Synergistic Inhibition Effect of Cd in Soil–Rice System from a Ca and Zn Enriched Karst Paddy: A Field-Based Study

Abstract

The geochemistry of karstic paddy soils significantly influences Cd bioavailability and its accumulation by rice. However, there is limited research on Cd translocation and accumulation in rice, grown in paddy soil with elevated CaO and Zn levels. Addressing this, a field-based study in Hanyuan County, Sichuan Province, China, examined the Cd distribution and translocation patterns across the soil–root–straw–grain continuum, aiming to elucidate how elevated CaO and Zn levels regulate Cd accumulation in grains. The geochemical characterization of the soil revealed elevated concentrations of cadmium (Cd), calcium oxide (CaO), and zinc (Zn), with mean values of 2.12 ± 2.93 mg/kg, 5.77 ± 5.80 wt.%, and 359 ± 472 mg/kg, respectively. The sequential extraction results (by Tessier) demonstrated that the distribution of Cd followed the general order: residual > Fe-Mn oxide-bound ≈ exchangeable ≈ carbonate-bound > organic matter-bound. The exchangeable Cd content ranged from 0.063 to 0.93 mg/kg, accounting for up to 21.4% of the total Cd on average. The correlation analysis, Bioconcentration Factor (BCF), and Transfer Factor (TF) of Cd in different rice tissues, and structural equation modeling (SEM) revealed that elevated CaO and Zn levels in soil exhibit synergistic effects in inhibiting Cd accumulation in grains. Specifically, the CaO in soil reduces the Cd bioavailability by the formation of carbonate-bound specie (CdF2), thereby inhibiting Cd uptake by roots. In rice tissues, Zn could limit Cd translocation, particularly from roots to straws. Consequently, the regional rice Cd exceedance rate (25.8%) was significantly lower than that reported for other similar karst soils in China (over 50%).

1. Introduction

Cadmium (Cd), a highly toxic metal with significant bioaccumulation potential, is a widespread contaminant in agricultural soils [1,2]. A recent nationwide survey conducted by the Ministry of Ecology and Environment of China revealed that approximately 16% of soils are contaminated based on China’s soil environmental quality limits, with Cd being the most severely contaminated metal [3]. The karst regions in southwestern China represent a critical region for Cd contamination, with over 235,000 km² exhibiting average concentrations approximating 2 mg/kg, primarily attributable to the distinctive geochemical processes of carbonate weathering [4,5,6,7].

Rice is a recognized Cd-accumulating crop species. Chronic exposure to “Cd-contaminated rice” can cause Itai-Itai disease, pulmonary edema, skeletal lesions, and various cancers [8,9]. The recurrent “Cd-contaminated rice” incidents have sparked substantial food safety concerns in recent years. For instance, the rice cultivation regions in Chongzhou City, Sichuan Province, exhibited approximately 100% prevalence of rice Cd exceeding 0.2 mg/kg [10]. Similarly, Tongling District, Anhui Province [11] and Jiangxi Province [12] reported mean Cd concentrations substantially surpassing the 0.2 mg/kg threshold. Notably, mean rice Cd levels exceeding 1 mg/kg were observed in the Diaojiang River Basin, Guangxi Province [13], Shaoguan City, Guangdong Province [14], and Duyun City, Guizhou Province [15].

The soil’s physicochemical properties govern the Cd bioavailability, with the Cd²⁺ and CdCl⁺ species exhibiting the highest absorption efficiency by rice roots [16]. In alkaline soil, Cd predominantly exists as CdHCO₃⁺ and CdCO₃, demonstrating limited mobility and bioavailability [17,18]. Conversely, acidic soil promotes the formation of mobile Cd species, primarily Cd²⁺ and CdCl⁺, resulting in enhanced Cd bioavailability [16,19]. Consequently, soil amendment with cost-effective alkaline materials, such as CaCO₃ and CaO, has been proven to effectively mitigate Cd uptake in rice through dual mechanisms involving increased soil pH, and facilitated the precipitation of CdCO₃ [20,21,22]. Meanwhile, the primary transporters mediating Cd uptake in rice roots and straws share significant functional overlap with those involved in Zn uptake [23,24], establishing a competitive inhibition mechanism where Zn²⁺ effectively suppresses Cd²⁺ absorption at the soil–root interface and subsequent translocation of Cd from roots to aerial tissues [25]. Recent investigations have demonstrated a synergistic interaction between Ca and Zn in mitigating Cd accumulation in rice. When implemented in conjunction with lime-induced substrate stabilization, Zn fertilizer application significantly enhances the antagonistic interaction between Zn²⁺ and Cd²⁺, achieving a 73% reduction in Cd accumulation in grains [26]. This remediation strategy demonstrates 32% greater efficacy compared to a single lime application [27].

