Fungicide dose-response trials in wheat: the basis for ...

Project Report No. 373 September 2005 Price: £5.00

Fungicide dose-response trials in wheat: the basis for

choosing ‘Appropriate Dose’

by

D. Lockley 1 and W.S. Clark 2

1ADAS Mamhead, Exeter, EX6 8HD 2ADAS Boxworth, Cambridge, CB3 8NN

This is the final report of HGCA-funded Project No. 2497 which started in May 2001, lasted for 38 months and was funded with a contract £289,379. It was then extended for a further 12 months by a contract of £82,320. The work was co-ordinated by N D Paveley, ADAS High Mowthorpe. Participants included S Oxley, SAC Edinburgh, A Ainsley, York, M Self, TAG, Morley, W S Clark, ADAS, Boxworth and K D Lockley, ADAS, Mamhead. The Home-Grown Cereals Authority (HGCA) has provided funding for this project but has not conducted the research or written this report. While the authors have worked on the best information available to them, neither HGCA nor the authors shall in any event be liable for any loss, damage or injury howsoever suffered directly or indirectly in relation to the report or the research on which it is based. Reference herein to trade names and proprietary products without stating that they are protected does not imply that they may be regarded as unprotected and thus free for general use. No endorsement of named products is intended nor is it any criticism implied of other alternative, but unnamed, products.

CONTENTS

PAGE

ABSTRACT 1

1.0 SUMMARY 2

2.0 INTRODUCTION 3

2.1 The dose-response curve 3

2.2 The recommended dose 4

2.3 Appropriate fungicide doses 4

2.4 Variation in dose-response curves 5

3.0 MATERIALS AND METHODS 7

3.1 Sites 7

3.2 Site selection and establishment 8

3.3 Experiment design 8

3.4 Fungicide treatments 8

3.5 Assessments and records 22

3.6 Data handling 23

3.7 Statistical analysis 23

4.0 RESULTS 25

4.1 Stagonospora nodorum experiments 25

4.2 Yellow rust experiments 43

4.3 Septoria tritici experiments 67

4.4 Brown rust experiments 96

4.5 Mildew experiments 104

5.0 CONCLUSIONS 112

Appendix 1 List of active ingredients and products 116

Appendix 2 List of products and active ingredients 117

1

ABSTRACT

Robust, comparative dose-response data sets were produced for the most widely used fungicides applied to

wheat in the UK. This includes active ingredients from azole, morpholine, strobilurin, spiroketalamine,

benzamide and carboxanilide fungicide groups. Up to three years of data on fungicides launched in 2005 were

obtained from these experiments. These included boscalid (in mixture with epoxiconazole in Tracker),

dimoxystrobin (in mixture with epoxiconazole in Swing Gold), fluoxastrobin (in mixture with prothioconazole

in Fandango), metrafenone (Flexity) and prothioconazole (Proline).

Information on these new products was published in the ‘Wheat Disease Management Guide - 2005

Update‘(published in February 2005) and on the HGCA web site (www.hgca.com) as an interactive tool in

March 2005.

Data on strobilurin performance against S. tritici clearly show a dramatic reduction in efficacy over the period

2002 – 2004. Despite measurements of the frequency of the resistance allele (G143A) conferring resistance to

strobilurin fungicides indicating that resistance levels in the UK were generally 80-100%, there was still a

measurable effect of strobilurin fungicides against S. tritici in these experiments. This phenomenon is not fully

understood.

Analysis of data since 1994 indicates a significant reduction in the activity of epoxiconazole (and by inference,

all other azole fungicides) against S. tritici. The observation of this effect in field trials was supported by

laboratory-based data showing changes in the sensitivity of isolates of S. tritici.

In spite of these changes in sensitivity in populations of mildew and S. tritici, most pathogens attacking wheat

crops are well-controlled by modern fungicides. The main pathogen of wheat, S. tritici, is well controlled by the

azole fungicides, chlorothalonil and boscalid. The morpholines, in mixture with azoles, also add to the control

of septoria. Although control of mildew by the strobilurin fungicides has almost been lost completely in the last

few years, it is still well controlled by cyprodinil, metrafenone, the morpholines, quinoxyfen, and spiroxamine.

The azoles also still add to mildew control. Yellow and brown rust are well controlled by many of the azole and

strobilurin fungicides.

Data from experiments were used to fit exponential curves describing the effect of fungicides on disease, green

leaf area, yield and grain quality. These data typically explained a very high proportion (over 90%) of the

variance. The fitted curves and their parameters are given in the report.

2

1.0 SUMMARY

Within the period of experimentation in this project there was a loss of activity of the strobilurins against

wheat powdery mildew and Septoria tritici. This had a dramatic effect on the efficacy of these products.

Analysis of data from the appropriate dose experiments since 1994 also showed a decline in activity of the

azole fungicides against S. tritici.

Robust, comparative dose-response data sets were gathered for the most widely used fungicides applied to

wheat. This includes active ingredients from azole, morpholine, strobilurin, spiroketalamine, benzamide

and carboxanilide fungicide groups. Up to three years of data on fungicides launched in 2005 were

gathered. These included boscalid (in mixture with epoxiconazole in Tracker), dimoxystrobin (in mixture

with epoxiconazole in Swing Gold), fluoxastrobin (in mixture with prothioconazole in Fandango),

metrafenone (Flexity) and prothioconazole (Proline).

Data on strobilurin performance against S. tritici clearly show a dramatic reduction in efficacy from 2002 to

2004. In other HGCA LINK experiments, measurements of the frequency of the resistance allele (G143A)

in the population of S. tritici indicated that resistance levels were generally greater than 80%. However, in

these experiments there was still a measurable effect of strobilurin fungicides against S. tritici.

Analysis of data since 1994 indicates a significant reduction in activity of epoxiconazole (and by inference,

all other azole fungicides) against S. tritici. The observation of this effect in field trials was supported by

laboratory-based data showing changes in the sensitivity of isolates of S. tritici. Information on these new

products was published in the HGCA ‘Wheat Disease Management Guide - 2005 Update’ (published in

February 2005) and on the HGCA web site as an interactive tool in March 2005. Opus (epoxiconazole)

provided the most effective and consistent control of S. tritici. Of the new fungicide introductions in 2005,

Tracker (epoxiconazole plus boscalid), Proline (prothioconazole) and Fandango (prothioconazole plus

fluoxastrobin) all gave control of S. tritici comparable to Opus.

The patterns of dose-response for yellow-rust control are substantially different than those for S. tritici. The

majority of the control of yellow rust is obtained from the first quarter dose. Provided sprays are well

timed, effective and consistent, control of yellow rust can be obtained with between a quarter and a half of

the label-recommended dose of most azole fungicides. There is no evidence of any shift in the sensitivity of

yellow rust to the triazoles since the mid 90s. The strobilurins continue to be very effective against yellow

and brown rust.

Flexity, Neon and Tern gave good control of mildew, particularly at higher doses. Proline, also gave good

control of mildew, particularly at higher doses.

3

2.0 INTRODUCTION

Advances in fungicide chemistry have helped cereal growers respond to the increased economic pressures

arising from European agricultural policies and falling world prices, by reducing unit cost of production.

Despite considerable rationalisation in the agrochemical industry, the flow of novel active ingredients continues,

with many new active ingredients being recently introduced. New products command premium prices, so it is

important that growers have access to independent data on their performance, in order to weigh benefits against

costs. Fungicides can also remain on the market for many years and some of the established materials offer

useful disease control at a lower price. However, the performance of pesticides is not static. Over time, less

sensitive pathogen strains are selected, resulting in a shift in the dose-response curve. Within the period of

experimentation in this report we saw a loss of activity of the strobilurins against wheat powdery mildew and S.

tritici. This had a dramatic effect on the efficacy of these products. Analysis of data from the appropriate dose

experiments since 1994 shows a decline in activity of the azole fungicides against S. tritici. This can be seen

from changes in the shape of the dose response curves over this time. Clearly the dose (and hence input cost)

required to achieve effective control can change over time.

2.1 The dose-response curve

If the severity of foliar disease is measured in experimental plots that received fungicide treatment, at a range of

doses, some time before, the results will typically look like those in Figure 2.1. Those plots that receive no

treatment will suffer a level of disease determined by the local 'disease pressure'. Fungicide treated plots will

suffer less disease and the higher the dose, the lower the disease severity. However, a law of diminishing returns

operates and each successive increase in dose causes a smaller additional effect. The decrease in disease with

increasing dose is commonly represented by a line, rather than bars, and is described as a 'dose-response curve'.

Figure 2.1 . Disease severity following fungicide treatment at a range of doses and the dose-response curve

4

The maximum dose that can be used is specified on the product label, as the recommended dose, and must not

be exceeded. However, there is no legal limit to the minimum dose that should be applied, and the majority of

crops now receive fungicides at doses substantially below those recommended on the product label. To

understand why, it is helpful to consider how the recommended dose is set.

2.2 The recommended dose

Complete disease control is usually either technically unachievable in the field on a consistent basis, or is not

cost effective. Furthermore, when the same fungicide is applied to control the same disease at a range of

locations, the response to the applied chemical varies from place to place. The dose that gives 90% control in

one field can be quite different to that which gives 90% control in another. To allow for this inherent variability

and to avoid product dissatisfaction, the label recommended dose is usually set at a level that consistently gives

a high level of control across locations and seasons, typically 80-90% control 80-90% of the time. During the

late 1980's and early 1990's, growers began to appreciate the safety margin built into the label recommended

dose and, under pressure to reduce input costs, began to reduce the doses of fungicides applied to cereal crops.

Survey data suggest that these reductions were, and still are, often made in an arbitrary manner.

2.3 Appropriate fungicide doses

Fungicide cost increases in direct proportion to the dose applied. As the loss of yield and grain quality is

proportional to the level of disease, a point can be found on the dose-response curve, beyond which the cost of

any further increase in dose would not be paid for by the resulting yield increase. At this point, profit is

maximised (Figure 2) and unnecessary pesticide use minimised - by definition the appropriate dose to apply.

Figure 2.2. Dose-response curve, margin over fungicide cost and appropriate dose

At doses below the appropriate dose, profit is reduced by ineffective disease control. At doses above the

appropriate dose, profit is reduced by excessive fungicide cost. It is important to note that the loss of profit is

more severe if the dose is reduced below the appropriate dose than if increased above it. Hence, where there is

5

uncertainty about the appropriate dose to apply, it is prudent to apply more, rather than less. The greater the

uncertainty, the greater the safety margin required.

On what basis can a crop manager decide on the appropriate dose to apply - given that, as the shape of the dose-

response curve varies from site to site and season to season, so must the appropriate dose? And how can the

uncertainty surrounding the choice of dose be minimised, to allow doses to be applied that are consistently close

to the economic optimum, without suffering occasional severe losses due to under-application? The answers

must come from taking account of the causes of the variation in disease control between sites and seasons.

2.4 Variation in dose-response curves

One of the main reasons for variation in disease control between sites and seasons is that, in the absence of

treatment, disease severity varies between sites and seasons. Figure 2.3 shows the effect on the dose-response

curve and the appropriate dose, of different levels of untreated disease. Curve (A) represents, for example, a

crop of a disease susceptible variety, that experienced weather conditions favourable to disease development;

curve (B) a more resistant variety or a susceptible variety under conditions less favourable to disease; and curve

(C) a variety with complete immunity to that disease.

