Published March 11, 2026 | Version online
Journal article Open

Aplicativos móveis para identificação de plantas medicinais: uma revisão sistemática

Authors/Creators

  • 1. (1) Fundação Oswaldo Cruz
  • 2. (2) Universidade Regional do Cariri
  • 3. (3) Centro Universitário – Faculdade de Tecnologia e Ciência
  • 4. (4) Fundação Oswaldo Cruz

Contributors

  • 1. (1) Fundação Oswaldo Cruz
  • 2. (2) Universidade Regional do Cariri
  • 3. (3) Centro Universitário – Faculdade de Tecnologia e Ciência
  • 4. (4) Fundação Oswaldo Cruz

Description

Esta revisão sistemática avaliou aplicativos para identificação de plantas medicinais, analisando suas principais características e apontando aspectos a serem aprimorados. As bases PUBMED, Embase e Scopus foram pesquisadas, utilizando Rayyan e JASP para análise de frequência de ano, localização, sistema operacional e linguagem. Dos 251 artigos encontrados, apenas 16 atenderam aos critérios de inclusão, focando em aplicativos de identificação de plantas. O sistema operacional Android foi o mais citado (61,11%), com predominância das linguagens Java e Android Studio (12,5% cada). O ano de 2020 concentrou o maior número de publicações (25%). Observou-se que as ferramentas existentes apresentam informações incompletas, especialmente quanto às características taxonômicas fundamentais, como floração e frutificação. Destaca-se a necessidade de aplicativos que integrem essas informações e utilizem algoritmos eficazes de inteligência artificial, criando bancos de dados botânicos mais robustos e confiáveis. A revisão evidenciou a escassez de pesquisas e a desatualização de dados nos aplicativos atuais, ressaltando a importância de colaboração interdisciplinar para o desenvolvimento de ferramentas mais precisas e úteis na identificação de plantas medicinais.

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Journal article: 2526-8236 (ISSN)

Dates

Available
2026-03-11
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https://cfp.revistas.ufcg.edu.br/cfp/index.php/RPECEN

