Explorando tendências e perspectivas futuras na investigação do terroir do café
DOI:
https://doi.org/10.26848/rbgf.v19.02.p7013-731Palavras-chave:
Análise bibliométrica, Indicação geográfica, Origem do café, PerspectivasResumo
O café é uma das bebidas mais consumidas, e seu sabor pode ser influenciado por diversos fatores, desde o cultivo até o preparo. Estudos realizados nos últimos anos intensificaram a busca pela compreensão de como as características edafoclimáticas (clima, relevo, temperatura e tipo de solo) podem influenciar o produto final. Portanto, este estudo teve como objetivo fornecer uma visão geral das tendências de pesquisa sobre o terroir do café, avaliando as palavras-chave, os autores, os países e as instituições mais importantes, e apresentar os temas básicos, de nicho, motores e em declínio do terroir do café. As principais tendências relacionadas ao terroir do café evoluíram significativamente ao longo dos anos, com a realização de estudos sobre a determinação da origem geográfica do café por meio de modelos estatísticos associados a características químicas, bem como uma avaliação mais específica das particularidades de uma microrregião produtora de café, associando práticas agrícolas, microrganismos e compostos químicos presentes no solo e nos frutos às características finais das bebidas.
Downloads
Referências
Agnoletti, B. Z., Pereira, L. L., Alves, E. A., Rocha, R. B., Debona, D. G., Lyrio, M. V. V., Moreira, T. R., Castro, E. V. R., Oliveira, E. C. S, & Filgueiras, P. R. (2024). The terroir of Brazilian Coffea canephora: Characterization of the chemical composition. Food Research International, 176, 113814. https://doi.org/10.1016/j.foodres.2023.113814
Alonso-Salces, R. M., Serra, F., Reniero, F., & Héberger, K. (2009). Botanical and Geographical Characterization of Green Coffee (Coffea arabica and Coffea canephora): Chemometric Evaluation of Phenolic and Methylxanthine Contents. Journal of Agricultural and Food Chemistry, 57(10), 4224-4235. https://doi.org/10.1021/jf8037117
Ampese, L. C., Buller, L. S., Monroy, Y. M., Garcia, M. P., Ramos-Rodriguez, A. R., & Forster-Carneiro, T. (2021). Macaúba’s world scenario: a bibliometric analysis. Biomass Conversion and Biorefinery, 13, 3329–334. https://doi.org/10.1007/s13399-021-01376-2
Anderson, L. C., & Smith, B. W. (2002). Chemical Profiling To Differentiate Geographic Growing Origins of Coffee. Journal of Agricultural and Food Chemistry, 50(7), 2068-2075. https://doi.org/10.1021/jf011056v
Aria, M., & Cuccuullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
Argumedo-García, M., Salas-Navarro, K., Acevedo-Chedid, J., & Ospina-Mateus, H. (2021). Bibliometric Analysis of the Potential of Technologies in the Humanitarian Supply Chain. Journal of Open Innovation: Technology, Market, and Complexity, 7, 232. https://doi.org/10.3390/joitmc7040232
Artêncio, M. M., Giraldi, J. de M. E., Oliveira, J. H. C. de. (2022). A cup of black coffee with GI, please! Evidence of geographical indication influence on a coffee tasting experiment. Physiology & Behavior, 245, 113671. https://doi.org/10.1016/j.physbeh.2021.113671
Ashardiono, F., & Trihartono, A. (2024). Optimizing the potential of Indonesian coffee: a dual market approach. Cogent Social Sciences, 10(1). https://doi.org/10.1080/23311886.2024.2340206
Atlanachew, M., Abebe, A., Wubieneh, T.A., & Hebtemariam, Y. (2021). Rapid and simultaneous determination of trigonelline, caffeine, and chlorogenic acid in green coffee bean extract. Food Science Nutrition, 9(9), 5028-5035. https://doi.org/10.1002/fsn3.2456
Aydın, A., & Temizkan, S. P. (2024). Factors influencing third wave coffee customers' satisfaction and revisit intentions. International Journal of Gastronomy and Food Science, 38, 101048. https://doi.org/10.1016/j.ijgfs.2024.101048
Bamel, U. K., Pandey, R., & Gupta, A. (2020). Safety climate: Systematic literature network analysis of 38 years (1980-2018) of research. Accident Analysis & Prevention, 135, 105387. https://doi.org/10.1016/j.aap.2019.105387
