Comparison study of the volatile profiles and microbial communities of Wuyi Qu and Gutian Qu, two major types of traditional fermentation starters of Hong Qu glutinous rice wine

紫色红曲霉 生物 葡萄酒 食品科学 红曲霉 发酵 偏最小二乘回归 植物 微生物种群生物学 微生物 细菌 数学 遗传学 统计
作者
Zhibin Liu,Zhiyao Wang,Xu‐Cong Lv,Xiaoping Zhu,Liling Chen,Li Ni
出处
期刊:Food Microbiology [Elsevier BV]
卷期号:69: 105-115 被引量:75
标识
DOI:10.1016/j.fm.2017.07.019
摘要

Hong Qu, which mainly contains Monascus sp. and other microorganisms, as well as numerous microbial metabolites, is used as the fermentation starter of Hong Qu glutinous rice wine, a traditional alcoholic beverage. Two widely-used types of Hong Qu, namely Wuyi Qu (WYQ) and Gutian Qu (GTQ), were thoroughly compared for their fermentation properties, volatile profiles, and microbiota structures in this study. Significantly higher color value, glucoamylase and α-amylase activities were discovered in WYQ. And substantial variation in volatile components and microbial communities were also observed between them. It was identified that bacterial genus Burkholderia dominated GTQ (71.62%) and Bacillus dominated WYQ (44.73%), while Monascus purpureus was the most abundant fungal species in both types of starters (76.99%). In addition, 213 bacterial genera and 150 fungal species with low-abundance were also detected. Since the Linear Discriminant Analysis Effect Size algorithm, 14 genus-level bacterial taxa and 10 species-level fungal taxa could be utilized to distinguish these two types of starters. Moreover, the potential correlation of the volatile components and microbiota within WYQ and GTQ were further analyzed, by utilizing Partial Least Squares Discriminant Analysis. Ultimately, this study provides detailed insight into the volatile profiles and microbial communities presented in Hong Qu.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
chen发布了新的文献求助10
1秒前
zz发布了新的文献求助10
1秒前
无极微光应助顺心的扬采纳,获得20
1秒前
夏xia完成签到 ,获得积分10
2秒前
2秒前
淡然宛凝发布了新的文献求助10
3秒前
3秒前
大白应助茕凡桃七采纳,获得10
4秒前
Starwalker应助bibi11采纳,获得30
4秒前
小马甲应助精明的花瓣采纳,获得10
4秒前
77777777完成签到,获得积分10
4秒前
chen完成签到,获得积分10
5秒前
6秒前
jialin完成签到,获得积分10
6秒前
xingfangshu完成签到,获得积分10
6秒前
甜蜜黎云完成签到,获得积分10
7秒前
7秒前
无忧应助醉熏的筮采纳,获得10
7秒前
找找找完成签到,获得积分10
7秒前
8秒前
8秒前
8秒前
Eden完成签到,获得积分10
9秒前
华仔应助Li采纳,获得10
9秒前
酷波er应助香菜碗里来采纳,获得10
10秒前
10秒前
阿兔子完成签到,获得积分10
11秒前
SHIKI发布了新的文献求助10
11秒前
科研通AI2S应助找找找采纳,获得10
12秒前
12秒前
Hello应助无情的凝蝶采纳,获得10
12秒前
田様应助tester_gater采纳,获得10
13秒前
称心问枫发布了新的文献求助10
13秒前
Tianping完成签到,获得积分10
13秒前
镯镯发布了新的文献求助10
13秒前
13秒前
李金梅发布了新的文献求助10
13秒前
希望天下0贩的0应助bai采纳,获得10
14秒前
wanci应助甜甜青雪采纳,获得10
14秒前
英勇含烟完成签到,获得积分10
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
Elevating Next Generation Genomic Science and Technology using Machine Learning in the Healthcare Industry Applied Machine Learning for IoT and Data Analytics 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6442992
求助须知:如何正确求助?哪些是违规求助? 8256980
关于积分的说明 17584489
捐赠科研通 5501550
什么是DOI,文献DOI怎么找? 2900761
邀请新用户注册赠送积分活动 1877782
关于科研通互助平台的介绍 1717445