利用遺傳演算法探討酸凝酪中原生菌生長速率之最適化

Study on the Optimal Growth Rates of Probiotics in Yogurt by Genetic Algorithms

陳明汝(Ming-Ju Chen) ； 陳坤男(Kun-Nan Chen) ； 林慶文(Chin-Wen Lin) ； 毛漢梅(Ham-Mei Mao)

《臺灣農業化學與食品科學》 42卷4期 (2004/08) Pp. 306-314

https://doi.org/10.6578/TJACFS.2004.040

摘要

本研究旨於探討脫脂乳中同時添加多種原生菌促生長物質，對發酵期間原生菌生長速率之影響。所以用之原生菌種為：Lactobacillus acidophilus、L. casei、Bifidobacterium longum 及B. bifidum。 在試驗設計方面，因添加因子眾多，使整個試驗龐大而複雜，故採用反應曲面法(response surface methods, RSM)之減次設計，減少試驗組數，以利試驗進行。本試驗添加三種原生菌促生長物質，分別為肽類、果寡醣及異麥芽寡醣，以此三者之濃度為變因，而以發酵10小時乳酸桿菌、雙叉乳桿菌及L. casei 之生長速率作為反應性狀 (response)，根據Box和Behnken之因子三階次設計，共得17個試驗組，於一個區集下進行試驗。試驗結果皆經由Design-Expert軟體分析找出最適方程式，再以遺傳演算法 (genetic algorithms, GAs)搜尋原生菌最佳生長模式。經GAs運算後所得肽類、果寡醣、異麥芽寡醣濃度之最適添加量，在發酵10小時期間分別為1.12、3、1.5%。將電腦預測結果經由實際試驗驗證，發現均無顯著差異。將GAs所推薦之最適解，進一步分析其發酵期間有機酸生成量與游離胺基酸組成，並與未添加促生長物質之脫脂乳發酵組比較，發現GAs組之有機酸生成量明顯高於脫脂乳組，且游離胺基酸總含量亦以GAs組較高。

關鍵字

原生菌 ； 最適化 ； 遺傳演算法

並列摘要

This research was to study the effects of addition of growth promoters to skim milk on the viability of probiotics (Lactobacillus acidophilus, L. casei, Bifidobacterium longum, and B. bifidum). The purpose of this study was to optimize the activity and viability of the probiotics by the response surface modeling and the genetic algorithms. Samples were prepared by addition of three different growth promoters (peptides, fructooligosaccharides, and isomaltooligosaccharides) to skim milk. A three-factor, three-level Box Behnken Design with five replicates at the centerpoint was used to reduce number of experimental trials and increase the R^2 of models. Seventeen combinations were obtained. The results showed that the quadratic model appeared to be the most accurate with no significant lack of fit with high R^2. The GA results indicated the optimal amounts of peptides, fructooligosaccharides, and isomaltooligosaccharides were 1.12, 3, and 1.5%, respectively, led to the highest growth rates of probiotics. Model verification was performed by additional independent trials, and the experimental values were very close to the predicted ones with no significant difference. The genetic algorithms (GAs) were proved to be very effective for optimizing the activity of probiotic cultures. The amount of organic acids and the composition of free amino acids in samples recommended by GAs during 10 hours fermentation were determined. Results showed addition of growth promoters could improve the activity and viability of probiotics resulting in increasing the amount of amino acids and organic acids.

並列關鍵字

Probiotics ； Optimization ； Genetic algorithms