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This study evaluates the impact of subsoil constraints on wheat yield and the effectiveness of constraint removal. Results show varied responses influenced by soil type, severity of constraint, and season, with factors affecting yield outcomes detailed. Takeaway messages emphasize benefits in severe constraints, typical constraints in high-yielding, wet locations, while risks are prevalent in mild constraints, low-yielding, dry areas with heavy soils.
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Imma Farre, Bill Bowden, Stephen Davies & Dennis van Gool Department of Agriculture and Food Western Australia Removal of a subsoil constraint. When does it pay?
The issue Aims of the work Methodology Results Conclusions Take home message Outline
Introduction - Subsoil constraints lead to a reduction in root growth, which results in reduced yield. - Constraint removal can have positive or negative effects on yield, depending on season, location, soil type and constraint level. - Simulation modelling can be used to give an indication of the level of risk associated with removal of subsoil constraints. - Aim: to assess the impact of soil type, location, season and severity of the constraint on the yield response of wheat to removal of a non-specific subsoil constraint.
Methods APSIM-Wheat simulations Loc: 30 locations in WA Soil types: loamy duplex (heavy) loamy sand (light) Years: 1957-2006 Constrained root growth at 20-40 cm depth: (non-specific constraint) unconstrained typical severe extreme
Results. Root depth (cm) The different levels of subsoil constraints caused a reduction in final root depth (cm) Mingenew, loamy sand, 1999
Return to amelioration Assuming amelioration cost $40/ha and return $250/t grain
Average yield response to constraint removal Loamy duplexTypical Loamy sandTypical
Frequency of positive responses to constraint removal Loamy duplexTypical Loamy sandTypical
Loamy duplexTypical Loamy duplexSevere Loamy sandTypical Loamy sandSevere
Conclusions • Wheat yield response to constraint removal is on average positive, but can be negative. • The information on probability of positive response becomes important in decision making. • Factors that have the major impact on the size and frequency of the response: • Soil type • Severity of the constraint • Season
Conclusions In summary for this study the following factors are associated with positive, variable or negative responses to constraint removal:
Take home message • Greater benefit if: • Severe and extreme constraints • Typical constraints & High yielding locations & Wet seasons • Light soils • Greater risk if: • Mild constraints & Low yielding locations & Dry seasons & Heavy soils
Paper available - Hard copies - email: imma.farre@agric.wa.gov.au - Online Proceedings of the Australian Agronomy Conference 2010 Thanks