<figure><img src="image_48.png" /></figure>

Check for updates

OPEN ACCESS

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

REVIEWED BY
Paul Wood,
Monash University, Australia
Sishir Kamalapuram,
Consultant, India
Ivana Gadjanski,
BioSense Institute, Serbia

*CORRESPONDENCE
J. Lahne
✉ jlahne@vt.edu

RECEIVED 03 November 2023

ACCEPTED 08 January 2024

PUBLISHED 23 January 2024

CITATION
To KV, Comer CC, O'Keefe SF and
Lahne J (2024) *A taste of cell-cultured meat:
a scoping review.
*Front. Nutr.* 11:1332765.
doi: 10.3389/fnut.2024.1332765

COPYRIGHT
© 2024 To, Comer, O'Keefe and Lahne. 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.

# A taste of cell-cultured meat: a scoping review

K. V. To¹, C. C. Comer², S. F. O'Keefe¹ and J. Lahne¹*

¹Department of Food Science and Technology, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States, ²University Libraries, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States

Cell-cultured meat (CM) is a novel meat product grown *in vitro* from animal cells, widely framed as equivalent to conventional meat but presented as produced in a more sustainable way. Despite its limited availability for human consumption, consumer acceptance of CM (e.g., willingness to purchase and consume) has been extensively investigated. A key but under-investigated assumption of these studies is that CM's sensory qualities are comparable to conventional, equivalent meat products. Therefore, the current review aims to clarify what is actually known about the sensory characteristics of CM and their potential impact on consumer acceptance. To this end, a structured scoping review of existing, peer-reviewed literature on the sensory evaluation of CM was conducted according to the PRISMA-ScR and Joanna Briggs Institute guidelines. Among the included studies (N = 26), only 5 conducted research activities that could be termed "sensory evaluation," with only 4 of those 5 studies evaluating actual CM products in some form. The remaining 21 studies based their conclusions on the sensory characteristics of CM and consequent consumer acceptance to a set of hypothetical CM products and consumption experiences, often with explicitly positive information framing. In addition, many consumer acceptance studies in the literature have the explicit goal to increase the acceptance of CM, with some authors (researchers) acting as direct CM industry affiliates; this may be a source of bias on the level of consumer acceptance toward these products. By separating what is known about CM sensory characteristics and consumer acceptance from what is merely speculated, the current review reported realistic expectations of CM's sensory characteristics within the promissory narratives of CM proponents.

KEYWORDS

cultivated meat, sensory evaluation, consumer acceptance, meat alternative, scoping review

## 1 Introduction

Cell-cultured meat (CM), also known as “lab-grown,” “*in-vitro*,” “cultured meat,” “cultivated meat,” “clean,” “synthetic,” “artificial,” and “cell-based” meat is a meat alternative grown *in vitro* from animal cells using tissue engineering techniques (1, 2). The concept of growing cells *in vitro* was first introduced in 1912 (3), but began to be intensively developed to be used in meat production in the early 2000s (1, 4–6). CM development has been justified for various reasons, from creating a novel food-source for long-term outer space expeditions to ensuring food security in the developing world. Of these, ensuring food sustainability and reducing the environmental impact of current agricultural practices are the two most frequently proposed reasons for developing CM (7–9).
As of mid-2023, over 100 companies worldwide have been involved in the development of CM, both in the meat production from cell lines as well as in lowering the cost of essential components (e.g., growth media or fermentor design) of this technology (10). However, the presence of CM in the market is still very limited. Recently, food agencies in the United States (USDA and FDA) have released regulations regarding human foods made using animal cell culture, and some CM companies (e.g., Upside Foods and Good Meat Inc.) have gained permission to market their products. So far, CM sales have only been approved in the United States and Singapore (11, 12).

Cultured meat has captured the public and scientific imagination across multiple fields. Beyond the technical and scientific challenges to developing such a novel biotechnology, perspectives, challenges, and developments on the topic have frequently been reviewed across many disciplines, from its environmental impacts to the current and possible consumer response to this kind of product (6, 10, 13). Consumer acceptance is a key determinant for the success of any novel food product (14, 15). Therefore, despite its still-extremely limited presence in the marketplace, many studies have been conducted to examine different determinants of consumer acceptance of CM worldwide (15–17). Attitudes toward the biotechnology itself have been studied through survey methodology, as well as the impact of other factors such as consumer demographics (e.g., age, gender, and nationality), psychological characteristics of the consumers (e.g., food neophobia or disgust), and information framing and promissory characteristics around the product [e.g., “Cultured meat is the only alternative to regular meat that consists of real meat. It therefore has the same taste, odor, tenderness, juiciness and mouthfeel as regular meat”; (18), p. 4]; these factors have been evaluated as potential determinants of consumer acceptance (6, 16, 18, 19). Among the tested factors, ‘having similar sensory characteristics as conventional meat’ consistently emerged as a determinant of stated consumer acceptance (20–22).

Meat flavor and texture (tenderness) are the most important sensory characteristics that determine consumer acceptability and purchasing decision of meat products overall (23–25). The limited room for compromise on meat palatability and eating experiences may be a key barrier for consumer adoption of meat substitutes (22, 26, 27). This challenge is especially relevant for CM as it is typically positioned as having the same sensory qualities and functionalities of conventional meat because it is chemically and, in some sense, biologically equivalent (18, 28–30). Because it is arguably “real meat,” it is extremely important that the sensory characteristics of CM align with those expected by consumers for typical meat products. However, due to the extremely limited availability of CM, knowledge of CM sensory characteristics is largely hypothetical, based on CM researchers’ and proponents’ own reports and consumers’ imaginations (28, 31–33).

As the body of literature around CM has grown rapidly, a number of reviews have been published within the broad topic of consumer acceptance of CM (34–36). However, none of these reviews have focused on this topic from the perspective of sensory science to answer critical questions: what are the observable or measurable sensory characteristics of CM, and how are those related to consumer acceptance of CM? Therefore, a scoping review was chosen as a tool to explore the current state of knowledge regarding the sensory characteristics of CM. Scoping reviews are used to map the key concepts and available evidence underpinning a research area (37). This study aimed to identify what is directly known about how CM

tastes, how CM is *expected* to taste, and how consumers respond to those sensory characteristics in imagination or reality.

# 2 Materials and methods

## 2.1 Protocol, main question, and definition

This scoping review aimed to answer the question “What are the known sensory characteristics of CM and how have those characteristics been evaluated?” The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline for scoping review (PRISMA-ScR) was used as a reporting guideline with the Joanna Briggs Institute (JBI) guidance as the methodological guideline (38). The inclusion and exclusion criteria were defined with an emphasis on the presence of comments on the sensory characteristics of CM regardless of actual product evaluation. CM was defined as a meat alternative produced through animal cell culture to grow meat *in vitro*.

## 2.2 Eligibility criteria

The literature included in this study are peer-reviewed journal articles published between the years 2000 and (June) 2023. The date range was chosen because, even though the concept of CM was introduced in 1912 (4, 5), the approach was not used to produce meat until the early 2000s. To be included in this review, articles had to meet the following criteria:

1. Must be a scholarly (peer-reviewed) publication.

2. The concept or product of cell-cultured meat (defined as “a meat alternative grown *in vitro* from animal cells”) is involved in the study, exclusively or compared to other meat alternatives.

3. Investigates or describes at least one *sensory* characteristic of cell-cultured meat. For this review, we defined sensory characteristics to be both analytic and affective: descriptions of taste or flavors as well as affective responses.

4. Article is written in English.

5. Articles published between January 1, 2000 and June 11, 2023.

Studies with the following characteristics were excluded:

1. Review or non-original research articles. Although not included, citation chasing was conducted on retrieved review articles to ensure maximum scope.

2. Articles focused only on the technical production of cell-cultured meat without evaluation by human subjects.

3. Studies only investigating other meat alternatives (e.g., plants, insects, fungi, etc.).

4. Articles not written in English.

5. Articles published before January 1, 2000.

## 2.3 Information sources and search strategy

Articles from peer-reviewed publications were the primary studies used for this scoping review. The primary studies were retrieved
through electronic searches of the following databases: Web of Science Core Collection (WOSCC; Web of Science), Food Science and Technology Abstracts (FSTA; EBSCOhost), and Center for Agriculture and Bioscience International (CABI; CAB Abstracts).

With support and feedback from the University Libraries at Virginia Tech (author CC), the following search strategy was developed iteratively to ensure optimal search results. The final search string as applied in Web of Science is shown in Table 1.

Title, abstract, and keywords search was conducted for all concepts in WOSCC and FSTA; all fields were searched in CABI. In all databases, limits were applied using built-in filters for document type (journal article) and publication year (Appendix 1). The format of this search string was modified for application on the other databases. Appendix 1 contains the detailed search strings used in each database. The initial search was performed in January 2023. Considering the rapid increase in publications on CM, monthly searches were performed in each database until June 2023 - the original search strings were reapplied to each database, but limited to (using built-in filters) from 2022 to 2023 to reduce the number of duplicate results. The work cited by articles that were related to topic but did not fully meet criteria (and were excluded) were scanned for additional relevant records (backward citation chasing).

## 2.4 Record screening and data extraction

All search results were exported from each database and imported into the systematic review management software Covidence (39), where duplicates identified by the software were removed automatically. Screening proceeded in stages detailed in Figure 1. First, the studies were screened based on the title and abstract, and obviously irrelevant studies were excluded. The full-text of potentially relevant studies was collected and further examined to ensure the studies met eligibility criteria (see Section 2.3). Both title and abstract screening and full-text screening were conducted by two independent reviewers (KT and JL). Discrepancies were resolved through discussions.

Data extraction was conducted in Covidence using a data extraction template developed by the authors. The full data extraction form is attached as Appendix 2. Data extracted included general information (e.g., article title, authors' name and affiliations, publication year, and DOI), country in which the study is conducted, framed value of CM, sampling methods, survey/sensory evaluation methods, types of sample tested, sensory/acceptance measures, and proposed determinant factors toward CM acceptance, among others.

<table><caption>TABLE 1 Search string to identify literature related to cell-cultured meat sensory characteristics in Web of Science, January 20, 2023.</caption><tr><td>1</td><td>("culture? meat" OR "cultivate? meat" OR "lab-grown meat" OR "cell-based" OR "clean meat" OR "in-vitro meat" OR "artificial meat" OR "synthetic meat" OR "cell* meat")</td></tr><tr><td>2</td><td>(accept* OR attitude OR preference OR perception OR fram* OR willingness OR awareness OR liking)</td></tr><tr><td>3</td><td>(taste OR texture OR flavo?r OR appearance OR look OR sensory)</td></tr><tr><td>4</td><td>#1 AND #2 AND #3</td></tr></table>

The extraction was focused to identify information related to the expected or actual sensory characteristics of CM, the evidence/experiment supporting the claim, and the determining factor(s) of CM acceptance. Relevant data were extracted by one author (KT) and reviewed for consistency by a second author (JL).

## 3 Results

The results encompass descriptive characteristics about each study, author-hypothesized determinants of CM acceptance among consumers, and consumer-reported sensory experiences of CM. Consumers' perceptions of CM's sensory experiences were treated according to the study method and whether or not they evaluated actual CM samples.

### 3.1 Description of sources

A total of 491 citations were obtained from the database search (WOS = 386 articles, CABI = 50 articles, FSTA = 55 articles) and 4 articles from backward citation chasing. Once duplicates were removed, 303 articles were screened by title and abstract. This first screening excluded 238 publications that were found to be irrelevant to the review objectives. Full texts of the remaining publications were then evaluated according to the eligibility criteria; 43 publications were excluded. Finally, 22 publications from the database search and 4 publications from backward citation chasing were included in the review, resulting in a final count of 26 publications (Figure 1).

Information about each study's characteristics is presented in Table 2. Of the studies included in this review, most involved participants from the "Global North": Europe (N=21 studies) and North America (N=7 studies). A minority involved participants from Asian countries (N=5 studies), Australia (N=1 study), and New Zealand (N=1 study). No studies involved participants from countries in South America or Africa. Typically, subjects were selected using simple, random sampling (N = 15 studies) or convenience sampling (N=7 studies). Most studies employed online surveys (N=21 studies) while only 2 studies used in-person, paper questionnaires. Qualitative methods (interviewing and focus groups) were in the minority of the selected studies (N=3 studies) and only 5 studies conducted an actual sensory evaluation—using human subjects to assess some aspect of the sensory properties of a food product—to evaluate CM products.

Although by definition of the search strategy all papers were related to the sensory evaluation of CM, the most common research question was only tangentially related to sensory evaluation: consumers' "willingness to try/eat" (N=17 studies) and "willingness to buy" (N=11 studies) CM were the main acceptance measures used among the included studies. Some studies measured their participants' willingness to replace conventional meat (N=4 studies) or other meat alternatives (N=2 studies) with CM and their willingness to recommend CM to other people (N=2 studies) to support their studies. Through close reading of study objectives, we concluded that evaluating the sensory properties of CM was considered a primary outcome in 6 studies, while 2 studies inferred the importance of CM's sensory properties. The majority (N=18 studies) included sensory evaluation as a secondary outcome.

<footnote>?: To retrieve words with the replacement of 1 character; *: To retrieve words with variant zero to many characters.</footnote>
<figure><img src="image_49.png" /></figure>

## 3.2 Hypothesized determinants for consumer acceptance of cell-cultured meat

The majority of the included studies examined consumers' attitudes toward CM as a food product (i.e., instead of as a technology or a social innovation). Each paper opened by reporting positive actual or (frequently) potential impacts of CM (Table 3). Most proposed CM as part of a solution to reducing environmental pollution (N=22 studies), minimizing the use of natural resources (N=18 studies), promoting animal welfare (N=19 studies), or promoting food security (N=7 studies) along with fulfilling the increasing demand for animal proteins (N=6 studies). CM was also said to have the same or possibly better nutritional value (N=8 studies), to be safer to consume than (N=11 studies), and to have the same sensory characteristics as conventional meat (N=6 studies).

Despite these proposed possible benefits of CM from the studies' authors, the factors measured in these studies and consumer responses

often indicate alternative and more negative perspectives. Table 4 presents various factors that authors explicitly or implicitly hypothesized as impacts on consumers' acceptance of CM. Common author-hypothesized determinants include views of animal welfare (N=11 studies), concern over environmental impact of CM and the current systems of meat production method (N=13 studies), familiarity and curiosity toward CM (N=11 studies), perception of naturalness of CM (N=6 studies), and psychological factors related to the individual such as food neophobia and disgust (N=10 studies). The need to evaluate these determinants indicates that the authors of these studies are concerned with and well aware of alternatives to the positive narratives and impacts proposed in the introductions to these studies. Moreover, participants frequently mentioned concerns about CM's health impacts, nutrition quality, or food safety (N=18 studies) and, often, the sensory properties of CM (e.g., how it would taste, N=18 studies), indicating that consumers echoed some of the concerns about whether CM will be a universally positive replacement for conventional meat products.
<table><caption>TABLE 2 Characteristics of the included studies based on geographic location, participants selection method, survey method, product (cell-cultured meat) acceptance measures, and if sensory evaluation of cell-cultured meat was considered the main outcome of the study.</caption><thead><tr><th>Country of studies</th><th></th><th>Number of studies<sup>a</sup></th><th>References</th></tr></thead><tbody><tr><td>Belgium</td><td rowspan="10">Europe</td><td>2</td><td>(40, 41)</td></tr><tr><td>Croatia</td><td>1</td><td>(42)</td></tr><tr><td>European Union</td><td>1</td><td>(33)</td></tr><tr><td>Finland</td><td>3</td><td>(22, 40, 43)</td></tr><tr><td>Greece</td><td>1</td><td>(42)</td></tr><tr><td>Italy</td><td>1</td><td>(44)</td></tr><tr><td>Netherlands</td><td>3</td><td>(18, 20, 45)</td></tr><tr><td>Poland</td><td>1</td><td>(20)</td></tr><tr><td>Portugal</td><td>2</td><td>(40, 46)</td></tr><tr><td>Spain</td><td>2</td><td>(20, 42)</td></tr><tr><td>United Kingdom</td><td>4</td><td>(20, 33, 40, 47)</td></tr><tr><td>Canada</td><td rowspan="2">North America</td><td>2</td><td>(48, 49)</td></tr><tr><td>United States</td><td>5</td><td>(7, 33, 50, 51, 52)</td></tr><tr><td>Israel</td><td rowspan="4">Asia</td><td>1</td><td>(53)</td></tr><tr><td>Japan</td><td>1</td><td>(54)</td></tr><tr><td>Singapore</td><td>2</td><td>(21, 55)</td></tr><tr><td>Turkey</td><td>1</td><td>(19)</td></tr><tr><td>Australia</td><td rowspan="2">Australia</td><td>1</td><td>(56)</td></tr><tr><td>New Zealand</td><td>1</td><td>(57)</td></tr><tr><td colspan="4"><strong>Participants selection method</strong></td></tr><tr><td>Random sampling</td><td></td><td>15</td><td>(18, 20, 33, 40, 44, 46, 47, 49, 50, 51, 52, 53, 54, 56, 57)</td></tr><tr><td>Convenience sampling</td><td></td><td>8</td><td>(7, 19, 22, 41, 43, 45, 48, 55)</td></tr><tr><td>Snowball sampling</td><td></td><td>1</td><td>(42)</td></tr><tr><td>Stratified sampling</td><td></td><td>1</td><td>(21)</td></tr><tr><td>N/A<sup>b</sup></td><td></td><td>1</td><td>(58)</td></tr><tr><td colspan="4"><strong>Survey method</strong></td></tr><tr><td>Online questionnaire</td><td></td><td>21</td><td>(18-21, 33, 40-51, 52, 54, 55, 56)</td></tr><tr><td>Paper questionnaire/ handouts</td><td></td><td>2</td><td>(53, 57)</td></tr><tr><td>Interview/ group discussion</td><td></td><td>3</td><td>(40, 56, 57)</td></tr><tr><td>Meat product evaluation</td><td></td><td>5</td><td>(7, 18, 53, 55, 58)</td></tr><tr><td colspan="4"><strong>Cultured meat acceptance measures</strong></td></tr><tr><td>Willingness to buy</td><td></td><td>11</td><td>(18, 21, 41, 42, 44, 47, 48, 49, 51, 52, 57)</td></tr><tr><td>Willingness to replace conventional meat</td><td></td><td>4</td><td>(21, 48, 51, 53)</td></tr><tr><td>Willingness to try/ eat</td><td></td><td>17</td><td>(18, 19, 21, 20, 33, 40, 41, 42, 43, 44, 45, 48, 50, 51, 52, 56, 57)</td></tr><tr><td>Willingness to reduce meat consumption</td><td></td><td>3</td><td>(20, 21, 42)</td></tr><tr><td>Willingness to replace other meat alternatives</td><td></td><td>2</td><td>(21, 48, 51)</td></tr><tr><td>Willingness to recommend to others</td><td></td><td>2</td><td>(19, 56)</td></tr><tr><td colspan="4"><strong>Sensory attributes as a primary outcome</strong></td></tr><tr><td>Primary</td><td></td><td>6</td><td>(18, 43, 47, 53, 55, 58)</td></tr><tr><td>Secondary</td><td></td><td>18</td><td>(7, 19, 21, 22, 33, 40, 41, 42, 45, 44, 46, 48, 49, 50, 51, 52, 54, 57)</td></tr><tr><td>Inference</td><td></td><td>2</td><td>(20, 56)</td></tr></tbody></table>

<footnote><sup>a</sup>More than one response could be selected for a study. Thus, the total number of studies in each category may exceed the total number of included studies (N = 26).</footnote>

<footnote><sup>b</sup>The corresponding study evaluated their samples instrumentally.</footnote>
<table><caption>TABLE 3 Author signified values of cell-cultured meat that are emphasized in the introduction or hinted throughout the study.</caption><thead><tr><td>Value framing</td><td>Number of studies<sup>a</sup></td><td>References</td></tr></thead><tbody><tr><td>Reduce environmental pollution</td><td>22</td><td>(18–22, 33, 40–44, 46–58)</td></tr><tr><td>Promote animal welfares</td><td>19</td><td>(18, 19, 22, 33, 40, 41, 42, 44, 45, 47, 48, 50, 51, 52, 54, 56–58)</td></tr><tr><td>Minimize the use of natural resources</td><td>18</td><td>(18, 20–22, 41, 44–54, 56–58)</td></tr><tr><td>Safer to consume than conventional meat</td><td>11</td><td>(18, 21, 22, 33, 40, 41, 42, 46, 47, 48, 53, 59)</td></tr><tr><td>As/ more nutritious than conventional meat</td><td>8</td><td>(18, 33, 41, 46, 47, 48, 50, 55)</td></tr><tr><td>Food security</td><td>7</td><td>(19, 21, 40, 41, 54, 56, 58)</td></tr><tr><td>Fulfill increasing demand of animal proteins</td><td>6</td><td>(18, 33, 41, 44, 56, 58)</td></tr><tr><td>Have the same sensory attributes/ experience as conventional meat</td><td>6</td><td>(18, 19, 49, 50, 52, 55)</td></tr><tr><td>Replace conventional meat</td><td>6</td><td>(33, 40, 42, 48, 51, 52)</td></tr><tr><td>Potential biodiversity loss</td><td>2</td><td>(20, 21)</td></tr><tr><td>Reduce meat consumption</td><td>1</td><td>(57)</td></tr><tr><td>Food source for outer space expeditions</td><td>1</td><td>(7)</td></tr><tr><td>Less familiar to the public</td><td>1</td><td>(43)</td></tr></tbody></table>

## 3.3 Perceived sensory experience of CM among tested consumers

Because most of these studies examined consumers' holistic attitudes toward CM, it could be argued that understanding the sensory characteristics of CM was not the primary focus of the studies' research designs. However, 18 out of the 26 included studies stated explicitly that sensory experience is a key determining factor for acceptance of this (or any) novel food product. When measuring participants' willingness to accept CM, the questions were always framed to compare CM to conventional meat or meat products. This is implicitly a sensory comparison in the context of a consumer choice study. Unless the type of CM was specified (e.g., cultured seafood), CM was generally compared to a red meat or red meat product. In the reviewed articles, sensory experiences of CM among consumers were evaluated under two conditions: in the absence or the presence of actual products (Table 5).

