基于响应面法单因素模型的l -精氨酸诱导茜草毛状根培养基优化

M. Ghorbani, M. Omidi, S. A. Peighambari
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引用次数: 3

摘要

通过统计试验设计,对毛状根产生次生代谢物的培养基优化进行了研究。采用响应面法(RSM)单因素模型,结合菌株(ATCC 15834、C58C1和R1000)、外植体类型(叶和茎)在共培养培养基(B5和MS)中诱导茜草(Rubia tinctorum L.)毛状根的3个分类因素,确定了茜草毛状根诱导的l -精氨酸氨基酸水平。采用Expert-Design®7.1软件进行实验设计和数据分析。根据结果进行建模和优化,条件包括l -精氨酸浓度为1.00 mM;菌株;评价C58C1、叶片外植体和B5培养基对HR的诱导频率为58%(可取点=0.986)。RSM预测的这些最佳条件可以促进毛状根诱导,为生物技术生产预期化合物提供了应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
L-Arginine optimization medium for hairy root induction of madder (Rubia tinctorum L.) based on one factor model of response surface methodology.
Medium optimization for hairy root cultures producing secondary metabolites was studied through statistical experimental design. In the following, one factor model of response surface methodology (RSM) was employed to formulate the L-Arginine amino acid levels alongside three categorical factors including bacterial strains (ATCC 15834, C58C1 and R1000), type of explant (Leaf and Stem) in co-cultivation media (B5 and MS) for hairy root induction of Madder ( Rubia tinctorum L.). Design of experiment and data analysis was carried out by using Expert-Design ® 7.1 software. According to the results, modeling and optimization conditions, including L-Arginine concentration 1.00 mM; bacterial strain; C58C1, leaf explant and B5 medium for HR induction frequency equal to 58% was evaluated (Desirability point=0.986). These optimal conditions predicted by RSM were confirmed to enhance hairy root induction as an application potential for biotechnological implementation to produce the anticipated compounds.
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