# Food of the future: Meat and dairy alternatives

**Edited by**

Antti Knaapila, Sghaier Chriki, Fang Fang, Jean-Francois Hocquette and Marie-Pierre Ellies-Oury

**Coordinated by**

James Ledo

**Published in**

Frontiers in Nutrition

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ISSN 1664-8714
ISBN 978-2-8325-4563-8
DOI 10.3389/978-2-8325-4563-8

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# Food of the future: Meat and dairy alternatives

**Topic editors**

Antti Knaapila — University of Helsinki, Finland

Sghaier Chriki — INRA UMR1213 Unité Mixte de Recherche sur les Herbivores (UMRH), France

Fang Fang — IEH Laboratories and Consulting Group, United States

Jean-Francois Hocquette — INRA UMR1213 Unité Mixte de Recherche sur les Herbivores (UMRH), France

Marie-Pierre Ellies-Oury — Professor - Bordeaux Sciences Agro, France

**Topic coordinator**

James Ledo — Cardiff Metropolitan University, United Kingdom

**Citation**

Knaapila, A., Chriki, S., Fang, F., Hocquette, J.-F., Ellies-Oury, M.-P., Ledo, J., eds. (2024). *Food of the future: Meat and dairy alternatives*. Lausanne: Frontiers Media SA. doi: 10.3389/978-2-8325-4563-8
Table of
contents

04 **Editorial: Food of the future: meat and dairy alternatives**
Jean-François Hocquette, Sghaier Chriki, Marie-Pierre Ellies-Oury, Fang Fang and Antti Knaapila

07 **Gene-Edited Meat: Disentangling Consumers' Attitudes and Potential Purchase Behavior**
Daniel Martin-Collado, Tim J. Byrne, Jonh J. Crowley, Tom Kirk, Guillermo Ripoll and C. B. A. Whitelaw

19 **Hybrid meat products and co-creation: What do consumers say, feel and think?**
Chris Ryder, Sylvia Jaworska and Simona Grasso

29 **Consumer perception of "artificial meat" in the educated young and urban population of Africa**
Moïse Kombolo Ngah, Sghaier Chriki, Marie-Pierre Ellies-Oury, Jingjing Liu and Jean-François Hocquette

46 **A comparison of the nutritional profile and nutrient density of commercially available plant-based and dairy yogurts in the United States**
Astrid E. D'Andrea, Amanda J. Kinchla and Alissa A. Nolden

59 **Perception of cultured "meat" by Italian, Portuguese and Spanish consumers**
Jingjing Liu, João M. Almeida, Nicola Rampado, Begoña Panea, Élise Hocquette, Sghaier Chriki, Marie-Pierre Ellies-Oury and Jean-François Hocquette

77 **Non-animal-based options for animal-based foods- towards a systematic terminology**
Nazanin Abbaspour, Ruben Sanchez-Sabate and Joan Sabaté

84 **Halal cultivated meat: an untapped opportunity**
Sophie Attwood, Shahid Jameel, Awal Fuseini, Eman AlKhalawi and Cother Hajat

90 **Barriers associated with pulse and plant-based meat alternative consumption across sociodemographic groups: a Capability, Opportunity, Motivation, Behaviour model approach**
Sini Kuosmanen, Mari Niva, Anne-Maria Pajari, Kirsi Korhonen, Toivo Muilu and Hanna Konttinen

103 **Evaluation of public submissions to the USDA for labeling of cell-cultured meat in the United States**
Morgan Failla, Helene Hopfer and Josephine Wee

114 **A taste of cell-cultured meat: a scoping review**
K. V. To, C. C. Comer, S. F. O'Keefe and J. Lahne

129 **Oat-based milk alternatives: the influence of physical and chemical properties on the sensory profile**
Roisin McCarron, Lisa Methven, Stephanie Grahl, Ruan Elliott and Stella Lignou
<figure><img src="image_2.png" /></figure>

OPEN ACCESS

EDITED AND REVIEWED BY
Michael Rychlik,
Technical University of Munich, Germany

*CORRESPONDENCE
Jean-François Hocquette
jean-francois.hocquette@inrae.fr

RECEIVED 05 February 2024
ACCEPTED 13 February 2024
PUBLISHED 27 February 2024

CITATION
Hocquette J-F, Chriki S, Ellies-Oury M-P, Fang F and Knaapila A (2024) Editorial: Food of the future: meat and dairy alternatives.
*Front. Nutr.* 11:1382337.
doi: 10.3389/fnut.2024.1382337

COPYRIGHT
© 2024 Hocquette, Chriki, Ellies-Oury, Fang and Knaapila. This is an open-access article distributed under the terms of the *Creative Commons Attribution License (CC BY)*. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Editorial: Food of the future: meat and dairy alternatives

Jean-François Hocquette¹*, Sghaier Chriki¹,²,
Marie-Pierre Ellies-Oury¹,³, Fang Fang⁴ and Antti Knaapila⁵

¹INRAE, Clermont Auvergne, Université Clermont Auvergne, VetAgro Sup, UMR1213, Recherches sur les Herbivores, Saint Genès Champanelle, France, ²Isara, Lyon, France, ³Feed & Food Department, Bordeaux Sciences Agro, Gradignan, France, ⁴IEH Laboratories and Consulting Group, Lake Forest Park, WA, United States, ⁵Department of Food and Nutrition, University of Helsinki, Helsinki, Finland

KEYWORDS

meat, dairy products, meat analogs, dairy analogs, dietary changes, future food

## Editorial on the Research Topic

### Food of the future: meat and dairy alternatives

In recent years, there has been increasing discussion about the impact of our dietary choices not only on our health, but also on global issues such as food security and climate change. Much emphasis has been placed on eating a plant-based diet and avoiding foods of animal origin, with vegetarian options becoming far more abundant across grocery stores and in restaurants. But are we on the right direction? Will meat and dairy alternatives satisfy consumers by living up to their promises? To contribute to this debate, 11 articles have been published in this special issue including 5 on what is called “cultured meat,” 4 on plant-based meat/dairy alternatives, and 2 on “hybrid meat” or other alternatives.

In June 2023, the United States became the second country after Singapore to approve the commercialization of “cultured meat” despite uncertainties about this product (1). Failla et al. analyzed 1,151 comments submitted to the 2021 U.S. Department of Agriculture’s Food Safety and Inspection Services (USDA-FSIS) call on the labeling of cell-cultured meat. Cultured meat was the preferred labeling term. The majority of comments came from people with unknown affiliation. However, many comments came from farmer advocacy groups and then cell-cultured meat companies. Comments from cell-cultured meat companies and animal welfare associations had the highest median word count. From a recent study, farmers do express complex and nuanced opinions related to food system control and transparency associated with cultured meat as well as potential impacts on the environment, the land, employment, and the life of farming/rural communities (2).

Most investment and research into cultured meat has so far occurred in the US. However, Attwood et al. argued that cultured meat is, so far, an untapped opportunity for the Muslim market thanks to the high projected increase in the world’s Muslim population in Asia and Africa. Whether cultured meat can be certified as halal is therefore of paramount importance. Then the potential acceptance of cultured meat by Muslim consumers’ needs to be studied in detail, taking into account their specific culture.

In South-Western Europe (Italy, Portugal, and Spain), Liu et al. observed a positive initial attitude toward cultured meat despite fragmented opinions. Indeed, almost two thirds of the respondents were willing to taste cultured meat but only 43% to eat it regularly and 94% would not pay more compared to conventional meat. Younger respondents, scientists or respondents unfamiliar with the meat sector had a higher acceptance. Ethical and environmental concerns were the major motives. Conversely, emotional resistance and
lower perceptions of the benefits of cultured meat and of the weaknesses of conventional meat were the main barriers to acceptance of cultured meat.

Using the same survey in 12 African countries (Cameroon, Congo, -DRC Democratic Republic of Congo, Ghana, Ivory Coast, Kenya, Morocco, Nigeria, Senegal South Africa, Tanzania, and Tunisia), Kombolo Ngah et al. confirmed some previous observations, especially the low willingness to pay for cultured meat. Furthermore, people were more likely to try this novel food in the richest and most educated countries surveyed. In addition, a large proportion of respondents strongly agreed that cultured meat would have a negative impact on the rural life confirming other studies conducted using the same protocol but on the French population (3).

Cultured meat is also expected to meet consumers' wishes in terms of sensory and nutritional value, which is not the case yet according to Fraeye et al. (4) and Olenic and Thorrez (1). To et al. analyzed 26 studies directly related to the sensory evaluation of cultured meat. Despite bias due to some potential conflicts of interest for many authors, To et al. attempted to distinguish between what is actually known and all the speculation in order to identify real expectations regarding the sensory characteristics of cultured meat, given the promising narratives of all the proponents.

The lack of standardized terminology for non-animal-based alternatives to animal-based foods has led to the interchangeable use of terms such as meat substitute, replacement, and analog. Addressing this ambiguity, Abbaspour et al. propose a welcome classification. They define “substitute” as a similar product from a culinary perspective, emphasizing functional and sensory properties. “Replacement” refers to options with similar nutritional properties. “Analog” seeks to match both culinary and nutritional attributes, while “alternative” represents a different choice, not necessarily mirroring the original product.

In a broader context, products derived from gene-edited farm animals could also be considered alternatives to conventional animal-based foods. In their study, Martin-Collado et al. explored societal attitudes toward gene-edited meat products. The findings revealed that consumers perceive gene-edited foods akin to genetically modified foods. The authors emphasized the importance of ongoing dialogue to inform consumers about this innovative technology.

Hybrid meat, combining both animal and plant-based proteins, has been observed to face a challenge in consumer acceptance due to limited familiarity (5). In a study by Ryder et al., consumers' verbal associations with hybrid meat improved after a co-creation task, demonstrating positive shifts as familiarity and ingredient knowledge increased. The research underscores a significant obstacle: consumers' lack of understanding regarding the nature and processes involved in developing hybrid meat products.

In their study, Kuosmanen et al. investigated consumers' perceived barriers associated with consumption of selected plant-based alternatives to meat (pulses and meat analogs). The authors employed the Capability, Opportunity, Motivation, Behavior (COM-B) model to interpret the results and observed that the most common perceived barriers for the consumption were unfamiliarity (capability), expensive price (opportunity), and unpleasant taste (motivation).

In addition to meat alternatives, dairy alternatives, such as plant-based milks and yogurts, are actively under study. In the research of D'Andrea et al., the nutritional value of plant-based yogurts was compared to that of dairy yogurts in the US market. The findings revealed that plant-based yogurts contained lower amounts of sugars and sodium, and more fiber, but less protein, calcium, and potassium compared to their dairy counterparts. This study underscores the variability in nutritional profiles between animal-based products and their plant-based alternatives.

McCarron et al. studied oat-based milk alternatives commercially available in the UK. The results indicated that achieving a small particle size is a key target feature, as it correlates with increased lightness, reduced perception of off-white color, and a diminished powdery mouthfeel. Furthermore, the findings suggested avoiding clear (transparent) packaging to prevent off-notes resulting from photo-oxidation. The study emphasizes the importance of sensory analysis in the development of new products.

The articles featured in this Research Topic illustrate that the partial evolution from animal-based to non-animal-based foods not only presents technological challenges but also demands considerations for integrating the alternatives into consumers' diets. Ensuring availability, an acceptable price, and attractive sensory properties are crucial aspects in addition to ethical and environmental benefits. Furthermore, it is essential to address consumer unfamiliarity through objective information based on scientific facts about ingredients, production processes, and nutritional values, as well as offering guidance on preparation. We hope this collection of articles provides insights that inspire further research on the topic.

## Author contributions

J-FH: Writing—original draft, Writing—review & editing.
SC: Writing—original draft, Writing—review & editing.
M-PE-O: Writing—original draft, Writing—review & editing.
FF: Writing—original draft, Writing—review & editing.
AK: Writing—original draft, Writing—review & editing.

## Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

## Conflict of interest

SC was employed by Isara. FF was employed by IEH Laboratories and Consulting Group.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated

organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

## References

1. Olenic M, Thorrez L. Cultured meat production: what we know, what we don't know and what we should know. *Ital J Anim Sci.* (2023) 22:749-53. doi: 10.1080/1828051X.2023.2242702

2. Manning L, Dooley JJ, Dunsford I, Goodman MK, MacMillan TC, Morgans LC, et al. Threat or opportunity? An analysis of perceptions of cultured meat in the UK farming sector. *Front. Sustain. Food Syst.* (2023) 7:1277511. doi: 10.3389/fsufs.2023.1277511

3. Hocquette É, Liu J, Ellies-Oury MP, Chriki S, Hocquette JF. Does the future of eat in France depend on cultured muscle cells? Answers from different

consumer segments. *Meat Sci.* (2022) 188:108776. doi: 10.1016/j.meatsci.2022.108776

4. Fraeye I, Kratka M, Vandenburgh H and Thorrez L. Sensorial and nutritional aspects of cultured meat in comparison to traditional meat: much to be inferred. *Front Nutr.* (2020) 7:35. doi: 10.3389/fnut.2020.00035

5. van Dijk B, Jouppila K, Sandell M, Knaapila A. No meat, lab meat, or half meat? Dutch and Finnish consumers' attitudes toward meat substitutes, cultured meat, and hybrid meat products. *Food Qual. Prefer.* (2023) 108:104886. doi: 10.1016/j.foodqual.2023.104886
<figure><img src="image_3.png" /></figure>

Check for
updates

# Gene-Edited Meat: Disentangling Consumers' Attitudes and Potential Purchase Behavior

OPEN ACCESS

**Edited by:**
Jean-François Hocquette,
INRA UMR1213 Unité Mixte de
Recherche sur les Herbivores
(UMRH), France

**Reviewed by:**
Maria Cecilia Mancini,
University of Parma, Italy
Shalander Kumar,
International Crops Research Institute
for the Semi-Arid Tropics
(ICRISAT), India

*Correspondence:
Daniel Martin-Collado
dmartin@cita-aragon.es

†ORCID:
Daniel Martin-Collado
orcid.org/0000-0002-2087-961X
Tim J. Byrne
orcid.org/0000-0002-8766-5421
Guillermo Ripoll
orcid.org/0000-0001-8042-8688
C. B. A. Whitelaw
orcid.org/0000-0002-2918-1605

**Specialty section:**
This article was submitted to
Nutrition and Food Science
Technology,
a section of the journal
Frontiers in Nutrition

**Received:** 17 January 2022
**Accepted:** 14 March 2022
**Published:** 05 April 2022

**Citation:**
Martin-Collado D, Byrne TJ, Crowley JJ, Kirk T, Ripoll G and Whitelaw CBA (2022) Gene-Edited Meat: Disentangling Consumers' Attitudes and Potential Purchase Behavior. Front. Nutr. 9:856491. doi: 10.3389/fnut.2022.856491

Daniel Martin-Collado<sup>1,2*†</sup>, Tim J. Byrne<sup>3†</sup>, Jonh J. Crowley<sup>3,4</sup>, Tom Kirk<sup>3</sup>, Guillermo Ripoll<sup>1,2†</sup> and C. B. A. Whitelaw<sup>5†</sup>

Novel gene-editing (GE) technologies provide promising opportunities to increase livestock productivity and to tackle several global livestock production sustainability and food security challenges. However, these technologies, as with previous genetic modification technologies in food production, are very likely to generate social controversy and opposition toward their use in the meat industry. Here, we explored public attitudes and consumption predisposition toward gene-edited meat products and their potential added benefits to livestock farming. Our results show that societal perception currently comes as a package, where the use of gene-editing technology acts as an extrinsic cue of meat products quality, and is used to make a range of inferences about all quality facets at once. Although consumers with anti-GE attitudinal positions generally were not sensitive to price discounts or added benefits, added benefits increased the consumption predisposition of most moderate and pro-GE consumers, where benefits related to animal welfare had larger effects than those relating to the environment or human health issues.

**Keywords:** livestock biotechnology, CRISPR, willingness to pay (WTP), added benefits, genetic modification (GM)

## IMPLICATIONS

We investigated consumer's attitudes and consumption predisposition toward gene-edited meat products and the potential effect of added benefits to consumption predisposition. We found that people's attitudes are formed toward all genetic engineering technologies without differentiating among them. According to our results, the inclusion of gene-edited meat in the food system will likely face societal opposition, and price discounts would not be an effective strategy to modify consumption predisposition. However, the use of gene-editing technology to reduce the negative impacts of livestock production can influence positively public opinion on the use of the technology in meat production.

<footnote n="1"><sup>1</sup> Department of Animal Science, Agrifood Research and Technology Centre of Aragon (CITA), Zaragoza, Spain, <sup>2</sup> AgriFood Institute of Aragon – IA2 (CITA-University of Zaragoza), Zaragoza, Spain, <sup>3</sup> AbacusBio International Limited, Roslin Innovation Centre, Edinburgh, United Kingdom, <sup>4</sup> Department of Agriculture, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada, <sup>5</sup> The Roslin Institute, Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, United Kingdom</footnote>
# INTRODUCTION

Novel gene-editing (GE) technologies offer new opportunities to increase agricultural productivity in the context of a growing human population and to tackle several global agricultural sustainability and food security challenges. These opportunities are particularly promising in livestock industries where the application of other genetic modification (GM) techniques has been relatively limited in scope and scale due to technical and social reasons (1, 2). Unlike previous GM techniques, current development of GE technology is already providing ground-breaking capabilities in livestock industries. Researchers have already generated tools to reduce environmental impacts from livestock production [e.g., increased productivity that leads to reduced environmental impact per unit of output; (3)], improve animal welfare [e.g., increase resistance to foot-and-mouth disease in pigs; (4), or animal dehorning; (5)], reduce risks for human health [e.g., elimination of allergens in eggs; (6)], and improve meat production composition and quality (7). As a relatively new technology, the potential of GE to further provide tools to tackle global livestock industry challenges is large. For example, there are already promising GE solutions to increase resistance to two diseases with a significant economic impact: tuberculosis in cows and porcine reproductive and respiratory syndrome in swine (7-9). To unlock the full potential of this technology would significantly improve the livestock industry's capacity to tackle important challenges of livestock production, in the context of a growing human population and increasing societal demands for environmental, animal welfare, human health and food quality improvements.

Some of these societal demands have and will very likely continue to generate controversy and opposition toward the application of GM and GE technologies in the food industry that go beyond the economic and technical issues (10). These controversies will very likely challenge the full deployment of GE technology in livestock industries, despite its promising potential benefits, as they have done before. Previous GM techniques, and especially transgenic technologies applied to plants (11, 12), faced strong opposition, especially in Europe, which, although this has weakened over time, is still significant (13, 14). Society's perceived risk of genetically modified food relates to unknown or unintended impact of human health, animal welfare and environment (15). Bartkowski and Baum (16) singled out three main factors driving societal concerns toward transgenic technologies, which are usually extrapolated by consumers toward all GM techniques: (a) the lack of precision in GM techniques which leads to doubts about undesirable side-effects, (b) the introduction of foreign DNA to the target species from other species or another variety of the same species (trans-and cis-genic, respectively), and (c) that GM technology has been developed and sold by multinational companies and used mainly in intensive crops and is oriented to the use of herbicides. Unlike traditional GM, GE technology does not introduce foreign DNA but, rather, allows the genome to be edited to exhibit desirable traits naturally expressed in other animals of the same (or closely related) species (17). This key difference removes the foundation of the three above-mentioned social concerns.

