Analysis of the Use of Mobile Application to Advance Agricultural Traceability
Resumo
Context: Nova Aliança has been industrializing the production of grapes by 410 families of winegrowers in Serra Gaúcha, since 2011. Grapes, the basis for beverages, are traced from the producer to the industry. Problem: In Brazil, traceability of plant products is a requirement of the market and became mandatory with Joint Normative Instruction ANVISA/SDA No. 2 of 07/02/2018, aiming at monitoring pesticide residues. However, little is known about the potential of digital tools for agricultural traceability. Solution: This article presents results of the transformation of physical documents to digital of the production areas and the use of harvest lots to improve the tracking of fruit loads, through a mobile application, developed under Design Science Research. IS Theory: It deals with challenges of Information Systems applied to Agriculture, under the Design Theory and Design Science paradigm. Method: The method is characterized by observational, analytical, and exploratory technological research, operationalized by Design Science Research, with initial evaluation of the artifact via action research in this real context of use and quantitative analysis of the results. Summary of Results: The mobile application was used by 127 families, representing 30.97% in the 20/21 harvest. It replaced the records in physical documents completely, made it possible to improve the traceability of production in 20 million kilograms of grapes and minimized problems regarding cargo compliance. Contributions and Impacts in the IS Area: This solution has been widely used by farmers and the results point to improved traceability and reinforce viability for agriculture.
Palavras-chave:
Agricultural Traceability, Agriculture 4.0, Mobile Application, Design Science Research
Referências
Brasil. 2018. Ministerio da Saúde e Agencia Nacional de Vigilância Sanitária - Instrução Normativa Conjunta ANVISA/SDA No. 2 de 07/02/2018. Retrieved May 12, 2022 from [link].
Fabiana C. V. Leonelli and José C. Toledo. 2006. Rastreabilidade em cadeias agroindustriais: conceitos e aplicações. Retrieved May 12, 2022 from [link].
L. M. Abenavoli, F. Cuzzupoli, V. Chiaravalloti, and A. R. Proto. 2016. Traceability system of olive oil: A case study based on the performance of a new software cloud. Agronomy Research 14, 4 (2016), 1247-1256. [link]
Julierme Z. Barbosa, Stephen A. Prior, Guilherme Q. Pedreira, Antonio C. V. Motta, Giovana C. Poggere, and Gabriel D. Goularte. 2020. Global trends in apps for agriculture. Multi-Science J. 3, 1 (2020), 16-20. https://doi.org/10.33837/msj.v3i1.1095
Antônio M. Buainain, Pedro Cavalcante, and Letícia Consoline. 2021. Estado atual da agricultura digital no Brasil: inclusão dos agricultores familiares e pequenos produtores rurais. Retrieved May 12, 2022 from https://hdl.handle.net/11362/46958
Aline Dresch, Daniel P. Lacerda, and José A. V. A. Junior. 2015. Design Science Research: Método de Pesquisa para Avanço da Ciência e Tecnologia. Bookman. Rio Grande do Sul, Brasil.
