Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning
Pectic oligosaccharides (POS) from citrus and apple pectin hydrolysis using ViscozymeL and Glucanex200G have been obtained. According to the results, maximum POS formation was achieved from citrus pectin after 30 min of hydrolysis with ViscozymeL, with a yield of 652 mg g–1 and average molecular mas...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/193555 |
| Acceso en línea: | http://hdl.handle.net/10261/193555 |
| Access Level: | acceso abierto |
| Palabra clave: | Pectic oligosaccharides ViscozymeL Glucanex200G Machine learning |
| Sumario: | Pectic oligosaccharides (POS) from citrus and apple pectin hydrolysis using ViscozymeL and Glucanex200G have been obtained. According to the results, maximum POS formation was achieved from citrus pectin after 30 min of hydrolysis with ViscozymeL, with a yield of 652 mg g–1 and average molecular mass (Mw) of 0.8–2.5 kDa, while with Glucanex200G, the yield was 518 mg g–1 and Mw was 0.8–7.1 kDa. Digalacturonic and trigalacturonic acids were identified among other low Mw compounds as di- and tri-POS. In addition, differences in GC-MS spectra of all oligosaccharides found in the hydrolysates were studied by employing random forests and other algorithms to identify structural differences between the obtained POS, and high prediction rates were shown for new samples. Chemical structures were proposed for some influential m/z ions, and 12 association rules that explain differences according to pectin and enzyme origin were built. This information could be used to establish structure–function relationships of POS. |
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