Proceedings
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| Filter results2 paper(s) found. |
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1. Machine Learning Techniques for Early Identification of Nitrogen Variability in MaizeCharacterizing and managing nutrient variability has been the focus of precision agriculture research for decades. Previous research has indicated that in-situ fluorescence sensor measurements can be used as a proxy for nitrogen (N) status in plants in greenhouse conditions employing static sensor measurements. Indeed, practitioners of precision N management require determination of in-season plant N status in real-time at field scale to enable the most efficient N fertilizer... D. Mandal, R.D. Siqueira, L. Longchamps, R. Khosla |
2. High Throughput Phenotyping of the Energy Cane Crop UAV-based LiDAR, Multispectral and RGB DataEnergy cane is a hybrid of sugarcane cultivated for their high biomass and fiber instead of sugar. It is used for production of biofuels and as feedstock for animals. As a relatively new crop, accurate knowledge of biophysical parameters such as height and biomass of different genotypes are pertinent to cultivar development. Such knowledge is also crucial to manage crop health, understand response to environmental effects, optimize harvest schedules, and estimate bioenergy yield. Nonetheless,... B. Ghansah, I. Khuimphukhieo, J.L. Scott, M. Bhandari, J. Foster, J. Da silva, H. Li, M. Starek |