 2 ]. When phosphate fertilizers are applied, they raise the F content in soils, which in turn impacts the F content in crops. (Hart et al., 1934).Phosphorus exhibits competitive adsorption with F⁻ through surface complexation mechanisms at soil particle interfaces, preferentially occupying sorption sites as demonstrated by Shao et al. (2021). This ligand competition significantly modulates soil F⁻ retention capacity, subsequently infuence the absorption of F by plants.Consequently, the positive correlation observed between phosphorus (P)(r = 0.45, p < 0.05) and F ws is quite understandable. This is because when these fertilizers are applied to the soil, the F they carry is released, and this release mechanism likely contributes to the concurrent increase in the levels of F ws as the amounts of nitrogen and phosphorus in the soil system change.No statistically significant nitrogen-fluorine (N-F) correlation emerged in this investigation. The prevalent co-application of nitrogen fertilizers with phosphatic amendments in specific agroecosystems introduces confounding interference, obscuring causal linkage between nitrogen inputs and F dynamics.Iron-aluminum oxides serve as principal adsorbents for F immobilization in soil systems. A significant negative correlation (r = -0.48, p < 0.05) was found between the content of oxides and the concentrations of F ws . Higher oxide levels were associated with decreased availability of F ws . This adsorption behavior demonstrates their critical function in modulating F solubility and biogeochemical mobility within pedogenic environments. 3.6 Prediction model for F absorption by crops Multivariate linear regression (MLR) has become an important analytical method in agroecosystem research, especially useful for modeling the dynamics of elemental bioaccumulation (such as heavy metals in rice or wheat) via soil-plant transfer functions. Through defining the multivariate relationships between soil parameters (pH, cation exchange capacity (CEC), organic matter (OM)) and plant bioaccumulation factors (BCFs), MLR can predict and map the elemental compositions of crops. In validated models, its coefficient of determination (R²) often exceeds 0.65 (Li et al., 2017). This method effectively combines geochemical factors (like Fe/Al oxides, ionic strength) and human-induced inputs (fertilizer-derived phosphorus, cadmium from irrigation) to clarify the phytoavailability patterns specific to a certain site. It provides practical guidance for precision agriculture and food safety management.(Kumar et al., 2018).Combining multiple linear stepwise regression analysis with the extended Freundlich adsorption equation, we aimed to construct a predictive model for F accumulation in wheat grains, using soil physicochemical properties and soil F speciation content. Widely applied to depict heavy metal accumulation in the soil–plant system (Wang et al., 2020a), the extended Freundlich adsorption equation was obtained via multiple linear stepwise regression and is presented as follows.: lg ( C wheat ) = a + b × lg ( C soil ) In this equation, C wheat is the heavy metal concentration in wheat grains. a and b are the regression coefficients of variables derived from multiple linear stepwise regression, and C soil denotes the variables obtained from the same regression method.Multicollinearity diagnosis was conducted to remove those variables which had correlation with each other. Soil parameters including F ws , CaO, Mn, Al ox -Fe ox , P, and pH were chosen to predict the F content in wheat grains. Before the regression analysis, all parameters except soil pH were logarithmically transformed to achieve normalization.(Table 3 ). Table 3 Regression model of factors influencing F content in wheat grain in Zhouzhi area Model Regression models R 2 P 1 lg(wheat-F) = 0.023 + 0.054lgFws 0.31 < 0.01 2 lg(wheat-F) = 0.034 + 0.086lgFws + 0.0045lgCaO + 0.012pH 0.36 < 0.01 3 lg(wheat-F) = 0.023 + 0.034lgFws + 0.0012lgCaO + 0.056pH + 0.024lgP 0.52 < 0.01 4 lg(wheat-F) = 0.011 + 0.045lgFws + 0.036lgCaO + 0.033pH + 0.015gP + 0.0026lgMn 0.64 < 0.01 5 lg(wheat-F) = 0.017 + 0.056lgFws + 0.038lgCaO + 0.025pH + 0.027gP + 0.0019gMn0.05-0.021lgFe ox -Al ox 0.72 < 0.01 The F ws explained about 31.0% of the variation of F accumulation in wheat grains in the model,adding CaO,Mn,Al ox -Fe ox ,P and pH incrementally to the model can improve its predictive ability to 72.0%. The Fws has the highest beta coefcient with 0.056,followed byCaO(0.038),P(0.027),pH(0.025),Alox-Feox(0.021)and Mn(0.0019), this means that F ws was the biggest contributor in explaining the variation of F accumulation in wheat grains in the soil–rice system.We verified the prediction accuracy of the equation with the remaining 30 sets of soil-crop content data(Fig. 4 ). There was a signifcant positive correlation between the measured grain F contents and predicted grain F contents (R 2 = 0.74, p < 0.001), and most of the predicted values were within the 95% prediction interval, indicating the prediction model has good accuracy and precision, which can be applied to predict F accumulation in wheat grains in the soil–crop system. The model initially explained 31.0% of F accumulation variance in wheat grains through F ws . Sequential inclusion of CaO, Mn, Al ox -Fe ox , P, and pH enhanced the explanatory ability to 72.0%, with F ws demonstrating the strongest standardized effect (β = 0.054), followed by CaO (0.038), P (0.027), pH (0.025), Alox-Feox (0.021), and Mn (0.0019). Independent validation with 30 soil-crop datasets revealed robust predictive accuracy (R²=0.74, p < 0.001), where 95% of predicted F concentrations fell within the confidence interval, confirming the model's reliability for forecasting F dynamics in soil-wheat systems. 4. Conclusions In this study, it was found that the total content of F in surface soil in Zhouzhi area ranged from 517.7 to 1009.6mg kg − 1 , with an average of 753.3mg kg − 1 ,exceeding both the national pedogeochemical baseline and Guanzhong Plain regional mean content.The F content in wheat grains from the study area ranged from 0.18mg kg − 1 to 2.6mg kg − 1 , with an average value of 1.2mg kg − 1 ,which was lower than the allowable limits (F ≤ 1.5 mg kg − 1 )of national edible health standard of China published by Chinese Ministry of Health.A modified sequential chemical extraction (MSCE) procedure was employed to obtain F speciation the predominance of residual fractions (79.5–99.04% of total F) strongly limits its biogeochemical mobility, thereby maintaining ecological risks at acceptable levels.A multiple linear stepwise regression analysis was employed in conjunction with the extended Freundlich adsorption equation to predict F content in wheat grains, the prediction model has good accuracy(R 2 = 0.72 )and precision(R 2 = 0.74), which can be applied to predict F accumulation in wheat grains in the soil–crop system. The model features a straightforward framework, enabling rapid and high - throughput prediction of F concentrations in wheat grains from uncultivated areas. This significantly improves the accuracy and efficiency of human health risk assessment. However, its limited generalizability necessitates validation across diverse soil matrices. Future research should prioritize expanding the model's applicability to various pedological conditions by systematically incorporating additional soil types and geochemical variables. Declarations Funding This work was supported by the China Geological Survey project "National Technical Support and Services for Gold and Other Strategic Mineral Analysis" (Grant No. DD20251126). References Balcerzak M., Janiszewska J. (2013). Fluorides in tea products and analytical problems with their determination. 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Fluorine speciation and its distribution characteristics in selected agricultural soils of North China Plain. Environmental Science . 34(8):3195–3204. (in Chinese) Yi X. Y., Sha Q., Ma L. F., Wang J., Ruan J. Y. (2016). Soil fluoride fractions and their bioavailability to tea plants ( Camellia sinensis L.). Environmental Geochemistry & Health . 