Influence of Wine Label Imagery: Eye‐Tracking Evidence and Regulatory Implications

ABSTRACT

Introduction

The visual design of alcohol beverage packaging plays a crucial role in shaping consumer perceptions and purchase decisions, yet regulations in many countries are relatively lax. Guidelines often focus on the inclusion of health warnings rather than overall label or packaging design, giving producers considerable freedom. In recent years, wine manufacturers have increasingly featured images on their labels that are unrelated to the product, most notably animals such as mammals, birds and insects, a strategy likely intended to exploit attentional bias. The present study examines how such imagery on wine labels influences consumer attention and memorisation.

Methods

A within‐subject experimental design was conducted with 93 participants, each exposed to two conditions: wine labels that feature either animals or inanimate objects. Attention was measured using an eye‐tracking method in a laboratory setting at a French university. Each participant viewed 16 different wine bottles, resulting in 1488 observations. After exposure, label recognition was assessed via a declarative method.

Results

Wine labels featuring animals captured attention more rapidly, sustained attention for longer and were better recognised than labels featuring inanimate objects.

Discussion and Conclusions

The findings suggest that, beyond mandating health warnings on alcohol packaging, policymakers should consider stricter regulations on the visual content of labels to limit the persuasive power of alcohol marketing.

1. Introduction

Alcoholic drinks contain ethanol, a psychoactive and harmful substance that can lead to addiction. Globally, in 2019, alcohol consumption was responsible for 1.6 million deaths from noncommunicable diseases—700,000 from injuries and 300,000 from communicable diseases [1]. The World Health Organization has made several recommendations to address this issue, including the implementation of alcohol warning labels to inform consumers about the dangers of alcohol consumption. However, the overall design of alcoholic beverage labels and packaging remains largely unregulated, giving producers considerable creative freedom, even though research and marketing practice have long established that packaging is a powerful marketing tool and a key driver of consumer behaviour [2].

The motivation for this research stems from the observation of a transformation in wine label designs. Examination of wine bottles with vintages over 20 years old reveals that their labels were primarily—or even exclusively—composed of typographic elements. When images were present, they typically depicted images of the winery, award medals from competitions or heraldic symbols suggesting a historical heritage (see Table A1). In contrast, wine producers have increasingly incorporated visual elements unrelated to the product itself in more recent years, notably images of various animals including mammals and birds (see Tables A2 and A3). Although this change may appear trivial, the presence of animate imagery on labels and packaging may have a substantial impact. Unlike other decorative or symbolic elements such as medals or coats of arms, animal imagery represents animate entities that naturally trigger distinct cognitive and perceptual mechanisms. Humans have an evolutionary predisposition to detect and attend to animate beings, making such imagery fundamentally different from other visually salient but inanimate designs.

In public health literature, the influence of animate design in consumer products has mainly been examined through cartoon‐style imagery. For instance, research shows that animate imagery—such as cartoon graphics on e‐cigarette and e‐juice packaging—has increased in prevalence and reduces the perceived harmfulness of e‐cigarettes [3, 4]. Moreover, research also shows that companies using cartoon images to market e‐cigarettes in their Instagram campaigns generate significantly higher user engagement, underscoring the strong appeal of cartoons to Instagram users [5]. Together, these findings highlight the powerful influence of animated imagery on consumer perceptions and judgements. However, cartoons are only one example within a broader category of animate depictions that attract human attention. In the present study, we focus specifically on naturalistic representations of animals—a type of animate imagery increasingly found on wine labels. While these depictions are visually realistic rather than exaggerated, they still engage perceptual and cognitive mechanisms associated with animacy. The inclusion of animate imagery could also have a significant effect on attention. Evolutionary theory suggests that humans have inherited an innate ability to pay greater attention to stimuli crucial for survival. Specifically, the ability to quickly detect and evaluate animate objects—whether as potential threats or prey—is a highly adaptive and beneficial skill [6]. Consistent with this theory, research has shown that individuals detect changes in images depicting animate objects (e.g., animals) significantly faster and more accurately than inanimate objects [7]. Similarly, Yang et al. demonstrated that images of animate objects were more likely to be observed and for longer than images of inanimate objects [8]. Introducing the topic of animacy in the context of alcohol label design, this study uses an eye‐tracking method to examine, for the first time to our knowledge, how animate imagery influences consumer attention. Specifically, we investigate the impact that images of animate versus inanimate objects on alcohol labels can have on consumer attention. Based on research in psychology and neuroscience, we test the following hypothesis:

Hypothesis 1

Wine labels featuring images of animate objects attract more attention than those featuring images of inanimate objects.

