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Journal of Ethnobiology and Ethnomedicine logoLink to Journal of Ethnobiology and Ethnomedicine
. 2023 Jul 8;19:28. doi: 10.1186/s13002-023-00603-6

Wild food plants of Brazil: a theoretical approach to non-random selection

Lailson César Andrade Gomes 1,✉, Patrícia Muniz de Medeiros 1, Ana Paula do Nascimento Prata 1
PMCID: PMC10329796  PMID: 37422690

Abstract

Ethnobiological investigations have focused on identifying factors that interfere with the criteria adopted for selection of plants, especially medicinal plants, by different populations, confirming the theory that plant selection is not random. However, regarding wild food plants, little effort has been made to confirm the theory in this context, especially in Brazil. Therefore, this systematic review aimed to contribute to the establishment of theoretical bases of the non-random selection of wild food plants by local populations in Brazil. For this, searches were made in 4 databases, namely, Web of Science, Scielo, Scopus and PubMed, using 8 sets of keywords in English and Portuguese in order to identify wild food plants occurring in Brazil. The steps were: application of inclusion and exclusion criteria, screening of articles, selection of studies based on risk of bias, data treatment and, finally, data analysis. Eighty articles met the inclusion criteria of this review. However, 45 of them were considered to present high risk of bias and thus 35 articles were kept for the identification of overused and underused families. The results were inferred through two different approaches (IDM and Bayesian). Annonaceae, Arecaceae, Basellaceae, Cactaceae, Capparaceae, Caryocaraceae, Myrtaceae, Passifloraceae, Rhamnaceae, Rosaceae, Sapotaceae, Talinaceae, and Typhaceae were considered overused. Eriocaulaceae, Orchidaceae, and Poaceae were considered underused. Therefore, considering that some families are more (or less) used than others, we confirm that the wild food plants occurring in Brazil, known and used by different populations, are not chosen at random.

Keywords: Unconventional food plants, Wild edible plants, Theory-based ethnobotany, Plants native to Brazil

Introduction

Ethnobiological investigations around the world have focused on identifying the criteria to select plants, especially those used in medicinal applications, in different populations. Among the different factors that can interfere with plant selection, taxonomic and phylogenetic aspects are addressed in a large number of studies, which are based on the theory of non-random selection, which states that plants can be overused or underused depending on factors that will determine their selection or not. One of the pioneering studies in this regard [1] investigated whether the use of medicinal plants by Native Americans was effective or placebo medicine only. Using a regression analysis, the author came to the conclusion that some taxonomic groups were more used than what was expected if plants were being randomly selected. Years later, seeking to understand the motivations for selectivity, Moerman [2] reported that the presence of biologically active properties as well as factors related to the knowledge about plants acquired over the years and passed from generation to generation contributed to the selection of some plants.

More recently, ethnobiological studies using different approaches and statistical tools have confirmed the theory that plants are not selected at random, but there are rather taxonomic biases that determine why some species are preferred over others [3–8]. There are other approaches using phylogenetic tools which also confirm this theory. These studies consider that closer species share characteristics that justify their use, and for this reason, there are groups that stand out, indicating that species of those groups are selected precisely because they have favorable characteristics, leading to the rejection of the possibility of randomness [9–13].

Some of the plant selection criteria, which can culminate in taxonomic biases, have been found and they are associated with availability, historical and cultural preferences, presence of alkaloids, terpenoids, and biologically active volatile compounds in the case of medicinal plants [6]. However, regarding wild food plants, little effort has been made to test the theory of non-random selection of plants, especially in Brazil, as there are no reports of investigations with this scope.

Among the multiple tools used to test the theory of non-random plant selection, two approaches are frequent in different socio-ecological contexts to demonstrate which taxonomic groups are the most used. The first is the Bayesian model, which assumes uncertainty only on the number of species of the investigated flora, that is, the number of useful plants [14]. The other is the Imprecise Dirichlet Model (IDM), which assumes that both the data on the number of species of the investigated flora and the data of the number of species of the overall flora of the investigated environment are uncertain [15]. The first studies in this sense used residual analysis of simple linear regressions to show overused and underused families [1], but this proposal was questioned due to the statistical inconsistency of the method [16]. Then, a binomial analysis was proposed [16], but it was also objected [14].

In this review, we aim to contribute to the establishment of theoretical bases for the theory of non-random plant selection by local populations, specifically in the context of food plants of the Brazilian flora, using the approaches of IDM and Bayesian model to identify patterns in the knowledge and use of wild food plants in Brazil from the identification of over- and underused families. The following question was the starting point: Are there botanical families over- or underused for food purposes by local populations in Brazil? Our hypothesis is that some botanical families are overused and others underused.