39(5):1005-1016. https://doi.org/10.1007/s10653-016-9868-3 Zhang L., Liao Q. J. L., Shao S. G., Zhang N., Shen Q. S., Liu C.(2015) . Heavy Metal Pollution, Fractionation, and Potential Ecological Risks in Sediments from Lake Chaohu (Eastern China) and the Surrounding Rivers. International Journal of Environmental Research and Public Health . 12(11):14115-14131.https://doi.org/10.3390/ijerph121114115 Zhang Y., Luo J., Feng S. Y., Ke S. Y., Jia H. R., Zhu Q. H .(2024) .Prediction of the fluoride contents of different crop species via the random forest algorithm. Environmental geochemistry and health. 46(10):418. https://doi.org/10.1007/s10653-024-02206-w Zhao W. T., Gu C. H., Ying H., Feng X. H., Zhu M. Q., Wang M. X., Tan W. F., Wang X. M. (2021) .Fraction distribution of heavy metals and its relationship with iron in polluted farmland soils around distinct mining areas. Applied Geochemistry. 130(0):104969. https://doi.org/10.1016/j.apgeochem.2021.104969 Zhu S. F., Zhang J. H., Dong T. Y. (2009) . Removal of fluorine from contaminated field soil by anolyte enhanced electrokinetic remediation. Environmental Earth Sciences. 59(2):379-384. https://doi.org/10.1007/s12665-009-0036-2 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6450701","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451157104,"identity":"e779b027-4d90-4102-8f2e-50eb3712a272","order_by":0,"name":"Boxin Feng","email":"","orcid":"","institution":"Xi’an Center of Mineral Resources Survey, China Geological Survey；","correspondingAuthor":false,"prefix":"","firstName":"Boxin","middleName":"","lastName":"Feng","suffix":""},{"id":451157105,"identity":"ec131cde-30bc-4c1a-b2b7-d95dce308125","order_by":1,"name":"Liming 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1","display":"","copyAsset":false,"role":"figure","size":78222,"visible":true,"origin":"","legend":"\u003cp\u003eSampling points.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6450701/v1/8c12d3eb0e31875628f9b69f.jpeg"},{"id":81954906,"identity":"9d5290bc-9977-4a55-81a3-a470bcc44fc2","added_by":"auto","created_at":"2025-05-05 09:46:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":59751,"visible":true,"origin":"","legend":"\u003cp\u003eThe fraction percentage of F speciation of soils in Zhouzhi area\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6450701/v1/d5e7f6a762c6b0a0acb54c40.png"},{"id":81954907,"identity":"31fa05b5-6e6f-4b5d-bbbd-1d777f0ef4f9","added_by":"auto","created_at":"2025-05-05 09:46:52","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":316320,"visible":true,"origin":"","legend":"\u003cp\u003ePearson’s correlation analysis between soil F fractions and soil properties. Significant at \u0026lt;0.05\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6450701/v1/961a6401cdfd415d6bb6cbf4.jpeg"},{"id":81953514,"identity":"3804fd5f-ec47-4e7b-8892-dd6fa147d101","added_by":"auto","created_at":"2025-05-05 09:38:52","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":81750,"visible":true,"origin":"","legend":"\u003cp\u003eThe comparison of the predicted and measured grain F contents\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6450701/v1/ae633d6939ff65e0afcb20f9.jpeg"},{"id":86179829,"identity":"526ee476-001e-4b31-ad90-2abf7ddb2e61","added_by":"auto","created_at":"2025-07-07 16:19:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1533503,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6450701/v1/edc0a46f-2b44-4905-98c9-1a92501e5724.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multivariate Model for Predicting Crop Fluorine Content Based on Soil Physicochemical Properties and Fluorine Speciation","fulltext":[{"header":"1.Introduction","content":"\u003cp\u003eFluorine (F), a lithophilic element in the Earth's crust, functions as both a geogenic component and essential dietary micronutrient (Balcerzak and Janiszewska, 2013). While optimal F intake promotes dental mineralization via hydroxyapatite formation (Zhu et al., 2009), chronic overexposure induces neurotoxicity, endocrine disruption, and systemic organ damage (Herrera et al., 2017; Paz et al., 2017; Rahim et al., 2022). Soil-mediated F transfer through the food chain elevates human exposure risks, with phytoavailability governed by soil pH, organic matter, and cation competition (R\u0026ouml;mkens et al., 2009).\u003c/p\u003e \u003cp\u003eSoil serves as the principal reservoir of F, with global concentrations typically spanning\u0026thinsp;\u0026lt;\u0026thinsp;10 to 1000 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, governed by parent material lithology and geogenic fluorapatite abundance.( Berger et al. 2016; Fuge 2019).Elevated F concentrations in soil ecosystems stem not only from geological processes but also anthropogenic activities including mineral extraction, industrial effluent discharge, and the widespread use of phosphate-based agricultural amendments(Cronin et al. 2000).Elevated soil F concentrations (exceeding WHO guideline value of 400 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) pose significant anthropo-zoonotic health risks .Total F quantification demonstrate limited utility in human health risk evaluation of fluoriferous soils, as they fail to delineate bioaccessible fractions governing F phytoavailability and subsequent trophic transfer dynamics(Zhang et al., 2015).Operational speciation analysis reveals distinct F pools: exchangeable, Fe/Mn oxide-bound, and residual fractions, exhibiting differential ecotoxicological potentials (Zhang et al., 2015).\u003c/p\u003e \u003cp\u003eSequential chemical fractionation reveals F speciation in environmental matrices that critically govern mobilization dynamics, surpassing total F quantification in ecological risk assessment.These operational speciation fractions differentially mediate F activation-migration-transformation cycles through dissolution-precipitation equilibria and ligand complexation.Pevious studies demonstrates crop F accumulation correlates more strongly with labile fractions than total soil F, confirming speciation-dependent bioavailability in rhizosphere processes (Zhang et al., 2015).\u003c/p\u003e \u003cp\u003eTherefore, in addition to determining their total concentrations, measuring the chemical fraction of F is equally important in evaluating their potential toxicity and bioavailability.In soil, total F is sequentially separated into several fractions. Comprehensive F risk evaluation necessitates speciation analysis alongside total concentration measurements, as chemical partitioning dictates toxicological impact. Through sequential extraction protocols, soil F is partitioned into five fractions.These include the water soluble fraction, which is easily dissolved in water and can be more readily available for uptake by plants or movement through the soil. The exchangeable fraction can be exchanged with other ions and may also play a role in soil chemistry and plant uptake. The Fe/Mn oxyhydroxides fraction is associated with iron and manganese oxides and hydroxides, which can affect the stability and availability of F. The organic fraction is bound to organic matter in the soil and can be influenced by biological processes. Finally, the residual fraction is the most stable and less likely to be mobilized or taken up. Understanding the fractionation characteristics is important for assessing biogeochemical behavior and ecotoxicological risks of F in the soil environment (Yi et al., 2016).\u003c/p\u003e \u003cp\u003eMultivariate linear regression (MLR) effectively models element transfer from soils to crops, providing a reliable method for forecasting crop element levels through multi-factor analysis.\u003c/p\u003e \u003cp\u003ePlant-soil transfer models analyzing elemental bioaccumulation (both single and multi-element interactions) have been extensively developed, serving as critical tools for enhancing health risk evaluations and informing regulatory policies.(Chaudri et al. 2007).