The second aim of the study was to investigate whether the presence of images of animate versus inanimate objects on alcohol labels could influence memory. According to the adaptive view of human memory [9], animate objects are more relevant to survival than inanimate ones, which may explain why animacy has a powerful effect on memory [10]. Evidence from psychology indicates that animate items are remembered better than inanimate ones, making animacy one of the strongest predictors of long‐term recall [11]. Moreover, this animacy effect appears early in development, as young children also tend to remember animate items better than inanimate ones [12]. Based on these findings, the following hypothesis is proposed:

Hypothesis 2

Wine labels featuring images of animate objects are more likely to be remembered than those featuring images of inanimate objects.

2. Method

The study used a within‐subject design to examine how wine labels featuring images of animate objects—specifically animals—affect participants' attention and memory. In response to calls for novel research methodologies to address complex health challenges [13], the study combined an eye‐tracking method with declarative measures. Eye‐tracking is emerging as a valuable method in public health research for studying attention, particularly in the fields of alcohol [14], tobacco [15] and nutrition [16]. The current study was conducted in France, the country with the second highest rate of wine consumption per inhabitant in the world, just after Portugal [17]. The study protocol received approval from the Ethics Committee of the School of Management where it was conducted (France) and adheres to the ethical principles of the Declaration of Helsinki.

2.1. Participants

The sample size was estimated using a power test (GPower 3.1.9.7.) in order to perform t‐tests for paired samples [18]. The results show that a minimum of 27 participants achieved significance (Cohen's d = 0.50; α err prob. = 0.05; Power = 0.80) [19]. The participants were recruited at a French university from informal encounters in the cafeteria and the corridors. Recruitment criteria were as follows: (i) aged 18 years old and over; (ii) normal or corrected‐to‐normal vision; and (iii) consumers of alcohol, even if only occasionally. In total, 93 participants took part in the study (68 women and 25 men; M_age = 30, SD = 11.82). The sample included both moderate‐risk drinkers (29%) and high‐risk drinkers (71%) (Table 1).

TABLE 1.

Sample characteristics.

	N (93)	%
Gender
Men	25	26.9
Women	68	73.1
Age, years
18–24	43	46.2
25–34	23	24.7
35–49	17	18.3
50 and over	10	10.8
Education
Associate degree	12	12.9
Bachelor's degree	70	75.3
Master's degree	11	11.8
Work status
Management level position	2	2.2
Intermediate level profession	7	7.5
Employee	25	26.9
Young worker recruited from a sandwich course program	59	63.4
Household's main buyer
No	38	40.9
Yes	55	59.1
Drinking profile (AUDIT‐C) cut‐off for high risk ≥ 4 for men and ≥ 3 for women
Moderate risk drinkers	27	29.0
High risk drinkers	66	71.0
Wine expertise cut‐off for high expertise ≥ 3
Low expertise	53	57.0
High expertise	40	43.0
Wine purchase frequency
Once a week or more often	2	2.2
Once every two or three weeks	23	24.7
Once a month	21	22.6
Once every two or three months	18	19.4
Less frequently	29	31.1
Wine consumption frequency
Once a week or more often	17	18.3
Once every two or three weeks	38	40.9
Once a month	10	10.8
Once every two or three months	6	6.5
Less frequently	22	23.5

2.2. Stimuli

To operationalise the concept of animacy, the study focused on depictions of animals, using real wine bottles whose labels featured animal imagery. Animals on packaging or labels could be represented in either a naturalistic manner or as cartoons with comically exaggerated features or anthropomorphic characteristics [5]. Based on observations of practices of wine producers, who tend to favour naturalistic representations, we decided to use the same type of depiction for the experiment. We selected 25 bottles with labels displaying naturalistic animal images and 25 with labels displaying inanimate object images. In a pre‐test, 30 participants (14 women and 16 men, aged 21 to 30 years old, who were not included in the main study) were asked to group the bottles based on the elements displayed on the labels, with no restriction on the number of groups they could form. The participants created four groups: one for birds, one for mammals, one for other animals (e.g., insects, fishes), and one without animals. Based on these results, the researchers selected four of the bottles with labels featuring birds (i.e., magpie, thrush, partridge, crane), four with labels featuring mammals (i.e., doe, cow, lion, ram) and eight with labels featuring inanimate objects (e.g., castle, landscape, coat of arms) as stimuli for the experiment.

