Influence of soil organic carbon, water holding capacity and moisture content on heavy metals in rice paddy soils of Western Ghats of India

doi:10.21203/rs.3.rs-1961747/v1

Analysis of soil samples collected from 16 rice paddy fields located in Western Ghats region was made to quantify the heavy metals concentration. Heavy metal analysis was done for Cu, Zn, Mn, Fe, Ni, Cr, Cd, and Pb using atomic absorption spectroscopy. High concentration of these heavy metals was found in rice paddy fields regularly being cultivated using agrochemicals. We compared this concentration with soils of rice paddy field that was not under cultivation. Cu, Zn, Mn, Fe, Cr, Ni, Pb, and Cd showed a build up at an order of 1.2, 1.3, 2.3, 2.2, 1.8, 2.8, 1.8, and 8.5 times higher in the rice paddy fields cultivated with agrochemical applications. Heavy metals exhibited maximum association (PCA) with soil moisture content (Zn, Fe, Cr, Ni, and Cd), organic carbon content (Fe, Cr, Ni, and Cd) and water holding capacity (Cu, Pb, and Cd). Such associations were absent in the reference site. This indicates the build-up of heavy metals in rice paddy soils under the strong influence of moisture content, water holding capacity, and organic carbon content of the soil.

Agrochemicals

Heavy metals

Rice paddy field

Soil contamination

Western Ghats

India

Heavy metal contamination issues in agricultural soils gained an intensive focus recently in India. Many documented cases are available on the metal toxicity due to mining, industry, foundry, powerplant and agriculture (Nagajyoti et al., 2010). The heavy metals are the significant environmental pollutants in agricultural soil (Atafar et al., 2010; Cai et al., 2012; Ashaiekh et al., 2017; Chen et al., 2022). The rice paddy is one of the most important crops being cultivated with modern technology and application of various agrochemicals (Rogan et al., 2009; Zhao et al., 2010). A large number of various agrochemicals are being applied to rice paddy soils and such applications are reported to be increasing the heavy metal contents of the soil (Reddy et al., 2013). Various earlier studies have recorded the increase in levels of heavy metals that is correlated to the application of synthetic agrochemicals and other managerial practices (Nagajyoti et al., 2010; Bhatti et al., 2016). Heavy metals are mostly persistent and toxic to organisms. Due to their persistency, heavy metals tend to remain in the soil and affect physiological and biological process of the plant (Nagajyoti et al., 2010; Alloway 2013) and organisms associated with the food chain (Nagajyoti et al., 2010).

Rice paddy is a major crop cultivated in Western Ghats region of Karnataka, India. The rice paddy is cultivated depending on the availability of water. The rice paddy cultivation involves intensive application of synthetic fertilizers and pesticides. However, the concentration of heavy metals in soils of rice paddy field is not well documented for the region. Therefore, the overall goals of this study were 1) to quantify the selected heavy metals in these rice paddy fields cultivated with and without usage of agro-chemicals and 2) to record the built up of heavy metal in surface soils of rice paddy fields and to analyse the possible reasons.

Study area

The study area located in a mosaic of different crops of cultivations in the hill terrains of Western Ghats (Fig. 1). The area has sub-tropical climate and the annual precipitation ranges between 769 mm and 1042 mm. Rice paddy cultivation is being done for more than 30 years, however, nearly from the past 10 years the agrochemical application has become a necessary managerial practice. The general information of the site i.e., cultivation history, cultivation pattern, frequency and type of agrochemical used in the sites are collected through questionnaire. During the survey, we found that the current general managerial practice of farming comprises the use of varieties of agrochemicals; synthetic fertilizers, pesticides, biosolids etc. Most of the farmers in the area have used NPK (Nitro-phosphorous and potash 17:17:17 or 20:20:20) or Ammonium phosphate and sulfate (20:20:0:13) or Ammonium phosphate (16:20:0) or DAP (Diammonium phosphate) or Urea and potash fertilizers and Machete (Butachlor, 50% EC, Herbicide), Chlorpyrifos 20% EC and dithiocarbomate fungicides (Table 1). The agrochemical usage varied depending on the managerial practices. In most of these rice paddy fields farmer used bio-organic fertilizer and biosolids as initial nutrient at time of tilling of soil for paddy cultivation (per observation). The rice paddy cultivation is being relayed on rainfed irrigation system. Single cropping per annum with single tillage is the general practice followed. The approximate yield of paddy fields in the area is 2 tons of grains per acre.