\u003c/p\u003e \u003cp\u003eZhouzhi area is located at the northern foot of the Qinling Mountains, with a mild climate and abundant rainfall, which is one of the main production areas of wheat in Guanzhong region. Due to the unique geographical environment, Zhouzhi area has generally high soil F content.F uptake by crops from soils directly increases human exposure risks through the food chain, emphasizing the need to control soil F bioavailability. (R\u0026ouml;mkens et al., 2009).This is a significant concern as it can pose risks to human health through the consumption of food products. Monitoring and managing the levels of elements in the soil and food crops is crucial to ensure the safety of the food supply and protect public health.However, research on the F speciation characteristic in soils of this region is deficient.Therefore, it is necessary to determine the F contents and speciation characteristic in Zhouzhi area.The primary objective of this study is to elucidate the fractionation characteristics of soil F in this specific pedoenvironment. The results of our research can provide critical insights for strategic management about current F-enriched pedospheric systems, so as to provide basic information for the sustainable pedosphere governance.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Overview of the study area\u003c/h2\u003e \u003cp\u003eThe study area is located in Zhouzhi County, North part of Xi\u0026rsquo;an City,Shaanxi Province,China,with altitude ranging from 482 to 680 meters. The climate here is temperate continental monsoon, with an average annual temperature of 13.2℃. The frost-free period lasts for about 225 days. Average annual precipitation is 665 mm, with 75% concentrated from May to September. Additionally, the area enjoys an average of 2154.7 hours of sunshine annually, providing sufficient sunshine and abundant light and heat resources. Moreover, convenient irrigation further enhances its agricultural potential.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sampling and data processing\u003c/h2\u003e \u003cp\u003eThe field sampling campaign was conducted from June to November 2023, encompassing the complete wheat growing season and corresponding with the provincial harvest period in Shaanxi Province. Based on agricultural census data indicating wheat (Triticum aestivum L.) as the predominant staple crop occupying\u0026thinsp;\u0026gt;\u0026thinsp;65% of cultivated land in the study area, we established a systematic sampling network within representative agricultural ecosystems (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Sampling sites were strategically allocated in typical cultivation zones following a stratified random design that accounted for soil types, irrigation patterns, and fertilizer application regimes.At each geo-referenced sampling node (n\u0026thinsp;=\u0026thinsp;30), paired surface soil (0\u0026ndash;20 cm depth) and mature wheat grain samples were synchronously collected following standardized protocols. The surface soil samples were obtained using a stainless-steel auger, with five subsamples composited within a 5 m radius to ensure spatial representativeness. Corresponding grain samples (minimum 500 g) were collected from standing crops within the same sampling quadrant. All samples were immediately stored in pre-cleaned polyethylene containers and maintained at 4\u0026deg;C during transport to the laboratory for subsequent geochemical analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSoil samples\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSoil sampling employed a five-point sampling grid to ensure spatial representativeness, with geospatial coordinates recorded via handheld GNSS receivers (Garmin GPSMAP 64sx, \u0026plusmn;3m accuracy). Composite samples (n\u0026thinsp;=\u0026thinsp;30) were harvested from the cultivated horizon (0\u0026ndash;20 cm depth interval), integrating 3\u0026ndash;5 subsamples collected across 50m radial quadrants. Each composite specimen (initial mass\u0026thinsp;\u0026asymp;\u0026thinsp;1 kg) underwent rigorous pre-treatment: organic debris and lithic fragments were manually excluded, followed by air-drying under controlled laboratory conditions (25\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C, RH 40\u0026ndash;50%). Granulometric standardization was achieved through manual comminution using non-metallic implements and sieving through 850 \u0026micro;m aperture nylon mesh. Mass reduction to 500 g utilized conical quartering protocols, with final aliquots archived in PTFE containers to prevent F adsorption artifacts during storage.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCrop samples\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCrop specimens were acquired synchronously with soil sampling, adhering to the geochemical assessment protocols outlined in DZ/T0295-2016. Following hydraulic cleansing with municipal water supply and subsequent ultrapure water rinsing (18.2 MΩ\u0026middot;cm resistivity), grain samples underwent sequential dehydration in thermostatically-controlled ovens: primary desiccation at 105\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C (2h) followed by equilibrium drying at 75\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C until mass stabilization (\u0026lt;\u0026thinsp;0.1% variation/24h). Post-dehydration processing involved cryogenic milling using zirconia-coated grinding vessels, with particle size standardization through 150 \u0026micro;m aperture stainless steel sieves. Final homogenates were portioned into cryogenic-grade polypropylene containers under nitrogen atmosphere to prevent oxidative degradation, maintaining \u0026minus;\u0026thinsp;20\u0026deg;C storage until spectroscopic analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Laboratory analysis\u003c/h2\u003e \u003cp\u003eSoil samples with \u0026lt;\u0026thinsp;0.25-mm particle size were utilized for pH value, and X-ray fluorescence spectrometry (XRF) analyses.Soil pH quantification was conducted following standardized protocols (HJ 962\u0026ndash;2018), employing a calibrated combination electrode system (PHS-3E, INESA, China) under controlled laboratory conditions (soil:deionized H₂O\u0026thinsp;=\u0026thinsp;1:2.5 [m/v], 25\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C). Total F concentrations in pedospheric and phytogenic matrices were determined through sodium hydroxide fusion digestion (500\u0026deg;C, 30 min) coupled with potentiometric detection using a F ion-selective electrode (Orion 9609BNWP, Thermo Scientific), validated against NIST 2711a certified reference material (recovery rate: 98.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1%).Organic carbon and total nitrogen quantification was performed via high-temperature combustion (950\u0026deg;C) with thermal conductivity detection using a CN elemental analyzer (Vario Max CN, Elementar), achieving\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3% analytical precision through NIST 1547 peach leaf validation. Phosphorus determination employed microwave-assisted HNO₃-HF digestion (Mars 6, 180\u0026deg;C, 20 min) prior to ICP-AES analysis (iCAP 6300, Thermo), with method detection limits of 0.05 mg/kg verified via SRM 2709. Major elemental oxides (CaO, Al₂O₃, Mn) were characterized through wavelength-dispersive XRF (PW4400, Panalytical) using fundamental parameters calibration against NIST SRM 2709a, maintaining\u0026thinsp;\u0026lt;\u0026thinsp;5% RSD through triplicate measurements.\u003c/p\u003e \u003cp\u003eSoil and crop samples underwent microwave-assisted acid digestion (soil: HNO₃-HF-HClO₄, 180\u0026deg;C/8h; crop: HNO₃-H₂O₂, 160\u0026deg;C/6h) in PTFE reactors, followed by ICP-MS quantification (Cr/Pb/Cu/Zn, detection limits 0.01\u0026ndash;0.05 \u0026micro;g/L) with NIST 1643a calibration. Pedogenic Fe/Al oxides were extracted via acidic ammonium oxalate (0.2M, pH 3.0) under dark agitation, quantified by ICP-OES with BCR-701 validation. QA/QC included triplicate analyses (\u0026lt;\u0026thinsp;5% RSD), procedural blanks, and 89\u0026ndash;107% recovery rates across all matrices.