To simulate a real‐life situation of products placed on a store shelf as closely as possible, the wine bottles were arranged on actual shelf units. Two shelves were used, each displaying eight wine bottles. On the first shelf unit (S1), four bottles with labels featuring images of birds were alternated with four bottles with labels depicting images of inanimate objects. On the second shelf unit (S2), four bottles with labels featuring images of mammals were alternated with four bottles with labels depicting images of inanimate objects. The layouts were designed to control for visual bias, as previous eye‐tracking research has shown that participants tend to focus more on items located at the centre of the screen [20]. Photographs were then taken of the shelf units. To exclude differences unrelated to the label content, a professional designer slightly modified the colour of the capsule, the shape of the bottles and the size of the labels, thereby standardising these elements across all the stimuli. Finally, the edited photos were presented on the screen during the experiment (Figure 1).

FIGURE 1.

Layout of wine bottles (some details have been blurred for copyright reasons, but they were fully legible and visible to the study participants).

2.3. Apparatus and Eye‐Tracking Measures

The eye‐tracking experiment took place in a controlled laboratory environment, free from external disturbances. Participants sat approximately 60 cm from a 24‐in. Hewlett Packard screen, with a binocular remote corneal reflection eye‐tracking system (SMI RED 250) installed in front. With a sampling rate of 250 Hz, points of regard were recorded every 4 milliseconds (ms). The experiment was conducted using the SMI Experiment Centre, and the data were exported via SMI BeGaze (Version 3.7.68). Fixations in the present study were defined by an absence of saccades and blinks for at least 50 milliseconds (ms). More details about the eye‐tracking method are provided in Table A4 following the guidelines outlined by Dunn et al. [21].

The label on each bottle was defined as an ‘area of interest’ (AOI) for gaze analysis (Figure 2). To quantify attention directed towards a designated AOI, two types of eye‐tracking measure were employed. The first type of measure assessed noticeability, reflecting how quickly an AOI captured the participant's attention. Typically, noticeability is assessed by the entry time metric, defined as the duration from the onset of stimulus until the AOI is first entered. The second type of measure evaluated the AOI's ability to sustain attention once noticed. Ability to sustain attention is generally assessed through three metrics such as fixation duration (total duration of fixations within the AOI), fixation count (number of eye fixations within the AOI), and revisit count (number of times an observer returns their gaze to a previously viewed AOI) [22].

FIGURE 2.

Illustration of areas of interest (highlighted in red).

2.4. Procedure

Each participant received an individualised welcome from a researcher, along with an explanation of the eye‐tracking procedure. Additionally, the researcher explained that each participant would be assigned a code number to ensure anonymity and that they were free to discontinue the experiment at any time if they so wished. Following this, the participants formally gave their written consent to partake in the study. They were then seated in front of a screen, and a 5‐point calibration procedure was implemented to ensure accurate localisation of eye position. This step was followed by an on‐screen instruction: ‘Imagine that a friend is hosting a party at their new apartment and you are responsible for bringing the wine. While shopping, you look at the wine aisle thinking about the upcoming party.’ To familiarise them with the task, participants were first exposed to a shelf unit in the form of drawings of eight wine bottles, then to S1 and S2 for 7 s each, a timespan used in similar studies [23]. A grey screen with a fixation cross lasting 1000 milliseconds was inserted between the shelf units to give the participants a short rest period.

Following the eye‐tracking recording, the participants filled out a questionnaire with sociodemographic information (age, gender, education, working status, whether they were the household's main buyer) and drinking patterns (AUDIT‐C) [24]. Subsequently, three scales were used to assess expertise with the product category, wine purchasing frequency, and wine consumption frequency [25]. Expertise with the product category was measured using a 3‐item 7‐point Likert scale (‘Wine is a product I believe I know well’; ‘I think I am capable of advising someone on choosing a wine’; ‘I consider myself to have a certain level of expertise regarding wine’). Wine purchasing frequency and wine consumption frequency were recorded using a 1‐item 5‐point scale for each, respectively ‘How often do you purchase wine?’ and How often do you consume wine?, both anchored by ‘Once a week or more often’, ‘Once every two or three weeks’, ‘Once a month’, ‘Once every two or three months’, ‘Less frequently’. Colour perception (colour blindness) was also recorded.

In the final part of the questionnaire, participants were exposed to 12 wine labels for a recognition task. These included six labels featuring images of animals and six featuring images of inanimate objects, presented in randomised order. Among them were two labels featuring images of animals and two labels featuring images of inanimate objects that had previously been displayed on the bottles on the shelves, while the remaining eight labels were new and had not been shown before. The participants were given the following instructions: ‘Look at the labels below and circle the ones you recognize as being displayed on the bottles on the shelves earlier.’ Finally, given their exposure to alcohol bottles, the participants were shown four prevention flyers created by Santé Publique France warning of the dangers of alcohol consumption. They were then debriefed, thanked and given a €25 store gift card for their participation in the study.