Literature relating to differential attitudes toward GM and GE technologies are often contradictory, and therefore need further investigation. Some authors have found in foods from plant origin (i.e., rice) that consumers valued gene-edited (i.e., CRISPR) and genetically modified food similarly, and significantly less than conventional food (18). However, other studies show that consumers are able to differentiate between GM technologies and have different attitudes toward them (19-21).

Attitudes toward traditional GM technologies in food production have been widely studied and found to be variable across time and cultures and influenced by several factors [e.g., (22)]. Consumer acceptance of genetically modified food is largely determined by perceived risk and perceived benefits (23). Novel foods in general, and genetically modified products in particular, are generally more acceptable if they provide tangible benefits for the consumer (23, 24). Knowledge and perceived knowledge on GM technologies are generally a key attitudinal driver, possibly by modulating the perceived risk of using the technologies (22). In this sense, Fernbach et al. (25) found that those people with the most negative view toward GM technologies are generally the least informed, though they believe themselves to be well informed. It has long been known that attitudes toward new technologies and GM use in food production vary in relation to the organism involved (animals, plants, microorganism) (23). Therefore, it is highly likely that societal attitudes toward GE food products of animal origin differ to those toward foods of plants origin. This is possibly because use of GE technology in livestock raises ethical issues that do not apply to crops, such as animal integrity and animal welfare, among others (26-28).

Given this social context, it has been argued that, like traditional genetically modified foods, the largest barrier to a widespread use of GE in the food system is not technical, but is in gaining wide-spread public acceptance and understanding (18). Therefore, in order to maximize the potential positive impact of GE technology in livestock production, it is important to understand public attitudes toward gene-edited meat products. However, there are only a few studies that have analyzed social perceptions of GE in livestock and these focus on very specific uses of the technology [i.e., Polled cattle, (29); GE alternative to castration in pigs, (30)]. This study takes a broader approach which complements the specific findings of the above two studies and other studies focusing on gene-edited plant-origin foods [i.e., (18, 31)]. As such, it aims to enhance the understanding of societal attitudes toward meat products from gene-edited livestock in general, and in relation to potential added benefits to livestock farming. Firstly, we assessed societal attitudes toward gene-edited meat products in the context of wider attitudes toward genetically modified food. Secondly, we analyzed consumption preferences based on consumer willingness to pay (WTP) for gene-edited meat products and how this WTP is affected by attitudes and by product benefits related to key societal concerns about to livestock production. Socioeconomic drivers and real and perceived knowledge of both attitudes and consumption preferences were considered. Ultimately, this study provides information to better understand the societal barriers to
the adoption and uptake of GE solutions for global food production challenges.

# MATERIALS AND METHODS

## Questionnaire Design and Survey Implementation

We developed a questionnaire that consisted of four sections: respondent profile, real and perceived knowledge of GE and GM technologies in food production, attitude toward GE and GM technologies in food production, and WTP for GE meat compared to standard meat. A compromise had to be reached between thoroughness, simplicity, and length. The questionnaire was anonymous, to guarantee a higher level of participation and honesty. Personal data were not required, and there was no financial compensation. Participants were clearly informed of the aim of the study and gave implicit consent for the use of their supplied information in the research according to European regulations. The questionnaire was distributed through an online survey developed using Online Survey platform (https://www. onlinesurveys.ac.uk/). United Kingdom (UK) citizens (n = 848) were recruited via Paid Facebook advertising (for 8 days) and the social media accounts of the Roslin Institute and the University of Edinburgh. This study was conducted according to the Declaration of Helsinki for studies on human subjects. The questionnaire was approved by the University of Edinburgh Human Ethical Research Committee (HERC).

The respondent profile section of the questionnaire included questions on gender, age, highest level of education achieved, living environment (either rural or urban), being vegetarian or not, and relationship with farming activity (either being a farmer, having a close family member being a farmer, or no relation). To evaluate real and perceived knowledge of GE technology, respondents were first asked how much they know about GE technology or how it can be used in food production. Possible answers were: “nothing,” “a little,” or “a lot.” Then, those who claimed to know either “a little” or “a lot” were asked a follow up question, where they had to choose the definition of GE technology from three options, only one of which was correct. Respondents were given the following five options:

1. “Taking selected genes from one species of animal or plant, and inserting those genes into a different species of animal or plant” (incorrect)

2. “Taking selected genes from an animal or plant, and inserting those genes into another animal or plant of the same species” (correct)

3. “Altering the DNA of an animal or plant using chemicals or targeted radiation to affect selected genes” (incorrect)

4. “None of the above” (incorrect)

5. “Not sure”

After this section, respondents were provided with the following succinct description of GM and GE technology, in order to ensure that they understood the difference between the technologies:

• “Transgenic food: A plant or animal which has had a useful gene transferred from a different species. For example, a cow with a gene transferred from a fish.”

• “Gene-edited food: A plant or animal which has had some of its genes deleted or replaced by genes from another plant or animal of the same species. For example, replacing a gene in a large cow with a gene from a small cow.”

The section on attitudes used Likert-type questions using a 7-point scale ranging from “Strongly disagree” to “Strongly agree”, with the midpoint being “Neutral.” Respondents were asked to state their level of agreement with six statements related to general attitudes toward GM and GE and specific attitude toward ethical, human-health, and environmental aspects of GE, and to the difference between using GE in animals and plants.

Finally, the questionnaire evaluated respondents' WTP for gene-edited meat products compared to “normal” meat. In this exercise, respondents were asked to select which product they would be more likely to purchase (there is an option for no preference) between “normal” chicken breast at a constant price of £6/kg and gene-edited chicken breast at variable price levels in an iterative process or “bidding game”. We used chicken breast because poultry it is the most widely consumer meat in the UK (32). The bidding game started with both products (i.e., gene-edited and “normal”) at the same price of £6/kg. If respondent chose gene-edited meat or had “no preference” then the bidding exercise ended. If respondent chose “normal” meat, then the question was repeated again with the gene-edited meat at £5/kg (i.e., £1/kg cheaper than “normal” meat). Questions continued until gene-edited meat was priced at £2/kg (i.e., £4/kg cheaper than “normal” meat). If in that final question respondent still chose “normal” meat, they were considered to not consume GE meat under any price scenario.

This exercise was repeated for gene-edited meat with added benefits to evaluate how purchasing behavior change when improvements in animal welfare, environmental impact, and human health are achieved using GE technologies. Specifically, the following three added-benefit scenarios were tested:

1. Added environmental benefits through breeding chickens that have a lower carbon footprint than non-gene-edited chickens.

2. Added human health benefits through breeding of chickens that produce higher levels of Omega 3 than non-gene-edited chickens.

3. Added animal welfare benefits through breeding chickens that are more resistant to certain diseases than non-gene-edited chickens.

In each scenario, the bidding game started with the gene-edited product at £7/kg, this is £1/kg more expensive than the “normal” product option.

## Data Analysis

We used factor and cluster analyses to explore the relationships between attitudes toward different aspects of GE technologies (i.e., ethical, environmental and animal welfare) and to determine if attitudinal groups of individuals could be found. Firstly, we implemented exploratory factor analysis to identify the latent
relational structure of the attitudinal aspects explored in the Likert-type questions. We used the “psych” and “GPArotation” packages of R software. The number of factors to select was determined using Horn's parallel analysis (33). We applied an Oblimin rotation and ordinary least squared factoring, which does not assume a multivariate normal distribution. Secondly, we used the root mean square of residuals (RMSR) and the Tucker-Lewis Index (TLI) to validate the factor model. Finally, we implemented k-means cluster analysis on the resulting factors to distinguish attitudinal groups across the sample. The number of clusters was determined by the partition with the highest loss of inertia (within cluster sum of squares). Differences in attitudinal group profiles were evaluated using ANOVA test and Bonferroni pairwise t-test for quantitative normally distributed variables and Pearson's chi-squared test for categorical variables.

We analyzed the WTP bidding-game results by comparing the proportion of respondents that prefer the gene-edited product over the standard one, at different price discounts in the different added-benefits scenarios. In addition, differences between attitudinal groups were determined according to their average WTP for gene-edited meat with added-benefits. Differences between groups were evaluated using the non-parametric Wilcoxon signed-rank test. Respondents who would not consume gene-edited meat at any price were not included in the WTP calculation.

# RESULTS

## Attitudes Toward GE Use in Food Production

We found that the latent relational structure of the attitudinal aspects was best described by just one factor. RMSR was 0.05 (should be close to 0) and TLI was 0.987 (should be above 0.9) showing the adequacy of the result. This single factor comprises attitudes toward GM and GE and all human-health, environment, and animal welfare components of GE (Table 1). We call this factor the “Attitude toward GE & GM factor” herein. The statement relating to differential treatment of animals and plants regarding GE is not part of this factor, meaning that this particular attitude is independent of respondents’ attitude toward GE and GM.

We ran the cluster analysis on two variables: the Attitude toward GE & GM factor and the (typified) variable corresponding to the attitudinal statement related to differential treatment of plants and animals (last statement in Table 1). The cluster analysis determined the existence of the following four groups of respondents (Table 2):

1. Anti-GE, Kingdom indifferent (18.9% of respondents): Respondents in this group had a very negative attitude toward GE and GM in food production, and consistently consider that animal and plant kingdoms should be treated in the same way when using GE for food production. Since this group made no distinction between animal and plant kingdoms, we called it Kingdom indifferent.

2. Anti-GE, Kingdom different (27.6%): Respondents in this group have a negative attitude toward GE and GM, but

contrary to the previous group, they strongly believe that plant and animal kingdoms should be treated differently for GE in food production.

3. Moderate (42.1%): It is the largest group of respondents in the sample. They have neutral or slightly positive attitudes toward GE and GM in food production and consider that animals and plants should be treated differently.

4. Pro-GE (11.4%): This is the smallest attitudinal group in the sample. This group has very positive attitudes toward GE and GM, and strongly considers that plants and animals should not be treated differently.

A more detailed description of the distribution of the attitudinal positions regarding GE in each group is presented in Figure 1.

## Socioeconomic Drivers of Attitudes

We found that attitudinal groups have different demographic profiles (Table 3). Groups with a more positive attitude toward GE and GM are associated with youth, being male, consuming meat, and living in an urban environment. There were no clear differences between attitudinal groups regarding education level, employment situation, or relationship with farming ($P > 0.05$).

Respondents that claimed to have no knowledge of GE had a less favorable attitudes toward GE & GM than respondents that declared some knowledge (either “a little” or “a lot”; Table 4), however, there was no (statistical) differences in attitude between those who believed to know “a lot” about GE and those who claimed to know “a little”. On the contrary, real knowledge about GE technology had no influence on attitudes. There were no statistical differences in the weight of the Attitude toward GE & GM factor between respondents who got the correct definition of GE technology, respondents who got it wrong, and respondents who were unsure about it. Furthermore, 57.1% of the people that claimed to know “a little” about GE technology and 78.8% of the people that claimed to know “a lot” were not able to select its correct definition. Note that real knowledge was only determined for respondents claiming to have some knowledge of GE, either “a little” or “a lot”.

## Willingness to Pay for Gene-Edited Meat Products

Figure 2 and Table 5 illustrate the results of the WTP exercise. Almost half (47.1%) of respondents stated that they would always choose “normal” meat instead of gene-edited meat regardless of the price discount. Adding benefits to gene-edited meat slightly changed this proportion; 40% would always choose normal meat instead of GE meat with improved animal welfare, 41% for lower environmental impacts, and 43.6% for increased human health benefits. On the other side, at equal prices 35% of respondents either prefer gene edited meat (without special features) or have no preference between gene-edited meat or “normal” meat. Finally, 17.9% of the respondents chose gene-edited meat when price discounts were offered. When respondents were asked to consider gene-edited meat in the context of additional benefits associated with GE technology, a large proportion of respondent would pay a premium of £1/kg (41.3% for improved animal
<table><caption>**TABLE 1** | Composition of the gene-editing (GE) attitudinal factor.</caption><thead><tr><th>Attitudinal statement</th><th>Factor 1</th><th>h2</th></tr></thead><tbody><tr><td>I have a positive perception toward genetically modified foods</td><td>0.90</td><td>0.82</td></tr><tr><td>I would be comfortable eating food produced using GE technology</td><td>0.95</td><td>0.90</td></tr><tr><td>GE in food production is ethical</td><td>0.92</td><td>0.85</td></tr><tr><td>GE in food production is safe for human health</td><td>0.95</td><td>0.90</td></tr><tr><td>GE in food production is safe for the environment</td><td>0.93</td><td>0.87</td></tr><tr><td>GE in animals and plants used for food production should be treated differently</td><td>-0.08</td><td>0.01</td></tr><tr><td>Proportion of variance explained</td><td>0.72</td><td></td></tr></tbody></table>

Standardized loading of attitudinal statements.

<table><caption>**TABLE 2** | Description of attitudinal groups according to the variables used in the cluster analysis.</caption><thead><tr><th>Attitudinal group</th><th>n</th><th><sup>a</sup>Attitude toward gene-editing and genetic modification (factor)</th><th>Attitude toward differential treatment of animals and plants in gene-editing (typified variable)</th></tr></thead><tbody><tr><td>Anti-gene-editing, Kingdom indifferent</td><td>160</td><td>-0.98<sup>A</sup> ± 0.37</td><td>-1.35<sup>A</sup> ± 0.34</td></tr><tr><td>Anti-gene-editing, Kingdom different</td><td>234</td><td>-0.81<sup>B</sup> ± 0.39</td><td>0.87<sup>D</sup> ± 0.54</td></tr><tr><td>Moderate</td><td>357</td><td>0.57<sup>C</sup> ± 0.5</td><td>0.29<sup>C</sup> ± 0.47</td></tr><tr><td>Pro gene-editing</td><td>97</td><td>1.31<sup>D</sup> ± 0.39</td><td>-1.05<sup>B</sup> ± 0.4</td></tr><tr><td>Total</td><td>848</td><td>0.0 ± 1.0</td><td>0.0 ± 1.0</td></tr></tbody></table>

welfare, 34.0% for lower environmental impact, and 31.8% for increased human health benefits).

Attitudinal groups clearly differentiated in their WTP for gene-edited meat and consumption predisposition (Table 5). On the one hand, “Anti-GE” groups had a lower WTP for gene-edited meat than the “Moderate” and the “Pro-GE” groups. Average WTP is negative in all groups but in “Pro-GE”, (which is very close to 0), meaning that price discounts were required for them to purchase the gene-edited meat. Furthermore, most people in “Anti-GE” groups (91.5 and 96.5% in “Kingdom indifferent” and “Kingdom different” groups, respectively) stated that they would not consume gene-edited meat regardless of the price discount and the associated benefits (Figure 3).

## Influence of Additional Benefits on WTP for Gene-Edited Meat Products

When considering gene-edited meat with additional benefits, WTP increased in all attitudinal groups; “Anti-GE” groups still showed a negative WTP, but both “Moderate” and “Pro-GE” groups showed a positive WTP (Table 5). Across all attitudinal groups, WTP was highest when benefits were associated with improving animal welfare (increasing animal disease resistance) and lowest when benefits were associated with human health (increased Omega 3 levels).

Finally, we found that some respondents that previously stated they would not eat standard gene-edited meat regardless of the price discount changed their mind when benefits were introduced (Figure 3). The proportion of respondents that changed their mind varied across attitudinal groups. Close to half

of the “Moderate” group (40%) changed their mind, but only a small proportion of “Anti-GE, Kingdom different” (11.5%) and “Anti-GE, Kingdom indifferent” (4.3%) groups would do so. Again, across all attitudinal groups, benefits associated with animal welfare and lowering GHG emissions where more important than benefits for human health.

## DISCUSSION

Societal opposition to GM use for food production has limited its adoption in agriculture, especially in European countries. Although nowadays there is less societal debate about GM technology than a decade ago, a large part of the society is still concerned about it use in the food industry [e.g., (13, 14)]. This historic debate focused on GM crops because its application to livestock production was very limited. Because new GE technology developments have been successfully applied in livestock [e.g., (4–7)], there is a renewed interest in analyzing the people’s specific attitudes toward its use in meat production. However, only a few studies have analyzed societal attitudes toward specific uses of GE technology in livestock production. To our knowledge, this study is the first to analyse general consumers’ attitudes toward GE technology in livestock production and WTP for gene-edited meat products with and without potential animal welfare, environmental, and human health benefits.

The results of our investigation add to a growing body of research which suggests that society will view gene-edited foods similarly to how they view genetically modified foods (18, 22),

<footnote><sup>a</sup>Negative values refer to negative attitudes toward gene-editing and genetic modification and that animals and plants should be treated in the same way. All consumer groups showed significant differences for the attitudinal factors according to ANOVA tests (P > 0.001).</footnote>

<footnote><sup>A-D</sup> Different letters indicate statistically significant differences between consumer groups according to Bonferroni pairwise t-test (P < 0.001).</footnote>
<figure><img src="image_4.png" /><figcaption>FIGURE 1 | Attitude toward different aspect related to gene-editing (GE) in food production across attitudinal groups.</figcaption></figure>

which implies that inclusion in the food system would be controversial. We found similar attitudinal groups and drivers of attitudes and consumption predisposition (i.e., age, gender, place of living and perceived knowledge) than previous studies. Our results also show that attitudes are likely to be positively affected by added benefits. Finally, unlike the use of GE in crops, gene-edited meat raises issues related to animal welfare, which affects both the intrinsic components of attitudes toward GE, and people's evaluation of potential benefits of this technology. These issues are discussed in detail below.

## Attitudinal Dimensions

According to our study, attitudes toward gene-edited meat products are built on two independent attitudinal dimensions: the attitude toward GM and GE technologies in food production, and the attitude toward the differential treatment of animals and plants. Attitudes (either positive or negative) toward the use of GE technology for food production are consistently created toward the “whole package” of GE and all its facets related to ethical aspects, human health, and environmental issues, without

distinguishing between them, along with genetically modified foods in general. This result shows that GE possibly functions as an extrinsic cue (i.e., signal) of food product quality (34), similarly to how meat origin, and animal feed or production system can signal food product quality (35). In this sense, GE would work as a consumer heuristic that backs up a story of the production process, which is used by people to make a whole range of inferences about product quality, leaving no space for nuance.

