Next Article in Journal
Identification and Monitoring of Irrigated Areas in Arid Areas Based on Sentinel-2 Time-Series Data and a Machine Learning Algorithm
Previous Article in Journal
Non-Commodity Agricultural Price Hedging with Minimum Tracking Error Portfolios: The Case of Mexican Hass Avocado
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 14
Issue 10
10.3390/agriculture14101694
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Influence and Mechanism of Fertilization and Irrigation of Heavy Metal Accumulation in Salinized Soils

by
Dandan Yu
1,2,
Qingfeng Miao
1,2,
Haibin Shi
1,2,*,
Zhuangzhuang Feng
1,2,
Weiying Feng
3,*,
Zhen Li
1,2 and
José Manuel Gonçalves
4
1
College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
2
High Efficiency Water-Saving Technology and Equipment and Soil and Water Environment Effect in Engineering Research Center of Inner Mongolia Autonomous Region, Hohhot 010018, China
3
School of Materials Science and Engineering, Beihang University, Beijing 100191, China
4
Polytechnic Institute of Coimbra, Coimbra Agriculture School, CERNAS—Research Centre for Natural Resources, Environment and Society, Bencanta, 3045-601 Coimbra, Portugal
*
Authors to whom correspondence should be addressed.
Agriculture 2024, 14(10), 1694; https://doi.org/10.3390/agriculture14101694
Submission received: 31 August 2024 / Revised: 18 September 2024 / Accepted: 23 September 2024 / Published: 27 September 2024
(This article belongs to the Section Agricultural Water Management)
Browse Figures
Versions Notes

Abstract

:
The impact of fertilization and irrigation on heavy metal accumulation in saline–alkali soil and its underlying mechanisms are critical issues given the constraints that soil salinization places on agricultural development and crop quality. This study addressed these issues by investigating the effects of adjusting organic fertilizer types, proportions, and irrigation volumes on the physicochemical properties of lightly to moderately saline–alkali soils and analyzing the interaction mechanisms between microorganisms and heavy metals. The results indicate that the rational application of organic fertilizers combined with supplemental irrigation can mitigate soil salinity accumulation and water deficits, and reduce the soil pH, thereby enhancing soil oxidation, promoting nitrogen transformation and increasing nitrate–nitrogen levels. As the proportion of organic fertilizers increased, heavy metal residues, enrichment, and risk indices in the crop grains also increased. Compared to no irrigation, supplemental irrigation of 22 mm during the grain-filling stage increased soil surface Cd content, Zn content, and the potential ecological risk index (HRI) by 10.2%, 3.1%, and 8%, respectively, while simultaneously reducing the heavy metal content in grains by 12–13.5% and decreasing heavy metal enrichment. Principal component analysis revealed the primary factors influencing Cu and Zn residues and Cd accumulation in the crop grains. Soil salinity was significantly negatively correlated with soil pH, organic matter, total nitrogen, and ammonium nitrogen, whereas soil organic matter, total nitrogen, ammonium nitrogen, soil pH, oxidation–reduction potential, soluble nitrogen, and microbial biomass nitrogen were positively correlated. The accumulation and residues of Zn and Cu in the soil were more closely correlated with the soil properties compared to those of Cd. Specifically, Zn accumulation on the soil surface was primarily related to aliphatic organic functional groups, followed by soil salinity. Residual Zn in the crop grains was primarily associated with soil oxidation–reduction properties, followed by soil moisture content. The accumulation of Cu on the soil surface was mainly correlated with the microbial biomass carbon (MBC), whereas the residual Cu in the crop grains was primarily linked to the soil moisture content. These findings provide theoretical insights for improving saline–alkali soils and managing heavy metal contamination, with implications for sustainable agriculture and environmental protection.

1. Introduction

Low soil organic matter content and severe salinization can inhibit crop growth and development. Therefore, appropriate irrigation and fertilization practices can reduce salt accumulation in the soil surface layer and improve fertilization efficiency [1]. Previous studies have shown that long-term application of large amounts of organic fertilizers can exacerbate soil salinization and the leaching of soluble salts [2], but it can also increase soil water content [3], improve soil nutrient status affected by salinity, promote plant growth, and increase crop yields [4]. It can also affect soil pH buffering capacity [5], reduce the sodium adsorption ratio (SAR) and thereby decrease soil salt content [6], increase the leaching of sodium under irrigation [7], enhance the inhibition of soil salinity on urea hydrolysis and nitrification [8], and reduce soil salinity in the root zone [9].
Appropriate irrigation can enhance soil organic matter and water content, increase soil microbial populations [10], significantly promote nitrogen absorption by prokaryotic microorganisms [11], and optimize the regulation of the microbial community structure [12]. The dynamic changes in soil organic carbon components following the application of organic fertilizers are a complex process influenced by various factors, such as environmental impacts, application rates, types of organic fertilizer, and soil properties [13,14]. The application of organic fertilizers leads to changes in the physical components and chemical structure of soil organic carbon [15,16].
Excessive application of chemical fertilizers and pesticides leads to the degradation of soil quality, heavy metal accumulation, and ecosystem degradation [17]. Appropriate application of organic fertilizers can reduce the environmental risks posed by heavy metals and improve soil quality. However, the presence of harmful elements, toxic substances, and heavy metals in organic fertilizers [18] can potentially contaminate soil and agricultural products. Studies have shown the presence of heavy metals, such as Cr and As, in soil and wheat grains under different nitrogen fertilizer treatments [19]. Long-term no-tillage and chicken manure application increased the availability of Cu, Zn, and Cd, and the potential ecological risk index for Hg in the chicken manure treatment was moderately strong [20]. Heavy metals that enter soil ecosystems have extremely complex ecotoxicological effects. The accumulation and enrichment of heavy metals in soil can affect crop yields, and their entry into the human body can have long-term negative effects, threatening human life and health [21]. In salinized farmland, soil salinity affects the biosorption of heavy metals by crop roots [22]. Ions in soil salinity and soil organic matter can form stable complexes with heavy metals, affecting their migration and bioavailability [23]. Furthermore, salinity may influence microbial activity, thereby affecting the biotransformation processes of heavy metals [24]. Methods for evaluating heavy metal pollution in farmland soils include index models, analytic hierarchy processes, fuzzy mathematics, and gray relational analysis models [25,26].
Previous studies have examined the impact of heavy metals on soil accumulation, crop heavy metal residues, and plant growth and development during the application of farmyard manure compost as well as the basic physicochemical properties of the soil under the combined application of organic and inorganic fertilizers. However, there is a lack of research focusing on the ecological and chemical properties of soil organic matter in lightly to moderately saline–alkali soils under organic fertilizer application and on heavy metal pollution in soil and crops under supplemental irrigation conditions. Therefore, this study conducted field experiments to explore the effects of water–fertilizer coupling on sunflowers as well as the soil properties and heavy metal migration patterns in saline–alkali soils with varying ratios of organic and inorganic fertilizers and supplemental irrigation amounts. The research hypotheses are as follows: Different ratios of organic to inorganic fertilizers have significant effects on soil physical properties, soil heavy metal content, and the absorption of heavy metals by sunflowers; and supplementary irrigation water quantity has significant effects on soil physical properties and the absorption of heavy metals by sunflowers.

2. Materials and Methods

2.1. Overview of the Study Area and Experimental Design

The study area was located in Wuyuan County, Bayan Nur City, Inner Mongolia, China. The annual average temperature ranges from 3.7 °C to 7.6 °C, with the highest temperatures occurring in July. Precipitation is scarce, with an annual average of 188 mm. Snowfall and rainfall are minimal during winter and spring, while the annual average evaporation rate is 2032~3179 mm, which is generally 10–30 times higher than that of precipitation. The soil type in this area is solonetz.
The test crop was sunflowers, specifically the Tongqing No. 6 variety (Jiuquan Tongqing Seed Industry Co., Ltd., Jiuquan, China). The experiment was conducted in 2023, and spring irrigation of 160 mm was applied before planting according to the local irrigation schedule. Two types of salt-affected farmland soils were selected: mildly saline soil (F1, salt < 2‰) and moderately saline soil (F2, 2‰ < salt < 4‰). Three organic to inorganic nitrogen fertilizer ratios were tested: 1:4 (25% organic), 1:2 (50% organic), and 3:4 (75% organic). The experimental design included three irrigation levels: 160 mm (W1), 182 mm (W2), and 204 mm (W3). The amount of organic fertilizer applied was determined as a proportion of the base fertilizer (60 kg/hm2 of pure nitrogen), and the topdressing amount was double the base fertilizer urea (N 46%) application rate. When organic fertilizer replaced part of the urea, the total nitrogen application decreased accordingly. Supplemental irrigation was applied through drip irrigation, with a single irrigation quota of 22 mm each, administered during the sunflower squaring stage (6 July 2023) and the pre-flowering stage (25 July 2023). Three types of organic fertilizers were used: sheep manure (SF), cow manure (CF), and commercial organic fertilizer (PF). The nutrient and heavy metal content of commercial organic fertilizers made from cow manure and sheep manure are shown in Table 1. Commercial organic fertilizers are composed of biomass carbon, soil microbial inoculants, complex amino acids, and other ingredients.
The experiment comprised 24 treatments with plot dimensions of 10 m × 6.5 m, as illustrated in Figure 1. The soil properties are summarized in Table 2, and the experimental design is presented in Table 3.

