Introduction

Wheat (Triticum aestivum L.) is the most widely crop grown in the world. Pakistan is well known as an agricultural country and its agriculture sector continues to play a vital role in the national economy (Adnan et al. 2009). Wheat production represents the leading food grain in Pakistan where the country is classified among the 10th wheat producer countries worldwide. Wheat, known as “Gandum,” is an essential ingredient for population as it constitutes by 60 % of the daily diet in Pakistan. Area under wheat has shown an increase of 0.5 % over last year and the production stood at 24.3 million tonnes, against the target of 25.5 million tonnes. To date, there is about 60 % yield gap in wheat, which needs to be narrowed. The major reasons for low productivity and instability include shortage of irrigation water. In fact, large fraction of agriculture areas in Pakistan falls within arid and semi-arid zones (Shah et al. 2011; Baig et al. 2013). About 75 % of the total cultivated area is irrigated, while the rest is rainfed (PCST, Pakistan Council for Science and Technology 2005). Being the key element of agricultural production, the availability of sufficient water for crop irrigation can reduce the impact of water scarcity (Falkenmark and Dolden 2008). Today, due to constraint in availability of fresh water for irrigation, wastewater especially sewage water is being used by farmers to satisfy crop water needs. Many studies confirm that treated sewage wastewater can be useful as an additional water resource for irrigation (Mehrdadi et al. 2007; Palese et al. 2009; Khan et al. 2016a) and as a big source of important minerals and nutrients which can reduce the cultivation costs due to synthetic N fertilizer use (Lone et al. 2003; Qadir et al. 2008). Although the reuse of sewage wastewater can be beneficial to agriculture and considering that safeguard the environment and the production of clean and safe food are the basic requirements of human existence, there are some environmental and health burdens that have been considered (Khan et al. 2016b). For instance, untreated sewage water irrigation is believed to be the major source of increasing soil and crop metals. It contains different types of poisonous compounds, and therefore, the extensive use of wastewater for irrigation purposes of food crops causes accumulation of these toxic compounds in plants (Singh et al. 2004). As metals cannot be broken down, when concentrations within the plant exceed optimal levels, they adversely affect the plant both directly and indirectly. Some of the direct toxic effects caused by high metal concentration include inhibition of cytoplasmic enzymes and damage to cell structures due to oxidative stress (Assche and Clijsters 1990; Jadia and Fulekar 2009), while the important feature of indirect toxic effect is the replacement of essential nutrients at cation exchange sites of plants (Taiz and Zeiger 2002).

In agriculture fields, some heavy metals, such as Cu, Fe, Ni, and Zn, are required in few amount by organisms. However, excessive amounts of these elements can become harmful and can negatively affect crop productivity. Since the complete removal of these toxic metals from the soil surface is not possible, they will find their way to enter in the food chain (Wilson and Pyatt 2007). Because antagonistic and synergistic behaviors exist among heavy metals, the presence of one heavy metal may affect the availability of another in soil and hence in plant. Salgare and Acharekar (1992) reported that the inhibitory effect of Mn on the total amount of mineralized C was antagonized by the presence of Cd. Similarly, Cu and Zn as well as Ni and Cd have been reported to compete for the same membrane carriers in plants (Clarkson and Luttge 1989). In contrast, Cu was reported to increase the toxicity of Zn in spring barley (Luo and Rimmer 1995). This implies that the interrelationship between heavy metals is quite complex.

In Pakistan, the province of Punjab is the focus of major agricultural planning and development efforts being the main source of agricultural production in the country. However, in the last few years, Punjab’s dominance in wheat production has greatly reduced due to stagnation in wheat production of the province. This stagnation was due to different issues including lack of sufficient watering system, low yields and quality, costly and otherwise intensive cultivation techniques, and less utilization of current innovation in wheat production. To reach the production target, National Research System has been developing wheat varieties for different ecological zones through PARC National Uniform Testing System (NUWYT). One of the new rust-resistant varieties (NIA Sarang-2013) was recommended to be cultivated in rainfed area of Punjab. In fact, in order to sustain wheat production in Pakistan, water source management and investment in water for irrigation through viable alternatives can help to achieve this goal. However, the increase of public concern on the viability and the effects of wastewater use on soil and human health, through food chain, are still under criticism. In this regard, in this study, we aimed to explore the potential for soil and wheat pollution irrigated with sewage wastewater and to evaluate the health hazards of heavy metals.

