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Silva, F.T.D.; Baierle, I.C.; Correa, R.G.D.F.; Sellitto, M.A.; Peres, F.A.P.; Kipper, L.M. Open Innovation in the transition to Agriculture 4.0. Encyclopedia. Available online: https://encyclopedia.pub/entry/45141 (accessed on 18 May 2024).
Silva FTD, Baierle IC, Correa RGDF, Sellitto MA, Peres FAP, Kipper LM. Open Innovation in the transition to Agriculture 4.0. Encyclopedia. Available at: https://encyclopedia.pub/entry/45141. Accessed May 18, 2024.
Silva, Francisco Tardelli Da, Ismael Cristofer Baierle, Ricardo Gonçalves De Faria Correa, Miguel Afonso Sellitto, Fernanda Araujo Pimentel Peres, Liane Mahlmann Kipper. "Open Innovation in the transition to Agriculture 4.0" Encyclopedia, https://encyclopedia.pub/entry/45141 (accessed May 18, 2024).
Silva, F.T.D., Baierle, I.C., Correa, R.G.D.F., Sellitto, M.A., Peres, F.A.P., & Kipper, L.M. (2023, June 02). Open Innovation in the transition to Agriculture 4.0. In Encyclopedia. https://encyclopedia.pub/entry/45141
Silva, Francisco Tardelli Da, et al. "Open Innovation in the transition to Agriculture 4.0." Encyclopedia. Web. 02 June, 2023.
Open Innovation in the transition to Agriculture 4.0
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This entry is adapted from the peer-reviewed paper 10.3390/su15118562

Industry 4.0 digital technologies in agribusiness will enable traditional farming systems to migrate to Agriculture 4.0. Open innovation emerges as an enabler for implementing these technologies and increased sector competitiveness.

Agriculture 4.0 agroindustry open innovation Industry 4.0

1. Background

Industrial revolutions usually include adopting new technologies that impact economic sectors, such as industries and services [1]. The main consequences of such adoptions are increased efficiency and productivity in economic activities. The associated technological changes usually convey to industries innovative transformations that result in the emergence of new technical and economic paradigms [2][3]. Innovation processes usually rely on cost-focused actions supported by opportunities for open innovation [4]. Open innovation includes business models and service innovation and aims to access, leverage, and absorb knowledge beyond the organizational boundary [5][6]. The fourth industrial revolution, or Industry 4.0, presents such features [3]. Industry 4.0 develops new structural and corporate aspects relying on digital technologies, such as artificial intelligence (AI), internet of things (IoT), cloud computing, computer vision (CV), autonomous robots (AR), Big Data, cybersecurity, augmented reality, and horizontal and vertical integrations of systems and software [7][8][9]. Several productive sectors, including agribusiness, already employ such technologies [10].
As for developing markets, the Brazilian agribusiness sector accounts for more than 26% of the gross domestic product (GDP) [11]. In recent years, the sector benefited from open innovation initiatives, mainly embracing crop and harvest productivity, loss reductions along the entire value chain, sustainability concerns [12], machine manufacturers [13], and logistics operators [14]. Even if the sector still depends on several artisanal processes [15], recent studies point to essential opportunities regarding efficiency in operations and resource-saving innovations [16][17]. An essential requirement for enhancing the economic results in modern agribusiness is disseminating open innovation findings. Open innovation implies adopting new technologies to boost agribusiness productivity, strongly contributing to affording future food requirements for an increasing global population [14]. Besides minimizing costs and losses, technological innovations supported by advanced electronics and information systems can help improve food quality and safety, reducing inequality in food availability, mainly in developing economies [18]. In short, Industry 4.0 technologies can trigger a massive migration process from traditional rural activity to the so-called Agriculture 4.0 [19]. Agribusiness can increase results by managing strategy, innovation, operations, and other competitive priorities [20]. Other studies consider the impact of innovation initiatives in other competitive criteria, such as cost, quality, and dependability, not only in enhancing business throughput [21][22]. Implementing open innovation through Industry 4.0 digital technologies should boost the migration from the traditional system to Agriculture 4.0, which may, even in the short term, expand the sector’s competitiveness.

