scholarly journals Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adam Sajnóg ◽  
Elwira Koko ◽  
Dariusz Kayzer ◽  
Danuta Barałkiewicz

AbstractIn this paper 13 elements, both physiological and causing toxic effects, were determined by inductively coupled plasma mass spectrometry in roots of 26 species of herbs used in Traditional Chinese Medicine. The herbs were purchased from online shop in two batches 1 year apart to verify the variability of elemental content in time. The multivariate statistical methods—multiple regression, canonical variates and interaction effect analysis—were applied to interpret the data and to show the relationships between elements and two batches of herb roots. The maximum permissible concentration of Cd (0.3 mg kg−1) was exceeded in 7 herb roots which makes 13% of all specimens. The multiple regression analysis revealed the significant relationships between elements: Mg with Sr; V with Pb, As and Ba; Mn with Pb; Fe with As and Ba; Co with Ni and Sr, Cu with Pb, Cd and As; Zn with Pb, Cd, As and Ba. The canonical variates analysis showed that the statistical inference should not be based solely on the type of herb or number of batch because of the underlying interaction effects between those two variables that may be a source of variability of the content of determined elements.

2014 ◽  
Vol 32 (No. 4) ◽  
pp. 354-359 ◽  
Author(s):  
M. Jarošová ◽  
D. Milde ◽  
M. Kuba

We determined the mineral nutrients and toxic elements (Ca, Cu, Fe, Mg, Zn, Cd, Cr, Mn, Ni, and Pb) in five types of coffee by atomic absorption spectrometry and inductively coupled plasma mass spectrometry. The decomposition of the samples took place in a microwave digestion system with HNO<sub>3</sub> and H<sub>2</sub>O<sub>2</sub> reagents. Partial validation of the method was performed by using the certified reference material (NCS ZC 73014). Univariate and multivariate statistical methods were used to compare both the coffee samples and the techniques used. No significant differences were found between two used methods. Significant differences occurred between the coffee samples but only the application of multivariate statistics helps to distinguish among samples from different locations.


Separations ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 119
Author(s):  
Konstantina Pasvanka ◽  
Marios Kostakis ◽  
Maria Tarapoulouzi ◽  
Pavlos Nisianakis ◽  
Nikolaos S. Thomaidis ◽  
...  

Major, minor and trace elements in wines from Greece were determined by inductively coupled plasma–mass spectrometry (ICP–MS). The concentrations of 44 elements (Na, Mg, P, K, Ca, Cu, Co, Cr, Zn, Sn, Fe, Mn, Li, Be, B, V, Sr, Ba, Al, Ag, Ni, As, Sn, Hg, Pb, Sb, Cd, Ti, Ga, Zr, Nb, Pd, Te, La, Sm, Ho, Tm, Yb, W, Os, Au, Tl, Th, U) in 90 white and red wines from six different regions in Greece for two consecutive vinification years, 2017 and 2018, were determined. Results for the elements aforementioned were evaluated by multivariate statistical methods, such as discriminant analysis and cluster analysis, and the wines were discriminated according to wine variety and geographical origin. Due to the specific choice of the analytes for multivariate statistical investigation, a prediction rate by cross-validation of 98% could be achieved. The aim of this study was not only to reveal specific relationships between the wine samples or between the chemical variables in order to classify the wines from different regions and varieties according to their elemental profile (wine authentication), but also to observe the annual fluctuation in the mineral content of the studied wine samples.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Trung Nguyen-Quang ◽  
Minh Bui-Quang ◽  
Minh Truong-Ngoc

Inductively coupled plasma mass spectrometry (ICP-MS) analytical method was used to determine the content of 40 elements in 38 soybean samples (Glycine Max) from 4 countries. Multivariate statistical methods, such as principal components analysis (PCA), were performed to analyze the obtained data to establish the provenance of the soybeans. Although soybean is widely marketed in many countries, no universal method is used to discriminate the origin of these cereals. Our study introduced the initial step to the identification of the geographical origin of commercial soybean marketed in Vietnam. The analysis pointed out that there are significant differences in the mean of 33 of the 40 analyzed elements among 4 countries’ soybean samples, namely, 11B, 27Al, 44Ca, 45Sc, 47Ti, 55Mn, 56Fe, 59Co, 60Ni, 63Cu, 66Zn, 69Ga, 75As, 78Se, 85Rb, 88Sr, 89Y, 90Zr, 93Nb, 95Mo, 103Rh, 137Ba, 163Dy, 165Ho, 175Lu, 178Hf, 181Ta, 182W, 185Re, 197Au, 202Hg, 205Tl, and 208Pb. The PCA analysis showed that the soybean samples can be classified correctly according to their original locations. This research can be used as a prerequisite for future studies of using the combination of elemental composition analysis with statistical classification methods for an accurate provenance establishment of soybean, which determined a variation of key markers for the original discrimination of soybean.


