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Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare

This study exploits quantitative algorithms of Raman spectroscopy to assess, at the molecular scale, the nutritional quality of individual kernels of the Japanese short-grain rice cultivar Koshihikari in terms of amylose-to-amylopectin ratio, fractions of phenylalanine and tryptophan aromatic amino...

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Autores principales: Pezzotti, Giuseppe, Tsubota, Yusuke, Zhu, Wenliang, Marin, Elia, Masumura, Takehiro, Kobayashi, Takuya, Nakazaki, Tetsuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606906/
https://www.ncbi.nlm.nih.gov/pubmed/37893662
http://dx.doi.org/10.3390/foods12203771
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author Pezzotti, Giuseppe
Tsubota, Yusuke
Zhu, Wenliang
Marin, Elia
Masumura, Takehiro
Kobayashi, Takuya
Nakazaki, Tetsuya
author_facet Pezzotti, Giuseppe
Tsubota, Yusuke
Zhu, Wenliang
Marin, Elia
Masumura, Takehiro
Kobayashi, Takuya
Nakazaki, Tetsuya
author_sort Pezzotti, Giuseppe
collection PubMed
description This study exploits quantitative algorithms of Raman spectroscopy to assess, at the molecular scale, the nutritional quality of individual kernels of the Japanese short-grain rice cultivar Koshihikari in terms of amylose-to-amylopectin ratio, fractions of phenylalanine and tryptophan aromatic amino acid residues, protein-to-carbohydrate ratio, and fractions of protein secondary structures. Statistical assessments on a large number of rice kernels reveal wide distributions of the above nutritional parameters over nominally homogeneous kernel batches. This demonstrates that genetic classifications cannot catch omic fluctuations, which are strongly influenced by a number of extrinsic factors, including the location of individual grass plants within the same rice field and the level of kernel maturation. The possibility of collecting nearly real-time Raman “multi-omic snapshots” of individual rice kernels allows for the automatic (low-cost) differentiation of groups of kernels with restricted nutritional characteristics that could be used in the formulation of functional foods for specific diseases and in positively modulating the intestinal microbiota for protection against bacterial infection and cancer prevention.
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spelling pubmed-106069062023-10-28 Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare Pezzotti, Giuseppe Tsubota, Yusuke Zhu, Wenliang Marin, Elia Masumura, Takehiro Kobayashi, Takuya Nakazaki, Tetsuya Foods Article This study exploits quantitative algorithms of Raman spectroscopy to assess, at the molecular scale, the nutritional quality of individual kernels of the Japanese short-grain rice cultivar Koshihikari in terms of amylose-to-amylopectin ratio, fractions of phenylalanine and tryptophan aromatic amino acid residues, protein-to-carbohydrate ratio, and fractions of protein secondary structures. Statistical assessments on a large number of rice kernels reveal wide distributions of the above nutritional parameters over nominally homogeneous kernel batches. This demonstrates that genetic classifications cannot catch omic fluctuations, which are strongly influenced by a number of extrinsic factors, including the location of individual grass plants within the same rice field and the level of kernel maturation. The possibility of collecting nearly real-time Raman “multi-omic snapshots” of individual rice kernels allows for the automatic (low-cost) differentiation of groups of kernels with restricted nutritional characteristics that could be used in the formulation of functional foods for specific diseases and in positively modulating the intestinal microbiota for protection against bacterial infection and cancer prevention. MDPI 2023-10-13 /pmc/articles/PMC10606906/ /pubmed/37893662 http://dx.doi.org/10.3390/foods12203771 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pezzotti, Giuseppe
Tsubota, Yusuke
Zhu, Wenliang
Marin, Elia
Masumura, Takehiro
Kobayashi, Takuya
Nakazaki, Tetsuya
Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare
title Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare
title_full Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare
title_fullStr Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare
title_full_unstemmed Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare
title_short Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare
title_sort raman multi-omic snapshots of koshihikari rice kernels reveal important molecular diversities with potential benefits in healthcare
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606906/
https://www.ncbi.nlm.nih.gov/pubmed/37893662
http://dx.doi.org/10.3390/foods12203771
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