Optimization of culture conditions of Cd-tolerant strain <i>Pseudomonas</i> TCd-1 based on response surface methodology

WANG Dunfei; ZHU Shengnan; XIAO Qingtie; ZHENG Xinyu; LIN Ruiyu

doi:10.11833/j.issn.2095-0756.20190587

Volume 37 Issue 5

Oct. 2020

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WANG Dunfei, ZHU Shengnan, XIAO Qingtie, ZHENG Xinyu, LIN Ruiyu. Optimization of culture conditions of Cd-tolerant strain Pseudomonas TCd-1 based on response surface methodology[J]. Journal of Zhejiang A&F University, 2020, 37(5): 914-921. doi: 10.11833/j.issn.2095-0756.20190587

Citation:

WANG Dunfei, ZHU Shengnan, XIAO Qingtie, ZHENG Xinyu, LIN Ruiyu. Optimization of culture conditions of Cd-tolerant strain Pseudomonas TCd-1 based on response surface methodology[J]. Journal of Zhejiang A&F University, 2020, 37(5): 914-921. doi: 10.11833/j.issn.2095-0756.20190587

Optimization of culture conditions of Cd-tolerant strain Pseudomonas TCd-1 based on response surface methodology

doi: 10.11833/j.issn.2095-0756.20190587

WANG Dunfei^1
,,
ZHU Shengnan¹,
XIAO Qingtie^{1, 2},
ZHENG Xinyu^{1, 2},
LIN Ruiyu^{1, 2
,
,}

1.
Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China
2.
Key Laboratory of Crop Ecology and Molecular Physiology of Fujian Province University, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China

Received Date: 2019-10-09
Rev Recd Date: 2020-03-31

Available Online: 2020-10-10

Publish Date: 2020-08-20

Abstract

Objective This study aims to optimize the culture conditions of Cd-tolerant Pseudomonas TCd-1 based on response surface methodology. Method Taking the basic fermentation conditions as the control, and the absorbance D(660) value of the strain as the evaluation index, the single factor test was carried out to determine the best carbon source, nitrogen source, and inorganic salt species of the culture medium components. The Plackett-Burman test design was used to evaluate the influence of 8 factors on the growth of the strain, including beef extract, yeast powder, magnesium chloride, culture temperature, initial pH, inoculation quantity, culture time, and rotation speed. The best combination of significant factors was obtained by the steepest climbing test. The culture conditions of TCd-1 were optimized by combining the box Behnken design test and response surface analysis. Result The best carbon source, nitrogen source, and inorganic salt of the strain culture medium components were beef extract, yeast powder, and magnesium chloride. The significant factors affecting the growth of the strain were yeast powder, culture temperature, and initial pH. The optimized culture conditions based on response surface methodology included beef extract 0.5%, yeast powder 1.0%, magnesium chloride 0.5%, pH 6.3, temperature 33 ℃, inoculation rate 1.25%, rotation speed 160 r·min⁻¹, and culture time 24 h. Conclusion According to the optimal conditions, the D(660) value of the optimized bacterial solution is 67.07% higher than that of the control after repeated experiments, which is consistent with the predicted value of the model, indicating that the optimized conditions could significantly promote the growth of the strain and achieve the desired goal.[Ch, 1 fig. 6 tab. 26 ref.]
- Pseudomonas sp.,
- Cd,
- Plackett-Burman design,
- optimized culture,
- response surface methodology