2.5. Statistical Analysis

To examine the impact of wine label design on attention and memorisation, paired‐sample t‐tests were performed. The four metrics mentioned above (entry time, fixation duration, fixation count, and revisit count) were analysed as a proxy for attention. For memorisation, we took both correct recognitions (hits) and false recognitions (false alarms) into consideration [26]. To account for both within‐subject and between‐subject factors, a mixed ANOVA approach was adopted to incorporate covariates (gender, age, education, working status, household's main buyer, drinking profile, wine expertise, wine purchase frequency, and wine consumption frequency) into the model.

3. Results

Quality control of the tracking process was performed before conducting the statistical tests. A tracking ratio of less than 80% of total recording time was considered insufficient [27]. Based on this criterion, two participants were excluded from the statistical tests for S1 (N = 91) and one participant for S2 (N = 92).

3.1. Influence of Animacy (Images of Animals Versus Images of Inanimate Objects) on Attention

Regarding noticeability, t‐tests for paired samples showed that for both S1 (birds) and S2 (mammals), wine labels featuring images of animals were detected faster than wine labels featuring images of inanimate objects (shorter entry time, S1: t(90) = 8.986, p < 0.001, d = 0.942; S2: t(91) = 2.606, p < 0.01, d = 0.272).

Moreover, regarding the ability to sustain attention, t‐tests for paired samples showed that for both S1 (birds) and S2 (mammals), wine labels featuring images of animals held participants' attention more effectively than wine labels featuring images of inanimate objects (higher fixation duration, S1: t(90) = 7.539, p < 0.001, d = 0.790; S2: t(91) = 7.830, p < 0.001, d = 0.816; higher fixation count, S1: t(90) = 9.644, p < 0.001, d = 1.011; S2: t(91) = 6.831, p < 0.001, d = 0.712; higher revisit count, S1: t(90) = 4.739, p < 0.001, d = 0.497; S2: t(91) = 7.477, p < 0.001, d = 0.780). Table 2 shows that regardless of the measures, the comparisons exhibited medium to large effect sizes. Therefore, H1 is supported.

TABLE 2.

Eye‐tracking measures during the visual exploration task (7000 ms).

		Wine labels featuring images of inanimate objects	Wine labels featuring images of animals	Paired‐samples t‐test
Measures		Mean (SD)	Mean (SD)	t	df	p value	Effect size d*	95% CI
								Lower	Upper
Noticeability
Entry time ms	S1 birds	2678 (840)	1801 (704)	8.986	90	< 0.001	0.942	0.693	1.187
	S2 mammals	2601 (749)	2379 (672)	2.606	91	< 0.01	0.272	0.063	0.479
Ability to sustain attention
Fixation duration ms	S1 birds	529 (171)	775 (219)	7.539	90	< 0.001	0.790	0.553	1.024
	S2 mammals	531 (166)	758 (175)	7.830	91	< 0.001	0.816	0.578	1.051
Fixation count	S1 birds	1.76 (0.57)	2.67 (0.76)	9.644	90	< 0.001	1.011	0.756	1.262
	S2 mammals	1.96 (0.59)	2.60 (0.74)	6.831	91	< 0.001	0.712	0.482	0.940
Revisit count	S1 birds	0.50 (0.37)	0.74 (0.43)	4.739	90	< 0.001	0.497	0.278	0.713
	S2 mammals	0.44 (0.41)	0.76 (0.39)	7.477	91	< 0.001	0.780	0.544	1.011

Abbreviation: CI, confidence interval.

^*Cohen‘s definition of effect sizes for t‐test (Cohen, 1988): small: d ≥ 0.20, medium: d ≥ 0.50, large: d ≥ 0.80.

The mixed ANOVA revealed no significant interaction effect between animacy and the covariates (gender, age, education, working status, household's main buyer, drinking profile, wine expertise, wine purchase frequency, and wine consumption frequency) on attention.

3.2. Influence of Animacy (Images of Animals Versus Images of Inanimate Objects) on Memorisation

Regarding memorisation, t‐tests for paired samples showed that for both S1 (birds) and S2 (mammals), wine labels featuring images of animals led to more correct recognitions than wine labels featuring images of inanimate objects (S1: t(92) = 1.715, p < 0.05, d = 0.178; S2: t(92) = 3.382, p < 0.001, d = 0.351).

