Proceedings
Authors
| Filter results3 paper(s) found. |
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1. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather InformationCorn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
2. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor AlgorithmNitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
3. Development and Field Validation of a Scalable UAV-Based Framework for Automated Cattle Counting and Herd Management in Extensive Production SystemsBrazil holds the largest commercial cattle herd in the world, with more than 230 million head, representing approximately 20% of the global population. In this context, technologies capable of optimizing herd monitoring are strategic for increasing production efficiency, reducing operational costs, and promoting sustainability in livestock systems. Among these technologies, computer vision–based systems have emerged as a promising alternative for automated animal detection and counting in... F. H. S. Sousa , T. S. Maciel, M. M. Dos Reis, R.D. Santos, A. M. Santos, A. M. S. De Souza, A. K. F. Veras, G. G. Ferreira, M. P. M. Nunes, M. C. R. Seruffo, L. C. C. Daher, A. G.m. Silva |