Baqueta, M. R., Costa-Santos, A. C., Rebellato, A. P., Luz, G. M., Azevedo, J., Marini, F., Teixeira, A. L., Rutledge, D. N., & Valderrama, P. (2024). Independent components–discriminant analysis for discrimination of Brazilian Canephora coffees based on their inorganic fraction: A preliminary chemometric study. Microchemical Journal, 196, 109603–109603. https://doi.org/10.1016/j.microc.2023.109603
Baqueta, M. R., Marini, F., Rocha, R. B., Valderrama, P., & Pallone, J. A. L. (2023). Authentication and discrimination of new Brazilian Canephora coffees with geographical indication using a miniaturized near-infrared spectrometer. Food Research International, 172, 113216–113216. https://doi.org/10.1016/j.foodres.2023.113216
Belej, L., Demianová, A., Danchenko, M., Mishra, S., Baráth, P., Jurčaga, L., Lidiková, J., Bobko, M., Poláková, K., Švecová, T., & Bobková, A. (2025). Proteomics coupled machine learning—innovative approach in geographical origin authentication of green Coffea arabica. Food Chemistry, 493, 145784. https://doi.org/10.1016/j.foodchem.2025.145784
Belletti, G., Marescotti, A., & Touzard, J.-M. (2017). Geographical Indications, Public Goods, and Sustainable Development: The Roles of Actors’ Strategies and Public Policies. World Development, 98, 45-57. https://doi.org/10.1016/j.worlddev.2015.05.004
Bordiga, M., Disca, V., Manfredi, M., Barberis, E., Carrà, F., Navarini, L., Lonzarich, V., & Arlorio, M. (2025). Fingerprinting of Green Arabica Coffee Volatile Organic Compounds (VOCs): HS-GC-IMS Versus GC × GC-MS. International Journal of Food Science, 2025, 1302823. https://doi.org/10.1155/ijfo/1302823
Candeias, D. N. C., Silva, K. M., Pereira, H. S., Bezerra, L. P., Silva J. D. S. da, Fernandes, D. D. S., & Diniz, P. H. G. D. (2025). Geographical origin authentication of instant coffee from southern Bahia using MIR and NIR spectroscopy coupled with DD-SIMCA. Food Chemistry, 479, 143698. https://doi.org/10.1016/j.foodchem.2025.143698
Caporaso, N., Whitworth, M. B., Cui, C., & Fisk, I. D. (2018). Variability of single bean coffee volatile compounds of Arabica and robusta roasted coffees analyzed by SPME-GC-MS. Food Research International, 108, 628-640. https://doi.org/10.1016/j.foodres.2018.03.077
Casal, S., Oliveira, M. B., Alves, M. R., & Ferreira, M.A. (2000). Discriminate analysis of roasted coffee varieties for trigonelline, nicotinic acid, and caffeine content. Journal of Agricultural and Food Chemistry, 48, 3420–3424. https://doi.org/10.1021/jf990702b
Cruz-O’Byrne, R., Piraneque-Gambasica, N., Aguirre-Forero, S., & Ramirez-Vergara, J. (2020). Microorganisms in coffee fermentation: A bibliometric and systematic literature network analysis related to agriculture and beverage quality (1965-2019). Coffee Science, 15, 1–14. https://doi.org/10.25186/.v15i.1773
Demianová, A., Bobková, A., Jurčaga, L., Bobko, M., Belej, Ľ., & Árvay, J. (2021). DETERMINATION OF GEOGRAPHICAL ORIGIN OF GREEN AND ROASTED COFFEE BASED ON SELECTED CHEMICAL PARAMETERS. Journal of Microbiology, Biotechnology and Food Sciences, 10(4), 706–710. https://doi.org/10.15414/jmbfs.2021.10.4.706-710
Dharmawan, A., Masithoh, R. E., & Amanah, H. Z. (2023). Development of PCA-MLP Model Based on Visible and Shortwave Near Infrared Spectroscopy for Authenticating Arabica Coffee Origins. Foods, 12(11), 2112. https://doi.org/10.3390/foods12112112
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W.M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
Filete, C. A., Moreira, T. R., Santos, A. R., Gomes, W. S., Guarçoni, R. C., Moreli, A. P., Augusto, M. I., de Oliveira Abreu, R., Simmer, M. M. B., Caliman, A. D. C., Guimarães, C. V., Berilli, S. S., Ferrão, M. A. G., Fonseca, A. F. A., Partelli, F. L., Berilli, A. P. C., Oliveira, E. C. S., & Pereira, L. L. (2022). The New Standpoints for the Terroir of Coffea canephora from Southwestern Brazil: Edaphic and Sensorial Perspective. Agronomy, 12(8), 1931. https://doi.org/10.3390/agronomy12081931
