Optimization of Lyophilized Protective Agent Formulation of <i>Lactobacillus casei</i> LTL1361 Based on Artificial Neural Network Coupled Genetic Algorithm (BP-GA)

ZHANG Xiyu; LI Ruiding; MO Minggui; MEI Lihua; LIU Yuping; ZHU Wenjun; LI Quanyang

doi:10.13386/j.issn1002-0306.2022010143

Volume 43 Issue 21

Oct. 2022

Turn off MathJax

Article Contents

Abstract

References

Science and Technology of Food Industry > 2022 > 43(21): 175-184. > DOI: 10.13386/j.issn1002-0306.2022010143

ZHANG Xiyu, LI Ruiding, MO Minggui, et al. Optimization of Lyophilized Protective Agent Formulation of Lactobacillus casei LTL1361 Based on Artificial Neural Network Coupled Genetic Algorithm (BP-GA)[J]. Science and Technology of Food Industry, 2022, 43(21): 175−184. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022010143.

Citation:

PDF (1599 KB)

Optimization of Lyophilized Protective Agent Formulation of Lactobacillus casei LTL1361 Based on Artificial Neural Network Coupled Genetic Algorithm (BP-GA)

1.
College of Light Industry and Food Engineering, Guangxi University, Nanning 500004, China
2.
Liuzhou Kangxiaole Dairy Co. Ltd., Liuzhou 545007, China
3.
Liuzhou No. 12 Middle School, Liuzhou 545026, China

More Information

Received Date: January 17, 2022
Available Online: August 31, 2022

Graphical Abstract

Abstract

Abstract

To improve the freeze-drying survival rate of Lactobacillus casei LTL1361 in the vacuum freeze-drying process, the single factor and Plackett-Burman designs were first conducted to verify the main factors affecting the freeze-drying survival rate of Lactobacillus casei LTL1361. According to the experimental results, the artificial network coupling genetic algorithm was constructed using the Box Behnken design. The artificial network coupled genetic algorithm (BP-GA) model was constructed to simulate and predict the lyophilized protective agent formulation of Lactobacillus casei LTL1361. The results showed that the three main factors affecting the lyophilisation survival rate of the strain were: Alginate, glutamic acid and mannitol, which were selected by single-factor and Plackett-Burman tests, and the three factors and the base skim milk were identified as the optimisation conditions for subsequent optimisation tests. The BP-GA model was used to find the optimum concentration of protectant for Lactobacillus casei LTL1361, which was 10.3% skim milk, 0.8% glutamic acid, 6.7% alginate and 4.0% mannitol, and the maximum lyophilisation survival rate of the strain was 89.56%. Using the BP-GA model, this study explored a probiotic lyophilisation protectant formulation with a high lyophilisation survival rate, and provided a reference for the preparation of lyophilised formulations of highly active strains and the development of commercial direct-injection ferments.
- Lactobacillus casei,
- lyophilized protectant,
- artificial neural network,
- genetic algorithm,
- optimization

FullText(HTML)

References (33)

