Article: FT-NIR spectroscopy analysis for monitoring the microbial production of 2-phenylethanol using crude glycerol as carbon source
Lebensmittel-Wissenschaft + [i.e. und] Technologie. 2022 Feb. 01, v. 155
2022
Abstract: The valorization of glycerol wastes through its conversion into high-added value products using biotechnological processes is very promising due to the high amount of glycerol generated from the bio-diesel industry. In this sense, it is important to ... ...
Abstract | The valorization of glycerol wastes through its conversion into high-added value products using biotechnological processes is very promising due to the high amount of glycerol generated from the bio-diesel industry. In this sense, it is important to develop rapid, reliable and, if possible, environmentally friendly analytical techniques for the monitoring of high-added value compounds. With this in mind, Fourier transform near infrared (FT-NIR) spectroscopy was explored for the assessment of biomass, glycerol, l-phenylalanine and 2-phenylethanol (2-PE) parameters during the biotechnological production of 2-PE. A total of 80 samples were collected and analyzed through FT-NIR spectroscopy. Partial least squares (PLS) regression method was selected for establishing quantification models. The obtained figures of merit, in terms of, coefficients of determination of prediction (R²P), range error-ratios (RER) and residual predictive deviation (RPD) yielded values higher than 0.85, 7.7 and 2.6, respectively, for all the parameters assessed. The obtained results reveal that all the developed PLS models can be considered as models with a good predictive accuracy and therefore attest the suitability of FT-NIR spectroscopy for the quantification of these parameters. Concluding, a new rapid, reliable, cost-effective, accurate, multi-parametric and environmentally friendly analytical technique exploring the potential of FT-NIR spectroscopy was successfully developed. |
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Keywords | biodiesel ; biomass ; carbon ; cost effectiveness ; glycerol ; industry ; phenylalanine ; phenylethyl alcohol ; prediction |
Language | English |
Dates of publication | 2022-0201 |
Publishing place | Elsevier Ltd |
Document type | Article |
ZDB-ID | 241369-3 |
ISSN | 0460-1173 ; 0023-6438 |
ISSN | 0460-1173 ; 0023-6438 |
DOI | 10.1016/j.lwt.2021.112951 |
Database | NAL-Catalogue (AGRICOLA) |
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