Species selection
Malabar spinach (B. alba) is a fast-growing, soft-stemmed vine is a very popular vegetable in Bangladesh (Table 1) which was selected for the experiment.
Table 1 Scientific classification
Experimental design
The pot experiment was laid out with five treatments including control with three replications (Table 2). During the investigation, morphological parameters (average length of stems, leaf area and wet weight) of plants were noted in with the help of measuring scale and digital balance for two times, i.e., 7 and 40 days of emergence. Two randomly selected plants were used from each treatment pot for collecting physiological data. A germination test was done prior to the experiment which indicated 100 % germination in both 100 % wastewater and 100 % fresh water. Four seeds were planted in each pot. The pots were irrigated with groundwater as the source of freshwater, textile wastewater as well as the mixture of the two in different ratios (Table 2). The characteristics of groundwater are given in Table 3.
Table 2 Irrigation scheme using textile wastewater
Table 3 Test report of physic-chemical properties of wastewater sample analysis
Collection and characterization of wastewater
Wastewater used in this experiment was raw and untreated point source collected from a textile industry of Savar, Dhaka (Bangladesh) and transported by standard methods as mentioned in APHA (1998). The wastewater sample was a mixture of different procedures such as washing, dying and rinsing, etc. To get the general idea of the characteristics, wastewaters from two different times were collected as sample 1 in the morning and sample 2 in the afternoon and their mixture was used for the experiment purposes. Within collection of half an hour Physic-chemical parameters electrical conductivity (EC), pH, DO was measured on the spot. EC, pH, and DO were measured by EC meter (EC 241, HANNA, Portugal), pH meter (Lab 851, SCHOTT Instruments, Germany), and DO meter (H19143, HANNA), respectively. Total hardness was measured by complexometric titration using EDTA; alkalinity was measured by titration method, total suspended solids (TSS) by gravimetric method, chemical oxygen demand (COD) by the closed reflux titrimetric method and biological oxygen demand (BOD5) by standard method (APHA 1998).
The sodium adsorption ratio (SAR) was calculated by the equation given by Richards (1954) in (meq/L)0.5.
$${\text{SAR}} = \frac{{{\text{Na}}^{ + } }}{{\sqrt {\frac{{{\text{Ca}}^{2 + } + {\text{Mg}}^{2 + } }}{2} } }}$$
(1)
where, Na+, Ca2+, Mg2+ are sodium, calcium and magnesium ion concentrations in meqL−1.
Collection and characterization of soil sample
Soil was collected from the agricultural land near Savar and considered as background soil. The soil belongs to the Madhupur clay formation. The soils are brown and red mottled, strongly acidic, friable clay loam to clay soils over deeply weathered red mottled Madhupur clay. The top soil is 10–15 cm thick (Huq et al. 2013). The clay minerals present in the Madhupur Clay soil of different areas of Savar and Dhaka are kaolinite (52.39 %), illite (36.39 %) and small amount of illite–smectite (11.21 %) (Haque et al. 2013). Cation exchange capacity (CEC) of Madhupur clay is low, pH 6.9 with poor moisture retention capacity (Hoque 1984).
Background soil before irrigation and that have passed 45 days after irrigation were collected, air-dried, ground by agate mortar and pestle, and sieved through a 150 μm mesh size sieve for metal analyses. For the ease of data interpretation percent change of physic-chemical parameter after 45 days of irrigation was compared using the following formula
$$\% {\text{Change}} = \frac{{{\text{N}}_{\text{Sample}} - {\text{N}}_{\text{background}} }}{{{\text{N}}_{\text{background}} }} \times 100$$
(2)
Nbackground = background data obtained for different parameters.
Nsample = sample data obtained after different treatments with unit expressed in %.
Collection and characterization of vegetable samples
Two randomly selected plants from five treatments with three replication pots were collected after 45 days of maturation. The plants were washed with double distilled water, chopped into smaller pieces, oven dried at 70 °C for 48–72 h, weighed and placed in a dehydrator. The dried samples were then ground and passed through 150 μm sieve.
