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Big data revolutionizes corn genomics and farming
Minnesota Ag Connection - 01/30/2024

The "Strategic Farming: Let's talk crops!" session, held recently, spotlighted the transformative impact of big data on corn genomics. Dr. Candy Hirsch, a corn geneticist, and Tom Hoverstad, a researcher, shared insights on how DNA sequencing could revolutionize corn production.

The key to maximizing corn yields lies in the vast expanse of corn genomic data. Dr. Hirsch's Maize Translational Genomics lab at the University of Minnesota is at the forefront, examining the intricate relationship between corn genetics, various environmental conditions, and phenotypic variation. The goal is to strategically place different hybrids for optimal performance.

Generating and deciphering terabytes of sequencing data is a complex, labor-intensive task. The genetic diversity in corn is surprisingly vast, with differences as significant as those between humans and chimpanzees.

One aspect of this diversity is SNP (single nucleotide polymorphism) variation, which involves a single gene change at a specific DNA location. Other variations include presence/absence and copy number variations.

An example of this diversity's impact is the sweet flavor of sweet corn, resulting from gene deletion. These variations play a crucial role in a plant's phenotype and have been instrumental in yield increases and environmental adaptation over time.

The environment plays an important role in crop yields, affected by climatic events like floods and droughts. Big data helps understand how different genotypes interact with varying environments, like how people react differently to weather. Understanding these genotype-environment interactions is increasingly important.

Dr. Hirsch's team employs drones for high-resolution phenotyping of various corn varieties in different environments. This approach allows for detailed analysis of plant growth patterns and adaptation strategies under diverse conditions.

The study also explored how corn plants interact with different management practices. A study, including 12 varieties with varying planting dates and densities, provided insights into lodging and recovery post-wind events.

Regarding climate change, Hoverstad notes the challenges in adapting corn genetics to rapidly changing climates. While new hybrids are developed for specific environments, the pace of climate change poses a significant challenge.

The use of big data in corn genomics by Dr. Hirsch's lab has unearthed a wealth of genetic diversity. This information is crucial in predicting corn performance across different environments, ultimately leading to an improved corn crop and more effective farming practices.


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