Figure 2.3. Effect of disease pressure on dose-response curve and appropriate dose (represented by an arrow)

Clearly, higher disease pressure justifies higher inputs. However, the appropriate dose also depends on

efficiency of control. Figure 2.4 takes the high disease pressure case (A) and shows the effect of applying

alternative products that are more (B), or less (C), effective. All else being equal, more effective products have

lower appropriate doses. However, efficacy is often reflected in price, so the best product/dose combination

needs to be selected to do the job.

6

Figure 2.4. Effect of fungicide activity on dose-response curves and appropriate dose. It can be seen, from the examples shown above, that the appropriate dose in a range of circumstances can vary

between the recommended dose and zero. A crop manager who is better able to quantify disease pressure and

predict efficiency of control, will be able to apply doses that are consistently closer to the economic optimum.

This will reduce unit cost of production and provide a sound rationale for the dose of pesticide used.

7

3.0 MATERIALS AND METHODS

3.1 Sites

This report covers work conducted over four harvest years at sites selected to target the main foliar diseases of

winter wheat – Septoria tritici, Stagonospora nodorum, yellow rust, brown rust and powdery mildew. The

location of sites and varieties used are listed in Table 3.1.

Table 3.1 Experiment numbers, sites, harvest years, varieties and target diseases

Experiment

number Site

Harvest

year Variety Target disease

1 Pelynt, Looe, Cornwall 2001 Savannah S. nodorum

2 Terrington-St Clement, Norfolk 2001 Brigadier Yellow rust

3 Henley, Ipswich, Suffolk 2001 Equinox Yellow rust

4 Morley, Wymondham, Norfolk 2001 Riband Brown rust/S. tritici

5 Milton, Leuchars, Fife 2001 Consort S. tritici

6 Dunecht, Aberdeenshire 2001 Riband Powdery mildew



9 Morley, Wymondham, Norfolk 2002 Brigadier Yellow rust

10 Otley, Suffolk 2002 Shamrock Brown rust

11 Kilrie, Kirkcaldy, Fife 2002 Consort S. tritici

12 Dunecht, Aberdeenshire 2002 Claire Powdery mildew



15 Morley, Wymondham, Norfolk 2003 Consort S. tritici


17 Coatown of Balgonie, Glenrothes, Fife 2003 Consort S. tritici

18 Dunecht, Alford, Aberdeenshire 2003 Claire Powdery mildew

19 Carlow, Ireland 2003 Madrigal S. tritici

20 Pelynt, Cornwall 2004 Savannah S. nodorum


22 Morley, Wymondham, Norfolk 2004 Consort S. tritici


24 Coaltown of Balgonie, Glenrothes, Fife 2004 Consort S. tritici

25 Dunecht, Aberdeenshire 2004 Claire Powdery mildew

26 Carlow, Ireland 2004 Madrigal S. tritici

8

3.2 Site selection and establishment

First wheat sites with at least a one-year break from cereals (excluding oats) were chosen. Soil was sampled for

pH and nutrient analysis and plots were drilled using a suitable plot drill (e.g. Øyjord) at a seed rate appropriate

for the locality and soil type. Plot size was variable to fit in with local farm tramlines, but was in the range of 20

- 60m². All inputs other than fungicides were applied to ensure that the crop remained free from nutritional

deficiencies, or severe pest or weed infestations. At yellow rust sites and some brown rust sites, pots of rust-

infected plants were planted out in a regular grid pattern in the spring to maximise the chance of disease

development.

3.3 Experiment design

A randomised block design incorporating between 33 and 45 treatments with three replicates was used for all

experiments. At sites targeting rusts or mildew, guard plots of a variety resistant to the target disease were

drilled alternately with treatment plots wherever possible.

3.4 Fungicide treatments

Fungicide treatments were applied as single sprays. The target stage for fungicide application was determined

by pathogen development. At the S. tritici sites, the target timing was at the emergence of eventual leaf 2. This

was usually at GS 33, but may have occurred at GS 32 in some crops. Crop development was checked regularly

from the beginning of GS 31 to ensure that the emergence of this leaf was identified correctly. This growth

stage was also the timing for the yellow rust and mildew sites, but at these sites, the timing was adjusted earlier

if early epidemic development required. Brown rust and S. nodorum are characterised by rapid development

late in the season, so the target timing for these sites was at GS 37-39 rather than GS 33 unless there was a risk

of severe disease development at GS 33.

Sprays were applied in 200-300 litres water/ha using hand-held pressurised plot spraying equipment fitted with

flat fan nozzles, selected to produce a medium spray quality at 200-300 kPa pressure. Each fungicide product

was applied at quarter, half, full and double the label recommended dose. Double dose treatments were applied

for specific experimental purposes and must not be applied by farmers to farm crops. . Crop that received double

dose treatments was disposed of safely at harvest.

Details of fungicide treatments at each site in each year are given in Tables 3.2 – 3.14.

9

Table 3.2 Treatments for Experiment 1 (Site 1, 2001)

Treatment code Active ingredient Product Dose product/ha

Standards

1 Epoxiconazole Opus 2.00 litre




5 Azoxystrobin Amistar 2.00 litre 6 Azoxystrobin Amistar 1.00 litre

7 Azoxystrobin Amistar 0.50 litre


Test actives

9 Trifloxystrobin Twist 4.00 litre




13 Picoxystrobin Acanto 2.00 litre




17 Pyraclostrobin Vivid 2.00 litre




21 Metconazole Caramba 3.00 litre




25 Fluquinconazole Flamenco 2.50 litre




29 Cyprodinil Unix 2.00 kg




33 Untreated - -

34 Untreated - -

10

Table 3.3 Treatments for Experiments 2, 3, 4 & 5 (Sites 2, 3, 4 & 5, 2001)


Standards








Test actives













21 Famoxadone -

22 Famoxadone -

23 Famoxadone -

24 Famoxadone -









33 Untreated - -

34 Untreated - -

11



Standards





5 Fenpropidin Tern 2.00 litre 6 Fenpropidin Tern 1.00 litre

7 Fenpropidin Tern 0.50 litre


Test actives









17 Spiroxamine Neon 3.00 litre








25 Quinoxyfen Fortress 0.60 litre




29

30

31

32

33 Untreated - -

34 Untreated - -

12



Standards








Test actives













21 Prothioconazole Proline 1.60 litre




25 Prothioconazole + fluoxastrobin Fandango 3.00 litre








33 Untreated - -

34 Untreated - -

13

Table 3.6 Treatments for Experiments 8, 9, 10 & 11 (Sites 2, 3, 4 & 5, 2002)


Standards








Test actives

























33 Untreated - -

34 Untreated - -

14



Standards








9 Fenpropimorph Corbel 2.00 litre




Test actives





17 Metrafenone + fenpropimorph Flexity + Corbel 1.00+1.08 litre
















33 Untreated - -

34 Untreated - -

15



Standards








Test actives

9 Trifloxystrobin Swift 1.00 litre




















29 Epoxiconazole + dimoxystrobin Swing Gold 3.00 litre




33 Untreated - -

34 Untreated - -

16

Table 3.9 Treatments for Experiments 14, 15, 16, 17 & 19 (Sites 2, 3, 4, 5 & 7, 2003)


Standards





Test actives

Pyraclostrobin + epoxiconazole Vivid + Opus 2.00+2.00 litre
























29 Trifloxystrobin + epoxiconazole Swift + Opus 1.00+2.00 litre




33 Untreated - -

34 Untreated - -

17



Standards












Test actives





















33 Untreated - -

34 Untreated - -

18


Treatment code Active ingredient Product Dose product/ha Standards

1 Epoxiconazole Opus 2.00 litre 2 Epoxiconazole Opus 1.00 litre 3 Epoxiconazole Opus 0.50 litre 4 Epoxiconazole Opus 0.25 litre 5 Chlorothalonil Bravo 4.00 litre 6 Chlorothalonil Bravo 2.00 litre 7 Chlorothalonil Bravo 1.00 litre 8 Chlorothalonil Bravo 0.50 litre

Test actives 9 Pyraclostrobin Vivid 2.00 litre

10 Pyraclostrobin Vivid 1.00 litre 11 Pyraclostrobin Vivid 0.50 litre 12 Pyraclostrobin Vivid 0.25 litre 13 Trifloxystrobin Swift 1.00 litre 14 Trifloxystrobin Swift 0.50 litre 15 Trifloxystrobin Swift 0.25 litre 16 Trifloxystrobin Swift 0.125 litre 17 Famoxadone + flusilazole Charisma 3.00 litres 18 Famoxadone + flusilazole Charisma 1.50 litres 19 Famoxadone + flusilazole Charisma 0.75 litre 20 Famoxadone + flusilazole Charisma 0.375 litre 21 Prothioconazole Proline 1.60 litre 22 Prothioconazole Proline 0.80 litre 23 Prothioconazole Proline 0.40 litre 24 Prothioconazole Proline 0.20 litre 25 Prothioconazole + fluoxastrobin Fandango 3.00 litre 26 Prothioconazole + fluoxastrobin Fandango 1.50 litre 27 Prothioconazole + fluoxastrobin Fandango 0.75 litre 28 Prothioconazole + fluoxastrobin Fandango 0.375 litre 29 Dimoxystrobin + epoxiconazole Swing Gold 3.00 litre 30 Dimoxystrobin + epoxiconazole Swing Gold 1.50 litre 31 Dimoxystrobin + epoxiconazole Swing Gold 0.75 litre 32 Dimoxystrobin + epoxiconazole Swing Gold 0.375 litre 33 Boscalid + epoxiconazole Tracker 3.00 litres 34 Boscalid + epoxiconazole Tracker 1.50 litres 35 Boscalid + epoxiconazole Tracker 0.75 litre 36 Boscalid + epoxiconazole Tracker 0.375 litre 37 HGCA9 Folpan 80WDG 4.00 kg 38 HGCA9 Folpan 80WDG 2.00 kg 39 HGCA9 Folpan 80WDG 1.00 kg 40 HGCA9 Folpan 80WDG 0.50 kg 41 Untreated --- --- 42 Untreated --- ---

19

Table 3.12 Treatments for Experiments 22, 24 & 26 (Sites 3, 5 & 7, 2004)


1 Epoxiconazole Opus 2.00 litre 2 Epoxiconazole Opus 1.00 litre 3 Epoxiconazole Opus 0.50 litre 4 Epoxiconazole Opus 0.25 litre 5 Chlorothalonil Bravo 4.00 litre 6 Chlorothalonil Bravo 2.00 litre 7 Chlorothalonil Bravo 1.00 litre 8 Chlorothalonil Bravo 0.50 litre