References

[1]	杨秀, 郭文慧. 益生菌的功能及安全性评价[J]. 食品安全导刊,2018(12):47−48. [YANG X, GUO W H. Function and safety evaluation of probiotics[J]. Food Safety Guide,2018(12):47−48. doi: 10.3969/j.issn.1674-0270.2018.12.050
[2]	阿热爱·巴合提, 谭春明, 李平兰. 益生菌的分类及其多领域应用研究现状[J]. 生物加工过程,2022,20(1):88−94. [AREAI B, TAN C M, LI P L. Classification and application of probiotics in many fields[J]. Chinese Journal of Bioprocess Engineering,2022,20(1):88−94. doi: 10.3969/j.issn.1672-3678.2022.01.012
[3]	陈健凯, 陈健旋, 林洵, 等. 养乐多饮料中影响干酪乳杆菌代田株活菌数因素的研究[J]. 中国酿造,2008(22):34−36. [CHEN J K, CHEN J X, LIN X, et al. Study on factors affecting viable count of Lactobacillus casei subcultured in Yakult beverage[J]. China Brewing,2008(22):34−36.
[4]	张猛, 贾星, 张和平, 等. 干酪乳杆菌Zhang在逆境条件下基因表达的差异分析[J]. 中国食品学报,2021,21(6):62−69. [ZHANG M, JIA X, ZHANG H P, et al. Differential analysis of gene expression of Lactobacillus casei Zhang under stress conditions[J]. Journal of Chinese Institute of Food Science and Technology,2021,21(6):62−69. doi: 10.16429/j.1009-7848.2021.06.008
[5]	MEDHA P, KOTLO K U, DUDEJA P K, et al. Role of short chain fatty acid receptors in intestinal physiology and pathophysiology[J]. Comprehensive Physiology,2019,8(3):109−115.
[6]	周庆珠, 李文津, 赵林. 真空冷冻干燥技术在食品加工方面的应用与实践[J]. 食品科学,1996,17(7):14−17. [ZHOU Q Z, LI W J, ZHAO L. Application and practice of vacuum freeze-drying technology in food processing[J]. Food Science,1996,17(7):14−17. doi: 10.3321/j.issn:1002-6630.1996.07.004
[7]	ROSEN R, BUCHINGER S, PFNDER R, et al. SOS gene induction and possible mutagenic effects of freeze-drying in Escherichia coli and Salmonella typhimurium[J]. Applied Microbiology & Biotechnology,2016,100(21):9255−9264.
[8]	BA SHOLLI-SALIHU M, MUELLER M, SALAR-BEHZADI S, et al. Effect of lyoprotectants on β-glucosidase activity and viability of Bifidobacterium infantis after freeze-drying and storage in milk and low pH juices[J]. LWT-Food Science and Technology,2014,57(1):276−282. doi: 10.1016/j.lwt.2014.01.011
[9]	蒲丽丽, 刘宁, 张英华, 等. 乳酸菌冻干保护剂及保护机理的研究进展[J]. 中国乳业,2005(6):50−52. [PU L L, LIU N, ZHANG Y H, et al. Research progress of lyophilized protective agents and protective mechanism of lactic acid bacteria[J]. Dairy Industry,2005(6):50−52. doi: 10.3969/j.issn.1671-4393.2005.06.019
[10]	梁敏山. 乳酸菌增殖培养及直投式酸奶发酵剂的研究[D]. 成都: 西华大学, 2010. LIANG M S. Study on lactic acid bacteria proliferation and culture and direct yoghurt starter[D]. Chengdu: Xihua University, 2010.
[11]	朱琳, 刘宁, 张英华, 等. 乳酸菌细胞膜的冻干损伤及保护[J]. 现代食品科技,2005,21(4):103−106. [ZHU L, LIU N, ZHANG Y H, et al. Damage and protection ofLactobacillus cell membrane by freeze-drying[J]. Modern Food Science and Technology,2005,21(4):103−106. doi: 10.13982/j.mfst.1673-9078.2005.04.032
[12]	胡渊. 干酪乳杆菌直投式发酵剂制备技术研究[D]. 长沙: 湖南农业大学, 2014. HU Y. Study on preparation technology of Lactobacillus casei direct fermentation agent[D]. Changsha: Hunan Agricultural University, 2014.
[13]	王琳. 干酪乳杆菌冷冻干燥保护剂筛选及作用机理研究[D]. 天津: 天津科技大学, 2012. WANG L. Screening and mechanism of protective agent for freeze drying of Lactobacillus casei[D]. Tianjin: Tianjin University of Science and Technology, 2012.
[14]	李伟平, 窦现东, 王振兴, 等. BPNN-HDMR非线性近似模型方法及应用[J]. 湖南大学学报(自然科学版),2014,41(5):32−38. [LI W P, DOU X D, WANG Z X, et al. BPNN-HDMR nonlinear approximate model method and its application[J]. Journal of Hunan University (Natural Science edition),2014,41(5):32−38.
[15]	王强, 冯玲然, 余晓斌. 基于BP神经网络和遗传算法优化番茄红素发酵培养基[J]. 食品与生物技术学报,2019,38(2):111−119. [WANG Q, FENG L R, YU X B. Optimization of lycopene fermentation medium based on BP neural network and genetic algorithm[J]. Journal of Food and Biotechnology,2019,38(2):111−119. doi: 10.3969/j.issn.1673-1689.2019.02.016
[16]	KUMAR A, PATHAK A K, GURIA C. NPK-10:26:26 complex fertilizer assisted optimal cultivation of Dunaliella tertiolecta using response surface methodology and genetic algorithm[J]. Bioresource Technology,2015,194:117−129. doi: 10.1016/j.biortech.2015.06.082
