Diagnosis about the perspectives of precision applications of coffee growing technologies in municipalities of Bahia, Brazil
Brazil is the largest coffee producer in the world and precision agriculture (PA) generates information for decision-making by farmers in crop management. However, one of the challenges is to better understand farmers' view of PA applications, challenges and benefits. This article presentes the applicability perspectives of Precision Agriculture techniques in Bahia state coffee farming, for greater efficiency and economic and environmental sustainability. To achieve the objective of this article, a virtual questionnaire was sent, sent to coffee growers in Bahia state. The questionnaire was sent by email in 2021 and the WhatsApp application, reaching 457 producers, 34 of whom, from all productive regions of Bahia, responded. The rate of return was 7.4%, within the expected by the application of the use. It was found that 59.3% of respondents have a high prospect of using PA in coffee growing, 26.6% have a medium perspective and 11.1%, a low perspective. The research shows that 67.6% do not use PA in the fields and that 51.7% consider the lack of training as a major obstacle to the use of PA and other digital technologies. Thus, the conclusion is reached that there is a promising scenario in Bahia state for the application of PA in coffee growing, as long as there is training for the development of techniques in farming.
Key words: Precision agriculture; survey; agribusiness; rural development.
BERNARDI, A. C. C. de. et al. Agricultura de precisão: Resultados de um novo olhar. Brasília: EMBRAPA, 2014. 596p.
FAGUNDES, ROZYMARIO. Precision coffee growing research, 2021. Available in: https://pt.slideshare.net/MrioBittencourt1/respostas-pesquisa-cafeicultura-depreciso. Access in: September 19, 2022.
BOLFE, E. L.; MASSRUHÁ, S. M. F. S. A transformação digital e a sustentabilidade agrícola. Agroanalysis, 40(3):32-34, 2020.
BOLFE, E. L. et al. Precision and digital agriculture: Adoption of technologies and perception of Brazilian farmers. Agriculture, 10(12):653, 2020.
BORGHI, E. et al. Adoption and use of precision agriculture in Brazil: Perception of growers and service dealership. Journal of Agricultural Science, 8(11):89-104, 2016.
CAMPO E NEGÓCIOS. Anuário de café 2021. Uberlândia, 2021. Available in: https://revistacampoenegocios.com.br/anuarios/ Access in: September 26, 2022.
CONFEDERAÇÃO NACIONAL DA AGRICULTURA - CNA. Relatório de Pesquisa Cafeeira: Safra 2021-2022. Available in: <https://www.cnabrasil.org.br/assets/images/Relatorio-Pesquisa-Cafeeira.pdf>. Access in: September 15, 2022.
EMPRESA BRASILEIRA DE PESQUISA AGROPECUÁRIA/ CENTRO NACIONAL DE PESQUISA DE MILHO E SORGO - EMBRAPA/CNPMS. Tecnologia em Mecanização no Brasil: Equipamentos e sistemas para o futuro. (Documentos nº 10), Sete Lagoas: Embrapa Milho e Sorgo. 1997. 35p.
FERRAZ, G. A. S. et al. Viabilidade econômica da cafeicultura de precisão. In: SILVA, F. M. da.; ALVES, M. C. de. (Org.). Cafeicultura de precisão. Lavras: Editora UFLA, p. 209-222, 2013.
FERRAZ, G. A. S. et al. Spatial variability of the dosage of P2O5 and K2O to fertilize in variable rate and in a conventional way in a coffee field. Coffee Science, 10(3):346-356, 2015.
FERRAZ, G. A. S et al. Methodology to determine the soil sampling grid for precision agriculture in a coffee field. DYNA, 84(200):316-325, 2017.
FIGUEIREDO, V. C. et al. Development of a methodology to determine the best grid sampling in precision coffee growing. Coffee Science, 13(3):312 - 323, 2018.
INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA - IBGE. Sistema Sidra. 2021. Available in: <https://sidra.ibge.gov.br/home/>. Access in: September 15, 2022.
JORGE, R. F. et al. RFJ spatial variability in fertigated coffee yields and plant nutrients in soil saturation extracts. International Journal for Innovation Education and Research, 7(11):347-60, 2019.
SILVA, M. B. da. et al. Nutricional balance and its relationship to yield in a coffee field: Inferences from geospatial analiysis. Revista Brasileira de Engenharia Agrícola e Ambiental, 24(12):834-839, 2020.
MCKINSEY & COMPANY. A mente do agricultor brasileiro na era digital. Rio de Janeiro, 2020. Available in: http://www.aeaprcuritiba.com.br/admin/arquivos/A%20mente%20do%20Agricultor%20Brasileiro%20na%20Era%20Digital%20[AGCO].pdf. Access in: September 15, 2022.
FAGUNDES, R. B. & BOLFE, E. L. PIVOTO, D. et al. Factors influencing the adoption of smart farming by Brazilian grain farmers. International Food and Agribusiness Management Review, 22(4):571-588, 2019.
PUNTEL, L. A. et al. How digital is agriculture in a subset of countries from South America? Adoption and limitations.
Crop & Pasture Science, 1-18, 2022.
SILVA, F. M.; ALVES, M. C. Cafeicultura de precisão. Lavras: Editora UFLA, 2013. 227.
SOTT, M. K. et al. Precision techniques and agriculture 4.0 technologies to promote sustainability in the coffee sector:
State of the art, challenges and future trends, IEEE. Access, 8:1-14, 2020,
STAFFORD, J. V. Implementing precision agriculture in the 21st century. Journal of Agricultural Engineering Research, 76(3):267-275, 2000.
TSCHIEDEL, M.; FERREIRA, M. F. Introdução à agricultura de precisão: Conceitos e vantagens. Ciência Rural, 32(1):159-163, 2002.
WHIPKER, L. D.; AKRIDGE, J. T. Precision agricultural services dealership survey results. 2008. Available in: <https://ageconsearch.umn.edu/record/46427/> Access in: September 15, 2022.
ZANELLA, M. A. et al. Spatial correlation between the chlorophyll index and foliar NPK levels in coffee crop.
Coffee Science, 15:e151765, 2020.
How to Cite
LicenseCopyright (c) 2022 Coffee Science - ISSN 1984-3909
Os direitos autorais dos artigos publicados nesta revista pertencem aos autores, com os primeiros direitos de publicação pertencentes à revista. Como os artigos aparecem nesta revista com acesso aberto, eles podem ser usados livremente, com as devidas atribuições, em aplicativos educacionais e não comerciais.