| Some useful rain in some
areas and the opportunity for decent prices for cotton have again stimulated
significant interest in dryland cotton.
One of the management techniques that dryland growers have at their
disposal is being able to modify row configuration. Growers can use
conventional solid row configurations or configurations that considerably
increase row spacing or remove entire rows.
Choosing a row configuration involves many, often complex, considerations.
The choice of configuration can influence the potential yield, the level
of variability or risk associated with production, fibre quality, input
costs, machinery set up, and general crop management.
Choosing skip-row configurations over solid in soils with reasonably
high soil water holding capacities and fertility may slightly reduce
crop yields, but insure against significant financial penalties associated
with poor fibre quality.
In some instances when fibre quality penalties are incurred, an extra
1.6 bales per hectare would need to be grown in the solid configuration
to meet the costs of production compared with skip configurations. It
emphasises that to optimise economic benefit in dryland cotton systems,
both good crop yields and fibre quality need to be achieved concurrently.
But growers need not take uncalculated risks when considering dryland
production. History and research can often serve as our best guide to
the potential risks and benefits of different dryland cropping strategies.
We have used data from field experiments and the cotton crop simulation
model OZCOT to explore the impact of row configuration on potential
yield and fibre quality of dryland production. This article presents
the information and the tools that are available to help growers choose
appropriate row configurations and assess their potential for dryland
cotton production.
The OZCOT model
The use of crop simulation models is a powerful way to explore different
cropping scenarios without suffering the consequent pain and real life
experience when misfortune strikes. The OZCOT model developed by Brian
Hearn (CSIRO Plant Industry) is a dynamic simulation model of cotton
growth, development and yield. It uses a daily time step with growth
and development being driven by temperature and intercepted radiation.
Growth processes are modified by soil moisture and nitrogen status.
In recent years the model has been used with growers to explore a range
of issues in dryland cotton production including selecting row configurations,
comparing cropping systems and the impacts of climate variability as
part of the FARMSCAPE initiative led by the Agricultural Production
Systems Research Unit (APSRU) based in Toowoomba. The cotton model in
APSIM is the OZCOT cotton simulation model.
In exploring the use of simulation models for crop management as part
of FARMSCAPE initiative, commercial dryland crops with various row configurations
were monitored and yields measured. The crops were grown across southern
Queensland and northern NSW production areas. Yields of these crops
were compared with those predicted by the OZCOT simulation model. This
process allowed growers to gain some confidence in the ability to use
simulation technology to explore crop management issues.
These tests confirmed that OZCOT was able to simulate commercial dryland
cotton production well, accounting for 70 per cent of the observed variation
across 30 crops (Figure 1). This degree of accuracy has been regarded
as acceptable by growers, especially when the reasons for the few poor
predictions were traced to non-optimal agronomy or insect control in
the measured commercial crops.
During this time significant demand has developed from farmers and crop
consultants for the use of simulation technology to benchmark performance
of commercial crops and assess the risks associated with different crop
management practices.
In using OZCOT to explore the potential yield of dryland production
in this article we assumed the following generalised conditions based
on current practices and typical soils:
• Cracking clay vertosol soil storing 200mm of available soil
moisture in a 1.5 metre profile;
• Crops sown on October 15; row spacing set at one metre; and,
• An established population of seven plants per metre of row.
The model simulates potential yield of a typical variety. It does not
account for the affects of insect pests, diseases, weeds, or soil nutrient
limitations other than N. OZCOT was then run every year with the historical
climate records available for each region.
Yield potential and row configuration
A number of field studies have been conducted to compare the relative
yield of skip row configurations (single and double) compared with solid
planted configurations. These studies generally show that when yields
of solid configurations are high, there is a considerable yield penalty
in using skip row configurations.
But when yields of solid configurations are low, the difference in yield
between skip row and solid configurations is negligible. When data from
these studies are combined (Figure 2) the single skip row configurations
yielded less than solid when the yield of solid was above 1.6 bales
per hectare and double skip yielded less than solid when solid was above
1.5 bales per hectare.
These comparisons provide useful and generally consistent information
that can allow growers to assess options based on their historic yield
potentials. But their limitation is that they do not account for seasonal
variation.
We used OZCOT to explore the long term variability in yield for the
different systems. In Table 1, average simulated yield for the three
different row configurations (solid, single and double) is presented
for nine regional centres along with the ‘probability of exceedence’
values.
Probability of exceedence is used to indicate variability that exists
with different climatic conditions experienced in each region. For example
an 80 per cent probability of exceedence means that there is an 80 per
cent chance of exceeding the nominated yield for the region.
Skip row plantings increased yields in a few years but reduced it in
most. The result is that there is an overall reduction in mean yield
for skip configurations, but the values of the 20 per cent percentile
were generally increased by skip row production. That is, the risk of
very low yields was reduced. In wet years there is enough water in the
profile for solid configurations, so the extra soil storage capacity
available to plants in skip configurations provides no advantage.
Often when significant yield advantages from skip row configurations
are not found, fibre quality is often enhanced compared with solid configurations.
The implications of this are now discussed.
Row configuration and fibre quality
Periods of insufficient soil water not only reduce the quantity of lint
produced but also impact significantly on fibre characteristics. Seasonal
temperature affects crop development and causes flowering time to vary
between seasons.
It is important for fibre development that adequate soil water for crop
growth coincides with the time of peak flowering and during boll filling.
