Trace Metal Accumulation in Rice Variety Kainat Irrigated with Canal Water

Abstract

Due to the rapid increase in industrial and urban areas, environmental pollution is increasing worldwide, causing unwanted changes in the air, water, and soil at biological, physical, and chemical levels, ultimately causing negative effects for living things. This work was performed in Jhang, Punjab, Pakistan, and examined and measured heavy metal levels in various plant parts of the rice (Oryza sativa) variety Kainat (roots, shoots, and grains) with results been set in relation to the soil around the root area. The samples were taken from five different sites. The mean level of trace metals (mg/kg) in grains was soil-dependent and varied from cadmium (Cd) (2.49–5.52), zinc (Zn) (5.8–10.78), copper (Cu) (4.82–7.85), cobalt (Co) (1.48–6.52), iron (Fe) (8.68–14.73), manganese (Mn) (6.87–13.93), and nickel (Ni) (2.3–8.34). Excluding Cd, the absorption of all metals under inspection was recorded within permissible limits, as recommended by the FAO and WHO. The pollution load index for Cd was highest at all sites. The enrichment coefficient of Co, Cd, and Cu were greater. The bioaccumulation factor at all studied sites was present, in order: Cu ˃ Zn ˃ Fe ˃ Mn ˃ Co ˃ Ni ˃ Cd. The translocation factor was present at five different sites: Mn ˃ Fe ˃ Cu ˃ Zn ˃ Co ˃ Cd ˃ Ni. The health risk index of all inspected metals was lower than 1 and was within safe limits. The higher pollution of Cd suggested maintenance of rice crop is recommended, decreasing health risks in humans.

1. Introduction

In Pakistan, rice is the second staple food after wheat, hence it is a vital crop for the nation’s economy, wealth, and food security. Its contribution to the economy is very significant as its foreign exchange earnings exceed USD 2 billion annually. Pakistan is the fourth largest rice exporter in 2020/2021, accounting for 4 billion metric tons, and rice is a widely distributed cereal crop around the globe [1].

Heavy metals enter the environment both through natural sources and human activities. Recently, heavy metals have attracted worldwide attention, owing to their non-biodegradability, and being accumulated in living things, thus posing considerable threats to humans and the broader ecosystem [2,3,4]. Rice is known to accumulate heavy metals such as cadmium (Cd), lead (Pb), and zinc (Zn); through the roots, it eventually delivers them to the shoots and grains [5,6,7], and consequently, these metals enter the food chain through rice consumption. Even low concentrations accumulated from the soil can cause toxicities in humans [8,9,10]. In short, rice grown on metal contaminated soils is a live challenge to food production, food quality, and food safety [11,12,13,14]; consequently, there are ever-increasing demands by governments, retail, and consumers for metal minimization in rice.

The cultivation of rice crops in polluted soils is a debated subject because of the plant’s capability to uptake and absorb hazardous metals from such contaminated soils. Few micronutrients such as zinc and copper are essential for healthy plant growth, however, others such as cadmium and lead have proven to be hazardous to ecosystems in general and to human health, especially when consumed in higher concentrations. Similarly, their persistence, due to their toxic nature, exposes serious health risks to other living organisms, too [15,16,17]. Contemporary investigations into toxicity and tolerance in metal-stressed plants are prompted by the growing metal pollution of the environment [18,19]. One contributor to this pollution is the intensive application of inorganic and organic fertilizers for intense agriculture [20,21]. Although the levels of heavy metals in agricultural soils are very small at the point of initial application, repeated use of phosphate fertilizers may lead to concerning level accumulation [22,23,24,25].

Many of these heavy metals are carcinogenic, resulting in various diseases, especially kidneys, cardiac, bone, and blood diseases. Heavy metals exert a toxic effect on food crops, animals and humans, and cause various clinical problems in humans [26,27,28,29,30]. Heavy metals are human carcinogens and are the critical basis for various diseases [31,32]. Heavy metal accumulation in soils is of concern in agricultural production because of the adverse effects on food safety and marketability, crop growth due to phytotoxicity, and environmental health of soil organisms [33,34]. The influence of plants and their metabolic activities affects the geological and biological redistribution of heavy metals through pollution of the air, water, and soil.