### 3.3.1 Sensory characteristics in the absence of product evaluation

The majority of the included studies (N=21 studies) did not involve subjects evaluating any actual meat samples, conventional or CM. The studies instead examined consumers' expectations of CM sensory experiences by provoking participants' imaginations: 2 studies asked consumers directly about their expectations for CM taste, and another 19 asked this question after providing an information frame (by words and/ or images) that was meant to affect consumers' expectations. A number of studies reported that participants did not believe that CM would be as tasty as conventional meat and CM products were described as unappealing, disgusting, and were not considered as meat (N=9 studies). Moreover, when compared in a variety of preference-ranking methods to other meat alternatives (e.g., soy- and other vegetarian products, insect-based proteins), CM was often placed at the bottom of the preference rankings along with insect-based alternatives, and consumers seemed to prefer the concept of plant-based alternatives (N=7 studies).

<table><caption>TABLE 4 Factors hypothesized (by authors) as determinants of cell-cultured meat acceptance among potential consumers.</caption><thead><tr><td>Factors</td><td>Number of studies<sup>a</sup></td><td>References</td></tr></thead><tbody><tr><td>Health/ nutrition/ safety</td><td>18</td><td>(18, 19, 21, 22, 33, 40, 42–44, 46–54, 56)</td></tr><tr><td>Taste (tasty, have the same sensory experience as conventional meat)</td><td>18</td><td>(19, 20, 21, 22, 40, 41, 42, 44, 45, 46, 47, 48, 50, 53, 54, 56, 57, 58)</td></tr><tr><td>Environmental impact</td><td>13</td><td>(19–22, 40–46, 49, 51)</td></tr><tr><td>Animal welfare</td><td>11</td><td>(19, 21, 22, 41, 42, 44, 45, 48, 49, 51, 57)</td></tr><tr><td>Consumer knowledge about cultured meat</td><td>11</td><td>(18, 20, 42, 43, 45, 46, 48, 50, 51, 56, 57)</td></tr><tr><td>Psychology (food neophobia, disgust, belief in technology/ attitude)</td><td>10</td><td>(18–21, 40, 43, 45, 47, 48, 54)</td></tr><tr><td>Economic (price, income)</td><td>10</td><td>(19, 20, 40, 41, 42, 48, 49, 51, 56, 57)</td></tr><tr><td>Framing/ labeling</td><td>8</td><td>(18, 33, 44, 45, 46, 48, 50, 52)</td></tr><tr><td>Naturalness</td><td>6</td><td>(19, 40, 41, 45, 54, 56)</td></tr><tr><td>Demographic background</td><td>5</td><td>(22, 33, 49, 51, 57)</td></tr><tr><td>Convenience</td><td>3</td><td>(20, 40, 56)</td></tr><tr><td>Media coverage (including social media)</td><td>1</td><td>(22)</td></tr></tbody></table>

In a large minority of studies (N=8), consumers responded positively toward CM as a meat product. Typically, the positive attitude was in response to positive information framing pertaining to product labeling (50), safety and health benefits (44), impact on the environment and animal welfare (45), or perceived naturalness

<footnote><sup>a</sup>More than one response could be selected for a study. Thus, the total number of studies in each category may exceed the total number of included studies (N = 26).</footnote>

<footnote><sup>a</sup>More than one response could be selected for a study. Thus, the total number of studies in each category may exceed the total number of included studies (N = 26).</footnote>
<table><caption>TABLE 5 Methods used to obtain consumers' perception of CM's sensory experience with and without a physical sample.</caption><thead><tr><th>How is opinion generated?</th><th>Framing theme</th><th>Number of studies<sup>a</sup></th><th>References</th></tr></thead><tbody><tr><td>Direct question of how they think CM would taste (no framing)</td><td></td><td>2</td><td>(21, 43)</td></tr><tr><td rowspan="2">Meat sample evaluation</td><td></td><td>5</td><td>(7, 18, 53, 55, 58)</td></tr><tr><td>Others (e.g., economic, technology, sensory characteristics, societal, ethics)</td><td>19</td><td>(18, 19, 33, 40-42, 44-51, 52, 54, 56, 57)</td></tr><tr><td rowspan="6">Positive framing</td><td>Health/safety</td><td>13</td><td>(18, 19, 33, 40, 42, 44, 46-51, 56)</td></tr><tr><td>Animal welfare</td><td>9</td><td>(19, 41, 42, 44, 45, 48, 49, 51, 57)</td></tr><tr><td>Labeling</td><td>8</td><td>(18, 33, 44-46, 48, 50)</td></tr><tr><td>Environmental benefits</td><td>6</td><td>(19, 41, 42, 44, 49, 51)</td></tr><tr><td>Naturalness</td><td>5</td><td>(40, 41, 45, 54, 56)</td></tr><tr><td>Meal setting &amp; placebo panel</td><td>2</td><td>(18, 46)</td></tr></tbody></table>

(40) - especially in regards to the production process. The overall measure of acceptance was mainly based on increases in participants' willingness to try and willingness to buy or pay for CM along with individual perception ratings of tested factors listed in section 3.2 (N=6). Decrease in disgust perception of CM and increase in perceived similarity of CM with conventional meat products were also considered positive responses (N=4). Introducing CM in familiar meals and providing placebo samples to provoke the idea of sensorial similarity of cultured to conventional meat was reported as effective in increasing tested participants' acceptance of CM (N=2 studies).

### 3.3.2 Sensory characteristics based on product evaluation

Actual evaluations of some sort of CM-relevant product were conducted in only 5 out of the 26 studies, with 1 study using a placebo sample and 4 studies evaluating an actual CM sample. Commercially produced beef was used in the placebo sensory testing while the CM samples were made in-house by the researchers. A detailed summary of each study's method and key findings is presented in Table 6.

Rolland et al. (18) conducted a sensory evaluation using placebo samples to gage consumers' likely response to CM with sensory qualities identical to conventional meat. In this experiment, Rolland et al. (18) evaluated participants' initial responses to the concept of CM and then measured changes to those responses after presentation of one of three positive information framings on the societal, personal,

or sensory/quality benefits of CM, and finally, measured actual liking and some basic sensory-quality measurements in response to evaluation of a placebo CM sample. In this case “placebo” means participants did not evaluate actual CM at any point in the study. Instead, cooked commercial beef burgers (patties) were served labeled as ‘cultured’ and ‘conventional’ in different sizes - ‘cultured’ burger was served as a smaller piece to indicate limited availability. Rolland et al. (18) found an initial positive perception of CM among participants who claimed to “know exactly what CM is” (p. 8). Participants who had never heard of CM or had heard of it but were unfamiliar with it experienced a greater increase in acceptance toward CM. The placebo sensory evaluation also increased consumer acceptance: after tasting the purported CM, a higher score in willingness to taste CM was observed, participants reported willingness to pay a premium price for CM (on average 37% higher price than conventional meat), and positive judgment on the taste of CM was observed.

Benjaminson et al. (7) reported the first successful attempt to grow CM in the form of goldfish tissue-explant “fish fillets.” The resulting product was then cooked and evaluated for its aroma and appearance (but not taste) by 4 employees of the lab without sensory-evaluation training. Cultured fish was reported to be as easy to harvest and to react the same way when cooked as conventional fish filets would. From a sensory point of view, cultured-fish filets were reported to be glistening, firm, and odorless (7).

In the last several decades, direct tissue-explant methods for growing CM have been largely superseded by scaffold-based methods, which is reflected in the more recent sensory-evaluation studies [N=3; (53, 55, 58)]. Ong et al. (55) used jackfruit/textured soy-protein (TSP)-based scaffolds to grow pork cells. This method was shown able to mimic seared beef's shrinking and color-changing behavior (although, not seared pork's) which the authors implied to as an “indicat[ion of] its utility to mimic cooked meat” (p. 5). Ong et al. (55) conducted a between-subject, visual sensory evaluation, asking each of the 2 groups of participants to evaluate a picture of either TSP-scaffolded (N=38 untrained participants) or jackfruit/TSP-scaffolded (N=40 untrained participants) cultured pork. Based on consumer evaluation of pictures of the grown cultured pork, the meat-like mimicry of the jackfruit/TSP significantly scaffold improved participants' perception of CM products by more than 8% compared to the TSP-based scaffold (55).

Lee et al. (58) also investigated the effects of novel scaffold on sensory-relevant characteristics of CM products. The authors created a TVP/fish gelatin-based scaffold and grew mouse cells as their CM model. Lee et al. (58) then instrumentally analyzed for color (colorimeter), texture (texture profile analysis in comparison to multiple beef brisket, chuck, and tenderloin), flavor (GC-MS), and taste (electronic tongue). The authors described their product as having a similar texture to a beef tenderloin, although the product was based on mouse cells. Flavor analysis of the cooked product confirmed the presence of common Maillard-browning produced aroma compounds, namely acetophenone, 2-ethyl-1-hexanol, nonanal, octanal, and nonanol (58), although it is important to note that these compounds are not the only or even the most characteristic products of Maillard browning, and that Maillard browning can occur whenever proteins and sugars are heated together, not only in meat products (60). Moreover, the listed compounds were not determinants of meat sensory characteristics as most key meaty aroma compounds from Maillard reaction are heterocyclic (61, 62). Taste analysis showed that

<footnote><sup>a</sup>More than one response could be selected for a study. Thus, the total number of studies in each category may exceed the total number of included studies (N=26).</footnote>
<table><caption>TABLE 6 Summary of product evaluation of meat products in the included studies (N = 5 studies).</caption><thead><tr><td>Papers Reference</td><td>Product</td><td>Sensory evaluation method</td><td>Key findings</td></tr></thead><tbody><tr><td>Rolland et al. (18)</td><td>Commercial beef burgers</td><td><ul><li>A wanting/ liking test was conducted on identical commercial beef burgers.</li><li>Samples were presented to panelists as 'conventional' and 'cultured'.</li><li>'Cultured' hamburgers were served in a smaller portion than 'conventional'.</li><li>Participants (N = 193) rated the hamburgers' appearance, color, smell, tenderness, and juiciness.</li></ul></td><td><ul><li>High acceptance of cultured meat among panelists when the known information about cultured meat is positive and supported by a favorable tasting experience.</li><li>Overall, participants perceived cultured meat as safe and appropriate food.</li></ul></td></tr><tr><td>Benjamison et al. (7)</td><td>Cultured goldfish</td><td><ul><li>Fried fish filets were evaluated for aroma and appearance by 4 panelists.</li></ul></td><td><ul><li>Cultured fish reacted to the cooking process as would fresh fish.</li><li>Panelists perceived the product acceptable as food despite the absence of tasting.</li></ul></td></tr><tr><td>Ong et al. (55)</td><td>Cultured pork [porcine myoblast on texturized soy protein (TSP) and jack fruit-containing scaffold (JFS)]</td><td><ul><li>A single-blind test was conducted on a photo of (created) cultured pork grown on JFS or TSP scaffold</li><li>Participants (N = 78 university students) rated their attitudes toward the product.</li></ul></td><td><ul><li>Pan fried JFS-cultured pork showed meat-like browning behavior and potentially shelf-stable meat-like color.</li><li>The use of JFS improved participants' perception of the product by more than 8%.</li></ul></td></tr><tr><td>Lee et al. (58)</td><td>Fish gelatin/ agar (GA)-coated textured vegetable protein (TVP) scaffold with mouse blast as model meat cells</td><td><ul><li>Scaffolds made of TVP, GA-coated TVP, and a GA-coated TVP with mouse myoblast were compared to commercial beef cuts (chuck, tenderloin, and brisket) for texture, flavor, and taste.</li><li>Evaluations were done using analytical instruments.</li></ul></td><td><ul><li>Cultured meat's texture, flavor, and taste implied as comparable to that of slaughtered meat due to the synergistic effect between the myoblast and scaffold.</li></ul></td></tr><tr><td>Pasitka et al. (53)</td><td>Cultured chicken (Mixed-breed chicken cultured adipocyte-like cells combined with extruded soy protein)</td><td><ul><li>Panel 1: cultured chicken was served as a meal and rated for overall impression, flavor, texture, aroma, and overall experience of the product (N = 13 participants).</li><li>Panel 2: cultured chicken tasted alongside soy-based chicken and rated for their texture and flavor in a blinded-test (N = 30 participants).</li><li>Panel 3: cultured and soy-based chicken in comparison to farm-raised chicken breast. Participants (N = 13) were asked to rate the general flavor, texture, aroma, and overall experience.</li></ul></td><td><ul><li>Overall, participants found the cultured chicken dish acceptable (average likelihood of 8/10 to replace farm-raised chicken with cultured chicken).</li><li>Sixty seven percent of the blind-tasting participants preferred cultured chicken over the soy-based alternative.</li></ul></td></tr></tbody></table>

compared to a beef-brisket sample, the cultured mouse sample had similar (predicted) bitterness with lower sourness and higher umami values. The perceived aftertastes ["the taste that remains on the tongue after completely swallowing the food"; (58), p. 38242], namely astringency, bitterness, and umami were similar to the tested beef-brisket.

The only study that conducted sensory evaluation with human subjects that involved actual tasting of a real CM product was published very recently by Pasitka et al. (53). Sensory evaluation by untrained panelists was conducted in 3 different studies which evaluated overall sensory characteristics of a hybrid plant-protein/cell-cultivated chicken product (N = 13 participants), a preference test comparing this hybrid-CM product against a soy-based chicken (N = 30 participants), and a preference test comparing the hybrid-CM, the soy-based chicken, and conventional chicken (N = 13 participants). Based on the (forced-choice) preference test, most participants (67% of 30 participants) favored cultured chicken over soy-based chicken in terms of sensory attributes. In the first sensory evaluation, when

participants (N = 13) were asked "how likely are you to replace your meat choice with this (cultured chicken) product?" ([53], p. 41), "the average likelihood stated by participants was 8/10" ([53], p. 41). The cultured chicken also showed remarkable similarities to conventional chicken in sensory attributes, including taste.

## 4 Discussion

The studies identified for this review were almost entirely affective consumer studies, with no analytical sensory evaluations (63). Although the eligibility criteria were not designed to identify solely affective studies (see section 2.2), the prevalence of affective studies speaks to the relation between products' sensory characteristics and consumers' decision-making when it comes to any food. This can be further explained by considering the complimentary relationship between sensory science and consumer science in the analysis of "product micro lifecycle" from product purchase to consumption (64).
Consumer science focuses on explaining consumers' choice based on psychological stimuli such as product information and past experiences while sensory science explains consumption based on psychophysics—a combination of physical stimuli and human perception (64). Therefore, understanding the concept and actual identity of CM is necessary.

## 4.1 Sensory perception based on imagined or expected products

The main discussion in this section revolves around the CM sensory characteristics claim and consumer acceptance based on evaluation of CM as an idea (positive information framing), not an actual product evaluation. As shown in the results (section 3.3.1), a majority of studies' respondents had negative expectations of CM as an imagined product, and particularly of its sensory qualities. Novel-product unfamiliarity was hypothesized as the main reason for consumer skepticism toward CM. For example, according to Weinrich et al. (65), pre-knowledge of a product was a mediator between one's demographic background and attitudes toward the product. On a similar note, Lin-Hi et al. (66) considered CM as a "radical innovation in food sector" - an innovation that radically breaks with familiar logic and habits - which they hypothesized explained the tendencies for consumers' skepticism toward this product. The implication is that this skepticism manifested in multiple ways including perceptions of disgust (67), and perceptions that CM is more unsafe and unnatural, leading to further rejection of new food products (33, 67-70).

In order to determine whether unfamiliarity, skepticism, or neophobia might drive negative expectations around CM, information framing was used in many of these studies to determine if different frames increased acceptance. Various positive framings from labeling to the use of 'placebo' products were conducted and, overall, these all tended to improve expected consumer acceptance toward the product when properly directed (section 3.3.1). Positive framing focused on aspects such as product safety, health benefits, and environmental sustainability was found to increase consumer acceptance. This aligned with suggestions from many studies to highlight the key drivers of consumer acceptance namely safety and health benefits as well as showing that CM is a natural product that resembles conventional meat (18, 71-73). These framing approaches to increasing acceptance may be necessary as some studies reported that while some consumers (initially) were willing to support CM because of the benefits to animal welfare and the environment (65, 70), many consumers are not actually aware of these adverse environmental and animal-welfare impacts of the conventional system of producing meat. Therefore, in many studies these frames may be simultaneously informing consumers of a problem and providing CM as a solution (13, 74).

It is important to note that all 26 studies reviewed framed CM positively, regardless of the specific frame. The selection criteria for the scoping review were not designed to select papers with a particular position on this sometimes-controversial biotechnology (75), so this result is itself noteworthy. Since many of the study authors are apparently invested in the potential of CM as a meat-production method, this preponderance of positive framing may not have been the explicit intention of authors of the reviewed studies, either.

However, since there have apparently been no sensory- or consumer-evaluation papers that investigated the effect of a negative framing on CM, this may be a source of bias in the literature, particularly confirmation bias.

As reported by Ryynänen and Toivanen [(22); see also (76)], based on their exploration of the role of written and online media in framing and presenting CM, most articles highlighted only benefits of CM, and presented the only challenges for CM as the current high cost of production and the possible imperfect reproduction of the sensory characteristics of conventional meat. This absence of real critical framing may create a critical knowledge gap, since CM cannot truly be said to be risk-free. For example, based on their intensive review, Bhat et al. (4) predict CM to be more likely to have a substrate contamination risk from the growth media, in contrast to the bacterial contamination from processing that is a problem for conventional meat. An overview by Broucke et al. (77) claims that the "addition of compounds and solutions like sera, growth-hormone factors (GHF), (bovine serum) albumin (BSA), and transferrin, withhold an additional risk due to possible introduction of harmful or pathogenic agents, especially in the case of *in vivo* gained animal sera (mostly fetal, but also new-born or adult source). Examples of possible contamination are prions, bacteria (including mycoplasma), and viruses (e.g., hepatitis virus)" (p. 7). Risks may also arise within the cell-handling and -cultivation process; not only additional contamination, but also potential genetic drift that can cause unintentional genome alteration of the cultured cells (78). Furthermore, it is possible for adult stem cells to become malignant in long-term culture (79). The effect of these more negative counter-narratives on consumer acceptance have yet to be explored, thus it may be premature to conclude that only positive framing has an effect on consumer willingness to buy/eat CM and their perceptions of its quality.

## 4.2 Sensory characteristics based on actual product evaluation

Despite the many promises and the insistence in the literature that CM will have sensory characteristics equivalent to conventional meat (18, 80, 81), there was very limited evidence of the actual sensory characteristics of CM. In this review, (meat) product evaluation was only found in 5 studies, with 1 conducted on a "placebo" consisting solely of conventional meat, and 4 on CM (see section 3.3.2). Overall, these studies did conclude that the evaluated CM closely resembled its conventional counterpart in both sensory characteristics and reaction to cooking. These studies speak to the potential for CM products to ultimately resemble their conventional equivalents.

However, the claim that CM products will always have, or even currently have, the same sensory characteristics as conventional meat products is not well-established in this current literature. Three main issues are as follows: (1) only one study reports an actual sensory evaluation with tasting of CM products; (2) in all studies excepting Rolland et al. (18) (which did not actually involve CM products), evaluations were conducted with unacceptably low numbers of human panelists (this standard is described with more detail in section 4.2.2); and (3) the CM products evaluated were not comparable to their target, conventional equivalents.
### 4.2.1 Lack of product tasting

Almost all studies did not involve actual tasting of a product, CM or otherwise. Lee et al. (58), Pasitka et al. (53), and Rolland et al. (18) stood out among the actual sensory evaluations for reporting details about taste and flavor in CM products (see section 3.3.2). Among these three studies, only the placebo panel by Rolland et al. (18) and the CM sensory evaluation by Pasitka et al. (53) included actual human-subject evaluation by taste of any product.

The result of the Rolland et al. (18) placebo panel (section 3.3.2) was considered a notable success in the acceptance of CM products, not only by the authors, but also by many others who have cited these results as proof that consumers will accept CM (59, 68, 82, 83). Compared to a past consumer liking test investigating novel food technologies by Tan et al. (84)—participants were served novel foods such as lamb brain, frog meat, or meal-worms burger and rated the products as inappropriate for food—Rolland et al. (18) results with a sensory panel evaluating placebo products found that ‘cultured’ hamburger was considered to taste slightly better than ‘conventional’, and to therefore be acceptable as a substitute. The authors also noted that among the 4 acceptance questions they used, “…the willingness to taste cultured meat had a much higher score than the responses to the other questions” ([18], p. 13). Interpreting this statement, the authors hypothesize “[a]s perceived danger is a major determinant for willingness to taste novel foods [26], this suggests that participants did not consider cultured meat dangerous” ([18], p. 13). Thus, “…a cultured meat hamburger is considered an appropriate food [by participants] when its sensory features are equivalent to conventional meat” ([18], p. 13).