[17]	郭慧慧. 基于BP神经网络与遗传算法的苏云金芽胞杆菌发酵优化[J]. 生物技术进展,2013(2):137−139. [GUO H H. Optimization of Bacillus thuringiensis fermentation based on BP neural network and genetic algorithm[J]. Biotechnology Advances,2013(2):137−139.
[18]	王恒. BP神经网络与遗传算法耦合优化马尾松树脂降解发酵培养基[J]. 福建农业科技,2020(3):6−12. [WANG H. Optimization of fermentation medium for masson pine resin degradation by BP neural network and genetic algorithm[J]. Fujian Agricultural Science and Technology,2020(3):6−12. doi: 10.13651/j.cnki.fjnykj.2020.03.002
[19]	刘栋. 罗伊氏乳杆菌LT018高密度培养及其冻干技术的研究[D]. 南宁: 广西大学, 2017 LIU D. Study on high density culture and lyophilization technology of Lactobacillus reuteri LT018[D]. Nanning: Guangxi University, 2017.
[20]	刘栋, 胡亚民, 刘洪吉, 等. 罗伊氏乳杆菌LT018高密度培养生长因素的研究[J]. 食品工业科技,2016,37(21):144−149. [LIU D, HU Y M, LIU H J, et al. Study on growth factors of Lactobacillus reuteri LT018 in high density culture[J]. Science and Technology of Food Industry,2016,37(21):144−149. doi: 10.13386/j.issn1002-0306.2016.21.020
[21]	刘焕燕, 郑光耀, 王衍彬, 等. 基于BP神经网络的微波辅助提取无花果黄酮工艺优化[J]. 食品工业科技,2017,38(19):197−202,207. [LIU H Y, ZHENG G Y, WANG Y B, el at. Optimization of microwave-assisted extraction of FIG flavonoids based on BP neural network[J]. Science and Technology of Food Industry,2017,38(19):197−202,207.
[22]	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 L F, ZHENG P. Artificial neural network and response surface methodology were used to optimize fermentation conditions of coix seed wine[J]. China Brewing,2021,40(1):142−147. doi: 10.11882/j.issn.0254-5071.2021.01.027
[23]	DONG Y N, LIU X M, CHEN H Q, et al. Enhancement of the hydrolysis activity of β-galactosidase from Geobacillus stearothermophilus by saturation mutagenesis[J]. 2011, 94(3): 1176−1184.
[24]	TANSTRATIAN S, PRADEAMCHAI M. Select a protective agent for encapsulation of Lactobacillus plantarum[J]. LWT,2020,12(3):109−115.
[25]	徐致远, 刘荣, 郭本恒, 等. 保护剂在乳酸菌冻干过程中的应用[J]. 乳业科学与技术,2006,28(4):155−157, 165. [XU Z Y, LIU R, GUO B H, et al. Application of protective agent in lyophilization of lactic acid bacteria[J]. Dairy Science and Technology,2006,28(4):155−157, 165. doi: 10.3969/j.issn.1671-5187.2006.04.002
[26]	NOORI N, HAMEDI H, KARGOZARI M, et al. Investigation of potential prebiotic activity of rye sprout extract[J]. Food Bioscience,2017,19:121−127. doi: 10.1016/j.fbio.2017.07.001
[27]	CARVALHO A S, SILVA J, HO P, et al. Protective effect of sorbitol and monosodium glutamate during storage of freeze-dried lactic acid bacteria[J]. Dairy Science Technology,2003,83(3):203−210. doi: 10.1051/lait:2003010
[28]	周佳豪, 雷文平, 刘成国, 等. 高活菌数干酪乳杆菌LZ183E冻干保护剂的制备[J]. 食品与发酵工业,2020,46(24):138−143. [ZHOU J H, LEI W P, LIU C G, et al. Preparation of lyophilized protective agent of Lactobacillus casei LZ183E with High viable count[J]. Food and Fermentation Industries,2020,46(24):138−143.
[29]	赵禹彤. 罗伊氏乳杆菌冻干保护剂的筛选及在发酵乳中的应用[D]. 长春: 吉林大学, 2020 ZHAO Y T. Screening of lyophilized protective agent of Lactobacillus reuteri and its application in fermented milk[D]. Changchun: Jilin University, 2020.
[30]	单静. 适于脱脂羊奶益生菌直投式发酵剂的研究[D]. 烟台: 烟台大学, 2019 SAN J. Study on direct delivery starter suitable for defatted sheep milk probiotics[D]. Yantai: Yantai University, 2019.
[31]	刘盟梦, 李银平, 延海莹, 等. 基于BP神经网络的牡蛎抗氧化活性肽制备工艺优化[J]. 食品工业科技,2016,37(20):206−210. [LIU M M, LI Y P, YAN H Y, et al. Optimization of preparation technology of oyster antioxidant active peptide based on BP neural network[J]. Science and Technology of Food Industry,2016,37(20):206−210.
[32]	马建春, 马灶亮, 张昊亮, 等. 补阳还五汤提取工艺的响应面法和人工神经网络模型优化[J]. 时珍国医国药,2019(2):337−340. [MA J C, MA Z L, ZHANG H L, et al. Optimization of response surface methodology and artificial neural network model for extraction of buyang huanwu decoction[J]. Shizhen Medicine and Herbal Research,2019(2):337−340.
[33]	周梦舟, 吴珊, 柳念, 等. 基于神经网络对枯草芽孢杆菌富硒过程的建模研究[J]. 中国食品学报,2016,16(12):66−74. [ZHOU M Z, WU S, LIU N, et al. Modeling of selenium enrichment process of Bacillus subtilis based on neural network[J]. Chinese Journal of Food Science,2016,16(12):66−74.