The translocation factor (TF) and bioaccumulation factor (BAF) are important in screening hyper-accumulators for the phytoremediation of heavy metals. The TF is the capacity of plants to transfer metals from roots to shoots, and BAF expresses the ability of plants to accumulate metals from soils to tissues [35,36].

This study was performed to examine the impact of canal water irrigation on metal uptake in rice through the soil and the potential health risk of this in humans.

2. Materials and Methods

2.1. Experimental Site

The agricultural area of Jhang, a district in central Punjab (Pakistan), was selected as a study site. Most of the land is cultivated except for the land present near the Chenab River. In winters, irregular rainfall occurs, while the annual average rainfall is 100–150 mm per year. The agricultural area of Jhang is about 8809 km².

At Moza Satiana, Chiniot road, five sites were selected to examine the levels of various metals present in soils of paddies irrigated through canal water.

A detailed description of the experimental sites studied is presented in Figure S1.

2.2. Sample Collection and Preparation

Four samples (using five replicates of each sample) of soil grown over Kainat (a popular variety of rice) from five different sites were selected for analysis. The soil was collected from 150 mm depth, dug up by a stainless augur, and following the method of Sanchez et al. [37]. Before placing the samples in the oven, they were dried in sunlight. The oven temperature was set to 105 °C.

Similarly, four samples of paddy grains, roots, and shoots (five replicas) were taken from the same five study sites, using a sterile apparatus. To remove dust particles, the grains were washed with deionized water, followed by a 0.5 M dilution of HCl. The grains were pre-dried in sunlight, followed by further oven drying at 105 °C for 5 days. The dry samples were taken out from the oven and were ground into a powder with a pestle or mortar.

For rice and soil, 2 g of ground samples were digested using an adoption of the “Wet Digestion Method” [38]. The samples were transferred into a digestion compartment and 10 mL of aqua regia (1:3 v/v) was added. The digestion mix was left overnight and on the next day, the mixture was heated on a hot plate (70 °C) for 4 h and under the addition of 2 mL H₂O₂. The digestion process was stopped once the solution turned colorless. During cooling, the sample solution was filtered by using a 42 µm filter paper and then diluted with distilled water to 50 mL volume.

2.3. Sample Analysis

The digested samples were analyzed in an atomic absorption spectrophotometer (AA-6300, Shimadzu, Japan) for the quantitative analysis of heavy metals. Seven metals were selected for investigation in this study, namely cadmium, zinc, copper, cobalt, iron, manganese, and nickel.

To prevent the risk of contamination during laboratory work, the apparatus was washed prior to use. All required chemicals and salts (for digestion and analysis on AAS) used in the experiments were supplied by Merck (Germany).

Concentrations among rice and soil samples were determined on a dry weight basis. All analyses were repeated in triplicate.

The bioaccumulation factor (BAF) was computed according to the equation below [39].

$$BAF=\frac{metal concentration in grain\left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)}{metal concentration in soil\left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)}$$

(1)

The translocation factor (TF) was determined as seen in Ref. [40]:

$$TF=\frac{the metal concentration \left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)in plant{s}^{\prime }shoot}{the metal concentration \left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)in plant{s}^{\prime }root }$$

(2)

The pollution load index (PLI) calculating the metal quantity in the soil samples was determined by [41]:

$$PLI=\frac{metal in examined soil \left(ppm\right)}{ standard value of soil metal \left(ppm\right)}$$

(3)

The enrichment factor (EF) describes the amount of metal retained in the soil. EF is reliant on the accessibility of metals according to their chemical form present in the soil, growth rate, and variance in the metal uptake ability of different plant species and has been calculated by [42]:

$$EF=\frac{\frac{metals \left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)at edible part of Oryza sativa}{metal \left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)in investigated soil}}{\frac{standard concentration of metals \left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)in edible part of Oryza sativa}{standard concentration \left(\frac{\mathrm{mg}}{\mathrm{kg}}\right)of metal in soil}}$$

(4)

The daily intake of metals (DIM) in adults was assessed by this formula [43]:

$$DIM=\frac{\left(C_{metal}\times C_{daily food intake}\right)}{\left(B_{average weight}\right)}$$

(5)

where C_metal = metal contents, C_{daily food intake} = daily consumption of food crops per person, per day in kg and B_{average weight} = average body weight of a person in the exact study area.

The average consumption of rice for this study location equates to 0.345 kg/person and the average body weight is 60 kg/person [44,45].

