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Gochis, D
Khot, L.R
Brorsen, W
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Authors
Khot, L.R
Ehsani, R
Albrigo, G
Campoy, J
Wellington, C
Swen, W
Camergo Neto, J
Mahoney, W
Barlage, M
Gochis, D
Chen, F
Poursina, D
Brorsen, W
Brorsen, W
Poursina, D
Patterson, C
Mieno, T
Edge, B
Nafziger, E.D
Topics
Precision Horticulture
Spatial Variability in Crop, Soil and Natural Resources
On Farm Experimentation with Site-Specific Technologies
On Farm Experimentation with Site-Specific Technologies
Type
Poster
Oral
Year
2012
2014
2022
2024
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Authors

Filter results4 paper(s) found.

1. Validation of Variable Rate Spray Decision Rules in Intricate Micro-Metrological Conditions

This study evaluated validity of modified spray decision rules formed to operate axial fan airblast sprayer retrofitted for use in citrus production. The sprayer was field tested in a spraying... L.R. Khot, R. Ehsani, G. Albrigo, J. campoy, C. Wellington, W. Swen, J. Camergo neto

2. Developing A High-Resolution Land Data Assimilation And Forecast System For Agricultural Decision Support

Technological advances in weather and climate forecasting and land surface and hydrology modeling have led to an increased ability to predict soil temperature, and soil moisture, near-surface weather elements. These variables are critical building blocks to the development of high-level agriculture-specific models such as pest models and crop yield models. The National Center for Atmospheric Research (NCAR) has developed a high-resolution agriculture-oriented land-data assimilation... W. Mahoney, M. Barlage, D. Gochis, F. Chen

3. Where to Put Treatments for On-farm Experimentation

On-farm experimentation has become more and more popular due to advancements in technology. These experiments are not as costly as before, as current machinery can allocate different levels of treatment to specific plots. The main goal of this kind of experiment is to obtain a site-specific nutrient level. The yield behavior is different based on the researcher’s treatment. One unanswered question for on-farm experimentation is how the treatments should be allocated in the first place such... D. Poursina, W. Brorsen

4. Using Informative Bayesian Priors and On-farm Experimentation to Predict Optimal Site-specific Nitrogen Rates

Most U.S. Corn Belt states now recommend the Maximum Return to Nitrogen (MRTN) method for determining optimal nitrogen rates, which is based on 15 years of on-farm yield response to nitrogen trials. The MRTN method recommends a uniform rate for a region of a state. This study combines Illinois MRTN data, Bayesian methods, and on-farm experimentation from the Data Intensive Farm Management (DIFM) project to provide site-specific nitrogen recommendations. On-farm trials are now being used to provide... W. Brorsen, D. Poursina, C. Patterson, T. Mieno, B. Edge, E.D. Nafziger