Looking closely at the context of the Rolland et al. (18) study, however, these results are scarcely indicative of consumers' acceptance of CM. Rather than perceiving CM as safe to eat, the high willingness to taste CM score could as plausibly be interpreted to reflect participants' curiosity about the product, considering it was not yet at all available in the market, and the notoriety of some of the study's authors, who were responsible for the first televised tasting of CM hamburger (85, 86). Since the study was *in vitro* it also does not establish whether consumers would be willing to continue consuming the product (87, 88). Furthermore, it should be emphasized, as conventional hamburger was the only sample presented in this study to taste, this study did not prove anything about the sensory characteristics or acceptability of CM; instead, it showed how much participants like the taste of conventional meat. The results are only generalizable to CM if it does indeed have exactly the same sensory characteristics of conventional, beef hamburger.

The study by Lee et al. (58), although included in our review because of the detailed attention to sensory characteristics of its CM sample, did not use human senses to evaluate the product. Instead, they use instrumental analyses to predict flavor, taste, and texture characteristics. Although created to model a human tongue, the sensor performance of an electric tongue differs with respect to sensitivity, selectivity, and detection limit for the compounds of interest (89). Regarding flavor as measured by volatile aroma compounds, the absence of furans, pyrazines, oxazoles, and other essential sulfur-containing flavor compounds in the final product are concerning, and may indicate that the CM will not have a flavor equivalent to conventional meat, since these are key aroma compounds for red meats (58, 90, 91). In the absence of any human sensory evaluation, these results should not be treated as indicative of the “true” sensory experience of CM.

The hybrid (plant and cell based) chicken product evaluated in the study by Pasitka et al. (53) is currently the only CM product currently reported in the literature to have undergone sensory evaluation for flavor by human subjects.

### 4.2.2 Low power sensory studies

Sensory evaluation focuses on person-product interaction; it requires an interaction between a person and a stimulus (63). Colloquially, sensory evaluation uses human subjects as “instruments” to determine the analytical or affective characteristics of a (food) product. Typically, sensory evaluation methods are broken down into three broad categories: discrimination tests (“are their perceptible differences among samples?”; require trained or untrained panelists), descriptive tests (“what are the perceived sensory differences among the samples?”; require trained panelists), and affective/hedonic tests (“how are these samples liked by different subjects?”; require untrained panelists) testing.

Among the included studies, the studies by Benjaminson et al. (7) and Pasitka et al. (53) were the only ones to involve direct person-to-CM evaluation. It is important to recall that Benjaminson et al. (7) did not allow subjects to taste the samples. Both studies based their results on a number of subjects that would be universally considered too low for statistical power by the standards of sensory science (see section 3.3.2). Both studies did not specify the specific objective(s) or research questions that were addressed by conducting sensory evaluation, but based on their results, the authors seemed interested in identifying similarities between their CM and its conventional counterpart as well as proving its acceptability among consumers. The recommended number of panelist in an affective study depends on several factors, including the expected quantitative differences among products, the specific research question, the method of collecting data, the desired population to which the results should generalize, and the complexity of the products themselves (92). To achieve a proper predictive validity, it is typically recommended to have 24-40 panelists for a simple difference test and 50-100 consumers for a hedonic test without post-hoc segmentation (63, 92, 93). Unfortunately, Benjaminson (N=4 panelists) and Pasitka (N≤30 panelists, depending on sub-study) simply did not include sufficient panelists in their studies.

Furthermore, within an affective test, Pasitka et al. (53) asked their untrained panelists to measure specific sensory attributes such as sweetness, savoriness, saltiness, aftertastes, chicken flavor, and other attributes (Table 6). This type of sensory-evaluation test should be done through descriptive sensory methods, which require 8-12 well-trained panelists: individuals that have been trained to evaluate reference standards and reach an objective, within-group consensus about the meaning of terms like “chicken flavor” (63). The statistical power of descriptive methods even with such a small number of panelists is typically justified by the reduction of variance through this calibration (training). Furthermore, recent research has shown that even “simple” terms like sweetness are not suitable for evaluation by untrained panelists (94). Thus, the conclusions about specific sensory attributes based on very small, untrained panels as in the study by Pasitka et al. (53) are unlikely to be reliable.

### 4.2.3 Non-equivalent sample evaluation

Of the few studies that actually produced CM samples for evaluation, two studies evaluated samples that do not correspond to meat that people usually consume, namely cultured goldfish and
cultured mouse. The creation of a goldfish filet by Benjaminson et al. (7) was the first success story for the creation of cultured fish. Although the process was not yet practical from a yield standpoint at that time, the authors stated that they had successfully “... addressed fundamental *in vitro* skeletal muscle growth parameters” and that “... the yield versus cost calculation projects a favorable outcome provided sufficient research effort and resources become available” [(7), p. 887]. Of course, humans do not typically consume goldfish, so this work on a model species was meant to be a stepping-stone toward the production of CM fish from actual food species. It is not unreasonable to observe that this study was published more than two decades ago; by now other labs working on cultured fish should surely have been able to improve on or at least replicate results of Benjaminson et al. (7). Unfortunately, this optimism does not seem to have been realized; not only is cultured fish not in the market as of this time of writing, but no further record of evaluation on cultured fish product(s) has been published for inclusion in this review.

The creation of CM that mimics the texture of beef tenderloins is certainly worthy of note (58). However, there is not yet evidence that this approach can succeed using cells from animal species that are more commonly consumed than mice. This consideration is not merely a quibble, considering the different genomic resources between species which confine cell differentiation to result in tissues that are species-specific (95, 96). Thus, being able to produce ‘cultured beef tenderloin’ from mouse cells does not guarantee that this approach will be successful for the creation of products with, for example, cow cells.

## 4.3 Realities of CM production

The majority of papers included in this review (N=24 studies) present CM as an entirely positive, transformational biotechnology. This is emphasized especially in studies that communicated these concepts to participants as framing (N=18 studies). In framing studies, participants are asked to believe that the given, invariably positive frame about CM is an unproblematic truth. These frames are typically consumer-appropriate versions of the arguments given in support of CM as a technology in the literature (N=18 studies; examples in Table 5 in "positive framing"). However, as reported in an increasing number of studies, these arguments in favor of CM are exactly that—arguments, not inevitable truths (77, 88). Predicting the future development of CM as both a process for producing a food and as a consumer product has turned out to be considerably more complicated.

Typically, arguments in the papers reviewed here imply that CM is isomorphic with conventional meat but produced in a more sustainable way. However, as long as CM has continued to be a hypothetical product, this claim has not been supported by enough evidence. CM typically is argued to be more sustainable because it would cause less environmental damage—requiring fewer natural resources and less land use, and causing lower greenhouse-effect gas-emission—than conventional forms of livestock production for meat (2, 4, 6). However, those statements are typically based on theoretical projections with large uncertainties (97, 98). In addition, although *in vitro* CM production may require lower agricultural inputs, including land use, it would require more intensive energy use in return. Lynch and Pierrehumbert (99) also reported that, although cattle farming has grater peak (global) warming effect, the warming

effect would not persist nor accumulate under reduced 'farming' system as would *in vitro* meat production. While CM production's benefits in terms of sustainability are likely to be much more complex and contingent, the papers reviewed here presented CM production only in terms of maximal, unalloyed benefits, both in argumentation (N=24 studies) and in experimental design (N=18 studies).

As for CM being exactly the same as 'real meat', the burger grown in Professor Mark Post's laboratory and presented in 2013 has been, to this date, the only consumed 'pure (cultured) meat' in real life. According to the three tasters, "...the burger was dry and a bit lacking in flavor" (85) in which one of them described "the bite [texture] feels like a "conventional hamburger" but that the meat tasted "like an animal-protein cake."" (85). The recently sold cultured chicken and fish products are a hybrid of animal cells and plant-based materials (100). This reality is reflected in this review; the only CM product that was evaluated by taste was a hybrid product of soy protein and chicken cells and not just 'animal meat' (53) as is typically presented in the framing and narratives documented in these studies.

Beyond the challenge of developing a CM product that can be an acceptable sensory substitute for conventional meat, high production costs have remained a hurdle. Proponents of CM have claimed that Moore's law - formulated for microprocessors, and arguing that the cost of production of novel products will always reduce exponentially over time - would apply to CM (88). Moore's law has, however, not typically been applied to biological systems, which are the basis of CM production, due to the complexity and unpredictability of biological events and the mechanisms behind it (88). Ten years ago, a five ounce burger costed over $300,000 to make (85, 101) and so far, CM products have been sold for about $18 per meal—a loss regarding which producers were not willing to share further details on (102). Thus far, reframing CM as a plant/animal-cell hybrid product seems to be more realistic both from a product-formulation and a production-cost point of view. Using cell cultures as flavorings of a plant-based meat is what most CM producers are moving toward (102). The future of CM has once again been proven unpredictable, suggesting the importance of sober and realistic interpretation of the literature in order to avoid bias and overexcitement.

Other than to further understand potential consumer attitudes toward CM, many consumer acceptance studies were directed to ensure the *increase* in consumer acceptance of CM (34–36). For example, after determining drivers for consumer acceptance and rejection of CM, the authors suggested ways to market CM such as framing CM as a solution to the existing food safety problems (68) and portraying CM as more natural, favorable, and addressed consumer concerns about the technology could improve consumer perceptions of the product (70). A similar pattern was also found in more recent publications (66, 72). This indicated that increasing consumer acceptance is the main interest of CM proponents which could be a critical source of bias throughout literature in this area.

## 4.4 Researcher investment in CM as an idea

The intense promotion of CM as a world-changing biotechnology makes research around this topic prone to bias. To investigate this, conflict of interest statements, study supports (source of funding, panelist, and samples), and authors affiliations were examined (Appendix 5). Based on the results, the panelists and sample sources were unlikely to be a source for bias/conflict of interest. This was
because the studies used random participants from a crowd sourcing website, conducted national/cross-country survey, or obtained random internal participants such as college students. Only the study by Benjaminson et al. (7) acknowledged using panelists who were their own lab members. As for sample sources, almost all studies that conducted a sensory panel made their own sample. Only one study bought commercial samples [hamburger; (18)]. Further details can be seen in the *Supplementary material*.

Possible sources of bias were sought in the conflict of interest statement, author affiliations, and funding sources (Appendix 5). Eight of the included studies did not include a conflict of interest statement while most studies (N=17) declared no conflict of interest. Ong et al. (55) was the only study that declared potential conflict of interest. Ong et al. (55) declared that portions of the reported research has been submitted for a patent (patent application no. PCT/SG2020/050432) to two of their authors, Shujian Ong and Hanry Yu. Furthermore, both Shujian Ong and Hanry Yu were affiliated with Ants Innovate Pte Ltd., a Singapore deep tech start-up that focuses on developing cultivated whole meat cuts. Studies' funding sources showed that many included studies were funded through a government grant and/or internal funding (N=12 studies), from independent-nonprofit organizations (N=12), and from the CM industry (N=2 studies). Upon examining the authors' affiliations, almost all authors were university affiliates, with only a few independent or industry researchers (N=3 studies). These 3 studies included at least an author that is affiliated with a CM industry: Ants Innovate Pte Ltd., Believer Meats, and Mosa Meat (Appendix 5).

While the development of cultured meat is happening across public research labs and private industry, most of the reported success in producing CM products is in private industries such as Upside foods, Good Meat Inc., SciFi foods, and Blue Nalu (100, 103). With CM formulation becoming companies' best-kept secret, perhaps for this reason the real sensory characteristics of CM are still unreported in the scientific literature. In this review, CM products that were evaluated were all made in-house by the research teams. This implies that CM products produced by industry were not made available for independent assessments. If CM is only developed by a handful of individuals that are likely proponents of this product, implicit bias of reporting positive results is very likely to take place; it is very unlikely that negative results will be published at all. In fact, the known consumer related studies and information given to the media are mostly the success stories of CM development (22, 76).

## 5 Limitations

This scoping review focused on identifying proof of the sensory characteristics of cell-cultured meat (CM), not to identify the consumers' responses toward CM or judging the product of CM. Thus, the results should be interpreted within this context, not necessarily in terms of the larger feasibility of making high-quality CM acceptable to consumers or even the possible *future* sensory characteristics of CM products.

In terms of data collection, this scoping review was restricted to publications in three agriculture-based databases. Considering the extremely active nature of publications around the topic of CM, it is likely that some manuscripts are not retrieved from our initial search. For example, while studies by Chriki et al. (104) and Liu et al. (105) were not captured by our search strategy, they were brought to our

attention after article submission. While these articles would not significantly change our conclusions about the state of the field—both asked consumers to hypothesize about how “tasty” cultured meat would be—they are an example of the active and rapid state of the discourse. A different result might be obtained if more than three databases were included or done in multidisciplinary databases (e.g., sociology, psychology, and communications) or related disciplines such as engineering. Furthermore, the review was restricted to publications written in English language. This means that the findings may not reflect the body of literature in other languages. The scoping review was designed to include the sensory characteristics of CM in general which was reflected in the absence of use of specific meat terms (e.g., “cultured seafood,” “cultured chicken”) in the search strategy. Thus, the results of this review should not be used to indicate a very specific type of CM.

As for the review method, the citation chasing approach could be improved. Instead of only backward citation chasing, a more thorough citation chasing could be done which includes checking all references in the included articles. Finally, data extraction was conducted by only one author with a second author as a reviewer (spot checking); although a valid approach, having more expert opinion in the process would further reduce the chances of misinterpretation.

## 6 Conclusion

Cell-cultured meat (CM) has been widely introduced as *meat produced in a more sustainable way*, implying it is better for the environment and will have the same sensory characteristics of conventional meat. Using structured, best-practice, scoping-review methods, the current state of knowledge regarding CM's sensory characteristics was surveyed, with a focus on both the directly known attributes and the methods used to identify those attributes in the literature.

In the literature CM sensory-attribute characterization was performed regardless of product availability where a majority (N=19 studies) of the included studies use positive framing to provoke stated preferences of CM among consumers and only a few (N=5) studies conducted anything that could be characterized as an actual product evaluation. All reviewed studies demonstrated some possible weaknesses for drawing certain conclusions about the sensory characteristics of CM, namely: not actually tasting CM, low statistical power, or evaluation of unrealistic CM samples. Therefore, we must conclude that there simply is not currently evidence of the strong claim found throughout the larger literature that CM will have the same sensory characteristics as conventionally produced meat products. What the large minority of the included studies did show were possibilities to create cell-cultured products (CM) that mimic the color, texture, and response to cooking (color change and shrinking) of their conventional counterparts.

In conclusion, with the strong flux of advancements and reformulations currently ongoing around CM production, the sensory characteristics of cultured meat remain a mystery. Based on what is known, it is fair to state that CM still has a long way to go before achieving the exact sensory characteristics of the conventional meat that is in the market today. Based on the reviewed studies, it seems that the future of CM may be a hybrid product of cultured animal cells and plant proteins, which may achieve desirable sensory characteristics but will almost certainly not be exactly equivalent in sensory
characteristics to conventional meat. Outside of the primary focus of this review it was observed that recent developments in CM are reported more in the mass media than in the peer-reviewed literature. Thus, media studies, communications studies, and sociological research in this area could contribute to clarifying what is expected and known about the actual sensory characteristics of CM. For the moment, from this review it is only possible to conclude that CM may someday succeed in producing a product with desirable and meat-like sensory characteristics; the guarantees and claims currently being made are not well-based in the peer-reviewed literature.

## Data availability statement

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

## Author contributions

KT: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing, Investigation. CC: Conceptualization, Methodology, Writing – review & editing. SO'K: Writing – review & editing. JL: Conceptualization, Data curation, Methodology, Supervision, Writing – review & editing, Resources, Writing – original draft.

## References

1. Edelman PD, McFarland DC, Mironov VA, Matheny JG. Commentary:In Vitro-Cultured Meat Production. *Tissue Eng.* (2005) 11:659-62. doi: 10.1089/ten.2005.11.659

2. Post MJ. Cultured meat from stem cells: challenges and prospects. *Meat Sci.* (2012) 92:297-301. doi: 10.1016/j.meatsci.2012.04.008

3. Carrel A. On the permanent life of tissues outside of the organism. *J Exp Med.* (1912) 15:516-28. doi: 10.1084/jem.15.5.516

4. Bhat ZF, Kumar S, Fayaz H. In vitro meat production: challenges and benefits over conventional meat production. *J Integr Agric.* (2015) 14:241-8. doi: 10.1016/S2095-3119(14)60887-X

5. Catts O, Zurr I. Disembodied livestock: the promise of a semi-living utopia. *Parallax.* (2013) 19:101-13. doi: 10.1080/13534645.2013.752062

6. Kumar P, Sharma N, Sharma S, Mehta N, Kumar Verma A, Chemmalar S, et al. In-vitro meat: A promising solution for sustainability of meat sector. *J Animal Sci Technol.* (2021) 63:693-724. doi: 10.5187/jast.2021.e85

7. Benjaminson MA, Gilchriest JA, Lorenz M. In vitro edible muscle protein production system (mpps): stage 1, fish. *Acta Astronaut.* (2002) 51:879-89. doi: 10.1016/S0094-5765(02)00033-4

8. Bhat ZF, Kumar S, Bhat HF. In vitro meat: A future animal-free harvest. *Crit Rev Food Sci Nutr.* (2017) 57:782-9. doi: 10.1080/10408398.2014.924899

9. Zhang L, Hu Y, Badar IH, Xia X, Kong B, Chen Q. Prospects of artificial meat: opportunities and challenges around consumer acceptance. *Trends Food Sci Technol.* (2021) 116:434-44. doi: 10.1016/j.tifs.2021.07.010

10. Behera R, Adhikary L. Review on cultured meat: ethical alternative to animal industrial farming. *Food Res.* (2023) 7:42-51. doi: 10.26656/fr.2017.7(2).772

11. Lucas A. (2023). U.S. regulators approve sale of cell-cultured chicken by two startups. CNBC. Available at: https://www.cnbc.com/2023/06/21/us-approves-sale-of-cell-cultured-chicken-to-two-start-ups.html

12. Scipioni J. (2020). This restaurant will be the first ever to serve lab-grown chicken (for $23). CNBC. Available at: https://www.cnbc.com/2020/12/18/singapore-restaurant-first-ever-to-serve-eat-just-lab-grown-chicken.html

13. Tomiyama AJ, Kawecki NS, Rosenfeld DL, Jay JA, Rajagopal D, Rowat AC. Bridging the gap between the science of cultured meat and public perceptions. *Elsevier Enhanced Reader.* (2020) 104:144-52. doi: 10.1016/j.tifs.2020.07.019

## Funding

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

## 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.

## Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2024.1332765/full#supplementary-material

14. Onwezen MC, Verain MCD, Dagevos H. Positive emotions explain increased intention to consume five types of alternative proteins. *Food quality and preference.* (2022) 96:104446. doi: 10.1016/j.foodqual.2021.104446

15. Zhang M, Li L, Bai J. Consumer acceptance of cultured meat in urban areas of three cities in China. *Food Control.* (2020) 118:107390. doi: 10.1016/j.foodcont.2020.107390

16. Carlsson F, Kataria M, Lampi E. How much does it take? Willingness to switch to meat substitutes. *Ecol Econ.* (2022) 193:107329. doi: 10.1016/j.ecolecon.2021.107329

17. Malek L, Umberger WJ. Protein source matters: understanding consumer segments with distinct preferences for alternative proteins. *Future Foods.* (2023) 7:100220. doi: 10.1016/j.fufo.2023.100220

18. Rolland NCM, Markus CR, Post MJ. The effect of information content on acceptance of cultured meat in a tasting context. *PloS One.* (2020) 15:e0231176. doi: 10.1371/journal.pone.0231176

19. Baybars M, Ventura K, Weinrich R. Can in vitro meat be a viable alternative for Turkish consumers? *Meat Sci.* (2023) 201:109191. doi: 10.1016/j.meatsci.2023.109191

20. Grasso AC, Hung Y, Olthof MR, Verbeke W, Brouwer IA. Older consumers' readiness to accept alternative, more sustainable protein sources in the European Union. *Nutrients.* (2019) 11:1904-4. doi: 10.3390/nu11081904

21. Leung AK, Chong M, Fernandez TM, Ng ST. Higher well-being individuals are more receptive to cultivated meat: an investigation of their reasoning for consuming cultivated meat. *Appetite.* (2023) 184:106496. doi: 10.1016/j.appet.2023.106496

22. Ryynänen T, Toivanen A. Hocus-pocus tricks and moral progressions: the emerging meanings of cultured meat in online news comments. *Food, Culture & Society.* (2023) 26:591-620. doi: 10.1080/15528014.2022.2027688

23. Behrends JM, Goodson KJ, Koohmaraie M, Shackelford SD, Wheeler TL, Morgan WW, et al. Beef customer satisfaction: USDA quality grade and marination effects on consumer evaluations of top round steaks. *J Anim Sci.* (2005) 83:662-70. doi: 10.2527/2005.833662x

24. Legako JF, Brooks JC, O'Quinn TG, Hagan TDJ, Polkinghorne R, Farmer LJ, et al. Consumer palatability scores and volatile beef flavor compounds of five USDA quality grades and four muscles. *Meat Sci.* (2015) 100:291-300. doi: 10.1016/j.meatsci.2014.10.026

25. Reicks AL, Brooks JC, Garmyn AJ, Thompson LD, Lyford CL, Miller MF. Demographics and beef preferences affect consumer motivation for purchasing fresh beef steaks and roasts. *Meat Sci.* (2011) 87:403-11. doi: 10.1016/j.meatsci.2010.11.018
26. Bogueva D, Marinova D. Cultured meat and Australia's generation Z. *Front Nutr.* (2020) 7:148. doi: 10.3389/fnut.2020.00148

27. Wilks M, Phillips CJ, Fielding K, Hornsey MJ. Testing potential psychological predictors of attitudes towards cultured meat. *Appetite*. (2019) 136:137–45. doi: 10.1016/j.appet.2019.01.027

28. Post MJ, Hocquette JF. New sources of animal proteins: cultured meat In: PP Purslow, editor. *New aspects of meat quality*. UK: Woodhead Publishing (2017). 425–41.