The pedogenesis in karstic regions exhibits distinctive geochemical properties due to variations in parent rock and weathering intensity [28,29,30]. Substantial evidence indicates Cd in karstic soils predominantly resides in residual fractions with low bioavailability [31,32,33]. Alternatively, some findings report 30~60% bioavailable Cd fraction in pristine, uncontaminated karstic soils [6,34]. Karstic soils consistently demonstrate elevated CaO concentrations and alkaline pH conditions, while exhibiting significant variability in Zn content [5,28,29,30,35]. These distinct geochemical conditions may substantially influence Cd accumulation in rice [34,36,37,38]. Nevertheless, there are few reports on Cd translocation and accumulation of rice plants in paddy soil with elevated CaO and Zn levels. Sichuan Province, a major rice-cultivating region in China, is characterized by many rice fields in the carbonate outcrops [39] and concurrently suffers from soil Cd contamination [10]. Despite this, systematic investigations into Cd bioavailability in karstic soils, especially in paddy soil with elevated CaO and Zn, and the natural regulation of soil–rice Cd accumulation remain scarce. To address this, paired soil–root–straw–grain samples were collected from karstic alluvial and eluvial paddy soils in Hanyuan County, Sichuan Province, focusing on high Cd, CaO, and Zn geological background. The research aimed to: (1) quantify soil Cd contamination levels and spatial distribution characteristics; and (2) determine rice Cd contamination levels and potential regulatory mechanisms of soil geochemical properties on grain Cd accumulation.

2. Materials and Methods

2.1. Study Area

The study area is situated in the central region of Hanyuan County, Sichuan Province, southwestern China (102°35′12”–102°41′46” E, 29°24′34”–29°30′4” N), characterizing a subtropical monsoon climate with a mean temperature of 17.9 °C and around 741.8 mm precipitation. The study area features distinct topographic variations, transitioning from the Liusha River valley to an adjacent alluvial area and subsequently to upland eluvium, encompassing an elevational gradient of approximately 2000 m (Figure 1a). The lowland alluvium primarily consists of paddy soils derived from calcareous residue, while the adjacent eluvium is dominated by limestone soils [40] (Figure 1c). The alluvium on both sides of the Liusha River comprise agricultural and residential zones, accounting for more than 90% of regional paddy fields. The region primarily cultivates indica-type three-line hybrid rice. Characterized by a dry-hot valley climate with relative aridity, the area relies mainly on natural rainfall for irrigation. Consequently, paddy fields are typically lined with impermeable plastic film at a depth of 50 cm to prevent water loss. The eastern sector of the study area is located at the northern endpoint of the Sichuan–Yunnan–Guizhou Pb-Zn metallogenic belt [41], containing many small-scale Pb-Zn mines. Additionally, the southwestern region hosts several small-scale coal mines (Figure 1).

Figure 1. Distribution of sampling sites. Soil type data were obtained from the National Earth System Science Data Center (https://www.geodata.cn, accessed on 12 April 2025). (a) Sample point distribution map; (b) Geographic distribution of the study area; (c) Soil type distribution map.

2.2. Sample Collection and Preparation

A systematic sampling scheme was implemented on paddy limestone soils, with equally spaced points collecting integrated soil–rice tissue (root, straw, grain) samples from the eluvial (S1–S14) and alluvial (S15–S31) layers, ensuring complete spatial coverage (Figure 1). Paddy soil samples were collected during the rice heading stage in June 2024, a critical period for rice Cd uptake from soil [42,43]. The samples were collected from the 5–15 cm layer by removing the surface layer (5 cm). Rice tissue samples were collected during the mature stage from corresponding sampling locations (September 2024). The soil and rice tissue samples collected by this institute were obtained while the soil was submerged, in order to minimize the impact of redox condition variations on Cd speciation. Whole plants were carefully uprooted and subsequently rinsed with irrigation water, followed by deionized water to eliminate surface soil and dust particles. All samples represented mixtures, incorporating at least four sub-samples collected within a 10 m radius of each sampling point. Using ceramic scissors, plant tissues were separated, naturally air-dried, and stored in sealed polyethene bags. Air-dried soil samples were meticulously cleared of organic debris and gravel, homogenized using an agate mortar to achieve a 100-mesh particle size, and preserved in sealed polyethylene bags. Grain samples were initially crushed using a mortar, followed by husk removal. The fine-grinding rice was then manually ground and stored in sealed polyethene bags. Roots and straw samples were initially shredded using ceramic scissors and then pulverized using a milling machine before being transferred to sealed polyethene bags. All processed samples were maintained at ambient temperature under light-protected conditions until they were subjected to subsequent analytical procedures.

