Sustainable development driven by technologies in agriculture
Keywords:Agricultura 4.0 ; Sustentabilidade ; Acesso ; Innovation.
The main focus of this research is digital technology in agriculture, also defined as agriculture 4.0, and its relationship with the Sustainable Development Goals included in the UN's 2030 Agenda. As a method, a systematic literature review was carried out, in order to seek elements that show how the topic has been described in scientific articles published in the last ten years. After the scan, 15 studies published in 2018, 2019, 2020 and 2021 were selected. These indicators show the growth of publications on agriculture 4.0. Among the articles, emphasis was placed on studies related to the development of digital technology models for specific agricultural crops, as well as studies that intended to understand the relationship between their use and the difficulties of implementing these in the productive context. All selected studies are unanimously related to the 9th objective of the UN Agenda, whose main goal is the construction of inclusive, sustainable, resilient productive processes, with a focus on innovation. In this case, innovation has a strong relationship with the digital in agriculture. The results also point to evidence of the need to formulate efficient public policies, of incentives and continuity, for large and small producers; suggest that this is one of the main aspects to be considered, considering the agricultural establishment, its culture and mode of production.
Aghi, D., Mazzia, V. & Chiaberge, M. (2020). Local Motion Planner for Autonomous Navigation in Vineyards with a RGB-D Camera-Based Algorithm and Deep Learning Synergy. Machines, 8 (2), 1-16.
Angeloni, S. (2020). Domo Farm 4.0. International Journal of Grid and Utility Computing, 11 (2), 135-142.
Bardin, L. (2016). Análise de conteúdo. São Paulo: Edições 70.
Belauda, J. P., Prioux, N., Vialle, C. & Sablayrolles, C. (2019). Big data for agri-food 4.0: Application to sustainability management for by-products supply chain. Computers and Industry, 111 (1), 41-50.
Bolfe, E. L., Jorge, L. A. C., Sanches, I. D., Luchiari Júnior, A., Costa, C. C., Victoria, D. C., Inamasu, R. Y., Grego, C. R., Ferreira, V. R. & Ramirez, A. R. (2020). Precision and Digital Agriculture: Adoption of Technologies and Perception of Brazilian Farmers. Agriculture, 10 (12), 1-16.
Bolfe, E. L., Barbedo, J. G. A., Massruhá, S. M. F. S., Souza, K. X. S. & Assad, E. D. (2020). Desafios, tendências e oportunidades em agricultura digital no Brasil. In: Massruhá, S. M. F. S., Leite, M. A. A., Oliveira, S. R. M., Meira, C. A. A., Luchiari Junior, A. & Bolfe, E. L. (2020). Agricultura digital: pesquisa, desenvolvimento e inovação nas cadeias produtivas. Brasília: Embrapa, 380-406.
Buainain, A. M., Cavalcante, P. & Consoline, L. (2021). Estado atual da agricultura digital no Brasil: Inclusão dos agricultores familiares e pequenos produtores rurais. Santiago: CEPAL.
Chidi, C. L., Zhao, W., Chaudhary, S., Xiong, D. & Wu, Y. (2021). Sensitivity Assessment of Spatial Resolution Difference in DEM for Soil Erosion Estimation Based on UAV Observations: An Experiment on Agriculture Terraces in the Middle Hill of Nepal. International Journal of Geo-Information, 10 (1), 1-17.
Chuang, J. H., Wang, J. H. & Liou, Y. C. (2020). Farmers’ Knowledge, Attitude, and Adoption of Smart Agriculture Technology in Taiwan. International Journal of Environmental Research and Public Health, 17 (7236), 1-8.
Clercq, M., Vats, A. & Biel, A. (2018). Agriculture 4.0: The future of farming technology. Dubai: World Government Summit.
Elkington, J. (2012). Sustentabilidade: canibais com garfo e faca. São Paulo: M Books do Brasil.
Flores, C. A. & Alba, J. M. F. (2014). A Pedologia e a Agricultura de Precisão. In: Bernardi, A. C. C., Naime, J. M., Resende, A. V., Bassoi, L. H. & Inamasu, R. Y. (Orgs.) Agricultura de precisão: resultados de um novo olhar. Brasília: Embrapa, 36-47.