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References


[2]	NIU Zhixing, SUN Lina, SUN Teiheng. Plant-microorganism combined remediation of heavy metals-contaminated soils: its research progress [J]. Chin J Ecol, 2009, 28(11): 2366 − 2373.
[3]	MENG Long, HUANG Tuhai, CHEN Jian, et al. Safe utilization of farmland soil with cadmium pollution: strategies and deliberations [J]. J Zhejiang Univ Agric Life Sci, 2019, 45(3): 263 − 271.
[4]	QIAN Chunxiang, WANG Mingming, XU Yanbo. Current situation of soil contamination by heavy metals and research progress in bio-remediation technique [J]. J Southeast Univ Nat Sci Ed, 2013, 43(3): 669 − 674.
[5]	JIANG Chengbin. Selection and Analysis of Bacteria Higher Tolerance and Enrichment to Cd²⁺[D]. Chengdu: Southwest Jiaotong University, 2007.
[6]	ZHANG Xin, FAN Zhongxue, GUO Dufa, et al. Effects of microorganisms on the growth of spinach under Cd stress [J]. Tianjin Agric Sci, 2011, 17(1): 81 − 83, 87.
[7]	WANG Wei, LI Yuanping, XIE Huiling, et al. Screening of carrier for Pseudomonas aeruginosa bacterial agent [J]. J Fujian Agric For Univ Nat Sci Ed, 2016, 45(3): 325 − 330.
[8]	HE Xiaosan, WANG Wei, XIAO Qingtie, et al. Effects of Pseudomonas aeruginosa on the growth and cadmium accumulation in rice (Oryza sativa L.) seedling under Cd stress [J]. Chin J Eco-Agric, 2018, 26(6): 884 − 891.
[9]	WANG Dunfei, ZHENG Xinyu, XIAO Qingtie, et al. Effects of Pseudomonas aeruginosa on root activity and leaf physiological characteristics in rice (Oryza sativa L.) seedling under cadmium stress [J]. Chin J Appl Ecol, 2019, 30(8): 2767 − 2774.
[10]	BRAUD A, JÉZÉQUEL K, BAZOT S, et al. Enhanced phytoextraction of an agricultural Cr-and Pb-contaminated soil by bioaugmentation with siderophore-producing bacteria [J]. Chemosphere, 2008, 74(2): 280 − 286.
[11]	RANE M R, SARODE P D, CHAUDHARI B L, et al. Exploring antagonistic metabolites of established biocontrol agent of marine origin [J]. Appl Biochem Biotechnol, 2008, 151(2): 665 − 675.
[12]	ZHOU Liying, YE Renjie, LIN Shuting, et al. Screening and identification of cadmium-tolerant bacteria from rhizosphere soils under rice [J]. Chin J Eco-Agric, 2012, 20(5): 597 − 603.
[13]	WANG Yongfei, WANG Chengguo. The application of response surface methodology [J]. J CUN Nat Sci Ed, 2005, 14(3): 236 − 240.
[14]	LI Li, ZHANG Sai, HE Qiang, et al. Application of response surface methodology in experiment design and optimization [J]. Res Explor Lab, 2015, 34(8): 41 − 45.
[15]	HAO Xuecai, YU Xiaobin, LIU Zhiyu, et al. The application of response surface methodology in optimization of microbial media [J]. Food Res Dev, 2006, 27(1): 38 − 41.
[16]	HU Ruiping, DING Xian, LI Laihao, et al. Optimization of fermentation medium composition by response surface methodology for the spore production of Bacillus subtilis [J]. Chin J Ecol, 2018, 37(2): 605 − 612.
[17]	YIN Yang, YI Yanjie, LI Ruifang, et al. Optimization of fermentation conditions of Megaterium bacillus RB10 by response surface methodology [J]. Biotechnology, 2013, 23(2): 84 − 88.
[18]	YUAN Huilin. Plant Growth Promoting Rhizobacreria Cultication Optimization and Mechanism Research[D]. Beijing: Chinese Academy of Forestry, 2011.
[19]	LIU Jianghong, REN Jingwei, JIA Yunpeng, et al. Optimization of culture conditions of S2 strain by response surface method [J]. J Hunan Univ Nat Sci, 2015, 42(6): 96 − 100.
[20]	GONG Zhijin, LIU Shengge, LIANG Xinxin, et al. Optimization of fermentation medium components for rhamnolipid production by Pseudomonas aeruginosa with response surface methodology [J]. China Brew, 2017, 36(9): 127 − 131.

[22]	LI Yonghong, LIU Bo, ZHAO Zongbao, et al. Optimized culture medium and fermentation conditions forlipid production by Rhodosporidium toruloides [J]. Chin J Biotechnol, 2006, 22(4): 650 − 656.
[23]	DAI Zhikai, ZHANG Cui, RUAN Zheng. The application of experimental design and optimization techniques in optimization of microbial medium [J]. Microbiol China, 2010, 37(6): 894 − 903.

