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Ritchie, G
Torino, M.S
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Authors
Torino, M.S
Ortiz, B.V
Fulton, J.P
Balkcom, K
Karn, R
Adedeji, O
Ghimire, B.P
Abdalla, A
Sheng, V
Ritchie, G
Guo, W
Ghimire, B
Karn, R
Adedeji, O
Ritchie, G
Guo, W
Topics
Sensor Application in Managing In-season Crop Variability
Precision Agriculture and Global Food Security
Decision Support Systems
Type
Poster
Oral
Year
2012
2024
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Filter results3 paper(s) found.

1. Evaluation of Differences in Corn Biomass and Nitrogen Uptake at Various Growth Stages Using Spectral Vegetation Indices

Application of canopy sensors for nitrogen (N) fertilizer management for corn grain production in the Southeast US requires... M.S. Torino, B.V. Ortiz, J. Fulton, K. Balkcom

2. Within Field Cotton Yield Prediction Using Temporal Satellite Imagery Combined with Deep Learning

Crop yield prediction at the field scale plays a pivotal role in enhancing agricultural management, a vital component in addressing global food security challenges. Regional or county-level data, while valuable for broader agricultural planning, often lacks the precision required by farmers for effective and timely field management. The primary obstacle in utilizing satellite imagery to forecast crop yields at the field level lies in its low temporal and spatial resolutions. This study aims to... R. Karn, O. Adedeji, B.P. Ghimire, A. Abdalla, V. Sheng, G. Ritchie, W. Guo

3. Simulating Climate Change Impacts on Cotton Yield in the Texas High Plains

Crop yield prediction enables stakeholders to plan farming practices and marketing. Crop models can predict crop yield based on cropping system and practices, soil, and other environmental factors. These models are being used for decision support in agriculture in a variety of ways. Cultivar selection, water and nutrient input optimization, planting date selection, climate change analysis and yield prediction are some of the promising area of applications of the models in field level farm management.... B. Ghimire, R. Karn, O. Adedeji, G. Ritchie, W. Guo