The NDSU Agricultural Data Analytics team began participation in the Genomes to Fields Genotype by Environment Prediction Competition starting on Nov. 15.
“The Genomes to Fields Competition aligns closely with the expertise of the NDSU Ag Data Analytics team,” said Ana Maria Heilman-Morales, NDSU Agricultural Data Analytics director. “Our team, composed of plant breeders, statisticians, computer scientists, and quantitative geneticists, saw this as a great opportunity to apply our knowledge in data analytics and compete at a high level. This competition also serves as a platform for learning and for providing innovative data solutions using agricultural, climate and other historical data.”
During the two months of competition, the NDSU Ag Data Analytics Team will be working with a provided dataset to develop models that obtain crucial insights from the data. The competition is an opportunity for the NDSU team to further develop data analytics skills and apply expertise in solving complex agricultural challenges.
The NDSU G2F team is led by Sikiru Atanda, Big Data Predictive Modeler at NDSU.
The Genomes to Fields Initiative is “a publicly initiated and led research initiative to catalyze and coordinate research linking genomics and predictive phenomics to achieve advances that generate societal and environmental benefits,” according to its website. The competition’s objective is to develop models to predict corn yield using 2024 G2F trials based on dataset and other publicly available data.
The competition is organized by USDA-ARS, University of Wisconsin, Iowa Corn Growers Association, North Carolina State University, Texas A&M, Cornell and Corteva. The competition goes from Nov. 15 to Jan. 15. The winner will receive a cash prize of $4,000 along with paid expenses for travel and registration to present in the competition at an international meeting.
The NDSU Agricultural Data Analytics is affiliated with the North Dakota Agricultural Experiment Station at NDSU. The team creates data solutions, including repositories, APIs, databases, applied statistical tools, automated pipelines, creates solutions to introduce new Ag emerging technologies to further agricultural research and development at the NDAES.
“This shared effort fosters teamwork and strengthens our collective knowledge while pushing us to excel in the competition and contribute to advancements in agricultural research,” Heilman-Morales said.
