Metabolomics is a tool used for quantitative assessment of metabolites that has been applied extensively in the field of food science. Recently, metabolomics-based gas chromatography-mass spectrometry (GC/MS) is becoming a common tool for analyzing, not only volatile compounds, but also non-volatile compounds due to the development of various derivatization methods. Although several studies have reviewed the application of metabolomics in food science, this present review article specifically focuses on metabolomics research using GC/MS for analysis of non-volatile compounds such as sugars, amino acids, and organic acids. From exhaustive literature research, the application of GC/MS-based metabolomics for non-volatile compounds in food science includes discriminating food samples based on cultivars and authentication of food samples to prevent food fraud, characterizing the profile of food samples to provide a general overview of the sample, evaluating stress-response, optimizing postharvest processes based on metabolic changes, monitoring changes during growth and food processing, evaluating and predicting food quality, and evaluating food shelf-life. GC/MS-based analysis of non-volatile compounds has been proven to be extremely valuable in food science, and might open new avenues for future researchers and engineers to develop instruments or improving production process in food industry.
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http://dx.doi.org/10.1016/j.jbiosc.2022.01.011 | DOI Listing |
Annu Rev Food Sci Technol
January 2025
4Division of Food and Nutrition, Chonnam National University, Gwangju, Republic of Korea; email:
Tea () is one of the most popular nonalcoholic beverages in the world, second only to water. Six main types of teas are produced globally: green, white, black, oolong, yellow, and Pu-erh. Each type has a distinctive taste, quality, and cultural significance.
View Article and Find Full Text PDFJ Agric Food Chem
January 2025
Yibin Academy of Southwest University, Yibin 644000, China.
Consumer concerns regarding food nutrition and quality are becoming increasingly prevalent. High-resolution mass spectrometry (HRMS)-based metabolomics stands as a cutting-edge and widely embraced technique in the realm of food component analysis and detection. It boasts the capability to identify character metabolites at exceedingly low abundances, which remain undetectable by conventional platforms.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Nutrition, Dietetics and Food Science, Brigham Young University, Provo, Utah, United States of America.
The objective of this study was to develop and to test the validity and reliability of a survey aimed to evaluate internal and external factors associated with college food insecurity. Researchers used a mixed methods approach to evaluate the College Perspectives around Food Insecurity survey. Survey items were constructed from interview data and assigned a social cognitive theory concept (environment, personal, or behavior).
View Article and Find Full Text PDFProc Natl Acad Sci U S A
February 2025
Department of Agricultural Biotechnology, and Research Institute of Agriculture and Life Sciences, CALS, Seoul National University, Seoul 08826, Republic of Korea.
The formation of superoxide dismutase 1 (SOD1) filaments has been implicated in amyotrophic lateral sclerosis (ALS). Although the disulfide bond formed between Cys57 and Cys146 in the active state has been well studied, the role of the reduced cysteine residues, Cys6 and Cys111, in SOD1 filament formation remains unclear. In this study, we investigated the role of reduced cysteine residues by determining and comparing cryoelectron microscopy (cryo-EM) structures of wild-type (WT) and C6A/C111A SOD1 filaments under thiol-based reducing and metal-depriving conditions, starting with protein samples possessing enzymatic activity.
View Article and Find Full Text PDFPLoS One
January 2025
SSL Lab, Dept. of CSE, Islamic University of Technology, Dhaka, Bangladesh.
Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In this study, we present a dataset named the "Assorted, Archetypal, and Annotated Two Million Extended (3A2M+) Cooking Recipe Dataset" that contains two million culinary recipes labeled in respective categories with extended named entities extracted from recipe descriptions.
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