2.2. Sample Collection and Measurement Methods

2.2.1. Measurement and Related Calculations of Soil Basic Properties

Soil sampling was conducted before planting, and soil samples were collected every 15 days thereafter, with additional sampling before irrigation during the growing period. The sampled soil layers were 0–20 cm, 20–40 cm, and 40–60 cm. The mass water content, electrical conductivity (EC, μs/cm), pH, and oxidation–reduction potential (ORP) of each layer were measured separately. Additional measurements were taken before and after supplemental irrigation, and the electrical conductivity (EC) of the soil solution and the soil pH were measured using the electrode method. Soil water content was determined using the oven-drying method. Soil oxidation–reduction potential (ORP) was measured using the potentiometric method.
SSC = 2 . 2811   ×   0 . 001   ×   EC   -   0 . 0015
In the formula, “SSC” (g/kg) refers to the soil salt content.
S W C = ∑ B D i × h i × S W C i
In the formula, B D i  represents the soil bulk density (g·cm−3), SWC represents the soil water content by mass within the 0–60 cm soil layer (cm3·cm−3), and h represents the thickness of the soil layer (cm).

2.2.2. Physicochemical Properties and Microbial Carbon and Nitrogen Determination in Soils

The chemical biological parameters of soil indicators were measured according to “Soil Agrochemical Analysis Methods”. OM was determined using the external heating–potassium dichromate titration method [27]. Soil microbial biomass carbon (MBC) and nitrogen (MBN) were measured using the chloroform fumigation–extraction method [28]. Total nitrogen, NH 4 + -N , and NO 3 − -N were determined using the Kjeldahl method and indophenol blue colorimetry, whereas soil nitrate nitrogen was measured using ultraviolet spectrophotometry [29,30,31]. The conversion factor between organic carbon and organic matter is 1.724 [32]. Soluble carbon and nitrogen were measured using ultraviolet spectrophotometry [33].
The formulae for calculating the accumulation of soil organic matter, total nitrogen, nitrate nitrogen, and ammonium nitrogen are as follows:
S o i l   m i c r o b i a l   q u o t i e n t = M B C / M B N
C / N = S O C / T N
X = h i × B D i × X i / 10
where X represents OM ,   T N ,   Dissolved   organic   carbon   ( DOC ) ,   DON ,   NH 4 + -N  and NO 3 − -N . NH 4 + -N stands for the accumulated amount of ammonium nitrogen (kg/hm2)  NO 3 − -N for the accumulated amount of nitrate nitrogen (kg/hm2), DOC for dissolved organic carbon (kg/hm2), DON for dissolved organic nitrogen (Kg/hm2), OM for soil organic matter (t/hm2), T N for soil total nitrogen (t/hm2), and SOC for soil organic carbon (g/kg). X i represents the contents (g/kg) of NH 4 + i ,  NO 3 − i ,   DOC i ,   DON i ,   BD i , OM i , and T N i in the corresponding soil layers. B D i  specifically refers to the bulk density of each soil layer (g/cm2), and hi represents the thickness of the soil layer (cm).

2.2.3. Determination of Organic Matter Functional Groups

A commonly used molecular method for analyzing soil organic matter components is Fourier-transform infrared (FTIR) spectroscopy, which can identify functional groups primarily derived from aliphatic carbon, aromatic carbon, and polysaccharide carbon [34]. Based on the existing literature, different characteristic regions of organic functional groups can be defined [35] as aliphatic carbons (2800–3010 cm−1), aromatic carbons (1580–1660 cm−1), polysaccharide carbons (1520–1546 cm−1), and alcohols/phenols (3620, 3448 cm−1) [36,37]. The infrared spectra of the soil samples were analyzed for characteristic peaks, and the corrected peak areas were calculated through integration. This approach allows for the quantitative assessment of the various functional groups present in soil organic matter, providing insights into its composition, stability, and potential for decomposition.

2.2.4. Determination of Heavy Metals in Soil and Crop Grains

Monitoring the accumulation of heavy metals (Cu, Zn, and Cd) in the soil and crop grains involves assessing the surface soil layer during the grain-filling stage of the crop using an atomic absorption spectrophotometer [38]. The soil samples were pretreated with a mixed acid of nitric acid and hydrochloric acid for digestion. After harvest, the heavy metal content of the crop grains was monitored. This process evaluates the cumulative pollution status of heavy metals in farmland soil and crop grains after the application of organic fertilizers. The cross-contamination of heavy metals in soil is a concern, and a potential ecological risk index (RI) has been proposed. The RI considers not only the concentration of heavy metals in the soil but also their toxicity response factors. It focuses on the migration and transformation patterns of heavy metal toxicity in soil, considering the interactive effects of toxicity among different heavy metals. This quantitative approach assesses the potential risks posed by heavy metals and comprehensively reflects their harmful effects on the environment. The formula for calculating RI is as follows:
R I = ∑ i = 1 n T r i C r i = ∑ i = 1 n T r i C t e s t i / C n i
In the formula, C t e s t i represents the measured concentration of heavy metal i in the soil. C n i is the evaluation standard for the element, specifically 1.49 mg/kg for Cd, 8.39 mg/kg for Cu, and 44.19 mg/kg for Zn. C r i is the pollution coefficient of the target element: T r i is the toxicity response factor, which is 30 for Cd, 5 for Cu, and 1 for Zn, as reported by Previous Research [39].
B C F = C v e g / C s o i l
In the formula, bioaccumulation factor (BCF) refers to the ratio of the concentration of a certain heavy metal in plant tissue to the concentration of heavy metals in the soil. A higher BCF indicates a stronger bioaccumulation capability. C v e g (mg/kg) represents the accumulated metal concentration in the plant tissue, and C s o i l (mg/kg) represents the metal concentration in the soil [40].
One method used to assess health risks based on consumption is to measure the daily metal intake. The daily intake of metals (DIM) can be calculated using the following formula:
D I M = C m e t a l × C f o o d   i n t a k e / B a v e r a g e   w e i g h t
In the formula, D I M represents the daily intake of metals. C m e t a l (mg/kg) is the metal concentration in the plant sample. C f o o d   i n t a k e (mg/kg) represents the daily food intake with a reference value of 0.056 g/day [41]. B a v e r a g e   (kg) represents the average body weight, which was 60 kg.
H R I = D I M O r a l   r e f e r e n c e   d o s e
In this formula, the health risk index (HRI) indicates the health threat to individuals consuming contaminated food. In this study, it was used to calculate the potential heavy metal exposure if humans consumed the crop samples. The oral reference doses (RfDs) used in this study for Zn, Cd, and Cu were 0.3, 0.001, and 0.041 mg/kg/d, respectively [40].

2.3. Data Analysis

Using SPSS software, a repeated-measures analysis of variance (ANOVA) was conducted to analyze the effects of the proportion of organic fertilizer and supplementary irrigation water on the monitored indicators. Marginal means were calculated and compared using the least significant difference (LSD) method, which is often considered more precise than simple means [42]. PCA was employed to identify the main heavy metals affected by organic fertilizers in both the soil and crop grains. Correlation analysis was performed to understand the relationships between the soil’s physical and chemical properties, whereas redundancy analysis was used to assess the impact of the soil’s properties on the migration and mobilization of heavy metals in the soil.