Methodology

Bibliographic search

We searched for scientific documents with an ethnobotanical approach that presented a list of food plants occurring in Brazil with at least one species. To this end, four databases were consulted: Web of Science, Scielo, Scopus and PubMed. Search queries were run using pre-established keywords, namely: (1) "Unconventional Food Plants" AND Brazil; (2) "Wild Food Plants" AND Brazil; (3) "Wild Edible Plants" AND Brazil; (4) “Useful Plants” AND Ethnobotany AND Brazil; (5) "Plantas Comestíveis" AND Brasil; (6) "Plantas Alimentícias Não Convencionais" AND Brasil; (7) "Plantas Alimentícias Silvestres" AND Brasil; (8) “Plantas Úteis” AND Etnobotânica AND Brasil. Search results refer to the knowledge and/or use of food plants. Searches were performed on the title, abstract and keywords of the articles.

Inclusion/exclusion criteria

Only studies published in Portuguese and English were included in the review. Works with more general approaches (useful plants) were selected for later extraction of data regarding food plants. Review articles were excluded, but their references were used for locating further articles with primary data. Studies conducted in the same community or using the same database were excluded and the one that contained more complete and detailed information was included. Also, studies that used systematic instruments for data collection, such as interviews, were included. We excluded studies that did not provide information about the data collection method and also those that did not mention the scientific names of the species.

Screening

Duplicates, that is, articles found more than once in different databases, were excluded; only one document was entered in the database. Subsequently, the abstract of each article was read and those without an ethnobotanical approach and reviews were removed (reviews were used for another purpose as mentioned in the inclusion/exclusion criteria section). Then, a second screening was performed. The articles selected in the first screening were read in full length. Those that did not present a list of species and those that did not identify the species were excluded.

Study selection method based on risk of bias

After application of inclusion/exclusion criteria and screening steps, the articles were classified as presenting low, moderate, and high risk of bias according to criteria for ethnobotanical studies of medicinal plants based on sample quality [17].

Articles presenting moderate and low risk underwent another classification that informed a possible increase in the level of risk based on the following information: complete or incomplete identification of plant material; presentation of a complete or partial list of species; presence of restrictions in the studied habit or taxonomic groups, for example, studies conducted only with herbs or forest species or studies with only one family [18].

Finally, articles classified as presenting moderate and low risk were included in the analysis and the others were removed.

Treatment of data

Data on food species and place where the study was carried out were extracted from each article according to the following information: bibliographic reference, biome, region, state, scientific name, family, popular name, part used, and form of use.

Information on all species occurring in Brazil was further extracted using the flora package in R [19]. The information included: scientific name, family, life form, habitat, type of vegetation, and establishment (origin) according to the listing of Flora do Brasil [20]. The correct spelling and accepted names of the species were checked also using this database. When a species was not mentioned in the listing of Flora do Brasil, the database World Flora Online was consulted [21].

Only the list of accepted native Angiosperm species was extracted from the listings of Flora do Brasil [20] and World Flora Online [21]. Naturalized, exotic, cultivated species, and those without the source information were excluded.

Data analysis

Two distinct approaches were used to identify overused and underused families: the Bayesian model based on Weckerle et al. [14] and the IDM based on Weckerle et al. [15]. While the Bayesian model assumes uncertainty only in the number of native food species, the IDM assumes that data on both the number of native food species and the number of overall native species are uncertain. The Excel Inv.BETA function was used calculate the range of the most probable values of θ (proportion of native food species for the overall flora) and θj (proportion of native food species for family j).

Families which obtained a lower limit of θj greater than the upper limit of θ were considered to be overused. Families which obtained a upper limit of θj lower than the lower limit of θ were considered underused. In cases of overlap between the limits of θj and θ, the family was considered neither over- nor underused.

Results

Eighty articles met the inclusion criteria. However, 45 of them were considered to present a high risk of bias, 17 a moderate risk, and 18 a low risk, according to the categorization of risks of bias in ethnobotanical studies in Brazil [17, 18]. Table 1 lists the 35 articles that composed this review.

Table 1.

Listing and general aspects of studies with an ethnobotanical approach addressing wild food plants carried out in Brazil