29. Ramalingam V, Song Z, Hwang I. The potential role of secondary metabolites in modulating the flavor and taste of the meat. *Food Res Int.* (2019) 122:174–82. doi: 10.1016/j.foodres.2019.04.007

30. Starowicz M, Kubara Poznar K, Zielinski H. What are the main sensory attributes that determine the acceptance of meat alternatives? *Curr Opin Food Sci.* (2022) 48:100924. doi: 10.1016/j.cofs.2022.100924

31. Dupont J, Fiebelkorn F. Attitudes and acceptance of young people toward the consumption of insects and cultured meat in Germany. *Food Qual Prefer.* (2020) 85:103983–3. doi: 10.1016/j.foodqual.2020.103983

32. Fraeye I, Kratka M, Vandenburgh H, Thorrez L. Sensorial and nutritional aspects of cultured meat in comparison to traditional meat: much to be inferred. *Front Nutr.* (2020) 7:1–7. doi: 10.3389/fnut.2020.00035

33. Krings VC, Dhont K, Hodson G. Food technology neophobia as a psychological barrier to clean meat acceptance. *Food Qual Prefer.* (2022) 96:104409–9. doi: 10.1016/j. foodqual.2021.104409

34. Siddiqui SA, Bahmid NA, Karim I, Mehany T, Gvozdenko AA, Blinov AV, et al. Cultured meat: processing, packaging, shelf life, and consumer acceptance. *LWT- Food Sci Technol.* (2022) 172:114192–2. doi: 10.1016/j.lwt.2022.114192

35. Bryant C, Barnett J. Consumer acceptance of cultured meat: A systematic review. *Meat Sci.* (2018) 143:8–17. doi: 10.1016/j.meatsci.2018.04.008

36. de Oliveira Padilha LG, Malek L, Ungerber WJ. Consumers' attitudes towards lab-grown meat, conventionally raised meat and plant-based protein alternatives. *Food Qual Prefer.* (2022) 99:104573–3. doi: 10.1016/j.foodqual.2022.104573

37. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. *Int J Soc Res Methodol.* (2005) 8:19–32. doi: 10.1080/1364557032000119616

38. Peters MDJ, Marnie C, Tricco AC, Pollock D, Munn Z, Alexander L, et al. Updated methodological guidance for the conduct of scoping reviews. *JBI Evidence Synthesis.* (2020) 18:2119–26. doi: 10.11124/JBIES-20-00167

39. *Covidence systematic review software*. Melbourne, Australia: Veritas Health Innovation. Available at: http://www.covidence.org

40. Verbeke W, Marcu A, Rutsaert P, Gaspar R, Seibt B, Fletcher D, et al. 'Would you eat cultured meat?: Consumers' reactions and attitude formation in Belgium, Portugal and the United Kingdom. *Meat Sci.* (2015) 102:49–58. doi: 10.1016/j.meatsci.2014.11.013

41. Verbeke W, Sans P, Loo E J. van. (2015). Challenges and prospects for consumer acceptance of cultured meat. *J Integr Agric.* doi: 10.1016/S2095-3119(14)60884-4, 14, 285–294.

42. Franceković P, García-Torralba L, Sakoulogeorga E, Vučković T, Perez-Cueto FJA. How do consumers perceive cultured meat in Croatia, Greece, and Spain? *Nutrients.* (2021) 13:1284. doi: 10.3390/nu13041284

43. Lunden S, Hopia A, Forsman L, Sandell M. Sensory and conceptual aspects of ingredients of sustainable sources-Finnish consumers' opinion. *FOODS.* (2020) 9:1669–35. doi: 10.3390/foods9111669

44. Mancini MC, Antonioli F. To what extent are consumers' perception and acceptance of alternative meat production systems affected by information? *Case of Cultured Meat Animals*. (2020) 10:656. doi: 10.3390/ani10040656

45. Cornelissen K, Piqueras-Fiszman B. Consumers' perception of cultured meat relative to other meat alternatives and meat itself: A segmentation study. *J Food Sci.* (2022) 88:91–105. doi: 10.1111/1750-3841.16372

46. Possidónio C, Prada M, Graça J, Piazza J. Consumer perceptions of conventional and alternative protein sources: A mixed-methods approach with meal and product framing. *Appetite.* (2021) 156:104860. doi: 10.1016/j.appet.2020.104860

47. Vural Y, Ferriday D, Rogers PJ. Consumers' attitudes towards alternatives to conventional meat products: expectations about taste and satisfaction, and the role of disgust. *Appetite.* (2023) 181:106394. doi: 10.1016/j.appet.2022.106394

48. Ruzgys S, Pickering GJ. Perceptions of cultured meat among youth and messaging strategies. *Front Sustain Food Syst.* (2020) 4:1–12. doi: 10.3389/fsufs.2020.00122

49. Slade P. If you build it, will they eat it? Consumer preferences for plant-based and cultured meat burgers. *Appetite.* (2018) 125:428–37. doi: 10.1016/j.appet.2018.02.030

50. Hallman WK, Hallman WK II. A comparison of cell-based and cell-cultured as appropriate common or usual names to label products made from the cells of fish. *J Food Sci.* (2021) 86:3798–809. doi: 10.1111/1750-3841.15860

51. Wilks M, Phillips CJ. Attitudes to in vitro meat: A survey of potential consumers in the United States. *PloS One.* (2017) 12:e0171904–14. doi: 10.1371/journal.pone.0171904

52. Hallman WK, Hallman WK. An empirical assessment of common or usual names to label cell-based seafood products. *J Food Sci.* (2020) 85:2267–2277.

53. Pasitka L, Cohen M, Ehrlich A, Gildor B, Reuveni E, Ayyash M, et al. Spontaneous immortalization of chicken fibroblasts generates stable, high-yield cell lines for serum-free production of cultured meat. *Nature Food.* (2022) 4:35–50. doi: 10.1038/s43016-022-00658-w

54. Takeda KF, Yazawa A, Yamaguchi Y, Koizumi N, Shineha R. Comparison of public attitudes toward five alternative proteins in Japan. *Food Qual Prefer.* (2023) 105:104787. doi: 10.1016/j.foodqual.2022.104787

55. Ong S, Loo L, Pang M, Tan R, Teng Y, Lou X, et al. Decompartmentalisation as a simple color manipulation of plant-based marbling meat alternatives. *Biomaterials.* (2021) 277:121107. doi: 10.1016/j.biomaterials.2021.121107

56. Lupton D, Turner B. Food of the future? Consumer responses to the idea of 3D-printed meat and insect-based foods. *Food & Foodways: History & culture of human nourishment.* (2018) 26:269–89. doi: 10.1080/07409710.2018.1531213

57. Tucker CA. The significance of sensory appeal for reduced meat consumption. *Appetite.* (2014) 81:168–79. doi: 10.1016/j.appet.2014.06.022

58. Lee M, Park S, Choi B, Kim J, Choi W, Jeong I, et al. Tailoring a gelatin/agar matrix for the synergistic effect with cells to produce high-quality cultured meat. *ACS Appl Mater Interfaces.* (2022) 14:38235–45. doi: 10.1021/acsmami.2c10988

59. Li H., Van Loo E. J., Trijp H C.M.Van, Chen J., Bai J. (2023). Will cultured meat be served on Chinese tables? A study of consumer attitudes and intentions about cultured meat in China. *Meat Sci*, 197,;109081. doi: 10.1016/j.meatsci.2022.109081

60. Sikorski ZE, Pokorny J, Damodaran S. Physical and chemical interactions of components in food systems In: S Damodaran, K Parkin and OR Fennema, editors. *Fennema's food chemistry*. Boca Raton, FL: CRC Press Taylor and Francis Group (2008). 850–81.

61. Farmer LJ, Patterson RL. Compounds contributing to meat flavour. *Food Chem.* (1991) 40:201–5. doi: 10.1016/0308-8146(91)90103-U

62. Khan MI, Jo C, Tariq MR. Meat flavor precursors and factors influencing flavor precursors—A systematic review. *Meat Sci.* (2015) 110:278–84. doi: 10.1016/j. meatsci.2015.08.002

63. Lawless HT, Heymann H. *Sensory evaluation of food: principles and practices*. New York: Springer (2010).

64. Grunert KG. The common ground between sensory and consumer science. *Curr Opin Food Sci.* (2015) 3:19–22. doi: 10.1016/j.cofs.2014.11.003

65. Weinrich R, Strack M, Neugebauer F. Consumer acceptance of cultured meat in Germany. *Meat Sci.* (2020) 162:107924. doi: 10.1016/j.meatsci.2019.107924

66. Lin-Hi N, Reimer M, Schäfer K, Böttcher J. Consumer acceptance of cultured meat: an empirical analysis of the role of organizational factors. *J Bus Econ.* (2023) 93:707–46. doi: 10.1007/s11573-022-01127-3

67. Koch JA, Bolderdijk JW, Van Ittersum K. Disgusting? No, just deviating from internalized norms. Understanding consumer skepticism toward sustainable food alternatives. *J Environ Psychol.* (2021) 76:101645. doi: 10.1016/j.jenvp.2021.101645

68. Bryant C, Barnett J. Consumer acceptance of cultured meat: an updated review (2018-2020). *Appl Sci.* (2020) 10:5201. doi: 10.3390/appl10155201

69. Hamlin RP, McNeill LS, Sim J. Food neophobia, food choice and the details of cultured meat acceptance. *Meat Sci.* (2022) 194:108964. doi: 10.1016/j. meatsci.2022.108964

70. Siddiqui SA, Khan S, Ullah Farooqi MQ, Singh P, Fernando I, Nagdalian A. Consumer behavior towards cultured meat: A review since 2014. *Appetite.* (2022) 179:106314. doi: 10.1016/j.appet.2022.106314

71. de Oliveira G A., Domingues C.H.F.De, Borges J. A. R. (2021). Analyzing the importance of attributes for Brazilian consumers to replace conventional beef with cultured meat. *PloS One*, 16,;e0251432. doi: 10.1371/journal.pone.0251432

72. Rosenfeld DL, Tomiyama AJ. Toward consumer acceptance of cultured meat. *Trends Cogn Sci.* (2023) 27:689–91. doi: 10.1016/j.tics.2023.05.002

73. Verbeke W, Hung Y, Baum CM, De Steur H. The power of initial perceived barriers versus motives shaping consumers' willingness to eat cultured meat as a substitute for conventional meat. *Livestock. (2021) 253:104705. doi: 10.1016/j.livsci.2021.104705

74. Baum CM, Verbeke W, De Steur H. Turning your weakness into my strength: how counter-messaging on conventional meat influences acceptance of cultured meat. *Food Qual Prefer.* (2022) 97:104485. doi: 10.1016/j.foodqual.2021.104485

75. Hocquette A, Lambert C, Sinquin C, Peteroffl L, Wagner Z, Bonny SPF, et al. Educated consumers don't believe artificial meat is the solution to the problems with the meat industry. *J Integr Agric.* (2015) 14:273–84. doi: 10.1016/S2095-3119(14)60886-8

76. Hopkins PD. Cultured meat in western media: the disproportionate coverage of vegetarian reactions, demographic realities, and implications for cultured meat marketing. *J Integr Agric.* (2015) 14:264–72. doi: 10.1016/S2095-3119(14)60883-2

77. Broucke K, Van Pamel E, Van Coillie E, Herman L, Van Royen G. Cultured meat and challenges ahead: A review on nutritional, technofunctional and sensorial properties, safety and legislation. *Meat Sci.* (2023) 195:109006. doi: 10.1016/j.meatsci.2022.109006

78. Hughes P, Marshall D, Reid Y, Parkes H, Gelber C. The costs of using unauthenticated, over-passaged cell lines: how much more data do we need? *Biotechniques.* (2007) 43:575–86. doi: 10.2144/000112598

79. Lazennec G, Jorgensen C. Concise review: adult multipotent stromal cells and cancer: risk or benefit? *Stem Cells.* (2008) 26:1387–94. doi: 10.1634/stemcells.2007-1006

80. Djisalov M, Knežić T, Podunavac I, Živojević K, Radonic V, Knežević NŽ, et al. Cultivating Multidisciplinarity: manufacturing and sensing challenges in cultured meat production. *Biology.* (2021) 10:204. doi: 10.3390/biology1003020
81. Siegrist M, Sütterlin B, Hartmann C. Perceived naturalness and evoked disgust influence acceptance of cultured meat. *Meat Sci.* (2018) 139:213–9. doi: 10.1016/j.meatsci.2018.02.007

82. Pakseresht A, Ahmadi Kaliji S, Canavari M. Review of factors affecting consumer acceptance of cultured meat. *Appetite.* (2022) 170:105829–9. doi: 10.1016/j.appet.2021.105829

83. Rubio NR, Xiang N, Kaplan DL. Plant-based and cell-based approaches to meat production. *Nat Commun.* (2020) 11:6276. doi: 10.1038/s41467-020-20061-y

84. Tan HSG, Fischer AR, van Trijp HC, Stieger M. Tasty but nasty? Exploring the role of sensory-liking and food appropriateness in the willingness to eat unusual novel foods like insects. *Food Qual Prefer.* (2016) 48:293–302. doi: 10.1016/j.foodqual.2015.11.001

85. Fountain H. (2013). A lab-grown burger gets a taste test—NYTimes.com. The New York Times. Available at: http://web.archive.org/web/20140706035754/http://www.nytimes.com/2013/08/06/science/a-lab-grown-burger-gets-a-taste-test.html?_r=0

86. Marta Z. Lab-grown beef taste test. 'Almost' like a burger. (2013). Washington Post. Available at: https://www.washingtonpost.com/national/health-science/lab-grown-beef-taste-test-almost-like-a-burger/2013/08/05/921a5996-fdf4-11e2-96a8-d3b921c0924a_story.html

87. Hwang J, You J, Moon J, Jeong J. Factors affecting consumers' alternative meats buying intentions: plant-based meat alternative and cultured meat. *Sustainability.* (2020) 12:5662. doi: 10.3390/su12145662

88. Wood P, Thorrez L, Hocquette J-F, Troy D, Gagaoua M. “Cellular agriculture”: current gaps between facts and claims regarding “cell-based meat”. *Anim Front.* (2023) 13:68–74. doi: 10.1093/af/vfac092

89. Dias LG, Meirinho SG, Veloso AC, Rodrigues LR, Peres AM. Electronic tongues and aptasensors In: Ligia R, Manuel M, editors. *Bioinspired materials for medical applications*. UK: Woodhead Publishing (2017). 371–402.

90. Sohail A, Al-Dalali S, Wang J, Xie J, Shakoor A, Asimi S, et al. Aroma compounds identified in cooked meat: A review. *Food Res Int.* (2022) 157:111385. doi: 10.1016/j.foodres.2022.111385

91. Whitfield FB, Mottram DS. Volatiles from interactions of Maillard reactions and lipids. *Crit Rev Food Sci Nutr.* (1992) 31:1–58. doi: 10.1080/10408399209527560

92. Mammasse N, Schlich P. Adequate number of consumers in a liking test. Insights from resampling in seven studies. *Food Qual Prefer.* (2014) 31:124–8. doi: 10.1016/j.foodqual.2012.01.009

93. Gacula M Jr, Rutenbeck S. Sample size in consumer test and descriptive analysis. *J Sens Stud.* (2006) 21:129–45. doi: 10.1111/j.1745-459X.2006.00055.x

94. Davis LA, Running CA. Good is sweet and bad is bitter: conflation of affective value of aromas with taste qualities in untrained participants. *J Sens Stud.* (2023) 38:e12820. doi: 10.1111/joss.12820

95. Chakraborty C, Agoramoorthy G. Stem cells in the light of evolution. *Indian J Med Res.* (2012) 135:813–9.

96. Jiwlawat N, Lynch E, Jeffrey J, Van Dyke JM, Suzuki M. Current Progress and challenges for skeletal muscle differentiation from human pluripotent stem cells using transgene-free approaches. *Stem Cells Int.* (2018) 2018:1–18. doi: 10.1155/2018/6241681

97. Mattick CS, Landis AE, Allenby BR, Genovese NJ. Anticipatory life cycle analysis of in vitro biomass cultivation for cultured meat production in the United States. *Environ Sci Technol.* (2015) 49:11941–9. doi: 10.1021/acs.est.5b01614

98. Tuomisto HL, Teixeira De Mattos MJ. Environmental impacts of cultured meat production. *Environ Sci Technol.* (2011) 45:6117–23. doi: 10.1021/es200130u

99. Lynch J, Pierrehumbert R. Climate impacts of cultured meat and beef cattle. *Front Sustain Food Syst.* (2019) 3:1–5. doi: 10.3389/fsufs.2019.00005

100. GASTROPOD. Where's the Beef? Lab-Grown Meat is Finally on the Menu— Gastropod. (2023). Available at: https://gastropod.com/wheres-the-beef-lab-grown-meat-is-finally-on-the-menu/

101. Kai K. Here It Comes ... the $375,000 lab-grown beef burger. (2013). Available at: https://www.science.org/content/article/here-it-comes-375000-lab-grown-beef-burger

102. TRANSCRIPT. Where's the beef? - gastropod. (2023). Available at: https://gastropod.com/transcript-wheres-the-beef/

103. Wiener-Bronner D. (2023). Lab-grown meat is cleared for sale in the United States | CNN business. CNN. Available at: https://www.cnn.com/2023/06/21/business/cultivated-meat-us-approval/index.html

104. Chriki S, Payet V, Pflanzer SB, Ellies-Oury MP, Liu J, Hocquette É, et al. Brazilian consumers' attitudes towards so-called "cell-based meat". *Foods*. (2021) 10:2588. doi: 10.3390/foods10112588

105. Liu J, Hocquette É, Ellies-Oury MP, Chriki S, Hocquette JF. Chinese consumers' attitudes and potential acceptance toward artificial meat. *Foods*. (2021) 10:353. doi: 10.3390/foods10020353
<figure><img src="image_50.png" /></figure>

Check for updates

OPEN ACCESS

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

REVIEWED BY
Antti Knaapila,
University of Helsinki, Finland
Alissa Allen Nolden,
University of Massachusetts Amherst,
United States

*CORRESPONDENCE

Stella Lignou

<figure><img src="image_51.png" /></figure>

s.lignou@reading.ac.uk

RECEIVED 27 November 2023

ACCEPTED 08 January 2024

PUBLISHED 05 February 2024

CITATION

McCarron R, Methven L, Grahl S, Elliott R and Lignou S (2024) Oat-based milk alternatives: the influence of physical and chemical properties on the sensory profile. *Front. Nutr.* 11:1345371.
doi: 10.3389/fnut.2024.1345371

COPYRIGHT

© 2024 McCarron, Methven, Grahl, Elliott and Lignou. This is an open-access article distributed under the terms of the [Creative Commons Attribution License (CC BY)](https://creativecommons.org/licenses/by/4.0/). 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.

# Oat-based milk alternatives: the influence of physical and chemical properties on the sensory profile

Roisin McCarron¹, Lisa Methven¹, Stephanie Grahl², Ruan Elliott³ and Stella Lignou¹*

¹Department of Food and Nutritional Sciences, Harry Nursten Building, University of Reading, Reading, United Kingdom, ²Arla Innovation Centre, Agro Food Park, Denmark, ³Department of Nutrition and Exercise Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom

**Introduction:** Oat-based milk alternatives (OMAs) have become increasingly popular, perhaps due to their low allergenicity and preferred sensory attributes when compared to other milk alternatives. They may also provide health benefits from unique compounds; avenanthramides, avenacosides, and the dietary fibre beta-glucan. This has led to a variety of commercial options becoming available. Being a fairly new product, in comparison to other plant-based milk alternatives (PBMAs), means little research has been undertaken on the sensory profile, and how it is influenced by the physical and chemical properties.

**Methods:** This study investigated the sensory, physical and chemical profiles of current commercially available OMAs, that varied in fortification, use of stabilisers, and oat content. The volatile compounds and their respective aromas were analysed using solid phase microextraction followed by gas chromatography mass spectrometry (GC-MS) and gas chromatography-olfactometry (GC-O). Liquid chromatography mass spectrometry (LC-MS) was used for identification of avenanthramides and avenacosides. Particle size and polydispersity index (PDI) were analysed using a Mastersizer and Zetasizer, respectively, with colour analysis carried out using a colourimeter, and viscosity measurements using a rheometer. Descriptive sensory profiling was used to assess the impact on the sensory characteristics of the different samples and the sensory data acquired were correlated with the instrumental data.

**Results:** Samples with smaller particle size appeared whiter—both instrumentally and perceptually. The only clear plastic packaged product differed substantially in volatile profile from all other products, with a higher abundance of many volatile compounds, and high overall perceived aroma. Avenanthramides and avenacosides were present in all samples, but differed significantly in abundance between them.
**Discussion:** The results suggested smaller particle size leads to whiter colour, whilst differences in processing and packaging may contribute to significant differences in aroma. Astringency did not differ significantly between samples, suggesting that the variation in the concentrations of avenacosides and avenanthramides were below noticeable differences.

KEYWORDS

oat, milk alternatives, sensory, physico-chemical, avenanthramides, GC-MS, particle size, LC-MS

# 1 Introduction

Plant based milk alternatives (PBMAs) have substantially increased in popularity, now accounting for around 8% of total retail “milk” sales in the UK (1). A shift away from cow’s milk may be due allergies and intolerances (2), and concerns over climate change, land and water use (3). Oat milk alternatives (OMAs) have received particular interest due to unique potential health benefits (2), including the presence of beta glucans — a dietary fibre shown to be beneficial in preventing diabetes, as well as lowering total blood cholesterol, and reducing the risk of cardiovascular diseases (4, 5). An increase in nut allergies (6) and soy allergies (7) make oat a popular alternative to other PBMA. Oats also contain unique compounds with antioxidant properties, including avenanthramides (8), a group of phenolic compounds unique to oats, which have been shown to have anti-inflammatory effects (9), and avenacosides, which exhibit antifungal properties (10).