2. Industry 4.0 and Digital Technologies

Digital technologies can drive economic and social development by including mechanisms from digital transformation processes already implemented in other industries, such as the automotive [23]. Digital transformation processes are continuous and dynamic and depend on digital strategies to achieve and maintain a proactive relationship between emerging technologies with the industrial processes and society [24]. Such an imbricated scenario develops upon Industry 4.0, which brings significant advances to the industry through disruptive applications of the digital technology [25]. Industry 4.0 primarily employs digital technologies, providing more efficient operations and supporting decision-making processes [26]. Usual implementations of Industry 4.0 comprise sixteen leading technologies, as presented in Table 1 [19].
Table 1. Industry 4.0 Digital Technologies.
Technologies Contributions
Big data analytics Can handle and process large volumes of structured or unstructured data [27].
Smart sensors They can generate and receive data and information, increasing the processes’ efficiency, flexibility, and security, and can cover up to four dimensions [28].
Cloud computing It presents on-demand internet access to computer resources, data storage, network resources, development tools, and other functions [29].
System Integration It allows the connection of different subsystems to a single system, integrating various Information Technology systems, services, and software, allowing them to work together [30].
Cyber–physical systems Systems that relate computing, communication, and control through networks and physical processes, through which it is possible to perform simulations, tests, and wear prediction [31].
Autonomous and collaborative robots Seek to achieve automation with flexibility and efficiency, allowing autonomous robots to act collaboratively [32].
Internet of things It comprises the network of physical objects joined with sensors, software, and other technologies to connect and exchange data with devices and systems connected to the internet [33][34].
Mobile systems and devices Comprise diverse sets of mobile devices and systems [35].
Artificial intelligence Artificial intelligence enables the enhanced use of machines and computers, reproducing human intelligence to act on relevant problems and make decisions [36].
Digitalization and virtualization Digitalization refers to the interaction between physical and computational systems, consisting of the virtualization of structural elements, which can reflect the reality aiming at the integration of technical and business layers of the enterprise [37].
Machine-to-machine communication Machine-to-machine communication allows connection through sensors and actuators, connecting machines efficiently, over considerable distances, and flexibly, with high safety, robustness, and availability [38].
Simulation Adopting digital simulation systems allows the early identification of problems in the processes, allowing the search for resolution before application [39].
Industrial internet This technology requires other technologies, such as cloud computing, networking, and big data, emphasizing the interconnection and collaboration between systems, devices, and people in the industrial environment, leading to lower costs and higher productivity [40][41].
Additive manufacturing It deals with emerging manufacturing based on 3D model data, producing parts on demand and according to need [42].
Cybersecurity Facilitates digital transformation through local protection and data security actions [43].
Augmented and virtual reality They are powerful tools capable of dealing with learning and training issues, achieving more efficient, interactive, and participatory responses [44].

3. Agriculture 4.0

In the past, the now-called Agriculture 1.0 era employed simple tools and animal traction, requiring manual labor and achieving low productivity. After industrial development, agriculture activities introduced new production strategies [45], such as Agriculture 2.0, which employed machinery and chemicals, increasing crop productivity and efficiency [46]. The development of the first computer programs created alternatives to improve production and agro-industrial systems [45]. One of them was the global positioning system (GPS), used until today to assist in satellite management, establishing the so-called Agriculture 3.0 era [43]. With the emergence of Industry 4.0, digital technologies came into agriculture, marking a new technological frontier [47] and incorporating open innovation into agribusiness, giving rise to the so-called Agriculture 4.0 era. Agriculture 4.0, or precision agriculture, is a logical development of existing food production systems [48], employing remote sensing strategies and embedded technologies to manage and control the overall systemic performance [49].
Agriculture 4.0 employs the Internet of Things and Big Data tools to manage agribusiness, relating precision farming solutions (sensors, artificial intelligence, robots, drones) with Smart Farming, which uses tools, such as management software, analytics, and cloud system, in the search for the development of agricultural processes and techniques [50]. Digital technologies optimize the use of inputs, reduce labor costs, improve the quality of products and services, reduce environmental impacts, and collect a large volume of data to support decision-making processes [51]. In short, Agriculture 4.0 poses challenges in moving from experience-based agriculture to the so-called smart agriculture. Innovative solutions and open innovation actions were essential in the transition to Agriculture 4.0 [52][53].