A calculation has been used to determine the hazard potential of heavy metal exposure involved via ingestion of rice. The so-called health risk index (HRI) was calculated through Ref. [46]:

$$HRI=\frac{Daily intake of metal}{Oral reference dose}$$

(6)

HRI < 1 in any food crop denotes that the consumer population is free from serious risks to health, while HRI > 1 designates significant health hazards.

2.4. Statistical Analysis

The results from all the samples were subjected to analysis of variance (ANOVA) according to Duncan’s multiple range test (p < 0.05). Multivariate statistical analysis (MSA) was performed for source apportionment [47]. Minitab 16 and SPSS 21 statistical software were used for the rest of the analysis results. Correlation analysis is considered an effective tool to show relationships between elements within a substance and with other substances. Concentrations of elements show a significant correlation disseminating from a similar or same source.

3. Results and Discussion

3.1. Concentrations of Heavy Metals Involved in Soil

ANOVA highlights the significant (p < 0.05) impact of metal concentrations in soil on Kainat (

Table 1. Mean concentration (mg/kg) of heavy metals in soil and grains of Kainat.

Site	Metal
	Cd	Zn	Cu	Co	Fe	Mn	Ni
Soil
Site-I	11.743 ± 0.005 c	14.481 ± 0.004 c	10.429 ± 0.006 c	11.631 ± 0.004 a	24.126 ± 0.005 a	22.478 ± 0.006 a	13.615 ± 0.005 b
Site-II	12.728 ± 0.005 b	12.465 ± 0.005 d	9.416 ± 0.004 d	9.615 ± 0.005 b	20.11 ± 0.005 b	20.464 ± 0.004 c	12.601 ± 0.005 c
Site-III	13.714 ± 0.004 a	15.452 ± 0.004 b	11.402 ± 0.006 b	4.6 ± 0.007 c	15.09 ± 0.005 d	21.448 ± 0.005 b	9.585 ± 0.005 e
Site-IV	10.702 ± 0.004 d	14.438 ± 0.005 c	8.385 ± 0.005 e	8.583 ± 0.005 b	18.077 ± 0.004 c	19.433 ± 0.006 d	11.573 ± 0.005 d
Site-V	9.688 ± 0.005 e	18.423 ± 0.005 a	12.373 ± 0.005 a	12.568 ± 0.005 a	19.063 ± 0.005 b	18.418 ± 0.005 e	14.558 ± 0.005 a
Maximum permissible limit	3 a	300 a	100 a	50 a	21,000 b	2000 a	50 a
Root
Site-I	9.538 ± 0.288 c	10.343 ± 0.420 cd	9.65 ± 0.288 b	9.09 ± 0.288 a	19.342 ± 0.220 a	15.596 ± 0.288 a	11.698 ± 0.288 b
Site-II	10.343 ± 0.388 b	9.642 ± 0.520 d	8.517 ± 0.220 c	7.078 ± 0.288 b	10.233 ± 0.220 d	16.581 ± 0.363 a	9.685 ± 0.480 c
Site-III	11.328 ± 0.788 a	13.63 ± 0.644 b	9.375 ± 0.288 b	3.064 ± 0.220 d	13.1 ± 0.288 c	11.568 ± 0.420 b	7.663 ± 0.363 d
Site-IV	9.313 ± 0.688 c	9.618 ± 0.488 d	7.267 ± 0.220 d	6.048 ± 0.363 c	12.983 ± 0.220 c	9.552 ± 0.288 c	8.645 ± 0.433 cd
Site-V	7.298 ± 0.488 d	16.602 ± 0.463 a	11.15 ± 0.144 a	8.033 ± 0.388 ab	15.85 ± 0.288 b	12.538 ± 0.320 b	12.63 ± 0.344 a
Maximum permissible limit	0.1–0.2 c	100 c	20 c	0.01 c	425.5 d	500 d	103 e
Shoot
Site-I	7.223 ± 0.541 c	10.286 ± 0.720 b	8.74 ± 0.288 a	7.235 ± 0.288 a	18.326 ± 0.220 a	15.595 ± 0.288 a	10.202 ± 0.288 a
Site-II	5.542 ± 0.488 d	8.276 ± 0.520 c	7.726 ± 0.220 b	6.222 ± 0.288 b	9.312 ± 0.288 cd	16.580 ± 0.363 a	8.175 ± 0.388 ab
Site-III	10.53 ± 0.344 a	10.262 ± 0.488 b	8.714 ± 0.220 a	2.207 ± 0.288 d	11.297 ± 0.288 d	11.567 ± 0.420 bc	5.170 ± 0.363 cd
Site-IV	8.515 ± 0.463 b	8.975 ± 0.724 c	6.700 ± 0.300 bc	5.192 ± 0.288 c	10.282 ± 0.288 c	9.551 ± 0.288 c	4.155 ± 0.220 d
Site-V	4.498 ± 0.563 d	12.232 ± 0.586 a	5.865 ± 0.220 c	6.18 ± 0.244 b	13.267 ± 0.288 b	12.537 ± 0.320 b	7.142 ± 0.288 b
Maximum permissible limit	0.1–0.2 c	100 c	20 c	0.01 c	425.5 d	500 d	103 e
Grains
Site-I	5.552 ± 0.004 b	9.855 ± 0.009 b	6.881 ± 0.004 b	6.521 ± 0.006 a	14.735 ± 0.005 a	13.933 ± 0.005 a	8.343 ± 0.004 a
Site-II	3.538 ± 0.005 c	7.835 ± 0.006 c	5.865 ± 0.005 c	5.504 ± 0.006 b	8.714 ± 0.004 bc	12.916 ± 0.004 b	6.331 ± 0.004 b
Site-III	2.523 ± 0.005 d	9.818 ± 0.005 b	7.852 ± 0.004 a	1.488 ± 0.005 e	9.702 ± 0.004 b	8.902 ± 0.006 d	3.318 ± 0.005 d
Site-IV	6.503 ± 0.006 a	5.803 ± 0.005 d	5.838 ± 0.005 c	3.473 ± 0.005 d	8.688 ± 0.005 c	9.888 ± 0.005 c	2.303 ± 0.005 e
Site-V	2.491 ± 0.004 d	10.788 ± 0.005 a	4.823 ± 0.005 d	4.46 ± 0.005 c	9.673 ± 0.005 b	6.873 ± 0.005 e	5.288 ± 0.005 c
Maximum permissible limit	0.1–0.2 c	100 c	20 c	0.01 c	425.5 d	500 d	103 e

