Exploring consumer affective response and sensory perception of a popular composite food made with a novel acidifier: a case study using verjuice in mayonnaise Open Access

Mayonnaise is a multi-ingredient product obtained from the emulsion of oil, egg, salt and acidifier (Mirzanajafi-Zanjani et al., 2019). It is a popular sauce in Western countries, in which its market growth is mainly driven by healthy ingredients and new flavors (Mirzanajafi-Zanjani et al., 2019). Vinegar and lemon juice are typically used as acidifiers (Elias et al., 2015) in both commercial and homemade mayonnaises, impacting emulsion structure and sensory characteristics, mainly acidity and texture (Mirzanajafi-Zanjani et al., 2019).

In this regard, verjuice (unripe grape juice) emerges as a promising acidifier ingredient, as it has been previously used in several food applications, such as salad dressings (Dupas de Matos et al., 2018), pickling vegetables (Dupas de Matos et al., 2019; Lassen et al., 2025), marinades (Sabzi et al., 2024) and others. Among applications, using verjuice in sauces was commonly cited by consumers in previous research (Dupas de Matos et al., 2023, 2024). Despite its potential, verjuice has not yet been explored as an acidifier alternative in sauces, like mayonnaise, representing an area underexplored in the literature.

Verjuice is generally made from grapes derived from thinning (Fia et al., 2022), which are usually left to rot. Verjuice represents a possibility to utilize discarded grapes, adding value to the food sector by creating a new ingredient that can be used in various use-case scenarios (Dupas de Matos et al., 2023). Different verjuice styles can be found in the market, with varied sensory characteristics (Hayoglu et al., 2009; Dupas de Matos et al., 2023, 2024), made from several grape varietals and processed under different conditions (Dupas de Matos et al., 2017; Lassen et al., 2025; Soares et al., 2025). Previous literature has shown that verjuice can be considered a suitable acidifier alternative to vinegar and lemon due to its acidic characteristic (Nikfardjam, 2008; Öncül and Karabiyikli, 2015). For instance, Dupas de Matos et al. (2018) showed that salads seasoned with verjuice received similar liking scores to those seasoned with lemon juice. Also, when verjuice was used to acidify pickles, liking scores were comparable to vinegar-based pickles (Dupas de Matos et al., 2019). More recently, Dupas de Matos et al. (2023) observed that verjuice has been indicated to be incorporated in beverages (e.g. cocktails and drinks) as well as a cooking ingredient (e.g. in marinades for deglazing). However, its application and performance in composite food is still little explored, which is essential to better position verjuice in the market.

Hedonic responses, not rarely, are not enough to discriminate samples in consumer studies (Ng et al., 2013). The evaluation of emotional responses has shown to be a powerful approach to go beyond liking, better understanding consumer experience holistically (Jaeger et al., 2019). High acceptance is usually followed by evoked positive emotions (King and Meilsmann, 2010). Jaeger et al. (2019) showed that the increase in positive emotional responses was directly linked to greater consumer involvement with the product. However, emotions may not present a standard pattern among consumers. Several research has shown that many factors can influence consumer emotional responses and food neophobia (FN) is a critical one (Fenko et al., 2015; Jaeger and Hedderley, 2013; Jaeger et al., 2022). Among a wide range of foods and beverages, FN has been associated with negative emotional valence and higher arousal (Jaeger et al., 2022). Also, negative emotional associations with certain attributes may indicate that consumers with high FN may be more sensitive to unfamiliar or strong sensory characteristics, which may evoke negative feelings (Tuorila and Hartmann, 2020). To date, there is a lack of scientific evidence regarding the impact of different acidifiers on affective responses and sensory characteristics of mayonnaise. This offers an opportunity to investigate how verjuice addition may impact consumer responses and sensory perception of mayonnaise, potentially offering a novel alternative to more commonly used acidifiers.

