Proceedings

Find matching any: Reset
R, P
Rudy, H
Reeks, M.C
Add filter to result:
Authors
Shanwad, U.K
Patil, M.B
H, V
B.G , M
R, P
N.L. , R
S, S
Khosla, R
Patil, V.C
Kross, A
Kaur, G
Callegari, D
Lapen, D
Sunohara, M
McNairn, H
Rudy, H
van Vliet, L
Kross, A
Kaur, G
Znoj, E
Callegari, D
Sunohara, M
McNairn, H
Lapen, D
Rudy, H
van Vliet, L
Czarnecki, J
Brooks, J.P
Reeks, M.C
Hu, J
Topics
Food Security and Precision Agriculture
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Land Improvement and Conservation Practices
Type
Poster
Year
2012
2018
2024
Home » Authors » Results

Authors

Filter results4 paper(s) found.

1. Precision Agriculture Initiative for Karnataka – A New Direction for Strengthening Farming Community

Strengthening agriculture is crucial to meet the myriad challenges of rural poverty, food security, unemployment, and sustainability of natural resources and it also needs strengthening at technical, financial and management levels. In this context... U.K. Shanwad, M.B. Patil, V. H, M. B.g , P. R, R. N.l. , S. S, R. Khosla, V.C. Patil

2. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

3. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean Yield

The ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet

4. Spatial and Temporal Variability of Soil Biological and Chemical Parameters Following the Introduction of Cover Crops into a Conventional Corn-cotton Rotational System

Methods 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