This paper is devoted to the chemical analysis of contaminated soils of India and the rice grown in the same area. Total reflection X-ray fluorescence spectroscopy is a well-established technique for elemental chemical analysis of environmental samples, and it can be a useful tool to assess food safety. Metals uptake in rice crop grown in soils from different areas was studied. In this work soil, rice husk and rice samples were analyzed after complete solubilization of samples by microwave acid digestion. Heavy metals concentration detected in rice samples decreases in the following order: Mn > Zn > Cu > Ni > Pb > Cr. The metal content in rice husk was higher than in rice. This study suggests, for the first time, a possible role of heavy metals filter played by rice husk. The knowledge of metals sequestration capability of rice husk may promote some new management practices for rice cultivation to preserve it from pollution.
Heavy-metal pollution of soil affects the quality of the environment leading to serious consequences. Heavy metals group includes Ag, Ba, Cd, Co, Cr, Mn, Hg, Mo, Ni, Pb, Cu, Sn, Tl, V, Zn, and some metalloids such as As, Sb, Bi, and Se. Arsenic, for example, is often considered as a heavy metal due to the similarity of its chemical properties and behavior with the other heavy metals. Heavy metals accumulation in soil, and in the environment in general, may be related to the phenomenon of bioaccumulation ability of living organisms, that is, increasing the concentration at human organism due to industrial activities and the food chain. The main sources of heavy-metal pollution in soil are irrigation, especially with sewage; solid-waste disposal, for example, sludge and compost refuse; the use of pesticides and fertilizers; and atmospheric deposition [
Plants acquire the necessary nutrients, such as N, P, and K, from the environment. However, they may also accumulate unnecessary and toxic metals, such as Pb and Cd. Several plants have the ability to accumulate high metal concentrations [
Rice is one of the most important and widespread cereals in the world. It is the staff of life for 3 billion people, mainly in Asia [
On this basis the presence of toxic heavy metals in rice, which may raise the metal daily intake, should be strongly avoided in order to prevent negative effects on human health. The following elements are considered macronutrients in rice and their content is usually in some %: P, S, K, Ca, and Mg. Other elements, like Mn, Fe, Cu, Zn, Se, and Ni, are classified as micronutrients and they are present in lower amount, while As, Cr, Pb, and Cd are undesirable elements because of their toxic effects even in very low quantity. As a consequence, it is crucially necessary to reduce possible accumulation effects in rice grains from the environment for safe food production. Great efforts are necessary to remediate polluted sites. Other approaches could be developed to reduce metals accumulation in edible parts of plants. For instance, favorable agronomic practices and chemical regulators may decrease plant heavy metals uptake. In this context it is important to identify which parts of the plant accumulate more toxic substances.
Rice husk (RH) is the external protecting covering of each rice grain. The chemical composition of RH varies from sample to sample depending on rice variety, climate, and origin. Organic compounds and water are the main components of RH (about 74%), followed by amorphous silica (between 15 and 22%) and other inorganic compounds (about 4%) such as Al2O3, Fe2O3, CaO, and MgO [
It is also known that the produced byproduct of rice husk is called rice husk ash (RHA). RHA is widely used by the steel industry in the production of high quality flat steel for automotive body panels [
It is very interesting to verify the higher capability of heavy accumulation by RH with respect to rice. This can play a fundamental role in the management of rice cultivation.
Elemental chemical analysis of rice is usually performed by normative techniques such as FAAS [
Elemental chemical analysis of soils coming from the central-east area of India, where soil contains high concentration of heavy metals, was performed. The state of Chhattisgarh (India) is rich in minerals such as iron, limestone, dolomite, coal, bauxite, garnet, quartz, marble, alexandrite, and diamonds. Because of the huge production of rice, Chhattisgarh district nickname is “rice bowl of Central India.” Industrial activities in this area increased a lot in the last years. In fact, the construction of new coal-fired power plants has increased up to 50% the production of ashes, which exposes the human and the environment to high pollution risks. Therefore, Raipur and Korba were chosen as the target cities of this study. Raipur is located at 21° 13′ 60 N and 81° 37′ 60 E, and hundreds varieties of rice grow. Different studies have already confirmed the presence of heavy metals in soils from this area, demonstrating a degradation of the environmental quality [
Type of samples and their corresponding numbers sampled from the studied areas.
