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Purpose

This study aims to examine how urban consumers in Brazil and Portugal conceptualise and engage with local and seasonal foods, addressing the lack of cross-cultural empirical evidence comparing the Global South and Southern European contexts in relation to these concepts.

Design/methodology/approach

A free-word association (FWA) task was used to elicit spontaneous associations from two quota-controlled (for sex, age group, education level and location) samples of Brazilian (n = 1,003) and Portuguese (n = 408) consumers. These projective insights were triangulated with structured items measured on seven-point anchored scales, assessing conceptual definitions, self-reported consumptions and purchasing locations, which allowed for comparison to be made between implicit associations and explicit evaluations, bringing a more robust perspective.

Findings

Quality and freshness dominated the FWA in both countries for local and seasonal food. Economic meanings diverged: Brazilians associated these with affordability, whereas the Portuguese emphasised trust-based and positive economic aspects. Correspondence analyses revealed clear regional and sociodemographic contrasts: in Brazil, higher-income and educated groups prioritised sensory/safety attributes, while lower-income groups emphasised price; in Portugal, Lisbon residents highlighted health and/or environmental aspects, whereas Porto residents underscored sensory and economic value. Definitions of local food grounded in direct producer ties and traditional markets drew the strongest agreement, evidencing relational proximity. The integrated “local seasonal” concept received weak endorsement, indicating limited communication and understanding.

Originality/value

By combining projective and structured methods, this study provides novel cross-cultural evidence showing that relational and cultural meanings outweigh geographic metrics in shaping perceptions of local and seasonal food, highlighting the need for context-sensitive strategies to support sustainable food system transitions.

The concepts of local and seasonal foods are subject to multiple interpretations, and their meanings vary considerably depending on context and the stakeholders involved. Although both terms are widely invoked in sustainability discourse, their use often assumes a clarity that is not always empirically supported. Recent literature shows considerable variation in how local and seasonal foods are defined and operationalised across studies and contexts (Vargas et al., 2021; Wallnoefer et al., 2021; Stein and Santini, 2022). Such divergence reinforces the need to understand how these categories are defined, recognised and mobilised by different consumer groups.

Local food is typically associated with geopolitical boundaries; however, producers, suppliers, and consumers often have different interpretations of what constitutes “local” (Kuhl et al., 2021; Kim and Huang, 2021). Although the distance between production and consumption is frequently used as an indicative parameter in specific public policies and marketing discourses, no consistent definition or standardised regulatory distance between production and consumption exists to classify food as local (European Parliament, 2014; Martinez et al., 2010). Recent analyses indicate that the notion of “local” is not reducible to spatial proximity alone (Enthoven and Van de Broeck, 2021; Merlino et al., 2022). Rather than functioning as a straightforward measure of distance, “local” is mobilised through diverse evaluative criteria that vary across and within national contexts, including territorial identity, market embeddedness, provenance claims and trusted supply relations.

While these conceptual extensions reveal the multidimensional character of the local concept, similar approaches surround the idea of seasonality. One perspective, frequently adopted in the literature, defines seasonal foods as any food cultivated in its natural growing season, regardless of geographic origin (Vargas et al., 2021; Régnier et al., 2022). Others link seasonality to locality, or interpret it culturally, as foods traditionally consumed at given times of the year, such as Christmas (Brooks et al., 2011). Vargas et al. (2021) identified three main concepts: “in season”, referring to availability alone; “produced in season”, connecting production and natural cycles; and “local seasonal”, combining locality, proximity, and seasonality, denoting foods cultivated and consumed locally within their natural growing period.

Understanding how consumers perceive, value, and evaluate local and seasonal foods—including their benefits and limitations—is essential (Roininen et al., 2006). However, most evidence derives from culturally homogeneous settings, offering limited insight into diverse food environments. Cross-cultural approaches are therefore needed to extend behavioural research beyond Western, Educated, Industrialised, Rich, and Democratic societies contexts (Henrich et al., 2010; Ares, 2018). As Ares (2018) notes, cultural contexts shape sensory perceptions and the meanings of food.

Recent studies also highlight the growing importance of food system resilience, particularly in the context of climate disruptions, geopolitical instability, and supply chain fragility (Béné, 2020; Hertel et al., 2023; von Braun et al., 2023). These pressures further underscore the need to understand how consumers interpret locality and seasonality-based cues in increasingly uncertain food environments.

Despite extensive scientific literature on local foods, empirical cross-cultural comparisons of consumer perceptions in this theme remain scarce, and research examining both locality and seasonality together, rather than as disconnected constructs, remains notably limited. This scarcity is even more pronounced when considering indirect and projective approaches, such as the free-word association (FWA) task, which elicits spontaneous associations and intuitive links with food concepts. Recent work demonstrates that such methods can capture subconscious, affective, and less rationalised dimensions of perception that remain inaccessible to direct questioning (Rojas-Rivas et al., 2023; de Souza et al., 2024), yet their application to local and seasonal food remains limited.

This study compares Brazil, a structurally diverse country in the Global South, and Portugal, a Southern European country, to examine how urban consumers perceive local and seasonal foods. Given the growing urban population and the climate-related disruptions to food supply chains, it is crucial to reconsider food consumption patterns in large urban areas (Preiss et al., 2017; Jia et al., 2023). Although united by language and historical legacies, the two countries diverge materially in governance arrangements, retail infrastructures, and climatic seasonality, structuring how proximity, availability, and trust are embedded in food consumption. In Brazil, inequality and regional heterogeneity shape consumption patterns that diverge from dominant Western consumer-citizen models (Barbosa and Veloso, 2014). Portugal occupies a peripheral European position, marked by Mediterranean-Atlantic food traditions and fragmented agri-food structures (Hernández, 2023). Moreover, differences in climatic regimes — from Portugal's marked seasonal cycles to Brazil's heterogeneous tropical and subtropical conditions — shape how seasonality becomes perceptible in everyday diets (Fujihira et al., 2023; Spence, 2021; Capita and Alonso-Calleja, 2005).

Taken together, these structural and cultural contrasts support three analytical propositions. First, local food should be understood by consumers as a culturally mediated construct rather than a purely spatial designation, such that not only Brazil and Portugal but also regions within each country may consider distinct criteria of proximity, provenance and trust, as well as associations with quality and freshness grounded in perceived authenticity, short circulation chains and sensory expectations. Second, consumers should conceptualise seasonality primarily as a temporal criterion anchored in availability cycles, rather than as an attribute of the production method or as a marker of geographic provenance. Third, distinctions in how local and seasonal foods are perceived and evaluated by urban consumers are likely to reflect sociodemographic differences.

This study examines how urban consumers in Brazil and Portugal conceptualise and perceive local and seasonal foods through methodological triangulation, combining FWA with quantitative analysis to assess the role of sociodemographic factors. Using such methodological triangulation offers several advantages by enhancing the depth and breadth of research findings (Guerrero and Xicola, 2018).

By elucidating how meanings and practices vary across consumer groups, this study offers empirically grounded evidence to inform policymaking and public discourse. It advances current debates on the transition towards food systems that are environmentally sustainable, socially inclusive, and culturally embedded (O'Neill et al., 2019; Grunert, 2011).

The study focused on urban consumers in both countries. In Brazil, participants were drawn from the two most populated states within each of the five macro-regions: Goiás and the Federal District (Centre-West), Paraná and Santa Catarina (South), São Paulo and Rio de Janeiro (Southeast), Pará and Rondônia (North), and Alagoas and Sergipe (Northeast) (IBGE, 2022). In Portugal, data collection targeted residents of the Lisbon and Porto metropolitan areas. Together, they account for over 51% and 44% of the respective national populations of 203.1 and 10.3 million (IBGE, 2022; INE, 2021a, b).

Participants were recruited using quota-controlled sampling to enhance sample diversity, balanced across age groups (18–29, 30–40, and 50+ years), gender (male and female), and educational level (with or without higher education). The quota sampling strategy prioritised sociodemographic heterogeneity over representativeness, allowing for the inclusion of age, gender, and education categories that capture much of the known diversity in food-related perceptions. Although this method does not permit full probabilistic inference, it is well-suited for exploratory cross-cultural analyses aimed at capturing a broad conceptual range rather than providing population-level estimates (Heckathorn, 2011; Ares, 2018).

The online survey was implemented in LimeSurvey, and participants were recruited through Prolific. Prior to participation, potential respondents were informed about the study objectives and provided their informed consent. Ethical approval was granted by the Ethics Committee of the Faculty of Nutrition and Food Sciences, University of Porto (Ref. 92/2022/CEFCNAUP) and the Brazilian Ethics Committee (CAAE—68052322.2.0000.0144). Following Jaeger and Cardello (2022), data-driven exclusion criteria were applied to both countries to enhance data quality, as further detailed in Section 3.1.

The survey was initially written in European Portuguese and subsequently adapted to Brazilian Portuguese to account for language and cultural differences, addressing subtle but important variations in word usage and meaning. Although both are forms of Portuguese, expressions can convey different nuances, requiring linguistic adjustments, as considered in previous research (Ares et al., 2016; van Zyl and Meiselman, 2016).

The instrument was structured in two parts, consisting of: (i) an FWA related to seasonal and local food; and (ii) questions related to the perception of seasonal and local foods.

