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| Filter results2 paper(s) found. |
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1. Rapid Data Acquisition For In-Field Plant PhenomicsHigh throughput sensing is necessary for the rapid acquisition of plant canopy physical and physiological parameters on field scales. Simultaneous measures of these descriptive parameters will provide a clearer picture of plant response to biotic and abiotic stressors. Information obtained can assist in early identification of desired genetic traits and the degree to which they are expressed. Identifying these traits and their expression can provide higher efficiency in genetic selection... M.R. Sclemmer, K.H. Holland |
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 |