City | Samples | Number of samples |
---|---|---|
Raipur | Soil | |
Raipur | A | 5 |
Raipur | B | 5 |
Raipur | Rice husk (RH) | 5 |
Raipur | Rice | 5 |
Korba | Soil | 5 |
Korba | Rice husk (RH) | 5 |
Korba | Rice | 5 |
Soil samples were homogenized through a mortar and dried for 90 min at 90°C. Samples were weighed before and after this process in order to determine their humidity. Rice samples were transported from India as they were collected. Rice grains were inside their husk. The separation of each rice grain from its outer shell (husk) was carried out manually in the first step of sample preparation. Some differences were noticed at a glance. Rice samples had different husk colors, from green to yellow, and crop dimensions.
About 0.5 g soil sample was added to 9 mL of nitric acid 65% (Fluka), 3 mL of hydrofluoric acid (Fluka), and 2 mL of hydrochloric acid 37% (Fluka) in Teflon vessels. HF was necessary to perform total solubilization of soil, probably due to the high content of silicates. This procedure was performed according to US-EPA 3050B method [
Chemical analysis of the solutions, obtained by digestion, was performed by means of TXRF spectroscopy. Quantitative analysis was performed by the internal standard addition procedure [
Humidity in Raipur soils was higher than in Korba samples. It ranges from 1.4 to 6.7%, while in Korba soils humidity was in the interval from 1.7 to 2.9%.
TXRF spectra of soil samples from Korba and Raipur are shown in Figure
TXRF spectra of soil samples from Korba (black) and Raipur (grey).
TXRF measurement was performed in air; for this reason it is not possible to give an accurate estimation of the content of lighter elements such as Al, P, and S. Their concentration may be underestimated and higher standard deviations may occur (about 20% in the case of Al). The content of Fe is higher compared to the other elements. For this reason, fitting of TXRF spectra was performed considering the pile up peak of Fe K
Results of quantitative analysis of soil samples are reported in Table
Elemental concentration (mg/kg) in soil samples from Korba and Raipur. Results are expressed as the average ± standard deviation.
Sample | Elements concentration (mg/Kg) | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
K | Ca | Ti | V | Cr | Mn | Fe | Ni | Cu | Zn | As | Ba | Sr | Pb | Bi | |
Korba | |||||||||||||||
S 1_K | 4524 ± 203 | 2560 ± 297 | 1550 ± 85 | 14 ± 1 | 22 ± 1 | 254 ± 12 | 7071 ± 309 | 9 ± 1 | 11 ± 1 | 52 ± 3 | 4 ± 1 | 152 ± 18 | 28 ± 2 | 11 ± 1 | n.d. |
