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| Filter results4 paper(s) found. |
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1. Categorization of Districts Based on Nonexchangeable Potassium: Generation GIS Maps and Implications in Efficient K Fertility Management in Indian AgricultureRecommendations of K fertilizer are made based on available (exchangeable + water soluble) K status only in India and other despite of substantial contribution of nonexchangeable fraction of soil K to crop K uptake. Present paper examines the information generated in the last 30 years on the status of nonexchangeable K in Indian soils, categorization of Indian soils based on exchangeable and nonexchangeable K fractions and making K recommendations. Data for both K fractions of different... C. Srinivasa rao, K. Rao, H. Magen, B. Venkateswarlu, A. Subba rao |
2. Factors Influencing the Timing of Precision Agriculture Technology Adoption in Southern U.S. Cotton ProductionTechnology innovators in cotton production adopted precision agriculture (PA) technologies soon after they became commercially available, while others adopted these technologies in later years after evaluating the success of the innovators. The timing of... D.M. Lambert, J.A. Larson, B.C. English, R.M. Rejesus, M.C. Marra, A.K. Mishra, C. Wang, P. Watcharaanantapong, R.K. Roberts, M. Velandia |
3. The Guelph Plot Analyzer: Semi-Automatic Extraction of Small-Plot Research Data from Aerial ImagerySmall-plot trials are the foundation of open-field agricultural research because they strike a balance between the control of an artificial environment and the realism of field-scale production. However, the size and scope of this research field is often limited by the ability to collect data, which is limited by access to labour. Remote sensing has long been investigated to allocate labour more efficiently, therefore enabling the rapid collection of data. Imagery collected by unmanned aerial... J. Nederend, D. Drover, B. Reiche, B. Deen, L. Lee, G.W. Taylor |
4. Next in Precision Agriculture: Detecting and Correcting Pixels with Machinery Track Line Within FarmsWith more satellites orbiting the earth, monitoring of fields using satellite data has become easier and ubiquitous. Frequent observations of a field can provide vital cues about field health and management practices. However, farm analytical statistics derived from such datasets often need modification to create practical applications. This paper focuses on the detection and removal of field machinery track line pixels to reduce their effect on satellite-based agronomic recommendation and product... G. Rathee, M. Sielenkemper |