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Introduction
Papaya (Carica papaya L.) fruit is the third most consumed tropical fruit worldwide and represents 15.36 % of the worldwide production of tropical fruits, being Mexico the sixth producer of this fruit at a global level (Evans & Ballen, 2012). Carica papaya L. is one of the most important fruit and vegetable products of the state of Colima. Around 128,000 tons of papaya are estimated to be produced per year in this state (SAGARPA, 2017), with an economic apportionment close to 844 million pesos in 2016, most of the state production is destined to exportation (United States of America and Canada) and the rest is for local consumption (SIAP, 2016).
Regulation and norms regarding chemical and microbiological food safety are an important part for the commercialization and the development of suppliesproducing activities; there are strict surveillance instruments and attached to take care of the health of human beings from the national to the international scope.
Foods are generally source of minerals, which play an important role in four types of functions in animals, such as structural, physiological, catalytic and regulatory functions (Suttle, 2010). On the other hand, elements called heavy metals, depending on their concentrations, are harmful to the environment and to human health, Pb, Cd, Se, Hg, Al, As, Ba, Be, Ni, Cr, Sn and V are this type of elements (Salma et al., 2015).
In fruit and vegetable products, these metals can bioaccumulate during the phenological development by transferring from the soil, irrigation and subterranean water, among others (Ogbonna et al., 2013; Kamal et al., 2016; Yami et al., 2016). Heavy metals represent a risk for human health since they can be toxic at low concentrations (Yerlikaya et al., 2015).
Maximum limits allowed of heavy metals in food are established in the codex general standard for contaminants and toxins in food and feed (CODEX STAN 193-1995) of the Food and Agriculture Organization of the United Nations and the World Health Organization (FAO/WHO, 2007).
Food global demand makes that each time more lands are used for cultivations without considering nearby activities, such as metallurgical industries, chemical or nuclear plants and sanitary landfill, which can be sources of contamination by distinct heavy metals (Zhuang et al., 2009; Salazar et al., 2012; Ogunmodede et al., 2016). Different studies have been conducted to determine metal content in fruits, such as apple, banana, avocado, cherry, cranberry, grape, lemon, mango, melon, papaya, among others (Ang & Ng, 2000; Fafar & Masud, 2003; Sobukola et al., 2010; Li, et al., 2012; Grembecka & Szefer, 2013; Islam et al., 2015).
In the analysis of complex samples, such as vegetal tissues, food and soils, different analytical techniques have been used for determining macrominerals, trace elements and heavy metals; for example, in the preparation of this type of samples, a previous digestion has to be performed to eliminate organic components and to solubilize target elements for analysis, methods that are generally used are moisture or dry content calcination (Subramanian, 1996; Akinyele & Shokunbi, 2014), digestion with acid mixture (Mohammed et al., 2017) and acid digestion by microwave assisted method (Rashid et al., 2016).
Once the sample was prepared, the determination can be performed by Attenuated Total Reflection-Fourier Transform Infra-Red Spectroscopy (ATR-FTIR) (Fadare et al., 2015), Atomic Absorption Spectrophotometry (AAS) (Ali & Al-Qahtani, 2012), Graphite Furnace Atomic Absorption Spectrophotometry (GFAAS) (Bakkali et al., 2009), Inductively Coupled Plasma Optical Emission Spectrophotometry (ICP-OES) (Adamu et al., 2016; Tóth et al., 2016), Inductively Coupled Plasma Mass Spectrometry (ICP-MS) (Hwang et al., 2016).
Due to the importance of these metals in human health, the present study aims to determine the content of macrominerals, trace elements and heavy metals in Carica papaya L. fruits, commercialized in local markets in the State of Colima, using ICP-OES and to evaluate Health Risk Index in consumers.
Material and Methods
Studying and sampling area.
The State of Colima is located in western Mexico and delimits at the north and east with the State of Jalisco, at the southeast with the State of Michoacan and at the south and west with the Pacific Ocean. It is divided into ten municipalities (Figure 1) and has a population of around 711,235 inhabitants and one of the main agricultural products of exportation and local consumption is papaya.
Fresh fruits were bought in markets of the ten head-municipalities of the State (two markets per municipality), six fruits per municipality were acquired in their maturation stage number 5 (Santamaría-Basulto et al., 2009) and immediately labelled and refrigerated at 15 ºC for their analysis.