References State Region Ecosystem Community type Area
Albuquerque et al. [22] Pernambuco NO CE Rural R
Alves et al. [23] Paraíba NO CA Rural R
Baptista et al. [24] Rio Grande do Sul S AF Artisanal fishermen U
Barreira et al. [25] Minas Gerais SE AF Rural R
Borges and Peixoto [26] Rio de Janeiro SE AF Caiçaras1 R
Bortolotto et al. [27] Mato Grosso do Sul MW PAN Rural R
Brito and Senna-Valle [28] Rio de Janeiro SE AF Caiçaras1 N/i
Campos et al. [29] Ceará NO CA Extractivists R
Chaves et al. [30] Piauí NO CA Rural R
Christo et al. [31] Rio de Janeiro SE AF Rural R
Conde et al. [32] Minas Gerais SE AF Quilombola2 R
Crepaldi and Peixoto [33] Espírito Santo SE AF Quilombola2 R
Florentino et al. [34] Pernambuco NO CA N/i N/i
Fonseca-Kruel and Peixoto [35] Rio de Janeiro SE AF Artisanal fishermen U
Gandolfo and Hanazaki [36] Santa Catarina S AF Native R
Hanazaki et al. [37] São Paulo SE AF Caiçaras1 R
Leal et al. [38] Santa Catarina S AF Rural U
Lobo et al. [39] Pernambuco NO AF Gypsies N/i
Lopes and Lobão [40] Espírito Santo SE AF Artisanal fishermen R
Lucena et al. [41] Paraíba NO CA Rural R
Lucena et al. [42] Paraíba NO CA Rural R
Medeiros et al. [43] Alagoas NO AF Farmers R
Medeiros et al. [44] Bahia NO CA Rural R
Moura et al. [45] Sergipe NO AF Artisanal fishermen R
Nascimento et al. [46] Pernambuco NO CA Rural R
Nascimento et al. [47] Pernambuco NO CA Rural R
Nunes et al. [48] Paraíba NO CA Rural R
Pedrosa et al. [49] Paraíba NO CA Rural R
Ribeiro et al. [50] Paraíba NO CA Rural R
Rodrigues et al. [51] São Paulo SE AF Quilombola2 R
Roque and Loiola [52] Rio Grande do Norte NO CA Rural R
Santos et al. [53] Sergipe NO AF Farmers R
Santos et al. [54] Ceará and Pernambuco NO CA Rural R
Strachulski and Floriani [55] Paraná S AF Rural R
Tuler et al. [56] Minas Gerais SE AF Farmers R
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Region: S South, SE Southeast, MW Midwest, NO Northeast, N North. Ecosystem: AF Atlantic Forest, PAN Pantanal, CA Caatinga. Area: U Urban, R Rural, N/i no information

1Traditional inhabitants of the coast of southeastern Brazil; 2 Descendants of Afro-Brazilian runaway slaves living in hideouts up-country called Quilombos

The overused and underused families are listed in Table 2. The Bayesian approach indicated 14 overused and 3 underused families. The IDM was more conservative, indicating a total of 13 overused families and only 1 underused family.

Table 2.