## Attitudinal Groups

The combination of both attitudinal dimensions in a factor analysis allowed us to identify four attitudinal groups of people; two anti-GE, one moderate, and one pro-GE. The opinion on the differential treatment of animals and plants was key to segmenting attitudinal positions, with the most extremely pro-GE attitudinal groups not differentiating between animals and plants under any circumstance. The two anti-GE groups differentiated in their position toward treating animal and plants differently. The existence of anti (“pessimistic”),
<table><caption>**TABLE 3** | Description of attitudinal groups; age, and proportion of females, vegetarians, and urban dwellers.</caption><thead><tr><th>Attitudinal group</th><th>n</th><th>Mean age</th><th>Females (%)</th><th>Vegetarians (%)</th><th>Urban (%)</th></tr></thead><tbody><tr><td>Anti-gene-editing, Kingdom indifferent</td><td>160</td><td>57.4<sup>A</sup> ± 12.2</td><td>74.5%</td><td>21.9%</td><td>49.4%</td></tr><tr><td>Anti-gene-editing, Kingdom different</td><td>234</td><td>56.9<sup>A</sup> ± 14.1</td><td>82.5%</td><td>28.2%</td><td>56.0%</td></tr><tr><td>Moderate</td><td>357</td><td>50.5<sup>B</sup> ± 18.2</td><td>72.0%</td><td>14.0%</td><td>63.9%</td></tr><tr><td>Pro- gene-editing</td><td>97</td><td>43.1<sup>C</sup> ± 17.4</td><td>49.5%</td><td>9.3%</td><td>69.1%</td></tr><tr><td>Total</td><td>848</td><td>47.6</td><td>68%</td><td>19%</td><td>61%</td></tr><tr><td>ANOVA test p-value</td><td></td><td>P < 0.001</td><td></td><td></td><td></td></tr><tr><td>Chi<sup>2</sup> p-value</td><td></td><td></td><td>P < 0.001</td><td>P < 0.001</td><td>P < 0.001</td></tr></tbody></table>

<table><caption>**TABLE 4** | Relation between attitude and perceived and real knowledge toward gene-editing technology.</caption><thead><tr><th></th><th>Number of respondents (%)</th><th>Attitude toward gene-editing and genetic modification factor (average and SD)</th></tr></thead><tbody><tr><td colspan="3"><strong>Perceived knowledge of gene-editing technology</strong></td></tr><tr><td>None</td><td>287 (28.5%)</td><td>-0.19<sup>A</sup> ± 0.77</td></tr><tr><td>A little</td><td>439 (51.4%)</td><td>0.00<sup>B</sup> ± 0.94</td></tr><tr><td>A lot</td><td>122 (20.1%)</td><td>0.33<sup>B</sup> ± 1.19</td></tr><tr><td colspan="3"><strong><sup>a</sup>Real knowledge; respondents guessing right the true definition of gene-editing technology</strong></td></tr><tr><td>Correct</td><td>157 (27.8%)</td><td>0.14 ± 0.96</td></tr><tr><td>Incorrect</td><td>345 (61.1%)</td><td>0.09 ± 1.04</td></tr><tr><td>Not sure</td><td>63 (11%)</td><td>-0.17 ± 0.92</td></tr></tbody></table>

moderates ("undecided"), and pro ("optimistic") groups have been consistently found by several authors when studying people perception on genetically modified food [e.g., (22)]. Unlike most of these studies which found that the "optimistic" group was usually rather large, our results show that when it comes to GE meat products, negative and moderate attitudinal positions dominate public opinion, with only a small proportion of respondent having pro-GE attitudes beyond doubt. The greater reluctance to use GE in livestock compared to using it in plants is very likely related to the great public concern for farm animal welfare (36, 37). Note that most respondents in our study consider that plant and animals are not the same and therefore should be treated differently in regard with GE.

## Attitudinal Drivers

Our study shows that youth and gender (i.e., males), and to a lesser extent place of living (i.e., urban), and non-vegetarianism, influenced positively attitudes toward GE use in meat production. These results are in line with previous studies which found that age and gender generally influence attitudes toward using GM technology in food production [e.g., (22, 38, 39)] and livestock welfare issues [e.g., (40-42)]. Similarly, urban inhabitants are usually found to have a more positive attitude toward GM use in food production [e.g., (43, 44)].

Perceived knowledge on genetically modified food has been widely studied, and is usually separated between real (tested) knowledge and perceived (self-assessed) knowledge. In accordance with House et al. (45), we found that the lower the

perceived knowledge of the respondent on GE technology the more negative the attitude toward it (and the lower WTP for GE meat products). Low knowledge increases risk perception, which has been proven to be strongly related to GM acceptability (22, 46). Contrary to other authors [e.g., (22, 45, 47)], we found no relationship between real knowledge and attitudes or WTP, however, these differences may be due to differences in the way "knowledge" is measured across studies (45).

## Consumption Predisposition, WTP and Perceived Benefits

The WTP exercise showed that respondent predisposition to consume gene-edited meat products is negative (i.e., price discounts are generally required) and is not influenced by further price discounts in large share of the respondents. Almost half of respondents would not consume gene-edited meat products regardless of the price, while around one third of the sample would have no problem consuming it. This means that only a small proportion of respondents (around 15%) were shown to be sensitive to price discounts. As expected, WTP from gene-edited meat products is very much related to attitudes toward it, with Anti-GE groups showing a much lower (negative) average WTP and a lower sensitivity to price discounts than Moderate and Pro-GE groups.

It is widely known that the use of GM to get added benefits increases consumers' acceptability and WTP for genetically modified products [e.g., (23, 24, 48)]. This has proved to also hold true for specific examples of GE technology use for increasing

<footnote>A-D Different letters indicate statistically significant differences between attitudinal groups, calculated according to Bonferroni pairwise t-test (P < 0.001).</footnote>

<footnote><sup>a</sup>Real knowledge was only determined for respondent declaring to have some knowledge on gene-editing, either "a little" or "a lot".</footnote>

<footnote>A-D Different letters indicate statistically significant differences between groups by perceived knowledge, calculated according to Bonferroni pairwise t-test (P < 0.001).</footnote>
A

Gene-edited without special features

<figure><img src="image_5.png" /></figure>

C

Improved disease resistance

<figure><img src="image_6.png" /></figure>

B

Lower greenhouse gases emission

<figure><img src="image_7.png" /></figure>

D

Increased omega 3

<figure><img src="image_8.png" /><figcaption>**FIGURE 2** | Willingness to pay for gene-edited meat (chicken breast) by its relative price compared to normal meat (£6/kg).</figcaption></figure>

animal welfare in livestock production; i.e., polled cattle (29) and alternative to castration in pigs (30). We indeed found, in a more general approach, that added benefits increased WTP for gene-edited meat products and that the effect was larger on benefits related to animal welfare, than to environmental or human health issues. This finding fits with the high relative importance that western society gives to animal rights within livestock production, and the higher importance of animal welfare compared to other livestock challenges [e.g., (29, 38)]. However, our study also shows that the respondent attitudes are affected by added benefits to a limited extent and differently across attitudinal groups. Most of the people who hold Anti-GE positions would not consume gene-edited meat products regardless of the price discount and they would not modify their consumption predisposition when either animal welfare, environmental or human health benefits are added. On the contrary, most Moderates and Pro-GE respondents attitudes are sensitive to added benefits. Actually, Moderates and Pro-GEs people, who on average would require price discounts to consume gene-edited meat products, would on average be willing to pay overprice (0.27–0.73£/Kg depending on the type of benefit) for gene-edited meat with added benefits. Our research suggests that GE technology use in meat production would

initially be acceptable to around half of consumers, although most of them would require a price discount or added-benefits to prefer gene-edited meat over normal meat.

## Limitations

This study has a number of limitations that should be acknowledged. Firstly, participants were recruited via online advertising, which, although provides a practical, cost-effective, and efficient way to gather a large and diverse sample, might bias the sampling toward internet users. Given the large usage of internet in UK households (90% of homes, 2020), we do not expect a large bias in this regard. We should also note that our sample might be slightly biased toward anti-GE positions as social groups that showed more negative attitudes toward GE use in meat production (rural, females, and aged) were to some extent overrepresented in the sample compared to overall UK population [(49); **Supplementary Table 1**]. Therefore, care is required when making inferences of the results of the survey about the whole UK population.

Similarly, our study was focused on the UK so its results cannot be immediately extrapolated to other countries. Previous studies on attitudes toward GM and GE food
<table><caption>**TABLE 5** | Willingness to pay for gene-edited meat with different beneficial features across attitudinal groups.</caption><thead><tr><th rowspan="2">¹Willingness to pay (£) for<br>gene-edited meat products</th><th colspan="5">Attitudinal group</th></tr><tr><th>Anti-gene-editing,<br>Kingdom indifferent<br>(n = 125)</th><th>Anti-gene-editing,<br>Kingdom different<br>(n = 168)</th><th>Moderate (n = 307)</th><th>Pro-gene-editing<br>(n = 88)</th><th>All (n = 688)</th></tr></thead><tbody><tr><td>Without special features</td><td>-2.10<sup>ab</sup> ± 1.6</td><td>-2.05<sup>a</sup> ± 1.28</td><td>-0.72<sup>b</sup> ± 1.13</td><td>-0.14<sup>c</sup> ± 0.46</td><td>-0.69 ± 1.14</td></tr><tr><td>From animal with increased<br>disease resistance</td><td>-0.87<sup>a</sup> ± 2.17</td><td>-0.19<sup>ab</sup> ± 1.63</td><td>0.49<sup>ab</sup> ± 0.99</td><td>0.73<sup>b</sup> ± 0.6</td><td>0.43 ± 1.11</td></tr><tr><td>From animal with lowered<br>GHG emission</td><td>-1.08<sup>ab</sup> ± 1.94</td><td>-0.89<sup>a</sup> ± 1.81</td><td>0.35<sup>bc</sup> ± 1.03</td><td>0.59<sup>c</sup> ± 0.62</td><td>0.25 ± 1.18</td></tr><tr><td>With increased Omega3<br>content</td><td>-1.0<sup>abc</sup> ± 2.16</td><td>-0.72<sup>a</sup> ± 1.69</td><td>0.27<sup>b</sup> ± 1.1</td><td>0.54<sup>c</sup> ± 0.69</td><td>0.22 ± 1.19</td></tr></tbody></table>

<figure><img src="image_9.png" /><figcaption>**FIGURE 3** | Influence of added benefits in gene-edited (GE) meat consumption across attitudinal groups.</figcaption></figure>

products across regions and countries [e.g., (18)], generally found similar attitudinal behaviors across western countries, with European citizens being the ones showing the greatest

concern. Therefore, the results of our study only apply to UK. However, given the similarity of UK society with other European societies, with regard to attitudes toward

<footnote n="1">¹Average and SD willingness to pay among those respondents willing to consume gene-edited meat. Negative values refer to discount required by consumers in order to purchase.</footnote>

<footnote>a-c Different letters indicate statistically significant differences between consumer groups, calculated according to Pairwise t-test variance (P < 0.05).</footnote>
GM and GE technology uses in food production, we would not expect results in other European countries to be very different. Extrapolation out of Europe should be done with care.

We should also note that attitudes that consumers express toward food products are not (always) strongly related to purchase behavior. However, this does not necessarily mean that attitude does not affect other behaviors, for example political behavior (34). Therefore, we should not interpret the implications of the results of our study only in terms of its impact people's role as consumers, but also in terms of potential influence on people's role as citizens. Currently, livestock production and meat consumption are important issues politically [e.g., (26, 50)]. Therefore, negative attitudes toward gene-edited meat found in our study might not (only) have a large effect on the future consumption of potential products, but are also likely to have a strong influence on public opinion and in turn in policy and regulatory decisions.

Finally, gene editing technology is still a largely unknown among the general public, which presumably will change as the technology develops and its adoption in the farming sector spreads. Since people's attitudes are largely influenced by their knowledge, as discussed above, it is possible that the attitudes reflected in this study change soon, particularly given the interest of GE technology developers in making society distinguish between this technology and traditional GM.

## Implications for GE Technologies Development

As GE technologies continue to advance, society must make decisions about their role in the food system. There are two clear messages emerging from our study. First, that perception of these technologies currently comes as a package; individuals start from either a supportive or a concerned stance for all genetic engineering technology. Our results add to a growing body of research which suggests that society will view gene-edited foods similarly to how they view genetically modified foods. The second conclusion is that there is a need for continued dialogue to provide the information that individuals seek. There remains an opportunity to differentiate people's perceptions between GE and GM, while our data strongly supports the need to communicate the benefits the technology offers to society. If there are real differences in the application and benefits of the different genetic engineering technologies, then these need to be better articulated to enable society to develop informed opinions. Consumer decisions on whether or not to buy GE food is not fixed, and changes in opinion remain possible. Changes will be reliant on clear, transparent dialogue around the benefits that the technology can deliver to society. The ability to appropriately communicate the improvements of GE technology over previous GM techniques on issues of

high importance to society, like meat quality, environmental impact and animal welfare, will likely shape the evolution of public attitudes toward it use in meat production, and in turn affect how the sector develops. In parallel, fair societal concerns around the ethics of artificially modifying animals' genomes remain, and these will continue to influence this dialogue. All actors have a role to play in the dialogue, from transparent representation by industry, to informed decision making by stakeholders, with trusted information sources likely to reside in recognized academic institutions. More research is needed to investigate the relationship between attitudes toward GE technologies and different messaging and communication strategies, and how consumers respond to labels highlighting different information or positive benefits associated with GE technology.

## DATA AVAILABILITY STATEMENT

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

## AUTHOR CONTRIBUTIONS

DM-C: methodology, formal analysis, writing—original draft, writing—review and editing, and visualization. TB: conceptualization, methodology, investigation, resources, writing—review and editing, supervision, and project administration. JC: methodology, formal analysis, investigation, writing—review and editing, and visualization. TK: conceptualization, methodology, formal analysis, investigation, writing—review and editing, and visualization. GR: writing—review and editing. CW: conceptualization, resources, writing—review and editing, supervision, and funding acquisition. All authors contributed to the article and approved the submitted version.

## FUNDING

The authors would like to thank the Biotechnology and Biological Sciences Research Council (BBSRC) for supporting this research, which was funded by a grant for the Roslin Institute, from BBSRC's Industrial Strategy Challenge Fund: Transforming Food Production initiative. CW was supported by the BBSRC through Institute Strategic Programme grants BB/P013732/1 and BB/P013759/1.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2022.856491/full#supplementary-material
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**Conflict of Interest:** TB, JC, and TK were employed by AbacusBio International Limited.

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Copyright © 2022 Martin-Collado, Byrne, Crowley, Kirk, Ripoll and Whitelaw. *This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*
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China Agricultural University, China

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**CITATION**

Ryder C, Jaworska S and Grasso S (2023)
Hybrid meat products and co-creation: What
do consumers say, feel and think?

Front. Nutr. 10:1106079.

doi: 10.3389/fnut.2023.1106079

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# Hybrid meat products and co-creation: What do consumers say, feel and think?

Chris Ryder<fnref n="1" />, Sylvia Jaworska<fnref n="1" />* and Simona Grasso<fnref n="2" />

**Introduction:** What consumers say about food and what kind of words they use to do so offers direct insights into their perceptions, preferences, reasoning, and emotions.

**Methods:** This study explores evaluations of hybrid meat products of 2,405 consumers from England, Denmark, and Spain. As part of a large survey, consumers were prompted to note down four words that come to mind when they read a description of a hybrid meat product, and then again after they were involved in a hypothetical co-creation task of a hybrid meat product. 18,697 words and phrases of language material was processed using computational corpus-based analysis and manual classification into semantic categories including: Evaluation, Sensory, Production, Emotion, Diets, Quality, Ethics, and Other.

**Results:** Consumers consider many dimensions when it comes to the evaluation of hybrid meat products including ethical conduct and sustainability. For all three languages, the number of positive words increased and the number of negative words decreased significantly ($p < 0.001$) following the co-creation task, suggesting that consumers see such products very positively once they are more familiar with them and know more about the ingredients. Subcategories that received most words include: taste, ingredients, healthiness, naturalness, innovation, and environment, implying that these areas are of most importance when it comes to the evaluation of hybrid meat products. The concept of nutrition (especially words pointing to positive aspects such as "rich in vitamins", "nutritious") also rose significantly in use after co-creation.

**Discussion:** The study reveals consumers' vocabulary of hybrid meat products across the three countries and offers important insights for food producers to help them create innovative products that better align with consumers' perceptions and expectations.

**KEYWORDS**

consumer, co-creation, word associations, evaluation, hybrid meat products, cross-cultural, United Kingdom, Spain, Denmark

## 1. Introduction

Flexitarian eating has been on the rise in recent years and seems to have accelerated post the Covid-19 pandemic and in younger populations referred to as Gen Z. According to the recent YouGov data, one in five 18-to-24-year-olds currently follow such a diet

<footnote n="1">¹Department of English Language and Linguistics, University of Reading, Reading, United Kingdom,</footnote>

<footnote n="2">²School of Agriculture and Food Science, University College Dublin, Belfield, Ireland</footnote>
and the number has doubled since 2019 (1). Flexitarian diet includes both: reducing meat consumption and meat portion size along the week, and having more plant-based and meat-free meals (2). In this context, a diversity of hybrid meat products have been introduced on the market; these products are specifically designed to blend meat and plant-based ingredients in convenient ready to cook forms, such as burgers, sausages or minced products (3). Despite the novelty of this hybrid concept, some consumer studies have already been carried out (4–6), and recent research has focussed on understanding consumer attitudes toward such products, including consumers’ views on their formulation and different types of messaging on them (7, 8).

Since consumers are an essential part in the new product development process and their attitudes and views can increase (or decrease) the likelihood of success of a new product on the market, co-creation has been suggested as a valuable tool to understand consumers’ concerns and perceptions, and engage them in the design of new food products (9). For example, consumer co-creation has been recently applied in a cross-country study involving consumers from United Kingdom, Spain, and Denmark, with the aim to understand the preferred ingredients to use in the manufacturing of hybrid meat products (8). A comparison of the consumption habits for processed meat in these three countries, to each other as well as to Europe and worldwide, can be seen in Table 1. Note that “Processed Meat” in this sense includes cold and roast meat products, ham and bacon, and sausages; fresh meat and pre-cooked meat-based ready-to-eat products are not included.

In the present study and covering the same countries, we use a linguistic word analysis approach to compare consumer attitudes toward hybrid meat products under two different conditions: the first condition exposed consumers to a written definition of hybrid meat products and the second invited them to a participative co-creation task of hybrid meat products, in which they could build their preferred product in a series of short steps. Following each condition, participants were prompted to provide any four words about the product that came to mind. Subsequently, the words were analysed systematically using frequencies and semantic categorisation.