For the first section of the survey, participants were asked to list the first three words that came to mind when thinking about the term “Local food products”, and to classify each word as either “positive”, “neutral”, or “negative” (Sousa et al., 2021). The same procedure was applied to the second stimulus, “Seasonal food”. To minimise priming, the FWA task was always administered before the structured conceptual items, avoiding lexical anchoring and conceptual carry-over effects (Ares et al., 2016).

The second section assessed participants' perceptions of local and seasonal food concepts, as well as their self-reported consumption and purchasing habits of these products. The conceptual statements were adapted from Vargas et al. (2021). For local food, three dimensions were included:

  1. Geographical: products produced within the country, state, or region of residence (geopolitical), or within 20 km or 100 km of the place of consumption;

  2. Regional: products certified with Protected Designation of Origin (PDO) or Protected Geographical Indication (PGI); and

  3. Holistic: products purchased directly from producers or at local/traditional markets.

For seasonal food, items were distinguished between products that are “in season”, “produced in season”, and “locally produced in season”. For the second section of the survey, all items were measured using 7-point anchored scales, ranging from 1 (strongly disagree) to 7 (strongly agree) for conceptual statements, and from 1 (never) to 7 (always) for reported consumption frequency.

2.3.1 Free-word association

All valid participant responses were included in the analysis. Data were examined through inductive content analysis, grouping semantically related terms into categories. Coding followed a triangulated approach (Guerrero et al., 2010), with two independent teams of three native Portuguese-speaking researchers, each familiar with their national context. These groups thoroughly evaluated the data for Brazil and Portugal separately, categorising terms into specified categories and dimensions. Within each team, classifications were first completed individually and later refined through consensus.

The initial analysis was conducted in Portuguese (both European and Brazilian, respectively), the native language of the data, and subsequently translated into English following the standardised guidelines provided by Anderson and Brislin (1976). Frequencies within each dimension were calculated based on the number of consumers who mentioned relevant words for each stimulus (Martins et al., 2019). To ensure interpretive relevance while retaining diversity, only categories cited by at least 5% of participants were included in the final analysis (Vidal et al., 2013).

A chi-square test of independence was conducted to determine whether significant associations existed between the dimensions of seasonal and local food consumption profiles and sociodemographic variables (age group, gender, and education level), using a 95% confidence interval. A per-cell chi-square test was used to identify the sources of variation observed in the global chi-square, based on the adjusted standardised residuals (Sharpe, 2015; Agresti, 2013).

Additionally, Correspondence Analysis (CA) was employed to examine the relationships between the dimensions and sociodemographic groups (gender and age). The CA was applied to the frequency table to produce a two-dimensional representation of the concepts and categories, facilitating the visualisation of similarities and differences and highlighting their principal characteristics (Greenacre, 2010). To prevent over-interpretation of marginal categories, interpretation was restricted to those exhibiting non-trivial contributions to the retained axes, following established contribution-filtering guidance in CA (Greenacre, 2007; Hjellbrekke, 2018).

2.3.2 Perceptions of seasonal and local food concepts

Descriptive statistics were applied to describe the sample's basic features, including frequencies, means, and standard deviations. Differences in variable scores among consumer groups were assessed using appropriate statistical tests. The Kolmogorov-Smirnov test was performed to assess the normality of the distribution of scores for various perception measures. Results indicated significant deviations from normal distributions, leading to the use of non-parametric tests for comparing scores.

The regular consumption of seasonal and local foods was analysed as a binary variable (yes/no). Participants who rated their consumption between 5 and 7, on a 7-point scale, were classified as “yes”, whereas those who rated between 1 and 4 were classified as “no” (adapted from Verbeke, 2015), thus allowing for a simpler classification of consumers of local and seasonal food.

Effect sizes were computed as r = Z/√N, where Z corresponds to the standardised statistic from the Mann–Whitney U test and N denotes the total number of observations (Rosenthal and Rubin, 1986; Tomczak and Tomczak, 2014). Effect sizes were interpreted using Cohen's (2013) conventional benchmarks (small ≈ 0.10, medium ≈ 0.30, and large ≈ 0.50), acknowledging their heuristic nature. All statistical tests were conducted at a 95% confidence level, unless otherwise specified. Data were analysed using IBM SPSS Statistics v. 29 (IBM Corp, 2023).

A total of 1,740 responses were collected from participants living in the selected Brazilian states, and 735 responses from participants residing in the metropolitan areas of Porto and Lisbon, Portugal. In Brazil, 265 incomplete answers, 276 respondents residing outside the target states, and five living in rural areas were excluded. Additionally, 36 individuals with a completion time of less than half of the median time were removed (Maniaci and Rogge, 2014; Behrend et al., 2011), as well as 13 participants who answered 18 or more of the 20 motivation questions with the same value (“straight-lining” behaviour), and 12 who repeated the same word in the FWA task. A further 114 participants were excluded for inconsistent responses (e.g. reporting product consumption while also stating they had never heard of it), and 21 were removed to prevent oversampling of specific demographic groups. The final Brazilian sample consisted of 1,003 participants.

In Portugal, 90 incomplete responses and another 71 from participants residing in rural areas were excluded. Respondents with a completion time of less than half of the median time (n = 69), “straight-lining” behaviour (n = 18), and those who repeated the same word in the FWA task (n = 5) were also removed. Additionally, 34 individuals were excluded due to inconsistent responses, and 40 were removed to prevent oversampling of specific demographic groups. The final Portuguese sample was comprised of 408 participants.

The socio-demographic characteristics of the selected participants in both countries are presented in Table 1.

Table 1

Socio-demographic characteristics of Brazilian (n = 1,003) and Portugal (n = 408) participants

Brazil (n = 1,003)Portugal (n = 408)
VariableCategoriesTotal (n = 1,003)Centre West (n = 208)South (n = 217)Southeast (n = 204)Northeast (n = 182)North (n = 192)p-value#Total (n = 408)Great Porto Area (n = 219)Great Lisbon Area (n = 189)p-value#
GenderFemale527 (52.5%)105b113a,b113a95a,b101a,b0.903213 (52.2%)116a,b97a,b0.740
Male476 (47.5%)103104918791195 (47.8%)10392
Level of EducationWithout Higher Education504 (50.2%)101a,b (+) ***108a,b (−) ***107b (+) ***93a,b (+) ***95a,b (+) ***0.945195 (47.8%)110a,b85a,b0.290
With Higher Education499 (49.8%)10 (−) ***109 (+) ***97 (−) ***89 (−) ***97 (−) ***213 (52.2%)109104
Age (in years)
Mean (n = 1,003): 39.64 (±14.21)
18–29330 (32.9%)66a,b65a57a72b (+) *70a,b0.015148 (36.3%)74a,b74a,b0.048
30–49365 (36.4%)7375786970146 (35.8%)7373
+50308 (30.7%)69776941 (−) **52114 (27.9%)72 (+) *42 (+) *
Family Incomea, bLow595 (59.3%)106a (−) **115a (−) *107a (−) *127b (+) **140b (+) ***<0.001187 (45.8%)106a,b81a,b0.351
High408 (40.7%)102 (+) **102 (+) *97 (+) *55 (−) **52 (−) ***221 (54.2%)113108

Note(s):

a

Income classification in Brazil followed the criteria of the Brazilian Institute of Geography and Statistics (IBGE, 2024), with classes E, D, and C grouped as low income

b

Income classification in Portugal was based on data from the National Statistics Institute (INE, 2025), with participants at or below the median gross income considered low income

# p-value according to the Mann-Whitney U Test, and a, b, c, d - homogeneous groups between regions, according to the Kruskal-Wallis test, at a 95% confidence level

(+) Alternatively, (−) indicates that the observed value is higher or lower than the expected theoretical value

***p < 0.001, **p < 0.01, and * p < 0.05; effect of the chi-square per cell

3.2.1 Local food products

The FWA task revealed contrasts and similarities in how Brazilian and Portuguese participants conceptualised local food products. In Brazil, 3,005 associations were elicited, comprising 691 distinct terms, whereas in Portugal, 1,224 associations were generated, with 371 unique terms; this lower volume primarily reflects the smaller sample size. Among the Brazilian participants, the most frequently reported associations with local food were “quality” (20.3%), “bean” (12.6%), and “meat” (12.3%), as shown in Table S1 (Supplementary Material). Across all five Brazilian regions, “quality” consistently emerged as a dominant descriptor, ranging from 17.6% in the Southeast and Northeast regions to 22.1% in the South and Centre-West, highlighting its central role in defining local food. Economic aspects were also salient, as reflected by frequent mentions of “price”, particularly in the Centre-West (15.4%) and North (11.5%).

In the Portuguese sample, the three most cited words were “fruits” (9.6%), “vegetables” (9.1%), and “quality” (8.1%). Other recurrent terms included “fresh” and “health” (6–7%), suggesting that local food in Portugal is closely associated with dietary groups and health-related attributes. In the Porto metropolitan area, participants emphasised “francesinha” – a popular local hearty sandwich, made with several meats and sausages, topped with melted cheese and sauce - (8.5%), “fruits” (8.1%), and “quality” (6.9%), whereas in the Lisbon metropolitan area, “vegetables” (10.6%), “fruits” (9.5%), and “fresh” (8.9%) were the predominant associations. These contrasts suggest that participants from Porto were more closely associated with local food and its regional culinary identity and quality. In comparison, Lisbon's consumers emphasised associations with horticultural produce and freshness.

