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Video: On-The-Go Sensor Technology At OSU

Oklahoma State University has been at the epicenter of on-the-go sensor technology. This video describes how the technology was developed and how it works. | Watch now

Video: Technology Benefits In Canada

This video supported by Farm Credit Canada demonstrates the benefits of precision agriculture use by Canadian farmers. | Watch now

Video: AutoProbe In Action

A demonstration of AgRobotics' AutoProbe on-the-go soil sampling system performed on a muddy field in Arkansas.

Ag Technology’s Leading Indicators

Sensors, imagery, wireless communication and better data integration top the precision agriculture trends to watch.

Pushing Sensors To The Next Level

Ag Leader and Holland Scientific are working together to research on-the-go sensing technology and techniques.

Precision Program Success Story

Advanced Cropping Systems is Central Valley Ag Coop's highly successful precision ag program. At the recent InfoAg Conference, Glen Franzluebbers, the program's technical director, spoke to attendees on how CVA guides customers through every step of precision agriculture, from the basic beginning stages to the complex advanced stages. | Video: CVA Program | Search: Variable Rate Application

Onset Adds Light Sensor Bracket

Onset Computer recently introduced a new bracket that makes it fast and convenient to mount the company’s light sensors for calculating Normalized Difference Vegetation Index (NDVI) values.

AgRobotics And GVM Form Strategic Alliance

AgRobotics and GVM Inc. have formed a strategic alliance and marketing partnership for a 'next generation' GPS/GIS telematics offering.

Trimble Acquires Farm Works Software Assets

Trimble has acquired the assets of CTN Data Service, creator of Farm Works software, to help expand Trimble's information management solutions.

On The Go Sensors In Cotton Country

On-the-go, optical sensing technologies have some advantages over aerial images. Both tools allow growers to identify variability in their fields, but with the sensor-based systems there is no need to acquire an image from an outside provider and the sensors are not weather dependent. There is also no time lag between in-field analysis using the sensors and variable-rate application of PGRs, fertilizers, or harvest aids.