3. Results and Analysis

3.1. The Influence of Irrigation Water Amount and the Ratio of Organic to Inorganic Fertilizer Application on the Properties of Salinized Soil

A repeated-measures ANOVA was conducted on the physical and chemical properties of the soil at different time points during the growth period, as shown in Figure 2, Figure 3, Figure 4 and Figure 5. According to Supplementary Materials Tables S1 and S2, in lightly and moderately salinized farmlands, soil moisture and salinity at a depth of 0–60 cm showed a trend of W3 > W2 for lightly salinized soil and W2 > W3 for moderately salinized soil. The soil pH values in lightly and moderately saline–alkali soils varied with the amount of irrigation, showing a trend of W3 > W2 > W1, and with different proportions of organic fertilizer, displaying a trend of 75% > 50% > 25%. Supplemental irrigation at 44 mm increased soil reducibility by 0.7% and 6.3% in lightly and moderately saline–alkali soils, respectively, whereas irrigation at 22 mm increased soil oxidizability by 0.9% in lightly saline–alkali soil and reducibility by 1.1% in moderately saline–alkali soil.
In the lightly saline–alkali soil, the soil organic matter (OM) content showed a trend of W1 > W2 > W3 with different irrigation amounts, whereas total nitrogen (TN) showed a trend of W2 > W1 > W3. For the 0–40 cm soil depth, under different proportions of organic fertilizer application, the OM values were the highest at 25%, followed by 50% and 75%, whereas the TN values were the highest at 25%, followed by 75% and 50%. In the moderately saline–alkali soil, the OM and total nitrogen (TN) content showed a trend of W3 > W2 > W1 with different irrigation amounts. For the 0–40 cm soil depth under different proportions of organic fertilizer, the OM values were the highest at 25%, followed by 75% and 50%, whereas the TN values were the highest at 25%, followed by 50% and 75%. In the lightly saline–alkali soil, supplemental irrigation reduced the soil NH 4 + -N content by 2.2–14.7% and increased the NO 3 − -N content by 3.2–15% in the 0–40 cm soil depth. For the 0–40 cm soil depth under different proportions of organic and inorganic fertilizer application, the NH 4 + -N content was highest at 25% organic fertilizer proportion, followed by 75% and 50%, whereas the NO 3 − -N content was highest at 75%, followed by 50% and 25%. In the moderately saline–alkali soil, supplemental irrigation increased the soil NH 4 + -N and NO 3 − -N content by 6.5–27.6% and 15.8–24.7%, respectively, at the 0–40 cm soil depth. Among them, the NH 4 + -N and NO 3 − -N values were the highest at the 50% organic fertilizer proportion.
In the lightly saline–alkali soil, both dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) showed a trend of W1 > W3 > W2. Supplemental irrigation at 22 mm increased the soil microbial biomass carbon (MBC) by 6%, whereas irrigation at 44 mm decreased the MBC by 12.5%. After supplemental irrigation, soil microbial biomass nitrogen (MBN) decreased by 17.5–20.5%, with the decrease becoming more pronounced as the irrigation amount increased. In the moderately saline–alkali soil, DOC showed a trend of W2 > W1 > W3, whereas MBC and MBN both showed a trend of W2 > W3 > W1. Supplemental irrigation of 44 and 22 mm increased the MBC by 6.2% and 25.3%, respectively.
In the lightly saline–alkali soil, supplemental irrigation at 22 mm reduced the contribution rate of nitrogen-containing organic functional groups in the soil and decreased the carbon cycling rate, whereas irrigation at 44 mm increased the contribution rate of nitrogen-containing organic functional groups in the soil organic matter. Aliphatic and aromatic amides showed an increasing trend with increasing organic fertilizer proportions, with 75% > 50% > 25%. In the moderately saline–alkali soil, supplemental irrigation increased the contribution rate of nitrogen-containing organic functional groups in the soil, indicating that the source of organic matter was more likely crop litter. When comparing cow manure, sheep manure, and commercial organic fertilizer, the soil amended with commercial organic fertilizer contained less recalcitrant organic matter.

3.2. Assessment of Heavy Metal Accumulation and Potential Ecological Risks in Salinized Soil

The residual amounts of the heavy metals Cu, Zn, and Cd in the soil surface layer under different proportions of organic and inorganic fertilizer application and irrigation amounts are shown in Figure 6. The Zn content in the soil was relatively high. In the lightly saline–alkali soil, compared to the treatment without supplemental irrigation (spring irrigation of 160 mm) with the same fertilizer proportion, the application of 25% organic fertilizer along with supplemental irrigation of 44 mm during the growth period increased the soil risk index by 5.7%, whereas a proportion of organic fertilizer ≥50% reduced the soil risk index by 2.4–13.4%. When the supplemental irrigation amount was 22 mm during the growth period, the application of different proportions of organic and inorganic fertilizer increased the soil risk index by 1.7–14.6%. As shown in Supplementary Materials Tables S3 and S4, the irrigation amount, organic fertilizer proportion, and organic fertilizer type had significant differential effects on heavy metal accumulation in the soil surface layer, ecological risk index, heavy metal (Cu, Zn, and Cd) residues in the grains, heavy metal enrichment factors, and health risk index in both the lightly and moderately saline–alkali soils.
In the lightly saline–alkali soil, under different irrigation amounts, the trends for Cd, Zn, and the risk index (RI) were W2 > W1 > W3, whereas Cu showed the order W3 > W2 > W1. Compared to the treatment without supplemental irrigation (spring irrigation of 160 mm), when the supplemental irrigation amount was 22 mm during the milking stage, soil Cd, Zn, and RI increased by 10.2%, 3.1%, and 8%, respectively. However, when the supplemental irrigation amount was 44 mm, Cd, Zn, and RI decreased by 5.3%, 4.1%, and 3.1%, respectively, indicating a reduction in soil risk index after supplemental irrigation. Under different proportions of organic and inorganic fertilizer application, Cd, Cu, and RI exhibited a trend of 75% > 25% > 50%, whereas Zn showed a trend of 25% > 75% > 50%.
In the moderately saline–alkali soil, compared to the treatment without supplemental irrigation, when the proportion of organic fertilizer was ≥75%, the risk index decreased by 10.1–11.1% and 0.4–13% with supplemental irrigation amounts of 44 mm and 22 mm, respectively, and the decrease was more pronounced with an increase in the proportion of organic fertilizer (and a corresponding decrease in total nitrogen). Under different irrigation amounts, Cd, Zn, and the risk index (RI) showed a trend of W1 > W2 > W3, whereas Cu showed a trend of W2 > W1 > W3. Compared to the treatment without supplemental irrigation (spring irrigation of 160 mm), during the milking stage, the application of supplemental irrigation amounts of 44 mm and 22 mm reduced the soil Cd, Zn, and RI by 1.3–6.3%, 29.4–46.1%, and 0.6–6.2%, respectively.

3.3. Heavy Metal Residues and Heavy Metal Enrichment in Crop Grains

Analysis of heavy metal (Cu, Zn, and Cd) residue accumulation, enrichment coefficients, and health risk indices in crop grains during the late growth stage under different proportions of organic and inorganic fertilizer application and irrigation amounts revealed the following trends. As shown in Figure 6, Supplementary Materials Tables S3 and S4, in lightly saline–alkali soil, the heavy metal residues, enrichment coefficients, and health risk indices of Cu, Zn, and Cd showed a trend of W3 > W1 > W2 under different irrigation amounts. Compared to the treatment without supplemental irrigation (spring irrigation of 160 mm), the application of 44 mm of supplemental irrigation increased the grain heavy metal content by 4.6–5.3%, heavy metal enrichment by 0.7–12.2%, and health risk index by 4.6–5.6%. In contrast, 22 mm of supplemental irrigation reduced the grain heavy metal content by 12–13.5%, heavy metal enrichment by 13.1–22.4%, and the health risk index by 12–15.9%. Under different proportions of organic and inorganic fertilizer application, the heavy metal residues, enrichment coefficients, and health risk indices of Cu, Zn, and Cd increased with an increase in the proportion of organic fertilizer.
Compared to the treatment without supplemental irrigation (spring irrigation of 160 mm), in moderately saline–alkali soil, the application of 44 mm of supplemental irrigation reduced the grain heavy metal content by 11.1–33.6%, heavy metal enrichment by 8.8–29.8%, and health risk index by 4.6–33.3%, but increased the Zn enrichment coefficient by 52.3%. When the supplemental irrigation amount was 22 mm, the grain heavy metal content decreased by 5.5–26.5%, heavy metal enrichment by 8.5–31.8%, and health risk index by 6.9–26.5%, while the Zn residue and health risk index increased by 4.9% and 4.6%, respectively. As the proportion of organic fertilizer increased, the Cu and Zn residues and risk indices in the crop grains increased. For the Cd residue, enrichment, and health risk indices, the trend was 50% > 25% > 75%. When the proportion of organic fertilizer was 50%, the Zn residues and risk indices were the highest. Supplemental irrigation reduced soil heavy metal accumulation and lowered the risk index, grain heavy metal residues, and risk indices. The application of commercial organic fertilizers resulted in lower soil heavy metal accumulation and soil ecological risk. Compared to farmyard manure, the application of commercial organic fertilizer had the lowest potential risk index.

