A Comparative Study of Health Risks of Fe and Ni in the Vegetables Collected from Selected Farming Areas of Peninsular Malaysia

Aziran Yaacob1, Chee Kong Yap1*, Rosimah Nulit1, Hishamuddin Omar1, Salman Abdo Al-Shami2 and Alireza Riyahi Bakhtiari3

1Department of Biology, Universiti Putra Malaysia, Malaysia

2Department of Biology, University of Tabuk, Saudi Arabia

3Department of Environmental Sciences, Tarbiat Modares University, Iran

Corresponding Author:
Chee Kong Yap
Department of Biology
Faculty of Science, Universiti Putra Malaysia
Malaysia
Tel: 603-89466616
Fax: 603-86567454
E-mail: [email protected]

Received date: March 27, 2018; Accepted date: April 17, 2018; Published date: April 24, 2018

Citation: Yaacob A, Yap CK, Nulit R, Omar H, Abdo Al-Shami SA, et al. (2018) A Comparative Study of Health Risks of Fe and Ni in the Vegetables Collected from Selected Farming Areas of Peninsular Malaysia. J Aquat Pollut Toxicol Vol.2 No.1:21

 
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Abstract

This study investigated the concentrations of Ni and Fe in 18 vegetables (12 fruit types and 6 leafy types) and their habitat topsoils collected from three farming sites in Peninsular Malaysia. The levels of Ni and Fe are all significantly (P<0.05) higher in the leafy vegetables than those in the fruit vegetables. It is found that the Ni levels in the vegetables are highly correlated with the three geochemical and non-resistant fractions of the habitat topsoils. This indicated that Ni geochemical fractions in the habitat topsoils are considered readily and potentially bioavailable to the vegetables. The Fe levels in the vegetables are highly correlated with the ‘acid-reducible’ fraction of the habitat topsoils, indicating the Fe transfer of this geochemical fraction is likely to occur to the vegetables. The positive relationships indicated the potential of edible vegetables as good biomonitors of Ni pollution in the habitat topsoils. For the health risk assessment, all the target hazard quotient values for Ni and Fe in the 18 vegetables investigated in both adult and children are all below 1.00. This indicated that there was no non-carcinogenic risk of Ni and Fe to the consumers for both adults and children.

Keywords

Ni and Fe; Vegetables; Target hazard quotient; Biomonitor

Introduction

Nickel (Ni) and iron (Fe) are essential for healthy plant life [1,2]. As a result, it is found naturally in most vegetables. Studies on Ni and Fe levels in the vegetables can are reported in the literature such as a study on Fe levels in the vegetables from East Africa and Ni levels in greenhouse vegetables [3,4].

Contaminated vegetables considered as one of the most important aspects of food quality assurance [5]. Since every year, millions of humans over the world are exposed to the contaminated vegetables by heavy metals [6]. Consequently, many researchers investigated the heavy metal levels in the daily consumable vegetables for its importance and significance from public health point of view.

The transfer of heavy metals from the vegetables to the human body can cause various diseases. This public concern can be justified based on the numerous papers published from developing countries such as Bangladesh, China, India, South Africa and Nigeria [2,7-10]. This indicated that the human health risks of metals in the vegetables have been widely reported in the literature [6,11,12]. It is important to investigate the soil pollution since the soil is the environmental matrix for the healthy growth of the vegetables. It is, therefore, studies on the relationships of metal levels between vegetables and their habitat soils are usually focused upon based on many reported studies such as from Chongqing, Southwest of China, Bangladesh and greenhouse vegetable cultivation from Kunming City (China) [13-15].

The objectives of this study are to: 1) assess the concentrations of Ni and Fe in vegetables at three farming areas in Peninsular Malaysia, 2) assess the human health risks of Ni and Fe in the fruit types and leafy types of vegetables and 3) to assess the potential of vegetables as good biomonitors of Ni and Fe by studying the relationships of both metals between the vegetables and geochemical fractions of the habitat top soils.

Materials and Methods

Study area and sampling

Eighteen species of vegetables were collected from Kg Ara Kuda (Ara), Kuala Ketil (Ketil) and Kg Sitiawan Manjung (Manjung) of Peninsular Malaysia. Manjung is an agricultural and residential area. Ara is also an agricultural area and is surrounded by palm oil plantation. Ketil is located in the vicinity of residential area and roadside. The main method of irrigation of the three vegetable farming sites is domestic wastewater from the nearby streams and tube well. All sampling of vegetables and their habitat topsoils were conducted between September 2016 and January 2017 (Figure 1).