2.3. Chemical Analysis

All analytical procedures for rice tissues and soil samples were conducted at the geochemistry laboratory of Chengdu University of Technology. Soil pH determination was performed according to the National Standard of China [44], using a calibrated pH electrode (LEI-CI, PHSJ-3F, Shanghai, China) to measure the pH in a 1:2.5 (w/v) soil–water suspension, following established protocols. The soil bioavailable Ca (Ca_bio) content was determined according to the Chinese Agricultural Industry Standard [45]. The cation exchange capacity (CEC) was determined using the hexaamminecobalt (III) chloride extraction-spectrophotometric method as specified in China’s National Environmental Standard [46].

Soil particle size and specific surface area (SSA) were determined using laser diffraction analysis (Mastersizer 3000, Malvern Panalytical, Malvern, UK), classifying sand (>20 μm), silt (2~20 μm), and clay (<2 μm). The main composition of soil was determined using X-ray fluorescence spectrometry (XRF, Axios max, Almelo, The Netherlands). Meanwhile, the soil samples were digested using a HNO₃-HClO₄-HF mixture (6:3:2, v/v/v), with Cd and Zn measured via inductively coupled plasma mass spectrometry (ICP-MS, Lab MS 3000, LabTech, Beijing, China), and Ti, Mn, and Ca were determined by inductively coupled plasma optical emission spectrometry (ICP-OES, Avio 500, PerkinElmer, Inc., Waltham, MA, USA). Rice tissues (roots, straw, and grains) were digested with a HNO₃-HClO₄ mixture (4:1, v/v), with Zn and Cd measured via ICP-MS, and Ca was determined by ICP-OES. All samples were analyzed in triplicate for Ca, Cd, and Zn concentrations, with the reported values representing the means. The corresponding method limits of detection (LOD) and quantification (LOQ) were: Ca (0.05 and 0.15 mg/L), Cd (0.005 and 0.02 μg/L), and Zn (0.01 and 0.03 μg/L). Quality assurance was maintained through reagent blanks, duplicate samples, and certified reference materials (CRMs: GBW07557 for soil and GBW(E) 100,357 for rice). The recovery for the certified reference soil materials were 98.3%, 92.5%, and 100% for Ca, Cd, and Zn, respectively, while the recovery for Cd in the certified rice material was 98.0%.

Sequential extraction, initially developed by Tessier, et al. [47] and modified by the Chinese standard [48], was implemented to determine the speciation of Zn and Cd into five geochemical fractions: exchangeable (F1), carbonate-bound (F2), Fe-Mn oxide-bound (F3), organic matter-bound (F4), and residual fraction (F5). Detailed extraction protocols for each fraction are presented in Table S1. Cd and Zn were determined via ICP-MS.

2.4. Chemical Index of Alteration (CIA)

The CIA serves as a quantitative indicator for assessing soil weathering intensity during pedogenesis from parent bedrock [49,50]. The CIA calculation formula is:

$$CIA={\displaystyle \frac{A{\mathrm{l}}_2{O}_3}{A{\mathrm{l}}_2{O}_3+K_{2}O+N{\mathrm{a}}_{2}O+Ca{O}^{\ast }}}\times 100\%$$

(1)

where oxide contents (Al₂O₃, K₂O, Na₂O, and CaO*) are expressed as molar percentages. CaO^* is the smaller of the molar fractions of Na₂O and CaO in the sample [51].

2.5. Bioconcentration Factor and Transfer Factor of Heavy Metals

The bioconcentration factor (BCF) is defined as the ratio of metal concentration in the crop’s edible tissues and paddy soil [52], measuring the heavy metals’ bioaccumulation capacity of the plants in the soil.

$$BC{F}_{n,soil-root}={\displaystyle \frac{C_{n,root}}{C_{n,soil}}}$$

(2)

where C_n,root and C_n,soil represent the heavy metal “n” concentration (mg/kg) in roots and soil. BCF_n,soil-root represents the bioconcentration factor of heavy metal “n” from soil to root.

The translocation factor (TF) infers the mobility of heavy metals from roots to aerial plant tissues [52]:

$$T{F}_{n,root-straw}={\displaystyle \frac{C_{n,straw}}{C_{n,root}}}$$

(3)

$$T{F}_{n,straw-grain}={\displaystyle \frac{C_{n,grain}}{C_{n,straw}}}$$

(4)

where C_n,root, C_n,straw, and C_n,grain represent the heavy metal “n” concentration (mg/kg) in roots, straws, and grains, respectively. TF_n,root-straw represents the bioconcentration factor of heavy metal “n” from root to straw; TF_{n,straw-grain} represents the bioconcentration factor of heavy metal “n” from straw to grain.

