Proceedings
Authors
| Filter results4 paper(s) found. |
|---|
1. Large-Scale Sugarcane Yield Prediction Across Regions by Integrating Multi-Source Remote Sensing and Machine LearningSugarcane (Saccharum officinarum L.) is one of the most important agro-industrial crops worldwide, playing a key role in sugar, bioethanol, and renewable energy production. Early and accurate yield estimation during the growing season is essential to support agricultural planning, resource management, and decision-making in the sugar-energy industry under increasing climate variability. However, most yield models are calibrated to single locations and struggle to transfer across regions. The primary... R. Fortes Gallego, F. Serra Burriel, M. Cabrera Dengra, C. Ferraz, A. Do Vale Dondo |
2. Recalibration of Spectral Models Using Spiking Techniques for Predicting Primary Nutrient AttributesSoil spectral libraries are an important strategy for rapid prediction of soil fertility atributes in digital agriculture projects. However, their predictive performance may decline when models are applied outside the specific conditions for which they were calibrated. Even in regions with similar pedoclimatic characteristics, management practices can limit model accuracy. In this context, spiking-based recalibration has been proposed as a practical strategy to improve model performance, although... A. Ten Caten, V. Ormeño, J.A. Henriques, M.M. Reva, M.S. Silva |
3. Determinants of the Intensity of Digital Precision Technology Adoption in Brazilian FeedlotsPrecision livestock farming has gained prominence as a tool to enhance managerial control and reduce risk in intensive production systems. In the case of Brazilian beef cattle feedlots, characterized by high price volatility, tight margins, and increasing pressure for environmental performance, the adoption of digital technologies represents a relevant strategy to improve decision-making processes. Unlike studies that focus solely on binary adoption (adopt/non-adopt), understanding adoption intensity... G. , M.J. Carrer, M. , L.C. David, H.M. Souza Filho, E. Bonjour |
4. Digital Transformation and Efficiency Gains in Intensive Livestock Systems: Evidence from Brazilian FeedlotsPrecision livestock farming has emerged as central strategies to enhance productive efficiency, reduce waste, and improve the sustainability of agricultural systems. In beef cattle feedlots, digital technologies such feeding automation sensors is particularly relevant. The technology reduces feed waste, improves the planning of input purchases and cost control, and reduces the need for manual labor for weighing and distributing feed, allowing the team to focus on strategic activities. In the Brazilian... L.C. David, M.J. Carrer, M. , H.M. Souza Filho |