4. Open Innovation and Agriculture 4.0

Open innovation is a methodological concept for developing environments with technological characteristics, encompassing the possibility of inserting new procedures and processes as new technologies enter the market. When applied, open innovation usually conveys economic local development [54] by transformative changes that influence the business [55]. Open innovation local systems typically rely on the interaction between innovation and technology [55], with the primary role of transfer of knowledge transferences and innovation diffusion. Open innovation is a distributed process involving knowledge flows within and across organizational boundaries [56].
Open innovation requires access to knowledge, depending on information flows, which can occur in two directions, from outside to inside and from inside to outside a company [53]. The outside inflow refers to adopting innovative processes from external systems. The inside outflow allows information generated within organizations to be used by other players, such as proprietary technologies and royalty payments [57]. Open innovation facilitates access to external partners, experiences, and knowledge, allowing, at the same time, to replace obsolete processes, improve existing systems, and avoid losses [58].
Adopting innovative processes to boost competitiveness in agriculture requires industrialization and digital technologies [14] provided by open innovation initiatives [59]. More competitiveness is essential to achieve higher productivity and increase the global food offer [60][61]. In this perspective, many companies and governments estimulate technological development to improve agriculture efficiency, aiming at rapid industrialization and innovation implementations in the agribusiness [62]. Business companies achieve several benefits from using digital technologies to minimize errors and ensure a higher quality of products [63]. The increase in competitiveness also gains prominence, especially with automation, since it can lead to increased productivity and, at the same time, reduce costs [60][64].

