Proceedings
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| Filter results9 paper(s) found. |
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1. Spatial and Temporal Variability of Soil Health Scores and their Relationship to Crop YieldSoil health is the continued capacity of the soil to function as a vital living ecosystem that sustains plants, animals, and humans. To assess and evaluate soil health, the Comprehensive Assessment of Soil Health (CASH) was established. In CASH, different soil health indicators are used to assign a score. These indicators are soil properties that can vary spatially and temporally. In this study, soil health scores were determined across a landscape to... E. Estrada, S. Phillips, R. Grant |
2. Precision Livestock Farming (PLF) in Laying Quail Farming: Monitoring Environmental ConditionsIn poultry farming, Precision Livestock Farming (PLF) has presented a strong positive impact, helping producers manage, monitor and control both poultry and egg production operations. Furthermore, PLF can solve problems that affect the welfare of birds and/or provide early warning of such problems, allowing producers to take action in the early stages. In this context, sensors can be used to monitor and control environmental parameters that directly affect the welfare of birds and, consequently,... D.D. Sampaio, L.P. Rodrigues, J.S. Ribeiro, A.B. Gomes |
3. Use of Textural and Spectral Data in Predictive Modeling of Sugarcane YieldSugarcane is one of the most important crops in Brazil, playing a strategic role in the production of sugar, ethanol, and bioenergy. Efficient monitoring of crop yield is essential for agricultural management and decision-making; however, conventional yield estimation methods are generally labor-intensive, destructive, and inefficient in capturing spatial variability within fields. In this context, the use of remote sensing techniques integrated with machine learning models emerges as a promising... L. Rodrigues , S. Luns, G. Rolim, T. Canata, V. Carreira |
4. Enhanced Deep Learning Framework Driven Grape Berry Temperature Estimation and 72-h Forecasting for Precision Heat Stress ManagementThe increasing frequency of extreme summer heat events poses a significant threat to grape production in the Pacific Northwest (PNW), U.S., and globally. Elevated temperatures can induce sunburn, accelerate organic acid degradation, and cause anthocyanin loss, ultimately reducing berry quality. Berry surface temperature (BST), which can exceed ambient air temperature by up to 15 °C, is a primary indicator of heat stress severity. However, BST dynamics are governed by complex, nonlinear thermodynamic... |
5. A Hybrid Non-Destructive Approach Combining Image Processing and Spectral Feature Selection for Grapevine Leaf Water Content EstimationReliable and continuous estimation of leaf water content (LWC) is essential for viticulture, as it enables assessment of spatiotemporal variability in vine water demand and supports improved irrigation management efficiency within Precision Agriculture (PA) practices. Although the gravimetric method based on fresh weight (FW) and dry weight (DW) measurements provides accurate LWC estimates, it is time-consuming, destructive, and exhibits limited scalability for large sample sizes. In contrast,... L.H. Bassoi, B.S. Costa, E.J. Ferreira, H. Oldoni, L.A. Jorge |
6. Mobile Edge AI for Detection of Grape Clusters and Disease Symptoms in VineyardsPrecision viticulture demands accessible technological solutions that enable rapid disease diagnosis and production monitoring directly in the field. In real-world production contexts, dependence on cloud connectivity, external servers, or specialized hardware limits the adoption of computer vision tools by small and medium-sized farmers. In this context, this work presents a solution based on artificial intelligence embedded in a mobile application for the detection of grape bunches and leaves... E.M. Da Silveira, F.I. Nogueira, S.D. Camargo, A. Freire Campos, J. Valiati, E.F. Leite |
7. Producing Ordinary Kriging Interpolated Maps for Biomass Observation Through Values Captured with NDVI and NDRE Imagery.Geostatistics is a well-established method in the scientific community for aiding decision-making in situations with spatial dependence. Generally, the methodology adopted for interpolating fertility maps is the use of data from soil sampling on the property, generating representative thematic maps. However, the number of samples required for this methodology can be problematic when the analysis site is a small farm or one divided into multiple plots, common scenarios in Brazilian coffee farming. Considering... H.F. Gebler, C.R. Grego, G.C. Rodrigues, A. Pereira, F. Fagundes |
8. Evaluation of Variable and Uniform Rate Prescriptions of Potassium Fertilizing for Small Plots in Family-run Coffee FarmsBrazil plays a central role in the global coffee supply as one of the primary providers for strategic international markets. As extreme weather threats, prolonged droughts, and international agricultural commodity price volatility increase, enhancing economic efficiency in input use has become fundamental for the sustainability and resilience of coffee production systems. Thus, efficiency in the use of agricultural inputs transcends economic concerns, becoming part of the broader discussion on... N. De S. Ludovico Almeida, B.S. Costa, J.L. Favarin, J.P. Molin |
9. Transforming Agronomic Tables into Continuous Sufficiency and Fertilizer-rate Functions for Digital Recommendation SystemsSoil-test interpretation tables and fertilizer recommendation tables are widely used in agronomic practice, but they typically classify results into discrete categories (e.g., very low, low, medium, and high). While this format is suitable for manual consultation, it introduces artificial “jumps” between classes and limits automation when implementing diagnostic and recommendation rules in computerized systems. In this study, we developed a two-step methodology to convert these tables... D. Fernandes Paiva, G.M. Chaer |