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1. Development Of An On-The-Spot Analyzer For Measuring Soil Chemical PropertiesProximal soil sensing (PSS) is a growing area of research and development focusing on the use of sensors to obtain information on the physical, chemical and biological attributes of soil when they are placed in contact with, or at a distance of less than 2 m, from the target. These sensor systems have been used to 1) make measurements at specific locations, 2) produce a set of measurements related to soil depth profiles, or 3) monitor changes in soil properties over time. In each... V.I. Adamchuk, N. Dhawale, F. Rene-laforest |
2. Measurement of In-field Variability for Active Seeding Depth Applications in Southeastern USProper seeding depth control is essential to optimize row-crop planter performance, and adjustment of planter settings to within field spatial variability is required to maximize crop yield potential. The objectives of this study were to characterize planting depth response to varying soil conditions within fields, and to discuss implementation of active seeding depth technologies in Southeastern US. This study was conducted in 2014 and 2015 in central Alabama for non-irrigated maize (Zea mays... A.M. Poncet, J.P. Fulton, T.P. Mcdonald, T. Knappenberger, R.W. Bridges, J. Shaw, K. Balkcom |
3. Integrated Analysis of Multilayer Proximal Soil Sensing DataData revealing spatial soil heterogeneity can be obtained in an economically feasible manner using on-the-go proximal soil sensing (PSS) platforms. Gathered georeferenced measurements demonstrate changes related to physical and chemical soil attributes across an agricultural field. However, since many PSS measurements are affected by multiple soil properties to different degrees, it is important to assess soil heterogeneity using a multilayer approach. Thus, analysis of multiple layers of geospatial... V.I. Adamchuk, N. Dhawale, A. Biswas, S. Lauzon, P. Dutilleul |
4. 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 |
5. Comparison and Validation of Different Soil Survey Techniques to Support a Precision Agricultural SystemThe data need of precision agriculture has resulted in an intensive increase in the number of modern soil survey equipment and methods available for farmers and consultants. In many cases these survey methods cannot provide accurate information under the used environmental conditions. On a 36 hectare experimental field, several methods have been compared to identify the ones which can support the PA system the best. The methods included contact and non contact soil scanning, yield mapping, high... V. Lang, G. Tóth, S. Csenki, D. Dafnaki |
6. 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 |
7. 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 |
8. Spectral Imaging Deep Learning Mapper for Precision AgricultureWith the growing variety of RGB cameras, spectral sensors, and platforms like field robots or unmanned aerial vehicles (UAV) in precision agriculture, there is a demand for straightforward utilization of collected field data. In recent years, deep learning has gained significant attention and delivered impressive results in the realm of computer vision tasks, such as semantic segmentation. These models have also found extensive applications in research related to precision agriculture and spectral... L. Thomas, B. Jakimow, A. Janz, P. Hostert, A. Lajunen |