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]

Low and high field Magnetic Resonance Imaging and its application in food science and plants / Cristina Ripoli , 2018 Nov 20., Anno Accademico 2016 - 2017. [10.14273/unisa-2589].

Low and high field Magnetic Resonance Imaging and its application in food science and plants

Ripoli, Cristina
2018

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]
20-nov-2018
Matematica, Fisica ed Applicazioni
Mri
T2
Food
De Pasquale, Salvatore
Scarpa, Roberto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4924478
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