Proceedings
Authors
| Filter results4 paper(s) found. |
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1. Assembly of an Ultrasound Sensors System for Mapping of Sugar Cane HeightIn Precision Agriculture, the use of sensors provides faster data collection on plant, soil, and climate, allowing collecting larger sample sets with better information quality. The objective of this study was the development of a system for plant height measurement in order to mapping of sugar cane crop, so that regions with plant growth variation and grow failures could be identified... A.H. Garcia, F.H. Rodrigues júnior, A.H. Bastos, P.S. Magalhaes, M.J. Silva |
2. Optimizing Site-Specific Adaptive Management Using A Probabilistic Framework: Evaluating Model Performance Using Historic DataAgricultural producers are tasked with managing crop yield responses to nitrogen (N) within systems that have high levels of spatial (biophysical), climatic, and price uncertainty. To date, the outcome of most variable rate application (VRA) research has focused on the spatial dimension, proposing optimal fertilizer prescription maps that can be applied year after year. However, temporally static prescriptions can result in suboptimal outcomes, particularly if they do... L.J. Rew, B.D. Maxwell, P.G. Lawrence |
3. Within Field Cotton Yield Prediction Using Temporal Satellite Imagery Combined with Deep LearningCrop yield prediction at the field scale plays a pivotal role in enhancing agricultural management, a vital component in addressing global food security challenges. Regional or county-level data, while valuable for broader agricultural planning, often lacks the precision required by farmers for effective and timely field management. The primary obstacle in utilizing satellite imagery to forecast crop yields at the field level lies in its low temporal and spatial resolutions. This study aims to... R. Karn, O. Adedeji, B.P. Ghimire, A. Abdalla, V. Sheng, G. Ritchie, W. Guo |
4. Simulating Climate Change Impacts on Cotton Yield in the Texas High PlainsCrop yield prediction enables stakeholders to plan farming practices and marketing. Crop models can predict crop yield based on cropping system and practices, soil, and other environmental factors. These models are being used for decision support in agriculture in a variety of ways. Cultivar selection, water and nutrient input optimization, planting date selection, climate change analysis and yield prediction are some of the promising area of applications of the models in field level farm management.... B. Ghimire, R. Karn, O. Adedeji, G. Ritchie, W. Guo |