S 2_K | 3829 ± 175 | 1448 ± 463 | 1562 ± 68 | 17 ± 2 | 25 ± 1 | 230 ± 10 | 8409 ± 379 | 10 ± 1 | 10 ± 1 | 58 ± 3 | 3 ± 1 | 76 ± 9 | 14 ± 2 | 12 ± 1 | n.d. |
S 3_K | 5705 ± 447 | 1101 ± 417 | 1572 ± 72 | 15 ± 2 | 19 ± 1 | 83 ± 4 | 5676 ± 246 | 10 ± 1 | 6 ± 1 | 14 ± 1 | 4 ± 1 | 57 ± 8 | 3 ± 0.1 | 10 ± 1 | n.d. |
S 4_K | 5031 ± 239 | 421 ± 25 | 1350 ± 59 | 15 ± 1 | 24 ± 1 | 102 ± 4 | 7257 ± 316 | 12 ± 1 | 7 ± 1 | 15 ± 1 | 5 ± 1 | 117 ± 13 | 11 ± 1 | 11 ± 1 | n.d. |
S 5_K | 6217 ± 511 | 441 ± 34 | 1293 ± 63 | 11 ± 1 | 15 ± 1 | 143 ± 7 | 5781 ± 254 | 7 ± 1 | 6 ± 1 | 22 ± 1 | 5 ± 1 | 136 ± 10 | 15 ± 1 | 13 ± 1 | n.d. |
Raipur | |||||||||||||||
S 1A_R | 7617 ± 391 | 2660 ± 1637 | 4337 ± 197 | 61 ± 6 | 112 ± 6 | 1455 ± 66 | 38863 ± 1737 | 39 ± 2 | 34 ± 2 | 60 ± 4 | 15 ± 1 | 166 ± 28 | 23 ± 6 | 64 ± 5 | 4 ± 1 |
S 1B_R | 8117 ± 356 | 786 ± 57 | 4893 ± 213 | 55 ± 4 | 120 ± 5 | 1055 ± 46 | 39578 ± 1716 | 45 ± 2 | 37 ± 2 | 60 ± 2 | 12 ± 2 | 162 ± 12 | 16 ± 1 | 55 ± 5 | 5 ± 1 |
S 2A_R | 6172 ± 318 | 1088 ± 228 | 4610 ± 222 | 65 ± 5 | 111 ± 5 | 973 ± 46 | 38183 ± 1671 | 45 ± 3 | 34 ± 2 | 60 ± 5 | 13 ± 2 | 160 ± 22 | 20 ± 3 | 46 ± 5 | 5 ± 1 |
S 2B_R | 4895 ± 226 | 1199 ± 66 | 4716 ± 207 | 60 ± 4 | 127 ± 6 | 463 ± 20 | 37942 ± 1647 | 49 ± 2 | 34 ± 1 | 51 ± 2 | 15 ± 2 | 158 ± 18 | 21 ± 1 | 46 ± 5 | 5 ± 1 |
S 3A_R | 9251 ± 477 | 837 ± 151 | 5246 ± 248 | 107 ± 10 | 145 ± 7 | 1855 ± 81 | 32937 ± 1437 | 80 ± 4 | 43 ± 2 | 60 ± 3 | 21 ± 3 | 170 ± 42 | 16 ± 2 | 55 ± 8 | 5 ± 2 |
S 3B_R | 9149 ± 400 | 786 ± 42 | 5959 ± 258 | 116 ± 7 | 121 ± 5 | 1389 ± 61 | 27203 ± 1331 | 75 ± 3 | 46 ± 2 | 50 ± 2 | 26 ± 1 | 147 ± 22 | 11 ± 2 | 44 ± 2 | 4 ± 1 |
S 4A_R | 5318 ± 233 | 1078 ± 115 | 4993 ± 218 | 74 ± 4 | 131 ± 6 | 1304 ± 58 | 42808 ± 1863 | 55 ± 2 | 36 ± 2 | 54 ± 7 | 18 ± 2 | 191 ± 13 | 17 ± 1 | 54 ± 5 | 5 ± 2 |
S 4B_R | 5497 ± 270 | 824 ± 137 | 5270 ± 254 | 116 ± 11 | 122 ± 6 | 1984 ± 90 | 31119 ± 1360 | 80 ± 5 | 49 ± 14 | 56 ± 3 | 30 ± 3 | 129 ± 30 | 11 ± 4 | 55 ± 6 | 4 ± 1 |
S 5A_R | 7477 ± 510 | 1275 ± 594 | 4672 ± 205 | 127 ± 8 | 174 ± 8 | 2597 ± 113 | 43853 ± 2203 | 79 ± 4 | 44 ± 2 | 54 ± 6 | 36 ± 3 | 261 ± 116 | 17 ± 6 | 69 ± 3 | 5 ± 1 |
S 5B_5 | 8599 ± 422 | 2557 ± 237 | 5285 ± 232 | 111 ± 6 | 155 ± 7 | 1701 ± 75 | 40033 ± 1767 | 71 ± 3 | 43 ± 2 | 55 ± 2 | 24 ± 3 | 427 ± 54 | 31 ± 3 | 67 ± 6 | 8 ± 1 |
Descriptive statistics of elemental content in soil samples is reported in Table
Descriptive statistics results of elemental chemical analysis for Korba and Raipur soils.