Test actives 9 Pyraclostrobin Vivid 2.00 litre

10 Pyraclostrobin Vivid 1.00 litre 11 Pyraclostrobin Vivid 0.50 litre 12 Pyraclostrobin Vivid 0.25 litre 13 Trifloxystrobin Swift 1.00 litre 14 Trifloxystrobin Swift 0.50 litre 15 Trifloxystrobin Swift 0.25 litre 16 Trifloxystrobin Swift 0.125 litre 17 Pyraclostrobin + epoxiconazole Vivid + Opus 2.00 + 0.50 litre 18 Pyraclostrobin + epoxiconazole Vivid + Opus 1.00 + 0.50 litre 19 Pyraclostrobin + epoxiconazole Vivid + Opus 0.50 + 0.50 litre 20 Pyraclostrobin + epoxiconazole Vivid + Opus 0.25 + 0.50 litre 21 Trifloxystrobin + epoxiconazole Swift +Opus 1.00 + 0.50 litre 22 Trifloxystrobin + epoxiconazole Swift +Opus 0.50 + 0.50 litre 23 Trifloxystrobin + epoxiconazole Swift +Opus 0.25 + 0.50 litre 24 Trifloxystrobin + epoxiconazole Swift +Opus 0.125 +0.50 litre 25 Famoxadone + flusilazole Charisma 3.00 litre 26 Famoxadone + flusilazole Charisma 1.50 litre 27 Famoxadone + flusilazole Charisma 0.75 litre 28 Famoxadone + flusilazole Charisma 0.375 litre 29 Prothioconazole Proline 1.60 litre 30 Prothioconazole Proline 0.80 litre 31 Prothioconazole Proline 0.40 litre 32 Prothioconazole Proline 0.20 litre 33 Prothioconazole + fluoxastrobin Fandango 3.00 litre 34 Prothioconazole + fluoxastrobin Fandango 1.50 litre 35 Prothioconazole + fluoxastrobin Fandango 0.75 litre 36 Prothioconazole + fluoxastrobin Fandango 0.375 litre 37 Boscalid + epoxiconazole Tracker 3.00 litre 38 Boscalid + epoxiconazole Tracker 1.50 litre 39 Boscalid + epoxiconazole Tracker 0.75 litre 40 Boscalid + epoxiconazole Tracker 0.375 litre 41 HGCA9 Folpan 80WDG 4.00 kg 42 HGCA9 Folpan 80WDG 2.00 kg 43 HGCA9 Folpan 80WDG 1.00 kg 44 HGCA9 Folpan 80WDG 0.50 kg 45 Untreated --- --- 46 Untreated --- ---

20

Table 3.13 Treatments for Experiments 21 & 23 (Sites 2 & 4, 2004)


1 Epoxiconazole Opus 2.00 litre 2 Epoxiconazole Opus 1.00 litre 3 Epoxiconazole Opus 0.50 litre 4 Epoxiconazole Opus 0.25 litre

Test actives 5 Pyraclostrobin Vivid 2.00 litre 6 Pyraclostrobin Vivid 1.00 litre 7 Pyraclostrobin Vivid 0.50 litre 8 Pyraclostrobin Vivid 0.25 litre 9 Trifloxystrobin Swift 1.00 litre

10 Trifloxystrobin Swift 0.50 litre 11 Trifloxystrobin Swift 0.25 litre 12 Trifloxystrobin Swift 0.125 litre 13 Azoxystrobin Amistar 2.00 litre 14 Azoxystrobin Amistar 1.00 litre 15 Azoxystrobin Amistar 0.50 litre 16 Azoxystrobin Amistar 0.25 litre 17 Famoxadone + flusilazole Charisma 3.00 litre 18 Famoxadone + flusilazole Charisma 1.50 litre 19 Famoxadone + flusilazole Charisma 0.75 litre 20 Famoxadone + flusilazole Charisma 0.375 litre 21 Prothioconazole Proline 1.60 litre 22 Prothioconazole Proline 0.80 litre 23 Prothioconazole Proline 0.40 litre 24 Prothioconazole Proline 0.20 litre 25 Prothioconazole + fluoxastrobin Fandango 3.00 litre 26 Prothioconazole + fluoxastrobin Fandango 1.50 litre 27 Prothioconazole + fluoxastrobin Fandango 0.75 litre 28 Prothioconazole + fluoxastrobin Fandango 0.375 litre 29 Boscalid + epoxiconazole Tracker 3.00 litre 30 Boscalid + epoxiconazole Tracker 1.50 litre 31 Boscalid + epoxiconazole Tracker 0.75 litre 32 Boscalid + epoxiconazole Tracker 0.375 litre 33 HGCA9 Folpan 80WDG 4.00 kg 34 HGCA9 Folpan 80WDG 2.00 kg 35 HGCA9 Folpan 80WDG 1.00 kg 36 HGCA9 Folpan 80WDG 0.50 kg 37 Untreated --- --- 38 Untreated --- ---

21



Standards












Test actives

















29 Metrafenone Flexity 1.00 litre




33 Untreated - -

34 Untreated - -

22

3.5 Assessments and records

3.5.1 Assessments of leaf disease and green leaf area

Levels of foliar disease and green leaf area were assessed as described below on 25-50 shoots sampled from

across the experiment area immediately prior to fungicide application.

Approximately three weeks and six weeks after treatments were applied, all plots were assessed, by randomly

sampling 10 shoots per plot and estimating the average percentage leaf area affected by disease symptoms

(including any necrosis or chlorosis attributable to disease) on each leaf layer. The first assessment was aimed

at quantifying disease on leaves 3and 4, giving an indication of eradicant activity of fungicides. The second

assessment recorded treatment effects on leaves 1 and 2 giving a measure of the protectant properties of the

fungicides.

3.5.2 Assessments of ear diseases

Diseases were assessed on a random sample of 10 ears per plot at GS 85 if more than 5% ear area or more than

five grain sites per ear were affected in untreated plots.

3.5.3 Stem-base disease

Stem-bases diseases (eyespot, sharp eyespot and Fusarium) were assessed on 25 stems per plot in untreated

plots at GS 75. If over 25% of stems had moderate or severe lesions, or if over 10% of stems had severe lesions,

then all plots were assessed.

3.5.4 Lodging

If plots were affected by lodging, the percentage plot area affected was recorded prior to harvest.

3.5.5 Yield

All plots were harvested using a plot combine harvester. Grain samples were taken for moisture determination

and grain quality assessments. Yields were calculated at 85% dry matter.

3.5.6 Grain quality

Specific weight of grain was measured for each plot and adjusted to 85% dry matter.

23

Agronomic records

Details of site, soil type and all agrochemical inputs were recorded.

3.6 Data handling

Disease, green leaf area, yield and grain quality data were collected manually or directly onto portable

computers. All data were transferred to Microsoft Excel worksheets after collection.

3.7 Statistical analysis

3.7.1 Individual season and site assessments

Each season, each assessment (site, variate, date, leaf layer) was summarised by analysis of variance and the

validity of the analysis was checked by examination of residuals. An over-assessment analysis of data from the

previous Appropriate Fungicide Dose project provides a more powerful assessment of the need for transformation

than can be obtained from analysis of a single assessment. Such an analysis has shown that, whilst no

transformation is needed for yield or specific weights, a logit transformation of %disease and %green leaf area

provides a more valid analysis. Thus disease and green leaf area were analysed on a logit scale and back-

transformed for presentation.

A small number of extreme outliers were removed from the data after consultation as to the cause.

In some cases plots of residuals against plot number showed a linear trend in the residuals within some of the

blocks. These trends were removed by using covariates on plot number within each block.

For each disease assessment, dose-response curves were plotted for each fungicide and exponential curves, of the

form y=a+bekx , where y = % disease and x = proportion of the recommended dose were fitted. Exponential

curves were also fitted to the green leaf areas and harvest variables. All curves were constrained to pass through

the mean of the untreated (dose=0) plots.

Variates that did not contribute useful information were excluded from further analysis. These were defined to be

variates for which there was no significant effect of treatment and of differences between products or doses,

disease variates for which there was an average of less than 5% disease on untreated plots, and green leaf areas

for which there was more than an average of 90% green leaf area on the untreated plots. In addition, assessments

where more than one disease was recorded on a particular date were examined to check whether they were

reliable. Any assessments felt to be unsafe were excluded from over-assessment means.

Over-assessment means were calculated for each site and disease, together with corresponding green leaf area

means. Means for all transformed variables were calculated on the logit scale and then back-transformed for

24

presentation. For Septoria tritici, means were calculated separately for protectant fungicide activity (leaves just

emerged, or still to emerge at time of treatment, together with ear disease), and eradicant fungicide activity (the

first two non-protectant leaves). For other diseases the eradicant and protectant categories were combined.

Each season, over-site means were calculated for each disease. These were constructed from valid assessments

and giving equal weight to each site, rather than each assessment. At each stage exponential curves were fitted to

the means.

3.7.2 Over-season means

As new fungicides have become available, some of them have been included in these experiments, whilst other,

less promising, or no longer widely used, products have been dropped from the trials. This leads to incomplete

tables of fungicides and doses by site and season.

In the previous project, incomplete tables means for fungicides and doses by site were analysed using the method

of fitting constants, which was has been widely used in the analysis of variety trials. More recently, residual

maximum likelihood (REML) has been developed for the analysis of this type of data (Patterson 1997) and is now

available in several general-purpose statistical computer packages, including GenStat. The REML method has the

advantage of including information on product differences that may be available in the site means, and of

calculating the appropriate weight to give this information in the combined means. REML means are always

between the unadjusted and the fitcon means of the data. If the variability between sites is large relative to the

variation within sites, as is usually the case with multi-site and season experiments, REML means will be close to

the fitcon means. Conversely if the variability between sites was small relative to the variation within sites,

REML means would be close to the unadjusted means.

The REML method is more flexible than the fitting constants method, but this flexibility does means that the most

appropriate form of the method for the data produced in this project needed to be investigated. REML analysis is

sensitive to the proportion of the data matrix that is missing. For the UK data, although it is theoretically possible

to include all the data from individual assessment dates and leaf layers at each site, the resulting data matrix is

very sparse and investigation has shown that the method often does not converge to give a solution. Several

versions of REML analysis have been examined. For the UK data, the average percent disease over assessments,

calculated from the first two leaves in each of the eradicant and protectant categories at each site, provides a

suitable measure of disease for combining over experiments using the REML method. The form of REML used

for calculating over site and season means was to have a fixed effect with levels representing each fungicide and

dose combination plus untreated, and a random effect with a level for each site and season.

Corresponding green leaf areas, yields and specific weights were summarised by REML in the same way.

Exponential curves were fitted to the REML adjusted means to provide over site and season summaries.

25

4.0 RESULTS

4.1 Stagonospora nodorum experiments

4.1.1 Disease control.

All currently available commercial varieties that are susceptible to S. nodorum are also susceptible to Septoria

tritici. Since both diseases are favoured by similar weather conditions, mixed infections frequently occur. It is

rarely possible to differentiate in the field between the foliar symptoms caused by the two fungi and activity of

fungicides against S. nodorum can therefore best be assessed by the ear symptoms known as glume blotch.

Figure 4.1 shows the dose response curves fitted from parameters given in Table 4.1 derived from data from the

2001 site (Experiment 1). A prolonged dry spell during May 2001 limited the development of disease on upper

leaves. Control of glume blotch from fungicides applied, as in this case, on 18 May, well before ear emergence,

largely reflects the fungicides’ ability to protect the upper leaves from infection from where inoculum could be

spread to the ears when wet weather returned during June. All fungicides showed activity against S. nodorum,

most azoles required between a half and full dose to achieve maximum control. The control of glume blotch

given by Flamenco, however, did not increase above quarter dose. All strobilurin fungicides reduced glume

blotch. The greatest reduction was given by Acanto at high doses but Amistar, Twist and Vivid gave good

control at between half and quarter dose.

