Optimization of Exocytopolysaccharide Production from Fermented Blueberry Juice by Complex Lactic Acid Bacteria Based on Response Surface Method and Artificial Neural Network

GONG Minhui; SHAN Chengjun; LI Shuangjian; YANG Suqun; WANG Ying; LIU Xiaoli; ZHOU Jianzhong

doi:10.13386/j.issn1002-0306.2022110110

Volume 44 Issue 17

Aug. 2023

Turn off MathJax

Article Contents

Abstract

References

Science and Technology of Food Industry > 2023 > 44(17): 242-250. > DOI: 10.13386/j.issn1002-0306.2022110110

GONG Minhui, SHAN Chengjun, LI Shuangjian, et al. Optimization of Exocytopolysaccharide Production from Fermented Blueberry Juice by Complex Lactic Acid Bacteria Based on Response Surface Method and Artificial Neural Network[J]. Science and Technology of Food Industry, 2023, 44(17): 242−250. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022110110.

Citation:

PDF (2539 KB)

Optimization of Exocytopolysaccharide Production from Fermented Blueberry Juice by Complex Lactic Acid Bacteria Based on Response Surface Method and Artificial Neural Network

1.
School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
2.
Institute of Agricultural Product Processing, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China

More Information

Received Date: November 10, 2022
Available Online: July 02, 2023

Graphical Abstract

Abstract

Abstract

To improve the content of extracellular polysaccharide (EPS) in fermented blueberry juice, three strains of lactic acid bacteria with high EPS production were selected in this study, and the fermentation conditions of blueberry juice were optimized by single-factor method and response surface methodology (RSM), and the four most influential factors were screened out, namely, initial pH, inoculum amount, fermentation temperature and fermentation time. Based on this, the optimal fermentation process conditions were obtained by artificial neural network (ANN) and genetic algorithm (GA). The optimized process conditions were 2:1:1 ratio of Lactobacillus plantarum 9sh, Lactobacillus fermentum SR2-6 and Citrobacter cepacia GM11, lactose was 6%, soybean peptide was 0.6%, the initial pH of blueberry juice was 4.5, the inoculum amount was 8%, fermentation temperature was 30 ℃, and fermentation time was 60 h. Under these conditions, the EPS content was 3.537 g/L. This study shows that RSM and ANN can be used to optimize the EPS production process of blueberry juice by lactic acid bacteria fermentation.

FullText(HTML)

References (35)

