Support vector machine in the elementomic evaluation of arugula (Eruca Sativa) and lettuce (Lactuca sativa) grown in soils from a decommissioned mining area

Hussain U., Afza R., Gul I., Sajad M.A., Shah G.M., Muhammad Z., Khan S.M.

Soil contaminated with heavy metals cause serious threat to the soil quality, biota, and human. The removal or stabilization of heavy metals through plants is an environment friendly approach. The aim of study was to assess the potential of Celosia argentea L. for the phytoremediation of heavy metals contaminated soil. Soil was spiked with different levels (0, 100, 200, 300, and 400 mg/kg) of chromium (Cr), copper (Cu), lead (Pb), and Zn (Zn). Experiment was carried out in greenhouse and impact of heavy metals was evaluated on plant by assessing the germination rate and plant growth. To evaluate either plant has potential to extract/stabilize the heavy metals, concentration in roots and shoot, translocation factor (TF), bioconcentration factor (BCF), and bioaccumulation factor (BAF) were determined. Application of heavy metals significantly affected the germination rate and minimum (26.6%) was observed in Cr spiked soil (400 mg/kg). Moreover, the biomass of C. argentea was also affected by the application of heavy metals. However, the concentration of heavy metals in roots and shoots were low. The BCF and BAF of C. argentea was lower than 1 except at lower levels of Pb and Zn, but the TF was greater than 1. The TF showed that plants have capability to transfer heavy metals to shoots once they are taken up by roots. However, based on the BCF and concentrations of heavy metals in shoots, it is evident that plant could play important role in the phytostabilization of heavy metals polluted soil.

Senila M., Resz M., Senila L., Torok I.

Although edible mushrooms are considered a source of many beneficial nutrients for human, they can also represent a risk to health due to their capacity to accumulate heavy metals. In this study, the total dissolved in soil solution and labile concentrations of heavy metals (Cd, Pb, Cu, Zn, Co, Cr, Mn, Ni, and Fe) in soil were measured and correlated with their concentrations accumulated in Russula virescens wild mushrooms. The diffusive gradient in thin films (DGT) technique was used to measure the labile metals content in the soil (CDGT), and corroborated with the metals concentrations in soil solution (Csoln) was used to calculate an R-value, which can estimate the metals resupply from soil solid phase when they are uptake by mushroom. The DGT-labile metal concentrations decreased in the order Mn > Fe > Zn > Cu > Co > Ni > Cd ≅ Pb > Cr. The R-values, calculated as the ratio between CDGT and Csoln decreased in the order: Cd (0.50) > Zn (0.37) > Pb (0.33) > Cu (0.24) ≅ Ni (0.24) ≅ Co (0.23) > Mn (0.16) > Fe (0.12) > Cr (0.04). For the first time, we compared the R-values with the bioaccumulation factors (BAFs) in mushrooms, and it was observed that, a similar increasing trend of BAFs with the R-values exists, thus the capacity of the soil solid phase to fast re-supply metals to soil solution increases BAFs. Although the soil samples were not contaminated with heavy metals above the legislative limits, the concentrations of heavy metals accumulated in mushrooms were high enough to pose risks for humans, mainly for children, due to their Cu content.

Ge H., Ji X., Lu X., Lv M., Jiang Y., Jia Z., Zhang Y.

This paper proposes to detect heavy metal pollutants in wheat using terahertz spectroscopy and deep support vector machine (DSVM). Five heavy metal pollutants, arsenic, lead, mercury, chromium, and cadmium, were considered for detection in wheat samples. THz spectral data were pre-processed by wavelet denoising. DSVM was introduced to further enhance the accuracy of the SVM classification model. According to the relationship between the accuracy and the training time with the number of hidden layers ranging from 1 to 4, the model performs the best when the hidden layer network has three layers. Besides, using the back-propagation algorithm to optimize the entire DSVM network. Compared with Deep neural network (DNN) and SVM models, the comprehensive evaluation index of the proposed model optimized by DSVM has the highest accuracy of 91.3 %. It realized the exploration enhanced the classification accuracy of the heavy metal pollutants in wheat.

Ribeiro M.D., de Abreu C.B., Pinho C.S., Ribeiro L.D., Neto A.D., Teixeira L.S., Azcarate S.M., Dias F.D.