For both countries, the elicited terms were grouped into categories and subsequently organised into 15 dimensions, divided into positive, negative, and neutral categories. In Brazil, 69 categories were identified, whereas in Portugal, the responses clustered into 64. Table 2 summarises the distribution of local food dimensions by polarity and sociodemographic group, while Table S2 (Supplementary Material) presents frequencies for detailed categories and representative terms. In both countries, the “Produce” dimension (e.g. of words: fruits, strawberries, tomato), characterised by positive associations, was the most frequently cited (26.4% in Brazil and 36% in Portugal), and was particularly prevalent among participants with higher education and those reporting regular consumption of local food.

Table 2

Absolute frequencies of mentions for the dimensions of the free word association (FWA) task related to “local food”, categorised by polarity and sociodemographic characteristics for Brazilian and Portuguese urban consumers

Brazil (n = 1,003)
Dimensions% participantsGender (x2 = 21.2#/p = 0.061##)Age groups (Years)
(x2 = 30.1#/p = 0.011#)
Education (x2 = 49.8#/p < 0.001##)Income (x2 = 41.26#p < 0.001##)Regular consumer of local food (x2 = 7.2#/p = 0.818##)Region of residence (x2 = 83.2#/p < 0.001##)
Male (n = 476)Female (n = 527)18–29 (n = 330)30–49 (n = 365)50+ (n = 308)No high education (n = 504)With high education (n = 499)Low (n = 595)High (n = 408)Yes (n = 778)No (n = 225)Centre West (n = 208)South (n = 217)Southeast (n = 204)Northeast (n = 182)North (n = 192)
Produce (positive)26.4%1311288510668108 (−) **151 (+) **78 (+) *37 (−) *2065340 (−) *28 (−) ***4763 (+) *81 (+) ***
Economical (negative)20.6%84123667863138 (+)***69 (−) ***134731555256 (+) *73 (+) ***4815 (−) ***15 (−) ***
Quality and Safety (positive)16.4%729241665757 (−) ***107 (+) ***80 (−) **84 (+) **134302412 (−) ***3149 (+) ***48 (+) **
Economical (positive)15.6%688847575258 (−) ***98 (+) ***81751253122 (−) *14 (−) ***3647 (+) ***37
Produce (negative)15.3%81725743 (−) *5396 (+) ***57 (−) ***41401173643 (+) *66 (+) ***345 (−) ***5 (−) ***
Quality and Safety Negative13.3%597534495183 (+) **51 (−) **80541043042 (+) **62 (+) ***222 (−) ***6 (−) ***
Processed Food (positive)11.5%64 (+) *51 (−) *3949276253423094211712 (−) **10 (−) **38 (+) ***38 (+) ***
Processed Food Negative8.4%444037 (+) *21 (−) *2656 (+) **28 (−) **147120711326 (+) *33 (+) ***195 (−) **1 (−) ***
Body, Health and Nutrition (positive)8.1%3051252234 (+) *24 (−) ***57 (+) ***414063189 (−) *5 (−) ***1824 (+) *25 (+) *
Hedonic and Sensory Proprieties (positive)8.1%433828252830 (−) *51 (+) *432660219 (−) *8 (−) *162226 (+) **
Economical (neutral)7.8%29492635174236512758201617141615
Gastronomy (positive)7.2%3735273114 (−) *3339106 (+) **47 (−) **55178 (−) *0 (−) ***1224 (+) **28 (+) ***
Produce (neutral)6.9%3138213018383159 (+) *25 (−) *50191917101112
Seasonal (positive)6.0%233714262025353426471384 (−) **151617
Body, Health and Nutrition (negative)5.9%2732132323322725 (−) *34 (+) *461322 (+) **171181 (−) ***
Portugal (n = 408)
Dimensions (polarity)%
Participants
Gender (x2 = 19.1#/p = 0.093##)Age groups (Years)
(x2 = 26.4#/p = 0.236##)
Education (x2 = 27.8#/p = 0.009##)Income (x2 = 22.4#/p = 0.060##)Regular consumer of local food (x2 = 12.4#/p = 0.675##)Area of residence (x2 = 34.2#/p < 0.001##)
Male (n = 195)Female (n = 213)18–29 (n = 148)30–49 (n = 146)50+ (n = 114)No high education (n = 195)With high education (n = 213)Low (n = 221)High (n = 187)Yes (n = 236)No (n = 172)Great Porto Area (n = 219)Great Lisbon Area (n = 189)
Produce (positive)36.00%767147544668796086876062 (−) **85 (+) **
Economical (positive)23.70%45524127294255455250476037
Food Quality and Safety (positive)22.80%39543037264548494450435439
Gastronomy (positive)18.40%41342827203936344043324629
Environmental (positive)12.70%223027 (+) *11 (−) *1414 (−) **38 (+) **183334182428
Hedonic and Sensory Proprieties (positive)12.20%18321519162129292128222624
Produce (neutral)11.80%24241918112325153228202226
Processed Food (positive)11.50%242318191028 (+) *19 (−) *242226211928
Social (positive)11.00%15 (−) *30 (+) *15201027 (+) *18 (−) *182527182817
Economical (neutral)9.10%15221911711 (−) *26 (+) *10 (−) *27 (+) *28 (+) *9 (−) *1720
Body, Health, and Nutrition (positive)8.80%1620817111818211420162016
Beverage (positive)6.60%18 (+) *9 (−) *81361314121417101512
Gastronomy (neutral)5.50%1471281 (−) *9121010101121 (+) ***1 (−) ***
Local (positive)5.40%1397964 (−) **18 (+) **8141481011

Note(s): # chi-square test of independence

##global chi-square test across all categories

(+) Alternatively, (−) indicates that the observed value is higher or lower than the expected theoretical value

***p < 0.001, **p < 0.01, and * p < 0.05; effect of the chi-square per cell

Significant sociodemographic variation emerged in Brazil, with regional disparities representing the strongest source of differentiation (χ2 = 83.2, p < 0.001). Education (χ2 = 49.8, p < 0.001) and income (χ2 = 41.26, p < 0.001) also contributed substantially, followed by age (χ2 = 30.1, p = 0.011). By contrast, patterns in Portugal were comparatively more homogeneous, although metropolitan area of residence (χ2 = 34.2, p < 0.001) and education (χ2 = 27.8, p = 0.009) still shaped responses. Gender and self-reported consumption frequency showed no significant effects in either country.

3.2.2 Seasonal food

The FWA task also revealed marked contrasts and similarities in how Brazilian and Portuguese participants conceptualised seasonal food. In Brazil, 3,009 associations were elicited, corresponding to 712 distinct terms. The most frequent associations were “quality” (13.6%), “fruits” (10.0%), and “price” (8.5%) (see Table S1). “Quality” was particularly emphasised in the South (17.5%), Southeast (15.2%), and Northeast (13.7%) regions, underscoring its importance as a defining attribute. The term “Fruits” was consistently cited across regions, especially in the North (10.9%) and Southeast (13.4%), reinforcing the perception that seasonality is closely linked to fruit availability.

Economic aspects were also salient, with terms such as “cheap” (5.3%) and “expensive” (3.8%) reflecting concerns over affordability, particularly among lower-income groups. In Portugal, 1,224 associations were identified, comprising 264 distinct terms, which again reflects the smaller sample size compared to Brazil. Responses were strongly dominated by fruit-related words, with “fruits” (27.5%), “strawberries” (22.1%), and “vegetables” (16.4%) as the most cited. Other recurrent associations included “cherries”, “watermelon”, and “chestnuts”, each mentioned by around 10% of participants. The elicited words were grouped into categories and organised into dimensions (15 in Brazil, 14 in Portugal), also divided according to polarity, as summarised in Table 3 and detailed in Table S3 (Supplementary Material).In both countries, the dimension “Produce” (e.g. fruits, mango, vegetables) with positive associations was the most frequently cited, accounting for 26.3% of responses in Brazil and 64.0% in Portugal. The second most cited responses were also related to “Produce”, but with negative polarity in Brazil (15.6%) and neutral in Portugal (20.6%). This pattern suggests that, even though seasonality was strongly positively associated with food groups in both contexts, it also elicited negative associations in Brazil and neutral associations in Portugal.