References

[1]	JIN-SIL P, WON C J, JOOYEON J, et al. Lactobacillus acidophilus improves intestinal inflammation in an acute colitis mouse model by regulation of Th17 and Treg cell balance and fibrosis development[J]. Journal of Medicinal Food,2018,21(3):1−10.
[2]	PIA A M, VITTORIO C, PASQUALE R, et al. Immunobiosis and probiosis: Antimicrobial activity of lactic acid bacteria with a focus on their antiviral and antifungal properties[J]. Applied Microbiology and Biotechnology,2018,102(23):9949−9958. doi: 10.1007/s00253-018-9403-9
[3]	李桐, 吴思琪, 曹鑫, 等. 具抗氧化功能益生菌菌株筛选及其对丙烯酰胺诱导肠上皮细胞氧化损伤的保护作用[J]. 食品科学,2020,41(2):173−180. [LI Tong, WU Siqi, CAO Xin, et al. Screening for antioxidant probiotics and their protective effect on oxidative damage induced by acrylamide in intestinal epithelial cell[J]. Food Science,2020,41(2):173−180. LI Tong, WU Siqi, CAO Xin, et al. Screening for antioxidant probiotics and their protective effect on oxidative damage induced by acrylamide in intestinal epithelial cell [J]. Food Science, 2020, 41(2): 173-180.
[4]	张将, 蒋凌霜, 孙梦莹, 等. 乳酸菌胞外多糖对结肠癌HT-29细胞增殖的影响[J]. 食品研究与开发,2019,40(7):7−15. [ZHANG Jiang, JIANG Lingshuang, SUN Mengying, et al. The effect of exopolysaccharides from Lactobacillus plantarum 12 on the proliferation of HT-29 cells[J]. Food Research and Development,2019,40(7):7−15. ZHANG Jiang, JIANG Lingshuang, SUN Mengying, et al. The effect of exopolysaccharides from Lactobacillus plantarum 12 on the proliferation of HT-29 cells [J]. Food Research and Development, 2019, 40(7): 7-15.
[5]	RUAS-MADIEDO P, HUGENHOLTZ J, ZOON P. An overview of the functionality of exopolysaccharides produced by lactic acid bacteria[J]. International Dairy Journal,2002,12(2):163−171.
[6]	BILIAVSKA L, PANKIVSKA Y, POVNITSA O, et al. Antiviral activity of exopolysaccharides produced by lactic acid bacteria of the genera Pediococcus, Leuconostoc and Lactobacillus against human adenovirus type 5[J]. Medicina,2019,55(9):1−12.
[7]	SIOK-KOON Y, MIN-TZE L. Effect of prebiotics on viability and growth characteristics of probiotics in soymilk[J]. Journal of the Science of Food and Agriculture,2010,90(2):267−275. doi: 10.1002/jsfa.3808
[8]	叶广彬, 陈源红, 王长丽, 等. 柠檬明串珠菌TD1产胞外多糖条件的响应面法优化及其抗氧化性研究[J]. 中国酿造,2018,37(11):70−75. [YE Guangin, CHEN Yuanhong, WANG Changli, et al. Optimization of conditions of exopolysaccharide production from Leuconostoc citreum TD1 by response surface methodology and its antioxidant activity[J]. China Brewing,2018,37(11):70−75. YE Guangin, CHEN Yuanhong, WANG Changli, et al. Optimization of conditions of exopolysaccharide production from Leuconostoc citreum TD1 by response surface methodology and its antioxidant activity [J]. China Brewing, 2018, 37(11): 70-75.
[9]	GADEKAR M R, AHAMMED M M. Modelling dye removal by adsorption onto water treatment residuals using combined response surface methodology-artificial neural network approach[J]. Journal of Environmental Management,2019,231(1):241−248.
[10]	GAMMOUDI N, MABROUK M, BOUHEMDA T, et al. Modeling and optimization of capsaicin extraction from Capsicum annuum L. using response surface methodology (RSM), artificial neural network (ANN), and Simulink simulation[J]. Industrial Crops & Products,2021,171(1):113869−113869.