Sources: ^a European Union (2006), ^b USEPA (1997), ^c FAO/WHO (2011), ^d FAO/WHO (2001), ^e SEPA (2005). Different lowercase letter(s) within a column for each parameter are significantly different from each other according to Duncan’s multiple range test (p < 0.05).

, Figure 1). At all sites, the metals were found in the following sequence: Mn ˃ Fe ˃ Zn ˃ Ni ˃ Cd ˃ Cu ˃ Co (Table 1).

In the current study, the levels of Fe, Cu, Mn, Zn, and Ni in irrigation soils (mg/kg) were lower compared to Cd contents and higher as compared to data recorded by Ekmekyapar et al. [48].

A lower amount of Cu content was determined in present soils than outcomes reported by Tariq et al. [1]. Amongst the soil of all sites, the levels of Ni, Zn, and Cu in this study were found within the acceptable range (except for Cd) as set by Awashthi et al. [49]. The concentrations of Mn and Co in soil were within the allowable limit set by the European Union [50] and the ferrous concentration in soil was lower than 21,000 mg/kg as proposed by EPA [51].

3.2. Concentration of Heavy Metals in Roots

Significant (p < 0.05) impact of Cd, Cu, Zn, Co, Mn, Fe, and Ni concentration was seen in roots (Table S1, Figure 1). The concentrations of metals at five sites were in this order: Mn ˃ Fe ˃ Zn ˃ Ni ˃ Cd ˃ Cu ˃ Co (Table 1).

In roots, the levels of Mn, Cu, Zn, Fe, and Ni were lower than levels presented (2.93, 5.37, 1.68, 1.85 and 0.0068 mg/kg, respectively) by Yadav et al. [52]. Co and Cd levels were higher than the concentrations (1.86 and 1.45 mg/kg) observed by Juen et al. [53]. In this study, all metals mean concentrations obtained from root samples were increased compared to Singh et al. [54]. Based on this study’s findings, Kainat rice is a hyper-accumulator plant having a significant potential for absorbing heavy metals from ground soil; this also agrees with the literature [55].

