Ameliorating sandy soils to overcome soil constraints and improve profit

Take home messages

  • Most of the sandy soils we have worked with have a physical constraint to crop root exploration and water use. New insights into the nature of the physical constraints suggest that both hard-setting and compaction processes are important.
  • Water repellence is a common constraint and, if severe, may present issues even when physical constraints are addressed.
  • Yield responses to ripping depths of less than 40cm have proven unreliable.
  • Analysis across our validation sites have shown that the net present value of the investment in amelioration is most dependent on the yield response but is also sensitive to cost assumptions and grain prices.
  • A whole of farm case study based on an Ouyen farm demonstrated that while the profit is positive in response to amelioration of sands, the returns are lower than achieved at the plot-level when farm-level cost and benefit factors are considered.
  • Major drivers of farm-level profit include investment costs and proportion of cropped land responsive to amelioration.
  • Recent responses to ripping using inclusion plates with high inclusion capacity suggest that we may be able to offer strategies that produce similar yield benefits and possibly longevity to full profile mixing (for example, spading), and which also leave the soil surface with less erosion-risk.

Background

Crop water-use and yields on sandy soils are commonly limited by a range of soil constraints that reduce root growth. Constraints can include a compacted or hard-setting layer preventing root proliferation, a water repellent surface layer causing poor crop establishment, soil pH issues (both acidity and alkalinity) and/or poor nutrient supply. The aim of the Sandy Soils project is to increase crop water use in underperforming sandy soils in the Southern cropping region by improving the diagnosis and management of constraints. Growers are experiencing a range of outcomes in response to amelioration of deep sands. Understanding the constraints, appropriate amelioration tools and a set up that will best address the constraints are critical to success. A profit-risk analysis can help growers and advisers think through the relevant components of the costs, the expected response and financial risks associated with amelioration of deep sands. This paper focuses on high soil disturbance interventions (deep ripping, spading and inclusion ripping) that require specialised machinery to break up compacted or hard-setting layers.

Method

Constraint identification

The key measurements for constraint identification include water repellence (water drop test), soil strength (penetration resistance) or bulk density, pH and soil nutritional status. A summary of these constraints for the validation program sites is given in Table 1. The grower guide for identifying constraints is currently available via Fraser (2020) and is being developed for inclusion in a web-based app. Further to this effort, there has been a post-doctoral project examining the nature of the physical constraints in sandy soils. This study has focused on the measurement of bulk density (compaction) and soil strength under drying soil water conditions (hard setting) (da Silva et al. 2021). Tests have also been completed to identify if cementing (irreversible hardening) was an important physical constraint at these sites. A simple test for cementing is demonstrated in this video link.

Testing amelioration techniques

A range of research experiments were established across the low to medium rainfall environments of the southern region with sites categorised according to their primary soil constraints identified (Table 1). Experiments for the research program were established between 2014 and 2019, while a broader validation program was established between 2019 and 2021, including a range of deep ripping (30-60cm deep), spading, inclusion ripping and/or inversion ploughing approaches, with/without additional amendments (fertiliser, N-rich hay, chicken manure, clay). All experiments monitored the effects of amelioration on crop growth and yield, while the research program had a further set of more detailed soil and crop measurements. It is only possible to present a subset of data in this paper, so we have focused on the effects of ripping depth on yield and economic response utilising the validation program data (2019-2020).

Economic analysis

Utilising 2019 and 2020 grain yields from the validation program, the discounted cashflow response to amelioration was evaluated for cost:benefit outcomes in response to ripping depth, utilising ripping costs provided by grower and industry consultation ($60-105/ha depending on ripping depth), 5-year average grain prices from the Gross Margin Guide (wheat (APW) five-year price was $294/t, SAGIT et al. 2021) and a discount rate of 6%. The sensitivity to cost of investment, grain prices, yield and discount rate was also analysed by comparing the base scenario to variations in these factors. The cash flow outcome is presented here as the net present value (NPV). The investment is worth undertaking if NPV is positive as it reflects that the present value of the future cash flow is bigger than the initial investment.

Further to this effort, several case study farms were developed in collaboration with Pinion Advisory Pty Ltd. Using results from the validation trial at Tempy, an Ouyen case study farm was developed to evaluate deep ripping as a ‘farm investment project’. The assumptions included dividing the farm into three classes of land and predicting the level of amelioration response for each class over a 3-year period. Of the 4,792ha cropping area, it was assumed that 30% would be ripped across a 6-year program (240ha/year), an $80,000 ripper would be purchased, and the farm would upgrade their tractor, with 30% of the tractor use assigned to ripping.