Table 1

Fertilizers and agrochemical usage in the rice paddy crop fields of the study area.
Sl. No.	Fertilizers/ Agrochemical used	Class	Target	Approx. Quantity Used	Site No.
1	Butachlor 50% EC	Acetanilide Herbicide	Broad leaf weeds and grasses	1000 mL acre ^− 1	1, 2, 4, 5,7–15
2	Chloropyriphos 20% EC	Organophosphate Insecticide	Hispa, leaf roller, gall midge, stem borer, whorl maggot	500–750 mL acre^− 1	3
3	Mancozeb 75% WP	Dithiocarbamate Fungicide	Rice blast fungi	1000g acre^− 1	6
4	NPK, Diammonium phosphate, Potash, Urea	Mineral fertilizers	Macronutrient supplement	50–300 kg acre^− 1	1–15
5	Bio-solids/ organic composts	Natural soil nutrients	-	3–7 tons acre^− 1
Note: EC- Effective Concentration, WP- Wettable Powder.

Sampling site and soil sampling

Sampling was made in the month of February 2018, which was a cultivation period in the selected sites which is generally characterized with low SMC (range 1.27% − 13%). Soil samples were collected from 16 different rice paddy fields (Fig. 1) located between 13° 43´ 49.3 ̋ ̶ 13° 46´14.6 ̋ N and 75° 38´ 004 ̋ ̶ 75° 38´ 29.8 ̋ E at an altitude ranged between 622 and 637 m msl. Out of 16 sampling sites, in 15 sites rice paddy was cultivated with prominent application of agrochemicals and are considered as “contaminated” sites and one site that has not been cultivated with any synthetic agrochemicals is considered as a “reference site”. Each site has an area of one acre. In each site, soil samples were collected at four locations following the methods described by Hoshmand (2006). At the time of soil sampling, the soil temperature (ºC) was recorded using a mercury bulb thermometer (precision 0.1 ºC). The samples are collected in a zip-lock polythene bag. Following each sampling, the soil samples were shade dried, powdered and sieved using soil sieve (Mesh size 2 mm – HACH soil testing Kit) and then used for chemical analyses.

Analyses of soil samples

Soil organic carbon (SOC %) content was estimated following Walkley and Black rapid titration method (Nelson and Sommers 1996). Soil pH, soil moisture contents (SMC %) and soil water holding capacity (WHC %) were recorded following the methods of Allen (1989). Following the acid extraction (EPA 3050B SW-846), total heavy metal concentrations (ppm) in the soil samples were analyzed using Atomic Absorption Spectrometry (PerkinElmer PinAAcle 900F) (USEPA 1996; Ashaiekh et al., 2019).

Statistical Analysis

Statistical data analysis was performed using SPSS V. 20 statistical software and MS Excel (Microsoft 2019). Basic statistical parameters such as range, mean\(\left(\stackrel{-}{x}\right)\), median, standard deviation (SD), standard error (SE) and skewness were computed. Shapiro-Wilk Lambda (w) was employed to test the normality of all data on soil properties and heavy metal concentrations. One-way ANOVA was used to detect the significant differences in the concentration of various parameters between reference and contaminated soils. Pearson`s correlation coefficient was used to test the association soil parameters and heavy metal concentrations in the soil. Principal Component Analysis (PCA) was used to reduce data and extract smaller number of independent factors for analyzing relationship among soil properties and heavy metal contents. Prior to PCA analysis the values of soil parameters and heavy metals were transformed to z- score. Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy significance < 0.05 is considered as an ideal condition for factor reduction.

