Proceedings
Authors
| Filter results4 paper(s) found. |
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1. Development and Field Validation of a Mid-Infrared Proximal Sensing System for In-Season, On-Vine Monitoring of Grape CompositionAccurate in-season monitoring of grape composition is important for precision agriculture, as it supports timely decisions on crop management and harvest scheduling. In practice, however, commonly used approaches for assessing internal quality—such as refractometry and near-infrared (NIR) spectroscopy—are often applied to harvested samples, which limits their use for truly non-destructive measurements on developing fruit in the field. We have been developing a novel mid-infrared... H. Furukawa |
2. An Integrated Water–Energy Vulnerability Index for Irrigated Agricultural RegionsThe growing interdependence between water availability and energy infrastructure has significantly increased the vulnerability of irrigated agricultural regions, particularly under conditions of climate variability, hydrological uncertainty, and seasonal demand peaks. Irrigated production systems simultaneously depend on reliable water supply and stable energy provision, making them particularly sensitive to disruptions in either domain. Although the water–energy nexus literature has advanced... T.A. Rodolfo, P.S. Schneider, M.A. Perez, F.D. Mantovan, H.R. Bressan, A.C. Reginatto |
3. Simplifying Lab Analysis for Mapping Texture and Om Content Via Sensor-based Inference: a Case Study Showing Maps of Eca and Traditional MethodsPrecision agriculture hinges on soil information at spatial resolutions that capture within-field variability, yet conventional laboratory workflows often constrain sampling density due to cost and turnaround time. In this study, we evaluated a laboratory-based sensor inference service for mapping soil organic matter (OM) and texture (clay and sand) using visible and near-infrared spectroscopy (vis-NIR) and X-ray fluorescence (XRF) spectroscopy. We further evaluated whether resulting maps are... -. -, E. Casciello, J. Pozzuto, T. Tavares, L. Da Silva, H.W. De Carvalho |
4. Automatic Detection of White Shrimp (Litopenaeus Vannamei) Feeding Activity Using Acoustic SignalsIn the cultivation of white shrimp (Litopenaeus vannamei), feeding management is one of the main challenges, accounting for approximately 40% to 60% of operational costs. Inaccurate feed management not only increases production costs but also compromises water quality, leading to environmental impacts. Shrimp produce acoustic events known as clicks, which makes it possible to use these signals as indicators of feeding activity. This study analyzes acoustic data collected over... F. Costa Filho, L. Affonso Guedes, S. Peixoto, I. Sánchez-gendriz |