Wet weather during May 2002 delayed spray application until 31 May (GS 49), a week after flag leaf

emergence. As a consequence, a severe epidemic of glume blotch developed. Fungicide performance largely

reflects eradicant activity on the flag leaf with the possibility of some protection of the ear. Again, all

fungicides gave some control of glume blotch, but most required a full dose to give reasonable control. The

exception was Vivid, which at half dose gave a level of control that was equivalent to, or better than, a full dose

of most other fungicides tested (Figure 4.2).

A moderate epidemic of S. nodorum developed in 2003. Spray timing coincided with the emergence of Leaf 2

(9 May) and therefore the control of glume blotch reflects the protectant activity of fungicides (Table 4.3 and

Figure 4.3). All products show low (more negative) k values and achieve maximum control of glume blotch at

between half and full dose. The two azole fungicides (Opus and Proline) gave similar control. Vivid remained

the most active of the strobilurin products and Swift (Twist SC) the least active. Azole/strobilurin mixtures

(Fandango and Swing Gold) showed a small improvement in disease control over the corresponding azole.

Glume blotch did not develop to any great extent at the Cornish site in 2004, possibly due to a severe epidemic

of S. tritici causing competition for infection sites on the upper leaves. Fungicides were applied on 10 May

when leaf 2 was just fully emerged, so disease control was due mainly to the protectant activity of products.

26

With low disease levels, it would be wrong to try to draw too many conclusions about fungicide activity.

However, Charisma, a azole/strobilurin mixture gave poor control relative to other azole/strobilurin mixtures.

Bravo, brought back into the experiment in 2004 because of increased popularity following concerns over S.

tritici resistance to strobilurin fungicides, proved to be a reasonable protectant option for S. nodorum control.

HGCA9, which was also a protectant fungicide was less effective (Table 4.4 and Figure 4.4).

27

Table 4.1 Parameter estimates for fitted dose response curves for glume blotch, Experiment 1, 2001

Parameter estimates

Fungicide a b k a+b a+bek

Mean R2

adjusted

Opus 12.28 5.81 -3.11 18.09 12.54 95.5

Amistar 12.20 5.89 -5.32 18.09 12.23 76.2

Twist 12.37 5.72 -4.62 18.09 12.43 90.6

Acanto 10.87 8.10 -2.23 18.09 10.87 95.1

Vivid 12.91 5.18 -16.63 18.09 12.91 53.4

Proline 14.46 3.98 -4.42 18.09 14.46 8.7

Caramba 13.58 4.67 -3.43 18.09 13.58 95.6

Flamenco 14.15 3.95 -20 18.09 14.15 50.1

Figure 4.1 Dose-response curves for glume blotch, Experiment 1, 2001

Opus

0

5

10

15

20

Sept

oria

nod

orum

(%)

Caramba

0

5

10

15

20

0 0.5 1 1.5 2

Dose

Sept

oria

nod

orum

(%)

Amistar

0

5

10

15

20Twist

0

5

10

15

20

Flamenco

0

5

10

15

20

0 0.5 1 1.5 2

Dose

Acanto

0

5

10

15

20

0 0.5 1 1.5 2

Dose

Vivid

0

5

10

15

20

Proline

0

5

10

15

20

0 0.5 1 1.5 2

Dose

28


Parameter estimates


Mean R2

adjusted

Opus 24.9 42.05 -2.22 66.95 29.5 98.4

Amistar 29.7 37.29 -2.33 66.95 33.3 97.9

Caramba 29.1 37.82 -2.46 66.95 32.4 97.6

Proline 26.5 40.49 -2.55 66.95 29.6 93.9

Twist 25.1 41.87 -1.48 66.95 34.6 96.8

Acanto 32.9 34.08 -3.07 66.95 34.5 99.6

Vivid 20.4 46.57 -4.67 66.95 20.8 97.0

Fandango 21.2 45.77 -2.44 66.95 25.2 98.0

Figure 4.2 Dose response curves for glume blotch, Experiment 7, 2002

Proline

0

10

20

30

40

50

60

70

80

90

Fandango

01020

30405060

708090

0 0.5 1 1.5 2

Dose

Opus

0

10

20

30

40

50

60

70

80

90

% S

. nod

orum

Twist

0102030405060708090

0 0.5 1 1.5 2

Dose

% S

. nod

orum

Amistar

0

10

20

30

40

50

60

70

80

90Caramba

0

10

20

30

40

50

60

70

80

90

Acanto

0102030405060708090

0 0.5 1 1.5 2

Dose

Vivid

0102030405060708090

0 0.5 1 1.5 2

Dose

29


Parameter estimates


Mean R2

adjusted

Opus 7.84 29.69 -6.4 37.5 7.9 58.8

Acanto 11.26 26.27 -8.91 37.5 11.3 20.4

Vivid 6.60 30.93 -10.37 37.5 6.6 24.0

Amistar 9.91 27.60 -6.34 37.5 10.0 54.9

Proline 8.57 28.96 -7.99 37.5 8.6 44.4

Fandango 6.44 31.09 -6.44 37.5 6.5 42.1

Swift 12.99 24.54 -7.38 37.5 13.0 -24.2

Swing Gold 7.20 30.30 -5.04 37.5 7.4 80.7


Opus

0

10

20

30

40

50

% S

. nod

orum

Proline

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

% S

. nod

orum

Acanto

0

10

20

30

40

50Vivid

0

10

20

30

40

50

Fandango

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Swift

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Amistar

0

10

20

30

40

50

Swing Gold

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

30


Parameter estimates


Mean R2

adjusted

Opus 6.3 4.6 -2.6 10.8 6.6 95.2

Swing Gold 5.8 5.0 -4.7 10.8 5.9 93.9

Tracker 5.0 5.9 -5.4 10.8 5.0 99.3

Bravo 6.5 4.4 -4.9 10.8 6.5 89.2

HGCA9 7.8 3.0 -16.0 10.8 7.8 66.7

Proline 6.5 4.4 -5.3 10.8 6.5 96.3

Fandango 6.2 4.7 -12.4 10.8 6.2 95.1

Charisma 8.0 2.9 -6.0 10.8 8.0 87.0

Vivid 6.8 4.0 -7.9 10.8 6.8 95.3

Swift 7.4 3.4 -11.4 10.8 7.4 96.7


Opus

0

5

10

% S

. nod

orum

Proline

0

5

10

0 0.5 1 1.5 2

Dose

% S

. nod

orum

Swing Gold

0

5

10

Tracker

0

5

10

Fandango

0

5

10

0 0.5 1 1.5 2

Dose

Charisma

0

5

10

0 0.5 1 1.5 2

Dose

Bravo

0

5

10

HGCA9

0

5

10

Vivid

0

5

10

0 0.5 1 1.5 2

Dose

Swift

0

5

10

0 0.5 1 1.5 2

Dose

31

4.1.2 Green leaf area

Because leaves were usually affected by a mixture of S. nodorum and S. tritici, green leaf area assessments

usually reflect the damage done by a combination of the two diseases. However, leaf 4 was primarily affected

by S. nodorum at the early assessment in 2001, and this leaf has been used to give an indication of how the

fungicides affected green leaf area at that site.

The effects of fungicides on the green leaf area on leaf 4 are an indication of their ability to eradicate disease

present at the time of spraying, some three weeks after that leaf emerged. All of the strobilurin fungicides,

except Amistar, maintained green leaf area well. Opus was the most effective azole, giving good levels of green

leaf area, even at half dose. Flamenco and Caramba were considerably less effective, suggesting that their

eradicant activity was being stretched too far, even at full dose (Table 4.5 and Figure 4.5)

32

Table 4.5 Parameter estimates for fitted dose response curves for green leaf area (leaf 4), Experiment 1, 2001

Parameter estimates


Mean R2

adjusted

Opus 54.6 -46.3 -3.29 8.3 52.9 89.1

Amistar 30.0 -21.7 -1.03 8.3 22.3 56.3

Twist 56.3 -48.0 -2.67 8.3 53.0 78.6

Acanto 77.7 -69.4 -0.91 8.3 49.8 86.3

Vivid 68.4 -60.1 -2.40 8.3 63.0 82.3

Proline -80.7 89.0 0.21 8.3 28.8 82.8

Caramba 88.0 -79.7 -0.34 8.3 31.4 98.6

Flamenco -105.1 113.4 0.09 8.3 19.5 92.3

Figure 4.5 Dose response curves for green leaf area (leaf 4), Experiment 1, 2001

Opus

0

10

20

30

40

50

60

70

80

90

% g

reen

leaf

are

a

Vivid

0102030405060708090

0 0.5 1 1.5 2

Dose

% g

reen

leaf

are

a

Amistar

0

10

20

30

40

50

60

70

80

90Twist

0

10

20

30

40

50

60

70

80

90

Proline

0102030405060708090

0 0.5 1 1.5 2

Dose

Caramba

0102030405060708090

0 0.5 1 1.5 2

Dose

Acanto

0

10

20

30

40

50

60

70

80

90

Flamenco

0102030405060708090

0 0.5 1 1.5 2

Dose

33

4.1.3 Yield

The relatively high untreated yield in 2001 reflects the low levels of disease which resulted from the dry May.

Yield increases from full doses of fungicides were small, often in the region of 0.5 t/ha and were probably due

to the control of low levels of glume blotch alone (Table 4.6 and Fig. 4.6).

In 2002, when disease levels were much higher, untreated yields were very low at 1.5 t/ha and full doses of

fungicides resulted in up to 3 t/ha yield increases. Vivid gave the highest yield response of the strobilurin

products, greater than the most effective azoles, Opus and Proline (Table 4.7 and Fig 4.7).

Vivid maintained this superiority in 2003 (Table 4.8 and Fig. 4.8), again reflecting good control of a substantial

glume blotch epidemic.

However, in 2004, when a severe epidemic of S. tritici displaced S. nodorum development, the best strobilurin

products could not match the performance of azole chemistry (Table 4.9 and Fig. 4.9). Strobilurin/azole

mixtures such as Swing Gold and Fandango still gave greater yield increases than their azole components alone

(Opus and Proline). The addition of boscalid to epoxiconazole (Tracker) also improved yield compared with

Opus alone. The protectant fungicide coded HGCA9 gave very small yield increases at all doses.