Optimising spading and deep ripping operations

The work to date (Ucgul et al. 2019) has developed new insights on how spading and inclusion ripping machinery are best set-up and used. The incorporation by spading of a surface-applied amendment or the mixing of a constrained sublayer achieves variable levels of mixing uniformity within the profile, which is a function of speed, depth and spader design. The mixing by spading process is cyclical rather than continuous and controlled principally by the spading ‘bite length’. The uniformity of mixing is greatly improved under dual-pass, low-speed (3km/h) spading, which can reduce the time to crop response from lime incorporation, relative to very delayed and diluted response with surface-applied lime. The high cost and greater erosion risks of high uniformity mixing requires caution and careful adoption where justified.

A lower risk profile-amelioration method consists of inclusion plates fitted behind deep ripping tines which promote the natural inclusion of the top layer into the loosened profile. Substantially enhanced inclusion capacity can be obtained when operating in loose, flowable top-soil conditions with optimised plate design and set-up, such as the plate upper-edge length and its lower-edge depth of reach. However, greater inclusion capacity correlates with increased power requirements and rougher surface finish. Pilot work has also revealed great potential for maximising the inclusion capacity under active inclusion systems that can also leave the surface finish ‘seeder-ready’. Active inclusion includes the use of twin plates that funnel topsoil into the inclusion zone. Early on-farm and commercial adoption of some of these ideas demonstrate the demand for improved deep ripping solutions. Two separate experiments at Younghusband (near Mannum) established in 2020 and 2021 have directly compared spading with inclusion ripping and ripping. The inclusion ripping treatments at this site have taken advantage of the knowledge to optimise the set-up of the inclusion plates.

Results and discussion

Constraint identification

Of the 19 validation sites, 12 have a severely constrained layer for soil strength and the remainder have a moderate constraint. Ten of the sites also have moderate to high water repellence (Table 1), while three also have issues of acidity, and 11 have problems with poor nutrient supply.

Table 1: Summary of constraint scores (0 = low, 1 = moderate, 2 = high)* at validation program sites including repellence measured as water drop infiltration time, presence of a physically constrained layer measured as penetration resistance, acidity measured as pH water, and soil nutrient status.

Research Site_Year Established

Repellence

Physical strength

Acidity

Nutrients

Physical constraints and low inherent nutrition

Koolonong_19

0

2

0

1

Buckleboo_19

0

2

0

1

Karkoo_19

0

1

0

1

Sherwood_19

0

2

0

1

Monia Gap_19

0

1

1

1

Cummins_19

0

2

1

1

Walpeup_20

0

2

0

0

Telopea Downs_20

0

1

0

0

Taplan_20

0

2

0

0

Water repellence, physical constraints and low inherent nutrition

Alawoona_18

2

1

0

1

Warnertown_19

1

2

0

0

Kybunga_19

1

2

0

0

Tempy_19

1

2

0

0

Wynarka_19

2

2

0

1

Mt Damper_19

1

1

0

1

Malinong_19

2

2

2

1

Younghusband_20

2

2

0

1

Wharminda_21

2

1

0

1

Coombe_21

2

1

0

0

*Repellence as water infiltration time: 0 = <5s, 1 = 5-240s, 2 = >240s; physically constrained layer as penetration resistance: 0 = <1.5Mpa, 1 = 1.5-2.5Mpa, 2 = >2.5Mpa; acidity as pH water: 0 = >6.5, 1 = 6-5.5, 2 = <5.5; and nutrients: 0 = sufficient, 1 = marginal, 2 = deficient measured through lab-based soil test reporting and inclusive of N, P, K, S, Zn, Mn, Cu status.

Hard setting and compaction can both contribute as physical constraints restricting root growth and exploration. Hard setting is a natural, moisture driven and reversible process, where particles become bound together as the soil dries. This increases soil strength and makes it more difficult for roots to grow. Compaction is a physical process where soil particles are packed together more tightly with reduced porosity because of external forces, such as machinery trafficking. Cementing is also a naturally occurring process, but unlike hard setting, it is irreversible when exposed to water because particles are chemically bound (through cementing agents). The difference between these physical constraints is likely to be important for understanding how crops respond to amelioration, and how long the benefits will last. The four sites that we were able to access in 2020/21 did not classify as having a cementing layer, but they did have a hard setting layer that is prone to becoming extremely hard (>3.5MPa, restricting all root penetration) with very small reductions in soil water content (just 4% w/w, from 9% to 5% w/w) (da Silva et al. 2021). This is likely to be a critical issue in low rainfall environments. We will continue to explore this hard setting response across a broader range of sites and contrast the process under different amelioration strategies.