Figure 1: Sampling map of vegetables from three farming areas in the northern part of Peninsular Malaysia (A=Ketil, B=Ara and C=Manjung).

About 3-15 individuals (depend on their size) of each vegetable species were randomly collected from each sampling site. Habitat topsoils (0-10 cm) were also collected from where the vegetables grew. The vegetables were harvested by hand carefully while the topsoils were collected by using a soil auger. All the collected samples were then stored in clean polythene bags.

In this study, the 18 vegetables with 12 fruit types and 8 leafy types were investigated. The morphology and classification of the vegetables from selected vegetables were identified according to Chin and Yap and Prohens and Nuez (Table 1) [16-18].

No. Site Sampling date Vegetable Edible parts Site description/ Source of irrigation
1 Manjung 26-Oct-16 Allium tuborosum Leave Agriculture and residential area/Domestic waste water
2 Ara 29-Sep-16 Amaranthus tricolor Leave Agriculture area surrounded by palm oil plantation/Tube well and stream
3 Ara 29-Sep-16 Amaranthus viridis Leave Road side of main road Penanti to Tasek Gelugor/Tube well and stream
4 Manjung 26-Oct-16 Brassica rapa Leave Road side and residential area/ Domestic waste water
5 Manjung 9-Nov-16 Ipomoea reptans Leave Road side, less than 1 km from coastal region/ Tube well and stream
6 Manjung 9-Nov-16 Lactuca sativa Leave Agriculture and residential area/ Domestic waste water
7 Ara 12-Oct-16 Abelmoschus esculentus Fruit Palm oil plantation, main road/ Tube well and stream
8 Ara 20-Oct-16 Benincasa hispida Fruit Main road Penanti to Tasek Gelugor/Tube well and stream
9 Ara 20-Oct-16 Capsicum annum Fruit Road side and surrounded by palm oil plantation/Tube well and stream
10 Ara 12-Oct-16 Cucumis sativus Fruit Main road Penanti to Tasek Gelugor/Tube well and stream
11 Ketil 11-Jan-17 Cucurbita moschata Fruit Residential area/Nearest stream
12 Ketil 21-Dec-16 Lagenaria siceraria Fruit Residential area/Nearest stream
13 Ketil 21-Dec-16 Luffa acutangula Fruit Road side of main road Baling to Petani River/Nearest stream
14 Ara 12-Oct-16 Momordica charantia Fruit Agriculture area surrounded by palm oil plantation/Tube well and stream
15 Ketil 8-Dec-16 Momordica charantia L. Fruit Private farm about 6 acres near residential area/Tube well and stream
16 Manjung 17-Nov-16 Solanum melongena Fruit Fisherman village/Domestic waste water and stream
17 Ketil 8-Dec-16 Tricosanthes celebica Fruit Residential area/Nearest stream
18 Ketil 8-Dec-16 Vigna sinesis Fruit Road side, in between Baling to Petani River/Nearest stream

Table 1: Description for sampling site of 18 vegetables collected from Kg Ara Kuda (Ara), Kuala Ketil (Ketil) and Kg Sitiawan Manjung (Manjung) of Peninsular Malaysia.

Preparation of vegetables and top soil samples

The vegetable samples were sorted in accordance with to their types of species. All samples were brought to the laboratory for analyses. The collected samples were washed with distilled water to remove soil particles. Then, the samples were cut into small pieces using a clean knife. They were dried in an oven at 60°C for 72 h until constant dry weights. After drying, the vegetable samples were grinded into a fine powder using a commercial blender and stored in polyethylene bags, before used for acid digestion.

For the topsoil samples, the collected samples were dried in an oven at 100°C for 72 h until constant dry weights. Later, the dried soils were grinded into a fine powder using a mortar and pestle and they were sieved under 63 μm mesh size sieve. For the geochemical fractionations, triplicates of the topsoils were fractionated into three fractions namely, first fraction as ‘easily, freely, leachable and exchangeable’ (F1), second fraction as ‘acid-reducible’ (F2) and third fraction as ‘oxidisable-organic’ (F3). The summation of F1, F2 and F3 will form the non-resistant (NR) fraction. The geochemical fraction analysis on the topsoils was based on Badri and Aston [19].

Determination of Ni and Fe

All samples stored in acid-washed pill boxes were analyzed by using an atomic absorption spectrophotometer (AAS) model Thermo Scientific iCE 3000 series for Ni and Fe at the Faculty of Science of Universiti Putra Malaysia. Auto zero by using blank was conducted for calibration of the instrument. Standard solutions of Ni and Fe were prepared from 1000 ppm stock solution of each metal provided by Sigma-Aldrich for both metals and the data obtained from the AAS were presented in mg/kg dry weight basis.