34

Opus

6

6.5

7

7.5

8

Yie

ld (t

/ha)

Vivid

6

6.5

7

7.5

8

0 0.5 1 1.5 2

Dose

Yie

ld (t

/ha)

Amistar

6

6.5

7

7.5

8Twist

6

6.5

7

7.5

8

Proline

6

6.5

7

7.5

8

0 0.5 1 1.5 2

Dose

Caramba

6

6.5

7

7.5

8

0 0.5 1 1.5 2

Dose

Acanto

6

6.5

7

7.5

8

Flamenco

6

6.5

7

7.5

8

0 0.5 1 1.5 2

Dose

Table 4.6 Parameter estimates for fitted dose response curves for yield, Experiment 1, 2001

Parameter estimates


Mean R2

adjusted

Opus 8.16 -1.33 -0.42 6.83 7.28 68.3

Amistar 9.02 -2.19 -0.32 6.83 7.43 79.2

Twist 7.62 -0.79 -5.82 6.83 7.62 83.9

Acanto 7.56 -0.73 -3.95 6.83 7.55 53.1

Vivid 7.58 -0.75 -6.31 6.83 7.58 77.8

Proline 7.39 -0.56 -3.77 6.83 7.38 99.0

Caramba 7.30 -0.47 -4.71 6.83 7.30 35.5

Flamenco 7.20 -0.37 <-20.00 6.83 7.20 33.3

Figure 4.6 Dose response curves for yield, Experiment 1, 2001

35


Parameter estimates


Mean R2

adjusted

Opus 5.46 -3.97 -0.76 1.49 3.60 93.9

Amistar 3.73 -2.24 -1.32 1.49 3.13 90.9

Caramba 3.57 -2.08 -1.47 1.49 3.09 95.4

Proline 5.57 -4.08 -0.76 1.49 3.65 99.5

Twist 4.09 -2.60 -1.02 1.49 3.16 98.9

Acanto 3.39 -1.90 -1.59 1.49 3.01 99.2

Vivid 5.61 -4.12 -1.95 1.49 5.02 98.7

Fandango 4.59 -3.10 -1.31 1.49 3.76 97.6


Opus

1

2

3

4

5

6

Yie

ld (t

/ha)

Twist

1

2

3

4

5

6

0 0.5 1 1.5 2

Dose

Yie

ld (t

/ha)

Amistar

1

2

3

4

5

6Caramba

1

2

3

4

5

6

Acanto

1

2

3

4

5

6

0 0.5 1 1.5 2

Dose

Vivid

1

2

3

4

5

6

0 0.5 1 1.5 2

Dose

Proline

1

2

3

4

5

6

Fandango

1

2

3

4

5

6

0 0.5 1 1.5 2

Dose

36


Parameter estimates


Mean R2

adjusted

Opus 4.87 -2.46 -1.73 2.41 4.44 97.8

Acanto 4.07 -1.66 -2.34 2.41 3.91 99.6

Vivid 4.91 -2.50 -3.43 2.41 4.84 92.5

Amistar 4.10 -1.69 -2.04 2.41 3.89 96.5

Proline 4.66 -2.25 -2.22 2.41 4.42 94.5

Fandango 4.75 -2.34 -3.08 2.41 4.65 91.3

Swift 4.50 -2.09 -1.80 2.41 4.16 95.8

Swing Gold 4.27 -1.86 -3.44 2.41 4.21 98.0


Amistar

2

3

4

5

Swing Gold

2

3

4

5

0 0.5 1 1.5 2

Dose

Opus

2

3

4

5

Yie

ld (t

/ha)

Proline

2

3

4

5

0 0.5 1 1.5 2

Dose

Yie

ld (t

/ha)

Acanto

2

3

4

5Vivid

2

3

4

5

Fandango

2

3

4

5

0 0.5 1 1.5 2

Dose

Swift

2

3

4

5

0 0.5 1 1.5 2

Dose

37


Parameter estimates


Mean R2

adjusted

Opus 7.4 -2.0 -1.1 5.4 6.7 97.7

Swing Gold 7.7 -2.3 -2.0 5.4 7.4 99.0

Tracker 8.1 -2.7 -2.5 5.4 7.9 92.9

Bravo 7.5 -2.1 -2.1 5.4 7.2 97.3

HGCA9 6.3 -0.9 -0.8 5.4 5.9 45.4

Proline 7.5 -2.0 -1.6 5.4 7.1 98.8

Fandango 7.6 -2.2 -3.7 5.4 7.6 80.8

Charisma 7.0 -1.5 -0.5 5.4 6.0 86.3

Vivid 6.6 -1.2 -3.0 5.4 6.5 87.0

Swift 6.7 -1.3 -1.6 5.4 6.4 85.0


Opus

5

5.5

6

6.5

7

7.5

8

8.5

Yiel

d (T

/ha)

Proline

5

5.5

6

6.5

7

7.5

8

8.5

0 0.5 1 1.5 2

Dose

Yie

ld (T

/ha)

Swing Gold

5

5.5

6

6.5

7

7.5

8

8.5Tracker

5

5.5

6

6.5

7

7.5

8

8.5

Fandango

5

5.5

6

6.5

7

7.5

8

8.5

0 0.5 1 1.5 2

Dose

Charisma

5

5.5

6

6.5

7

7.5

8

8.5

0 0.5 1 1.5 2

Dose

Bravo

5

5.5

6

6.5

7

7.5

8

8.5HGCA9

5

5.5

6

6.5

7

7.5

8

8.5

Vivid

5

5.5

6

6.5

7

7.5

8

8.5

0 0.5 1 1.5 2

Dose

Swift

5

5.5

6

6.5

7

7.5

8

8.5

0 0.5 1 1.5 2

Dose

38

4.1.4 Specific weight

Specific weight of grain was not significantly affected by fungicide treatments at the S. nodorum site in the low

disease year 2001, and for some products it was not possible to fit curves to the data (Table 4.10 and Figure

4.10).

Poor specific weights in untreated plots were increased substantially by fungicide treatments in 2002 as a result

of the control of severe glume blotch (Table 4.11 and Figure 4.11). The effect of different products on specific

weights was in line with their effect on yield.

The shapes of the dose-response curves for specific weights in 2003 (Figure 4.12) were similar to those obtained

for yield. Fandango gave greater specific weights than Proline at quarter dose and half dose, but not at full dose.

Vivid was the most effective strobilurin product at increasing specific weight, equivalent to Opus.

In 2004, the improvement shown by Tracker over straight epoxiconazole in yield was also evident in specific

weights (Table 4.13 and Figure 4.13). Specific weight was not increased by Swift beyond a quarter dose. The

fitted curves for Fandango and Swing Gold were flat beyond a half dose.

39

Table 4.10 Parameter estimates for fitted dose response curves for specific weight, Experiment 1, 2001

Parameter estimates


Mean R2

adjusted

Opus Response curve not fitted

Amistar 66.7 0.6 -20 67.3 66.7 -50.0

Twist Response curve not fitted

Acanto 67.3 0.0 -20 67.3 67.3 -50.0

Vivid 67.1 0.1 -5.76 67.3 67.1 -47.7

Proline 67.7 -0.4 -0.55 67.3 67.4 -31.7

Caramba 67.1 0.2 -20 67.3 67.1 -50.0

Flamenco 67.1 0.1 -2.4 67.3 67.1 -45.8

Figure 4.10 Dose response curves for specific weight, Experiment 1, 2001

.

Opus

65

66

67

68

69

70

Sp W

t (kg

/hl)

Vivid

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Sp W

t (kg

/hl)

Amistar

65

66

67

68

69

70Twist

65

66

67

68

69

70

Proline

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Caramba

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Acanto

65

66

67

68

69

70

Flamenco

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Data not fitted

Data not fitted

40


Parameter estimates


Mean R2

adjusted

Opus 63.7 -14.0 -0.60 49.7 56.0 99.2

Amistar 56.0 -6.3 -2.26 49.7 55.3 93.9

Caramba 64.1 -14.4 -0.36 49.7 54.0 97.0

Proline 63.5 -13.9 -0.71 49.7 56.7 94.1

Twist 61.4 -11.7 -0.74 49.7 55.8 97.3

Acanto 52.3 -4.6 -3.24 49.7 54.1 95.7

Vivid 63.2 -13.6 -2.40 49.7 62.0 95.8

Fandango 61.7 -12.0 -1.04 49.7 57.4 98.5


Opus

45

50

55

60

65

Sp

Wt (

kg/h

l))

Twist

45

50

55

60

65

0 0.5 1 1.5 2

Dose

Sp

Wt (

kg/h

l)

Amistar

45

50

55

60

65Caramba

45

50

55

60

65

Acanto

45

50

55

60

65

0 0.5 1 1.5 2

Dose

Vivid

45

50

55

60

65

0 0.5 1 1.5 2

Dose

Proline

45

50

55

60

65

Fandango

45

50

55

60

65

0 0.5 1 1.5 2

Dose

41


Parameter estimates


Mean R2

adjusted

Opus 70.7 -4.80 -2.59 65.9 70.4 99.5

Acanto 69.5 -3.57 -1.98 65.9 69.0 73.6

Vivid 70.9 -4.95 -3.09 65.9 70.7 97.3

Amistar 69.8 -3.90 -1.73 65.9 69.1 82.6

Proline 71.2 -5.31 -2.24 65.9 70.7 94.2

Fandango 70.5 -4.56 -4.21 65.9 70.4 99.6

Swift 69.9 -4.01 -2.24 65.9 69.5 91.6

Swing Gold 69.7 -3.80 -3.86 65.9 69.7 99.7


Opus

65

66

67

68

69

70

71

72

Sp

Wt (

kg/h

l)

Proline

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Sp

Wt (

kg/h

l)

Acanto

65

66

67

68

69

70

71

72Vivid

65

66

67

68

69

70

71

72

Fandango

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Swift

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Amistar

65

66

67

68

69

70

71

72

Swing Gold

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

42


Parameter estimates


Mean R2

adjusted

Opus 69.0 -6.2 -0.8 62.8 66.1 94.1

Swing Gold 68.0 -5.2 -6.1 62.8 67.9 94.2

Tracker 69.3 -6.6 -3.1 62.8 69.0 96.6

Bravo 67.4 -4.6 -3.2 62.8 67.2 89.8

HGCA9 66.1 -3.4 -1.0 62.8 64.9 48.2

Proline 67.7 -5.0 -2.0 62.8 67.0 98.0

Fandango 68.0 -5.3 -8.7 62.8 68.0 94.6

Charisma 66.5 -3.8 -1.7 62.8 65.8 76.0

Vivid 68.2 -5.5 -1.0 62.8 66.2 89.4

Swift 66.2 -3.4 -16.0 62.8 66.2 88.0


Opus

62

63

64

65

66

67

68

69

70

Sp W

t (kg

/hl)

Proline

62

63

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Sp W

t (kg

/hl)

Swing Gold

62

63

64

65

66

67

68

69

70Tracker

62

63

64

65

66

67

68

69

70

Fandango

62

63

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Charisma

62

63

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Bravo

62

63

64

65

66

67

68

69

70HGCA9

62

63

64

65

66

67

68

69

70

Vivid

62

63

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Swift

62

63

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

43

4.2 Yellow rust experiments

4.2.1 Disease control

With the exception of Experiment 4 in 2001, which was conducted on Equinox, all yellow rust experiments used

the very susceptible variety Brigadier. Occasionally, when weather conditions favoured epidemics of both S.

tritici and yellow rust, the effect of fungicides on yellow rust alone was difficult to assess, particularly late in the

season. Where possible, protectant and eradicant activity of fungicides has been separated.

Parameter estimates for protectant activity of fungicides against yellow rust in 2001 are given in Table 4.14.

and the fitted dose-response curves are shown in Fig. 4.14. Although the levels of yellow rust are low, the

curves suggest that Opus, Proline, Amistar and Acanto all provide very good control of yellow rust, at

quarter/half dose, when applied as protectant sprays.

In 2002, yellow rust data were obtained from two sites, Terrington and Morley. Pooled data from both sites

have been analysed to provide information on protectant and eradicant activity of fungicides. Parameter

estimates and fitted dose-response curves are shown in Table 4.15 and Fig. 4.15 for protectant sprays and in

Table 4.16 and Fig 4.16 for eradicant applications. Individual fungicide products behaved similarly in

protectant and eradicant situations. Opus was very effective, giving good control at a quarter dose. Other azole

products were slightly less effective. Prothioconazole (Proline) was slightly improved by the addition of

fluoxastrobin (Fandango) and Flamenco was the least active of the azoles tested. Vivid was the most active of

the strobilurin products and at half dose gave as good control of yellow rust as full doses of other strobilurins.

