scholarly journals Rapid Identification of Geographical Origin of Commercial Soybean Marketed in Vietnam by ICP-MS

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Trung Nguyen-Quang ◽  
Minh Bui-Quang ◽  
Minh Truong-Ngoc
Keyword(s):  
Inductively Coupled Plasma ◽  
Geographical Origin ◽  
Initial Step ◽  
Rapid Identification ◽  
Composition Analysis ◽  
Universal Method ◽  
Multivariate Statistical ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry

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.

scholarly journals Multielement Analysis of Pakchoi (Brassica rapa L. ssp. chinensis) by ICP-MS and Their Classification according to Different Small Geographical Origins

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Trung Nguyen-Quang ◽  
Giang Do-Hoang ◽  
Minh Truong-Ngoc
Keyword(s):  
Brassica Rapa ◽  
Inductively Coupled Plasma ◽  
Statistical Interpretation ◽  
Universal Method ◽  
Multivariate Statistical ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Food Market ◽  
First Time

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.

scholarly journals Elemental analysis of coffee: a comparison of ICP-MS and AAS methods 

2014 ◽  
Vol 32 (No. 4) ◽  
pp. 354-359 ◽  
Author(s):  
M. Jarošová ◽  
D. Milde ◽  
M. Kuba
Keyword(s):  
Inductively Coupled Plasma ◽  
Microwave Digestion ◽  
Absorption Spectrometry ◽  
Mineral Nutrients ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Microwave Digestion System

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.

scholarly journals ICP–MS Analysis of Multi-Elemental Profile of Greek Wines and Their Classification According to Variety, Area and Year of Production

Separations ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 119
Author(s):  
Konstantina Pasvanka ◽  
Marios Kostakis ◽  
Maria Tarapoulouzi ◽  
Pavlos Nisianakis ◽  
Nikolaos S. Thomaidis ◽  
...  
Keyword(s):  
Inductively Coupled Plasma ◽  
Mineral Content ◽  
Statistical Investigation ◽  
Multivariate Statistical ◽  
Annual Fluctuation ◽  
Inductively Coupled ◽  
Elemental Profile ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
And Cluster Analysis

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.

scholarly journals The effect of collecting area on the element content of Hungarian acacia honeys

2018 ◽  
pp. 129-138
Author(s):  
Nikolett Czipa ◽  
Andrea Kántor ◽  
Loránd Alexa ◽  
Béla Kovács
Keyword(s):  
Inductively Coupled Plasma ◽  
Geographical Origin ◽  
Optical Emission ◽  
Emission Spectrometry ◽  
Linear Discriminant ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Plasma Optical Emission Spectrometry ◽  
One Way Anova

Six macroelements and twelve microelements were identified in thirty-six Hungarian acacia honeys collected from ten counties by inductively coupled plasma optical emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS). One-Way ANOVA (LSD and Dunnett T3 test) and linear discriminant analysis (LDA) were used to determine the statistically verified differences among the honey samples with different geographical origin. Significant differences were established among the samples from different counties in Na, P, S, Fe, Ni, Cu and Sr concentrations. Based on the macroelement content of honeys, the separation of samples with different geographical origin was not successful because the percent of correctly categorised cases was only 64.9%. However, examining the As, B, Ba, Cu, Fe Mn, Ni and Sr concentration, the separation of different groups was convincing since the percent of correctly classified cases was 97.2%. Thus, the examination of microelement concentration may be able to determine the geographical origin of acacia honeys.

scholarly journals From Soil to Grape and Wine: Geographical Variations in Elemental Profiles in Different Chinese Regions

Foods ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3108
Author(s):  
Xiaoyun Hao ◽  
Feifei Gao ◽  
Hao Wu ◽  
Yangbo Song ◽  
Liang Zhang ◽  
...  
Keyword(s):  
Environmental Factor ◽  
Inductively Coupled Plasma ◽  
Bioconcentration Factor ◽  
Geographical Origin ◽  
Linear Discriminant ◽  
Inductively Coupled ◽  
Geographical Variations ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Grape Wine

Elemental profiles are frequently applied to identify the geographical origin and authenticity of food products, to guarantee quality. The concentrations of fifteen major, minor, and trace elements (Na, Mg, K, Ca, Al, Fe, Mn, Cu, Zn, Rb, Sr, Li, Cd, Cs, and Ba) were determined in soils, “Meili” grapes, and wines from six regions in China by inductively coupled plasma mass spectrometry (ICP-MS). The elemental concentrations in these samples, according to the geographical origins, were analyzed by one-way analysis of variance (ANOVA) with Duncan’s multiple comparisons. The bioconcentration factor (BCF) from soil to grape and the transfer factor (TF) from grape to wine were calculated. Mg, K, Ca, Cu, Zn, Rb, Sr, and Ba presented higher BCF values than the other seven elements. The TF values of six elements (Na, Mg, K, Zn, Li, and Cs) were found to be greater than one. Moreover, the correlation of element content between the pairs of soil–grape, grape–wine, and bioconcentration factor (BCF)–environmental factor were analyzed. Significant correspondences among soil, grape, and wine were observed for K and Li. Two elements (Sr and Li) showed significant correlations between BCF and environmental factor (relative humidity, temperature, and latitude). A linear discriminant analysis (LDA) with three variables (K, Sr, Li) revealed a high accuracy (>90%) to determine the geographical origin for different Chinese regions.

