Proceedings
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| Filter results7 paper(s) found. |
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1. Innovative Optical Sensors For Diagnosis, Mapping And Real-time Management Of Row Crops: The Use Of Polyphenolics And FluorescenceForce-A’s Dualex® leaf-clips and Multiplex® proximal optical sensors give rapid and quantitative estimations of chlorophyll and polyphenolics of crops by measuring the fluorescence and absorption properties of these molecules. The in vivo and real-time assessments of these plant compounds allow us to define new indicators of crop nitrogen status, health and quality. The measurements of these indicators allow consultants and farmers to monitor the nitrogen status of row crops,... V. Martinon, , C. Duval, J. Fumery |
2. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer ResponseImproving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer |
3. Stem Characteristics and Local Environmental Variables for Assessment of Alfalfa Winter SurvivalAlfalfa (Medicago sativa L.) is considered the queen of forage due to its high yield, nutritional qualities, and capacity to sequester carbon. However, there are issues with its relatively low persistency and winter survival as compared to grass. Winter survival in alfalfa is affected by diverse factors, including the environment (e.g., snow cover, hardiness period, etc.) and management (e.g., cutting timing, manure application, etc.). Alfalfa's poor winter survival reduces the number of living... M. Saifuzzaman, V. Adamchuk, M. Leduc |
4. LoRa Flood-messaging Sensor-data TransportThe practice of precision agriculture assumes the ability to place and monitor sensors. Remote monitoring is often employed as a means of alleviating tedious manual data gathering and recording. For remote monitoring to work, there has to be some automated means of reading sensor values and transmitting them to a basestation, someplace where the data is recorded and analyzed. If the data are recorded and analyzed at the point of sensing, some means is still required to send the results to wherever... P.G. Raeth |
5. 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 |
6. Integrating Collected Field Machine Vibration Data with Machine Learning for Enhanced Precision in Agricultural OperationsIn this research, we provide an innovative combination of the Agricultural Vibration Data Acquisition Platform (avDAQ) with cutting-edge machine learning methods for data collecting from agricultural machinery. The avDAQ system, which has a strong connection to a GPS sensor, provides precise spatial information to the vibration data that has been collected, providing an in-depth explanation of the locations of the vibrations. The objective is to fully utilize avDAQ's potential to extract detailed... S. Janbazialamdari, E. Brokesh |
7. 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 |