Preparation of two strains of lignin-degrading bacteria solid inoculum

LI Yalin; LI Suyan; SUN Xiangyang; HAO Dan; CAI Linlin; CHANG Xiaotong

doi:10.11833/j.issn.2095-0756.20210311

Volume 39 Issue 2

Mar. 2022

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LI Yalin, LI Suyan, SUN Xiangyang, HAO Dan, CAI Linlin, CHANG Xiaotong. Preparation of two strains of lignin-degrading bacteria solid inoculum[J]. Journal of Zhejiang A&F University, 2022, 39(2): 364-371. doi: 10.11833/j.issn.2095-0756.20210311

Citation:

LI Yalin, LI Suyan, SUN Xiangyang, HAO Dan, CAI Linlin, CHANG Xiaotong. Preparation of two strains of lignin-degrading bacteria solid inoculum[J]. Journal of Zhejiang A&F University, 2022, 39(2): 364-371. doi: 10.11833/j.issn.2095-0756.20210311

Preparation of two strains of lignin-degrading bacteria solid inoculum

doi: 10.11833/j.issn.2095-0756.20210311

College of Forestry, Beijing Forestry University, Beijing 100083, China

Received Date: 2021-04-21
Rev Recd Date: 2021-08-16

Available Online: 2022-03-25

Publish Date: 2022-03-25

Abstract

Objective With two different lignin-degrading bacteria, strain A (Aspergillus nidulans) and strain Q (Trametes sp.) used as materials, this study is aimed to research the production of high-efficiency solid fermentation inoculants for degradation or composting of garden greening wastes. Method First, a single factor experiment was employed to determine the types of carbon and nitrogen sources and additional nutrient components of the solid fermentation medium. Then, the orthogonal experiment design was adopted to optimize the amount of carbon and nitrogen sources to be added, based on which, efforts were made to figure out the inoculation amount of additional nutrient components and the best solid medium fermentation conditions of the two lignin-degrading bacteria using a uniform experiment combined with the artificial neural network algorithm. Result The optimized solid inoculum medium matrix (mass ratio) of strain Q was with 30.000 g bran as the base, 3.000 g soybean meal powder and 0.188 g corn flour added, with extra nutrients (based on the mass ratio of the matrix) being MgSO₄ 1.434%, KH₂PO₄ 0.115%, FeSO₄·7H₂O 1.497% whereas the inoculation conditions being 6.000% of inoculation, with the ratio of material to water as 1.000∶0.992, and the protective agent as 1.000%. The optimized solid inoculum medium matrix (mass ratio) of strain A was with 30.000 g bran as the base, 1.500 g soybean meal powder and 1.500 g sodium lignosulfonate were added, with extra nutrients (based on the mass ratio of the matrix) being MgSO₄ 0.123%, KH₂PO₄ 0.213%, FeSO₄·7H₂O 1.280% whereas the inoculation conditions being 21.000% inoculation amount with the ratio of material to water as 1∶1 and the protective agent as 19.000%. Strain Q and strain A were fermented on the optimized medium for 7−9 days to get the largest fermentation biomass with the D(260) value of strain Q being 0.596 and the D(260) value of strain A being 0.478. Conclusion The solid inoculum prepared by two lignin-degrading bacteria under optimized fermentation conditions were featured with high biomass and certain potential for degrading the lignin of landscaping wastes. [Ch, 6 fig. 5 tab. 22 ref.]
- lignin-degrading bacteria,
- optimization,
- solid inoculum,
- fermentation

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园林绿化废弃物资源化利用^[1-2]已成为研究热点，其中堆肥化是一种比较理想的处理方式。由于园林绿化废弃物木质素含量较高、起始微生物数量较少等原因，堆肥效率较低，因此如何提高堆肥过程中的微生物数量成为推进园林绿化废弃物堆肥的关键^[3-4]。添加微生物菌剂是提高堆体微生物数量最直接的方式之一。目前，针对木质素降解的菌剂较少，且多集中于液体菌剂。然而液体菌剂对无菌条件要求较高，运输及产品储存有诸多不便^[5]。固体菌剂在生产和储存方面能弥补液体菌剂的不足，同时，固体菌剂生产成本更低、生产工艺也相对简单，对促进园林绿化废弃物堆肥化过程的优势更明显^[6]。生产固体菌剂，除了设计固体发酵的培养基，还要优化其发酵条件，主要流程为试验设计、数学建模和优化设计3个部分^[7]。合理的试验设计能用较少的试验数据进行建模，从而获取各因素范围内的最优解。已有研究对于固态发酵的优化多是使用响应面法^[8-9]。但是有研究发现^[10]：人工神经网络算法优化培养基比响应面法优化培养基验证结果更准确，误差更小。本研究拟采用单因素试验和正交试验确定作为固态发酵培养基碳源、氮源的较优种类和水平，然后根据碳氮源优化结果，通过单因素试验确定外加营养组分种类，最后采用均匀实验结合人工神经网络建模与优化，寻找2株木质素降解菌的外加营养组分接种量和最佳固体培养基发酵条件，以期得到最大发酵生物量，制作高效固体菌剂用于园林绿化废弃物堆肥。