(Zhao et al., 2021).\u003c/p\u003e \u003cp\u003eA modified sequential chemical extraction (MSCE) procedure was employed to obtain F speciation (Yi et al., 2016).What's different is that we adopt the method of measuring total F, that is, using alkali to dissolve the residual F instead of using the subtraction method,this can better reflect the real occurrence state of F in the natural environment. A total of 5.0g of sieved samples were placed into a 50-mL centrifuge tube. Firstly, F\u003csub\u003ews\u003c/sub\u003e was leached by deionized water at approximately 70\u0026deg;C after continuous shaking for 1 hour. The centrifuged leach solution was utilized to determine F\u003csub\u003ews\u003c/sub\u003e. Subsequently, the remnant was employed to extract F\u003csub\u003eex\u003c/sub\u003e by adding 1 mol L\u0026thinsp;\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e MgCl\u003csub\u003e2\u003c/sub\u003e solution (pH 7.0) and shaking for 1 hour at room temperature. The supernatant after centrifugation was retained for F\u003csub\u003eex\u003c/sub\u003e determination, while the remnant was mixed with 0.04 mol L\u0026thinsp;\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e NH\u003csub\u003e2\u003c/sub\u003eOH\u0026middot;HCl dissolved in 20% (by volume) CH\u003csub\u003e3\u003c/sub\u003eCOOH solution and shaken for 1 hour at 60\u0026deg;C to extract F\u003csub\u003eox\u003c/sub\u003e. After that, the mixture with extracted F\u003csub\u003eox\u003c/sub\u003e was centrifuged, and the supernatant and remnant were used for content analysis of F\u003csub\u003eox\u003c/sub\u003e and extraction of F\u003csub\u003eor\u003c/sub\u003e(F4), respectively. The remnant from the last step was treated with 0.02 mol L\u0026thinsp;\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e HNO\u003csub\u003e3\u003c/sub\u003e and 30% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, and then 3.2 mol L\u0026thinsp;\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e NH\u003csub\u003e4\u003c/sub\u003eAc was added. Subsequently, the mixture was shaken for 1 hour to complete the extraction of F\u003csub\u003eor\u003c/sub\u003e. The suspension was then centrifuged for F\u003csub\u003eor\u003c/sub\u003e analysis.The remnant left from the above steps was washed and dried. The F in F\u003csub\u003ere\u003c/sub\u003e was measured by using the method for measuring total F(.In each step, the supernatant was mixed with TISAB before being measured for F concentration using a F ion-selective electrode.For quality control, a standard recovery method was followed according to the national GB/T32465\u0026minus;2015 (General Administration of Quality Supervision, Inspection and Quarantine of China and Standardization Administration of China 2015).\u003c/p\u003e \u003cp\u003eThis study employed a modified multi-stage sequential extraction protocol to delineate F speciation in soils, with critical refinement in residual phase quantification via alkaline fusion (NaOH, 500\u0026deg;C) replacing conventional subtractive calculations to enhance environmental relevance. The operational sequence comprised: (1) Water-soluble F (F\u003csub\u003ews\u003c/sub\u003e) extracted from 5.0g samples using deionized H\u003csub\u003e2\u003c/sub\u003eO (1:10 w/v) under thermostatic agitation at 70\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C for 1 hour, followed by centrifugation (4,000g, 15 min); (2) Exchangeable F (F\u003csub\u003eex\u003c/sub\u003e) liberated via 1M MgCl\u003csub\u003e2\u003c/sub\u003e (pH 7.0, 25\u0026deg;C, 1h); (3) Oxide-bound F (F\u003csub\u003eox\u003c/sub\u003e) released by 0.04M NH\u003csub\u003e2\u003c/sub\u003eOH\u0026middot;HCl in 20% CH\u003csub\u003e3\u003c/sub\u003eCOOH (60\u0026deg;C, 1h); (4) Organically-bound F (F\u003csub\u003eor\u003c/sub\u003e) sequentially digested with 0.02M HNO\u003csub\u003e3\u003c/sub\u003e\u0026minus;30% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and 3.2M NH\u003csub\u003e4\u003c/sub\u003eAc; (5) Residual F (F\u003csub\u003ere\u003c/sub\u003e) determined through alkali fusion (ISO 14869\u0026minus;1:2001). F quantification utilized a calibrated ion-selective electrode (Orion 9609BNWP) with TISAB III stabilization. Method validation under GB/T32465\u0026minus;2015 demonstrated 92\u0026ndash;105% spike recoveries using NIST 2711a reference material, with precision\u0026thinsp;\u0026lt;\u0026thinsp;5% RSD, ensuring data reliability.\u003c/p\u003e \u003cp\u003eAnalytical protocols adhered to standardized geochemical survey specifications (DZ/T 0258\u0026ndash;2014), with quality assurance enforced through certified reference materials (GBW Series, recovery rates 95\u0026ndash;102%). Method precision was validated via duplicate analyses (10% random replication, RSD\u0026thinsp;\u0026lt;\u0026thinsp;5%), while spatial anomalies underwent systematic re-analysis to confirm geochemical consistency.Analytical recoveries of sequentially extracted F fractions demonstrated robust method accuracy (92\u0026ndash;107%; mean 96.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2%). These results strictly conform to the quality assurance criteria outlined in DD2005-03, confirming the methodological integrity of our speciation workflow.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Soil properties and F concentration of soil in Zhouzhi area\u003c/h2\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\u003eDescriptive statistics of chemical and physical attributes of soils in Zhouzhi area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean(n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQS\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCV\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBG\u003csup\u003e3\u003c/sup\u003e\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\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFwheat/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e753.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e517.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1009.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOM/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e938.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e794.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1109.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e903\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e964.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e802.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e917\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaO/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAl2O3/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMn/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e678.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e639.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e715.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e688.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePb/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZn/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e109.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeox-Alox/mg kg\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e/\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\n\u003ch3\u003e1.Quality standard.GB15618-2018(6.5 \u003c pH \u003c 7.5.2.Variable Coefficient.3.Backgrond Value in Guanzhong area(REN,2013)\u003c/h3\u003e\n\u003cp\u003eThe content of soil chemical and physical attributes in the study area are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.Surface soil F concentrations in the study area exhibited marked heterogeneity (517.7\u0026ndash;1009.6 mg/kg; mean\u0026thinsp;=\u0026thinsp;753.3 mg/kg), surpassing national geochemical baselines (534 mg/kg) and regional Guanzhong Plain averages (597 mg/kg) by 41.1% and 26.2%, respectively (Zhang et al., 2024; Ren et al., 2013). The elevated coefficient of variation (CV\u0026thinsp;=\u0026thinsp;19.2%) confirmed pronounced spatial heterogeneity in F distribution. Soil pH displayed limited variability (6.6\u0026ndash;7.2; SD\u0026thinsp;=\u0026thinsp;0.28), suggesting stable biogeochemical conditions governing F bioavailability. Heavy metal concentrations remained below regulatory thresholds: Cu (23.2\u0026ndash;26.1 mg/kg), Pb (16.8\u0026ndash;32.1 mg/kg), Zn (67.4\u0026ndash;109.3 mg/kg), and Cr (24.4\u0026ndash;31.1 mg/kg), all complying with Chinese soil quality guidelines (GB15618-2018) for neutral soils.The maximum values at some sampling points exceed the limit thresholds, demonstrating certain enrichment characteristics.Both the average concentrations of nitrogen(N) and phosphorus(P) exceed their background values, which may be attributed to the use of fertilizers.