2018 Syngenta Crop Challenge in Analytics winner announced

  • A team from The International Center for Tropical Agriculture in Colombia won first place
  • Entrants developed models to predict how corn hybrids will perform in untested locations, in an effort to help plant breeders improve hybrid performance predictions
  • Winning team developed a strategy using machine learning

RESEARCH TRIANGLE PARK, N.C.--()--Syngenta and the Analytics Society of INFORMS are proud to recognize a team from The International Center for Tropical Agriculture (CIAT) in Colombia as the winner of the 2018 Syngenta Crop Challenge in Analytics.

“Genotype - Environment Interaction (G by E) Analysis using Deep Neural Networks Approach”

The competition, hosted by the Analytics Society of the Institute for Operations Research and the Management Sciences (INFORMS), concluded during the 2018 INFORMS Conference on Business Analytics & Operations Research in Baltimore, Maryland, where five finalist teams presented their submissions to the Crop Challenge prize committee.

This year’s Challenge asked participants to use a real-world dataset to develop models that predict how well corn hybrids will perform in untested locations. Finalist teams from Brazil, Colombia, Germany and the U.S. presented their models, which have the potential to help plant breeders make better decisions regarding which hybrids to advance commercially and provide to growers—while confronting the ongoing challenge of field-testing limitations.

The winning team, which included Andres Aguilar, Hugo “Andres” Dorado Bentencourt, Sylvain Delerce, Michael Caraccio, Juan Camilo Rivera, Maria Camila Gomez, Steven Humberto Sotelo and Anestis Gkanogiannis, was awarded a $5,000 prize for the submission, “Speeding up maize hybrids breeding schemes using machine learning.”

The team represents CIAT, a not-for-profit research and development organization that aims to reduce poverty and hunger in developing countries by helping farmers improve crop production sustainably.

“In this specific challenge we had to deal with genetic data, which was a little bit new for us,” said CIAT team member Sylvain Delerce. “And what we see is that analytics and optimization can really play a big role and it’s very promising.”

The submissions were evaluated by the prize committee based on the rigor and validity of the process used to determine optimal corn hybrids, the quality of the proposed solution and the finalists’ ability to clearly articulate their approach.

“The finalists’ submissions represent the type of analytical thinking which can enable the sustainable agriculture of the future,” said Dan Dyer, head of seed product development, Syngenta, and Crop Challenge judge. “When we look at the plant breeding of the future, we see data scientists and mathematicians playing an increasingly critical role. By collaborating with them, we can find new ways to improve crop production.”

The runner-up submission, “Bridging concepts from Bayesian theory, Artificial Intelligence and Genetics: A novel Bayesian Network methodology for predictions and decision-making,” authored by Jhonathan Pedroso Rigal dos Santos from Brazil, received a $2,500 prize. The third place entry, “Genotype - Environment Interaction (G by E) Analysis using Deep Neural Networks Approach,” authored by Saeed Khaki, Hans Mueller and Lizhi Wang from Iowa State University, received a $1,000 prize.

“All of the finalists brought an exceptional level of sophistication and creativity to their entries,” said Nicolas Martin, assistant professor at the University of Illinois at Urbana-Champaign, Crop Challenge prize committee chair and member of INFORMS. “These insights from data analytics experts can help us solve some of the complex challenges found in agriculture.”

The Syngenta Crop Challenge in Analytics was established in 2015 with funding provided by prize winnings awarded to Syngenta in connection with its receipt of the 2015 Franz Edelman Award for Achievement in Operations Research and the Management Sciences. The competition aligns with Syngenta’s commitment to make crops more efficient – one of the tenets of The Good Growth Plan, a global initiative to improve the sustainability of agriculture.

For more information about the Syngenta Crop Challenge in Analytics, visit www.ideaconnection.com/syngenta-crop-challenge. Join the conversation online – connect with Syngenta at social.syngentaUS.com.

About Syngenta
Syngenta is a leading agriculture company helping to improve global food security by enabling millions of farmers to make better use of available resources. Through world class science and innovative crop solutions, our 27,500 people in over 90 countries are working to transform how crops are grown. We are committed to rescuing land from degradation, enhancing biodiversity and revitalizing rural communities. To learn more, visit www.syngenta.com and www.goodgrowthplan.com. Follow us on Twitter at www.twitter.com/Syngenta and www.twitter.com/SyngentaUS.

About INFORMS
With 12,500 members from nearly 90 countries, INFORMS is the largest international association of operations research (O.R.) and analytics professionals and students. INFORMS provides unique networking and learning opportunities for individual professionals, and organizations of all types and sizes, to better understand and use O.R. and analytics tools and methods to transform strategic visions and achieve better outcomes.

The INFORMS Analytics Society, a subdivision of INFORMS, promotes the integration of a wide range of analytical techniques and supports activities that illuminate significant innovations and achievement in the growing field of analytics.

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Cautionary Statement Regarding Forward-Looking Statements
This document contains forward-looking statements, which can be identified by terminology such as ‘expect’, ‘would’, ‘will’, ‘potential’, ‘plans’, ‘prospects’, ‘estimated’, ‘aiming’, ‘on track’ and similar expressions. Such statements may be subject to risks and uncertainties that could cause the actual results to differ materially from these statements. For Syngenta, such risks and uncertainties include risks relating to legal proceedings, regulatory approvals, new product development, increasing competition, customer credit risk, general economic and market conditions, compliance and remediation, intellectual property rights, implementation of organizational changes, impairment of intangible assets, consumer perceptions of genetically modified crops and organisms or crop protection chemicals, climatic variations, fluctuations in exchange rates and/or commodity prices, single source supply arrangements, political uncertainty, natural disasters, and breaches of data security or other disruptions of information technology. Syngenta assumes no obligation to update forward-looking statements to reflect actual results, changed assumptions or other factors.

©2018 Syngenta. 9 Davis Drive, Research Triangle Park, NC 27709. The Syngenta logo is a registered trademark of a Syngenta Group Company. All other trademarks are the property of their respective owners.

Syngenta supports but is not a sponsor of this INFORMS challenge. Entrants must read and agree to terms and conditions of the challenge, found with the registration mate materials.

Contacts

Syngenta
Chris Tutino, 919-226-7238
chris.tutino@syngenta.com
or
Cindy Whitt, 919-870-5718
cwhitt@gscommunications.com
or
INFORMS
Ashley Kilgore, 443-757-3560
ashley.kilgore@informs.org

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Syngenta and the Analytics Society of INFORMS announce the winner of 2018 Crop Challenge in Analytics.

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