3. 结论

本研究结果表明：人工神经网络算法优化后菌株Q的预测值为0.6020，实测值为0.5960，误差为1.000%；菌株A的预测值为0.485，实测值为0.478，误差为1.500%。基于人工神经网络构建的模型拟合度较好。

根据单因素试验和人工神经网络算法结果，确定了2株木质素降解菌的最优固体发酵条件。菌株Q：固体菌剂培养基基质为麸皮30.000 g作为基底，添加豆饼粉10.000%和玉米粉0.625%，外加营养组分为MgSO₄ 1.434%、KH₂PO₄ 0.115%和FeSO_4·7H₂O 1.497%；接种条件为接菌量6.000%、料水比1.000∶0.992、保护剂1.000%。菌株A：固体菌剂培养基基质为麸皮30.000g作为基底，添加豆饼粉5.000%和木质素磺酸钠为5.000%，外加营养组分为MgSO₄ 0.123 %、KH₂PO₄ 0.213 %、FeSO₄·7H₂O 1.280%；接种条件为接菌量21.000%、料水比1∶1、保护剂19.000%。

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处理	豆饼粉/%	木质素磺酸钠/%	D(260)
T₁	1.250	2.500	0.228±0.009
T₂	1.250	5.000	0.241±0.001
T₃	1.250	10.000	0.207±0.018
T₄	2.500	2.500	0.216±0.007
T₅	2.500	5.000	0.213±0.008
T₆	2.500	10.000	0.245±0.010
T₇	5.000	2.500	0.237±0.010
T₈	5.000	5.000	0.249±0.003
T₉	5.000	10.000	0.241±0.007

处理	豆饼粉/%	玉米粉/%	D(260)
T₁	1.250	0.625	0.101±0.003
T₂	1.250	2.500	0.224±0.006
T₃	1.250	5.000	0.214±0.005
T₄	5.000	0.625	0.101±0.003
T₅	5.000	2.500	0.162±0.008
T₆	5.000	5.000	0.232±0.020
T₇	10.000	0.625	0.261±0.003
T₈	10.000	2.500	0.191±0.002
T₉	10.000	5.000	0.102±0.003

试验号	因素水平(实际用量/%)						D(260)
试验号	MgSO₄	KH₂PO₄	FeSO₄·7H₂O	接菌量	料水比	海藻糖	D(260)
实测值1	1(0.600)	2(0.800)	3(1.000)	5(25.000)	7(1.00∶0.50)	10(16.000)	0.4110
仿真值1	1(0.600)	2(0.800)	3(1.000)	5(25.000)	7(1.00∶0.50)	10(16.000)	0.4109
实测值2	2(0.800)	4(1.200)	6(0.600)	10(25.000)	3(1.00∶0.65)	9(12.000)	0.4500
仿真值2	2(0.800)	4(1.200)	6(0.600)	10(25.000)	3(1.00∶0.65)	9(12.000)	0.4499
实测值3	3(1.000)	6(0.600)	9(1.200)	4(20.000)	10(1.00∶0.95)	8(8.000)	0.4800
仿真值3	3(1.000)	6(0.600)	9(1.200)	4(20.000)	10(1.00∶0.95)	8(8.000)	0.4801
实测值4	4(1.200)	8(1.000)	1(0.600)	9(20.000)	6(1.00∶0.30)	7(4.000)	0.4430
仿真值4	4(1.200)	8(1.000)	1(0.600)	9(20.000)	6(1.00∶0.30)	7(4.000)	0.4431
实测值5	5(1.400)	10(1.400)	4(1.200)	3(15.000)	2(1.00∶0.50)	6(0.000)	0.3860
仿真值5	5(1.400)	10(1.400)	4(1.200)	3(15.000)	2(1.00∶0.50)	6(0.000)	0.3859
实测值6	6(0.600)	1(0.600)	7(0.800)	8(15.000)	9(1.00∶0.80)	5(16.000)	0.4620
仿真值6	6(0.600)	1(0.600)	7(0.800)	8(15.000)	9(1.00∶0.80)	5(16.000)	0.4619
实测值7	7(0.800)	3(1.000)	10(1.400)	2(10.000)	5(1.00∶0.95)	4(12.000)	0.4630
仿真值7	7(0.800)	3(1.000)	10(1.400)	2(10.000)	5(1.00∶0.95)	4(12.000)	0.4635
实测值8	8(1.000)	5(1.400)	2(0.800)	7(10.000)	1(1.00∶0.30)	3(8.000)	0.2930
仿真值8	8(1.000)	5(1.400)	2(0.800)	7(10.000)	1(1.00∶0.30)	3(8.000)	0.2929
实测值9	9(1.200)	7(0.800)	5(1.400)	1(5.000)	8(1.00∶0.65)	2(4.000)	0.4450
仿真值9	9(1.200)	7(0.800)	5(1.400)	1(5.000)	8(1.00∶0.65)	2(4.000)	0.4453
实测值10	10(1.400)	9(1.200)	8(1.000)	6(5.000)	4(1.00∶0.80)	1(0.000)	0.4230
仿真值10	10(1.400)	9(1.200)	8(1.000)	6(5.000)	4(1.00∶0.80)	1(0.000)	0.4231