Parameters of soil and heavy metals in reference site

In the reference site (Loc. 75°38`24.5” N — 13°44`25.4” E, altitude: 627 m asl) the soil temperature ranged between 28°C and 30°C. The pH of the reference site remained acidic to circumneutral, recorded between 5.3 and 7.2. Statistics of parameters of soil and heavy metal concentrations of reference site are presented in Table 2. The SMC and SOC of the reference site are low while, WHC was recorded up to 25%. The SMC, SOC and WHC showed a little variance over the study period. In reference site, we analyzed and recorded concentrations (ppm) of Copper (Cu), Zinc (Zn), Manganese (Mn), Iron (Fe), Chromium (Cr), Nickel (Ni), Lead (Pb) and Cadmium (Cd). The statistics of these parameter represents that all these values are normally distributed. Further, Table 2 also presents concentrations of heavy metals recorded in reference site with general heavy metal concentrations recorded for typical uncontaminated agricultural soil (Nagajyoti et al., 2010). Except the concentration of Cu, all other heavy metals recorded in the reference site fall within the upper limit of the concentrations detailed for uncontaminated soils. In the reference site, we recorded Cu at a concentration 140.33 ± 0.021 ppm which is higher than those cited by Nagajyoti et al., (2010) for uncontaminated sites.

Table 2

Descriptive statistics of parameters of soil and heavy metals in reference site. The SMC, SOC and WHC of soil are represented in percentage (%) and all heavy metals are represented as mg kg^− 1 of soil.
Parameter		Max	Range		SE	Variance		Kurtosis
SMC	1.20	1.30	0.10	1.27	0.236	0.002	-1.414	1.5	—
SOC	0.72	0.78	0.06	0.75	0.123	0.001	0.000	1.5	—
WHC	22.50	23.00	0.50	22.83	0.118	0.06	-1.414	1.5	—
Cu	140.10	140.50	0.40	140.33	0.850	0.03	-1.056	1.5	2-100
Zn	26.20	26.60	0.40	26.43	0.850	0.03	-1.056	1.5	10–300
Mn	162.60	163.00	0.40	162.77	0.850	0.03	1.056	1.5	100-4,000
Fe	9600.00	9695.00	95.0	9650.00	19.472	1516.67	-0.381	1.5	7,000–55,000
Cr	77.70	81.40	3.70	79.97	0.811	2.63	-1.270	1.5	5-3000
Ni	30.40	31.70	1.30	30.93	0.278	0.31	1.111	1.5	10–100
Pb	16.20	18.30	2.10	16.93	0.484	0.94	1.403	1.5	2-200
Cd	0.10	0.20	0.10	0.13	0.024	0.002	1.414	1.5	0.001-0.7
*Nagajyoti et al. (2010)

Result of correlation co-efficient analysis

Table 3 details correlation coefficient between parameters of soil and heavy metal concentration in reference site. The analysis indicates the reduction in concentration of Mn, Ni, and Pb, with increase in SMC (%). In contrast, the concentration of Zn showed an increase with SMC at a significant level. The increase in SOC the concentration of Mn and Ni are reduced. The Cu concentration increased with increasing WHC while Cd concentration decreased significantly. Among the correlations of heavy metals, the increase in Cd concentration has decreased the Cu content. Increase in lead content concurrently increased the concentration of Mn and Ni and decreased Zn concentration. Increase in Fe content showed an increase in Cr content while similar increase was observed between Pb and Ni. Among the parameters of the soil, the SMC comprised maximum correlation with heavy metals. This exhibited R² = 0.942; F = 32.667, p = 0.029. The WHC, SMC, SOC and pH of the soil did not exhibit correlation in reference site.

