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Frontiers of Environmental Science & Engineering

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Front. Environ. Sci. Eng.    2020, Vol. 14 Issue (6) : 114    https://doi.org/10.1007/s11783-020-1331-0
RESEARCH ARTICLE
Predicting non-carcinogenic hazard quotients of heavy metals in pepper (Capsicum annum L.) utilizing electromagnetic waves
Marzieh Mokarram1(), Hamid Reza Pourghasemi2, Huichun Zhang3()
1. Department of Range and Watershed Management, College of Agriculture and Natural Resources of Darab, Shiraz University, Shiraz 71946-84471, Iran
2. Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz 71441-65186, Iran
3. Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
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Abstract

• There was significant absorption of heavy metals by the pepper in contaminated soils.

• The target hazard quotient (THQ) indices followed the order of Pb>Zn>>Cd » Ni.

• Relationships exist between contaminated plants and electromagnetic wave.

• PCA and random search can select the main spectra and predict THQ for each element.

Given the tendency of heavy metals to accumulate in soil and plants, the purpose of this study was to determine the contamination levels of Cd, Ni, Pb, and Zn on peppers (leaves and fruit) grown in contaminated soils in industrial centers. For this purpose, we measured the uptake of the four heavy metals by peppers grown in the heavy metal contaminated soils throughout the four growth stages: two-leaf, growth, flowering, and fruiting, and calculated various vegetation indices to evaluate the heavy metal contamination potentials. Electromagnetic waves were also applied for analyzing the responses of the target plants to various heavy metals. Based on the relevant spectral bands identified by principal component analysis (PCA) and random search methods, a regression method was then employed to determine the most optimal spectral bands for estimating the target hazard quotient (THQ). The THQ was found to be the highest in the plants contaminated by Pb (THQ= 62) and Zn (THQ= 5.07). The results of PCA and random search indicated that the spectra at the bands of b570, b650, and b760 for Pb, b400 and b1030 for Ni, b400 and b880 for Cd, and b560, b910, and b1050 for Zn were the most optimal spectra for assessing THQ. Therefore, in future studies, instead of examining the amount of heavy metals in plants by chemical analysis in the laboratory, the responses of the plants to the electromagnetic waves in the identified bands can be readily investigated in the field based on the established correlations.

Keywords Heavy metals      Plants      Target Hazard Quotient (THQ)      Principal Component Analysis (PCA)      Random search      Electromagnetic wave     
Corresponding Author(s): Marzieh Mokarram,Huichun Zhang   
Issue Date: 19 November 2020
 Cite this article:   
Marzieh Mokarram,Hamid Reza Pourghasemi,Huichun Zhang. Predicting non-carcinogenic hazard quotients of heavy metals in pepper (Capsicum annum L.) utilizing electromagnetic waves[J]. Front. Environ. Sci. Eng., 2020, 14(6): 114.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-020-1331-0
https://academic.hep.com.cn/fese/EN/Y2020/V14/I6/114
Fig.1  Amounts of heavy metal pollution in the leaves and fruit of the peppers.
Fig.2  (a) The EDI values in the leaves and fruits of the peppers, (b) THQ for non-carcinogenic hazards, (c) HI for different stages of growth, and (d) BCF in the leaves and fruits of the peppers.
Fig.3  Response of the leaves of the peppers to electromagnetic waves in various growth stages under different treatments.
Metal Vegetation index Stage 1 Stage 2 Stage 3 Control sample
Cd NDVI 0.46 -0.03 0.2 0.75
SAVI 0.42 -0.03 0.19 0.86
OSAVI 0.38 -0.02 0.17 0.68
PVI 2.69 0.95 1.49 7.13
DVI 0.37 -0.02 0.17 1.19
IPVI 0.73 0.49 0.6 0.88
Pb NDVI 0.75 -0.54 0.22 0.73
SAVI 0.64 -0.44 0.19 0.81
OSAVI 0.61 -0.43 0.18 0.65
PVI 7.04 0.3 1.56 6.32
DVI 0.5 -0.33 0.16 1.03
IPVI 0.88 0.23 0.61 0.86
Ni NDVI 0.73 0.27 0.49 0.74
SAVI 0.74 0.29 0.5 0.82
OSAVI 0.63 0.24 0.42 0.66
PVI 6.42 1.75 2.88 6.56
DVI 0.75 0.32 0.53 1.08
IPVI 0.87 0.64 0.74 0.87
Zn NDVI 0.3 -0.25 0.2 0.73
SAVI 0.28 -0.19 0.15 0.81
OSAVI 0.25 -0.19 0.15 0.65
PVI 1.86 0.6 1.48 6.32
DVI 0.24 -0.13 0.1 1.03
IPVI 0.65 0.38 0.6 0.86
Tab.1  Vegetation index results for different treatments at different stages of growth
Fig.4  Schematic distribution of weights allocated to different wavelengths obtained as first, second, and third principal components for the 4 target contaminants.
Heavy metal Model Unstandardized Coefficients Standardized Coefficients Sig.
B Std. Error Beta
Cd (Constant) 0.178 0.095 0.011
b400 0.002 0.073 0.018 0.080
b880 -0.075 0.044 -0.958 0.037
Ni (Constant) 0.001 0.001 0.073
b400 0.0002 0.002 -0.295 0.027
b1030 0.006 0.000 -0.081 0.091
Pb (Constant) -123.690 0.000 0.043
b570 202.835 0.000 1.506 0.052
b650 665.101 0.000 4.248 0.098
b760 -485.185 0.000 -1.995 0.027
Zn (Constant) 5.989 0.000 0.053
b560 -10.231 0.000 -0.662 0.053
b910 -2.007 0.000 -0.406 0.078
b1050 5.213 0.000 0.426 0.065
Tab.2  Significance coefficients of THQ using the Pearson correlation method in contaminated plants
BCF: Bioconcentration Factors
DVI: Differential Vegetation Index
EDI: Estimated Daily Intake
EF: Estimated Frequency
HI: Hazard Index
IPVI: Infrared Percentage Vegetation Index
NDVI: Normalized Difference Vegetation Index
OSAVI: Optimized Soil-Adjusted Vegetation Index
PCA: Principal Component Analysis
SAVI: Soil-Adjusted Vegetation Index
THQ: Target Hazard Quotient
  
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