K | Ca | Ti | V | Cr | Mn | Fe | Ni | Cu | Zn | As | Ba | Rb | Sr | Pb | Bi | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Korba | ||||||||||||||||
Mean | 5061.10 | 1195.82 | 1465.22 | 14.38 | 20.78 | 162.39 | 6838.82 | 9.54 | 7.96 | 32.20 | 4.20 | 107.51 | 23.62 | 14.24 | 11.35 | n.d. |
SD | 942.97 | 880.66 | 133.32 | 2.29 | 4.10 | 76.01 | 1136.39 | 1.90 | 2.29 | 21.11 | 0.64 | 39.98 | 7.20 | 8.98 | 1.20 | n.d. |
Min | 3829.12 | 420.76 | 1292.66 | 11.08 | 14.56 | 82.90 | 5676.19 | 6.54 | 5.95 | 14.15 | 3.38 | 56.99 | 13.81 | 3.16 | 9.85 | n.d. |
Max | 6216.60 | 2559.93 | 1571.93 | 17.32 | 24.68 | 253.70 | 8409.31 | 11.62 | 10.84 | 58.18 | 4.86 | 171.60 | 30.73 | 27.82 | 12.80 | n.d. |
Raipur | ||||||||||||||||
Mean | 7209.17 | 1309.09 | 4988.11 | 89.34 | 131.88 | 1477.54 | 37201.98 | 61.84 | 39.59 | 55.86 | 20.96 | 197.05 | 26.24 | 18.45 | 55.45 | 5.11 |
SD | 1628.34 | 707.36 | 471.33 | 28.31 | 20.11 | 596.58 | 5189.52 | 16.60 | 5.91 | 3.86 | 8.05 | 88.00 | 16.64 | 6.32 | 8.94 | 1.18 |
Min | 4895.48 | 785.77 | 4336.85 | 55.44 | 111.48 | 462.53 | 27202.51 | 39.34 | 31.09 | 50.03 | 11.90 | 129.43 | 10.23 | 10.76 | 43.55 | 3.83 |
Max | 9251.30 | 3659.98 | 5958.69 | 126.84 | 173.61 | 2579.07 | 43354.00 | 79.93 | 48.51 | 60.11 | 35.68 | 427.57 | 71.32 | 32.75 | 69.21 | 8.15 |
A comparison of our results with the guidelines and limits proposed for the determination of heavy metals pollution [
A more detailed comparison of our data with those obtained in other studies of soil contamination in the same area reveals a good agreement. The comparison with data reported by Kabata Pendias for uncontaminated soils (Cr 0.4–29 mg/kg, Mn 25–8000 mg/kg, Ni 3–150 mg/kg, Cu 0.5–135 mg/kg, Zn 1–750 mg/kg, and Pb 0.6–63 mg/kg) [
Statistical analysis was used to evaluate the correlation of the elements present in soil. Cluster analysis was used to highlight the differences between soils from Korba and Raipur. Hierarchical division was performed using the Ward method, which is based on the analysis of variances instead of distances. The varimax rotation with Kaiser normalization method was used for factor analysis. By extracting the eigenvalues, the number of significant factors was determined. Data treatment was performed using the JMP 10 software. Results of cluster analysis are reported in Figure
Dendrogram of cluster analysis for Korba (red) and Raipur (green) samples.
Results of factor analysis show that the three eigenvalues explain 90,18% of the variance. Therefore, they were selected for further factor analysis. The loadings of elements with respect to each one of the three identified factors are reported in Table
Rotated component matrix for soil samples.
Variables | Rotated factor | ||
---|---|---|---|
1 | 2 | 3 | |
Al | 0.4877 | 0.3792 | 0.7279 |
K | 0.5859 | −0.0676 | 0.5477 |
Ca | 0.0419 | 0.9249 | 0.1358 |
Ti | 0.9527 | 0.1259 | 0.0972 |
V | 0.9167 | 0.0068 | 0.3339 |
Cr | 0.9421 | 0.1997 | 0.203 |
Mn | 0.8834 | 0.0792 | 0.2768 |
Fe | 0.8929 | 0.3231 | 0.0015 |
Ni | 0.9423 | −0.0077 | 0.2811 |
Cu | 0.9715 | 0.1256 | 0.1389 |
Zn | 0.6599 | 0.5904 | −0.1872 |
As | 0.8862 | −0.04 | 0.29 |
Rb | 0.0402 | 0.147 | 0.9675 |
Sr | 0.0761 | 0.9325 | 0.2809 |
Ba | 0.4065 | 0.5243 | 0.6689 |
Pb | 0.9163 | 0.287 | 0.1481 |
Bi | 0.8439 | 0.3457 | 0.2535 |
Variance explained by each factor | |||
---|---|---|---|
Factor | Variance | Percent | Cum. percent |
Factor 1 | 9.5731 | 56.313 | 56.313 |
Factor 2 | 2.9045 | 17.085 | 73.398 |
Factor 3 | 2.8535 | 16.785 | 90.183 |
TXRF spectra of rice and rice husk are shown in Figure
Elemental concentration in rice (R) and rice husk (RH) samples from Korba and Raipur.
