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Background
and Objective:
In Western Canada, dandelion (Taraxacum officinale Weber in Wiggers) has long
been considered an important weed. Until recently, however, dandelion has not been
considered a significant pest within annual cropping systems. Surveys of western Canadian
fields conducted in 1986-89 and 1995-97 show an alarming increase in dandelion frequency
in Western Canada. In 1986-89, dandelion was present in 6 percent of wheat (Triticum
aestivum L.) fields and 13 percent of canola (Brassica napus L.) fields in the
Prairie Provinces. In 1995-97, however, dandelion presence increased to 20 percent of
wheat fields and 23 percent of canola fields. Based on a relative abundance index, there
was an increase in rank of 17 in wheat fields and an increase in rank of 7 in canola
fields. In Manitoba alone, dandelion has not increased in rank, whereas in Alberta and
Saskatchewan dandelion has increased in rank by 3 and 9, respectively.
The majority of the interest paid to dandelion by researchers in the past has been
related to its ability to infest forage crops and urban lawns. Perennial weeds such as
Canada Thistle (Cirsium arvense (L.) Scop.), Quackgrass (Elytrigia repens
(L.) Nevski.), and Perennial Sowthistle (Sonchus arvensis L.) have garnered
considerable research attention in Western Canada in recent years. A considerable amount
of information has been gathered regarding their competitive ability, and management
techniques have been devised. This research groundwork has not yet been laid for dandelion
in field crop scenarios. We do not understand how to properly quantify a dandelion
infestation. It is expected that dandelion interference has the ability to reduce crop
productivity, yet to what extent? Efficient methods of cultural and chemical control of
dandelion populations have not yet been devised. This research aims to develop a
foundation from which these concerns might be addressed.
The overall objective of this project was to improve the understanding of
dandelions role as a crop pest in Manitoba. The project was divided into two
components: 1) Distribution and Interference, and 2) Control.
The studies on distribution and interference were designed to answer questions relating
to dandelions distribution throughout fields, its ability to compete with crops, and
its propensity to reduce productivity on a whole-field basis. Our objectives were to
determine: 1) the effect of dandelion interference on canola yield, 2) an effective
measure of dandelion infestation, 3) an estimate of canola yield loss from dandelion on a
whole-field basis, and 4) the patchiness of dandelion in minimum and conventional-tillage
fields.
Dandelion control studies were designed to address the questions of how tillage and
glyphosate control dandelion populations.
Procedure and Project Activities:
Distribution and Interference Studies
The distribution of dandelion was mapped in six fields across southern Manitoba, which
were seeded to canola in 2000. Four of the fields were conventional-tillage fields while
two were minimum-tillage fields. Minimum-tillage fields included no more than one harrow
pass per year (excluding seeding as a tillage operation) within the past three years.
Conventional-tillage fields had at least one year of tillage within the past three years,
which included a tillage tool providing more intensive tillage action than a harrow, as
well as one spring tillage pass with a tillage tool providing more intensive tillage than
a harrow prior to seeding. Within these six fields, fixed quadrats
that contained dandelion were marked and within these quadrats all other weeds were
controlled by hand weeding. Quadrats were covered with plastic sheeting during in-crop
herbicide applications. Quadrat areas were chosen in each field that represented a range
of dandelion infestation levels. In each quadrat, the measurements made of canola and
dandelion included: 1) dandelion ground cover in-crop, 2) canola ground cover
in-crop, 3) dandelion density in-crop, 4) canola density in-crop, 5) total dandelion leaf
diameter in-crop, 6) dandelion leaf area at crop harvest, 7) total dandelion dry biomass
at crop harvest, 8) dandelion density at crop harvest, 9) total accumulated dandelion root
diameter at crop harvest, and 10) canola yield in weed-free and in dandelion infested
quadrats. Correlation analysis was conducted between measures of dandelion infestation and
canola yield loss. Yield loss models were created for measures of dandelion infestation
that were strongly correlated to canola yield loss.
Dandelion Control in Roundup Ready Canola
Trials were conducted at Carman and Oakville, Manitoba in 1999 and 2000. All sites had
established dandelion infestations. Dandelion density was determined prior to applying
glyphosate or tillage treatments. Plots were arranged in a randomized split block design
with three replicates, with spring pre-seeding tillage (or no tillage) performed across a
replicate. This design facilitated the operation of mechanized tillage equipment.
Individual plot size was 2 m by 4 m at all sites. Treatments are outlined in Table 2 and
included a range of Roundup Transorb rates applied at various crop stages, and in split
and single application timings. All treatments were performed both on plots that were
either tilled prior to seeding (high disturbance) or direct-seeded (low-disturbance).