Table 3

Pearson correlation co-efficient between parameters of soil and heavy metals of reference site (N = 16).
Parameter	SMC	SOC	WHC	Cu	Zn	Mn	Fe	Cr	Ni	Pb	Cd
SMC	-
SOC	0.866	-
WHC	-0.500	-0.866	-
Cu	-0.277	-0.721	0.971*	-
Zn	0.971*	0.721	-0.277	-0.038	-
Mn	-0.971*	-0.961*	0.693	0.500	-0.885	-
Fe	-0.817	-0.419	-0.091	-0.327	-0.932	0.655	-
Cr	-0.625	-0.151	-0.363	-0.577	-0.794	-0.419	0.961*	-
Ni	-0.975*	-0.955*	0.679	0.482	-0.894	1.000**	0.670	0.438	-
Pb	-0.999**	-0.886	0.536	0.318	-0.960*	0.980*	0.792	0.592	0.984*	-
Cd	0.500	0.866	-1.000**	-0.971*	0.277	-0.693	0.091	0.363	-0.679	-0.536	-

*Significant at 0.05 level (2 tailed)

**Significant at 0.01 level (2 tailed)

Parameters of soil and Heavy metals in contaminated sites

In contaminated sites (15 sites located 75°38`00.4” — 75° 38`29.8” N and 13° 43`20.0” — 13° 49`0.3” E; altitude: range 624 — 637 m. asl) the soil temperature ranged between 25°C and 35° C. Circumneutral pH ranged between 5.6 and 7 was recorded. Table 4 details the statistics of parameters of soil and heavy metals. The SMC and organic carbon content remained low; while WHC ranged between 21 and 49%. The values of heavy metal concentration of different contaminated sites over the study period showed a considerably low variance and data are normally distributed. Except concentration of Cu and Cd, the values of all other parameters were found within the range detailed for typical uncontaminated soils (Nagajyoti et al., 2010). The Cu and Cd concentration was found to be high.

Table 4

Descriptive statistics of parameters of soil and heavy metals in contaminated sites. The SMC, SOC and WHC of soil are represented in percentage (%) and all heavy metals are in mg kg^− 1.
Parameter	Min	Max	Range	Mean	SE	Variance	Skewness	Kurtosis
SMC	1.67	12.43	10.76	5.98	0.827	10.267	0.711	-0.346
SOC	0.36	1.10	0.74	0.70	0.702	0.74	0.256	-1.1557
WHC	21.67	48.13	26.46	33.15	2.173	70.837	0.999	-0.097
Cu	126.63	202.10	75.47	162.49	5.798	504.286	-0.151	-0.504
Zn	27.40	43.70	16.30	34.76	1.429	30.620	0.475	-1.265
Mn	92.20	943.33	851.13	368.25	66.838	67009.817	1.205	0.238
Fe	10946.6	33336.67	22390.00	21253.89	1693.542	43021273.920	0.155	-0.649
Cr	22.50	255.83	233.33	147.50	18.597	5187.474	-0.147	-0.708
Ni	17.60	177.87	160.27	86.21	12.630	2392.581	0.473	-0.416
Pb	11.27	83.03	71.76	30.35	4.991	373.658	1.605	2.920
Cd	0.40	6.03	5.63	1.10	0.358	1.921	3.660	13.816

Result of correlation co-efficient analysis

Table 5 represents correlation co-efficient analysis between parameters of soil and heavy metals. The SMC showed a strong correlation with Zn, Fe, Cr, Ni, and Cd. The concentration of Zn, Fe, Cr, Ni and Cd have showed an increase with the increase in concentration of SMC. Whereas, the concentration of Fe, Cr, Ni and Cd decreased with increase in SOC content. Similarly, with the increase in WHC of the soil the Cu concentration decreased and Pd and Cd concentration increased. Among the heavy metals the Cd concentration has increased with an increase in Fe, Cr, Ni, and Pb. While, Pb showed only positive correlation with Mn; as Pb increased the concentration of Mn increased. Ni content showed a strong positive correlation with Cu, Zn, Fe, and Cr. An increase in Ni content increased the concentration of these metals.