Table 3

Absolute frequencies of mentions for the dimensions of the free word association (FWA) task related to “seasonal food”, categorised by polarity and sociodemographic characteristics for Brazilian and Portuguese urban consumers

Brazil (n = 1,003)
Dimensions% participantsGender (x2 = 18.3#/p = 0.143##)Age groups (Years)
(x2 = 36.7#/p = 0.001##)
Education level (x2 = 52.9#/p < 0.001##)Income (x2 = 47.9#/p < 0.001##)Regular consumer of seasonal food (x2 = 14.7#/p = 0.419##)Region of residence (x2 = 85.7#/p < 0.001##)
Male (n = 476)Female (n = 527)18–29 (n = 330)30–49 (n = 365)50+ (n = 308)No higher education (n = 504)With higher education (n = 499)Low (n = 595)High (n = 408)Yes (n = 777)No (n = 226)Centre West (n = 208)South (n = 217)Southeast (n = 204)Northeast (n = 182)North (n = 192)
Produce (positive)26.3%13113381118 (+) **65 (−) *1231414822482240 (−) *26 (−) ***4667 (+) ***85 (+) ***
Produce (negative)15.6%817568 (+) **40 (−) **48100 (+) ***56 (−) ***4724472448 (+) **62 (+) ***356 (−) ***5 (−) ***
Quality and Safety Positive13.3%49 (−) *84 (+) *32 (−) *534846 (−) ***87 (+) ***65 (−) *68 (+) *65 (−) *68 (+) *2115 (−) **2835 (+) **34 (+) *
Hedonic and Sensory Properties (positive)12.8%547433514443 (−) ***85 (+) ***3716371616 (−) *11 (−) ***3235 (+) **34 (+) **
Economical (negative)11.2%486433384160527339733932 (+) *38 (+) **227 (−) ***13
Produce (neutral)11.1%53584439286051676167612929231614
Economical (positive)10.9%456426 (−) *424131 (−) ***78 (+) ***50 (−) **59 (+) **50 (−) **59 (+) **156 (−) ***2732 (+) **29 (+) *
Quality and Safety Negative10.2%475533412864 (+) **38 (−) **6834683430 (+) *38 (+) ***197 (−) **8 (−) **
Seasonal (positive)7.2%324017272819 (−) ***53 (+) ***27 (−) ***45 (+) ***27 (−) ***45 (+) ***176 (−) **23 (+) *1412
Hedonic and Sensory Proprieties (negative)7.1%274424242343 (+) *28 (−) *1541101541102129 (+) ***132 (−) ***6 (−) *
Gastronomy (positive)7.0%39 (+) *25 (−) *2621172935694269426 (−) *7 (−) *1123 (+) ***17
Economical (neutral)6.8%30382220263830422642261118151311
Body, Health, and Nutrition (positive)6.0%213927 (+) *14 (−) *19205353426342676 (−) *1224 (+) ***11
Seasonal (neutral)5.8%27311329 (+) *1620 (−) *38 (+) *24 (−) **34 (+) **24 (−) **34 (+) **121414108
Body, Health, and Nutrition (negative)5.3%21322019143 (+) **17 (−) **371637161525 (+) ***82 (−) **3 (−) *
Gastronomy (negative)5.3%282524 (+) *131640 (+) ***13 (−) ***10254102541521 (+) **151 (−) **1 (−) **
Quality and Safety Neutral5.2%262613182130223220322091371211
Seasonal (negative)5.2%23292018142824322032201415142 (−) **7
Portugal (n = 408)
Dimensions (polarity)%
Participants
Gender (x2 = 16.2#/p = 0.105##)Age groups (Years)
(x2 = 41.3#/p < 0.001##)
Education (x2 = 14.9#/p = 0.402##)Income (x2 = 16.4#/p = 0.420##)Regular consumer of seasonal food (x2 = 18.2#/p = 0.084##)Area of residence (x2 = 33.9/p < 0.001#v)
Male (n = 195)Female (n = 213)18–29 (n = 148)30–49 (n = 146)50+ (n = 114)No higher education (n = 195)With higher education (n = 213)Low (n = 221)High (n = 187)Yes (n = 310)No (n = 98)Great Porto Area (n = 219)Great Lisbon Area (n = 189)
Produce (Positive)64.00%138 (+) *123 (−) *1009863 (−) *124137114145195 (−) *66 (+) *123 (−) ***138 (+) ***
Produce (neutral)20.6%453944 (+) **2614 (−) **3747364765194341
Food Quality and Safety (positive)16.9%26431825263237333553164128
   Hedonic and Sensory Proprieties (positive)12.3%18327 (−) ***1627 (+) ***26242524351535 (+) *15 (−) *
Environmental (positive)12.2%183219151616 (−) *34 (+) *15 (−) *33 (+) *46 (+) *4 (−) *2723
Seasonal (positive)8.8%16201012141719161928829 (+) **7 (−) **
Economical (positive)8.6%171813715152013212692312
Body, Health, and Nutrition (positive)7.6%102171311141715142742110
Gastronomy (positive)5.9%12122 (−) **13 (+) *91311141016819 (+) *5 (−) *
Environmental (neutral)5.6%91416 (+) ***43101381522 (+) *1 (−) *1112
Seasonal (neutral)5.00%911108214 (+) *6 (−) *8111551010

Note(s): # chi-square test of independence

##global chi-square test across all categories

(+) Alternatively, (−) indicates that the observed value is higher or lower than the expected theoretical value

***p < 0.001, **p < 0.01, and * p < 0.05; effect of the chi-square per cell

Seasonal food associations were dominated by the “Produce” dimension (26.3% in Brazil; 64.0% in Portugal), followed by negative associations with “Produce” and “Quality and Safety”, indicating that seasonality is primarily understood through the availability of fruits and vegetables (Table 3). In Brazil, significant sociodemographic differences emerged, with regional variation representing the strongest source of differentiation (χ2 = 85.7, p < 0.001), followed by education (χ2 = 52.9, p < 0.001), income (χ2 = 47.9, p < 0.001), and age (χ2 = 36.7, p = 0.001). In contrast, patterns in Portugal were comparatively more homogeneous, although metropolitan area (χ2 = 33.9, p < 0.001) and age (χ2 = 41.3, p < 0.001) still shaped responses.

3.2.3 Correspondence analysis: local and seasonal food dimensions

The CA of the FWA aggregated data provides further insights into how sociodemographic characteristics shape perceptions of local and seasonal food in Brazil and Portugal. In both countries, only dimensions cited by at least 5% of participants within each polarity were retained. Sociodemographic variables that showed no significant variation or did not influence the distribution of associations in the analysis were excluded. Figure 1 presents the perceptual maps for local food in Brazil and Portugal, whereas Figure 2 depicts the corresponding maps for seasonal food. Detailed distributions are provided in Tables 2 and 3, respectively.

Figure 1
Two symmetric plots show F 1-F 2 relationships between sociodemographics and food-related dimensions.The plots are labeled “A” and “B”, each showing a symmetric correspondence plot with horizontal axis “F 1” and vertical axis “F 2”. A legend in both plots shows two types of scattered points: “Sociodemographics” and “Dimensions”. Plot A: The title reads “Symmetric plot (axes F 1 and F 2: 82.96 percent)”. The horizontal axis is labeled “F 1 (75.54 percent)” and ranges from negative 1 to 1.2 in increments of 0.2 units. The vertical axis is labeled “F 2 (7.42 percent)” and ranges from negative 0.6 to 0.6 in increments of 0.2 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Processed Food (p)”, “Gastronomy (p)”, and “Fresh Food (p)”. “Sociodemographics” include “N underscore H I underscore N H E”, “N E underscore H I underscore N H E”, “N E underscore L I underscore N H E”, and “S E underscore L I underscore H E”. Lower left quadrant: “Dimensions” include “Food Quality and Safety (p)”, “Body, Health and Nutrition (p)”, “Economical (p)”, “Seasonal (p)”, and “Hedonic and Sensory Properties (p)”. “Sociodemographics” include “S E underscore H I underscore H E”, “C W underscore H I underscore H E”, “N E underscore H I underscore H E”, “N underscore H I underscore H E”, “N underscore L I underscore H E”, and “N E underscore L I underscore H E”. Upper right quadrant: “Dimensions” include “Fresh Food (no)”, “Fresh Food (n)”, “Processed Food (n)”, and “Economical (n)”. “Sociodemographics” include “C W underscore L I underscore N H E”, “C W underscore L I underscore H E”, “S underscore L I underscore N H E”, and “S underscore L I underscore H E”. Lower right quadrant: “Dimensions” include “Food Quality and Safety (n)”, “Body, Health and Nutrition (n)”, and “Economical (no)”. “Sociodemographics” include “S E underscore L I underscore N H E”, “S underscore H I underscore H E”, “S E underscore H I underscore N H E”, “S underscore H I underscore N H E”, and “C W underscore H I underscore H E”. Plot B: The title reads “Symmetric Plot (axes F 1 and F 2: 56.16 percent)”. The horizontal axis is labeled “F 1 (32.57 percent)” and ranges from negative 0.4 to 1.4 in increments of 0.2 units. The vertical axis is labeled “F 2 (23.59 percent)” and ranges from negative 0.8 to 0.6 in increments of 0.2 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Processed Food (p)”, “Produce (p)”, and “Produce (no)”. “Sociodemographics” include “L x underscore M underscore N slash H E” and “L x underscore F underscore N slash H E”. Lower left quadrant: “Dimensions” include “Beverage (p)”, “Body, Health and Nutrition (p)”, “Environmental (p)”, and “Economical (no)”. “Sociodemographics” include “L x underscore M underscore H E” and “L x underscore F underscore H E”. Upper right quadrant: “Dimensions” include “Gastronomy (p)”, “Gastronomy (no)”, and “Social (p)”. “Sociodemographics” include “P r t underscore M underscore N slash H E” and “P r t underscore M underscore H E”. Lower right quadrant: “Dimensions” include “Food Quality and Safety (p)”, “Local (p)”, “Economical (p)”, and “Hedonic and Sensory Properties (p)”. “Sociodemographics” include “P r t underscore F underscore H E” and “P r t underscore F underscore N slash H E”.

