Principais Coleções do Repositório
Submissões Recentes
Dados de pesquisa
Diário de campo Semear Digital
(2024) Caroline Mendonça Nogueira Paiva
This document presents an anonymized version of the field diary produced during the first technical visit to the Ingaí Agrotechnological District (DAT), Minas Gerais, Brazil, conducted in March 2024 as part of the Semear Digital project. The record contains observations on the territory’s socioeconomic and productive context, the dairy farming value chain, available infrastructure, connectivity conditions, technology use, and interactions with rural producers and institutional stakeholders. The field diary was part of the qualitative stage of the territorial diagnosis and supported the planning of research and intervention activities, as well as scientific publications related to the establishment and development of the Ingaí DAT. For public dissemination, names, contact details, properties, specific locations, and other information that could lead to the identification of participants were removed or generalized.
Artigo
Pathways to rural sustainability: opportunities and challenges in the creation of an agrotechnological district in Ingaí City, Brazil
(2024) Caroline Mendonça Nogueira Paiva; Derick David Quintino; Thacyo Bruno Custódio de Morais; Elisa Guimarães Cozadi; Jaqueline Severino da Costa; Paulo Henrique Montagnana Vicente Leme; José Roberto Soares Scolforo
An agrotechnological district (ATD) integrates sustainable agricultural practices and technologies, aiming to transform rural communities by stimulating socioeconomic development and addressing the UN Sustainable Development Goals. Ingaí, a dairy-producing municipality in Minas Gerais, Brazil, stands to benefit from the implementation of an ATD. This study aimed to identify the opportunities and challenges for the implementation of an ATD in the municipality, considering its socioeconomic characteristics, the level of producers’ technological adoption, connectivity infrastructure, support networks, and rural and market management. The method was based on an exploratory case study, using semi-structured group interviews for data collection, conducted in March 2024, with agricultural stakeholders. As a result, key challenges emerged: limited connectivity infrastructure; ineffective property management; rural family succession problems; barriers in accessing credit; resistance to the adoption of technologies; and dependence on the local government. Opportunities included the strengthening of support networks among the agents of rural productive activity; the promotion of technology adoption by producers; and creating training and rural extension programs. The adoption of these initiatives can stimulate Ingaí’s economic and social development, generate multiplier effects in its region of influence, and serve as a model for other initiatives in the state of Minas Gerais, the main dairy hub in the country, and one of the primary drivers of Brazilian agribusiness.
dissertação
Identificação do estádio de Maturação de frutos de café com a utilização de visão computacional
(Universidade Federal de Lavras, 2024-07-12) Fernandes, Alysson Alves; Ferreira Júnior, Luiz de Gonzaga; .; Ferreira, Danton Diego; https://orcid.org/0000-0002-4504-7721; Barbosa, Bruno Groenner; Volpato, Margarete Marin Lordelo
This work proposes and presents the results of a system based on computer vision for iden- tifying different maturation stages of coffee fruits. This identification plays a crucial role at the time of harvest, as the degree of maturation directly influences the quality of the final product. The system was developed using client-server architecture, in which a mobile application (client) is res- ponsible for capturing photos and sending them to a web application (server), where the image is processed by a Deep Learning model (Mask RCNN or YOLOv8 ). After processing, the informa- tion obtained is returned to the mobile application for user viewing. All communication was done via HTTPS protocol. In order to deal with network and asynchrony problems, on both sides of the system there is a database storing all photos and information. Results related to image processing were obtained in three different contexts: (i) for green, sugarcane, cherry and raisin/dried fruits, (ii) for green and ripe fruits, and (iii) fruit identification (counting) regardless of the stage of matu- ration. The Mask RCNN model presented the best performance when the results were compared, presenting an average APE in context (iii) of 9.61%, in context (i) the lowest APE obtained was 9.12% for the green-cane class and in the context (ii) obtaining its lowest APE for the mature class, in the amount of 8.22%. The web system was developed, with its server implemented in Python, where the best performing Deep Learning model (Mask RCNN) was integrated. The mobile appli- cation was implemented using the React Native framework, being able to send photos and receive reports from the server.