In a globally competitive market, food companies face the challenge of developing new products to meet consumer wants and needs. In fact, the failure rate of new food products still remains above 80% (Rutkowski, 2022). Importantly, consumer acceptance and attitude towards novel products is a complex phenomenon and clustering consumers based on specific characteristics has been shown to be an important tool (Guzek et al., 2017; Pagliarini et al., 2022). Santa Cruz et al. (2007) emphasized the importance of consumer segmentation based on sensory acceptability and sociodemographic profile of commercial mayonnaises. However, among several consumers’ traits that impact food acceptance (e.g. consumer innovativeness profile, among others), FN remains as one of the most popular in current literature. FN, the reluctance to try new or unfamiliar foods (Pliner and Hobden, 1992), significantly affects food acceptance, with individuals with higher FN being less likely to consume or try many foods (Jaeger et al., 2023). FN can also influence consumer sensory, emotional and cognitive associations to novel foods (Aqueveque, 2016; Tuorila and Hartmann, 2020) as well as foods with sustainable ingredients (Pagliarini et al., 2022).

In these scenarios, the present work presents two hypotheses:

Considering the gap in the literature towards utilization of verjuice in composite foods and the importance of FN on the insertion of novel products and ingredients on the market, the main objectives of this research were to evaluate verjuice as a novel acidifier to vinegar and lemon juice in mayonnaise and to identify the sensory characteristics best suited for this use-case scenario. A secondary, exploratory objective was to examine how FN influences affective responses and perceived sensory attributes in mayonnaises prepared with traditional and novel acidifiers.

The verjuice sample set was established based on the diverse sensory characteristics of previous literature (Dupas de Matos et al., 2024) while also representing a range of countries of origin and grape varietals. Three verjuices were used. One commercial verjuice was purchased from Domaine Wardy (Zahle, Lebanon), and the other was purchased from Quinta dos Sentidos (Algarve, Portugal). The experimental verjuice was produced from Isabel varietal (Vitis labrusca) based on protocol described by Lassen et al. (2025). Briefly, grapes were harvested at ripening stage between 29 and 31 (between peppercorn- to pea-sized berries) (Coombe, 1995), bunches were destemmed and berries were washed with tap water and sanitized with a chlorinated solution (at 100 ppm for 15 min) and then re-washed. The berries were crushed and pressed in a perforated basket (40 cm diameter, 50 cm high, holes of 2 mm) until the juice was completely extracted. Then, 0.5 kg/L of potassium metabisulfite was added to the juice to avoid microbial growth and oxidation. The juice was left at 0 °C for 25 days for precipitation of tartrate crystals followed by vacuum filtration (filter paper 11 µm). The bottles were then pasteurized (75 °C for 1 min), left to cool down and stored at 5 °C until analysis.

Alcohol vinegar (Rosina, Flores da Cunha, Rio Grande do Sul (RS), Brazil), commercial lemon juice (Castelo, Jundiaí, São Paulo, Brazil), pasteurized egg yolk (Naturovos, Salvador do Sul, RS, Brazil) and soybean oil (Liza, Belo Horizonte, Minas Gerais, Brazil) were purchased in a local supermarket (São Luiz Gonzaga, RS, Brazil). The mayonnaise production followed a protocol proposed by Di Mattia et al. (2015), according to the following steps: (1) 500 g of soybean oil and 120 g of pasteurized eggs were mixed in a 1 L-domestic blender (Philco, PMP1600, 1700 W, Manaus, Amazonas) until a homogeneous mixture was obtained; (2) addition of 1 g salt and 30 g acidifier (whether vinegar, lemon juice or verjuice) followed by mixing until achieving total homogeneity. The samples were then cooled down to 5 °C and kept for 24 h to stabilize (based on pilot tests) before analysis. The final five mayonnaise samples were: LEB (with Lebanese verjuice added as acidifier), POR (with Portuguese verjuice), EXP (with experimental verjuice made in-house), VIN (with vinegar) and LEM (with lemon juice). Physicochemical characterization (pH and acidity) of mayonnaise samples is reported in Table S1.