[11]	BHUSHANAM V, MALOTHU R. Bioprocess optimization of L-lysine production by using RSM and artificial neural networks from Corynebacterium glutamicum ATCC13032[J]. Chemical Product and Process Modeling,2020,0(0):1−12.
[12]	李虹甫, 杨鑫焱, 刘昕宇, 等. 植物乳杆菌发酵蓝莓果汁工艺优化及其抗氧化能力[J]. 食品工业科技,2019,40(17):127−133. [LI Hongfu, YANG Xinyan, LIU Xinyu, et al. Fermentation process optimization of blueberry juice fermented by Lactobacillus plantarum and analysis of antioxidant capacity[J]. Science and Technology of Food Industry,2019,40(17):127−133. LI Hongfu, YANG Xinyan, LIU Xinyu, et al. Fermentation process optimization of blueberry juice fermented by Lactobacillus plantarum and analysis of antioxidant capacity [J]. Science and Technology of Food Industry, 2019, 40(17): 127-133.
[13]	曹桢. 紫薯乳酸发酵汁工艺优化及品质特性研究[D]. 重庆: 西南大学, 2022 CAO Zhen. Study on technological optimization and quality characteristics of purple potato lactic acid fermented juice[D]. Chongqing: Southwest University, 2022.
[14]	戴意强, 单成俊, 刘小莉, 等. 乳酸菌发酵黑莓汁增加胞外多糖工艺初探[J]. 江苏农业科学,2020,48(18):214−218. [DAI Yiqiang, SHAN Chengjun, LIU Xiaoli, et al. Preliminary study on lactic acid bacteria fermentation of blackberry juice to increase exopolysaccharide[J]. Jiangsu Agricultural Sciences,2020,48(18):214−218. DAI Yiqiang, SHAN Chengjun, LIU Xiaoli, et al. Preliminary study on lactic acid bacteria fermentation of blackberry juice to increase exopolysaccharide [J]. Jiangsu Agricultural Sciences, 2020, 48(18): 214-218.
[15]	中华人民共和国国家卫生和计划生育委员会. GB 4789.2-2016 食品微生物学检验菌落总数测定[S]. 北京: 中国标准出版社, 2016 National Health and Family Planning Commission of the People’s Republic of China. GB 4789.2-2016 Food microbiological analysis Determination of total bacterial count[S]. Beijing: China Standards Press, 2016.
[16]	徐素云, 王艳萍, 周聪, 等. 纯种混合发酵红茶菌工艺优化及品质分析[J]. 食品研究与开发,2022,43(15):138−145. [XU Suyun, WANG Yanping, ZHOU Cong, et al. Optimization and quality analysis of pure and mixed fermentation of Kombucha[J]. Food Research and Development,2022,43(15):138−145. XU Suyun, WANG Yanping, ZHOU Cong, et al. Optimization and quality analysis of pure and mixed fermentation of Kombucha [J]. Food Research and Development, 2022, 43(15): 138-145.
[17]	张玉慧. 乳酸菌发酵蓝莓果汁的工艺研究[D]. 沈阳: 沈阳农业大学, 2016 ZHANG Yuhui. Study on processing technology of blueberry juice fermented by lactic acid bacteria[D]. Shenyang: Shenyang Agricultural University, 2016.
[18]	孔德卉, 蒋家璇. 高产胞外多糖能力的乳酸菌筛选及其培养条件的优化[J]. 兰州文理学院学报(自然科学版),2020,34(3):53−59. [KONG Dehui, JIANG Jiaxuan. Screening of lactic acid bacteria with high extracellular polysaccharide capacity and optimization of culture conditions[J]. Journal of Lanzhou University of Arts and Science(Natural Sciences),2020,34(3):53−59. KONG Dehui, JIANG Jiaxuan. Screening of lactic acid bacteria with high extracellular polysaccharide capacity and optimization of culture conditions [J]. Journal of Lanzhou University of Arts and Science(Natural Sciences), 2020, 34(3): 53-59.
[19]	杜梦帆, 王露. 不同碳源对小球藻生长的影响[J]. 生物化工,2022,8(4):93−95. [DU Mengfan, WANG Lu. Effects of different carbon sources on the growth of chlorella[J]. Biological Chemical Engineering,2022,8(4):93−95. DU Mengfan, WANG Lu. Effects of different carbon sources on the growth of chlorella [J]. Biological Chemical Engineering, 2022, 8(4): 93-95.