Reference reagents and materials.
Deionized water was used with a restistivity of 18.2 MΩcm to wash and prepare samples. Reagents were used as they were received from the manufacturer. Nitric acid 70 % (Sigma-Aldrich), hydrogen peroxide 30 % for trace analysis (Sigma-Aldrich). Reference standards were acquired from Accustandard, Inc. brand (United States of America) and count on NIST traceability certificate. All plastic and glass materials were washed with phosphate-free detergent and 10 % nitric acid solution 24 h before being used.
Moisture determination.
Moisture determination was performed according to established AOAC International procedure, in which fresh samples were washed with distilled water to eliminate dust particles, then with a 0.1 M nitric acid solution, rinsed with deionized water and dried exteriorly with paper. The skin was removed posteriorly, fruits were cut into pieces of 4 cm3 and 150 g of each fruit were pooled to make a compound sample, which was placed on polypropylene trays in an oven with forced air circulation MMM brand Venticell 222 model (United States of America) at 70 oC±5 oC from 48 to 72 h and moisture content was determined at constant weight. Once the sample dried, it was placed in a Bel Art mill Micro model (United States of America) until reducing particle size with a 2 mm sieve. Dried, ground and homogenous sample portions were placed in hermetic polypropylene bags and were stored at 4 ºC for their posterior analysis (AOAC, 2005).
Elemental analysis by ICP-OES
Sample digestion.
Digestion process by microwave assisted method is based on EPA-3052 method of the Environmental Protection Agency (US-EPA) and is applicable to extraction/dissolution of available metals in fruit and vegetal tissues samples.
In this method, 0.3±0.05 g of dry samples were weighted with 2 mm particle size in triplicate in an analytic weighting scale Sartorius brand Secura 224-1S model (Germany), 2±0.1 mL of 30 % hydrogen peroxide and 7±0.1 mL of concentrated nitric acid were added. A system of digestion by microwave Anton Paar brand Multiwave PRO model (Austria) was used with the following operating conditions: Temperature ramp from 25 ºC to 180±5 ºC in 10 minutes, maintaining temperature at 180±5 ºC for 10 minutes more. Digested samples were filtered with ashes-free filter paper Whatman No. 42 and were diluted to 50 mL (Jones et al., 1988).
Determination by ICP-OES spectrophotometry.
The elemental analysis was performed in an equipment Perkin Elmer brand 8300 DV Optima model (United States of America). Quantifications were determined in relation with calibration curves with standard solutions from Accutrace reference, AccuStandard brand, with levels of concentration of 0.1, 0.5, 1, 5 and 7 mg L-1. Elements and recommended wavelengths for its analysis based on EPA-6010C (Jones, 1987) and Perkin Elmer manufacturer Manual (Boss & Fredeen, 2004) are shown in Table 1. Operating conditions of ICP-OES equipment is shown in Table 2.
Table 1 List of elements (wavelengthsa in nm) (Jones, 1987).
| Aluminum (308.215) |
Berylium (313.042) |
Copper (324.754) |
Mercury (194.227 x2) |
Silver (328.068) |
| Antimony (206.833) |
Cadmium (226.502) |
Iron (259.94) |
Molybdenum (202.03) |
Sodium (588.995) |
| Arsenic (193.696) |
Calcium (317.933) |
Lead (220.353) |
Nickel (231.604 x2) |
Thalium (190.864) |
| Boron (249.678 x2) |
Chromium (267.716) |
Magnesium (279.079) |
Potassium (766.491) |
Vanadium (292.402) |
| Barium
(455.403) |
Cobalt
(228.616) |
Manganese
(257.61) |
Selenium
(196.026) |
Zinc
(213.856 x2) |
aThe wavelengths listed (where x2 indicates second order) are recommended because of their sensitivity.
Table 2 ICP-OES operating conditions.
| RF Power (kW) | 1.3 |
| Nebulizer | SeaSpray |
| Spray chamber | Cyclonic |
| Plasma Viewinga | Axial |
| Processing mode | Area |
| Gas flow rate (L/min). Plasma | 15 |
| Gas flow rate (L/min). Auxiliary | 1.5 |
| Gas flow rate (L/min). Nebulizer | 0.94 |
| Read delay (s) | 40 |
| Rinse (s) | 30 |
| Replicates | 3 |
aRadial viewing was used to determine Ca, Na, P and K due to their higher concentrations.