One gram of dry matter was weighed into 50-mL glass beakers, followed by the addition of 10 mL mixture of analytical grade acids of HNO3 (concentration 70 %) and HClO4 (concentration 70 %) in the ratio 5:1. The digestion was performed at a water bath (temperature 80 °C) to heat for 72 h until a light color solution was obtained. After cooling, the solution was made up to a final volume of 25 mL with distilled water in a volumetric flask. Triplicate digestion of each sample was carried out together. For soil sample analysis the same procedure was followed. Analysis of heavy metals in water, soil and plant (Cu, Pb and Zn) were carried out by FLAAS (Flame Atomic Absorption Spectrophotometer Model: SHIMADZU AA-6800 series) with the detection limit for Fe (0.5 mg/L) Cu (0.0025 mg/L), Zn (0.01 mg/L), Pb (0.09 mg/L) and Cd (0.25 mg/L) in the Laboratory of Bangladesh Rice Research Institute. Ca and Mg were extracted by ammonium acetate method (Peech et al. 1947) and determined in FLAAS with the detection limit 0.50 and 0.3 mg/L, respectively. Flame Photometer PFP7 was used for the determination of Na (0.20 mg/L).
Total nitrogen content was analyzed by Kjeldahl method (Kjeldahl apparatus, model no. P/N 21284-01, critical value 0.12), percent organic matter (OM) was measured by ashing method (Storer 1984), total organic carbon (TOC) was measured by wet oxidation method as described in Huq and Alam (2005). Soil sulfur was measured turbidimetrically as sulfate (Hunt 1980) (using Tween-80) by UV-Spectrophotometer (Model: SPECORD 222A433, Analytik Jena AG, Germany) at 420 nm wavelength. All the instruments were calibrated before measurement and reagents were of analytical grade (AnalaR). All the glassware, containers and tools were soaked overnight with 20 % (v/v) nitric acid and finally rinsed with deionized water. All samples were filtered through 0.22 μm polycarbonate membrane filter.
Measurement of transfer factor (TF)
Heavy metal concentrations of soils and crops were calculated on the basis of dry weight. The soil-to-plant transfer factor (TF) of heavy metals (Fe, Cu, Pb, Zn, Cd) from soils to vegetables were calculated using the method of Cui et al. (2004) as follows:
$${\text{Transfer Factor }}\left( {\text{TF}} \right) = P/S$$
(3)
where, P and S is the residual concentration of the trace metal in plant tissues and in soil, respectively (ppm dry wt).
Measurement of daily intake of metal (DIM) and health risk index (HRI)
Health risk index (HRI) was calculated according to the method of Cui et al. (2004). The average daily leafy vegetable intake rate among Bangladeshi people is 0.0361 kg as found from the survey of Bangladesh Bureau of Statistics (BBS 2011). Data on average adult body weight of Bangladesh was 49.50 kg (Walpole et al. 2012). Using daily intake of metals (DIM) and reference oral dose (R
fD), the HRI value was obtained using the following equation.
$${\text{HRI}} = {\text{DIM}} / R_{\text{fD}}$$
(4)
where, R
fD is the reference oral dose (0.7, 0.04, 0.3, 0.004, 0.001 mg/kg BW/day) for Fe, Cu, Pb, Zn, and Cd, respectively (US-EPA IRIS 2006).
If the value of HRI is less than 1 then the exposed population is said to be safe (Zhuang et al. 2009).
The daily intake of metals (DIM) was calculated to averagely estimate the daily metal loading into the body system of a specified body weight of a consumer. This will inform the relative phyto-availability of metal. This does not take into cognizance the possible metabolic ejection of the metals but can easily tell the possible ingestion rate of a particular metal (Cui et al. 2004).
$${\text{DIM}} = C_{{{\text{metal conc}} .}} \times C_{f} \times D_{\text{food intake}} / {\text{BW}}$$
(5)
where, DIM is daily intake of metal mg/kg/day; C
metal conc. is heavy metal concentration in plants (mg/kg), C
f
is the conversion factor of 0.085 to convert fresh vegetable weight to dry weight, D
food intake is daily intake of leafy vegetables, based on average daily vegetable intake of the country (g) and BW = average body weight (kg).
Statistical Analysis
Data were put in Excel. Average of three replications and their standard error was calculated. Preparation of graphs and statistical analysis correlation coefficient and one way ANOVA with post hoc Tukey test was calculated in Origin 9.0 (OriginLab, USA). A 0.05 level of probability was used to calculate the critical value of F. If F falls below a fixed threshold, it can be concluded that all the sets of samples have equal averages. Pearson’s correlation coefficient with 95 % confidence interval of metal values between soil sample and plant samples were analyzed.