Table 5

Pearson correlation co-efficient between parameters of soil and heavy metals of contaminated sites (N = 60).
Parameter	SMC	SOC	WHC	Cu	Zn	Mn	Fe	Cr	Ni	Pb	Cd
SMC	-
SOC	-207	-
WHC	0.213	0.032	-
Cu	0.237	0.164	-0.343**	-
Zn	0.552**	0.128	-0.022	0.636**	-
Mn	-0.038	0.009	0.039	0.248	0.292*	-
Fe	0.399**	-0.259*	-0.016	0.233	0.697**	0.257*	-
Cr	0.342**	-0.557**	-0.008	-0.50	0.343**	0.055	0.839**	-
Ni	0.421**	-0.309*	-0.126	0.384**	0.699**	0.160	0.927**	0.824**	-
Pb	0.118	0.103	0.358**	-0.162	0.244	0.328*	0.191	0.082	-0.019	-
Cd	0.582**	-0.306*	0.554**	-0.127	0.248	0.144	0.401**	0.463**	0.295*	0.686**	-
*Significant at 0.05 level (2 tailed)
**Significant at 0.01 level (2 tailed)

Increase in Cr concentration showed an increase in Zn and Fe concentration. Whereas increase in Fe concentration showed an increase in Zn and Mn concentration but Zn has showed a significant positive correlation with Cu. The correlation analysis between concentration of heavy metal and quantity of synthetic fertilizer or pesticide applied did not yield significant result except the association between synthetic fertilizer and cadmium (r = 0.594, p = 0.019). Further, pH of the soil did not show any correlation with other parameters of soil or heavy metal concentration.

Heavy metal concentration in contaminated sites

All heavy metals recorded have showed a clear increase in their concentration in the contaminated sites (Fig. 2). The magnitude of increase differs among different heavy metals. Table 6 represents the result of ANOVA and parameter of soil and heavy metals between the reference and contaminated sites. On an average, the SMC and WHC of contaminated rice paddy soil showed 4.7 and 1.5 times increase in their concentrations compared to reference site and found to be statistically significant (p < 0.05). However, SOC content slightly decreased in contaminated sites (0.9% of reference site) and differences with reference site is insignificant. All heavy metals have showed clear increase in their concentration in contaminated sites; represented 1.2, 1.3, 2.3, 2.2, 1.8, 2.8, 1.8 and 8.5 times increase for Cu, Zn, Mn, Fe, Cr, Ni, Pb and Cd respectively compared to their concentration in reference site. Among these Zn, Fe, and Ni, showed highly significant statistical difference (p < 0.01) between

Table 6

ANOVA and parameters of the soil and heavy metals showing the statistical difference between reference and contaminated sites.
Parameter	Total sum of squares	df	Mean square	F	p
WHC	1327.8229	18	335.9433	5.76	0.028126
SMC	213.9422	18	70.1939	8.3	0.010372
SOC	1.044495	18	0.007895	0.13	0.722873
Cu	8609.9858	18	1549.8938	3.73	0.070291
Zn	647.8236	18	219.0527	8.69	0.009000
Mn	1071472.8484	18	13333.3231	2.42	0.138214
Fe	1027513644.41	18	425211259.542	12	0.002966
Cr	87032.9038	18	14400.3815	3.37	0.083949
Ni	43146.2713	18	9649.2113	4.9	0.040817
Pb	5802.3432	18	568.33	1.85	0.191548
Cd	29.865607	18	2.9631	1.87	0.189284

reference and contaminated sites. Although, Cu and Cr were represented 1.2 and 1.8 times higher concentration, the differences are marginally significant (p < 1). Which could be due to high variance of data. Mn, Cr, Pb and Cd though represented at higher concentration did not show statistical significance. Among these, the values of Mn, Cr, and Pb also had high variance in their data. Therefore, it is apparent that Cu, Zn, Mn, Fe, Cr, Ni, and Pb have showed a strong buildup in their concentration in contaminated sites.

