Proceedings
Authors
| Filter results4 paper(s) found. |
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1. Late Season Imagery for Harvest ManagementThe overall objective of this project was to preliminarily assess the use of UAV-based thermal imagery to sense harvest-related factors. Results suggested that thermal imagery can be used to detect areas of high grain moisture content late in the harvest season. Time periods closer to physiological maturity were less likely to show significant differences in thermal imagery data. Additional research is needed to determine if moisture content trends with other measurable quantities... J. Ward, G. Roberson, R. Phillips |
2. Spatial and Temporal Variability of Soil Biological and Chemical Parameters Following the Introduction of Cover Crops into a Conventional Corn-cotton Rotational SystemMethods to characterize soil microbial diversity and abundance are labor intensive and require destructive sampling that incurs a per unit cost. There are advantages to replacing current methods with remote sensing approaches; the most obvious of which is spatially explicit representation of microbes on agricultural landscapes. Such a method will ultimately address open questions related to (1) the spatial scale of variability in soil microbial activity, and (2) the behavior of microbes in cover... J. Czarnecki, J.P. Brooks, M.C. Reeks, J. Hu |
3. A Decision-support Tool to Optimize Mid-season Corn Nitrogen Fertilizer Management from Red, Green, Blue SUAS ImagesCorn receives more nitrogen (N) fertilizer per unit area than any other row crop and optimized soil fertility management is needed to help maximize farm profitability. In Arkansas, N fertilizer for corn is delivered in two- or three-split applications. Three-split applications may provide a better match to crop needs and contribute to minimizing yield loss from N deficiency. However, the total amounts are selected based on soil texture and yield goal without accounting for early-season losses... A. Poncet, T. Bui, W. France, T. Roberts, L. Purcell, J. Kelley |
4. Predicting Soil Cation Exchange Capacity from Satellite Imagery Using Random Forest ModelsCrop yield variability is often attributed to spatial variation in soil properties. Remote sensing offers a practical approach to capture soil surface properties over large areas, enabling the development of detailed soil maps. This study aimed to predict cation exchange capacity (CEC), a key indicator of soil quality, in the agricultural fields of the Lower Mississippi Alluvial Valley using digital soil mapping techniques. A total of 15,586 soil samples were collected from agricultural fields... I. Muller, J. Czarnecki, M. Li, B.K. Smith |