This kind of free word association analysis is a very powerful tool that can tap into consumers' involuntary, and therefore more authentic preferences, expectations, reasoning and emotions when it comes to evaluating novel food products [e.g., (10–12)]. This is important to understand since most of the consumers' everyday decision making is determined by a constellation of spontaneous experiential, affective, and reasoning factors (13), and words that come to mind spontaneously can reflect these constellations unlike experiments conducted in laboratory settings. What consumers think spontaneously about hybrid meat products can therefore help producers of such products understand why certain products are preferred over others, and therefore more likely to be purchased. Research has shown that the understanding of this kind of free and spontaneous word associations facilitate an effective food product development and can assist with successful introduction of novel of healthy foods [e.g., for a systematic review on this research see (14)]. Furthermore, since co-creation has been shown to increase the likelihood of success of novel food products, word association analysis post a co-creation task can further enhance our understanding of the role of consumer engagement in novel food creation, and provide food manufacturers with relevant

information to help them align the development of hybrid meat products with consumers' preferences and expectations. This study therefore aims to explore the following research questions:

1. How do consumers perceive and evaluate hybrid meat products upon first presentation?

2. How do these perceptions change following the co-creation of a hybrid meat product?

3. In what ways does the linguistic and cultural context affect perceptions of hybrid meat products both before and after co-creation?

This study takes an innovative approach to the examination of hybrid meat products, firstly due to its foundations in Grasso et al. (8) pioneering study into the co-creation of hybrid meat products in the United Kingdom, Spain, and Denmark, and secondly by building on the corpus-linguistic approach to investigating perceptions and preferences around this kind of products that was established by Grasso and Jaworska (3) in the study of online reviews of hybrid meat products. In doing so, this study contributes to the growing body of research which utilises a combination of qualitative, projective techniques with quantitative methods to gain a more holistic understanding of consumers' perceptions, preferences and attitudes (14), here specifically in relation to novel hybrid meat products before and after co-creation.

## 2. Data and methods

Grasso et al. (8) outline the process of participant recruitment for the questionnaire that was put to consumers in the United Kingdom, Spain, and Denmark, including an element in which consumers “co-created” their own hybrid meat product, in order to identify willingness to try (WTT) and willingness to buy (WTB) hybrid meat products in each of these countries. In this questionnaire, consumers were presented with a hybrid meat product and asked to provide four words that came to mind based on their first impression; they were asked to repeat this exercise when presented with the hybrid meat product that they had developed as part of the co-creation task. While studies focussing on general terms often ask participants to note down three words, most research on food and food behaviour that used the word association technique required more words mostly four [e.g., (11, 12)] to account for the diversity of dimensions and aspects that people associate with food and give participants a bit more “space” to report on those. We followed this parameter in this study too and selected four as the number of words to write down.

For the purpose of this study, “word” in the context of a consumer’s response refers to any single response from a user regardless of its length; thus, a “word” may be anything from the individual words *healthy*, *gross*, or *awareness* to phrasal responses such as *environmentally-friendly* or *a bit weird*. In some instances, consumers provided longer clausal responses such as *good way to get more vegetables* or *I wouldn’t buy it* and those were considered too.

Subsequently, all lexical items were categorised according to their dominant semantic meanings. Seven main categories were identified including: Evaluation, Sensory, Production, Emotion,
<table><caption>TABLE 1 Average volume (kg) per capita for estimated 2023 consumption of processed meat.ª</caption><thead><tr><td>Region</td><td>Cold and roast meat</td><td>Ham and bacon</td><td>Sausages</td><td>Total</td></tr></thead><tbody><tr><td>UK</td><td>8.2</td><td>2.1</td><td>2.7</td><td>12.9</td></tr><tr><td>Spain</td><td>4.4</td><td>2.7</td><td>4.1</td><td>11.2</td></tr><tr><td>Denmark</td><td>7.1</td><td>2.6</td><td>8.6</td><td>18.3</td></tr><tr><td>Europe</td><td>18.8</td><td>7.2</td><td>3.2</td><td>7.4</td></tr><tr><td>Worldwide</td><td>2.3</td><td>0.8</td><td>1.9</td><td>5.1</td></tr></tbody></table>

Diets, Quality, Ethics, and Other. Given the wide range of words and phrases provided by consumers, each main category was then divided into relevant subcategories of meanings. The process of classifying the words and phrases into the categories was conducted iteratively and often by considering the context, that is, the other words that were provided in the response. Because of the explicit nature of the task, the meanings of most words and phrases were unambiguous and easy to categorise. In some ambiguous cases, the Oxford English Dictionary was consulted (16). An interrater was employed to classify 30% of the data with words and phrases from each category and subcategory. The agreement rate was generally high above 85%; any inconsistencies were resolved on the spot, and changes adopted.

A total of 802 participants in each of the United Kingdom and Demark, and 801 in Spain, provided words in English, Spanish, or Danish. Some respondents in Spain and Denmark provided their responses in English; for those who responded in Spanish and Danish, words were translated for the purposes of analysis. Theoretically, the total possible word yield for each language was 3,208 (3,204 for Spanish); however, certain words were rejected from the analysis for one of the following reasons:

* they appeared to be nonsense or gibberish, or were perhaps the result of a typo so severe that the original meaning could not be determined;

* the same word occurred more than once in a single set of four-word responses from a single consumer, i.e., the consumer repeated a word;

* a phrasal/clausal response was spread across more than one field—for example, one user responded with *I, don't, like*, and *it*, which were amalgamated as the single response *I don't like it*.

The total number of words for each language in each condition—both before (—CC) and after (+CC) the co-creation of a hybrid meat product—is provided in Table 2. Note that clausal responses were significantly (*p* < 0.001) more common in responses from Danish consumers when compared to English and

Spanish, accounting for the majority of the variation in number of words for that language since therefore multiple fields were more often amalgamated into one response.

Throughout the analysis that follows, statistical significance was determined through treatment of the figures above as six individual corpora and a calculation of the log-likelihood value. This standard measure of statistical significance in corpus linguistics takes the frequency of a particular phenomenon in one corpus or “body” of words and compares it to another, relative to the total size of each corpus; the log-likelihood is therefore a probability statistic that measures the likelihood of frequency differences between two or more corpora as occurring due to chance. This is then compared to a table of critical values to determine the statistical significance—or lack thereof—of the difference in frequency between the corpora. More information on the use of statistical analyses in corpus linguistics can be found in McEnery and Hardie (17).

## 3. Perceptions and evaluations of hybrid meat products

Following the process of classifying the words in accordance with their meanings, the following main semantic categories (with subcategories) emerged: Evaluation, Sensory, Production, Emotion, Diets, Quality, Ethics and Other. The full set of categories is provided in Table 3, with examples for each. As Table 3 shows, consumers referred to a range of dimensions when prompted to provide four words about hybrid-meat products before (—CC) and after (+CC) co-creation. While categories such as Sensory or general Evaluation are expected, there were also other aspects that were deemed relevant by consumers such as Ethics and varied dimensions of Quality and Emotion. This suggests that, when it comes to new hybrid food products, consumers do not just focus on one aspect—for example, only the sensory experience—but consider a variety of issues related to food production and consumption, including ethical conduct and sustainability, that are not often clearly communicated by food manufacturers.

Some interesting differences can be observed regarding the responses provided by the three national groups of consumers. Whereas, and as expected, Evaluation was relevant for all, words pointing to Emotion and Ethics were more often employed by Danish respondents, especially before the co-creation task, but this also remained quite relevant after the co-creation task. This suggests that Danish consumers might place more value on ethical and sustainable food production and consumption, and tend to express their preferences in a more emotional way. In addition, dimensions involved in Production of the hybrid meat products

<table><caption>TABLE 2 Words provided by participants in each language before and after co-creation of a hybrid meat product.</caption><thead><tr><td></td><td>English<br/>n = 802</td><td>Spanish<br/>n = 801</td><td>Danish<br/>n = 802</td></tr></thead><tbody><tr><td>—CC</td><td>3,151</td><td>3,168</td><td>3,022</td></tr><tr><td>+CC</td><td>3,153</td><td>3,177</td><td>3,026</td></tr></tbody></table>

<footnote>ªSource: Statista (15).</footnote>
<table><caption>TABLE 3 Frequency of consumer responses by category both before and after co-creation for each language.</caption><thead><tr><th rowspan="2">Semantic category</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Evaluation</td><td>3,151</td><td>3,153</td><td>3,168</td><td>3,177</td><td>3,022</td><td>3,026</td></tr><tr><td>Sensory</td><td>644</td><td>806</td><td>425</td><td>707</td><td>454</td><td>626</td></tr><tr><td>Production</td><td>320</td><td>361</td><td>451</td><td>471</td><td>406</td><td>440</td></tr><tr><td>Emotion</td><td>305</td><td>308</td><td>333</td><td>280</td><td>444</td><td>387</td></tr><tr><td>Diets</td><td>174</td><td>27</td><td>211</td><td>41</td><td>113</td><td>18</td></tr><tr><td>Quality</td><td>1,006</td><td>1,030</td><td>1,217</td><td>1,148</td><td>900</td><td>881</td></tr><tr><td>Ethics</td><td>217</td><td>151</td><td>254</td><td>189</td><td>347</td><td>262</td></tr><tr><td>Other</td><td>219</td><td>161</td><td>131</td><td>109</td><td>144</td><td>153</td></tr></tbody></table>

(including ingredients and nutritional value) seem to be more important for Spanish and Danish respondents than those from the United Kingdom.

In the sections that follow, each of the categories listed in Table 4 is taken in turn and noteworthy observations are made about some or all of the subcategories therein, noting statistical significance where appropriate to demonstrate a reasonable conclusion that the findings relate to real-world differences between consumers' perceptions before co-creation of a hybrid meat product versus after. In the tables, the following notation has been used alongside +CC figures where appropriate to indicate the level of the statistically significant difference from the -CC figures: *p* < 0.05; **p* < 0.01; ***p* < 0.001; ****p* < 0.0001.

## 3.1. Evaluation

The category of evaluation is of particular note, not only in isolation but especially when cross-referenced with figures from the other categories and subcategories that follow. Since this category exemplifies the spirit of the words that consumers gave, it highlights whether they are viewing the product—and the specific features of the product identified by the subcategories—as positive or negative. Neutral words (those with no clear positive or negative association) were also identified, as well as words that were ambiguous in that they were likely to have a positive or negative association that was impossible to determine without further context; for example, the adjective *optimistic* may imply a positive outlook, or it may be a negative warning as to the potential for the product to be successful. The total number of words in each Evaluation category used by speakers in each language before and after co-creation are presented in Table 5.

For all three languages, the number of positive words increased and the number of negative words decreased significantly (*p* < 0.001) following the co-creation task; the number of neutral and ambiguous words also decreased slightly in each case, indicating that there was a direct shift from negative to positive words after co-creation.

Table 6 shows the top 15 words used by the three groups of consumers before and after co-creation, with neutral and negative words highlighted in light and dark grey respectively. It is clear from this that the amount of negative words has been reduced, but it is also interesting to note the way in which specific words change

in evaluation, sometimes from a negative word to its direct positive opposite. In most cases, before co-creation, consumers perceived the hybrid meat products as expensive, but this perception was diminished after the task, with Spanish consumers even using the word *cheap*, suggesting that they are now more amenable to paying more for the products (the possible interpretation of this word as meaning “poorly-made” seems unlikely given its contrast with *expensive* before co-creation). This seems plausible in light of the increased attention to nutrition, as indicated by the more frequent use of words such as *nutritious*, *nourishing*, and *balanced*, which made it to the top words following the co-creation task; the implication here is that consumers perceive a hybrid meat product as better value for money once they are more informed about its nutritional value. It is also noteworthy that lexical items pointing to positive taste experiences (*tasty*, *delicious*, *appetising*) remain in the top words in both conditions, whereas those that are negative (*tasteless*, *insipid*, *bland*, *boring*) disappear from this list.

In isolation, this could be considered a mixed result for the hybrid meat product market: on the one hand, it implies that consumers see such products very positively once they are more familiar with them and know what is included in the product or have some choice of what “goes in.” On the other hand, this result highlights that informing or educating consumers about hybrid meat products and their ingredients is a key factor in determining consumer attitudes, since their first impressions before the co-creation were considerably more negative.

Evaluation was cross-referenced with the demographic of gender to determine any link to consumers' attitudes. Men were found to respond with more negative words than women both before and after co-creation for all three languages, to a statistically significant degree of *p* < 0.05 or greater. Accordingly, female consumers gave more positive responses than male consumers before co-creation in all three languages (*p* < 0.01 or greater), and after co-creation for Spanish and Danish (*p* < 0.001); in English, the difference in the number of positive words between men and women was not found to be statistically significant.

Evaluation was also cross-referenced with further demographic information regarding the age range, education level, and purchasing responsibility of the respondents, but no significant differences were observed; for this reason and those of space, these demographics were not further considered in the analysis.
## 3.2. Sensory

Although this category looked at all senses relevant to the consumption of food, the only subcategory that achieved a number of responses of any note was taste (Table 7). For this category, once again there was a clear and significant ($p < 0.001$) increase in positive words (delicious, tastes good, well-seasoned) and decrease in negative words (gross, bland, weird flavours) for all three languages following the co-creation of a hybrid meat product. This is particularly interesting since the consumers have not of course

<table><caption>TABLE 4 Categories and subcategories with examples.</caption><thead><tr><th>Semantic category</th><th>Semantic subcategory</th><th>Examples<sup>a</sup></th></tr></thead><tbody><tr><td rowspan="4">Evaluation</td><td>Positive</td><td>great-tasting, I like it, recommend</td></tr><tr><td>Negative</td><td>greasy, not enough, repellent</td></tr><tr><td>Neutral</td><td>basil, recipe, umami</td></tr><tr><td>Ambiguous</td><td>challenging, no meat, surprising</td></tr><tr><td rowspan="5">Sensory</td><td>Appearance</td><td>colourful, unappealing</td></tr><tr><td>Consistency</td><td>chewy, stodgy</td></tr><tr><td>Smell</td><td>fragrant, rank</td></tr><tr><td>Taste</td><td>bland, yum</td></tr><tr><td>Texture</td><td>crispy, rubbery</td></tr><tr><td rowspan="5">Production</td><td>Ingredients</td><td>falafel, olives</td></tr><tr><td>Nutrition</td><td>high in vitamins, low salt</td></tr><tr><td>Process</td><td>homemade, wok food</td></tr><tr><td>Side effects</td><td>diuretic, flatulence</td></tr><tr><td>Confusion</td><td>bewildered, I don't know what to say</td></tr><tr><td rowspan="5">Emotion</td><td>Expectation</td><td>doubt, sceptical</td></tr><tr><td>Intention</td><td>I wouldn't buy it, yes please</td></tr><tr><td>Interest</td><td>don't care, intriguing</td></tr><tr><td>Mood</td><td>heart-warming, shocking</td></tr><tr><td>Trust</td><td>misleading, trick</td></tr><tr><td rowspan="7">Diets</td><td>Allergies</td><td>gluten, lactose-free</td></tr><tr><td>Disorders</td><td>anorexia, diabetes</td></tr><tr><td>Religion</td><td>halal, sin</td></tr><tr><td>Veganism</td><td>herbivorous, vegan shit</td></tr><tr><td>Vegetarianism</td><td>not as good as vegetarian, veggie burger</td></tr><tr><td>Weight loss</td><td>fat-free, slimming</td></tr><tr><td>Freshness</td><td>fresh, perishable</td></tr><tr><td rowspan="7">Quality</td><td>Healthiness</td><td>digestible, immune-building</td></tr><tr><td>Innovation</td><td>inventive, novelty</td></tr><tr><td>Naturalness</td><td>laboratory, pretend</td></tr><tr><td>Potential</td><td>profitable, waste of time</td></tr><tr><td>Prestige</td><td>niche, snobbery</td></tr><tr><td>Price</td><td>cheaper, overpriced</td></tr><tr><td>Animal welfare</td><td>animal rights, cruelty-free</td></tr><tr><td rowspan="4">Ethics</td><td>Environment</td><td>environmentally-friendly, polluting</td></tr><tr><td>General</td><td>kinder, more ethical</td></tr><tr><td>Brands</td><td>Heck, Jamie Oliver</td></tr><tr><td>Choice</td><td>available, rarity</td></tr><tr><td rowspan="2">Other</td><td>Convenience</td><td>flexible, practical</td></tr><tr><td>Trendiness</td><td>fashionable, politically-correct</td></tr></tbody></table>

had the opportunity to taste the products between the two times at which they provided their responses; this implies that consumers' perceptions of taste can be “imagined” or primed by features of the product and its ingredients that they are exposed to during the task.

## 3.3. Production

The subcategory of nutrition (Table 8) was of particular note in this category, showing the same trend that positive attitudes to nutrition (rich in vitamins, nutritious, without saturated fat) increased significantly ($p < 0.001$) for all languages following co-creation. In this case, there were very few negative (fatty, lack of vitamins) or ambiguous (fat content, without carbohydrates) words given relating to nutrition in any language or condition, and the handful of neutral words (nutrition, protein) did not change in any significant way.

There was a significant ($p < 0.001$) decrease in the amount that consumers in all languages discussed the ingredients of a hybrid meat product following its co-creation. While the overwhelming majority of words were neutral in nature, since they were merely references to the specific ingredients that could be found in the product (pepper, chickpeas), it shows that there is a shifting of focus among consumers of the topics that are of importance to them once they have engaged in a co-creation task. Indeed, cross-referencing the subcategories of ingredients and nutrition demonstrated that, prior to co-creation, responses relating to ingredients were significantly ($p < 0.001$) more prevalent than those relating to nutrition, but that this statistical significance is reversed following co-creation—that is, responses relating to nutrition were significantly ($p < 0.001$) more prevalent than those relating to ingredients. This suggests that, by becoming more intimately involved with the process of creating a hybrid meat product, consumers are prompted to think more carefully about its nutrition rather than the top-level ingredients that it contains; this may have important implications for the impact of co-creation on consumers' understanding of nutrition and the healthiness of their diets.

## 3.4. Emotion

Consumer confusion (Table 9), as indicated by words that overtly expressed confusion (bewildered, complicated) or those that implied it through a lack of knowledge (why, I don't know), formed only a small number of responses both before and after co-creation; nevertheless, there was a statistically significant decrease in its prevalence for English ($p < 0.01$), Spanish ($p < 0.05$), and Danish ($p < 0.025$). The number of responses in the subcategory of interest also decreased, although it may be that some of these, such as intriguing, indicated a desire to know more about hybrid meat products which was somewhat sated by the end of the co-creation task.