Before the study, a round table discussion was conducted as described by Maschio et al. (2023) to generate sensory attributes to compose a check-all-that-apply (CATA) list. The panel (n = 9), consisting of regular mayonnaise consumers, evaluated the samples (n = 5) monadically to allow comparisons. After that, they were asked to write down the sensory characteristics using their own words focusing on the samples’ differences. Then, all words were written on a blackboard, and the discussion was conducted by an experienced moderator. This phase was performed to check words and/or terms with similar connotations and/or meanings and whether the sensory attributes were related to appearance, aroma, taste, mouthfeel, texture or residual aftertaste. A consensus of the words was made between 2 experienced researchers, and a final list including 28 sensory attributes (Table S2) was used in the consumer study, as described in Section 2.4.3.1. These volunteers did not participate in the consumer study.

Participants (n = 113), recruited through posters on the university campus (São Luiz Gonzaga, RS, Brazil) and via social media, met the following criteria: regularly consume mayonnaise, over 18 years old, no intolerance or allergies to eggs, sulfites or alcohol and not pregnant or lactating.

The work was approved by the Ethics Committee of the State University of Rio Grande do Sul (protocol number 6.864.640) and Certificate of Presentation of Ethical Appreciation (number 76632523.6.0000.8091). The participants provided written consent prior participation. Upon completion of the study, the participants were offered a snack as a thank-you for their time.

Three types of responses were obtained. The first was liking using a structured nine-point fully labeled scale (1: dislike extremely and 9: like extremely). Emotion was next and performed using CATA. EsSense 25 profile (Nestrud et al., 2016) was used with a few modifications. The emotion “pleasant” was removed, given its similar meaning to “happy” (King and Meiselman, 2010; Jaeger et al., 2019; Dupas de Matos et al., 2024); “bored” and “joyful” were removed due to error in translation from English to Portuguese and “warm” was replaced by “affectionate” from the EsSense Profile (King and Meiselman, 2010) since “warm” in Portuguese (“caloroso”, “aquecido”) does not present a clear translation from English and “affectionate” represents a closer meaning to “warm.” The final list consisted of 22 terms (Table S3).

Finally, sensory product characterization was conducted also using CATA, which was modality specific (Table S2): (1) appearance: light yellow color, intense yellow color, shiny, opaque, with lumps, without lumps, liquid/thin and thick; (2) aroma: egg, vegetable oil, vinegar, lemon, homemade mayonnaise-like and industrial mayonnaise-like and (3) in-mouth: sour, sweet, salty and bitter (tastes); egg, vegetable oil, vinegar, lemon, homemade mayonnaise-like, industrial mayonnaise-like (flavors) and creamy, oily, spicy/burning and astringent (textures/mouthfeels). To minimize order bias, both emotion and sensory term order were randomized across consumers, but each consumer retained the same order throughout the session.

At the end of evaluation, the Food Neophobia Scale (FNS) questionnaire (Pliner and Hobden, 1992), previously translated and validated in Portuguese (Previato and Behrens, 2015), was used to evaluate participant FN level by using a structured seven-point fully labeled scale (1: strongly disagree and 7: strongly agree).

Participant’s gender, age, consumption frequency of mayonnaise, type and occasion of mayonnaise consumption were measured with a short survey at the end of session.

The study was conducted as central location test at the Universidade Estadual do Rio Grande do Sul campus (São Luiz Gonzaga, RS, Brazil). The samples (20 g) were served chilled (∼5 °C) in 30ml clear plastic cups coded with three-digit random codes and evaluated by using a plastic spoon, under white lighting in a neutral test room (20 ± 2 °C). The samples were served monadically and presented according to a complete and balanced design based on a Williams Latin Square. At the beginning of the session, consumers were instructed about study procedures, with meaning of sensory (Table S2) and emotions terms (Table S3) verbally explained. There was a minimum forced 1-min break between samples, and to minimize carryover effects, the participants were instructed to cleanse their palate during this time with a bite of cracker (Isabela, Pinhais, Paraná, Brazil) followed by water. Data were collected using Compusense (Guelph, Ontario, Canada), with consumers using their personal mobile devices.

