28  / SEEDWORLD.COM  JUNE 2026
> With imaging platforms, aerial analysis and 
growing datasets, breeders are beginning 
to shorten selection timelines and improve 
accuracy.
> By Treena Hein, Seed World U.S. Contributor
> initializing_model(“plant_reader”)
> training...
> Teaching 
 Teaching 
Machines to 
Machines to 
Read Plants
Read Plants
> status: learning
IT’S 
safe to say crop breeding has never been more 
exciting. Decades ago, breeders transformed the 
field by scaling up plot numbers and enabling wide-scale phe­
notype selection. Years later, genome mapping and new genetic 
technologies drove another shift. Now, AI is pushing crop breed­
ing into its next phase, and the industry is paying attention.
First, the big picture. In 2025 alone, researchers published 
numerous scientific reviews examining how AI is changing crop 
breeding. In one review, a team in India explains that “advances 
in genomics, phenomics and environmental sensing have ena­
bled the development of high-dimensional datasets, fostering 
more precise and efficient breeding strategies.” They note that 
AI-driven approaches, including machine learning models such 
as random forests and convolutional neural networks, improve 
phenotypic predictions and yield forecasting. Deep learning also 
accelerates genotype-to-phenotype mapping by extracting key 
traits from large-scale datasets.
The team adds “AI-powered genomic selection and gene 
editing tools... are revolutionizing targeted breeding.”
In June 2025, U.S. Department of Agriculture (USDA) scien­
tists Worasit Sangjan, Daniel Kick and Jacob Washburn pub­
Chris Reberg-Horton, North Carolina State 
University researcher, works with large-scale 
plant imaging datasets designed to train AI 
systems to recognize species, growth stages and 
key traits across environments. 
PHOTO: NC STATE 

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