Projection of dimensions related to “Local food” elicited through the FWA task with: (a) Brazilian and (b) Portuguese urban consumers, alongside sociodemographic characteristics (region of residence, income level (for BR)-, gender (for PT)-, and level of education) in the correspondence analysis space, where: Region of residence = CW – Centre-West; S -South; SE- Southeast; NE – Northeast; N- North; Lx - Lisbon; Prt - Porto; Income Level = HI- High Income; LI – Low Income; Educational level = NHE – No Higher Education; HE - with Higher Education. Gender = F—Female; M—Male; Polarity = n: Negative; no: Neutral; p: Positive

Figure 1
Two symmetric plots show F 1-F 2 relationships between sociodemographics and food-related dimensions.The plots are labeled “A” and “B”, each showing a symmetric correspondence plot with horizontal axis “F 1” and vertical axis “F 2”. A legend in both plots shows two types of scattered points: “Sociodemographics” and “Dimensions”. Plot A: The title reads “Symmetric plot (axes F 1 and F 2: 82.96 percent)”. The horizontal axis is labeled “F 1 (75.54 percent)” and ranges from negative 1 to 1.2 in increments of 0.2 units. The vertical axis is labeled “F 2 (7.42 percent)” and ranges from negative 0.6 to 0.6 in increments of 0.2 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Processed Food (p)”, “Gastronomy (p)”, and “Fresh Food (p)”. “Sociodemographics” include “N underscore H I underscore N H E”, “N E underscore H I underscore N H E”, “N E underscore L I underscore N H E”, and “S E underscore L I underscore H E”. Lower left quadrant: “Dimensions” include “Food Quality and Safety (p)”, “Body, Health and Nutrition (p)”, “Economical (p)”, “Seasonal (p)”, and “Hedonic and Sensory Properties (p)”. “Sociodemographics” include “S E underscore H I underscore H E”, “C W underscore H I underscore H E”, “N E underscore H I underscore H E”, “N underscore H I underscore H E”, “N underscore L I underscore H E”, and “N E underscore L I underscore H E”. Upper right quadrant: “Dimensions” include “Fresh Food (no)”, “Fresh Food (n)”, “Processed Food (n)”, and “Economical (n)”. “Sociodemographics” include “C W underscore L I underscore N H E”, “C W underscore L I underscore H E”, “S underscore L I underscore N H E”, and “S underscore L I underscore H E”. Lower right quadrant: “Dimensions” include “Food Quality and Safety (n)”, “Body, Health and Nutrition (n)”, and “Economical (no)”. “Sociodemographics” include “S E underscore L I underscore N H E”, “S underscore H I underscore H E”, “S E underscore H I underscore N H E”, “S underscore H I underscore N H E”, and “C W underscore H I underscore H E”. Plot B: The title reads “Symmetric Plot (axes F 1 and F 2: 56.16 percent)”. The horizontal axis is labeled “F 1 (32.57 percent)” and ranges from negative 0.4 to 1.4 in increments of 0.2 units. The vertical axis is labeled “F 2 (23.59 percent)” and ranges from negative 0.8 to 0.6 in increments of 0.2 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Processed Food (p)”, “Produce (p)”, and “Produce (no)”. “Sociodemographics” include “L x underscore M underscore N slash H E” and “L x underscore F underscore N slash H E”. Lower left quadrant: “Dimensions” include “Beverage (p)”, “Body, Health and Nutrition (p)”, “Environmental (p)”, and “Economical (no)”. “Sociodemographics” include “L x underscore M underscore H E” and “L x underscore F underscore H E”. Upper right quadrant: “Dimensions” include “Gastronomy (p)”, “Gastronomy (no)”, and “Social (p)”. “Sociodemographics” include “P r t underscore M underscore N slash H E” and “P r t underscore M underscore H E”. Lower right quadrant: “Dimensions” include “Food Quality and Safety (p)”, “Local (p)”, “Economical (p)”, and “Hedonic and Sensory Properties (p)”. “Sociodemographics” include “P r t underscore F underscore H E” and “P r t underscore F underscore N slash H E”.

Projection of dimensions related to “Local food” elicited through the FWA task with: (a) Brazilian and (b) Portuguese urban consumers, alongside sociodemographic characteristics (region of residence, income level (for BR)-, gender (for PT)-, and level of education) in the correspondence analysis space, where: Region of residence = CW – Centre-West; S -South; SE- Southeast; NE – Northeast; N- North; Lx - Lisbon; Prt - Porto; Income Level = HI- High Income; LI – Low Income; Educational level = NHE – No Higher Education; HE - with Higher Education. Gender = F—Female; M—Male; Polarity = n: Negative; no: Neutral; p: Positive

Close modal
Figure 2
Two symmetric correspondence plots show labelled category points positioned across four quadrants along F 1 and F 2.The plots are labeled “A” and “B”, each presenting a symmetric correspondence plot with horizontal axis “F 1” and vertical axis “F 2”. A legend in both plots shows two types of scattered points: “Sociodemographics” and “Dimensions”. Plot A: The title reads “Symmetric Plot (axes F 1 and F 2: 73.57 percent)”. The horizontal axis is labeled “F 1 (64.57 percent)” and ranges from negative 0.8 to 1.2 in increments of 0.2 units. The vertical axis is labeled “F 2 (9,00 percent)” and ranges from negative 0.6 to 0.6 in increments of 0.2 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Hedonic and Sensory Properties (p)”, “Seasonal (n p)”, “Seasonal (p)”, “Economical (p)”, and “Food Quality and Safety (p)”. “Sociodemographics” include “S E underscore H I underscore H E”, “S E underscore L I underscore H E”, “N E underscore H I underscore H E”, “N E underscore L I underscore H E”, “N E underscore L I underscore H E”, and “C W underscore H I underscore H E”. Lower left quadrant: “Dimensions” include “Body, Health and Nutrition (p)”, “Food Quality and Safety (n p)”, “Economical (n p)”, “Produce (p)”, and “Gastronomy (p)”. “Sociodemographics” include “N underscore H I underscore H E”, “N underscore L I underscore N H E”, “N E underscore L I underscore N H E”, “N underscore H I underscore N H E”, and “N E underscore H I underscore N H E”. Upper right quadrant: “Dimensions” include “Seasonal (n)”, “Economical (n)”, “Produce (n)”, and “Body, Health and Nutrition (n)”. “Sociodemographics” include “C W underscore H I underscore N H E”, “S E underscore H I underscore N H E”, “S underscore H I underscore H E”, and “S underscore L I underscore N H E”. Lower right quadrant: “Dimensions” include “Food Quality and Safety (n)”, “Hedonic and Sensory Properties (n)”, “Gastronomy (n)”, and “Produce (n p)”. “Sociodemographics” include “C W underscore L I underscore H E”, “C W underscore L I underscore N H E”, “S underscore H I underscore N H E”, “S underscore L I underscore N H E”, and “S underscore L I underscore H E”. Plot B: The title reads “Symmetric Plot (axes F 1 and F 2: 81.35 percent)”. The horizontal axis is labeled “F 1 (65.74 percent)” and ranges from negative 0.8 to 0.8 in increments of 0.2 units. The vertical axis is labeled “F 2 (15.61 percent)” and ranges from negative 0.5 to 0.5 in increments of 0.1 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Environmental (no)”, “Environmental (p)”, “Seasonal (no)”, and “Produce (no)”. “Sociodemographics” include “L x underscore 50 positive” and “P r t underscore 18 to 29”. Lower left quadrant: “Dimensions” include “Produce (p)”. “Sociodemographics” include “L x underscore 18 to 29” and “L x underscore 30 to 49”. Upper right quadrant: “Dimensions” include “Economical (p)”, “Food Quality and Safety (p)”, “Body, Health and Nutrition (p)”, “Hedonic and Sensory Properties (p)”, and “Seasonal (p)”. “Sociodemographics” include “P r t underscore 50 positive”. Lower right quadrant: “Dimensions” include “Gastronomy (p)”. “Sociodemographics” include “P r t underscore 30 to 49”.