All statistical analysis were performed using R software version 4.3.0 (R Core Team, 2020) in R studio version 2023.12.1 and XLSTAT (2023.3.0). The α-risks were set at 5%.

FNS data were evaluated by α-Cronbach coefficient, considered with good reliability when α ≥ 0.70 (Previato and Behrens, 2015). After checking reliability, consumers were clustered into two groups: (1) higher in FN (named herein as higher) and (2) lower in FN (lower), by using the mean value of the entire population based on the sum of the answers for the 10 items (Meiselman et al., 2010). FN scores ranged from 10 to 49 with an average sum of 29.4 (cut-off). The higher group had a FN mean ≥ 30, with an average of 37.3 ± 5.4, whereas the lower group had a FN mean ≤ 29, with average score of 20.5 ± 6.0. The mean of each FNS statement was compared by Fisher’s test to evaluate homogeneity of the variances followed by Student’s t-test, as suggested by Aqueveque (2016).

Liking was evaluated by two-way analysis of variance (ANOVA) (sample and FN cluster as fixed factors) to ascertain any differences or interactions. Normality of data and homogeneity of variances were evaluated by Shapiro–Wilk and Hartley’s maximum F tests, respectively, for each cluster before performing ANOVA.

Since emotions were evaluated as binary data (non-parametric), the effect of sample, cluster and sample*cluster on each emotion term and sensory attribute were evaluated by generalized linear model (GLM) as described by Fryer et al. (2025). Analysis of deviance and associated chi-square tests were used to determine the statistical significance between the independent variables and their interaction. Post hoc tests were conducted subsequently, using Tukey's Honestly Significant Difference for pairwise comparisons.

Penalty-lift analysis was performed for each CATA term to determine the mean impact of term on liking (Meyners et al., 2013). A threshold of 10% citation was used. Herein, also, for each FN cluster, frequencies of mention were determined by counting the number of consumers that check each term to describe each sample within a cluster, and the non-parametric Cochran’s Q test was applied to detect differences in terms among samples by clusters.

Participants (n = 113) were predominantly female (73%), with an average age of 30.3 ± 12.5 years old. Detailed information regarding consumers’ frequency of consumption is presented in Table S4.

The reliability of FNS questionnaire was checked with the calculated α-Cronbach of 0.764. The clustering resulted in two groups: higher (53.1%, FN mean ≥ 30, average of 37.3 ± 5.4) and lower (46.9%, FN mean ≤ 29, average of 20.5 ± 6.0). Detailed information on FN scores for each statement is presented in Table S5.

When analyzing differences in liking, significant differences were observed for cluster (p = 0.038) and sample (p = 0.003), whereas cluster*sample interaction was not significant (p = 0.875). Figure 1 shows mean liking scores of mayonnaise samples considering samples (Figure 1a) and group (Figure 1b) as factors. Figure 1a shows that LEB and POR samples presented higher (p < 0.05) liking scores compared to VIN, on average, and did not differ from EXP and LEM (p > 0.05). Between clusters, consumers with lower FN presented higher liking scores than consumers with higher FN (Figure 1b).

Table 1 shows deviance and associated p-values with effect of sample, cluster and their interaction by emotion for mayonnaise samples. Specifically, a significant cluster*sample interaction was observed for “secure” and “tame” (Table 1). However, there were no significant pairwise differences found across samples for “tame” or between clusters for “secure” despite significant p-values (Figure S1). The citation for “good” was significant among samples and between clusters (Table 1), in which the higher FN cluster more often cited it compared to the lower FN cluster (Figure 2). Among samples, POR received a higher citation for this emotion compared to VIN, while LEM did not differ from the verjuice-based samples, on average (Figure S2). For “calm” and “disgusted”, citation statistically differed between clusters but not among samples (Table 1). The higher FN cluster cited “calm” more often and “disgusted” less often compared to Lower FN cluster. “Aggressive” citation was significant among samples (Table 1); however, further pairwise evaluation did not show differences (Figure S2) due to low frequency of citation for this term despite a significant p-value.