However, OMAs may face nutritional, sensory, and physicochemical challenges. The qualities of oat milk have not yet been fully investigated in comparison to other PBMA s such as soya, which has been on the market for over 70 years and for which there is extensive available research and literature (7). Despite being designed to have similar sensory properties to cow’s milk, some consumers find the difference in attributes to be unacceptable (11) whilst the nutritional value tends to be low in comparison to bovine milk (12).

The full production process of oats to OMAs is described by Zhang et al. (13) to include the following steps: dehulling groats, flaking, wet milling, enzyme hydrolyses, decanting, followed by additional ingredient formulation, ultra-heat treatment (UHT), and finally storage. However, with a variety of commercial OMAs available, it is possible these production steps may vary considerably, leading to varying sensory, and physicochemical properties. Processing can lead to a loss of vitamins and minerals (14), with a shorter UHT holding time enabling beverages to retain a higher level of vitamins during storage (13). Processing methods may also modify the physicochemical characteristics of beta glucans, with these effects being highly process-dependant and difficult to predict (15). Some differences may be due to drivers in industry, with some producers driven more by flavour cues focussing on how the product looks, acts and tastes, some influenced by concern over environmental or health claims, and others by nutrition (1).

The appearance of OMAs has been shown to have a significantly lower whiteness index than cow's milk, making them easily

distinguishable (7). A slight brownish colour may be due to natural pigments, and colour differences could result from differences in size and concentration of particles (16). Colour analyses on milks has shown those with lower particle size have a higher lightness index than those with larger particle size, as a result of light scattering (17). This may lead to an “off-white” colour some consumers could find unappealing (16). Bovine milk and soy milk contain only a small fraction of large particles, whilst oat milk has been shown to have twice as many large particles (>3 µm) as small particles (<3 µm) (18). Stability may affected by the polydisperse distribution of particles in OMAs, leading to an increased separation rate, with high amounts of sedimentation and creaming (7). Particle size has also been found to be highly correlated with stability in milks — with more stable milks measuring smaller particles (18). The high concentration of starch in OMAs can lead to increased viscosity (2), whilst the fortification of PBMA s may lead to chemical instability of the nutrients and nutraceuticals added (11).

Off-flavours in OMAs may result from the presence of unsaturated fatty acids and lipoxygenases that can lead to the formation of n-hexanal and n-hexanol, which are associated with a “beany” or “off” flavour (2). Production and storage can lead to lipid degradation and oxidation, causing the development of these off-notes (13). This may be problematic, as hexanal is considered a rancidity marker and may affect the acceptability of OMAs (19). In order to provide sensory attributes similar to those of cow’s milk, many OMAs contain stabilisers, emulsifiers, and flavourings (1).

The phenolic compounds in oats, including the previously mentioned avenanthramides, may also affect the sensory properties, as these have been found to correlate with bitter and astringent sensations (20). Astringent compounds can react with salivary proteins, leading to a loss of lubricity and result in a rough-tactile feeling in the mouth (21). However, it still remains to be established as to whether the phenolic compounds in OMAs are present in sufficient quantities to be perceived as astringent. Research has also shown that these phytate and oxalates present in oats may have anti-nutritional effects, reducing absorption of minerals (22). Cow’s milk naturally provides a variety of minerals including calcium, as well as vitamins B₂, B₁₂, A, and E, therefore OMA’s may be fortified to closer match this (11). However, mineral fortification may be undermined if absorption of the added minerals is hindered by phenolics, phytate and oxalates. Cow’s milk also contains proteins with all of the essential amino acids required by humans, being highly digestible and bioavailable (23), whereas OMAs are generally low in protein in comparison (12), with just
<table><caption>TABLE 1 Stated ingredients for the six products used in this study collected from online sources and/or product packaging at time of purchase.</caption><thead><tr><td>Sample</td><td>Ingredients</td><td>Packaging</td><td>Shelf life</td></tr></thead><tbody><tr><td>A</td><td>Oat base (water, oats 10%), rapeseed oil, calcium carbonate, calcium phosphates, salt, vitamins (D2, riboflavin, B12), potassium iodide</td><td>Liquid carton packaging (paperboard)</td><td>Long life</td></tr><tr><td>B</td><td>Oats (15%), water, rapeseed oil, salt</td><td>Liquid carton packaging (paperboard)</td><td>Long life</td></tr><tr><td>C</td><td>Oats 9%, oat flour 1%, plant fibre from citrus, water, salt</td><td>Clear plastic</td><td>Short</td></tr><tr><td>D</td><td>Oat base [water, oat (9.8%)], chicory root fibre, sunflower oil, calcium (tri-calcium phosphate), sea salt, stabiliser (gellan gum), vitamins (B2, B12, D2)</td><td>Liquid carton packaging (paperboard)</td><td>Long life</td></tr><tr><td>E</td><td>Water, oats (10%), rapeseed oil, tricalcium phosphate, calcium carbonate, salt</td><td>Liquid carton packaging (paperboard)</td><td>Long life</td></tr><tr><td>F</td><td>Spring water, organic gluten-free oats (11%), organic cold-pressed sunflower oil, sea salt</td><td>Liquid carton packaging (paperboard)</td><td>Long life</td></tr></tbody></table>

0.4–1% protein content (24). The protein in oats is also limited in the amino acid lysine, and may have poor digestibility (25).

Differences in the physicochemical, and volatile profiles may affect the taste, appearance, mouthfeel, and functionality of products. The sensory profile may be affected by astringency, resulting from avenanthramides and avenacosides, whilst differences in processing and packaging may possibly lead to off-notes. It is also possible that particle size and polydispersity index may lead to differences in stability and appearance. These differences found in individual products may affect overall acceptability of OMAS. Therefore, this paper focuses on the sensory, physicochemical and volatile profile of existing OMAS, and explores how these relate to one another. The aim is to identify specific compounds and properties in OMA's and investigate how they contribute to the sensory profile. With such information it is anticipated that future developments in formulation and process optimisation may lead to an improved sensory profile of OMAS and increase consumer acceptability.

# 2 Materials and methods

## 2.1 Materials

### 2.1.1 Oat milk alternatives

Six different OMA products were used for analyses, labelled; A, B, C, D, E, and F. These were standard commercial products from the UK market and selected based on the commercial availability, with factors such as price, accessibility and popularity taken into consideration, in order to accurately reflect a range of standard products for the industry. The selected samples had varying levels of fortification (Table 1) in order to analyse the potential effect of this fortification on resulting sensory attributes. The nutritional composition of the samples also varied, as shown in Table 2. All products selected were original versions—avoiding “barista,” flavoured, or sugar-free alternatives, to ensure comparable products were assessed. All samples were UHT long shelf-life products packed in paperboard carton packaging, aside from sample C which was packaged in clear plastic, stored refrigerated and had a shorter shelf life. During this study commercial production of product C ceased, however, analysis of this product was completed as the substantial differences between this and other products were of interest. Samples from the same batch code were used for each sample for the sensory and flavour analyses, with the samples

opened and analysed within the same day for the sensory panel and GC-MS analyses. Mastersizer, Zetasizer and colourimeter analyses were also carried out within 24 h of opening from the same batch codes. Samples were then frozen, to be thawed at a later date for GC-O, LC-MS, and rheological analyses. Each analytical method was carried out in replicates from 3 separate cartons to account for batch to batch variation.

### 2.1.2 Chemicals

For solid-phase microextraction (SPME), compounds used as standards were obtained from Sigma-Aldrich Co. Ltd. (Gillingham, UK): 1,2-dichlorobenzene (10 ppm in methanol) and the alkane standards C<sub>6</sub>-C<sub>25</sub> (100 µg/mL) in diethyl ester. Sodium chloride, and HPLC grade water, methanol and hexane, were obtained from Fisher Scientific UK. LC-MS grade formic acid (98–100%) and acetonitrile were purchased from Merck (Darmstadt, Germany). Standards avenanthramide A (i.e., 2p), avenanthramide B (i.e., 2f), and avenanthramide C (i.e., 2c), avenanthramide D (phyproof<sup>®</sup>, and avenacoside A (>95%), were purchased from Sigma Aldrich Co. Ltd. (Gillingham, UK).

<table><caption>TABLE 2 Nutritional information of samples as stated on the product packaging at time of purchase.</caption><thead><tr><td>Typical values</td><td>A</td><td>B</td><td>C</td><td>D</td><td>E</td><td>F</td></tr></thead><tbody><tr><td>Energy (Kcal)</td><td>57</td><td>51</td><td>50</td><td>43</td><td>48</td><td>43</td></tr><tr><td>Fat (g)</td><td>2.8</td><td>1.5</td><td>0.8</td><td>1.5</td><td>2.1</td><td>1.6</td></tr><tr><td>Saturates (g)</td><td>0.3</td><td>0.3</td><td>0</td><td>0.1</td><td>0.2</td><td>0.4</td></tr><tr><td>Carbohydrate (g)</td><td>6.6</td><td>7.7</td><td>11</td><td>6.6</td><td>9.5</td><td>6.1</td></tr><tr><td>Sugars (g)</td><td>4.1</td><td>3.2</td><td>4.8</td><td>3.2</td><td>4.5</td><td>4.1</td></tr><tr><td>Fibre (g)</td><td>0.8</td><td></td><td>0</td><td>1.4</td><td></td><td>0.3</td></tr><tr><td>Protein (g)</td><td>1</td><td>1.3</td><td>0</td><td>0.3</td><td>0.2</td><td>0.8</td></tr><tr><td>Salt (g)</td><td>0.1</td><td>0.18</td><td>0.05</td><td>0.09</td><td>0.1</td><td>0.1</td></tr><tr><td>Vitamin B2 (mg)</td><td>0.21</td><td></td><td></td><td>0.21</td><td></td><td></td></tr><tr><td>Vitamin B12 (µg)</td><td>0.38</td><td></td><td></td><td>0.38</td><td></td><td></td></tr><tr><td>Vitamin D (µg)</td><td>1.1</td><td></td><td></td><td>0.75</td><td></td><td></td></tr><tr><td>Potassium (mg)</td><td>151</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calcium (mg)</td><td>120</td><td></td><td></td><td>120</td><td>120</td><td></td></tr><tr><td>Iodine (µg)</td><td>22.5</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
## 2.2 Sensory analysis

For the sensory analyses, descriptive sensory profiling was carried out over the course of 2 weeks, using the trained sensory panel at the Sensory Science Centre (University of Reading) comprising of eleven panellists. All panellists had a minimum of 6 months experience, as well as four specific sessions training (30-min each session) on the OMA's used during this study. During week one, vocabulary development and training sessions contributed to the selection of thirty-five different attributes for scoring. To develop these attributes, coded samples were given to the panellists, and they were asked to describe appearance, aroma, taste, flavour, mouthfeel, and aftertaste/after-effects and produce as many descriptive terms as seemed appropriate. Reference materials (Supplementary Table 1) were used for assessors to confirm if the attribute was the appropriate descriptor. The vocabulary development and training sessions were carried out in a discussion room, whilst the quantitative sensory assessment took place in isolated sensory booths, each equipped with an iPad.

Once the consensus vocabulary was set, the panellists re-evaluated the OMAs and decided on anchors for the line scales. This led to an agreed profile of 8 appearance terms, 4 odour terms, 10 taste/flavour terms, 4 mouthfeel terms and 9 aftertaste/after-effects terms. Compusense Cloud Software (Compusense, Guelph, ON, Canada) was used to acquire the sensory data. The samples were provided in glass cups, with a saucer placed over the top—prepared approximately 5 min in advance of each sampling to create a headspace for aroma detection, tested at room temperature. The samples were randomly assigned two three-digit codes each (one for each of the two repeats) and given to the panel in a sequential balanced order. Over 3 days, the panel analysed each of the samples twice, and scored for each attribute using unstructured line scales (0–100). Panellists were instructed to sniff the samples first to score the aroma attributes, then assess the appearance before tasting (and swallowing) the samples to score the overall taste/flavour and mouthfeel attributes. There was a 30-s pause after the end of mouthfeel attributes and the panellists then scored the after-effects. Between samples, panellists cleansed their palate with water and crackers, with a 30-s pause between samples.

## 2.3 Instrumental analysis

### 2.3.1 Volatile compounds

#### 2.3.1.1 Solid-phase microextraction followed by gas chromatography-mass spectrometry (SPME GC-MS)

Three millilitres of each sample were weighed into a SPME vial of 15 mL fitted with a screw cap and 0.5 g of sodium chloride was added along with 5 µL of 1,2-dichlorobenzene (10 ppm in methanol) as an internal standard. After equilibration at 40°C for 10 min, a 50/30 µm DVB/CAR/PDMS fibre was exposed to the headspace above the sample for 30 min. Four replicates from different product cartons were carried out over 3 days, in a randomised order each time. A blank run, using an empty carton, was used to ensure any volatile compounds from the lab or equipment were subtracted, as well as gain an indication of what compounds were present from the packaging. For this, a carton from Sample A was rinsed thoroughly and shaken with

water, with 3 mL of this water analysed as a blank run. After extraction, the SPME fibre was inserted into the injection port of an Agilent 7890A-5975C gas chromatography mass spectrometer equipped with an automated injection system (CTC-CombiPAL). For the chromatographic separation, a capillary column HP-5MS (30 m × 0.25 mm × 0.25 µm film thickness) (Agilent, Santa Clara, CA, USA) was used. The oven temperature programme used was 2 min at 40°C isothermal and an increase 4°C/min to 250°C. Helium was used at 3 mL/min as carrier gas. The sample injection mode was splitless. Mass spectra were measured in electron ionisation mode with an ionisation energy of 70 eV, the scan range from 20 to 280 m/z and the scan rate of 5.3 scans/s. The data were recorded by HP G1034 Chemstation system. Volatile compounds were identified or tentatively identified by comparison of each mass spectrum with spectra from authentic compounds analysed in our laboratory, or from the NIST mass spectral database (26), or spectra published elsewhere. A spectral quality value of >80 was used alongside linear retention index (LRI) to support the identification of compounds where no authentic standards were available. LRI was calculated for each volatile compound using the retention times of a homologous series of C<sub>6</sub>-C<sub>25</sub> n-alkanes and by comparing the LRI with those of authentic compounds analysed under similar conditions. The approximate quantification of volatile compounds was calculated from GC peak areas, by comparison with the peak area of the 1,2-dichlorobenzene standard, using a response factor of 1.

#### 2.3.1.2 Solid-phase microextraction followed by gas chromatography-olfactometry (SPME GC-O)

After extraction (using the same optimal extraction conditions as used for GC-MS), the SPME fibre was inserted into the injection port of an Agilent 7890B series ODO 2 (SGE) GC-O system equipped with an HP-5MS column (30 m × 0.25 mm × 0.25 µm film thickness). The outlet was split between a flame ionisation detector and a sniffing port. The injector and detector temperatures were maintained at 280 and 250°C, respectively. The oven temperature programme used was 2 min at 40°C isothermal and an increase 4°C/min to 250°C. Helium was used at 2 mL/min as carrier gas. Three assessors with normal olfactory function, from the Department of Food and Nutritional Sciences, were trained and carried out the procedure. Each assessor evaluated by sniffing each sample in duplicate and documented the odour description, retention time, and odour intensity (OI) on a seven-point scale (2–8), where <3 = weak, 5 = medium, and >7 = strong. n-Alkanes C<sub>6</sub>-C<sub>25</sub> were analysed under the same conditions to obtain LRI values for comparison with the GC-MS data.

### 2.3.2 Avenanthramides and avenacosides

#### 2.3.2.1 Sample preparation

The extraction was conducted according to Günther-Jordanland et al. (20), with some modifications to adapt from oats to oat-based milk. Each sample (10 mL) was placed into a separating funnel and 10 mL of hexane was added, shaken for 5 s and left to equilibrate for 15 min before removing the fat. The samples were then centrifuged at 4°C for 10 min at 9000 rpm, then the remaining hexane and fat layer was removed using a glass mini pipette. After this step, 500 µL of the sample was added to 1.5 mL of acetonitrile containing 50 µL of formic acid. This was then shaken for 1 h, centrifuged for 10 min at 9000 rpm, filtered
using a 1.4 µm filter and analysed by LC-MS/MS. Each sample was
analysed in triplicate.

2.3.2.2 LC-MS/MS analysis

An aliquot (1µL) of the prepared sample was injected into a UPLC-MS/MS QQQ system, LCMS 8050 (Shimadzu) combined with Luna Phenyl-Hexyl (150 mm × 2.0 mm inner diameter, 5 µm, Phenomenex, Aschaffenburg, Germany) equipped with a guard column of the same type. Eluent A was composed of 0.1% formic acid in water, and Eluent B was composed of 0.1% formic acid in acetonitrile. Using a flow rate of 300 µL/min, the system was operated at 25°C, starting with 32% B under isocratic conditions for 1 min, then increasing the content of B to 70% over 3 min, followed by an increase to 100% B over 2 min, and keeping isocratic conditions for 3 min. Eluent was pumped down again to 32% over 2 min and held isocratically for a further 3 min. Analysis was performed in ESI- mode using the following MRM transitions: avenanthramide A: 298 > 254.15 298 > 133.9 298 > 159.85, avenanthramide B: 327.8 > 284.25, 327.8 > 268.1, 327.8 > 160.85, avenanthramide C: 314 > 178.2, 314 > 134.85, 314 > 134.2, avenanthramide D: 282 > 238.2, 282 > 118.95, 282 > 144.85, avenacoside A: 1061.7 > 899.3, 1061.7 > 163. Dwell time was 10 ms for each transition and Q1, collision energy and Q3 voltages were optimised using standards of each compound.

The calibration curves were run with a linear curve fit,
a weighting of 1/C^2, and were not forced through the
origin. A quantitative method with external standards was used;
avenanthramide A, B, C (referred to in some literature as Bp,
Bf, and Bc, respectively) and D, as well as avenacoside A.
According to literature avenanthramides A, B and C are the
three major forms in oats (9), with avenacoside A as another
primary component (27), and thus a targetted approach was
followed searching for these compounds. Each standard was
diluted with 75% acetonitrile, 25% water, in order to match the
sample conditions for solvent composition. Quantifier ions used for
identification were; avenanthramide A 298 > 254, avenanthramide
B 328 > 284, avenanthramide C 314 > 178, avenanthramide D
282 > 238, and avenacoside A 1107.05 > 1061.45, respectively.
Data acquisition and quantification was performed in Labsolutions
Insight software (Shimadzu).

2.3.3 Colour analysis

Using a colourimeter, Konica Minolta Chroma metre CR-400,
CIELAB system (illuminant C, 10° viewing angle, with an 8 mm
diameter port), three repeated measurements were obtained for
each sample. The samples were held in a glass cell (diameter
60 mm × 15 mm) and the lightness (L*), red/green coordinate
(± a*) and yellow/blue coordinate (± b*) were recorded to give
a measure of the lightness and colour.

2.3.4 Particle size analysis

A Malvern Mastersizer S was used to obtain measurements of
particle size [suitable for readings above 1 µm (1000 nm)]. Three
repeats were carried out, one after the other on the instrument,
with the water flushed out between each reading to reduce residual
particles. A Malvern nanoseries ZS zetasizer was used to obtain
measurements of the polydispersity index. Polydispersity index is
a measure of the heterogeneity of a sample based on size, and is

determined by dynamic light scattering (28). Each sample (1 ml aliquot in a cuvette) was measured in triplicate, with three technical replicates per aliquot. Data were recorded and analysed using the Malvern zetasizer software. Default settings were selected with Angle 173, with run conditions 25°C for 200 s.

2.3.5 Rheological properties

Rheological properties were studied using a controlled stress rheometer (MCR 302, Anton Paar Ltd. St Albans, UK) using parallel plate geometry (50 mm diameter). OMA samples were frozen and thawed prior to rheological analyses. The gap size was 1 mm and a resting time of 300 s prior to measurement was established for sample relaxation and temperature equilibration. Apparent viscosity was measured as a function of shear rate over the 1 to 1000 s⁻¹ range, at 25°C. Measurements were carried out in triplicate for each of the samples, with an average viscosity calculated for each at shear rate 50 s⁻¹.

2.4 Statistical analysis

The quantitative data for each compound identified in the GC-MS and LC-MS analyses, or physicochemical measurements (colour, particle size, PDI, viscosity) were analysed by one-way analysis of variance (ANOVA) using XLSTAT Sensory (Version 2022.5. 1. 1388). For those compounds or physicochemical parameters exhibiting significant difference in the one-way ANOVA, Tukey's honest significant difference (HSD) test was applied for multiple pairwise comparisons. SENPAQ (Qi Statistics, Kent, UK) was used to carry out ANOVA and principal component analysis (PCA) using the covariance matrix, of the sensory panel data. For the sensory data two-way ANOVA was used where the samples were fitted to fixed effects and the assessor as random effects, and both of these treatments were tested against the sample by assessor interaction. Tukey's HSD post-hoc test was applied for pairwise comparisons. In all multiple pairwise comparisons, significance was assumed at *p* ≤ 0.05. Multiple factor analysis was applied to correlate the means for the sensory data (taken over the assessors) with the means of volatile data.

3 Results

3.1 Sensory analysis

The trained sensory panel agreed to use 35 terms for the
quantitative assessment of the samples and the mean panel scores
for these attributes are shown in Table 3. Overall, 16 out of 34
attributes were significantly different between the six samples. The
panellists' individual results were analysed for repeatability and
reliability. No obvious anomalies were observed as the panel scored
to a consistent standard with one another.