Gines, K. R. S., Garcia, E. V., Sagum, R. S., & Bautista VII, A. T. (2025). Geographical origin differentiation of Philippine Robusta coffee (C. canephora) using X-ray fluorescence-based elemental profiling with chemometrics and machine learning. Food Chemistry, 478, 143676. https://doi.org/10.1016/j.foodchem.2025.143676
Giraudo, A., Grassi, S., Savorani, F., Gavoci, G., Casiraghi, E., & Geobaldo, F. (2019). Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis. Food Control, 99, 137-145. https://doi.org/10.1016/j.foodcont.2018.12.03
Gomes, W. S., Pereira, L. L., Luz, J. M. R., Silva, M. C. S, Veloso, T. G. R., & Partelli, F. L. (2024). Exploring the microbiome of coffee plants: Implications for coffee quality and production. Food Research International, 179, 113972. https://doi.org/10.1016/j.foodres.2024.113972
Gonçalves, M. C. P., Kieckbush, T. G., Perna, R. F., Fujimoto, J. T., Morales, S. A. V., Romanelli, J. P. (2019). Trends on enzyme immobilization researches based on bibliometric analysis. Process Biochemistry, 76, 96-110. https://doi.org/10.1016/j.procbio.2018.09.01
Górnaś, P., Dwiecki, K., Siger, A. Tomaszewska-Gras, J., Michalak, M., & Polewski, K. (2016). Contribution of phenolic acids isolated from green and roasted boiled-type coffee brews to total coffee antioxidant capacity. European Food Research and Technology, 242, 641–653. https://doi.org/10.1007/s00217-015-2572-1
Jeszka-Skowron, M., Sentkowska, A., Pyrzyńska, K., & Peña, Maria Paz de. (2016). Chlorogenic acids, caffeine content and antioxidant properties of green coffee extracts: influence of green coffee bean preparation. European Food Research and Technology, 242, 1403–1409. https://doi.org/10.1007/s00217-016-2643-y
Kim, J.-S., Pak, J., Choi, J., Park, S.-E. Bae, S., Cho, H., Kwak, S., Son, H.-S. (2025). Factors influencing metabolite profiles in global Arabica green coffee beans: Impact of continent, altitude, post-harvest processing, and variety. Food Research International, 208, 116187. https://doi.org/10.1016/j.foodres.2025.116187
Ledezma, D. B., Sartori, C., & Tomasino, E. (2025). Sensory Perception and Physicochemical Characteristics of Geisha Coffee From Different Production Zones in Panama. Food Science & Nutrition, 13(12), e71278. https://doi.org/10.1002/fsn3.71278
Mehari, B., Redi-Abshiro, M., Chandravanshi, B.S., Combrinck, S., Mccrindle, R. (2016). Characterization of the Cultivation Region of Ethiopian Coffee by Elemental Analysis. Analytical Letters, 49, 2474-2489. https://doi.org/10.1080/00032719.2016.1151023
Moraes-Neto, V. F. de, Baqueta, M. R., Caramês, E. T. dos S., Santana, F. B. de, Alves, E. A., & Pallone, J. A. L. (2024). Discrimination of Brazilian green canephora coffee beans by ultraviolet–visible spectroscopy as a non-target analysis: A tool for recognizing geographical indications. Microchemical Journal, 202, 110737. https://doi.org/10.1016/j.microc.2024.110737
Moraes-Neto, V.F. de, Baqueta, M.R., Caramês, E.T. dos S., Rocha, R.B., & Pallone, J.A.L. (2025). Authentication of ‘Robusta Amazônico’ geographical indication for green coffee: UV–vis and NIR spectroscopy-based approaches combined with chemometrics. Food Chemistry, 493, 145612. https://doi.org/10.1016/j.foodchem.2025.145612
Oliveira, R. S., Costa, L. S., Santiago, H. de A., Mutz, Y. da S., Faria, R. de O., Figueiredo, L.P., Guimarães, P. H. S., Curi, N. C., & Menezes, M. D. de. (2025). Decoding local terroir: Data mining to predict sensory profiles of coffee beverage. Agricultural Systems, 230, 104487. https://doi.org/10.1016/j.agsy.2025.104487
Portela, C.S., Viencz, T., Pimentel, T.C., & Benassi, M.T. (2025). Behavior patterns of coffee consumption in Brazil and the United States of America: a social media analysis. British Food Journal, 127(12), 4210–4225. https://doi.org/10.1108/BFJ-11-2024-1120
Risticevic, S., Carasek, E., & Pawliszyn, J. (2008). Headspace solid-phase microextraction–gas chromatographic–time-of-flight mass spectrometric methodology for geographical origin verification of coffee. Analytica Chimica Acta, 617, 72-84. https://doi.org/10.1016/j.aca.2008.04.009