[25]	LI Fang, LIU Bo, HUANG Sufang. Effect of temperature on Paecilomyces lilacinus culture characteristics and its toxicity to Ditylenchus destructor [J]. Chin J Eco-Agric, 2007, 15(4): 130 − 133.
[26]	GOUVEIA E R, BAPTISTA-NETO A, Jr BADINO A C. Optimisation of medium composition for clavulanic acid production by Streptomyces clavuligerus [J]. Biotechnol Let, 2001, 23: 157 − 161.

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《全国土壤污染状况调查公报》显示，中国耕地土壤污染点位超标率高达19.4%，重金属污染点位超标率为15.5%，其中镉的点位超标率为7.0%，居首位^[1]。镉是一种毒性很强的人体非必需元素，极易被作物吸收进入食物链，从而危害人体健康^[2]。如何阻遏环境中的镉进入食物链，已成为当前土壤及生态环境领域的研究热点之一^[3]。目前，微生物修复技术成为镉污染治理的研究方向之一^[4]。蒋成斌^[5]筛选到2种耐镉细菌：腐败希瓦菌Shewanella putrefaciens和假单胞菌Pseudomonas sp.，在LB(Luria-Bertani)固体和液体培养上耐受重金属镉离子(Cd²⁺)浓度分别达到150和40 mmol·L⁻¹。张欣等^[6]在模拟镉轻度污染(1 mg·kg⁻¹)试验中通过施入微生物菌剂(枯草芽孢杆菌Bacillus subtilis、光合细菌和乳酸菌)后使菠菜Spinacia oleracea镉含量平均下降14.5%。王微等^[7]和何小三等^[8]利用硅藻土制备的铜绿假单胞菌Pseudomonas aeruginosa菌剂能够显著促进镉胁迫苗期水稻Oryza sativa的生长，抑制镉在根、茎鞘、叶片中的迁移与积累。汪敦飞等^[9]研究指出：耐镉铜绿假单胞菌及其菌剂能显著提高镉胁迫水稻苗期的根系活力，增强水稻叶片抗氧化酶系统的活力，提高水稻叶片抗氧化物的含量，从而有效缓解水稻镉胁迫效应。假单胞菌为革兰氏阴性菌，环境适应能力强，世代周期短，具有根际促生能力，已被广泛用作生防菌^[10-11]。本课题组前期从水稻根际土壤筛选了1株耐镉的假单胞菌TCd-1，能在高达900 mg·L⁻¹ Cd²⁺下生长，在100 mg·L⁻¹镉处理下，菌株体内吸收的镉质量分数为9.04 mg·g⁻¹，镉富集系数达到90.4，具有较强镉富集能力，因此有应用于镉污染的修复潜力^[12]。但该菌株的培养条件有待优化。响应面分析法是一种综合试验设计和数学建模的方法，既能有效减少试验次数又能考察各个因素之间的交互作用^[13-14]，在优化试验设计中，被人们广泛使用^[15]。胡瑞萍等^[16]利用响应面法优化了枯草芽孢杆菌 Bacillus subtilis NHS1菌株培养基组分，使芽孢含量比优化前提高1.5倍。印杨等^[17]利用响应面法优化了生防菌株(巨大芽孢杆菌Megaterium bacillus RB10)的发酵培养条件参数，证实了Box-Behnken设计的有效性和模型的准确可靠^[17]。袁辉林^[18]以植物促生菌SZ7-1为研究对象，在5 L自动发酵罐中采用单因素试验设计及响应曲面法进行扩大培养，结果表明：优化后的培养条件更利于菌株的生长，且活菌数是优化前的1.62倍。刘江红等^[19]通过响应面法优化了芽孢杆菌Bacillus S2的培养条件，使最优乳化指数(E24)提高为81.20%。巩志金等^[20]利用响应面法优化了铜绿假单胞菌产鼠李糖脂的发酵培养基，结果使其产量提高了14.43%。本研究基于响应面法通过单因素筛选试验、Plackett-Burman试验、Box-Behnken 试验和响应面分析法，对TCd-1菌株培养条件进行优化，以期为菌株潜在价值的开发利用和菌剂制备提供技术支持。

