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Background: Interviews are a common practice for gathering information in scientific studies. Although there is an extensive work about how to conduct and analyze an interview, transcription has usually remained a minor issue. Transcribing is the transformation of oral speech into a written and meaningful text that includes relevant information from the interview and that can be analyzed. Objectives: This article addresses and discusses the main conceptual and practical issues, as well as the main challenges involved in interview transcription, using an integrative approach. Main topics under analysis:What is the definition of transcription? Which types of transcripts exist? What content must be transcribed? How should an interview be transcribed? What special measures should be taken during a transcription? What are the main difficulties? Conclusion: Given the lack of universal protocols or rules for transcription, researchers should state their practices and decisions, which may influence data analysis.

The mixture of Eucalyptus globulus wood (EGW) and cheese whey powder (CWP) was proposed for intensification of simultaneous saccharification and fermentation (SSF) at high temperature and solid loadings using the industrial Saccharomyces cerevisiae Ethanol Red® strain. High ethanol concentration (93 g/L), corresponding to 94% ethanol yield, was obtained at 35 °C from 37% of solid mixture using cellulase and β-galactosidase enzymes (24.2 FPU/g and 20.0 U/g, respectively). The use of CWP mixed with pretreated EGW increased the ethanol concentration in 1.5-fold, in comparison with SSF experiments without CWP for both Ethanol Red® and CEN.PK113-7D strains. Moreover, 1.4-fold higher ethanol concentration was obtained with Ethanol Red®, in comparison with CEN.PK113-7D strain. Ethanol Red® strain was genetically engineered for β-galactosidase production in order to advance towards a fully integrated process. This work shows the feasibility of attaining high ethanol concentrations in second generation bioprocesses by a multi-waste valorization approach.

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