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  <channel rdf:about="https://www.alice.cnptia.embrapa.br/alice/handle/item/197">
    <title>DSpace Coleção: Artigo em anais de congresso (CNPTIA)</title>
    <link>https://www.alice.cnptia.embrapa.br/alice/handle/item/197</link>
    <description>Artigo em anais de congresso (CNPTIA)</description>
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        <rdf:li rdf:resource="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187715" />
        <rdf:li rdf:resource="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187153" />
        <rdf:li rdf:resource="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185941" />
        <rdf:li rdf:resource="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185940" />
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    <dc:date>2026-07-05T11:23:45Z</dc:date>
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  <item rdf:about="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187715">
    <title>Environmental challenges of pastoral farming systems in tropical areas.</title>
    <link>https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187715</link>
    <description>Título: Environmental challenges of pastoral farming systems in tropical areas.
Autoria: CARVALHO, P. C. F.; BARIONI, L. G.; FREUA, M. C.; BOVAL, M.
Conteúdo: The need to increase food production has become urgent. Pastoral farming systems based on grasslands in the tropics are essential players in this scenario, considering the surface area and stakeholders they represent. Improving productivity from existing grasslands can be a way forward to produce food, because most of them still produce less than the potential primary and secondary production they could achieve if constraints to pasture and animal growth were surpassed using existing technologies. This potential production could be reached without increasing the surface area used. However, the technologies available to support this intensification process are generally based on an input approach, and are associated with increased use of natural resources and pollution. This classical anthropogenic effect has already been experienced in the temperate grasslands of developed countries, and has raised environmental concerns there. Pastoral farming systems in the tropics seemed to be following the same trend, but are currently being called upon to increase production without such side effects. Dealing with these new environmental drivers and unraveling the production vs. conservation dilemma requires pastoral farming to take a new process-oriented approach. Grassland science is responding to this environmental constraint, and is being asked to build innovative systems devoted to sustainable intensification, at a time when urgency contrasts with a seeming lack of creativity and innovation. Here we explore these issues, focusing on Brazilian pastoral farming trends. This case study is of worldwide interest because of its major place in the global market, and its impact on food security and natural resource conservation in Brazil and elsewhere.</description>
    <dc:date>2013-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187153">
    <title>Cattle weight estimation from dense point clouds.</title>
    <link>https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187153</link>
    <description>Título: Cattle weight estimation from dense point clouds.
Autoria: CASTANHEIRO, L. F.; TETILA, E. C.; FURUYA, D. E. G.; SILVA, J. P. da; BARBEDO, J. G. A.; ROMANI, L. A. S.; BOLFE, E. L.
Conteúdo: Cattle weight is essential for decision-making in precision livestock farming, directly supporting nutrition management, animal welfare, and production efficiency. Existing methods rely on close-range measurements or manual intervention, limiting scalability. This work proposes an workflow for cattle weight estimation based on point clouds derived from aerial images. RGB images acquired at low altitude were processed using Structure from Motion (SfM) techniques to generate dense point clouds. Individual animals were automatically segmented from the reconstructed 3D scene, and voxel-based volumetric features were extracted for each animal. Body weight was then estimated through linear regression models calibrated with ground truth measurements obtained from individual weighing. The proposed approach was evaluated on Nellore cattle in a feedlot environment and achieved a root mean square error (RMSE) of 8.35 kg, corresponding to an average relative error of approximately 2.29%. The results highlight the potential of UAV-based photogrammetry as a cost-effective decision support tool for digital and sustainable livestock management.</description>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185941">
    <title>Prospective analysis of the adoption of digital technologies in agriculture.</title>
    <link>https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185941</link>
    <description>Título: Prospective analysis of the adoption of digital technologies in agriculture.
Autoria: DIBBERN, T.; ROMANI, L. A. S.; EVANGELISTA, S. R. M.; MARTINS, V. A.; MASSRUHÁ, S. M. F. S.
Conteúdo: Open innovation emerges when knowledge, experience, and capabilities are distributed across various organizations, enabling innovative activities inside and outside research institutions within a collaborative system. In the agricultural sector, this phenomenon is manifested through innovation ecosystems that involve multiple stakeholders, including universities, governments, research institutes, companies, cooperatives, and financial markets. However, one of the main challenges is measuring an innovation's success, especially in the early stages of developing technology-based products. Given this context, this paper proposes a methodological model for developing indicators that measure the level of success in adopting digital technology in the field, from the initial stages of technological product development. Five stages and the results obtained in the benchmarking phase are presented.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185940">
    <title>The role of Landsat and Sentinel-2 data harmonization in monitoring agricultural dynamics on smallholder farming regions.</title>
    <link>https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185940</link>
    <description>Título: The role of Landsat and Sentinel-2 data harmonization in monitoring agricultural dynamics on smallholder farming regions.
Autoria: PARREIRAS, T. C.; BOLFE, E. L.
Conteúdo: This study explores the potential of Harmonized Landsat Sentinel-2 (HLS) data for detailed agricultural mapping in diversified farming regions of São Paulo, Brazil. Focusing on Casa Branca and Caconde, the research integrates multitemporal HLS imagery (2021–2024) to perform crop classifications at multiple levels. In Caconde, high-resolution temporal data (2–4 day revisit) enabled strong performance in distinguishing perennial crops, particularly coffee, which achieved an average sensitivity of 0.97 and specificity of 0.91. Phenological stages of coffee, such as Producing and Newly Planted, were reliably mapped, while Stumping and Skeletoning showed lower consistency. In Casa Branca, six field campaigns supported the construction of a robust training dataset across up to nine growing seasons. Integrating Landsat 9 into the HLS collection more than doubled temporal resolution over the study period, enhancing model accuracy and phenological tracking. Future work will focus on model transferability across time and space and on evaluating the relative performance of HLS versus individual Landsat and Sentinel data.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
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