Rosenberg, M. (2023). Transforming Burundian “taste of place”: From shunned in commercial blends to specialty coffee. Norsk Geografisk Tidsskrift - Norwegian Journal of Geography, 77(4), 255–267. https://doi.org/10.1080/00291951.2023.2248997
Santanatoglia, A., Navarini, L., Angeloni, A., & Caprioli, G., (2025). Quercetin derivatives in roasted Coffea arabica and its popular beverages. Food Chemistry, 473, 143035. https://doi.org/10.1016/j.foodchem.2025.143035
Santos, W. W. V., Lima, K. B. L., Lucena, R. L. de, Arruda, L. L. A. L. de, Oliveira, R. L. de, Silva, M. E. dos S., & Silva, S. P. da. (2024). Effect of different materials of filter holder on sensory profile of coffee beverages. Journal of Sensory Studies, 39, 3, e12929. https://doi.org/10.1111/joss.12929
Scholz, M. B. S., Kitzberger, C. S. G., Prudencio, S. & Silva, R. S. S. F. (2018). The typicity of coffees from different terroirs determined by groups of physico-chemical and sensory variables and multiple factor analysis. Food Research International, 114, 72–80. https://doi.org/10.1016/j.foodres.2018.07.058
Silva, M. M. P. da, Tarone, A. G., Giomo, G. S., Ferrarezzo, E. M., Filho, O. G., & Teramoto, J. R. S. (2024). Predicting best planting location and coffee cup quality from chemical parameters: An evaluation of raw Arabica coffee beans from São Paulo over two harvests. Food Research International, 195, 114911. https://doi.org/10.1016/j.foodres.2024.114911
Silva, S. A., Queiroz, D. M., Pinto, F. A. C. & Santos, N. T. (2014). Characterization and delimitation of the terroir coffee in plantations in the municipal district of Araponga, Minas Gerais, Brazil. Revista Ciência Agronômica, 45, 18-26. https://doi.org/10.1590/S1806-66902014000100003
Smith, J. (2018). Coffee Landscapes: Specialty Coffee, Terroir, and Traceability in Costa Rica. Culture, Agriculture. Food and Environment, 40, 36-44. https://doi.org/10.1111/cuag.12103
Suksomboon, P. (2023). Coffee Products and the Protections Under the Aspect of Geographical Indication (GI) Law: A Case Study of Doi Tung Coffee. Journal of Multidisciplinary in Social Sciences, 19(3), 23–31. https://so03.tci-thaijo.org/index.php/sduhs/article/view/274228
Tassew, A. A., Yadessa, G. B., Bote, A. D., & Obso, T. K. (2021). Influence of location, elevation gradients, processing methods, and soil quality on the physical and cup quality of coffee in the Kafa Biosphere Reserve of SW Ethiopia. Heliyon, 7(8), e07790. https://doi.org/10.1016/j.heliyon.2021.e07790
Tieghi, H., Pereira, L. de A., Viana, G. S., Katchborian-Neto, A., Santana, D. B., Mincato, R. L., Dias, D.F., Paula, D. A. C., Soares, M.G., Araújo, W.G. de, & Bueno, P. C. P. (2024). Effects of geographical origin and post-harvesting processing on the bioactive compounds and sensory quality of Brazilian specialty coffee beans. Food Research International, 186, 114346. https://doi.org/10.1016/j.foodres.2024.114346
Toledo, P. R. A. B., Pezza, L., Pezza, H. R., & Toci, A. T. (2016). Relationship Between the Different Aspects Related to Coffee Quality and Their Volatile Compounds. Comprehensive reviews in food science and food safety, 15, 4, 705–719. https://doi.org/10.1111/1541-4337.12205
Urugo, M. M., Tola, T. B., Kebede, B.T., Onwuchekwa, O., Mattinson, D. S. (2024). Utilizing HS-SPME-GC-MS for Regional Classification of Ethiopian Green Coffee Beans: An In-Depth Analysis of Volatile Compounds. ACS Food Science & Technology, 4(5). https://doi.org/10.1021/acsfoodscitech.4c00101
Vivo, A. de, Balivo, A., & Sarghini, F. (2023). Volatile Compound Analysis to Authenticate the Geographical Origin of Arabica and Robusta Espresso Coffee. Applied Sciences, 13(9), 5615. https://doi.org/10.3390/app13095615
Voica, C., Feher, I., Iordache, A. M., Cristea, G., Dehelean, A., Magdas, D. A., & Mirel, V. (2016). Multielemental Analysis of Coffee by Inductively Coupled Plasma-Mass Spectrometry. Analytical Letters, 49(16), 2627–2643. https://doi.org/10.1080/00032719.2015.1116003
Wang, Y., Wang, X., Dong, J., Li, L., Du, P., Liu, X., & Yang, Q.2 (2026). Coffee blending: development trend under the new wave. Food Chemistry, 507, 148167. https://doi.org/10.1016/j.foodchem.2026.148167
