With the rapid global trend towards mechanized, continuous and dense cropping
systems that provide agricultural efficiency to meet consumer demand, soil
compaction has become a recognized problem. Soil compaction under modern
machines has had immense impact on productive land‘s physical, chemical and
biological properties, including soil-water storage capacity, fertiliser use efficiency,
and plant root architecture. As a result, farms are experiencing substantially reduced
crop yields and economic returns. The percentage of soil compaction increases with
increased soil clay fraction. Numerous investigations have been conducted to
evaluate the technical, economic and soil-crop efficiency of compaction mitigation
strategies, but deep tillage has not received sufficient consideration, particularly in
relation to high clay content soils.
This study was conducted to technically and economically evaluate a range of deep
ripping systems, and study the effect of tillage on soil and crop grown on cohesive
soils. A series of field experiments were conducted to parametrise a soil tillage force
prediction model, previously developed by Godwin and O‘Dogherty (2007) and the
Agricultural Productions Systems sIMulator (APSIM) developed by the Agricultural
Production Systems Research Unit in Australia (Holzworth et al., 2014; Keating et
al., 2003). The behaviour of soil physical properties, power requirements of ripping
operations and cost, and agronomic and economic performance of sorghum and
wheat were assessed at the University of Southern Queensland‘s research ground in
Toowoomba, Queensland (Australia) over two consecutive seasons (2015-16 and
2016-17). The work was conducted by replicating the soil conditions commonly
found in non-controlled or ‗random‘ traffic farming systems, referred to as RTF.
Sorghum was also grown at a commercial farm located in Evanslea near
Toowoomba, under controlled traffic (CTF) conditions (a farm system based on a
permanent lanes for machinery traffic) during the 2018 summer crop season.
The soil types at the two sites are Red Ferrosol (69.1% clay, 10.0% silt, and 20.9%
sand) and Black Vertosol (64.8% clay, 23.4% silt, and 11.8% sand). Three levels of
deep ripping depth, namely, Deep Ripping 1 (D1= 0-0.3 m), Deep Ripping 2 (D2= 0-
0.6 m), and Control (C= no ripping) were applied using a Barrow single tine ripper at
the Ag plot site - USQ, and a Tilco eight-tine ripper was used at the Evanslea site.
The tillage operations were performed at 2.7 km/h. A predetermined optimum N
fertiliser rate was applied after sorghum and wheat sowing at the Ag plot site. The
field experiments were conducted according to the randomized complete block
design (RCBD). The Statistical Package for Social Scientists (SPSS) software was
utilized to analyse the significance of the differences between the variables at the
probability level of 5% as the least significant difference (LSD).
The statistical analysis results showed that the D2 treatment significantly reduced
soil bulk density and soil strength by up to 5% and 24% for Red Ferrosol soil, and by
up to 6% and 40% for Black Vertosol soil respectively, and increased water content
compared with the D1 and C treatments. Overall results showed that D2 was superior in ameliorating the properties of both soils. In both soils, energy requirement results showed that tillage draft force and tractor power requirements were dependent on tillage depth, but for both tillage treatments, energy consumption was slightly lower for the CTF system (Evanslea site) than the RTF system at Ag plot site.
