Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 476

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Fermentation of plant-based milk alternatives for improved flavour and nutritional value

Open access
Tangyu, Muzi, Muller, Jeroen, Bolten, Christoph J., Wittmann, Christoph·2019·Applied Microbiology and Biotechnology

Abstract

Non-dairy milk alternatives (or milk analogues) are water extracts of plants and have become increasingly popular for human nutrition. Over the years, the global market for these products has become a multi-billion dollar business and will reach a value of approximately 26 billion USD within the next 5 years. Moreover, many consumers demand plant-based milk alternatives for sustainability, health-related, lifestyle and dietary reasons, resulting in an abundance of products based on nuts, seeds or beans. Unfortunately, plant-based milk alternatives are often nutritionally unbalanced, and their flavour profiles limit their acceptance. With the goal of producing more valuable and tasty products, fermentation can help to the improve sensory profiles, nutritional properties, texture and microbial safety of plant-based milk alternatives so that the amendment with additional ingredients, often perceived as artificial, can be avoided. To date, plant-based milk fermentation mainly uses mono-cultures of microbes, such as lactic acid bacteria, bacilli and yeasts, for this purpose. More recently, new concepts have proposed mixed-culture fermentations with two or more microbial species. These approaches promise synergistic effects to enhance the fermentation process and improve the quality of the final products. Here, we review the plant-based milk market, including nutritional, sensory and manufacturing aspects. In addition, we provide an overview of the state-of-the-art fermentation of plant materials using mono- and mixed-cultures. Due to the rapid progress in this field, we can expect well-balanced and naturally fermented plant-based milk alternatives in the coming years.

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 · 10.1007/s00253-019-10175-9

Cites

6 of 6 references verified0 citation errors · 0 not checkable

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

Cites

Show all 6 references

Cited by

Metadata

Authors
Tangyu, M., Muller, J., Bolten, C. J., & Wittmann, C.
Venue
Applied Microbiology and Biotechnology
Published
2019-11-04
Volume
103
Issue
23-24
Pages
9263-9275
ISSN
  • 0175-7598 (ISSN-L)
  • 1432-0614
OpenAlex
W2987670143
Cited by
476
References
6
FWCI
29.04
Type
journal article
Language
en
Open access
hybrid

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

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.