The objective of this work was to evaluate elemental changes in pepper exposed to Cd stress through different chemometric tools. For this purpose, pepper plants were grown under five different treatments with different Cd concentrations in the nutrient solution. Considering the hypothesis that pepper plants exposed to Cd stress during growth undergo changes in the macro- and microelemental distribution in leaves, stems, and roots, principal component analysis (PCA) and parallel factor (PARAFAC) analysis were applied to compare bidirectional and multivariate chemometric strategies to assess elemental changes in pepper plants. Since the number of variables and the data generated were large and complex, the application of chemometric tools was justified to facilitate the visualization and interpretation of results. The mineral composition, namely the Ca, Cd, Cu, Fe, K, Mg, Mn, N, and P contents, was assessed in 180 samples of leaves, stems, and roots of the cultivated peppers. Then, PCA and PARAFAC analysis were applied to compare bidirectional and multivariate chemometric strategies to assess elemental changes throughout pepper plants. The visualization of the trend om each sample and their intrinsic relationship with the variables were possible with the application of PCA. The use of PARAFAC analysis permitted the simultaneous study of all samples in a straightforward representation of the information that facilitated a quick and comprehensive understanding of the spatial distribution of elements in plants. Thus, macroelements (Ca, K, Mg, N, and P) that were found in higher concentrations in leaves did not present significant differences in the distribution along the plants under different treatment conditions. In contrast, a significant impact on the microelement (Cu, Fe, and Mn) distribution was produced between uncontaminated and contaminated samples. This analysis revealed a significant accumulation of Cd in roots and adverse effects on normal plant growth, demonstrating their level of phytotoxicity to pepper.

da Silva F.L., Lima F.E., Andrade Neto D.M., de Menezes F.L., M.U.D. Fechine L., Akhdhar A., Ribeiro L.P., Nogueira A.R., Fechine P.B., Lopes G.S., Matos W.O.

An alternative analytical method was developed for the quantification of inorganic arsenic (iAs) in rice by ICP OES. Iron nanoparticles modified with an organophosphorus compound were used as the solid phase for MSPE of iAs from the plant matrix. The MSPE procedure was performed using 4 mL of a buffer solution with pH 4.0, 20 mg of the nanomaterial, and a 15-min extraction time. The total As (tAs) by ICP OES was also quantified using the same MSPE procedure after solubilization of the samples by a block digester. The accuracy of tAs and iAs quantification was verified using CRM NIST 1568b (97 % and 101 % recovery, respectively). The precision (RSD < 15 %) and LOD and LOQ (1.08 and 3.70 µg kg-1, respectively) of the proposed method were satisfactory. The rice samples had tAs contents between 0.090 and 0.295 mg kg-1 and iAs mass fractions between 0.055 and 0.109 mg kg-1.

Tang Z., You T., Li Y., Tang Z., Bao M., Dong G., Xu Z., Wang P., Zhao F.

Excessive accumulation of cadmium (Cd) in rice grains threatens food safety and human health. Growing low Cd accumulating rice cultivars is an effective approach to produce low-Cd rice. However, field screening of low-Cd rice cultivars is laborious, time-consuming, and subjected to the influence of environment × genotype interactions. In the present study, we investigated whether machine learning-based methods incorporating genotype and soil Cd concentration can identify high and low-Cd accumulating rice cultivars. One hundred and sixty-seven locally adapted high-yielding rice cultivars were grown in three fields with different soil Cd levels and genotyped using four molecular markers related to grain Cd accumulation. We identified sixteen cultivars as stable low-Cd accumulators with grain Cd concentrations below the 0.2 mg kg−1 food safety limit in all three paddy fields. In addition, we developed eight machine learning-based models to predict low- and high-Cd accumulating rice cultivars with genotypes and soil Cd levels as input data. The optimized model classifies low- or high-Cd cultivars (i.e., the grain Cd concentration below or above 0.2 mg kg−1) with an overall accuracy of 76%. These results indicate that machine learning-based classification models constructed with molecular markers and soil Cd levels can quickly and accurately identify the high- and low-Cd accumulating rice cultivars.

Sut-Lohmann M., Grimm M., Kästner F., Raab T., Heinrich M., Fischer T.

