Authors
| Filter results5 paper(s) found. |
|---|
1. Issues in Analysis of Soil-Landscape Effects in a Large Regional Yield Map CollectionYield maps are commonly collected by producers and precision-agriculture service providers and are accumulating in warehouse scale data-stores. A key goal in analysis of yield maps is to understand how climate interacts with soil landscapes to cause spatial and temporal variability in grain yield. However, there are many issues that limit utilization of yield map data for this purpose including: i) yield-landscape inversion between climate years,... N.R. Kitchen, K.A. Sudduth, D.B. Myers |
2. Estimating Soil Quality Indicators with Diffuse Reflectance SpectroscopyKnowledge of within-field spatial variability in soil quality indicators is important to assess the impact of site-specific management on the soil. Standard methods for measuring these properties require considerable time and expense, so sensor-based approaches would be... R.J. Kremer, N.R. Kitchen, K.A. Sudduth, D.B. Myers |
3. Estimation of Soil Profile Properties Using a VIS-NIR-EC-force ProbeCombining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. Other common soil sensors include penetrometers that measure soil strength and apparent electrical conductivity (ECa) sensors. Previous field research has related those sensor measurements... Y. Cho, K.A. Sudduth |
4. A Long-Term Precision Agriculture System Maintains ProfitabilityAfter two decades of availability of grain yield-mapping technology, long-term trends in field-scale profitability for precision agriculture (PA) systems and conservation practices can now be assessed. Field-scale profitability of a conventional or ‘business-as-usual’ system with an annual corn (Zea mays L.)-soybean (Glycine max [L.]) rotation and annual tillage was assessed for 11 years on a 36-ha field in central Missouri during 1993 to 2003. Following this, a ‘precision agriculture... M.A. Yost, N.R. Kitchen, K.A. Sudduth, S.T. Drummond, R.E. Massey |
5. Predicting Corn Emergence Uniformity with On-the-go Furrow Sensing TechnologyIntegration of proximal soil sensors into commercial row-crop planter components have allowed for a dense quantification of within-field soil spatial variability. These technologies have potential to guide real-time management decisions, such as on-the-go variable seeding rate or depth. However, little is known about the performance of these systems. Therefore, research was conducted in central Missouri, USA to determine the relationship between planter sensor metrics, and corn (Zea mays L.) ... L.S. Conway, C. Vong, N.R. Kitchen, K.A. Sudduth, S.H. Anderson |