1. 材料与方法

1.1. 菌种及其活化培养

供试菌株为耐镉的假单胞菌Pseudomonas sp. TCd-1(专利号CN 103952333A)^[21]，甘油保存于−80 ℃冰箱。菌株活化时取出塑料冻存管，立即置于30~40 ℃恒温水浴锅中匀速摇动进行快速复苏，待冻存管内结冰全部溶解后，开启冻存管，将内容物转移至种子液培养基内培养。

种子液培养条件：采用牛肉膏蛋白胨培养基(牛肉膏3.0 g，蛋白胨10.0 g，氯化钠 5.0 g，琼脂 15.0~20.0 g，1.0 L蒸馏水，pH 7.2~7.4)。菌株长出后选取直径约为3 mm的菌落进行平板划线法过夜培养，再从2次培养的固体培养基上挑取1环菌落至100 mL的三角瓶，150 r·min⁻¹，37 ℃，恒温培养18 h，制成菌株种子液。发酵培养条件：牛肉膏蛋白胨液体培养基100 mL，质量分数为0.5%氯化钠，1.0%种子液，150 r·min⁻¹，37 ℃恒温培养24 h。

1.2. 试验设计

1.2.1. 单因素试验

在发酵培养条件下，选择不同氮源：N₁为酵母粉，N₂为硫酸铵[(NH₄)₂SO₄]，N₃为硝酸铵(NH₄NO₃)，N₄为蛋白胨，N₅为硝酸钾(KNO₃)，N₆为氯化铵(NH₄Cl)，N₇为硝酸纳(NaNO₃)，设置质量分数为0.5%、1.0%、1.5% 3个水平；不同碳源：C₁为牛肉膏，C₂为可溶性淀粉，C₃为葡萄糖，C₄为蔗糖，设置质量分数为0.1%、0.3%、0.5% 3个水平；不同无机盐：W₁为氯化钙(CaCl₂)，W₂为氯化镁(MgCl₂)，W₃为氯化钠(NaCl)，W₄为氯化钾(KCl)，W₅为磷酸氢二钠(Na₂HPO₄)，W₆为硫酸钠(Na₂SO₄)，W₇为磷酸二氢钠(NaH₂PO₄)，设置质量分数为0.2%、0.5%、0.8% 3个水平。以菌株最大吸收波长660 nm下的吸光度D(660)作为评价指标，筛选最适的碳源、氮源、无机盐及其质量分数。

1.2.2. Plackett-Burman试验

根据单因素试验得到的最适碳源(牛肉膏)、氮源(酵母粉)、无机盐(MgCl₂)，进行Plackett-Burman试验。试验设计如表1。试验次数 n=12，各因素水平设置为高低2个水平，高水平(1)取值为低水平(−1)的1.25倍，其中 D、H、K为空白试验，用于误差估计。考察牛肉膏(A)、酵母粉(B)、MgCl₂(C)、培养温度(E)、初始pH(F)、接菌量(G)、培养时间(I)和转速(J) 8个因素对菌株生长的影响，确定影响菌株生长的关键因素。

因素	水平		因素	水平		因素	水平
因素	−1	1	因素	−1	1	因素	−1	1
A 牛肉膏/%	4.0	5.0	E 温度/%	30.0	37.50	I 培养时间/h	20	24
B 酵母粉/%	0.8	1.0	F 初始pH	6.0	7.50	J 转速/(r·min⁻¹)	160	200
C MgCl₂/%	4.0	5.0	G 接菌量/%	1.0	1.250	K 空白3
D 空白1			H 空白2