Gilson A. Helfer, Adilson B. da Costa, Rodrigo S. Bavaresco, and Jorge L. V. Barbosa. 2021. Tellus-Onto: uma ontologia para classificação e inferência de solos na agricultura de precisão. In XVII Brazilian Symposium on Information Systems (SBSI 2021). Association for Computing Machinery, New York, NY, USA, Article 13, 1–7. https://doi.org/10.1145/3466933.3466946
Rose D. Christian and Chilvers Jason. 2018. Agriculture 4.0: Broadening Responsible Innovation in an Era of Smart Farming. Frontiers in Sustainable Food Systems 2, (21 December 2018), 1-7. https://doi.org/10.3389/fsufs.2018.00087
Per Frankelius, Charlotte Norrman, and Knut Johansen. 2019. Agricultural Innovation and the Role of Institutions: Lessons from the Game of Drones. J. of Agricultural and Environmental Ethics 32, (2019) 681-707. https://doi.org/10.1007/s10806-017-9703-6
Nikola M. Trendov, Samuel Varas, and Meng Zeng. 2019. Digital Technologies in Agriculture and Rural Areas. Retrieved May 12, 2022 from https://www.fao.org/3/ca4887en/ca4887en.pdf
Sara O. Araújo, Ricardo S. Peres, José Barata, Fernando Lidon, and José C. Ramalho. 2021. Characterising the Agriculture 4.0 Landscape: Emerging Trends, Challenges and Opportunities. Agronomy 11, 4 (2021), 667. https://doi.org/10.3390/agronomy11040667
Luciana A. S. Romani, Gabriel Magalhães, Martha D. Bambini, and Silvio R. M. Evangelista. 2015. Improving digital ecosystems for agriculture: Users participation in the design of a mobile app for agrometeorological monitoring. In Proceedings of the 7th International ACM Conference on Management of Computational and CollEctive Intelligence in Digital EcoSystems (MEDES 2015). ACM, New York, NY, 234–241. https://doi.org/10.1145/2857218.2857270
Rafael Simionato, José R. T. Neto, Carla J. dos Santos, Bruno S. Ribeiro, Fernando C. B. de Araújo, Antonio R. de Paula, Pedro A. de L. Oliveira, Paulo S. Fernandes, and Jin H. Yi. 2020. Survey on connectivity and cloud computing technologies: State-ofthe-art applied to Agriculture 4.0. Revista Ciência Agronômica 51, (2020), 1–19. https://doi.org/10.5935/1806-6690.20200085
Jesús M. Talavera, Luis E. Tobón, Jairo A. Gómez, María A. Culman, Juan M. Aranda, Diana T. Parra, Luis A. Quiroz, Adolfo Hoyos, Luis E. Garreta. 2017. Review of IoT applications in agro-industrial and environmental fields. Computers and Electronics in Agriculture 142, Part A (November 2017), 283-297. https://doi.org/10.1016/j.compag.2017.09.015
Konstantinos Ioannou, Dimitris Karampatzakis, Petros Amanatidis, Vasileios Aggelopoulos, and Ilias Karmiris. 2021. Low-cost automatic weather stations in the internet of things. Information 12, 4 (2021), 146. https://doi.org/10.3390/info12040146
Gift Bonire and Abiodun Gbenga-Ilori. 2021. Towards artificial intelligence-based reduction of greenhouse gas emissions in the telecommunications industry. Scientific African 12, (July 2021), e00823. https://doi.org/10.1016/j.sciaf.2021.e00823
J. Daniel F. Selvaraj, P. Mano Paul, and I. Diana J. Jingle. 2019. Automatic Wireless Water Management System (AWWMS) for Smart Vineyard Irrigation using IoT Technology. International Journal of Oceans and Oceanography 13, 1 (2019), 211–218.
Fernanda de P. B. Furlaneto and Leandro M. Manzano. 2010. Agricultura de precisão e a rastreabilidade de produtos agrícolas. Retrieved May 12, 2022 from http://www.infobibos.com/artigos/2010_2/agriculturaprecisao/index.htm
Suporn Pongnumkul, Pimwadee Chaovalit, and Navaporn Surasvadi. 2015. Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research. Journal of Sensors 2015, Article ID 195308 (2015), 18. https://doi.org/10.1155/2015/195308
Francesco Nutini, Roberto Confalonieri, Alberto Crema, Ermes Movedib, Livia Palearib, Dimitris Stavrakoudisc, and Mirco Boschettia. 2018. An operational workflow to assess rice nutritional status based on satellite imagery and smartphone apps. Computers and Electronics in Agriculture 154, (November 2018), 80–92. https://doi.org/10.1016/j.compag.2018.08.008
