Optimization of enzymatic hydrolysis of waste cotton fibers for nanoparticles production using response surface methodology

被引:0
|
作者
T. Fattahi Meyabadi
F. Dadashian
机构
[1] Amirkabir University of Technology,Textile Engineering Department
来源
Fibers and Polymers | 2012年 / 13卷
关键词
Waste cotton fibers; Enzymatic hydrolysis; Cellulose nanoparticles; Response surface methodology;
D O I
暂无
中图分类号
学科分类号
摘要
A Box-Behnken design (BBD) was used for optimization of enzymatic hydrolysis of waste cotton fibers in order to obtain finest cellulose particles. The effect of three factors including hydrolysis time (h), substrate concentration (g/l) and enzyme loading (%) were investigated. The median size of the hydrolyzed particles was defined as the response function of the design. Results of BBD were subjected to analysis of variance (ANOVA) and a quadratic polynomial equation was developed for predicting the particle size. According to the fitted model, the optimal conditions i.e. hydrolysis time, substrate concentration and enzyme loading were suggested as 175 h, 5 g/l and 2.3 %, respectively. The suspension prepared under optimum conditions was subjected to ultrasonic treatment, and the resulted stable suspension of cellulose nanoparticles was characterized. It was found that these nanoparticles are spherical and most of them are in the range of 40–90 nm. The enzymatic and ultrasonic treatments caused an increase in the crystallinity and a decrease in the degree of polymerization of cotton.
引用
收藏
页码:313 / 321
页数:8
相关论文
共 50 条
  • [21] OPTIMIZATION OF ENZYMATIC HYDROLYSIS FOR PREPARATION OF SHRIMP FLAVOR PRECURSOR USING RESPONSE SURFACE METHODOLOGY
    Guo, Xiaoxun
    Han, Xiaoxiang
    He, Yanfei
    Du, Huan
    Tan, Zhongqin
    JOURNAL OF FOOD QUALITY, 2014, 37 (04) : 229 - 236
  • [22] Short communication: Production of antihypertensive peptide HLPLP by enzymatic hydrolysis: Optimization by response surface methodology
    Quiros, A.
    Hernandez-Ledesma, B.
    Ramos, M.
    Martin-Alvarez, P. J.
    Recio, I.
    JOURNAL OF DAIRY SCIENCE, 2012, 95 (08) : 4280 - 4285
  • [23] Optimum conditions for the enzymatic hydrolysis of citron waste juice using response surface methodology (RSM)
    Ji Young Lim
    Hyang-Sik Yoon
    Kwang-Yup Kim
    Ki-Sik Kim
    Jae Goan Noh
    In Gyu Song
    Food Science and Biotechnology, 2010, 19 : 1135 - 1142
  • [24] Optimum Conditions for the Enzymatic Hydrolysis of Citron Waste Juice Using Response Surface Methodology (RSM)
    Lim, Ji Young
    Yoon, Hyang-Sik
    Kim, Kwang-Yup
    Kim, Ki-Sik
    Noh, Jae Goan
    Song, In Gyu
    FOOD SCIENCE AND BIOTECHNOLOGY, 2010, 19 (05) : 1135 - 1142
  • [25] Optimization of enzymatic hydrolysis of mango kernel starch by response surface methodology
    G. V. Chowdary
    S. Hari Krishna
    G. Hanumantha Rao
    Bioprocess Engineering, 2000, 23 : 681 - 685
  • [26] Optimization of enzymatic hydrolysis of mango kernel starch by response surface methodology
    Chowdary, G.V.
    Hari, Krishna, S.
    Hanumantha, Rao, G.
    Bioprocess and Biosystems Engineering, 2000, 23 (06) : 681 - 685
  • [27] OPTIMIZATION OF ENZYMATIC DESIZING AND SCOURING OF COTTON FABRIC BY RESPONSE SURFACE METHODOLOGY
    Grujic, Dragana
    Savic, Aleksandar
    Papuga, Sasa
    Milosevic, Milena
    Kolar, Mitja
    Milanovic, Predrag M.
    Milanovic, Jovana Z.
    CELLULOSE CHEMISTRY AND TECHNOLOGY, 2023, 57 (1-2): : 167 - 184
  • [28] Optimization of enzymatic hydrolysis of mango kernel starch by response surface methodology
    Chowdary, GV
    Krishna, SH
    Rao, GH
    BIOPROCESS ENGINEERING, 2000, 23 (06) : 681 - 685
  • [29] Optimization of Enzymatic Hydrolysis of Chicken Fat in Emulsion by Response Surface Methodology
    Teng, Dike
    Le, Rensi
    Yuan, Fang
    Yang, Jia
    He, Li
    Gao, Yanxiang
    JOURNAL OF THE AMERICAN OIL CHEMISTS SOCIETY, 2009, 86 (05) : 485 - 494
  • [30] Optimization of Enzymatic Production Process of Oat Milk Using Response Surface Methodology
    Deswal, Aastha
    Deora, Navneet Singh
    Mishra, Hari Niwas
    FOOD AND BIOPROCESS TECHNOLOGY, 2014, 7 (02) : 610 - 618