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(Referência obtida automaticamente do SciELO, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Yeast fermentation of sugarcane for ethanol production: Can it be monitored by using in situ microscopy?

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Autor(es):
V. L. Belini [1] ; G. A. P. Caurin [2] ; P. Wiedemann [3] ; H. Suhr [4]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] Federal University of São Carlos. Department of Electrical Engineering - Brasil
[2] University of São Paulo. Department of Mechanical Engineering - Brasil
[3] Hochschule Mannheim. Fakultät für Biotechnologie - Alemanha
[4] Hochschule Mannheim. Fakultät für Informationstechnik - Alemanha
Número total de Afiliações: 4
Tipo de documento: Artigo Científico
Fonte: Brazilian Journal of Chemical Engineering; v. 34, n. 4, p. 949-959, 2017-10-00.
Resumo

ABSTRACT This paper addresses some key issues related to the automation of fermentation process analysis in the context of industrial-scale ethanol production from sugarcane substrates. As the current methods for the determination of cell density and viability are time consuming and laborious, high resolution in situ microscopy (0.5µm) is proposed as a promising alternative. Laboratory-scale experiments presented here show that this imaging technique allows automatic, on-line, and real-time monitoring of yeast cells suspended in sugarcane molasses used in the ethanol industry. In particular, the feasibility of cell concentration measurements of Saccharomyces cerevisiae SA-1 in industrial sugarcane molasses is demonstrated. Automated concentration measurements exhibit a linear correlation with manual reference values using a Neubauer chamber from 3×106 cells/mL up to a saturation level at approximately 2×108 cells/mL. Furthermore, it was demonstrated that the microscopic resolution of this technique, combined with its large statistics, allows a morphological assessment of the size, shape and some internal structures of the yeast cells. On average, the accuracy of the algorithm´s yeast cells classification was 0.80. The results obtained suggest that the ISM is a suitable tool to perform in-line sugarcane fermentation monitoring. (AU)

Processo FAPESP: 12/01126-5 - Sonda in-situ para o monitoramento em tempo real da viabilidade da biomassa de leveduras durante a fermentação do etanol
Beneficiário:Valdinei Luís Belini
Modalidade de apoio: Bolsas no Exterior - Pesquisa