For quality assurance and quality control, all the glass wares used in this study were acid-washed to avoid external contamination. Two certified reference materials (CRM) were used to check for the analytical procedures and accuracy of the method used. The CRM for Ni and Fe included were NSC DC 73319 for soil and NIST 1547 for Peach Leaf. Based on the soil CRM, the recovery for Ni was 131% but it was not available for Fe. The Peach Leaf CRM for Fe and Ni were 97 and 117.2%, respectively (Table 2).

  NSC DC 73319 (Soil) Standard Reference Materials for Peach Leaves NIST 1547
Certified value Measured value Recovery (%) Certified value Measured value Recovery (%)
Fe NA 14585 - 219.8 211 97.0
Ni 20.4 ± 1.8 26.68 ± 0.4 130.76 0.689 0.81 117

Table 2: Comparisons of metal concentrations (mg/kg dry weight) between certified and measured values.
The certified values were based on Certified Reference Materials for Soils (NSC DC 73319) and Standard Reference Materials for Peach Leaves (NIST 1547)

Determination of water content and conversion factor

Water content in the samples was calculated to determine the amount of moisture trapped in the samples until get the constant weight. The percentage of water content (WC) was calculated as below:

WC=(wet weight (g) ‒ dry weight (g)) × 100%/wet weight (g)

The means values of conversion factor (CF) of the edible parts of all vegetables are presented in Table 3.

No. Vegetables CF
1. Abelmoschus esculentus 0.095
2. Allium tuborosum 0.084
3. Amaranthus tricolor 0.101
4. Amaranthus viridis 0.080
5. Benincasa hispida 0.052
6. Brassica rapa 0.099
7. Capsicum annum 0.091
8. Cucumis sativus 0.043
9. Cucurbita moschata 0.160
10. Ipomoea reptans 0.100
11. Lactuca sativa 0.068
12. Lagenaria siceria 0.056
13. Luffa acutangular 0.054
14. Momordica charantia 0.061
15. Momordica charantia L 0.046
16. Solanum melongena 0.080
17. Tricosanthes celebica 0.052
18. Vigna sinensis 0.094

Table 3: Conversion factor (CF) of the edible parts of 18 vegetables from three farming sites in Peninsular Malaysia.

Data treatment

For the human health risk assessment, the present metal concentrations in dry weight (dw) basis were converted into wet weight basis because consumption (or cooking) of the vegetables is assumed to be in wet weight (ww). Therefore, the present concentrations (mg/kg dry weight) of Fe and Ni were converted to wet weight basis by using respective conversion factor for each vegetable, as shown in Table 3.

The estimated daily intake (EDI) value was calculated using the following formula:

EDI=(Mc × CR)/BW

Where, Mc=The metal concentration in vegetables (mg/kg wet weight); CR=The consumption rate of vegetables (345 g/day for adults and 232 g/day for children) and average body weight (55.90 kg for adults and 32.70 kg for children), respectively [5]. The present study is a preliminary study from Malaysia. The consumption rate of vegetables for Malaysian is not clearly available in the literature. So, we applied that from an Asian country like China for the present study [5].

In this study, a non-cancer risk assessment method is based on the use of target hazard quotient (THQ), a ratio between the estimated dose of contaminant and the reference dose. The THQ value below 1.0 indicates there will not be any non-carcinogenic risk of metal investigated. The THQ determined with the formula described by USEPA [20]:

THQ=EDI/RfD

Where, EDI=Estimated daily intake calculated previosuly; RfD=The oral reference dose.

The RfD values (μg/kg/day) used in this study were: Ni: 20.0 and Fe: 700, provided by the USEPA's regional screening level [21].

The transfer factor (TF) can be used to evaluate the potential capability of crops to transfer metals from soil to edible parts. It is defined as the ratio of the metal concentration in the edible part of crop to metal concentration in the habitat soils [14,22]. This factor represents the potential capability of heavy metals’ transmission from soil to the edible parts of vegetable [23,24]. The TF was calculated based on dry weight, as follows:

TF=Cvegetable/Csoil

Where, Cvegetable=The metal concentration (mg/kg dry weight) in the vegetable; Csoil=The metal concentration (mg/kg dry weight) in the geochemical fractions namely F1, F2, F3 and NR in the habitat top soils.

