Authors
Filter results4 paper(s) found. |
---|
1. Seasonal Patterns of Vegetative Indices Over Cropping SystemsRemote sensing of reflectance in the visible and near-infrared portions of the spectrum has been used for agronomic applications for a number of years. The combination of different wavelengths into vegetative indices have proven useful for a variety of applications that range from biomass, leaf area, leaf chlorophyll, yield, crop residue, and crop damage. To help refine our understanding of vegetative indices studies were conducted on corn (Zea mays L.), soybean (Glycine max (L.) Merr.), wheat... J.L. Hatfield, J.H. Prueger |
2. Spatial Patterns of Nitrogen Response Within Corn Production FieldsCorn (Zea mays L.) yield response to nitrogen (N) application is critical to being able to develop management practices that reduce N application or improve N use efficiency. Nitrogen rate studies have been conducted within small plots; however, there have been few field scale evaluations. This study was designed to evaluate N response across 14 corn fields in central Iowa using different rates of N applied in strips across fields. These fields ranged in size from 15 to 130 ha with N... J.L. Hatfield |
3. Three Years of On-Farm Evaluation of Dynamic Variable Rate Irrigation: What Have We Learned?This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015, 2016 and 2017 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed within... V. Liakos, W. Porter, X. Liang, M. Tucker, A. Mclendon, C. Perry, G. Vellidis |
4. Management Zone Delineation for Irrigation Based on Sentinel-2 Satellite Images and Field PropertiesThis paper presents a case study of the first application of the dynamic Variable Rate Irrigation (VRI) System developed by the University of Georgia to cotton. The system consists of the EZZone management zone software, the University of Georgia Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2017 in a cotton field to evaluate the performance of the system in cotton. The field was divided into four parallel strips. All four strips... V. Liakos, G. Vellidis, L. Lacerda, W. Porter, M. Tucker, C. Cox |