Analysis of deviance indicated sample, cluster and interaction effects on sensory terms as shown in Table 2. The only significant interaction was for “astringent” (Table 2); however, based on the conservative Tukey’s test, there were no significant differences among samples or between FN groups (Figure S3) despite a significant p-value.

Figure 3 shows the citation proportion for the significant sensory attributes, considering each sensory modality.

For appearance, “shiny” significantly differed between clusters (Table 2), with the higher FN cluster citing this term more often compared to the lower FN group (Figure 3a). Among aroma attributes, “egg smell” differed between clusters, with the higher cluster citing more this term (Figure 3b). On the other hand, “vegetable oil,” “VIN,” “lemon” and “homemade mayonnaise-like” aromas differed among samples (Table 2). The EXP sample received higher citations for “vegetable oil aroma” compared to VIN, while LEM did not differ from other verjuice-based samples, which did not differ between them (Figure S4). As expected, VIN had significantly higher citation frequency of “VIN aroma,” followed by LEM and the verjuice-based samples. For “lemon aroma,” LEM did not differ from VIN and LEB but presented higher citations than POR and EXP. For homemade mayonnaise-like aroma, LEB and POR received higher citation than VIN and LEM, while EXP did not differ from other verjuice-based samples or the samples made from traditional acidifiers (Figure S4). For taste, “sour” was the only term with difference among samples (Table 2). VIN and LEM presented higher citation compared to the samples with verjuices, which did not differ among them (Figure S4). For flavor, “egg flavour” and “industrial mayonnaise-like” presented differences between clusters (Table 2). The higher FN cluster cited “egg flavor” more often than the lower FN, whereas the lower cluster cited “industrial mayonnaise-like flavor” more often than the higher FN group (Figure 3). “VIN” and “lemon” flavors citation differed among samples (Table 2). Figure S3 shows that similar behavior was observed for VIN flavor and aroma, in which VIN presented a higher portion of citation than other samples. For “lemon flavor,” LEM and LEB presented higher citation than VIN, with no differences found between verjuice-based samples for this attribute. Finally, for texture and/or mouthfeel, “oily” differed among samples, with higher citation observed for LEB compared to VIN, but no differences between verjuice-based samples and LEM were observed.

Penalty-lift analysis provided further insights into differences between clusters based on drivers of liking (Table 3). “Sour” had a significant negative impact on liking, while “homemade mayonnaise-like” (aroma and flavor) and “creamy” positively impacted liking. For the higher cluster, “without lumps” and “lemon” (aroma and flavor) positively impacted liking, while “oily” negatively impacted liking. For the lower cluster, “homemade mayonnaise-like” (aroma and flavor) and “creamy” texture positively impacted liking, whereas “opaque,” “vegetable oil,” “Vinegar” (aroma and flavor), “industrial mayonnaise-like aroma” and “bitter” had a negative impact on liking. Cochran’s Q test indicated that the number of attributes discriminating samples was similar between clusters. Out of 28 attributes, 8 were statistically significant for both clusters.

The liking scores varied between 6.5 ± 1.5 and 7.4 ± 1.8, which is within the acceptance range reported by previous literature (Santa Cruz et al., 2007). As the interaction was not significant, which indicates that the pattern of sample liking was consistent across consumer clusters and not changing depending on sample, consequently, clusters and samples were evaluated separately.