References

  1. Rymarczyk, J. Technologies, opportunities and challenges of the industrial revolution 4.0: Theoretical considerations. Entrep. Bus. Econ. Rev. 2020, 8, 185–198.
  2. Drath, R.; Horch, A. Industrie 4.0: Hit or Hype? . Ind. Electron. Mag. IEEE 2014, 8, 56–58.
  3. Gauss, L.; Lacerda, D.; Sellitto, M. Module-based machinery design: A method to support the design of modular machine families for reconfigurable manufacturing systems. Int. J. Adv. Manuf. Technol. 2019, 102, 3911–3936.
  4. Perez, C. Technological revolutions and techno-economic paradigms. Camb. J. Econ. 2010, 34, 185–202.
  5. West, J.; Salter, A.; Vanhaverbeke, W.; Chesbrough, H. Open Innovation: The Next Decade. Res. Policy 2014, 43, 805–811.
  6. Chesbrough, H.W. Open Innovation from Technology. Harv. Bus. Sch. Press 2016, 1, 2–3.
  7. Rizvi, A.T.; Haleem, A.; Bahl, S.; Javaid, M. Artificial Intelligence (AI) and Its Applications in Indian Manufacturing: A Review. In Proceedings of the International Conference on Recent Advances in Mechanical Engineering Research and Development (ICRAMERD 2020), Bhubaneswar, India, 24–26 July 2020; Volume 52, pp. 825–835.
  8. Kumar, A.; Mangla, S.; Kumar, P. Barriers for Adoption of Industry 4.0 in Sustainable Food Supply Chain: A Circular Economy Perspective. Int. J. Product. Perform. Manag. 2022; ahead-of-print.
  9. Baierle, I.; Sellitto, M.; Frozza, R.; Schaefer, J.; Habekost, A. An Artificial Intelligence and Knowledge-Based System to Support the Decision-Making Process in Sales. S. Afr. J. Ind. Eng. 2019, 30, 17–25.
  10. Yadav, V.; Singh, A.; Raut, R.; Mangla, S.; Luthra, S.; Kumar, A. Exploring the application of Industry 4.0 technologies in the agricultural food supply chain: A systematic literature review. Comput. Ind. Eng. 2022, 169, 108304.
  11. Cruz, J.; Medina, G.; Júnior, J. Brazil’s Agribusiness Economic Miracle: Exploring Food Supply Chain Transformations for Promoting Win–Win Investments. Logistics 2022, 6, 23.
  12. Liu, Y.; Ma, X.; Shu, L.; Hancke, G.; Abu-Mahfouz, A. From industry 4.0 to agriculture 4.0: Current status, enabling technologies, and research challenges. IEEE Trans. Ind. Inform. 2020, 17, 4322–4334.
  13. Baierle, I.; Silva, F.; Correa, R.; Schaefer, J.; Costa, M.; Benitez, G.; Nara, E. Competitiveness of Food Industry in the Era of Digital Transformation towards Agriculture 4.0. Sustainability 2022, 14, 11779.
  14. Sellitto, M.A.; Borchardt, M.; Pereira, G.M.; Gomes, L.P. Environmental performance assessment of a provider of logistical services in an industrial supply chain. Theor. Found. Chem. Eng. 2012, 46, 691–703.
  15. Nuhoff-Isakhanyan, G.; Wubben, E.; Omta, O.; Pascucci, S. Network Structure in Sustainable Agro-Industrial Parks. J. Clean. Prod. 2017, 141, 1209–1220.
  16. Skoronski, E.; Oliveira, D.; Fernandes, M.; Silva, G.; Magalhães, M.; João, J. Valorization of agro-industrial by-products: Analysis of biodiesel production from porcine fat waste. J. Clean. Prod. 2016, 112, 2553–2559.
  17. Souza, J.; Alves, J. Lean-Integrated Management System: A Model for Sustainability Improvement. J. Clean. Prod. 2018, 172, 2667–2682.
  18. Pagliosa, M.; Tortorella, G.; Ferreira, J. Industry 4.0 and Lean Manufacturing: A systematic literature review and future research directions. J. Manuf. Technol. Manag. 2021, 32, 543–569.
  19. Nara, E.; Costa, M.; Baierle, I.; Schaefer, J.; Benitez, G.; Santos, L.; Benitez, L. Expected Impact of Industry 4.0 Technologies on Sustainable Development: A Study in the Context of Brazil’s Plastic Industry. Sustain. Prod. Consum. 2021, 25, 102–122.
  20. Sellitto, M.; Hermann, F. Prioritization of green practices in GSCM: Case study with companies of the peach industry. Gestão Produção 2016, 23, 871–886.
  21. González-Benito, J.; Dale, B. Supplier Quality and Reliability Assurance Practices in the Spanish Auto Components Industry: A Study of Implementation Issues. Eur. J. Purch. Supply Manag. 2001, 7, 187–196.