References

  • Ambreen H., Bidushi B., Ahmed O., Raouf A. & Taufiq A. (2021) Performance of mobileNetV3 transfer learning on handheld device-based real-time tree species identification. 26th international conference on automation and computing: system intelligence through automation and computing.
  • Boho D., Rzanny M., Wäldchen J., Nitsche F., Deggelmann A., Wittich H.C., Seeland M. & Mäder P. (2020) Flora Capture: a citizen science application for collecting structured plant observations. BMC Bioinformatics, 21: 576. https://doi.org/10.1186/s12859-020-03920-9
  • Campbell N., Peacock J. & Bacon K.L. (2023) A repeatable scoring system for assessing Smartphone applications ability to identify herbaceous plants. PLoS ONE, 18(4): e0283386. https://doi.org/10.1371/journal.pone.0283386
  • Chathura P.H.A. & Withanage D.K. (2015) Computer assisted plant identification system for Android (p. 148–153). Moratuwa: Moratuwa Engineering Research Conference. https://doi.org/10.1109/MERCon.2015.7112336
  • de Fatima R.P.R., Cordeiro P.H.F., Periotto F. & Baron D. (2020) QR code technology in a sensory garden as a study tool. Ornamental Horticulture, 26(2): 220–224. https://doi.org/10.1590/2447-536X.v26i2.2114
  • Harjanti T.W. & Madenda S. (2019) Development of Feature Extraction on Leaf Image for Medicinal Plants Identification. International Journal of Recent Technology and Engineering, 8(2): 163–168. https://doi.org/10.35940/ijrte.B1040.0782S719
  • Hussain A., Barua B., Osman A., Abozariba R. & Asyhari A.T. (2024) Performance of MobileNetV3 Transfer Learning on Handheld Device-based Real-Time Tree Species Identification. 26th International Conference on Automation and Computing: System Intelligence through Automation and Computing. Portsmouth: ICAC. https://doi.org/10.23919/ICAC50006.2021.9594222
  • Joly A., Goëau H., Bonnet P., Bakić V., Barbe J., Selmi S., Yahiaoui I., Carré J., Mouysset E., Molino J.-F., Boujemaa N. & Barthélémy D. (2014) Interactive plant identification based on social image data. Ecological Informatics, 23: 22–34. https://doi.org/10.1016/j.ecoinf.2013.07.006
  • Jones H.G. (2020) What plant is that? Tests of automated image recognition apps for plant identification on plants from the British flora. AoB PLANTS, 12(6): plaa052. https://doi.org/10.1093/aobpla/plaa052
  • Krause J., Sugita G., Baek K. & Lim L. (2018) WTPlant (What's That Plant?): A Deep Learning System for Identifying Plants in Natural Images. Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval. New York: ACM. https://doi.org/10.1145/3206025.3206089
  • Mäder P., Boho D., Rzanny M., Seeland M., Wittich H.C., Deggelmann A. & Wäldchen J. (2021) The Flora Incognita app – Interactive plant species identification. Methods in Ecology and Evolution, 12(7): 1335–1342. https://doi.org/10.1111/2041-210X.13611
  • Malik O.A., Ismail N., Hussein B.R. & Yahya U. (2022) Automated Real-Time Identification of Medicinal Plants Species in Natural Environment Using Deep Learning Models—A Case Study from Borneo Region. Plants, 11(15): 1952. https://doi.org/10.3390/plants11151952
  • Marques M.A., Santino F.H.F., Mariguchi P., Martins E. & Nascimento A.V. (2023) Aplicativo para smartphone na identificação de plantas medicinais através da leitura de Qr code. Expressa Extensão, 28(3): 21–23.
  • Min Gao, Lang Lin & Sinnott R.O. (2017) A Mobile Application for Plant Recognition through Deep Learning. IEEE 13th International Conference on e-Science. Auckland: IEEE. https://doi.org/10.1109/eScience.2017.15
  • Ouzzani M., Hammady H., Fedorowicz Z. & Elmagarmid A. (2016) Rayyan—a web and mobile app for systematic reviews. Systematic Reviews, 5: 210. https://doi.org/10.1186/s13643-016-0384-4
  • Prasad S., Peddoju S.K. & Ghosh D. (2013) Mobile plant species classification: A low computational approach. IEEE Second International Conference on Image Information Processing (ICIIP-2013), Shimla: IEEE. https://doi.org/10.1109/ICIIP.2013.6707624
  • Priya K., Ranjana S. & Manimegala R. (2020) Medicinal plant identification using andr oid application based on leaf image. European Journal of Molecular & Clinical Medicine, 7(9): 1496–1506. https://doi.org/10.31838/ejmcm.07.09.161
  • Ripoll S., Mayoral O. & Azkárraga J.M. (2017) Proyecto Quick Natura. Técnologías móviles aplicadas a rutas botánicas urbanas. Modelling in Science Education and Learning, 10(1): 185–192. https://doi.org/10.4995/msel.2017.6661
  • Sofiene M., Ither I.Y., Anne V.-B., Laurent J., Souheil S. & Hervé G. (2013) An Android Application for Leaf-based Plant Identification. ICMR - Proceedings of the 3rd ACM International Conference on Multimedia Retrieval. Dallas: ICMR. https://doi.org/10.1145/2461466.2461520
  • Sun Y., Liu Y., Wang G. & Zhang H. (2017) Deep Learning for Plant Identification in Natural Environment. Computational Intelligence and Neuroscience, 2017: 7361042. https://doi.org/10.1155/2017/7361042
  • Tao L. & Cheng C. (2018) Plant Identification Based on Image Set Analysis. In: Aiello M., Yang Y., Zou Y. & Zhang L.J. (Eds). Artificial Intelligence and Mobile Services. Lecture Notes in Computer Science, 10970. https://doi.org/10.1007/978-3-319-94361-9_6
  • Thanikkal J.G., Dubey A.K. & Thomas M.T. (2023) An Efficient Mobile Application for Identification of Immunity Boosting Medicinal Plants using Shape Descriptor Algorithm. Wireless Personal Communications, 131(2): 1189–1205. https://doi.org/10.1007/s11277-023-10476-3
  • Tran A.C., Nhu Y N.T., Thoa P.K., Tran N.C. & Duong-Trung N. (2020) Real-time Recognition of Medicinal Plant Leaves Using Bounding-box Based Models. International Conference on Advanced Computing and Applications (ACOMP). Quy Nhon: ICACA. https://doi.org/10.1109/ACOMP50827.2020.00013
  • Ullah R., Alqahtani A.S., Noman O.M.A., Alqahtani A.M., Ibenmoussa S. & Bourhia M. (2020) A review on ethno-medicinal plants used in traditional medicine in the Kingdom of Saudi Arabia. Saudi Journal of Biological Sciences, 27(10): 2706–2718. https://doi.org/10.1016/j.sjbs.2020.06.020
  • Wang B., Brown D., Gao Y. & Salle J.L. (2013) Mobile plant leaf identification using smart-phones. IEEE International Conference on Image Processing. Melbourne: VIC. https://doi.org/ 10.1109/ICIP.2013.6738910
  • Zhao Z.Q., Ma L.H., Cheung Y.M., Wu X., Tang Y. & Chen C.L.P. (2015) ApLeaf: An efficient android-based plant leaf identification system. Neurocomputing, 151(P3): 1112–1119. https://doi.org/10.1016/j.neucom.2014.02.077