Josman P. Pérez-Expósito, Tiago M. Fernández-Caramés, Paula Fraga-Lamas, and Luis Castedo. 2017. An IoT monitoring system for precision viticulture. In Proceedings 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), (2017), 662–669. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.104
Arturo Aquino, Borja Millan, Daniel Gaston, María-Paz Diago, and Javier Tardaguila. 2015. vitisFlower®: Development and testing of a novel android-smartphone application for assessing the number of grapevine flowers per inflorescence using artificial vision techniques. Sensors 15, 9 (2015), 21204–21218. https://doi.org/10.3390/s150921204
Lisa M. Given, Alain Deloire, Wade Kelly, and Philip Paschke. 2017. User-engaged app development: Building better apps for the vineyard. In Proceedings of the Association for Information Science and Technology 54, 1 (2017), 685–686. https://doi.org/10.1002/pra2.2017.14505401116
Nicholas J. Car, Evan W. Christen, John W. Hornbuckle, and Graham A. Moore. 2012. Using a mobile phone SMS for irrigation scheduling in Australia - Farmers’ participation and utility evaluation. Computers and Electronics in Agriculture 84, (2012), 132–143. https://doi.org/10.1016/j.compag.2012.03.003
Umberto A. Camargo, Jorge Tonietto, and Alexandre Hoffmann. 2011. Progressos na viticultura brasileira. Revista Brasileira de Fruticultura 33 (spe1), (October 2011), 144-149. https://doi.org/10.1590/s0100-29452011000500017
José F. da S. Protas, Umberto A. Camargo, and Loiva M. R. de Melo. 2002. A viticultura brasileira: realidade e perspectivas. Retrieved May 12, 2022 from [link].
Loiva M. R. de Melo and Carlos A. E. Machado. 2002. Cadastro Vitícola do Rio Grande do Sul: 2013 a 2015. Retrieved May 12, 2022 from https://ainfo.cnptia.embrapa.br/digital/bitstream/item/176223/1/ebookA4-5.pdf
Andrei Cechin. 2014. Cooperativas brasileiras nos mercados agroalimentares contemporâneos: limites e perspectivas. Retrieved May 27, 2022 from [link].
Hongmei Gao, Zhida Wang, and Liu Yuchuan. 2019. Application of Intelligent Traceability Management System in Agriculture - Take Aodong Fruit and Vegetable Planting Cooperative as an Example. Journal of Physics: Conference Series 1302, 2 (2019), 022046. https://doi.org/10.1088/1742-6596/1302/2/022046
Cheng Xu, Kai Chen, Min Zuo, Hongzhe Liu, and Yanan Wu. 2021. Urban Fruit Quality Traceability Model Based on Smart Contract for Internet of Things. Wireless Communications and Mobile Computing 2021, Article ID 9369074 (August 2021), 1-10. https://doi.org/10.1155/2021/9369074
Leonardo Reffatti, Guilherme G. de Oliveira, and Marília Shibata. 2021. Fruit traceability via mobile application. Comunicata Scientiae 12, (October 2021), e3483. https://doi.org/10.14295/cs.v12.3483
Fabiana C. V. Leonelli and José C. Toledo. 2006. Rastreabilidade em cadeias agroindustriais: conceitos e aplicações. Retrieved May 12, 2022 from [link].
L. M. Abenavoli, F. Cuzzupoli, V. Chiaravalloti, and A. R. Proto. 2016. Traceability system of olive oil: A case study based on the performance of a new software cloud. Agronomy Research 14, 4 (2016), 1247-1256. [link]
Julierme Z. Barbosa, Stephen A. Prior, Guilherme Q. Pedreira, Antonio C. V. Motta, Giovana C. Poggere, and Gabriel D. Goularte. 2020. Global trends in apps for agriculture. Multi-Science J. 3, 1 (2020), 16-20. https://doi.org/10.33837/msj.v3i1.1095
Antônio M. Buainain, Pedro Cavalcante, and Letícia Consoline. 2021. Estado atual da agricultura digital no Brasil: inclusão dos agricultores familiares e pequenos produtores rurais. Retrieved May 12, 2022 from https://hdl.handle.net/11362/46958
Aline Dresch, Daniel P. Lacerda, and José A. V. A. Junior. 2015. Design Science Research: Método de Pesquisa para Avanço da Ciência e Tecnologia. Bookman. Rio Grande do Sul, Brasil.