Overused and underused families of wild food plants from the Brazilian flora

Family (J) nj xj Lower (B) Upper (B) Status (B) Lower (I) Upper (I) Status (I)
Acanthaceae 472 0 0.0000000 0.0077850 ns 0.0000000 0.0183457 ns
Achariaceae 19 0 0.0000000 0.1764669 ns 0.0000000 0.3491221 ns
Achatocarpaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Adoxaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Alismataceae 35 1 0.0007231 0.1491721 ns 0.0006660 0.2480494 ns
Alstroemeriacea 41 0 0.0000000 0.0860438 ns 0.0000000 0.1865620 ns
Amaranthaceae 132 0 0.0000000 0.0275592 ns 0.0000000 0.0635684 ns
Amaryllidacea 131 0 0.0000000 0.0277666 ns 0.0000000 0.0640326 ns
Anacardiaceae 58 5 0.0285860 0.1898260 Overused 0.0271514 0.2421587 Overused
Anisophylleaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Annonaceae 377 9 0.0109729 0.0448327 Overused 0.0108858 0.0545119 Overused
Apiaceae 70 1 0.0003616 0.0770438 ns 0.0003468 0.1343938 ns
Apocynaceae 787 4 0.0013865 0.0129619 ns 0.0013812 0.0181709 ns
Apodanthaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Aptandraceae 10 0 0.0000000 0.3084971 ns 0.0000000 0.5381315 ns
Aquifoliaceae 54 1 0.0004687 0.0989152 ns 0.0004441 0.1700398 ns
Araceae 504 0 0.0000000 0.0072925 ns 0.0000000 0.0171943 ns
Araliaceae 94 0 0.0000000 0.0384834 ns 0.0000000 0.0877318 ns
Arecaceae 300 27 0.0601495 0.1282425 Overused 0.0595455 0.1383209 Overused
Aristolochiacea 84 0 0.0000000 0.0429649 ns 0.0000000 0.0974808 ns
Asparagaceae 14 0 0.0000000 0.2316358 ns 0.0000000 0.4343179 ns
Asphodelaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Asteraceae Bercht 2066 9 0.0019938 0.0082533 ns 0.0019909 0.0101093 ns
Balanophoraceae 15 0 0.0000000 0.2180194 ns 0.0000000 0.4141775 ns
Basellaceae 2 1 0.0125791 0.9874209 Overused 0.0050508 0.9949492 ns
Bataceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Begoniaceae 215 0 0.0000000 0.0170112 ns 0.0000000 0.0396879 ns
Berberidaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Bignoniaceae 411 1 0.0000616 0.0134812 ns 0.0000612 0.0245522 ns
Bixaceae 7 1 0.0036103 0.5787232 ns 0.0025286 0.7376219 ns
Bonnetiaceae 8 0 0.0000000 0.3694166 ns 0.0000000 0.6097426 ns
Boraginaceae 146 3 0.0042577 0.0588739 ns 0.0041716 0.0855848 ns
Brassicaceae 6 0 0.0000000 0.4592581 ns 0.0000000 0.7007049 ns
Bromeliaceae 1356 9 0.0030393 0.0125619 ns 0.0030326 0.0153734 ns
Brunelliaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Burmanniaceae 26 0 0.0000000 0.1322746 ns 0.0000000 0.2735152 ns
Burseraceae 117 2 0.0020769 0.0603860 ns 0.0020248 0.0945588 ns
Cabombaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Cactaceae 276 12 0.0226646 0.0747156 Overused 0.0224188 0.0871251 Overused
Calophyllaceae 94 0 0.0000000 0.0384834 ns 0.0000000 0.0877318 ns
Calyceraceae 6 0 0.0000000 0.4592581 ns 0.0000000 0.7007049 ns
Campanulaceae 57 0 0.0000000 0.0626675 ns 0.0000000 0.1392432 ns
Canellaceae 6 0 0.0000000 0.4592581 ns 0.0000000 0.7007049 ns
Cannabaceae 14 0 0.0000000 0.2316358 ns 0.0000000 0.4343179 ns
Cannaceae 4 0 0.0000000 0.6023646 ns 0.0000000 0.8159484 ns
Capparaceae 29 3 0.0218637 0.2735152 Overused 0.0197672 0.3643923 Overused
Caprifoliaceae 17 0 0.0000000 0.1950643 ns 0.0000000 0.3789268 ns
Cardiopteridaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Caricaceae 8 1 0.0031597 0.5265097 ns 0.0022990 0.6920953 ns
Caryocaraceae 16 2 0.0155136 0.3834762 Overused 0.0130122 0.5120293 Overused
Celastraceae 141 2 0.0017224 0.0502983 ns 0.0016865 0.0791681 ns
Ceratophyllaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Chloranthaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Chrysobalanaceae 280 2 0.0008662 0.0255628 ns 0.0008570 0.0407470 ns
Cistaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Cleomaceae 34 0 0.0000000 0.1028179 ns 0.0000000 0.2190962 ns
Clethraceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Clusiaceae 140 2 0.0017348 0.0506509 ns 0.0016983 0.0797087 ns
Combretaceae 61 1 0.0004150 0.0879881 ns 0.0003955 0.1523635 ns
Commelinaceae 106 1 0.0002388 0.0514431 ns 0.0002322 0.0912983 ns
Connaraceae 71 0 0.0000000 0.0506294 ns 0.0000000 0.1139373 ns
Convolvulaceae 400 2 0.0006061 0.0179441 ns 0.0006016 0.0287148 ns
Costaceae 23 0 0.0000000 0.1481851 ns 0.0000000 0.3015404 ns
Coulaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Crassulaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Cucurbitaceae 146 2 0.0016633 0.0486066 ns 0.0016297 0.0765714 ns
Cunoniaceae 12 0 0.0000000 0.2646485 ns 0.0000000 0.4808911 ns
Cyclanthaceae 36 0 0.0000000 0.0973938 ns 0.0000000 0.2087019 ns
Cymodoceaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Cyperaceae 636 1 0.0000398 0.0087290 ns 0.0000396 0.0159494 ns
Cyrillaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Dichapetalaceae 26 0 0.0000000 0.1322746 ns 0.0000000 0.2735152 ns
Dilleniaceae 78 0 0.0000000 0.0461924 ns 0.0000000 0.1044437 ns
Dioscoreaceae 136 2 0.0017859 0.0521120 ns 0.0017473 0.0819470 ns
Droseraceae 32 0 0.0000000 0.1088812 ns 0.0000000 0.2305750 ns