In contrast to H1, the use of verjuice in mayonnaises presented higher acceptance than the use of vinegar. Results showed that mayonnaises made with verjuices and lemon juice presented higher mean liking scores, indicating that this novel sustainable ingredient presents high potential to be used in composite foods. Food acceptance is strongly influenced by familiarity (Tuorilla and Hartmann, 2020), and food familiarity or the lack thereof has a key role in neophobic behavior (Henriques et al., 2009). Also, changes in sensory characteristics can sometimes lead to negative consumer reactions, mainly in traditional foods (Guerrero et al., 2009; Ares et al., 2010). Participants in the present study were regular consumers of mayonnaise, and although the acidifiers typically used by these consumers was not collected, vinegar and lemon juice are widely utilized to season and acidify mayonnaises in Southern of Brazil (Elias et al., 2015). Additionally, vinegar is the most popular acidifier among Brazilian consumers, especially in the Rio Grande do Sul region (Elias et al., 2015), while verjuice remains unknown in Brazil. In fact, consumers are generally unaware of verjuice’s incorporation into dishes and beverages (Dupas de Matos et al., 2023), although its sensory profile can be perceived to be like lemon juice when used as a salad dressing (Dupas de Matos et al., 2018).

As expected, and in line with H2, consumers with lower FN scored higher for liking than those with higher FN, in line with previous research (e.g. Henriques et al., 2009; Fenko et al., 2015). FN can impact the acceptance of novel foods (Tuorilla and Hartmann, 2020), since neophobic consumers tend to be more reluctant to try new foods and incorporate their personal values into the evaluation, implying their choice process is more complex (Berrena and Sanchez, 2013). Also, high neophobic consumers, along with reluctance to try unfamiliar foods, tend to present higher rejection of foods in general, mainly due to complexity and perceived dangerousness, which are known to elicit high levels of physiological and psychological arousal (Jaeger et al., 2023). Consequently, neophobics tend to evaluate novel food products more affectively and neophilics more cognitively (Fenko et al., 2015). Laureati et al. (2018) observed that foods related to high levels of warning stimuli (e.g. bitterness, sourness and astringency) presented lower acceptance for higher neophobic consumers. The authors also observed that higher arousal was experienced when consuming foods perceived as unpleasant or potentially dangerous plays a key role in differences in liking across varying levels of FN. Additionally, Jaeger et al. (2023) observed that arousal is a strong determinant of liking and that this underlies the rejection of both familiar and novel foods. Yet, authors observed that other arousal-inducing factors (e.g. flavour intensity) play an important role in FN. As food acceptance is shaped by a range of intrinsic and extrinsic factors (Kourouniotis et al., 2016), this study highlights the importance in considering FN prior to launching innovation within this product category.

The findings indicate that verjuice is a suitable acidifier for mayonnaises in culinary and industrial applications given acceptance presented herein in addition to verjuice’s nutraceutical and sustainability credentials (e.g. Fia et al., 2022; Dupas de Matos et al., 2023). These features can create opportunities for marketing strategies when introducing this novel ingredient to be used in other composite foods and beverages such as desserts, drinks, cocktails and others.

The study of emotions in sensory research provides a more holistic understanding of consumer experience, going beyond acceptance. FN has shown to impact emotional response to foods, and exploring its influence on a wider range of food categories is important to understand preferences and choices, which can support the design of marketing strategies to specific target audiences (Aqueveque, 2016). In this study, FN level impacted emotional responses with a few emotions (“good,” “calm,” “secure,” “aggressive,” “disgusted” and “tame”) discriminating the samples. Thus, H2 was partially accepted, since FN level did not present large changes on affective responses. Dupas de Matos et al. (2024) investigated emotional response to the general idea of verjuice as a product. The authors found that it evoked mainly positive emotions, with “happy” and “satisfied” showing significant differences based on consumers’ familiarity level with the product (Dupas de Matos et al., 2024). Conversely, negative emotions such as “aggressive” and “disgusted” received very low ratings, suggesting that the general concept of verjuice did not elicit negative feelings (Dupas de Matos et al., 2024). It is important to note that in Dupas de Matos et al.'s (2024) work, emotional responses were based on the concept of verjuice as a product, without involving tasting. In the present study, samples were presented blindly, without informing participants about the inclusion of verjuice. Thus, based on previous literature on verjuice and current findings, informing consumers about its presence could be beneficial, as it may help foster positive emotions and enhance the overall experience.

