High-density Phenotype Data of Intermediate Phenotypes Associated with Stalk Lodging Resistance in Maize

TL;DR

This paper introduces a large dataset of 11 plant traits related to stalk strength in maize, which can help improve lodging resistance and crop yields.

Contribution

The study provides a high-density phenotypic dataset of intermediate traits for stalk lodging resistance in maize.

Findings

A dataset of 11 intermediate phenotypes was collected from 31,260 stalks across four environments.

The dataset enables genetic mapping and machine learning analyses to understand stalk lodging resistance.

The trait-level resolution allows evaluation of individual traits' contributions to stalk strength.

Abstract

Stalk lodging causes global maize (Zea mays L.) yield losses exceeding $6 billion annually. The poorly resolved genetic architecture of stalk lodging resistance, a key determinant of the ability of a plant to remain upright, poses a major constraint for genetic improvement. Characterizing natural variation in plant traits that influence stalk strength across multiple biological scales, referred to as intermediate phenotypes, is critical for enhancing lodging resistance. Here, we present a high-density phenotypic dataset comprising 11 intermediate phenotypes measured on 31,260 stalks from a maize diversity panel of 566 inbred lines grown in four environments. The dataset captures variation in structural and geometric properties of stalks and provides a foundation for genetic mapping, predictive modeling, and machine learning analyses to dissect the genetic basis of stalk lodging resistance. Moreover, trait-level resolution across a genetically diverse panel enables evaluation of the relative contribution of individual phenotypes to stalk strength. Beyond maize improvement for grain and forage production, this dataset offers valuable opportunities for improving stalk lodging resistance in other grasses.

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