Table 1. Factors and levels of Plackett-Burman design

1.2.3. 最陡爬坡及Box-Behnken试验

根据Plackett-Burman试验筛选得到的显著影响菌株生长的关键因素(酵母粉、温度、初始pH)，确定最陡爬坡试验的步长和方向，获得最佳的响应区域。

以最陡爬坡试验得到最佳响应区域(2号试验)作为Box-Behnken试验设计的中心点，各因素取3个水平，以(−1，0，1)表示，设计包括了5个中心点(0，0，0)，即酵母粉0.9%、温度35 ℃、pH 7，共17个组合的响应面试验。各处理3次重复。

试验号	B 酵母粉/%	E 温度/℃	F 初始pH	编码	吸光度
1	0.8	40	8.0	(−1，1，1)	1.079±0.058 c
2	0.9	35	7.0	(0，0，0)	1.720±0.006 a
3	1.0	30	6.0	(1，−1，−1)	1.681±0.015 b
说明：不同小写字母表示差异显著(P＜0.05)

Table 4. Factors and levels of steepest ascent design

1.2.4. 响应面分析

根据Box-Behnken试验结果，进行方差分析，并拟合线性回归方程，检验拟合防方程的符合程度；利用拟合方程获得最佳培养条件，并在最佳培养条件下进行验证试验。

1.3. 数据处理

数据处理和作图使用Excel 2016进行，统计分析使用Design Experts 10和IBM SPSS 22。试验结果以平均值±标准差表示，采用Duncan法进行数据差异显著性检验(P=0.05)。

3. 讨论与结论

3.1. Plackett-Burman试验中显著因素对菌株生长影响

Plackett-Burman 是一种基于非完全平衡块原理的近饱和的两水平试验设计方法。通过N次试验最多可以考察N−1个因素，用最少试验次数可以从众多因素中快速有效地筛选出最为重要的几个主效因子，每个因素取低和高2个水平，高水平取低水平的1.25倍^[22-23]。

在本试验中，Plackett-Burman试验从多个因素[牛肉膏(A)、酵母粉(B)、氯化镁(C)、培养温度(E)、初始pH(F)、接菌量(G)、培养时间(I)和转速(J)]中快速筛选出具有显著影响的因素为：酵母粉、pH和温度。其中酵母粉之所以能显著影响菌株生长，在于它能提供优质氮源满足细菌繁殖所必需，而且天然酵母粉主要由多种酵母菌自然繁殖而成，是一种纯天然、无污染的健康营养源^[24]。有机氮源比无机氮源含有更丰富的氨基酸、维生素及生长因子等营养物质，其中氨基酸可以直接参与微生物体内的转氨或脱氨作用(图1)，更适用于菌株生长。温度是诸多因素中显著影响因素之一，因为可能随着温度升高，菌体生长速度及营养消耗的速率也随之加快，明显缩短进入生长稳定期的时间；从酶本身特性来看，酶具有高效催化性，能够降低生化反应的活化能，但酶本身作用条件较温和，对温度比较敏感，很容易因温度过高而丧失活性^[25]。温度也会影响细胞膜的流动性，进而影响膜内外物质(水分、有机物、各种离子等)的交换和吸收。pH 显著影响菌株生长速率可能在于其对菌株生长需要的酶、各种生物大分子的稳定性造成破坏等，导致失去生物活性；pH也会影响到培养基中金属离子的存在形式，造成其不易或者不被吸收；pH同样会影响微生物细胞膜所带电荷状态，进而改变细胞膜的通透性，最终直接或间接影响微生物对所需营养物质的吸收和代谢产物的排出。

3.2. 响应面在优化培养条件的应用

响应面分析是利用统计学和数学模型的方法对需要优化的多因素系统进行建模和分析^[13-15]，Box-Behnken试验设计是其中拟合模型之一，目前常被用于生物发酵过程培养基和培养条件的优化。该方法不仅可以建立连续变量的曲面模型和拟合方程，还可以对影响微生物生长和发酵过程的各种因子及其交互作用进行评价，确定最佳水平范围，通过最少的试验组数获得更为精确有效的结论，极大地节约资源和降低成本，使其效应最大化^[26]。