Projection of dimensions related to “seasonal food” elicited through the FWA task with: (a) Brazilian and (b) Portuguese urban consumers, alongside sociodemographic characteristics (region of residence, income level (for BR), and level of education (for BR), age group (for PT)) in the correspondence analysis space, where: Place of residence = CW – Centre-West Region; S -South Region; SE- Southeast Region; NE – Northeast region; N- North Region; Lx - Lisbon metropolitan area; Prt - Porto metropolitan area; Income Level = HI- High Income; LI – Low Income; Educational level = NHE – No Higher Education; HE - with Higher Education; Age group = 18-29 – 18 to 29 years old; 30-49 – 30 to 49 years old; 50+ or more years old; Polarity = n: Negative; no: Neutral; p: Positive

Figure 2
Two symmetric correspondence plots show labelled category points positioned across four quadrants along F 1 and F 2.The plots are labeled “A” and “B”, each presenting a symmetric correspondence plot with horizontal axis “F 1” and vertical axis “F 2”. A legend in both plots shows two types of scattered points: “Sociodemographics” and “Dimensions”. Plot A: The title reads “Symmetric Plot (axes F 1 and F 2: 73.57 percent)”. The horizontal axis is labeled “F 1 (64.57 percent)” and ranges from negative 0.8 to 1.2 in increments of 0.2 units. The vertical axis is labeled “F 2 (9,00 percent)” and ranges from negative 0.6 to 0.6 in increments of 0.2 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Hedonic and Sensory Properties (p)”, “Seasonal (n p)”, “Seasonal (p)”, “Economical (p)”, and “Food Quality and Safety (p)”. “Sociodemographics” include “S E underscore H I underscore H E”, “S E underscore L I underscore H E”, “N E underscore H I underscore H E”, “N E underscore L I underscore H E”, “N E underscore L I underscore H E”, and “C W underscore H I underscore H E”. Lower left quadrant: “Dimensions” include “Body, Health and Nutrition (p)”, “Food Quality and Safety (n p)”, “Economical (n p)”, “Produce (p)”, and “Gastronomy (p)”. “Sociodemographics” include “N underscore H I underscore H E”, “N underscore L I underscore N H E”, “N E underscore L I underscore N H E”, “N underscore H I underscore N H E”, and “N E underscore H I underscore N H E”. Upper right quadrant: “Dimensions” include “Seasonal (n)”, “Economical (n)”, “Produce (n)”, and “Body, Health and Nutrition (n)”. “Sociodemographics” include “C W underscore H I underscore N H E”, “S E underscore H I underscore N H E”, “S underscore H I underscore H E”, and “S underscore L I underscore N H E”. Lower right quadrant: “Dimensions” include “Food Quality and Safety (n)”, “Hedonic and Sensory Properties (n)”, “Gastronomy (n)”, and “Produce (n p)”. “Sociodemographics” include “C W underscore L I underscore H E”, “C W underscore L I underscore N H E”, “S underscore H I underscore N H E”, “S underscore L I underscore N H E”, and “S underscore L I underscore H E”. Plot B: The title reads “Symmetric Plot (axes F 1 and F 2: 81.35 percent)”. The horizontal axis is labeled “F 1 (65.74 percent)” and ranges from negative 0.8 to 0.8 in increments of 0.2 units. The vertical axis is labeled “F 2 (15.61 percent)” and ranges from negative 0.5 to 0.5 in increments of 0.1 units. A vertical line and a horizontal line intersect at the point (0, 0), dividing the plot into four quadrants. Upper left quadrant: “Dimensions” include “Environmental (no)”, “Environmental (p)”, “Seasonal (no)”, and “Produce (no)”. “Sociodemographics” include “L x underscore 50 positive” and “P r t underscore 18 to 29”. Lower left quadrant: “Dimensions” include “Produce (p)”. “Sociodemographics” include “L x underscore 18 to 29” and “L x underscore 30 to 49”. Upper right quadrant: “Dimensions” include “Economical (p)”, “Food Quality and Safety (p)”, “Body, Health and Nutrition (p)”, “Hedonic and Sensory Properties (p)”, and “Seasonal (p)”. “Sociodemographics” include “P r t underscore 50 positive”. Lower right quadrant: “Dimensions” include “Gastronomy (p)”. “Sociodemographics” include “P r t underscore 30 to 49”.

Projection of dimensions related to “seasonal food” elicited through the FWA task with: (a) Brazilian and (b) Portuguese urban consumers, alongside sociodemographic characteristics (region of residence, income level (for BR), and level of education (for BR), age group (for PT)) in the correspondence analysis space, where: Place of residence = CW – Centre-West Region; S -South Region; SE- Southeast Region; NE – Northeast region; N- North Region; Lx - Lisbon metropolitan area; Prt - Porto metropolitan area; Income Level = HI- High Income; LI – Low Income; Educational level = NHE – No Higher Education; HE - with Higher Education; Age group = 18-29 – 18 to 29 years old; 30-49 – 30 to 49 years old; 50+ or more years old; Polarity = n: Negative; no: Neutral; p: Positive

Close modal

Across the four correspondence maps (Figures 1 and 2), the first axis consistently accounted for the largest share of explained variance, ranging from 56% to 76%, depending on the country and stimulus. By contrast, the second axis contributed more modestly, ranging from only 7.42% in the Brazilian local-food map and 9.00% in the Brazilian seasonal-food map, to higher but still secondary values of 15.61% and 23.59% in the Portuguese seasonal- and local-food maps, respectively. These F2 contributions therefore reflect finer-grained contrasts that complement, rather than redefine, the principal differentiation captured along F1.

For local food (Figure 1), the CA revealed clear regional divisions in Brazil. Respondents from the North and Northeast clustered on the left side of the plot, associating local food with positive dimensions such as “Produce”, “Economical”, and “Gastronomy”. In contrast, participants from the South, Southeast, and Centre-West were positioned to the right, linking their responses predominantly to negative associations with “Economical”, “Produce”, and “Food Quality and Safety”. This indicates greater concern regarding affordability, price volatility, and the quality or availability of fresh produce. Exceptions were observed among higher-income and higher-educated participants in the Centre-West and Southeast, who associated local food more positively with “Economical”, “Hedonic and Sensory Properties”, and “Food Quality and Safety”.

In Portugal, differences emerged according to education and metropolitan area. In Lisbon, participants without higher education associated local food with “Processed Food” and “Produce”, emphasising accessibility and practicality. Higher-educated Lisbon residents, however, associated local food with the “Body, Health and Nutrition” and “Environmental” dimensions, indicating a stronger orientation toward health and sustainability. In Porto, female participants emphasised “Hedonic and Sensory Properties”, “Food Quality and Safety”, and “Economical”. This may reflect a greater emphasis on sensory quality and affordability. In this case, the first axis primarily distinguished environmentally framed and health-oriented associations from more utilitarian or economically oriented categories, while the second axis separated hedonic and gastronomy meanings.

For seasonal food (Figure 2), Brazilian respondents also exhibited a regional divide. Participants from the North and Northeast were more likely to associate seasonal food with positive dimensions, whereas those from the South, Southeast, and Centre-West linked it to negative references within the dimensions “Economical”, “Produce”, and “Food Quality and Safety”. These patterns reinforce concerns regarding price, accessibility, and food safety risks in more agriculturally developed regions. In the Brazilian map for seasonal food, the first axis (64.6%) primarily contrasted positive associations—particularly “Produce”, “Quality and Safety”, and “Hedonic and Sensory Properties”—positioned on the right side, with negative “Produce” and “Economical” categories on the left. The second axis (9.0%) differentiated sensory-oriented categories, typically located in the lower quadrants, from seasonal or economically directed associations in the upper quadrants.

The spatial configuration illustrates that higher-educated and higher-income participants from the South and Southeast are situated near positive produce and quality-related dimensions, whereas respondents with lower education or income—especially those from the North and Northeast—appear closer to negative economic and produce categories.

In Portugal, age emerged as the primary differentiator. Younger participants in Lisbon (18–49 years old) associated seasonal food with “Produce”, emphasising the availability of fresh products, whereas older participants (50+ years) were more likely to link it to “Environmental”, indicating greater concern for sustainability. In Porto, younger participants showed more diffuse associations, while older consumers (50+ years) emphasised “Hedonic and Sensory Properties” and “Seasonal”, reflecting the value placed on tradition and sensory enjoyment. In this Portuguese map of seasonal food, the first axis (65.74%) separated environmentally oriented and economically oriented associations with a negative valence on the left, from more favourable sensory, seasonal, and economic categories on the right. The second axis (15.61%) further differentiated gastronomy-related categories, located in the lower-right quadrant, from environmentally framed or produce-related categories, which were positioned in the upper-left quadrant.

Table 4 presents participants' perceptions of the statements regarding concepts associated with local and seasonal produce, measured on a 7-point anchored scale. Scores between 5 and 7 indicate agreement with the statement.

Table 4

Perceptions of local and seasonal food concepts§ across food consumption contexts in Brazil and Portugal