Consumers' perceptions relating to intention were of particular note in this category: those that indicate positive intention (appetising, I'd try, want to buy)—that is, a desire to buy or eat the product—rose significantly ($p < 0.001$) across all three languages following co-creation, and, correspondingly, those that

<footnote><sup>a</sup>Examples include some of the most frequent words as well as phrasal responses.</footnote>
<table><caption>TABLE 5 Frequency figures for subcategories of evaluation.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Positive</td><td>1,346</td><td>2,390****</td><td>1,376</td><td>2,448****</td><td>1,153</td><td>1,992****</td></tr><tr><td>Negative</td><td>1,038</td><td>308****</td><td>876</td><td>229****</td><td>993</td><td>368****</td></tr><tr><td>Neutral</td><td>594</td><td>366</td><td>751</td><td>410</td><td>725</td><td>537</td></tr><tr><td>Ambiguous</td><td>173</td><td>89</td><td>165</td><td>90</td><td>151</td><td>129</td></tr><tr><td>Totals</td><td>3,151</td><td>3,153</td><td>3,168</td><td>3,177</td><td>3,022</td><td>3,026</td></tr></tbody></table>

<table><caption>TABLE 6 Top 15 words given by consumers in each of the three languages both before (–CC) and after (+CC) co-creation, with neutral and negative words highlighted.</caption><thead><tr><th rowspan="2"></th><th colspan="4">English</th><th colspan="4">Spanish</th><th colspan="4">Danish</th></tr><tr><th colspan="2">-CC</th><th colspan="2">+CC</th><th colspan="2">-CC</th><th colspan="2">+CC</th><th colspan="2">-CC</th><th colspan="2">+CC</th></tr><tr><th></th><th>Word</th><th>Fq.</th><th>Word</th><th>Fq.</th><th>Word</th><th>Fq.</th><th>Word</th><th>Fq.</th><th>Word</th><th>Fq.</th><th>Word</th><th>Fq.</th></tr></thead><tbody><tr><td>1</td><td>Healthy</td><td>237</td><td>Tasty</td><td>450</td><td>Healthy</td><td>361</td><td>Tasty</td><td>509</td><td>Healthy</td><td>177</td><td>Healthy</td><td>318</td></tr><tr><td>2</td><td>Tasty</td><td>141</td><td>Healthy</td><td>363</td><td>Tasty</td><td>102</td><td>Healthy</td><td>508</td><td>New</td><td>77</td><td>Delicious</td><td>145</td></tr><tr><td>3</td><td>Tasteless</td><td>116</td><td>Different</td><td>132</td><td>Vegan</td><td>91</td><td>Nutritious</td><td>165</td><td>Tasteless</td><td>70</td><td>Tasty</td><td>136</td></tr><tr><td>4</td><td>Expensive</td><td>98</td><td>Nutritious</td><td>104</td><td>Expensive</td><td>82</td><td>Appetising</td><td>74</td><td>Expensive</td><td>68</td><td>Exciting</td><td>101</td></tr><tr><td>5</td><td>Different</td><td>92</td><td>New</td><td>67</td><td>Insipid</td><td>80</td><td>Good</td><td>69</td><td>Boring</td><td>67</td><td>New</td><td>90</td></tr><tr><td>6</td><td>Vegan</td><td>82</td><td>Interesting</td><td>65</td><td>Weird</td><td>77</td><td>Natural</td><td>59</td><td>Taste</td><td>67</td><td>Tasteful</td><td>69</td></tr><tr><td>7</td><td>Bland</td><td>80</td><td>Healthier</td><td>59</td><td>Vegetarian</td><td>63</td><td>Different</td><td>57</td><td>Healthier</td><td>54</td><td>Taste</td><td>65</td></tr><tr><td>8</td><td>Healthier</td><td>54</td><td>Good</td><td>41</td><td>Flavour</td><td>59</td><td>Original</td><td>48</td><td>Exciting</td><td>51</td><td>Healthier</td><td>55</td></tr><tr><td>9</td><td>Fake</td><td>52</td><td>Unique</td><td>41</td><td>Natural</td><td>59</td><td>Balanced</td><td>44</td><td>Environmentally-friendly</td><td>49</td><td>Different</td><td>54</td></tr><tr><td>10</td><td>Vegetarian</td><td>51</td><td>Ethical</td><td>39</td><td>Different</td><td>51</td><td>Cheap</td><td>41</td><td>Different</td><td>48</td><td>Environmentally-friendly</td><td>51</td></tr><tr><td>11</td><td>Boring</td><td>43</td><td>Nice</td><td>39</td><td>Ecological</td><td>51</td><td>Delicious</td><td>36</td><td>Environment</td><td>45</td><td>Interesting</td><td>44</td></tr><tr><td>12</td><td>Interesting</td><td>43</td><td>Spicy</td><td>36</td><td>Artificial</td><td>44</td><td>Flavour</td><td>34</td><td>Delicious</td><td>43</td><td>Nourishing</td><td>44</td></tr><tr><td>13</td><td>Sustainable</td><td>43</td><td>Delicious</td><td>34</td><td>Vegetable</td><td>42</td><td>Weird</td><td>34</td><td>Vegetarian</td><td>39</td><td>Expensive</td><td>41</td></tr><tr><td>14</td><td>New</td><td>40</td><td>Nutritional</td><td>30</td><td>Fake</td><td>41</td><td>Expensive</td><td>33</td><td>Vegan</td><td>37</td><td>OK</td><td>40</td></tr><tr><td>15</td><td>Good</td><td>38</td><td>Fun</td><td>29</td><td>Sustainable</td><td>39</td><td>Novel</td><td>33</td><td>Interesting</td><td>33</td><td>Easy</td><td>34</td></tr></tbody></table>

<table><caption>TABLE 7 Frequency figures for subcategories of sensory.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Appearance</td><td>26</td><td>15</td><td>29</td><td>23</td><td>45</td><td>32</td></tr><tr><td>Consistency</td><td>31</td><td>43</td><td>29</td><td>34</td><td>38</td><td>30</td></tr><tr><td>Smell</td><td>5</td><td>2</td><td>3</td><td>5</td><td>9</td><td>9</td></tr><tr><td>Taste</td><td>528</td><td>729</td><td>328</td><td>628</td><td>331</td><td>533</td></tr><tr><td>Texture</td><td>54</td><td>17</td><td>36</td><td>17</td><td>31</td><td>22</td></tr><tr><td>Totals</td><td>644</td><td>806</td><td>425</td><td>707</td><td>454</td><td>626</td></tr></tbody></table>

<table><caption>TABLE 8 Frequency figures for subcategories of production.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Ingredients</td><td>213</td><td>117****</td><td>326</td><td>189****</td><td>318</td><td>239****</td></tr><tr><td>Nutrition</td><td>88</td><td>236</td><td>102</td><td>266</td><td>63</td><td>185</td></tr><tr><td>Process</td><td>18</td><td>8</td><td>20</td><td>10</td><td>22</td><td>16</td></tr><tr><td>Side effects</td><td>1</td><td>0</td><td>3</td><td>6</td><td>3</td><td>0</td></tr><tr><td>Totals</td><td>320</td><td>361</td><td>451</td><td>471</td><td>406</td><td>440</td></tr></tbody></table>
<table><caption>TABLE 9 Frequency figures for subcategories of production.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Confusion</td><td>55</td><td>26***</td><td>41</td><td>24*</td><td>50</td><td>28**</td></tr><tr><td>Expectation</td><td>8</td><td>3</td><td>14</td><td>12</td><td>26</td><td>17</td></tr><tr><td>Intention</td><td>70</td><td>98</td><td>99</td><td>158</td><td>81</td><td>96</td></tr><tr><td>Interest</td><td>111</td><td>94</td><td>40</td><td>26</td><td>143</td><td>82</td></tr><tr><td>Mood</td><td>22</td><td>66</td><td>51</td><td>34</td><td>75</td><td>136</td></tr><tr><td>Trust</td><td>39</td><td>21****</td><td>88</td><td>26****</td><td>69</td><td>28****</td></tr><tr><td>Totals</td><td>305</td><td>308</td><td>333</td><td>280</td><td>444</td><td>387</td></tr></tbody></table>

<table><caption>TABLE 10 Frequency figures for subcategories of diets.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Allergies</td><td>3</td><td>0</td><td>1</td><td>0</td><td>6</td><td>0</td></tr><tr><td>Disorders</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>0</td></tr><tr><td>Religious</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td></tr><tr><td>Vegan</td><td>86</td><td>4****</td><td>101</td><td>9****</td><td>53</td><td>2****</td></tr><tr><td>Vegetarian</td><td>73</td><td>18****</td><td>72</td><td>11****</td><td>49</td><td>10****</td></tr><tr><td>Weight loss</td><td>11</td><td>5</td><td>36</td><td>20</td><td>2</td><td>6</td></tr><tr><td>Totals</td><td>174</td><td>27</td><td>211</td><td>41</td><td>113</td><td>18</td></tr></tbody></table>

<table><caption>TABLE 11 Frequency figures for subcategories of quality.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Freshness</td><td>23</td><td>22</td><td>10</td><td>8</td><td>8</td><td>16</td></tr><tr><td>Healthiness</td><td>341</td><td>466</td><td>466</td><td>609</td><td>292</td><td>431</td></tr><tr><td>Innovation</td><td>197</td><td>302****</td><td>220</td><td>227</td><td>207</td><td>195</td></tr><tr><td>Naturalness</td><td>205</td><td>75</td><td>309</td><td>114</td><td>197</td><td>70</td></tr><tr><td>Potential</td><td>80</td><td>76</td><td>69</td><td>57</td><td>79</td><td>69</td></tr><tr><td>Prestige</td><td>16</td><td>11</td><td>21</td><td>18</td><td>7</td><td>8</td></tr><tr><td>Price</td><td>144</td><td>78</td><td>122</td><td>115</td><td>110</td><td>92</td></tr><tr><td>Totals</td><td>1,006</td><td>1,030</td><td>1,217</td><td>1,148</td><td>900</td><td>881</td></tr></tbody></table>

<table><caption>TABLE 12 Frequency figures for subcategories of ethics.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Animal welfare</td><td>20</td><td>6</td><td>13</td><td>6</td><td>38</td><td>28</td></tr><tr><td>Environment</td><td>152</td><td>72</td><td>218</td><td>141</td><td>282</td><td>206</td></tr><tr><td>General</td><td>45</td><td>73</td><td>23</td><td>42</td><td>27</td><td>28</td></tr><tr><td>Totals</td><td>217</td><td>151</td><td>254</td><td>189</td><td>347</td><td>262</td></tr></tbody></table>

indicated negative intention (avoid, no thanks, I'm not eating that) fell significantly ($p < 0.01$), again across all languages. It is clear then that the co-creation task undertaken by consumers had a positive effect on their WTT and WTB that prompts further investigation.

A relatively small number of words relating negatively to trust (deceptive, scam, swindle) were found before co-creation, forming

the majority of the words relating to this subcategory. Following the co-creation task, such words were found to have decreased in use significantly ($p < 0.001$) for all three languages, although there was little or no rise in the number of positive words relating to trust; rather, the topic seemed to no longer be of focus to consumers once they had undertaken the task and understood how hybrid meat products are made and the science behind them.
<table><caption>TABLE 13 Frequency figures for subcategories of other.</caption><thead><tr><th rowspan="2">Semantic subcategory</th><th colspan="2">English</th><th colspan="2">Spanish</th><th colspan="2">Danish</th></tr><tr><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th><th>-CC</th><th>+CC</th></tr></thead><tbody><tr><td>Brand</td><td>53</td><td>2</td><td>3</td><td>1</td><td>7</td><td>2</td></tr><tr><td>Choice</td><td>43</td><td>38</td><td>53</td><td>45</td><td>59</td><td>58</td></tr><tr><td>Convenience</td><td>30</td><td>82</td><td>17</td><td>45</td><td>21</td><td>70</td></tr><tr><td>Trendiness</td><td>93</td><td>39****</td><td>58</td><td>18****</td><td>57</td><td>23****</td></tr><tr><td>Totals</td><td>219</td><td>161</td><td>131</td><td>109</td><td>144</td><td>153</td></tr></tbody></table>

Only a small number of consumer responses were related to mood, and there was a general tendency toward those that were positive in meaning (*delightful*, *exciting*, *inspirational*). These positive mood words increased significantly (*p* < 0.001) for English and Danish consumers, but there was no change to be found for Spanish consumers.

## 3.5. Diets

Overall there were very few words for any of the diet-related subcategories (Table 10). In this category, consumers spoke most often about vegetarianism (*semi-vegetarian*, *veggie sausages*) and veganism (*vegan-mad veganish*), and there was a statistically significant (*p* < 0.001) decrease in words relating to these topics following co-creation for all three languages. Since the majority of words for vegetarianism and veganism were neutral in any case, it is likely that this topic simply became irrelevant for many consumers once they had learned more about hybrid meat products and the fact that they do contain meat (and are hence not vegetarian or vegan products). There is the wider implication here that the proper marketing of these products to highlight their meat content is likely to increase the number of consumers who are willing to try them as they will not be so easily dismissed by meat-eaters as suitable only for vegetarian or vegan diets.

## 3.6. Quality

One important focus for many consumers—and indeed for manufacturers—was the price of the hybrid meat products (Table 11). For English consumers, the number of responses related to this topic decreases following co-creation, but for Spanish and Danish consumers it remains a topic of interest. However, by cross-referencing with evaluation scores, it is clear that the number of negative responses relating to price (*expensive*, *overpriced*, *unaffordable*) decreased significantly for English and Spanish (*p* < 0.001) as well as Danish (*p* < 0.025) consumers. An increase in positive words relating to price (*cheaper*, *economical*, *worth the price*) was significant only for Spanish consumers (*p* < 0.001).

The healthiness of the products was a topic of a great amount of focus for consumers, and for all three languages over 94% of words relating to healthiness were positive in nature (*good for you*, *wellbeing*, *it's healthier*) even before the co-creation task. Despite this, positive responses concerning healthiness increased significantly (*p* < 0.001) to over 98% for all languages following the task. This is in contrast to some extent to the concept of naturalness, which was more often perceived negatively by

many consumers both before and after the co-creation task. Nevertheless, the degree to which consumers responded with negative words about naturalness (*artificial*, *fake*, *Frankenstein*) decreased significantly (*p* < 0.001) for all languages following co-creation and the increased understanding of how hybrid meat products are developed.

The perception of innovation of the hybrid meat products was addressed by a number of consumers and was done so with an overwhelmingly positive outlook (*progressive*, *pioneering*, *futuristic*); this remained constant for Spanish and Danish following the co-creation task, while for English it increased further to a statistically significant extent (*p* < 0.001).

## 3.7. Ethics

For words relating to ethical considerations (Table 12)—mostly restricted to matters of the environment and animal welfare—consumers generally gave positive responses (*more climate-friendly*, *animal-friendly*, *no guilt*). Following co-creation, these generally seemed to decline, although the shift was not majorly significant and did not result in any increase in the number of negative words relating to ethical matters. In general, then, ethical topics were of less interest to consumers following co-creation, likely because of the increase in focus of matters relating specifically to the product that they had created—its naturalness, healthiness, affordability, etc.—and because, once an ethical issue had been registered upon the first viewing of the product, it did not seem necessary to repeat this fact after co-creation.

## 3.8. Other

The subcategory of convenience (Table 13) shows that many consumers were concerned with how easy the products would be to prepare and cook, but in general this was the case only following co-creation. While topics such as ingredients, animal and environmental welfare, and vegetarianism/veganism were more frequent before the task, once they had created their own hybrid meat product many consumers focused more frequently on the level of convenience of the products, doing so in a positive way (*easy to cook*, *straightforward*, *helpful*), and increasingly so to a significant degree (*p* < 0.05) in all languages.

Some consumers also commented on the trendiness of the product; this subcategory produced a number of words that were ambiguous in nature, since the perception that something is “trendy” or “fashionable” is not always considered a positive
attribute. Following the co-creation task, the number of words
relating to trendiness fell significantly (p < 0.001) in all languages,
and this was primarily from those that were evaluated as
negative (*gimmicky*, *faddish*, *bandwagon*) or ambiguous (*modern*,
*fashionable*, *politically-correct*). In the same way as figures for
the subcategories of vegetarianism and veganism, it seems that
perceptions of the products as being limited to a specific group or
type of person are decreased once the co-creation task has been
completed.

4. Conclusion

It is clear that the process of co-creation results in much more
favourable perceptions of hybrid meat products. Following co-
creation, consumers have been shown to have a more positive
perception of the nutritional value of a product, as well as more
trust and stronger intentions to try or buy them. Regarding taste—a
factor of great importance to consumers—the majority of negative
considerations of taste disappear following co-creation; while this
could imply that consumers might decide they would like the
product after all, it might also suggest that those consumers who
would not personally find the product appealing can at least
appreciate the positive aspects of the product as an available
option in the supermarket. In addition, while the majority of
consumers consider the products healthy even before co-creation,
following the task these perceptions are significantly increased
and any concerns about the unnaturalness of the hybrid meat
products are diminished.

While it is possible that there is an effect here caused by the
fact that the consumer has had a hand in the products development
(a kind of “I made it” effect), the key difference following co-
creation is that the consumer now has a better understanding of
what the product is and how it is developed. This is exemplified by
the words that the consumers used to describe them, particularly
through (1) a decrease in words relating to confusion, (2) a
greater focus on nutritional value over basic ingredients, and (3)
a decrease in words such as *vegetarian* and *vegan* that highlight
misunderstandings of the nature of a hybrid meat product. It is
reasonable to conclude therefore that a major barrier to the positive
perception of hybrid meat products is a lack of understanding about
their nature and the processes involved in their development. This
finding can be seen in a positive light: to rephrase a paragraph
from section 3.1, although there is a considerable proportion of
consumers who perceive hybrid meat products negatively, there
is hope in that these perceptions can be significantly minimalized
through education. However, the package may not be the place to
undertake this education, since consumer opinions can be formed
very quickly and on very little information (¹⁸); instead, it is likely
that consumers will need to have a positive perception of a hybrid
meat product before they enter the supermarket. Future work
should focus on understanding the best way to communicate to
consumers what hybrid meat products are and what their potential
benefits might be. Another challenge lies in the fact that hybrid
meat products currently are somewhere “in-between,” so while
they surely do not belong to the vegan and vegetarian isles in
the supermarkets, they should be given a dedicated and somehow
highlighted section in the meat aisle to point out their differences
from the meat-only products available.

Perhaps owing to the fact that hybrid meat products are an
innovation to most markets, few differences were found between
the three languages studied. Nevertheless, those differences that
were found may be of importance: Danish consumers focused
significantly more on ethical issues and gave more responses in
relation to emotion, while they and Spanish consumers were
both more concerned with the production process (including
both the ingredients and the nutritional value) compared to
English consumers. These differences in focus suggest that different
marketing strategies should be employed in each market in order to
successfully appeal to the consumers therein.