Wei, F., Furihata, K., Koda, M., Hu, F., Kato, R., Miyakawa, T l. & Tanokura, M. (2012). 13C NMR-Based Metabolomics for the Classification of Green Coffee Beans According to Variety and Origin. Journal of Agricultural and Food Chemistry, 60(40), 10118-10125. https://doi.org/10.1021/jf3033057
Williams, S. D., Bronwyn, J. B., Rose, T. J., & Liu, L. (2022). Does Coffee Have Terroir and How Should It Be Assessed?. Foods, 11(13): 1907. https://doi.org/10.3390/foods11131907
Woldegebriel, A. M. (2025). Coffee (Coffea arabica L.) Cup Quality Varies with Growing Environments in Ethiopia: Climate and Soil Perspectives. Coffee Science, 20, e202295. https://doi.org/10.25186/.v20i.2295
Worku, M. (2023). Production, productivity, quality and chemical composition of Ethiopian coffee. Cogente Food & Agriculture, 9, 2196868. https://doi.org/10.1080/23311932.2023.2196868
Yang, S., Li, C., Mei, Y., Liu, W., Liu, R., Chen, W., Han, D., & Xu, K. (2021). Determination of the Geographical Origin of Coffee Beans Using Terahertz Spectroscopy Combined With Machine Learning Methods. Frontiers in nutrition, 8, 680627. https://doi.org/10.3389/fnut.2021.680627
Zhang, S.-B., Zhao, G.-H., Lv, T.-R., Gong, 9C.-Y., Shi, Y.-Q., Nan, W. & Zhang, H.-H. 2023). Bibliometric and visual analysis of microglia-related neuropathic pain from 2000 to 2021. Frontiers in Molecular Neuroscience, 16, 1142852. https://doi.org/10.3389/fnmol.2023.1142852
Zinsli, M. (2022). Authorizing the ‘taste of place’ for Galápagos Islands coffee: scientific knowledge, development politics, and power in geographical indication implementation. Agriculture and Human Values, 40(6), 1-17. https://doi.org/10.1007/s10460-022-10364-
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 1969 Wallysson Wagner Vilela Santos, Wanessa Braz da Silva, Marcelo Edvan dos Santos Silva, Rodrigo Lira de Oliveira, Suzana Pedroza da Silva

Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
Autores que publicam na Revista Brasileira de Geografia Física concordam com os seguintes termos:
Autores mantêm os direitos autorais e concedem à revista o direito de primeira publicação, com o trabalho simultaneamente licenciado sob a licença Creative Commons Atribuição 4.0 Internacional (CC BY 4.0) que permite o compartilhamento do trabalho com reconhecimento da autoria e publicação inicial nesta revista.
Autores têm autorização para assumir contratos adicionais separadamente, para distribuição não-exclusiva da versão do trabalho publicada nesta revista (exemplo: depositar em repositório institucional ou publicar como capítulo de livro), com reconhecimento de autoria e publicação inicial nesta revista.
Autores têm permissão para disponibilizar seu trabalho online antes ou durante o processo editorial, em redes sociais acadêmicas, repositórios digitais ou servidores de preprints. Após a publicação na Revista Brasileira de Geografia Física, os autores se comprometem a atualizar as versões preprint ou pós-print do autor, nas plataformas onde foram originalmente disponibilizadas, informando o link para a versão final publicada e outras informações relevantes, com o reconhecimento da autoria e da publicação inicial nesta revista.
Qualquer usuário tem direito de:
Compartilhar — copiar e redistribuir o material em qualquer suporte ou formato para qualquer fim, mesmo que comercial.
Adaptar — remixar, transformar e criar a partir do material para qualquer fim, mesmo que comercial.
O licenciante não pode revogar estes direitos desde que você respeite os termos da licença.
De acordo com os termos seguintes:
Atribuição — Você deve dar o crédito apropriado, prover um link para a licença e indicar se mudanças foram feitas. Você deve fazê-lo em qualquer circunstância razoável, mas de nenhuma maneira que sugira que o licenciante apoia você ou o seu uso.
Sem restrições adicionais — Você não pode aplicar termos jurídicos ou medidas de caráter tecnológico que restrinjam legalmente outros de fazerem algo que a licença permita.






