Biomechanics of nodal, seminal and lateral roots of barley: effects of diameter, waterlogging and mechanical impedance

Abstract

Biomechanical properties of cereal root systems largely control both resistance to root lodging and their ability to stabilise soil. Abiotic stresses can greatly modify root system growth and form. In this paper the effect of waterlogging and moderate mechanical impedance on root biomechanics is studied for both lateral roots and the main axes of barley. Barley (Hordeum vulgare) plants were subjected to transient water-logging and moderate mechanical impedance in repacked soil columns. Roots were excavated, separated into types (nodal, seminal or lateral) and tested in tension to measure strength and elastic modulus. Water-logging and mechanical impedance substantially changed root system growth whilst root biomechanical properties were affected by waterlogging. Root strength was generally greater in thin roots and depended on root type. For example, seminal roots 0.4–0.6 mm in diameter were approximately seven times stronger and five times stiffer than lateral roots of the same diameter when mechanically impeded. Root sample populations typically exhibited negative power-law relationships between root strength and diameter for all root types. Mechanical impedance slowed seminal root elongation by approximately 50 % and resulted in a 15 % and 11 % increase in the diameter of in nodal and seminal roots respectively. Power-law relationships between root diameter and root biomechanical properties corresponded to the different root types. Coefficients for between root diameter, strength and elastic modulus improved when separated by root type, with R2 values increasing in some roots from 0.05 to 0.71 for root strength and 0.08 to 0.74 for elastic modulus. Moderate mechanical impedance did not influence the tensile strength of roots, but, waterlogging diminished the relationship between root strength and diameter. Separation of root type improved predictions of root strength and elastic modulus using power-law regressions.