The results of this study show that co-creation matters for
consumers' perceptions of certain aspects of hybrid meat products,
and therefore any new launches should be carefully co-created
with consumers from the outset. The food industry should use
co-creation tools more as they can provide valuable insights
before products are developed and launched into the market,
and therefore increase the chances of successful, competitive and
tailored products on the shelves. In any case, the need for greater
education regarding the nature of hybrid meat products is clear, and
should be the first priority.

4.1. Limitations and further study

As a pioneering examination of the topic of attitudes to hybrid
meat products in this way, this study has generally taken an
approach that is broader than it is deep. It covers a large number
of categories of words given by participants to analyse the overall
trends in relation to positivity and negativity, and how these
are influenced by an online co-creation task that helps educate
consumers about the nature of hybrid meat products. A key area
for future study, therefore, is to examine these trends in greater
detail, with reference to demographic qualities of the respondents
and any differences to be found therein. Although categories such
as gender, age, education level and purchasing responsibility were
considered initially, no significant differences were identified on
the surface level and so these were not pursued further. It is
highly anticipated that this type of study could be repeated with
greater emphasis on demographic characteristics of the consumers
now that the most significant concerns have been identified and
that the positive benefits of the co-creation task on consumer
attitudes has been established. Given that food choices often have
to do with lifestyle preferences, further research would benefit
from operationalising and including lifestyle as a factor alongside
established demographic variables such as age and gender.

The socioeconomic situations in the United Kingdom, Spain,
and Denmark have been addressed in this study, but, needless
to say, the door has been opened for the same types of
examination of further situations. These could be expanded within
the same countries, such as a comparison of attitudes within
each of the Home Nations of the United Kingdom, or could be
widened to consider the same languages as spoken in alternative
socioeconomic areas, such as the United States and Canada, Mexico
and South America, and Greenland. Finally, there is great scope to
broaden the study into further languages, in particular those spoken
in Europe within the same socioeconomic bloc, such as French,
German, and Swedish.

The approach taken here has combined qualitative with
quantitative techniques, employing corpus-linguistic methods to
analyse attitudes based on frequency counts that rise and fall following the co-creation task. Further studies could benefit from this approach, but it would also be invaluable to employ more qualitative research methodologies such as focus groups with consumers in each country and language, as these may yield more comprehensive and nuanced results. Beyond lexical prompts, such focus groups could involve sensory stimuli to tap into more immediate corporeal perceptions of hybrid meat products. Although the technique of spontaneous free word associations has been identified as a powerful tool to understand consumers' perceptions, expectations and their food behaviour, future studies could complement word associations with other projective techniques, such as those involving, for example, story techniques and completion tasks to gain more holistic insights into consumers perceptions of hybrid meat products [e.g., (14)].

## Data availability statement

The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

## Ethics statement

The studies involving human participants were reviewed and approved by University of Reading Ethics Committees. The patients/participants provided their written informed consent to participate in this study.

## References

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## Author contributions

SG collected the data for the study and contributed to refining the final version. CR organised the database and completed the statistical analysis. SJ and CR performed data categorisation and analysis and wrote the first draft. All authors contributed to the article and approved the submitted version.

## Funding

This work was supported by EIT Food; project number 20206 and titled "Consumer attitudes towards healthier processed meat products".

## Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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<figure><img src="image_11.png" /></figure>

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EDITED BY
Haohao Wu,
Ocean University of China, China

REVIEWED BY
Nina Drejerska,
Warsaw University of Life Sciences, Poland
Aida Turrini,
Independent Researcher,
Scansano, Italy

*CORRESPONDENCE
Jean-François Hocquette
✉ jean-francois.hocquette@inrae.fr

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Food Chemistry,
a section of the journal
Frontiers in Cardiovascular Medicine

RECEIVED 19 December 2022
ACCEPTED 23 March 2023
PUBLISHED 14 April 2023

CITATION
Kombolo Ngah M, Chriki S, Ellies-Oury M-P, Liu J and Hocquette J-F (2023) Consumer perception of “artificial meat” in the educated young and urban population of Africa. *Front. Nutr.* 10:1127655. doi: 10.3389/fnut.2023.1127655

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© 2023 Kombolo Ngah, Chriki, Ellies-Oury, Liu and Hocquette. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Consumer perception of “artificial meat” in the educated young and urban population of Africa

Moïse Kombolo Ngah¹, Sghaier Chriki¹,², Marie-Pierre Ellies-Oury¹,³, Jingjing Liu¹ and Jean-François Hocquette¹*

¹INRAE, Clermont Auvergne, Université Clermont Auvergne, VetAgro Sup, UMR1213, Recherches sur les Herbivores, Saint Genès Champanelle, France, ²Isara, Lyon, France, ³Bordeaux Sciences Agro, Feed & Food Department, Gradignan, France

African's population is expected to grow especially in cities to reach about 2.5 billion in 2050. This will create an unprecedented boom in the demand for animal products over the coming years which will need to be managed properly. Industry stakeholders worldwide have been touting the potential benefits of "artificial meat" in recent years as a more sustainable way of producing animal protein. "Artificial meat" is therefore moving into the global spotlight and this study aimed to investigate how African meat consumers of the coming generations perceive it, i.e., the urban, more educated and younger consumers. Three surveys were conducted with more than 12,000 respondents in total. The respondents came from 12 different countries (Cameroon, Congo, -DRC Democratic Republic of Congo, Ghana, Ivory Coast, Kenya, Morocco, Nigeria, Senegal South Africa, Tanzania and Tunisia). Respondents in this survey preferred the term "artificial meat". This term was therefore used throughout the survey. "Artificial meat" proved to be fairly well known in the surveyed countries as about 64% the respondents had already heard of "artificial meat." Only 8.9% were definitely willing to try "artificial meat" (score of 5 on a scale of 1–5) mostly males between 31 and 50 years of age. Furthermore, 31.2% strongly agreed that "artificial meat" will have a negative impact on the rural life (score of 5 on a scale of 1–5) and 32.9% were not prepared to accept "artificial meat" as a viable alternative in the future but were still prepared to eat meat alternatives. Of all the results, we observed significant differences in responses between respondents' countries of origin, age and education level with interactions between these factors for willingness to try. For instance, the richest and most educated countries that were surveyed tended to be more willing to try "artificial meat." A similar pattern was observed for willingness to pay, except that gender had no significant effect and age had only a small effect. One major observation is that a large majority of respondents are not willing to pay more for "artificial meat" than for meat from livestock.

KEYWORDS

consumer survey, cultured meat, cell-based food, food security, willingness to engage, livestock

## Introduction

The African population is expected to reach about 2.5 billion people in 2050. About 80% of this increase will occur in cities, with nearly 1.5 billion Africans living in urban areas (1). This
increase in urban population along with increased income is set to
increase the demand for animal-sourced food (2-4).

The livestock sector in some African countries is the fastest
growing agricultural subsector (5). It contributes not only to food and
nutrition security but also to economic growth by providing important
foreign exchange through increased trade within and between African
countries, as well as with other regions, such as the Middle East (6).
Africa's livestock accounts for one third of the world's livestock
population (3) and about 40% of agricultural GDP in Africa, ranging
from 10 to 80% depending on the country (6).

Unfortunately, African livestock farming systems are less efficient and productive than their counterparts in more developed countries with smallholders being the main suppliers of animal-derived food (6). These smallholders are also far from markets and depend on abattoirs with limited infrastructures, thereby making it difficult to meet the growing demand for meat (7).

Between 2018 and 2020, one African person consumed on average 13 kg of meat per year, with chicken being the most consumed at 5.75 kg per capita. By 2030, Africa's meat consumption is expected to increase by 30% and growth in consumption will outpace the expansion of domestic production (7), and the amount of meat consumed is expected to increase to 26 kg of meat in 2050 (6, 8). Consumption patterns across Africa vary significantly; some countries consume as little as 10 kg of meat per person, around half of the continental average. Countries with higher incomes such as South Africa, consume between 60–70 kg of meat per person (9).

In addition to this demographic pressure, livestock farming
systems across Africa will have to cope with climate change and
develop sustainable methods of production. African livestock
production already has a significant impact on the environment (10).
More than 70% of agricultural greenhouse gas emissions in Africa
comes from the livestock sector, dominated by enteric methane (CH4)
emissions (3).

Furthermore, the most significant environmental impacts and
nutritional issues associated with animal-sourced food consumption
are predicted to occur in Africa and as well as in other low- and
middle-income countries of the World (11). It will therefore be a
challenge for Africa to produce meat quantitatively and qualitatively
for its population. Consequently, there is a huge opportunity for the
private sector due to the continent's swelling dietary needs. There will
be a need for the private sector to invest in veterinary services, drugs,
vaccines, animal feed and infrastructures. Smallholders, with limited
production resources, cannot reach these objectives.

Given this context, and especially with regard to the expected
environmental challenge and the growing demand for animal protein
in Africa, “artificial meat” appears to be a viable solution as suggested
by its proponents. This novel food product makes use of ground-
breaking technologies such as tissue culture and bioreactor
engineering to increase the production of meat alternatives that may
become a threat to the conventional meat industry (12, 13). “Artificial
meat” is produced by *in vitro* tissue or cell culture, or by three
dimensional (3D) printing of meat (14). “Artificial meat” currently
faces its own problems, such as technological barriers, sensory,
nutritional, health and safety challenges, in order to be fully accessible
to developing food meat markets (15, 16).

“Artificial meat” is a technical revolution, but it could also
be considered as a potential economic and societal revolution, which
could disrupt the traditional meat sector (17). Consumer acceptance

of this novel product has been studied in many European (18–22),
American (23, 24) and Asian countries (25), but little is known about
the potential acceptance of “artificial meat” in African countries,
despite the world’s greatest challenges in terms of meat demand,
climate issues and socio-economic challenges as described above.

The aim of this study is therefore to explore the responses of African consumers of the next generations (i.e., mainly urban, more educated and younger consumers) to relevant questions in order to investigate their attitudes, outlook, potential acceptance, and willingness to engage with “artificial meat,” and to provide insight into the factors that may lead to the acceptance of “artificial meat” in the general context of Africa.

Materials and methods

Design of the questionnaire

Three surveys were conducted. All surveys adhered entirely to the ESOMAR (European Society for Opinion and Market Research) guideline for ethical online research (ESOMAR, 2011). Indeed, all respondents had to give their explicit informed consent to take part in the survey and their personal data was protected. In addition, respondents' data was collected in an anonymous way with a "do not wish to answer" option and with no personally identifiable information. This research was conducted in accordance with the published guidelines of the countries in which it was performed with, when required, the approval of ethics committees (such as in Brazil: CAAE number: 37924620.5.0000.5404 (23)).

As an introduction to all the surveys, basic information on
“artificial meat” was provided with a small text and an illustration to
avoid confusion with any other type of “artificial meat,” e.g., from plant
proteins (Figure 1). In at least one question, different wordings (such
as “cell-based meat,” “cultured meat,” “lab meat,” etc) were used for
better understanding and to avoid any bias in the answers. In this
specific question, respondents were asked for the best wording of this
new product.

The three surveys were organized around six sets of questions:

1. Socio-demographic information: this involved the collection of information such as gender, age, education level, area of work, net monthly income, meat consumption, and familiarity with “artificial meat” (Supplementary material - Questions 1 to 8).

2. General questions: These questions were asked as a preamble regarding the respondents' food purchasing criteria and whether they had ever heard of this product (Supplementary material - Questions 9–10).

3. Attitude towards societal challenges: the objective here was to collect information on the respondents' attitude towards the societal challenges facing conventionally produced meat (meat from conventionally raised farm animals) and “cell-based meat,” with regard to ethical, environmental, traditional meat industry, and rural life issues (Supplementary material - Questions 11 to 16).

4. Characteristics of the product. Questions were related to the perception of healthiness and eating quality of “artificial meat” (Supplementary material—Questions 17–18).
<figure><img src="image_12.png" /><figcaption>FIGURE 1
Introduction of "artificial meat" provided to respondents adapted from (23).</figcaption></figure>

5. **Potential interests:** these questions aimed to evaluate consumer acceptance of “artificial meat.” They also had the aim to capture personal perceptions of this novel food compared to conventionally produced meat, including a question on how to name this product (Supplementary material—Questions 19 to 27).

6. **Development strategies:** the respondents were asked about future development strategies for the marketing of “cell-based meat” (Supplementary material—Questions 28 to 32).

Whereas the third survey included the six groups of questions, the survey 1 included the 4 first groups, and survey 2 the 2 last.

## Data collection

Respondents were randomly recruited using the KASI Insight platform. KASI Insight is an African-based consulting firm that conducts surveys for market research. Kasi insight implemented a computer assisted self-interviewing (CASI) process as its main methodology which is conducted at respective connected locations (businesses, community centers, etc.) which offer respondents access to complete the survey on a desktop, without incurring data costs. CASI is a technique for survey data collection in which the respondent uses a computer to complete on-line the survey questionnaire without an interviewer administering it to the respondent. This assumes the respondent can read well (enough) and understand either English or French.

A primary rationale for CASI is that some questions are so sensitive that if researchers hope to obtain an accurate answer, respondents must use a highly confidential method of responding.

The CASI process includes multiple quality controls, including trained interviewers available at the interview sites to assist respondents when they have questions. The CASI process also include: (1) Cross-checking and authentication: All completed surveys are checked and 20% of questionnaires are cross-checked. (2) Verification of data entry: validation and verification include predefined survey rules and matching processes.

Data were collected through monthly surveys. The target population for these surveys was the adult population of major urban cities in each of the participating countries. In most of these countries, this population is representative of the economically active population, and the main decision makers in household purchases. Rural residents were therefore excluded from the surveys.

Survey responses were voluntary. Each interview took an average of 15 to 20 min. Interviews were conducted in English and French. No quotas were imposed on the survey, allowing city residents of all demographics a fair chance to be included in the survey.

The first and second surveys were conducted in the main urban centers of 12 African countries: Cameroon (Yaoundé and Douala), Congo (Brazzaville), DRC Congo (Kinshasa), Ghana (Accra, Labadi, Teshie, Nunua, Kumasi), Ivory Coast (Abidjan, Yopougon, Angre, Abodo, Bouake, Williamsville), Kenya (Nairobi, Mombasa, Nakuru), Morocco (Rabat, Casablanca), Nigeria (Lagos, Abuja, Port harcourt, Abia), Senegal (Dakar), South Africa (Johannesburg, Cape Town), Tanzania (Dar Salaam, Arusha) and Tunisia (Tunis).

The complete survey process flow is shown in Figure 2. The first survey was constituted of 21 questions. This survey (Supplementary material-Questions 1 to 19, then 29 and 31) analyzed environmental and ethical concerns of the respondents (global warming, animal welfare, animal suffering, and slaughter) as well as the disadvantages associated with conventional meat as perceived by these respondents (limited agricultural resources and population growth).

The second survey (Supplementary material-Questions 1 to 7 and 20 to 32, excluding 29) analyzed respondents' acceptance of “artificial meat” through their willingness to try (WTT), willingness to pay (WTP), and willingness to eat regularly (WTE).

The third survey was a combination on the first 2 surveys which was constituted of 33 questions. This survey analyzed both aspects (societal challenges and respondent acceptance) with fewer respondents (n=1,111) from only 5 countries (Cameroon, Ghana, Kenya, Morocco, and South Africa) to represent different parts of Africa (Central, West, East, North, and South, respectively) and with the greatest potential to obtain more responses in a limited time period due to time constraints. The results of the two surveys were compared to assess the replicability of the methodology.

An average sample of 500 people per country was surveyed, targeting men and women over the age of 18. Because the population size of these sampled cities is generally greater than 500,000, the minimum recommended sample size for this population is 377, and we collected between 728 and 1,345 answers per country (for Cameroon, Ghana, Kenya, Morocco and South Africa) after pooling data from the first or second survey on one hand and from the third survey on the other hand in order to explore respondents' opinions.

Pooling two or more cross-sectional survey data sets (i.e., stacking comparable data sets on top of one another) can serve different
<figure><img src="image_13.png" /><figcaption>FIGURE 2
Survey process flow.</figcaption></figure>

purposes including to increase the sample size in hopes of improving the precision of a point estimate. The latter purpose is especially common when making inferences on a subgroup, or domain, of the target population insufficiently represented by a single survey data set (26). Consequently, answers to questions numbers 25 to 28 related to WTT, WTE and WTP for 5 countries (Cameroun, Ghana, Kenya, Morocco and South Africa) were pooled to be analyzed together. For all other questions, results were compared between surveys without pooling to take into account data from the 12 countries from surveys 1 and 2.

## Statistical analyses

The data were analyzed using R software (Version 4.0.2) (27). For most of the questions, respondents were asked to provide responses on a Likert-scale: strongly disagree (score 1), somewhat disagree (score 2), undecided (score 3), somewhat agree (score 4), and strongly agree (score 5), with the exception of a few qualitative variables which were then coded as quantitative variables to assess the influence of socio-demographic variables on WTT, WTP and WTE. The chi-2 test was used to compare the distribution of results between the two surveys.

WTT was coded quantitatively from “Definitely not” = 1 to “Definitely yes” = 5 and WTP: from “Much less” = 1 to “Much more” = 5. For WTE, the question was initially asked with multiple responses and was coded as “1” (for respondents who answered: In restaurants, At home, In prepackaged ready-to-eat meals, I do not want to eat “artificial meat” regularly, Other) and “2” (do not want to eat “artificial meat” regularly).

The initial investigations targeted the relationships between socio-demographic information and variables of willingness by means of ANOVA supplemented with a pairwise comparison between significant groups using Tukey HSD (by the R package “agricolae”). The one-way analysis of variance (ANOVA) was used to highlight any statistically significant differences between the means of the different groups corresponding to the levels of each factor of variation studied. The model was performed with the data collected from the second and

third survey and for 5 different countries (Cameroon, Ghana, Kenya, Morocco and South Africa) with the different socio-demographic factors: $y = Country + Gender + Age + Education + Income + Country \times Gender + Country \times Age + Country \times Education + Country \times Income + Gender \times Age + Gender \times Education + Gender + Income + Age \times Education + Age \times Income + Income \times Age$. ANOVA was run a second time with only the significant factors and significant interactions included in the model. Differences were considered significant at a value of *p* < 0.05. *Lsmeans* (Least-Squares Means which are means that are computed based on a linear model such as ANOVA) were calculated in order to detect statistical differences across the different groups (28).

After performing the ANOVA, the effect size was investigated. Effect sizes could be used beyond significance tests (*p*-values), because they estimate the magnitude of effects, independent from sample size (29). The effect size was evaluated in R software (Version 4.0.2) with the package “sjstats.” The effect size was calculated by eta squared -denoted as $\eta^2$. The eta squared corresponds to the total variability in the dependent variable accounted for by the variation in the independent variable. It is calculated as the ratio of the sum of squares for each group level to the total sum of squares. It can be interpreted as percentage of variance accounted for by a variable (30). The effect sizes are reported in the *Supplementary material*. Effect sizes varied between 0.01 and 0.02. for the different variables, which is considered to be low to moderate (30) (< 0.01 corresponds to a Small effect size, between 0.01 and 0.06 to a medium effect size and > 0.14 correspond to a large effect size).