Statistical analysis

Statistical analysis for metal concentration in different edible parts of vegetables and soil were calculated by using SPSS Statistics 22. Correlation analysis of metals between the vegetables and their habitat top soils using Spearman’s rank was applied, because of N<30. The graphical relationships of metals between the leafy types and fruit types of vegetables were done by using Kaleidagraph version 3.08. The rationale of using F1, F2 and F3 for the correlation of metals with vegetables was due to the fact these three geochemical fractions are mostly related to anthropogenic sources [19]. Therefore, it is more relevant from eco-toxicological point of view to correlate with the metal levels in the vegetables rather than to correlate with the total concentrations of metals in the top soils [25]. Comparison between two samples was conducted by using t-test in SPSS Statistics 22.

Results and Discussion

Concentrations of Ni and Fe

The Ni concentrations (mg/kg dw) in the fruit vegetables range from 0.18 to 2.32 (mean: 1.31) while 1.22 to 4.85 (mean: 2.44) for the leafy vegetables. The Fe concentrations (mg/kg dw) in the fruit vegetables range from 89.8 to 155 (mean: 117) while 175 to 306 (mean: 213) for the leafy vegetables. The levels of Ni and Fe are all significantly (P<0.05) higher in the leafy vegetables than those in the fruit vegetables (Tables 4-7).

Fruit vegetables Ni NiF1 NiF2 NiF3 NiNR Ni/F1 Ni/F2 Ni/F3 Ni/NR
Momordica charantia 2.17 0.15 1.62 2.54 4.31 14.5 1.34 0.85 0.50
Abelmoschus esculentus 1.45 0.14 1.52 2.40 4.06 10.4 0.95 0.60 0.36
Cucumis sativus 1.40 0.13 1.55 2.26 3.94 10.8 0.90 0.62 0.36
Benincasa hispida 1.98 0.15 1.29 2.14 3.58 13.2 1.53 0.93 0.55
Capsicum annum 1.02 0.12 0.99 1.40 2.47 8.50 1.03 0.73 0.41
Solanum melongena 2.32 0.17 1.44 2.47 4.08 13.7 1.61 0.94 0.57
Momordica charantia L. 0.18 0.08 0.19 0.37 0.57 2.25 0.95 0.49 0.32
Vigna sinesis 0.92 0.09 0.47 0.94 1.42 10.2 1.96 0.98 0.65
Lagenaria siceraria 1.12 0.06 0.46 1.07 1.59 18.7 2.43 1.05 0.70
Luffa acutangula 0.68 0.12 0.26 0.72 0.99 5.67 2.62 0.94 0.69
Tricosanthes celebica 1.62 0.09 0.71 1.74 2.54 18.0 2.28 0.93 0.64
Cucurbita moschata 0.87 0.02 0.32 0.38 0.72 43.5 2.72 2.29 1.21
Minimum 0.18 0.02 0.19 0.37 0.57 2.25 0.90 0.49 0.32
Maximum 2.32 0.17 1.62 2.54 4.31 43.5 2.72 2.29 1.21
Mean (12) 1.31 0.11 0.90 1.54 2.52 14.1 1.69 0.95 0.58
Standard deviation 0.64 0.04 0.56 0.83 1.43 10.4 0.69 0.46 0.24
Standard error 0.18 0.01 0.16 0.24 0.41 3.00 0.20 0.13 0.07

Table 4: The concentration (mean ± SD, mg/kg dry weight) of Ni in the fruit vegetables, geochemical fractions of the habitat top soils and their transfer factors (Ni/F1, Ni/F3, Ni/F3 and Ni/NR) collected from three farming sites in Peninsular Malaysia.

Leafy vegetables Ni NiF1 NiF2 NiF3 NiNR Ni/F1 Ni/F2 Ni/F3 Ni/NR
Amaranthus viridis 3.93 0.19 1.84 3.98 6.01 20.7 2.14 0.99 0.65
Amaranthus tricolor 4.85 0.19 2.69 5.17 8.05 25.5 1.80 0.94 0.60
Lactuca sativa 1.22 0.15 1.43 2.21 3.79 8.13 0.85 0.55 0.32
Ipomoea reptans 1.71 0.13 1.88 1.64 3.65 13.2 0.91 1.04 0.47
Brassica rapa 1.41 0.05 0.96 0.78 1.79 28.2 1.47 1.81 0.79
Allium tuborosum 1.50 0.09 0.75 1.60 2.44 16.7 2.00 0.94 0.61
Minimum 1.22 0.05 0.75 0.78 1.79 8.13 0.85 0.55 0.32
Maximum 4.85 0.19 2.69 5.17 8.05 28.2 2.14 1.81 0.79
Mean (6) 2.44 0.13 1.59 2.56 4.29 18.7 1.53 1.05 0.57
Standard deviation 1.55 0.06 0.70 1.67 2.34 7.58 0.55 0.41 0.16
Standard error 0.63 0.02 0.29 0.68 0.96 3.10 0.22 0.17 0.07

Table 5: The concentration (mean ± SD, mg/kg dry weight) of Ni in the leafy vegetables, geochemical fractions of the habitat top soils and their transfer factors (Ni/F1, Ni/F3, Ni/F3 and Ni/NR) collected from three farming sites in Peninsular Malaysia.