2.6. Statistical Analysis

The structural equation modeling (SEM) model was employed to investigate direct and indirect effects of soil geochemical characteristics on grain Cd accumulation. All data were standardized to achieve linearity and normality. Parameters were estimated using the maximum likelihood method. Model fit was evaluated by Chi-square to degrees of freedom ratio (χ²/df), p-value, comparative fit index (CFI), and root mean square error of approximation (RMSEA) [53]. Good model fits were reflected by χ²/df < 3, p > 0.05, CFI > 0.9, and RMSEA < 0.08 [54].

3. Results

3.1. Soil Properties

Table 1 shows the geochemical characteristics of the paddy soils. The soil pH, a critical factor influencing heavy metal distribution, averages 7.57 ± 0.41, slightly higher than the levels reported in Hanyuan County and Chengdu Plain, Sichuan Province [10,55], but comparable to karstic soil in Guizhou Province, China [28]. The soil clay was 17.87%, significantly lower than both the Sichuan background soils and the documented karstic soils [56,57]. The soils exhibited moderate CEC with a mean value of 17.50 ± 5.53 cmol⁺/kg, consistent with reported karstic soils in Guizhou Province [28].

Table 1. Geochemical characteristics of the paddy soil.

Properties	Maximum	Minimum	Average ± SD	Background a
pH	8.06	6.33	7.57 ± 0.41	6.60
CEC (cmol+/kg)	30.7	4.33	17.50 ± 5.53	/
Cabio (mg/kg)	27.18	2.23	13.31 ± 6.40	/
Cd (mg/kg)	11.0	0.38	1.73 ± 2.11	0.079
Zn (mg/kg)	1950	77.6	291 ± 326	86.5
Ti (g/kg)	6.01	1.23	4.17 ± 0.94
CaO (wt. %)	27.4	0.55	5.30 ± 5.56	/
MgO (wt. %)	13.9	0.95	3.40 ± 2.60	/
CIA	80.9	65.9	74.6 ± 5.1	/
CdF1 (%)	41.8	2.1	21.4 ± 8.8	/
CdF2 (%)	40.6	3.8	19.6 ± 8.1	/
CdF3 (%)	37.7	6.9	24.0 ± 6.9	/
CdF4 (%)	5.5	-	2.1 ± 1.5	/
CdF5 (%)	64.2	16.4	32.9 ± 11.9	/
ZnF1 (%)	2.7	0.14	0.66 ± 0.63	/
ZnF2 (%)	16.4	1.5	4.0 ± 2.8	/
ZnF3 (%)	38.4	9.4	23.6 ± 8.4	/
ZnF4 (%)	6.7	-	2.3 ± 1.6	/
ZnF5 (%)	85.4	43.8	69.5 ± 9.9	/

Ca_bio: bioavailable Ca; -: not detected; /: no relevant value; ^a: [57].

The soil CaO weight percentage was 5.30 ± 5.56 wt. %, consistent with soil characteristics observed in karst regions [5,28,58]. Accordingly, the Ca_bio levels were notably high, averaging 13.31 ± 6.40 mg/kg. Notably, the MgO is 3.40 ± 2.60 wt. % in the soil exceeds the values reported for karstic soils in southwestern China [6,28,30], potentially attributable to the dolomitic bedrock in Hanyuan County.

The paddy soils contained elevated Cd concentrations (1.73 ± 2.11 mg/kg), representing around 22-fold enrichment compared to the Sichuan background [57], yet comparable to karst soils from Guangxi and Guizhou Provinces [12]. The paddy soils exhibited Zn concentrations averaging 291 ± 326 mg/kg, representing about 3.4-fold enrichment relative to Sichuan background levels and exceeding typical karstic soils in Guizhou and Guangxi Provinces [28,29,37,57]. When evaluated against the soil environmental quality risk control standards of China [59], the mean Cd level surpasses the risk screening value. Overall, 77.4% of soil samples exceeded the Cd risk screening value (notably 6.5% reaching risk intervention value), while 32.3% exceeded the Zn risk screening value (Figure 2).

Figure 2. Box plots of Cd and Zn contents in paddy soil and grain. (a) Box plot of Cd content in soil samples; (b) Box plot of Cd content in soil samples; (c) Box plot of Cd content in grain samples.

The soil particle distribution exhibited slight differentiation, with alluvial soils displaying relatively finer textures characterized by increased silt fraction proportions, while both soil layers maintained nearly identical clay content (Table S2). Notably, both Cd and Zn exhibited comparable spatial distribution patterns, with pronounced enrichment hotspots located in the eluvium (Figure S1). The average Cd content of the eluvium soil was 2.47 ± 2.95 mg/kg, ~2.2 times higher than that of the alluvial soil (1.13 ± 0.61 mg/kg). Similarly, the eluvium soil Zn content was 396 ± 462 mg/kg, which was twice as much as the alluvial soil (204 ± 93.0 mg/kg).