3.3. Concentration of Heavy Metals in Shoot

ANOVA results determined a significant (p < 0.05) influence of Co, Cu, Fe, Cd, Mn, and Ni in the shoot, whereas Zn exhibited a non-significant impact on the plants (Table 1, Figure 1). Following trends were seen for concentrations of metals at all sites: Mn ˃ Fe ˃ Zn ˃ Cu ˃ Cd ˃ Ni ˃ Co (Table 1).

In this study, the levels of Cu, Cd, and Zn were higher than the values (0.24, 0.76, and 0.49 mg/kg) determined by Ogunkunle et al. [56]. Similarly, the values of Cu, Cd, Zn, Mn, and Fe metals were also higher than the findings reported by Yap et al. [15]. However, Yadav et al. [52] presented lower levels of Fe, Mn and Ni compared to current findings.

3.4. Concentration of Heavy Metals in Grains

The result from ANOVA depicted a significant (p < 0.05) impact of Zn, Cd, Fe, Co, Ni, Cu in the sites and Mn in the case of grains (Table 1). The descending order of metals in grains of five sites was: Mn ˃ Fe ˃ Zn ˃ Cu ˃ Ni ˃ Co ˃ Cd (Table 1).

When the mean concentration of heavy metals was compared with SEPA (2005) standards, the Cd concentration noticed in grains was greater, while Ni, Zn, and Cu were lower. Similarly, analyzed Fe, Mn, and Co concentrations in the present study were also below the recommended standards [57]. Metals level ranking in grains of Kainat was Mn ˃ Fe ˃ Zn ˃ Cu ˃ Ni ˃ Co ˃ Cd. Mean levels of Cd, Ni, Co were larger and Zn, Fe, Mn, Cu were found to be lower compared to the findings of Shaar et al. [58]. Comparing metal contents with Jaishree et al. [59], the concentrations of Cd, Cu, and Ni were lower, while Mn, Zn, and Cd were increased.

3.5. Correlation

A positive and significant correlation of cadmium, zinc, cobalt, and cuprous was detected in the cases of soil-root and root-shoot and shoot-grain interaction. Fe displayed a positive but non-significant correlation with soil-root, while root-shoot and shoot-grain detected a positive and significant correlation. Similarly, a positive significant correlation was also noticed for soil-root in the case of Mn, but a positive and non-significant correlation was observed for root-shoot and shoot-grain. Nickel exhibited a positive, but non-significant correlation with soil-root and root-shoot’s relationship, whereas a positive and significant correlation from shoot-grain was detected (

Table 2. Metals correlation between (soil-root, root-shoot and shoot-grain) of Kainat.

Metal	Soil-Root	Root-Shoot	Shoot-Grain
Cd	1.00 **	0.993 **	0.954 *
Zn	0.898 *	0.997 **	0.896 *
Cu	0.972 **	0.984 **	0.965 **
Co	0.946 **	0.964 **	0.922 **
Fe	0.980	0.907 *	0.899 *
Mn	0.880 *	0.956 *	0.863
Ni	0.521	0.416	0.894 *

*, **: Correlation was significant at the 0.05 and 0.01 levels.

).

Again, a positive significant correlation was detected for Cd, Co, Zn and Cu in cases of soil-root, root-shoot, and shoot-grain. Against the present results, Satpathy et al. [60] found a positive significant correlation in soil-grains, in the case of Cd, Cu and Zn, except for Mn. A positive significant correlation was exhibited in root-shoot and shoot-grain for Fe metal while soil-root and root-shoot in the case of Mn. Positive and non-significantly correlated shoot-grain was observed for Mn, while in the case of Fe it is a soil-root correlation. Nickel exhibited a positive and non-significant correlation between soil-root and root-shoot and a positive significant correlation for shoot-grain. Similarly, Woldetsadik et al. [61] assessed during their study the strong positive significant correlation in the case of Ni and Co.

3.6. Bioaccumulation Factor

At Site-I, the BAF for Cu, Mn, Ni, and Zn was recorded to be larger than Cd, Fe, and Co. At Site-II, the BAF of Ni, Fe, and Cd was lesser than Cu, Mn, Zn, and Co. At Site-III, Fe, Zn, and Cu were greater than Ni, Co, Mn, and Cd while BAF at Site-IV was observed to be higher for Cu, Cd, Mn, and Fe than Ni, Co, and Zn. Finally, in the case of Site-V, the BAF for Cu, Zn and Fe were higher than Mn, Ni, Co, and Cd. Amongst all five sites, the maximum BAF was presented by Ni and Mn while Cd and Co showed the lowest BAF index value (

Table 3. Bioaccumulation and translocation factors for Kainat.

