Norhan Elerakey, Abdel-Hamied M. Rasmey, Youseef M. Mohammed, Akram A. Aboseidah, Heba Hawary
{"title":"利用丁酸梭菌NE133最大限度地利用西瓜皮生产生物氢：采用Plackett-Burman和Box-Behnken设计的统计优化方法","authors":"Norhan Elerakey, Abdel-Hamied M. Rasmey, Youseef M. Mohammed, Akram A. Aboseidah, Heba Hawary","doi":"10.1186/s13068-025-02652-3","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Biohydrogen production from agricultural waste is a promising strategy to address climate change and energy challenges. This study aimed to optimize the process parameters for biohydrogen production from watermelon peels (WMP) by <i>Clostridium butyricum</i> NE133 using statistical optimization techniques. Initial screening of eight significant variables influencing hydrogen production including, initial pH, incubation temperature, WMP concentration, inoculum volume, yeast extract, tryptone, sodium acetate, and ammonium acetate concentration was conducted by a Plackett–Burman (PB) design.</p><h3>Results</h3><p>The results showed that four variables including, initial pH (<i>P</i> < 0.001), WMP concentration (<i>P</i> < 0.001), sodium acetate (<i>P</i> = 0.023), and ammonium acetate (<i>P</i> = 0.048) had statistically significant effects on hydrogen production. The model curvature (<i>P</i> = 0.040) indicated that it was significant. Box–Behnken (BB) design under response surface methodology (RSM) was employed to optimize the four selected variables to maximize hydrogen production. The optimal conditions for maximizing hydrogen production from WMP by <i>C. butyricum</i> were: initial pH of 8.98, WMP concentration of 44.75%, sodium acetate 4.49 gL<sup>−1</sup>, and ammonium acetate 1.15 gL<sup>−1</sup> at with predicted H<sub>max</sub> of 4703.23 mLL<sup>−1</sup>. The determination coefficient R<sup>2</sup> of the model was 0.9902 with the lack of fit F-value was 1.86.</p><h3>Conclusions</h3><p>The confirmation experiment revealed only a 0.59% difference between the predicted and experimental hydrogen production, indicating that the optimum conditions were actual with the least error. Improvement of about 103.25% in hydrogen production from WMP by <i>C. butyricum</i> NE133 was achieved after the optimization process.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":494,"journal":{"name":"Biotechnology for Biofuels","volume":"18 1","pages":""},"PeriodicalIF":6.1000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://biotechnologyforbiofuels.biomedcentral.com/counter/pdf/10.1186/s13068-025-02652-3","citationCount":"0","resultStr":"{\"title\":\"Maximizing biohydrogen production from watermelon peels using Clostridium butyricum NE133: a statistical optimization approach with Plackett–Burman and Box–Behnken designs\",\"authors\":\"Norhan Elerakey, Abdel-Hamied M. Rasmey, Youseef M. Mohammed, Akram A. Aboseidah, Heba Hawary\",\"doi\":\"10.1186/s13068-025-02652-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Biohydrogen production from agricultural waste is a promising strategy to address climate change and energy challenges. This study aimed to optimize the process parameters for biohydrogen production from watermelon peels (WMP) by <i>Clostridium butyricum</i> NE133 using statistical optimization techniques. Initial screening of eight significant variables influencing hydrogen production including, initial pH, incubation temperature, WMP concentration, inoculum volume, yeast extract, tryptone, sodium acetate, and ammonium acetate concentration was conducted by a Plackett–Burman (PB) design.</p><h3>Results</h3><p>The results showed that four variables including, initial pH (<i>P</i> < 0.001), WMP concentration (<i>P</i> < 0.001), sodium acetate (<i>P</i> = 0.023), and ammonium acetate (<i>P</i> = 0.048) had statistically significant effects on hydrogen production. The model curvature (<i>P</i> = 0.040) indicated that it was significant. Box–Behnken (BB) design under response surface methodology (RSM) was employed to optimize the four selected variables to maximize hydrogen production. The optimal conditions for maximizing hydrogen production from WMP by <i>C. butyricum</i> were: initial pH of 8.98, WMP concentration of 44.75%, sodium acetate 4.49 gL<sup>−1</sup>, and ammonium acetate 1.15 gL<sup>−1</sup> at with predicted H<sub>max</sub> of 4703.23 mLL<sup>−1</sup>. The determination coefficient R<sup>2</sup> of the model was 0.9902 with the lack of fit F-value was 1.86.</p><h3>Conclusions</h3><p>The confirmation experiment revealed only a 0.59% difference between the predicted and experimental hydrogen production, indicating that the optimum conditions were actual with the least error. 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Maximizing biohydrogen production from watermelon peels using Clostridium butyricum NE133: a statistical optimization approach with Plackett–Burman and Box–Behnken designs
Background
Biohydrogen production from agricultural waste is a promising strategy to address climate change and energy challenges. This study aimed to optimize the process parameters for biohydrogen production from watermelon peels (WMP) by Clostridium butyricum NE133 using statistical optimization techniques. Initial screening of eight significant variables influencing hydrogen production including, initial pH, incubation temperature, WMP concentration, inoculum volume, yeast extract, tryptone, sodium acetate, and ammonium acetate concentration was conducted by a Plackett–Burman (PB) design.
Results
The results showed that four variables including, initial pH (P < 0.001), WMP concentration (P < 0.001), sodium acetate (P = 0.023), and ammonium acetate (P = 0.048) had statistically significant effects on hydrogen production. The model curvature (P = 0.040) indicated that it was significant. Box–Behnken (BB) design under response surface methodology (RSM) was employed to optimize the four selected variables to maximize hydrogen production. The optimal conditions for maximizing hydrogen production from WMP by C. butyricum were: initial pH of 8.98, WMP concentration of 44.75%, sodium acetate 4.49 gL−1, and ammonium acetate 1.15 gL−1 at with predicted Hmax of 4703.23 mLL−1. The determination coefficient R2 of the model was 0.9902 with the lack of fit F-value was 1.86.
Conclusions
The confirmation experiment revealed only a 0.59% difference between the predicted and experimental hydrogen production, indicating that the optimum conditions were actual with the least error. Improvement of about 103.25% in hydrogen production from WMP by C. butyricum NE133 was achieved after the optimization process.
期刊介绍：
Biotechnology for Biofuels is an open access peer-reviewed journal featuring high-quality studies describing technological and operational advances in the production of biofuels, chemicals and other bioproducts. The journal emphasizes understanding and advancing the application of biotechnology and synergistic operations to improve plants and biological conversion systems for the biological production of these products from biomass, intermediates derived from biomass, or CO2, as well as upstream or downstream operations that are integral to biological conversion of biomass.
Biotechnology for Biofuels focuses on the following areas:
• Development of terrestrial plant feedstocks
• Development of algal feedstocks
• Biomass pretreatment, fractionation and extraction for biological conversion
• Enzyme engineering, production and analysis
• Bacterial genetics, physiology and metabolic engineering
• Fungal/yeast genetics, physiology and metabolic engineering
• Fermentation, biocatalytic conversion and reaction dynamics
• Biological production of chemicals and bioproducts from biomass
• Anaerobic digestion, biohydrogen and bioelectricity
• Bioprocess integration, techno-economic analysis, modelling and policy
• Life cycle assessment and environmental impact analysis
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