OPTIMIZATION OF FERMENTATION PROCESS FOR TEQUILA PRODUCTION USING RESPONSE SURFACE METHODOLOGY (RSM)

被引:0
|
作者
Tellez-Mora, P. [1 ,2 ]
Peraza-Luna, F. A. [2 ]
Feria-Velasco, A. [3 ]
Andrade-Gonzalez, I. [1 ]
机构
[1] Inst Tecnol Tlajomulco, Tlajomulco De Zuniga 45640, Jalisco, Mexico
[2] Inst Tecnol Tizimin, Yucatan 97900, Mexico
[3] Univ Guadalajara, Zapopan, Jalisco, Mexico
来源
关键词
optimization; Saccharomyces; Agave (tequilana); fermentation; macronutrients; tequila; SACCHAROMYCES-CEREVISIAE; ASSIMILABLE NITROGEN; VOLATILE COMPOSITION; YEASTS; SELECTION; WINES; GRAPE; PARAMETERS; AGAVE; STUCK;
D O I
暂无
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
The objective of this work was to optimize sugar concentrations, nitrogen and phosphorus in the medium, in order to increase the efficiency production, establishing the influence of these macronutrients in the flavor compounds listed in the Mexican legislation (NOM-006-SCFI-2005). It was used two strains of Saccharomyces yeasts and two types of must: 100% Agave and mixed Agave (Agave plus sucrose). At first it was used a factorial design (2(4-1)). Control variables: sugar concentration, nitrogen and phosphorus, and temperature. Response variables: fermentation efficiency and concentrations of the compounds listed in the NOM. The objective function was determined by minimum squares for each response variable with its restrictions. For the efficiency of 94.58% (with a desirable function of 0.891312), the program suggested, mixed Agave (Agave and sucrose), Saccharomyces THL 110; 8 degrees Bx; 0.797979 g/ 1 N; 0.376875 g/ 1 P, and at 40 degrees C.
引用
收藏
页码:163 / 176
页数:14
相关论文
共 50 条
  • [1] Biotransformation of Agricultural Wastes into Lovastatin and Optimization of a Fermentation Process Using Response Surface Methodology (RSM)
    Javed, Sadia
    Azeem, Muhammad
    Mahmood, Saqib
    Al-Anazi, Khalid Mashay
    Abul Farah, Mohammad
    Ali, Sajad
    Ali, Baber
    [J]. AGRONOMY-BASEL, 2022, 12 (11):
  • [2] Optimization of fermentation parameters in phage production using response surface methodology
    Grieco, Sung-Hye H.
    Wong, Ann Y. K.
    Dunbar, W. Scott
    MacGillivray, Ross T. A.
    Curtis, Susan B.
    [J]. JOURNAL OF INDUSTRIAL MICROBIOLOGY & BIOTECHNOLOGY, 2012, 39 (10) : 1515 - 1522
  • [3] Optimization of fermentation conditions for ting production using response surface methodology
    Adebo, Oluwafemi Ayodeji
    Njobeh, Patrick Berka
    Mulaba-Bafubiandi, Antoine Floribert
    Adebiyi, Janet Adeyinka
    Desobgo, Zangue Steve Carly
    Kayitesi, Eugenie
    [J]. JOURNAL OF FOOD PROCESSING AND PRESERVATION, 2018, 42 (01)
  • [4] Optimization of Spore Production of Aspergillus niger by Response Surface Methodology (RSM) in Solid-State Fermentation
    Yuan, Hongwei
    Zhang, Qinyu
    Li, Zhu
    Guo, Bokai
    Chen, Hufang
    Gao, Dongmin
    Liu, Xuece
    Xiao, Yang
    Yang, Long
    [J]. JOURNAL OF BIOBASED MATERIALS AND BIOENERGY, 2019, 13 (02) : 214 - 220
  • [6] Optimization of succinic acid fermentation with Actinobacillus succinogenes by response surface methodology(RSM)
    Yunjian ZHANG Qiang LI Yuxiu ZHANG Dan WANG Jianmin XING School of Chemical and Environmental EngineeringChina University of Mining and TechnologyBeijingBeijing ChinaState Key Laboratory of Biochemical EngineeringInstitute of Process EngineeringChinese Academy of SciencesBeijing China
    [J]. Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)., 2012, 13 (02) - 110
  • [7] Optimization of succinic acid fermentation with Actinobacillus succinogenes by response surface methodology (RSM)
    Zhang, Yun-jian
    Li, Qiang
    Zhang, Yu-xiu
    Wang, Dan
    Xing, Jian-min
    [J]. JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE B, 2012, 13 (02): : 103 - 110
  • [8] Optimization of succinic acid fermentation with Actinobacillus succinogenes by response surface methodology (RSM)
    Yun-jian Zhang
    Qiang Li
    Yu-xiu Zhang
    Dan Wang
    Jian-min Xing
    [J]. Journal of Zhejiang University SCIENCE B, 2012, 13 : 103 - 110
  • [9] Optimization and production of bioplastic from bio waste using response surface methodology (RSM)
    Magesh, A.
    Jayabalan, K.
    Kannan, R. Rajesh
    Rathakrishnan, P.
    Dilipkumar, M.
    Suriyaprakash, M.
    [J]. ENVIRONMENTAL QUALITY MANAGEMENT, 2022, 32 (01) : 179 - 190
  • [10] Optimization of dark fermentation for biohydrogen production using a hybrid artificial neural network (ANN) and response surface methodology (RSM) approach
    Wang, Yunshan
    Yang, Gang
    Sage, Valerie
    Xu, Jian
    Sun, Guangzhi
    He, Jun
    Sun, Yong
    [J]. ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY, 2021, 40 (01)