The correlation analysis reveals a maximum significant association of heavy metals (Zn, Fe, Cr, Ni and Cd) with SMC. This followed by organic carbon content of soil (with Fe, Cr, Ni and Cd) and WHC of the soil (with Cu, Pb and Cd). The Principal Component Analysis (PCA) was performed following standard procedure to illustrate the relationship of these three parameters with heavy metal concentration. The Table 7 details the component of PCA and eigen values while, Fig. 3 illustrates Principal Component Analysis (PCA) of parameters of soil and heavy metals. These three parameters together contribute 78% of the total association. Overall, the Zn, Fe, Mn, Cr, Ni and Cd correlated with PC1. Similarly, Cu, Zn, Pb and Cd with PC2 and Zn, Mn, and Pb exhibited correlation on PC3. The test revealed a significant (p = 0.001) value for Bartlett test of sphericity with a KMO = 0.484 and ꭓ² = 128.946, df 55. Among these three parameters, the WHC revealed maximum correlation (40.259% variance) followed by SMC (20.854% variance) and SOC (16.832% variance) indicates their influence for the buildup of heavy metal in the contaminated sites. The data on parameters of the soil and heavy metal with quantity of synthetic fertilizers or pesticides did not yield significant result (KMO sampling adequacy = 0.317). Thus, data on the synthetic fertilizer or pesticide were not considered to process PCA.

Table 7

Total variance explained and component matrix for the parameters of soil and heavy metals in Rice paddy field soil
Component	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
Component	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total
1	4.428	40.259	40.259	4.428	40.259	40.259	3.306
2	2.294	20.854	61.112	2.294	20.854	61.112	2.509
3	1.851	16.832	77.944	1.851	16.832	77.944	3.442
4	0.877	7.974	85.917
5	0.605	5.498	91.415
6	0.385	3.501	94.916
7	0.326	2.966	97.883
8	0.160	1.458	99.341
9	0.048	0.438	99.779
10	0.016	0.148	99.926
11	0.008	0.074	100.000

Parameter/ Elements		Component Matrix ^∗				Pattern matrix ^{∗ ●}			Structure Matrix ^∗●
Parameter/ Elements		PC1	PC2		PC3	PC1	PC2	PC3	PC1		PC2	PC3
WHC			-0.668		0.431		-0.795				-0.771
SMC		0.654				0.482			0.543		-0.453
SOC		0.507			0.655			0.913				0.852
Cu			0.779			0.800			0.726
Zn		0.650	0.520		0.493	0.961			0.948
Fe		0.897				0.671		-0.503	0.768			-0.640
Mn		0.666			-0.424			-0.838				-0.850
Cr		0.872						-0.841	0.456			-0.899
Ni		0.862				0.736		-0.498	0.820			-0.613
Pb			-0.464		0.624		-0.829				-0.802
Cd		0.661	-0.580				-0.829				-0.891	-0.472
	Kaiser-Meyer-Olkin Measure of Sampling Adequacy.									0.484
Bartlett's Test of Sphericity				Approx. Chi-Square						128.946
				df						55
				Sig.						.001
∗ Extraction method: Principal Component Analysis

● Rotation method: Oblimin with Kaiser Normalization

In the present study the reference site has low concentration of heavy metals (except Cu) comparable to those of heavy metals reported for agriculture soils (Nagajyoti et al., 2010). In the reference site SMC, SOC, and WHC were also represented low and these parameters did not show association within themselves by correlation. The pH of the soil was considered as the most important factor regulating the solubility and mobility of heavy metals (Reddy et al., 2013; Salem et al., 2020). Further, it has been observed that higher pH resulted in lower concentration of heavy metals in rice paddy fields (Zeng et al., 2011). This represents the importance of pH in regulating heavy metal concentration in rice paddy field. However, in the present study both in contaminated and reference sites, the pH of soil remained acidic to circumneutral and did not indicate any correlation with heavy metals.

In contaminated sites, the concentrations of heavy metals have clearly increased compared to the reference site at an order of 1.2, 1.3, 2.3, 2.2, 1.8, 2.8, 1.8, and 8.5 time respectively for Cu, Zn, Mn, Fe, Cr, Ni, Pb, and Cd (Fig. 2). Increase in heavy metal content is generally attributed to application of fertilizer (Liu et al., 2007; Huang et al., 2021); agrochemicals (Zhao et al., 2010) natural sources (Song et al., 2018), industrial sources and various soil amendments (Wang et al., 2020). In the present study, there is clear evidence of application of agro-chemicals and pesticides in contaminated sites, however, the pesticides and concentrations of synthetic fertilizers did not show a clear correlation. Further, there were no other sources of heavy metals like industrial effluent entering into rice paddy fields. The farmers apply natural organic materials such as organic vermicompost, humic substances, plant extract in addition to synthetic fertilizers. In the present study, it has been observed that there is a strong correlation existing between only SMC-Zn, SMC-Fe, SMC-Cr, SMC-Ni, SMC- Cd and SOC-Fe, SOC-Cr, SOC-Ni, SOC-Cd; similarly, WHC with Cu, Pb, and Cd.

