Characterisation of Uruguayan Honeys by Multi-Elemental Analyses as a Basis to Assess Their Geographical Origin

In this work, we evaluated the possibility of predicting the geographic origin of Uruguayan honeys using discriminant analysis (DA) on mineral concentration. Although the DA results appeared to discriminate between honeys from the south, central and north, the subsequent cross-validation analysis did not confirm this result. We also compared honeys from Uruguay and the Buenos Aires province (Argentina) using DA on mineral composition data. In this case, a clear difference between these two origins was observed. It seems possible to differentiate between Uruguayan honeys and those produced in a neighbouring country based on multivariate statistical methods.

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Discrimination of the Geographical Origin of Soybeans Using NMR-Based Metabolomics

Foods ◽

10.3390/foods10020435 ◽

2021 ◽

Vol 10 (2) ◽

pp. 435

Author(s):

Yaoyao Zhou ◽

Seok-Young Kim ◽

Jae-Soung Lee ◽

Byeung-Kon Shin ◽

Jeong-Ah Seo ◽

...

Keyword(s):

Metabolic Profiling ◽

Cross Validation ◽

Geographical Origin ◽

Multivariate Statistical ◽

Essential Information ◽

Future Studies ◽

Unit Variance ◽

The Republic ◽

Leave One Out ◽

Geographical Locations

With the increase in soybean trade between countries, the intentional mislabeling of the origin of soybeans has become a serious problem worldwide. In this study, metabolic profiling of soybeans from the Republic of Korea and China was performed by nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to predict the geographical origin of soybeans. The optimal orthogonal partial least squares-discriminant analysis (OPLS-DA) model was obtained using total area normalization and unit variance (UV) scaling, without applying the variable influences on projection (VIP) cut-off value, resulting in 96.9% sensitivity, 94.4% specificity, and 95.6% accuracy in the leave-one-out cross validation (LOO-CV) test for discriminating between Korean and Chinese soybeans. Soybeans from the northeastern, middle, and southern regions of China were successfully differentiated by standardized area normalization and UV scaling with a VIP cut-off value of 1.0, resulting in 100% sensitivity, 91.7%–100% specificity, and 94.4%–100% accuracy in a LOO-CV test. The methods employed in this study can be used to obtain essential information for the authentication of soybean samples from diverse geographical locations in future studies.

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Mineral Composition through Soil-Wine System of Portuguese Vineyards and Its Potential for Wine Traceability

Beverages ◽

10.3390/beverages4040085 ◽

2018 ◽

Vol 4 (4) ◽

pp. 85 ◽

Cited By ~ 5

Author(s):

Sofia Catarino ◽

Manuel Madeira ◽

Fernando Monteiro ◽

Ilda Caldeira ◽

Raúl Bruno de Sousa ◽

...

Keyword(s):

Elemental Composition ◽

Mineral Composition ◽

Quantitative Method ◽

Geographical Origin ◽

Geographic Origin ◽

Multivariate Statistical ◽

Icp Ms ◽

Geological Formations ◽

Composition Pattern ◽

Grape Musts

The control of geographic origin is one of a highest priority issue regarding traceability and wine authenticity. The current study aimed to examine whether elemental composition can be used for the discrimination of wines according to geographical origin, taking into account the effects of soil, winemaking process, and year of production. The elemental composition of soils, grapes, musts, and wines from three DO (Designations of Origin) and for two vintage years was determined by using the ICP-MS semi-quantitative method, followed by multivariate statistical analysis. The elemental composition of soils varied according to geological formations, and for some elements, the variation due to soil provenance was also observed in musts and wines. Li, Mn, Sr and rare-earth elements (REE) allowed wine discrimination according to vineyard. Results evidenced the influence of winemaking processes and of vintage year on the wine’s elemental composition. The mineral composition pattern is transferred through the soil-wine system, and differences observed for soils are reflected in grape musts and wines, but not for all elements. Results suggest that winemaking processes and vintage year should be taken into account for the use of elemental composition as a tool for wine traceability. Therefore, understanding the evolution of mineral pattern composition from soil to wine, and how it is influenced by the climatic year, is indispensable for traceability purposes.