Data for protectant and eradicant situations were combined in 2003 and are presented in Table 4.17 and Fig.

4.17. Opus remained slightly more effective than Proline. Vivid appeared to be slightly less effective than in

previous years, but it remained the most effective strobilurin fungicide. Strobilurin/azole mixtures were also

very effective in controlling yellow rust.

Eradicant and protectant data were also combined in 2004 and are shown in Table 4.18 and Fig 4.18. Under

lower disease pressure in 2004, both Opus and Proline were equally effective in protectant situations. Other

strobilurin treatments were similar, although Swift was the least effective. The strobilurin/azole mixture

Charisma was not as effective as the best azoles or strobilurin products alone.

44

Table 4.14 Parameter estimates for fitted dose response curves for yellow rust (protectant), Experiment 2, 2001

Parameter estimates


Mean R2

adjusted

Opus 0.1 5.5 -8.37 5.5 0.1 95.0 Caramba 1.5 4.1 -20 5.5 1.5 -50.0 Amistar 0.3 5.2 -9.3 5.5 0.3 20.3 Vivid 1.6 4.0 -7.52 5.5 1.6 65.5 Proline 0.4 5.2 -20 5.5 0.4 -50.0 Flamenco 1.7 3.9 -20 5.5 1.7 -50.0 Acanto 0.1 5.4 -20 5.5 0.1 -50.0 Twist 0.4 5.1 -5.58 5.5 0.5 -28.3

Figure 4.14 Dose-response curves for yellow rust (protectant), Experiment 2, 2001

Opus

0

2

4

6

8

% Y

ello

w ru

st

Proline

0

2

4

6

8

0 0.5 1 1.5 2

Dose

% Y

ello

w ru

st

Caramba

0

2

4

6

8Amistar

0

2

4

6

8

Flamenco

0

2

4

6

8

0 0.5 1 1.5 2

Dose

Acanto

0

2

4

6

8

0 0.5 1 1.5 2

Dose

Vivid

0

2

4

6

8

Twist

0

2

4

6

8

0 0.5 1 1.5 2

Dose

45

Table 4.15 Parameter estimates for fitted dose-response curves for yellow rust (protectant),

Experiments 8 & 9, 2002

Parameter estimates


Mean R2

adjusted

Opus 2.9 28.0 -20 30.9 2.9 -50.0 Proline 3.2 27.7 -4.79 30.9 3.4 92.0 Fandango 2.7 28.2 -6.64 30.9 2.8 86.3 Flamenco 6.0 24.9 -4.63 30.9 6.3 50.3 Amistar 1.7 29.2 -2.61 30.9 3.9 79.0 Acanto 1.9 29.1 -1.48 30.9 8.5 96.3 Vivid 3.6 27.4 -8.74 30.9 3.6 63.8 Twist 3.9 27.0 -1.77 30.9 8.5 91.7

Figure 4.15 Dose-response curves for yellow rust (protectant), Experiments 8 & 9, 2002

Opus

0

10

20

30

40

% Y

ello

w ru

st

Amistar

0

10

20

30

40

0 0.5 1 1.5 2

Dose

% Y

ello

w ru

st

Proline

0

10

20

30

40Fandango

0

10

20

30

40

Acanto

0

10

20

30

40

0 0.5 1 1.5 2

Dose

Vivid

0

10

20

30

40

0 0.5 1 1.5 2

Dose

Flamenco

0

10

20

30

40

Twist

0

10

20

30

40

0 0.5 1 1.5 2

Dose

46

Table 4.16 Parameter estimates for fitted dose-response curves for yellow rust (eradicant),


Parameter estimates


Mean R2

adjusted

Opus 2.1 22.5 -20 24.5 2.1 -50.0 Proline 2.2 22.4 -5.98 24.5 2.2 77.2 Fandango 1.5 23.0 -8.28 24.5 1.5 83.2 Flamenco 3.7 20.8 -8.26 24.5 3.7 52.8 Amistar 2.6 21.9 -2.31 24.5 4.8 95.2 Acanto 3.3 21.3 -2.65 24.5 4.8 91.7 Vivid 1.7 22.8 -11.25 24.5 1.7 77.7 Twist 3.2 21.3 -2.59 24.5 4.8 64.5

Figure 4.16 Dose-response curves for yellow rust (eradicant), Experiments 8 & 9, 2002

Opus

0

10

20

30

% Y

ello

w ru

st

Amistar

0

10

20

30

0 0.5 1 1.5 2

Dose

% Y

ello

w ru

st

Proline

0

10

20

30Fandango

0

10

20

30

Acanto

0

10

20

30

0 0.5 1 1.5 2

Dose

Vivid

0

10

20

30

0 0.5 1 1.5 2

Dose

Flamenco

0

10

20

30

Twist

0

10

20

30

0 0.5 1 1.5 2

Dose

47

Table 4.17 Parameter estimates for fitted dose-response curves for yellow rust (combined eradicant and

protectant), Experiment 14, 2003

Parameter estimates


Mean R2

adjusted

Opus 0.4 24.5 -20.1 25.0 0.5 -36.7 Proline 1.1 23.9 -7.55 25.0 1.1 54.9 Fandango 0.7 24.3 -7.86 25.0 0.7 46.4 Acanto 1.2 23.8 -3.19 25.0 2.2 79.6 Vivid 1.6 23.4 -6.13 25.0 1.6 36.6 Swift (Twist SC) -0.9 25.9 -0.85 25.0 10.2 97.6 Vivid + Opus 0.2 24.8 -16.82 25.0 0.2 7.3 Swift + Opus 0.2 24.8 -10.88 25.0 0.2 77.5

Figure 4.17 Dose-response curves for yellow rust (combined eradicant and protectant), Experiment 14, 2003

Opus

0

10

20

30

% Y

ello

w ru

st

Vivid

0

10

20

30

0 0.5 1 1.5 2

Dose

% Y

ello

w ru

st

Proline

0

10

20

30Fandango

0

10

20

30

Swift

0

10

20

30

0 0.5 1 1.5 2

Dose

Vivid + Opus

0

10

20

30

0 0.5 1 1.5 2

Dose

Acanto

0

10

20

30

Swift + Opus

0

10

20

30

0 0.5 1 1.5 2

Dose

48

Table 4.18 Parameter estimates for fitted dose response curves for yellow rust (combined eradicant and


Parameter estimates


Mean R2

adjusted

Opus 0.2 19.8 -16.0 19.9 0.2 90.5 Proline 0.1 19.8 -16.0 19.9 0.1 77.5 Fandango 0.2 19.7 -16.0 19.9 0.2 98.9 Tracker 0.2 19.7 -13.8 19.9 0.2 99.6 Amistar 0.5 19.4 -8.4 19.9 0.5 81.9 Vivid 0.7 19.2 -13.4 19.9 0.7 96.6 Swift (Twist SC) 2.4 17.5 -14.1 19.9 2.4 63.6 Charisma 1.4 18.5 -5.1 19.9 1.5 95.6

Figure 4.18 Dose-response curves for yellow rust (combined eradicant and protectant), Experiment 21, 2004

Opus

0

5

10

15

20

% Y

ello

w ru

st

Amistar

0

5

10

15

20

0 0.5 1 1.5 2

Dose

% Y

ello

w ru

st

Proline

0

5

10

15

20Fandango

0

5

10

15

20

Vivid

0

5

10

15

20

0 0.5 1 1.5 2

Dose

Swift

0

5

10

15

20

0 0.5 1 1.5 2

Dose

Tracker

0

5

10

15

20

Charisma

0

5

10

15

20

0 0.5 1 1.5 2

Dose

49


Yellow rust pustules dry out and become difficult to assess as they become older. They also are accompanied

by necrosis of surrounding leaf tissue. Yellow rust assessments carried out later in the season may therefore

underestimate the damage caused by the disease. In such situations, green leaf area assessments can give a good

indication of the leaf’s photosynthetic ability and a better assessment of the efficacy of fungicide treatment.

Parameter estimates and dose-response curves for green leaf area at the yellow rust site in 2001 (Table 4.19 and

Fig. 4.19) are for the flag leaf and therefore reflect the protectant activity of the fungicides. Green leaf area was

relatively high in the untreated plots at the time of assessment, but all fungicides increased green leaf area. Opus

was the most effective azole product. All strobilurin fungicides gave similar increases in green leaf area.

For disease data in 2002, protectant and eradicant activity are shown separately for green leaf area over the two

yellow rust sites (Tables 4.20 and 4.21 and Figs. 4.20 and 4.21). Opus was more effective at increasing green

leaf area than Proline and Flamenco, particularly at lower doses, while Vivid was the most effective strobilurin.

For each product, the shape of its dose-response curve in protectant and eradicant situations, was similar. Most

products were slightly more effective when applied as protectants rather than eradicants, and this was most

noticeable with Amistar.

Fungicides gave large increases in green leaf area in 2003. Opus and azole/strobilurin mixtures were most

effective in maintaining green leaf area, even at low doses. Strobilurin fungicides alone were considerably less

effective, possibly due to the development of S. tritici.

Opus, Proline, Fandango and Tracker all gave large increases in green leaf area, even at a quarter dose in 2004

(Table 4.23 and Fig. 4.23). Strobilurins were also reasonably effective with Amistar and Vivid slightly better

than Swift (a new formulation of trifloxystrobin equivalent to Twist).

