Finding a balance – optimising sorghum agronomy in Central Queensland and how it has changed over the last 15 years

Author: | Date: 04 Dec 2018

Take home message

  • Many of the agronomy packages for CQ were based on MR-Buster or older Pioneer varieties and have served growers well for many years
  • Higher yielding hybrids are now available with new attributes and characteristics, however, many have not had agronomic packages developed to the same level as MR-Buster which has caused quality and management issues
  • Yield optimisation is a continuous challenge of trying to find an agronomic balance between raw yield and grain quality using the agronomic tools and environment we operate within.

Sorghum has always been considered a key crop in Central Queensland (CQ) and for good reason. The region has a tendency towards a summer predominant rainfall pattern, highly suitable soils and ideal climate for sorghum. However, in the late 1990s/early 2000s it had become apparent to range of growers, consultants and researchers that the industry could be doing significantly better with respect to agronomic management of the crop.

At the time, the Queensland Department of Primary Industries (QDPI) and the Grains Research and Development Corporation (GRDC) had recently funded (1997) phase 1 of a development and extension project – the Central Queensland Sustainable Farming Systems (CQSFS) project.  Sorghum agronomy was quickly identified as a key area of R&D for the group to focus on. This is how a technical report from the project released in November 2002 described the state of play prior to the research commencing:

“Sorghum has the potential to perform better in Central Queensland (CQ) than it currently does. Yield losses from poor stands, weeds, inadequate nutrition, variable and unpredictable rainfall, high temperatures and evaporation, and rain at harvest all combine to increase the riskiness of the crop and reduce overall profitability. The use of wide row and skip row configurations in sorghum has been suggested as a means of metering out water to the growing plant such that there will be some water left between the rows at the end of the season to set grain. Therefore, wide rows and skip row configurations are about maximizing yield in dry finishes rather than maximizing plant growth, which is important in CQ where dry finishes are common.”
(Wide row and skip row configurations in sorghum in Central Queensland - 2001/02 Technical Report (Reid, et al. November 2002))

Over eight years and two phases of the CQSFS project, wide ranging research was conducted into sorghum agronomy within the CQ farming environment. The project partnered with local consultants, seed companies and many grower co-operators right across CQ. Trials were conducted into a range of areas relevant to sorghum agronomy including row spacing and population, weed management and crop nutrition.

The findings

The first technical report, quoted above, was released in 2002 at the end of the first phase of the CQSFS project. It reported on trials conducted over a particularly low rainfall period, so had a strong emphasis on crop security rather the top end yield, and the recommendations reflect this. A second technical report was released, detailing the work conducted from late 2002 to 2004. It sought to answer again specifically on row configurations and plant populations, however this time hoping to fill in the gaps around the effect of wide rows and population in higher yielding scenarios.

By the end of 2004, the project released the second technical report with the following recommendations:

“The effect of configuration on yield appears independent of plant population for both low- and high yielding situations indicating that plant population does not compensate for any yield loss incurred with wide rows. For yield potentials around 4 t/ha, the benefits of wide rows were variable while benefits were again evident in some lower-yielding situations. Tillering was also reduced with wide row configurations.

In high-yielding situations, established plant populations should be around 50,000 plants/ha while in low- to moderate-yielding situations populations should be 40 – 45,000 plants/ha. Populations below these may incur greater tillering, which could increase management difficulties in the crop.

Grain quality was not adversely affected by wide rows. This would be expected if wide rows reduce moisture stress and help plants to remain healthier during the grain filling period. Further, there was no evidence that plant lodging was affected by row width.

As a guide for row configuration and plant population decisions:

  • If yield prospects are low (say < 3 t/ha), aim for around 40,000 plants/ha in wide rows. While a low population/wide row strategy may provide sound yields in tough seasons, a penalty may be expected if the season turns out favourably.
  • If yield prospects are intermediate (say 3 – 4 t/ha), a best-bet low-risk strategy would be to aim for a moderate plant population (40 – 45,000 plants/ha in wide rows.)
  • If yield prospects are high (say > 4 t/ha), aim for around 50,000 plants/ha with a standard row width.”

(Effect of row configurations and plant populations on sorghum production in central Queensland - 2003/04 Technical Report (Reid, et al. 2004)

Weeds

As row spacing increased, crop competition decreased, which allowed significantly more opportunities for weeds to establish and affect yield potential. Vikki Osten and her weeds team in CQ conducted a range of research trials looking at the effect of wide row sorghum on weed management and the possible yield penalties. Table 1 illustrates what type of yield penalties were identified.

