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Journal of Food Composition and Analysis
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Carbohydrate fraction characterisation of functional yogurts containing pectin and pectic oligosaccharides through convolutional networks

Authors: Sabater, Carlos; Abad García, Celia; Delgado, Paloma; Corzo, Nieves; Montilla, Antonia;

Carbohydrate fraction characterisation of functional yogurts containing pectin and pectic oligosaccharides through convolutional networks

Abstract

The carbohydrate fraction of functional yogurts supplemented with citrus and artichoke pectin and their pectic oligosaccharides (POS) has been characterised, including carbohydrates from raw material (milk, pectin and POS) and formed during yogurt manufacture (POS and galactooligosaccharides GOS). Viable cell count and pH values accomplished the quality standards required for yogurts. The content of lactose and lactic and acetic acids was in the range 3.5–4.0; 0.85–1.16 and 0.04−0.07 g 100 g−1, respectively. Other sugars from pectin (arabinose, galacturonic acid, POS), milk (glucose, galactose, myo-inositol and GOS, GOS) were also quantified. GC-EI-MS spectra of yogurt carbohydrates were classified using machine learning, and structure-relative retention time relationships were calculated determining the abundance of specific fragments on larger oligosaccharide structures. All information generated was correlated using a convolutional network that established characteristic patterns in the complete carbohydrate fraction of each yogurt, as well as changes during fermentation in the carbohydrate profile. It was found that di-, tri- and tetra-POS formed by rhamnose and xylose attached to acetylated-galacturonic acid were released during fermentation in yogurts with artichoke POS. Structures elucidated by these algorithms were confirmed by MALDI-TOF-MS. These models may allow structural differences to be determined among novel oligosaccharides present in food matrices.

This work has been funded by MICINN: Ministry of Science and Innovation of Spain, Projects AGL2014-53445-R and AGL2017-84614-C2-1-R. Carlos Sabater thanks his FPU Predoc contract from Spanish MECD (FPU14/03619).

Peer reviewed

Keywords

Functional yogurt, Pectic oligosaccharides, Artichoke and citrus pectins, Convolutional neural networks, In silico fragmentation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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