Moreover, wine labels with images of animals led to fewer false recognitions (i.e., remembering a label that had not been presented on the shelves) (S1: t(92) = 1.637, p = 0.053, d = 0.170; S2: t(92) = 7.336, p < 0.001, d = 0.761). Table 3 shows that regardless of the measures, the comparisons exhibited small to medium effect sizes. Therefore, H2 is supported.

TABLE 3.

Memorisation measures after the visual exploration task.

		Wine labels featuring images of inanimate objects	Wine labels featuring images of animals	Paired‐samples t‐test
Measures		Mean (SD)	Mean (SD)	t	df	p value	Effect size d*	95% CI
								Lower	Upper
Correct recognitions (hits)	S1 birds	0.366 (0.48)	0.495 (0.50)	1.715	92	0.045	0.178	−0.028	0.382
	S2 mammals	0.226 (0.42)	0.484 (0.50)	3.382	92	< 0.001	0.351	0.140	0.559
False recognitions (false alarms)	S1 birds	0.247 (0.93)	0.140 (0.37)	1.637	92	0.053	0.170	−0.035	0.374
	S2 mammals	0.505 (0.61)	0.022 (0.14)	7.336	92	< 0.001	0.761	0.528	0.990

Abbreviation: CI, confidence interval.

^*Cohen‘s definition of effect sizes for t test (Cohen, 1988): small: d ≥ 0.20, medium: d ≥ 0.50, large: d ≥ 0.80.

The mixed ANOVA revealed one interesting interaction between animacy and wine consumption frequency (for S1 birds, F(4,86) = 2.882, p < 0.05, η²p = 0.118; for S2 mammals, F(4,87) = 2.740, p < 0.05, η²p = 0.112). It showed that participants with a high frequency of wine consumption obtained better recognition scores for labels with animals than for labels with inanimate objects, whereas those who consumed wine less frequently got better recognition scores for labels with inanimate objects than for labels with animals. No interaction was found between animacy and other covariates.

4. Discussion

The present study applied the theoretical framework of evolutionary psychology which posits that humans are inherently predisposed to pay more attention to animate objects than to inanimate ones. With the use of eye‐tracking, a neuroscientific method, we demonstrated that wine labels featuring images of animate objects—specifically mammals and birds—attract more attention than those depicting images of inanimate objects. Specifically, wine labels featuring images of animals draw attention more rapidly (as indicated by shorter entry times) and sustain attention for longer (as evidenced by higher fixation counts, fixation durations, and re‐entry counts) than labels depicting images of inanimate objects. Furthermore, participants remembered labels featuring images of animals better, leading to higher correct recognition scores and fewer false recognitions. These effects were consistently observed across two different categories of animals, namely, mammals and birds. Interestingly, the influence of animacy on memorisation was moderated by participants' wine consumption frequency. Participants with a high frequency of wine consumption obtained better recognition scores for labels with animals compared to labels with inanimate objects, whereas those who consumed wine less frequently exhibited better recognition for inanimate labels. One possible explanation is that frequent wine consumers may engage with wine in a more experiential or symbolic manner, forming affective associations with visual elements such as animal imagery. These associations could facilitate memory encoding and retrieval, making animate labels more memorable. In contrast, infrequent consumers may adopt a more analytical or factual processing style when evaluating wine labels, relying on structured cues such as typographic or inanimate elements, which may enhance memory for these labels. This interpretation remains a hypothesis that could be examined and tested in future research.

A product's ability to capture consumer attention in visually cluttered environments, such as retail shelves, is a major issue for manufacturers, who rely on design elements to stand out from their competitors. Eye‐tracking research shows that products visually distinct from their surroundings are more likely to attract attention, even under time pressure [28]. In the context of alcohol products, visual attention has been established as a key factor in shaping consumer choices. Specifically, findings demonstrate that the longer a consumer spends observing a particular bottle, the more likely they are to choose it [29, 30].

From a public health perspective, these findings underscore the need for policymakers to consider stricter regulations in the design of alcohol labels. Research in marketing has consistently demonstrated the persuasive power of product packaging, as evidenced by the substantial sums firms spend on design [31, 32]. The global graphic design market was valued at 50.4 billion USD in 2022, with projections reaching 83.8 billion USD by 2032 [33]. Alcohol manufacturers clearly recognise the strategic value of visually appealing designs, particularly in capturing and maintaining consumer attention.