Yield and economic response to ripping at validation sites (two-year response)

In line with the presence of physical constraints at many sites, most scenarios have been responsive to ripping, particularly to depths greater than 40cm (Figure 1). The most consistent responses have been generated at depths of 50cm, with an average discounted NPV of $247/ha (Figure 1). As the database consolidates to combine both the validation and research program datasets, the confidence in the optimal depth for yield and economic benefit will improve.

Figure 1. Panel A plots the yield increase (that is, the difference between treated and control yield) at various ripping depths. Panel B is the average 2-year cumulative yield response to each ripping depth. A non-linear regression of this relationship is shown in Panel C, where the shading represents the confidence interval and shows that there is less data for analysis at 60cm depth. Panel D and E show average cumulative discounted costs and benefits of different ripping depths. Panel F shows the cumulative discounted net cash flow mirrors the curvilinear yield relationship as given in Panel B and C. These relationships will continue to consolidate as the database accumulates the research program and 2021 yield data.

Figure 1. Panel A plots the yield increase (that is, the difference between treated and control yield) at various ripping depths. Panel B is the average 2-year cumulative yield response to each ripping depth. A non-linear regression of this relationship is shown in Panel C, where the shading represents the confidence interval and shows that there is less data for analysis at 60cm depth. Panel D and E show average cumulative discounted costs and benefits of different ripping depths. Panel F shows the cumulative discounted net cash flow mirrors the curvilinear yield relationship as given in Panel B and C. These relationships will continue to consolidate as the database accumulates the research program and 2021 yield data.

The discounted cash flow analysis to derive NPV depends on discount rate, treatment cost, grain prices, and grain yield response (that is, the difference in yield between treated and control plots). Information on cost and prices were obtained from various published sources and expert opinion. However, our findings are sensitive to changes in cost and prices. For this reason, sensitivity analysis is presented along with a base case scenario in Figure 2. As expected, our analysis suggests that the yield response is a key driver of the ripping NPV outcome. A 25% increase in the yield response increased NPV by $16-249/ha. The NPV was less sensitive to cost (which ranged from $60-105/ha) with a $28-47/ha reduction in NPV with 50% cost increase, while a 25% reduction in grain price (base price $294/t) generated a $2-256/ha reduction in NPV (Figure 2).

Figure 2. Sensitivity analysis of ripping net present value response base scenario compared with an increase in ripping cost (+50%), a decrease in grain prices (-25%) and an increase in yield response +25%). Each column on the figure represents a site x treatment response value. The baseline scenario has a wheat price of $294/ha (but other crops are represented as per label), ripping costs of $60-105/ha dependent on ripping depth and yield benefits ranging from -0.5-1.0t/ha.

Figure 2. Sensitivity analysis of ripping net present value response base scenario compared with an increase in ripping cost (+50%), a decrease in grain prices (-25%) and an increase in yield response +25%). Each column on the figure represents a site x treatment response value. The baseline scenario has a wheat price of $294/ha (but other crops are represented as per label), ripping costs of $60-105/ha dependent on ripping depth and yield benefits ranging from -0.5-1.0t/ha.

Using the Ouyen case study farm example, the net present value of the investment was predicted to be $55/ha with a payback period of approximately 6 years. This case study involved purchasing a tractor (with partial attribution of tractor use to ripping) and ripper. In addition, only a portion of land was assumed responsive to ripping and able to be treated in any one year. Exploration of the sensitivity of the case study outcomes to assumptions suggested the purchasing options (ripping investment cost), level of crop responsiveness in land area, longevity of response (assumed here to be 3 years) and selection of crop sequence are all highly sensitive factors influencing the return on investment. However, it is consistently the case that analysis at the farm-level reveals a lower level of predicted return than simple extrapolation from plot-scale data.

Optimising cost and crop response to inclusion ripping

Given the importance of the yield response and managing the cost of the deep ripping investment, we have several sites at which optimisation of the deep ripping operation is examined. This includes the design of the ripper set up (for example, wing attachments), tine spacing and operational speed through to modification of the ripper for inclusion to allow for multiple constraints to be addressed simultaneously. The process of inclusion allows for repellency to be addressed to some degree because topsoil is included into deeper soil layers, diluting the repellency in the surface, but also redistributing organic matter and nutrients in the topsoil layer. At the same time, the soil physical constraint is addressed. Recent results from Younghusband (Figure 3) suggest that inclusion ripping may provide a useful alternative to spading with reduced erosion risk and a more seeder-ready finish. Year-1 wheat yield benefits in 2020 (decile 7) were 1.9t/ha from enhanced inclusion-ripping (modified 60cm long plates, at 60cm ripping depth) compared with a 1.1t/ha benefit for deep ripping alone (control yield 2.8t/ha).

