Inovações tecnológicas no campo: : mapeamento e tendências futuras da literatura científica

Bruno Gomes de Carvalho; Juliana Resende Paviani; Anne Irene Cunha Vaz; Cleber Carvalho de Castro; Paulo Henrique Montagnana Vicente Leme

doi:10.5585/2023.24901

Autores/as

Bruno Gomes de Carvalho Universidade Federal de Lavras – UFLA / Lavras (MG) https://orcid.org/0000-0003-1187-7003
Juliana Resende Paviani Universidade Federal de Lavras – UFLA / Lavras (MG) https://orcid.org/0000-0002-7816-5222
Anne Irene Cunha Vaz Universidade Federal de Lavras – UFLA / Lavras (MG) https://orcid.org/0000-0002-6800-4118
Cleber Carvalho de Castro Universidade Federal de Lavras – UFLA / Lavras (MG) https://orcid.org/0000-0002-6443-9501
Paulo Henrique Montagnana Vicente Leme Universidade Federal de Lavras – UFLA / Lavras (MG) https://orcid.org/0000-0003-4174-5642

DOI:

https://doi.org/10.5585/2023.24901

Palabras clave:

Agtech, Desarrollo sostenible, Innovación, Tecnología, Sostenibilidad, Prácticas Agrícolas

Resumen

Objetivo: Las Agtechs son startups enfocadas en el desarrollo de soluciones tecnológicas para la agroindustria. Debido a su relevancia en la literatura, este trabajo tiene como objetivo mapear la producción científica y señalar las tendencias de futuros estudios sobre Agtechs, buscando identificar el panorama de contribución a la producción de tecnologías sostenibles.

Metodología/enfoque: Este estudio empleó una revisión sistemática de la literatura, utilizando métodos bibliométricos y de análisis de contenido para analizar el estado de la investigación Agtech.

Resultados principales: Los resultados indican la importancia del tema y su creciente popularidad en la investigación científica. Además, el análisis identificó nuevas líneas de investigación que merecen ser exploradas por la comunidad científica: el radar tecnológico agrícola; Sostenibilidad; Consecuencias de la agricultura 4.0; Desarrollo Rural y Ordenamiento Organizacional de Agtechs.

Aportes teóricos/metodológicos: El estudio de las Agtechs tiene implicaciones significativas para las perspectivas teóricas relacionadas con la innovación tecnológica. En consecuencia, se necesita una mejor comprensión del creciente interés en el tema entre los académicos para aprovechar sus implicaciones y posibilidades.

Aportes sociales/gerenciales: El análisis indica que las Agtech son clave para guiar la revolución agrícola hacia un crecimiento sostenible global, siendo consideradas esenciales para optimizar toda la producción de alimentos de manera sostenible.

Descargas

Los datos de descargas todavía no están disponibles.

Biografía del autor/a

Bruno Gomes de Carvalho, Universidade Federal de Lavras – UFLA / Lavras (MG)

Mestre em Administração Pública. Universidade Federal de Lavras – UFLA. Lavras, Minas Gerais

Juliana Resende Paviani, Universidade Federal de Lavras – UFLA / Lavras (MG)

Mestranda em Administração. Pós-Graduação em Gestão Pública

Anne Irene Cunha Vaz, Universidade Federal de Lavras – UFLA / Lavras (MG)

Mestranda em Administração. Universidade Federal de Lavras – UFLA

Cleber Carvalho de Castro, Universidade Federal de Lavras – UFLA / Lavras (MG)

Doutor em Agronegócios, Universidade Federal de Lavras – UFLA

Paulo Henrique Montagnana Vicente Leme, Universidade Federal de Lavras – UFLA / Lavras (MG)

Doutor em Administração. Universidade Federal de Lavras – UFLA

Citas

Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive Science mapping analysis. Journal of informetrics, 11(4), 959-975. Doi: https://doi.org/10.1016/j.joi.2017.08.007

Avellan, A., et al. (2019). Nanoparticle size and coating chemistry control foliar uptake pathways, translocation, and leaf-to-rhizosphere transport in wheat. ACS nano, 13(5), 5291-5305. Doi: https://doi.org/10.1021/acsnano.8b09781