Table 1. Identified yield penalties due to weeds for different row configurations of sorghum (Source: V. Osten, DPI&F Emerald)

Row Spacing

Weed free yield (t/ha)

Weedy yield (t/ha)

Yield penalty due to weeds (%)

Weed biomass (g/m2)

Weed seed production

(no./ m2)

2003 trial

1m solid

4.6

1.9

58

230

N/A

1m single skip

3.8

1.6

57

241

N/A

1m double skip

2.9

1.8

39

174

N/A

2004 trial

1m solid

3.0

2.0

33

268

11788

1m single skip

2.6

1.9

29

259

7526

1m double skip

2.7

2.2

19

302

37462

2005 trial

1m solid

3.2

0.6

81

172

2843

1m single skip

2.7

1.2

56

323

13353

1m double skip

2.1

0.5

76

484

20999

It is important to note that while feathertop Rhodes grass was present and causing issues within some areas at this time, it was not yet the region-wide issue it was set to become. Despite this, the table clearly illustrates the effect poorly managed weeds within a crop can have, and how much quicker a wide row spacing system can increase weed seed under these systems.

Work was also being conducted on ground cover effects of different row spacing configurations. Again, it was apparent that there was a trade-off between crop security, ground cover and ultimately fallow water storage. The two graphs in Figure 1 show that as row spacing widened, both ground cover post-harvest and ultimately water stored in the fallow were reduced.

These two column graphs show the graphs taken from ‘More grain from your rain’ or ‘more crop for your drop’: managing rainfall in central queensland dryland cropping systems (Routley et al. 2006) showing the effect of rowspacing on residual ground cover and fallow water storage. Figure 1. Graphs taken from ‘More grain from your rain’ or ‘more crop for your drop’: managing rainfall in Central Queensland dryland cropping systems (Routley et al. 2006) showing the effect of rowspacing on residual ground cover and fallow water storage.

At the end of the second phase of the CQSFS in 2007, an extensive evaluation of the project benefits to farming systems in CQ was made. To provide a snapshot of how things had changed, I have pulled the following caption from pg. 56 of that report:

Row spacing and plant population

Substantial research undertaken by the project helped quantify the effect of wide row configurations on yield of wheat and sorghum. This research has shown that wide row configurations (>1m) are an effective risk management tool in sorghum production and that minimal yield losses are experienced with wheat row spacings of up to 50cm in most conditions. The wheat and sorghum row spacings used in Central Queensland have both increased considerably over the last five years as producers have become aware of the benefits of wider row systems.

There has been a decrease in the average target sorghum plant population used by producers from 45 300 plant/ha to 35 500 plants per ha over the last five years. This change has been supported by project research that has demonstrated that these lower populations are adequate to achieve optimum yield in most seasons and have some benefits in terms of yield stability in dry seasons.

It was pleasing to note a large increase in the number of producers who are prepared to vary plant populations and row configuration in response to seasonal conditions or yield targets, particularly for sorghum. This flexible approach will allow producers to optimise production in an extremely variable climatic environment.” CQSFS 2 (2002 – 2007) An evaluation of project achievements, benefits and outcomes.

10 years on… what’s changed?

Post CQSFS 2 finishing, focus has moved away from direct sorghum agronomy onto other more pressing issues. Growers’ adoption of the wide row spacing systems was extensive and that significantly improved the reliability of the crop in the region and the quality of the grain being produced.

However, feathertop Rhodes grass continued to become more of an issue, particularly in wide row sorghum. Newer chickpea varieties were released which were better suited to CQ and the growth in farm price of chickpea saw growers move away from sorghum as the key crop that it once was, particularly in southern and eastern parts of the CQ region.  Seed companies were also releasing newer sorghum hybrid varieties with traits such as stay green, which didn’t seem to follow the agronomy rules around spray out and desiccation of the older varieties, causing issues with harvest and grain quality.

In 2014, GRDC funded a new northern region project with QAAFI, ‘UQ 000075 Increasing sorghum yield with tactical agronomy’ to address the gaps in knowledge, particularly around maximising yield with newer hybrid types and evaluate if the ‘agronomy rules’ needed to be updated. The project again looked at a range of agronomic configurations, including population x hybrid in various environments and row spacing configurations from CQ down to NNSW.

