Start Date

3-12-2014 12:00 AM

Description

The digital transformation of row crop agriculture has been a work in progress for over 20 years. It started with the development of combine yield monitoring equipment in 1992, gained additional traction with the adoption of GPS targeted soil sampling in the mid 1990’s, and developed into a major ag industry by the mid 2000’s as documented by widespread adoption of autosteering and section control technology. Precision agriculture initiatives focused on right time, right place, and right rate input management as well as waste reduction associated with automated machine controls has played a key role in improving on-farm productivity and profitability in the last two decades of agriculture. Over the past 18 months there has been strong growth in a new industry that promises additional advances in management and decision tools that can further improve on-farm profitability. This new industry goes by many different names including Big Data, Decision Agriculture, and Digital Agriculture. While the terminology may vary, the goals are consistent—to merge ag production data, complex weather and environment models, satellite and UAV imagery, and crop input choices into a comprehensive decision support solution which empowers producers to make more informed, lower risk, and broadly sustainable decisions.

DOI

https://doi.org/10.31274/icm-180809-136

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Dec 3rd, 12:00 AM

Big Data—The catalyst for a transformation to digital agriculture

The digital transformation of row crop agriculture has been a work in progress for over 20 years. It started with the development of combine yield monitoring equipment in 1992, gained additional traction with the adoption of GPS targeted soil sampling in the mid 1990’s, and developed into a major ag industry by the mid 2000’s as documented by widespread adoption of autosteering and section control technology. Precision agriculture initiatives focused on right time, right place, and right rate input management as well as waste reduction associated with automated machine controls has played a key role in improving on-farm productivity and profitability in the last two decades of agriculture. Over the past 18 months there has been strong growth in a new industry that promises additional advances in management and decision tools that can further improve on-farm profitability. This new industry goes by many different names including Big Data, Decision Agriculture, and Digital Agriculture. While the terminology may vary, the goals are consistent—to merge ag production data, complex weather and environment models, satellite and UAV imagery, and crop input choices into a comprehensive decision support solution which empowers producers to make more informed, lower risk, and broadly sustainable decisions.

 

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