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Calcareous soils are widely spread in arid and semi-arid regions and cover almost one-third of the world's land surface area. This chapter gives an overview of the distribution and characteristics of calcareous soils, the limitations of calcareous soils for crop production, and some of the sustainable management practices to overcome crop productivity constraints in calcareous soils. Calcareous soils are characterized by the presence of calcium carbonate (CaCO3) in the soil parent material and the consequent accumulation of free CaCO3in the soil profile. The pH of these soils is usually above 7, and, in the presence of free sodium carbonate, it may exceed 9. In some soils, the free CaCO3can concentrate into hard layers, known as ‘caliche’, that are impermeable to water infiltration and plant root penetration. Although calcareous soils may be dominated by free CaCO3, they may also contain significant amounts of iron (Fe), aluminium (Al), and manganese (Mn) either as discrete and mixed minerals, coatings on soil inorganic size fractions such as clay, sand, and silt, or complexed with soil organic matter. The major crop productivity constraints in calcareous soils include phosphorus and trace element (e.g., iron, zinc, and copper) deficiency, surface crust formation, and an impermeable subsurface compact layer. Soil productivity constraints in calcareous soils can be overcome by proper choice and placement of fertilizers, addition of organic matter, which promotes stable aggregate formation that inhibits dispersion and resists crust formation, and deep ripping to break through the compacted pan layer, thereby allowing root access to soil water and nutrients beneath this layer.

Rotations and associated management practices in rainfed farming systems of southwest Australia have shifted towards intensified cropping. Survey data from 184 fields spanning 14Mha of southwest Australia were used to document water use efficiency (WUE) and water-limited yield potential (WLYP) of commercial crops and crop sequences and identify biophysical variables influencing WUE. WUE achieved in commercial wheat crops was 10.7kggrain/ha.mm. Using a boundary function Ywl=25×(WU−45), farmers achieved 54% of WLYP. Climate variables affected WUE more than management and biotic variates, the highest latitude region having WUE of 9.0kggrain/ha.mm, compared to 11.8kggrain/ha.mm for regions further south. Increased soil nitrogen and nitrogen fertiliser increased WUE, as did sowing earlier; in keeping with farmers in southern Australia sowing crops earlier and trebling fertiliser nitrogen usage since 1990. Wheat yield and WUE increased a small amount after break crop or pasture (12.5kggrain/ha.mm) compared to wheat grown after wheat (11.2kggrain/ha.mm), due to good weed and root pathogen control, and high fertiliser nitrogen application. However, WUE of wheat declined to 8.4kggrain/ha.mm when more than three wheat crops were grown in succession. Farmers continue to improve WUE with increased inputs and new technologies replacing some traditional functions of break crops and pasture. However, break crops and pastures are still required within the rotation to maintain WUE and break effects need to be measured over several years.

Transient salinity associated with increased dispersion of clays is arguably one of the most economically important soil constraints in Australia because it occurs on land that is regularly cropped. However, this issue is rarely studied. This paper examines the occurrence of transient salinity on agricultural land in the south-west of Western Australia and the factors causing it. We analysed four soil datasets from the region, collected at scales varying from the entire south-west to a single paddock. A variety of soil parameters were correlated with increased electrical conductivity (EC1:5). The most significant relationships were invariably with measures of exchangeable sodium (Na+; 53–85% of variance accounted for), and this factor appears to be most responsible for transient salinity. Another parameter correlated with increased EC1:5 was alkalinity. This has been associated with the increased dispersion of kaolinite and consequent decreases in soil hydraulic conductivity; kaolinite is the most common clay mineral in the south-west of Western Australia. Other factors correlated with increased EC1:5 were increasing clay, increasing depth in the soil profile and decreasing rainfall. These factors are environmental indicators of transient salinity. Affected soils might be ameliorated by application of agents to increase soil hydraulic conductivity, such as gypsum and/or elemental sulfur.

A survey was conducted of commercial broadacre paddocks in the south-west cropping zone of Western Australia from 2010 to 2013. In total, 687 paddock years of data were sampled from 184 paddocks. The land use of each paddock was recorded together with measurements of weed density, the incidence of soilborne pathogen DNA, and soil inorganic nitrogen (nitrate and ammonium). The dynamics of these biophysical variables were related to the crop and pasture sequences employed. Wheat was the most frequent land use (60% of paddock years), followed by canola and pasture (12% each), and lupins and barley (6% each). Four crop species, wheat, canola, barley and lupins, accounted for 84% of land use. By region, wheat, canola, barley and lupin accounted for 90% of land use in the Northern Agricultural Region (NAR), 83% in the Central Agricultural Region (CAR) and 78% in the Southern Agricultural Region (SAR). Conversely, pasture usage in the SAR was 21%, compared with 12% in the CAR and 7% in the NAR. Over the surveyed paddocks, weed density, soilborne pathogens and soil N were maintained at levels suitable for wheat production. The inclusion of land uses other than wheat at the frequency reported maintained the condition of these biophysical variables.