Sample | Elemental concentration (mg/Kg) | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
K | Ca | Ti | Cr | Mn | Fe | Ni | Cu | Zn | Rb | Sr | Ba | Pb | |
Korba | |||||||||||||
1 R_K | 2179 ± 122 | 267 ± 67 | 1.9 ± 0.4 | 0.0 ± 0.0 | 44 ± 2 | 18 ± 3 | 0.4 ± 0.1 | 2.2 ± 0.2 | 29 ± 1 | 18.6 ± 1.0 | 0.67 ± 0.14 | n.d. | 0.27 ± 0.01 |
2 R_K | 2911 ± 160 | 225 ± 19 | 0.5 ± 0.3 | 0.0 ± 0.0 | 29 ± 1 | 19 ± 2 | 0.9 ± 0.1 | 2.4 ± 0.1 | 30 ± 1 | 35.2 ± 1.7 | 0.33 ± 0.05 | n.d. | 0.51 ± 0.03 |
3 R_K | 2603 ± 184 | 227 ± 17 | 4.0 ± 0.3 | 0.0 ± 0.0 | 32 ± 1 | 21 ± 1 | 0.5 ± 0.1 | 3.0 ± 0.2 | 39 ± 2 | 4.2 ± 0.3 | 0.52 ± 0.03 | n.d. | 0.25 ± 0.02 |
4 R_K | 1604 ± 111 | 223 ± 20 | 1.4 ± 0.4 | 0.0 ± 0.0 | 27 ± 1 | 13 ± 1 | 2.0 ± 0.6 | 3.0 ± 0.2 | 22 ± 1 | 5.7 ± 0.3 | 0.29 ± 0.02 | n.d. | 0.08 ± 0.02 |
5 R_K | 2162 ± 113 | 175 ± 11 | 0.7 ± 0.2 | 0.0 ± 0.0 | 24 ± 1 | 15 ± 1 | 0.4 ± 0.1 | 2.5 ± 0.1 | 24 ± 1 | 22.5 ± 1.0 | 0.33 ± 0.01 | n.d. | 0.13 ± 0.01 |
1 RH_K | 4152 ± 303 | 1500 ± 68 | 2.8 ± 0.9 | 0.4 ± 0.1 | 325 ± 15 | 93 ± 4 | 0.6 ± 0.1 | 2.0 ± 0.1 | 32 ± 1 | 22.3 ± 1.2 | 4.76 ± 0.22 | 32 ± 2 | 0.41 ± 0.04 |
2 RH_K | 3894 ± 311 | 1277 ± 61 | 7.3 ± 2.4 | 0.0 ± 0.0 | 174 ± 8 | 161 ± 11 | 3.3 ± 0.2 | 1.8 ± 0.4 | 26 ± 1 | 28.7 ± 2.0 | 2.68 ± 0.13 | 15 ± 1 | 0.47 ± 0.03 |
3 RH_K | 2277 ± 152 | 1485 ± 106 | 59.9 ± 45.6 | 0.9 ± 0.2 | 210 ± 9 | 409 ± 26 | 1.0 ± 0.1 | 2.1 ± 0.2 | 33 ± 3 | 3.7 ± 0.3 | 4.49 ± 0.23 | 26 ± 2 | 0.70 ± 0.07 |
4 RH_K | 4441 ± 196 | 1072 ± 47 | 6.0 ± 2.4 | 0.2 ± 0.1 | 213 ± 9 | 184 ± 9 | 2.6 ± 0.1 | 2.2 ± 0.1 | 28 ± 1 | 11.1 ± 0.5 | 2.24 ± 0.10 | 25 ± 1 | 0.43 ± 0.02 |
5 RH_K | 3782 ± 167 | 948 ± 61 | 2.3 ± 0.3 | 0.0 ± 0.0 | 206 ± 9 | 93 ± 4 | 0.6 ± 0.1 | 1.9 ± 0.1 | 27 ± 2 | 23.4 ± 1.1 | 2.89 ± 0.15 | 30 ± 1 | 1.02 ± 0.05 |
Raipur | |||||||||||||
1 R_R | 3021 ± 221 | 395 ± 54 | 2.4 ± 1.1 | 0.3 ± 0.1 | 21 ± 1 | 33 ± 22 | 0.6 ± 0.1 | 3.4 ± 0.4 | 30 ± 2 | 0.6 ± 0.03 | 0.31 ± 0.03 | n.d. | 0.38 ± 0.02 |
2 R_R | 2201 ± 101 | 232 ± 12 | 0.8 ± 0.2 | 0.0 ± 0.0 | 20 ± 1 | 13 ± 1 | 0.2 ± 0.1 | 1.7 ± 0.1 | 19 ± 1 | 3.2 ± 0.2 | 0.38 ± 0.02 | n.d. | 0.45 ± 0.04 |
3 R_R | 2621 ± 120 | 347 ± 98 | 3.2 ± 0.4 | 0.3 ± 0.1 | 33 ± 1 | 24 ± 1 | 0.4 ± 0.1 | 2.3 ± 0.2 | 31 ± 2 | 1.1 ± 0.1 | 0.55 ± 0.04 | n.d. | 0.40 ± 0.03 |