3.2. Fraction Distributions of Cd and Zn in Soils

Generally, the order of biological effectiveness for metal fractions is exchangeable (F1) > Fe-Mn oxide-bound (F3) > organic matter-bound (F4) > carbonate-bound (F2) > residual fraction (F5) [60]. In Table 1, soil Cd is primarily present in the residual Cd (Cd_F5), with an average content of 0.76 ± 1.45 mg/kg. Other concentrations of exchangeable Cd (Cd_F1), carbonate-bound Cd (Cd_F2), Fe-Mn oxide-bound Cd (Cd_F3), and organic matter-bound Cd (Cd_F4) were 0.29 ± 0.21, 0.35 ± 0.41, 0.44 ± 0.54, and 0.027 ± 0.020 mg/kg, respectively. That is, the Cd fraction demonstrates relative uniformity, with the following order: Cd_F5 > Cd_F3 ≈ Cd_F2 ≈ Cd_F1 > Cd_F4 (Figure 3). Notably, the Cd_F3 (24.0 ± 6.9%), Cd_F1 (21.4 ± 8.8%) and Cd_F2 (19.6 ± 8.1%) fractions constitute substantial proportions of the bulk soil Cd, exhibiting similarity to the karstic soils in Guangxi Province, China [5]. The soils exhibit moderate chemical weathering intensity (CIA = 74.6 ± 5.1), coupled with elevated concentrations of Cd_F2 (0.35 ± 0.41 mg/kg). These characteristics indicate that ongoing carbonate weathering could potentially activate substantial quantities of Cd_F2. In contrast, Zn fractions demonstrated higher concentrations and greater variability than those of Cd fractions, with average concentrations of exchangeable Zn (Zn_F1), carbonate-bound Zn (Zn_F2), Fe-Mn oxide-bound Zn (Zn_F3), and organic matter-bound Zn (Zn_F4) and residual Zn (Zn_F5) being 0.66 ± 0.63%, 4.0 ± 2.8%, 23.6 ± 8.4%, 2.3 ± 1.6%, 69.5 ± 9.9%, respectively. The minimal organic matter-bound (F4) fractions of Cd and Zn indicate limited influence of organic matter on metal mobility in the paddy soil system.

Figure 3. Percentage of soil Cd and Zn fractions.

3.3. Cd and Zn Concentrations in Root, Straws, and Grains

Table 2 presents the distribution characteristics of Cd and Zn concentrations in rice tissues. The bulk Cd and Zn concentrations in roots reached 4.71 ± 4.20 mg/kg and 80.8 ± 35.6 mg/kg, respectively. In straws, concentrations declined to 1.42 ± 4.10 mg/kg for Cd and 48.0 ± 32.4 mg/kg for Zn. The grains demonstrate the lowest metal accumulation, with 0.18 ± 0.21 mg/kg for Cd and 18.8 ± 3.90 mg/kg for Zn. Based on maximum permissible concentration of Cd (0.2 mg/kg) in rice grains (GB 2762-2022) [61], 25.8% of the grain exceeded threshold (Figure 2), a lower exceedance rate than the average rice in China (33.5%) [12] and the cultivated on karstic paddy soils (50%) [6,36]. The Zn concentration in grains is relatively safe, collectively below the Chinese food safety maximum limitation [62].

Table 2. Characteristics of Cd and Zn contents and transfer in rice tissues.

Elements	Properties	Maximum	Minimum	Average ± SD	Limitation
Cd	Roots (mg/kg)	15.6	0.36	4.71 ± 4.20
	Straws (mg/kg)	22.6	0.05	1.42 ± 4.10
	Grains (mg/kg)	0.83	0.014	0.18 ± 0.21	0.2 a
	BCFCd,root-soil	17.7	0.21	4.05 ± 3.91
	TFCd,root-straw	3.59	0.013	0.30 ± 0.69
	TFCd,straw-grain	5.79	0.004	0.90 ± 1.3
Zn	Roots (mg/kg)	150	31.1	80.8 ± 35.6
	Straws (mg/kg)	156	9.8	48.0 ± 32.4
	Grains (mg/kg)	26.9	10.9	18.8 ± 3.90	10–40 b
	BCFZn,root-soil	1.12	0.07	0.38 ± 0.24
	TFZn,root-straw	1.53	0.11	0.63 ± 0.33
	TFZn, straw-grain	1.69	0.082	0.55 ± 0.34

^a Maximum level of contaminants in foods (GB 2762-2022) [61]; ^b Standard for uses of food nutrition fortification substances (GB 14880-2012) [62].