细菌生长和培养是一个动态发酵过程，受外部发酵环境以及内部培养基成分的共同影响。此次试验以牛肉膏蛋白胨培养基为基础，通过单因素试验、Plackett-Burman试验、最陡爬坡试验、Box-Behnken试验确定菌株培养基组分和外部培养条件，系统优化了重金属镉耐性假单胞菌TCd-1培养体系，为后续进一步深入研究其菌剂制备及应用于重金属镉污染土壤的修复效应奠定了基础。

Reference (26)

[1]	环境保护部和国土资源部. 全国土壤污染状况调查公报[EB/OL]. 2014-04-17[2020-03-31]. http://www.mee.gov.cn/gkml/sthjbgw/qt/201404/t20140417_270670.htm.
[2]	牛之欣, 孙丽娜, 孙铁珩. 重金属污染土壤的植物-微生物联合修复研究进展[J]. 生态学杂志, 2009, 28(11): 2366 − 2373.	NIU Zhixing, SUN Lina, SUN Teiheng. Plant-microorganism combined remediation of heavy metals-contaminated soils: its research progress [J]. Chin J Ecol, 2009, 28(11): 2366 − 2373.
[3]	孟龙, 黄涂海, 陈謇, 等. 镉污染农田土壤安全利用策略及其思考[J]. 浙江大学学报(农业与生命科学版), 2019, 45(3): 263 − 271.	MENG Long, HUANG Tuhai, CHEN Jian, et al. Safe utilization of farmland soil with cadmium pollution: strategies and deliberations [J]. J Zhejiang Univ Agric Life Sci, 2019, 45(3): 263 − 271.
[4]	钱春香, 王明明, 许燕波. 土壤重金属污染现状及微生物修复技术研究进展[J]. 东南大学学报(自然科学版), 2013, 43(3): 669 − 674.	QIAN Chunxiang, WANG Mingming, XU Yanbo. Current situation of soil contamination by heavy metals and research progress in bio-remediation technique [J]. J Southeast Univ Nat Sci Ed, 2013, 43(3): 669 − 674.
[5]	蒋成斌. 重金属Cd²⁺高耐受和富集细菌的筛选与分析[D]. 成都: 西南交通大学, 2007.	JIANG Chengbin. Selection and Analysis of Bacteria Higher Tolerance and Enrichment to Cd²⁺[D]. Chengdu: Southwest Jiaotong University, 2007.
[6]	张欣, 范仲学, 郭笃发, 等. 3种微生物制剂对轻度镉污染土壤中菠菜生长的影响[J]. 天津农业科学, 2011, 17(1): 81 − 83, 87.	ZHANG Xin, FAN Zhongxue, GUO Dufa, et al. Effects of microorganisms on the growth of spinach under Cd stress [J]. Tianjin Agric Sci, 2011, 17(1): 81 − 83, 87.
[7]	王微, 李圆萍, 谢惠玲, 等. 铜绿假单胞菌菌剂载体的筛选[J]. 福建农林大学学报(自然科学版), 2016, 45(3): 325 − 330.	WANG Wei, LI Yuanping, XIE Huiling, et al. Screening of carrier for Pseudomonas aeruginosa bacterial agent [J]. J Fujian Agric For Univ Nat Sci Ed, 2016, 45(3): 325 − 330.
[8]	何小三, 王微, 肖清铁, 等. 铜绿假单胞菌对镉胁迫水稻苗期生长与镉积累的影响[J]. 中国生态农业学报, 2018, 26(6): 884 − 891.	HE Xiaosan, WANG Wei, XIAO Qingtie, et al. Effects of Pseudomonas aeruginosa on the growth and cadmium accumulation in rice (Oryza sativa L.) seedling under Cd stress [J]. Chin J Eco-Agric, 2018, 26(6): 884 − 891.
[9]	汪敦飞, 郑新宇, 肖清铁, 等. 铜绿假单胞菌对镉胁迫苗期水稻根系活力及叶片生理特性的影响[J]. 应用生态学报, 2019, 30(8): 2767 − 2774.	WANG Dunfei, ZHENG Xinyu, XIAO Qingtie, et al. Effects of Pseudomonas aeruginosa on root activity and leaf physiological characteristics in rice (Oryza sativa L.) seedling under cadmium stress [J]. Chin J Appl Ecol, 2019, 30(8): 2767 − 2774.
[10]	BRAUD A, JÉZÉQUEL K, BAZOT S, et al. Enhanced phytoextraction of an agricultural Cr-and Pb-contaminated soil by bioaugmentation with siderophore-producing bacteria [J]. Chemosphere, 2008, 74(2): 280 − 286.
[11]	RANE M R, SARODE P D, CHAUDHARI B L, et al. Exploring antagonistic metabolites of established biocontrol agent of marine origin [J]. Appl Biochem Biotechnol, 2008, 151(2): 665 − 675.
[12]	周丽英, 叶仁杰, 林淑婷, 等. 水稻根际耐镉细菌的筛选与鉴定[J]. 中国生态农业学报, 2012, 20(5): 597 − 603.	ZHOU Liying, YE Renjie, LIN Shuting, et al. Screening and identification of cadmium-tolerant bacteria from rhizosphere soils under rice [J]. Chin J Eco-Agric, 2012, 20(5): 597 − 603.