One of the key observations from that project was that there was still much to do with respect to optimising yield for a given amount of plant available water. Figure 2(a) shows average mean yield for each trial treatment achieved at all the trials completed across Queensland and NSW compared to expected or predicted yield of MR-Buster (environmental yield) for the conditions. Figure 2(b) shows yield achieved for the plant available water for each of the trial sites. As can be seen by the yield variations for any one level of PAW, optimising planting configurations to suit a given hybrid and the conditions it is being planted into can result in significant benefits.

These scatter plots show the treatment mean yield versus environment yield i.e. mean of site yield from all the treatments (a), and (b) relationship between treatment means and available water estimated as soil moisture at sowing (0-1.2m) plus in crop rainfall and added irrigation (if any). Results under preparation for publication. (Rodriguez et al. 2017) Figure 2. Treatment mean yield versus environment yield i.e. mean of site yield from all the treatments (a), and (b) relationship between treatment means and available water estimated as soil moisture at sowing (0-1.2m) plus in crop rainfall and
added irrigation (if any). Results under preparation for publication. (Rodriguez et al. 2017)

Yields ain’t yields

While maximising yield for the water available to the plant is generally always the goal of growers, achieving this at the cost of high screenings and resulting price penalties or screening costs to make the product marketable is not. As part of the tactical agronomy project in CQ, in 2017 four hybrids were grown on both skip row and solid 1m row spacing configurations.

The trial was planted at three different target population densities on two row spacing configurations.

This figure shows yields achieved and yield response curves for the four hybrids used in CQ in 2017 showing significant yield difference between configurations. There was a significant quadratic plant density effect. I.e. A common curve was fit to each combination of hybrid and configuration with each curve having a different intercept value. A common optimum plant density was determined to be at 6.04 plants/m2 (P<0.05) There was a significant difference between the hybrids. Solid configuration had a significantly higher yield than the single skip configuration.   Figure 3. Yields achieved and yield response curves for the four hybrids used in CQ in 2017 showing significant yield difference between configurations. There was a significant quadratic plant density effect. I.e. A common curve was fit to each combination of hybrid and configuration with each curve having a different intercept value. A common optimum plant density was determined to be at 6.04 plants/m2 (P<0.05) There was a significant difference between the hybrids. Solid configuration had a significantly higher yield than the single skip configuration.

PAW at planting (14/02/2017) was 195mm with an additional 222mm in crop, 143 kg of N was available at planting, with an additional 138 kg applied post emergence. The aim was to provide a non-limiting supply of N & P and a full profile of moisture at planting, but then treat the trial as a dryland crop after planting. Most of the 222mm had fallen by the end of March, setting the crop up for a big yield potential, however, there was no additional rain during flowering or grain fill to finish the crop.

Figure 3 shows the yield response curve and actual yields for both the skip row and solid row spacing configurations. After statistical analysis, the yield response curves were added and clearly show that the narrow row, high population configuration maximised yields for the trial conditions for all hybrids. Figure 4 then shows on average for both row configurations, how the four hybrids were developing the yield, for the three population levels.  Typically for all four hybrids in the trial, as population increases, tiller contribution to total yield declines - an observation which is very consistent even in the CQSFS data.

This column graph shows the main stem and tiller contribution to total yield and average screenings across population treatments. There was a significant difference between hybrids for average screenings across treatments (P=0.03), however, there was not a significant difference when hybrid x population density was considered. Figure 4. Main stem and tiller contribution to total yield and average screenings across population treatments. There was a significant difference between hybrids for average screenings across treatments (P=0.03), however, there was not a significant difference when hybrid x population density was considered.

However, when grain size is considered, we observed average screenings for two of the hybrids starting to spike above 5%, and individual plot results in excess of 10% for some of the solid row spacing, higher population treatments (Figure 5).  This raises some interesting observations:

  • Tillers typically have a higher level of screenings than the main stem
  • Significantly lower tiller numbers per plant in high population treatments compared to low population treatments
  • We have repeatedly observed (data not shown) that for a given population, we will typically see more tillering on narrow row configurations than wider row configurations due to higher in-row density in the wide rows.

