Proceedings
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| Filter results5 paper(s) found. |
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1. Not Possible In Real Life: Precision Agriculture’s Future In 3D Virtual WorldsImmersive 3D virtual worlds may be several years away from mainstream adoption, but thousands of scientists, educators, and visionary thinkers are already using these environments to network with colleagues, conduct research, create engaging simulations, and develop instructional models that can reach global audiences. Virtual reality offers the potential to create dynamic content that is either not possible to build in real life, or prohibitively expensive. Travel costs can be reduced by bringing... L. Phillips |
2. A Comparison of Three-Dimensional Data Acquisition Methods for Phenotyping ApplicationsCurrently Phenotyping is primarily performed using two-dimensional imaging techniques. While this yields interesting data about a plant, a lot of information is lost using regular cameras. Since a plant is three-dimensional, the use of dedicated 3D-imaging sensors provides a much more complete insight into the phenotype of the plant. Different methods for 3D-data acquisition are available, each with their inherent advantages and disadvantages. These have to be addressed depending on the particular... O. Scholz, F. Uhrmann, S. Gerth, K. Pieger, J. Claußen |
3. Using Canopy Hyperspectral Measurements to Evaluate Nitrogen Status in Different Leaf Layers of Winter WheatNitrogen (N) is one of the most important nutrient matters for crop growth and has the marked influence on the ultimate formation of yield and quality in crop production. As the most mobile nutrient constituent, N always transfers from the bottom to top leaves under N stress condition. Vertical gradient changes of leaf N concentration are a general feature in canopies of crops. Hence, it is significant to effectively acquire vertical N information for optimizing N fertilization managements.... X. Xu, Z. Li, G. Yang, X. Gu, X. Song, X. Yang, H. Feng |
4. A Passive-RFID Wireless Sensor Node for Precision AgricultureAccurate soil data is crucial for precision agriculture. While existing optical methods can correlate soil health to the gasses emitted from the field, in-soil electronic sensors enable real-time measurements of soil conditions at the effective root zone of a crop. Unfortunately, modern soil sensor systems are limited in what signals they can measure and are generally too expensive to reasonably distribute the sensors in the density required for spatially accurate feedback. In this... P.J. Goodrich, C. Baumbauer, A.C. Arias |
5. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in ArgentinaThe lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomist... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito |