한빛사 논문
Ramachandran Chelliah1, Eric Banan-MwineDaliri1, Imran Khan12, Shuai Wei13, Fazle Elahi1, Su-Jung Yeon1, Vijayalakshmi Selvakumar1, Fred Kwame Ofosu1, Momna Rubab1, Hum Hun Ju4, Harikrishna Reddy Rallabandi1, Inamul Hasan Madar5, Ghazala Sultan6, Deog Hwan Oh1
1Department of Food Science and Biotechnology, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon, Gangwon-do 24341, Korea.
2Department of Biotechnology, University of Malakand, Khyber Pakhtunkhwa Pakistan.
3Guangdong Provincial Key Laboratory of Aquatic Product Processing and Safety, College of Food Science and Technology, Guangdong Ocean University, Zhanjiang 524088, China.
4Department of Biological Environment, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon, Gangwon-do 24341, Korea.
5Department of Biochemistry, School of Life Science, Bharathidasan, University, Thiruchirappalli, Tamilnadu, India.
6Department of Computer Science, Aligarh Muslim University, Aligarh, Uttar Pradesh, 202002, India.
Corresponding authors: D.H. Oh, R. Chelliah, D
Abstract
There is currently a transformed interest toward understanding the impact of fermentation on functional food development due to growing consumer interest on modified health benefits of sustainable foods. In this review, we attempt to summarize recent findings regarding the impact of Next-generation sequencing and other bioinformatics methods in the food microbiome and use prediction software to understand the critical role of microbes in producing fermented foods. Traditionally, fermentation methods and starter culture development were considered conventional methods needing optimization to eliminate errors in technique and were influenced by technical knowledge of fermentation. Recent advances in high-output omics innovations permit the implementation of additional logical tactics for developing fermentation methods. Further, the review describes the multiple functions of the predictions based on docking studies and the correlation of genomic and metabolomic analysis to develop trends to understand the potential food microbiome interactions and associated products to become a part of a healthy diet.
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