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投稿时间:2019-07-31
投稿时间:2019-07-31
中文摘要: 该文研究新型玉米浸泡工艺和玉米浸泡过程中菌群的结构组成与变化规律。利用H2O2与乳酸协同浸泡玉米,通过正交试验确定最优浸泡条件,并利用Miseq高通量测序技术对浸泡过程中的细菌进行多样性分析。正交试验表明,玉米浸泡的最优条件为初始乳酸浓度0.6%、乳酸作用时间16 h、H2O2浓度3%、H2O2作用时间22 h,在最优条件下,淀粉得率由传统工艺的56.02%提高到68.53%,浸泡时间缩短32 h。Miseq高通量测序分析结果表明,浸泡初期细菌结构组成较为丰富,一段时间后,乳酸杆菌Lactobacillaceae生长繁殖成为优势菌种并伴随运算的分类单位(operational taxonomic unit,OTU)水平的降低,浸泡末期Lactobacillaceae进入衰亡期,其他细菌数量明显增加。对浸泡液中细菌的群落结构与环境相关性进行分析,发现引起菌落结构差异的影响因素依次为乳酸含量、葡萄糖含量、浸泡液pH值、浸泡温度。
中文关键词: H2O2 玉米浸泡 Miseq高通量测序 菌群结构 绿色浸泡
Abstract:In this paper,the new corn steeping technology of and studying structure composition and changing rule of microflora in corn steeping process were studied.H2O2and lactic acid were used to co-steep corn,the optimal steeping conditions were determined by orthogonal experiment,and the diversity of bacteria in the steeping process was analyzed by Miseq high-throughput sequencing technology.Orthogonal test showed that the optimal conditions for steeping corn were initial lactic acid concentration of 0.6%,lactic acid action time of 16 h,H2O2concentration of 3%,and H2O2action time of 22 h.Under the optimal conditions,the starch yield increased from 56.02%to 68.53%,and the steeping time was shortened by 32 h.The results of Miseq highthroughput sequencing analysis showed that the bacterial structure and composition were relatively rich at the early stage of immersion.After a period of time,Lactobacillaceae grew and became the dominant species,accompanied by the reduction of operational taxonomic unit (OUT) level.At the end of immersion,Lactobacillaceae entered the decline period,and the number of other bacteria significantly increased.By analyzed the correlation between the community structure of the bacteria in the steeping solution and the environment,it was found that the influencing factors causing the differences in the colony structure were lactic acid content,glucose content,the pH of the steeping solution,and steeping temperature in turn.
文章编号:202014017 中图分类号: 文献标志码:
基金项目:山东省重点研发计划项目(2019GSF109017);山东省重大科技创新工程项目(2018CXGC0608);山东省重点研发计划项目(2017GSF221014)
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