tese
Soil multifunctionality in tropical agroecosystems through agroforestry and biochar-based management
(Universidade Federal de Lavras, 2026-06-30) Olaya-Montes, Andrés; Olaya, Adriana Silva; https://orcid.org/0000-0001-6320-2644; Melo, Leônidas Carrijo Azevedo; https://orcid.org/0000-0002-4034-4209; Carneiro, Marco Aurelio Carbone; https://orcid.org/0000-0003-4349-3071; Silva, Carlos Alberto; https://orcid.org/0000-0003-4519-8930; Frazão, Leidivan Almeida; https://orcid.org/0000-0002-7180-7915; Bonilla, Germán Andrés Estrada; https://orcid.org/0000-0001-8742-5957
tSoil degradation compromises the sustainability of tropical agroecosystems by reducing the capacity of soils to sustain productivity and provide essential ecosystem services. This thesis evaluated soil multifunctionality and the provision of soil ecosystem services in two contrasting contexts: the transition from pastures to agroforestry systems in the Colombian Amazon and the use of biologically activated biochar in Andean coffee systems. In the first study, paired systems of primary forest, pasture, and cacao-based agroforestry were evaluated. Soil physical, chemical, and biological indicators, measured down to 1.0 m depth, were integrated into ecosystem service indices. Primary forest showed the highest overall functionality, whereas pastures exhibited functional simplification and lower integrated service provision. Cacaobased agroforestry systems partially restored soil multifunctionality, especially functions related to climate regulation, acidity control, and fertility, indicating their potential as a functional recovery strategy in degraded Amazonian landscapes. In the second study, conducted in acidic soils of the Andean coffee region, the effects of application rates of biologically activated coffee wood biochar were evaluated in combination with mineral fertilizer reduction and different application methods. The most consistent responses occurred in soil chemical attributes, with increases in pH, exchangeable bases, organic carbon, and available phosphorus, along with reduced aluminum saturation. These changes were partially reflected in foliar nutrition and coffee productivity. Activated biochar combined with a 25% reduction in mineral fertilization maintained or increased productivity in some treatments, whereas surface application was generally more favorable than incorporation. Overall, the results show that the restoration of soil multifunctionality in tropical agroecosystems can occur through complementary strategies at different scales. At the landscape scale, agroforestry systems contribute to recovering functions lost after forest-to-pasture conversion. At the plot scale, biologically activated biochar acts as a regenerative soil conditioner, improving soil fertility and favoring more efficient fertilizer use. Thus, this thesis demonstrates that integrated soil indicators can guide regenerative management strategies aimed at recovering ecosystem services in Colombian agricultural landscapes.
dissertação
Fazendas leiteiras com maior eficiência zootécnica e econômica tem potencial menor intensidade de emissões de gases de efeito estufa
(Universidade Federal de Lavras, 2026-05-28) Araújo, Thaynan Ferreira de; Casagrande, Daniel Rume; https://orcid.org/0000-0003-0732-6196; Caetano, Giovane da Costa; https://orcid.org/0009-0006-3114-1916; Paiva, Adenilson José; https://orcid.org/0000-0002-7256-8581
The objective of this study was to investigate the relationship between greenhouse gas (GHG) emissions, production efficiency, and the economic viability of dairy farms located in the Central-West region of Minas Gerais. The research was conducted in loco across production units with a minimum of 12 months of prior technical and managerial monitoring. Emission intensity was measured using the PecCalc (ESGpec) tool, and the emission data were crossreferenced with zootechnical indicators (daily production per cow, proportion of lactating cows, and productivity per area) and economic indicators (gross margin, net margin, and profitability). The results revealed an average emission intensity of 1.52 kg CO2e/Kg FPCM of milk. It was found that feed production and pasture management accounted for the largest share of emissions (48.2%), surpassing enteric methane (43.4%). Statistical analysis revealed a negative correlation between emissions per liter and profitability, demonstrating that technical efficiency and financial success work in tandem to mitigate emissions per liter of milk produced. However, a territorial duality was observed, wherein the intensification required to increase profitability demanded higher stocking rates, consequently leading to an increase in absolute emissions per hectare. Aligned with the guidelines of the Sustainable Rural Project – Cerrado (Projeto Rural Sustentável – Cerrado) and the ABC+ Plan (Plano ABC+), this study concludes that more efficient farms are capable of producing milk with a lower environmental impact and higher profitability. Nevertheless, additional measures, such as proper land management, remain necessary to ensure the long-term sustainability of productio