Materials and methods

Study area

This study was conducted under pot conditions in Nursery, University College of Agriculture Sargodha, province of Punjab (Pakistan). The study location is about 9.7 km north from University of Sargodha. Climate is characterized primarily as desert or near desert. The country stands among the most arid countries with an annual rainfall of below 240 mm (Farooq et al. 2007). Climate conditions in Sargodha are usually characterized by very hot summer temperature and temperate weather in winter. The extreme temperature in summer reaches 50 °C while 12 °C represents the lowest temperature recorded in winter.

Experiment set up

Sarang variety of wheat was sown at the end of December 2014 in plastic pots using three replicates with a total of 15 pots in each replicate. Each pot was filled up with 2.5 kg of fertile soil and then ten seeds were sown per pot. Different water qualities were applied to wheat pots using ground/fresh water (GW) and untreated municipal sewage water (SW) alone or in combination with different concentrations. The experimental pots were irrigated with five treatments: T-I (100 % GW), T-II (75 % GW+25 % SW), T-III (50 % GW+50 % SW), T-IV (25 % GW+75 % SW), and T-V (100 % SW). Sewage water was taken from sewage water ponds, which was located in the front of Agricultural College, University of Sargodha, Sargodha. After maturation, four plants per pot were left while others were eradicated. Crop was harvested at the end of April 2015. Grain samples were taken from each pot where they were detached from husks and then ground in grinder to get wheat grain flour. The resulted wheat flour was kept in the oven for 3 days at temperature of 104 °C. After 3 days, samples were digested using wet digestion method (Bowman 1989) for the determination of heavy metals in wheat samples.

Sample preparation and metals determination

Samples of fine grain flour dried in oven and samples of soil (about 2 g) were prepared by digesting in H2O2 and HNO3 in 2:1 on a hot plate for about 1 h. Later, 2 ml of H2O2 were added to each digested sample. The digestion method sustained until the mixture of digestion for each sample comes to be clear. Then, sample mixture was filtered and diluted using distilled water up to 50 ml (Khan et al. 2016a, b). In order to determine metal and metalloid concentrations in the digested grains and soil samples, an atomic absorption spectrophotometer (model AA-6300 Shimadzu) was used. To proceed with the analysis, the standards of investigated heavy metals (Cd, Cu, Cr, Ni, Fe, Zn, and Pb) were prepared (Khan et al. 2016a, b). Results of heavy metal concentrations were expressed as mean value (mg kg−1) on dry weight (± SE) of three sub-samples collected from each treatment.

Indexes calculation

To reach the objectives of our study, the pollution load index (PLI), translocation factor (AF), daily intake (DIM), and health risk index (HRI) were calculated as follows:

Translocation factor

The ability of heavy metals to translocate from the soil to the fruits or grains of agriculture crops is referred to using an accumulation factor (AF). Previous studies have calculated this factor using different terms, i.e., bio-concentration factor (BCF) (Raskin et al. 1994; Cui et al. 2004) and transfer factor (TF) (Chojnacka et al. 2005; Bi et al. 2010; Wang et al. 2006). For the calculation of AF in this study, heavy metal concentrations in wheat grains from each treatment were used. The AFs of Cd, Zn, Pb, Cu, Cr, Ni, and Fe were then calculated following the methodology described by Li et al. (2012). The following equation was used for the calculation:

$$ AF=\mathrm{Metal}\ \mathrm{concentration}\ \mathrm{in}\ \mathrm{edible}\ \mathrm{parts}\ \mathrm{of}\ \mathrm{crop}/\mathrm{Metal}\ \mathrm{concentration}\ \mathrm{in}\ \mathrm{the}\ \mathrm{soil} $$

Pollution load index

Contamination levels in soil are analyzed using pollution load index (PLI) proposed by Tomlinson et al. (1980) and Angulo (1996). Based on the concentration factor of each metal in the soil, PLI gave us an estimation to the metal contamination status and the necessary action that should be taken. In this study, we estimate PLI for each treatment following the methodology described by Liu et al. (2005). The equation used for the estimation is as follows:

$$ PLI=\mathrm{concentration}\ \mathrm{of}\ \mathrm{metal}\ \mathrm{in}\ \mathrm{soil}/\mathrm{reference}\ \mathrm{value}\ \mathrm{of}\ \mathrm{metal}\ \mathrm{in}\ \mathrm{soil} $$

Daily intake of metals

For finding out consumer-based health risks, certain methods are taken into consideration. In this study, the daily intake of metal method was used to estimate health risks (see also Balkhair and Ashraf 2016). The daily intake of metals (DIM, mg kg−1 person−1 day−1) was calculated as in the following equation:

$$ \mathrm{DIM}={C}_{\mathrm{metal}\kern0.75em }\times {C}_{\mathrm{factor}}\times {C}_{\mathrm{intake}}/{B}_{\mathrm{weight}} $$

where C metal represents concentration of metal ingrains, C factor represents conversion factor, C food intake represents the daily food intake, and B average weight represents average body weight.

Health risk index

It was measured to find overall risks of exposure to all heavy metals via ingestion of particular food crops. This shows the risk to people, which consume contaminated foodstuff. It is defined as ratio of daily intake of metals in food crops to the oral reference dose (USEPA, US Environmental Protection Agency 2002). Therefore, health risk index was calculated as in the following equation:

$$ \mathrm{Health}\ \mathrm{Risk}\ \mathrm{Index}\ (HRI)=\mathrm{daily}\ \mathrm{intake}\ \mathrm{of}\ \mathrm{metals}\ \left(\mathrm{DIM}\right)/\mathrm{oral}\ \mathrm{reference}\ \mathrm{dose}\ (RfD) $$

HRI higher than 1 for any metal in plant’s edible part(s) is considered to be not safe for human health which can cause a serious health risk. However, HRI <1 means that the exposure to heavy metals by population is assumed to be safe.

Statistical analysis

The average concentrations of metal and metalloid in the wheat grains and soil were obtained. For both soil and grains data, the SPSS software was used and one-way ANOVA was applied. Correlation between wheat grains and soil with respect to each metal concentration was determined.

Results and discussion

Concentration of metals

The concentrations of heavy metals (Cr, Cd, Ni, and Pb) and trace elements (Cu, Zn, and Fe) in wheat grains and soil are reported in Fig. 1. Results indicated that concentration of heavy metals in both soil and grains did not follow a regular trend. However, most of the metals showed higher concentrations when SW was used for irrigation, with only some exceptions.

Fig. 1
figure 1

Average heavy metal and trace element concentration in soil and grain

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The concentrations of heavy metals (as mg/kg) obtained in soil samples showed high concentrations, except for Zn which was much higher in wheat. In fact, Zn in grain was not satisfactorily predicted by total soil contents of Zn. Among the investigated metals, higher levels of Fe and Zn were observed in both soil and grain compared to the other metals. Most of metal levels in the SW irrigation water (used as a reference) resulted beyond the suggested reference values for maximum permissible level in irrigation water (Table 1). The same Table indicates also that Cd and Cu levels in GW exceed the maximum permissible level for irrigation water. In the soil, all studied elements were found to be below the maximum allowable limits compared to reference values (Table 2).

Table 1 Average heavy metal concentration of different water combinations used for irrigation and average heavy metal concentration in ground (GW) and sewage (SW) water compared to the permissible maximum level (PML)
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Table 2 Metal concentrations (mg kg−1 dry weight ± SE) in soil under the different treatments
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Concentration of metals in the water

The heavy metal concentrations in water used for wheat irrigation are reported in Table 1. To establish a baseline data for heavy metals found in our irrigation water, the average data from different studies on heavy metal concentrations in GW (Tariq et al. 2006) as well as in SW (Murtaza et al. 2010) from different nearby cities of Pakistan were used (Table 1). Since safe limits for heavy metals in irrigation water, soil, and food crops have not been established yet in Pakistan (Hassan et al. 2013), heavy metals in this study were compared to permissible maximum limits from WHO/FAO and Ewers (1991), Standard Guidelines in Europe, taken from Chiroma et al. (2014) and Pescod (1992).

Concentration of metals in the soil

After the analysis of soils within treatments, heavy metal traces were recorded in all samples. A wide range of soil heavy metal concentrations were observed (Table 2). The results ranged from 1.19–2.5, 0.11–1.9, 0.25–1.93, 4.79–9.70, 0.53–2.59, 2.76–7.50, and 0.65–1.38 mg kg−1 for Cd, Cr, Cu, Fe, Ni, Zn, and Pb, respectively. The heavy metal concentrations were below the PML for soil (Ewers 1991 and Chiroma et al. 2014). The most prevalent heavy metals were Fe and Zn (7.16 and 5.12 mg kg−1, respectively). Their concentrations were higher in soils irrigated with GW (T-I) and lower in T-V for Fe and in T-IV for Zn, respectively. In a previous study, Kansal et al. (1996) found that utilization of SW for irrigation of food crops extensively raises the accumulation of Zn, Cu, Pb, and Cd in soil from different localities of Punjab (Pakistan). In particular, the authors found that the concentration of Zn and Fe was greater in soils receiving SW of factories. This was in agreement with the average data reported in our study (Fig. 1), indicating that the concentrations of Zn and Fe are the highest in soil compared to the other metals.

In overall, the amount of Pb in soil was found to be the lowest among studied metals with the lowest value being reported in T-I. The other metals (Cd, Cr, Cu, and Ni) were reported in close concentrations (ranging between 1.05 and 1.98 mg kg−1). Results obtained show that the mean concentrations of metals and metalloids in the soil of T-I treatment were Pb<Ni<Cu<Cr<Cd<Zn<Fe, whereas in T-II Pb<Cr<Ni<Cu<Cd<Zn<Fe. However, in T-III treatment, the mean concentrations were as follows: Pb<Ni<Cr<Cu<Cd<Zn<Fe. Finally, in T-IV and T-V, the metals levels were Cr<Pb<Cu<Cd<Ni<Zn<Fe and Cr<Cu<Pb<Ni<Cd<Zn<Fe, respectively (Table 2).

Concentration of metals in wheat

The comparison of mean concentration of metals in wheat grains under the five treatments indicated that the mean concentration (mg kg−1) of Cr was the lowest, whereas Zn concentration was the highest (Table 3). As in the soil, the analysis data revealed that the most prevalent heavy metals in wheat were Fe and Zn (Fig. 1). However, the Zn concentration in the grain was higher than Fe (an opposite behavior was observed in the soil). This higher amount of Zn in wheat grain was far below the PML; therefore, the relatively small amount of Zn did not cause health problems. In fact, Pakistan agricultural research council (PARC) stated that small amount of Zinc in food products is necessary for human health. In particular, wheat variety having 50 % Zn has health benefits. Karatas et al. (2006) found that the average amount of Zn (22.31 mg kg−1) was highest in wheat grains irrigated with wastewater. This was not in line with our findings; however, the concentration value of Zn in wheat grain was lower. The lower value reported for Zn might be due to the fact that, in present study, there was less accumulation of toxic metals from smoke of industries. The lead level observed in the present study was similar to the findings of Karatas et al. (2006).

Table 3 Metal concentrations (mg kg−1 dry wt. ± SE) in wheat grain irrigated with five different treatments
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Among the treatments, the distribution of Zn indicated that the maximum levels in wheat grain samples were found in T-IV, whereas the highest concentration for Fe was reported in T-II (8.43 mg kg−1). The other metals (Cd, Cu, Ni and Pb) reported a close average which ranged between the lowest (0.136 mg kg−1) for Pb and the highest (1.204 mg kg−1) for Cu. Trace of Cr metal was reported with the lowest concentration (0.068 mg kg−1) among the studied metals in wheat grain samples (Fig. 1). Despite its lower amount compared to other metals, treatments with different combination of GW and SW show no significant effect on Cr concentration. Its presence in wheat grain across the treatments shows the lowest concentrations being reported in T-IV.