Lessons can be drawn from the fight against smoking, where research has shown that the combination of prominent health warnings and measures to reduce packaging attractiveness yields maximum effectiveness. This has led several countries to implement plain packaging for cigarettes—an approach shown to reduce brand awareness, impair consumers' ability to identify specific brands, reduce the product's overall attractiveness, and ultimately increase the likelihood that smokers engage in cessation‐related behaviours [34, 35]. However, in France—the country where our study was conducted—a switch to plain packaging for alcoholic beverages is unlikely in the short term, particularly given the strong cultural barriers and intense lobbying by producers, since France is the world's largest wine producer [36]. As an initial step, policymakers and producers could instead give priority to label designs that focus on informative, product‐related content, using typography rather than imagery, as was common several decades ago. One potential positive outcome of this study would be to prompt greater involvement of policymakers in regulating alcohol label design, thereby preventing the design and marketing of alcohol packaging from being controlled solely by producers—many of whom are large corporations that leverage design as a central component of their persuasion strategies.

Despite its valuable contributions, this study has certain limitations. First, it focused exclusively on wine. Expanding future research to include other alcoholic beverages such as beer and spirits (e.g., vodka, whisky, gin) could provide further relevant insights. Given the evolutionary psychology framework underlying our study, we anticipate that similar findings would emerge across other types of alcohol. Second, it was conducted in a laboratory environment using remote eye‐tracking technology. Future research could benefit from being conducted in a real store environment with participants using wearable eye‐tracking glasses, although such an approach may come with reduced experimental control.

Finally, the study fills a gap in the existing public health literature by extending prior findings on cartoon‐based imagery to realistic animal representations and by using an innovative neuroscientific method—eye‐tracking—to examine how animacy cues on alcohol labels attract attention, highlighting the need to consider stricter regulations with respect to alcohol label designs.

Author Contributions

Each author certifies that their contribution to this work meets the standards of the International Committee of Medical Journal Editors. Conceptualisation: O.D., A.B.G., S.L.‐B.; formal analysis: S.L.‐B.; methodology: O.D., A.B.G., S.L.‐B.; roles/writing – original draft: O.D., A.B.G., S.L.‐B.; writing – review and editing: O.D., A.B.G., S.L.‐B.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A.

TABLE A1.

Examples of wine labels featuring inanimate objects.

Picture	Name of the product	Origin	Website
Images of the winery	Domaine de la solitude	France	https://www.domainedelasolitude.com/les‐vins/domaine‐de‐la‐solitude‐blanc/
Award medals from competitions	Sylvaner	France	https://henri‐ehrhart.com/fr/3‐nos‐incontournables
Heraldic symbols	Châteauneuf‐du‐Pape	France	https://domaine‐saintlaurent.com/nos‐vins/chateauneuf‐du‐pape‐rouge/

TABLE A2.

Examples of wine labels featuring animate nonhuman objects (i.e., mammals).

Picture	Name of the product	Origin	Website
Mule	Vieille mule	France	https://www.jeffcarrel.com/fr/9‐contenu‐fr/by‐jeff‐carrel/37‐vieille‐mule‐by‐jeff‐carrel‐rouge
Doe	La Part Des Biches	France	https://www.vivino.com/FR/fr/jean‐luc‐baldes‐la‐part‐des‐biches/w/9412770?srsltid=AfmBOoqUrm58guHoPH5Pk_K6zwzpquRM7F2JJcl4fxjJFJgkNseO0eSd
Stag	Le Bois du Cerf	France	https://www.vivino.com/FR/fr/vico‐le‐bois‐du‐cerf/w/7157744?srsltid=AfmBOoqv3Kf1NZOwTs2hFA6Kp_oaZGaGQuc‐U6Z6lKENSY2tn6weQ0PF
Whale	Terres de la baleine	France	https://www.vindessalins.com/terres‐de‐la‐baleine
Cat	Gato San Pedro	Chilli	https://www.tipicochileno.cl/nuestros‐productos/
Bat	Chauve qui peut	France	https://chateaufontbarriele.fr/product/chauve‐qui‐peut‐bio‐le‐carton‐de‐6‐bouteilles
Horse	Domaine Hipparion	France	https://www.vivino.com/FR/fr/domaine‐hipparion‐cotes‐du‐rhone‐villages‐visan/w/11085663?srsltid=AfmBOopLJzfGDb3r1UimHVv‐BKFpeY‐g5w3KwLxnmGjcApn‐ZilMjNaD
Pig	Franco de Porc	France	https://www.vivino.com/FR/fr/chevalerie‐cuvee‐franco‐d‐porc‐bourgueil/w/1847812?srsltid=AfmBOoqzl0amjoTQi1_8EQ9KiBaFmrff6zcNAqaRXNqtYjgHIqeNtVRW
Elephant	Elephant Rose	France	https://m.familleperrin.com/R1SM2F
Hedgehog	Hérisson Biodynamic	France	https://www.jacquesfrelin.com/nos‐vins‐bio/herisson‐malin‐biodynamic/
Hare	Le lièvre d'Ostara	France	https://www.domainedamiens.com/pages/nos‐vins/les‐vins‐1761233894.html
Lion	Leone Rosso	Italy	https://castellosonnino.it/prodotto/toscana‐rosso‐igt‐leone‐rosso‐2019‐castello‐sonnino/
Wolf	Black Wolf	France	https://www.vinello.fr/black‐wolf‐languedoc‐aop‐vignobles‐vellas
Sheep	Farigoulette	France	https://www.domaine‐anglas.com/boutiques/vins‐rouges/
Fox	Retour de chasse	France	https://www.vivino.com/FR/fr/retour‐de‐chasse‐corbieres/w/1856311
Rhinoceros	Tussock jumper	South Africa	https://www.tussockjumperwines.com/discover‐a‐world‐of‐wine/
Wild boar	Tussock Jumper	France	https://www.tussockjumperwines.com/our‐wines/pinot‐noir/
Young boar	Le Marcassin	France	https://www.vivino.com/FR/fr/mont‐tauch‐le‐margassin‐vallee‐du‐torgan‐vallee‐du‐torgan‐rose‐wine/w/5724555?srsltid=AfmBOopdTGp0DU6aViftk13ub9FQgJfQplohE90n1UZRv‐9H_Cctzkqy
Bull	Coste di moro Lunaria	Italy	https://www.vinello.fr/coste‐di‐moro‐montepulciano‐0‐375l‐lunaria
Cow	Les laïs	France	https://www.olivierpithon.com/vins/
Kangaroo	Yellow tail	Australia	https://www.yellowtailwine.com/au/our‐wines/