Fruit vegetables Fe FeF1 FeF2 FeF3 FeNR Fe/F1 Fe/F2 Fe/F3 Fe/NR
Momordica charantia 127 4.55 200 1444 1649 27.9 0.63 0.09 0.08
Abelmoschus esculentus 123 3.86 183 1388 1576 31.8 0.67 0.09 0.08
Cucumis sativus 109 3.60 159 1310 1473 30.3 0.69 0.08 0.07
Benincasa hispida 115 5.14 166 2354 2525 22.3 0.69 0.05 0.05
Capsicum annum 110 1.29 25.2 651 678 85.6 4.37 0.17 0.16
Solanum melongena 120 3.65 183 1382 1569 32.8 0.65 0.09 0.08
Momordica charantia L. 112 2.16 162 1321 1485 51.7 0.69 0.08 0.08
Vigna sinesis 155 1.06 275 1597 1873 146 0.56 0.10 0.08
Lagenaria siceraria 105 2.41 131 1299 1432 43.6 0.80 0.08 0.07
Luffa acutangula 125 3.98 202 2392 2598 31.5 0.62 0.05 0.05
Tricosanthes celebica 108 4.91 1489 1311 1465 22.0 0.73 0.08 0.07
Cucurbita moschata 89.8 0.62 86.6 2182 2269 145 1.04 0.04 0.04
Minimum 89.8 0.62 25.2 651 678 22.0 0.56 0.04 0.04
Maximum 155 5.14 275 2392 2598 146 4.37 0.17 0.16
Mean (12) 117 3.10 160 1553 1716 55.9 1.01 0.08 0.08
Standard deviation 15.8 1.55 62.0 510 534 45.3 1.06 0.03 0.03
Standard error 4.56 0.45 17.9 147 154 13.1 0.31 0.01 0.01

Table 6: The concentration (mean ± SD, mg/kg dry weight) of Fe in the fruit vegetables, geochemical fractions of the habitat top soils and their transfer factors (Fe/F1, Fe/F3, Fe/F3 and Fe/NR) collected from three farming sites in Peninsular Malaysia.

Leafy vegetables Fe FeF1 FeF2 FeF3 FeNR Fe/F1 Fe/F2 Fe/F3 Fe/NR
Amaranthus viridis 179 4.57 391 5827 6223 39.1 0.46 0.03 0.03
Amaranthus tricolor 199 5.45 344 4945 5294 36.5 0.58 0.04 0.04
Lactuca sativa 306 1.22 920 3250 4171 251 0.33 0.09 0.07
Ipomoea reptans 232 5.53 344 2652 3002 41.9 0.67 0.09 0.08
Brassica rapa 187 4.95 372 3795 4172 37.8 0.50 0.05 0.04
Allium tuborosum 175 0.32 346 2907 3254 548 0.51 0.06 0.05
Minimum 175 0.32 344 2652 3002 36.5 0.33 0.03 0.03
Maximum 306 5.53 920 5827 6223 548 0.67 0.09 0.08
Mean (6) 213 3.67 453 3896 4353 159 0.51 0.06 0.05
Standard deviation 49.9 2.29 229 1247 1223 208 0.11 0.03 0.02
Standard error 20.4 0.94 93.7 509 499 85.1 0.05 0.01 0.01

Table 7: The concentration (mean ± SD, mg/kg dry weight) of Fe in the leafy vegetables, geochemical fractions of the habitat top soils and their transfer factors (Fe/F1, Fe/F3, Fe/F3 and Fe/NR) collected from three farming sites in Peninsular Malaysia.

Based on the cited data from Li et al. [22], the Ni concentrations (mg/kg ww) in the fruit vegetables range from 0.054 to 0.536 (mean: 0.184). For the leafy vegetables, the levels of Ni range from 0.110 to 0.322 (mean: 0.195). Therefore, Li et al. [22] findings supported the present results on the higher levels of Ni in the leafy vegetables than those in the fruit vegetables. The higher levels of heavy metals in the leafy vegetables agreed with previous findings in the literature [4,24,26]. This indicated that leafy vegetables have higher transportation rates than other vegetable types [27]. This might be due to the more barriers preventing heavy metals’ transmission from soil to fruits than those to leaves [28] (Tables 8 and 9).