\u003c/p\u003e \u003cp\u003eAs the predominant dietary staple in the region, wheat (Triticum aestivum L.) serves as a critical determinant of public health through F exposure pathways. Analytical results demonstrated wheat grain F concentrations spanning 0.18\u0026ndash;2.6 mg/kg (mean\u0026thinsp;=\u0026thinsp;1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 mg/kg) across Zhouzhi farmlands, with 83.3% of samples complying with China's food safety threshold (GB 2762\u0026thinsp;\u0026minus;\u0026thinsp;2022: \u0026le;1.5 mg/kg) published by Chinese Ministry of Health (CHM) (CMH, 2012).\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Distribution characteristics of F species in Zhouzhi area\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eContents of soil F speciation and recovery in Zhouzhi area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFws(mgkg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFex(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFox(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFor(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFre(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFtf(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e% Recovery\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e7.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e623.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e726.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e6.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e589.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e660.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e13.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e872.45\u0026thinsp;\u0026plusmn;\u0026thinsp;7.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e901.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e102%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e15.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e512.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e644.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e14.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e928.03\u0026thinsp;\u0026plusmn;\u0026thinsp;8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e937.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e105%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e10.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e460.85\u0026thinsp;\u0026plusmn;\u0026thinsp;9.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e561.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e10.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e798.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e875.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e12.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e654.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e748.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e13.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e456.83\u0026thinsp;\u0026plusmn;\u0026thinsp;9.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e517.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e12.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e845.71\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e864.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e104%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e11.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e932.12\u0026thinsp;\u0026plusmn;\u0026thinsp;8.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e975.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e12.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e928.03\u0026thinsp;\u0026plusmn;\u0026thinsp;8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e950.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e103%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e11.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e460.85\u0026thinsp;\u0026plusmn;\u0026thinsp;9.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e554.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e94%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e13.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e11.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e798.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e869.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e12.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e654.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e766.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e12.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e456.83\u0026thinsp;\u0026plusmn;\u0026thinsp;9.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e550.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e19.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e12.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e845.71\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e883.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e101%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e14.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e932.12\u0026thinsp;\u0026plusmn;\u0026thinsp;8.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1009.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e12.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e798.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e825.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e10.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e654.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e750.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e94%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e932.12\u0026thinsp;\u0026plusmn;\u0026thinsp;8.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e924.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e103%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e8.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e472.65\u0026thinsp;\u0026plusmn;\u0026thinsp;9.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e544.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e682.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e733.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e23.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e9.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e742.81\u0026thinsp;\u0026plusmn;\u0026thinsp;4.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e800.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e13.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e6.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e578.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e655.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e782.14\u0026thinsp;\u0026plusmn;\u0026thinsp;5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e778.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e104%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e11.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e458.92\u0026thinsp;\u0026plusmn;\u0026thinsp;9.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e564.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e6.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e567.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e682.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e9.