Significant differences were found in all appearance attributes,
with sample C displaying the most off-white colour, yet the least
froth/foam, bubble size and glass cling. Samples E and F were
found to have significantly less off-white colour than all other
samples, whilst sample A displayed the most glass- cling. For aroma,
significance was found within the overall aroma intensity, wet oats,
<table><caption>TABLE 3 Mean panel scores for sensory attributes of the six OMA samples.</caption><thead><tr><th rowspan="2">Attributes</th><th colspan="6">Mean score (0-100)<sup>a</sup></th><th rowspan="2">Significance of sample<br>(p-value)<sup>b</sup></th></tr><tr><th>A</th><th>B</th><th>C</th><th>D</th><th>E</th><th>F</th></tr></thead><tbody><tr><td><strong>Aroma</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Overall intensity</td><td>32.8<sup>ab</sup></td><td>26.9<sup>b</sup></td><td>41.4<sup>a</sup></td><td>33.3<sup>ab</sup></td><td>33.5<sup>ab</sup></td><td>35.8<sup>ab</sup></td><td>0.002</td></tr><tr><td>Sweet</td><td>18.0</td><td>16.3</td><td>22.6</td><td>20.9</td><td>19.6</td><td>21.0</td><td>0.172</td></tr><tr><td>Wet oat</td><td>25.4<sup>ab</sup></td><td>18.8<sup>b</sup></td><td>33.6<sup>a</sup></td><td>27.3<sup>ab</sup></td><td>27.1<sup>ab</sup></td><td>31.1<sup>a</sup></td><td>0.002</td></tr><tr><td>Malt</td><td>12.7<sup>a</sup></td><td>2.7<sup>b</sup></td><td>10.0<sup>ab</sup></td><td>8.3<sup>ab</sup></td><td>7.9<sup>ab</sup></td><td>6.6<sup>ab</sup></td><td>0.031</td></tr><tr><td>Nutty</td><td>3.7</td><td>1.8</td><td>5.9</td><td>5.9</td><td>4.3</td><td>7.8</td><td>0.196</td></tr><tr><td>Stale</td><td>7.0</td><td>8.0</td><td>8.4</td><td>4.4</td><td>8.9</td><td>6.2</td><td>0.670</td></tr><tr><td>Single cream</td><td>0.4</td><td>1.7</td><td>0.4</td><td>3.0</td><td>0.5</td><td>2.8</td><td>0.183</td></tr><tr><td>Brown bread</td><td>12.9<sup>ab</sup></td><td>1.6<sup>c</sup></td><td>16.8<sup>a</sup></td><td>10.8<sup>abc</sup></td><td>15.5<sup>ab</sup></td><td>6.4<sup>bc</sup></td><td>0.0001</td></tr><tr><td><strong>Appearance</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Off white colour</td><td>56.4<sup>ab</sup></td><td>52.3<sup>b</sup></td><td>67.3<sup>a</sup></td><td>50.5<sup>b</sup></td><td>39.3<sup>c</sup></td><td>31.0<sup>c</sup></td><td>&lt;0.0001</td></tr><tr><td>Glass cling</td><td>41.8<sup>a</sup></td><td>29.9<sup>b</sup></td><td>24.8<sup>b</sup></td><td>28.9<sup>b</sup></td><td>26.0<sup>b</sup></td><td>35.6<sup>ab</sup></td><td>&lt;0.001</td></tr><tr><td>Froth/foam</td><td>47.2<sup>a</sup></td><td>43.6<sup>a</sup></td><td>26.3<sup>b</sup></td><td>37.7<sup>ab</sup></td><td>39.9<sup>ab</sup></td><td>46.9<sup>a</sup></td><td>&lt;0.001</td></tr><tr><td>Bubble size</td><td>25.9<sup>a</sup></td><td>26.3<sup>a</sup></td><td>14.5<sup>b</sup></td><td>24.5<sup>a</sup></td><td>26.6<sup>a</sup></td><td>28.2<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td><strong>Taste</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sweet</td><td>27.1<sup>ab</sup></td><td>25.4<sup>ab</sup></td><td>21.9<sup>b</sup></td><td>30.4<sup>a</sup></td><td>28.7<sup>ab</sup></td><td>25.1<sup>ab</sup></td><td>0.034</td></tr><tr><td>Bitter</td><td>12.2</td><td>12.3</td><td>15.0</td><td>9.2</td><td>9.7</td><td>14.5</td><td>0.087</td></tr><tr><td>Acid/tang</td><td>3.6</td><td>7.5</td><td>9.8</td><td>4.6</td><td>5.5</td><td>7.3</td><td>0.162</td></tr><tr><td>Metallic</td><td>8.0</td><td>9.6</td><td>9.4</td><td>7.1</td><td>7.6</td><td>8.8</td><td>0.801</td></tr><tr><td><strong>Flavour</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Malty</td><td>9.7</td><td>4.9</td><td>6.8</td><td>10.5</td><td>6.6</td><td>4.8</td><td>0.260</td></tr><tr><td>Wet oats</td><td>29.3</td><td>27.9</td><td>32.6</td><td>29.0</td><td>29.8</td><td>33.1</td><td>0.434</td></tr><tr><td>Nutty</td><td>6.0</td><td>6.9</td><td>6.2</td><td>9.0</td><td>9.2</td><td>12.2</td><td>0.105</td></tr><tr><td>Stale</td><td>6.7</td><td>5.3</td><td>7.2</td><td>3.8</td><td>5.7</td><td>4.4</td><td>0.653</td></tr><tr><td>Single cream</td><td>7.3<sup>ab</sup></td><td>9.5<sup>a</sup></td><td>0.0<sup>b</sup></td><td>9.2<sup>ab</sup></td><td>10.4<sup>a</sup></td><td>9.2<sup>ab</sup></td><td>0.024</td></tr><tr><td>Brown bread</td><td>11.5<sup>ab</sup></td><td>4.9<sup>b</sup></td><td>14.8<sup>a</sup></td><td>10.1<sup>ab</sup></td><td>11.5<sup>ab</sup></td><td>6.2<sup>ab</sup></td><td>0.008</td></tr><tr><td><strong>Mouthfeel</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mouthcoating</td><td>32.7</td><td>32.0</td><td>23.3</td><td>26.7</td><td>27.3</td><td>29.7</td><td>0.101</td></tr><tr><td>Body</td><td>31.5<sup>a</sup></td><td>26.4<sup>a</sup></td><td>18.2<sup>b</sup></td><td>28.8<sup>a</sup></td><td>26.5<sup>a</sup></td><td>30.3<sup>a</sup></td><td>&lt;0.001</td></tr><tr><td>Powdery</td><td>13.8<sup>ab</sup></td><td>22.8<sup>a</sup></td><td>22.4<sup>a</sup></td><td>7.0<sup>b</sup></td><td>7.1<sup>b</sup></td><td>6.7<sup>b</sup></td><td>0.0001</td></tr><tr><td>Astringency</td><td>14.3</td><td>18.8</td><td>21.4</td><td>13.8</td><td>17.6</td><td>16.9</td><td>0.135</td></tr><tr><td><strong>Aftertaste</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Bitter</td><td>10.6</td><td>9.2</td><td>14.0</td><td>9.0</td><td>9.2</td><td>12.6</td><td>0.288</td></tr><tr><td>Metallic</td><td>8.4</td><td>10.5</td><td>11.5</td><td>6.0</td><td>7.5</td><td>8.8</td><td>0.068</td></tr><tr><td>Sweet</td><td>16.5<sup>ab</sup></td><td>20.2<sup>a</sup></td><td>13.3<sup>b</sup></td><td>17.5<sup>ab</sup></td><td>19.6<sup>ab</sup></td><td>16.5<sup>ab</sup></td><td>0.040</td></tr><tr><td>Wet oats</td><td>19.4</td><td>19.6</td><td>23.4</td><td>19.8</td><td>21.2</td><td>24.1</td><td>0.387</td></tr><tr><td>Single cream</td><td>3.1</td><td>8.3</td><td>0.4</td><td>8.0</td><td>7.9</td><td>5.3</td><td>0.023</td></tr><tr><td><strong>After effects</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mouthcoating</td><td>18.4</td><td>18.6</td><td>13.0</td><td>17.9</td><td>16.6</td><td>14.9</td><td>0.225</td></tr><tr><td>Powdery</td><td>11.1</td><td>12.9</td><td>13.6</td><td>4.8</td><td>5.6</td><td>4.8</td><td>0.006</td></tr><tr><td>Astringent</td><td>19.8</td><td>18.3</td><td>18.8</td><td>14.4</td><td>16.7</td><td>16.5</td><td>0.467</td></tr><tr><td>Salivating</td><td>20.6</td><td>23.5</td><td>23.5</td><td>20.7</td><td>22.2</td><td>24.4</td><td>0.700</td></tr></tbody></table>

<footnote><sup>a</sup>Means not labelled with the same letters are significantly different (p < 0.05); means are from two replicate samples. <sup>b</sup>Probability of a significant difference between samples.</footnote>
malt and brown bread aromas. Overall intensity was highest in sample C, as well as wet oats and brown bread, yet the malty aroma was highest in sample A. In terms of significant differences in taste, sample D was found to be the sweetest, with sample C the least sweet. For flavour, sample C was the highest in the brown bread note, yet was the only sample to score no single cream flavour at all. Significant differences were found in the mouthfeel of the samples, with A scoring the highest in body, whilst sample C was the lowest. Samples B and C also had significantly more powdery mouthfeel than all other samples. For aftertaste, B was found to be the most sweet, with sample C again being the least. There were no significant differences for any other after effects. Although there were no significant differences between samples for astringency, within mouthfeel or as an after-effect, astringency was perceived in all samples. The relationship between this astringency and non-volatile compounds was further evaluated.

## 3.2 Instrumental analysis

### 3.2.1 Volatile compounds

#### 3.2.1.1 GC-MS-Optimisation of the extraction conditions

In order to determine the optimal conditions for volatile extraction, sample A was used with varying conditions, based on previous studies of other plant-based alternatives (29, 30), as well as bovine milk (31). The following parameters were evaluated: incubation and extraction temperature (40°C and 50°C), incubation time (10, 20 and 30 min), extraction time (10, 20, and 30 min), and salt (sodium chloride) addition varied from 0, 0.5, 0.75, and 1 g. Optimal conditions were selected considering the overall amount of the extracted volatiles. Increasing salt from 0 to 0.5 g resulted in an improved efficacy of the extraction, however, increasing above 0.5 g showed no additional effect, therefore 0.5 g was selected. Additionally, increasing incubation time above 10 min showed no obvious differences, whereas increasing the extraction time from 10 to 30 min resulted in more abundant peaks. Finally, increasing the temperature above 40°C did not improve efficacy of the procedure, therefore 40°C was selected as the incubation and extraction temperature. In conclusion, the optimal parameters were set at 40°C, 10 min incubation time, 30 min extraction time, and addition of 0.5 g of NaCl.

#### 3.2.1.2 SPME GC-MS

More than 35 compounds were identified in the headspace of the six samples (Table 4) including four esters, eleven aldehydes, five ketones, four terpenes, one alkane, three alkenes, three alcohols, and four furans.

Of the esters, sample C was significantly lower in methyl propanoate, methyl butanoate, and methyl 2-methylbutanoate, however, it exhibited the highest abundance in methyl acetate. Samples A and E were generally higher in esters, both being the highest in methyl butanoate and methyl propanoate, whilst A, E and B were significantly higher than C in butanoic acid.

Hexanal was the most abundant aldehyde in the samples, and was significantly higher in sample F, followed by sample C. Sample D exhibited significantly more 2-heptenal and furfural than all others, whilst sample C was found to have high abundance in octanal, 3-methylbutanal and 2-methylbutanal, and was the only

sample to contain non-anal. Sample E was the second highest in 3-methylbutanal, 2-methylbutanal and octanal, whilst being the highest in 2-methylpropanal. Sample B was generally found to have low levels of aldehydes such as 2-methylpropanal and heptanal, with no 2-hexanal, furfural, 2-heptenal, octanal or non-anal being detected. B was also significantly lower than all others aside from F in 3-methylbutanal and 2-methylbutanal. Despite being lower in 3-methylbutanal and 2-methylbutanal, F exhibited the highest abundance in heptanal and 2-hexanal, a compound only present in C and F.

Of the alcohols detected, sample F was significantly higher than all others in hexanol and pentanol. Octen-3-ol was present in all samples, with C exhibiting significantly higher abundance than A and E.

In terms of ketones, sample E was abundant in 2-butanone, butanedione, and 3 methyl 2-butanone. 6-methyl-5-hepten-2-one was only detected in sample C, whilst 3-methyl-2-pentanone was detected in only B and C.

Of the furans, 2-pentylfuran was significantly higher in sample E, followed by, A, and then C. Sample B exhibited the lowest abundance in all furans aside from 2-ethylfuran, which it was found to be the second lowest, following sample D.

Most terpenes, including alpha-pinene, beta-pinene and camphene were highest in sample B, whereas limonene was the highest in sample C.

Multiple factor analysis was used to determine correlations between the sensory results and volatile compounds for each sample (Figure 1), from which multiple significant correlations were found. Brown bread aroma was found to be significantly positively correlated with 2-methylpropanal, 3-methylbutanal and 2-methylbutanal—all branched chain aldehydes described as having a malty and chocolate aroma (32), as well as with methyl acetate. Brown bread flavour was also significantly positively correlated with methyl acetate, 2-methylbutanal and 3-methylbutanal. 3-methylbutanal is an amino acid-derived key flavour compound in bread, with a fairly low taste threshold (32), which may have resulted in the brown bread aroma and flavour correlation.

A nutty aroma was found to be positively correlated with heptanal, a compound typically described as having a fatty aroma when in isolation (33). Sweet and wet oats aroma were also both found to be significantly positively correlated with heptanal, yet negatively correlated with methyl 2-methylbutanoate.

Wet oats flavour was shown to be positively correlated with hexanal, which often imparts a green aroma (33), as well as with pentanol, 2-hexenal and heptanal, yet was again negatively correlated with methyl 2-methylbutanoate. Single cream flavour was significantly positively correlated with methyl propanoate and 3-methyl-2-butanone, whilst being negatively correlated with benzaldehyde, 6-methyl-5-hepten-2-one, limonene and non-anal.

Sensory attributes malty, stale and single cream aroma, and malty, nutty and stale flavour, were not found to be significantly positively or negatively correlated with any compounds identified in the samples.

#### 3.2.1.3 SPME GC-O

Gas chromatography-olfactometry analysis of the samples yielded a total of 24 distinct odorants in the chromatogram that were of note due to multiple panellists perceiving them, which are
<table><caption>TABLE 4 Volatile compounds identified in the headspace of six samples analysed by SPME GC-MS.</caption><thead><tr><th rowspan="2">Compounds</th><th rowspan="2">LRI<sup>a</sup></th><th rowspan="2">Aroma descriptor<sup>b</sup></th><th colspan="6">Estimated quantities<sup>c</sup></th><th rowspan="2">Significance (p-value)<sup>d</sup></th></tr><tr><th>A</th><th>B</th><th>C</th><th>D</th><th>E</th><th>F</th></tr></thead><tbody><tr><td colspan="10"><strong>Esters</strong></td></tr><tr><td>Methyl acetate</td><td>515</td><td>Sweet</td><td>1.57<sup>bc</sup></td><td>1.17<sup>c</sup></td><td>3.73<sup>a</sup></td><td>2.17<sup>abc</sup></td><td>3.56<sup>ab</sup></td><td>1.08<sup>c</sup></td><td>0.001</td></tr><tr><td>Methyl propanoate</td><td>629</td><td>Fruity, rum</td><td>8.49<sup>a</sup></td><td>6.28<sup>ab</sup></td><td>2.62<sup>b</sup></td><td>6.36<sup>ab</sup></td><td>8.55<sup>a</sup></td><td>7.06<sup>a</sup></td><td>0.003</td></tr><tr><td>Methyl butanoate</td><td>720</td><td>Fruity, creamy</td><td>11.37<sup>a</sup></td><td>7.74<sup>ab</sup></td><td>4.76<sup>b</sup></td><td>9.52<sup>ab</sup></td><td>12.82<sup>a</sup></td><td>9.46<sup>ab</sup></td><td>0.013</td></tr><tr><td>Methyl 2-methylbutanoate</td><td>775</td><td>Fruity</td><td>5.46<sup>a</sup></td><td>5.56<sup>a</sup></td><td>2.12<sup>b</sup></td><td>4.57<sup>ab</sup></td><td>5.21<sup>ab</sup></td><td>3.60<sup>ab</sup></td><td>0.020</td></tr><tr><td colspan="10"><strong>Aldehydes</strong></td></tr><tr><td>2-Methylpropanal</td><td>552</td><td>Wet cereal, straw</td><td>1.21<sup>bc</sup></td><td>0.70<sup>c</sup></td><td>2.48<sup>ab</sup></td><td>1.24<sup>bc</sup></td><td>2.87<sup>a</sup></td><td>1.37<sup>abc</sup></td><td>0.002</td></tr><tr><td>3-Methylbutanal</td><td>649</td><td>Fruity</td><td>6.29<sup>b</sup></td><td>2.35<sup>b</sup></td><td>15.10<sup>a</sup></td><td>7.08<sup>b</sup></td><td>14.40<sup>a</sup></td><td>2.34<sup>b</sup></td><td>&lt;0.0001</td></tr><tr><td>2-Methylbutanal</td><td>659</td><td>Cocoa</td><td>5.11<sup>bcd</sup></td><td>2.39<sup>cd</sup></td><td>10.06<sup>ab</sup></td><td>6.10<sup>bc</sup></td><td>7.77<sup>ab</sup></td><td>1.93<sup>d</sup></td><td>&lt;0.0001</td></tr><tr><td>Hexanal</td><td>802</td><td>Green</td><td>94.29<sup>c</sup></td><td>31.76<sup>d</sup></td><td>207.09<sup>b</sup></td><td>54.71<sup>cd</sup></td><td>40.86<sup>cd</sup></td><td>316.31<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>2-Hexenal</td><td>853</td><td>Green</td><td>nd<sup>c</sup></td><td>nd<sup>c</sup></td><td>1.13<sup>b</sup></td><td>nd<sup>c</sup></td><td>nd<sup>c</sup></td><td>1.89<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>Furfural</td><td>836</td><td>Bready</td><td>nd<sup>a</sup></td><td>nd<sup>a</sup></td><td>2.65<sup>a</sup></td><td>11.96<sup>a</sup></td><td>nd<sup>a</sup></td><td>nd<sup>a</sup></td><td>0.163</td></tr><tr><td>Heptanal</td><td>903</td><td>Green</td><td>3.05<sup>cd</sup></td><td>1.59<sup>d</sup></td><td>6.39<sup>a</sup></td><td>5.75<sup>ab</sup></td><td>4.17<sup>bc</sup></td><td>6.65<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>(2E)-Heptenal</td><td>951</td><td>Green</td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>2.37<sup>b</sup></td><td>23.52<sup>a</sup></td><td>5.92<sup>b</sup></td><td>4.92<sup>b</sup></td><td>&lt;0.0001</td></tr><tr><td>Benzaldehyde</td><td>959</td><td>Almond</td><td>1.38<sup>b</sup></td><td>1.26<sup>b</sup></td><td>2.12<sup>a</sup></td><td>0.92<sup>bc</sup></td><td>0.47<sup>c</sup></td><td>1.34<sup>b</sup></td><td>0.000</td></tr><tr><td>Octanal</td><td>1007</td><td>Fruit-like</td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>2.97<sup>a</sup></td><td>nd<sup>b</sup></td><td>2.61<sup>a</sup></td><td>nd<sup>b</sup></td><td>&lt;0.0001</td></tr><tr><td>Non-anal</td><td>1087</td><td>Rose-orange</td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>5.10<sup>a</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>0.00</td></tr><tr><td colspan="10"><strong>Ketones</strong></td></tr><tr><td>Butanedione</td><td>593</td><td>Buttery</td><td>2.33<sup>c</sup></td><td>1.84<sup>c</sup></td><td>3.58<sup>abc</sup></td><td>5.35<sup>ab</sup></td><td>6.04<sup>a</sup></td><td>2.51<sup>bc</sup></td><td>0.001</td></tr><tr><td>2-Butanone</td><td>598</td><td>Sharp sweet</td><td>34.38<sup>ab</sup></td><td>20.47<sup>bc</sup></td><td>12.69<sup>c</sup></td><td>21.60<sup>bc</sup></td><td>42.90<sup>a</sup></td><td>25.24<sup>abc</sup></td><td>0.002</td></tr><tr><td>2-Methyl-3-pentanone</td><td>749</td><td>Mint</td><td>nd<sup>c</sup></td><td>6.87<sup>a</sup></td><td>3.21<sup>c</sup></td><td>nd<sup>c</sup></td><td>nd<sup>c</sup></td><td>nd<sup>c</sup></td><td>&lt;0.0001</td></tr><tr><td>3-Methyl-2-butanone</td><td>661</td><td>Camphor</td><td>11.10<sup>a</sup></td><td>10.08<sup>a</sup></td><td>3.76<sup>b</sup></td><td>8.73<sup>ab</sup></td><td>11.72<sup>a</sup></td><td>9.10<sup>ab</sup></td><td>0.007</td></tr><tr><td>6-Methyl-5-hepten 2-one</td><td>787</td><td>Citrus, fruity</td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>5.16<sup>a</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>&lt;0.0001</td></tr><tr><td colspan="10"><strong>Furans</strong></td></tr><tr><td>2-Methylfuran</td><td>603</td><td>Chocolate</td><td>0.67<sup>bc</sup></td><td>0.16<sup>c</sup></td><td>1.26<sup>b</sup></td><td>0.94<sup>bc</sup></td><td>2.37<sup>a</sup></td><td>1.00<sup>bc</sup></td><td>&lt;0.0001</td></tr><tr><td>3-Methylfuran</td><td>611</td><td></td><td>0.40<sup>a</sup></td><td>nd<sup>b</sup></td><td>0.32<sup>a</sup></td><td>nd<sup>b</sup></td><td>0.36<sup>a</sup></td><td>0.27<sup>ab</sup></td><td>0.000</td></tr><tr><td>2-Ethylfuran</td><td>700</td><td>Malty, beany</td><td>4.53<sup>b</sup></td><td>0.57<sup>d</sup></td><td>2.66<sup>cd</sup></td><td>0.45<sup>d</sup></td><td>1.74<sup>cd</sup></td><td>6.18<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>2-Pentyl furan</td><td>992</td><td>Fruity, green</td><td>15.50<sup>b</sup></td><td>2.46<sup>c</sup></td><td>12.62<sup>b</sup></td><td>4.55<sup>c</sup></td><td>3.88<sup>c</sup></td><td>33.23<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td colspan="10"><strong>Alkanes</strong></td></tr><tr><td>Octane</td><td>800</td><td>Gasoline</td><td>12.66<sup>c</sup></td><td>132.70<sup>a</sup></td><td>6.32<sup>c</sup></td><td>49.52<sup>b</sup></td><td>120.59<sup>a</sup></td><td>32.43<sup>bc</sup></td><td>&lt;0.0001</td></tr><tr><td>1-Octene</td><td>794</td><td>Gasoline</td><td>nd<sup>c</sup></td><td>nd<sup>c</sup></td><td>0.76<sup>c</sup></td><td>14.10<sup>b</sup></td><td>18.65<sup>a</sup></td><td>nd<sup>c</sup></td><td>&lt;0.0001</td></tr><tr><td>(E)-2-Octene</td><td>804</td><td></td><td>nd<sup>c</sup></td><td>1.25<sup>c</sup></td><td>0.91<sup>c</sup></td><td>61.49<sup>a</sup></td><td>33.34<sup>b</sup></td><td>nd<sup>c</sup></td><td>&lt;0.0001</td></tr><tr><td>(Z)-2-Octene</td><td>811</td><td></td><td>nd<sup>b</sup></td><td>1.17<sup>b</sup></td><td>1.08<sup>b</sup></td><td>31.06<sup>a</sup></td><td>30.96<sup>a</sup></td><td>nd<sup>b</sup></td><td>&lt;0.0001</td></tr><tr><td colspan="10"><strong>Terpenes</strong></td></tr><tr><td>α-Pinene</td><td>739</td><td>Pine</td><td>1.88<sup>b</sup></td><td>186.64<sup>a</sup></td><td>1.78<sup>b</sup></td><td>0.34<sup>b</sup></td><td>nd<sup>b</sup></td><td>9.78<sup>b</sup></td><td>0.000</td></tr><tr><td>β-Pinene</td><td>978</td><td>Woody green, pine</td><td>nd<sup>b</sup></td><td>35.71<sup>a</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>0.51<sup>b</sup></td><td>&lt;0.0001</td></tr><tr><td>Limonene</td><td>1034</td><td>Citrus</td><td>0.60<sup>b</sup></td><td>5.63<sup>b</sup></td><td>40.08<sup>a</sup></td><td>0.71<sup>b</sup></td><td>0.59<sup>b</sup></td><td>nd<sup>b</sup></td><td>0.037</td></tr><tr><td>Camphene</td><td>951</td><td>Woody</td><td>nd<sup>b</sup></td><td>16.41<sup>1a</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>&lt;0.0001</td></tr><tr><td colspan="10"><strong>Alcohols</strong></td></tr><tr><td>Pentanol</td><td>763</td><td>fermented</td><td>9.77<sup>bc</sup></td><td>2.62<sup>cd</sup></td><td>12.15<sup>d</sup></td><td>4.76<sup>cd</sup></td><td>2.38<sup>d</sup></td><td>27.94<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>Hexanol</td><td>867</td><td>Herbal</td><td>4.08<sup>b</sup></td><td>nd<sup>b</sup></td><td>0.98<sup>b</sup></td><td>nd<sup>b</sup></td><td>nd<sup>b</sup></td><td>55.01<sup>a</sup></td><td>&lt;0.0001</td></tr><tr><td>Octen-3-ol</td><td>969</td><td>Mushroom</td><td>0.88<sup>a</sup></td><td>2.72<sup>abc</sup></td><td>4.30<sup>c</sup></td><td>3.46<sup>bc</sup></td><td>2.29<sup>ab</sup></td><td>4.09<sup>bc</sup></td><td>&lt;0.0001</td></tr></tbody></table>