TABLE A3.

Examples of wine labels featuring animate nonhuman objects (i.e., birds).

Picture	Name of the product	Origin	Web site
Duck	Whistling Duck	Australia	https://www.vivino.com/IT/fr/whistling‐duck‐shiraz/w/4168450?srsltid=AfmBOooB4gJScRrgiXJ4MT5Ge1DEEy9BuCJZt_DSPIXpI8AAbnb5eqOe
Goldfinch	Le Chardonneret élégant	France	https://boutique.cavederauzan.com/fr/accueil/81‐jack‐le‐chardonneret‐elegant‐bordeaux‐rose.html
Owl	Mythique	France	https://www.mythique‐wine.com/
Stork	Pinot Nero di Mora Bassa	Italy	https://www.morabassa.it/prodotto/pinot‐nero‐doc/
Hummingbird	Le colibri	France	https://domainedelaiguillette.fr/vin/colibri/
Cock	Coq léon	France	https://www.vivino.com/FR/fr/dominique‐piron‐coq‐leon/w/8997835?srsltid=AfmBOooqZw5DGqkFxQ5qkp2y3g4JENuhKIyXc‐dYcLEn8mr‐vPcguyfS
Flamingo	Les Pluviers Sable de Camargue	France	https://www.vivino.com/FR/fr/louis‐chatel‐les‐pluviers‐sable‐de‐camargue‐rose/w/11785824?srsltid=AfmBOorgs0bPmJcOMDofe5XKFNj35iHIkqHtcDC2p6YBN_Uxap8P6bhk
Woodcock	Domaine de la Mordorée	France	https://www.domaine‐mordoree.com/nos‐vins/
Thrush	Premières grives	France	https://www.tariquet.com/premieres‐grives/
Swallow	Les hirondelles		https://www.vivino.com/fr/michel‐et‐pompilia‐les‐hirondelles/w/2475035?srsltid=AfmBOooVx_QS6ddRIHABJIq1wxuDR5KfcUwTXDDMoo8agkjEYQD2LAB2
Hoopoe	Pinuaga Pico Largo	Spain	https://www.vivino.com/FR/fr/pinuaga‐pico‐largo‐single‐vineyard‐garnacha‐castilla‐la‐mancha/w/11444910?srsltid=AfmBOoq6bEn15HMsfV62bJDD1i4KRDH6DK3MLgNgn‐aa6KD96i6iGEfB
Oriole	Rigogolo di Castellina	Italy	https://www.vivino.com/IT/fr/castellare‐di‐castellina‐rigogolo‐di‐castellina‐toscana/w/3257579?srsltid=AfmBOoqcK7KWn_17BYc1OIJGlQLxJ_3f6jCSgD2KYKlcBGAhqvQnDIFH
Moorhen	La marouette	France	https://www.jacquesfrelin.com/nos‐vins‐bio/la‐marouette‐sans‐sulfites‐ajoutes‐rouge/
Swift	L'envol de Martinet	France	https://www.pomerol.com/accueil/3301‐l‐envol‐de‐martinet‐2016.html
Goose	La vieille ferme	France	https://m.familleperrin.com/CQWYCF
Partridge	Noms d'oiseaux	France	https://domainedelachevalerie.fr/noms‐doiseaux/
Parrot	Il Pappagallo	Italy	https://www.vivino.com/IT/fr/abbazia‐il‐pappagallo‐moscato‐d‐asti/w/11324066?srsltid=AfmBOooOSSs2XlthGGwjAGREHCmdHowaeCUZ6qAOj2qXDYFgA5Ga3rJI
Magpie	La voliera	Italy	https://www.vivino.com/FR/fr/girolamo‐la‐voliera‐negroamaro/w/2478964?srsltid=AfmBOor7dRdqAFsGokdkpcJ0ZRWjccxwj1HidjoybdvC7EvbKvFZGBrc
Hen	La pépie	France	https://vins‐etonnants.com/search?q=La%20p%C3%A9pie
Nuthatch	Les insouciants	France	https://www.comtessedubarry.com/les‐insouciants‐merlot‐le‐rose‐volubile‐75cl.html
Heron	Réserve Naturelle Cinsault	France	https://www.vivino.com/fr/terroirs‐vivants‐pays‐d‐oc‐reserve‐naturelle‐cinsault/w/4630262?srsltid=AfmBOorvfTOqMpzAsJbMHN8QF1fE1t_AVii4Tw_NyTj8e18WFCpD2VTp
Tit	Mesange gardien!	France	https://chateaufontbarriele.fr/product/mesange‐gardien‐bio‐le‐carton‐de‐6‐bouteilles‐copie
Linnet	Tête de linotte	France	https://www.vivino.com/fr/albert‐besombes‐tete‐de‐linotte‐bourgueil/w/6735549?srsltid=AfmBOoq35CB0jy‐fv‐EVchU_9h13WfsCzpzy1CZNCCObz6imlP8fZAtK