3.4. The Main Factors Influencing Heavy Metal Residue Variations in Saline–Alkali Soil and Crop Grains

The primary factors influencing soil heavy metal accumulation and changes in heavy metal residues in grains were analyzed under varying ratios of organic fertilizer and irrigation water volumes. A PCA was conducted on soil heavy metal accumulation, grain heavy metal residues, and evaluation indicators, as shown in Figure 7. Based on the first PCA, F1 exhibited the pattern Cu > Zn > Cd, whereas F2 showed the pattern Cd > Cu > Zn. In the mildly saline–alkali soil, varying proportions of organic fertilizer and supplemental irrigation primarily affected the Cu and Zn residues in the crop grains and the accumulation of Cd in the surface soil during the grain-filling stage. A positive correlation was observed between the contents of the three heavy metals (Cu, Zn, and Cd) in the soil surface layer and among the heavy metal residues in the crop grains. Conversely, there was an inverse correlation between the heavy metals (Cu, Zn, and Cd) in the soil and their corresponding residues in the crop grains. In the moderately saline–alkali soil, the primary effects were similar to those in the mildly saline–alkali soil, affecting the residues of Cd and Cu in the crop grains and the accumulation of Cd in the surface soil during the grain-filling stage. A positive correlation was also evident among the three heavy metals in both the soil surface layer and crop grains, as well as between the heavy metals in the soil surface layer and their residues in the crop grains.
Based on the PCA results of the heavy metal risk assessment indicators, the first PCA (F1) revealed that the performance was characterized by BCF2 > BCF1 > BCF3, whereas F2 showed HR1 > HRI3 > BCF1, as depicted in Figure 7. In mildly saline–alkali soil, the proportion of organic fertilizer and irrigation volume have significant effects on heavy metal bioaccumulation factors (BCFs) used as pollution assessment indicators for soil and crop grains. There was an inverse relationship between the BCFs of crop grains and the soil ecological risk indices. Notably, the BCF of Cd and its health risk index (HRI) exhibited the strongest correlation with soil ecological risk indices. Among the heavy metal assessment indicators for crop grains, the BCFs of various heavy metals are positively correlated with each other, as are their HRIs. In moderately saline–alkali soils, the HRI for Cu, the BCFs of Cd and Cu, and the HRI for copper show an inverse relationship with the BCF of Zn in crop grains and soil ecological indices. In contrast, the BCFs of Cu and Cd were positively correlated with the soil ecological indices. The soil ecological risk index had the most profound influence on the HRI of Cu.

3.5. Effects of Soil Properties on Heavy Metal Residues in Soil and Crop Grains

An analysis was conducted to explore the relationships between the basic chemical properties of the soil, soil nutrients, active fractions of organic carbon and nitrogen, organic carbon functional groups, heavy metal accumulation, and risk in soil and crop grains. Redundancy analysis was performed to eliminate highly correlated soil indicators. As shown in Figure 8, the soil salinity at 0–60 cm depth exhibited a significantly strong negative correlation with soil pH, organic matter, total nitrogen, and ammonium nitrogen. There was also a significant, moderately negative correlation between soluble nitrogen and microbial biomass nitrogen. Soil organic matter, total nitrogen, and ammonium nitrogen contents had a significantly strong positive correlation with soil pH and redox potential at the 0–60 cm depth. Among the active fractions of soil organic carbon and nitrogen, soluble nitrogen and microbial biomass nitrogen showed a significantly strong positive correlation with soil organic matter, total nitrogen content, and pH. Among the organic functional groups, carboxyl groups showed a significantly weak correlation with the aliphatics, aromatics, and aromatic amides, whereas the aromatic amides exhibited a significantly high positive correlation with the aromatic amines.
As shown in Figure 9, a comprehensive analysis of the relationship between soil properties and heavy metal residues in lightly and moderately saline–alkali soils revealed that the accumulation of heavy metals in the soil and crop grains was more strongly correlated with the soil properties for Zn and Cu than for Cd. Specifically, the accumulation of Zn in the soil surface layer had the strongest correlation with the aliphatic organic functional groups in the soil, followed by soil salinity. Zn residue in crop grains was most strongly correlated with soil redox properties, followed by soil moisture content. The accumulation of Cu in the soil surface layer had the strongest correlation with the MBC in the soil, whereas the Cu residue in the crop grains was most strongly correlated with the soil moisture content. The accumulation and residue of Cd, a heavy metal in soil and crops, are less influenced by soil physicochemical properties than the other two heavy metals.

4. Discussion

Supplemental irrigation in waterlogged farmlands can effectively alleviate soil water deficits and enhance the ability of plants to absorb water and nutrients [43]. The results of this study indicate that under the combined application of organic and inorganic fertilizers in saline–alkali soils, soil salinity is negatively correlated with water accumulation, nitrogen accumulation, and soil pH. This is because the application of organic fertilizer affects soil structure by reducing soil pH, thereby reducing salt accumulation [44]; salt accumulation is also decreased through supplemental irrigation [45]. The use of organic fertilizers in saline–alkali soil as a substitute for inorganic fertilizers to reduce nitrogen application lowers the soil pH and prevents excessive alkalization [1]. Water management in saline–alkali soils is constrained by climatic and topographical factors that affect the stability and decomposition rate of soil organic matter. After supplemental irrigation, the accumulation of soluble carbon and nitrogen decreased in mildly saline–alkali soil, possibly because of accelerated organic matter decomposition [46], leading to the conversion of carbon and nitrogen into other forms and reducing their accumulation in the soil. The content and distribution of organic carbon functional groups can reflect the sources, degree of decomposition, and stability of soil organic carbon [47]. Molecular-level indicators of soil organic matter can link various aspects of ecological change at the macro- and ecosystem levels [48]. Organic fertilizers improve labile organic carbon functional groups and compounds but increase insoluble organic matter [49].
Existing studies have shown that applying organic fertilizers to saline–alkali soil can improve crop yield and quality, as well as enhance soil quality [50]. However, it can also increase heavy metal accumulation [18], which gradually increases with continued application [51]. By analyzing experiments conducted on lightly and moderately saline–alkali soils with different proportions of organic fertilizer application and supplemental irrigation, it was found that the soil pollution risk is greater in lightly saline–alkali soils than in moderately saline–alkali soils. This contrasts with previous studies on the migration of Cu, Cd, and Zn induced by saline factors, which found that increased ionic strength of the salts promoted the release of Cd [52]. This difference can be attributed to the varying solubility of organic fertilizers in lightly and moderately saline–alkali soils, which affects the activation of heavy metals.
As the proportion of organic fertilizer increased, the heavy metal residues, enrichment, and risk index of the crop grains also increased. This aligns with existing research, which shows that the accumulation of Cd in soil from fertilizers and the indirect influence of fertilizers on Cd availability to plants both increase with increasing fertilizer application rates [17]. Appropriate supplemental irrigation reduces heavy metal enrichment and enhances the utilization efficiency of organic fertilizers in saline–alkali soils [53]. However, excessive supplemental irrigation in lightly saline–alkali soils can increase the proportion of heavy metal residues and the risk index of crop grains. One possible reason for this is that the soil moisture content in moderately saline–alkali soil is higher than that in lightly saline–alkali soil, making it easier for some heavy metals to accumulate in grains after supplemental irrigation in lightly saline–alkali soil [54]. Another possibility is that other ions in the soil may compete with heavy metals for adsorption sites, thereby reducing the absorption of heavy metals by crop roots [55].
Compared to the application of cow dung and sheep manure, commercial organic fertilizer resulted in lower heavy metal residues, enrichment coefficients, and health risk indices in crop grains. This may be attributed to the chemical composition and structure of commercial organic fertilizers as well as the hydrophobicity of the contaminants [56], which reduces the upward transport of heavy metals. Alternatively, the lower nitrogen content and higher application rate of farm manure may lead to a greater input of heavy metals than commercial organic fertilizers. In lightly and moderately saline–alkali soils, the combination of different proportions of organic fertilizers and supplemental irrigation mainly affected Cu and Zn residues in the crop grains and the soil heavy metal Cd. This is consistent with previous research showing that salt ions promote Cd activation [52]. In lightly saline–alkali soil, there is an inverse relationship between heavy metals (Cu, Zn, and Cd) in the soil and their corresponding residues in crop grains. In contrast, in moderately saline–alkali soil, there is a direct relationship between heavy metals in the surface soil and their residues in grains, indicating that the heavy metal risk from organic fertilizer application has a greater impact on crops than on soil. Among Cu, Zn, and Cd accumulation in lightly and moderately saline–alkali soils, Cd was most affected by the proportion of organic fertilizer and irrigation amount. In lightly saline–alkali soil, a higher heavy metal enrichment coefficient in crops is associated with a lower soil ecological risk. In moderately saline–alkali soil, the salt content is a factor, and apart from Zn, a higher enrichment coefficient for Cu and Cd is associated with a higher soil ecological risk. This may be because soil pH and organic matter in lightly saline–alkali soil help immobilize heavy metals, reducing their availability to crops [57], and the crops themselves may have stronger tolerance. However, in highly saline–alkali soil, tolerance decreases, leading to higher heavy metal activation and greater absorption by crops, resulting in soil heavy metal migration to crops. In moderately saline–alkali soil, heavy metals primarily exist in insoluble or fixed forms, and metal speciation affects metal bioavailability, toxicity to biota, transport and mobilization, and interactions with the environment [58]. Therefore, even if the total heavy metal content in the soil is high, crops may have difficulty absorbing and accumulating these heavy metals.
The application of organic fertilizers in saline–alkali soils is negatively correlated with soil salinity, pH, organic matter, total nitrogen, ammonium nitrogen, soluble nitrogen, and microbial biomass nitrogen. This aligns with previous research showing that high salinity inhibits soil bacterial communities, thereby affecting nitrogen metabolism and cycling [59]. There were significant positive correlations between soil organic matter, total nitrogen, ammonium nitrogen content, soil pH, and redox potential, which is consistent with studies on the effects of land-use patterns on soil organic carbon, nitrogen content, and redox potential, where organic carbon was found to correlate with soil pH and redox potential [60]. Zn accumulation in the soil surface layer showed the strongest correlation with aliphatic organic functional groups in the soil. This is consistent with research on the relationship between structural changes in organic matter in poultry litter and heavy metal solubility during composting, where composting occurs through the modification of the most unstable structures (carbohydrates, peptides, and fatty acid fragments) [61]. Residual Zn in crop grains correlates most strongly with soil redox properties, reflecting significant changes in soil chemistry from aerobic conditions in wheat to anaerobic conditions in rice [62]. Most soil redox processes are mediated by microorganisms, rather than by direct chemical reactions. Variations in soil redox conditions are influenced by differences in the soil moisture status [63]. The accumulation of Cu in the soil surface layer and its residual levels in crop grains were correlated with soil microbial biomass carbon and soil moisture content. This aligns with previous research on the effects of Cu contamination in the surface soil of apple orchards on soil microbial biomass and microbial communities, in which Cu had a significant impact on the microbial biomass [64].

