Brace root phenotypes predict root lodging susceptibility and the contribution to anchorage in maize

A changing global climate brings increasingly prevalent and severe storms that threaten crop production by imparting mechanical stresses. Plant failure due to mechanical stress is termed lodging and in the United States, yield loss due to lodging has been estimated at 7-25% for maize (Zea mays). In maize, the presence of specialized aerial brace roots has been shown to increase anchorage and root lodging resistance. However, beyond scoring for presence, there have been limited attempts to define the brace root phenotypes that optimize anchorage. This study reports variable root lodging and plant biomechanics in a population of 52 maize inbred lines. To quantify the variation in brace root phenotypes within this population, a semi-automated phenotyping workflow was developed. These empirical measurements were integrated into predictive random forest models to demonstrate that brace root phenotypes can classify root lodging incidence and plant biomechanics. The prediction accuracy of these models is driven by multiple brace root phenotypes suggesting that anchorage can be optimized by the manipulation of multiple functional traits. Plant height has been previously associated with lodging susceptibility yet the inclusion of plant height as a predictor does not always improve prediction accuracy. Previously, brace root node number has been shown to be genetically linked to plant height and here we show that additional brace root phenotypes are linked to plant height but with opposing effects on root lodging susceptibility. Together these data define the important brace root phenotypes that predict root lodging resistance and demonstrate the need to uncouple the linkage between plant height and root traits for the development of climate resilient crops.

Maize brace roots provide stalk anchorage

Mechanical failure, known as lodging, negatively impacts yield and grain quality in crops. Limiting crop loss from lodging requires an understanding of the plant traits that contribute to lodging-resistance. In maize, specialized aerial brace roots are reported to reduce root lodging. However, their direct contribution to plant biomechanics has not been measured. In this manuscript, we find that brace roots establish a rigid base (i.e. stalk anchorage) to limit plant deflection in maize. The more brace root whorls that contact the soil, the greater the contribution of brace roots to anchorage. Previous studies have linked the number of brace root whorls to flowering time in maize. To determine if flowering time selection alters the brace root contribution to anchorage, a subset of the Hallauer’s Tusón tropical population was analyzed. Despite a significant change in flowering time, selection neither altered the number of brace root whorls in the soil nor the overall contribution of brace roots to anchorage. These results demonstrate that brace roots provide a rigid base in maize, but the contribution to anchorage is not linearly related to flowering time.

Measurement accuracy and uncertainty in plant biomechanics

All scientific measurements are affected to some degree by both systematic and random errors. The quantification of these errors supports correct interpretation of data, thus supporting scientific progress. Absence of information regarding reliability and accuracy can slow scientific progress, and can lead to a reproducibility crisis. Here we consider both measurement theory and plant biomechanics literature. Drawing from measurement theory literature, we review techniques for assessing both the accuracy and uncertainty of a measurement process. In our survey of plant biomechanics literature, we found that direct assessment of measurement accuracy and uncertainty is not yet common. The advantages and disadvantages of efforts to quantify measurement accuracy and uncertainty are discussed. We conclude with recommended best practices for improving the scientific rigor in plant biomechanics through attention to the issues of measurement accuracy and uncertainty.