Ebenaceae 62 2 0.0039308 0.1117191 ns 0.0037483 0.1704563 ns
Elaeocarpaceae 43 0 0.0000000 0.0822111 ns 0.0000000 0.1789644 ns
Elatinaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Ericaceae 106 1 0.0002388 0.0514431 ns 0.0002322 0.0912983 ns
Eriocaulaceae 591 0 0.0000000 0.0062223 Underused 0.0000000 0.0146882 ns
Erythropalaceae 22 0 0.0000000 0.1543725 ns 0.0000000 0.3121903 ns
Erythroxylaceae 133 0 0.0000000 0.0273548 ns 0.0000000 0.0631109 ns
Escalloniaceae 9 0 0.0000000 0.3362671 ns 0.0000000 0.5718585 ns
Euphorbiaceae 946 7 0.0029800 0.0151862 ns 0.0029706 0.0192930 ns
Euphroniaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Fabaceae 2857 21 0.0045556 0.0112140 ns 0.0045508 0.0124605 ns
Gelsemiaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Gentianaceae 124 0 0.0000000 0.0293109 ns 0.0000000 0.0674816 ns
Geraniaceae 7 0 0.0000000 0.4096164 ns 0.0000000 0.6524529 ns
Gesneriaceae 226 0 0.0000000 0.0161900 ns 0.0000000 0.0378056 ns
Goodeniaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Goupiaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Griseliniaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Gunneraceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Haemodoraceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Haloragaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Heliconiaceae 25 0 0.0000000 0.1371852 ns 0.0000000 0.2822644 ns
Hernandiaceae 11 0 0.0000000 0.2849142 ns 0.0000000 0.5079757 ns
Humiriaceae 37 1 0.0006840 0.1416031 ns 0.0006327 0.2366374 ns
Hydnoraceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Hydrocharitaceae 13 0 0.0000000 0.2470526 ns 0.0000000 0.4564565 ns
Hydroleaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Hypericaceae 54 0 0.0000000 0.0660315 ns 0.0000000 0.1461991 ns
Hypoxidaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Icacinaceae 11 0 0.0000000 0.2849142 ns 0.0000000 0.5079757 ns
Iridaceae 198 0 0.0000000 0.0184582 ns 0.0000000 0.0429964 ns
Ixonanthaceae 4 0 0.0000000 0.6023646 ns 0.0000000 0.8159484 ns
Juncaceae 23 0 0.0000000 0.1481851 ns 0.0000000 0.3015404 ns
Juncaginaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Krameriaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Lacistemataceae 11 0 0.0000000 0.2849142 ns 0.0000000 0.5079757 ns
Lamiaceae 515 4 0.0021202 0.0197663 ns 0.0021079 0.0276439 ns
Lauraceae 461 0 0.0000000 0.0079700 ns 0.0000000 0.0187779 ns
Lecythidaceae 121 1 0.0002092 0.0451861 ns 0.0002042 0.0805345 ns
Lentibulariaceae 90 0 0.0000000 0.0401589 ns 0.0000000 0.0913878 ns
Lepidobotryaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Linaceae 15 0 0.0000000 0.2180194 ns 0.0000000 0.4141775 ns
Linderniaceae 12 0 0.0000000 0.2646485 ns 0.0000000 0.4808911 ns
Loasaceae 17 0 0.0000000 0.1950643 ns 0.0000000 0.3789268 ns
Loganiaceae 121 0 0.0000000 0.0300266 ns 0.0000000 0.0690761 ns
Loranthaceae 86 0 0.0000000 0.0419870 ns 0.0000000 0.0953616 ns
Lythraceae 222 0 0.0000000 0.0164793 ns 0.0000000 0.0384690 ns
Magnoliaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Malpighiaceae 581 3 0.0010661 0.0150152 ns 0.0010606 0.0222272 ns
Malvaceae 836 3 0.0007407 0.0104510 ns 0.0007380 0.0155001 ns
Marantaceae 220 1 0.0001151 0.0250641 ns 0.0001135 0.0452871 ns
Marcgraviaceae 34 0 0.0000000 0.1028179 ns 0.0000000 0.2190962 ns
Martyniaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Mayacaceae 4 0 0.0000000 0.6023646 ns 0.0000000 0.8159484 ns
Melastomataceae 1439 4 0.0007579 0.0071017 ns 0.0007563 0.0099761 ns
Meliaceae 92 1 0.0002752 0.0590779 ns 0.0002665 0.1043084 ns
Menispermaceae 108 1 0.0002344 0.0505105 ns 0.0002281 0.0896999 ns
Menyanthaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Metteniusaceae 16 0 0.0000000 0.2059072 ns 0.0000000 0.3957846 ns
Microteaceae 9 0 0.0000000 0.3362671 ns 0.0000000 0.5718585 ns
Molluginaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Monimiaceae 46 0 0.0000000 0.0770618 ns 0.0000000 0.1686589 ns
Moraceae 205 3 0.0030281 0.0421693 ns 0.0029843 0.0617255 ns
Muntingiaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Myristicaceae 64 1 0.0003955 0.0840103 ns 0.0003778 0.1458632 ns
Myrtaceae 1054 31 0.0200695 0.0414894 Overused 0.0200123 0.0446612 Overused
Nartheciaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Nyctaginaceae 61 0 0.0000000 0.0586812 ns 0.0000000 0.1309357 ns
Nymphaeaceae 23 1 0.0011002 0.2194866 ns 0.0009733 0.3486788 ns
Ochnaceae 207 0 0.0000000 0.0176628 ns 0.0000000 0.0411791 ns
Olacaceae 13 1 0.0019456 0.3602974 ns 0.0015811 0.5237708 ns
Oleaceae 14 0 0.0000000 0.2316358 ns 0.0000000 0.4343179 ns
Onagraceae 62 0 0.0000000 0.0577626 ns 0.0000000 0.1290113 ns
Opiliaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Orchidaceae 2340 0 0.0000000 0.0015752 Underused 0.0000000 0.0037373 Underused
Orobanchaceae 41 0 0.0000000 0.0860438 ns 0.0000000 0.1865620 ns
Oxalidaceae 108 0 0.0000000 0.0335796 ns 0.0000000 0.0769556 ns
Passifloraceae 164 10 0.0296245 0.1092759 Overused 0.0290853 0.1294375 Overused