Gilson A. Helfer, Adilson B. da Costa, Rodrigo S. Bavaresco, and Jorge L. V. Barbosa. 2021. Tellus-Onto: uma ontologia para classificação e inferência de solos na agricultura de precisão. In XVII Brazilian Symposium on Information Systems (SBSI 2021). Association for Computing Machinery, New York, NY, USA, Article 13, 1–7. https://doi.org/10.1145/3466933.3466946
Rose D. Christian and Chilvers Jason. 2018. Agriculture 4.0: Broadening Responsible Innovation in an Era of Smart Farming. Frontiers in Sustainable Food Systems 2, (21 December 2018), 1-7. https://doi.org/10.3389/fsufs.2018.00087
Per Frankelius, Charlotte Norrman, and Knut Johansen. 2019. Agricultural Innovation and the Role of Institutions: Lessons from the Game of Drones. J. of Agricultural and Environmental Ethics 32, (2019) 681-707. https://doi.org/10.1007/s10806-017-9703-6
Nikola M. Trendov, Samuel Varas, and Meng Zeng. 2019. Digital Technologies in Agriculture and Rural Areas. Retrieved May 12, 2022 from https://www.fao.org/3/ca4887en/ca4887en.pdf
Sara O. Araújo, Ricardo S. Peres, José Barata, Fernando Lidon, and José C. Ramalho. 2021. Characterising the Agriculture 4.0 Landscape: Emerging Trends, Challenges and Opportunities. Agronomy 11, 4 (2021), 667. https://doi.org/10.3390/agronomy11040667
Luciana A. S. Romani, Gabriel Magalhães, Martha D. Bambini, and Silvio R. M. Evangelista. 2015. Improving digital ecosystems for agriculture: Users participation in the design of a mobile app for agrometeorological monitoring. In Proceedings of the 7th International ACM Conference on Management of Computational and CollEctive Intelligence in Digital EcoSystems (MEDES 2015). ACM, New York, NY, 234–241. https://doi.org/10.1145/2857218.2857270
Rafael Simionato, José R. T. Neto, Carla J. dos Santos, Bruno S. Ribeiro, Fernando C. B. de Araújo, Antonio R. de Paula, Pedro A. de L. Oliveira, Paulo S. Fernandes, and Jin H. Yi. 2020. Survey on connectivity and cloud computing technologies: State-ofthe-art applied to Agriculture 4.0. Revista Ciência Agronômica 51, (2020), 1–19. https://doi.org/10.5935/1806-6690.20200085
Jesús M. Talavera, Luis E. Tobón, Jairo A. Gómez, María A. Culman, Juan M. Aranda, Diana T. Parra, Luis A. Quiroz, Adolfo Hoyos, Luis E. Garreta. 2017. Review of IoT applications in agro-industrial and environmental fields. Computers and Electronics in Agriculture 142, Part A (November 2017), 283-297. https://doi.org/10.1016/j.compag.2017.09.015
Konstantinos Ioannou, Dimitris Karampatzakis, Petros Amanatidis, Vasileios Aggelopoulos, and Ilias Karmiris. 2021. Low-cost automatic weather stations in the internet of things. Information 12, 4 (2021), 146. https://doi.org/10.3390/info12040146
Gift Bonire and Abiodun Gbenga-Ilori. 2021. Towards artificial intelligence-based reduction of greenhouse gas emissions in the telecommunications industry. Scientific African 12, (July 2021), e00823. https://doi.org/10.1016/j.sciaf.2021.e00823
J. Daniel F. Selvaraj, P. Mano Paul, and I. Diana J. Jingle. 2019. Automatic Wireless Water Management System (AWWMS) for Smart Vineyard Irrigation using IoT Technology. International Journal of Oceans and Oceanography 13, 1 (2019), 211–218.
