Focus paddocks 2014 trial report

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As a result of analyses of samples from 184 focus paddocks, we defined several key findings and ordered them into eleven categories: crop and pasture sequence; pasture quality; soil carbon; soil acidity; soil nitrogen (N); soil phosphorus (P); soil potassium (K); soil sulphur (S); soil micronutrients; PreDicta B; and herbicide resistance.

Crop and pasture sequence

The survey results reflect recent changes in farming systems in south-western Australia and the regional differences that would be expected.

Wheat continues to dominate land use — used over 60% of the time.

The amount of wheat used was greatest in the Northern Agricultural Region (NAR) — 68% compared to the Central Agricultural Region (CAR) (58%) and Southern Agricultural Region (SAR) (49%).

Canola was the most used break crop at around 10% for each region.

Diversity of crop species was limited, with four species — wheat, canola, barley and lupin — accounting for 84% of land use.

By region, wheat, canola, barley and lupin accounted for 90% of land use in the NAR, 83% in the CAR and 78% in the SAR.

Pastures made up 12% of land use overall.

There was also a regional difference in pasture usage — in the NAR (7%), CAR (12%) and SAR (21%).

The regional differences in land use described above resulted in different crop and pasture sequences being employed across regions.

For example, the number of paddocks that were one-year in, one-year out of wheat, that is, W/x/W/x was 61% in the NAR, 46% in the CAR and only 30% in the SAR.

Piechart showing percentage of Northern Agricultural Region paddocks with different sequences of crop and pastures from  2010 to 2012
Figure 1 Northern Agricultural Region crop and pasture sequences in each paddock, 2010–12 (W = wheat, Pa = pasture, B = barley, C = canola, L = legume)

Pasture quality

There is a large range in pasture legume content across the monitored paddocks, from zero to almost 100%.

Composition at establishment generally reflects pasture composition in spring.

Plant density and legume content was related to the intensity of pasture within a crop sequence.

Table 1 Intensity of pasture phases according to region in 2013
Years from previous pasture NAR CAR SAR
0 2 1 14
1 1 8 -
2 or more 4 2 2
Bar graph showing average total and legume plant density at different intensities of pasture phases in 2012 and 2013
Figure 2 Average total and legume plant density at different intensities of pasture phases in 2012 and 2013

Soil carbon

In our survey, we observed soil carbon content to be strongly related to rainfall or biomass production, with the focus paddocks recording average soil carbon of 0.9% in the NAR, 1.0% in the CAR and 2.4% in the SAR.

We predicted growing season mineralisation based on a C:N ratio of 13 to derive a soil organic nitrogen content of which 4% was estimated to mineralise over the growing season.

This gave an average growing season mineralisation rate of 46 kilograms of nitrogen per hectare (kg N/ha) for the NAR, 65kg N/ha CAR and 98kg N/ha SAR.

Map of agricultural zone of Western Australia showing soil carbon classes over various sites.
Figure 3 Soil carbon (see legend for classes) measured at 0–10cm from 2010–13

Soil acidity

Soil acidity (low soil pH) is a widespread problem within the wheatbelt of Western Australia.

This was observed with 75% of paddocks sampled having pHCa values of <5.5 in the topsoil (0–10cm) and <4.8 in the mid soil layer (10–20cm), or both.

Regional differences were observed with NAR paddocks having 50% of soils acidic in the top 10cm compared to the CAR (31%) and the SAR (90%).

However, the frequency of acid soil in the layers below 10cm was higher in the NAR (48%) compared to the CAR (18%) and SAR (5%).

Map of agricultural zone of Western Australia showing soil pH for the 0-10cm layer at various sites.
Figure 4 Soil pHCa for the 0–10cm soil layer (average over 2012 and 2013 measurements)
Map of agricultural zone of Western Australia showing soil pH for the 10-20cm layer at various sites.
Figure 5 Soil pHCa for the 10–20cm soil layer (average over 2012 and 2013 measurements)

Soil nitrogen

Soil profile inorganic nitrogen (N) of the focus paddocks was high, with average values ranging from 83 to 96kg N/ha for the four sampling years.

Variations in soil profile inorganic N related to fallow period rainfall (1 October to 31 April).

The occurrence of summer rainfall events was highly variable between the monitoring years and the regions.

However, soil profile inorganic N content of <60kg/ha was more frequent in 2013 (39%) and 2012 (30%) compared to 2010 (20%) and 2011 (19%).

This variation was associated with rainfall within the fallow period.

Regional differences were observed with the NAR paddocks having yearly averages for soil profile inorganic N ranging from 72-92kg N/ha, in the CAR from 94–117kg N/ha, and in the SAR from 81–73kg N/ha.

There were effects relating to the growth of legumes.

In 2012 paddocks following legumes grown in 2011 had on average 14kg N/ha higher soil profile N content than paddocks following wheat or canola grown in 2011.