scholarly journals IonFlow: a galaxy tool for the analysis of ionomics data sets

Metabolomics ◽  
2021 ◽  
Vol 17 (10) ◽  
Author(s):  
J. Iacovacci ◽  
W. Lin ◽  
J. L. Griffin ◽  
R. C. Glen
Keyword(s):  
Data Analysis ◽  
Inductively Coupled Plasma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Data Sets ◽  
Multivariate Statistical ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Elemental Profiling

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.

scholarly journals 87sr/86sr ratio in vineyard soils from Portuguese denominations of origin and its potential for origin authentication

OENO One ◽  
2014 ◽  
Vol 48 (1) ◽  
pp. 21 ◽  
Author(s):  
Patrícia Martins ◽  
Manuel Madeira ◽  
Fernando Monteiro ◽  
Raúl Bruno de Sousa ◽  
António Sérgio Curvelo-Garcia ◽  
...  
Keyword(s):  
Inductively Coupled Plasma ◽  
Geographical Origin ◽  
Isotopic Ratio ◽  
Soil Types ◽  
Inductively Coupled ◽  
Analytical Protocol ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Ratio Determination ◽  
Vineyard Soils

<p style="text-align: justify;"><strong>Aim</strong>: The control of geographical origin is one of the most challenging topics regarding wine authenticity. The aim of the present study was to assess the <sup>87</sup>Sr/<sup>86</sup>Sr ratio of vineyard soils from Portuguese Denominations of Origin (DO) and evaluate its suitability as a tool for origin authentication.</p><p style="text-align: justify;"><strong>Methods and results</strong>: An analytical protocol was optimized (chromatographic separation of Sr and Rb, followed by inductively coupled plasma-mass spectrometry (ICP-MS) analysis) for <sup>87</sup>Sr/<sup>86</sup>Sr isotopic ratio determination in soil-wine system. The <sup>87</sup>Sr/<sup>86</sup>Sr ratios of soils from four vineyards located in three Portuguese DO (Dão, Óbidos and Palmela), established on distinct soil types, were determined. Significant differences were found between soils of different DO regions. The soil in the Dão DO, developed on granites, showed a statistically higher <sup>87</sup>Sr/<sup>86</sup>Sr ratio than the other soils, which were developed on sedimentary formations.</p><p style="text-align: justify;"><strong>Conclusion</strong>: The results show clearly that <sup>87</sup>Sr/<sup>86</sup>Sr ratio may represent a suitable fingerprint for these Portuguese DO.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: This study highlights the relevance of setting up an international databank of <sup>87</sup>Sr/<sup>86</sup>Sr values for use for geographical identification and authentication.</p>

scholarly journals Tracing the Geographical Origin of Thai Hom Mali Rice in Three Contiguous Provinces of Thailand Using Stable Isotopic and Elemental Markers Combined with Multivariate Analysis

Foods ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2349
Author(s):  
Supalak Kongsri ◽  
Phitchan Sricharoen ◽  
Nunticha Limchoowong ◽  
Chunyapuk Kukusamude
Keyword(s):  
Mass Spectrometry ◽  
Multivariate Analysis ◽  
Inductively Coupled Plasma ◽  
Geographical Origin ◽  
Isotope Ratio Mass Spectrometry ◽  
Valuable Insight ◽  
Linear Discriminant ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry

Rice is a staple food for more than half of the world’s population. The discrimination of geographical origin of rice has emerged as an important issue to prevent mislabeling and adulteration problems and ensure food quality. Here, the discrimination of Thai Hom Mali rice (THMR), registered as a European Protected Geographical Indication (PGI), was demonstrated. Elemental compositions (Mn, Rb, Co, and Mo) and stable isotope (δ18O) in the rice were analyzed using inductively coupled plasma mass spectrometry (ICP-MS) and elemental analyzer isotope ratio mass spectrometry (EA-IRMS), respectively. The recoveries and precisions of all elements were greater than 98% and lower than 9%, respectively. The analytical precision (±standard deviation) was below ±0.2‰ for δ18O measurement. Mean of Mn, Rb, Co, Mo, and δ18O levels was 14.0 mg kg−1, 5.39 mg kg−1, 0.049 mg kg−1, 0.47 mg kg−1, and 25.22‰, respectively. Only five valuable markers combined with radar plots and multivariate analysis, linear discriminant analysis (LDA) could distinguish THMR cultivated from three contiguous provinces with correct classification and cross-validation of 96.4% and 92.9%, respectively. These results offer valuable insight for the sustainable management and regulation of improper labeling regarding geographical origin of rice in Thailand and other countries.

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
Keyword(s):  
Multiple Regression ◽  
Inductively Coupled Plasma ◽  
Toxic Effects ◽  
Elemental Content ◽  
Multivariate Statistical ◽  
Effect Analysis ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Canonical Variates ◽  
Plasma Mass Spectrometry

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.

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