[13]	王永菲, 王成国. 响应面法的理论与应用[J]. 中央民族大学学报(自然科学版版), 2005, 14(3): 236 − 240.	WANG Yongfei, WANG Chengguo. The application of response surface methodology [J]. J CUN Nat Sci Ed, 2005, 14(3): 236 − 240.
[14]	李莉, 张赛, 何强, 等. 响应面法在试验设计与优化中的应用[J]. 实验室研究与探索, 2015, 34(8): 41 − 45.	LI Li, ZHANG Sai, HE Qiang, et al. Application of response surface methodology in experiment design and optimization [J]. Res Explor Lab, 2015, 34(8): 41 − 45.
[15]	郝学财, 余晓斌, 刘志钰, 等. 响应面方法在优化微生物培养基中的应用[J]. 食品研究与开发, 2006, 27(1): 38 − 41.	HAO Xuecai, YU Xiaobin, LIU Zhiyu, et al. The application of response surface methodology in optimization of microbial media [J]. Food Res Dev, 2006, 27(1): 38 − 41.
[16]	胡瑞萍, 丁贤, 李来好, 等. 响应面法优化枯草芽孢杆菌NHS1产芽孢发酵培养[J]. 生态学杂志, 2018, 37(2): 605 − 612.	HU Ruiping, DING Xian, LI Laihao, et al. Optimization of fermentation medium composition by response surface methodology for the spore production of Bacillus subtilis [J]. Chin J Ecol, 2018, 37(2): 605 − 612.
[17]	印杨, 伊艳杰, 李瑞芳, 等. 响应面法优化巨大芽孢杆菌RB10的发酵培养条件[J]. 生物技术, 2013, 23(2): 84 − 88.	YIN Yang, YI Yanjie, LI Ruifang, et al. Optimization of fermentation conditions of Megaterium bacillus RB10 by response surface methodology [J]. Biotechnology, 2013, 23(2): 84 − 88.
[18]	袁辉林. 植物促生菌培养优化及作用机理研究[D]. 北京: 中国林业科学研究院, 2011.	YUAN Huilin. Plant Growth Promoting Rhizobacreria Cultication Optimization and Mechanism Research[D]. Beijing: Chinese Academy of Forestry, 2011.
[19]	刘江红, 任静薇, 贾云鹏, 等. 响应面法优化S2菌株的培养条件[J]. 湖南大学学报(自然科学版), 2015, 42(6): 96 − 100.	LIU Jianghong, REN Jingwei, JIA Yunpeng, et al. Optimization of culture conditions of S2 strain by response surface method [J]. J Hunan Univ Nat Sci, 2015, 42(6): 96 − 100.
[20]	巩志金, 刘胜格, 梁鑫鑫, 等. 响应面法优化铜绿假单胞菌产鼠李糖脂发酵培养基的研究[J]. 中国酿造, 2017, 36(9): 127 − 131.	GONG Zhijin, LIU Shengge, LIANG Xinxin, et al. Optimization of fermentation medium components for rhamnolipid production by Pseudomonas aeruginosa with response surface methodology [J]. China Brew, 2017, 36(9): 127 − 131.
[21]	林瑞余, 肖清铁, 周丽英, 等. 1种镉耐性细菌及其抑制水稻吸收重金属镉的方法: CN103952333A [P]. 2014-07-30.
[22]	李永红, 刘波, 赵宗保, 等. 圆红冬孢酵母菌发酵产油脂培养基及发酵条件的优化研究[J]. 生物工程学报, 2006, 22(4): 650 − 656.	LI Yonghong, LIU Bo, ZHAO Zongbao, et al. Optimized culture medium and fermentation conditions forlipid production by Rhodosporidium toruloides [J]. Chin J Biotechnol, 2006, 22(4): 650 − 656.
[23]	代志凯, 张翠, 阮征. 试验设计和优化及其在发酵培养基优化中的应用[J]. 微生物学通报, 2010, 37(6): 894 − 903.	DAI Zhikai, ZHANG Cui, RUAN Zheng. The application of experimental design and optimization techniques in optimization of microbial medium [J]. Microbiol China, 2010, 37(6): 894 − 903.
[24]	李志斌. 天然酵母中种面团及其制作方法: CN104757043A [P]. 2015-07-08.
[25]	李芳, 刘波, 黄素芳. 温度对淡紫拟青霉NH-PL-03菌株培养特性及毒力的影响[J]. 中国生态农业学报, 2007, 15(4): 130 − 133.	LI Fang, LIU Bo, HUANG Sufang. Effect of temperature on Paecilomyces lilacinus culture characteristics and its toxicity to Ditylenchus destructor [J]. Chin J Eco-Agric, 2007, 15(4): 130 − 133.
[26]	GOUVEIA E R, BAPTISTA-NETO A, Jr BADINO A C. Optimisation of medium composition for clavulanic acid production by Streptomyces clavuligerus [J]. Biotechnol Let, 2001, 23: 157 − 161.