5. Conclusions

Applying commercial organic fertilizer to saline–alkali soils in arid regions can reduce the total amount of nitrogen applied, and when combined with appropriate drip irrigation during the sunflower growth period can help reduce salt accumulation in the 0–60 cm soil layer, prevent soil alkalization, and decrease nitrate–nitrogen accumulation. Supplementary irrigation enhances the stability of soil organic matter.
When combining organic and inorganic fertilizers with reduced nitrogen application, there was a slight potential ecological risk index in the soil surface during the crop’s grain-filling stage, with the Zn content in the soil being relatively high. Applying organic fertilizer to mildly saline–alkali soil is more likely to increase the risk of soil pollution than when applied to moderately saline–alkali soil. Appropriate supplemental irrigation can reduce heavy metal accumulation; however, unreasonable irrigation volumes can increase the residual proportion and risk index of heavy metals in crop grains. Soil properties have a greater influence on the accumulation and residues of Zn and Cu in crop grains compared to those of Cd. Among the soil properties, organic carbon functional groups, such as aliphatic groups, redox potential (Eh), microbial biomass carbon (MBC), and soil moisture content are correlated with the accumulation and residue of heavy metals from organic fertilizers.
Therefore, when applying organic fertilizer, it is necessary to apply it reasonably based on the current soil conditions and crop growth needs. Due to the limitations of field experiments, such as potential confounding variables and the generalizability of the results, future research should be conducted across multiple locations, over a longer period of time, and with a variety of crops, while increasing the sample size. Furthermore, future studies should incorporate other environmental factors such as climate change to comprehensively assess the coupled effects of water and fertilizer management on soil property changes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture14101694/s1, Table S1. Significant differences in the marginal mean values of soil salinity, water content, inorganic nitrogen, and active organic carbon and nitrogen repetition under different organic fertilizer ratios and irrigation amounts in 2023. Table S2. Significant differences in the marginal mean of soil salinity, water content, inorganic nitrogen, and active organic carbon and nitrogen repeats in moderately saline–alkali land under different organic fertilizer ratios and irrigation amounts in 2023. Table S3. Analysis of significant differences in the mean values of the surface heavy metals, potential ecological index, seed heavy metal residues, enrichment coefficient, and health risk index in light saline soils under different organic and inorganic fertilizer ratios and irrigation volumes in 2023. Table S4. Analysis of significant differences in the mean values of the surface heavy metals, potential ecological index, seed heavy metal residues, enrichment factor, and health risk index in moderately saline soil under different organic and inorganic fertilizer ratios and irrigation volumes in 2023.

Author Contributions

D.Y.: Investigation, Writing—original draft, and Visualization; Q.M.: Writing—original draft, Writing—Reviewing and Editing; H.S.: Funding and supervision; Z.F.: Resources, Writing—original draft and Writing—Reviewing; W.F.: Writing—Reviewing and Editing; Z.L.: Resources and Methodology; J.M.G.: Conceptualization and Editing. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Inner Mongolia Autonomous Region “Unveiling the List with Commanders” Project, China (2023JBGS0003). This study was supported by the State Key Program of the National Natural Science Foundation of China (2021YFD1900602-06). The National Natural Science Foundation of China (52269014, 52009056). The Project of Science and Technology of Inner Mongolia Province (2022YFHH0044). The National Sustainable Development agenda innovation demonstration zone construction key project of Ordos City (No. ZD20232301). The key special project identifier for the ‘Science and Technology Xingmeng’ initiative is (NMKJXM202303-04).