BrazilPortugal
StatementsMean (±SD)
(n = 1,003)
Local food consumptionMean (±SD)
(n = 408)
Local food consumption
Consume regularly local food (n = 778)Do not consume regularly local food (n = 225)p-value#r##Consume regularly local food (n = 236)Do not regularly consume local food (n = 172)p-value#r##
Products acquired directly from the local producer5.8 (±1.56)a,b6.0 (±1.70)a5.1 (±1.69)a,b<0.0010.245.9 (±1.41)a6.1 (±1.26)a5.7 (±1.57)a0.3790.10
Produced in the State/District where you reside5.8 (±1.46)a,b5.9 (±1.62)a5.2 (±1.80)a<0.0010.215.3 (±1.68)b,c5.4 (±1.63)b,c,d5.2 (±1.75)c0.1060.05
Produced in Brazil/Portugal5.8 (±1.76)a5.9 (±1.33)a5.2 (±1.98)a<0.0010.185.4 (±1.83)b,c5.6 (±1.79)a,b5.3 (±1.70)a,b0.3310.08
Products acquired in a local/traditional market5.7 (±1.47)a,b5.9 (±1.45)a5.1 (±1.82)a,b<0.0010.235.6 (±1.49)b5.7 (±1.33)a,b,c5.4 (±1.67)a,b0.7710.06
Produced in your region (e.g. North, Northeast/Lisbon, Algarve)5.7 (±1.59)b5.9 (±165)a4.9 (±1.98)a,b,c<0.0010.225.4 (±1.61)b,c5.5 (±1.53)b,c,d5.3 (±1.88)a,b0.2120.06
Produced within 20 km of the place where they are consumed habitually5.3 (±1.81)c5.5 (±1.73)b4.6 (±1.93)b,c<0.0010.205.2 (±1.73)c,d5.3 (±1.68)c,d5.1 (±1.80)c,d<0.0010.04
Produced within 100 km of the place where they are consumed habitually5.3(±1.68)c5.5 (±1.42)b4.8 (±1.90)a,b,c<0.0010.164.8 (±1.65)e4.8 (±1.69)e4.6 (±1.82)d,e0.192−0.01
Products with protected designation of origin or geographical indication (PDO or PGI)5.0 (±1.78)d5.1 (±1.37)c4.6 (±1.62)c<0.0010.124.9 (±1.72)d,e5.2 (±1.60)d4.9 (±1.60)e0.0460.18
StatementsMean (±SD)
(n = 1,003)
Seasonal food consumptionMean (±SD)
(n = 408
Seasonal food consumption
Consume regularly seasonal food (n = 777)Do not consume regularly seasonal food (n = 226)p-value#r ##Consume regularly seasonal food (n = 310)Do not regularly consume seasonal food (n = 98)p-value#r ##
Food available at specific periods of the year [Seasonal*]5.9 (±1.37)a6.1 (±1.22)a5.3 (±0.1.64)a<0.0010.236.3 (±1.10)a6.4 (±0.96)a5.9 (±0.1.41)a0.0020.15
Food available at specific periods of the year and produced without the use of greenhouses [Produced in season*]5.5 (±1.74)b5.7 (±1.65)b4.7 (±0.1.84)b<0.0010.235.8 (±1.39)b5.9 (±1.33)b5.7 (±0.1.56)a0.3420.05
Local seasonal - Food available at specific periods of the year, produced without the use of greenhouses, and produced near your residence [Local Seasonal*]5.2 (±1.79)c5.5 (±1.71)b4.4 (±0.1.82)c<0.0010.264.9 (±1.78)c5.0 (±1.76)c4.6 (±0.1.83)b0.0510.10

Note(s): § evaluated on Likert scales (1: “totally disagree” and 7: “totally agree”)

# p-value between consumers and non-consumers according to the Mann-Whitney U Test

##r = effect size measure (correlation coefficient) derived from the Mann-Whitney U Test

a, b, c - homogeneous groups within local and seasonal food concepts according to the Friedman´s Test, at a 95% confidence level *Author definitions, which were not presented to participants

In Brazil, the concept of local food was defined by geopolitical markers, such as “Produced in the state of residence” (5.8 ± 1.46), “Produced in Brazil” (5.8 ± 1.76), and “Produced in your region” (5.7 ± 1.59), rather than by absolute distance thresholds, including “within 20 km” (5.3 ± 1.81) or “within 100 km’” (5.3 ± 1.68). Trusted supply chains also scored high ratings, with “Products acquired directly from the local producer” (5.8 ± 1.56) and “Purchases in local markets” (5.7 ± 1.47).

In contrast, definitions based on PDO or PGI were rated lowest. The Mann-Whitney U tests revealed significant differences between regular and non-regular consumers across all items (p < 0.001), with regular consumers expressing stronger agreement with the local food concept. Effect sizes ranged from small to moderate (r = 0.12–0.24), with the most significant values observed for “Products acquired directly from the local producer” (r = 0.24), “Products acquired in local markets” (r = 0.23), and “Produced in the state of residence” (r = 0.21), indicating that these definitions most clearly distinguished regular from non-regular consumers.

In Portugal, producer and market-based definitions were most salient. “Products acquired directly from the local producer” achieved the highest mean (5.9 ± 1.41), followed by “Products obtained from local or traditional markets” (5.6 ± 1.49). Unlike Brazil, geopolitical markers such as “Produced in your region” (5.5 ± 1.53) and “Produced in the country” (5.3 ± 1.70) received comparatively lower recognition, indicating that local food proximity is interpreted through social and commercial ties rather than administrative/geographical boundaries. Even within this framing, products with a PDO or PGI received the second-lowest rating, and “Produced within 100 km” received the lowest rating.

For seasonal food, participants in both Brazil and Portugal strongly associated the concept with temporal availability. In Brazil, “Seasonal” received the highest mean score (5.9 ± 1.37). In Portugal, the same definition obtained an even higher rating (6.3 ± 1.10), confirming its central role in both contexts. The second-highest mean score in both countries referred to “Produced in season” with values of 5.5 ± 1.74 in Brazil and 5.8 ± 1.39 in Portugal. In both countries, the integrated “local seasonal” definition received the lowest mean score among the three options (Brazil: 5.2 ± 1.79; Portugal: 5.0 ± 1.76).

In Brazil, statistically significant differences (p < 0.05) were observed between regular and non-regular consumers across all three concepts of seasonal food, with regular consumers consistently showing stronger agreement. Effect sizes were again small to moderate (r = 0.23–0.26), with the highest value for the integrated “local seasonal” definition (r = 0.26), indicating that this concept yielded the clearest behavioural differentiation.

In Portugal, by contrast, perceptions were generally more homogeneous across consumer groups, except for the “Seasonal” concept, which showed a significant difference (p = 0.002) between regular and non-regular consumers. The corresponding effect size was small (r = 0.15), supporting the relative conceptual alignment of Portuguese consumers across seasonal food purchasing frequencies.

Table S4 (Supplementary Material) reports the different places of purchase for local and seasonal products between regular consumers in Brazil and Portugal, with respondents allowed to indicate more than one location. In Brazil, supermarkets were the most frequently reported for both local (79.2%) and seasonal foods (69.4%). Small grocery stores, municipal markets, fairs, and street vending also played a central role (66.2% for local; 64.4% for seasonal). Direct purchases from producers (28.4% local; 29.9% seasonal) and specialised local product stores (29.0% and 29.0%) were not mentioned as often, while organic baskets and farmers' cooperatives accounted for smaller shares (15–16%). In Portugal, patterns diverged: for local food, small grocery stores, municipal markets, fairs, or street vending were the leading sources (81.4%), followed by supermarkets (67.8%), direct purchases from producers (32.6%), and specialised stores (31.4%). For seasonal food, supermarkets (78.4%) and markets/fairs (79.4%) were equally dominant, with lower shares for producer sales (28.7%) and specialised stores (17.4%).

Across Brazil and Portugal, quality emerged as the most recurring theme in the FWA task, though it was expressed in context-specific ways. In Brazil, “quality” was the most frequently given response for local food across all five regions and for seasonal food in the South, Southeast, and Northeast. In Portugal, positive mentions of various produce, particularly fruits and vegetables, highlighted the association between local and seasonal food and attributes such as freshness, safety, and nutritional value.

These findings align with previous research showing that consumers often prioritise quality when making fresh food choices (Anis et al., 2022; Wu et al., 2021) and tend to perceive local and seasonal products as trustworthy and high-value options (Merlino et al., 2022; Régnier et al., 2022; Autio et al., 2013; Chambers et al., 2007). More broadly, the prominence of quality across both contexts suggests that sensory and safety considerations continue to underpin consumer interpretations of proximity-based foods, supporting theoretical perspectives that conceptualise authenticity and trust as structuring elements of local food meanings (Zocchi et al., 2021; Carfora and Catellani, 2023).

Differences between the two countries reflect broader dietary and cultural patterns. Portugal's Mediterranean tradition—rich in fish, olive oil, and seasonal produce—aligns local and seasonal foods with health, freshness, and authenticity (Barros and Delgado, 2022; Lopes et al., 2017; Bach-Faig et al., 2011). In Brazil, traditional staples such as rice and beans coexist with high meat intake and rising consumption of ultra-processed foods (da Costa Louzada et al., 2018), reflecting ongoing nutrition transition dynamics (Castro et al., 2023; Ronto et al., 2018). These trajectories may explain why Portuguese participants linked local and seasonal food to produce, while Brazilians emphasised quality alongside stronger concerns with price and safety.

In Brazil, participants from the South, Centre-West, and Southeast regions, which are more agriculturally developed (IBGE, 2019, 2025), expressed the most negative associations with local and seasonal food, mainly under the “Economical”, “Produce”, and “Food Quality and Safety” dimensions. Paradoxically, these areas account for most of Brazil's gross domestic product (IBGE, 2024). One explanation for the negative “Economical” associations lies in the proliferation of supermarkets and “atacarejo” outlets, which blend retail and wholesale formats (ABRAS, 2024). Their pricing power and broad sourcing capabilities may reinforce perceptions that local products sold in traditional markets are more expensive or less competitive (Križan et al., 2023; James, 2016). Within this context, Brazil's recurrent inflationary cycles and high food-price volatility further heighten the importance of price considerations in everyday food choices, reinforcing a framing in which local and seasonal foods are evaluated primarily through an economic lens rather than through relational or symbolic attributes (Fernandes et al., 2022; Muñoz-Villamizar et al., 2024; de Oliveira et al., 2025).

