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Fenotipagem digital integrada a modelos mistos para seleção de genótipos em trigo
(Universidade Federal de Lavras, 2026-03-28) Cunha, Renan Simões; Pádua, José Maria Villela; Zambiazzi, Scheila Roberta Guilherme; Matias, Filipe Inácio; Zambiazzi, Scheila Roberta Guilherme; Santos, Pedro Henrique Araújo Diniz
High Throughput Phenotyping (HTP), based on images acquired by unmanned aerial vehicles (UAVs), has emerged as a promising tool to complement conventional phenotyping by enabling rapid, precise, and non-destructive data collection on plant development. In wheat (Triticum aestivum L.) breeding programs, the integration of digital phenotypes with robust statistical methods may increase the efficiency of selecting superior genotypes. In this context, the objective of this study was to evaluate the potential use of digital phenotypes derived from multispectral drone imagery as auxiliary variables in selection methods for grain yield in wheat under different statistical modeling approaches. Public data from a wheat breeding experiment conducted by the North Dakota State University (NDSU) breeding program were used. The dataset comprised 106 wheat lines evaluated in a randomized complete block design during the 2021 growing season. Throughout the crop cycle, 15 UAV flights equipped with a multispectral sensor were performed, generating RGB orthomosaics, multispectral images, and digital surface models. Statistical analyses were conducted in the R environment, including the estimation of heritability, correlations between digital phenotypes and agronomic traits, and the comparison of different selection methods based on observed means, Best Linear Unbiased Estimators (BLUE), and Best Linear Unbiased Predictions (BLUP), with and without the inclusion of secondary variables derived from digital phenotyping. The results revealed high heritability for some digital phenotypes, particularly traits associated with estimated plant height and individual bands. Correlations among the different selection models ranged from 0.47 to 0.99, indicating agreement in genotype ranking. Overall, the evaluated models showed high consistency in identifying superior lines, suggesting that simpler statistical approaches may be applied without substantial loss of information in genotype selection.
A mobilização do modelo AIR no ensino do conceito de calor: tensões e potencialidades sob a ótica do professor-pesquisador
(Universidade Federal de Lavras, 2026-02-27) Lucas, Mateus Loures; Neves, Jefferson Adriano; Maciel, Antônio Marcelo Martins; Charret, Iraziet da Cunha; Balthazar, Wagner Franklin; Neves, Jefferson Adriano
Despite the broad consensus regarding the importance of Scientific Literacy, there is still a lack of guidance on how to operationalize and monitor it in initial teacher education. In light of this gap, this study investigated the implementation of the AIR Model (Aims, Ideals, Reliable Processes) in the planning, enactment, and reflection stages of a Teaching and Learning Sequence (TLS) on the evolution of the concepts of Heat. A qualitative approach was adopted, characterized as research on one’s own practice, and conducted with a first-semester Physics Teacher Education class. The objective was to analyze the tensions, challenges, and potentialities associated with mobilizing this framework to foster epistemic development in the classroom from the perspective of the teacher-researcher. The empirical findings diverged from the expectation of ideal engagement, revealing strong student resistance grounded in an Epistemology of Authority. Significant tensions were identified in the negotiation of the didactic contract, as well as barriers to the transition toward inquiry-based teaching. Nevertheless, the analysis of the Reflective Journals demonstrated that the AIR Model transcends its original function as a student assessment framework. Within the context of teacher education, the findings suggest that the framework serves as a powerful metacognitive support, promoting the epistemic emancipation of the teacher-researcher from the inertia of transmissive teaching practices and strengthening their professional identity as a mediator of school scientific culture.
Desafios da gestão escolar na implementação da política pública de ensino médio em tempo integral sob a ótica da cidadania deliberativa
(Universidade Federal de Lavras, 2026-05-29) Mello, Maísa Claudia de; Pereira, José Roberto; Carvalho, Marco Antônio de; Ferreira, Patrícia Aparecida
This dissertation investigates the conception and implementation of the Full-Time High School (Ensino Médio em Tempo Integral – EMTI) public policy in the state of Minas Gerais, focusing on the municipality of São Sebastião do Paraíso since 2017, based on the perceptions of students, teachers, and school administrators. The research problem is guided by the following question: how was this policy conceived and how has it been implemented in the local context, particularly regarding school management practices in addressing the challenges of ensuring student access, retention, and learning in high school education? The study presents the foundations and guidelines of national and state full-time education policies, examines their implementation at the municipal level, and analyzes the perceptions of the school actors involved. Methodologically, this is a qualitative case study based on semi-structured interviews conducted with administrators, teachers, and students from two state schools offering EMTI in the municipality, complemented by documentary analysis of policy regulations and guidelines. The findings reveal advances, limitations, and tensions in everyday school management, especially concerning curriculum organization, infrastructure, teacher training, and conditions for student retention. The study concludes that school management plays a central role in mediating between policy design and its practical implementation, being decisive for achieving the educational objectives of full-time high school education. This research contributes to the discussion on public educational policies and to improving the implementation of EMTI in the state education system.