Statistical analysis
All data were statistically analyzed and have been presented as means, range and standard deviation. Average values of the analyzed elements in papaya samples collected in the different municipalities of the state of Colima were compared using a Student t-test for independent samples. A probability of p<0.05 was used as significant statistical level. Statistical analysis was performed by using SPSS software version 1.0.0.800 (IBM).
Health Risk Assessment.
Health Risk Assessment by papaya consumption with the concentration of metals obtained in this study was performed through the determination of Daily Intake of Metals (DIM) and Health Risk Index (HRI). Aforementioned values were evaluated based on the method reported by (Khan et al., 2013).
Daily Intake of Metals (DIM).
Values for Daily Intake of Metals (DIM) were calculated according to the following formula:
Where Dfood intake is food intake rate (16.71 g day-1 per capita) (National Agricultural Planning 2017-2030, 2017), Cmetal is the concentration (µg g-1) of the element present in papaya and Baverage weight represents the average body weight (71.75 kg) of an adult consumer in Mexico (CANAIVE, 2018). Calculated values were compared with recommended values by the expert committee of the Food and Agriculture Organization and the World Health Organization (FAO/WHO, 2010).
Health Risk Index (HRI).
Health Risk Index (HRI) was calculated according to the following formula:
Where DIM is the Daily Intake of Metals and RfD is Reference Dose, which is an estimation of the daily exposition to a contaminant to which the human population may be continually exposed throughout life without any risk of harmful effects (Akoto et al., 2014) with values of Cr 0.003, Cd 0.001 and Pb 0.004 mg kg-1 day-1 of the Environmental Protection Agency (US-EPA, 2004; 2012). HRI<1 indicates that there is no apparent health risk for consumers.
Total Health Risk Index, which is the sum of Health Risk Index of each metallic species, considers that in presence of several heavy metals, the toxic effect is additive and may suppose a risk for human health if its value is higher than 1 (Zheng et al., 2007).
Results and Discussion
Moisture determination.
The average moisture content of the analyzed samples was 88.99±0.54 %. Results of moisture content are shown in Table 3, where samples from Tecomán municipality presented the highest moisture content with a 91.88±1.12 %, while those from Villa de Álvarez municipality presented a moisture content of 85.59±1.19 %, which was the lowest of all municipalities. These values were similar to those reported in other studies (Ang & Ng, 2000; Sobukola et al., 2010; Grembecka & Szefer, 2013).
Table 3 Macrominerals (mg kg-1 wet wt.) n=3 and moisture content (%) n=5.
| Municipality | Ca | K | Mg | Na | P | % Moisture |
| Armería | 305.80 | 3,389.60 | 285.00 | 403.50 | 172.30 | 88.86 |
| Colima | 259.83 | 3,458.06 | 217.49 | 355.21 | 154.84 | 88.71 |
| Comala | 301.21 | 3,340.05 | 224.39 | 643.69 | 184.78 | 88.95 |
| Coquimatlán | 373.58 | 2,945.22 | 359.68 | 423.54 | 156.38 | 86.97 |
| Cuauhtémoc | 249.46 | 2,591.49 | 243.07 | 529.84 | 150.93 | 90.86 |
| Ixtlahuacán | 155.87 | 2,598.35 | 216.47 | 468.71 | 163.87 | 89.05 |
| Manzanillo | 131.69 | 1,980.78 | 161.54 | 346.17 | 111.30 | 90.59 |
| Minatitlán | 140.04 | 2,717.86 | 184.69 | 380.13 | 179.89 | 88.49 |
| Tecomán | 135.95 | 2,127.72 | 177.39 | 253.84 | 126.62 | 91.88 |
| Villa de Álvarez | 117.97 | 2,260.62 | 181.03 | 251.11 | 168.09 | 85.59 |
| Mean
(SD) |
217.15
(91.71) |
2,740.97
(533.70) |
225.08
(59.67) |
405.58
(120.21) |
156.90
(22.98) |
88.99
(0.54) |
SD= Standard Deviation.
Chemical characterization by ICP-OES.
