NMR metabolic fingerprinting of some plants and fruits

Nicolescu Alina Florica; Ciobanu Mihaela; Stavarache Cristina; Ailiesei Gabriela; Danila Doina; Stefanache Camelia Paula; Silion Mihalea; Macsim Ana-Maria; Ciocarlan Alexandru; Deleanu Călin

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2021-03-29 21:41

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NICOLESCU, Alina Florica, CIOBANU, Mihaela, STAVARACHE, Cristina, AILIESEI, Gabriela, DANILA, Doina, STEFANACHE, Camelia Paula, SILION, Mihalea, MACSIM, Ana-Maria, CIOCARLAN, Alexandru, DELEANU, Călin. NMR metabolic fingerprinting of some plants and fruits. In: Physical Methods in Coordination and Supramolecular Chemistry, 8-9 octombrie 2015, Chişinău. Chisinau, Republic of Moldova: 2015, XVIII, p. 31.

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Physical Methods in Coordination and Supramolecular Chemistry
XVIII, 2015

Conferința ""Physical Methods in Coordination and Supramolecular Chemistry""
Chişinău, Moldova, 8-9 octombrie 2015

NMR metabolic fingerprinting of some plants and fruits

Pag. 31-31

Nicolescu Alina Florica¹², Ciobanu Mihaela¹, Stavarache Cristina², Ailiesei Gabriela¹, Danila Doina³, Stefanache Camelia Paula³, Silion Mihalea¹, Macsim Ana-Maria¹, Ciocarlan Alexandru⁴, Deleanu Călin¹²

¹ “Petru Poni” Institute of Macromolecular Chemistry,
² "C.D. Nenitzescu" Centre of Organic Chemistry, Romanian Academy,
³ Center of Biological Sciences „Stejarul”, Piatra Neamţ,
⁴ Institute of Chemistry

Disponibil în IBN: 20 aprilie 2020

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NMR spectroscopy is already established as a powerful analytical tool in plant research. The main advantage of this technique is that it provides the sample’s profile in one analysis. The chemical composition of different vegetal matrices is important for life sciences such as food science and medicine. One of the ways to characterize plants through high resolution NMR is to analyze the juice obtained by squeezing different plant components. The paper presents a feasibility study for fast and automatic discrimination of natural or processed juices from different plants (like Arnica Montana L.) and fruits (like apples, oranges, etc). The NMR data have been subjected to statistical processing in order to develop a model for plants and fruits discrimination based on metabolomic spectral fingerprinting.

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