Pentaphylacaceae 19 0 0.0000000 0.1764669 ns 0.0000000 0.3491221 ns
Peraceae 18 0 0.0000000 0.1853020 ns 0.0000000 0.3634240 ns
Peridiscaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Phyllanthaceae 133 0 0.0000000 0.0273548 ns 0.0000000 0.0631109 ns
Phytolaccaceae 11 0 0.0000000 0.2849142 ns 0.0000000 0.5079757 ns
Picramniaceae 22 0 0.0000000 0.1543725 ns 0.0000000 0.3121903 ns
Picrodendraceae 4 0 0.0000000 0.6023646 ns 0.0000000 0.8159484 ns
Piperaceae 462 2 0.0005247 0.0155497 ns 0.0005213 0.0249137 ns
Plantaginaceae 126 2 0.0019281 0.0561622 ns 0.0018831 0.0881340 ns
Plumbaginaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Poaceae 1297 2 0.0001868 0.0055591 Underused 0.0001864 0.0089526 ns
Polygalaceae 213 1 0.0001189 0.0258790 ns 0.0001172 0.0467335 ns
Polygonaceae 84 1 0.0003014 0.0645520 ns 0.0002910 0.1135534 ns
Pontederiaceae 26 0 0.0000000 0.1322746 ns 0.0000000 0.2735152 ns
Portulacaceae 20 1 0.0012651 0.2487328 ns 0.0011002 0.3878119 ns
Potamogetonaceae 13 0 0.0000000 0.2470526 ns 0.0000000 0.4564565 ns
Primulaceae 141 1 0.0001795 0.0388805 ns 0.0001758 0.0695934 ns
Proteaceae 37 0 0.0000000 0.0948906 ns 0.0000000 0.2038647 ns
Putranjivaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Quiinaceae 35 0 0.0000000 0.1000324 ns 0.0000000 0.2137733 ns
Quillajaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Ranunculaceae 15 0 0.0000000 0.2180194 ns 0.0000000 0.4141775 ns
Rapateaceae 41 0 0.0000000 0.0860438 ns 0.0000000 0.1865620 ns
Rhabdodendraceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Rhamnaceae 44 5 0.0379437 0.2455768 Overused 0.0354563 0.3080913 Overused
Rhizophoraceae 10 0 0.0000000 0.3084971 ns 0.0000000 0.5381315 ns
Rosaceae 29 3 0.0218637 0.2735152 Overused 0.0197672 0.3643923 Overused
Rubiaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Ruppiaceae 194 3 0.0032005 0.0445247 ns 0.0031515 0.0651099 ns
Rutaceae 1388 4 0.0007857 0.0073621 ns 0.0007841 0.0103409 ns
Sabiaceae 9 0 0.0000000 0.3362671 ns 0.0000000 0.5718585 ns
Salicaceae 99 0 0.0000000 0.0365757 ns 0.0000000 0.0835533 ns
Samydaceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Santalaceae 54 0 0.0000000 0.0660315 ns 0.0000000 0.1461991 ns
Sapindaceae 418 3 0.0014825 0.0208301 ns 0.0014719 0.0307607 ns
Sapotaceae 237 6 0.0093461 0.0542860 Overused 0.0092286 0.0699907 Overused
Sarraceniaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Schlegeliaceae 7 0 0.0000000 0.4096164 ns 0.0000000 0.6524529 ns
Schoepfiaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Scrophulariaceae 17 0 0.0000000 0.1950643 ns 0.0000000 0.3789268 ns
Simaroubaceae 37 0 0.0000000 0.0948906 ns 0.0000000 0.2038647 ns
Siparunaceae 20 0 0.0000000 0.1684335 ns 0.0000000 0.3358891 ns
Smilacaceae 32 0 0.0000000 0.1088812 ns 0.0000000 0.2305750 ns
Solanaceae 468 9 0.0088303 0.0361911 ns 0.0087738 0.0440812 ns
Staphyleaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Stemonuraceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Strelitziaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Strombosiaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Styracaceae 25 0 0.0000000 0.1371852 ns 0.0000000 0.2822644 ns
Surianaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Symplocaceae 45 0 0.0000000 0.0787051 ns 0.0000000 0.1719599 ns
Taccaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Talinaceae 2 2 0.1581139 1.0000000 Overused 0.0527450 1.0000000 Overused
Tetrameristaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Theaceae 1 0 0.0000000 0.9750000 ns 0.0000000 0.9936905 ns
Thismiaceae 16 0 0.0000000 0.2059072 ns 0.0000000 0.3957846 ns
Thurniaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Thymelaeaceae 25 0 0.0000000 0.1371852 ns 0.0000000 0.2822644 ns
Tofieldiaceae 4 0 0.0000000 0.6023646 ns 0.0000000 0.8159484 ns
Trigoniaceae 26 0 0.0000000 0.1322746 ns 0.0000000 0.2735152 ns
Triuridaceae 13 0 0.0000000 0.2470526 ns 0.0000000 0.4564565 ns
Tropaeolaceae 4 0 0.0000000 0.6023646 ns 0.0000000 0.8159484 ns
Turneraceae 163 0 0.0000000 0.0223770 ns 0.0000000 0.0519043 ns
Typhaceae 3 2 0.0942993 0.9915962 Overused 0.0432719 0.9957893 Overused
Ulmaceae 6 0 0.0000000 0.4592581 ns 0.0000000 0.7007049 ns
Urticaceae 108 2 0.0022506 0.0652965 ns 0.0021896 0.1019933 ns
Velloziaceae 225 0 0.0000000 0.0162614 ns 0.0000000 0.0379693 ns
Verbenaceae 284 0 0.0000000 0.0129050 ns 0.0000000 0.0302424 ns
Violaceae 78 0 0.0000000 0.0461924 ns 0.0000000 0.1044437 ns
Vitaceae 50 1 0.0005062 0.1064695 ns 0.0004776 0.1821078 ns
Vivianiaceae 2 0 0.0000000 0.8418861 ns 0.0000000 0.9472550 ns
Vochysiaceae 166 0 0.0000000 0.0219771 ns 0.0000000 0.0509987 ns
Winteraceae 3 0 0.0000000 0.7075982 ns 0.0000000 0.8818828 ns
Ximeniaceae 5 0 0.0000000 0.5218238 ns 0.0000000 0.7551368 ns
Xyridaceae 198 0 0.0000000 0.0184582 ns 0.0000000 0.0429964 ns
Zingiberaceae 20 0 0.0000000 0.1684335 ns 0.0000000 0.3358891 ns
Zygophyllaceae 4 0 0.0000000 0.6023646 ns 0.0000000 0.8159484 ns
Total geral 32,740 254 0.0068357 0.0088651 0.0068357 0.0088651
Open in a new tab

