THE POTENTIAL TO USE CARBON ISOTOPE DISCRIMINATION AS A SELECTION TOOL TO IMPROVE WATER-USE EFFICIENCY IN SOYBEAN
1Queensland Department of Primary Industries, PO Box 23, Kingaroy, Qld 4610
2Department of Agronomy and Farming Systems, University of Adelaide, Roseworthy, SA 5371
Soybean (Glycine max) is an important grain legume in rainfed production systems, where intermittent water stress can severely limit yields. Water-use efficiency (WUE), defined as the total yield per unit of water transpired, is a trait that can increase dry matter production when water resources are limited. The substantial effort required in measuring WUE directly has limited its use in plant breeding. Recent research has demonstrated that measurements of carbon isotope discrimination (Δ), or even specific leaf area (SLA), can provide simple indirect estimates of WUE. This paper describes an experiment to assess genotypic variation in soybean, and the degree of correlation of Δ, and SLA with WUE.
An experiment conducted at Kingaroy, south-east Queensland, in which mini-lysimeters were embedded in small canopies. Total water transpired and total biomass (including roots), were measured and WUE calculated for six soybean genotypes of diverse origin. Fully irrigated and water stressed treatments were imposed over a 60 day period during the late vegetative to early reproductive phase. Δ and SLA (cm2/g) were measured on leaf samples at the end of the period.
Significant genotypic variation in WUE was demonstrated, ranging from 1.66 to 2.44 g/kg and 2.03 to 2.78 g/kg under irrigated and water stressed conditions, respectively. There was highly significant correlation between Δ and WUE under both treatments (Fig.1), while SLA and WUE were poorly correlated. The results suggest that Δ may be a useful selection index for improved WUE in soybean breeding programs.
Figure 1. The relationship between WUE and Δ for soybean genotypes under well watered (open symbols) and stressed (closed symbols) conditions.
Funded by the Australian Centre for International Agricultural Research (PN9216).