4 R_R | 2441 ± 134 | 345 ± 40 | 2.2 ± 0.5 | 0.2 ± 0.1 | 35 ± 2 | 22 ± 1 | 1.4 ± 0.1 | 3.1 ± 0.2 | 30 ± 5 | 6.7 ± 0.3 | 0.49 ± 0.02 | n.d. | 0.26 ± 0.02 |
5 R_R | 2295 ± 119 | 453 ± 182 | 1.7 ± 0.7 | 1.6 ± 0.7 | 26 ± 1 | 32 ± 2 | 1.8 ± 0.1 | 2.3 ± 0.1 | 25 ± 4 | 4.9 ± 0.3 | 0.59 ± 0.12 | n.d. | 0.24 ± 0.04 |
1 RH_R | 6134 ± 284 | 1407 ± 237 | 24.8 ± 7.7 | 1.7 ± 0.9 | 159 ± 7 | 747 ± 43 | 0.9 ± 0.3 | 3.1 ± 0.3 | 32 ± 3 | 1.3 ± 0.1 | 2.89 ± 0.15 | 5 ± 1 | 4.04 ± 0.18 |
2 RH_R | 5088 ± 320 | 1727 ± 284 | 11.6 ± 2.8 | 1.0 ± 0.2 | 155 ± 8 | 601 ± 32 | 0.8 ± 0.4 | 2.2 ± 0.1 | 38 ± 8 | 4.8 ± 0.3 | 4.24 ± 0.56 | 5 ± 1 | 1.04 ± 0.12 |
3 RH_R | 5474 ± 273 | 2165 ± 284 | 6.8 ± 0.7 | 0.8 ± 0.1 | 263 ± 12 | 589 ± 26 | 0.5 ± 0.1 | 2.4 ± 0.1 | 34 ± 2 | 1.8 ± 0.4 | 5.63 ± 0.26 | 8 ± 2 | 0.76 ± 0.05 |
4 RH_R | 4866 ± 214 | 1367 ± 113 | 11.4 ± 0.7 | 43.3 ± 2.3 | 398 ± 18 | 957 ± 50 | 38.0 ± 1.9 | 2.9 ± 0.2 | 33 ± 3 | 9.2 ± 0.4 | 3.13 ± 0.19 | 14 ± 1 | 1.05 ± 0.07 |
5 RH_R | 5930 ± 341 | 1441 ± 220 | 42.7 ± 11.5 | 8.4 ± 0.5 | 232 ± 10 | 918 ± 167 | 13.0 ± 0.6 | 2.7 ± 0.8 | 33 ± 4 | 7.1 ± 0.3 | 3.62 ± 0.23 | 6 ± 1 | 0.87 ± 0.34 |
Spectra of rice husk (black) and rice (gray) sample 2 from Korba measured by S2 Picofox.
Elemental composition of rice husk and rice is similar for all the studied samples, even if Ca, Ti, Mn, Fe, and Pb are higher in RH with respect to rice. The concentration of metals in the two matrices is usually correlated. In the samples from Korba the highest concentrations of Ti, Fe, and Zn were detected in sample 3 for both the analyzed matrices (3R_K and 3RH_K) and the highest concentration of Ca and Mn in sample 1 (1R_K and 1RH_K). In the samples from Raipur the highest concentrations of Fe and Zn are found in sample 3 (3R_R and 3RH_R), while the highest content of Mn was in sample 4 (4R_R and 4RH_R). Rice husk samples of Korba contain Cr that is not detected in rice, while Cr is present in both the matrices collected in Raipur, with the usual correlation. This can be due to the higher concentration of Cr in Raipur than Korba soils. The correlation observed for the other elements is not present in the case of Pb. Indeed, the highest value of Pb for rice husk samples is present in sample 5RH_K, while the highest value of Pb for rice is present in sample 2R_K. A similar behavior is observed for Ca and Ti in the samples from Raipur.
