Metabolomic Technology in Quality and Safety of Agricultural Products and Foods

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Food Metabolomics".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 2161

Special Issue Editor


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Guest Editor
Research Center for Advanced Analysis, National Agriculture and Food Research Organization (NARO), Tsukuba 305-8642, Japan
Interests: metabolomics; NMR; data science; food chemistry; analytical chemistry; bioinformatics

Special Issue Information

Dear Colleagues,

Metabolomics is a powerful tool for the analysis and evaluation of the complex and diverse metabolite mixtures found in agricultural products and foods. Metabolomic studies provide useful information, e.g., how to improve nutritional and functional qualities, prevent food poisoning, and understand the processing and storage effects. In addition, the metabolomic technology in this field is constantly being advanced owing to the recent developments in computer science and information technology.

This Special Issue focuses on the recent advancements in metabolomic technology that has been made to address agricultural products and foods. The topics to be covered include an application of metabolomic technology for the evaluation and analysis of agricultural products and foods as well as the methodological advancements in metabolomic analysis using agricultural and food big data.

Dr. Yasuhiro Date
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • metabolomics
  • metabolic profiling
  • metabolic fingerprinting
  • foodomics
  • nuclear magnetic resonance spectroscopy
  • mass spectrometry
  • multivariate analysis
  • machine learning

Published Papers (2 papers)

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Research

13 pages, 13204 KiB  
Article
Explorative Study on Volatile Organic Compounds of Cinnamon Based on GC-IMS
by Yu Pan, Liya Qiao, Shanshuo Liu, Ye He, Danna Huang, Wuwei Wu, Yingying Liu, Lu Chen and Dan Huang
Metabolites 2024, 14(5), 274; https://doi.org/10.3390/metabo14050274 - 9 May 2024
Viewed by 795
Abstract
Cinnamon is one of the most popular spices worldwide, and volatile organic compounds (VOCs) are its main metabolic products. The misuse or mixing of cinnamon on the market is quite serious. This study used gas chromatography-ion migration spectroscopy (GC-IMS) technology to analyze the [...] Read more.
Cinnamon is one of the most popular spices worldwide, and volatile organic compounds (VOCs) are its main metabolic products. The misuse or mixing of cinnamon on the market is quite serious. This study used gas chromatography-ion migration spectroscopy (GC-IMS) technology to analyze the VOCs of cinnamon samples. The measurement results showed that 66 VOCs were detected in cinnamon, with terpenes being the main component accounting for 45.45%, followed by aldehydes accounting for 21.21%. The content of esters and aldehydes was higher in RG-01, RG-02, and RG-04; the content of alcohols was higher in RG-01; and the content of ketones was higher in RG-02. Principal component analysis, cluster analysis, and partial least squares regression analysis can be performed on the obtained data to clearly distinguish cinnamon. According to the VIP results of PLS-DA, 1-Hexanol, 2-heptanone, ethanol, and other substances are the main volatile substances that distinguish cinnamon. This study combined GC-IMS technology with chemometrics to accurately identify cinnamon samples, providing scientific guidance for the efficient utilization of cinnamon. At the same time, this study is of great significance for improving the relevant quality standards of spices and guiding the safe use of spices. Full article
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17 pages, 2604 KiB  
Article
A Data-Driven Approach to Sugarcane Breeding Programs with Agronomic Characteristics and Amino Acid Constituent Profiling
by Chiaki Ishikawa, Yasuhiro Date, Makoto Umeda, Yusuke Tarumoto, Megumi Okubo, Yasujiro Morimitsu, Yasuaki Tamura, Yoichi Nishiba and Hiroshi Ono
Metabolites 2024, 14(4), 243; https://doi.org/10.3390/metabo14040243 - 21 Apr 2024
Viewed by 856
Abstract
Sugarcane (Saccharum spp. hybrids) and its processed products have supported local industries such as those in the Nansei Islands, Japan. To improve the sugarcane quality and productivity, breeders select better clones by evaluating agronomic characteristics, such as commercially recoverable sugar and cane [...] Read more.
Sugarcane (Saccharum spp. hybrids) and its processed products have supported local industries such as those in the Nansei Islands, Japan. To improve the sugarcane quality and productivity, breeders select better clones by evaluating agronomic characteristics, such as commercially recoverable sugar and cane yield. However, other constituents in sugarcane remain largely unutilized in sugarcane breeding programs. This study aims to establish a data-driven approach to analyze agronomic characteristics from breeding programs. This approach also determines a correlation between agronomic characteristics and free amino acid composition to make breeding programs more efficient. Sugarcane was sampled in clones in the later stage of breeding selection and cultivars from experimental fields on Tanegashima Island. Principal component analysis and hierarchical cluster analysis using agronomic characteristics revealed the diversity and variability of each sample, and the data-driven approach classified cultivars and clones into three groups based on yield type. A comparison of free amino acid constituents between these groups revealed significant differences in amino acids such as asparagine and glutamine. This approach dealing with a large volume of data on agronomic characteristics will be useful for assessing the characteristics of potential clones under selection and accelerating breeding programs. Full article
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