Proceedings :: International Society of Precision Agriculture

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Ritchie, G

Roberts, R.K

Rousseau, J

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Authors

Lambert, D.M

Larson, J.A

English, B.C

Rejesus, R.M

Marra, M.C

Mishra, A.K

Wang, C

Watcharaanantapong, P

Roberts, R.K

Velandia, M

Douche, H

Rousseau, J

Karn, R

Adedeji, O

Ghimire, B.P

Abdalla, A

Sheng, V

Ritchie, G

Guo, W

Ghimire, B

Karn, R

Adedeji, O

Ritchie, G

Guo, W

Topics

Global Proliferation of Precision Agriculture and its Applications

Precision A-Z for Practitioners

Precision Agriculture and Global Food Security

Decision Support Systems

Type

Poster

Oral

Year

2012

2010

2024

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Filter results4 paper(s) found.
1. Factors Influencing the Timing of Precision Agriculture Technology Adoption in Southern U.S. Cotton Production Technology innovators in cotton production adopted precision agriculture (PA) technologies soon after they became commercially available, while others adopted these technologies in later years after evaluating the success of the innovators. The timing of... D.M. Lambert, J.A. Larson, B.C. English, R.M. Rejesus, M.C. Marra, A.K. Mishra, C. Wang, P. Watcharaanantapong, R.K. Roberts, M. Velandia Download paper
2. Oenoview : Bringing Remote Sensing To Wine Quality Oenoview is born in 2006 from the partnership between Infoterra, an EADS Astrium company specialised in earth observation and the Institut Cooperatif de Vin, a French company of services for the wine industry. Oenoview is an operating precision viticulture service, dedicated to vine monitoring, harvest optimisation and input management. In France, this service implemented in 2009 on a commercial scale is now used by clients as different as large... H. Douche, J. Rousseau Download paper
3. Within Field Cotton Yield Prediction Using Temporal Satellite Imagery Combined with Deep Learning Crop yield prediction at the field scale plays a pivotal role in enhancing agricultural management, a vital component in addressing global food security challenges. Regional or county-level data, while valuable for broader agricultural planning, often lacks the precision required by farmers for effective and timely field management. The primary obstacle in utilizing satellite imagery to forecast crop yields at the field level lies in its low temporal and spatial resolutions. This study aims to... R. Karn, O. Adedeji, B.P. Ghimire, A. Abdalla, V. Sheng, G. Ritchie, W. Guo
4. Simulating Climate Change Impacts on Cotton Yield in the Texas High Plains Crop yield prediction enables stakeholders to plan farming practices and marketing. Crop models can predict crop yield based on cropping system and practices, soil, and other environmental factors. These models are being used for decision support in agriculture in a variety of ways. Cultivar selection, water and nutrient input optimization, planting date selection, climate change analysis and yield prediction are some of the promising area of applications of the models in field level farm management.... B. Ghimire, R. Karn, O. Adedeji, G. Ritchie, W. Guo

Filter results4 paper(s) found.

1. Factors Influencing the Timing of Precision Agriculture Technology Adoption in Southern U.S. Cotton Production

Technology innovators in cotton production adopted precision agriculture (PA) technologies soon after they became commercially available, while others adopted these technologies in later years after evaluating the success of the innovators. The timing of... D.M. Lambert, J.A. Larson, B.C. English, R.M. Rejesus, M.C. Marra, A.K. Mishra, C. Wang, P. Watcharaanantapong, R.K. Roberts, M. Velandia

Download paper

2. Oenoview : Bringing Remote Sensing To Wine Quality

Oenoview is born in 2006 from the partnership between Infoterra, an EADS Astrium company specialised in earth observation and the Institut Cooperatif de Vin, a French company of services for the wine industry. Oenoview is an operating precision viticulture service, dedicated to vine monitoring, harvest optimisation and input management. In France, this service implemented in 2009 on a commercial scale is now used by clients as different as large... H. Douche, J. Rousseau

Download paper

3. Within Field Cotton Yield Prediction Using Temporal Satellite Imagery Combined with Deep Learning

Crop yield prediction at the field scale plays a pivotal role in enhancing agricultural management, a vital component in addressing global food security challenges. Regional or county-level data, while valuable for broader agricultural planning, often lacks the precision required by farmers for effective and timely field management. The primary obstacle in utilizing satellite imagery to forecast crop yields at the field level lies in its low temporal and spatial resolutions. This study aims to... R. Karn, O. Adedeji, B.P. Ghimire, A. Abdalla, V. Sheng, G. Ritchie, W. Guo

4. Simulating Climate Change Impacts on Cotton Yield in the Texas High Plains

Crop yield prediction enables stakeholders to plan farming practices and marketing. Crop models can predict crop yield based on cropping system and practices, soil, and other environmental factors. These models are being used for decision support in agriculture in a variety of ways. Cultivar selection, water and nutrient input optimization, planting date selection, climate change analysis and yield prediction are some of the promising area of applications of the models in field level farm management.... B. Ghimire, R. Karn, O. Adedeji, G. Ritchie, W. Guo