Ayaz, M., et al. (2019). Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk. IEEE access, 7, 129551-129583. Doi: 10.1109/ACCESS.2019.2932609

Babenko, V., et al. (2022). Agritech startup ecosystem in Ukraine: ideas and realization. In Digital Transformation Technology. Springer, Singapore, 311-322. Doi: https://doi.org/10.1007/978-981-16-2275-5_19

Bornmann, L., & Mutz, R. (2015). Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology, 66(11), 2215-2222. Doi: https://doi.org/10.1002/asi.23329

Chen, C. (2004). Searching for intellectual turning points: Progressive knowledge domain visualization. Proceedings of the National Academy of Sciences, 101(Suppl_1), 5303-5310. Doi: https://doi.org/10.1073/pnas.0307513100

Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transiente patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359-377. Doi: https://doi.org/10.1002/asi.20317

Costa, J. T. F., & Costa, V. S. (2022). O pagamento por serviços ambientais: uma análise para o desenvolvimento sustentável da agricultura familiar do Rio Grande do Sul Payment for environmental services: an analysis for the sustainable development of family agriculture in Rio Grande do Sul. Brazilian Journal of Development, 8(2), 10172-10186. DOI:10.34117/bjdv8n2-114

Dayioglu, M. A., & Turker, U. (2021). Digital Transformation for Sustainable Future-Agriculture 4.0: A review. Journal of Agricultural Sciences, 27(4), 373-399. Doi: https://doi.org/10.15832/ankutbd.986431

Donthu, N., et al. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. Doi: https://doi.org/10.1016/j.jbusres.2021.04.070

Dutia, S. (2014). Agtech: Challenges and opportunities for sustainable growth. Available at SSRN 2431316. Doi: http://dx.doi.org/10.2139/ssrn.2431316

Eck, N. J. V., & Waltman, L. (2014). Visualizing bibliometric networks. In Measuring scholarly impact. Springer, Cham, 285-320. Doi: https://doi.org/10.1007/978-3-319-10377-8_13

Farooq, M. S., et al. (2020). Role of IoT technology in agriculture: A systematic literature review. Electronics, 9(2), 319. Doi: 10.3390/electronics9020319

Filser, L. D., et al. (2017). State of research and future research tendencies in lean healthcare: a bibliometric analysis. Scientometrics, 112(2), 799-816. Doi: https://doi.org/10.1007/s11192-017-2409-8

Gomes, L. A. V., et al. (2018). Unpacking the innovation ecosystem construct: Evolution, gaps and trends. Technological Forecasting and Social Change, 136, 30-48. Doi: https://doi.org/10.1016/j.techfore.2016.11.009

Hofmann, T., et al. (2020). Technology readiness and overcoming barriers to sustainably implement nanotechnology-enabled plant agriculture. Nature Food, 1(7), 416-425. Doi: https://doi.org/10.1038/s43016-020-0110-1

Iddy, J. J., & Alon, I. (2019). Knowledge management in franchising: a research agenda. Journal of Knowledge Management, 23(4), 763-785. Doi: https://doi.org/10.1108/JKM-07-2018-0441

Kah, M., et al. (2018). A critical evaluation of nanopesticides and nanofertilizers against their conventional analogues. Nature nanotechnology, 13(8), 677-684. Doi: https://doi.org/10.1038/s41565-018-0131-1

Kah, M., et al. (2019). Nano-enabled strategies to enhance crop nutrition and protection. Nature nanotechnology, 14(6), 532-540. Doi: https://doi.org/10.1038/s41565-019-0439-5

Kakani, V., et al. (2020). A critical review on computer vision and artificial intelligence in the food industry. Journal of Agriculture and Food Research, 2, 100033. Doi: https://doi.org/10.1016/j.jafr.2020.100033

Klerkx, L., & Rose, D. (2020). Dealing with the game-changing technologies of Agriculture 4.0: How do we manage diversity and responsibility in food system transition pathways?. Global Food Security, 24, 100347. Doi: https://doi.org/10.1016/j.gfs.2019.100347

Kumar, S., et al. (2019). Nano-based smart pesticide formulations: Emerging opportunities for agriculture. Journal of Controlled Release, 294, 131-153. Doi: https://doi.org/10.1016/j.jconrel.2018.12.012

