Utilizza questo identificativo per citare o creare un link a questo documento: http://elea.unisa.it/xmlui/handle/10556/4385
Titolo: Low and high field Magnetic Resonance Imaging and its application in food science and plants
Autore: Ripoli, Cristina
Scarpa, Roberto
De Pasquale, Salvatore
Parole chiave: Mri;T2;Food
Data: 20-nov-2018
Editore: Universita degli studi di Salerno
Abstract: Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) are techniques that have seen a remarkable success and a fast growth over the past decades. Thanks to its non-invasivity and non-descrutivity, the MRI enhances its potential to perform inspections and studies of the internal structure of intact samples such as fruits and vegetables. without modifications caused by the measurements Due to the presence of a high water content in these products, MRI can be useful to obtain information about tissue properties and, thanks to the high sensitivity, can trace water distribution and migration. The characteristic NMR relaxation times are used as parameters for the quantification of water content or for the extraction of information related to changes in microstructure. The idea behind this thesis is the investigation of new methodologies intended to carry out fast and accurate evaluation of moisture content in a food matrix through MRI. At the same time the development of appropriate protocols and analysis tools allowing a simple extraction of those information in a reproducible and reliable way. Two different approaches have been used, both based on data extracted by MR Imaging and a comparison of the two methods is presented. The goal is to exploit MRI as a real measurement instrument with a simple and fast measurement protocol: to achieve this goal we need to identify quantitative MR parameters that provide the most relevant information with respect to the physical quantities we want to measure. To use and validate the MRI as quantitative tool is our major challenge and the results obtained in this thesis keep us confident about the achievement of this goal. This could hopefully open a way for new methods to perform MRI analysis. [edited by Author]
Descrizione: 2016 - 2017
URI: http://elea.unisa.it:8080/xmlui/handle/10556/4385
http://dx.doi.org/10.14273/unisa-2589
È visualizzato nelle collezioni:Matematica, Fisica ed Applicazioni

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tesi di dottorato C. Ripoli.pdftesi di dottorato5,51 MBAdobe PDFVisualizza/apri
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