TABLE A4.

Methodological quality specific to eye‐tracking method.

A1 Manufacturer and model	SensoMotoric instruments (SMI) RED 250, Berlin, Germany
A2 Software and firmware versions	Eye movement recordings and stimulus timing were controlled by Experiment Center software (version 3.7.68.) [by SMI]. Fixations, saccades, and blinks were extracted with the BeGaze software [by SMI]. The resulting values were analysed with SPSS Version 27.
A3 Eye‐tracking technology	A video‐based binocular remote corneal reflection eye‐tracking system
A4 Sampling frequency	250 Hz (point‐of‐gaze was captured every 4 ms)
A5 Head movement restrictions	No equipment is placed on the participants, giving participants relatively large freedom of movement.
A6 Eye(s) recorded	Eye positions were recorded for both eyes
A7 Parameters recorded	The eye tracker recorded horizontal and vertical gaze position in pixels on the screen, where (0.0) corresponds to the top‐left of the screen.
A8 Environment lighting	A light‐controlled and soundproof room dedicated to eye‐tracking
A9 Calibration	The experiment started with a calibration and a validation. The calibration was performed for each eye by fixating a small red dot on the screen (0.3° diameter), presented on a grey background, and validated using a four‐point validation procedure.
A10 Measurement uncertainty	Gaze position accuracy: 0.4° Spatial resolution (RMS): 0.03°
A11 Data processing steps	The data processing steps in eye‐tracking involve several key stages. First, quality control of the tracking process ensures the accuracy and reliability of the recorded data by checking calibration, completeness, and identification of tracking losses. Next, Areas of Interest (AOIs) are created to define specific areas relevant to the study, enabling focused analysis of gaze behaviour. Once the setup is complete, the data is exported in structured formats for further processing. Finally, statistical analyses are performed to extract key metrics, providing insights into visual attention and behaviour patterns.
A12 Data loss	A tracking ratio of less than 80% of the total recording time was considered incomplete
B1 Signal latencies	Not applicable
C1 Participant‐to‐display monitor distance	The participants were positioned about 60 cm from a 24‐in. (52 × 32.5 cm) Hewlett Packard screen

Droulers O., Bigoin Gagnan A., and Lacoste‐Badie S., “Influence of Wine Label Imagery: Eye‐Tracking Evidence and Regulatory Implications,” Drug and Alcohol Review 45, no. 1 (2026): e70094, 10.1111/dar.70094.