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Luns Hatum de Almeida , S

Norquest, S

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Authors

Puntel, L

Thompson , L

Mieno, T

Norquest, S

Puntel, L

Balboa, G

Thompson, L

Oliveira, M.F

Ortiz, B.V

Hanyabui, E

Costa Souza, J.B

Sanz-Saez, A

Luns Hatum de Almeida , S

Pilcon, C

Vellidis, G

Topics

Decision Support Systems

Site-Specific Nutrient, Lime and Seed Management

Proximal and Remote Sensing of Soils and Crops (including Phenotyping)

Type

Oral

Poster

Year

2022

2024

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Filter results3 paper(s) found.
1. Evaluation of Crop Model Based Tools for Corn Site-specific N Management in Nebraska There is a critical need to reduce the nitrogen (N) footprint from corn-based cropping systems while maintaining or increasing yields and profits. Digital agriculture technologies for site-specific N management have been demonstrated to improve nitrogen use efficiency (NUE). However, adoption of these technologies remains low. Factors such as cost, complexity, unknown impact and large data inputs are associated with low adoption. Grower’s hands-on experience coupled with targeted research... L. Puntel, L. Thompson , T. Mieno, S. Norquest Download paper
2. Site Specific Evaluation of Dynamic Nitrogen Recommendation Tools Management tools are a potential solution for increased profit and N use efficiency (NUE) in corn production. Most previous studies evaluating these tools used small plot research which does not accurately represent large scale performance and inhibits adoption. Two dynamic model-based N management tools, which were commercially available in 2021 and 2022 (Adapt-N and Granular), were tested at fifteen on-farm research locations in Nebraska. The objective of this study were to evaluate the site-specific... S. Norquest, L. Puntel, G. Balboa, L. Thompson Download paper
3. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in Alabama Harvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis Download paper

Filter results3 paper(s) found.

1. Evaluation of Crop Model Based Tools for Corn Site-specific N Management in Nebraska

There is a critical need to reduce the nitrogen (N) footprint from corn-based cropping systems while maintaining or increasing yields and profits. Digital agriculture technologies for site-specific N management have been demonstrated to improve nitrogen use efficiency (NUE). However, adoption of these technologies remains low. Factors such as cost, complexity, unknown impact and large data inputs are associated with low adoption. Grower’s hands-on experience coupled with targeted research... L. Puntel, L. Thompson , T. Mieno, S. Norquest

Download paper

2. Site Specific Evaluation of Dynamic Nitrogen Recommendation Tools

Management tools are a potential solution for increased profit and N use efficiency (NUE) in corn production. Most previous studies evaluating these tools used small plot research which does not accurately represent large scale performance and inhibits adoption. Two dynamic model-based N management tools, which were commercially available in 2021 and 2022 (Adapt-N and Granular), were tested at fifteen on-farm research locations in Nebraska. The objective of this study were to evaluate the site-specific... S. Norquest, L. Puntel, G. Balboa, L. Thompson

Download paper

3. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in Alabama

Harvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis

Download paper