AbstractNowadays, many sites are considered waste, due to high potentially toxic metal (PTM) concentration. Recycling of globally critical metals requires development of environmentally friendly processes for metal recovery. To study plants response to elevated Zn and Cu concentration in soil, a greenhouse experiment was designed using hyperaccumulator Brassica juncea. Plants were irrigated daily with PTM solutions, with final mass of both Zn and Cu added to the soil reaching 104.5, 209, 313.5, and 330 mg. After 8 weeks, samples were harvested, dried, weighed, and elemental analysis was conducted using atomic emission spectrometry (Agilent Technologies 4210 MP-AES). Phytotoxicity was determined based on visual observation, biomass, and chlorophyll measurements. The highest accumulation of Zn and Cu was found in the stem and leaf material, with observed concentrations of Zn in the leaf being 16.750 mg kg−1 and 7.170 mg kg−1 of Cu in the stem. The highest allocated in the biomass mass of Zn and Cu was in T4 treatment reaching 25.8 mg and 9.5 mg, respectively. Treatment with 330 mg Zn and Cu application displayed a 62.3% decrease in stem mass, a 25% decrease in average root mass (LD30 reached), and a 59% decrease in leaf mass when compared with the control. With increasing PTM concentration, root, biomass (from about 0.4 to 0.1 g; from about 3.8 to 2.0 g, respectively) and chlorophyll “a” (from about 24 to 19 μg/cm2) decline was observed, which correlates with observed chlorosis. This study reaffirmed the capabilities of B. juncea to bioaccumulate Zn and Cu from an enriched soil and provided further understanding as to how Zn and Cu translocate within plant tissues.

Zhao B., Zhu W., Hao S., Hua M., Liao Q., Jing Y., Liu L., Gu X.

Rapid and accurate prediction of metal bioaccumulation in crops are important for assessing metal environmental risks. We aimed to incorporate machine learning modeling methods to predict heavy metal contents in rice crops and identify influencing factors. We conducted a field study in Jiangsu province, China, collecting 2123 pairs of soil-rice samples in a uniform measurement and using 10 machine learning algorithms to predict the uptake of Cd, Hg, As, and Pb in rice grain. The Extremely Randomized Tree model exhibited the best performance for rice-Cd and rice-Hg (Cd: R2 = 0.824; Hg: R2 = 0.626), while the Random Forest model performed best for As and Pb (As: R2 = 0.389; Pb: R2 = 0.325). The feature importance analysis showed that soil-Cd and pH had the highest impact on rice-Cd risk, which is in line with previous studies; while temperature and soil organic carbon were more important to rice-Hg than soil-Hg. Then, based on another set of 1867 uniformly distributed paddy soil samples in Jiangsu province, the Cd and Hg risks of soil and rice were visualized using the established models. Mapping result revealed an inconsistent pattern of hotspot distribution between soil-Hg and rice-Hg, i.e., a higher rice-Hg risk in the northern area, while higher soil-Hg in south. Our findings highlight the importance of temperature on Hg bioaccumulation risk to crops, which has often been overlooked in previous risk assessment processes.

Carneiro C.N., Gomez F.J., Spisso A., Silva M.F., Santos J.L., Dias F.D.

In this work, microwave-induced plasma optical emission spectrometry was applied for multielement determination in South American wine samples. The analytes were determined after acid digestion of 47 samples of Brazilian and Argentinian wines. Then, logistic regression, support vector machine, and decision tree for exploratory analysis and comparison of these algorithms in differentiating red wine samples by region of origin were carried out. All wine samples were classified according to their geographical origin. The quantification limits (mg L−1) were P: 0.06, B: 0.08, K: 0.17, Mn: 0.002, Cr: 0.002, and Al: 0.02. The accuracy of the method was evaluated by analyzing the wine samples by ICP OES for results’ comparison. The concentrations in mg L−1 found for each element in wine samples were as follows: Al (< 0.02–1.82), Cr (0.15–0.50), Mn (< 0.002–0.8), P (97–277), B (1.7–11.6), Pb (< 0.06–0.3), Na (8.84–41.57), and K (604–1701), in mg L−1.

Paz-Sabillón M., Torres-Sánchez L., Piña-Pozas M., Del Razo L.M., Quintanilla-Vega B.

In recent years, the background level of environmental pollutants, including metals, has increased. Pollutant exposure during the earliest stages of life may determine chronic disease susceptibility in adulthood because of genetic or epigenetic changes. The objective of this review was to identify the association between prenatal and early postnatal exposure to potentially toxic metals (PTMs) and their adverse effects on the genetic material of offspring. A systematic review was carried out following the Cochrane methodology in four databases: PubMed, Scopus, Web of Science, and the Cochrane Library. Eligible papers were those conducted in humans and published in English between 2010/01/01 and 2021/04/30. A total of 57 articles were included, most of which evaluated prenatal exposure. Most commonly evaluated PTMs were As, Cd, and Pb. Main adverse effects on the genetic material of newborns associated with PTM prenatal exposure were alterations in telomere length, gene or protein expression, mitochondrial DNA content, metabolomics, DNA damage, and epigenetic modifications. Many of these effects were sex-specific, being predominant in boys. One article reported a synergistic interaction between As and Hg, and two articles observed antagonistic interactions between PTMs and essential metals, such as Cu, Se, and Zn. The findings in this review highlight that the problem of PTM exposure persists, affecting the most susceptible populations, such as newborns. Some of these associations were observed at low concentrations of PTMs. Most of the studies have focused on single exposures; however, three interactions between essential and nonessential metals were observed, highlighting that metal mixtures need more attention.

