Proceedings
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| Filter results6 paper(s) found. |
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1. Nitrogen Management in Lowland RiceRice is staple diet for more than fifty percent of the world population and nitrogen (N) deficiency is one of the major yields limiting constraints in most of the rice producing soils around the world. The lowland rice N recovery efficiency is <50% of applied fertilizers in most agro-ecological regions. The low N efficiency is associated with losses caused by leaching, volatilization, surface runoff, and denitrification. Hence, improving N use efficiency is crucial for higher yields, low cost... N.K. Fageria, A.B. Santos |
2. Optimum Spatial Resolution for Precision Weed ManagementThe occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the objective... R.G. Trevisan, M.T. Eitelwein, M.N. Ferraz, T.R. Tavares, J.P. Molin, D.C. Neves |
3. Use of Precision Technologies to Conduct Successful Within-field, On-farm TrialsPerforming randomized replicated trials in row crop field environments has the potential to increase crop production in environmentally sustainable ways. Successful implementation requires an understanding of implement capabilities and sources of potential systematic error, including operator error. Equipment capabilities can be thought of as a series of several critical “links in a chain,” each with implications that propagate downstream. We will... M. Stelford, A. Krmenec |
4. Predicting Secondary Soil Fertility Attributes Using XRF Sensor with Reduced Scanning Time in Samples with Different Moisture ContentTo support future in situ/on-the-go applications using X-ray fluorescence (XRF) sensors for soil mapping, this study aimed at evaluating the XRF performance for predicting organic matter (OM), base saturation (V), and exchangeable (ex-) Mg, using a reduced analysis time (e.g., 4 s) in soil samples with different moisture contents. These attributes are considered secondary for XRF prediction because they do not present emission lines in the XRF spectrum. Ninety-nine soil samples... T.R. Tavares, J.P. Molin, T.R. Da silva , H.W. De carvalho |
5. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US MidwestEffective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan |
6. Supervised Feature Selection and Clustering for Equine Activity RecognitionIn this paper we introduce a novel supervised algorithm for equine activity recognition based on accelerometer data. By combining an approach of calculating a wide variety of time-series features with a supervised feature significance test we can obtain the best suited features using just 5 labeled samples per class and without requiring any expert domain knowledge. By using a simple cluster assignment algorithm with these obtained features, we get a classification algorithm that achieves a mean... T. De waele, D. Peralta, A. Shahid, E. De poorter |