Fernanda de P. B. Furlaneto and Leandro M. Manzano. 2010. Agricultura de precisão e a rastreabilidade de produtos agrícolas. Retrieved May 12, 2022 from http://www.infobibos.com/artigos/2010_2/agriculturaprecisao/index.htm
Suporn Pongnumkul, Pimwadee Chaovalit, and Navaporn Surasvadi. 2015. Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research. Journal of Sensors 2015, Article ID 195308 (2015), 18. https://doi.org/10.1155/2015/195308
Francesco Nutini, Roberto Confalonieri, Alberto Crema, Ermes Movedib, Livia Palearib, Dimitris Stavrakoudisc, and Mirco Boschettia. 2018. An operational workflow to assess rice nutritional status based on satellite imagery and smartphone apps. Computers and Electronics in Agriculture 154, (November 2018), 80–92. https://doi.org/10.1016/j.compag.2018.08.008
Josman P. Pérez-Expósito, Tiago M. Fernández-Caramés, Paula Fraga-Lamas, and Luis Castedo. 2017. An IoT monitoring system for precision viticulture. In Proceedings 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), (2017), 662–669. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.104
Arturo Aquino, Borja Millan, Daniel Gaston, María-Paz Diago, and Javier Tardaguila. 2015. vitisFlower®: Development and testing of a novel android-smartphone application for assessing the number of grapevine flowers per inflorescence using artificial vision techniques. Sensors 15, 9 (2015), 21204–21218. https://doi.org/10.3390/s150921204
Lisa M. Given, Alain Deloire, Wade Kelly, and Philip Paschke. 2017. User-engaged app development: Building better apps for the vineyard. In Proceedings of the Association for Information Science and Technology 54, 1 (2017), 685–686. https://doi.org/10.1002/pra2.2017.14505401116
Nicholas J. Car, Evan W. Christen, John W. Hornbuckle, and Graham A. Moore. 2012. Using a mobile phone SMS for irrigation scheduling in Australia - Farmers’ participation and utility evaluation. Computers and Electronics in Agriculture 84, (2012), 132–143. https://doi.org/10.1016/j.compag.2012.03.003
Umberto A. Camargo, Jorge Tonietto, and Alexandre Hoffmann. 2011. Progressos na viticultura brasileira. Revista Brasileira de Fruticultura 33 (spe1), (October 2011), 144-149. https://doi.org/10.1590/s0100-29452011000500017
José F. da S. Protas, Umberto A. Camargo, and Loiva M. R. de Melo. 2002. A viticultura brasileira: realidade e perspectivas. Retrieved May 12, 2022 from [link].
Loiva M. R. de Melo and Carlos A. E. Machado. 2002. Cadastro Vitícola do Rio Grande do Sul: 2013 a 2015. Retrieved May 12, 2022 from https://ainfo.cnptia.embrapa.br/digital/bitstream/item/176223/1/ebookA4-5.pdf
Andrei Cechin. 2014. Cooperativas brasileiras nos mercados agroalimentares contemporâneos: limites e perspectivas. Retrieved May 27, 2022 from [link].
Hongmei Gao, Zhida Wang, and Liu Yuchuan. 2019. Application of Intelligent Traceability Management System in Agriculture - Take Aodong Fruit and Vegetable Planting Cooperative as an Example. Journal of Physics: Conference Series 1302, 2 (2019), 022046. https://doi.org/10.1088/1742-6596/1302/2/022046
Cheng Xu, Kai Chen, Min Zuo, Hongzhe Liu, and Yanan Wu. 2021. Urban Fruit Quality Traceability Model Based on Smart Contract for Internet of Things. Wireless Communications and Mobile Computing 2021, Article ID 9369074 (August 2021), 1-10. https://doi.org/10.1155/2021/9369074
Leonardo Reffatti, Guilherme G. de Oliveira, and Marília Shibata. 2021. Fruit traceability via mobile application. Comunicata Scientiae 12, (October 2021), e3483. https://doi.org/10.14295/cs.v12.3483
Publicado
16/05/2022
Como Citar
REFFATTI, Leonardo; PORTO, Josiane Brietzke; BARBOSA, Jorge.
Analysis of the Use of Mobile Application to Advance Agricultural Traceability. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 18. , 2022, Curitiba.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