Site	Metal
	Cd	Zn	Cu	Co	Fe	Mn	Ni
Bioaccumulation factor
Site-I	0.4728	0.6806	1.5157	0.5607	0.6108	0.6108	0.6198
Site-II	0.2779	0.6286	1.6054	0.5725	0.4333	0.6311	0.5024
Site-III	0.1839	0.6354	1.4521	0.3234	0.6429	0.4150	0.3461
Site-IV	0.6077	0.4019	1.4364	0.4046	0.4806	0.5088	0.1989
Site-V	0.2571	0.5856	2.5656	0.3549	0.5074	0.3732	0.3632
Translocation factor
Site-I	0.7719	0.8128	0.9057	0.7959	0.9475	0.9130	0.8722
Site-II	0.5359	0.8584	0.9072	0.8792	0.9100	0.9179	0.8454
Site-III	0.9296	0.7529	0.9495	0.7204	0.8624	0.9602	0.6747
Site-IV	0.9145	0.9332	0.9221	0.8585	0.7919	0.8658	0.4807
Site-V	0.6164	0.7368	0.5099	0.7694	0.8371	0.8946	0.5655

). The BAF order at Site-I was Cu > Zn > Mn > Ni > Fe > Co > Cd, for Site-II was Cu > Mn > Zn > Co > Ni > Fe > Cd, Site-III was Cu > Fe > Zn > Mn > NI > Co > Cd, Site-IV was Cu > Cd > Mn > Fe > Co > Zn > Ni and in Site-V the observed BAF order was Cu > Zn > Fe > Mn > Ni > Co > Cd.

In the current work, the BAF for Co, Cu, Fe, Mn, and Ni was bigger than the ones recorded by Badawy et al. [62]. BAF levels observed for Cd and Zn in present results were lower than those presented in Singh et al. [63]. BAF of all investigated metals, except Cu, was below 1.00 in this study. Among all the sites, the higher BAF for Cu and Zn displayed that these metals were maximally absorbed in the rice grains from the soil [41].

3.7. Translocation Factor (TF)

Site-I and Site-II showed that the TF trend observed for Fe, Ni, Cu, and Mn was greater than Co, Cd and Zn, whereas, in the case of Site-III, Zn, Cd, and Ni was lesser against Mn, Cu, Fe and Co metals. TF trend in Site-IV presented higher concentrations for Mn, Cu, Zn, and Cd metals than Co, Ni, and Fe. Finally, in Site-V TF for Ni, Cu and Cd were lower compared to Co, Mn, Zn, and Fe. Amongst all the sites, maximum TF concentration was given by Fe and Mn, but Co and Cd gave their minimum concentration (Table 3).

The TF sequence studied in Site-I was Fe > Mn > Cu > Ni > Zn > Co > Cd.

The TF trend in Site-II was Mn > Fe > Cu > Co > Zn > Ni > Cd.

The TF in Site-III was Mn> Cd> Cu > Fe > Zn > Co > Ni.

For Site-IV, the TF ranking was Zn> Cu> Cd > Mn > Co > Fe > Ni.

Conversely, the TF trend within Site-V was Mn> Fe> Co> Zn > Cd > Ni > Cu.

TF concentrations recorded for Cd, Zn, Cu, and Fe were bigger, while Mn was lesser than that described in Kumar et al. [64]. Compared to Satpathy et al. [60], a significantly higher TF trend was observed for Zn and Cu, while Mn and Cd were lower in present results. TF values for Ni were higher and the least amount of Co was observed in this study compared to Emurotu et al. [65].

Amongst all sites, the maximum TF value of Fe and Mn revealed that the rice plants have accumulated Mn and Fe concentration from roots to shoots [66]. Minimum TF in the cases of cadmium and cobalt indicate that paddy roots act as barriers to these two metals’ absorption and contamination. The possible reason behind the fact was that the heavy metals under instant investigation had dissimilar properties and in this way, every metal has an explicit absorption, translocation, and accumulation ability [40].

