基于响应面法优化鲁氏酵母培养基

doi:10.11924/j.issn.1000-6850.casb2023-0350

摘要/Abstract

摘要：

为了提高鲁氏酵母的菌量，并解决酱油工业化生产中发酵时间过长的问题，研究通过单因素试验，利用基于响应面法对鲁氏酵母培养基成分进一步优化。首先，采用Plackett-Burman设计方法，在影响鲁氏酵母活菌数的9个因素中快速而有效地筛选出了3个显著性影响因素：葡萄糖、豆粕、硫酸锰，随后，通过最陡爬坡试验确定了最大响应值区间，并使用 Box-Behnken设计方法得到最优培养基组合：葡萄糖58 g/L、玉米粉20 g/L、磷酸二氢铵5 g/L、豆粕43 g/L、磷酸二氢钾1 g/L、磷酸氢二钠2 g/L、硫酸锌0.04 g/L、硫酸锰0.04 g/L、硫酸镁0.5 g/L。在最优培养基组合下，鲁氏酵母活菌数达到12.81×10⁸cfu/mL，是优化前的3.64倍。本研究的发现为酱油工业化生产提供了一种有效提高鲁氏酵母菌量的方法，有望显著缩短发酵时间。

关键词: 鲁氏酵母, 酱油生产, 单因素实验, 响应面实验, 培养基优化

Abstract:

The aim of this study was to increase the amount of Zygosaccharomyces rouxii and break the bottleneck of long fermentation time in the industrialized production of soy sauce. On the basis of single factor experiment, response surface methodology was used to optimize the composition of the medium. 3 significant factors were quickly and effectively screened out of 9 factors affecting the amount of Zygosaccharomyces rouxii by Plackett-Burman design: glucose, soybean meal, manganese sulfate. The maximum response interval was obtained by the steepest climb test and the optimal medium combination was obtained by Box-Behnken design. The optimal medium combination was as follows: glucose 58 g/L, corn meal 20 g/L, phosphate dibasic Ammonium hydrogen 5 g/L, soybean meal 43 g/L, potassium dihydrogen phosphate 1 g/L, disodium hydrogen phosphate 2 g/L, zinc sulfate 0.04 g/L, manganese sulfate 0.04 g/L, magnesium sulfate 0.5 g/L. Under the optimal medium combination, the amount of Zygosaccharomyces rouxii reached 12.81×10⁸ cfu/mL, which was 3.64 times higher than that before optimization.

Key words: Zygosaccharomyces rouxii, soy sauce production, single factor experiment, response surface experiment, medium optimization

潘冬梅, 杨传伦, 张心青, 郭南南, 张萧萧, 高保军, 王秀芝, 司更花, 和富明, 傅英旬, 田杰伟, 刘光彬, 赵辉. 基于响应面法优化鲁氏酵母培养基[J]. 中国农学通报, 2024, 40(15): 124-131.

PAN Dongmei, YANG Chuanlun, ZHANG Xinqing, GUO Nannan, ZHANG Xiaoxiao, GAO Baojun, WANG Xiuzhi, SI Genghua, HE Fuming, FU Yingxun, TIAN Jiewei, LIU Guangbin, ZHAO Hui. Zygosaccharomyces rouxii Culture Medium: Optimization Based on Response Surface Methodology[J]. Chinese Agricultural Science Bulletin, 2024, 40(15): 124-131.

图/表 11

参考文献 20

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因素	回归系数	标准误	F值	P值	显著性
A	1.38	0.041	1148.44	0.0009	显著
B	0.086	0.041	4.45	0.1694	不显著
C	-0.13	0.041	10.87	0.0810	不显著
D	0.43	0.041	112.94	0.0087	显著
E	4.167E-003	0.041	0.010	0.9278	不显著
F	0.086	0.041	4.45	0.1694	不显著
G	0.071	0.041	3.03	0.2239	不显著
H	-0.20	0.041	25.17	0.0375	显著
J	0.036	0.041	0.78	0.4715	不显著

因素	回归系数	标准误	F值	P值	显著性
A	1.38	0.041	1148.44	0.0009	显著
B	0.086	0.041	4.45	0.1694	不显著
C	-0.13	0.041	10.87	0.0810	不显著
D	0.43	0.041	112.94	0.0087	显著
E	4.167E-003	0.041	0.010	0.9278	不显著
F	0.086	0.041	4.45	0.1694	不显著
G	0.071	0.041	3.03	0.2239	不显著
H	-0.20	0.041	25.17	0.0375	显著
J	0.036	0.041	0.78	0.4715	不显著

试验号	葡萄糖/ (g/L)	豆粕/ (g/L)	硫酸锰/ (g/L)	酵母活菌数/ (×10⁸cfu/mL)
1	45	30	0.06	9.45
2	48	33	0.055	9.98
3	51	36	0.05	11.25
4	54	39	0.045	11.70
5	57	42	0.04	12.51
6	60	45	0.035	10.54

试验号	葡萄糖/ (g/L)	豆粕/ (g/L)	硫酸锰/ (g/L)	酵母活菌数/ (×10⁸cfu/mL)
1	45	30	0.06	9.45
2	48	33	0.055	9.98
3	51	36	0.05	11.25
4	54	39	0.045	11.70
5	57	42	0.04	12.51
6	60	45	0.035	10.54

方差来源	平方和	自由度	均方	F值	P值	显著性
模型	2.74	9	0.30	9.84	0.0032	显著
A	0.22	1	0.22	7.25	0.0310	显著
B	0.13	1	0.13	4.28	0.0773	不显著
C	0.012	1	0.012	0.39	0.5532	不显著
AB	0.027	1	0.027	0.88	0.3797	不显著
AC	0.38	1	0.38	12.21	0.0101	显著
BC	0.032	1	0.032	1.05	0.3405	不显著
A²	0.79	1	0.79	25.48	0.0015	显著
B²	0.49	1	0.49	15.76	0.0054	显著
C2	0.46	1	0.46	14.85	0.0063	显著
残差	0.22	7	0.031	-	-	-
失拟项	0.17	3	0.056	4.75	0.0832	不显著
纯误差	0.048	14	0.012	-	-	-
总离差	2.96	16	-	-	-	-