Integrating yield gap analysis to capture genotype by environment by management interactions for Australian broadacre sorghum cropping systems

Abstract

Context

Australia contributes ∼ 3 % of the global grain sorghum production despite relatively large gaps between water-limited potential (PYw) and attainable on-farm (AYw) yields. With sorghum yield gaps typically 59 % of the PYw in Australia, it is important to identify the drivers of these yield gaps and what are the optimal genotype (G) × environment (E) × management (M) combinations needed for sustainable improvement of sorghum productivity.

Objectives

APSIM farming systems modelling framework was used to simulate comprehensive G × E × M scenarios for sorghum in Australia using modern hybrids and current management to (1) define the PYw fronts and identify key drivers of spatial sorghum yield variability, and (2) determine desirable G × M combinations that can improve sorghum productivity and stability across the expected range of seasonal evapotranspiration (ET) for the Australian Target Population of Environments (TPE).

Methods

We use a set of 70 comprehensive national variety trials (NVT) data from 2017 – 2021 to parameterize and evaluate APSIM and then subsequently apply the model to define the range of G × E × M dimensions for sorghum TPEs in Australia. From these, we systematically simulate 93 sites-soil combinations for 103 years to extend the NVT to other fields beyond the NVT sites directly sampled. Using yield frontier analysis, we then define the expected PYw fronts, yield variability and the drivers of this variability.

Results

A non-linear relationship was observed between simulated grain yields and seasonal ET with most yields between 2.6 and 4.5 t ha⁻¹ associated with an ET of 167 – 420 mm. The yield opportunity frontiers were estimated to fall between 9.4 t ha⁻¹ (Q80 %) and 12.0 t ha⁻¹ (Q99 %). Nitrogen application rate at sowing explained the greatest component of the grain yield variation across most subregions. We found that most crop failures (defined as yield at or below Q10 %; 1.1 t ha⁻¹) occurred under low N and high plant density with greater risks in North-East and North-Central Queensland. Yield failure risks were higher at higher densities, while earlier sowing buffered against these crop failures.

Conclusions

This study estimated PYw fronts and yield gap distributions for sorghum, elucidating the drivers of spatial sorghum yield variability for the Australian sorghum TPE. This finding highlights potential opportunities to close the on-farm yield gaps through optimized region-specific agronomic recommendations.