The general trend of the results shown in Table 3 indicated that the mean concentrations of Cd as well as Cu decreased, while Pb reached the maximum level when the amount of sewage water irrigation increased. In T-I, the concentration of metals and metalloids in grains was Cr<Pb<Cd<Ni<Cu<Fe<Zn. The same metal concentration order was also reported in T-II and T-III. In T-IV, the mean concentration of metals and metalloids in grains was Pb<Cr<Cd<Ni<Cu<Fe<Zn. In wheat irrigated with 100 % SW, the mean concentration of metals and metalloids was as follows: Cr<Cd<Pb<Ni<Cu<Fe<Zn (Table 3).

For all studied metals (Cr, Cd, Cu, Ni, Fe, Zn, and Pb), the results showed no significant effect (P > 0.05) on metal and metalloid concentrations in wheat, while a significant effect on the metal concentration in the soil was observed (Table 4).

Table 4 Analysis of variance of data for metal contents in soil and wheat grain
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Calculation of parameters

Based on heavy metal concentration in soil and in wheat grain samples, the pollution load index (PLI), translocation/accumulation factor (AF), daily intake of metals (DIM), and health risk index (HRI) were calculated (Fig. 2).

Fig. 2
figure 2

Comparison of mean average studied metals for the calculated parameters

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Translocation factor

The study of heavy metal accumulation from SW by the crops is important, highlighting a direct possible effect on human health through the food chain. The data analysis of AF indicates that there was variability within treatments and across metals. It is believed that soil-metal levels, soil cation exchange capacity, soil types, and pH as well as crop varieties affect the uptake of metals by plants (Barancikova et al. 2004).

The present results suggest a general increase of metal uptake by wheat grains irrigated with SW. The maximum accumulation value from soil to plants of metals was for Zn, indicating a strong accumulation of the respective metal by wheat (Table 5), while the lowest AF was reported for Pb. The higher value of Zn accumulation resulted in higher concentration in wheat grain compared to the other metals. Similar result was obtained by Jolly et al. (2013) who found that Zn had the highest AF in vegetables.

Table 5 Heavy metal translocation factors (on dry weight basis) for wheat grown under different irrigated soils
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Data in Table 5 show that the AF values were lower for Pb, Fe, Cr, and Cd and higher for Zn, Cu, and Ni, respectively (with some exceptions). The variation in AF values could be due to differences in water quality used to irrigate wheat and the associated metal concentration. The trends of AF for heavy metals in wheat grain of T-I were Cu>Zn>Ni>Cr>Pb>Cd>Fe and in the order of Zn>Cu>Ni>Cd>Pb>Cr>Fe for T-II treatment. However, in T-III, the AF order was Cu>Cr>Zn>Cd>Ni>Pb>Fe, while for T-IV and T-V were Zn>Cu>Cd>Ni>Cr>Pb>Fe and Zn>Cu>Pb>Ni>Cr>Cd>Fe, respectively.

Pollution load index

Contamination level in soil can be explored using pollution load index (Angulo 1996). This index provides a simple and comparative means for assessing the quality of different combinations of water irrigation. As described by Tomlinson et al. (1980), a value of zero indicates no risk, whereas a value of one and values above one would indicate progressive deterioration of the site irrigated with this water quality. In the present study, PLI values for water-irrigated soil under the different treatments are reported in Table 6. All values were below one and ranged between the minimum of 0.007 for Cr in T-III and the maximum of 0.557 for Fe in T-I and T-II, respectively. Among the studied metals, the PLI of Cr and Fe reported the lowest and the highest, respectively. In the case of average value across treatments, Fe and Zn were the highest distributed metals in both soil and wheat grain. In average, PLI values for the different metals have followed the order of: Cr<Pb<Ni<Cu<Zn<Cd<Fe. According to Ahmad et al. (2010), the order of PLI for heavy metals in soil was Pb>Cr>Ni>Cd>Fe>Cu>Zn. This was against the PLI order in the present study, where PLI value for Pb, Cr, and Ni was less and Zn, Fe, and Cu was higher. The order of contamination in T-I was Cr<Pb<Ni<Cu<Zn<Cd<Fe. In T-II, the order was Cr<Pb<Ni<Cu<Cd<Zn<Fe, whereas in T-III, T-IV, and T-V the order was Cr<Pb<Ni<Cd<Zn<Cu<Fe, Cr<Pb<Cd<Ni<Cu<Fe<Zn and Cr<Pb<Ni<Cd<Cu<Fe<Zn, respectively (Table 6).