The translocation of heavy metals from soil to grains can be conceptualized through three primary stages: soil-to-root translocation, root-to-straw transport, and straw-to-grain redistribution [23,25]. The roots displayed the highest BCF levels, with 87.1% of samples showing BCF_Cd,root-soil > 1 (Figure 4). The TF reflects the capacity of rice for metal transport and enrichment from lower to aerial tissues [63]. The results reveal that TF_{Cd,root-straw} < TF_{Cd,straw-grain}, with 6.5% of samples exhibiting TF_{Cd,root-straw} > 1 and 25.8% showing TF_{Cd,straw-grain} > 1 (Figure 4). For the Cd, the BCF_Cd,_root-soil is 4.05, with the TF_{Cd,root-straw} being 0.30, which then increases from straws to grains (TF_{Cd,straw-grain} = 0.90). In contrast, Zn demonstrates a distinct pattern, exhibiting a lower BCF_Zn,root-soil (0.38). Within rice tissues, TF_{Zn,root-straw} is 0.63, which subsequently decreases to 0.55 for TF_{Zn,straw-grain}. These reveal a clear tissue-specific partitioning of Cd and Zn in rice plants, predominant Cd sequestration in roots, and preferential Zn allocation to straws.

Figure 4. Rice tissue bioconcentration factors and transfer factors. (a) Box plot of the BCF_Cd,root-soil; (b) Box plot of the TF_{Cd,root-straw}; (c) Box plot of the TF_{Cd,straw-grain}.

4. Discussion

4.1. Migration of Cd and Zn During Erosion

Given the inherently low mobility of titanium (Ti) and aluminum (Al), the ratio of Ti/Al₂O₃ is utilized as a resistant proxy to determine the material sources of soil [5,64]. In this study, a significant linear correlation was observed between Ti and Al₂O₃ in soils (Figure S2, r = 0.83, p < 0.01), indicating that the paddy soil originates from weathering of homogeneous parent bedrock [30].

Karstic soils, characterized by thin soil layers, abundant gaps, and several bedrock fissures [56], experiencing significant erosion-induced alterations in both soil particle size and spatial patterns of metal concentrations [6,36,65]. Generally, alluvial soils should contain higher total Cd, Cd_F1, and clay content relative to eluvium, primarily due to erosion [6,36]. In this study, the alluvial and eluvial soils showed negligible differences in clay content (Table S2), but both were substantially lower than both the Sichuan background soils and well-preserved karstic soils [56,57]. However, this study revealed that eluvial soils contained roughly twice the total Cd and Zn concentrations compared to alluvial soils (Figure 5). Similarly, the Cd and Zn fractions (F2, F3, F4, and F5) in eluvial soils are roughly twice those found in alluvial soils. These suggest that soil erosion could have occurred in the study area, resulting in significant losses of Cd and Zn, particularly from the alluvial soil.

Figure 5. The Cd (a) and Zn (b) content and percentage of soil and grain fractions.

In this study, the ratios of highly mobile to low-mobility elements (total Cd/Ti and total Zn/Ti) in soils exhibited significant variations (Figure S4), with the eluvial soils showing roughly 2.6-fold and 2.1-fold increases over those in alluvium, respectively. These indicate that significant chemical migration has occurred in the alluvial soil [64,66]. However, the content of Cd_F1 in alluvial soils was comparable to that in eluvial soils. In Table S3, an independent T-test revealed no significant difference in CIA values between eluvium and alluvial karst soils (p > 0.05), indicating the extra Cd_F1 and Zn_F1 in alluvial soils cannot be attributed to differential weathering. Field investigation reveals that the study area predominantly adopts a rice–garlic rotation system, where the alternating flooded-drained cycles induce dynamic redox fluctuations that could mobilize Cd and Zn bound in fractions F2, F3, F4, and F5, promoting their transformation into the labile F1 fraction [67,68]. As reported by Tessier, Campbell and Bisson [47], the F1 fraction is strongly influenced by clays, Fe/Mn-hydrated oxides. In this study, the alluvial and eluvial soils exhibited similar characteristics in clays, Fe₂O₃, total Mn, CEC, and SSA (Table S3). The rotation system, therefore, could facilitate the transformation of other fractions into F1, facilitating their immobilization in soils and thereby compensating for the F1 fraction lost in the alluvial soil.

