Influence of photothermal quotient in the critical period on yield potential of cereals–A comparison of wheat and barley

Abstract

Context

Research in grain crops has focused on understanding the critical period (CP) for yield formation to develop genetic and agronomic options that minimize stress or resource limitation during this time. While the link between the photothermal quotient (PTQ) in the CP and yield potential is known for wheat, it needs re-evaluation with current genetics and agronomy, and is less explored in barley, especially in high productivity areas.

Objective

Our aim was to determine if a) the PTQ-yield relationship in wheat has evolved with new cultivars and agronomic practices, and b) if barley shares similar CP timing and duration with wheat or requires species-specific adjustments in high production zones.

Methods

From trials In the Australian high production zones, we compiled a dataset (25 site-years) of high-yielding wheat and barley from carefully managed field experiments. The sites analysed had barley and wheat varying in genetics and management across different photothermal environments and where seasonal water supply exceeded 400 mm, and were not constrained by nutrients, allowing us to evaluate the sensitivity to relationship between radiation and temperature during the CP on yield potential.

Results

We created a new PTQ-based yield potential frontier for wheat and barley, measuring yield increase per PTQ unit. The best model used PTQ data from 20 days before to 10 days after flowering. In barley, changes in the CP timing and length didn't affect the results as expected. The slope of the relationship was lower for barley, indicating lower yields at higher PTQ compared to wheat, highlighting their physiological differences.

Conclusions

Our study shows Australia's wheat and barley yields, over 15 Mg ha⁻¹ in wheat and >12 Mg ha⁻¹ in barley respectively, are more influenced by PTQ during the CP than by seasonal water when water supply estimates exceed 400 mm in Australia. We present a simple, physiologically sound PTQ equation as a yield benchmark for wheat (WPYptq= 10.62PTQ-2.85) and barley (BPYptq= 6.73PTQ+1.65).

Implications

Efforts in agronomy and breeding should aim at enhancing resource availability and partitioning during the CP and aligning the CP with environmental conditions. The straightforward PTQ model for predicting yield potential in Australia's higher production areas matches complex simulations well, aiding in optimizing production systems and guiding future yield potential research.