Macrominerals content in the analyzed samples is presented in Table 3. The trend for average mineral content on a humid basis is 2,740.97; 405.58; 225.08; 217.15 and 156.9 mg kg-1 for K>Na>Mg>Ca>P, respectively
There is a significant difference in results obtained in Table 3 between two groups of municipalities, possibly due to the fact that municipalities of Colima, Comala, Coquimatlán and Cuauhtémoc represent 22 % of the state production and soil and irrigation water characteristics are similar among them, in contrast, municipalities of Ixtlahuacán, Manzanillo and Tecomán, which represent 69 % of the production have similar concentrations among them (SIAP, 2016).
The comparison of average values obtained in this study with previous studies is presented in Table 4. Potassium content in all reference studies was higher than the other minerals, but lower than 4,200 mg kg-1 reported by (Othman, 2009). The aforementioned showed that papaya is a rich source of this mineral with a higher content than banana (Musa paradisiaca) with 140 mg kg-1 and (Musa L.) 1,580 mg kg-1 (Fafar & Masud, 2003; Grembecka & Szefer, 2013).
Table 4 Comparative values of Macrominerals in other countries (mg kg-1 wet wt).
| Country | Ca | K | Mg | Na | P |
| Mexico*(This study) | 217.15 | 2,740.97 | 225.08 | 405.58 | 156.90 |
| Brazila | 149.00 | 1,250.00 | 127.00 | 33.00 | 139.00 |
| Pakistanb | 17.70 | 149.00 | 9.57 | 14.70 | --- |
| Ivory Coasta | 145.00 | 1,050.00 | 206.00 | 33.70 | 117.00 |
Macroelements and some trace elements generally come from the soil, for the particular case of this study, Na, Ca and Mg concentrations above reference studies in other countries suggest the use in the state of Colima of irrigation waters with a high concentration of this elements (Pérez-Zamora, 2002).
Trace elements are shown in Table 5 with a decreasing trend Fe>Cu>Li>Ni>Zn>Ba>Mn>Be, in an average range from 0.05±0.02 to 2.4±0.52 mg kg-1 of fresh fruit.
Table 5 Trace elements (mg kg-1 wet wt) n=3.
| Municipality | Fe | Ni | Cu | Zn | Mn | Be | Li | Ba |
| Armeria | 1.67 | 0.56 | 2.64 | 0.93 | 1.00 | ND | 2.04 | 0.93 |
| Colima | 2.45 | 0.56 | 2.33 | 0.56 | 0.38 | 0.02 | 1.99 | ND |
| Comala | 3.13 | 0.37 | 1.86 | 0.37 | 0.18 | ND | 2.03 | 1.84 |
| Coquimatlán | 2.82 | 0.65 | 2.80 | 0.65 | 0.43 | 0.04 | 2.39 | 0.22 |
| Cuauhtémoc | 1.68 | 0.49 | 1.80 | 0.37 | 0.29 | 0.03 | 1.63 | 0.15 |
| Ixtlahuacán | 2.54 | 0.80 | 2.29 | 0.35 | 0.13 | 0.07 | 1.94 | 0.01 |
| Manzanillo | 2.65 | 0.69 | 1.84 | 0.36 | 0.32 | 0.06 | 1.67 | 0.17 |
| Minatitlán | 2.52 | 0.77 | 2.11 | 0.53 | 0.11 | 0.08 | 2.03 | ND |
| Tecomán | 1.76 | 0.75 | 1.71 | 0.27 | 0.14 | 0.07 | 1.43 | ND |
| Villa de Álvarez | 2.80 | 0.79 | 1.98 | 0.37 | 0.19 | 0.08 | 1.91 | 0.14 |
| Mean | 2.40 | 0.64 | 2.14 | 0.48 | 0.32 | 0.05 | 1.90 | 0.35 |
| (SD) | (0.52) | (0.14) | (0.37) | (0.20) | (0.26) | (0.02) | (0.27) | (0.67) |
ND= Not Detected SD= Standard Deviation.
The comparison of results of trace metals obtained in this study with those previously published are presented in Table 6, minerals with lower concentrations were found for Iron and Beryllium with 2.40±0.52 and 0.05±0.02 mg kg-1 of fresh fruit respectively. Up to this time, there were no reports on Li and Ba content in papaya fruits, values in this study were 1.9±0.27 mg kg-1 and 0.35±0.67 mg kg-1 of fresh fruit, therefore a comparison was not possible these results gave a framework of reference to know the detailed mineral content of this produce.