Fruit vegetables Scientific name Ni
Eggplant Solanum melongena 0.137
Tomato Lycopersicon esculentum 0.054
Cucumber Cucumis sativus L. 0.074
Suakwa towel gourd Luffa cylindrical (Linn.) Roem. 0.077
Bitter gourd Momordica charantia 0.224
Green cowpea Vigna unguiculata (Linn.) 0.536
  Minimum 0.054
  Maximum 0.536
  Mean 0.184
  Standard deviation 0.183
  Standard error 0.075

Table 8: The mean concentrations (mg/kg wet weight) of fruit vegetables in the vegetables grown on reclaimed tidal flat soils in the Pearl River Estuary (China). Data cited from Li et al. [22].

Leafy vegetables Scientific name Ni
Cabbage Brasssica oleracea L. var capitata L. 0.201
Chinese lactuca Lactuca sativa L. var. asparagina 0.322
Pakchoi Brassica chinensis 0.110
Chinese flowering cabbage Brassica rapa chinensis 0.256
Romaine lettuce Lactuca sativa L. var. longifolia 0.197
Edible amaranth Amaranthus mangostanus L. 0.167
Water spinach Ipomaea aquatica Forssk 0.112
Leaf mustard Brassica juncea Coss 0.196
  Minimum 0.110
  Maximum 0.322
  Mean 0.195
  Standard deviation 0.070
  Standard error 0.025

Table 9: The mean concentrations (mg/kg ww) of leafy vegetables grown on reclaimed tidal flat soils in the Pearl River Estuary (China). Data cited from Li et al. [22].

Based on Tables 4 and 5, the Ni concentrations (mg/kg dw) in the F1, F2, F3 and NR of the habitat top soils range from 0.02-0.19, 0.19-2.69, 0.37-5.17 and 0.57-8.05, respectively. Based on Tables 6 and 7, the Fe concentrations (mg/kg dw) in the F1, F2, F3 and NR of the habitat top soils range from 0.32-5.53, 25.2-920, 651- 5827 and 678-6223, respectively.

Transfer factor

Between the fruit types and leafy types of vegetables, the levels of Ni and Fe are significantly (P<0.05) higher in the leafy vegetables than those in the fruit vegetables. The TF values of leafy vegetables in Ni and Fe were higher than those in the fruit vegetables, based on F1 of the habitat top soils. However, this pattern is not well indicated based on F2, F3 and NR geochemical fractions (Tables 4-7).

Based on the Ni TF for the fruit vegetables, they range from 2.25- 43.5 for Ni/F1, 0.90-2.72 for Ni/F2, 0.49-2.29 for Ni/F3 and 0.32- 1.21 for Ni/NR. Based on the Ni TF for the leafy vegetables, they range from 8.13-28.2 for Ni/F1, 0.85-2.14 for Ni/F2, 0.55-1.81 for Ni/F3 and 0.32-0.79 for Ni/NR (Tables 4 and 5).

Based on the Fe TF for the fruit vegetables, they range from 22.0- 146 for Fe/F1, 0.56-4.37 for Fe/F2, 0.04-0.17 for Fe/F3 and 0.04- 0.16 for Fe/NR. Based on the Fe TF for the leafy vegetables, they range from 36.5-548 for Fe/F1, 0.33-0.67 for Fe/F2, 0.03-0.09 for Fe/F3 and 0.03-0.08 for Fe/NR. The present study indicated that TF values varied greatly with the vegetable species and this agreed with those reported by Cui et al. [29] and Qureshi et al. [30] (Tables 6 and 7).

From Tables 4 to 7, the mean values of TF for Ni/F1 and Fe/F1 in leafy vegetables are higher than those in the fruit vegetables. This implies that Cd and Pb can be easily accumulated in the leafy vegetables from the F1 fraction of the top soils. The higher Fe TF values than those for Ni were consistent with the findings of Qureshi et al. [30] and Liu et al. [31]. These results also demonstrate that Fe is easily transferable to leafy vegetables, while transfer of Ni from soils into the edible parts of vegetables faced much more resistance [6]. It is generally argued that Fe has more capacity to make strong binding with enzymes as compared to Ni when both metals simultaneously enter into the plant cells because Ni and Fe affect nucleic acid metabolism in the same manner [32]. Consequently, Fe is easier than Ni to transfer from soil to the edible part of crops. In fruit vegetables, TF values were lower in tomatoes and radish which might be due to the observed differences in soil properties. The variations in TF of metals in different vegetables are also related to each vegetable's absorption capability, soil nutrient management and soil properties [33]. Therefore, by consuming selective vegetables with low levels of Ni and Fe accumulation and TF values, the risk of human exposure to the contamination of both metals can be significantly reduced.

