Genetic Gain Performance Metric Accelerates Agricultural Productivity

Joseph Byrum (), Bill Beavis (), Craig Davis (), Greg Doonan (), Tracy Doubler (), Kaster Von (), Ron Mowers () and Sam Parry ()
Additional contact information
Joseph Byrum: Syngenta Seeds, Inc., Slater, Iowa 50244
Bill Beavis: Iowa State University, Ames, Iowa 50011
Craig Davis: Syngenta Seeds, Inc., Slater, Iowa 50244
Greg Doonan: Syngenta Seeds, Inc., Slater, Iowa 50244
Tracy Doubler: Syngenta Seeds, Inc., Slater, Iowa 50244
Kaster Von: Syngenta Seeds, Inc., Slater, Iowa 50244
Ron Mowers: Syngenta Seeds, Inc., Slater, Iowa 50244
Sam Parry: Arizona State University, Phoenix, Arizona 85004

Interfaces, 2017, vol. 47, issue 5, 442-453

Abstract: The agricultural seed industry invests billions of dollars each year to improve our understanding of how best to unlock a seed’s full potential. This investment brings a significant benefit to agricultural customers—the farmers who grow commodity crops, such as corn, soybeans, and wheat. Commodity farmers expect new crop varieties to be adapted to local conditions and have greater genetic potential for yield. We refer to the amount of increase in the genetic potential for yield as “genetic gain.” The agricultural seed industry needs a universal, unbiased metric for genetic gain performance (GGP). Therefore, in 2010 we developed and implemented an algorithm that calculates an unbiased GGP metric that eliminates environmental factors (e.g., solar radiation, rainfall, and temperature) and is applicable at each stage of the product development pipeline. We subsequently used this metric during the variety development stage of our breeding projects to measure the impact of operational changes. We used weighted averages of GGP to retrospectively evaluate changes in genetic gain across 10 years of our breeding pipeline to quantify the benefit. We estimate that genetic gains are now 40 percent greater than the gains seen before implementation of the GGP in 2010. Our analyses show that the GGP metric has saved Syngenta approximately $250 million in varietal development costs, which would otherwise have been required to improve genetic gain by 40 percent. Syngenta scientists now use GGP to evaluate the genetic gain of all breeding projects. It serves as a valuable early-warning system. At the end of each growing season, we collect yield data and update the GGP database. This allows our scientists to perform an annual evaluation of genetic advances in each market segment. These assessments identify potential performance gaps likely to surface in the next growing season so that they can be avoided. Our successful development and deployment of a genetic gain metric is an important advance for both Syngenta and the entire agricultural industry.

Keywords: operational decisions; genetic gain improvement; genetic gain performance; algorithm; agriculture; varietal developmen (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1287/inte.2017.0909 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:47:y:2017:i:5:p:442-453

Access Statistics for this article

More articles in Interfaces from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().