{"title":"应用多响应优化技术探索益生菌发酵条件","authors":"S. Rheem","doi":"10.22424/jdsb.2023.41.2.45","DOIUrl":null,"url":null,"abstract":"This review serves two purposes: first, to promote the use of improved optimization techniques in response surface methodology (RSM); and second, to enhance the optimum conditions for the fermentation of probiotics. According to research in dairy science, Lactiplantibacillus plantarum K79 is a candidate probiotic that has beneficial health effects, such as lowering blood pressure. The optimum conditions for L. plantarum K79 to produce peptides with angiotensin-converting enzyme (ACE) inhibitory activity were proposed, through modeling each of ACE inhibitory activity and pH as a function of the four factors that are skim milk concentration (%), incubation temperature (°C), incubation time (hours), and starter added amount (%). To estimate optimum conditions, the researchers employed a desirability-based multi-response optimization approach, utilizing third-order models with a nonsignificant lack of fit. The estimated optimum fermentation conditions for L. plantarum K79 were as follows: a skim milk concentration of 10.76%, an incubation temperature of 36.9°C, an incubation time of 23.76 hours, and a starter added amount of 0.098%. Under these conditions, the predicted ACE inhibitory activity was 91.047%, and the predicted pH was 4.6. These predicted values achieved the objectives of the multi-response optimization in this study.","PeriodicalId":15410,"journal":{"name":"Journal of Dairy Science and Biotechnology","volume":"6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applying Multi-Response Optimization to Explore Fermentation\\n Conditions of Probiotics\",\"authors\":\"S. Rheem\",\"doi\":\"10.22424/jdsb.2023.41.2.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This review serves two purposes: first, to promote the use of improved optimization techniques in response surface methodology (RSM); and second, to enhance the optimum conditions for the fermentation of probiotics. According to research in dairy science, Lactiplantibacillus plantarum K79 is a candidate probiotic that has beneficial health effects, such as lowering blood pressure. The optimum conditions for L. plantarum K79 to produce peptides with angiotensin-converting enzyme (ACE) inhibitory activity were proposed, through modeling each of ACE inhibitory activity and pH as a function of the four factors that are skim milk concentration (%), incubation temperature (°C), incubation time (hours), and starter added amount (%). To estimate optimum conditions, the researchers employed a desirability-based multi-response optimization approach, utilizing third-order models with a nonsignificant lack of fit. The estimated optimum fermentation conditions for L. plantarum K79 were as follows: a skim milk concentration of 10.76%, an incubation temperature of 36.9°C, an incubation time of 23.76 hours, and a starter added amount of 0.098%. Under these conditions, the predicted ACE inhibitory activity was 91.047%, and the predicted pH was 4.6. These predicted values achieved the objectives of the multi-response optimization in this study.\",\"PeriodicalId\":15410,\"journal\":{\"name\":\"Journal of Dairy Science and Biotechnology\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Dairy Science and Biotechnology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22424/jdsb.2023.41.2.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Dairy Science and Biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22424/jdsb.2023.41.2.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
这篇综述有两个目的:第一,促进改进的优化技术在响应面方法(RSM)中的应用;二是提高益生菌发酵的最佳条件。根据乳制品科学的研究,植物乳杆菌K79是一种候选益生菌,对健康有有益的影响,比如降低血压。通过建立乳脂浓度(%)、培养温度(℃)、培养时间(h)和发酵剂添加量(%)对ACE抑制活性和pH的影响模型,确定了L. plantarum K79生产具有血管紧张素转换酶(ACE)抑制活性肽的最佳条件。为了估计最佳条件,研究人员采用了一种基于可取性的多响应优化方法,利用三阶模型,不显着缺乏拟合。植物乳杆菌K79的最佳发酵条件为:脱脂乳浓度10.76%,发酵温度36.9℃,发酵时间23.76 h,发酵剂添加量0.098%。在此条件下,预测ACE抑制活性为91.047%,预测pH为4.6。这些预测值达到了本研究多响应优化的目的。
Applying Multi-Response Optimization to Explore Fermentation
Conditions of Probiotics
This review serves two purposes: first, to promote the use of improved optimization techniques in response surface methodology (RSM); and second, to enhance the optimum conditions for the fermentation of probiotics. According to research in dairy science, Lactiplantibacillus plantarum K79 is a candidate probiotic that has beneficial health effects, such as lowering blood pressure. The optimum conditions for L. plantarum K79 to produce peptides with angiotensin-converting enzyme (ACE) inhibitory activity were proposed, through modeling each of ACE inhibitory activity and pH as a function of the four factors that are skim milk concentration (%), incubation temperature (°C), incubation time (hours), and starter added amount (%). To estimate optimum conditions, the researchers employed a desirability-based multi-response optimization approach, utilizing third-order models with a nonsignificant lack of fit. The estimated optimum fermentation conditions for L. plantarum K79 were as follows: a skim milk concentration of 10.76%, an incubation temperature of 36.9°C, an incubation time of 23.76 hours, and a starter added amount of 0.098%. Under these conditions, the predicted ACE inhibitory activity was 91.047%, and the predicted pH was 4.6. These predicted values achieved the objectives of the multi-response optimization in this study.