Relationships of metals between vegetables and geochemical fractions of the top soils

The relationships of Ni between the vegetables and their habitat top soils (four geochemical fractions: F1, F2, F3 and NR), are presented in Figure 2. It is found that the Ni levels in the vegetables are highly correlated with the F1 (R=0.70), F2 (R=0.83), F3 (R=0.94) and NR (R=0.92) fractions of the habitat top soils. This indicated that Ni geochemical fractions (F1, F2, F3 and NR) in the habitat top soils are considered readily and potentially bioavailable to the vegetables [31]. Therefore, continuous root uptake of Ni from the habitat top soils to the vegetables can be expected because of their significant (P<0.05) correlations of Ni between the vegetables and habitat top soils (Figure 2).

Figure 2: Relationships of Ni between the vegetables and their habitat topsoils (four geochemical
fractions: F1, F2, F3 and NR).
*F1=Easily, freely, leachable or exchangeable fraction; F2=Acid-reducible fraction;
F3=Oxidisable-organic fraction
NR: Non-Resistant Fraction (summation of F1, F2 and F3 fractions)

Fan et al. [4] studied the correlation of heavy metal levels between the greenhouse vegetables and soil general properties (including the geochemical fractions). They found that the concentrations of Ni in greenhouse leafy vegetables were highly (R=0.85) correlated with concentrations of Ni bound to the geochemical fraction of organic matter and sulfides in greenhouse soil. This showed that Ni in vegetables could be predicted by Ni concentrations in the organic matter and sulfides of the soils. Therefore, present study indicated that Ni bioaccumulation in the vegetables can be indicated by the Ni levels in the geochemical fractions of EFLE, ‘acid-reducible’, ‘oxidisable-organic’ and non-resistant of the habitat top soils.

The relationships of Fe between the vegetables and their habitat top soils (four geochemical fractions: F1, F2, F3 and NR), are presented in Figure 3. It is found that the Fe levels in the vegetables are highly correlated particularly with the F2 only (R=0.94), followed by NR (R=0.67) and F3 (0.60). Obviously, there is no relationship of Fe between the vegetables and F1. Liu et al. [34] also found that the metal concentrations in vegetables and corresponding soils were poorly correlated (Figure 3).

Figure 3: Relationships of Fe between the vegetables and their habitat topsoils (four geochemical fractions: F1, F2, F3 and NR).
*F1=Easily, freely, leachable or exchangeable fraction; F2=Acid-reducible fraction; F3=Oxidisable-organic fraction NR: Non-Resistant Fraction (summation of F1, F2 and F3 fractions)

Besides the root uptake of Ni and Fe to the leaves of vegetables, atmospheric deposition could influence the bioavailability and contamination of both metals in local vegetables [14]. The difference of soil bioavailability between the Ni and Fe to the vegetables was generally dependent on the particular metal and vegetable species [35].

As shown in Figures 2 and 3, the correlations of Ni and Fe between vegetables and geochemical fractions of the habitat topsoils varied greatly for different vegetable types. This agrees to those reported by Fan et al. [4] and Yang et al. [36]. This was probably due to different absorption mechanism of metals in different types of vegetables [37]. There was no significantly correlation of Fe levels between the vegetables and the F1 fraction of the habitat top soils. It was probably due to other factors such as cation exchange capacity, which could have influenced the Fe availability in the habitat top soils.

Health risk assessments

The values of EDI and THQ of Ni and Fe in the 18 vegetables for adults and children from the present study are presented in Table 10. Overall statistical values of EDI and THQ values for adults and children from the present study are given in Table 11. The EDI values of Ni for adults and children range from 0.08-2.45 and 0.10-2.81, respectively. The EDI values of Fe for adults and children range from 35.3-143 and 40.6-165, respectively. The THQ values of Ni for adults and children range from 0.004-0.120 and 0.038-0.140, respectively. The THQ values of Fe for adults and children range from 0.05-0.20 and 0.06-0.24, respectively. Therefore, all the THQ values in the 18 vegetables for Ni and Fe in both adult and children are all below 1.0. This indicates there are no non-carcinogenic risks of Ni and Fe via the consumption of the 18 vegetables from the present study (Tables 10 and 11).

