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 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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American Chemical Society
2019
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Subjects: | Pectic oligosaccharides, ViscozymeL, Glucanex200G, Machine learning, |
Online Access: | http://hdl.handle.net/10261/193555 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003176 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100011033 |
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dig-cial-es-10261-1935552021-03-03T04:28:16Z Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning Sabater, Carlos Ferreira-Lazarte, Alvaro Montilla, Antonia Corzo, Nieves Ministerio de Educación, Cultura y Deporte (España) Agencia Estatal de Investigación (España) Ministerio de Ciencia, Innovación y Universidades (España) Ministerio de Economía y Competitividad (España) Ministerio de Ciencia e Innovación (España) Montilla, Antonia [0000-0003-2117-6999] Corzo, Nieves [0000-0002-6420-2344] Pectic oligosaccharides ViscozymeL Glucanex200G Machine 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 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. This work has been funded by MICINN of Spain, Projects AGL2014-53445-R and AGL2017-84614-C2-1-R. C.S. is thankful for his FPU Predoc contract from Spanish MECD (FPU14/03619). Peer reviewed 2019-10-28T10:05:27Z 2019-10-28T10:05:27Z 2019 artículo http://purl.org/coar/resource_type/c_6501 Journal of Agricultural and Food Chemistry 67(26): 7435-7447 (2019) 0021-8561 http://hdl.handle.net/10261/193555 10.1021/acs.jafc.9b00930 1520-5118 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003176 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100011033 en #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2014-53445-R AGL2017-84614-C2-1-R/AEI/10.13039/501100011033 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/AGL2017-84614-C2-1-R Postprint http://dx.doi.org/10.1021/acs.jafc.9b00930 Sí open American Chemical Society |
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Pectic oligosaccharides ViscozymeL Glucanex200G Machine learning Pectic oligosaccharides ViscozymeL Glucanex200G Machine learning |
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Pectic oligosaccharides ViscozymeL Glucanex200G Machine learning Pectic oligosaccharides ViscozymeL Glucanex200G Machine learning Sabater, Carlos Ferreira-Lazarte, Alvaro Montilla, Antonia Corzo, Nieves Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning |
description |
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. |
author2 |
Ministerio de Educación, Cultura y Deporte (España) |
author_facet |
Ministerio de Educación, Cultura y Deporte (España) Sabater, Carlos Ferreira-Lazarte, Alvaro Montilla, Antonia Corzo, Nieves |
format |
artículo |
topic_facet |
Pectic oligosaccharides ViscozymeL Glucanex200G Machine learning |
author |
Sabater, Carlos Ferreira-Lazarte, Alvaro Montilla, Antonia Corzo, Nieves |
author_sort |
Sabater, Carlos |
title |
Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning |
title_short |
Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning |
title_full |
Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning |
title_fullStr |
Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning |
title_full_unstemmed |
Enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: A GC-MS study using random forests and association rule learning |
title_sort |
enzymatic production and characterization of pectic oligosaccharides derived from citrus and apple pectins: a gc-ms study using random forests and association rule learning |
publisher |
American Chemical Society |
publishDate |
2019 |
url |
http://hdl.handle.net/10261/193555 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003176 http://dx.doi.org/10.13039/501100003329 http://dx.doi.org/10.13039/501100011033 |
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