Australian cropping systems are dominated by winter cereals; however, grain legumes, oilseeds and summer cereals play an important role as break crops. Inputs of phosphorus (P) fertiliser account for a significant proportion of farm expenditure on crop nutrition, so effective fertiliser-use guidelines are essential. A national database (BFDC National Database) of field experiments examining yield responses to P fertiliser application has been established. This paper reports the results of interrogating that database using a web application (BFDC Interrogator) to develop calibration relationships between soil P test (0–10cm depth; Colwell NaHCO3 extraction) and relative grain yield. Relationships have been developed for all available data for each crop species, as well as for subsets of those data derived by filtering processes based on experiment quality, presence of abiotic or biotic stressors, P fertiliser placement strategy and subsurface P status. The available dataset contains >730 entries but is dominated by data for lupin (Lupinus angustifolius; 62% of all P experiments) from the south-west of Western Australia. The number of treatment series able to be analysed for other crop species was quite small (<50–60 treatment series) and available data were sometimes from geographic regions or soil types no longer reflective of current production. There is a need for research to improve information on P fertiliser use for key species of grain legumes [faba bean (Vicia faba), lentil (Lens culinaris), chickpea (Cicer arietinum)], oilseeds [canola (Brassica napus), soybean (Glycine max)] and summer cereals [sorghum (Sorghum bicolor), maize (Zea mays)] in soils and farming systems reflecting current production. Interrogations highlighted the importance of quantifying subsurface P reserves to predict P fertiliser response, with consistently higher 0–10cm soil test values required to achieve 90% maximum yield (CV90) when subsurface P was low (<5mg P/kg). This was recorded for lupin, canola and wheat (Triticum aestivum). Crops grown on soils with subsurface P >5mg/kg consistently produced higher relative yields than expected on the basis of a 0–10cm soil test. The lupin dataset illustrated the impact of improving crop yield potentials (through more effective P-fertiliser placement) on critical soil test values. The higher yield potentials arising from placement of P-fertiliser bands deeper in the soil profile resulted in significantly higher CV90 values than for crops grown on the same sites but using less effective (shallower) P placement. This is consistent with deeper bands providing an increased and more accessible volume of profile P enrichment and supports the observation of the importance of crop P supply from soil layers deeper than 0–10cm. Soil P requirements for different species were benchmarked against values determined for wheat or barley (Hordeum vulgare) grown in the same regions and/or soil types as a way of extrapolating available data for less researched species. This approach suggested most species had CV90 values and ranges similar to winter cereals, with evidence of different soil P requirements in only peanut (Arachis hypogaea – much lower) and field pea (Pisum sativum – slightly higher). Unfortunately, sorghum data were so limited that benchmarking against wheat was inconclusive.

Accurate definition of the sulfur (S) soil test–crop grain yield increase (response) relationship is required before soil S test measurements can be used to if there are likely to be responses to S fertilisers. An analysis was done using the Better Fertiliser Decision for Crops (BFDC) National Database using a web application (BFDC Interrogator) to develop calibration relationships between soil S tests (KCl-40 and MCP) using a selection of sampling depths and grain relative yields (RY). Critical soil test values (CSTV) and critical soil test ranges (CSTR) were defined at RY 90%. The ability of the KCl-40 extractable S soil test to predict grain yield response to applied S fertiliser was examined for wheat (Triticum aestivum L.) grown in Western Australia (WA), New South Wales (NSW), and Victoria and canola (Brassica napus L.) grown in WA and NSW. A smaller dataset using MCPi-extractable S was also assessed. The WA-grown wheat KCl-40 S CSTV, using sampling depth to 30cm for soil types Chromosols (Coloured), Chromosols (Sesqui-Nodular), Kandosols (Grey and Yellow), Tenosols (Brown and Yellow), and Tenosols (Grey, Sesqui-Nodular), was 2.8mgkg-1 with an associated CSTR 2.4–3.2mgkg-1 and a correlation coefficient (r) 0.87. Similarly, KCl-40 S CSTV was defined using sampling depth to 10cm for these selected soil types and for wheat grown on Vertosols in NSW. The accuracy of the KCl-40 S CSTV for canola grown in WA was improved using a sampling to a depth of 30cm instead of 10cm for all soil types. The canola KCl-40 S CSTV using sampling depth to 30cm for these soil types was 7.2mgkg-1 with an associated CSTR 6.8–7.5 and an r value 0.70. A similar KCl-40 S CSTV of 7.0mgkg-1 was defined using a sampling depth of 10cm, but the CSTR was higher (6.4–7.7mgkg-1) and the r value lower (0.43). A lower KCl-40 S CSTV of 3.9mgkg-1 or 31.0kgha-1 using a sampling depth of 60cm was defined for canola grown in NSW using a limited number of S-rate calibration treatment series. Both MCPi (r=0.32) and KCl-40 (r <0.20) soil S test–NSW canola response relationships using a 0–10cm sampling depth were weak. The wheat KCl-40 S CSTR of 2.4–3.2mgkg-1 can be used widely on soil types where soil sulfate is not leached during the growing season. However, both the WA canola CSTR of 6.4–7.2mgkg-1 using a sampling depth of 30cm and NSW canola CSTR of 25–39kgha-1 or 3.1–4.9mgkg-1 using a sampling depth of 60cm can be considered in regions outside of WA and NSW.