journal article
Feb 01, 2016
Advanced Analytics for Agricultural Product Development
Joseph Byrum
Craig Davis
Gregory Doonan
Tracy Doubler
David Foster
Bruce Luzzi
Ronald Mowers
Chris Zinselmeier
Jack Kloeber
Dave Culhane
Stephen Mack
Interfaces
Vol. 46
No. 1
pp. 5-17
·
Institute for Operations Research and the Management Sciences (INFORMS)
Abstract
Syngenta, a leading developer of crop varieties (seeds) that provide food for human and livestock consumption, is committed to bringing greater food security to an increasingly populous world by creating a transformational shift in farm productivity. Syngenta Soybean Research and Development (R&D) is leading Syngenta’s corporate plant-breeding strategy by developing and implementing a new product development model that is enabling the creation of an efficient and effective soybean breeding strategy. Key to the new strategy is the combination of advanced analytics and plant-breeding knowledge to find opportunities to increase crop productivity and optimize plant-breeding processes. Syngenta uses discrete-event and Monte Carlo simulation models to codify Syngenta Soybean R&D best practices, and uses stochastic optimization to create the best soybean breeding plans and strategically align its research efforts. As a result of using these new analytical tools, Syngenta estimates that it will save more than $287 million between 2012 and 2016.
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References
1
[1]
Sleper D (2006)
Metrics
17
Citations
1
References
Details
- Published
- Feb 01, 2016
- Vol/Issue
- 46(1)
- Pages
- 5-17
Authors
Cite This Article
Joseph Byrum, Craig Davis, Gregory Doonan, et al. (2016). Advanced Analytics for Agricultural Product Development. Interfaces, 46(1), 5-17. https://doi.org/10.1287/inte.2015.0823
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