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

Plant domestication may create trade-offs between growth and stress tolerance, raising concerns about yield stability in future climates. Previous studies have found limited direct evidence for such trade-offs, often focusing on weakened defenses associated with higher growth rates. Trade-offs can also occur when traits optimized for favorable conditions perform less efficiently under stress. Deciphering these mechanisms is crucial for maintaining growth in changing environments. We examine one key aspect of vegetative growth, leaf elongation, in six species of grasses. We use a machine learning-enabled pipeline to extract cell dimensions and positions from leaf microscope images to study cell kinematics. We find that domesticated plants generally have longer leaves, larger division zones, and higher cell production rates. While no clear trade-off is observed between domestication and drought response in final leaf length, a trade-off occurs in development; wild species exhibit a smalle..., The species studied are listed in Table 1. Both domesticated wheat varieties (Triticum turgidum L. var. Durum 'Langdon' and 'Svevo', Triticum aestivum 'Chinese Spring') and wild emmer wheat (Triticum turgidum L. subsp. dicoccoides 'Zavitan' and 'Vavilovii') were subjected to a pre-germination treatment at 32°C dry conditions for 7 days, followed by 4°C dry conditions for 2 days. Domesticated oat (Avena sativa cv. 'Sang'), wild oat (Avena insularis 'BYU 207'), domesticated barley (Hordeum vulgare 'Morex'), wild barley (Hordeum vulgare L. subsp. spontaneum), and Brachypodium distachyon (Bd21) seeds were placed at 4°C in water for 7 days to synchronize germination. After cold treatment, all seeds were soaked in Gibberellic Acid for 1 day to promote uniform germination. Seeds were then planted in Kord square pots (the HC Companies, OH, USA) filled with 70g of Profile porous ceramic rooting media (Profile Products, Buffalo Grove, IL).

Common name
Scientific name
Accession identifier
Name ..., , # A machine learning enabled approach to assess trade-offs between growth and stress tolerance in Pooideae grasses following domestication

[https://doi.org/10.5061/dryad.47d7wm3pp](https://doi.org/10.5061/dryad.47d7wm3pp)

This folder contains data and microscopy images for the paper: 

Jie Yun, Chenyang Yuan, Katherine Irelan, Marie-Jeanne Kabongo, Eldar Urkumbayev, David L Des Marais, A machine learning enabled approach to assess trade-offs between growth and stress tolerance in Pooideae grasses following domestication, *Journal of Experimental Botany*

Comments and requests should be addressed to Jie Yun ([[e-mail]](mailto:[e-mail])).

This folder contains

* leaf_elongation_data.xlsx 

This dataset includes the tab leaf_elongation_data, which has the 3rd leaf length measurement along with thermal time in samples harvested for leaf elongation. The tab sample_info has sample species and conditions.

In the leaf_elongation_data tab, columns are thermal time, and rows are n...,