Giannoccaro, N. I., Persico, G., Strazzella, S., Lay-Ekuakille, A. & Visconti, P. (2020). A System for Optimizing Fertilizer Dosing in Innovative Smart Fertigation Pipelines: Modeling, Construction, Testing and Control. International Journal of Precision Engineering and Manufacturing, 21 (1), 1581-1596.
López-Morales, J. Á., Martínez, J. Á., Caro, M., Erena, M. & Skarmeta, A. F. (2021). Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety. Sensors Journal, 21 (3867) 1-27.
Massruhá, S. M. F. S. & Leite, M. A. A. (2017). Agro 4.0 – rumo à agricultura digital. In: Magnoni Júnior, L., Stevens, D., Silva, W. T. L., Vale, J. M. F., Purini, S. R. M., Magnoni, M. G. M., Sebastião, E., Branco Júnior, G., Adorno Filho, E. F., Figueiredo, W. S. & Sebastião, I. (Orgs.). JC na Escola Ciência, Tecnologia e Sociedade: mobilizar o conhecimento para alimentar o Brasil. 2. ed. São Paulo: Centro Paula Souza. 28-35
Mattivi, P., Pappalardo, S. E., Nikolic, N., Mandolesi, L., Persichetti, A., Marchi, M. & Masin, R. (2021). Can Commercial Low-Cost Drones and Open-Source GIS Technologies Be Suitable for Semi-Automatic Weed Mapping for Smart Farming? A Case Study in NE Italy. Remote sensing, 13 (1869), 1-21.
Matulovic, M., Putti, F. F., Cremasco, C. P. & Gabriel filho, L. R. A. (2021). Technology 4.0 with 0.0 costs: fuzzy model of lettuce productivity with magnetized water. Acta Scientiarum Agronomy, 43 (1), 1-15.
Moher, D., Liberati, A., Tetzlaff, J. & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PloS Med, 6 (7), 2-9.
Norasma, C. Y. N., Abu Sari, M. Y., Fadzilah, M. A., Ismail, M. R., Omar, M. H., Zulkamari, B., Hassim, Y. M. M. & Tarmidi, Z. (2018). Rice crop monitoring using multirotor UAV and RGB digital camera at early stage of growth. Earth Environmental Science, 169 (1), 24-25.
ONU. Organização das Nações Unidas. (2015). Agenda 2030. Nova York: UNDP.
Rahimi-Ajdadi, F. & Khani, M. (2021). Remote sensing-based detection of tea land losses: The case of Lahijan, Iran. Remote Sensing Applications: Society and Environment, 23 (568) 1-9.
Rose, D. C., Wheeler, R., Winter, M., Lobley, M. & Chivers, C. A. (2021). Agriculture 4.0: Making it work for people, production, and the planet. Land Use Policy, 100 (1), 1-5.
Rovira-Mas, F., Saiz-Rubio, V. & Cuenca-Cuenca, A. (2021). Augmented Perception for Agricultural Robots Navigation. Sensors Journal, 21 (10), 11712-11727.
Saccaro Júnior, N. L. & Vieira Filho, J. E. R. (2018). Agricultura e sustentabilidade: esforços brasileiros para mitigação dos problemas climáticos. Brasília: IPEA.
Salgado, T. P. & Kuva, M. A. (2019). Levantamento de problemas fitossanitários e tomada de decisão. Jaboticabal: Universidade Estadual Paulista.
Traversari, S., Cacini, S., Galieni, A., Nesi, B., Nicastro, N. & Pane, C. (2021). Precision Agriculture Digital Technologies for Sustainable Fungal Disease Management of Ornamental Plants. Sustainability, 13 (3707), 1-22.
Safanelli, J. L., Demattê, J. A. M., Chabrillat, S., Poppiel, R. R., Rizzo, R., Dotto, A. C., Silvero, N. E. Q., Mendes, W. S., Bonfatti, B. R., Ruiz, L. F. C., Caten, A. & Dalmolin, R. S. D. (2021). Leveraging the application of Earth observation data for mapping cropland soils in Brazil. Geoderma, 396 (15), 1-13.
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