4.2. Heavy metals in plants and factors affecting metal uptake by plants
It is well known that concentrations of Cd in edible vegetables range from 0.05 to 0.9 μg g−1
(DW: dry weight) and leafy plants such as lettuce, cabbage, spinach contain relatively higher Cd than grain or fruit plants such as apple, barley, corn, oat and rice [20
]. Although Cd concentrations in plants grown on uncontaminated or unmineralized soils generally do not exceed 1.0 μg g−1
], over 1 μg g−1
(DW) has been found in some plant leaves grown on contaminated soils from mining activities [11
]. In the study area, the maximum Cd levels of 2.2 μg g−1
(DW) was found in spring onion. Grain samples (corn and jujube), however, contained relatively lower Cd concentrations than leafy samples (spybean and spring onion) (p < 0.05). In addition, ratios of average Cd contents in plants sampled in the mining area to those in the control area ranged from 1.1 in jujube grain to 4.2 in spring onion. Thus, plants grown in the mining area contained high Cd concentrations compared to those in the control area, especially in red peppers, soybean leaves and spring onions (p < 0.05).
Although Cu is essential for plant growth, a very small amount of Cu is required by plants, for example, 5 to 20 μg g−1
(DW) in plant tissue [18
]. However, over 20 μg g−1
(DW) can be found in plants from contaminated area, especially plant roots grown in mining and smelting sites [11
]. In the study area, average Cu concentrations in plants grown in the mining area ranged from 8.95 μg g−1
(DW) in corn grain to 26.4 μg g−1
(DW) in spring onion. Although no Cu toxicity was found, most plant samples exceeded 20 μg g−1
(DW), with the exception of grain samples.
Plant Pb content is generally very low due to its low bioavailability. Lead concentrations in various plants range from 0.01 to 3.85 μg g−1
(DW), with an average value of 0.05 μg g−1
]. Average concentrations of Pb in plant samples from the mining area ranged from 0.19 μg g−1
(DW) in corn grain to 4.23 μg g−1
(DW) in spring onions. In addition, ratios of mean Pb concentrations in plants sampled in the mining area to those in the control area ranged from 1.2 in jujube grain to 3.2 in red peppers.
Zinc is also one of micronutrients essential for normal plant growth, but only a small amount of Zn is required (25∼150 μg g−1
in dry tissue) [18
]. In the study area, the maximum Zn content was found in spring onion with 383 μg g−1
(DW). In comparison with the normal amount of Zn for plant growth (25∼150 μg g−1
), soybean leaves and spring onions have concentrations exceeding the range. Other plants, however, usually approximated to normal plant growth. In conclusion, this study confirms that soybean and perilla leaves have more metals than corn and jujube grains. Metal concentrations determined from plant samples of the study area decreased in the order spring onions > soybean leaves > perilla leaves > red pepper > corn grain ≈ jujube grain.
Metal uptake by plants can be affected by several factors including metal concentrations in soils, soil pH, cation exchange capacity, organic matter content, types and varieties of plants, and plant age. It is generally accepted that the metal concentration in soil is the dominant factor [7
]. Relationships between total metal contents in plants and surface soils are shown in Figure 3
. Levels of most metals in plants were highly comparable with those of soil counterparts, although the gradient can differ between plant species. Metals in corn and jujube grains, however, did not show any significant correlations with those of soils.
As mentioned above, there is a combination of factors affecting metal uptake by plants. Thus, stepwise linear multiple regression method was applied to find the dominant factors influencing metal uptake by plants, such application was extended further to predict metal concentrations in plants under these specific soils and climatic conditions. Obtaining a best fit regression equation is undertaken by a step-by-step procedure. The first independent variable was always total metal content in surface soils. From the correlation matrix, the second major factor was found, and the regression equation was calculated using a statistical package. At every stage, the significance of the equation was tested by the coefficient of determination (r2) and probability (P). If the equation was not significant, i.e., a low r-squared value or high probability, other factors were used to obtain the best fit regression equation for predicting metal concentrations in plants.
The results of linear multiple regressions are presented in Table 5
. Total metal concentrations in soil are the main factor, being correlated positively with metals in plants on each occasion. In addition, soil pH, correlated negatively with metals in plants, played an important role in governing metal uptake by plants. Other factors such as cation exchange capacity, loss-on-ignition and soil texture also contributed to the prediction of metal concentrations in plants in some cases.