Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 461

The DOI matches its Crossref record.

Sustainable Protein Sources

Open access
·2017·Elsevier eBooks

Abstract

The Special Issue Reprint provides a collection of recent developments in sustainable protein source technologies that scientists have developed to meet the rising global demand for nutritious yet environmentally friendly food systems. The research work investigates protein sources, which include plant materials, microalgae, fungi, and microbial biomass, through their extraction methods, and their structural characteristics, and their food application functions.The Reprint demonstrates how different processing technologies, including enzymatic treatment, extrusion, germination, molecular fractionation, conjugation, and mechanical disruption, change protein structure, protein digestibility, protein bioavailability, and protein techno-functional properties. The research reveals structurefunction relationships and shows how specific processing methods can improve emulsifying, foaming, and nutritional characteristics while reducing allergenic and safety risks. The research investigates how sustainable proteins function in food formulation together with hybrid protein systems, and the creation of new food products that include meat analogs and functional items.The Reprint presents the current research results that connect basic protein research with practical food development. The document provides essential information that researchers and industry experts need to develop and use sustainable protein ingredients in contemporary food production methods.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/c2014-0-03542-3

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 461

Metadata

Venue
Elsevier eBooks
Publisher
Elsevier
Published
2017
OpenAlex
W4237783701
Cited by
461
References
0
FWCI
28.73
Type
book
Language
en
Open access
diamond

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Sustainable Protein Sources. https://app.cochat.ai/papers/10.1016/c2014-0-03542-3
The paper
Sustainable Protein Sources. (2017). Elsevier eBooks. https://doi.org/10.1016/c2014-0-03542-3

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.