Predição da força lateral em pneus inteligentes a partir de técnicas de aprendizagem de máquina
(Universidade Federal de Lavras, 2024-08-28) Souza, Rhuan Carlos Silva de; Barbosa, Bruno Henrique Groenner; Ferreira, Danton Diego; Santos, Murillo Ferreira dos; Pereira, Daniel Augusto
Intelligent tires are tires that feature sensors within their structure capable of communicating with advanced driver assistance systems for the purpose of estimating parameters and states of vehicles. This project aims to develop a model to estimate the lateral force in a intelligent tire using Machine Learning techniques, based on measured acceleration signals, which exhibit high levels of noise that impact the estimation process. To achieve this, the reconstruction of the signal is proposed through the use of the adaptive heuristic EMD (Empirical Mode Decomposition) for each tire rotation, with distinct configurations that optionally consider the application of a low-pass Butterworth filter at 400Hz. The reconstruction of the signals was applied to the acceleration signals along the x, y, and z axes corresponding to approximately one complete tire rotation (0° to 359.5°), as well as to a specific rotation interval of the tire (145.5° to 215.0°) that aligns more closely with the contact region of the tire with the ground. To evaluate each proposed configuration, Machine Learning models such as Random Forest (RF) and Gaussian Process Regression (GPR) were used to estimate the lateral force, with NRMSE (Normalized Root Mean Square Error) and the coefficient of determination r² metrics to assess the performance of each proposed learning model. The two best models obtained using RF and GPR, particularly those incorporating the signal reconstruction step and information from outside the tire-ground contact region, exhibited NRMSEs of 16.33% and 16.57%, respectively, with r² values of 0.91 and 0.90, respectively. These results highlight the models’ ability to explain the lateral force based on acceleration signals, emphasizing the significance of data collected outside the tire-ground contact region. Compared to the results of Barbosa et al. (2022), the models demonstrated robust performance, especially those integrating signal reconstruction via EMD, underscoring its potential in improving the prediction of lateral force.
Land use changes and its impacts on bird diversity and community homogenization in fragmented Atlantic Forest landscapes of Minas Gerais
(Universidade Federal de Lavras, 2026-06-25) Santos, Kassius Klay; Passamani, Marcelo; Passamani, Marcelo; Pompeu, Paulo dos Santos; Hasui, Érica; Perazzi, Paolo Ramoni; Resende, Renato de Oliveira
Land-use changes and the resulting modification of natural environments represent one of the major threats to Neotropical biodiversity, especially in highly fragmented biomes such as the Atlantic Forest. In this thesis, composed of three scientific articles, I investigate how different anthropogenic land uses - including pastures and coffee and eucalyptus monocultures - affect the taxonomic and functional diversity of bird communities in agricultural landscapes within the Atlantic Forest domain of southern Minas Gerais. The work integrates bibliographic synthesis, methodological assessment, and empirical field analysis. The first article presents a systematic review of studies published between 2001 and 2024 that examine the impacts of land use on Neotropical forest birds. The review reveals consistent patterns of decline among forest specialists, frugivores, and insectivores in areas converted to agriculture and pasturelands, as well as evidence that species richness often masks profound shifts in community composition and functional structure. The second article compares the efficiency of in person point counts and low-cost autonomous recording units for sampling birds across the studied land use types, demonstrating that the two methods are complementary and that their integration increases detection capacity, reduces sampling biases, and enhances avifaunal monitoring in heterogeneous and highly fragmented landscapes. The third and main article evaluates whether anthropogenic land uses promote biotic homogenization and functional simplification of regional bird assemblages, using native forest communities as a reference. The results reveal high beta diversity driven primarily by species turnover, strong environmental filtering in coffee plantations and eucalyptus stands - with coffee showing the greatest homogenization potential - and the maintenance of higher functional integrity in forest remnants. Taken together, the findings demonstrate that land use change selectively reorganizes bird communities, reducing functional diversity and redundancy while favoring a small set of generalist species. These shifts undermine the functional resilience of these systems and reinforce the importance of forest remnants and landscape heterogeneity for the conservation of avifauna and the ecological processes it sustains. The results presented in this thesis provides essential guidance for avian conservation planning and for the development of more sustainable agricultural practices in the highly fragmented landscapes of the Atlantic Forest.