Uma Análise Bibliométrica da Produção Científica em Apicultura de Precisão

• Carolina Alves Ribeiro UFC
• Isaura Nelsivania Sombra Oliveira UFC
• Danielo G. Gomes UFC

DOI: https://doi.org/10.5753/ercemapi.2022.226438

Abstract

Bibliometrics is a quantitative and statistical technique to contrast metrics of production and dissemination of scientific knowledge. Therefore, the objective of this article is to highlight the global trends of research in the area of precision beekeeping through bibliometric analysis. The datasets used were extracted from Scopus and Web of Science databases. Analyzes were performed using Biblioshiny from the Bibliometrix library, used in RStudio software. In the annual scientific production, the years with the most publications on precision beekeeping were 2020-2021. Latvia was the country with the most published works. Computers and Electronics in Agriculture, Engineering for Rural Development and Biosystems Engineering were the journals that stood out. And the trend topics in precision beekeeping from 2016 to 2021 were determined.

References

Buschbacher, K., Ahrens, D., Espeland, M., and Steinhage, V. (2020). Image-based species identification of wild bees using convolutional neural networks. Ecological Informatics, 55:37 - 45.

FAPESP (2010). Análise da produção científica a partir de indicadores bibliométricos. Fundação de Amparo à Pesquisa do Estado de São Paulo: FAPESP, 2010. cap. 4. p. 4-71. Disponível em: [link]. Acesso em: 04 out. 2021.

Matos, M. T. d., Condurú, M. T., and Benchimol, A. C. (2022). Interseções na produção científica da ciência da informação e ciência de dados. Acervo, 35(2):1-18.

Moreira, P. S. d. C., Guimarães, A. J. R., and Tsunoda, D. F. (2020). Qual ferramenta bibliométrica escolher? um estudo comparativo entre softwares. P2P E INOVAÇÃO, 6(2):140-158.

Okubo, Y. (1997). Bibliometric indicators and analysis of research systems. OECD Science, Technology and Industry Working Papers, pages 1-70.

Pritchard, A. (1969). Statistical bibliography or bibliometrics. Journal of documentation, 25(4):348-349.

Santana, F., Costa, A., Truzzi, F., Silva, F., Leal, S., Francoy, T., and Saraiva, A. (2014). A reference process for automating bee species identification based on wing images and digital image processing. Ecological Informatics, 24.

Zacepins, A. and Meitalovs, J. (2014). Implementation of multi-node temperature measurement system for bee colonies online monitoring. In Proceedings of the 2014 15th International Carpathian Control Conference (ICCC), pages 695-698.

Zgank, A. (2021). Iot-based bee swarm activity acoustic classification using deep neural networks. Sensors, 21(3).