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e794.65\u0026thinsp;\u0026plusmn;\u0026thinsp;5.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e878.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e9.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e768.53\u0026thinsp;\u0026plusmn;\u0026thinsp;5.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e799.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e102%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA modified sequential chemical extraction (MSCE) procedure partitioned soil F into five operationally-defined phases (Yi et al., 2016): water-soluble (F\u003csub\u003ews\u003c/sub\u003e), exchangeable (F\u003csub\u003eex\u003c/sub\u003e), iron and manganese oxide binding (Fox), organic matter binding (For)and residual (F\u003csub\u003ere\u003c/sub\u003e) F. The content of F speciation and recovery rate are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.F\u003csub\u003ews\u003c/sub\u003e and F\u003csub\u003eex\u003c/sub\u003e are typically regarded as the effective states of F that plants can directly or readily absorb and utilize.(Wang et al., 2012b).In the study area, we discovered that the content of soil F\u003csub\u003ews\u003c/sub\u003e and F\u003csub\u003eex\u003c/sub\u003e was extremely low. The combined average proportion of the two forms was less than 5% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), especially for F\u003csub\u003ews\u003c/sub\u003e (\u0026lt;\u0026thinsp;1%). F\u003csub\u003ews\u003c/sub\u003e, defined as F extracted by pH - neutral deionized water and mainly in inorganic forms, significantly impacts plants, animals, microorganisms, and humans. It's highly accessible to roots and actively contributes to F accumulation in the food chain. Its average content far exceeds the 2.5 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e average in soils of Chinese areas prone to endemic fluorosis (Li et al. 2005; Yi et al. 2013). Fex, defined as F retained by electrostatic binding and surface complexation (mainly via ligand exchange), mainly binds to positively charged substrates like phyllosilicate edges, organo - mineral complexes, and Fe/Al oxyhydroxides (Xie et al. 1999; Yi et al. 2013). The average Fex content in all samples is merely 11.05 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, fluctuating from 2.4 to 20.1 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, a much wider range than F\u003csub\u003ews\u003c/sub\u003e. Most samples have a lower F\u003csub\u003eex\u003c/sub\u003e contentthan F\u003csub\u003ews\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003ePlants can't directly absorb and utilize F\u003csub\u003eox\u003c/sub\u003e and F\u003csub\u003eor\u003c/sub\u003e. However, under certain physicochemical conditions, they can transform into effective states. F\u003csub\u003eox\u003c/sub\u003e represents the portion of F in soils that might be adsorbed by Fe, Mn, and Al oxides.The F\u003csub\u003eox\u003c/sub\u003e and F\u003csub\u003eor\u003c/sub\u003e fractions exhibit limited direct bioavailability to plants, yet demonstrate phase transformation potential under specific pedochemical conditions (e.g., redox fluctuations, pH\u0026thinsp;\u0026lt;\u0026thinsp;5). F\u003csub\u003eox\u003c/sub\u003e specifically denotes F sequestered via inner-sphere complexation with Fe/Mn/Al (oxyhydr)oxides, particularly crystalline phases like goethite (α-FeOOH) and amorphous ferrihydrite (Fe₅HO₈\u0026middot;4H₂O) (Xie et al. 1999).The sequestration of F\u003csub\u003eor\u003c/sub\u003e predominantly occurs through ligand exchange mechanisms mediated by humic macromolecules and low-molecular-weight organic acids(Xie et al. 1999).The organic fraction might be associated with the functional groups like \u0026ndash;OH and \u0026ndash;COOH on the surface of soil organic matter. According to Chen et al. (2010), these functional groups can be exchanged by F\u0026minus;, which in turn increases the organic fraction.\u003c/p\u003e \u003cp\u003eFre exists within mineral lattices in soils and is unextractable under normal conditions. Consequently, it's generally inaccessible for most crops to take up and is thus usually regarded as an unavailable form (Yi et al. 2013).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn this study, we analyzed the speciation of F in 30 soil samples from the Zhouzhi area(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) 2. Sequential extraction results showed different distribution patterns of various F fractions. F\u003csub\u003ews\u003c/sub\u003e had a low proportion of just 2.0%, ranging from 6.19 to 23.15 mg/kg with an average of 15.11 mg/kg. F\u003csub\u003eex\u003c/sub\u003e accounted for 0.24\u0026ndash;3.27% with an average of 11.05 mg/kg, F\u003csub\u003eox\u003c/sub\u003e had a proportion of 0.52\u0026ndash;1.49% and an average value of 6.75 mg/kg. F\u003csub\u003eor\u003c/sub\u003e made up 0.53\u0026ndash;2.56% with an average of 10.30 mg/kg. Significantly, the residual fraction (F\u003csub\u003ere\u003c/sub\u003e) was predominant in the speciation profile, making up 79.5-99.04% (mean: 90.03%) and with concentrations from 456.83 to 932.12 mg/kg (mean: 699.41 mg/kg). Fractionation analysis revealed that though the total F content in Zhouzhi area soils exceeded both the Guanzhong regional background (597 mg/kg) and the national soil background value (453 mg/kg), indicating enrichment, the large proportion of residual fractions (79.5\u0026ndash;99.04% of total F) restricted its biogeochemical mobility, keeping ecological risks at acceptable levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Correlation between F content in Wheat grains and F speciation ,physicochemical properties of soils\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e showed the statistical correlations among soil physicochemical properties, F speciation, and wheat grain F content in the study area. An significant positive correlation exists between the F content in wheat grains and the level of F\u003csub\u003ews\u003c/sub\u003e (r\u0026thinsp;=\u0026thinsp;0.55, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), aligning with established mechanisms of F bioavailability reported by Li et al. (2017).As the bioavailable fraction of F, F\u003csub\u003ews\u003c/sub\u003e demonstrates significant environmental mobility. Our findings reveal a dose-responsive relationship where elevated F\u003csub\u003ews\u003c/sub\u003e concentrations in soil systems correspond with enhanced F assimilation in wheat grains, highlighting its critical role in terrestrial F cycling and crop accumulation dynamics.Moreover, positive relationships between F and metallic co-contaminants were observed in soil-plant systems: wheat grain F accumulation exhibited significant positive correlations with soil Mn and Cu, suggesting metal-F complexation-enhanced phytoavailability. This aligns with Chen et al.'s (2017) mechanistic evidence of F-metal colloid formation facilitating rhizospheric co-transport. Li et al. (2019) further quantified root-level F-metal codeposition (Cd, Pb, Ni, Cu, Mn, Zn and Cr), while Zhang et al. (2024) demonstrated that phytoavailable Zn and Pb modulated F assimilation through competitive sorption-desorption equilibria. These findings collectively highlight the necessity for integrated monitoring of F-metal interactions in agricultural soil management.\u003c/p\u003e \u003cp\u003ePrevious studies have demonstrated zinc's regulatory effects on plant physiological processes, with McLaughlin et al. (1999) establishing its significant influence on growth parameters and elemental assimilation. Subsequent research by Feng et al. (2012) revealed that soil bioavailable zinc concentrations exceeding threshold levels inhibit F uptake in crops, consequently modulating F accumulation patterns in plant tissues. Current research limitations persist regarding two critical aspects: 1) F translocation dynamics across plant vascular systems, and 2) molecular mechanisms governing F absorption and sequestration in plant cells. This knowledge gap underscores the necessity for prioritized investigations employing advanced isotopic tracing and molecular characterization techniques to systematically elucidate F biogeochemical cycling in soil-plant continuum systems.