nj, number of species for group J; xj, number of food species of group J; lower (B), lower limit for the Bayesian model; upper (B), upper limit for the Bayesian model; status (B), status according to the Bayesian model; lower (I), lower limit for the IDM; upper (I), upper limit for the IDM; status (I), status according to the IDM

All overused and underused families found with the IDM approach were the same as those found with the Bayesian approach (Anacardiaceae, Annonaceae, Arecaceae, Cactaceae, Capparaceae, Caryocaraceae, Myrtaceae, Passifloraceae, Rhamnaceae, Rosaceae, Sapotaceae, Talinaceae, and Typhaceae were overused, and Orchidaceae was underused), since the latter was less conservative in relation to the IDM approach. Thus, in the Bayesian model, in addition to the families found with the IDM approach, there was one more family considered overused (Basellaceae) and two additional families considered underused (Eriocaulaceae and Poaceae).

Discussion

The results found in this review provide further evidence supporting the theory of non-random selection of plants, in this case, of wild food plants in Brazil. Similar findings have been reported in different socioecological contexts for medicinal plants such as in Brazil [57], India [4], Papua New Guinea [3], Italy [58], Ecuador [59], Africa [6], Europe [60], Nepal [7], and South Africa [8].

The results of this study were consistent with those observed in the literature for medicinal plants. For example, in a study conducted in Brazil regarding medicinal plants, with a similar methodology to the one employed here (using Bayesian and IDM approaches), the families Anacardiaceae, Capparaceae, Caryocaraceae, Rhamnaceae, and Rosaceae were identified as overused, while Eriocaulaceae, Orchidaceae, and Poaceae were considered underused [57]. In Italy, a study using linear regression, the binomial method, and the Bayesian approach showed that Rosaceae was overused while Poaceae and Orchidaceae were underused [58], similar to the findings in our study. In Papua New Guinea, using the Bayesian approach, Anacardiaceae and Arecaceae were considered overused, and Poaceae and Orchidaceae underused [3]. In India, also with the Bayesian approach, Anacardiaceae and Cactaceae were found to be overused and with a binomial analysis, Poaceae showed to be underused [4]. Finally, in a review with useful plants from Chile, specifically those of the edible category, the families Myrtaceae, Cactaceae and Anacardiaceae were considered overused through the IDM and Bayesian approaches [5], similar to the results found in the present review.