试验号	因素水平(实际用量/%)						D(260)
试验号	CaSO₄	MgSO₄	KH₂PO₄	接菌	料水比	海藻糖	D(260)
实测值1	1(0.600)	2(0.800)	3(1.000)	5(25.000)	7(1.00∶0.50)	10(16.000)	0.3930
仿真值1	1(0.600)	2(0.800)	3(1.000)	5(25.000)	7(1.00∶0.50)	10(16.000)	0.3930
实测值2	2(0.800)	4(1.200)	6(0.600)	10(25.000)	3(1.00∶0.65)	9(12.000)	0.4020
仿真值2	2(0.800)	4(1.200)	6(0.600)	10(25.000)	3(1.00∶0.65)	9(12.000)	0.4020
实测值3	3(1.000)	6(0.600)	9(1.200)	4(20.000)	10(1.00∶0.95)	8(8.000)	0.4260
仿真值3	3(1.000)	6(0.600)	9(1.200)	4(20.000)	10(1.00∶0.95)	8(8.000)	0.4260
实测值4	4(1.200)	8(1.000)	1(0.600)	9(20.000)	6(1.00∶0.30)	7(4.000)	0.3930
仿真值4	4(1.200)	8(1.000)	1(0.600)	9(20.000)	6(1.00∶0.30)	7(4.000)	0.3930
实测值5	5(1.400)	10(1.400)	4(1.200)	3(15.000)	2(1.00∶0.50)	6(0.000)	0.3900
仿真值5	5(1.400)	10(1.400)	4(1.200)	3(15.000)	2(1.00∶0.50)	6(0.000)	0.3900
实测值6	6(0.600)	1(0.600)	7(0.800)	8(15.000)	9(1.00∶0.80)	5(16.000)	0.4320
仿真值6	6(0.600)	1(0.600)	7(0.800)	8(15.000)	9(1.00∶0.80)	5(16.000)	0.4320
实测值7	7(0.800)	3(1.000)	10(1.400)	2(10.000)	5(1.00∶0.95)	4(12.000)	0.4110
仿真值7	7(0.800)	3(1.000)	10(1.400)	2(10.000)	5(1.00∶0.95)	4(12.000)	0.4110
实测值8	8(1.000)	5(1.400)	2(0.800)	7(10.000)	1(1.00∶0.30)	3(8.000)	0.3650
仿真值8	8(1.000)	5(1.400)	2(0.800)	7(10.000)	1(1.00∶0.30)	3(8.000)	0.3650
实测值9	9(1.200)	7(0.800)	5(1.400)	1(5.000)	8(1.00∶0.65)	2(4.000)	0.3770
仿真值9	9(1.200)	7(0.800)	5(1.400)	1(5.000)	8(1.00∶0.65)	2(4.000)	0.3770
实测值10	10(1.400)	9(1.200)	8(1.000)	6(5.000)	4(1.00∶0.80)	1(0.000)	0.4210
仿真值10	10(1.400)	9(1.200)	8(1.000)	6(5.000)	4(1.00∶0.80)	1(0.000)	0.4210

Preparation of two strains of lignin-degrading bacteria solid inoculum

doi: 10.11833/j.issn.2095-0756.20210311

Abstract

References

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通讯作者: 陈斌, bchen63@163.com

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