Lowry, G. V., et al. (2019). Opportunities and challenges for nanotechnology in the agri-tech revolution. Nature nanotechnology, 14(6), 517-522. Doi: https://doi.org/10.1038/s41565-019-0461-7

Mahmud, R., Ramamohanarao, K., & Buyya, R. (2020). Application management in fog computing environments: A taxonomy, review and future directions. ACM Computing Surveys (CSUR), 53(4), 1-43. Doi: https://doi.org/10.1145/3403955

Minayo, M. C. S. (2000). O desafio do conhecimento: pesquisa qualitativa em saúde (7a ed.). São Paulo: Hucitec; Rio de Janeiro: Abrasco, p. 197-211.

Prado, J. W., et al. (2016). Multivariate analysis of credit risk and bankruptcy research data: a bibliometric study involving different knowledge fields (1968-2014). Scientometrics, 106(3), 1007-1029. Doi: https://doi.org/10.1007/s11192-015-1829-6

Pranckutė, R. (2021). Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications, 9(1), 12. Doi: https://doi.org/10.3390/publications9010012

Quintam, C. P. R., & de Assunção, G. M. (2023). Panorama do Agronegócio Exportador Brasileiro. RECIMA21-Revista Científica Multidisciplinar https://doi.org/10.47820/recima21.v4i7.3642

Ries, E. (2012). A startup enxuta. Leya.

Rose, D. C., & Chilvers, J. (2018). Agriculture 4.0: Broadening responsible innovation in an era of smart farming. Frontiers in Sustainable Food Systems, 2, 87. Doi: https://doi.org/10.3389/fsufs.2018.00087

Rotz, S., et al. (2019). Automated pastures and the digital divide: How agricultural technologies are shaping labor and rural communities. Journal of Rural Studies, 68, 112-122. Doi: https://doi.org/10.1016/j.jrurstud.2019.01.023

Sesso Filho, U. A., et al. (2021). Measurement of the agro-industrial complex in the world: a comparative study between countries. Revista de Economia e Sociologia Rural, 60. Doi: https://doi.org/10.1590/1806-9479.2021.235345

Spanaki, K., et al. (2022). Disruptive technologies in agricultural operations: a systematic review of AI-driven AgriTech research. Annals of Operations Research, 308(1), 491-524. Doi: https://doi.org/10.1007/s10479-020-03922-z

Suominen, A., Seppänen, M., & Dedehayir, O. (2019). A bibliometric review on innovation systems and ecosystems: a research agenda. European Journal of Innovation Management, 22(2), 335-360. Doi: https://doi.org/10.1108/EJIM-12-2017-0188

Udayanga, D., et al. (2011). The genus Phomopsis: biology, applications, species concepts and names of common phytopathogens. Fungal diversity, 50(1), 189-225. Doi: https://doi.org/10.1007/s13225-011-0126-9

UN, Transforming Our World: The 2030 Agenda for Sustainable Development (UN, New York, 2015); http://bit.ly/TransformAgendaSDG-pdf

Vieira Filho, J. E. R., & Fishlow, A. (2017). Agricultura e indústria no Brasil: inovação e competitividade.

Weersink, A., et al. (2018). Opportunities and challenges for big data in agricultural and environmental analysis. Annual Review of Resource Economics, 10(1), 19-37. Doi: https://doi.org/10.1146/annurev-resource-100516-053654

Wojnarowicz, J., Chudoba, T., & Lojkowski, W. (2020). A review of microwave synthesis of zinc oxide nanomaterials: Reactants, process parameters and morphologies. Nanomaterials, 10(6), 1086. Doi: https://doi.org/10.3390/nano10061086

Xu, J., et al. (2021). Current and emergent analytical methods for monitoring the behavior of agricultural functional nanoparticles in relevant matrices: A review. Current Opinion in Chemical Engineering, 33, 100706. Doi: https://doi.org/10.1016/j.coche.2021.100706

Zhao, L., et al. (2020). Nano-biotechnology in agriculture: Use of nanomaterials to promote plant growth and stress tolerance. Journal of Agricultural and Food Chemistry, 68(7), 1935-1947. Doi: https://doi.org/10.1021/acs.jafc.9b06615