Proceedings
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| Filter results8 paper(s) found. |
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1. Affordable Multi-Rotor Remote Sensing Platform for Applications In Precision Horticulture.Satellite and aerial imaging technologies have been explored for a long time as an extremely useful source of collecting cost-effective data for agricultural applications. In spite of the availability of such technologies, very few growers are using the technology... R. Ehsani, S. Sankaran, J.M. Maja, J.C. Neto |
2. Development Of Ground-based Sensor System For Automated Agricultural Vehicle To Detect Diseases In Citrus PlantationsAn integrated USDA-funded project involving Carnegie Mellon University, University of Florida, Cornell University and John Deere is ongoing, to develop an autonomous tractors for sustainable specialty crop farming. The research teams have come together to develop an automated system for detecting plant stress, estimating yields, and reducing chemical usage through precision spraying for specialty crops. The goals of the automation process are to reduce the tractor-related labor costs, reduce... S. Sankaran, R. Ehsani, A. Mishra, C. Dima |
3. Radio Frequency Identification For Implementing Traceability In The Cotton Production In The Brazilian MidwestAccording to the International Cotton Advisory Committee - ICAC projection for the fiber in cotton production for the crop year 2012/2013 is expected to reach an amount of 15.19 million tons , according to a forecast released in August 2012 . In the Brazilian context , according to the Ministry of Agriculture, Livestock and Supply of Brazil cotton cultivation in Brazil has grown especially in the Midwest . In particular , exports of cotton fiber increased twice in one season in 2003/2004... C. Santos, E.O. Weschter, M.A. Dota, C.E. Cugnasca |
4. Specification Of Data Dimension To Measure The Data Quality On Cotton ProductionThe management of cotton cultivation and agriculture in general, depend on quality data enabling the retrieving of useful information as an aid in decision making related to management techniques and farm management . Part of this task depends intelligible data generated through the processes that make up this segment . Creating means for enabling the classification data is the starting point for making decisions regarding any corrections or adjustments in the mass data . The heterogeneity... C. Santos, A. Hirakawa |
5. Rapid Sensing For Water Stress Detection In Foxtail Millet (Setaria Italica)In recent years, the drought conditions due to changing climate patterns have adversely affected the U.S. agriculture. The 2012 drought that damaged major crops in Midwest was one of the most severe in last 25 years. It has resulted in losses of production, revenue, livestock and jobs, and has increased food prices. Under these circumstances, farmers are focused to use the water resources carefully. The researchers are working together to develop new crop varieties resistant to water... S. Sankaran, M. Wang, P. Ellsworth, A. Cousins |
6. Unmanned Aerial System Applications In Washington State AgricultureThree applications of unmanned aerial systems (UAS) based imaging were explored in row, field, and horticultural crops at Washington State University (WSU). The applications were: to evaluate the necrosis rate in potato field crop rotation trials, to quantify the emergence rates of three winter wheat advanced yield trials, and detecting canker disease-infection in pear. The UAS equipped with green-NDVI imaging was used to acquire field aerial images. In the first application,... L. Khot, S. Sankaran, D. Johnson, A. Carter, S. Serra, S. Musacchi, T. Cummings |
7. Automated Pipeline for Research Plot Extraction and Multi-polygon Shapefile Generation for Phenotype and Precision Agriculture ApplicationsThe plant breeding community increasingly adopt remote sensing platforms like unmanned aerial vehicles (UAVs) to collect phenotype data on various crops. These platforms capture high-resolution multi-spectral (MS) image data during extensive field trials, enabling concurrent evaluation of hundreds of plots with diverse seed varieties and management practices. Currently, the plant breeders rely on manual and intricate data extraction, processing, and analysis of high-resolution imagery to draw... A. Sharda, A. Dua, W. Schapaugh, R. Hessel |
8. Rapid Assessment of Yield Using Machine Learning Models and UAV Multispectral Imagery for Soybean Breeding PlotsAdvances in precision agriculture in data collection, crop monitoring, screening, and management over the 10-15 years are revolutionizing on-farm agricultural research trials. In crop breeding plots, this approach is called "High Throughput Phenotyping", which uses innovative technology to extract phenotypic data for large populations. Remote sensing has become one of the commonly used platforms for rapid acquisition of imagery data at spatial and temporal scale. Particularly, the unmanned... A. Dua, A. Sharda, W. Schapaugh, R. Hessel, S. Rai |