  22. Siluk, J.C.M.; Kipper, L.M.; Nara, E.O.B.; Neuenfeldt Júnior, A.L.; Dal Forno, A.J.; Soliman, M.; Chaves, D.M.d.S. A Performance Measurement Decision Support System Method Applied for Technology-Based Firms’ Suppliers. J. Decis. Syst. 2017, 26, 93–109.
  23. Frank, A.; Dalenogare, L.; Ayala, N. Industry 4.0 technologies: Implementation patterns in manufacturing companies. Int. J. Prod. Econ. 2019, 210, 15–26.
  24. Arora, C.; Kamat, A.; Shanker, S.; Barve, A. Integrating Agriculture and Industry 4.0 under “Agri-Food 4.0” to Analyze Suitable Technologies to Overcome Agronomical Barriers. Br. Food J. 2022, 124, 2061–2095.
  25. Tortorella, G.; Vergara, A.; Garza-Reyes, J.; Sawhney, R. Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers. Int. J. Prod. Econ. 2020, 219, 284–294.
  26. Lenart-Gansiniec, R. Organizational Learning in Industry 4.0. Probl. Zarz. ISSUES 2019, 17, 96–108.
  27. Lee, J.; Kao, H.-A.; Yang, S. Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment. Procedia CIRP 2014, 16, 3–8.
  28. Oztemel, E.; Gursev, S. Literature Review of Industry 4.0 and Related Technologies. J. Intell. Manuf. 2020, 31, 127–182.
  29. Jan, Z.; Ahamed, F.; Mayer, W.; Patel, N.; Grossmann, G.; Stumptner, M.; Kuusk, A. Artificial Intelligence for Industry 4.0: Systematic Review of Applications, Challenges, and Opportunities. Expert Syst. Appl. 2023, 216, 119456.
  30. Sanchez, M.; Exposito, E.; Aguilar, J. Industry 4.0: Survey from a System Integration Perspective. Int. J. Comput. Integr. Manuf. 2020, 33, 1017–1041.
  31. Lee, J.; Kundu, P. Integrated Cyber-Physical Systems and Industrial Metaverse for Remote Manufacturing. Manuf. Lett. 2022, 34, 12–15.
  32. Heyer, C. Human-Robot Interaction and Future Industrial Robotics Applications. In Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18–22 October 2010; pp. 4749–4754.
  33. Beier, G.; Niehoff, S.; Xue, B. More Sustainability in Industry through Industrial Internet of Things? Appl. Sci. 2018, 8, 219.
  34. Bersani, C.; Ruggiero, C.; Sacile, R.; Soussi, A.; Zero, E. Internet of Things Approaches for Monitoring and Control of Smart Greenhouses in Industry 4.0. Energies 2022, 15, 3834.
  35. Almada-Lobo, F. The Industry 4.0 Revolution and the Future of Manufacturing Execution Systems (MES). J. Innov. Manag. 2015, 3, 16–21.
  36. Lee, J.; Davari, H.; Singh, J.; Pandhare, V. Industrial Artificial Intelligence for Industry 4.0-Based Manufacturing Systems. Manuf. Lett. 2018, 18, 20–23.
  37. Borangiu, T.; Trentesaux, D.; Thomas, A.; Leitão, P.; Barata, J. Digital Transformation of Manufacturing through Cloud Services and Resource Virtualization. Comput. Ind. 2019, 108, 150–162.
  38. Weyrich, M.; Schmidt, J.; Ebert, C. Machine-to-Machine Communication. IEEE Softw. 2014, 31, 19–23.
  39. Wang, S.Y.; Wan, J.F.; Zhang, D.Q.; Li, D.; Zhang, C.H. Towards Smart Factory for Industry 4.0: A Self-Organized Multi-Agent System with Big Data Based Feedback and Coordination. Comput. Netw. 2016, 101, 158–168.
  40. Malik, P.K.; Sharma, R.; Singh, R.; Gehlot, A.; Satapathy, S.C.; Alnumay, W.S.; Pelusi, D.; Ghosh, U.; Nayak, J. Industrial Internet of Things and Its Applications in Industry 4.0: State of The Art. Comput. Commun. 2021, 166, 125–139.
  41. Li, J.-Q.; Yu, F.R.; Deng, G.; Luo, C.; Ming, Z.; Yan, Q. Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges. IEEE Commun. Surv. Tutor. 2017, 19, 1504–1526.
  42. Frazier, W.E. Metal Additive Manufacturing: A Review. J. Mater. Eng. Perform. 2014, 23, 1917–1928.
  43. Sott, M.K.; Nascimento, L.S.; Foguesatto, C.R.; Furstenau, L.B.; Faccin, K.; Zawislak, P.A.; Mellado, B.; Kong, J.D.; Bragazzi, N.L. A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure. Sensors 2021, 21, 7889.
  44. Scott, H.; Baglee, D.; O’Brien, R.W.; Potts, R. An Investigation of Acceptance and E-Readiness for the Application of Virtual Reality and Augmented Reality Technologies to Maintenance Training in the Manufacturing Industry. Int. J. Mechatron. Manuf. Syst. 2020, 13, 39–58.
