Title | Simultaneous Detection and Quantification of Organic Acids and Furans in Lignocellulosic Biomass Hydrolysate Through High-Performance Liquid Chromatography With Diode Array Detector |
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Publication Type | Articolo su Rivista peer-reviewed |
Year of Publication | 2025 |
Authors | Casella, Patrizia, Loffredo Raffaele, Rao Maria Antonietta, Liuzzi Federico, De Bari Isabella, and Molino Antonio |
Journal | Journal of Separation Science |
Volume | 48 |
Type of Article | Article |
ISSN | 16159306 |
Abstract | Lignocellulosic biomass is gaining attention as low-cost renewable resources for sugars for fermentation and as a source of energy. Pretreatments and fermentation of these biomasses can generate organic acids and furans. Many liquid chromatography protocols have been developed for the analysis of these compounds. Organic acids are typically detected and quantified using diode array detector, while furans can be analyzed by using refractive index or ultraviolet detectors. In this work, the identification of succinic, lactic, formic, and acetic acids and two furans (5-hydroxymethylfurfural and furfural) was performed by ultra-high-performance liquid chromatography coupled with diode array detector and ion chromatography columns. Different chromatographic conditions were tested by varying the column temperature and the flow rate of sulfuric acid 5 mM. Calibration curves, peak resolution, limit of detection, and limit of quantification were calculated using analytical standards at known concentrations for each compound. The accuracy was evaluated by the recovery of the compounds in wheat straw hydrolysate. For succinic acid, the best condition was at a flow rate of 0.6 mL/min and a column temperature of 60°C while formic and lactic acids and furans were better recovered at 1.0 mL/min and 60°C. © 2025 The Author(s). Journal of Separation Science published by Wiley-VCH GmbH. |
Notes | Cited by: 0 |
URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-105010844074&doi=10.1002%2fjssc.70216&partnerID=40&md5=0c14d546a62a0e1365e3d1ad6609e670 |
DOI | 10.1002/jssc.70216 |
Citation Key | Casella2025 |