Shoot biomass of dandelion was measured in the spring of the year following application of
the treatments, and was expressed as a percentage of untreated control for each site and
tillage treatment prior to statistical analysis.
Results and Discussion:
Dandelion Distribution and Interference
In both minimum- and conventional-tillage fields, dandelion can be a widespread problem
with the ability to significantly reduce spring canola (Brassica napus L.) yield.
Dandelion distribution was not generally associated with tillage regime. Dandelion could
be broadly distributed across either minimum or conventional-tillage fields. Dandelion
distribution showed some relationship to past cropping history, especially the recent
presence of alfalfa in rotation.
The strength of correlationship between measures of dandelion infestation level and
canola yield loss was associated with tillage regime. For conventional-tillage fields,
there was no correlation between reduction in canola yield and any measurements of
dandelion infestation level. For minimum-tillage fields, the most reliable measures of
dandelion interference level were dandelion ground cover, total root diameter, total leaf
diameter, and relative ground cover. Dandelion can cause great yield
loss in canola. A dandelion infestation providing 50% ground cover caused between 39% and
64% canola yield loss (Figure 1). On a whole-field basis, dandelion has the potential to
dramatically reduce canola yield. For example, at one of the field sites, even though
dandelion was present in only 18% of quadrats, if dandelion cover averaged only 50% where
dandelion was present, yield would be reduced by 7% for the entire field. Producers can
scout fields to determine whether dandelion affects small areas of a field or the entire
field. With the difficulty in predicting level of competitiveness of dandelion
infestations, producers must default to the position that if it is present to a noticeable
extent in canola fields, control is warranted.
Dandelion Control in Roundup Ready Canola
Spring tillage prior to seeding had a significant impact on dandelion populations (Table
1). In the 1999 trials, dandelion biomass was reduced by more than 80% with spring tillage
alone. The high intensity of these tillage operations using a rotovator was, however,
expected to provide significant control. Tillage in spring was quite effective because, at
this time, dandelion roots have moved a large portion of their reserves aboveground,
leaving the root in a weakened state. It was expected that dandelion control due to
tillage would not be as great in the 2000 trials as only one pass was made with the
cultivator in high disturbance plots. This hypothesis was correct as the three trials in
2000 exhibited only a 40% reduction in dandelion biomass. Cultivation in 1999 was also to
a slightly greater depth than in 2000. In most conventional-tillage systems, farmers use
seeding systems that are designed to cut off all aboveground plant biomass. The more
intense the tillage action in the seeding system, the greater the dandelion control will
be.
Table 1.
Influence of tillage (soil
disturbance) on dandelion shoot dry matter (standard errors in
parentheses) in the untreated control plots plots which did not receive
a herbicide treatment) as assessed the following spring (i.e. the year
following treatment).
|
Location |
Year |
Dandelion shoot dry matter |
|
Low disturbance (g/m2) |
High disturbance (g/m2) |
LSD (0.10) |
|
Carman |
1999 |
83.6 (25.4) |
13.4 (6.3) |
55.9 |
|
Oakville |
1999 |
52.0 (21.1) |
11.6 (5.2) |
46.3 |
|
Carman (early
seeded) |
2000 |
114.2 (19.4) |
93.3 (3.9) |
42.2 |
|
Carman (late
seeded) |
2000 |
277.4 (15.7) |
129.6 (6.2) |
36.0 |
|
Oakville |
2000 |
120.3 (22.9) |
57.3 (17.3) |
61.3 |
|
Overall |
|
129.5 (22.3) |
61.0 (12.7) |
43.7 |
If multiple applications of glyphosate fit with a producers production system,
residual dandelion populations can be reduced to near-negligible levels (Table 2). Two 450
g a.i. ha-1 (1/2 L Roundup Transorb) applications of glyphosate in-crop can
provide significant control of dandelion in both low and high disturbance systems. The
greatest control of dandelion was found when 900 g a.i. ha-1 (1 L of Roundup
Transorb) application was made post-harvest, following an application or applications of
glyphosate earlier in the year. Weakening the dandelion plants earlier in the growing
season with glyphosate appears to make them more susceptible to post-harvest applications
of 900 g a.i. ha-1. If producers can justify several passes across a field,
sequential applications of glyphosate might be the preferred method for reducing dandelion
populations to negligible levels.
Table 2.