Data Availability Statement

Data already exists in the manuscript.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. Wang, X.; Riaz, M.; Babar, S.; Eldesouki, Z.; Liu, B.; Xia, H.; Li, Y.; Wang, J.; Xia, X.; Jiang, C. Alterations in the Composition and Metabolite Profiles of the Saline-Alkali Soil Microbial Community through Biochar Application. J. Environ. Manag. 2024, 352, 120033. [Google Scholar] [CrossRef] [PubMed]
  2. Hao, X.; Chang, C. Does Long-Term Heavy Cattle Manure Application Increase Salinity of a Clay Loam Soil in Semi-Arid Southern Alberta? Agric. Ecosyst. Environ. 2003, 94, 89–103. [Google Scholar] [CrossRef]
  3. Cheng, Y.; Luo, M.; Zhang, T.; Yan, S.; Wang, C.; Dong, Q.; Feng, H.; Zhang, T.; Kisekka, I. Organic Substitution Improves Soil Structure and Water and Nitrogen Status to Promote Sunflower (Helianthus annuus L.) Growth in an Arid Saline Area. Agric. Water Manag. 2023, 283, 108320. [Google Scholar] [CrossRef]
  4. Wang, X.; Yang, J.; Yao, R.; Xie, W.; Zhang, X. Manure plus Plastic Film Mulch Reduces Soil Salinity and Improves Barley-Maize Growth and Yield in Newly Reclaimed Coastal Land, Eastern China. Water 2022, 14, 2944. [Google Scholar] [CrossRef]
  5. Gruba, P.; Mulder, J. Tree Species Affect Cation Exchange Capacity (CEC) and Cation Binding Properties of Organic Matter in Acid Forest Soils. Sci. Total Environ. 2015, 511, 655–662. [Google Scholar] [CrossRef]
  6. Wang, Y.; Gao, M.; Chen, H.; Chen, Y.; Wang, L.; Wang, R. Organic Amendments Promote Saline-Alkali Soil Desalinization and Enhance Maize Growth. Front. Plant Sci. 2023, 14, 1177209. [Google Scholar] [CrossRef]
  7. Jalali, M.; Ranjbar, F. Effects of Sodic Water on Soil Sodicity and Nutrient Leaching in Poultry and Sheep Manure Amended Soils. Geoderma 2009, 153, 194–204. [Google Scholar] [CrossRef]
  8. Shi, Y.; Liu, X.; Zhang, Q.; Li, G.; Wang, P. Biochar Rather than Organic Fertilizer Mitigated the Global Warming Potential in a Saline-Alkali Farmland. Soil Tillage Res. 2022, 219, 105337. [Google Scholar] [CrossRef]
  9. Ni, P.; Wang, S.; Liu, B.; Sun, H. Effects of Organic Manure and Biochar-Based Fertilizer Application on Soil Water and Salt Transport in Brackish Water Irrigated Soil Profile. J. Soil Sci. Plant Nutr. 2023, 23, 3120–3136. [Google Scholar] [CrossRef]
  10. Li, C.; Jia, Z.; Tang, L.; Wu, Y.; Li, Y. Effect of moedl of fertilization on microblial abundance and enzyme activity in oasis farmland soil. Acta Pedol. Sin. 2012, 49, 567–574. [Google Scholar]
  11. Wang, C.; Ma, H.; Feng, Z.; Yan, Z.; Song, B.; Wang, J.; Zheng, Y.; Hao, W.; Zhang, W.; Yao, M.; et al. Integrated Organic and Inorganic Fertilization and Reduced Irrigation Altered Prokaryotic Microbial Community and Diversity in Different Compartments of Wheat Root Zone Contributing to Improved Nitrogen Uptake and Wheat Yield. Sci. Total Environ. 2022, 842, 156952. [Google Scholar] [CrossRef] [PubMed]
  12. Guo, J.; Liu, W.; Zhu, C.; Luo, G.; Kong, Y.; Ling, N.; Wang, M.; Dai, J.; Shen, Q.; Guo, S. Bacterial Rather than Fungal Community Composition Is Associated with Microbial Activities and Nutrient-Use Efficiencies in a Paddy Soil with Short-Term Organic Amendments. Plant Soil 2018, 424, 335–349. [Google Scholar] [CrossRef]
  13. He, Z.; Pagliari, P.; Waldrip, H. Applied and Environmental Chemistry of Animal Manure: A Review. Pedosphere 2016, 26, 779–816. [Google Scholar] [CrossRef]
  14. Yu, Z.; Liu, J.; Kattel, G. Historical Nitrogen Fertilizer Use in China from 1952 to 2018. Earth Syst. Sci. Data 2022, 14, 5179–5194. [Google Scholar] [CrossRef]
  15. Li, Z.; Zhang, Z.; Li, M.; Zhang, H.; Song, X.; Wu, H. Contents of Organic Carbon and Dissolved Organic Carbon and Characteristics of Functional Group Structure in Surface Soils of Salt Marshes in Yellow River Delta. Wetl. Sci. 2019, 17, 645–650. [Google Scholar] [CrossRef]
  16. Duan, Y.; Chen, L.; Zhang, J.; Li, D.; Han, X.; Zhu, B.; Li, Y.; Zhao, B.; Huang, P. Long-Term Fertilisation Reveals Close Associations between Soil Organic Carbon Composition and Microbial Traits at Aggregate Scales. Agric. Ecosyst. Environ. 2021, 306, 107169. [Google Scholar] [CrossRef]
  17. Grant, C.A.; Sheppard, S.C. Fertilizer Impacts on Cadmium Availability in Agricultural Soils and Crops. Hum. Ecol. Risk Assess. Int. J. 2008, 14, 210–228. [Google Scholar] [CrossRef]
  18. Adhikari, T.; Gowda, R.C.; Wanjari, R.H.; Singh, M. Impact of Continuous Fertilization on Heavy Metals Content in Soil and Food Grains under 25 Years of Long-Term Fertilizer Experiment. Commun. Soil Sci. Plant Anal. 2021, 52, 389–405. [Google Scholar] [CrossRef]
  19. Zhang, Y.; Yin, C.; Cao, S.; Cheng, L.; Wu, G.; Guo, J. Heavy Metal Accumulation and Health Risk Assessment in Soil-Wheat System under Different Nitrogen Levels. Sci. Total Environ. 2018, 622–623, 1499–1508. [Google Scholar] [CrossRef]
  20. Yang, N.; Wang, K.; Yang, Z.; Zhang, J.; Wen, Y.; Xi, J. Effects of tillage measures and organic manure on soil heavy metal pollution in dryland wheat fields. Chin. J. Eco-Agric. 2024, 32, 164–173. [Google Scholar] [CrossRef]
  21. Gong, Q.; Chen, P.; Shi, R.; Gao, Y.; Zheng, S.-A.; Xu, Y.; Shao, C.; Zheng, X. Health Assessment of Trace Metal Concentrations in Organic Fertilizer in Northern China. Int. J. Environ. Res. Public Health 2019, 16, 1031. [Google Scholar] [CrossRef] [PubMed]
  22. Lutts, S.; Qin, P.; Han, R.-M. Salinity Influences Biosorption of Heavy Metals by the Roots of the Halophyte Plant Species Kosteletzkya Pentacarpos. Ecol. Eng. 2016, 95, 682–689. [Google Scholar] [CrossRef]
  23. Matijevic, L.; Romic, D.; Romic, M. Soil Organic Matter and Salinity Affect Copper Bioavailability in Root Zone and Uptake by Vicia faba L. Plants. Environ. Geochem. Health 2014, 36, 883–896. [Google Scholar] [CrossRef] [PubMed]
  24. Yin, K.; Wang, Q.; Lv, M.; Chen, L. Microorganism Remediation Strategies towards Heavy Metals. Chem. Eng. J. 2019, 360, 1553–1563. [Google Scholar] [CrossRef]
  25. Zhang, J.; Zhao, A.; Wang, Z.; Ke, H.; Chen, H. Discussion on the differences of heavy metals contam ination in soil assessment with Nemerou index and geo-accumulation index with Xiaoqinling gold beltas example. Gold 2010, 31, 43–46. [Google Scholar]
  26. Xue, R.; Wang, C.; Liu, M.; Zhang, D.; Li, K.; Li, N. A New Method for Soil Health Assessment Based on Analytic Hierarchy Process and Meta-Analysis. Sci. Total Environ. 2019, 650, 2771–2777. [Google Scholar] [CrossRef]
  27. Huang, X.; Du, L.; Hong, J.; Chen, G.; Wang, S.; Lian, Z.; Zhang, G.; Jiang, L.; Zhang, L.; Ye, L. Study on the correlation between potassium dichromate external heating method and ASI for soil organic matter determination. Hubei Agric. Sci. 2020, 59, 122. [Google Scholar] [CrossRef]
  28. Chen, M.; Sheng, R.; Zhang, W.; Hou, H.; Wei, W.; Ge, T.; Wang, S. The effect of cropping patterns on soil microbial biomass carbon and nitrogen in reddish paddy soil. Res. Agric. Mod. 2023, 44, 692–700. [Google Scholar] [CrossRef]
  29. Qin, L.; Huang, S.; Zhong, L.; Zhou, H.; Zhao, S.; Xiang, B.; Lei, S. Comparison of Dumas combustion and Kjeldahl methods for determining total nitrogen content in soil. Soil Fertil. Sci. China 2020, 4, 258–265. [Google Scholar]
  30. Bai, J.; Cui, B.; Li, X.; Zhou, L. Ammonium nitrogen concentration seasonal dynamic in soils from reed wetlands in Xianghai. Acta Pratacul Turae Sin. 2006, 15, 117–119. [Google Scholar]