Alsafran M., Usman K., Ahmed B., Rizwan M., Saleem M.H., Al Jabri H.

Potentially toxic elements (PTEs) such as cadmium (Cd), lead (Pb), chromium (Cr), and arsenic (As), polluting the environment, pose a significant risk and cause a wide array of adverse changes in plant physiology. Above threshold accumulation of PTEs is alarming which makes them prone to ascend along the food chain, making their environmental prevention a critical intervention. On a global scale, current initiatives to remove the PTEs are costly and might lead to more pollution. An emerging technology that may help in the removal of PTEs is phytoremediation. Compared to traditional methods, phytoremediation is eco-friendly and less expensive. While many studies have reported several plants with high PTEs tolerance, uptake, and then storage capacity in their roots, stem, and leaves. However, the wide application of such a promising strategy still needs to be achieved, partly due to a poor understanding of the molecular mechanism at the proteome level controlling the phytoremediation process to optimize the plant’s performance. The present study aims to discuss the detailed mechanism and proteomic response, which play pivotal roles in the uptake of PTEs from the environment into the plant’s body, then scavenge/detoxify, and finally bioaccumulate the PTEs in different plant organs. In this review, the following aspects are highlighted as: (i) PTE’s stress and phytoremediation strategies adopted by plants and (ii) PTEs induced expressional changes in the plant proteome more specifically with arsenic, cadmium, copper, chromium, mercury, and lead with models describing the metal uptake and plant proteome response. Recently, interest in the comparative proteomics study of plants exposed to PTEs toxicity results in appreciable progress in this area. This article overviews the proteomics approach to elucidate the mechanisms underlying plant’s PTEs tolerance and bioaccumulation for optimized phytoremediation of polluted environments.

do Prado N.B., de Abreu C.B., Pinho C.S., Junior M.M., Silva M.D., Espino M., Silva M.F., Dias F.D.

• This work showed the use of exploratory analysis for evaluation of abiotic stress in Basil. • The plants were subjected to five different concentrations of cadmium, lead and aluminum. • The concentration of phenolic compounds was evaluated as a response to stress. Basil is an edible, aromatic plant, which makes the study of the ecotoxicity of metals in plant metabolism relevant. Given the above, the objective of this study was to evaluate the effects of metals, aluminum, lead, and cadmium, in the synthesis of phenolic compounds and in the dry mass of basil plants ( O. basilicum L.) grown in a hydroponic system. The plants were subjected to four different concentrations of cadmium (0.2, 0.6, 1.2, and 1.8 mmol L -1 ), lead and aluminum (0.04, 0.08, 0.12, and 0.16 mmol L -1 ), and compared with the control. After desiccation of the plant material, the total dry mass was obtained and then, hydroethanolic extracts (43% distilled water and 57% ethanol) were made for biochemical analyzes, which consisted of the determination of caffeic acid (CA) and rosmarinic acid (RA) by high performance liquid chromatography analysis with a diode detector (HPLC-DAD); total phenolics (TP) and total flavonoids (TF) by spectrophotometry. The data were submitted to analysis of variance and multivariate analysis (principal component analysis-PCA and hierarchical cluster analysis-HCA) was applied for data association. The phenolic compounds showed a high positive correlation with each other, and the total dry mass showed low and negative correlations with the analyzed variables. The results showed that the metals aluminum, lead, and cadmium promoted a stress condition in basil plants, which resulted in the reduction of the dry matter mass and an increase in the synthesis of phenolic compounds, according to the type and concentration of the metal.

Hu X., Wei X., Ling J., Chen J.

