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Sanchez, L.A
Rhea, S.T
Quinn, D.
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Authors
Sanchez, L.A
Klein, L.J
Claassen, A
Lew, D
Mendez-Costabel, M
Sams, B
Morgan, A
Hinds, N
Hamann, H.F
Dokoozlian, N
Ferreyra, R
Applegate, D.B
Berger, A.W
Berne, D.T
Craker, B.E
Daggett, D.G
Gowler, A
Bullock, R.J
Haringx, S.C
Hillyer, C
Howatt, T
Nef, B.K
Rhea, S.T
Russo, J.M
Nieman, S.T
Sanders, P
Wilson, J.A
Wilson, J.W
Tevis, J.W
Stelford, M.W
Shearouse, T.W
Schultz, E.D
Reddy, L
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
Precision Horticulture
Standards & Data Stewardship
In-Season 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
2014
2016
2022
2024
2026
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Authors

Filter results7 paper(s) found.

1. Effect Of A Variable Rate Irrigation Strategy On The Variability Of Crop Production In Wine Grapes In California

Pruning and irrigation are the cultural practices with the highest potential impact on yield and quality in wine grapes. In particular, irrigation start date, rates and frequency can be synchronized with crop development stages to control canopy growth and, in turn, positively influence light microclimate, berry size and fruit quality. In addition, canopy management practices can be implemented in vineyards with large canopies to ensure fruit zone microclimate... L.A. Sanchez, L.J. Klein, A. Claassen, D. Lew, M. Mendez-costabel, B. Sams, A. Morgan, N. Hinds, H.F. Hamann, N. Dokoozlian

2. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPT

AgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy

3. 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

4. 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

5. 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

6. 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

7. 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...