For most of the emotions, the level of FN did not impact the citation proportion except a few terms with positive valence. It was expected that FN level would impact emotional responses, since individuals with higher FN tend to present higher arousal when presented with food stimuli (Raudenbush and Capiola, 2012). The slight but significant differences in emotions evoked relate to some literature, indicating that liking (and possibly emotions) is also influenced by sensory attributes' intensity (Laureati et al., 2018; Jaeger et al., 2023). Also, this may be related to expectations. Expectation is based on the product’s hedonic and sensory perception prior to food consumption, which is then contrasted with people’s feelings and sensations when the product is consumed (Ares et al., 2010). Food neophobic consumers tend to negatively anticipate liking of foods (Costa et al., 2025), and if the actual taste goes against their expectation, following the contrast theory (Cardello and Sawyer, 1992), consumers may be more favorable to product evaluation. This might explain why the higher cluster cited more frequently “good,” “calm” and “secure” compared to the lower cluster.

Verjuice-based mayonnaise (POR) received higher citation of “good” compared to the VIN-based sample (VIN), highlighting that although verjuice is an unknown product in Brazil, its addition to mayonnaise elicited more positive emotional response than mayonnaises prepared with a traditional acidifier. Also, verjuice-based samples were accepted at the same level as the mayonnaise with LEM, another traditional acidifier commonly used. Thus, H1 was partially accepted, since verjuice-based mayonnaises impacted slightly on emotions evoked. Future studies should investigate whether affective responses would change if consumers were informed about the acidifier beforehand. Understanding the impact of prior knowledge on emotional response and sensory perception can provide valuable insights for the food industry in future product positioning in the market.

Although overall acceptance patterns were similar across neophobia levels, penalty-lift analysis offered deeper insight into the specific sensory drivers of liking. Among the 28 terms evaluated, based on the FN level, consumers discriminated samples for only four attributes (“shiny,” “egg aroma and flavor” and “industrial mayonnaise flavor”). However, these attributes did not impact liking positively or negatively by either of the clusters, suggesting that other sensory features were more relevant. Consumers with higher FN more frequently cited “shiny” and “egg aroma and flavor,” while the opposite was observed for “industrial mayonnaise-like flavor.” Previous research suggests that food neophobics may develop hypersensitivity to warning sensations to some tastes and flavors making them particularly cautious with certain foods (Laureatti et al., 2018).

“Vegetable oil aroma,” more often cited in a verjuice-based mayonnaise compared to the vinegar-based sample, was a driver of dislike for the lower FN group, suggesting that the addition of verjuice made in-house enhanced the perception of this sensory characteristic in mayonnaise. As expected, “Vinegar aroma and flavor” were more frequently cited in the vinegar-based sample. Surprisingly, these attributes were drivers of disliking only for the lower FN, showing that the acetic note was more critical for this group of consumers. As expected, “lemon aroma” was highly cited for lemon-based sample; however, it did not differ from the verjuice-based (LEB) and VIN samples. Verjuice is characterized by a lemon and/or citric note like lemon juice (Dupas de Matos et al., 2017, 2024), in line with results herein. In terms of product development, acidity levels need to be carefully considered. The citation of “sour” (negative impact on liking for both clusters) was higher in vinegar- and lemon-based samples compared to the verjuice-based samples. In fact, when vinegar and verjuice were used to acidify pickles, vinegar was perceived as having higher acidity (Dupas de Matos et al., 2018). In contrast, Dupas de Matos et al. (2018) found that salads seasoned with verjuice were more likely to be described as having “high acidity” compared to those with vinegar or lemon. This suggests that the type of food in which verjuice is used plays a role in influencing consumer’s perception of acidity. Additionally, pH (3.91–4.52) and acidity (31.8–17.4 g/Kg) values of samples were in line with previous work that produced sauces with similar ingredient ratios (Di Mattia et al., 2015).

