首页|Study Findings from Jiangnan University Broaden Understanding of Machine Learning (Predicting the Multispecies Solid-state Vinegar Fermentation Process Using Single-cell Raman Spectroscopy Combined With Machine Learning)
Study Findings from Jiangnan University Broaden Understanding of Machine Learning (Predicting the Multispecies Solid-state Vinegar Fermentation Process Using Single-cell Raman Spectroscopy Combined With Machine Learning)
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NETL
NSTL
Elsevier
Researchers detail new data in Machine Learning. According to news reporting originating in Wuxi, People’s Republic of China, by NewsRx journalists, research stated, “Microbial community is a key contributing factor for flavor formation in natural food fermentation. However, it is a challenge to maintain batch -to -batch uniformity during the fermentation process due to the diversity and variability of microbial community.” Financial supporters for this research include National Key Research and Devel- opment Program of China, National Natural Science Foundation of China (NSFC), International Science and Technology Cooperation Research Program of Zhenjiang, Jiangsu Provincial project. The news reporters obtained a quote from the research from Jiangnan University, “A rapid detection of the structure and function of the microbial community in the whole fermentation process is of great importance for quality control of the final fermentation products. Firstly, we employed amplicon sequencing to target the dominant operational taxonomic units in the microbial community of Zhenjiang aromatic vinegar, a traditional cereal vinegar. Secondly, we isolated and created a Raman database for 13 dominant bacterial species from vinegar culture, enabling us to establish a logistic regression model with 96.4% accuracy in species classification. Finally, a Raman -fermentation phase regression model was established, achieving an R2 of 0.952, accurately determining the actual fermentation phase of vinegar.”
WuxiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningJiangnan University
NETL
NSTL
Elsevier