Metabolomics ◽  
2021 ◽  
Vol 17 (10) ◽  
Author(s):  
J. Iacovacci ◽  
W. Lin ◽  
J. L. Griffin ◽  
R. C. Glen

Abstract Introduction Inductively coupled plasma mass spectrometry (ICP-MS) experiments generate complex multi-dimensional data sets that require specialist data analysis tools. Objective Here we describe tools to facilitate analysis of the ionome composed of high-throughput elemental profiling data. Methods IonFlow is a Galaxy tool written in R for ionomics data analysis and is freely accessible at https://github.com/wanchanglin/ionflow. It is designed as a pipeline that can process raw data to enable exploration and interpretation using multivariate statistical techniques and network-based algorithms, including principal components analysis, hierarchical clustering, relevance network extraction and analysis, and gene set enrichment analysis. Results and Conclusion The pipeline is described and tested on two benchmark data sets of the haploid S. Cerevisiae ionome and of the human HeLa cell ionome.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Trung Nguyen-Quang ◽  
Giang Do-Hoang ◽  
Minh Truong-Ngoc

Statistical interpretation of the concentrations of 42 elements, determined using solution-based inductively coupled plasma mass spectrometry (ICP-MS) analysis and multivariate statistical methods, such as principal components analysis (PCA), was used to establish the provenance of pakchoi (Brassica rapa L. ssp. chinensis) from 6 areas in Ha Noi, Vietnam. Although pakchoi is widely cultivated and manufactured, no universal method is used to discriminate the origin of this vegetable. Our study introduced for the first time a method to classify pakchoi in small geographical areas. 42 metallic elements of pakchoi were detected by ICP-MS, which were further analyzed using multivariate statistical analysis to perform clusters based on the geographical locations. Eleven elements, i.e., 28Si; 56Fe; 59Co; 63Cu; 69Ga; 75As; 85Rb; 93Nb; 107Ag; 118Sn, and 137Ba, were identified as discriminators to distinguish pakchoi from those areas. Results from this study presented a new method to discriminant the geographical origins of pakchoi, which could apply to other types of vegetables on the food market.


Molecules ◽  
2020 ◽  
Vol 25 (9) ◽  
pp. 2179
Author(s):  
Georgios Koutrotsios ◽  
Georgios Danezis ◽  
Constantinos Georgiou ◽  
Georgios I. Zervakis

Few data exist about the effect of substrates’ elemental content on the respective concentrations in cultivated mushrooms, on the degradation of lignocellulosics or on production parameters. Sixteen elements (14 metals and 2 metalloids) were measured by inductively coupled plasma mass spectrometry (ICP-MS) in Pleurotus ostreatus and Cyclocybe cylindracea mushrooms, and in their seven cultivation substrates composed of various plant-based residues. Results revealed a high variability in elemental concentration among substrates which generally led to significant differences in the respective mushroom contents. High bioconcentration factors (BCFs) were noted for Cd, Cu, Mg and Zn for both species in all substrates. BCF of each element was variously affected by substrates’ pH, crude composition, and p and K content. Significant positive correlations were demonstrated for Cu, Fe, Mn and Li concentrations vs. a decrease of cellulose and hemicellulose in P. ostreatus substrates, and vs. mushrooms’ biological efficiency. In the case of C. cylindracea, Be, Mg and Mn concentrations were positively correlated with the decrease of hemicellulose in substrates, while a significant positive correlation was also recorded vs. mushroom productivity. Finally, it was found that 15% to 35% of the daily dietary needs in Mg, Se and Zn could be covered by mushroom consumption.


2019 ◽  
Author(s):  
Ingo Strenge ◽  
Carsten Engelhard

<p>The article demonstrates the importance of using a suitable approach to compensate for dead time relate count losses (a certain measurement artefact) whenever short, but potentially strong transient signals are to be analysed using inductively coupled plasma mass spectrometry (ICP-MS). Findings strongly support the theory that inadequate time resolution, and therefore insufficient compensation for these count losses, is one of the main reasons for size underestimation observed when analysing inorganic nanoparticles using ICP-MS, a topic still controversially discussed.</p>


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