Identification of Geographical Origin of Honeysuckle (Lonicera Japonica Thunb) by Discriminant Analysis Using Rare Earth Elements

2016 ◽  
Vol 49 (14) ◽  
pp. 2312-2321 ◽  
Author(s):  
Zhanglin Ni ◽  
Qing Yu ◽  
Yihua Liu ◽  
Fubin Tang
2016 ◽  
Vol 213 ◽  
pp. 238-245 ◽  
Author(s):  
Spiros A. Drivelos ◽  
Georgios P. Danezis ◽  
Serkos A. Haroutounian ◽  
Constantinos A. Georgiou

2018 ◽  
Vol 98 (12) ◽  
pp. 4769-4777 ◽  
Author(s):  
Donata Bandoniene ◽  
Thomas Meisel ◽  
Alessandra Rachetti ◽  
Christoph Walkner

2020 ◽  
Author(s):  
Manfred Sager

<p></p><p></p><p>Because the abundances of rare earth elements are strongly intercorrelated, lacking data can be estimated from adjacent element concentrations. Because Ce can be oxidized to Ce(IV) and Eu can be reduced to Eu(II), deviations from the calculated values have been defined as positive or negative anomalies. The anomalies permit conclusions of mineral weathering, transportation and adsorption.</p><p>Anomalies detected in soils did not cause respective anomalies in apple leaves, blossom leaves nor fruits, which prevents conclusions of geographical origin. In the apple plants, Ce showed negative anomalies throughout, particularly in the blossom leaves. To the contrary, Eu showed positive anomalies throughout, particularly in the green leaves, which suggests uptake similar to Ca.</p><p>In green leaves (apples) growing in the temperate climatic zone, concentrations of rare earth elements increase with age, like for other elements of low physiological interaction also, whereas nutritional and essential trace elements remain constant or decrease.</p><p> </p>


2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Maria Olga Varrà ◽  
Sergio Ghidini ◽  
Emanuela Zanardi ◽  
Anna Badiani ◽  
Adriana Ianieri

In this work, stable isotope ratio (SIR) and rare earth elements (REEs) analyses, combined with multivariate data elaboration, were used to explore the possibility to authenticate European sea bass (Dicentrarchus labrax L.) according to: i) production method (wild or farmed specimens); ii) geographical origin (Western, Central or Eastern Mediterranean Sea). The dataset under investigation included a total of 144 wild and farmed specimens coming from 17 different European areas located in the Mediterranean Sea basin. Samples were subjected to SIR analysis (carbon and nitrogen) and REEs analysis (lanthanum, europium, holmium, erbium, lutetium, and terbium). Then, Analytical data were handled by Principal Component Analysis (PCA) and then by Orthogonal Partial Last Square Discriminant Analysis (OPLS-DA), to obtain functional classification models to qualitatively discriminate sea bass according to the conditions under study. OPLSDA models provided good correct classification rate both for production method and geographical origin. It was confirmed that chemometric elaboration of data obtained from SIR and REEs analyses can be a suitable tool for an accurate authentication of European sea bass.


2020 ◽  
Vol 17 (2) ◽  
pp. 148 ◽  
Author(s):  
Dana Alina Magdas ◽  
Olivian Marincas ◽  
Gabriela Cristea ◽  
Ioana Feher ◽  
Nicoleta Vedeanu

Environmental contextRare earth element profiles of foodstuffs reflect both the soil fingerprint and the specific agricultural practice for a certain location. This review describes the advantages and limitations of using rare earth elements as markers for geographical discrimination as a function of food matrix. The technique has great potential for establishing the geographical origin of foodstuffs. AbstractThe present work aims to present the application of the content of rare earth elements (REEs) in the authentication of food and beverage studies, mainly regarding the geographical origin. Therefore, the potential, as well as the limitation, of these emerging markers are separately presented for different food matrices. It is observed that for most of the discussed matrices, the highest discrimination potential is provided by the LREEs (light REEs). It has also been suggested in the literature that the content of REEs is minimally affected by harvesting years, which enhances the potential to differentiate between samples from different origins. Reported studies have shown that the efficiency of the REEs profile is the most effective for the unprocessed food matrix (e.g. vegetables, fruits and meat) and has a low efficiency for commodities like wine, which suggests that the fractionation of REEs that occurs during the wine making process limits the use of these elements as geographical tracers.


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