Proceedings
Authors
| Filter results5 paper(s) found. |
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1. Field-Based Evaluation of Targeted Herbicide Spraying Efficacy: A Comparison of Qualitative and Quantitative ApproachesWeed control remains one of the main challenges for maintaining agricultural productivity. In this context, selective spraying based on optical sensors and embedded vision systems emerges as a promising alternative for localized weed management, aligned with the principles of precision agriculture and sustainability. However, the adoption of these technologies on a commercial scale demands robust methods to evaluate agronomic efficacy and operational performance under real field conditions. This... R. Luiz Panini, A.R. Tamara, G.M. Franco, V.C. De Oliveira, H.R. Lemos, M. Nishikawa, P.R. Forti, M. Biagi, L.F. Dudek, M.C. Hauschild, G.N. Ruscito, M.P. Da Silva, E. Claro, Z.M. De Souza |
2. Mobile Robotic Soil Moisture Sensing and Mapping for Precision Agriculture in Small-Scale FarmingThe spatial variability of soil moisture is a key factor for efficient irrigation management and agricultural productivity, particularly in small-scale farming systems where access to precision agriculture technologies remains limited due to cost and operational complexity. This study presents the development and preliminary evaluation of a robotic sensing system for georeferenced soil moisture data acquisition, focusing on spatial mapping in small agricultural areas. The proposed system... D.H. Hall, M. Hosser, R.L. Machado, R. Galli, A.L. Machado |
3. 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 |
4. Synchronization of Machine Vision and Nozzle Spraying Systems on Boom Sprayer for Effective Management of Colorado Potato BeetleIn real-time spot application schemes of pesticides using machine vision on boom sprayers, pressure surges during target spraying may be caused by random and frequent nozzle activation and deactivation. To mitigate these surges and reduce pressure settling time, a novel technique to use a machine vision system that detects Colorado potato beetle is used not only to control pressure in boom. This proactive contorl of pressure may replace traditional pressure feedback technique which is characeterized... A. Al-mallahi, H. Maambo, T.J. Esau, I. Hassan, M. Motalab |
5. Who is the Agricultural Practitioner of the Future?An agricultural industry that continues to adopt new technologies and rely on data-driven decisions demands a unique skillset from its practitioners that goes beyond traditional agricultural training. Despite this demand, relatively few technology-focused agriculture programs are available at the post-secondary level worldwide. In 2020, Olds College of Agriculture & Technology (Alberta, Canada) created a 2-year diploma in Precision Agriculture (launched in 2020) and a 4-year Bachelor of Digital... D. Karran, B. Hoffos, F.H. Karp |