Figure 3. (Top) Comparison of cereal yield responses to deep ripping (60cm), spading (30cm) and inclusion ripping (60cm) at Younghusband in 2020-2021 for the validation trial and (bottom) Year-1 barley responses to dep ripping (45cm), spading (30cm) and inclusion ripping (45cm) at an adjacent trial in 2021.

Figure 3. (Top)Comparison of cereal yield responses to deep ripping (60cm), spading (30cm) and inclusion ripping (60cm) at Younghusband in 2020-2021 for the validation trial and (bottom) Year-1 barley responses to dep ripping (45cm), spading (30cm) and inclusion ripping (45cm) at an adjacent trial in 2021.

In 2021 (decile 1), residual year-2 barley yield benefits from inclusion ripping maintained a 1.1t/ha gain compared with a 0.4t/ha benefit for deep ripping alone which was equivalent to the soil wetter treatment (control yield of 0.9t/ha). In both years, a spading treatments to 30cm depth yielded +0.1t/ha and +0.6t/ha above the deep ripping only treatment, respectively. A year-1 response of +2.0t/ha to deep ripping at 45cm and +2.3t/ha to inclusion ripping at 45cm was concurrently obtained at an adjacent trial (Figure 3) in 2021. The rapid reduction in response to ripping in year-2 compared with the magnitude of year-1 responses suggests there may be limited longevity for ripping alone treatments at the site, which may relate to the impact of a hardsetting layer.

Although inclusion ripping may appear an attractive option over spading, anecdotal variability in topsoil inclusion and crop responses alongside elevated running costs can pose challenges for reliable return on investment. Experiments in WA and SA Mallee sands have shown higher draft requirements (+24% to +40%), reduced workrate (-24%), and extra fuel use (+3.7L/ha) with baseline inclusion ripping technology compared to ripping alone (Parker at al. 2019). Further work in SA (Ucgul et al. 2020) has shown that higher power requirement is primarily influenced by how deep the lower plate edge is set relative to the deep ripping point, with draft increase of up to 80% possible. High draft may not always correlate with higher inclusion capacity, which is influenced by speed and plate length. The optimisation of inclusion ripping has not yet been fully explored and remains an area of research in high demand from growers trying to manage sands with the combination of physical and repellency constraints.

Acknowledgements

The research undertaken as part of this project is made possible by the significant contributions of growers through both trial cooperation and the support of the GRDC, the author would like to thank them for their continued support. We thank the technical teams who deliver the experimentation for the Sandy Soils Project. We thank Pinion Advisory for their role in the analysis and development of farm case studies. This research has been enriched by preceding research trials, the significant contributions of growers and consultants across the Southern region, and the support of the GRDC and SAGIT (for the Younghusband 2021 site). GRDC project CSP00203 research and validation activities are a collaboration between the CSIRO, the University of South Australia, the SA Government Department of Primary Industries and Regions SA, Mallee Sustainable Farming Inc., Frontier Farming Systems, Trengove Consulting, AgGrow Agronomy, AIREP, and MacKillop Farm Management Group.

References

da Silva . (2021) Physical constraints in sandy soils: identifying and understanding cementing behaviour. “Proceedings of the Soil Science Australia and the New Zealand Society of Soil Science Joint Conference ‘Soils, Investing in our Future’. Cairns, Australia”, 27 June – 2 July 2021.

Fraser M (2020) Sandy soil constraints in south east South Australia: a guide to their diagnosis and treatment. Mackillop Farm Management Group, Naracoorte, SA.

Parker W, Ucgul M, Saunders W (2019). Advice to match design of inclusion plates to soil type for optimum effect. GRDC GroundCover Supplement: Soil Constraints Part 1, Nov-Dec 2019.

SAGIT, GRDC, SA Sheep Industry Fund, PIRSA (2021) Farm gross margin and enterprise planning guide 2021. Rural Solutions SA, Adelaide.

Ucgul M, Saunders C, Desbiolles J (2019) The use of computer simulation as a decision making tool to improve machinery set-up, usage and performance. “Proceedings of the 19th Australian Agronomy Conference ‘Cells to Satellites’. Wagga Wagga, NSW”, 25—29 August 2019.

Ucgul M, Desbiolles J, Saunders C (2020). Science of deep ripping. InGrain Magazine 1(5) Summer 2020, 20-25.

Contact Details

Therese McBeath
CSIRO Agriculture & Food
Waite Road, Urrbrae SA
5064 08 8303 8455
therese.mcbeath@csiro.au

GRDC Project Code: CSP1606-008RMX,