The use of two-dimensional NMR relaxometry in bread staling: a valuable tool?

Curti, Elena; Carini, Eleonora; Cobo, Miriam; Bocher, Temesgen; Vittadini, Elena

doi:10.1016/j.foodchem.2017.05.143

Cited by 18 publications

(9 citation statements)

References 21 publications

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“…In good time, multi-dimensional NMR techniques are well developed within the NMR community. With the development of fast and highly efficient multidimensional Inverse Laplace decomposition algorithm [22][23][24], and the recent demonstration of two-dimensional lowfield NMR relaxometry applications [24][25][26]] maybe the answer. By decomposing the multiple proton relaxation reservoirs arising from the water-protein interactions in red blood cells (RBCs), one could hypothetically capture the unique phenotypic expression (e.g., physiological patterns) at every stage of infection.…”

Section: Towards the Nmr-based Personalized Malaria Medicinementioning

confidence: 99%

“…These phenotypic variations could be based on geographical location or differential transmission setting or even the different ring developmental stage or other genetic factors that needs to work together to reveal a phenotype [29]. Therefore, the NMR or other spectroscopic technologies [25,30,31] could aid with the challenges we are facing in detecting anti-malarial drug resistance providing more meaningful information as rapid phenotyping rather than genotyping.…”

Section: Towards the Nmr-based Personalized Malaria Medicinementioning

confidence: 99%

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Rapid phenotyping towards personalized malaria medicine

Veiga

Peng

2020

Malar J

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Malaria is major public health concerns which continues to claim the lives of more than 435,000 people each year. The challenges with anti-malarial drug resistance and detection of low parasitaemia forms an immediate barrier to achieve the fast-approaching United Nations Sustainable Development Goals of ending malaria epidemics by 2030. In this Opinion article, focusing on the recent published technologies, in particularly the nuclear magnetic resonance (NMR)-based diagnostic technologies, the authors offer their perspectives and highlight ways to bring these pointof-care technologies towards personalized medicine. To this end, they advocate an open sourcing initiative to rapidly close the gap between technological innovations and field implementation.

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Section: Towards the Nmr-based Personalized Malaria Medicinementioning

confidence: 99%

Section: Towards the Nmr-based Personalized Malaria Medicinementioning

confidence: 99%

Rapid phenotyping towards personalized malaria medicine

Veiga

Peng

2020

Malar J

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“…Analysis of the NMR spectra resulting from NMR spectroscopy of cereal samples provides precise information on the amount and type of chemical bonds present in their structure (Belton, 2011). NMR spectroscopy is able to detect changes in nuclei concentration of carbon and/or hydrogen and thus can be used to evaluate the content and distribution of polysaccharides, water, and oil in food products (Curti, Carini, Cobo, Bocher, & Vittadini, 2017;Nielsen, Hyldig, Nielsen, & Nielsen, 2005;Vil en, Lundqvist, Jouanneau, Helbert, & Sandstr€ om, 2010;Windt, Gerkema, & Van As, 2009). The first application of NMR technology was in the study of the molecular structure of organic chemical compounds in the late 1940s (Gutowsky, Kistiakowsky, Pake, & Purcell, 1949).…”

Section: Resonance Spectroscopymentioning

confidence: 99%

Advancing the science of wheat quality evaluation using nuclear magnetic resonance (NMR) and ultrasound‐based techniques

et al. 2018

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Background and objectives The need for cost‐effective, fast, and reliable techniques to evaluate wheat protein content and quality has led to the modification of available methods as well as the development of new methods. This review provides information on two emerging methods, that is, low‐field nuclear magnetic resonance (LF‐NMR) and low‐intensity ultrasound, with potential for evaluating wheat protein content and quality. Findings New techniques with additional capabilities have been developed over the years to provide wheat researchers with information that could not be acquired by the use of conventional methods. LF‐NMR and low‐intensity ultrasound are two emerging techniques in the world of cereal science whose speed, ease of operation, and reliability could promote their applications to wheat screening research studies. This review of these two potential wheat protein quality evaluation methods highlights the necessity of developing such cutting‐edge tools which are advantageous over the conventional tools. Conclusions Easy‐to‐use LF‐NMR and low‐intensity ultrasound seem to have the potential to provide nondestructive, fast evaluation methods that are superior to the currently used techniques in terms of accuracy and cost, respectively. However, further investigations to achieve complete development of such methods are still required. Significance and novelty The potential of LF‐NMR and low‐intensity ultrasound as fast, accurate, and cost‐effective wheat screening tools was confirmed through critical discussions and comparisons of a variety of most widely used wheat quality evaluation techniques.

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“…High resolution nuclear magnetic resonance (NMR) spectroscopy is a powerful and attractive approach in biochemistry (e.g., protein analysis, 1 metabolomics, 2‐4 ) and inorganic chemistry 5 . In recent years however, with the rapid advances in NMR engineering (e.g., IC‐based spectrometer, 6‐12 microfluidic‐based chip, 13‐17 artificial intelligence 18,19 ) utilizing small foot‐print permanent magnet, time‐domain NMR instrumentations have seen a myriad of interesting applications from point‐of‐care testing (PoCT) medical diagnosis 7,13,20‐26 to industrial food science 27,28 and in‐situ oil‐gas exploration 29,30 …”

Section: Introductionmentioning

confidence: 99%

Clustering Nuclear Magnetic Resonance: Machine learning assistive rapid two‐dimensional relaxometry mapping

Peng

2021

Engineering Reports

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Low‐field nuclear magnetic resonance (NMR) relaxometry is an attractive approach from point‐of‐care testing medical diagnosis to in situ oil‐gas exploration. One of the problems, however, is the inherently long relaxation time of the (liquid) samples, (and hence low signal‐to‐noise ratio) which causes unnecessarily long repetition time. In this work, a new class of methodology is presented for rapid and accurate object classification using NMR relaxometry with the aid of machine learning. It is demonstrated that the sensitivity and specificity of the classification is substantially improved with higher order of (pseudo)‐dimensionality (e.g., 2D‐ or multi‐dimensional). This new methodology (termed as ‘Clustering NMR’) may be extremely useful for rapid and accurate object classification (in less than a minute) using low‐field NMR.

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The use of two-dimensional NMR relaxometry in bread staling: a valuable tool?

Cited by 18 publications

References 21 publications

Rapid phenotyping towards personalized malaria medicine

Rapid phenotyping towards personalized malaria medicine

Advancing the science of wheat quality evaluation using nuclear magnetic resonance (NMR) and ultrasound‐based techniques

Clustering Nuclear Magnetic Resonance: Machine learning assistive rapid two‐dimensional relaxometry mapping

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