Influence of glyphosate dosage and time of application on dandelion
shoot dry matter (standard errors in parentheses) as assessed in the
spring following the year of treatment). A glyphosate resistant canola
crop was grown in all plots in the year of treatment.
|
Treatment no. |
Glyphosate dosage (g/ha) |
Application timing (stageb) |
Dandelion shoot dry mattera
(% of controls) |
Canola yield |
|
Low disturbance (g/m2) |
High disturbance (g/m2) |
|
1 |
- |
- |
100 (7.6) |
52 (16.0) |
139 (17.7) |
|
2 |
900 |
pre-plant |
40 (6.0) |
158 (12.6) |
178 (16.4) |
|
3 |
1350 |
pre-plant |
36 (7.4) |
159 (14.0) |
165 (14.2) |
|
4 |
1800 |
pre-plant |
38 (7.5) |
157 (13.9) |
151 (12.0) |
|
5 |
450 |
0-3 leaves |
68 (9.5) |
154 (21.5) |
161 (12.5) |
|
6 |
900 |
0-3 leaves |
61 (8.6) |
142 (15.8) |
161 (20.1) |
|
7 |
450+ |
0-3 leaves |
|
|
|
| |
450 |
4-6 leaves |
43 (5.2) |
124 (17.4) |
174 (15.6) |
|
8 |
900 |
maturity |
47 (8.4) |
N/Ad
(N/A) |
|
|
9 |
1800 |
maturity |
25 (5.0) |
N/A (N/A) |
|
|
10 |
900 |
post-harvest |
4 (1.4) |
N/A (N/A) |
|
|
11 |
1800 |
post-harvest |
6 (3.3) |
N/A (N/A) |
|
|
12 |
2700 |
post-harvest |
2 (1.1) |
N/A (N/A) |
|
|
13 |
900+ |
pre-plant |
|
|
|
| |
900 |
post-harvest |
1 (0.4) |
172 (15.0) |
142 (12.8) |
|
14 |
450+ |
0-3 leaves |
|
|
|
|
14 |
450+ |
4-6 leaves |
|
|
|
| |
900 |
post-harvest |
1 (0.3) |
123 (19.4) |
161 (13.8) |
|
LSD (0.05 |
|
|
14.7 |
28.6 (28.0) |
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a
based on results of analysis of variance,
dandelion shoot dry matter (expressed as % of untreated control) was
pooled over sites and tillage intensities and canola yield was pooled
only over sites.
b
canola crop stage. This time of application is commercially
referred to as 'pre-harvest'.
N/A - Not
applicable. Those treatments that were applied at canola crop
maturity or post-harvest were not expected to influence canola yield.
In both low and high disturbance plots, post-harvest applications of glyphosate (900 to
2700 g a.i. ha-1) provided significant control, yet control was not improved by
increasing glyphosate rate. The fact that control was excellent and high rates were not
necessary provides good evidence that post-harvest applications of glyphosate provided the
greatest efficacy. If a simple herbicide system is desired to control dandelion
post-harvest application of glyphosate at a rate of 900 g a.i. ha-1 in either
direct seeded or conventional-tillage systems would suit. It is possible that 900 g a.i.
ha-1 is a more than adequate rate and a lesser rate could be used, but this was
not tested. The value of even lower rates is limited, however, because glyphosate is
relatively inexpensive and the cost savings from reduced rates might not balance the
increased risk of weed escapes. Producers may also want to intensify their tillage
operations to improve effectiveness in cutting off all aboveground dandelion biomass,
possibly at greater depths in the soil profile.
When residual dandelion populations were compared among treatments receiving single
applications of 900 g a.i. ha-1 of glyphosate, it became clear that
post-harvest applications provide the greatest control.
Dandelion is becoming a problem weed in western Canadian field cropping systems. Its
distribution in fields is not necessarily related to the level of tillage practiced within
that field, but more likely related to the cropping history in that field and the presence
of perennial crops in rotation in which dandelion remained uncontrolled. It is difficult
to predict the impact of dandelion infestation on canola yield. Measures of dandelion
relating to canola yield loss were more reliable in fields receiving less tillage.
Dandelion can, however, cause high levels of yield loss, and even a moderate and patchy
infestation of dandelion in a canola field could warrant control. Control with glyphosate
is best achieved at rates of 900 g a.i. ha-1 (I L Roundup Transorb/acre)
applied post-harvest in either direct-seeded or conventional-tillage systems.
Acknowledgements:
The authors acknowledge the financial support of Canada-Manitoba Agri-Food Research and
Development Initiative (ARDI), the Natural Sciences and Engineering Research Council, and
generous financial support and staff help from Monsanto Canada.
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