It is worth noting that attractive factors differ between food and medicinal plants, especially from a physicochemical point of view. When similar results are found in the two categories, this does not necessarily mean that the same selection criteria apply for both. The fact that some families are concomitantly overused or underused in both categories may indicate that physicochemical properties are not the only aspect that leads a taxonomic group to be chosen or not. For example, Orchidaceae usually occurs at a low frequency in the environment and most of its plants grow as epiphytes; these characteristics could hinder experimentation in this group of plants and their consequent incorporation into medicinal and food systems.

Since the physicochemical requirements for the selection of medicinal and food plants differ, other shared factors are likely responsible for several families being overused for both purposes. The fact that some families are concomitantly under- or overexplored for food and medicinal purposes, as found in this review and in other phytosociological studies carried out in Brazil, may be related to the ease of access, because many species are widely dominant in Brazilian ecosystems. For example, Anacardiaceae was among the richest families in studies carried out in the Atlantic Forest with native species [61] and also in Caatinga, in an anthropized area [62]. Arecaceae was one of the species with the highest number of species in a study conducted in the Amazon [63]. Myrtaceae and Anacardiaceae were very well represented in terms of number of species in Cerrado [64]. The good representativity of species of these families in the environment is likely a contributing factor for people to find them easily, leading to more contact and greater chances of identifying their uses, ultimately causing these families to stand out as families of both medicinal and food plants.

Besides the ease of access, it is possible that these plants have other attractive characteristics. For example, various studies carried out in Brazil have identified the fruit of food species as the most used plant organ [27, 43, 44, 65]. The absence of such attractive characteristics may explain why some underutilized families have few or none species mentioned as food plant in the wild group, such as Orchidaceae, Eriocaulaceae, and Poaceae in this review. In the case of the latter, despite the family has representatives of great economic importance worldwide and this could theoretically encourage the use of other species of the family, this did not happen in the present review. Only two out of a total of 1297 species of Poaceae from the native flora of Brazil were mentioned as wild food plants.

The results found in the literature indicate that families that have fleshy fruits, such as Arecaceae, Myrtaceae, and Passifloraceae, tend to be better known and used. Fruits of Myrtaceae are known to have a large number and concentration of phenolic compounds with important antioxidant properties, which are beneficial to human health [66]. Some fruits of the family Arecaceae have high nutritional value and are rich in bioactive compounds [67]. Passifloraceae fruits are rich in magnesium and zinc, in addition to containing phenolic compounds, triterpenes, steroids, and flavonoids [68]. These characteristics are key for the determination of their uses, because their presence can contribute to people selecting the plants for consumption.

Conclusions

The selection of wild food plants occurring in Brazil, known and used by different populations, presents a marked taxonomic bias. The identification of overused and underused families contributes to the discovery of families with potential for popularization. In addition, this work is important from the point of view of conservation of wild plants and for the promotion of food and nutritional security. Therefore, efforts are needed to identify the species that could be incorporated into the diet of populations in view of characteristics that make plants more used in relation to others. Furthermore, investigating which parts are most used, their nutritional value, which are the forms of consumption, which are the promising species in the group of wild food species in Brazil, and defining strategies for the management of use are also fields yet to be explored.

In view of their wide geographical distribution, families such as Anacardiaceae Myrtaceae, Arecaceae, and Passifloraceae can be strategic for food prospecting aimed at popularization.

Acknowledgements

Not applicable.

Author contributions

Conception and design: LCAG, PMM and APNP. Analysis and Interpretation: LCAG and PMM; Writing of the manuscript: LCAG, PMM and APNP. All authors read and approved the final manuscript.

Funding

This work was funded by the Coordination for the Improvement of Higher Education Personnel (CAPES) through the Graduate Program in Agronomy of the Federal University of Alagoas, in Rio Largo, Alagoas, Brazil.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the repository [Google Drive] [https://docs.google.com/spreadsheets/d/1hLIJT54-r0-06Obg-RGCIN7yS4uOf4i9/edit#gid=1936773480]. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethical approval and consent to participate

Not applicable.

Consent for publication

All authors consent to publication.

Competing interests

The authors declare that they have no conflicts of interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Lailson César Andrade Gomes, Email: lailson.gomes@ceca.ufal.br.

Patrícia Muniz de Medeiros, Email: patricia.medeiros@ceca.ufal.br.

Ana Paula do Nascimento Prata, Email: ana.prata@ceca.ufal.br.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available in the repository [Google Drive] [https://docs.google.com/spreadsheets/d/1hLIJT54-r0-06Obg-RGCIN7yS4uOf4i9/edit#gid=1936773480]. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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