[20]	洪厚胜, 朱曼利, 李伟, 等. 葡萄果渣酵素的发酵工艺优化及其理化特性[J]. 食品科学,2019,40(8):63−72. [HONG Housheng, ZHU Manli, LI wei, et al. Optimization of fermentation process and physicochemical properties of probiotic fermented grape pomace[J]. Food Science,2019,40(8):63−72. HONG Housheng, ZHU Manli, LI wei, et al. Optimization of fermentation process and physicochemical properties of probiotic fermented grape pomace [J]. Food Science, 2019, 40(8): 63-72.
[21]	马永轩, 张名位, 魏振承, 等. 不同种类活性短肽的理化与功能特性比较[J]. 中国粮油学报,2016,31(6):57−62. [MA Yongxuan, ZHANG Mingwei, WEI Zhencheng, et al. Comparison of physicochemical and functional properties of different active peptides[J]. Journal of the Chinese Cereals and Oils Association,2016,31(6):57−62. MA Yongxuan, ZHANG Mingwei, WEI Zhencheng, et al. Comparison of physicochemical and functional properties of different active peptides [J]. Journal of the Chinese Cereals and Oils Association, 2016, 31(6): 57-62.
[22]	赵丽霞. 高活性抗炎多肽的筛选与其作用机制研究[D]. 镇江: 江苏大学, 2021 ZHAO Lixia. Screening of highly active anti-inflammatory peptides and study on its mechanism[D]. Zhenjiang: Jiangsu University, 2021.
[23]	李彬. 产胞外多糖菌株的筛选及胞外多糖性质和结构分析[D]. 南京: 南京理工大学, 2016 LI Bin. Screening of exopolysaccharide-producing strains and properties and structure analysis of the exopolysaccharides[D]. Nanjing: Nanjing University, 2016.
[24]	赵紫君, 杜全能, 杨正, 等. 鸡枞菌产水溶性胞外多糖发酵条件及抗氧化活性的初步研究[J]. 中国酿造,2021,40(6):102−108. [ZHAO Zijun, DU Quanneng, YANG Zheng, et al. Preliminary study on fermentation conditions and antioxidant activity of water soluble exopolysaccharide from Collybia albuminosa[J]. China Brewing,2021,40(6):102−108. ZHAO Zijun, DU Quanneng, YANG Zheng, et al. Preliminary study on fermentation conditions and antioxidant activity of water soluble exopolysaccharide from Collybia albuminosa [J]. China Brewing, 2021, 40(6): 102-108.
[25]	李春雨, 杨棒棒, 周佳, 等. 红杆菌NBS58-1产胞外多糖发酵条件优化及其保湿性研究[J]. 中国酿造,2022,41(11):155−160. [LI Chunyu, YANG Bangbang, ZHOU Jia, et al. Optimization of fermentation conditions and moisture retention of exopolysaccharide from Rufibacter hautae NBS58-1[J]. China Brewing,2022,41(11):155−160. LI Chunyu, YANG Bangbang, ZHOU Jia, et al. Optimization of fermentation conditions and moisture retention of exopolysaccharide from Rufibacter hautae NBS58-1 [J]. China Brewing, 2022, 41(11): 155-160.
[26]	廖乾伟. 侗族酸肉中3株乳酸菌产胞外多糖的研究[D]. 贵阳: 贵州大学, 2017 LIAO Qianwei. Study on exopolysaccharide of three strains of lactic acid bacteria isolated from sour meat of Dong minority[D]. Guiyang: Guizhou University, 2017.
[27]	胡盼盼, 宋微, 单毓娟, 等. 影响乳酸菌胞外多糖产量的因素[J]. 食品科技,2014,39(9):31−37. [HU Panpan, SONG Wei, SHAN Yujuan, et al. Factors contributing to the yield of exopolysaccharide by lactic acid bacteria[J]. Food Science and Technology,2014,39(9):31−37. HU Panpan, SONG Wei, SHAN Yujuan, et al. Factors contributing to the yield of exopolysaccharide by lactic acid bacteria [J]. Food Science and Technology, 2014, 39(9): 31-37.
[28]	YAO Y, WU M, HUANG Y, et al. Appropriately raising fermentation temperature beneficial to the increase of antioxidant activity and gallic acid content in Eurotium cristatum-fermented loose tea[J]. LWT-Food Science and Technology,2017,82:248−254. doi: 10.1016/j.lwt.2017.04.032