In addition, a Principal Component Analysis (PCA) (by the R packages “FactoMineR” and “Factoextra”) was performed with the quantitative data of the third survey for which all responses from the same respondents were available to represent and model multidimensional point cloud surveys, showing whether relationships exist between the variables as previously done with similar data (19). PCA allows for the calculation of new variables, called principal components, which capture the variability in the data. This enables information to be described with fewer variables than originally present. The principal components are linear combinations of the original variables. The first principal
component is the combination of variables that explains the greatest amount of variability in the data. The second and subsequent principal components describe the maximum amount of remaining variability and must be independent (orthogonal) between them and to the first principal component.

## Results

The sociodemographic characteristics of the respondents of the three surveys are detailed in Table 1. The result description follows the outline below:

- Comparison of socio demographics data between the 3 surveys (questions 1 to 8).

- Comparison of results between survey 1 (in 12 countries) and survey 3 (in 5 countries) concerning respondents' perspective in relation to societal challenges (questions 11 to 16 in common between surveys 1 and 3).

- Comparison of results between survey 1 (in 12 countries) and survey 3 (in 5 countries) concerning the respondents' potential interest in "artificial meat" (questions 19 to 27).

- Comparison of results between survey 2 (in 12 countries) and survey 3 (in 5 countries) (questions 19 to 31 in common between both surveys) concerning the potential acceptance of "artificial meat" by the respondents. Then, analysis of pooled results of WTT, WTE and WTP from 5 counties in common between surveys 2 and 3 (questions 25 to 28).

- Potential drivers of acceptance of "artificial meat" from data of survey 3 (answers to all questions from respondents of 5 countries).

A summary of the respondents' profile and answers is shown in Figure 3.

## Socio-demographic data for all respondents

The first survey had 5,485 respondents, the second survey had 5,528 (the percentages of respondents per country in both surveys varied between 7 and 10%) and the 3rd survey had 1,111 responses (the percentages of respondents per country varied between 19 and 20%). The socio-demographic characteristics of the respondents for all surveys are shown in Table 1.

All surveys had the same structure for gender and age with a majority being males representing 50.3, 52.9 and 58.2% of respondents in surveys 1, 2 and 3, respectively, and respondents between 31 and 50 years of age being the largest group (68.3%, 65%, and 49% respectively).

Most of the respondents were graduates in all surveys (58.7%, 56.6%, and 61.5% respectively) and had a monthly income of less than 1,500 USD (58.5%, 57.5%, and 43.6% respectively) (Table 1).

The respondents ate meat regularly, several times a week in surveys 1 and 3 (38% in survey 1 and 38.2% in survey 3) and had heard of "artificial meat" (63.9% in survey 1 and 55.3% in survey 3) (data not shown).

In both surveys, most of the respondents were not scientists, and the majority did not work in the meat sector (54.9% in survey 1 and 50.5% in survey 3) (data not shown).

## Respondents' perspective in relation to societal challenges

For all questions related to societal challenges (Table 2), no statistical difference was observed between the results of the two surveys which addressed these issues.

In surveys 1 and 3, most of the respondents disagreed with the idea that livestock can cause environmental problems (43.3% of responses

<table><caption>TABLE 1 Distribution of responses with respect to socio-demographics.</caption><thead><tr><th rowspan="2">Question</th><th rowspan="2">Response option</th><th colspan="2">Survey 1</th><th colspan="2">Survey 2</th><th colspan="2">Survey 3</th></tr><tr><th>Number of responses</th><th>Percentage (%)<sup>a</sup></th><th>Number of responses</th><th>Percentage (%)<sup>a</sup></th><th>Number of responses</th><th>Percentage (%)<sup>a</sup></th></tr></thead><tbody><tr><td rowspan="2">Gender</td><td>Female</td><td>2,725</td><td>49.7</td><td>2,602</td><td>47.1</td><td>464</td><td>64,741.8</td></tr><tr><td>Male</td><td>2,760</td><td>50.3</td><td>2,926</td><td>52.9</td><td>647</td><td>58.2</td></tr><tr><td rowspan="3">Age</td><td>18–30 years</td><td>1,583</td><td>28.9</td><td>1763</td><td>31.9</td><td>517</td><td>46.5</td></tr><tr><td>31–50 years</td><td>3,745</td><td>68.3</td><td>3,593</td><td>65.0</td><td>544</td><td>49.0</td></tr><tr><td>&gt;51 years</td><td>157</td><td>2.8</td><td>172</td><td>3.1</td><td>50</td><td>4.5</td></tr><tr><td rowspan="5">Education</td><td>Primary school</td><td>216</td><td>4.0</td><td>205</td><td>3.7</td><td>27</td><td>2.4</td></tr><tr><td>High school</td><td>412</td><td>7.5</td><td>410</td><td>7.4</td><td>52</td><td>4.7</td></tr><tr><td>Undergraduate</td><td>149</td><td>2.7</td><td>168</td><td>3.1</td><td>25</td><td>2.25</td></tr><tr><td>Technical Training</td><td>1,490</td><td>27.1</td><td>1,615</td><td>29.2</td><td>324</td><td>29.2</td></tr><tr><td>Graduate</td><td>3,218</td><td>58.7</td><td>3,130</td><td>56.6</td><td>683</td><td>61.5</td></tr><tr><td rowspan="2">Monthly income</td><td>Under USD1,500</td><td>3,208</td><td>58.5</td><td>3,179</td><td>57.5</td><td>484</td><td>43.6</td></tr><tr><td>More than USD1,500</td><td>2,277</td><td>41.5</td><td>2,349</td><td>42.5</td><td>627</td><td>56.4</td></tr><tr><td colspan="2">Total</td><td>5,485</td><td>100</td><td>5,528</td><td>100</td><td>1,111</td><td>100</td></tr></tbody></table>

<footnote><sup>a</sup>Percentage of people who answered the questionnaire.</footnote>
<figure><img src="image_14.png" /><figcaption>FIGURE 3
Respondents' profile summary towards "artificial meat".</figcaption></figure>

were 1 and 2 on a scale of 0–5 point in survey 1 and 50% in survey 3) and ethical problems (48.8% in survey 1 and 52.1% in survey 3).

The respondents in both surveys also disagreed with the reduction of meat consumption as a solution to the problems caused by on-farm breeding (39.3% of responses were 1 or 2 in survey 1 and 48.3% in survey 3). The respondents disagreed on the fact that “artificial meat” would be healthier (36.7% of responses were 1 or 2 on scale of 0–5 in survey 1 and 55.1% in survey 3) and tastier (40.1% of responses were 1 or 2 on a scale of 0–5 in survey 1 or 52.3% in survey 3) than conventional meat. The respondents in both surveys agreed that “artificial meat” would have a negative impact on rural life (42.1% of responses were 4 or 5 in survey 1 and 27% in survey 3).

Some respondents expressed some emotional resistance to “artificial meat” in both surveys (22.9% of responses were 4 or 5 in survey 1 and 14.2% in survey 3) (Table 2).

## Potential interest in "artificial meat"

In both surveys, respondents considered price (18.8% in survey 1 and 20.1% in survey 3) as the most important criterion when purchasing meat, followed by meat quality (17.2% in survey 1 and 15.8% in survey 3) (Table 3). Some respondents in both surveys considered “artificial meat” as safe (14.2% in survey 1 and 18.1% in survey 3).

When asked how they perceive “artificial meat,” respondents from both surveys followed the same pattern. Of the three options proposed, most consumers found it “fun and/or intriguing” in both surveys with 59.1% in the first survey and 44.7% in the third one. In the first survey, 22.7% found it “promising and/or acceptable” while 18.3% found it “absurd and/or disgusting.” In the third survey, the figures were 39.3% and 15.9%, respectively.

The largest proportion of respondents in survey 1 are consumers of both meat and meat alternatives and did not consider artificial meat as a viable meat alternative (they represent 32.9% in Survey 1 and 25.8% in Survey 3), while the largest proportion in survey 2 did not eat meat substitutes and considered “artificial meat” as a viable alternative (they represent 33.4% in survey 3 and 28.8% in survey 1, Table 3).

In both surveys, ethical concerns were the most likely to convince respondents to eat “artificial meat” (13.8% in survey 1 and 17.3% in survey 3), while safety concerns were a major reason why respondents were not willing to eat “artificial meat” (13.9% in survey 1 and 12.3% in Survey 3). In addition, a significant proportion of respondents found “artificial meat” to be unnatural (20% in survey 3 and 12.7% in survey 1, Table 3).

In both surveys, most respondents preferred to consume “artificial meat” at home (25.9% in survey 1 and 30.0% in survey 2), followed by restaurants (23.9% in survey 1 and 29.3% in survey 2) and pre-packaged ready-to-eat meat (19.9% in survey 1 and 23.6% in survey 3, Table 3).

Majority of the respondents preferred the name “artificial meat” (18%) (followed by “Clean Meat”: 13.66%; “Lab meat”: 13.36%; “Cultured Meat”: 13.22%; “Cellular Meat”: 11.13%; “In-vitro Meat”: 11.59%) and 61% agreed the product could be labelled as meat when commercialized, whereas 39% thought the opposite (data not shown).

## Potential acceptance of "artificial meat"

### Willingness to try (WTT)

In surveys 2 and 3, many respondents were willing to try “artificial meat.” Indeed, in survey 2, 39.2% were willing to try
<table><caption>TABLE 2 Respondents' perspective with respect to societal challenges in both survey 1 and survey 2.</caption><thead><tr><th rowspan="2">Question</th><th rowspan="2"></th><th colspan="5">Response (1: completely disagree—5: completely agree)</th></tr><tr><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th></tr></thead><tbody><tr><td rowspan="2">In your opinion does on-farm breeding cause important environmental issues, e.g., huge water consumption and greenhouse gas emissions?</td><td>Survey 1</td><td>794 (14.5%)</td><td>1,579 (28.8%)</td><td>1727 (31.5%)</td><td>1,138 (20.7%)</td><td>246 (4.5%)</td></tr><tr><td>Survey 2</td><td>221 (19.9%)</td><td>334 (30.1%)</td><td>370 (33.3%)</td><td>159 (14.3%)</td><td>27 (2.4%)</td></tr><tr><td rowspan="2">Do you believe that on-farm breeding can cause important ethical problems (e.g., animal suffering, animal slaughter)?</td><td>Survey 1</td><td>859 (15.7%)</td><td>1813 (33.1%)</td><td>1,527 (27.8%)</td><td>1,056 (19.3%)</td><td>229 (4.2%)</td></tr><tr><td>Survey 2</td><td>301 (27.1%)</td><td>267 (25%)</td><td>376 (33.8%)</td><td>147 (13.2%)</td><td>20 (1.8%)</td></tr><tr><td rowspan="2">In your opinion, can the potential problems of on-farm breeding be dealt with by reducing our meat consumption?</td><td>Survey 1</td><td>735 (13.4%)</td><td>1,420 (25.9%)</td><td>1717 (31.3%)</td><td>1,314 (24%)</td><td>298 (5.4%)</td></tr><tr><td>Survey 2</td><td>243 (21.9%)</td><td>293 (26.4%)</td><td>374 (33.7%)</td><td>179 (16.1%)</td><td>22 (2%)</td></tr><tr><td rowspan="2">Do you believe that if people ate Artificial meat instead of conventional meat, it would improve the welfare of animals and reduce animal suffering?</td><td>Survey 1</td><td>656 (12%)</td><td>1,246 (22.7%)</td><td>1790 (32.6%)</td><td>1,437 (26.2%)</td><td>355 (6.5%)</td></tr><tr><td>Survey 2</td><td>252 (22.7%)</td><td>276 (24.8%)</td><td>383 (34.5%)</td><td>180 (16.2%)</td><td>20 (1.8%)</td></tr><tr><td rowspan="2">Using the following rating scale, do you think that Artificial meat could negatively impact livestock farming and the meat industry (e.g., by reducing the number of jobs available?)</td><td>Survey 1</td><td>547 (10%)</td><td>1,055 (19.2%)</td><td>1,599 (29.1%)</td><td>1,764 (32.2%)</td><td>519 (9.5%)</td></tr><tr><td>Survey 2</td><td>239 (21.5%)</td><td>270 (24.3%)</td><td>343 (30.9%)</td><td>205 (18.4%)</td><td>54 (4.9%)</td></tr><tr><td rowspan="2">Do you think that Artificial meat would have a negative impact on rural life?</td><td>Survey 1</td><td>503 (9.2%)</td><td>1,098 (20%)</td><td>1,570 (28.6%)</td><td>1713 (31.2%)</td><td>600 (10.9%)</td></tr><tr><td>Survey 2</td><td>201 (18.1%)</td><td>278 (25%)</td><td>332 (29.9%)</td><td>231 (20.8%)</td><td>69 (6.2%)</td></tr><tr><td rowspan="2">To what extent do you believe that Artificial meat would be healthier & have higher nutritional value than normal meat?</td><td>Survey 1</td><td>724 (13.2%)</td><td>1,291 (23.5%)</td><td>1913 (34.9%)</td><td>1,185 (21.6%)</td><td>371 (6.8%)</td></tr><tr><td>Survey 2</td><td>292 (26.3%)</td><td>264 (23.8%)</td><td>397 (35.7%)</td><td>132 (11.8%)</td><td>26 (2.3%)</td></tr><tr><td rowspan="2">In your opinion do you believe that Artificial meat is tastier compared to normal meat.</td><td>Survey 1</td><td>1,032 (18.8%)</td><td>1,171 (21.3%)</td><td>1,898 (34.6%)</td><td>1,095 (20%)</td><td>288 (5.2%)</td></tr><tr><td>Survey 2</td><td>284 (25.6%)</td><td>297 (26.7%)</td><td>399 (35.9%)</td><td>118 (10.6%)</td><td>13 (1.2%)</td></tr><tr><td rowspan="2">In your opinion would you say that you have emotional resistance to trying out Artificial meat (e.g., disgust or nervousness)?</td><td>Survey 1</td><td>548 (9.9%)</td><td>1,516 (27.4%)</td><td>2,197 (39.7%)</td><td>853 (15.4%)</td><td>414 (7.5%)</td></tr><tr><td>Survey 2</td><td>294 (26.5%)</td><td>288 (25.9%)</td><td>371 (33.4%)</td><td>112 (10.1%)</td><td>46 (4.1%)</td></tr></tbody></table>

"artificial meat" (8.9% definitely try and 30.3% probably try), 36.6% were unsure or not yet decided whether they would try "artificial meat" and 24.2% were not willing to try "artificial meat" (14.7% will probably not try, 9.5% will definitely not try). In survey 3, a majority (55.2%) is willing to try "artificial meat" (26.1% will definitely not, 29.1% will probably try) as in the first survey compared to 18.36% who are unwilling to try (4.7% definitely not, 13.7% probably not), with 26.5% of respondents being undecided (Table 3).

In survey 3, WTT was also significantly affected by the perceived impacts of conventional meat on livestock, rural life, the environment, ethics (p < 0.0001) and the interaction between the country and the frequency of meat consumption (p < 0.0001).

The pooled data for the 5 countries in common between surveys 2 and 3 was analyzed for 5 countries (Cameroun, Ghana, Kenya, Morocco and South Africa). The results showed that WTT differed significantly according to country, age, income and education (Figure 4; Table 1,). Interactions were significant between country
<table><caption>TABLE 3 Potential interest in "artificial meat" in both survey 2 and survey 3.</caption><thead><tr><th rowspan="2">Question</th><th rowspan="2">Response options</th><th colspan="2">Survey 1 and 2 (n=11,013)</th><th colspan="2">Survey 3 (n=1,111)</th></tr><tr><th>Number of responses</th><th>Percentages (%)</th><th>Number of responses</th><th>Percentages (%)</th></tr></thead><tbody><tr><td rowspan="4">Which of the following would you say are important considerations for you when you go to shop for meat? Which of the following would you say are important considerations for you when you go to shop for meat? (multiple choice question)</td><td>Ethics of how the meat was produced, e.g., were the animals allowed to roam freely</td><td>923</td><td>5.5</td><td>491</td><td>12.5</td></tr><tr><td>Environmental impact of the food/ meat during its production</td><td>1,572</td><td>9.4</td><td>501</td><td>12.7</td></tr><tr><td>Price</td><td>3,150</td><td>18.8</td><td>792</td><td>20.1</td></tr><tr><td>Quality of the meat (taste, juiciness, tenderness) ...</td><td>2,884</td><td>17.2</td><td>624</td><td>15.9</td></tr><tr><td rowspan="4">Would you accept Artificial Meat as a viable alternative to normal meat in the future (Just like other meat substitutes like Soy proteins)?</td><td>Appearance of the meat (e.g., its color, freshness)</td><td>2,220</td><td>13.3</td><td>483</td><td>12.3</td></tr><tr><td>Yes, I already eat meat substitutes or meat alternatives</td><td>837</td><td>15.3</td><td>278</td><td>25.1</td></tr><tr><td>Yes, but I do not eat meat substitutes or meat alternatives</td><td>1,579</td><td>28.8</td><td>371</td><td>33.4</td></tr><tr><td>No, but I eat meat and/or meat alternatives</td><td>1,804</td><td>32.9</td><td>286</td><td>25.7</td></tr><tr><td rowspan="6">Which of the following reasons would be most likely to persuade you to try Artificial meat?ª</td><td>No, I do not eat meat substitutes and/or meat alternatives</td><td>1,265</td><td>23.1</td><td>176</td><td>15.8</td></tr><tr><td>As a solution to feed the ever-growing human population</td><td>1,647</td><td>12.2</td><td>445</td><td>14.4</td></tr><tr><td>It has more attractive pricing than conventional meat</td><td>1,646</td><td>12.2</td><td>509</td><td>16.4</td></tr><tr><td>Ethics - it improves the wellbeing of animals and reduces animal slaughter</td><td>1,861</td><td>13.8</td><td>535</td><td>17.3</td></tr><tr><td>Less risk of Zoonosis (disease that can be transmitted from animals to people, e.g., Foot &amp; mouth disease)</td><td>1,630</td><td>12.1</td><td>462</td><td>14.9</td></tr><tr><td>Attractiveness of high-tech technologies</td><td>1,371</td><td>10.1</td><td>330</td><td>10.6</td></tr><tr><td></td><td>Curiosity</td><td>1,584</td><td>11.7</td><td>260</td><td>8.4</td></tr></tbody></table>