4.2. Effect of Soil Composition on Cd Enrichment in Rice

Studies demonstrated that over 50% of grain cultivated on karstic soils exceeds China’s food safety standard for Cd [6,36]. The predominant Cd bioavailable forms absorbed by rice roots are Cd²⁺ and CdCl⁺ (Cd_F1) [16]. In this study, despite the relatively high Cd_F1 levels (0.29 ± 0.21 mg/kg) consistent with values reported by Wei et al. [6] and Xia et al. [36], the grain Cd exceedance rate (25.8%) was significantly lower than both comparable karst soils (over 50%) [6,36] and the national average (33.5%) [12]. In addition, the independent T-test revealed no significant difference (p > 0.05) in grain Cd between the eluvial and alluvial soils. This discrepancy suggests the presence of natural Cd-regulation mechanisms in soil–rice systems.

4.2.1. Effects of Ca on Cd Uptake by Roots

Roots, the primary interface for soil-biosorption, are the initial defense against Cd toxicity in rice. After absorption by roots, Cd moves upwards through the plant tissues [69,70]. The BCF_Cd,root-soil in this study was 4.05, which was lower than the levels reported for heavily contaminated areas such as Hunan, Jiangsu, and Zhejiang Provinces [12,34,71], but higher than those observed in typical karstic regions, including Wanshan in Guizhou Province and Binyang in Guangxi Province (Table 3). This could potentially be attributed to the elevated Cd concentration in the soil. However, the BCF_Cd,root-soil remained at a relatively low level compared to karstic soils with similar Cd_F1 contents in Duyun, Guizhou Province [72] and the Xijiang River Basin, Guangxi Province [34], suggesting potential suppression of root Cd accumulation (Table 3).

Table 3. Cd content of the soil, paddy roots, and BCF values in China.

Study Area	Cdsoil (mg/kg)	Cdroot (mg/kg)	BCFCd,root-soil	References
Hanyuan, Sichuan	1.73 ± 2.11	4.71 ± 4.20	4.05 ± 3.98	This study
Duyun, Guizhou	1.18	-	~18	[72]
Yixing, Jiangsu	0.77	7.14	11.79	[73]
Dongting Lake area	0.57	0.44–87.71	9.12	[74]
Xijiang Basin, Guangxi	3.45	20.5	~6.03	[34]
Wenling, Zhejiang	0.83	~4.1	5.01	[71]
Qingyuan, Guangdong	0.44	1.27	2.89	[75]
Binyang, Guangxi	0.29	0.71	2.36	[76]
Chengdu, Sichuan	0.95	1.44	1.66	[10]
Wanshan, Guizhou	0.35	2.6	0.35	[77]

Cd_soil: the content of Cd in soil; Cd_root: the content of Cd in root.

Researchers have demonstrated that soil CaO can effectively reduce root absorption of Cd, primarily through pH-mediated reduction in Cd mobility [21,22,37]. In this study, the limited effect of CaO on alkaline soils leads to a non-significant correlation between soil pH and BCF_Cd,soil-root (Figure 6). This suggests that Cd absorption reduction via CaO in rice roots operates through mechanisms other than elevated pH, particularly given the minor pH variation observed. Notably, a significant positive correlation occurred between CaO and Cd_F2 (r = 0.64, p < 0.01, Figure 6), indicating that elevated CaO levels could promote the formation of Cd_F2, thereby reducing Cd mobility [60]. Furthermore, the analogous ionic radii and shared transport pathways of Ca²⁺ and Cd²⁺ facilitate competitive inhibition, where Ca²⁺ uptake reduces Cd²⁺ absorption [21]. In this study, Cd_root showed no significant correlation with either CaO or Ca_root, while a significant negative correlation between Cd_root and Ca_bio or Cd_F1 (r = −0.47, p < 0.01) or (Ca/Cd)_root (r = −0.96, p < 0.01) supported this potential competitive inhibition [78]. The Ca concentrations in rice roots, straw, and grains were 7.43 ± 1.85, 2.94 ± 0.33, and 0.13 ± 0.09 g/kg, respectively; meanwhile, a significant negative correlation was observed between root Ca and Cd contents (Figure S3, r = −0.401, p < 0.05). In validation, bioavailable Ca levels were notably high in the soil, averaging 13.31 ± 6.40 mg/kg, about 46-fold higher than in Cd_F1 (0.29 ± 0.21 mg/kg). As a result, the bioavailable Ca content would inhibit the Cd root absorption from the soil.

Figure 6. Correlation heatmap between soil physicochemical properties and Cd in rice tissues.

Meanwhile, the SEM model further revealed the influence of soil physicochemical characteristics on Cd accumulation in rice tissues. Elevated soil CaO content decreases Cd bioavailability through enhanced formation of Cd_F2, consequently reducing root Cd uptake (Figure 7). Simultaneously, increased CaO levels elevate available Ca²⁺, raising the Ca_bio/Cd_F1 ratio and further suppressing root Cd accumulation. Within rice tissues, Ca²⁺ competitively inhibits Cd uptake in rice root systems via ionic antagonism (Figure 6).

