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| Filter results2 paper(s) found. |
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1. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water StressesThis paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthing... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman |
2. Machine Learning Algorithms in Detecting Long-term Effect of Climatic Factors for Alfalfa Production in KansasThe water levels of the Ogallala Aquifer are depleting so much that agricultural land returns in Kansas are expected to drop by $34.1 million by 2050. It is imperative to understand how frequent droughts and the contrasting rates of groundwater withdrawal and recharge are affected by climate shifts in Kansas. Alfalfa, the ‘Queen of Forages’, is a water demanding crop which supplies high nutritional feed for beef industry that offered Kansas producers a $500 million production value... F. Nazrul, J. Kim, S. Dey, S. Palla, D. Sihi, B. Whitaker, G. Jha |