50

Table 4.19 Parameter estimates for fitted dose response curves for green leaf area, Experiment 2, 2001

Parameter estimates


Mean R2

adjusted

Opus 98.7 -10.1 -10.9 88.6 98.7 99.4 Caramba 96.7 -8.1 -20 88.6 96.8 82.4 Amistar 98.0 -9.4 -7.9 88.6 98.0 97.2 Vivid 96.9 -8.3 -7.65 88.6 97.0 95.9 Proline 97.6 -9.0 -20 88.6 97.6 98.9 Flamenco 96.3 -7.7 -20 88.6 96.3 82.0 Acanto 98.0 -9.4 -20 88.6 98.0 99.4 Twist 97.9 -9.3 -8.1 88.6 98.0 92.4

Figure 4.19 Dose-response curves for green leaf area, Experiment 2, 2001

Opus

85

90

95

100

% G

reen

leaf

are

a

Proline

85

90

95

100

0 0.5 1 1.5 2

Dose

% G

reen

leaf

are

a

Caramba

85

90

95

100Amistar

85

90

95

100

Flamenco

85

90

95

100

0 0.5 1 1.5 2

Dose

Acanto

85

90

95

100

0 0.5 1 1.5 2

Dose

Vivid

85

90

95

100

Twist

85

90

95

100

0 0.5 1 1.5 2

Dose

51

Table 4.20 Parameter estimates for fitted dose-response curves for green leaf area (protectant),


Parameter estimates


Mean R2

adjusted

Opus 95.3 -28.0 -20 67.4 95.3 82.9 Proline 95.7 -28.3 -3.45 67.4 94.8 98.5 Fandango 95.8 -28.4 -5.52 67.4 95.7 98.8 Flamenco 95.1 -27.7 -3.83 67.4 90.6 81.2 Amistar 97.5 -30.1 -2.25 67.4 94.3 86.1 Acanto 97.8 -30.4 -1.17 67.4 88.3 96.7 Vivid 94.7 -27.3 -9.35 67.4 94.7 95.4 Twist 95.2 -27.8 -1.55 67.4 89.3 94.8

Figure 4.20 Dose-response curves for green leaf area (protectant), Experiments 8 & 9, 2002

Opus

50

60

70

80

90

100

% G

reen

leaf

are

a

Amistar

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

% G

reen

leaf

are

a

Proline

50

60

70

80

90

100Fandango

50

60

70

80

90

100

Acanto

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Vivid

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Flamenco

50

60

70

80

90

100

Twist

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

52

Table 4.21 Parameter estimates for fitted dose-response curves for green leaf area (eradicant),


Parameter estimates


Mean R2

adjusted

Opus 93.1 -39.6 -20 53.5 93.1 98.6 Proline 93.1 -39.6 -4.92 53.5 83.4 95.3 Fandango 93.3 -39.7 -8.13 53.5 61.2 95.2 Flamenco 89.6 -36.1 -7.78 53.5 65.2 96.7 Amistar 91.5 -38.0 -2.91 53.5 87.7 94.8 Acanto 90.7 -37.1 -3.19 53.5 86.3 94.6 Vivid 93.7 -40.2 -12.73 53.5 75.7 99.4 Twist 91.9 -38.4 -3.5 53.5 53.9 81.1

Figure 4.21 Dose-response curves for green leaf area (eradicant), Experiments 8 & 9, 2002

Opus

50

60

70

80

90

100

% G

reen

leaf

are

a

Amistar

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

% G

reen

leaf

are

a

Proline

50

60

70

80

90

100Fandango

50

60

70

80

90

100

Acanto

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Vivid

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Flamenco

50

60

70

80

90

100

Twist

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

53

Table 4.22 Parameter estimates for fitted dose-response curves for green leaf area (combined eradicant and


Parameter estimates


Mean R2

adjusted

Opus 95.7 -48.9 -12.44 46.8 95.7 91.1 Proline 94.1 -47.3 -3.95 46.8 93.1 99.9 Fandango 93.2 -46.5 -12.79 46.8 93.2 73.1 Acanto 91.1 -44.3 -2.39 46.8 87.0 71.3 Vivid 86.0 -39.2 -4.89 46.8 85.7 82.2 Swift (Twist SC) 35.8 11.0 0.75 46.8 59.0 94.1 Vivid + Opus 96.1 -49.3 -13.15 46.8 96.1 95.7 Swift + Opus 96.7 -50.0 -7.28 46.8 96.7 92.5

Table 4.22 Dose-response curves for green leaf area (combined eradicant and protectant), Experiment 14, 2003

Opus

40

50

60

70

80

90

100

% G

reen

leaf

are

a

Vivid

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

% G

reen

leaf

are

a

Proline

40

50

60

70

80

90

100Fandango

40

50

60

70

80

90

100

Swift

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Vivid + Opus

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Acanto

40

50

60

70

80

90

100

Swift + Opus

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

54

Table 4.23 Parameter estimates for fitted dose-response curves for green leaf area (combined eradicant and


Parameter estimates


Mean R2

adjusted

Opus 98.2 -32.1 -13.0 66.1 98.2 88.4 Proline 99.1 -32.9 -16.0 66.1 99.1 93.9 Fandango 98.8 -32.7 -15.3 66.1 98.8 100.0 Tracker 98.4 -32.3 -10.8 66.1 98.4 99.8 Amistar 95.7 -29.6 -6.4 66.1 95.6 94.8 Vivid 95.2 -29.0 -9.4 66.1 95.2 98.9 Swift (Twist SC) 90.8 -24.7 -16.0 66.1 90.8 85.8 Charisma 95.3 -29.2 -3.9 66.1 94.7 98.5

Figure 4.23 Dose-response curves for green leaf area (combined eradicant and protectant), Experiment 21,

2004

Opus

60

70

80

90

100

% G

reen

leaf

are

a

Amistar

60

70

80

90

100

0 0.5 1 1.5 2

Dose

% G

reen

leaf

are

a

Proline

60

70

80

90

100Fandango

60

70

80

90

100

Vivid

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Swift

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Tracker

60

70

80

90

100

Charisma

60

70

80

90

100

0 0.5 1 1.5 2

Dose

55

4.2.3 Grain yield

The yield data at Terrington in 2001 (Table 4.24 and Fig. 4.24) are difficult to reconcile with the yellow rust

activity of treatments. Most products increased yield by about 1.0 t/ha at quarter or half dose, and beyond that

point, the fitted dose-response curve was flat. Exceptions were Caramba and Twist, which, although not giving

the best yellow rust control, continued to increase yield at higher doses.

Mean yield data over two sites (Terrington and Morley) are presented in Table 4.25 and Fig. 4.25. At each

dose, Opus gave a greater yield increase than any other product. The benefit from the addition of fluoxastrobin

to prothioconazole in Fandango, compared with Proline, which was evident in the rust assessments, was also

reflected in improved yield.

The performance of Proline relative to Opus improved in 2003, although it was still less effective at quarter dose

(Table 4.26 and Fig. 4.26). The new formulation of trifloxystrobin (Swift), used for the first time in 2003,

appeared to be less effective than the original formulation (Twist). However, mixtures of both Swift plus Opus

and Vivid plus Opus gave good yield increases.

In 2004, the experiment at Terrington (Experiment 21) was severely affected by S. tritici in addition to yellow

rust and the yield data therefore reflect the level of control of both diseases. The relatively poor performance of

Amistar, Swift and Vivid may be explained by poor control of strobilurin-resistant S. tritici (Table 4.27 and Fig.

4.27). Proline, Tracker and Fandango gave yield responses similar to Opus. Proline gave poorer control of

yellow rust than Opus but had similar yield.

Mean yield data across all yellow rust sites between 2001 and 2003 are presented in Table 4.28 and Fig. 4.28.

Data for 2004 have not been included because of the overriding effect of S. tritici in that year. Of the azole

fungicides, Opus gave the overall greatest yield increases. All strobilurin products, with the exception of Vivid,

gave yield increases up to double dose; the dose response curve for Vivid flattened out at half dose. The new

formulation of trifloxystrobin did not appear to offer any yield advantage over the original formulation. The

greatest mean yield increases over the yellow rust sites were given by the azole/strobilurin mixtures, Vivid +

Opus, Swift + Opus and Fandango.

56

Table 4.24 Parameter estimates for fitted dose response curves for grain yield, Experiment 2, 2001

Parameter estimates


Mean R2

adjusted

Opus 8.1 -1.23 -11.59 6.9 8.1 79.6 Caramba 8.7 -1.85 -1.87 6.9 8.5 95.1 Amistar 7.9 -1.03 -8.66 6.9 7.9 60.4 Vivid 8.2 -1.32 -20.00 6.9 8.2 54.7 Proline 8.1 -1.22 -10.90 6.9 8.1 70.8 Flamenco 8.3 -1.38 -3.39 6.9 8.2 72.9 Acanto 8.0 -1.12 -6.96 6.9 8.0 91.6 Twist 8.7 -1.78 -3.09 6.9 8.6 75.1

Figure 4.24 Dose-response curves for yield, Experiment 2, 2001

Opus

6

7

8

9

Yie

ld (t

/ha)

Proline

6

7

8

9

0 0.5 1 1.5 2

Dose

Yiel

d (t/

ha)

Caramba

6

7

8

9Amistar

6

7

8

9

Flamenco

6

7

8

9

0 0.5 1 1.5 2

Dose

Acanto

6

7

8

9

0 0.5 1 1.5 2

Dose

Vivid

6

7

8

9

Twist

6

7

8

9

0 0.5 1 1.5 2

Dose

57

Table 4.25 Parameter estimates for fitted dose-response curves for yield., Experiments 8 & 9, 2002.

Parameter estimates


Mean R2

adjusted

Opus 7.1 -3.2 -3.26 4.0 7.0 93.7 Proline 6.0 -2.0 -2.8 4.0 5.9 98.1 Fandango 6.9 -3.0 -2.36 4.0 6.6 97.1 Flamenco 6.2 -2.2 -1.9 4.0 5.8 95.1 Amistar 7.7 -3.8 -0.98 4.0 6.3 98.0 Acanto 16.5 -12.6 -0.12 4.0 5.3 97.1 Vivid 6.6 -2.6 -3.13 4.0 6.5 94.0 Twist 7.1 -3.1 -0.89 4.0 5.8 92.2

Figure 4.25 Dose-response curves for yield, Experiments 8 & 9, 2002

Opus

4

5

6

7

8

Yie

ld (t

/ha)

Amistar

4

5

6

7

8

0 0.5 1 1.5 2

Dose

Yiel

d (t/

ha)

Proline

4

5

6

7

8Fandango

4

5

6

7

8

Acanto

4

5

6

7

8

0 0.5 1 1.5 2

Dose

Vivid

4

5

6

7

8

0 0.5 1 1.5 2

Dose

Flamenco

4

5

6

7

8

Twist

4

5

6

7

8

0 0.5 1 1.5 2

Dose

58

Table 4.26 Parameter estimates for fitted dose-response curves for yield, Experiment 14, 2003

Parameter estimates


Mean R2

adjusted

Opus 8.9 -2.5 -13.14 6.4 8.9 88.9 Proline 8.8 -2.4 -4.51 6.4 8.8 98.9 Fandango 9.1 -2.7 -6.43 6.4 9.1 93.2 Acanto 8.6 -2.2 -2.66 6.4 8.4 92.4 Vivid 8.4 -2.0 -4.24 6.4 8.4 94.9 Swift (Twist SC) 8.1 -1.7 -1.51 6.4 7.7 90.2 Vivid + Opus 9.4 -3.0 -9.16 6.4 9.4 98.1 Swift + Opus 9.3 -2.9 -5.41 6.4 9.3 99.4


Opus

6

7

8

9

10

Yie

ld (t

/ha)

Vivid

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Yiel

d (t/

ha)

Proline

6

7

8

9

10Fandango

6

7

8

9

10

Swift (Twist SC)

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Vivid + Opus

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Acanto

6

7

8

9

10

Swift + Opus

6

7

8

9

10

0 0.5 1 1.5 2

Dose

59

Table 4.27 Parameter estimates for fitted dose-response curves for yield, Experiment 21, 2004

Parameter estimates


Mean R2

adjusted

Opus 9.0 -4.0 -5.0 5.0 9.0 93.5

Proline 8.7 -3.7 -6.5 5.0 8.7 99.2

Fandango 9.2 -4.2 -5.3 5.0 9.2 97.8

Tracker 9.2 -4.2 -4.1 5.0 9.2 99.7

Amistar 7.3 -2.3 -3.9 5.0 7.3 97.4

Vivid 7.2 -2.2 -4.3 5.0 7.2 97.3

Swift 6.5 -1.4 -10.6 5.0 6.5 93.5

Charisma 7.4 -2.3 -2.0 5.0 7.1 100.0


Opus

5

6

7

8

9

10

Yiel

d t/h

a

Amistar

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Proline

5

6

7

8

9

10Fandango

5

6

7

8

9

10

Vivid

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Swift

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Tracker

5

6

7

8

9

10

Charisma

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

60

Table 4.28 Parameter estimates for fitted dose-response curves for yield, mean data for all yellow rust sites