<footnote><sup>a</sup>Linear retention index on a HS-5MS column. <sup>b</sup>Aromas obtained from TheGoodScents company, and PubChem. <sup>c</sup>Estimated quantities (ng) collected from the headspace of 3 mL of OMA sample calculated by comparison with 20 µl of 10 ppm 1,4-dichlorobenzene used as internal standard; means (from three replicate samples) not labelled with the same letter in a row were significantly different (p < 0.05); as determined by Tukey's Honestly significant difference (at p = 0.05); nd, not detected. <sup>d</sup>Significance of sample effect (p-value).</footnote>
<figure><img src="image_52.png" /><figcaption>FIGURE 1
Multiple factor analysis correlating sensory data with volatile results.</figcaption></figure>

presented in Table 5. General aroma intensity of all samples was fairly low with only a few strong odours.

Six aromas detected by GC-O were identified in the GC-MS analysis. From Table 5, it can be seen that multiple compounds present in the GC-MS results can be directly associated with detected aromas, due to similar descriptors and LRIs. These included 2-methylbutanal, methyl 2-methylbutanoate, hexanal, and octen-3-ol. Aromas such as buttery and caramel/buttery with LRIs of 552 and 593 (both below 600) in the GC-O were identified as 2-methylpropanal and butanedione based on the GC-MS results.

Other aromas are likely to have resulted from volatile compounds that were not identified by the GC-MS, however, their descriptors and LRIs closely match specific odour compounds present in an internal database used in our lab with authentic compounds ran and analysed at similar conditions. These included 2-methyl-3-furanthiol, methional, 2-furanmethanethiol, 2-acetylpyrroline, 2-isopropyl-3-methoxypyrazine, guaiacol, and 2,6-dimethylphenol. Eleven other aromas were found within the GC-O results, however, an associated volatile compound for these aromas was not found, suggesting they were highly odour active compounds and below the limit of detection of the GC-MS.
<table><caption>TABLE 5 Mean GC-O scores from 3 assessors.</caption><thead><tr><th>Odour description<sup>a</sup></th><th>LR<sup>b</sup></th><th>Compound</th><th>Confidence<sup>c</sup></th><th>A</th><th>B</th><th>C</th><th>D</th><th>E</th><th>F</th></tr></thead><tbody><tr><td>Milk/butter/cheese</td><td>&lt;600</td><td>Unknown</td><td></td><td></td><td></td><td>2</td><td></td><td></td><td></td></tr><tr><td>Butter</td><td>&lt;600</td><td>2-methylpropanal</td><td>A</td><td></td><td></td><td>3</td><td></td><td></td><td>4</td></tr><tr><td>Caramel/buttery</td><td>&lt;600</td><td>Butanedione</td><td>A</td><td>3.5</td><td>5.3</td><td>5</td><td>3.5</td><td>3.8</td><td>3.3</td></tr><tr><td>Cocoa</td><td>651</td><td>2-methylbutanal</td><td>A</td><td></td><td></td><td>4</td><td></td><td></td><td></td></tr><tr><td>Sulphur/toast</td><td>667</td><td>Unknown</td><td></td><td></td><td>4.3</td><td></td><td>3</td><td>2</td><td></td></tr><tr><td>Boiled milk</td><td>675</td><td>Unknown</td><td></td><td>2</td><td></td><td>2</td><td></td><td></td><td>3</td></tr><tr><td>Oat milk/buttery</td><td>741</td><td>Unknown</td><td></td><td></td><td></td><td>2</td><td></td><td>2</td><td>3</td></tr><tr><td>Fruity/sweet</td><td>767</td><td>Methyl<br>2-methylbutanoate</td><td>A</td><td></td><td></td><td>3.5</td><td></td><td>2</td><td></td></tr><tr><td>Green/citrus</td><td>801</td><td>Hexanal</td><td>A</td><td>3.4</td><td>4.4</td><td>4</td><td>2.7</td><td>3</td><td>3.7</td></tr><tr><td>Soily/herb</td><td>849</td><td>Unknown</td><td></td><td></td><td></td><td></td><td>2.5</td><td>5</td><td></td></tr><tr><td>Marmite/yeast</td><td>873</td><td>2-methyl-3-furanthiol</td><td>B</td><td></td><td></td><td>4.5</td><td>3.5</td><td>3.3</td><td>4</td></tr><tr><td>Soily/wood</td><td>885</td><td>Unknown</td><td></td><td></td><td>2.7</td><td></td><td></td><td></td><td></td></tr><tr><td>Potatoes</td><td>874</td><td>Unknown</td><td></td><td></td><td>3.3</td><td>5</td><td>4.7</td><td></td><td></td></tr><tr><td>Soup/bread/potato</td><td>911</td><td>Methional</td><td>B</td><td>4.3</td><td>4.8</td><td>3.8</td><td>3.7</td><td>3.5</td><td>3.6</td></tr><tr><td>Coffee</td><td>913</td><td>2-furanmethanethiol</td><td>B</td><td></td><td></td><td>6</td><td></td><td></td><td>5</td></tr><tr><td>Starch/wheat/wet bread</td><td>918</td><td>Unknown</td><td></td><td></td><td></td><td>3.5</td><td></td><td></td><td>5</td></tr><tr><td>Cereal/buttery biscuits</td><td>930</td><td>2-acetylpyrroline</td><td>B</td><td></td><td></td><td>3</td><td>4</td><td></td><td>3</td></tr><tr><td>Mushroom</td><td>982</td><td>Octen-3-ol</td><td>A</td><td>4.2</td><td>3.8</td><td>4.6</td><td>5.2</td><td>4.2</td><td>5.2</td></tr><tr><td>Green chemical</td><td>992</td><td>Unknown</td><td></td><td></td><td>4</td><td>3</td><td>3.5</td><td>3.3</td><td></td></tr><tr><td>Soil/mushroom/mould/coffee/wood</td><td>1097</td><td>2-isopropyl-3-<br>methoxypyrazine</td><td>B</td><td>2</td><td>4.5</td><td>5.3</td><td>3</td><td>3.3</td><td></td></tr><tr><td>Toasted bread/smokey meat</td><td>1099</td><td>Guaiacol</td><td>B</td><td>4</td><td>4.3</td><td>4.3</td><td>3</td><td></td><td>3</td></tr><tr><td>Ink/chemical</td><td>1104</td><td>2,6-dimethylphenol</td><td>B</td><td></td><td></td><td></td><td></td><td></td><td>4</td></tr><tr><td>Sweet milk/caramel</td><td>1116</td><td>Unknown</td><td></td><td></td><td></td><td>3.7</td><td></td><td></td><td></td></tr><tr><td>Cocoa/makeup powder/dusty/soil</td><td>1161</td><td>Unknown</td><td></td><td></td><td>3.5</td><td>4</td><td>4.3</td><td>2.5</td><td>4</td></tr></tbody></table>

## 3.2.2 Avenanthramides and avenacosides (LC-MS/MS)

Figure 2 shows that avenanthramides A, B and C were present in all samples. Avenanthramide D was measured above the limit of detection (LOD), however, was below the limit of quantification (LOQ) in all samples, and therefore has not been included in the results.

Avenanthramide B was detected in the higher concentrations in all samples, in comparison to avenanthramides A and C, which is to be expected due to it being the most abundant of these compounds in oats. Figure 2 shows that samples C and D were significantly higher in avenanthramide B, than all other samples, whilst sample F was significantly lowest in both. However, avenanthramides A and C, were found to be significantly highest in sample B.

Figure 3 demonstrates that avenacosides were present in higher concentrations than avenanthramides in the OMA samples. However, the levels did not follow the same patterns with avenanthramides, with sample F being significantly highest, and B and C significantly lower in avenacoside A than all other samples.

## 3.2.3 Colour analysis

Figure 4 shows that the lightness for all samples was significantly different. Sample C measured the lowest lightness and F the highest, followed by E. However, figure 4 also shows that D, F, and A all had significantly more green note than C, whilst D had significantly more of a yellow colour.

## 3.2.4 Particle size analysis

Figure 5 shows that sample C had significantly larger particle size, being the highest in volume weighted mean, surface weighted mean, and median particle size. Sample E and F generally measured lower in particle size, with F measuring the lowest in volume weighted mean, and E the lowest in surface weighted mean, and median particle size.

Figure 6 indicates that sample A measured the highest reading for polydispersity index, significantly higher than all others, aside from C. Samples E and F measured significantly lower polydispersity index than all other samples.

<footnote><sup>a</sup>Odour description given by assessors (some terms were grouped together due to similarity of the meaning). <sup>b</sup>Linear retention index calculated from a linear equation between each pair of straight chain n-alkanes C<sub>6</sub>-C<sub>25</sub>. <sup>c</sup>Confidence in accuracy of associated compounds; A = LRI in agreement with those of authentic compound-compound present in the GC-MS results; B = LRI in agreement with those of authentic compounds, however, the compound was not present in the GC-MS results. The associations with the compounds found, were based on aroma descriptions from Pubchem, and the goodsentscompany, and the LRIs and quantities found from an internal database with compounds analysed under similar conditions in our lab.</footnote>
<figure><img src="image_53.png" /><figcaption>FIGURE 2</figcaption></figure>

Concentration of Avenanthramides (µM in OMA sample). Data represents means of three instrumental replicates of three sample replicates ± standard deviations (p-value < 0.0001). Differing small letter represent sample significance from multiple comparisons as determined by Tukey's honest significant difference (at p = 0.05).

<figure><img src="image_54.png" /><figcaption>FIGURE 3</figcaption></figure>

Concentration of Avenacoside A (µM in OMA sample). Data represents means of three instrumental replicates of three sample replicates ± standard deviations (p-value < 0.0001). Differing small letter represent sample significance from multiple comparisons as determined by Tukey's Honest significance difference (at p = 0.05).

### 3.2.5 Rheological properties

Figure 7 shows that all samples decreased in viscosity with increasing shear rate, indicating that these products show non-Newtonian shear thinning behaviour (N < 1). Samples B, C and

D were higher in viscosity and a larger drop in viscosity with increasing shear rate, in comparison to samples A, E and F, at lower shear rates (<100⁻¹). At higher shear rates, however (>500⁻¹), shear thickening behaviour can be observed, with a slight increase
<figure><img src="image_55.png" /><figcaption>FIGURE 4</figcaption></figure>

Colorimetre readings for lightness (L\*) green direction (a\*) and yellow direction (b\*). Data represents means of three replicates ± standard deviations (*p*-value < 0.0001). Differing small letter represent sample significance from multiple comparisons as determined by Tukey's HSD (at *p* = 0.05). Green note was measured in minus values, converted to positives for clarity on graph.

<figure><img src="image_56.png" /><figcaption>FIGURE 5</figcaption></figure>

Particle Size Measurements: D, 4, 3 (volume weighted mean/mass moment mean diameter) mm. Data represents means of three replicates ± standard deviations (*p*-value < 0.0001). Differing small letter represent sample significance from multiple comparisons as determined by Tukey's HSD (at *p* = 0.05).

in viscosity in all samples. However, it may be the case that the viscosity recordings above 500⁻¹ are outside of the experimental limit, leading to this increase in viscosity as a result of experimental error (34). Sample C contained the highest carbohydrate content as shown in Table 2 and was also found to have the highest viscosity at lower shear rates.

A comparison of samples at shear rate 50 s⁻¹ is often used as this is thought to represent the shear rate of the oral cavity, however, it is important to note that there more recent studies have shown a large range of sheer rates from 1 to 1000 s⁻¹ (35). The mean values of viscosity of the samples at this shear rate are given in Table 6. Samples C and D were found to demonstrate a
<figure><img src="image_57.png" /><figcaption>**FIGURE 6**

Polydispersity Index (PDI) of non-filtered samples. Data represents means of three replicates ± standard deviations (p-value < 0.0001). Differing small letter represent sample significance from multiple comparisons as determined by Tukey's HSD (at p = 0.05).</figcaption></figure>

<figure><img src="image_58.png" /><figcaption>**FIGURE 7**

Sample viscosity as a function of shear rate.</figcaption></figure>

<table><caption>TABLE 6 Viscosity values of samples at shear rate 51.8 (1/s).</caption><thead><tr><th>Sample</th><th>A</th><th>B</th><th>C</th><th>D</th><th>E</th><th>F</th></tr></thead><tbody><tr><td>Viscosity (mPa.s)</td><td>2.83<sup>bc</sup></td><td>3.24<sup>c</sup></td><td>6.42<sup>d</sup></td><td>6.68<sup>d</sup></td><td>1.54<sup>a</sup></td><td>1.95<sup>ab</sup></td></tr></tbody></table>

Data represents means of three replicates. Differing small letter represent sample significance from multiple comparisons as determined by Tukey's HSD (at *p* < 0.05).

significantly higher viscosity than all others at this shear rate, whilst sample E was significantly lower, at 1.54 mPa.s.

### 3.2.6 Extent of separation

**Figure 8** demonstrates the visible separation after 24 h in samples A, C and F. With sample A having the highest PDI, and C the highest volume weighted mean, this suggests that increased PDI and particle size may relate to increased separation. However, it does appear from **figure 8** that separation is also occurring in

sample F, despite having a much lower particle size and PDI. It is not entirely clear as to why this may be the case, however, it is likely that this is due to other factors such as stabilisers used; **Table 1** shows that F did not contain any stabilisers, whilst some of the less separated samples contained stabilisers including plant fibres and gellan gum.

## 4 Discussion

### 4.1 Avenanthramides and avenacosides in relation to ingredients and sensory attributes

Oat concentration did not appear to be directly influencing the perceived astringency of samples, as samples highest in oat content
<figure><img src="image_59.png" /><figcaption>FIGURE 8
Extent of separation. Samples stored in glass vials for 24 h at 5°C for visual comparison of separation. Order from left to right: (A–F).</figcaption></figure>

did not score higher in astringency. Nor was a trend found between protein content and astringency, despite an association within literature between protein and astringency (36). Avenanthramides and avenacosides are known to contribute to both astringency and bitter taste (20); sensations that were present at low levels in all samples. However, the samples did not differ in these attributes; samples with higher concentrations in these compounds were not detected as more astringent or bitter. Therefore, we suggest that the differences in avenanthramides and avenacosides between samples were below their just-noticeable-difference thresholds.

It is possible that the levels of astringency may be affected by other factors, including acids, dehydrating agents, and salts (37). In addition, the lipid content of the samples may have masked the perception of astringency (38). Sample C had the lowest fat content, and sample A had the highest (Table 2). However, although the mean astringency value was highest in C and amongst the lowest in A, which fits the lipid hypothesis, these differences in mean astringency values were not significant. Overall, whether the level of astringency and bitterness found in the samples would be detected by untrained consumers, and whether it is a factor in consumer acceptance, requires further investigation.

It is apparent from the LC-MS results that the levels of avenanthramides and avenacoside did not reflect the oat content (Table 1); with samples C and D containing the lowest quantities of oats, yet the highest overall concentration of avenanthramides. Sample B contained the highest quantity of oats, yet the lowest concentration of avenacoside A. With oats being the only possible source of these compounds, this may suggest that loss is occurring throughout stages of production. Phenolic compounds in oats have been found to decrease by 85% after the first 6 months of storage and remain at that level for the rest of the 12 months storage (39). This may suggest that the differences in phenolic compounds found within the 6 samples, may be related to storage time. Differences in the oat genotype and growing conditions may also affect the concentration of avenanthramides in the oat material (40). The differences in concentrations between

avenanthramides and avenacosides, may suggest that certain compounds are more or less susceptible to degradation or loss than others. Steaming of oats has previously been shown to moderately reduce content of avenanthramide A, yet not affect avenanthramides B and C (9). Total avenanthramide concentration in oats has been found to range from 1.2 to 79.7 mg/kg, depending on the genotype (41). The total concentration of avenanthramides A, B, and C combined in the samples ranged from 8.6 to 25.9 µM, which is the equivalent of 0.00973–0.0293 mg/kg. This is substantially lower than what has been found in the literature, however, it is important to consider the high moisture content of the samples, in comparison to pure dehulled oat grain.

Within the sensory results sweet taste was found to be significant, with sample D measuring a significantly sweeter taste than sample C. This does not, however, match the nutritional information shown in Table 2, which shows D and B to contain the least quantity of sugar, with C the most. It is not clear as to why this may be the case other than these differences in sugars being below the threshold of noticeable differences for taste. The sweet taste perception may also be more complicated than just the reported level of sugar, due to the presence of complex carbohydrates (42).

These findings suggest that the effect of ingredients on the sensory profile is complicated and therefore may be difficult to predict.

## 4.2 Relationships between volatile compounds and sensory attributes

Steaming of oats has been shown to increase the concentration of certain compounds, including 3-methylbutanal, benzaldehyde, heptanal, hexanal, and 2-pentylfuran, whilst the combined effect of kilning and steaming may boost the amount of Maillard reaction-related volatiles (43). This may suggest that samples with higher concentrations of these compounds may have been affected by processing. Of these, a significantly higher abundance
of benzaldehyde, was measured in sample C. Benzaldehyde has been suggested to likely result from interactions of reducing sugars and amino acids (44), and has been shown to significantly increase during storage of processed oats (39). Many other volatile compounds were also significantly higher in sample C, including nonanal, 6-methyl-5-hepten-2-one, limonene, and octen-3-ol. This increased abundance of many volatiles in sample C may have resulted in the significantly higher overall aroma as determined by the sensory panel, as well as the total of 15 distinct aromas detected in the GC-O analysis – the joint highest amount alongside sample B. Processed oats have been found to emit a higher odour than native oats (39), again suggesting this sample may have been affected by processing.

