Evidence map›Paper›PMID 41876921›Full record

ArticleWorld journal of microbiology & biotechnology2026

Optimization of fermentation conditions and enzymatic properties of extracellular lipase produced by Serratia marcescens derived from food waste.

Xiaodong Tian, Chuyun Huang, Shen Wang, Qihui Meng, Yuxin Chang, Zheng Zhang, Mingguo Jiang

Abstract read
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In one paragraph

Article in World journal of microbiology & biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Xiaodong TianGuangxi Key Laboratory of Polysaccharide Materials and Modification, Guangxi Minzu University, Nanning, China.
Chuyun HuangGuangxi Key Laboratory of Polysaccharide Materials and Modification, Guangxi Minzu University, Nanning, China.
Shen WangGuangxi Key Laboratory of Polysaccharide Materials and Modification, Guangxi Minzu University, Nanning, China.
Qihui MengGuangxi Key Laboratory of Polysaccharide Materials and Modification, Guangxi Minzu University, Nanning, China.
Yuxin ChangGuangxi Key Laboratory of Polysaccharide Materials and Modification, Guangxi Minzu University, Nanning, China.
Zheng ZhangGuangxi Key Laboratory of Polysaccharide Materials and Modification, Guangxi Minzu University, Nanning, China. 1070595374@qq.com.
Mingguo JiangGuangxi Key Laboratory of Polysaccharide Materials and Modification, Guangxi Minzu University, Nanning, China. mzxyjiang@163.com.

Funding

2024 Guangxi University for Nationalities Postgraduate Education Innovation Program Project (gxmzu-chxs2024240National Natural Science Foundation of China 32460009the 2024 Guangxi Science Popularization and Rural Revitalization Program-Papaya Science and Technology Backyard in Liangqing HT-00001499-004
6 · The paper itself

Abstract

A high lipase-producing strain, C41802, was isolated from a food-waste environment and identified as Serratia marcescens based on morphological traits, physiological and biochemical assays, and phylogenetic analysis. To enhance lipase production, fermentation conditions were optimized using a genetic algorithm–artificial neural network (GA–ANN) model. Under the optimized conditions, the enzymatic properties of the crude extracellular lipase were characterized. The GA–ANN model outperformed response surface methodology (RSM–CCD) in predicting optimal fermentation parameters and maximum enzyme yield, achieving a relative error of 0.67% compared with 2.54% for RSM–CCD. Optimization yielded the following conditions: olive oil 10 g/L, glucose 8 g/L, beef extract 3.1 g/L, K₂HPO₄ 2 g/L, inoculum size 3.5%, cultivation time 26.2 h, temperature 30 °C, and initial pH 5. Under these conditions, lipase production reached 613.39 U/mL, representing a 6.45-fold increase over the unoptimized baseline. The crude extracellular lipase exhibited an optimal temperature of 70 °C and an optimal pH of 7, retaining 52.56% of its activity after 12 h of incubation at 50 °C. These properties underscore the industrial potential of the lipase produced by S. marcescens C41802.

Indexed as

FermentationLipaseSerratia marcescensCulture MediaFood Loss and WasteGenetic AlgorithmsGlucoseHydrogen-Ion ConcentrationNeural Networks, ComputerPhylogenyTemperatureCulture MediaFood Loss and WasteGlucoseLipaseArtificial neural networkEnzymatic propertiesFermentation optimizationGenetic algorithmLipase

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.