Table 6 Comparative values of trace elements in other studies (mg kg-1 wet wt).
| Country | Fe | Ni | Cu | Zn | Mn | Be |
|---|---|---|---|---|---|---|
| Mexico* | 2.40 | 0.64 | 2.14 | 0.48 | 0.32 | 0.05 |
| Brazila | 4.50 | 0.04 | 0.20 | 0.90 | 0.10 | --- |
| Pakistanb | 6.58 | --- | 0.77 | 26.20 | --- | --- |
| Chinac | --- | 0.24 | 0.34 | 1.96 | --- | --- |
| Indiad | 75.50 | 0.90 | 1.4 | 7.20 | 1.20 | 7.60 |
| Nigeriae | --- | 0.11 | 0.003 | 0.045 | --- | --- |
| Malaysiaf | --- | 0.65 | 3.48 | 8.13 | --- | --- |
| Ivory Coasta | 5.40 | 0.10 | 0.30 | 0.50 | 0.10 | --- |
| Bangladeshg | --- | 0.85 | 3.70 | --- | --- | --- |
ND= Not Detected --- = Not Analyzed.
*This study; a(Grembecka & Szefer, 2013); b(Fafar & Masud, 2003); c(Li, et al., 2012); d(Basha et al., 2014); e(Sobukola et al., 2010); f(Ang & Ng, 2000); g(Islam et al., 2015).
Values of trace elements were generally in the range of reported values in reference studies, these concentrations were due to soil and water characteristics of the place where fruits were produced and did not necessarily represent an indicator of the quality regarding fruits from other regions.
Of all the heavy metals analyzed in this study (Al, Cd, Co, Cr, Pb, Sb, Se, Sn, Tl and V), only Cadmium, Chrome and Lead were detected with an average concentration of 1.50±0.3 mg kg-1, 0.16±0.15 mg kg-1 and 0.35±0.15 mg kg-1 of fresh fruit respectively. Results for these three heavy metals determined in fruits sampled in the ten municipalities are shown in Table 7. The content of these metals was in a range of 1.03-2.04 mg kg-1 for Cd, 0.00-0.56 mg kg-1 for Cr and 0.20-0.64 mg kg-1 for Pb.
Table 7 Heavy metals (mg kg-1 wet wt) n=3.
| Municipality | Cd | Cr | Pb |
|---|---|---|---|
| Armería | 1.58 | 0.56 | 0.30 |
| Colima | 1.51 | ND | 0.64 |
| Comala | 1.66 | 0.18 | 0.55 |
| Coquimatlán | 1.74 | 0.22 | 0.28 |
| Cuauhtémoc | 1.13 | 0.08 | 0.20 |
| Ixtlahuacán | 1.49 | 0.13 | 0.31 |
| Manzanillo | 1.22 | 0.15 | 0.22 |
| Minatitlán | 1.55 | 0.09 | 0.48 |
| Tecomán | 1.03 | 0.08 | 0.22 |
| Villa de Álvarez | 2.04 | 0.11 | 0.27 |
| Mean | 1.50 | 0.16 | 0.35 |
| (SD) | (0.3) | (0.15) | (0.15) |
SD=Standard Deviation.
The comparison of heavy metals obtained in published studies are presented in Table 8, Pb and Cr content in this study was within the range found in fruits of these countries. Due to the Cd concentration was above the reference studies, it is necessary to identify the source of this metal in order to exhibit soil and water conditions in the State of Colima.
Table 8 Comparative values of heavy metals (mg kg-1 wet wt).
| Country | Pb | Cr | Cd | Al | As |
|---|---|---|---|---|---|
| Mexico (This study)* | 0.350 | 0.159 | 1.500 | ND | --- |
| Brazil | --- | 0.030 | --- | --- | --- |
| Pakistan | 0.640 | 0.130 | 0.340 | --- | --- |
| China | 0.051 | 0.109 | 0.002 | --- | --- |
| India | 0.900 | 1.700 | 0.023 | 47.5 | --- |
| Nigeria | 0.072 | --- | 0.003 | --- | --- |
| Malaysia | 1.380 | 0.580 | 0.550 | --- | --- |
| Ivory Coast | --- | 0.030 | --- | --- | --- |
| Bangladesh | 0.280 | 1.500 | 0.028 | --- | 0.22 |
ND= Not Detected.