3.8. Pollution Load Index (PLI)

The metal pollution difference level within sites was derived from PLI [67]. PLI pattern at Site-I and Site-II was Cd > Ni > Cu > Co > Mn > Fe > Zn. The sequences of PLI at Site-III was Cd > Ni > Co > Cu > Mn > Zn > Fe, Site-IV was Cd > Ni > Cu > Co > Mn > Zn > Fe and Site-V was Cd > Ni > Cu > Zn > Mn >Fe > Co, respectively. The pollution load index at all five sites for the case of cadmium was recorded as being higher, while that for Fe and Zn was lowest (

Table 4. Pollution load index and enrichment factor for metals of Kainat.

Site	Metal
	Cd	Zn	Cu	Co	Fe	Mn	Ni
Pollution load index
Site-I	7.8809	0.3277	0.8201	0.4845	0.4240	0.4808	1.50278
Site-II	8.5419	0.2821	0.6990	0.6047	0.3534	0.4377	1.3908
Site-III	9.2041	0.3497	0.9358	0.9767	0.2652	0.4588	1.0579
Site-IV	7.1823	0.3267	0.6958	0.5930	0.3177	0.4157	1.2773
Site-V	6.5017	0.4169	0.5748	0.2674	0.3350	0.3940	1.6068
Reference value	1.49 a	44.19 a	8.39 a	9.1 b	56.9 c	46.75 d	9. 06 a
Enrichment factor
Site-I	3.5222	0.3007	0.6358	2.4108	0.0971	0.0571	0.5999
Site-II	2.0707	0.2778	0.6735	2.9162	0.0772	0.0637	0.5984
Site-III	1.3703	0.2808	0.6092	5.1452	0.0718	0.0563	0.2597
Site-IV	4.5273	0.1776	0.6026	0.7453	0.0609	0.0428	0.1433
Site-V	1.9155	0.2588	1.0763	1.1881	0.0971	0.0502	0.5999

Sources: ^a Sing et al. (2010a), ^b Dutch Standards (2000), ^c Dosumu et al. (2005), ^d Singh et al. (2010b).

).

In this work, Ni, Zn, and Cu contamination was lowered in soils and Cd contaminations were higher than values by Singh et al. [54], which were Ni (9.06 mg/kg), Cu (8.39 mg/kg), Zn (44.19 mg/kg) and Cd (1.49 mg/kg), respectively. Fe contamination in soil was recorded less than 56.9 mg/kg. In the case of present Co and Mn concentrations, PLI was lower than values presented by Dosumu et al. [68] and Singh et al. [54], respectively.

The reason behind the decreased PLI in these selected study areas was the normal canal water irrigation practice, as there is no flow of industrial effluents on agricultural lands. The presented study obtains values of lower PLI for Zn, Cu, Co, Ni, Fe, and Mn when compared to Ahmad et al. [69].

3.9. Enrichment Factor

Tinker et al. [42] stated that EF is a metals binding capability in soil. The enrichment factor is associated with the availability of metals in soil and variances in uptake capability of metals from soil and plant species growth rate. Enrichment factors greater than 1 equate to a hyper-accumulation ability for metal absorption from the soil by the rice crop [55].

In the present study, at five different sites, the EF of Kainat was present and ranked as Co ˃ Cd ˃ Cu ˃ Ni ˃ Zn ˃ Mn ˃ Fe (Table 4).

Among five different sites, EF for examined metals in recent research had ranges as follows: Cd (1.3703–3.5222), Zn (0.1776–0.3007), Cu (0.6026–1.0763), Co (0.7453–5.1452), Mn (0.0428–0.0637), Ni (0.1433–0.5999) and Fe (0.06609–0.0971) mg/kg, respectively. The transfer of metals for Cd and Fe was superior and for Cu, Co Zn and Ni were lower than values reported by Khan et al. [70] findings.

3.10. Daily Intake of Metal

Liu et al. [71] considered that rice intake is a source of heavy metal interaction with human beings. Amongst all the selected sites, the maximum DIM value was observed for ferrous metals, while cobalt metal showed a minimum value for this index.

The DIM sequence found at Site-I was Fe > Mn > Zn > Cu > Ni > Co > Cd, Site-II was Mn > Cu > Fe > Zn > Ni > Co > Cd, Site-III was Cu > Zn > Fe > Mn > Ni > Co > Cd, Site-IV was Mn > Fe > Cu > Cd > Zn > Ni > Co and Site-V was Cu > Zn > Fe > Mn > Ni > Co > Cd (

Table 5. Daily intake of metal and health risk index of Kainat.

