A new study published in/Plant Biotechnology Journal/details the efforts
of Iowa State University agronomy professor Jianming Yu in
predictingcorn traitsbased ongenomicsand data analytics. Yu has devoted
much of his research into "turbo charging" the seemingly endless amount
of genetic stocks contained in the world's seed banks.

The study focused on predicting eight corn traits based on the shoot
apical meristem (SAM), a microscopic stem cell niche that generates all
the above-ground organs of the plant. The researchers used their
analytical approach to predict traits in 2,687 diverse maize inbred
varieties based on a model they developed from studying 369 inbred
varieties that had been grown and had their shoot apical meristems
pictured and measured under the microscope. The researchers then
validated their predictions with data obtained from 488 inbreds to
determine their prediction accuracy ranged from 37% to 57% across the
eight traits they studied.

Yu said that plant breeders can bump up the accuracy of those genomic
predictions by increasing the number of plants per inbred for
measurement and findings-improved prediction algorithms. More
importantly, plant breeders can finetune their selection process for
which inbreds to study closely by leveraging the "U values," a
statistical concept that accounts for the reliability of estimates. Yu
also said the study shows that implementing a selection process that
accounts for prediction and statistical reliability can help plant
breeders zero in on desirable crop genetics faster.

Making sense of a universe of corn genetics â?? News Service â?? Iowa State
University (iastate.edu)
[www.news.iastate.edu]