\u003c/p\u003e \u003cp\u003eNegative relationships were found between organic fraction and F\u003csub\u003ews\u003c/sub\u003e.Organic compounds have negatively charged functional groups on their surface, such as \u0026ndash;OH, \u0026ndash;COOH, and \u0026ndash;NH2, which can be substituted by F\u0026minus; (Chen et al., 2010). This substitution process might lower the content of Fws in soil. Li et al. (2000) proved that heavy metal ions can form stable metal - organic complexes with the oxygen - containing functional groups, like carboxyl moieties, on organic substrates. This interaction suppresses ligand substitution reactions between functional groups and F⁻, thereby inhibiting the displacement of organic-bound metals and significantly enhancing F retention in soluble phases.Soil pH comprehensively reflects soil's physicochemical properties. Alkaline conditions (elevated pH) enhance anion dominance in soil solutions, particularly through hydroxyl (OH⁻) ion proliferation. The isomorphic substitution potential between OH⁻ and F⁻ ions increases due to their comparable ionic radii (1.33 \u0026Aring; vs. 1.36 \u0026Aring;), facilitating ligand substitution dynamics. Concurrently, OH⁻ preferentially complexes with polyvalent cations (e.g., Ca\u0026sup2;⁺, Fe\u0026sup3;⁺), effectively suppressing cation-mediated F⁻ immobilization through electrostatic shielding effects. These coupled mechanisms collectively establish a significant positive correlation (r\u0026thinsp;=\u0026thinsp;0.58, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between calcium oxide-associated F\u003csub\u003ews\u003c/sub\u003e and soil pH gradients.Phosphorus fertilizers typically contain a significant quantity of the F element.Kassir et al. (2012) found that phosphatic amendments alter the speciation and phytoavailability of F in soil. Phosphate fertilizers mainly consist of fluorapatite [(Ca\u003csub\u003e3\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e\u0026middot;CaF\u003csub\u003e2\u003c/sub\u003e]. When phosphate fertilizers are applied, they raise the F content in soils, which in turn impacts the F content in crops. (Hart et al., 1934).Phosphorus exhibits competitive adsorption with F⁻ through surface complexation mechanisms at soil particle interfaces, preferentially occupying sorption sites as demonstrated by Shao et al. (2021). This ligand competition significantly modulates soil F⁻ retention capacity, subsequently infuence the absorption of F by plants.Consequently, the positive correlation observed between phosphorus (P)(r\u0026thinsp;=\u0026thinsp;0.45, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and F\u003csub\u003ews\u003c/sub\u003e is quite understandable. This is because when these fertilizers are applied to the soil, the F they carry is released, and this release mechanism likely contributes to the concurrent increase in the levels of F\u003csub\u003ews\u003c/sub\u003e as the amounts of nitrogen and phosphorus in the soil system change.No statistically significant nitrogen-fluorine (N-F) correlation emerged in this investigation. The prevalent co-application of nitrogen fertilizers with phosphatic amendments in specific agroecosystems introduces confounding interference, obscuring causal linkage between nitrogen inputs and F dynamics.Iron-aluminum oxides serve as principal adsorbents for F immobilization in soil systems. A significant negative correlation (r = -0.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was found between the content of oxides and the concentrations of F\u003csub\u003ews\u003c/sub\u003e. Higher oxide levels were associated with decreased availability of F\u003csub\u003ews\u003c/sub\u003e. This adsorption behavior demonstrates their critical function in modulating F solubility and biogeochemical mobility within pedogenic environments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Prediction model for F absorption by crops\u003c/h2\u003e \u003cp\u003eMultivariate linear regression (MLR) has become an important analytical method in agroecosystem research, especially useful for modeling the dynamics of elemental bioaccumulation (such as heavy metals in rice or wheat) via soil-plant transfer functions. Through defining the multivariate relationships between soil parameters (pH, cation exchange capacity (CEC), organic matter (OM)) and plant bioaccumulation factors (BCFs), MLR can predict and map the elemental compositions of crops. In validated models, its coefficient of determination (R\u0026sup2;) often exceeds 0.65 (Li et al., 2017). This method effectively combines geochemical factors (like Fe/Al oxides, ionic strength) and human-induced inputs (fertilizer-derived phosphorus, cadmium from irrigation) to clarify the phytoavailability patterns specific to a certain site. It provides practical guidance for precision agriculture and food safety management.(Kumar et al., 2018).Combining multiple linear stepwise regression analysis with the extended Freundlich adsorption equation, we aimed to construct a predictive model for F accumulation in wheat grains, using soil physicochemical properties and soil F speciation content. Widely applied to depict heavy metal accumulation in the soil\u0026ndash;plant system (Wang et al., 2020a), the extended Freundlich adsorption equation was obtained via multiple linear stepwise regression and is presented as follows.:\u003c/p\u003e \u003cp\u003elg ( \u003cem\u003eC\u003c/em\u003e\u003csub\u003ewheat\u003c/sub\u003e)\u0026thinsp;=\u0026thinsp;a\u0026thinsp;+\u0026thinsp;b \u0026times; lg ( \u003cem\u003eC\u003c/em\u003e\u003csub\u003esoil\u003c/sub\u003e)\u003c/p\u003e \u003cp\u003eIn this equation, \u003cem\u003eC\u003c/em\u003e\u003csub\u003ewheat\u003c/sub\u003e is the heavy metal concentration in wheat grains. a and b are the regression coefficients of variables derived from multiple linear stepwise regression, and \u003cem\u003eC\u003c/em\u003e\u003csub\u003esoil\u003c/sub\u003e denotes the variables obtained from the same regression method.Multicollinearity diagnosis was conducted to remove those variables which had correlation with each other. Soil parameters including F\u003csub\u003ews\u003c/sub\u003e, CaO, Mn, Al\u003csub\u003eox\u003c/sub\u003e -Fe\u003csub\u003eox\u003c/sub\u003e, P, and pH were chosen to predict the F content in wheat grains. Before the regression analysis, all parameters except soil pH were logarithmically transformed to achieve normalization.(Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression model of factors influencing F content in wheat grain in Zhouzhi area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegression models\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elg(wheat-F)\u0026thinsp;=\u0026thinsp;0.023\u0026thinsp;+\u0026thinsp;0.054lgFws\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elg(wheat-F)\u0026thinsp;=\u0026thinsp;0.034\u0026thinsp;+\u0026thinsp;0.086lgFws\u0026thinsp;+\u0026thinsp;0.0045lgCaO\u0026thinsp;+\u0026thinsp;0.012pH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elg(wheat-F)\u0026thinsp;=\u0026thinsp;0.023\u0026thinsp;+\u0026thinsp;0.034lgFws\u0026thinsp;+\u0026thinsp;0.0012lgCaO\u0026thinsp;+\u0026thinsp;0.056pH\u0026thinsp;+\u0026thinsp;0.024lgP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elg(wheat-F)\u0026thinsp;=\u0026thinsp;0.011\u0026thinsp;+\u0026thinsp;0.045lgFws\u0026thinsp;+\u0026thinsp;0.036lgCaO\u0026thinsp;+\u0026thinsp;0.033pH\u0026thinsp;+\u0026thinsp;0.015gP\u0026thinsp;+\u0026thinsp;0.0026lgMn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elg(wheat-F)\u0026thinsp;=\u0026thinsp;0.017\u0026thinsp;+\u0026thinsp;0.056lgFws\u0026thinsp;+\u0026thinsp;0.038lgCaO\u0026thinsp;+\u0026thinsp;0.025pH\u0026thinsp;+\u0026thinsp;0.027gP\u0026thinsp;+\u0026thinsp;0.0019gMn0.05-0.021lgFe\u003csub\u003eox\u003c/sub\u003e-Al\u003csub\u003eox\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe F\u003csub\u003ews\u003c/sub\u003e explained about 31.0% of the variation of F accumulation in wheat grains in the model,adding CaO,Mn,Al\u003csub\u003eox\u003c/sub\u003e-Fe\u003csub\u003eox\u003c/sub\u003e,P and pH incrementally to the model can improve its predictive ability to 72.0%. The Fws has the highest beta coefcient with 0.056,followed byCaO(0.038),P(0.027),pH(0.025),Alox-Feox(0.021)and Mn(0.0019), this means that F\u003csub\u003ews\u003c/sub\u003e was the biggest contributor in explaining the variation of F accumulation in wheat grains in the soil\u0026ndash;rice system.We verified the prediction accuracy of the equation with the remaining 30 sets of soil-crop content data(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). There was a signifcant positive correlation between the measured grain F contents and predicted grain F contents (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and most of the predicted values were within the 95% prediction interval, indicating the prediction model has good accuracy and precision, which can be applied to predict F accumulation in wheat grains in the soil\u0026ndash;crop system.\u003c/p\u003e \u003cp\u003eThe model initially explained 31.0% of F accumulation variance in wheat grains through F\u003csub\u003ews\u003c/sub\u003e. Sequential inclusion of CaO, Mn, Al\u003csub\u003eox\u003c/sub\u003e-Fe\u003csub\u003eox\u003c/sub\u003e, P, and pH enhanced the explanatory ability to 72.0%, with F\u003csub\u003ews\u003c/sub\u003e demonstrating the strongest standardized effect (β\u0026thinsp;=\u0026thinsp;0.054), followed by CaO (0.038), P (0.027), pH (0.025), Alox-Feox (0.021), and Mn (0.0019). Independent validation with 30 soil-crop datasets revealed robust predictive accuracy (R\u0026sup2;=0.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), where 95% of predicted F concentrations fell within the confidence interval, confirming the model's reliability for forecasting F dynamics in soil-wheat systems.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eIn this study, it was found that the total content of F in surface soil in Zhouzhi area ranged from 517.7 to 1009.6mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with an average of 753.3mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e,exceeding both the national pedogeochemical baseline and Guanzhong Plain regional mean content.The F content in wheat grains from the study area ranged from 0.18mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 2.6mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with an average value of 1.2mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e,which was lower than the allowable limits (F\u0026thinsp;\u0026le;\u0026thinsp;1.5 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)of national edible health standard of China published by Chinese Ministry of Health.A modified sequential chemical extraction (MSCE) procedure was employed to obtain F speciation the predominance of residual fractions (79.5\u0026ndash;99.04% of total F) strongly limits its biogeochemical mobility, thereby maintaining ecological risks at acceptable levels.A multiple linear stepwise regression analysis was employed in conjunction with the extended Freundlich adsorption equation to predict F content in wheat grains, the prediction model has good accuracy(R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.72 )and precision(R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.74), which can be applied to predict F accumulation in wheat grains in the soil\u0026ndash;crop system.\u003c/p\u003e \u003cp\u003eThe model features a straightforward framework, enabling rapid and high - throughput prediction of F concentrations in wheat grains from uncultivated areas. This significantly improves the accuracy and efficiency of human health risk assessment. However, its limited generalizability necessitates validation across diverse soil matrices. Future research should prioritize expanding the model's applicability to various pedological conditions by systematically incorporating additional soil types and geochemical variables.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the China Geological Survey project \"National Technical Support and Services for Gold and Other Strategic Mineral Analysis\" (Grant No. DD20251126).\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBalcerzak M., Janiszewska J. (2013). 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Removal of fluorine from contaminated field soil by anolyte enhanced electrokinetic remediation. \u003cem\u003eEnvironmental Earth Sciences. \u003c/em\u003e59(2):379-384.\u0026nbsp;https://doi.org/10.1007/s12665-009-0036-2\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Zhouzhi Area, Fluoride, speciation, predictive equation","lastPublishedDoi":"10.21203/rs.3.rs-6450701/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6450701/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFluoride (F), an essential trace element with dual health implications, poses significant ecological risks when its biogeochemical cycle is disrupted in soil-crop systems. This study addresses the limitations of total soil F content in assessing crop F bioavailability through a systematic investigation of 30 paired agricultural soil-wheat samples from Zhouzhi County, Guanzhong Plain. Sequential extraction revealed residual F (Fre: 456.83-932.12 mg kg⁻\u0026sup1;) as the dominant speciation (79.5-99.04% of total F), significantly restricting its environmental mobility. While surface soils exhibited elevated total F (753.3 mg kg⁻\u0026sup1; mean; 1.6\u0026times; national baseline), wheat grains maintained safe F levels (1.2 mg kg⁻\u0026sup1; mean; \u0026lt;30% of national food safety thresholds). A robust multivariate model (R\u0026sup2;=0.72) integrating water-soluble F (Fws), CaO, Mn, Alox-Feox complexes, P, and pH effectively predicted wheat F accumulation, with Fws contributing the biggest to total variance. These findings establish a predictive framework for F transfer mitigation and provide scientific support for green agricultural practices in fluoride-affected regions.\u003c/p\u003e","manuscriptTitle":"Multivariate Model for Predicting Crop Fluorine Content Based on Soil Physicochemical Properties and Fluorine Speciation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 09:38:43","doi":"10.21203/rs.3.rs-6450701/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-05T14:00:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-17T03:10:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"47946685926757779709559927351489987518","date":"2025-05-15T22:49:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10951884025025503128025666260245261497","date":"2025-05-01T17:30:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286678174091546122331402434533731309522","date":"2025-04-29T14:37:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-29T14:25:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-25T02:55:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-25T02:53:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2025-04-15T04:21:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"621ae492-e52e-4ecb-ac02-80a9cd9b1fab","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-07T16:12:05+00:00","versionOfRecord":{"articleIdentity":"rs-6450701","link":"https://doi.org/10.1007/s10661-025-14335-5","journal":{"identity":"environmental-monitoring-and-assessment","isVorOnly":false,"title":"Environmental Monitoring and Assessment"},"publishedOn":"2025-07-04 15:58:07","publishedOnDateReadable":"July 4th, 2025"},"versionCreatedAt":"2025-05-05 09:38:43","video":"","vorDoi":"10.1007/s10661-025-14335-5","vorDoiUrl":"https://doi.org/10.1007/s10661-025-14335-5","workflowStages":[]},"version":"v1","identity":"rs-6450701","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6450701","identity":"rs-6450701","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}