Differences in oat varieties have been shown to significantly affect sensory characteristics, including oat aroma, bitter taste, metallic, oat and creamy flavour, and oats and metallic after flavour (45). This may have contributed to the differences seen in the sensory results. Sample C was found to have the highest stale flavour by the sensory panel, although not significantly, as well as containing significantly higher 3-methylbutanal than all other samples. This may be associated with the reference of flaked almonds used by the panel for the attribute of stale, as 3-methylbutanal is described as one of the most predominant compounds in roasted almonds (46). This could also be related to the presence of benzaldehyde, an aroma associated with almonds (33), in which sample C measured significantly higher than all other samples. Methyl acetate, 3-methylbutanal, octanal, non-anal, 6-methyl-5 hepten-2-one and limonene, are all described as a sweet or citrus aromas, and could potentially have influenced the highest sweet aroma found in the sensory results, and the highest caramel note and fruity/sweet aromas within the GC-O results.

Hexanal, which has been shown to be the predominant aldehyde in oats (47), was also found to be the most abundant aldehyde in these samples. Hexanal is a lipid oxidisation product, which has been shown to increase during storage periods of processed oats (39), and therefore may have been affected by photo-oxidation from the clear plastic packaging in sample C, leading to the increased abundance. Photo-oxidation in oats may occur during processing, and is one of multiple reactions that can trigger the formation of lipid derived volatile compounds that may exhibit off-flavours (43). Differences in hexanal may also result from the possibility of a protein rich kernel to eliminate hexanal, as well as from variability of process conditions (48), having been shown to rapidly rise after heat treatment (47).

Sample B had the lowest mean overall aroma intensity, brown bread and wet oats aroma as determined by the sensory panel. This may have been influenced by the limited volatiles, as this sample was also found to have the lowest mean abundance in 16 of the compounds measured in the GC-MS; significantly lower than sample C in 14 compounds. Sample B exhibited the lowest abundance in all furans aside from 2-ethylfuran, in which it was found to be the second lowest, following sample D. Thermal processing is reported to be a main cause of furan formation, occurring to a large extent during the Maillard reaction (49).

Multiple factor analysis also found multiple correlations between the sensory results and volatile compounds, including sweet, wet oats and nutty aromas with heptanal, and brown bread aroma with methyl acetate, 2-methylpropanal, 3-methylbutanal and 2-methylbutanal. Wet oats flavour was shown to be positively

correlated with pentanol, hexanal, 2-hexenal and heptanal. Single cream flavour with methyl propanoate, and 3 methyl 2-butanone, and brown bread flavour with methyl acetate, 3-methylbutanal and 2-methylbutanal. Such correlations do not necessarily indicate that the volatile compounds are responsible for the resulting flavours, they can be incidental correlations where volatiles group together. However, from the literature we can reflect that some volatile compounds may be influencing these sensory characteristics; for example branched chain aldehydes, specifically 3-methylbutanal, being flavour compounds associated with bread (32), whilst positively correlating with brown bread aroma and flavour.

The stale aroma which was detected in low levels in all samples by the sensory panel may be related to the highly scoring mushroom aroma picked up in every sample during the GC-O and identified as octen-3-ol. Despite the low concentrations of octen-3-ol detected, this compound has a very low odour threshold (> 1 ppb) and may indicate an off-odour in oats (50). Octen-3-ol is produced by lipid oxidation, and increases greatly with storage time (51), therefore due to oats high lipid content, and active lipolytic enzymes (50), this may have resulted in the octen-3-ol detected within these samples. The sweet aroma detected in all samples may relate to the caramel note detected highly within all samples in the GC-O results and identified as butanedione.

## 4.3 Lightness, particle size, and rheology properties

The sensory results demonstrated that samples F and E were perceived to have the least off-white colour, with sample C the most. A similar finding was presented in the colourimeter results, as C was again found to have the least lightness, with F measuring the highest lightness, followed by E. The colour measurements did not find C to have more red or green colour than the other samples, which suggests that the off-white colour perceived by the panel, is due to lack of lightness, rather than influence from colour. The particle size measurements showed samples F and E to be the smallest, which may have influenced the increased lightness as a result of light scattering (17), and thus supports the hypothesis that lower particle size may contribute to increased whiteness.

The sensory results demonstrated that C was significantly more powdery than D, E, and F, as well as having the most powdery after effect. This also corresponds with particle size, as sample C was measured to have the largest volume weighted mean, and F the least, suggesting that larger particles may be resulting in a powdery mouthfeel and after-effect.

The rheology measurements found sample C to be the most sheer thinning during the lower sheer rates (below 10 mPa.s), followed by B and then D. This negatively correlates with the fat content listed in the nutritional information, with sample C containing the lowest fat content, followed by B and D. Sample C also exhibited the highest particle size which may have affected the rheology. OMAs in general have been shown to have a higher viscosity than other plant-based milks, potentially due to a higher carbohydrate content (52). This is also seen in sample C with the highest carbohydrate content, and generally higher viscosity at lower sheer rates.
This study may have been affected by slight limitations in
analytical conditions. Due to the various methods used, it was
not possible to carry out all of the sensory, chemical and physical
analyses on the same batch at the same time. Also due to product
C ceasing to be manufactured, which was out of the control of the
study, all products needed to be frozen and thawed between sets of
analyses. In ideal conditions all samples would have been analysed
fresh, after opening the same day. However, all of the six products
were analysed in the exact same conditions, all being frozen and
thawed at the same time, therefore the difference in findings
between the samples will still be an accurate representation.

5 Conclusion

The combined results from all six samples help to conclude
influences between the physicochemical, sensory, and volatile
properties, along with effects from ingredients and packaging.
These include the likelihood that smaller particle size may lead
to increased lightness and less perceived off-white colour, as
well as reduced powdery mouthfeel—which may be beneficial
for the sensory profile. Smaller particle size, as well as the
potential addition of stabilisers may both contribute to a decreased
separation. The results also suggested that certain compounds
were detected in higher abundances in the GC-MS analysis in
the clear-packaged non-UHT sample—potentially resulting from
photo-oxidation. This appeared to have contributed to perceived
aromas through GC-O, and through sensory results, suggesting
that the avoidance of clear packaging may help to prevent off-notes.

The results also demonstrated that avenanthramides and
avenacosides were present in all samples, which may be beneficial
for determining the nutritional value of oat-based milk alternatives.
These compounds were not only present, but significantly different
between samples and not directly related to the differences in
oat content. This may suggest that future analyses on the effects
of processing, storage and packaging on these compounds, may
be very beneficial to ensure preservation. The lack of significant
differences between the samples for bitter taste and astringency,
despite differences in avenanthramides and avenacosides, may
suggest that there is the potential to increase these compounds
without having a negative effect on the sensory profile. These
results may be useful in combination for considerations of future
OMA development, to improve the sensory profile and nutritional
content going forward.

Data availability statement

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

Ethics statement

Ethical review and approval were not necessary for this study
as the study involved tasting standard commercial samples by a
trained sensory panel that are employees and have consented to
taste and rate food as part of their job.

Author contributions

RM: Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review and editing, Conceptualization. LM: Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review and editing. SG: Supervision, Writing – review and editing. RE: Conceptualization, Funding acquisition, Supervision, Writing – review and editing. SL: Conceptualization, Funding acquisition, Methodology, Software, Supervision, Validation, Writing – review and editing.

Funding

The author(s) declare financial support was received for the
research, authorship, and/or publication of this article. This study
received funding from Biotechnology and Biological Sciences
Research Council (BBSRC) in conjunction with Arla Foods amba
through a FoodBioSystems DTP CASE studentship. The funder
had the following involvement with the study: supervision and
writing-review and editing the manuscript.

Acknowledgments

We thank Nicholas Michael (University of Reading) for technical assistance with the development of the LC-MS/MS method for the analysis of the avenanthramides and avenacosides in the samples. MMR Research Sensory Science Centre in the UK are thanked for their access to the trained sensory panel. Compusense are thanked for their access to their software through the academic consortium.

Conflict of interest

SG was employed by Arla Foods amba.

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.

Supplementary material

The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fnut.2024.
1345371/full#supplementary-material
References

1. Clay N, Sexton AE, Garnett T, Lorimer J. Palatable disruption: the politics of plant milk. *Agric Hum Values*. (2020) 37:945-62. doi: 10.1007/s10460-020-10022-y

2. Sethi S, Tyagi SK, Anurag RK. Plant-based milk alternatives an emerging segment of functional beverages: a review. *J Food Sci Technol.* (2016) 53:3408-23. doi: 10.1007/s13197-016-2328-3

3. Kanyama AC, Hedin B, Katzeff C. Differences in environmental impact between plant-based alternatives to dairy and dairy products: a systematic literature review. *Sustainability*. (2021) 13:12599. doi: 10.3390/su132212599

4. El Khoury D, Cuda C, Luhovyy BL, Anderson GH. Beta glucan: health benefits in obesity and metabolic syndrome. *J Nutr Metab*. (2012) 2012:851362. doi: 10.1155/2012/851362

5. Daou C, Zhang H. Oat beta-glucan: its role in health promotion and prevention of diseases. *Compr Rev Food Sci Food Saf*. (2012) 11:355-65. doi: 10.1111/j.1541-4337.2012.00189.x

6. Brough HA, Turner PJ, Wright T, Fox AT, Taylor SL, Warner JO, et al. Dietary management of peanut and tree nut allergy: what exactly should patients avoid? *Clin Exp Allergy*. (2015) 45:859-71. doi: 10.1111/cea.12466

7. Jeske S, Zannini E, Arendt EK. Evaluation of physicochemical and glycaemic properties of commercial plant-based milk substitutes. *Plant Foods Hum Nutr.* (2017) 72:26-33. doi: 10.1007/s11130-016-0583-0

8. Peterson DM, Emmons CL, Hibbs AH. Phenolic antioxidants and antioxidant activity in pearling fractions of oat groats. *J Cereal Sci.* (2001) 33:97-103. doi: 10.1006/jcrs.2000.0347

9. Meydani M. Potential health benefits of avenanthramides of oats. *Nutr Rev.* (2009) 67:731-5. doi: 10.1111/j.1753-4887.2009.00256.x

10. Pecio Ł, Wawrzyniak-Szolkowska A, Oleszek W, Stochmal A. Rapid analysis of avenacosides in grain and husks of oats by UPLC-TQ-MS. *Food Chem.* (2013) 141:2300-4. doi: 10.1016/j.foodchem.2013.04.094

11. McClements DJ. Development of next-generation nutritionally fortified plant-based milk substitutes: structural design principles. *Foods*. (2020) 9:421. doi: 10.3390/foods9040421

12. Bonke A, Sieuwerts S, Petersen IL. Amino acid composition of novel plant drinks from oat, lentil and pea. *Foods*. (2020) 9:429. doi: 10.3390/foods9040429

13. Zhang H, Onning G, Triantafyllou A, Öste R. Nutritional properties of oat-based beverages as affected by processing and storage. *J Sci Food Agric.* (2007) 87:2294-301. doi: 10.1002/jsfa.2987

14. Klose C, Arendt EK. Proteins in oats; their synthesis and changes during germination: a review. *Crit Rev Food Sci Nutr.* (2012) 52:629-39. doi: 10.1080/10408398.2010.504902

15. Henrion M, Francey C, Lè K-A, Lamothe L. Cereal B-glucans: the impact of processing and how it affects physiological responses. *Nutrients*. (2019) 11:1729. doi: 10.3390/nu11081729

16. McClements DJ, Newman E, McClements IF. Plant-based milks: a review of the science underpinning their design, fabrication, and performance. *Compr Rev Food Sci Food Saf.* (2019) 18:2047-67. doi: 10.1111/1541-4337.12505

17. Pugliese A, Cabassi G, Chiavaro E, Paciulli M, Carini E, Mucchetti G. Physical characterization of whole and skim dried milk powders. *J Food Sci Technol.* (2017) 54:3433-42. doi: 10.1007/s13197-017-2795-1

18. Durand A, Franks GV, Hosken RW. Particle sizes and stability of UHT bovine, cereal and grain milks. *Food Hydrocolloids*. (2003) 17:671-8. doi: 10.1016/S0268-005X(03)00012-2

19. Alqahtani NK, Ashton J, Katopo L, Gorczyca E, Kasapis S. Shelf-life studies of flavour characteristics in model UHT liquid systems enriched with wholegrain oat. *Heliyon*. (2018) 4:e00566. doi: 10.1016/j.heliyon.2018.e00566

20. Günther-Jordanland K, Dawid C, Dietz M, Hofmann T. Key phytochemicals contributing to the bitter off-taste of oat (Avena sativa L.). *J Agric Food Chem.* (2016) 64:9639-52. doi: 10.1021/acs.jafc.6b04995

21. Jiang Y, Gong NN, Matsunami H. Astringency: a more stringent definition. *Chem Senses.* (2014) 39:467-9. doi: 10.1093/chemse/bju021

22. Muhammad A, Dangoggo S, Tsafe A, Itodo A, Atiku F. Proximate, minerals and anti-nutritional factors of Gardenia aqualla (Gauden dutse) fruit pulp. *Pak J Nutr.* (2011) 10:577-81. doi: 10.3923/pjn.2011.577-581

23. Marangoni F, Pellegrino L, Verduci E, Ghiselli A, Bernabei R, Calvani R, et al. Cow's milk consumption and health: a health professional's guide. *J Am Coll Nutr.* (2018) 38:1-12. doi: 10.1080/07315724.2018.1491016

24. Röös E, Patel M, Spångberg J. Producing oat drink or cow's milk on a Swedish farm — Environmental impacts considering the service of grazing, the opportunity cost of land and the demand for beef and protein. *Agric Syst.* (2016) 142:23-32. doi: 10.1016/j.agsy.2015.11.002

25. Basinskiene L, Cizeikiene D. Chapter 3 - Cereal-based nonalcoholic beverages. In: Galanakis CM editor. *Trends in Non-alcoholic Beverages*. New York, NY: Academic Press (2020). doi: 10.1016/B978-0-12-816938-4.00003-3

26. NIST/EPA/NIH Mass Spectral Database. *National Institute of Standards and Technology (NIST)*. (2021). doi: 10.18434/T4D303

27. Wang P, Yang J, Yerke A, Sang S. Avenacosides: Metabolism, and potential use as exposure biomarkers of oat intake. *Mol Nutr Food Res.* (2017) 61:1700196.

28. Mudalige T, Qu H, Van Haute D, Ansar SM, Paredes A, Ingle T. Chapter 11 - Characterization of nanomaterials: tools and challenges. In: López Rubio A, FABRA Rovira MJ, Martínez Sanz M, Gómez-Mascaraque LG editors. *Nanomaterials for Food Applications*. Amsterdam: Elsevier (2019). doi: 10.1016/B978-0-12-814130-4.00011-7

29. Manousi N, Zachariadis GA. Determination of volatile compounds in nut-based milk alternative beverages by HS-SPME prior to GC-MS analysis. *Molecules*. (2019) 24:3091. doi: 10.3390/molecules24173091

30. Achouri A, Boye JI, Zamani Y. Identification of volatile compounds in soymilk using solid-phase microextraction-gas chromatography. *Food Chem.* (2006) 99:759-66. doi: 10.1016/j.foodchem.2005.09.001

31. Tunick MH, Iandola SK, Van Hekken DL. Comparison of SPME methods for determining volatile compounds in milk, cheese, and whey powder. *Foods*. (2013) 2:534-43. doi: 10.3390/foods2040534

32. Smit BA, Engels WJM, Smit G. Branched chain aldehydes: production and breakdown pathways and relevance for flavour in foods. *Appl. Microbiol Biotechnol.* (2009) 81:987-99. doi: 10.1007/s00253-008-1758-x

33. McGorrin RJ. Key aroma compounds in oats and oat cereals. *J Agric Food Chem.* (2019) 67:13778-89. doi: 10.1021/acs.jafc.9b00994

34. Ewoldt RH, Johnston MT, Caretta LM. Experimental challenges of shear rheology: how to avoid bad data. In: Spagnolie SE editor. *Complex Fluids in Biological Systems: Experiment, Theory, and Computation*. New York, NY: Springer (2015). doi: 10.1007/978-1-4939-2065-5_6

35. Payne C, Methven L, Fairfield C, Bell A. Consistently inconsistent: commercially available starch-based dysphagia products. *Dysphagia*. (2011) 26:27-33. doi: 10.1007/s00455-009-9263-7

36. Vlädescu S-C, Agurto MG, Myant C, Boehm MW, Baier SK, Yakubov GE, et al. Protein-induced delubrication: how plant-based and dairy proteins affect mouthfeel. *Food Hydrocol.* (2023) 134:107975. doi: 10.1016/j.foodhyd.2022.107975

37. Pires MA, Pastrana LM, Fuciños P, Abreu CS, Oliveira SM. Sensorial perception of astringency: oral mechanisms and current analysis methods. *Foods*. (2020) 9:1124. doi: 10.3390/foods9081124

38. Withers CA, Lewis MJ, Gosney MA, Methven L. Potential sources of mouth drying in beverages fortified with dairy proteins: a comparison of casein- and whey-rich ingredients. *J Dairy Sci.* (2014) 97:1233-47. doi: 10.3168/jds.2013-7273

39. Heiniö R-L, Lehtinen P, Oksman-Caldentey K-M, Poutanen K. Differences between sensory profiles and development of rancidity during long-term storage of native and processed oat. *Cereal Chem.* (2002) 79:367-75. doi: 10.1094/CCHEM.2002.79.3.367

40. Li X-P, Li M-Y, Ling AJ, Hu X-Z, Ma Z, Liu L, et al. Effects of genotype and environment on avenanthramides and antioxidant activity of oats grown in northwestern China. *J Cereal Sci.* (2017) 73:130-7. doi: 10.1016/j.jcs.2016.12.005

41. Wise ML, Doehlert DC, Mcmullen MS. Association of avenanthramide concentration in oat (Avena sativa L.) grain with crown rust incidence and genetic resistance. *Cereal Chem.* (2008) 85:639-41. doi: 10.1094/CCHEM-85-5-0639

42. Low JYQ, Lacy KE, Mcbride RL, Keast RSJ. Evidence supporting oral sensitivity to complex carbohydrates independent of sweet taste sensitivity in humans. *PLoS One*. (2017) 12:e0188784. doi: 10.1371/journal.pone.0188784

43. Li X, Oey I, Kebede B. Effect of industrial processing on the volatiles, enzymes and lipids of wholegrain and rolled oats. *Food Res Int.* (2022) 157:111243. doi: 10.1016/j.foodres.2022.111243

44. Sides A, Robards K, Helliwell S, An M. Changes in the volatile profile of oats induced by processing. *J Agric Food Chem.* (2001) 49:2125-30. doi: 10.1021/jf0010127

45. Zhou M, Robards K, Glennie-Holmes M, Helliwell S. Contribution of volatiles to the flavour of oatmeal. *J Sci Food Agric.* (2000) 80:247-54. doi: 10.1002/(SICI)1097-0010(20000115)80:2<247::AID-JSFA525>3.3.CO;2-S

46. Erten E, Cadwallader K. Identification of predominant aroma components of raw, dry roasted and oil roasted almonds. *Food Chem.* (2016) 217:244-53. doi: 10.1016/j.foodchem.2016.08.091

47. Klensdorf D, Jeleń HH. Effect of heat treatment on the flavor of oat flakes. *J Cereal Sci.* (2008) 48:656-61. doi: 10.1016/j.jcs.2008.02.005
48. Lehto S, Laakso S, Lehtinen P. Enzymatic oxidation of hexanal by oat. *J Cereal Sci.* (2003) 38:199-203. doi: 10.1016/S0733-5210(03)00028-6

49. Seok Y-J, Her J-Y, Kim Y-G, Kim MY, Jeong SY, Kim MK, et al. Furan in thermally processed foods - A review. *Toxicol Res.* (2015) 31:241-53. doi: 10.5487/TR.2015.31.3.241

50. Molteberg EL, Magnus EM, Bjørge J, Nilsson A. Sensory and chemical studies of lipid oxidation in raw and heat-treated oat flours. *Cereal Chem.* (1996) 73:579-87.

51. Cai C, Zhao Z, Zhang Y, Li M, Li L, Cheng P, et al. Molecular hydrogen improves rice storage quality via alleviating lipid deterioration and maintaining nutritional values. *Plants*. (2022) 11:2588. doi: 10.3390/plants11192588

52. Yao Y, He W, Cai X, Bekhit AE-DA, Xu B. Sensory, physicochemical and rheological properties of plant-based milk alternatives made from soybean, peanut, adlay, adzuki bean, oat and buckwheat. *Int J Food Sci Technol.* (2022) 57:4868-78. doi: 10.1111/ijfs.15814
Frontiers in
Nutrition

Explores what and how we eat in the context
of health, sustainability and 21st century food
science

A multidisciplinary journal that integrates research
on dietary behavior, agronomy and 21st century
food science with a focus on human health.

Discover the latest
Research Topics

See more

<figure><img src="image_60.png" /></figure>

<figure><img src="image_61.png" /></figure>

frontiers

Frontiers in
Nutrition

<figure><img src="image_62.png" /></figure>

Frontiers

Avenue du Tribunal-Fédéral 34
1005 Lausanne, Switzerland
frontiersin.org

Contact us

+41 (0)21 510 17 00
frontiersin.org/about/contact

<figure><img src="image_63.png" /></figure>

frontiers

Research Topics