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Application of Interactive Regularized Discriminant Analysis to Wine Data

Austrian Journal of Statistics ◽

10.17713/ajs.v35i1.347 ◽

2016 ◽

Vol 35 (1) ◽

Cited By ~ 2

Author(s):

Ute Römisch ◽

Dimitar Vandev ◽

Katrin Zur

Keyword(s):

Discriminant Analysis ◽

Model Building ◽

Geographical Origin ◽

Data Bank ◽

Optimal Choice ◽

Error Rates ◽

Nonlinearity Parameter ◽

Multivariate Statistical Methods ◽

Multivariate Statistical ◽

Discriminant Model

Testing the possibility of determining the geographical origin (country) of wines on the base of chemico-analytical parameters was the aim of the European project ”Establishing of a wine data bank for analytical parameters for wines from Third countries (G6RD-CT-2001-00646-WINE DB)” supported by the European Commission. Therefore a data base containing 400 samples of commercial and authentic wines from Hungary, Czech Republic, Romania and South Africa was created. For each of those samples around 100 analytical parameters, among them rare earth elements and isotopic ratios were measured.Besides other multivariate statistical methods of discrimination and classification the method of regularized discriminant analysis (RDA) was used to distinguish the wines of the different countries on the base of a minimal number of the most important parameters. A MATLAB-program, developed by Vandev (2004) which allows an interactive stepwise discriminant model building on the base of an optimal choice of the “nonlinearity” parameter alpha was used. This program will be described shortly and models for commercial wines with corresponding classification and prediction error rates will be given.As a result of using RDA it was possible to reduce the number of analytical parameters to the eight to infer the geographical origin of these commercial wines.

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Long-term variations in individual particle types in the aerosol of Phoenix, Arizona, as determined using automated electron microprobe analysis and multivariate statistical techniques

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100149544 ◽

1993 ◽

Vol 51 ◽

pp. 742-743

Author(s):

Karen A. Katrinak ◽

James R. Anderson ◽

Peter R. Buseck

Keyword(s):

Electron Microprobe ◽

Fine Fraction ◽

Coarse Fraction ◽

Motor Vehicles ◽

Multivariate Statistical Methods ◽

Multivariate Statistical ◽

X Ray ◽

Mineral Particles ◽

Anthropogenic Air Pollutants

Aerosol samples were collected in Phoenix, Arizona on eleven dates between July 1989 and April 1990. Elemental compositions were determined for approximately 1000 particles per sample using an electron microprobe with an energy-dispersive x-ray spectrometer. Fine-fraction samples (particle cut size of 1 to 2 μm) were analyzed for each date; coarse-fraction samples were also analyzed for four of the dates.The data were reduced using multivariate statistical methods. Cluster analysis was first used to define 35 particle types. 81% of all fine-fraction particles and 84% of the coarse-fraction particles were assigned to these types, which include mineral, metal-rich, sulfur-rich, and salt categories. "Zero-count" particles, consisting entirely of elements lighter than Na, constitute an additional category and dominate the fine fraction, reflecting the importance of anthropogenic air pollutants such as those emitted by motor vehicles. Si- and Ca-rich mineral particles dominate the coarse fraction and are also numerous in the fine fraction.

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Pollen morphology of some Tamarix (Tamaricaceae) species of Iran

Acta Botanica Hungarica ◽

10.1556/034.62.2020.1-2.9 ◽

2020 ◽

Vol 62 (1-2) ◽

pp. 151-161

Author(s):

T. Shagholi ◽

M. Keshavarzi ◽

M. Sheidai

Keyword(s):

North Africa ◽

Pollen Grains ◽

Ecological Niches ◽

Multivariate Statistical Methods ◽

Multivariate Statistical ◽

Qualitative And Quantitative ◽

Petal Length ◽

Electron Microscopes ◽

High Level ◽

Scanning Electron Microscopes

Tamarix L. (Tamaricaceae) is a halophytic shrub in different parts of Asia and North Africa. Taxonomy and species limitation of Tamarix is very complex. This genus has three sections as Tamarix, Oligadenia, and Polyadenia, which are mainly separated by petal length, the number of stamens, the shape of androecial disk and attachment of filament on the androecial disk. As there was no palynological data on pollen features of Tamarix species of Iran, in the present study 12 qualitative and quantitative pollen features were evaluated to find diagnostic ones. Pollen grains of 8 Tamarix species were collected from nature. Pollen grains were studied without any treatment. Measurements were based on at least 50 pollen grains per specimen. Light and scanning electron microscopes were used. Multivariate statistical methods were applied to clarify the species relationships based on pollen data. All species studied showed monad and tricolpate (except some individuals of T. androssowii). Some Tamarix species show a high level of variability, in response to ecological niches and phenotypic plasticity, which make Tamarix species separation much more difficult. Based on the results of the present study, pollen grains features are not in agreement with previous morphological and molecular genetics about the sectional distinction.

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