Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 307

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Exploring consumers' attitude towards cultured meat in Italy

Mancini, Maria Cecilia, Antonioli, Federico·2019·Meat Science

Abstract

Cultured meat may be a novel food that would overcome the limits of conventional meat production. This paper assesses the willingness to try, buy and pay for cultured meat among a sample of Italian consumers, unveiling the attitudes towards an engineered food on the part of a consumer oriented in favour of the Mediterranean diet. A survey was conducted by submitting a questionnaire to 525 Italian consumers. Consumers showed higher agreement with the statements concerning positive externalities than the intrinsic characteristics of cultured meat, and more than half of the respondents (54%) stated that they would be willing to try cultured meat. The profile for a potential consumer of cultured meat was young, highly educated, somewhat familiar with cultured meat, a meat consumer and willing to reduce meat consumption. However, the survey findings may be biased by the unavailability of the product on the market and the information provided to the respondents focused on the potential benefits of cultured meat.

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/j.meatsci.2018.12.014

Cites

2 of 2 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 2 references

Cited by

See all 307

Metadata

Authors
Mancini, M. C., & Antonioli, F.
Venue
Meat Science
Publisher
Elsevier BV
Published
2019-04
Volume
150
Pages
101-110
ISSN
0309-1740 (ISSN-L)
OpenAlex
W2907167757
Cited by
307
References
2
FWCI
12.99
Type
journal article
Language
en
Open access
closed

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: Exploring consumers' attitude towards cultured meat in Italy. https://app.cochat.ai/papers/10.1016/j.meatsci.2018.12.014
The paper
Mancini, M. C., & Antonioli, F. (2019). Exploring consumers' attitude towards cultured meat in Italy. Meat Science. https://doi.org/10.1016/j.meatsci.2018.12.014

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.