Vegetables   EDI THQ
Ni Fe Ni Fe
Momordica charantia (n=6) Adults 0.95 55.33 0.05 0.08
Children 1.09 63.60 0.05 0.09
Abelmoschus esculentus (n=12) Adults 0.99 83.46 0.05 0.12
Children 1.13 95.94 0.06 0.14
Cucumis sativus (n=7) Adults 0.52 40.42 0.03 0.06
Children 0.60 46.47 0.14 0.07
Amaranthus viridis (n=16) Adults 2.45 111.21 0.12 0.16
Children 2.81 127.84 0.14 0.18
Amaranthus tricolor (n=16) Adults 2.38 97.45 0.12 0.14
Children 2.73 112.02 0.05 0.16
Benincasa hispida (n=6) Adults 0.89 51.22 0.04 0.07
Children 1.02 58.88 0.03 0.08
Capsicum annum (n=12) Adults 0.57 62.04 0.03 0.09
Children 0.66 71.31 0.03 0.10
Lactuca sativa (n=6) Adults 0.51 127.62 0.03 0.18
Children 0.59 146.71 0.06 0.21
Ipomoea reptans (n=18) Adults 1.06 143.20 0.05 0.20
Children 1.22 164.62 0.06 0.24
Solanum melongena (n=6) Adults 1.09 56.14 0.05 0.08
Children 1.25 64.53 0.05 0.09
Brassica rapa (n=8) Adults 0.93 123.10 0.05 0.18
Children 1.07 141.51 0.04 0.20
Allium tuborosum (n=22) Adults 0.77 89.78 0.04 0.13
Children 0.88 103.20 0.04 0.15
Momordica charantia L. (n=6) Adults 0.08 51.57 0.004 0.07
Children 0.10 59.28 0.02 0.08
Vigna sinesis (n=16) Adults 0.32 54.40 0.02 0.08
Children 0.37 62.54 0.04 0.09
Lagenaria siceraria (n=6) Adults 0.72 67.23 0.04 0.10
Children 0.82 77.29 0.01 0.11
Luffa acutangula (n=6) Adults 0.22 41.47 0.01 0.06
Children 0.26 47.68 0.03 0.07
Tricosanthes celebica (n=6) Adults 0.53 35.28 0.03 0.05
Children 0.61 40.55 0.03 0.06
Cucurbita moschata (n=5) Adults 0.45 45.94 0.02 0.07
Children 0.51 52.82 0.03 0.08

Table 10: Estimated daily intake (EDI) and target hazard quotient (THQ) values of Ni and Fe in the 18 vegetables for adults and children from the present study.

  EDI THQ
Adults Ni Fe Ni Fe
Minimum 0.08 35.28 0.004 0.05
Maximum 2.45 143.20 0.120 0.20
Mean 0.86 74.27 0.043 0.11
Standard deviation 0.64 33.50 0.031 0.05
Standard error 0.15 7.90 0.007 0.01
Children Ni Fe Ni Fe
Minimum 0.10 40.55 0.038 0.06
Maximum 2.81 164.62 0.140 0.24
Mean 0.98 85.38 0.048 0.12
Standard deviation 0.73 38.51 0.037 0.06
Standard error 0.17 9.08 0.009 0.01

Table 11: Overall statistics of estimated daily intake (EDI) and target hazard quotient (THQ) values of Ni and Fe for adults and children from the present study.

Based on a study by Qureshi et al. [30], the highest Fe contribution to the consumer intake came from lettuce, which was 10 times higher than all other vegetables. From Tables 6 and 7, the highest level of Fe was also found in lettuce (Lactuca sativa), indicating its capacity to accumulate Fe. However, the Fe THQ for L. sativa was below 1.0. Therefore, the consumption of lettuce will not induce any adverse health (non-carcinogenic) effects arising largely from Fe exposure.

Conclusion

From the present study, the levels of Ni and Fe are all lower in the fruit vegetables than those in the leafy vegetables. It is found that the Ni levels in the vegetables are highly correlated with the three geochemical and NR fractions of the habitat top soils. The Fe levels in the vegetables are highly correlated with the ‘acid-reducible’ fraction of the habitat top soils. The positive relationships indicated the potential of edible vegetables as good biomonitors of Ni pollution in the habitat top soils. For the health risk assessment, al the THQ values for Ni and Fe in the 18 vegetables investigated in both adult and children are all below 1.00. This indicated that there was no non-carcinogenic risk of Ni and Fe to the consumers for both adults and children. Nevertheless, regular monitoring and management of the vegetable farms is still needed.

Acknowledgement

The authors wish to acknowledge the partial financial support provided through the Fundamental Research Grant Scheme (FRGS), [Vote no.: 5524953], by Ministry of Higher Education, Malaysia.

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