  31. Tu, C.; Huang, W.; CHen, A.; Song, G.; Chen, C.; Wang, W.; Xie, X. Comparison Between Ultraviolet Spectrophotometry and Cadmium Reduction Method in Determination of Soil Nitrate-N. Soils 2016, 48, 147–151. [Google Scholar] [CrossRef]
  32. Guo, Y.; Qi, W.; Yao, Y.; Liu, L. Soil Organic Carbon in Small Watershed Terraces and Association with Physical Properties. Ecol. Environ. Sci. 2020, 29, 748–756. [Google Scholar] [CrossRef]
  33. Luo, X.; Cang, L.; Hao, X.; Li, L.; Zhou, D. In-situ sampling of Soil Solution and Determination of Dissolved Organic Carbon (DOC) with UV Absorption Method (UVA254). Soils 2007, 39, 943–947. [Google Scholar]
  34. Zhang, Y.; Hu, Y.; Guo, S. Accumulation of Trace Element and Organic Functional Groups in Different Size Fractions of a Loess Topsoil After Long-term Micronutrient Fertilization. Acta Pedol. Sin. 2022, 59, 1420–1431. [Google Scholar]
  35. Demyan, M.S.; Rasche, F.; Schulz, E.; Breulmann, M.; Müller, T.; Cadisch, G. Use of Specific Peaks Obtained by Diffuse Reflectance Fourier Transform Mid-infrared Spectroscopy to Study the Composition of Organic Matter in a Haplic Chernozem. Eur. J. Soil Sci. 2012, 63, 189–199. [Google Scholar] [CrossRef]
  36. Ge, M.; Wang, C.; Xu, H.; Yang, F.; Wu, Z.; Lin, S.; Zhang, Y.; Li, X.; Wang, W. Organic Carbon Distribution and Molecular StructureCharacteristics of Soil Aggregatesin Fuding Tea Garden. J. Soiland Water Conserv. 2023, 37, 201–208. [Google Scholar] [CrossRef]
  37. Shao, P.; Liang, C.; Rubert-Nason, K.; Li, X.; Xie, H.; Bao, X. Secondary Successional Forests Undergo Tightly-Coupled Changes in Soil Microbial Community Structure and Soil Organic Matter. Soil Biol. Biochem. 2019, 128, 56–65. [Google Scholar] [CrossRef]
  38. Gong, L.; Zheng, H. Determination of Heavy Metals in Soil, Mushroom and Plant Samples by Atomic Absorption Spectrometry. Shandong Chem. Ind. 2020, 49, 101–102+107. [Google Scholar] [CrossRef]
  39. Wu, M.; LIu, S.; Yuan, Y.; Zhao, J.; Liu, Y.; Liu, S.; Liu, Y. Optimization of Potential Ecological Risk Index Method for Soil HeavyMetals—A Case Study of Chengkou County, Chongqing City. Chin. J. Soil Sci. 2023, 54, 473–480. [Google Scholar] [CrossRef]
  40. Guo, L.; Nie, Z.; Zhou, J.; An, F.; Zhang, L.; Zhang, S.; Tóth, T.; Yang, F.; Wang, Z. Effects of Organic Amendments on Soil Bacterial Community Structure and Yield in a Saline-sodic Soil Cropped with Rice. Land Degrad. Dev. 2023, 34, 5514–5527. [Google Scholar] [CrossRef]
  41. Bae, Y.-J.; Kim, M.-H.; Choi, M.-K. Dietary Mineral Intake from Nuts and Its Relationship to Hypertension Among Korean Adults. Biol. Trace Elem. Res. 2022, 200, 3519–3528. [Google Scholar] [CrossRef] [PubMed]
  42. Schrepf, A.; Clevenger, L.; Christensen, D.; DeGeest, K.; Bender, D.; Ahmed, A.; Goodheart, M.J.; Dahmoush, L.; Penedo, F.; Lucci, J.A.; et al. Cortisol and Inflammatory Processes in Ovarian Cancer Patients Following Primary Treatment: Relationships with Depression, Fatigue, and Disability. Brain Behav. Immun. 2013, 30, S126–S134. [Google Scholar] [CrossRef] [PubMed]
  43. Li, S.-X.; Wang, Z.-H.; Malhi, S.S.; Li, S.-Q.; Gao, Y.-J.; Tian, X.-H. Chapter 7 Nutrient and Water Management Effects on Crop Production, and Nutrient and Water Use Efficiency in Dryland Areas of China. In Advances in Agronomy; Elsevier: Amsterdam, The Netherlands, 2009; Volume 102, pp. 223–265. ISBN 978-0-12-374818-8. [Google Scholar]
  44. Rengasamy, P. Soil Processes Affecting Crop Production in Salt-Affected Soils. Funct. Plant Biol. 2010, 37, 613. [Google Scholar] [CrossRef]
  45. Behera, S.K.; Panda, R.K. Integrated Management of Irrigation Water and Fertilizers for Wheat Crop Using Field Experiments and Simulation Modeling. Agric. Water Manag. 2009, 96, 1532–1540. [Google Scholar] [CrossRef]
  46. Trost, B.; Prochnow, A.; Drastig, K.; Meyer-Aurich, A.; Ellmer, F.; Baumecker, M. Irrigation, Soil Organic Carbon and N2O Emissions. A Review. Agron. Sustain. Dev. 2013, 33, 733–749. [Google Scholar] [CrossRef]
  47. Kaiser, M.; Ellerbrock, R.H. Functional Characterization of Soil Organic Matter Fractions Different in Solubility Originating from a Long-Term Field Experiment. Geoderma 2005, 127, 196–206. [Google Scholar] [CrossRef]
  48. Simpson, M.J.; Simpson, A.J. The Chemical Ecology of Soil Organic Matter Molecular Constituents. J. Chem. Ecol. 2012, 38, 768–784. [Google Scholar] [CrossRef]
  49. Senesi, N. Composted Materials as Organic Fertilizers. Sci. Total Environ. 1989, 81–82, 521–542. [Google Scholar] [CrossRef]
  50. Mohiuddin, M.; Irshad, M.; Sher, S.; Hayat, F.; Ashraf, A.; Masood, S.; Bibi, S.; Ali, J.; Waseem, M. Relationship of Selected Soil Properties with the Micronutrients in Salt-Affected Soils. Land 2022, 11, 845. [Google Scholar] [CrossRef]
  51. Qian, X.; Wang, Z.; Shen, G.; Chen, X.; Tang, Z.; Guo, C.; Gu, H.; Fu, K. Heavy Metals Accumulation in Soil after 4 Years of Continuous Land Application of Swine Manure: A Field-Scale Monitoring and Modeling Estimation. Chemosphere 2018, 210, 1029–1034. [Google Scholar] [CrossRef]
  52. Acosta, J.A.; Jansen, B.; Kalbitz, K.; Faz, A.; Martínez-Martínez, S. Salinity Increases Mobility of Heavy Metals in Soils. Chemosphere 2011, 85, 1318–1324. [Google Scholar] [CrossRef] [PubMed]
  53. Alam, M.; Hussain, Z.; Khan, A.; Khan, M.A.; Rab, A.; Asif, M.; Shah, M.A.; Muhammad, A. The Effects of Organic Amendments on Heavy Metals Bioavailability in Mine Impacted Soil and Associated Human Health Risk. Sci. Hortic. 2020, 262, 109067. [Google Scholar] [CrossRef]
  54. Song, T.; Das, D.; Hu, Q.; Yang, F.; Zhang, J. Alternate Wetting and Drying Irrigation and Phosphorus Rates Affect Grain Yield and Quality and Heavy Metal Accumulation in Rice. Sci. Total Environ. 2021, 752, 141862. [Google Scholar] [CrossRef] [PubMed]
  55. Teixeira, E.; Kersebaum, K.C.; Ausseil, A.-G.; Cichota, R.; Guo, J.; Johnstone, P.; George, M.; Liu, J.; Malcolm, B.; Khaembah, E.; et al. Understanding Spatial and Temporal Variability of N Leaching Reduction by Winter Cover Crops under Climate Change. Sci. Total Environ. 2021, 771, 144770. [Google Scholar] [CrossRef]
  56. García-Delgado, C.; Marín-Benito, J.M.; Sánchez-Martín, M.J.; Rodríguez-Cruz, M.S. Organic Carbon Nature Determines the Capacity of Organic Amendments to Adsorb Pesticides in Soil. J. Hazard. Mater. 2020, 390, 122162. [Google Scholar] [CrossRef] [PubMed]
  57. Xu, P.; Sun, C.-X.; Ye, X.-Z.; Xiao, W.-D.; Zhang, Q.; Wang, Q. The Effect of Biochar and Crop Straws on Heavy Metal Bioavailability and Plant Accumulation in a Cd and Pb Polluted Soil. Ecotoxicol. Environ. Saf. 2016, 132, 94–100. [Google Scholar] [CrossRef]
  58. Shah, S.B. Heavy Metals in the Marine Environment—An Overview. In Heavy Metals in Scleractinian Corals; Shah, S.B., Ed.; Springer International Publishing: Cham, Switzerland, 2021; pp. 1–26. ISBN 978-3-030-73613-2. [Google Scholar]
  59. Li, X.; Wang, A.; Wan, W.; Luo, X.; Zheng, L.; He, G.; Huang, D.; Chen, W.; Huang, Q. High Salinity Inhibits Soil Bacterial Community Mediating Nitrogen Cycling. Appl. Environ. Microbiol. 2021, 87, e01366-21. [Google Scholar] [CrossRef]
  60. Zhao, Q.; Tang, J.; Li, Z.; Yang, W.; Duan, Y. The Influence of Soil Physico-Chemical Properties and Enzyme Activities on Soil Quality of Saline-Alkali Agroecosystems in Western Jilin Province, China. Sustainability 2018, 10, 1529. [Google Scholar] [CrossRef]