Site	Metal
	Cd	Zn	Cu	Co	Fe	Mn	Ni
Daily intake of metal
Site-I	0.0319	0.0567	0.0510	0.0375	0.0847	0.0801	0.0479
Site-II	0.0203	0.0451	0.0541	0.0316	0.0501	0.0743	0.0364
Site-III	0.0145	0.0565	0.0656	0.0086	0.0558	0.0512	0.0191
Site-IV	0.0374	0.0334	0.0482	0.0110	0.0491	0.0569	0.0132
Site-V	0.0143	0.0620	0.0711	0.0256	0.0556	0.0395	0.0304
Health risk index
Site-I	0.0214	0.0013	0.0071	0.8719	0.0015	0.0017	0.0053
Site-II	0.0137	0.0010	0.0064	0.7360	0.0009	0.0016	0.0040
Site-III	0.0097	0.0012	0.0078	0.1989	0.00098	0.0011	0.0021
Site-IV	0.0251	0.0008	0.0057	0.4643	0.00088	0.0012	0.0015
Site-V	0.0096	0.0014	0.0085	0.5964	0.00097	0.00084	0.0034
RfD * (mg/kg/day)	1 × 10−3	3 × 10−1	4 × 10−2	43 × 10−2	1 × 10−1	14 × 10−1	2 × 10−2

Source: * USEPA (2002).

).

The DIM findings of Cd (0.05 µg/kg/bw/day) in Sun et al. [72] was lower than presented results within this study. Similarly, DIM recorded for Cu was larger, while for Zn was lesser than those given in other studies (i.e., Ref. [56]). Whereas, a higher Ni and Mn (5.2 and 1.6 mg/kg/person/day respectively) intake was proposed by Balkhair et al. [73] than in the present investigation. Daily intake of Cu and Ni was found to be larger, while Zn and Mn were lesser to the recorded results of Singh et al. [52]. The current work cleared the DIM of Ni, Cu, Zn and Fe, which were found to be within the recommended oral reference doses of EPA [46].

3.11. Health Risk Index

HRI value was calculated to quantify the heavy metals risk assessment resulted in by consuming polluted food crops [45,46]. If any food crop specified the HRI value below 1.00, it should be safe for human consumption, while >1.00 is poisonous for public health [46]. The ascendancy sequence for HRI on Site-I was Co > Cd > Cu > Ni > Mn > Fe > Zn, Site-II was Co > Cd > Cu > Ni > Mn > Zn > Fe, Site-III was Co > Cd > Cu > Ni > Zn > Mn > Fe, Site-IV was Co > Cd > Cu > Ni > Mn > Zn > Fe and at Site-V was Co > Cd > Cu > Ni > Zn > Fe > Mn (Table 5).

The health risk index of metals such as Zn, Cu and Ni was lowered compared to Verma et al. [74]. Singh et al. [54], who reported higher values of HRI than the present findings. The HRI value of Mn described in this study was lower compared with the literature (i.e., Ref. [75]). The HRI value for Fe was less than the permitted reference value (1 × 10⁻¹ mg/kg/day) of EPA [51].

In the present analysis, it was also noted that HRI value of Mn (14 × 10⁻¹ mg/kg/day), Zn (3 × 10⁻¹ mg/kg/day) and Cu (4 × 10⁻² mg/kg/day) were lowered, while Cd (1 × 10⁻³ mg/kg/day) and Ni (2 × 10⁻² mg/kg/day) values were higher against their permitted EPA [46] findings. EPA [76] also suggested the reference value of cobalt metal to be 43 × 10⁻² mg/kg/day, which would seem to be lesser than found in the present investigation.

4. Conclusions

The current research demonstrated that transmission of heavy metals from soils considerably accumulated in grains. Rice grains were watered by water originating from a canal that has increased heavy metal contents due to the water’s accumulation of agri-chemical and industrial wastes. This water was tainted by soils and eventually, this was absorbed by the rice grains, posing a threat to human health.

Comparing grain and soil in respect to the absorption of metals, greater levels of heavy metals were identified to remain in the soil. The level of cadmium was above the allowable range issued by FAO/WHO, while the pollution load index of the canal water irrigated sites was very high and there is a need of attention for environmental cleanup.