Negative associations with the “Food Quality and Safety” and “Produce” dimensions in these Brazilian regions likely stem from apprehensions regarding pesticide use, industrialised production, and limited transparency in farming practices (Simoglou and Roditakis, 2022; Cao et al., 2023). The predominance of large-scale farms—averaging 322 ha in the Centre-West and exceeding the national mean in the South and Southeast (IBGE, 2019, 2025; Parré et al., 2024)—may obscure the distinction between local and industrial agriculture. In the Brazilian context, large-scale and export-oriented agricultural production has been consistently associated with high levels of pesticide use, both in absolute terms and per hectare, reinforcing public concerns regarding food safety and environmental externalities (Bombardi, 2019; Rigotto et al., 2020; da Silva et al., 2023). As a result, even small-scale producers of fruits and vegetables can become associated with negative attributes of industrial agriculture, reinforcing scepticism regarding cost, safety, and environmental impact.

These findings suggest that, although spatial proximity is often associated with higher levels of trust in local food systems (Hasanzade et al., 2022; László et al., 2024), this relationship varies across contexts and market structures. In agro-industrial contexts, this may lead to more ambivalent or negative associations with local food related to price, safety, and quality, underscoring the conditional nature of trust in contemporary food systems (Assis et al., 2023; Wu et al., 2021).

Nevertheless, despite the negative associations with local food observed in southern Brazil, this region reported the highest incidence of direct purchases from local producers (41.2%) among all regions. This apparent contradiction may indicate that negative symbolic or evaluative associations do not necessarily inhibit behavioural engagement. Rather, it highlights the importance of relational proximity, rooted in repeated interactions, familiarity, and trust developed through direct exchange, which can mitigate structural constraints and price sensitivities in shaping everyday food procurement practices.

In Portugal, negative economic associations fell below 5%, while positive views highlighted fair prices, producer support, and local economic benefits. These align with the EU Common Agricultural Policy's goals of fair remuneration, rural development, and shorter supply chains (European Commission, 2020; Matthews, 2018). Portugal's small and fragmented farms—averaging 14.4 ha nationally and under 12 ha in northern regions (INE, 2021a, b)—reinforce trust-based proximity between producers and consumers. This trust is evident in the firm reliance of Portuguese respondents on municipal markets, fairs, and small grocery stores for local and seasonal foods, which reinforces perceptions of authenticity, transparency, and social embeddedness (Joint Research Centre, Institute for Prospective Technological Studies, 2013; Renting et al., 2003). Recent evidence highlights the importance of relational proximity—grounded in social ties, trust, and market interactions—over distance alone, in shaping consumer meanings of “local” (Gugerell et al., 2021; Masson and Bubendorff, 2022; Zhong, 2025).

Sociodemographic effects also showed contrasting patterns. In Brazil, higher education was associated with stronger positive mentions of “quality” and “health”, while lower-educated groups more often connected local and seasonal foods with price and gastronomy, appreciating them for their traditional culinary roles. In Portugal, metropolitan variation was decisive: participants from the metropolitan area of Lisbon, with higher education, associated local food with health and environmental dimensions, whereas participants from the metropolitan area of Porto emphasised sensory and economic attributes. These results align with research showing that education enhances environmental awareness and sustainable dietary choices in European contexts (Saari et al., 2021).

Notably, the FWA task enabled the identification of culturally embedded and less consciously articulated meanings surrounding local and seasonal food. By capturing spontaneous associations, this approach revealed symbolic tensions, such as the coexistence of negative evaluations with continued engagement in local purchasing, that would be less visible through structured attitudinal measures alone, thereby strengthening the interpretative depth of the analysis.

Building on the perceptions identified in the FWA task, it was crucial to explore how consumers in Brazil and Portugal express their attitudes towards local and seasonal food when presented with formal concepts from the literature (Vargas et al., 2021). Moreover, connecting FWA-derived associations with structured conceptual items makes it possible to observe how implicit cultural meanings align with more formal definitions, thereby strengthening the theoretical interpretation of local and seasonal food.

In both countries, there is a strong agreement with local food definitions, emphasising direct relationships with producers and acquisition in traditional markets, confirming that proximity is framed not only geographically but also relationally and commercially. This aligns with wider literature that links local food to trust, embeddedness, and community ties (Feagan, 2007; Autio et al., 2013; László and Wahlen, 2024). This convergence between relational definitions and consumer endorsement highlights that “local” operates not merely as a spatial indicator but as a socially embedded construct grounded in trust-based interactions, consistent with multidimensional frameworks that conceptualise local food through relational, cultural and experiential forms of proximity (Chicoine et al., 2022).

In Brazil, the endorsement of geopolitical definitions, such as food produced within a state, region, or country, coincides with participants' self-reported reliance on supermarkets as the primary source of purchase for local and seasonal products. In this context, “local” is primarily articulated through administrative or territorial markers rather than direct producer–consumer relations. This interpretation is consistent with the FWA results, which revealed limited references to specific producers or relational ties and a greater emphasis on attributes related to quality, price, and food safety.

In Portugal, however, greater weight was given to relational and market-based definitions, while geopolitical markers such as “Produced in Portugal” elicited weaker differentiation between regular and non-regular consumers. This pattern is consistent with the FWA results, which show that associations with local and seasonal food are strongly anchored in fresh produce, traditional markets, and attributes linked to proximity, familiarity, and everyday purchasing practices. Together, these findings reinforce the view that local food is socially constructed, with the meaning of proximity interpreted differently across cultural and market contexts (Fonte, 2008; Hiroki et al., 2016).

The contrast between Brazil and Portugal reveals two distinct conceptual framings of local food: a predominantly geopolitical and administrative understanding in Brazil versus a relationally embedded interpretation in Portugal. This cross-cultural divergence illustrates how country-specific market infrastructures and food provisioning systems condition consumer interpretations of proximity.

Taken together, these findings empirically substantiate the first analytical proposition of this study, demonstrating that “local food” is interpreted by consumers as a culturally mediated construct rather than a purely spatial designation. Across both countries, meanings attributed to local food emerge from trust, familiarity, and market embeddedness, albeit articulated through distinct cultural, economic, and market configurations.

For seasonal food, temporal availability was the dominant reference in local and seasonal consumption in both countries, with “food available at specific periods of the year” achieving the highest ratings. This finding confirms the widespread association of seasonality with freshness, taste, and natural cycles (Vargas et al., 2021; Chambers et al., 2007). However, the strength of this temporal framing also indicates that seasonality is perceived primarily as a naturalised, time-bound characteristic rather than as a relational or provenance-based attribute, in contrast to the multifaceted meanings observed for local food (Chicoine et al., 2022; Vargas et al., 2021). This pattern directly supports the second analytical proposition, indicating that seasonality is cognitively anchored in temporal availability rather than being spontaneously integrated with notions of place, production, or relational proximity.

Notably, the integrative concept of “local seasonal” received the lowest ratings in both countries, despite its relevance for sustainable food consumption. This suggests that, while “local” and “seasonal” are individually culturally meaningful, their combined framing is less embedded in consumer practices and narratives, limiting recognition of their ecological and socio-economic synergies (Régnier et al., 2022; Spence, 2021; Coelho et al., 2018). This conceptual gap challenges normative assumptions in sustainability discourses that treat “local seasonal” as an intuitively coherent category.

Finally, the observed variation in the results of the FWA task by education, income, and region of residence directly supports the third analytical proposition, indicating that perceptions of local and seasonal food are socially differentiated rather than uniformly shared. These meanings are shaped by social position and lived food environments, reinforcing the role of sociodemographic factors in structuring how proximity, quality, and value are interpreted.

This study provides new insights into how urban consumers in Brazil and Portugal conceptualise and engage with local and seasonal foods in the context of sustainable consumption. Across both countries, consumers attributed rich and differentiated meanings to local and seasonal foods, revealing shared patterns alongside context-specific interpretations. Brazilian participants emphasised geopolitical markers and economic considerations, while Portuguese consumers prioritised relational and market-based proximity. In both contexts, the integrated concept of “local seasonal” was weakly endorsed, reflecting limited recognition of its ecological and socio-economic benefits. Trust in producers and traditional markets linked these concepts to culinary heritage rather than territorial distance.

From a policy and practice perspective, the findings suggest that interventions should focus less on increasing sustainability awareness and more on reshaping the contexts in which meanings of local and seasonal food are formed. For consumers, facilitating repeated engagement through stable access to familiar seasonal products and consistent points of purchase may be more effective than information-based campaigns. For retailers, integrating local and seasonal food into routine assortments can help normalise these practices. For public agencies, supporting everyday food environments through regulation and procurement frameworks that prioritise continuity over symbolic labelling may strengthen trust and sustained consumption.

This study presents important limitations that should be acknowledged. Data were collected through online surveys, which may exclude digitally marginalised populations and rely on self-reported practices rather than observed behaviour. The focus on urban consumers limits the generalisability of findings to rural contexts, where proximity and food access may operate differently. Additionally, quota sampling and differences in sample sizes between countries limit the extent of direct comparability across national contexts.

Future research should address these limitations by incorporating mixed-method approaches, including ethnographic observation, longitudinal designs, and experimental studies, to better capture behavioural dynamics over time. Expanding cross-country comparisons to include additional Global South and Southern European contexts, as well as rural–urban contrasts, would further advance the understanding of how cultural food systems, market structures, and socio-economic conditions shape the meanings of local and seasonal food.

The supplementary material for this article can be found online.

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