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From seed to cup: internet of things technology in the quality coffee production chain

Grant number: 21/06968-3
Support type:Research Projects - Thematic Grants
Duration: January 01, 2022 - December 31, 2026
Field of knowledge:Agronomical Sciences - Agronomy - Soil Science
Cooperation agreement: MCTI/MC
Principal researcher:Luiz Roberto Guimarães Guilherme
Grantee:Luiz Roberto Guimarães Guilherme
Home Institution: Escola de Ciências Agrárias. Universidade Federal de Lavras (UFLA). Ministério da Educação (Brasil). Lavras , SP, Brazil
Pesquisadores principais:
André Pimenta Freire ; Antonio Chalfun Junior ; Cleiton Antônio Nunes ; Júlio Cézar Estrella ; Laurence Rodrigues do Amaral ; Luiz Henrique Andrade Correia ; Marco Aurélio Carbone Carneiro ; Matheus de Souza Gomes ; Michele Duarte de Menezes ; Sérgio Henrique Godinho Silva
Assoc. researchers: Ana Carla Marques Pinheiro ; Andrew John Margenot ; Bruno Teixeira Ribeiro ; Charith Perera ; Cynthia de Oliveira ; Emilene Zitkus de Andrade ; Erick Galani Maziero ; Líbia Diniz Santos ; Marcelo Braga Bueno Guerra ; Patrick H. Brown ; Pedro Luiz Lima Bertarini ; Rafael Serapilha Durelli ; Raphael Ricon de Oliveira ; Somsubhra Chakraborty ; Stephan Reiff-Marganiec ; Yufang Jin

Abstract

Brazil is the world's largest producer (ca. 48.8 million bags of Arabica coffee in 2020) and exporter of coffee, which is one of the most important sources of income for Brazilian economy. Currently, the coffee agribusiness encompasses about 1900 producing municipalities, 370,000 coffee growers, 1 million rural workers, and more than 8 million Brazilians who depend on the agro-industrial activity of the coffee chain. Maintaining this leadership in beans production volumes is strategic, but quality is another very important issue. The qualitative attributes perceived in the coffee beverage depend on the genetic, environmental, and technological factors involved in beans development. Environmental factors are composed of temperature, humidity, altitude, latitude, solar radiation, water, and soil. Each factor contributes individually to beverage quality, yet the coffee plant in nature will express itself according to the interactions of these factors. Because of these characteristics, coffee is essentially a terroir product, i.e., influenced directly by environmental resources and conditions. The Arabica coffee production in Brazil extends North-South, providing the formation of diverse environments. As a result of these interactions between the crop and the various environments, coffees from Brazil have an immense diversity of aromas and flavors and distinct characteristics and attributes, which allow for countless combinations and the elaboration of highly differentiated products. Thus, studying the different interactions of environmental factors is key to explain the complexity of the quality phenomenon. This project aims to investigate the use of internet of things technology to improve the production chain of coffee aiming at cup quality. The project is composed of an international interdisciplinary team with researchers from Soil and Plant Sciences, Computer Science, and Design. The research encompasses technological challenges in different stages of the coffee production chain. The first stage of the project targets remote and proximal sensing to identify/characterize soils, plants, agricultural inputs, and environmental features that interact with each other to give directions for predicting applied variables in order to supply information for better decision-making during the production, harvesting, and post-harvesting steps, which will improve the understanding of producers, consumers, and exporters on coffee quality aspects. The second stage comprises research about network and communication technologies used in the field and at different locations involved in the production chain, such as cooperative warehouses. The third stage targets research on infrastructure to receive, store, and process information using cloud computing. The fourth stage comprises research on Data Science techniques to support decision-making in different aspects of the coffee production chain. Finally, the fifth stage involves research on the design and evaluation of interactive applications used in different stages of the coffee production chain, such as dashboards with visual analytics for producers and exporters, and consumer applications to trace origin and quality characteristics, based on data collected throughout the production chain. The project's expected outcomes include technological and scientific advancements in the application of internet of things technologies to the coffee production chain. The project has significant economic and social impact, using internet technologies to improve one of the most relevant agricultural activities in Brazil. Moreover, the project will generate scientific contributions not only to coffee production research, but also to the advancement of challenges to use internet of things in the field and innovative interactive applications employing Data Science. Lastly, we understand that many outcomes of this project will be certainly applicable to many other agricultural production chains in Brazil. (AU)

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