[29]	陈宠, 苏亚平, 岳雅欣, 等. 海棠酵素微生物菌相分析及其功能初步研究[J]. 中国酿造,2020,39(8):70−76. [CHEN Chong, SU Yaping, YUE Yaxin, et al. Analysis of microbial community in Malus pruniflolia Jiaosu and preliminary study on its function[J]. China Brewing,2020,39(8):70−76. CHEN Chong, SU Yaping, YUE Yaxin, et al. Analysis of microbial community in Malus pruniflolia Jiaosu and preliminary study on its function [J]. China Brewing, 2020, 39(8): 70-76.
[30]	邢瀚文. 肠膜明串珠菌DRP105胞外多糖发酵条件优化及其性质研究[D]. 天津: 天津大学, 2018 XIN Hanwen. Fermentation optimization and characterization of exopolysaccharide isolated from Leuconosto mesenteroides DRP105[D]. Tianjin: Tianjin University, 2018.
[31]	PRASANNA P H P, GRANDISON A S, CHARALAMPOPOULOS D. Effect of dairy-based protein sources and temperature on growth, acidification and exopolysaccharide production of Bifidobacterium strains in skim milk[J]. Food Research International,2012,47(1):6−12. doi: 10.1016/j.foodres.2012.01.004
[32]	谢晓阳, 范毅, 王伟, 等. 响应面法优化刺梨果多糖发酵工艺研究[J]. 中国酿造,2021,40(4):177−182. [XIE Xiaoyang, FAN Yi, WANG Wei, et al. Optimization of fermentation technology of Rosa roxburghii fruit polysaccharide by response surface method[J]. China Brewing,2021,40(4):177−182. XIE Xiaoyang, FAN Yi, WANG Wei, et al. Optimization of fermentation technology of Rosa roxburghii fruit polysaccharide by response surface method [J]. China Brewing, 2021, 40(4): 177-182.
[33]	宋艺君, 郭涛, 刘世军, 等. 响应面法优化黄精-大枣果酒发酵工艺及其抗氧化活性[J]. 食品工业科技,2021,42(1):156−161. [SONG Yijun, GUO Tao, LIU Shijun, et al. Optimization of fermentation process and antioxidant activity of Polygonati Rhizoma-jujubae fructus fruit wine by response surface methodology[J]. Science and Technology of Food Industry,2021,42(1):156−161. SONG Yijun, GUO Tao, LIU Shijun, et al. Optimization of fermentation process and antioxidant activity of Polygonati Rhizoma-jujubae fructus fruit wine by response surface methodology [J]. Science and Technology of Food Industry, 2021, 42(1): 156-161.
[34]	郭玲玲, 周瑶, 张睿. 白芸豆乳酸菌饮料的工艺研究[J]. 粮食加工,2021,46(3):62−64. [GUO Lingling, ZHOU Yao, ZHANG Rui. Study on the technology of white kidney bean lactobacillus beverage[J]. Grain Processing,2021,46(3):62−64. GUO Lingling, ZHOU Yao, ZHANG Rui. Study on the technology of white kidney bean lactobacillus beverage [J]. Grain Processing, 2021, 46(3): 62-64.
[35]	邹立飞, 郑鹏. 人工神经网络和响应面法优化薏苡仁酒发酵条件[J]. 中国酿造,2021,40(1):142−147. [ZOU Lifei, ZHENG Peng. Optimization of fermentation conditions of coix seed wine by artificial neural network and response surface method[J]. China Brewing,2021,40(1):142−147. ZOU Lifei, ZHENG Peng. Optimization of fermentation conditions of coix seed wine by artificial neural network and response surface method [J]. China Brewing, 2021, 40(1): 142-147.

Supplements (0)

Cited By

Cited by

Periodical cited type(4)

1.	严和平，徐世娟，蔡朴春，张举成. 基于响应面法和神经网络优化野生狼牙刺中总黄酮的提取工艺. 黑龙江科学. 2025(02): 20-25 .
2.	乌日娜，赵玉莲，郭佳，史海粟，安飞宇. 微生物发酵食品新进展. 微生物学杂志. 2025(01): 1-13 .
3.	王宁晓璇，李欣，黄玉立，王雅利，赖海梅，杨梦露，汤臣薇，葛黎红，赵楠. 机器学习在传统发酵食品微生物结构及品质控制中的应用研究进展. 食品工业科技. 2024(13): 360-367 . 本站查看
4.	茆鑫，郑剑斌，李广耀，曲敏，郑心琪. 响应曲面法优化刺五加-五味子混菌发酵工艺的研究. 食品科技. 2023(09): 57-64 .