来源	均方和	自由度	均方	F	P	显著性	效应系数	显著性排序	效应正负
模型	0.780 00	8	0.098 00	70.01	0.002 5	**	1.430
A 牛肉膏	0.004 07	1	0.004 07	2.91	0.186 5		0.018	7	＋
B 酵母粉	0.200 00	1	0.200 00	141.15	0.001 3	**	0.130	2	＋
C 氯化镁	0.004 84	1	0.004 84	3.46	0.159 8		0.020	5	＋
E 温度	0.540 00	1	0.540 00	387.22	0.000 3	**	−0.210	1	−
F pH	0.017 00	1	0.017 00	12.45	0.038 7	*	−0.038	3	−
G 接菌量	0.004 76	1	0.004 76	3.40	0.162 2		−0.020	6	＋
I 时间	0.000 03	1	0.000 03	0.022	0.892 7		0.002	8	＋
J 转速	0.013 00	1	0.013 00	9.49	0.054 1		−0.033	4	−
说明：表示差异显著(P＜0.05)，*表示差异极显著(P＜0.01)

来源	均方和	自由度	均方	F	显著性	来源	均方和	自由度	均方	F	显著性
模型	1.638 00	9	0.182 00	182.747	**	B²	0.002 36	1	0.002 36	2.371
B	0.020 00	1	0.020 00	20.091	**	E²	0.820 50	1	0.820 00	824.161	**
E	0.756 00	1	0.756 00	759.257	**	F²	0.005 14	1	0.005 14	5.159
F	0.008 90	1	0.008 91	8.951	**	残差	0.006 97	7	0.001 00
BE	0. 000 06	1	0.000 06	0.064		失拟项	0.004 91	3	0.001 64	3.179	不显著
BF	0.000 48	1	0.000 48	0.486		纯误差	0.002 06	4	0.000 52
EF	0.006 64	1	0.006 64	6.672	*	总和	1.644 00	16
说明：变异系数为2.08%，相关系数为0.995 8，校正决定系数为0.9903，预测系数为0.950 3。表示显著差异(P＜0.05)，*表示极显　　　　　著差异(P＜0.01)