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| Filter results5 paper(s) found. |
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1. Detection Of Fruit Tree Water Status In Orchards From Remote Sensing Thermal ImageryIn deciduous fruit trees there is a growing need of using water status indicators for scheduling irrigation and adopt regulated deficit irrigation (RDI) strategies taking into account spatial variability of orchards. RDI strategies have been successfully adopted for many fruit trees as a means for reducing water use and because yield and quality at harvest are not sensitive to water stress at some developmental stages. Although water status is generally monitored by measuring tree... P.J. Zarco-tejada, V. Gonzalez-dugo, J. Girona, E. Fereres, J. Bellvert |
2. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather InformationCorn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
3. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor AlgorithmNitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
4. Variable Rate Nitrogen Approach in a Potato-wheat-wheat Cropping SystemNitrogen application in agriculture is a vital process for optimal plant growth and yield outcomes. Different factors such as topography, soil properties, historical yield, and crop stress affect nitrogen (N) needs within a field. Applying variable N within a field could improve precision agriculture. Optimal N management is a system that involves applying a conservative variable base rate at or shortly after planting followed by in-season assessment and, if needed, variable rate application—with... E.A. Flint, M. Yost, B.G. Hopkins |
5. From Pocket to Pixels: Smartphone-Based Proximal Sensing for Quantitative Monitoring of Peach Canopy DynamicsMonitoring peach canopy dynamics is essential for optimizing irrigation scheduling and promoting sustainable water management in intensively managed orchards. In well-watered systems, conventional irrigation practices often overlook spatial and temporal variability in canopy size and leaf area index (LAI), potentially leading to inefficient water use. Canopy size, as reflected by LAI—the ratio of total leaf area to ground area—serves as a key biophysical indicator linked to crop transpiration... L. Katz, K. Genkin, A. Landau, Y. Ness, O. Crane, R. Golan, N. Rotbart, E. Nevo, O. Shapira, E. Fereres, O. Reichmann, A. Brook |