----= Not Analyzed.
*This study; a(Grembecka & Szefer, 2013); b(Fafar & Masud, 2003); c(Li, et al., 2012); d(Basha et al., 2014); e(Sobukola et al., 2010); f(Ang & Ng, 2000); g(Islam et al., 2015).
Although K, Ca, Cu, Mg, Mn, Ba, Fe, Ni, Zn, Cr and Pb have been found in atmospheric particles in the state of Colima, with possible sources of emission such as: volcanic activity, volcanic ashes, automobile and industrial emissions (Miranda et al., 2004; Campos-Ramos et al., 2009), it was not possible to determine the influence of these sources on metal content in soil and water, which are transferred to food.
Health Risk Assessment
Daily Intake of Metals (DIM) and Health Risk Index (HRI).
The presence of Cadmium, Chrome and Lead detected in the present study urged to assess the health risk that implies these quantities in analyzed samples. Calculations obtained from the Daily Intake of Metals (DIM) and Health Risk Index (HRI) are shown in Table 9. The results are below the limit allowed by the Food and Agriculture Organization and the World Health Organization (FAO/WHO, 2010).
Table 9 Daily Intake of Metals (DIM) (µg kg-1 day-1) and Health Risk Index (HRI) in fruits of Carica papaya L.
| Municipality | Index | Cd | Cr | Pb | Total* |
|---|---|---|---|---|---|
| Armería | DIM | 3.68E-04 | 1.30E-01 | 6.92E-02 | |
| HRI | 3.68E-01 | 4.33E-02 | 1.73E-02 | 4.28E-01 | |
| Colima | DIM | 3.51E-01 | 0 | 1.49E-01 | |
| HRI | 3.51E-01 | 0 | 3.72E-02 | 3.88E-01 | |
| Comala | DIM | 3.86E-01 | 4.29E-02 | 1.29E-01 | |
| HRI | 3.86E-01 | 1.43E-02 | 3.22E-02 | 4.33E-01 | |
| Coquimatlán | DIM | 4.05E-01 | 5.06E-02 | 6.58E-02 | |
| HRI | 4.05E-01 | 1.69E-02 | 1.64E-02 | 4.38E-01 | |
| Cuauhtémoc | DIM | 2.63E-01 | 1.77E-02 | 4.61E-02 | |
| HRI | 2.63E-01 | 5.91E-03 | 1.15E-02 | 2.80E-01 | |
| Ixtlahuacán | DIM | 3.49E-01 | 2.98E-02 | 7.23E-02 | |
| HRI | 3.49E-01 | 9.92E-03 | 1.81E-02 | 3.77E-01 | |
| Manzanillo | DIM | 2.85E-01 | 3.40E-02 | 5.11E-02 | |
| HRI | 2.85E-01 | 1.13E-02 | 1.28E-02 | 3.09E-01 | |
| Minatitlán | DIM | 3.62E-01 | 2.05E-02 | 1.12E-01 | |
| HRI | 3.62E-01 | 6.85E-03 | 2.79E-02 | 3.97E-01 | |
| Tecomán | DIM | 2.41E-01 | 1.89E-02 | 5.05E-02 | |
| HRI | 2.41E-01 | 6.31E-03 | 1.26E-02 | 2.60E-01 | |
| Villa de Álvarez | DIM | 4.76E-01 | 2.57E-02 | 6.30E-02 | |
| HRI | 4.76E-01 | 8.58E-03 | 1.57E-02 | 5.00E-01 | |
| Mean | DIM | 3.48E-01 | 3.70E-02 | 8.07E-02 | |
| HRI | 3.48E-01 | 1.23E-02 | 2.02E-02 | 3.81E-01 |
*Values obtained in this study.
Conclusion
Results obtained for macrominerals and trace elements were within the range found in the studies cited in the comparative Tables. Papaya fruits commercialized in markets of the state of Colima were rich in Potassium and Sodium. Calculations of the Daily Intake of Metals (DIM) and of the Health Risk Index (HRI) were found below the value of 1, therefore Chrome, Cadmium and Lead contents in analyzed samples did not present any health risks for consumers.
Monitoring the content of potentially toxic metals is a highly important public health issue. Complementary studies are needed, in which soil, irrigation water, plant and produced fruits should be analyzed to identify the origin of the metals found and to assess their transference and bioaccumulation index.