(Continued)
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th rowspan="2">Question</th><th rowspan="2">Response options</th><th colspan="2">Survey 1 and 2 (n=11,013)</th><th colspan="2">Survey 3 (n=1,111)</th></tr><tr><th>Number of responses</th><th>Percentages (%)</th><th>Number of responses</th><th>Percentages (%)</th></tr></thead><tbody><tr><td rowspan="7">And which of the following would be the most likely reasons why you would not be willing to try Artificial meat?ª</td><td>It is unnatural</td><td>1,756</td><td>12.7</td><td>47</td><td>20.0</td></tr><tr><td>It is less tasty/appealing</td><td>1,587</td><td>11.4</td><td>15</td><td>6.4</td></tr><tr><td>I am worried about its safety</td><td>1,929</td><td>13.9</td><td>29</td><td>12.3</td></tr><tr><td>It is more expensive than normal meat</td><td>1,667</td><td>12.0</td><td>15</td><td>6.4</td></tr><tr><td>I am reluctant (feel disgusted/ nervous)</td><td>1,584</td><td>11.4</td><td>22</td><td>9.4</td></tr><tr><td>It has a negative impact on local farmers</td><td>1,546</td><td>11.2</td><td>22</td><td>9.4</td></tr><tr><td>Negative impact on local farmers & their jobs</td><td>1,426</td><td>10.3</td><td>28</td><td>11.9</td></tr><tr><td rowspan="7">Which of the following statements would you associate with Artificial meat?ª</td><td>I do not trust laboratories and artificial meat start-up companies</td><td>966</td><td>7.0</td><td>37</td><td>15.7</td></tr><tr><td>Adequate nutrition</td><td>1,241</td><td>9.0</td><td>468</td><td>13.5</td></tr><tr><td>Tasty /tastes similar to real/normal meat</td><td>1,527</td><td>9.2</td><td>497</td><td>14.3</td></tr><tr><td>Safety</td><td>1,923</td><td>14.0</td><td>626</td><td>18.1</td></tr><tr><td>Less as a solution to feed the ever-growing human population</td><td>1,548</td><td>11.3</td><td>452</td><td>13.0</td></tr><tr><td>It is less expensive or has better pricing than conventional meat</td><td>1,354</td><td>9.9</td><td>406</td><td>11.7</td></tr><tr><td>It has a smaller environmental footprint</td><td>1,267</td><td>9.2</td><td>327</td><td>9.4</td></tr><tr><td rowspan="4">In which of the following cases would you be most likely to eat Artificial meat regularly?</td><td>Leads to the reduction of farming</td><td>1,161</td><td>8.5</td><td>264</td><td>7.6</td></tr><tr><td>Leads to no farming</td><td>1,038</td><td>7.6</td><td>218</td><td>6.3</td></tr><tr><td>At the restaurant</td><td>1,323</td><td>23.9</td><td>462</td><td>29.3</td></tr><tr><td>At home</td><td>1,431</td><td>25.9</td><td>474</td><td>30.0</td></tr><tr><td></td><td>In prepackaged ready-to-eat meals (e.g., lasagna...)</td><td>1,101</td><td>19.9</td><td>372</td><td>23.6</td></tr><tr><td></td><td>I do not want to eat artificial meat regularly</td><td>821</td><td>14.8</td><td>141</td><td>8.9</td></tr><tr><td></td><td>Other</td><td>852</td><td>15.4</td><td>129</td><td>8.2</td></tr></tbody></table>

(Continued)
<table><caption>TABLE 3 (Continued)</caption><thead><tr><th rowspan="2">Question</th><th rowspan="2">Response options</th><th colspan="3">Survey 1 and 2 (n=11,013)</th><th colspan="2">Survey 3 (n=1,111)</th></tr><tr><th>Number of responses</th><th>Percentages (%)</th><th>Number of responses</th><th>Percentages (%)</th></tr></thead><tbody><tr><td rowspan="5">Now that you have learnt a little bit more about Artificial meat, what do you think about it?</td><td>It is promising and / or acceptable</td><td>1,257</td><td>22.7</td><td>437</td><td>39.3</td></tr><tr><td>It is fun and/or intriguing</td><td>3,262</td><td>59</td><td>497</td><td>44.7</td></tr><tr><td>It is absurd and/or disgusting</td><td>1,009</td><td>18.2</td><td>177</td><td>15.9</td></tr><tr><td>In the short term - 1 to 5 years</td><td>1,208</td><td>21.8</td><td>408</td><td>36.7</td></tr><tr><td>In the medium term - 6 to 15 years</td><td>2,381</td><td>43.0</td><td>345</td><td>31.0</td></tr><tr><td rowspan="2">Artificial meat is already available in some countries, when do you think artificial meat will be widely accepted?</td><td>In the long term - more than 16 years</td><td>1,124</td><td>20.3</td><td>261</td><td>23.5</td></tr><tr><td>Never</td><td>815</td><td>14.7</td><td>97</td><td>8.7</td></tr></tbody></table>

*Only major answers are indicated.

and age, country and income, country and education, gender and income and education and income (Table 1).

South Africa came out as the country that was the most willing to try “artificial meat” while Ghana was the least willing to do so (Figure 4).

Those most willing to try were aged between 31 and 50 and had revenue less than $1,500 (data not shown). Respondents with a technical education were more willing to try (Figure 4).

## Willingness to eat (WTE) regularly

Most respondents were willing to eat “artificial meat” on a regular basis (85.3%) in survey 2 as well as in survey 3 (87.22%).

In survey 3, WTE was also significantly affected by the perceived impacts of conventional meat on livestock (p < 0.0001), rural life (p < 0.0001), the environment (p < 0.006), ethics (p < 0.002) as well as the frequency of meat consumption (p < 0.004).

The pooled data for the 5 countries in common between survey 2 and 3 showed that WTE significantly according to country and age (Figure 5; Table 2). Interactions were significant between country and age, country and gender, country and income, country and education and education and income (Table 2).

Kenya was the most willing to eat “artificial meat” but did not differ significantly from South Africa and Cameroon (Figure 5).

Those most willing to eat were over 51 years of age but did differ significantly from respondents aged 31–50. WTE was higher for males with higher incomes and for females with low incomes ($3,000–4,000 and $4,000 or more and $1,500 or more for females). These 3 groups did not differ significantly. Respondents with a technical education were more willing to try.

## Willingness to pay (WTP)

In survey 2, 60.7% of respondents were willing to pay less than for conventional meat (36.4% were willing to pay less and 24.3% were willing to pay much less than for conventional meat) while 12.7% were willing to pay more (8.6% more and 4.1% much more than for conventional meat) and 26.7% were willing to pay the same price as for conventional meat.

The same pattern was observed in survey 3, 70.0% of the respondents were willing to pay less than for conventional meat (36.4% were willing to pay less and 33.6% were willing to pay much less than for conventional meat) while 10.9% were willing to pay more (7.9% more and 3.0% much more than for conventional meat) while 19.1% were willing to pay the same price as for conventional meat.

Pooled results of the two surveys are indicated in Figure 6.

In survey 3, WTP was also significantly affected by the perceived impacts of conventional meat on livestock, rural life, the environment, ethics (p < 0.0001) as well as the frequency of meat consumption (p = 0.004).

Analyses of the data pool for 5 countries in common between survey 2 and 3 showed that WTP differed significantly according to country and education (Figure 7; Table 3). Interactions were significant between country and age, country and income, and education and income (Table 3).

The country that was the most willing to pay was South Africa and the least willing to pay was Kenya (Figure 7).
<figure><img src="image_15.png" /><figcaption>**FIGURE 4**
Significant factors affecting willingness to try "artificial meat."</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>**FIGURE 5**
Significant factors affecting the willingness to eat "artificial meat."</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>**FIGURE 6**
Percentages for willingness to pay for "artificial meat".</figcaption></figure>
<figure><img src="image_18.png" /><figcaption>FIGURE 7
Significant factors affecting the willingness to pay for "artificial meat."</figcaption></figure>

<figure><img src="image_19.png" /><figcaption>FIGURE 8
Principal Component Analysis of the main quantitative variables studied in survey 3.</figcaption></figure>

## Potential drivers of acceptance of "artificial meat"

A PCA was performed to investigate the underlying motives and barriers to acceptance of “artificial meat” by respondents, with all quantitative variables of survey 3 for which all responses from the same respondents were available (Figure 8) (12 questions).

The PCA revealed 2 groups of correlated variables on either side of the vertical axis. WTT was positively correlated with “artificial

meat” perceived as a viable alternative to meat and its perceived timeline for availability. WTP was positively correlated with societal challenges (concerns about the ethics and environmental problems caused by on-farm breeding, animal suffering, impact on rural life and livestock) and negatively correlated with emotional resistance.

In this analysis, WTE was negatively correlated with WTT (r = -0.40; *p* < 0.001) but very slightly correlated to WTP (r = 0.04; *p* < 0.05). WTT was negatively correlated to WTP (r = -0.30; *p* < 0.001). Emotional resistance was negatively correlated with WTT (r = -0.50; *p* < 0.001) but positively correlated with WTE and WTP (r = 0.30 for both; *p* < 0.001).
# Discussion

## What factors will affect the acceptance of "artificial meat" across Africa?

The acceptance of “artificial meat” depends on several factors such as age, income and education.

Contrary to other studies which evidenced a gender effect (23–25, 31), in this study, gender did not have an effect on the acceptance (WTE & WTT) of “artificial meat,” as argued by other studies that did not find an association between gender and food neophobia (32–34). This contradiction could be explained by the fact that our survey was not fully representative of the African population in terms of urban and rural populations, with 58% of Sub-Saharan Africa being rural and only about 30% in North Africa (35, 36). In addition, in previous surveys, different interactions of the effect of gender with other effects have been observed, which explains why the effect of gender is not consistent (23, 37).

According to the PCA, WTP could be associated with positive acceptance of “artificial meat.” WTT was negatively correlated with WTP and WTE. This result is counterintuitive as one would expect WTT to be a precursor to WTE. This result may indicate that WTT may have different motives from WTP and WTE. The main motive for WTT would be curiosity (19), while WTP and WTE are motivated by ethics and environmental issues related to livestock, as well as price, as discussed below. This has also been observed in other studies that like in Taiwan where consumers are willing to buy plant-based meat alternatives for sustainable development of the environment despite their high prices. This study concluded that consumers’ perception of green value will affect their attitude toward green products (38, 39). It was also suggested that that consumers who are highly concerned about animal welfare and environmental issues are likely to consider livestock meat production as causing more ethical and environmental problems than their counterparts, which may affect negatively their consumption of meat or positively their consumption of meat alternatives (40).

Other factors that have affected African consumers’ perspective on “artificial meat” are also discussed.

### Age

Age was the most important factor in our study. Other studies have shown that “artificial meat” is more attractive to younger respondents in France, Brazil and Germany (19, 23, 41). In our study, older respondents (>30 years) were the most willing to accept (WTT & WTE) “artificial meat” but age had no influence on WTP. This is in line with results in China where young respondents had the lowest WTT (25). This is also in line with the Australian survey of the Generation Z (18–24 years of age) who feared betraying Australia as a meat-eating nation (42). In Africa, livestock entrepreneurship is a self-employment option where unemployment rates are still high for younger populations (43). However, these results can be mitigated because our survey did not represent younger respondents very well. Indeed, 40% of the African population is under 15 years of age (44) and this age group was not included in the survey.

### Country

Our survey suggests that although there is a general positive outlook on “artificial meat,” the extent of this potential acceptance is

not the same in all countries. This indicates the diversity of African consumers in terms of food behavior, income, gender, age and education, as all of these differ in these countries. In our study, consumers from South Africa were the most willing to try and pay for “artificial meat,” with no difference to Kenyan consumers who were the most willing to eat. In a previous study that surveyed 10 countries, South Africa was shown to have a high level of acceptance of “artificial meat,” second only to Mexico (21). The suggested reason by this study was that South Africa has been influenced from other countries such as UK or the Netherlands. This observation may also be due to the various migrants in the country. Indeed, South Africa has the highest number of migrants in its population, followed by Kenya, Cameroon, Ghana and Morocco (45, 46). The fact that Ghana and Morocco have the least migrant populations could explain why they are the least accepting of “artificial meat.”

These countries with a higher percentage of migrant population are therefore more open to novel foods and will consequently have higher levels of acceptance of “artificial meat.” South Africa differs from a number of other African countries due to the strong influence of European cuisine (21). The migrant population from other countries may differ between South Africa and other African countries. Indeed, African immigration is mostly characterized by movements within the continent (47), with the exception of South Africa which has had a more western migrant population compared to other African countries (21).

Added to this, South Africa is home to the first company to produce “artificial meat” on the African continent and this company has been funded by overseas investors as well as South Africans themselves. Kenya appears to be the country the most willing to eat “artificial meat” due to its forefront position in relation to drought (48).

Otherwise, Kenya is currently losing its livestock due to drought and may perceive “artificial meat” as a source of relief for its meat consumption but is less willing to pay for “artificial meat.” Ghana appears to be less willing to accept “artificial meat.” “Artificial meat” companies must therefore have a country-specific strategy, targeting those with similar demographics and food consumption habits.

### Income

Income as well as purchasing power in Africa are increasing, but despite this, respondents are still willing to pay less for “artificial meat” than for meat. In the pooled data, most respondents had a monthly income of more than USD 1,500 (43.56% < USD 1,500 and 53.44% > USD 1,500). The average salary in Africa is approximately USD 758 with great variability between countries (49–51) but the price of beef is much lower than in European countries, which means that purchasing power should be adjusted accordingly. The price of beef in the countries surveyed varies from USD 4 to USD 13 (52). The African Development Bank (AfDB) classification measures the middle class as people living on an income of between USD 2 and 20 per person per day, or USD 60 and USD 600 per month (2011) (53). This difference between countries was also reflected by the interaction effect between income and country in the ANOVA model.

Therefore, with this information, our survey only discriminated between rich and non-rich people. Despite this limitation, this can be considered as an indication that the WTP for “artificial meat” of African countries might be very low and, in any case, lower than for conventional meat.
This could lead to the conclusion that “artificial meat” will not be considered a premium product. A report from the consulting firm Mckinsey (54) indicated that “artificial meat” will initially bear a premium price tag, therefore putting it out of reach of some consumers, especially African consumers. Prices are likely to fall as the industry scales up, therefore pushing it on the spectrum of the long term (55). Most respondents consider “artificial meat” will be available in the medium term (6–15 years), as do the French (40.6%) and the Chinese (45.1%) respondents, but different from Brazil where 38.9% of respondents consider that “artificial meat” will be available in the long term (> 15 years).

## Education

The literature has shown that education is a predictor of “artificial meat” acceptance since this product is more appealing to more educated consumers (56–58). Those with lower levels of education are more likely to have food neophobia (59). There has been an increase in the education level in Africa (60) but despite this increase, inequalities are still a critical issue (61). On average, only 9% of Africans were indeed enrolled in post-secondary education in 2019 (62) compared to 73% in Europe (62). In the cities of countries studied in this work, these proportions are 14% in Cameroon, 10% in Kenya, 17% in Ghana, 24% South Africa and 41% in Morocco. The respondents of our survey therefore represent only a minority of actual African citizens, as most of them have higher education.

Our survey showed that “artificial meat” is more appealing to respondents with a technical background. The reason for this might be that respondents with a technical background are more open to technological innovations. Our survey did not include non-educated respondents. Some experts believe that meat alternatives will create new job opportunities along the production chain (63–65). Others discussed the possibility of using plant ingredients as culture media instead of bovine serum (64). Some African countries could therefore become a supplier to this industry. On the other hand, these new technologies will require more trained and qualified staff. Education will therefore play a crucial role in ensuring that “artificial meat” is produced on the African continent. Animal farmers, crop-growing farmers and the rural community are indeed not generally highly educated and may suffer income losses and job losses as a result of the transition to more urban meat production, as they may not be qualified (63).

Education also had an interaction effect with income on WTP and WTE. This is because education is more accessible to those with higher incomes, especially in some developing countries.

## Acceptance of “artificial meat”

Most of the respondents in Brazil, France, China (19, 23, 25) and Africa (this study) were willing to pay less for “artificial meat” than for conventional meat but the percentage of African citizens was lower compared to the situation in the other countries (71%, 69%, and 87%, respectively, and 65% for Africa).

Overall, our results show that there may be a positive perspective on “artificial meat” in Africa. However, with the same questionnaire and methodology, WTT was lower than for Brazil, France and China (50%, 51%, and 66%, respectively, vs 47.2% on average in Africa) (19, 23, 25) but WTE was much higher (> 80%). This could be due to the fact that African countries found “artificial meat” more fun and/or

intriguing than other countries (35%, 23%, and 49%, respectively, and 52% for Africa) (19, 23, 25). It appears that African consumers are keen to adopt “artificial meat” in their diets, and therefore it makes less sense to simply try it.

Interestingly, African and Chinese consumers show less emotional resistance (18.6 and 16.1%) compared to French and Brazilian respondents (55.5% and 32.4%) (23, 25). This may be explained by the fact that African and Chinese consumers are more open-minded and have more diverse dietary habits, such as eating insects (as in Africa) or plant proteins (as in China).

WTT was negatively correlated with WTP and was not associated with prospects for societal changes. This negative correlation suggests that African consumers who are ready to try “artificial meat” may not be willing to pay a high price for this product.

## How can “artificial meat” pave its way in a diverse continent?

Africa is vast and diverse. Consumers do not have the same expectations. “artificial meat” industries must therefore have strategies tailored to each country or at least to the five commonly known subregions: North or Northern Africa, West Africa, Central or Middle Africa, East Africa, and Southern Africa.

## Price

Africans consider price as the most important factor when it comes to purchasing meat.

Price is considered to be a common negative factor for “artificial meat” (16). This could lead to consumer reluctance if “artificial meat” prices are high. This is why, in both surveys, respondents were willing to pay less than for conventional meat. In order to gain more mainstream recognition, “artificial meat” must be cheaper and possibly produce high quality cuts at a comparatively lower price, as indicated by (66). In practice, price competitiveness is therefore an important factor to take into consideration for African countries at least. Price does not only pose a problem on the consumption side but also on the production side since production costs are still high (67).

Another important point to be considered is how “artificial meat” will be made available to African consumers. Two scenarios can be hypothesized. The first is based on the idea that “artificial meat” would be imported from developed countries, with the exception of South Africa which has already started to produce “artificial meat.” The second scenario implies that African countries would have to produce “artificial meat” themselves. Both these scenarios raise certain issues. First of all, it might be more expensive to import “artificial meat” because of its current high price and limited production compared to conventional meat. Secondly, it could be more efficient or less expensive for African governments to implement better policies by helping local farmers rather than building new “artificial meat” industries.

African consumers may be willing to try “artificial meat” because they suppose it will be cheaper than conventional meat, since price is the primary driver in purchasing meat. Even though they are less willing to try “artificial meat,” they would be prepared to eat it regularly if the price was affordable. Furthermore, unlike in developed countries, Africans are unsure about the effects of livestock on the environment and ethical issues, which explains why price is by far the most important driver of “artificial meat” acceptance.