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中国精品科技期刊2020
周金雨, 庞雪辉, 吴桐, 张秋雪, 孟祥晨. 响应面法优化植物乳杆菌高密度发酵参数[J]. 食品工业科技, 2016, (14): 206-209. DOI: 10.13386/j.issn1002-0306.2016.14.033
引用本文: 周金雨, 庞雪辉, 吴桐, 张秋雪, 孟祥晨. 响应面法优化植物乳杆菌高密度发酵参数[J]. 食品工业科技, 2016, (14): 206-209. DOI: 10.13386/j.issn1002-0306.2016.14.033
ZHOU Jin- yu, PANG Xue- hui, WU Tong, ZHANG Qiu- xue, MENG Xiang- chen. Optimization of high- density fermentation conditions for Lactobacillus plantarum by response surface methodology[J]. Science and Technology of Food Industry, 2016, (14): 206-209. DOI: 10.13386/j.issn1002-0306.2016.14.033
Citation: ZHOU Jin- yu, PANG Xue- hui, WU Tong, ZHANG Qiu- xue, MENG Xiang- chen. Optimization of high- density fermentation conditions for Lactobacillus plantarum by response surface methodology[J]. Science and Technology of Food Industry, 2016, (14): 206-209. DOI: 10.13386/j.issn1002-0306.2016.14.033

响应面法优化植物乳杆菌高密度发酵参数

Optimization of high- density fermentation conditions for Lactobacillus plantarum by response surface methodology

  • 摘要: 本研究应用响应面法优化植物乳杆菌KLDS 1.0391的高密度发酵参数。以玉米浆粉为培养基,活菌数为指标,在单因素实验基础上,采用中心组合实验设计优化发酵温度、发酵p H以及接种量。结果发现三个因素对发酵液中活菌数影响大小依次为:发酵温度>接种量>p H;获得的最优发酵参数为:发酵温度为34.7℃、p H为6.2、接种量为3.1%。在此条件下,发酵11 h后,发酵液中的活菌数达到9.58 lg CFU/m L,与模型预测值的相对误差为1.33%,差异不显著。说明所建立的模型能够较好地反映实际发酵情况。 

     

    Abstract: In this study,response surface methodology was applied to optimize high density fermentation parameters for Lactobacillus plantarum KLDS 1.0391.Central composite design was used to optimize fermentation temperature,fermentation p H and inoculation following the single factor tests. Corn steep powder was used as fermentation medium and the total number of viable bacteria was used as the main indicator. The results showed that the influence of three factors on the number of viable bacteria in the fermentation broth was in order as follows: fermentation temperature > inoculation > fermentation p H. The number of viable bacteria achieved9.58 lg CFU / m L under the optimum fermentation parameter which included fermentation temperature of 34.7 ℃,fermentation p H of 6.2,inoculation of 3.1% and fermentation time of 11 h.There's no significant difference between the results obtained according to optimum conditions and the predicted value,and the relative error was 1.33%between them.The established model can effectively reflect the actual fermentation conditions.

     

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