Cobalt is a transition metal located in the fourth row of the periodic table and is a neighbor of iron and nickel. It has been considered an essential element for prokaryotes, human beings, and other mammals, but its essentiality for plants remains obscure. In this article, we proposed that cobalt (Co) is a potentially essential micronutrient of plants. Co is essential for the growth of many lower plants, such as marine algal species including diatoms, chrysophytes, and dinoflagellates, as well as for higher plants in the family Fabaceae or Leguminosae. The essentiality to leguminous plants is attributed to its role in nitrogen (N) fixation by symbiotic microbes, primarily rhizobia. Co is an integral component of cobalamin or vitamin B12, which is required by several enzymes involved in N2 fixation. In addition to symbiosis, a group of N2 fixing bacteria known as diazotrophs is able to situate in plant tissue as endophytes or closely associated with roots of plants including economically important crops, such as barley, corn, rice, sugarcane, and wheat. Their action in N2 fixation provides crops with the macronutrient of N. Co is a component of several enzymes and proteins, participating in plant metabolism. Plants may exhibit Co deficiency if there is a severe limitation in Co supply. Conversely, Co is toxic to plants at higher concentrations. High levels of Co result in pale-colored leaves, discolored veins, and the loss of leaves and can also cause iron deficiency in plants. It is anticipated that with the advance of omics, Co as a constitute of enzymes and proteins and its specific role in plant metabolism will be exclusively revealed. The confirmation of Co as an essential micronutrient will enrich our understanding of plant mineral nutrition and improve our practice in crop production.

Proshad R., Islam M.S., Kormoker T., Sayeed A., Khadka S., Idris A.M.

The research aimed to find out physiochemical properties, metal concentration, sources of metals using statistical analyses, and positive matrix factorization (PMF) model using 315 soil and 250 foodstuff samples (25 species) in Jhenidah as well as Kushtia district, Bangladesh. The range of Pb, Cd, As, Cu, Ni and Cr contents (mg/kg) in soils were found to be 0.97–114.72, 0.11–7.51, 1.07–23.38, 0.89–122.91, 0.91–77.32 and 0.7–23.03 mg/kg, respectively, whereas those in foodstuff samples were found to be 0.46–11.48, 0.30–11.54, 0.47–9.21, 0.20–3.59, 0.001–1.76, and 0.27–5.93 mg/kg, respectively. PMF model revealed that Cu (81.4%) in the study area soils were predominantly contributed by vehicular fuel combustion, Cr (84.9%) was primarily of natural origin, Pb (73%) resulted from traffic emissions, Cd (74.3%), and As (63.4%) mainly came from agricultural practices while Ni (70.9%) was dominated as industrial pollution. EF > 1.5 of Cu, As, and Pb suggesting mild contamination; however, soils from all the studied sites revealed moderate potential ecological risk. Cr recorded BCF values of >1 in the majority of the examined crops, suggesting higher uptake of Cr than other metals. Cr, Ni, As, and Pb showed cancer risks from food intake and risk values were greater than the threshold range (10 −4 ), suggesting potential cancer risks. • Pollutant monitoring was performed for assessing PTMs on soils and foodstuffs. • Sources and health hazards of PTMs were critically determined. • PMF model was applied for several sources of metals in soil. • Cr, Ni, As in soils and Cr, Ni, As and Pb in foodstuffs showed cancer risk.

Atikpo E., Okonofua E.S., Uwadia N.O., Michael A.

Abstract Investigation of lead (Pb), cadmium (Cd), zinc (Zn) and chromium (Cr) in soils and vegetables; and the consequent health risks connected with ingestion of the vegetables was conducted at Agbabu farm (F) settlement close to bitumen mining area of Ondo State, Nigeria. Soil and eleven vegetables were sampled from ten farms (Fs) and analyzed for Pb, Cd, Zn and Cr concentrations. Health risk parameters such as daily intake of metal (DIM), health risk index (HRI), target health quotient (THQ), and total diet target health quotient (TTHQ) were evaluated. Except Cd, other metals in soils were below their respective maximum allowable concentrations (MACs) set for agro soils. Only Cd and Pb were higher in vegetables than their respective MACs. Bioconcentration factors (BCFs) of the metals were higher in Talinum triangulare but lower for Cd, Zn, Cr and Pb in Solanum macrocarpon, Vernonia amygdalina, Ocimum gratissimum, and Taraxacum officinale respectively. DIMs of Cd, Zn and Pb for adults and children were higher than 0.0035, 0.001 and 0.300 mg/kg/day respective values of oral reference doses (RfD). The DIMs of Cr ingestion by children were above the RfD of Cr for all vegetables, while DIMs of ingesting Cr by adults were above Cr RfD for some vegetables. The (HRI >1) for Pb, Cd and Zn; (THQ >1) for Pb, Cd; and (TTHQ >1) indicated health risks in connection with the ingestion of these vegetables. These health risks were higher for children.