Supplements (0)

Cited By

Cited by

Periodical cited type(8)

1.	韩军，王怡，张开屏，田建军. 罗伊氏粘液乳杆菌JBR3生物学特性分析及保护剂对其活力的影响. 食品工业科技. 2025(03): 166-177 . 本站查看
2.	邓忠惠，谢微. 罗汉果籽吸附氟离子效果的不同预测模型研究. 食品安全质量检测学报. 2024(06): 246-255 .
3.	刘国祎，郭建章，陈星，王威强. 响应面法和人工神经网络对亚临界CO_2萃取红花籽油的建模与优化. 食品工业科技. 2024(10): 225-233 . 本站查看
4.	马诗瑜，何敬成，詹陆川，林伟杰，林思濠，胡小刚，卞晓岚. 基于人工神经网络算法的自拟清瘟方制备工艺优化探索. 中国药业. 2023(12): 56-62 .
5.	赵清香，李大军，李亚萍，姜宇纯，李庚，袁永旭. 反向传播神经网络耦联遗传算法与响应面设计烤制鸽肉工艺优化. 中国调味品. 2023(10): 128-133 .
6.	周雷进雨，马精阳，袁月明，李锦生，冯伟志，周丽娜. 干酪乳杆菌复合冻干保护剂工艺优化. 饲料工业. 2023(22): 86-93 .
7.	渠一聪，张绍绒，罗理勇，曾亮. 基于人工神经网络耦合遗传算法（BP-GA）优化茶氨酸-葡萄糖美拉德反应的条件. 食品工业科技. 2023(24): 183-192 . 本站查看
8.	靳浩文，朱巧梅. 益生菌微胶囊技术对益生菌存活率影响的研究进展. 食品安全导刊. 2022(25): 181-183 .