The use of skip row configurations provides some insurance against poor
fibre quality at this time by providing a larger soil reserve available
to the crop and so delaying moisture stress.
Severe water deficits during fibre elongation reduce fibre length and
historically it is this characteristic that is most seriously affected
in dryland cotton production. Achieving commercially desirable fibre
length requires adequate soil moisture during the first 20 days of boll
development following flowering. Once length is determined, fibre thickening
then occurs.
Micronaire is the other fibre quality trait that is often affected in
dryland cotton production. The desirable fibre for cotton spinners lies
in the micronaire range 3.8–4.5.
Low micronaire is likely to occur in crops that are continually stressed
during boll filling. Conversely, high micronaire cotton is most likely
to occur in dryland crops in situations when the crop suffers early
boll loss, due to either heavy insect pressure or water stress, and
then encounters good late season growing conditions.
Surplus photosynthate will be deposited in a reduced number of bolls,
resulting in excessively thick fibres and a reduction in quality for
spinning.
A considerable number of field trials showed that there were significant
effects of row configuration on fibre quality. In these studies there
were always fewer instances of fibre quality discounts in skip configurations
compared with solid planted cotton. Instances of low micronaire were
also more frequent in the solid row configuration treatments. Some instances
of high micronaire were found in skip treatments.
Table 2 highlights the considerable discounts that can be incurred for
fibre lengths below base grade, or micronaire either below or above
base grade. The table also illustrates the increasing importance that
has been placed on producing quality fibre, as shown by the increase
in the size of discounts since 1996.
Consequently, given experimental results showing fewer instances of
discountable quality in skip row configurations, consideration of fibre
quality issues and their impact on economics of dryland production systems
is an important component when choosing row configurations.
Economics of different row configurations for
dryland cotton
Various economic analyses of cotton production using alternative row
configurations which include costs of production have been provided
by both the QDPI and NSW Department of Agriculture. In many cases there
is some financial gain in using skip row configurations, not from increased
yields, but by reducing variable costs.
But it is important to note that the use of skip row does not always
reduce costs. In some cases skip row configurations will require additional
use of plant growth regulators, late season insect sprays, and additional
inter-row cultivation or herbicide sprays for weed control.
While superior gross margins from skip row cotton can be achieved due
to savings in variable costs, additional gains (or reduced risk of losses)
can be made by maintaining fibre quality through the extra soil water
available for developing bolls. We explored the impact of the combined
differences in yield, costs of production and fibre quality on gross
margins of solid and double skip configurations for a single season.
We chose to compare solid and double skip as there are generally greater
gains in fibre quality in double compared with single skip configurations,
and the relative yield differences between solid and double are greater.
To compare the relative differences in gross margins we used the relationship
that compares the relative yield of double skip versus solid from the
combined dataset collected all from field experiments (Figure 2).
Assumptions used in the analysis are presented in Table 3. The analysis
also assumed that no adjustment for input costs was made when expected
yields were likely to be low.
When no deductions for fibre quality were applied, the analysis showed
that the gross margin for double skip was less than that of solid configurations
when the potential yield of the solid crop was 3.8 bales per hectare
or more (Figure 3a). The divergence in gross margins as potential yields
for solid increased was mainly due to the differences in yield potential
between solid and double skip configurations as for yield comparisons
in Figure 2.
The intersection of the relationships for the two configurations occurred
at a higher point because of the difference in production costs. But
when a discount for low staple length was applied to the solid configuration,
it had a significant effect on the gross margin compared with double
skip (Figure 3b). At no point did the gross margin of the solid configuration
exceed that of double skip. Additionally, an extra 1.6 bales per hectare
would need to be grown in the solid configuration to meet the costs
of production compared with double skip.
This analysis demonstrates the importance of considering quality aspects
as well as yield and costs of production when choosing row configuration.
But the risk of incurring discounts for fibre quality is unlikely to
be constant across yield levels. We need more detailed experiments to
examine this issue.
These analyses act only as a general guide to the potential yield and
risks of dryland production and row configuration choices for different
regions. The outcomes and interpretation may change depending on a number
of farm specific factors — for example, soil water-holding capacity,
starting soil moisture and costs. Most benefit comes from assessing
growers’ specific conditions using their own soil type and costs.
Seasonal climate forecasts
Over the past decade the development of seasonal climate forecasts,
based on the El Niño–Southern Oscillation (ENSO) phenomenon,
has introduced the possibility of allowing for climate variability to
some extent. Adjusting management in the light of probable future weather
trends offers considerable opportunities for managers of agricultural
systems.
Crop models can be linked with this climatic information to help assess
potential yields and risks of production in different years. Similar
to seasonal rainfall, estimates of cotton yield for each year in a climate
record can be associated with the Southern Oscillation Index (SOI) phase,
a measure of the strength of the ENSO phenomenon, at some useful time
of forecast such as land preparation or sowing time.
Simulation models, when used in conjunction with the SOI can therefore
provide opportunities for growers to tailor their management decisions
more appropriately to the anticipated seasonal conditions. Information
of this nature has been used successfully with dryland cotton growers
in southern Queensland to assist with their choice of row configuration
(solid versus skip).
In future
Improvements currently being made to the OZCOT crop simulation model
to encompass the effects of environment on fibre quality will add significant
value to using the model to choose row configuration in dryland cotton
systems.
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