Proceedings :: International Society of Precision Agriculture

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Thomson, S.J

Wever, H

Chen, Z

Abban-Baidoo, E

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Authors

Thomson, S.J

DeFauw, S.L

English, P.J

Hanks, J.E

Fisher, D.K

Foster, P.N

Zimba, P.V

Lu, J

Chen, Z

Miao, Y

Li, Y

Zhang, Y

Zhao, X

Jia, M

Michels, M

Bonke, V

Wever, H

Mußhoff, O

Duarte, P.R

Ortiz, B.V

Abban-Baidoo, E

Francisco, E

de Oliveira, M.F

Nunes, L

Francisco, E

Prasad, R

Ortiz, B.V

Abban-Baidoo , E

Worosz, M

Robinette , M

O'Connor, C

Gamble, A

Parbi, B

Ortiz, B.V

Abban-Baidoo , E

Sanz-Saez, A

Velasco, J.S

Topics

Remote Sensing Application / Sensor Technology

In-Season Nitrogen Management

Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture

In-Season Nitrogen Management

Extension or Outreach Education of Precision Agriculture

Drainage Optimization and Variable Rate Irrigation

Type

Oral

Poster

Year

2008

2022

2024

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Authors

Filter results6 paper(s) found.
1. Thermal Characterization and Spatial Analysis of Water Stress in Cotton (Gossypium Hirsutum L.) and Phytochemical Composition Related to Water Stress in Soybean (Glycine Max) Studies were designed to explore spatial relationships of water and/or heat stress in cotton and soybeans and to assess factors that may influence yield potential. Investigations focused on detecting the onset of water/heat stress in row crops using thermal and multispectral imagery with ancillary physicochemical data such as soil moisture status and photosynthetic pigment concentrations. One cotton field with gradations in soil texture showed distinct patterns in thermal imagery, matching patterns... S.J. Thomson, S.L. Defauw, P.J. English, J.E. Hanks, D.K. Fisher, P.N. Foster, P.V. Zimba Download paper
2. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data Nitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia Download paper
3. Farming for a Greener Future: the Behavioural Drive Behind German Farmers’ Alternative Fuel Machinery Purchase Intentions Climate change due to greenhouse gas emissions, e.g. anthropogenic carbon dioxide (CO2), in the atmosphere will lead to damages caused by global warming, increases in heavy rainfall, flooding as well as permafrost melt. One of the main issues for reducing greenhouse gas emissions is the dependence on oil for fueling transportation and other sectors. Accordingly, policy makers aim to reduce dependency on fossil fuels with the accelerated roll-out of renewable energy. Among others, the... M. Michels, V. Bonke, H. Wever, O. Mußhoff Download paper
4. Exploring the Use of a Model-based Nitrogen Recommendation Tool and Vegetation Indices for In-season Corn Nitrogen Management in Alabama Efficient nitrogen (N) management is critical for sustainable agriculture. Crop N needs and uptake changes within a field and it is annually influenced by weather conditions. Hence, site-specific in-season N application strategies are important to achieve optimum corn yield while minimizing negative impacts on the environment. This study evaluates the Adapt-N tool for in-season variable rate N application at two farmers’ fields in Alabama. The Adapt-N tool integrates soil and crop-based... P.R. Duarte, B.V. Ortiz, E. Abban-baidoo, E. Francisco, M.F. De oliveira Download paper
5. Participatory Irrigation Extension Programs to Increasing Adoption of Best Irrigation Strategies Farmers in Alabama, Tennessee, and other US southeastern states lack experience in irrigation water management and adoption of the state-of-the-art technologies and practices to increase irrigation water use efficiency. Several federal and state-funded projects are being implemented to demonstrate and train farmers and consultants on irrigation scheduling strategies and variable rate irritation. Half a dozen on-farm demonstration sites are selected every year to evaluate, demonstrate, and train... L. Nunes, E. Francisco, R. Prasad, B.V. Ortiz, E. Abban-baidoo , M. Worosz, M. Robinette , C. O'connor, A. Gamble
6. Evaluation of Peanut Response to Soil Water Levels Using the Crop Water Stress Index Generated from Infrared Thermal Sensors and Imagery In precision agriculture, precise monitoring of crop water stress is crucial for optimizing water use, increasing crop yield, and promoting environmental sustainability. Achieving high water use efficiency in peanut production is key to producing high-quality crop. This study investigates the efficiency of infrared thermal sensors and thermal imagery from satellites and unmanned aerial vehicles (UAVs) for determining peanut crop water stress index (CWSI). Furthermore, this research explores the... B. Parbi, B.V. Ortiz, E. Abban-baidoo , A. Sanz-saez, J.S. Velasco