Crop performance results showed that at the Ag plot site, the grain and biomass
yields were highest by up to 19% for sorghum and by up to 30% for wheat when the
D2 treatment was applied, compared to the D1 and C treated crop yield components. Also, the grain and biomass yields were highest for fertilised soil by up to 10% for sorghum and by up to 16% and 25% for wheat respectively, in comparison with the non-fertilised treatments soils yield. Fertilising of D2 treated soil produced the highest significant yield of sorghum grain (5360 kg/ha), biomass (13269 kg/ha),
wheat grain (2419 kg/ha), and biomass (5960 kg/ha) compared to the yield of the
other treatment interactions. However, at Evanslea site, the D1 treatment showed
significantly higher yield and yield components for sorghum compared with C
practice (by up to 17% higher yield), and no differences were observed for treatment
D2. Economically, the D1 treatment required the lowest total operational cost at both
sites, which was estimated at AUD125/ha and AUD25.8/ha at the Ag plot and
Evanslea sites, respectively. These results compare to AUD139.3/ha (Ag plot) and
AUD30.8/ha (Evanslea) for the D2 ripping system. With regard to economic returns,
at the Ag plot site, D2 yielded the highest sorghum gross benefit (AUD1422/ha) and
net benefit (AUD1122/ha), wheat gross benefit (AUD590/ha) and net benefit (AUD482.3/ha), 2017 season gross benefit (AUD 2011.7/ha) and 2017 season net
benefit (AUD 1604.7/ha), compared to D1 and C soil benefits. The economic
fertiliser application at this site achieved the highest gross benefit for sorghum
(AUD1384.2/ha), wheat (AUD555.6/ha), and 2017 season (AUD1939.8/ha)
respectively, in comparison with the non-fertilised soils‘ total return. Also, fertilised
D2 treated soil resulted in the highest sorghum gross benefit (AUD1512.9/ha) and
net benefit (AUD1170.3/ha), wheat gross benefit (AUD633.7/ha) and net benefit
(AUD492.4/ha), 2017 season gross benefit (AUD2146.6/ha), and net benefit
(AUD1662.7/ha) compared to other interactions‘ benefits. At the Evanslea site, D1
significantly increased sorghum gross benefit and net benefit by up to 17%
(AUD2277.9/ha) and by up to 20% (AUD1825.5/ha), respectively compared to C
benefits, and no differences were observed with treatment D2.
The average of APSIM derived results for the long-term (1980-2017) at the Ag plot
site showed that the D2 treatment reported consistently higher grain sorghum (4192
kg/ha), biomass (11454 kg/ha), wheat grain (3783 kg/ha), and biomass (10623
kg/ha), compared to the D1 and C treatments‘ yields under the same long-term
conditions. However, at the Evanslea site, for long-term (1980-2018), APSIM
simulation showed that D1 treatment increased the yield of sorghum grain and
biomass significantly by up to 10% (5823 kg/ha) and 11% (12171 kg/ha),
respectively compared to C treatment‘s production, but these increases were found
not significant with the D2 yields‘ components. APSIM model simulation of field
experiment conditions during 2017 season at the Ag plot site showed that the D2
treatment also had the highest significant yield of sorghum grain (5284 kg/ha),
biomass (12488 kg/ha), wheat grain (2341 kg/ha) and biomass (6081 kg/ha)
compared to the C and D1 crop yields. Similarly, APSIM model simulation of field
experiment circumstances during the 2018 season at the Evanslea site showed that
the D1 treatment produced the highest yield of sorghum grain (7129 kg/ha), biomass
(13364 kg/ha) yields, compared to the C and D1 crop yields.
Overall, both the long and short-term model outputs were in good agreement with
experimental data, suggesting beneficial effects of deep tillage in improving cereal
crops‘ productivity in this region. Moreover, in comparison with the study findings,
the model prediction error rate was ±7, which indicates that the developed model
approach is valid and calibrated during this study.
Results derived from the G&O soil tillage mechanics model under the Ag plot and
Evanslea soil conditions showed that the required tractive force increases with the
increasing operation working depth. Furthermore, the D1 was superior, requiring the
lowest draft force at Ag plot (7.48 kN) and Evanslea (19.65 kN) soils, compared to
the D2 required forces which were 43.28 kN and 41.41kN at both sites, respectively.
In general, the model values were in line with the experiments' draft forces and when compared with the study readings, the model prediction error rate was ±8, which indicates that it is also valid and calibrated during this study.
Finally, the study provides conclusions and recommendations that contribute to crop production improvement in the face of recurrent and increasing challenges, as well as emphasizing the necessity of correct management and cultivation of economically important crops after the application of deep ripping to produce accurate results that serve decision-making in the agricultural sector.