Thus, H1 and H2 are accepted, since acidifier impacted sensory perception of mayonnaise by consumers. Similar findings were found between FN groups.

Penalty-lift analysis and Cochran’s Q test results indicated that, for the higher FN group, six attributes positively impacted liking (“without lumps,” “lemon aroma and flavor,” “homemade mayonnaise-like aroma and flavor” and “creamy” texture) and two negatively impacted liking (sour and oily mouthfeel). Also, within the higher FN group, eight attributes discriminated against samples, in which two were significant drivers of liking (“homemade mayonnaise-like” aroma and flavor) and two drivers of dislike (“sour” taste and “oily” texture). For the lower FN group, ten attributes impacted liking, where three drove liking (“homemade mayonnaise-like” aroma and flavor and “creamy”) and seven drove dislike (“opaque,” “vegetable oil,” “Vinegar” and “industrial mayonnaise-like” aromas, “sour,” “bitter,” and “Vinegar” flavor). Yet, for the lower FN group, out of the seven attributes discriminating samples, only two (vinegar aroma and flavor) impacted liking negatively. The differences based on the FN level and their impact on liking may also be linked to expectations (Cardello and Sawyer, 1992). This suggests that while both clusters were able to discriminate samples based on a similar number of attributes, more attributes influenced the acceptance of the products positively than negatively.

Although 113 consumers took part in the study, it would be prudent to use larger segments, particularly among consumers with a high neophobic profile to ensure a more representative distribution (e.g. low, moderate and high). Also, considering that the level of product involvement (e.g. frequency of consumption) may influence responses (e.g. Lee et al., 2021), future research could extend these findings by incorporating measures of product involvement to better understand how it interacts with FN. Additionally, consumers’ profile and other consumers’ traits (e.g. food technology neophobia and consumer innovativeness) may influence novel food acceptance and should be also evaluated in further works on verjuice within unexplored markets.

Overall, verjuice-based mayonnaises received higher mean liking scores than the vinegar-based sample within the conditions of this study, despite vinegar being a widely used acidifier in Brazil. This suggests that verjuice may be a viable alternative acidifier in mayonnaise formulations, but its potential application should be interpreted in the context of the specific consumer group and product formulation evaluated. The success of verjuice-based products is therefore likely to depend on consumer segmentation as well as target market positioning rather than generalized consumer acceptance. FN level impacted affective and sensory responses of mayonnaises, where consumers with lower FN presented significantly higher mean liking than the higher FN group. However, the magnitude of this difference should be interpreted with caution. In contrast to current literature, consumers with higher FN more frequently cited positive emotions than those with lower FN, suggesting that other traits (e.g. expectation or familiarity) may have influenced emotional responses. FN level had a slight impact on sensory perception, and the attributes differing between clusters were not drivers of liking or disliking. The addition of vinegar to mayonnaise influenced responses by eliciting emotions with both positive and negative connotations, with the former likely due to familiarity with vinegar-based mayonnaise sensory characteristics. In contrast, the use of verjuice enhanced the perception of mayonnaise-like flavors, evoking positive emotions and potentially contributing to increasing acceptance. Variation in responses to a novel acidifier in a popular multi-ingredient product emphasizes the importance of accounting for consumer characteristics when introducing new ingredients to the market. Further research across different food matrices and consumer populations is needed to better understanding the role of verjuice in composite foods and beverages.

The authors would like to thank the student Eduarda Ruaro, Family Berá, Domaine Wardy and Agroindústria Cantina Santa Fé (Braga, Brazil) for their valuable support with this project.

The supplementary material for this article can be found online.