Proceedings :: International Society of Precision Agriculture

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Quinn, D.

Taylor, R.K

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Authors

Taylor, R.K

Bennur, P

Solie, J.B

Wang, N

Weckler, P

Raun, W.R

Mizuta, K

Miao, Y

Morales, A.C

Lacerda, L.N

Cammarano, D

Nielsen, R.L

Gunzenhauser, R

Kuehner, K

Wakahara, S

Coulter, J.A

Mulla, D.J

Quinn, D.

McArtor, B

Morales, A.C

Quinn, D.

Mizuta, K

Miao, Y

Rubaino Sosa, S.A

Quinn, D.

Armstrong, S

Paulus Scheffer, B

Quinn, D.

Magalhaes Cisdeli, P.H

Jin, J

Qin, Z

Ciampitti, I

Rubaino Sosa, S.A

Quinn, D.

Armstrong, S

Topics

Remote Sensing for Nitrogen Management

In-Season Nitrogen Management

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

Predictive Modeling, Phenotyping, and Digital Tools for Decision Support

Site-Specific Nutrient, Lime and Seed Management

Type

Oral

Poster

Year

2008

2022

2024

2026

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Authors

Filter results6 paper(s) found.
1. Controller Performance Criteria for Sensor Based Variable Rate Application Sensor based variable rate application of crop inputs provides unique challenges for traditional rate controllers when compared to map based applications. The controller set point is typically changing every second whereas with a map based systems the set point changes much less frequently. As applied data files for a sensor based variable rate nitrogen applicator were obtained from a wheat field in north central Oklahoma. These data were analyzed to determine the magnitude and frequency of rate... R.K. Taylor, P. Bennur, J.B. Solie, N. Wang, P. Weckler, W.R. Raun Download paper
2. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana Precision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor Download paper
3. Effects of Crop Rotation on In-season Estimation of Optimal Nitrogen Rates for Corn Based on Proximal and Remote Sensing Data A remote sensing and calibration strip-based precision nitrogen (N) management (RS-CS-PNM) strategy has been developed by the Precision Agriculture Center at the University of Minnesota to provide in-season N recommendation rates based on satellite imagery. This strategy involves the application of multiple N rates before planting and the identification of the agronomic optimum N rate (AONR) at V7-V8 growth stages using normalized difference vegetation index (NDVI) calculated using satellite imagery.... A.C. Morales, D. . Quinn, K. Mizuta, Y. Miao
4. Using Remote Sensing to Evaluate Cover Crop Performance and Plan Variable Rate Management The adoption of cover crops (CC) in row-crop production, particularly in states like Indiana, has surged due to their recognized benefits in nutrient scavenging, soil health improvement, and erosion prevention. However, the spatial and temporal dynamics of CC performance pose challenges for efficient assessment and management. Traditional methods of quantifying CC production involve labor-intensive and time-consuming processes, creating a lag between data collection and decision-making for farmers.... S.A. Rubaino Sosa, D. . Quinn, S. Armstrong
5. Integrating Proximal Hyperspectral and Machine Learning to Predict Nitrogen in Short- and Full-stature Corn Hybrids at Early Growth Stage in Indiana, USA Nitrogen (N) fertilizer use is a complex challenge, as underapplication can harm yield and overapplication can harm profitability and the environment. N accounts for roughly 58% of total US corn fertilizer use (an annual expense of ~$8 billion), with overapplication estimated at 15% ($1.2 billion for possible savings). Within this setting, early-season yield prediction is a high-value capability for breeding and farmers. If plot-level plant N can be forecasted with high accuracy before the corn... B. Paulus Scheffer, D. . Quinn, P.H. Magalhaes Cisdeli, J. Jin, Z. Qin, I. Ciampitti
6. Enhancing Corn Management with Variable Rate Fertilizer Maps: A Spatial Evaluation of Cover Crops Farmers and agronomists need accurate, efficient methods for evaluating cover crop (CC) biomass and nutrient content to optimize fertilization strategies and improve soil health. Traditional biomass assessments are labor-intensive and time-consuming, often delaying timely data-driven management decisions. While multispectral cameras, including near-infrared (NIR) and RedEdge sensors, provide high-accuracy data for this purpose, their high cost limits accessibility for many farmers. This study...

Filter results6 paper(s) found.

1. Controller Performance Criteria for Sensor Based Variable Rate Application

Sensor based variable rate application of crop inputs provides unique challenges for traditional rate controllers when compared to map based applications. The controller set point is typically changing every second whereas with a map based systems the set point changes much less frequently. As applied data files for a sensor based variable rate nitrogen applicator were obtained from a wheat field in north central Oklahoma. These data were analyzed to determine the magnitude and frequency of rate... R.K. Taylor, P. Bennur, J.B. Solie, N. Wang, P. Weckler, W.R. Raun

Download paper

2. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana

Precision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor

Download paper

3. Effects of Crop Rotation on In-season Estimation of Optimal Nitrogen Rates for Corn Based on Proximal and Remote Sensing Data

A remote sensing and calibration strip-based precision nitrogen (N) management (RS-CS-PNM) strategy has been developed by the Precision Agriculture Center at the University of Minnesota to provide in-season N recommendation rates based on satellite imagery. This strategy involves the application of multiple N rates before planting and the identification of the agronomic optimum N rate (AONR) at V7-V8 growth stages using normalized difference vegetation index (NDVI) calculated using satellite imagery.... A.C. Morales, D. . Quinn, K. Mizuta, Y. Miao

4. Using Remote Sensing to Evaluate Cover Crop Performance and Plan Variable Rate Management

The adoption of cover crops (CC) in row-crop production, particularly in states like Indiana, has surged due to their recognized benefits in nutrient scavenging, soil health improvement, and erosion prevention. However, the spatial and temporal dynamics of CC performance pose challenges for efficient assessment and management. Traditional methods of quantifying CC production involve labor-intensive and time-consuming processes, creating a lag between data collection and decision-making for farmers.... S.A. Rubaino Sosa, D. . Quinn, S. Armstrong

5. Integrating Proximal Hyperspectral and Machine Learning to Predict Nitrogen in Short- and Full-stature Corn Hybrids at Early Growth Stage in Indiana, USA

Nitrogen (N) fertilizer use is a complex challenge, as underapplication can harm yield and overapplication can harm profitability and the environment. N accounts for roughly 58% of total US corn fertilizer use (an annual expense of ~$8 billion), with overapplication estimated at 15% ($1.2 billion for possible savings). Within this setting, early-season yield prediction is a high-value capability for breeding and farmers. If plot-level plant N can be forecasted with high accuracy before the corn... B. Paulus Scheffer, D. . Quinn, P.H. Magalhaes Cisdeli, J. Jin, Z. Qin, I. Ciampitti

6. Enhancing Corn Management with Variable Rate Fertilizer Maps: A Spatial Evaluation of Cover Crops

Farmers and agronomists need accurate, efficient methods for evaluating cover crop (CC) biomass and nutrient content to optimize fertilization strategies and improve soil health. Traditional biomass assessments are labor-intensive and time-consuming, often delaying timely data-driven management decisions. While multispectral cameras, including near-infrared (NIR) and RedEdge sensors, provide high-accuracy data for this purpose, their high cost limits accessibility for many farmers. This study...