Table 6 Pollution load index values for wheat
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Daily metal intake

To assess the health risk of a pollutant element, we estimated the possible exposure level of humans to each element through food chain pathways. In the present study, the intake pathway of the studied metals was assumed to be the consumption of wheat grain. In this regard, the DIM values were estimated according to the average wheat grain consumption by adults. The obtained data are reported in Table 7. Across treatments, the analysis between values of DIM revealed that Fe and Zn had the higher intake, whereas Cr and Pb showed the lower daily intake values. The DIM values obtained in this study (Table 7) were close to those reported by Mahmood and Malik (2014), where DIM was found to be higher for Zn, Ni, and Cu and lower for Cr, Pb, and Cd. The order of DIM and metalloids considering the average of the five treatments was Zn>Fe>Cu>Ni>Cd>Pb>Cr (Fig. 2).

Table 7 Values of daily metal intake (DIM, mg kg−1 person−1 day−1) in wheat
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Health risk index

Human risk assessment caused by eating polluted food through food chain pathway was carefully measured by health risk index (USEPA, US Environmental Protection Agency 2002; Cui et al. 2004 and Wang et al. 2005). The quantification of this index is of great importance especially in countries where the wastewater irrigation practice remains unregulated. If the value of HRI of a specific food material is <1, it was assumed to be safe for human consumption. However, if it is >1, serious threat to human health is possible (USEPA, US Environmental Protection Agency 2002).

In our study, the HRI was calculated under each treatment and metal. Results from the HRI calculation are presented in Table 8. These results revealed that HRI for Zn was the highest in all treatments, indicating a possible human health risk via the intake of food crop. This was in agreement with the findings of Bansal and Singh (2015) who found that the HRI value for Zn was higher than 1 in food materials. The HRI value for Cd in T-I and T-III also exceeded the permissible values, which may pose a potential threat to human health. The HRI of other metals (i.e., Cr, Cu, Fe, Ni, and Pb) reported lower-than-permissible values under all treatments, indicating no risk for human health. Among the studied elements, Cr reported the lowest values for HRI; therefore, metals (i.e., Cr, Cu, Fe, Ni, and Pb) indicate safe consumption for human. The order for health risk index of the metals in T-I and T-II was Cr<Fe<Ni<Cu<Pb<Cd<Zn. The order for health risk index of the metals in T-III was Cr<Fe<Ni<Pb<Cu<Cd<Zn. Metal concentration was in order of Cr<Fe<Pb<Cu<Ni<Cd<Zn and Cr<Fe<Ni<Cu<Pb<Cd<Zn in T-IV and T-V, respectively (Table 8).

Table 8 Health risk index values
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Correlation soil-wheat and metal concentration

Results on correlation between soil-metal concentration and wheat-metal concentration showed positive non-significant correlation of Cu and Ni, and negative and non-significant correlation of Cd, Cr, and Zn. The only positive and significant correlation between wheat grains and soil was found in Fe (Table 9). In present study, results of the correlation for Fe and Cu were comparable to previous studies conducted by Ahmad et al. (2010), revealing that the correlation between soil and food crop was significant and positive for Fe, while it was non-significant for Cu.

Table 9 Metal and metalloid correlation between soil and wheat
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Conclusions

Irrigation with polluted water may contaminate readily the soil and cultivated land. Wheat grain and soil samples showed significant deviation in mean concentrations of significant metals. The accumulation of heavy metals from soil to plant varied according to metals and treatment; however, they did not follow any particular pattern. The results of risk assessment suggest that Zn and Cd contamination in wheat grain had a potential health risk for consumers. Thus, with the increase of population and industrialization, the heavy metal concentrations in wastewater would linearly increase influencing also water quality. Despite the high concentration of some metals found also in ground water, this study should support the future political plans to increase the public awareness about the use of irrigation water with hazardous substances. This study can also help to establish a baseline data regarding environmental safety and suitability of sewage irrigation in future crop production. However, more wide-ranging sampling is needed to study such areas, and further investigation on contamination of other cereals is required.