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Puntel, L
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Authors
Puntel, L
Pagani, A
Archontoulis, S
Balboa, G
Puntel, L
Melchiori, R
Ortega, R
Tiscornia, G
Bolfe, E
Roel, A
Scaramuzza, F
Best, S
Berger, A
Hansel, D
Palacios, D
Thompson, L
Puntel, L
Archontoulis, S
Cesario Pereira Pinto, J
Thompson, L
Mueller, N
Mieno, T
Balboa, G
Puntel, L
Puntel, L
Thompson , L
Mieno, T
Norquest, S
Thompson, L
Archontoulis, S
Grassini, P
Puntel, L
Mieno, T
Cesario Pinto, J
Thompson, L
Mueller, N
Mieno, T
Puntel, L
Paccioretti, P
Balboa, G
dos Santos, C.L
Miguez, F
Puntel, L
Bullock, D
Balboa, G
Puntel, L
Thompson, L
Paccioretti, P
Norquest, S
Puntel, L
Balboa, G
Thompson, L
Dalla Betta, M.M
Puntel, L
Thompson, L
Mieno, T
Luck, J.D
Cafaro La Menza, N
Paccioretti, P
Puntel, L
Thompson, L
Balboa, G
Mieno, T
Paccioretti, P
Topics
Decision Support Systems
ISPA Community: Latin America
Decision Support Systems
In-Season Nitrogen Management
Digital Agriculture Solutions for Soil Health and Water Quality
On Farm Experimentation with Site-Specific Technologies
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Site-Specific Nutrient, Lime and Seed Management
In-Season Nitrogen Management
Type
Oral
Poster
Year
2018
2022
2024
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Authors

Filter results12 paper(s) found.

1. Prediction of Corn Economic Optimum Nitrogen Rate in Argentina

Static (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aires,... L. Puntel, A. Pagani, S. Archontoulis

2. How Digital is Agriculture in South America? Adoption and Limitations

A rapidly growing population in a context of land and water scarcity, and climate change has driven an increase in healthy, nutritious, and affordable food demand while maintaining the current cropping area. Digital agriculture (DA) can contribute solutions to meet the demands in an efficient and sustainable way. South America (SA) is one of the main grain and protein producers in the world but the status of DA in the region is unknown. This article presents the results from a systematic review... G. Balboa, L. Puntel, R. Melchiori, R. Ortega, G. Tiscornia, E. Bolfe, A. Roel, F. Scaramuzza, S. Best, A. Berger, D. Hansel, D. Palacios

3. Evaluating APSIM Model for Site-Specific N Management in Nebraska

Many approaches have been developed to estimate the optimal N application rates and increase nitrogen use efficiency (NUE). In particular, in-season and variable-rate fertilizer applications have the potential to apply N during the time of rapid plant N uptake and at the rate needed, thereby reducing the potential for nitrogen fertilizer losses. However, there remains great challenges in determining the optimal N rate to apply in site-specific locations within a field in a given year. Additionally,... L. Thompson, L. Puntel, S. Archontoulis

4. Evaluation of Nitrogen Recommendation Tools for Winter Wheat in Nebraska

Attaining both high yield and high nitrogen (N) use efficiency (NUE) simultaneously remains a current research challenge in crop production. Digital ag technologies for site-specific N management have been demonstrated to improve NUE. This is due to the ability of digital technologies to account for the spatial and temporal distribution of crop N demand and available soil N in the field which varies greatly according to... J. Cesario pereira pinto, L. Thompson, N. Mueller, T. Mieno, G. Balboa, L. Puntel

5. 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

6. Crop Modeling-based Framework to Explore Region-specific Impact of Nitrogen Fertilizer Management on Productivity and Environmental Footprint

To maintain current crop production while reducing negative environmental impacts, improved understanding of the relative impact of the 4Rs for nitrogen (N) management (rate, time, place, and source) for a given geo-agroecosystem are needed and can play a critical role in driving policy, recommendations, and local practices. However, the timeframe and cost required to assess and characterize the impact of N rate and timing over years and weather conditions through field experiments is prohibitive.... L. Thompson, S. Archontoulis, P. Grassini, L. Puntel, T. Mieno

7. Site-specific Evaluation of Sensor-based Winter Wheat Nitrogen Tools Via On-farm Research

Crop producers face the challenge of optimizing high yields and nitrogen use efficiency (NUE) in their agricultural practices. Enhancing NUE has been demonstrated by adopting digital agricultural technologies for site-specific nitrogen (N) management, such as remote-sensing based N recommendations for winter wheat. However, winter wheat fields are often uniformly fertilized, disregarding the inherent variability within the fields. Thus, an on-farm evaluation of sensor-based N tools is needed to... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, P. Paccioretti, G. Balboa

8. Integrating Nonlinear Models and Remotely Sensed Data to Estimate Crop Cardinal Dates

Crop planting and harvest dates are a major component affecting agricultural productivity, risk, and nutrient cycling. The ability to track these cardinal dates allows researchers to investigate strategies to manage risk and adapt to climate change. This study was conducted to determine whether nonlinear statistical models combined with remotely sensed data from satellites can be used to estimate planting and harvest dates. Time of planting and harvest were reported by farmers for 16 commercial... C.L. Dos santos, F. Miguez, L. Puntel, D. Bullock

9. Barriers and Adoption of Precision Ag Tehcnologies for Nitrogen Management Nebraska

A statewide survey of Nebraska farmers shows that they determine the N rate based on soil lab recommendations (82%),  intuition, traditional rate, and own experience (67%). The adoption of dynamic site-specific models (23%), and sensor-based algorithms (11%) remains low. The survey identified the main barriers to the adoption of these N management technologies.  ... G. Balboa, L. Puntel, L. Thompson, P. Paccioretti

10. 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

11. Determining Site-Specific Soybean Optimal Seeding Rate Using On-Farm Precision Experimentation

Ten on-farm precision experiments were conducted in Nebraska during 2018 – 2022 to address the following: i) determine the Economic Optimal Seeding Rates (EOSR), ii) identify the most important site-specific variables influencing the optimal seeding rates for soybeans. Seeding rates ranged from 200,000 to 440,000 seeds ha-1, and treatments were randomized and replicated in blocks across the entire field. The study was implemented using a variable rate prescription. Yield... M.M. Dalla betta, L. Puntel, L. Thompson, T. Mieno, J.D. Luck, N. Cafaro la menza, P. Paccioretti

12. Effect of Terrain and Soil Properties on the Effectiveness of Crop-model Based Variable Rate Nitrogen in Corn

Growers may be reluctant to adopt variable rate nitrogen (VRN) management because of potential loss in profit and yield. This study assessed the influence of terrain attributes and soil characteristics on the effectiveness of crop-model-based variable rate nitrogen (N) for corn. To evaluate the effectiveness of the VRN methods, yield, total N rate, and N use efficiency (NUE) were compared with the grower’s management. As a crop-model-based recommendation tool, Adapt-N was used. Production... L. Puntel, L. Thompson, G. Balboa, T. Mieno, P. Paccioretti