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1. Assessment Of The Success Of Variable Rate Seeding Based On EMI MapsGood plant establishment is the critical first step in growing a crop. To achieve this, the correct seed rate must be calculate. This is done by assessing the optimum target plant population per m² and then making an estimate of any losses over winter. Losses will depend on the quality of seedbed created which is related to texture, stoniness and compaction of the soil. If there is any variation in these field characteristics then the correct seed... S. Griffin, M. Darr |
2. Proper Implementation Of Precision Agricultural Technologies For Conducting On-farm ResearchPrecision agricultural technologies provide farmers, practitioners and researchers the ability to conduct on-farm or field-scale research to refine farm management, improve long term crop production decisions, and implement site-specific management strategies. However, the limitations of these technologies must be understood to draw accurate and meaningful conclusions from such investigations. Therefore, the objective of this paper was to outline the limitations of several... J.P. Fulton, M.J. Darr, R.K. Taylor, T.P. Mcdonald |
3. Spatial Variability Of Spikelet Sterility In Temperate Rice In ChileSpikelet sterility (blanking) causes large economic losses to rice farmers in Chile. The most common varieties are susceptible to low air and water temperatures during pollen formation and flowering, which is the main responsible for the large year to year variation observed in terms of blanking and, therefore, of grain yield. The present work had for objective to study the spatial variability of spikelet sterility within two rice fields, during two consecutive seasons, and relate it to water... R.A. Ortega, D.E. Del solar, E. Acevedo |
4. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV ImageryGoss Wilt has become a common disease in corn fields in North Dakota. It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew |
5. Comparative Analysis of Light-weight Deep Learning Architectures for Soybean Yield Estimation Based on Pod Count from Proximal Sensing Data for Mobile and Embedded Vision ApplicationsCrop yield prediction is an important aspect of farming and food-production. Therefore, estimating yield is important for crop breeders, seed-companies, and farmers to make informed real-time financial decisions. In-field soybean (Glycine max L.(Merr.)) yield estimation can be of great value to plant breeders as they screen thousands of plots to identify better yielding genotypes that ultimately will strengthen national food security. Existing soybean yield estimation tools,... J.J. Mathew, P.J. Flores, J. Stenger, C. Miranda, Z. Zhang, A.K. Das |