In 2013 this difference was not observed.

It should be noted that soil profile measurements taken in autumn will underestimate the N benefits of previous legumes because these measurements only account for fallow period mineralisation and further mineralisation will occur during the growing season.


Sulphur (S) levels were good with an average of 20mg S/kg across all paddocks at 0–10cm.

The majority of paddocks (90%) had 0–10cm levels considered adequate for wheat.

We also tested for sulphur-deficient paddocks using 0–30cm soil samples.

Using this method, we identified that 7% of paddocks required fertiliser application to grow wheat and 25% required fertiliser application to grow canola.

It should also be noted that S nutrition in cropping systems is managed by the application of phosphorous and nitrogen fertiliser containing S.

For example, ammonium sulphate contains 24% S and many of the commercial compound fertiliser products contain 3–17%, while urea contains none.

Hence, it is highly likely that paddocks will have S applied annually.


Levels of soil phosphorus (P) were generally good, with the average of all paddocks of 36mg P/kg at 0–10cm and in many cases P levels were well in excess of crop requirements.

The majority of paddocks (71%) had 0–10cm levels considered adequate for wheat.

There was a regional trend, with the NAR at 30mg P/kg, the CAR at 38mg P/kg and the SAR at 48mg P/kg at 0–10cm.

It should be noted that on many sandy textured soils within the Mingenew and adjacent shires soils were low in P in the top 10cm.

However, of the NAR paddocks, 97% had good levels of mid soil P (>4mg P/kg at 10–20cm).

The phosphorus buffering index (PBI) was <70 for 82% of paddocks and where the PBI was >70, all paddocks had P soil test values >25mg/kg.


Potassium (K) levels were generally good with an average K of 132mg/kg at 0–10cm.

The majority of paddocks (85%) had 0–10cm levels considered adequate for wheat.

By region, the proportion of soil test values above 50mg K/kg was NAR (85%), CAR (82%) and SAR (97%).

There was little difference between regional averages, with the NAR 134mg K/kg, CAR 140mg K/kg and SAR 121mg K/kg.


Soil B test values were <0.5mg/kg in 34% of paddocks.

Values >12mg B/kg in soil layers below 10cm — an indication of B toxicity — occurred in 6% of paddocks.

Soil Cu test values of <0.4mg Cu/kg occurred in 24% of paddocks.

Soil Zn test values of <0.4mg Zn/kg occurred in only 4% of paddocks.

There was a high frequency (70%) of paddocks with soil Mn test values of <10mg Mn/kg.

Hence, additional plant testing should be undertaken to determine Mn fertiliser requirements, especially when lupin are grown on limed soils.

PreDicta B

There were few paddocks (<5%) that had root pathogens present at levels that would cause yield loss above 15%, according to the PreDicta B results.

The incidence and severity of some diseases, including rhizoctonia and crown rot, increased over the period of the survey.

Of the nematodes, Pratylenchus neglectus was found in 36% of paddocks, Pratylenchus teres in 6% and Pratylenchus thornei in 3%.

In most cases, these were at low levels and yield loss was not estimated to be high.

By region, there were differences in disease spread.

For example, common root rot was most common in the NAR and crown rot was most common in the SAR.

These observations are consistent with current understanding of the ranges of these pathogens.

The level of disease was affected by the crop species used and this was reflected within the crop sequences.

Notably, canola reduced the build-up of both rhizoctonia and take-all, and including canola in the rotation reduced inoculum levels for the rest of the crop sequence.

Herbicide resistance

Ryegrass populations from 108 paddocks were collected and tested for resistance to a range of herbicides.

Resistance to the herbicides tested was common — populations in 90% of paddocks survived the application of one herbicide; 64% survived two herbicides and 4% survived three herbicides.

The majority of paddocks (81%) contained ryegrass populations resistant to Hoegrass.

The amount of resistance found was greatest in the NAR (97%), CAR (86%) and SAR (64%).

The majority of paddocks (90%) contained ryegrass populations resistant to Logran.

The amount of resistance found was greatest in the NAR (97%), followed by the CAR (86%) and the SAR (64%).

Overall, 8% of paddocks contained populations that were either resistant or developing resistance to Select.

The number of resistant populations was 3% in the NAR, 11% in the CAR and zero in the SAR.

One paddock was found with ryegrass resistant to trifluralin in the CAR.

There were no populations with atrazine or glyphosate resistance.


This study was funded by the Grain Research and Development Corporation (GRDC) through DAFWA project DAW00213.

We acknowledge the support of many grain growers who hosted experiments on their properties and staff from the Mingenew–Irwin Group, Liebe Group, Western Australian No-Till Farmers Association, Facey Group and DAFWA for field monitoring.

We also thank DAFWA Technical Officer Jo Walker for coordinating field monitoring across these groups.


Martin Harries
Geoff Anderson