Probiotic fermentation environment control under intelligent data monitoring

被引:1
|
作者
Wu, Mingxia [1 ,2 ]
Liu, Wei [1 ]
Zheng, Shengyang [1 ,2 ]
机构
[1] Ningde Normal Univ, Coll Life Sci, Ningde 352100, Fujian, Peoples R China
[2] Haixi Marine Characterist Biol Germplasm Resources, Ningde 352100, Fujian, Peoples R China
来源
SLAS TECHNOLOGY | 2024年 / 29卷 / 04期
关键词
Internet of things; Probiotic fermentation; Nutrient composition; Data monitoring;
D O I
10.1016/j.slast.2024.100153
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Probiotic fermentation studies are vital in many areas, particularly when it comes to feeding applications. This work examines probiotic fermentation in oil tea crops. The assessment of tea saponin-degrading bacteria and optimization of fermentation conditions using fermented oil tea cake under natural conditions, screening out six strains with strong ability to degrade tea saponin; selection of the best tea saponin degradation strain L.2 and recognition of its morphological features and ITS sequence to obtain L.2 strain is Aspergillus Niger. Oil tea is rich in tea saponin. Aspergillus Niger degraded tea saponins in oil teacakes at a rate of 93.96 % under the ideal conditions of 31.3 oC, 103.5 h, and 4.57 mL of initial acid addition. This has been accomplished via solid-state fermentation of L.2 using single factor studies and surface response optimization experiments. Moreover, Aspergillus Niger degraded tea saponins in oil tea cakes at a rate of 93.96% at the ideal circumstances of 31.3 C, 103.5 h, and 4.57 mL of initial acid addition.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Distributed intelligent urban environment monitoring system
    Du, Jinsong
    Wang, Wei
    Gao, Jie
    Cong, Rigang
    3RD INTERNATIONAL CONFERENCE ON ADVANCES IN ENERGY RESOURCES AND ENVIRONMENT ENGINEERING, 2018, 113
  • [42] Intelligent Robotic Sensor Agents for environment monitoring
    Petriu, EM
    Patry, GG
    Whalen, TE
    Al-Dhaher, A
    Groza, VZ
    VIMS 2002: IEEE INTERNATIONAL SYMPOSIUM ON VIRTUAL AND INTELLIGENT MEASUREMENT SYSTEMS: DISTRIBUTED INTELLIGENT SENSING FOR ADVANCED INTEGRATED VIRTUAL ENVIRONMENTS, 2002, : 14 - 19
  • [43] Design of intelligent home environment monitoring system
    Wang, Mimi
    Cao, Fengping
    PROCEEDINGS OF THE 2017 5TH INTERNATIONAL CONFERENCE ON MECHATRONICS, MATERIALS, CHEMISTRY AND COMPUTER ENGINEERING (ICMMCCE 2017), 2017, 141 : 1459 - 1463
  • [44] Intelligent Environment Monitoring System for University Laboratories
    Zhai, Linbo
    Jiang, Wenwen
    FUTURE INTERNET, 2018, 10 (11)
  • [45] MONITORING AND CONTROL OF ANAEROBIC FERMENTATION SYSTEMS
    TAYA, M
    HAKKOKOGAKU KAISHI-JOURNAL OF THE SOCIETY OF FERMENTATION TECHNOLOGY, 1987, 65 (04): : 249 - 263
  • [46] Analysis of multi-source data for monitoring and control of intelligent technological systems
    Rymarczyk, Tomasz
    Przysucha, Bartosz
    Pawlik, Pawel
    PRZEGLAD ELEKTROTECHNICZNY, 2020, 96 (09): : 95 - 98
  • [47] Data mining and knowledge discovery for monitoring and intelligent control of a wastewater treatment plant
    Manesis, S.
    Deligiannis, V.
    Koutri, M.
    ICINCO 2008: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL ICSO: INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION, 2008, : 86 - 93
  • [48] Research on Intelligent Monitoring and Concentration Prediction for Penicillin Fermentation Process
    Zhang, Yin
    Zhang, Kai
    Hu, Ting
    Yuan, Libo
    BIOTECHNOLOGY AND BIOENGINEERING, 2025, 122 (03) : 570 - 578
  • [49] An intelligent learning environment for data modeling
    Hall, L
    Gordaon, A
    INTELLIGENT TUTORING SYSTEMS, 1998, 1452 : 608 - 608
  • [50] Data analysis in the intelligent building environment
    Kriksciuniene, Dalia
    Pitner, Tomas
    Kucera, Adam
    Sakalauskas, Virgilijus
    International Journal of Computer Science and Applications, 2014, 11 (01) : 1 - 17