In general, heavy metals in soil are in the form of cations and retained on soil particles by forming chemical bonds with organic or inorganic ligand ions (Zeng et al., 2017). The soil organic content is known to affect significantly on speciation and total concentration of heavy metals due to its strong complexation ability (Zhang et al., 2020). Similarly, WHC and SMC are contributing significantly for heavy metal transformation (Zhang et al., 2020). Therefore, in the present study, we observed a strong correlation between the parameters of the soil and all heavy metals. Among the contaminated sites, the probable source of additional heavy metal is the application of synthetic fertilizers. However, high content of WHC, SMC and SOC might have retained these heavy metals at a higher concentration over the period. This requires further investigation. It has been noted that organic matter contains the hydroxyl and carboxyl functional groups, which forms an organic metal complex resulting in increasing metal concentration (Wang et al., 2020). In the present study the build-up of heavy metal was recorded in contaminated sites and three soil parameters have achieved 78% of total association with heavy metals. The build-up of heavy metal could be due to influence of SOC, WHC and SMC on the heavy metals that were induced to rice paddy soils by the application of synthetic agro-chemicals. Further, in multi-metal contaminated soils, it has been recorded that presence of one metal can alleviate the immobilization efficiency of the others (Kumpiene et al., 2008). Thus, in many cases, the interacting concentrations among Pb, Cd and Zn was recorded (Rodríguez-Vila et al., 2014). In our study, we found increase in Pb content with the increase in Cd content of the soil. In these rice paddy fields, farmer used bio-organic fertilizer and biosolids as initial nutrient at time of tilling of soil for paddy cultivation. These bio-organic fertilizers are known to accelerate soil organic matter and enhances the fertility and water retention (Vijesekara et al., 2017; Wu, 2017). Therefore, agriculture practices and types of soil nutrient supplements may influence the build-up of heavy metals in rice paddy soils by enhancing organic content and water holding capacity.

Our study showed that the heavy metal concentrations in cultivated rice paddy soil has exceed the concentrations of same metals recorded for references site. The heavy metals have clearly showed a buildup at an order of 1.2, 1.3, 2.3, 2.2, 1.8, 2.8, 1.8, and 8.5 time respectively for Cu, Zn, Mn, Fe, Cr, Ni, Pb, and Cd in contaminated sites. In addition to correlation among the heavy metals, we observed a strong correlation between SMC-Zn, SMC-Fe, SMC-Cr, SMC-Ni, SMC- Cd and SOC-Fe, SOC-Cr, SOC-Ni, SOC-Cd; similarly, WHC with Cu, Pb, and Cd, indicating that the soil moisture content, soil organic content and water holding capacity of the soil determines the heavy metal build-up as these three parameters have contributed a total of 78% association with heavy metals and such correlation between soil properties and heavy metals are absent in reference site.

Author Contributions All authors contributed to the study conception and design. Data collection, Formal analysis, Investigation, writing draft was performed by Ranjana R H. Field work, Formal analysis, Investigation, Review and editing was performed by M V Chethana Kumara. Conceptualization, Methodology, Software, Validation, Formal analysis, Resources, Data curation, Review and editing, Visualization, Supervision was performed by S V Krishnamurthy. All authors read and approved the final manuscript.

Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability The data that support the findings of this study are available from the corresponding author upon request.

Competing Interests, the authors have no relevant financial or non-financial interests to disclose.

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No competing interests reported.

Influence of soil organic carbon, water holding capacity and moisture content on heavy metals in rice paddy soils of Western Ghats of India

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Abstract

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Introduction

Materials And Methods

Statistical Analysis

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Discussion

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