  61. Souza, C.D.C.B.D.; Amaral Sobrinho, N.M.B.D.; Lima, E.S.A.; Lima, J.D.O.; Carmo, M.G.F.D.; García, A.C. Relation between Changes in Organic Matter Structure of Poultry Litter and Heavy Metals Solubility during Composting. J. Environ. Manag. 2019, 247, 291–298. [Google Scholar] [CrossRef]
  62. Sadeghzadeh, B.; Rengel, Z. Zinc in Soils and Crop Nutrition. In The Molecular and Physiological Basis of Nutrient Use Efficiency in Crops; Hawkesford, M.J., Barraclough, P., Eds.; John Wiley & Sons: Hoboken, NJ, USA, 2011. [Google Scholar] [CrossRef]
  63. Impa, S.M.; Johnson-Beebout, S.E. Mitigating Zinc Deficiency and Achieving High Grain Zn in Rice through Integration of Soil Chemistry and Plant Physiology Research. Plant Soil 2012, 361, 3–41. [Google Scholar] [CrossRef]
  64. Masakazu, A.; Ryo, T. Effects of Heavy Metal Pollution of Apple Orchard Surface Soils Associated with Past Use of Metal-Based Pesticides on Soil Microbial Biomass and Microbial Communities. J. Environ. Prot. 2013, 2013, 30818. [Google Scholar] [CrossRef]
Agriculture 14 01694 g001
Figure 1. Experimental plot.
Figure 1. Experimental plot.
Agriculture 14 01694 g001
Agriculture 14 01694 g002
Figure 2. Characteristics of changes in mean soil water content and EC in the vertical direction under different organic fertilizer ratios and irrigation rates in 2023.
Figure 2. Characteristics of changes in mean soil water content and EC in the vertical direction under different organic fertilizer ratios and irrigation rates in 2023.
Agriculture 14 01694 g002
Agriculture 14 01694 g003aAgriculture 14 01694 g003b
Figure 3. Characteristics of soil pH and Eh changes in light to medium farmland under different organic fertilizer ratios and irrigation rates in 2023.
Figure 3. Characteristics of soil pH and Eh changes in light to medium farmland under different organic fertilizer ratios and irrigation rates in 2023.
Agriculture 14 01694 g003aAgriculture 14 01694 g003b
Agriculture 14 01694 g004
Figure 4. Physical and chemical properties of soil under different types of organic fertilizers and ratios in 2023.
Figure 4. Physical and chemical properties of soil under different types of organic fertilizers and ratios in 2023.
Agriculture 14 01694 g004
Agriculture 14 01694 g005
Figure 5. Infrared spectra of soil under different organic and inorganic fertilizer ratios and irrigation rates in 2023.
Figure 5. Infrared spectra of soil under different organic and inorganic fertilizer ratios and irrigation rates in 2023.
Agriculture 14 01694 g005
Agriculture 14 01694 g006aAgriculture 14 01694 g006b
Figure 6. Accumulation of heavy metals in the soil surface and ecological risk indices (Cu, Zn, and Cd are in mg/kg). Cus, Zns, and Cds (μg/kg) represent the content of heavy metals in grains. BCF1, BCF2, and BCF3 (‰) represent the enrichment coefficients of the heavy metals Cus, Zns, and Cds, respectively. HRI1, HRI2, and HRI3 represent the health risk indices of the heavy metals Cus, Zns, and Cds, respectively.
Figure 6. Accumulation of heavy metals in the soil surface and ecological risk indices (Cu, Zn, and Cd are in mg/kg). Cus, Zns, and Cds (μg/kg) represent the content of heavy metals in grains. BCF1, BCF2, and BCF3 (‰) represent the enrichment coefficients of the heavy metals Cus, Zns, and Cds, respectively. HRI1, HRI2, and HRI3 represent the health risk indices of the heavy metals Cus, Zns, and Cds, respectively.
Agriculture 14 01694 g006aAgriculture 14 01694 g006b
Agriculture 14 01694 g007
Figure 7. Principal component analysis. (a) F1 Heavy metal content in soil surface layer and crop grains. (b) F2 Heavy metal content in soil surface layer and crop grains. (c) F1 Ecological risk index, health risk index, and heavy metal enrichment coefficient. (d) F2 Ecological risk index, health risk index, and heavy metal enrichment coefficient.
Figure 7. Principal component analysis. (a) F1 Heavy metal content in soil surface layer and crop grains. (b) F2 Heavy metal content in soil surface layer and crop grains. (c) F1 Ecological risk index, health risk index, and heavy metal enrichment coefficient. (d) F2 Ecological risk index, health risk index, and heavy metal enrichment coefficient.
Agriculture 14 01694 g007
Agriculture 14 01694 g008
Figure 8. Correlation analysis of soil properties.
Figure 8. Correlation analysis of soil properties.
Agriculture 14 01694 g008
Agriculture 14 01694 g009
Figure 9. Redundancy analysis of soil properties and heavy metal residues in soil and grains.
Figure 9. Redundancy analysis of soil properties and heavy metal residues in soil and grains.
Agriculture 14 01694 g009
Table 1. Nutrient properties and heavy metal content of organic fertilizers.
Table 1. Nutrient properties and heavy metal content of organic fertilizers.
OM (%)TN (%)TP (%)Cd (mg/kg)Cu (mg/kg)Zn (mg/kg)
SF32.852.151.630.500.0390.168
CF48.641.951.570.730.0220.780
PF16.4811.5811.761.070.0170.057
Table 2. Soil physicochemical properties.
Table 2. Soil physicochemical properties.
Soil Depth (cm)BD
(g/cm3)		 θ c
(%)		 θ s
(%)		Ψ
(%)		EC
(μs/cm)		pHOM
(g/kg)		TN
(g/kg)		 NH 4 + -N
(g/kg)		 NO 3 − -N
(g/kg)		TP
(g/kg)		TK
(g/kg)
F10–201.4926.0828.5484.812197.8413.710.898.927.230.9821.90
20–401.4524.5729.3586.172057.849.750.6913.3425.680.6717.88
40–601.4924.6428.4586.022077.8510.070.7918.3537.180.5816.22
F20–201.4329.5130.9184.213198.038.430.6610.513.230.6615.69
20–401.5126.2727.4086.173678.037.860.5512.2643.680.6014.83
40–601.4727.9432.3687.184508.027.020.4719.2358.250.5716.19
Note: BD: Soil bulk density; θ c : Field water holding capacity; θ s : Saturated moisture content; ψ: porosity; EC: soil (1:5) solution conductivity; pH: soil (1:5) solution pH; OM: Organic matter content; TN: Soil total nitrogen content; NO 3 − -N : Soil nitrate nitrogen content; NH 4 + -N : Soil ammonium nitrogen content; TP: Soil total phosphorus content; TK: Total potassium content of the soil.
Table 3. Experimental design.
Table 3. Experimental design.
TreatmentSeedling Stage (Calculation of Pure Nitrogen Content)The Current Bud Period
Organic Fertilizer kg/haUrea
kg/ha		Urea
kg/ha
W1 (No supplemental irrigation)CK (Control)000
PF25 (25%PF + 75% urea)154590
PF50 (50% PF + 50% urea)303060
PF75 (75% PF + 25% urea)451530
SF75 (75%SF + 25% urea)451530
CF75 (75%CF + 25% urea)451530
W2 (Drip irrigation 22 mm)PF25 (25% PF + 75% urea)154590
PF50 (50% PF + 50% urea)303060
PF75 (75% PF + 25% urea)451530
W3 (Drip irrigation 44 mm)PF25 (25% PF + 75% urea)154590
PF50 (50% PF + 50% urea)303060
PF75 (75% PF + 25% urea)451530
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yu, D.; Miao, Q.; Shi, H.; Feng, Z.; Feng, W.; Li, Z.; Gonçalves, J.M. Influence and Mechanism of Fertilization and Irrigation of Heavy Metal Accumulation in Salinized Soils. Agriculture 2024, 14, 1694. https://doi.org/10.3390/agriculture14101694

AMA Style

Yu D, Miao Q, Shi H, Feng Z, Feng W, Li Z, Gonçalves JM. Influence and Mechanism of Fertilization and Irrigation of Heavy Metal Accumulation in Salinized Soils. Agriculture. 2024; 14(10):1694. https://doi.org/10.3390/agriculture14101694

Chicago/Turabian Style

Yu, Dandan, Qingfeng Miao, Haibin Shi, Zhuangzhuang Feng, Weiying Feng, Zhen Li, and José Manuel Gonçalves. 2024. "Influence and Mechanism of Fertilization and Irrigation of Heavy Metal Accumulation in Salinized Soils" Agriculture 14, no. 10: 1694. https://doi.org/10.3390/agriculture14101694

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop