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Stalk lodging (structural failure crops prior to harvest) significantly reduces annual yields of vital grain crops. The lack of standardized, high throughput phenotyping methods capable of quantifying biomechanical plant traits prevents comprehensive understanding of the genetic architecture of stalk lodging resistance. A phenotyping pipeline developed to enable higher throughput biomechanical measurements of plant traits related to stalk lodging is presented. The methods were developed using principles from the fields of engineering mechanics and metrology and they enable retention of plant-specific data instead of averaging data across plots as is typical in most phenotyping studies. This pipeline was specifically designed to be implemented in large experimental studies and has been used to phenotype over 40,000 maize stalks. The pipeline includes both lab- and field-based phenotyping methodologies and enables the collection of metadata. Best practices learned by implementing this pipeline over the past three years are presented. The specific instruments (including model numbers and manufacturers) that work well for these methods are presented, however comparable instruments may be used in conjunction with these methods as seen fit. • Efficient methods to measure biomechanical traits and record metadata related to stalk lodging. • Can be used in studies with large sample sizes (i.e., > 1,000). 

Context: Stalk lodging causes up to 43 % of yield losses in maize (Zea mays L.) worldwide, significantly worsening food and feed shortages. Stalk lodging resistance is a complex trait specified by several structural, material, and geometric phenotypes. However, the identity, relative contribution, and genetic tractability of these intermediate phenotypes remain unknown. Objective: The study is designed to identify and evaluate plant-, organ-, and tissue-level intermediate phenotypes associated with stalk lodging resistance following standardized phenotyping protocols and to understand the variation and genetic tractability of these intermediate phenotypes. Methods: We examined 16 diverse maize hybrids in two environments to identify and evaluate intermediate phenotypes associated with stalk flexural stiffness, a reliable indicator of stalk lodging resistance, at physiological maturity. Engineering-informed and machine learning models were employed to understand relationships among intermediate phenotypes and stalk flexural stiffness. Results: Stalk flexural stiffness showed significant genetic variation and high heritability (0.64) in the evaluated hybrids. Significant genetic variation and comparable heritability for the cross-sectional moment of inertia and Young’s modulus indicated that geometric and material properties are under tight genetic control and play a combinatorial role in determining stalk lodging resistance. Among the twelve internode-level traits measured on the bottom and the ear internode, most traits exhibited significant genetic variation among hybrids, moderate to high heritability, and considerable effect of genotype × environment interaction. The marginal statistical model based on structural engineering beam theory revealed that 74–80 % of the phenotypic variation for flexural stiffness was explained by accounting for the major diameter, minor diameter, and rind thickness of the stalks. The machine learning model explained a relatively modest proportion (58–62 %) of the variation for flexural stiffness.