Figure 7. SEM framework describing the effects of soil geochemical characteristics on Cd accumulation in rice tissues.

4.2.2. Effect of Zn on Cd Transfer in Rice Tissues

Rice is a Zn-accumulating species with an intrinsic mechanism that Zn can alleviate Cd translocation [79]. The shared chemical properties and transport pathways between Zn²⁺ and Cd²⁺ facilitate competitive interactions during root absorption and subsequent tissue partitioning [26,70,80]. In this study, significant negative correlations were observed between (Zn/Cd)_root and BCF_Cd,root-soil (r = −0.68, p < 0.01), (Zn/Cd)_straw and TF_{Cd,root-straw} (r = −0.57, p < 0.01), and (Zn/Cd)_grain and TF_{Cd,straw-grain} (r = −0.53, p < 0.01), demonstrating Zn could share antagonistic mechanisms in Cd translocation within rice tissues (Figure 6). These findings are consistent with prior studies showing that higher Zn/Cd ratios decrease Cd accumulation in crops because of the antagonistic effects [81,82]. Notably, the Zn content in roots exceeds Cd by approximately 17-fold. During root-to-straw translocation, the Zn-Cd antagonism becomes more pronounced, reaching a maximum of 34-fold in straws, which ultimately reduces grain Cd accumulation (Table S4). A similar study found that a Zn/Cd molar ratio of 100 in soil could reduce Cd accumulation in grains [83]. In this study, the Zn/Cd molar ratio ranged from 78.8 to 508 (mean: 333), indicating that elevated Zn concentrations in soil may suppress Cd accumulation in grains. Moreover, foliar Zn application has been shown to more effectively inhibit Cd accumulation in grains [79,84,85], suggesting that Zn likely plays a significant role in the aboveground tissues (stems and leaves) of rice plants. Similarly, the contrasting transport patterns of Cd and Zn are particularly evident: Cd exhibits the highest BCF_Cd,root-soil but lowest TF_root-straw, while Zn demonstrates the highest TF_{Zn,root-straw} but lowest BCF_Zn,root-soil. This differential behavior suggests that straws may preferentially transport Zn, thereby enhancing antagonistic effects and inhibiting Cd translocation.

The SEM model further revealed that Zn inhibited Cd accumulation in rice tissues (Figure 7). Zn differentially suppressed Cd translocation across three critical processes: soil-to-root, root-to-straw, and straw-to-grain. Distinctively, Zn primarily inhibited Cd accumulation in straws and grains. While 87.1% of rice tissues exhibited BCF_Cd,soil-root > 1, only 6.1% showed TF_{Cd,straw-root} > 1, indicating root-to-straw translocation as the critical procedure for reduced Cd accumulation in grains [26]. This aligns with the primary action pathway of Zn (Figure 7).

5. Conclusions

This study provides insights into Cd contamination and factors inhibiting Cd accumulation in grain within the soil–rice system of Hanyuan’s karstic paddy soil in Sichuan Province, China. It revealed elevated soil Cd and Zn concentrations, with 75.8% and 36.4% of samples exceeding regulatory limits, respectively. Spatial distribution patterns showed that while eluvial soils contained approximately twice the total Cd and Zn concentrations of alluvium, both eluvial and alluvial soils exhibited comparable levels of exchangeable Cd, Zn, and clay, indicating that soil erosion played a significant role in Cd loss within alluvium. Furthermore, the analogous geochemical characteristics (clay, Fe₂O₃, total Mn, CEC, and SSA) governing the F1 fraction resulted in nearly identical Cd_F1 and Zn_F1 concentrations across both soil types.

The paddy soils contained exchangeable Cd (Cd_F1) at 0.29 ± 0.21 mg/kg. Yet, the Cd exceedance rate (25.8%) in rice grains was lower than that of comparable national (33.5%) and karst soils (over 50%), owing to the synergistic effects of Ca and Zn in inhibiting Cd accumulation. Specifically, soil CaO could reduce the Cd bioavailability by the formation of Cd_F2 species, while the resulting exchangeable Ca from high CaO content competitively inhibits Cd uptake by rice roots. Within rice tissues, Zn could antagonistically inhibit Cd translocation, particularly inhibiting Cd transfer from roots to straws. Based on the finding that soil Zn and CaO inhibit Cd accumulation in rice, the moderate application of lime and Zn is recommended as a management strategy to produce safer rice in Cd-contaminated karst regions.