SEPTEMBER 2026  SEEDWORLD.COM /  31
or drones. The June print edition of Seed World 
U.S. explored how AI accelerates phenotyping and 
breeding progress through image analysis.
Another emerging application is helping 
breeders evaluate how leaf orientation traits can 
support higher crop productivity — particularly 
in corn, where high-density planting is the norm. 
Using realistic digital versions of breeding plots, or 
“virtual fields,” researchers can test thousands of 
canopy scenarios before a single seed goes into 
the ground.
High plant density means increased shading 
from close-by plants, which limits light capture 
by individual leaves and in turn, limits overall yield 
potential. In response, some corn plants naturally 
reorient their canopies to optimize light capture 
(orienting leaves perpendicular to the row), a pro­
cess known as canopy reorientation. 
A multi-disciplinary team at Iowa State 
University (ISU) is among worldwide groups of 
scientists working to understand this adaptive 
response is a team. In 2025, the team published 
a study describing an end-to-end AI framework 
that combines realistic 3D reconstructions of 
field-grown corn with models that measure how 
effectively plant leaves absorb photosynthetically 
active radiation (PAR).
How Corn Reorients Its Canopy
Team member and ISU geneticist Yan Zhou 
explains that a corn plant's initial leaf orientation 
is determined by how the kernel is planted. Under 
the shady conditions created by high planting 
densities, however, some plants can reorient their 
canopies to capture more sunlight.
“The optimal re-orientation is off-row-parallel,” 
Zhou says, “because a canopy of plants exhibiting 
this orientation does a better job of capturing the 
sunlight.” 
To understand how canopy architecture influ­
ences light interception, researchers first needed a 
reliable way to measure it. Because light and shade 
shift throughout the day and as the crop develops, 
traditional field measurements capture only part 
of the picture. The team addressed that challenge 
by creating digital twins of corn genotypes to build 
and validate "virtual fields," while using computa­
tional models to evaluate PAR.
This team found that (at 30-inch row spacing) 
off-row-parallel leaf orientations intercepted, 
on average, about 22% more PAR than on-row-
parallel and about 14% more than random 
orientations. While greater PAR interception does 
not directly translate into an equivalent increase 
in yield, it identifies canopy architectures that may 
offer breeders additional opportunities to improve 
hybrid performance. They also made a detailed 
analysis of the impact of canopy orientations, plant 
and row spacings, and planting row directions 
on PAR interception throughout an entire typical 
growing season.
AI Moves From Analysis to Selection
Zhou explains that the team’s research attracted 
AI-generated virtual 
canopies allow 
researchers to 
compare different 
leaf orientations and 
measure how each 
configuration 
captures sunlight 
throughout the day, 
helping breeders 
identify promising 
plant architectures 
before field testing.
PHOTO: NASLA SALEEM, 
IOWA STATE UNIVERSITY

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