Descriptive statistics of elemental content in rice and rice husk samples is reported in Table
Descriptive statistics results of elemental chemical analysis for rice and rice husk from Korba and Raipur.
K | Ca | Ti | Cr | Mn | Fe | Ni | Cu | Zn | Rb | Sr | Ba | Pb | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Korba | |||||||||||||
Rice | |||||||||||||
Mean | 2291.61 | 223.52 | 1.71 | 0.00 | 31.19 | 17.25 | 0.85 | 2.61 | 28.92 | 17.24 | 0.43 | n.d. | 0.25 |
SD | 495.62 | 32.67 | 1.41 | 0.00 | 7.63 | 3.14 | 0.67 | 0.36 | 6.64 | 12.79 | 0.16 | n.d. | 0.17 |
Min | 1603.61 | 175.06 | 0.47 | 0.00 | 23.97 | 13.20 | 0.39 | 2.22 | 22.18 | 4.18 | 0.29 | n.d. | 0.08 |
Max | 2910.56 | 267.13 | 4.02 | 0.00 | 43.67 | 20.86 | 2.01 | 3.00 | 39.09 | 35.19 | 0.67 | n.d. | 0.51 |
RH | |||||||||||||
Mean | 3709.19 | 1256.24 | 15.67 | 0.32 | 225.62 | 188.03 | 1.62 | 2.01 | 29.49 | 17.85 | 3.41 | 25.62 | 0.61 |
SD | 839.90 | 245.48 | 24.83 | 0.09 | 57.67 | 130.03 | 1.22 | 0.13 | 3.22 | 10.18 | 1.14 | 6.45 | 0.26 |
Min | 2277.06 | 947.76 | 2.30 | 0.00 | 174.33 | 92.74 | 0.62 | 1.85 | 25.87 | 3.69 | 2.24 | 15.40 | 0.41 |
Max | 4440.80 | 1499.97 | 59.92 | 0.90 | 325.00 | 408.97 | 3.25 | 2.17 | 33.31 | 28.69 | 4.76 | 31.96 | 1.02 |
Raipur | |||||||||||||
Rice | |||||||||||||
Mean | 2515.78 | 354.45 | 2.09 | 0.47 | 26.85 | 24.73 | 0.88 | 2.56 | 27.07 | 3.29 | 0.46 | n.d. | 0.34 |
SD | 323.75 | 81.34 | 0.88 | 0.11 | 6.91 | 8.24 | 0.66 | 0.71 | 5.09 | 2.56 | 0.12 | n.d. | 0.09 |
Min | 2200.82 | 231.92 | 0.84 | 0.00 | 19.66 | 12.67 | 0.22 | 1.66 | 19.09 | 0.58 | 0.31 | n.d. | 0.24 |
Max | 3020.55 | 452.90 | 3.24 | 1.60 | 34.50 | 32.61 | 1.77 | 3.44 | 31.36 | 6.69 | 0.59 | n.d. | 0.45 |
RH | |||||||||||||
Mean | 5498.53 | 1621.25 | 19.48 | 11.02 | 241.33 | 762.37 | 10.64 | 2.66 | 34.12 | 4.84 | 3.90 | 7.67 | 1.55 |
SD | 538.45 | 335.42 | 14.63 | 18.30 | 99.08 | 172.01 | 6.21 | 0.35 | 2.13 | 3.39 | 1.09 | 3.86 | 1.39 |
Min | 4866.02 | 1366.79 | 6.83 | 0.80 | 155.14 | 588.74 | 0.52 | 2.19 | 32.18 | 1.31 | 2.89 | 4.67 | 0.76 |
Max | 6134.38 | 2165.07 | 42.73 | 43.26 | 397.79 | 956.78 | 38.05 | 3.08 | 37.65 | 9.21 | 5.63 | 14.17 | 4.04 |
Metal uptake is higher for plants germinated in soils enriched with metals from anthropogenic factors. Therefore, bioaccumulation ability of plants is one of the most critical problems faced in agriculture and environmental studies. Transfer factor (TF) is an indicator of the plant species ability or tendency to uptake a certain element from the soil [
TFs calculated for rice and RH using the average values of elemental concentration in rice, RH, and soils of Korba and Raipur are shown in Figure
Concentration of hazardous elements in rice samples reported in different literature studies: (a) arithmetic means; (b) arithmetic standard deviations; (c) [
Element | Area |
|
AM (a) | ASD (b) | MIN | MAX |
---|---|---|---|---|---|---|
Cu | Taizhou | 13 | 4260 | 826 | 3037 | 5184 |
Commercial rice, China | 5 | 3326 | 774 | 2812 | 4478 | |
Vietnam (c) | 31 | 2600 | 1100 | 5800 | ||
Bangladesh (d) | — | — | — | — | ||
Hangzhou (e) | — | — | — | — | ||