  45. Silveira, F.; Lermen, F.; Amaral, F. An overview of agriculture 4.0 development: Systematic review of descriptions, technologies, barriers, advantages, and disadvantages. Comput. Electron. Agr. 2021, 198, 106405.
  46. Zhai, Z.; Martínez, J.F.; Beltran, V.; Martínez, N.L. Decision Support Systems for Agriculture 4.0: Survey and Challenges. Comput. Electron. Agric. 2020, 170, 105256.
  47. Moreira, E.E.; Alves, F.S.; Martins, M.; Ribeiro, G.; Pina, A.; Aguiam, D.E.; Sotgiu, E.; Fernandes, E.P.; Gaspar, J. Industry 4.0: Real-Time Monitoring of an Injection Molding Tool for Smart Predictive Maintenance. In Proceedings of the 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vienna, Austria, 8–11 September 2020; pp. 1205–1208.
  48. Spanaki, K.; Karafili, E.; Despoudi, S. AI Applications of Data Sharing in Agriculture 4.0: A Framework for Role-Based Data Access Control. Int. J. Inf. Manag. 2021, 59, 102350.
  49. Yandun Narvaez, F.; Reina, G.; Torres-Torriti, M.; Kantor, G.; Cheein, F.A. A Survey of Ranging and Imaging Techniques for Precision Agriculture Phenotyping. IEEE/ASME Trans. Mechatron. 2017, 22, 2428–2439.
  50. Scuderi, A.; La Via, G.; Timpanaro, G.; Sturiale, L. The Digital Applications of “Agriculture 4.0”: Strategic Opportunity for the Development of the Italian Citrus Chain. Agriculture 2022, 12, 400.
  51. Basso, B.; Antle, J. Digital agriculture to design sustainable agricultural systems. Nat. Sustain. 2020, 3, 254–256.
  52. Baierle, I.; Siluk, J.; Gerhardt, V.; Michelin, C.; Neuenfeldt, Á.; Nara, E. Worldwide innovation and technology environments: Research and future trends involving open innovation. J. Open Innov. Technol. Mark. Complex. 2021, 7, 229.
  53. Baierle, I.; Benitez, G.; Nara, E.; Schaefer, J.; Sellitto, M. Influence of Open Innovation Variables on the Competitive Edge of Small and Medium Enterprises. J. Open Innov. Technol. Mark. Complex. 2020, 6, 179.
  54. Zarelli, P.R.; Carvalho, A. de P. Analysis of Open Innovation in Innovation Habitats. Braz. J. Dev. 2021, 7, 17380–17397.
  55. Amitrano, C.; Tregua, M.; Spena, T.; Bifulco, F. On Technology in Innovation Systems and Innovation-Ecosystem Perspectives: A Cross-Linking Analysis. Sustain. 2018, 10, 744.
  56. Chesbrough, H. The future of open innovation. Res. Manag. 2017, 60, 35–38.
  57. Bogers, M.; Chesbrough, H.; Heaton, S.; Teece, D. Strategic management of open innovation: A dynamic capabilities perspective. Calif. Manag. Rev. 2019, 62, 77–94.
  58. Guertler, M.R.; Sick, N. Exploring the Enabling Effects of Project Management for SMEs in Adopting Open Innovation—A Framework for Partner Search and Selection in Open Innovation Projects. Int. J. Proj. Manag. 2021, 39, 102–114.
  59. West, J.; Bogers, M. Open innovation: Current status and research opportunities. Innovation 2017, 19, 43–50.
  60. Campos, H. The Innovation Revolution in Agriculture a Roadmap to Value Creation: A Roadmap to Value Creation; Springer Nature: Cham, Switzerland, 2021.
  61. Alcantara, I.; Schimidt, J.; Vian, C.; Belardo, G. Agriculture 4.0: Origin and Features in the World and Brazil. Quaestum 2021, 2, 1–14.
  62. Berthet, E.T.; Hickey, G.M.; Klerkx, L. Opening Design and Innovation Processes in Agriculture: Insights from Design and Management Sciences and Future Directions. Agric. Syst. 2018, 165, 111–115.
  63. Costa, E.; Martins, M.; Vendruscolo, E.; Silva, A.; Zoz, T.; Binotti, F.; Witt, T.; Seron, C. Greenhouses within the Agricultura 4.0 Interface. Rev. Cienc. Agron. 2020, 51, 1–12.
  64. Bogers, M.; Burcharth, A.; Chesbrough, H. Open innovation in Brazil: Exploring opportunities and challenges. Int. J. Innov. 2018, 7, 178–191.
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Subjects: Agricultural Economics & Policy
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Francisco Tardelli da Silva
,
Ismael Cristofer Baierle
,
Ricardo Gonçalves de Faria Correa
,
Miguel Afonso Sellitto
,
Fernanda Araujo Pimentel Peres
,
Liane Mahlmann Kipper
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