Study a marriage of technology and first-hand knowledge

Figure 1. Gap between potential and actual yield within a paddock in Buntine.

By Mike Wong, Greg Lyle, Kathy Wittwer, Richard Bell, Senthold Asseng, Niraf Khimashia and Osamu Sasaki

The latest technology and farmers" firsthand knowledge will be combined in a three-year project to map and measure the impact of subsoil constraints in Western Australia.

The results are expected to directly benefit growers, whose yields can be lowered by up to two tonnes per hectare in good years - at a cost to the grower of about $400 a hectare.

This collaboration between CSIRO and Murdoch University aims to work with growers to improve their ability to manage subsoil constraints for profits based on more precise knowledge of their spatial distribution and their impact on grain yield and income. A student will be trained in research methods related to subsoil constraints as part of the project, thereby boosting capacity to tackle this challenge.

The project team will work with growers to develop:

Buntine (Liebe Group) and Mingenew (Mingenew Irwin Group), both within the Northern Agricultural Region of Western Australia, are the project sites but the benefits of the knowledge gained will spread further afield in WA because it will be based on understanding of underlying biophysical processes.

The findings will be spread through the WA Grower Group Alliance. This work will be linked with our studies in precision agriculture (SIP09), the DAWA/UWA subsoil project UWA00081, DAW00014 (lime injection to counteract subsoil acidity) and subsoil mapping activities carried out under project CSO216 in the Mallee of South Australia.

Table 1 illustrates the importance of knowing the spatial distribution of subsoil constraints, since areas within the same paddock can have both acidic (locations 4, 8, 11, 12 and 14) and alkaline subsoils (locations 16 and 17). Yield at the extremely subsoil acidic sites 11 and 14 were low (Figure 1) but wheat did well on the subsoil alkaline sites 16 and 17.

Adding lime to locations such as 16 and 17 would adversely affect lupin yield and could result in micronutrient deficiencies in wheat for several years; hence the importance of locating where different types of subsoil constraints occur.

Figure 1. Gap between potential and actual yield within a paddock in Buntine.

To predict the spatial distribution and severity of subsoil constraints, the project is using several layers of evidence including yield maps, satellite imagery, digital terrain models, soil conductivity, gamma radiometric and soil maps together with the farmers" own knowledge. The spatial prediction of subsoil constraints uses the Weight of Evidence model developed for soil property and land suitability mapping in CSIRO/GRDC co-funded project CSO 205.

Initial analysis of the spatial data involved:

Our EM38 values were not clearly related to residual water, presumably because of large differences in soil clay content, gravel content and salinity. These factors impact on the electrical conductivity sensed by EM38 and complicate simple relationships with residual moisture and areas of subsoil constraints;

The financial impact of subsoil constraints depends on both seasonal and management factors. These subsoil-season-management interactions are being modelled in APSIM in order to determine risk factors, management strategies and the benefits of subsoil ameliorations compared with the costs.

We used 50 years of climate data for the Liebe and Mingenew Irwin groups to simulate the effect of various patterns of subsoil constraints on root growth and wheat yield under a range of seasonal conditions.

The simulations showed that the benefits of subsoil amelioration are more pronounced in good years when there is more spatial yield variability than in poor years when yield variability is low as all sites perform poorly.

In good years, subsoil amelioration can double yield from 2 to 4t/ha. These yield increases give us an estimate of the benefits of subsoil amelioration. The APSIM predictions will be compared with field data derived from past studies and if possible with contemporary data derived from current DAWA/UWA subsoil work and CSIRO"s northern sandplain project.

In good years, subsoil constraints can lower yield by 2t/ha costing the grower about $400/ha. The cost of identifying and improving these subsoil constraints is not clear yet but more data should become available as the initiative progresses. The initial findings of this project have recently been presented to growers.

For more information: Mike Wong, 08 9333 6299, Mike.Wong@csiro.au
Mike Wong, Greg Lyle, Kathy Wittwer, Senthold Asseng and Niraf Khimashia are from CSIRO. Richard Bell and Osamu Sasaki are from Murdoch University.

GRDC Research Code: CSO00031, program 4