Proceedings
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| Filter results7 paper(s) found. |
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1. Adoption and Tendencies of Precision Agriculture Technologies in the Tocantins State, BrazilAlthough precision agriculture is widely used throughout Brazilian crop production, it has not been used to increase the efficiency use of agricultural inputs. Besides, technologies available have not been... L. Bortolon, E. Borghi, A. Luchiari Junior, E.S. Bortolon, A.A. Freitas, R.Y. Inamasu, J.C. Avanzi |
2. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry FieldsWild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve crop... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan |
3. Adoption Level Of Precision Agriculture For Brazilian Farmers - 2011/12 Crop YearAlthough Precision Agriculture (PA) concepts and technologies are widespread in Brazil, its application still little used in some important crop production regions. The purpose of this study was to survey the current adoption level of PA by printed and online questionnaire. We started making a specific questionnaire to farmers and PA service companies using some technology related to PA. The questionnaires were developed based on the methodology of Whipker and Akridge (2009),... E. Borghi, A. Luchiari Junior, L. Bortolon, E.S. Bortolon, R.Y. Inamasu, A.C. Bernardi, J.C. Avanzi |
4. Canopy Temperature Mapping with a Vineyard RobotThe wine industry is a strategic sector in many countries worldwide. High revenues in the wine market typically result in higher investments in specialized equipment, so that producers can introduce disruptive technology for increasing grape production and quality. However, many European producers are approaching retirement age, and therefore the agricultural sector needs a way for attracting young farmers who can assure the smooth transition between generations; digital technology offers an opportunity... V. Saiz-rubio, M. Diago, J. Tardaguila, S. Gutierrez, F. Rovira-más, F. Alves |
5. A Architecture for GNSS-Based Autonomous Navigation in Agricultural RobotsGlobal Navigation Satellite Systems (GNSS), especially when used with real-time correction techniques such as Real-Time Kinematic (RTK), are widely employed in precision agriculture due to their ability to provide accurate absolute positioning. This capability enables georeferenced operations such as planting, selective spraying, and autonomous navigation across large agricultural areas, even in environments with few structural references. In contrast, modern robotic navigation frameworks, such... V. Fonteca, C. Guimarães, M. Monteiro, I. Azevedo, A. Da Rosa, N.K. Wagner, C. Teixeira |
6. Evaluation of Transfer Learning in Semantic Segmentation Models for Soybean SeedlingsSeed vigor evaluation is fundamental in the quality control of commercial lots, as it is directly associated with the rapid and uniform emergence of seedlings and the initial performance of crops in the field. Traditional methods, although widely used, present limitations such as long execution time, dependence on the evaluator’s experience, and subjectivity. In this context, systems based on Computer Vision emerge as promising alternatives for automating vigor assessment, as they enable... E. Freitas, J. Martins Neto, P. Dos Santos E Silva, H.F. Abud, D.G. Gomes, V.C. Secundino |
7. Prediction of Olive Productivity Using Machine Learning Associated with Aerial Multispectral and Thermal ImageryAccurate estimation of productivity in olive orchards is fundamental for agricultural planning, resource optimization, and timely decision-making. Conventional methods for assessing productivity are labor-intensive and limited in their ability to represent spatial variability at field scale. Remote sensing using unmanned aerial vehicles (UAVs) combined with machine learning techniques offers a scalable and non-destructive approach for predicting productivity at field scale. This study evaluated... M. Antônio, G. Koch, P.A. Moura, F. Silva, C.C. Santana |