Raipur | 5 | 2560 | 710 | 1662 | 3438 | |
Korba | 5 | 2610 | 360 | 2222 | 2995 | |
|
||||||
Pb | Taizhou | 13 | 2042 | 2070 | 256 | 2602 |
Commercial rice, China | 4 | 356 | 267 | 167 | 745 | |
Vietnam (c) | — | — | — | — | ||
Bangladesh (d) | 3 | 2370.0 | 1980.0 | 2010.0 | 2400.0 | |
Hangzhou (e) | 5 | 131 | 103 | 45 | 308 | |
Raipur | 5 | 340 | 90 | 235 | 452 | |
Korba | 5 | 250 | 170 | 78 | 514 | |
|
||||||
Ni | Taizhou | 13 | 761 | 391 | 339 | 1134 |
Commercial rice, China | 4 | 476 | 276 | 201 | 818 | |
Vietnam (c) | 31 | 869 | <100 | 2022 | ||
Bangladesh (d) | — | — | — | — | ||
Hangzhou (e) | — | — | — | — | ||
Raipur | 5 | 880 | 660 | 216 | 1770 | |
Korba | 5 | 850 | 670 | 387 | 2009 | |
|
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Mn | Taizhou | 13 | 28640 | 5570 | 21977 | 37490 |
Commercial rice, China | 4 | 9363 | 3288 | 5804 | 12708 | |
Vietnam (c) | 31 | 9900 | 5900 | 16300 | ||
Bangladesh (d) | — | — | — | — | ||
Hangzhou (e) | — | — | — | — | ||
Raipur | 5 | 2685 | 6910 | 19700 | 34500 | |
Korba | 5 | 31200 | 7600 | 24000 | 43700 | |
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Cr | Taizhou | 13 | 107 | 83 | 6 | 279 |
Commercial rice, China | 4 | 199 | 157 | 62 | 424 | |
Vietnam (c) | — | — | — | — | ||
Bangladesh (d) | 3 | 740 | 340 | 650 | 830 | |
Hangzhou (e) | — | — | — | — | ||
Raipur | 5 | 470 | 110 | 0 | 1600 | |
Korba | 5 | n.d. | n.d. | n.d. | n.d. |
Transfer factors calculated for rice and rice husk samples with respect to soil samples from Korba and Raipur.
Despite all the reported data of metal content in rice, according to the national standard for safety milled rice criteria [
Statistical analysis does not show any significant difference between rice and rice husk samples of the two areas of interest.
Figure
Concentration of elements in soil, rice husk, and rice samples from Korba and Raipur.
This work reports the chemical composition study of soils, rice, and rice husk, from Korba and Raipur (India), by means of TXRF. Results show some metals uptake from soil to rice, in particular Pb and Cr from the Raipur region. The novelty of this study is the chemical characterization of rice, made in parallel with the analysis of soils and corresponding rice husk. A detailed analysis of all the data shows that rice husk accumulates more heavy metals than rice, suggesting a possible barrier effect of the husk. Despite that, dedicated studies should be done to verify the clear role of husk and other parameters, such as rice species, soils characteristics (pH, clay content, and organic matter), and other variables. Based on the extremely interesting results obtained in this study, some approaches may be developed to promote low metals accumulation in rice.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This study was supported by LIFE+, the financial instrument of the European Community to support environmental projects (LIFE+ 2011 Project ENV/IT/000256). The authors are grateful to Directorate-General Environment, European Commission for inclusion of COSMOS-RICE Project in Science for Environment Policy, Information Service (see