This column graph shows the average screenings per treatment from both the main stem and tiller stems. For main stem, LSD between treatments was 0.67 of 1% (P=0.05). For tiller stems there was a difference (P=0.055) between population densities across all hybrids, however there was no significant difference in varieties x population x configuration treatments.  Figure 5. Average screenings per treatment from both the main stem and tiller stems. For main stem, LSD between treatments was 0.67 of 1% (P=0.05). For tiller stems there was a difference (P=0.055) between population densities across all hybrids, however there was no significant difference in varieties x population x configuration treatments.

Conclusion

In this nutritionally unlimited trial scenario, the best yields came from high population, narrow row configurations, despite the dry finish. Post-harvest water and N were assessed and there was still 140 mm of PAW available down to 150 cm (though over half of that was sitting below 1 m), yet total screenings (Figure 4) between varieties were significantly different, and tiller screenings were approaching a significant difference (P=0.08) between population densities.

Consistent with the work by the CQSFS team, even in this high yielding scenario, the wider row configurations for all varieties provided good yields with low screenings across the population range and were an obvious safe option even at the higher populations. However, that safety came at a cost of up to 1 t/ha for any given population planted.

When the system was pushed in to the narrower configurations and higher populations than those recommended by the CQSFS work, we were able to achieve a significant yield boost from all varieties. However, we paid the penalty with a spike in screenings, particularly in the hybrids with greater stay-green attributes.  This raises the question, the top end yield of all four hybrids wasn’t that different; were the agronomic practices applied to all not ideal for the stay-green varieties? Do some stay-green or newer hybrids need different management strategies? Is this consistent across other commercial stay-green lines? Interestingly, it is usually the high row density or high population treatments which ripen quicker than the low-density treatments, so if you were going to have issues related to premature spray out, you would have expected higher screenings in the tillers of the low-density treatments.

Precision ag brings with it the potential to spatially place any seed anywhere we want it in the field and any distance away from any other seed. This could be a game changer for many, particularly if we are able find a commercially competitive uniculm or non-tillering sorghum variety to pair with that technology. These innovations, along with herbicide tolerant hybrids, have the potential to rewrite the agronomy book when it comes to sorghum management.

Acknowledgements

The research undertaken as part of this project is made possible by the significant contributions of growers and consultants through both trial cooperation and the support of the GRDC, the author would like to thank them for their continued support.

References

Queensland grains research 2017-18, Regional agronomy, compiled by Jayne Gentry and Tonia Grundy on behalf of the Regional Agronomy Team, Crop and Food Science, Department of Agriculture and Fisheries QLD and GRDC

Summary of recent results from Tactical agronomy for maize and sorghum in the northern grains region, Daniel Rodriguez, QAAFI 2017

Increasing sorghum yield with tactical agronomy, Simon Clarke, Joseph Eyre, Loretta Serafin and Daniel Rodriguez, QAAFI & NSWDPI 2018

‘More grain from your rain’ or ‘more crop for your drop’: managing rainfall in central Queensland dryland cropping systems, Richard Routley, Principal Agronomist, QDPI&F, 2007

Wide row and skip row configurations in sorghum in central Queensland - 2001/02, Technical report – November 2002, Reid, DA, Agius, PB, Bell, MB, Buck, SB, Collins, RB, Conway, MC, Doughton, JC, Farquharson, AD, Kuskie, JC, McCoskerC, K, Osten, VC, and Spackman, GE. QLD Department of Primary Industries and Fisheries & GRDC

Effect of row configurations and plant populations on sorghum production in central Queensland - 2003/04, Technical report – December 2004, Reid, DA, Agius, PB, Buck, SB, Collins, RB, Conway, MC, Kuskie, JC, Spackman, GD, and Sullivan, AC. QLD Department of Primary Industries and Fisheries & GRDC

Project update, newsletter for the CQ Sustainable Farming Systems Project, Issues 17, 19, 20 & 24, December 2002 through to September 2004, written, compiled and edited by CQSFS staff during that period.

Contact details

Darren Aisthorpe
Department of Agriculture and Fisheries
99 Hospital Rd
Emerald QLD 4720
Ph: 07 4991 0808
Email: darren.aisthorpe@daf.qld.gov.au

GRDC codes:
DAQ382 - Farming systems research
DAQ00049 - Phases 1 & 2 of the Central QLD Sustainable farming systems project (GRDC and QLD DPI)
UQ000075 - Tactical agronomy for sorghum and maize

GRDC Project code: DAQ382, DAQ00049, UQ000075