Filter results6 paper(s) found.

1. Thermal Characterization and Spatial Analysis of Water Stress in Cotton (Gossypium Hirsutum L.) and Phytochemical Composition Related to Water Stress in Soybean (Glycine Max)

Studies were designed to explore spatial relationships of water and/or heat stress in cotton and soybeans and to assess factors that may influence yield potential. Investigations focused on detecting the onset of water/heat stress in row crops using thermal and multispectral imagery with ancillary physicochemical data such as soil moisture status and photosynthetic pigment concentrations. One cotton field with gradations in soil texture showed distinct patterns in thermal imagery, matching patterns... S.J. Thomson, S.L. Defauw, P.J. English, J.E. Hanks, D.K. Fisher, P.N. Foster, P.V. Zimba

Download paper

2. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data

Nitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia

Download paper

3. Farming for a Greener Future: the Behavioural Drive Behind German Farmers’ Alternative Fuel Machinery Purchase Intentions

Climate change due to greenhouse gas emissions, e.g. anthropogenic carbon dioxide (CO2), in the atmosphere will lead to damages caused by global warming, increases in heavy rainfall, flooding as well as permafrost melt. One of the main issues for reducing greenhouse gas emissions is the dependence on oil for fueling transportation and other sectors. Accordingly, policy makers aim to reduce dependency on fossil fuels with the accelerated roll-out of renewable energy. Among others, the... M. Michels, V. Bonke, H. Wever, O. Mußhoff

Download paper

4. Exploring the Use of a Model-based Nitrogen Recommendation Tool and Vegetation Indices for In-season Corn Nitrogen Management in Alabama

Efficient nitrogen (N) management is critical for sustainable agriculture. Crop N needs and uptake changes within a field and it is annually influenced by weather conditions. Hence, site-specific in-season N application strategies are important to achieve optimum corn yield while minimizing negative impacts on the environment. This study evaluates the Adapt-N tool for in-season variable rate N application at two farmers’ fields in Alabama. The Adapt-N tool integrates soil and crop-based... P.R. Duarte, B.V. Ortiz, E. Abban-baidoo, E. Francisco, M.F. De oliveira

Download paper

5. Participatory Irrigation Extension Programs to Increasing Adoption of Best Irrigation Strategies

Farmers in Alabama, Tennessee, and other US southeastern states lack experience in irrigation water management and adoption of the state-of-the-art technologies and practices to increase irrigation water use efficiency. Several federal and state-funded projects are being implemented to demonstrate and train farmers and consultants on irrigation scheduling strategies and variable rate irritation. Half a dozen on-farm demonstration sites are selected every year to evaluate, demonstrate, and train... L. Nunes, E. Francisco, R. Prasad, B.V. Ortiz, E. Abban-baidoo , M. Worosz, M. Robinette , C. O'connor, A. Gamble

6. Evaluation of Peanut Response to Soil Water Levels Using the Crop Water Stress Index Generated from Infrared Thermal Sensors and Imagery

In precision agriculture, precise monitoring of crop water stress is crucial for optimizing water use, increasing crop yield, and promoting environmental sustainability. Achieving high water use efficiency in peanut production is key to producing high-quality crop. This study investigates the efficiency of infrared thermal sensors and thermal imagery from satellites and unmanned aerial vehicles (UAVs) for determining peanut crop water stress index (CWSI). Furthermore, this research explores the... B. Parbi, B.V. Ortiz, E. Abban-baidoo , A. Sanz-saez, J.S. Velasco