Optimization of bioethanol production from cheese whey using Kluyveromyces marxianus URM 7404
The objective of this study was to optimize the ethanol production from cheese whey, using the yeast Kluyveromyces marxianus URM 7404. The response surface methodology (RSM) with a central composite rotational design (CCRD) was used to evaluate the effects of pH (4–6), temperature (30–36 °C), and la...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Recursos: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unesp.br:11449/189175 |
| Acesso em linha: | http://dx.doi.org/10.1016/j.bcab.2019.101182 http://hdl.handle.net/11449/189175 |
| Access Level: | acceso abierto |
| Palavra-chave: | Biofuel Cheese whey Kluyveromyces Optimization Scale–up Yeasts |
| Resumo: | The objective of this study was to optimize the ethanol production from cheese whey, using the yeast Kluyveromyces marxianus URM 7404. The response surface methodology (RSM) with a central composite rotational design (CCRD) was used to evaluate the effects of pH (4–6), temperature (30–36 °C), and lactose concentration (50–70 g.L−1). Cheese whey underwent 17 fermentations and further three fermentations were conducted for the validation of the equation obtained by RSM. After the validation of the optimization, the fermentation process was scaled-up to the volumes of 1 L, 6 L, 21 L, and 36 L, and ethanol production (g.L−1), productivity (QP g.L−1. h−1), conversion (YP/S g.g−1), yield (η %), and chemical oxygen demand (mg COD. L−1) were evaluated. Temperature was the most significant factor used for the optimization of the ethanol production, followed by pH and lactose concentration. The conditions for the ethanol production of higher than 90% were as follows: temperature range from 32.5 to 35.0 °C, pH from 4.8 to 5.3, and lactose concentration from 61.0 to 65.0 g.L−1. The equation generated from the optimization process was validated and presented excellent values and precision for the use of this model in scale-up process, obtaining volume of 36 L, η 95.80%, QP 2.57 g.L−1. h−1, and YP/S 0.50 g.g−1. The COD of the cheese whey was reduced by 78.94%, proving it to be an effective process to reduce the environmental damages caused by this effluent. |
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