Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

A machine learning-enabled approach to assess trade-offs between growth and stress tolerance in <i>Pooideae</i> grasses following domestication

Jie Yun, Chenyang Yuan, Katherine Irelan, Marie-Jeanne Kabongo, Eldar Urkumbayev, David L. Des Marais

Journal of Experimental Botany · 2025

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Summary

This study employs machine learning-enabled phenotyping of leaf cell kinematics to characterise trade-offs between domestication and drought stress tolerance across six grass species. Domesticated plants exhibited longer leaves, larger division zones, and higher cell production rates than wild species. Whilst final drought-stressed leaf length showed no trade-off, a developmental trade-off emerged: wild species maintained elongation zone size better under drought, suggesting domesticated grasses compensate through extended elongation duration or elevated cell production rather than stress-protective developmental plasticity.

UK applicability

These findings are relevant to UK cereal breeding and climate adaptation strategies, particularly for wheat and barley resilience. The identification of compensatory mechanisms in domesticated grasses may inform breeding programmes seeking to enhance drought resilience without sacrificing yield potential in future climates.

Key measures

Leaf length, division zone size, cell production rates, elongation zone size, cell dimensions and positions (extracted via machine learning from microscope images), drought response in six grass species

Outcomes reported

The study quantified leaf elongation traits (cell dimensions, division zone size, cell production rates) in domesticated versus wild grass species under control and drought conditions using machine learning image analysis. Trade-offs in developmental response to drought were identified: domesticated species showed greater reductions in elongation zone size under drought stress compared with wild species, despite similar final leaf length outcomes.

Theme
Climate & resilience
Subject
Cereals & grains
Study type
Research
Study design
Comparative experimental study
Source type
Peer-reviewed study
Status
Published
System type
Arable cereals
DOI
10.1093/jxb/eraf344
Catalogue ID
SNmoqqtc08-ae6g9k

Topic tags

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