2001-2003 (Experiment s 2, 8, 9 & 14)

Parameter estimates


Mean R2

adjusted

Opus 7.75 -2.45 -5.02 5.3 7.73 96.2 Caramba 7.53 -2.23 -2.87 5.3 7.40 95.9 Flamenco 7.26 -1.96 -2.42 5.3 7.09 95.1 Proline 7.20 -1.90 -4.01 5.3 7.16 99.5 Fandango 7.95 -2.65 -3.03 5.3 7.83 96.8 Acanto 7.50 -2.20 -1.30 5.3 6.90 97.9 Amistar 7.99 -2.69 -1.46 5.3 7.37 96.3 Vivid 7.30 -2.00 -5.74 5.3 7.30 95.7 Twist 7.90 -2.60 -1.34 5.3 7.22 92.1 Swift (Twist SC) 6.91 -1.61 -1.05 5.3 6.35 89.0 Vivid + Opus 8.05 -2.75 -8.71 5.3 8.05 98.5 Swift + Opus 7.92 -2.62 -5.07 5.3 7.91 99.5

61

Figure 4.28 Dose-response curves for yield – mean of all yellow rust sites 2001-2003

(Experiments 2, 8, 9 & 14 )

Opus

5

6

7

8

9

10

Yiel

d (t/

ha)

Amistar

5

6

7

8

9

10

0 0.5 1 1.5 2

Yiel

d (t/

ha)

Caramba

5

6

7

8

9

10Flamenco

5

6

7

8

9

10

Acanto

5

6

7

8

9

10

0 0.5 1 1.5 2

Vivid

5

6

7

8

9

10

0 0.5 1 1.5 2

Fandango

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Yiel

d (t/

ha)

Vivid+Opus

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Swift+Opus

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Swift

5

6

7

8

9

10

0 0.5 1 1.5 2

Dose

Proline

5

6

7

8

9

10

Twist

5

6

7

8

9

10

0 0.5 1 1.5 2

62

4.2.4 Specific weights

Some of the specific weight data for Terrington in 2001 were variable and in particular, the fitted curves for

Caramba and Flamenco were not good fits with the observed data (Table 4.29 and Fig. 4.29). Specific weight

curves for other products were generally better fits and are similar in shape to the yield curves. Most products

did not increase specific weight beyond full dose, but Twist was an exception giving an additional 1.0 kg/hl at

double dose.

In 2002, the specific weight dose-response curves fitted the observed mean data for Terrington and Morley well

(Table 4.30 and Fig. 4.30). Specific weight was not increased above full dose for azole products, but

strobilurins gave increases in specific weight up to double dose, much in line with the yield data.

The shapes of the fitted dose-response curves for specific weights at Terrington in 2003 (Table 4.31 and Fig.

4.31) correlated well with the yield curves. The poorer performance of Proline compared with Opus at quarter

doses was also evident. Swift was slightly less effective in increasing specific weight than other strobilurin

fungicides at the 2003 site.

In 2004, however, Swift gave considerably greater specific weights than other strobilurins, corresponding to its

yield advantage at this site where S. tritici was also a factor. (Table 4.32 and Fig. 4.32). Opus was again

superior to Proline (and Fandango). Tracker and Charisma gave the greatest increases in specific weights

63


Parameter estimates


Mean R2

adjusted

Opus 70.9 -2.30 -5.60 68.6 70.89 81.0 Caramba 71.3 -2.69 -7.20 68.6 71.28 71.3 Amistar 71.6 -3.03 -5.16 68.6 71.61 95.5 Vivid 71.7 -3.11 -6.64 68.6 71.70 90.9 Proline 71.3 -2.70 -8.13 68.6 71.29 90.5 Flamenco 70.7 -2.12 -20.00 68.6 70.71 19.6 Acanto 71.3 -2.66 -5.56 68.6 71.25 91.4 Twist 72.3 -3.67 -1.73 68.6 71.62 84.2


Opus

68

69

70

71

72

73

Sp W

t (kg

/hl)

Proline

68

69

70

71

72

73

0 0.5 1 1.5 2

Dose

Sp

Wt (

kg/h

l)

Caramba

68

69

70

71

72

73Amistar

68

69

70

71

72

73

Flamenco

68

69

70

71

72

73

0 0.5 1 1.5 2

Dose

Acanto

68

69

70

71

72

73

0 0.5 1 1.5 2

Dose

Vivid

68

69

70

71

72

73

Twist

68

69

70

71

72

73

0 0.5 1 1.5 2

Dose

64

Table 4.30 Parameter estimates for fitted dose-response curves for specific weight, Experiments 8 & 9, 2002.

Parameter estimates


Mean R2

adjusted

Opus 66.1 -5.4 -2.68 60.7 65.7 99.5 Proline 64.7 -4.0 -3.74 60.7 64.6 95.5 Fandango 66.2 -5.5 -2.45 60.7 65.7 91.5 Flamenco 64.0 -3.3 -4.6 60.7 63.9 82.1 Amistar 69.6 -8.9 -0.66 60.7 65.0 98.2 Acanto 69.0 -8.4 -0.41 60.7 63.5 98.4 Vivid 65.6 -4.9 -1.72 60.7 64.7 98.9 Twist 69.7 -9.0 -0.46 60.7 64.0 99.3

Figure 4.30 Dose-response curves for specific weight, Experiments 8 & 9, 2002

Opus

60

61

62

63

64

65

66

67

68

Sp W

t (kg

/hl)

Amistar

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

Sp

Wt (

kg/h

l)

Proline

60

61

62

63

64

65

66

67

68Fandango

60

61

62

63

64

65

66

67

68

Acanto

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

Vivid

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

Flamenco

60

61

62

63

64

65

66

67

68

Twist

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

65

Table 4.31 Parameter estimates for fitted dose-response curves for specific weight, Experiment 14, 2003

Parameter estimates


Mean R2

adjusted

Opus 66.6 -5.38 -9.96 61.2 66.6 96.9 Proline 66.1 -4.87 -3.4 61.2 65.9 77.9 Fandango 65.6 -4.43 -19.88 61.2 65.6 61.9 Acanto 65.1 -3.89 -2.73 61.2 64.8 67.8 Vivid 65.6 -4.42 -2.83 61.2 65.5 62.1 Swift (Twist SC) 65.0 -3.76 -2.24 61.2 64.6 95.4 Vivid + Opus 67.0 -5.77 -20 61.2 67.0 98.4 Swift + Opus 66.9 -5.66 -5.26 61.2 66.8 96.1

Figure 4.31 Dose-response curves for specific weight, Experiment 14, 2003

Opus

60

61

62

63

64

65

66

67

68

Sp W

t (kg

/hl)

Vivid

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

Sp

Wt (

kg/h

l)

Proline

60

61

62

63

64

65

66

67

68Fandango

60

61

62

63

64

65

66

67

68

Swift (Twist SC)

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

Vivid + Opus

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

Acanto

60

61

62

63

64

65

66

67

68

Swift + Opus

60

61

62

63

64

65

66

67

68

0 0.5 1 1.5 2

Dose

66

Table 4.32 Parameter estimates for fitted dose-response curves for specific weight, Experiment 21, 2004

Parameter estimates


Mean R2

adjusted

Opus 74.1 -8.0 -9.7 66.1 74.1 94.5 Proline 71.8 -5.7 -3.2 66.1 71.6 65.4 Fandango 69.8 -3.7 -1.8 66.1 69.2 54.0 Tracker 75.7 -9.6 -3.4 66.1 75.4 97.0 Amistar 70.2 -4.1 -16.0 66.1 70.2 72.8 Vivid 68.5 -2.4 -6.2 66.1 68.5 78.6 Swift (Twist SC) 73.5 -7.3 -6.2 66.1 73.4 98.4 Charisma 75.0 -8.9 -7.1 66.1 75.0 99.5


Opus

666768697071727374757677

Sp W

t (kg

/hl)

Amistar

666768697071727374757677

0 0.5 1 1.5 2

Dose

Sp

Wt (

kg/h

l)

Proline

666768697071727374757677

Fandango

666768697071727374757677

Vivid

666768697071727374757677

0 0.5 1 1.5 2

Dose

Swift (Twist SC)

666768697071727374757677

0 0.5 1 1.5 2

Dose

Tracker

666768697071727374757677

Charisma

666768697071727374757677

0 0.5 1 1.5 2

Dose

67

4.3 Septoria tritici experiments

4.3.1 Disease control

There were a larger number of sites targeting S. tritici than any other disease, and it is therefore possible to

present cross-site mean data for some years. By assessing each leaf layer separately, it is also possible to show

data for the protectant and eradicant activity of fungicides.

The cross-site analysis for 2001 (Suffolk, Norfolk and Fife) showed that Opus was equally effective as a

protectant or eradicant treatment (Tables 4.33 and 4.34 and Figures 4.33 and 4.34). Proline and Flamenco were

more effective as protectants, while Caramba gave better control of S. tritici when applied as an eradicant, at

least at higher doses. Most of the strobilurin fungicides (Amistar, Acanto and Twist) were more effective when

applied as protectants. Vivid was equally effective applied as a protectant or eradicant.

There was only one S. tritici site in 2002 (Fife). All fungicides applied as protectant sprays gave good control of

relatively low levels of disease. Proline, Twist and Vivid gave almost complete control at a quarter dose (Table

4.35 and Figure 4.35). Levels of S. tritici were greater on lower leaves but most fungicides applied as eradicant

sprays continued to give good control at half or full dose. Amistar was the weakest product (Table 4.36 and

Figure 4.36).

The first indication of poor control of S. tritici by strobilurin fungicides was seen in 2003. Mean data from three

sites in eastern England, Scotland and Ireland, showed that Acanto, Swift and Vivid were less effective

protectant sprays than in previous years (Table 4.37 and Figure 4.37). When applied as eradicant sprays, these

strobilurins gave very poor control of S. tritici (Table 4.38 and Figure 4.38). Mixture of strobilurins with azoles

(Fandango, Swift + Opus and Vivid + Opus) gave better disease control.

By 2004, Vivid and Swift were giving very little control of S. tritici at a quarter dose, and increasing dose, even

to double the label dose had no effect (Tables 4.39 and 4.40 and Figures 4.39 and 4.40). The lack of dose

response beyond a quarter dose by the strobilurins was also seen when Swift and Vivid were applied in mixtures

with half dose Opus. The level of control from the mixture was just slightly better than the equivalent control

given by half dose Opus alone. There was also an indication that azoles such as Opus, were becoming less

effective against S. tritici.

68

Table 4.33 Parameter estimates for fitted dose response curves for S. tritici (protectant)

Experiments 3, 4 & 5, 2001

Parameter estimates


Mean R2

adjusted

Opus 5.9 20.3 -3.53 26.2 6.5 95.2 Proline 4.4 21.8 -2.05 26.2 7.2 98.6 Caramba 11.0 15.3 -7.2 26.2 11.0 89.7 Flamenco 8.5 17.7 -2.96 26.2 9.5 86.0 Amistar 7.7 18.5 -3.42 26.2 8.3 99.5 Acanto 5.3 20.9 -4.06 26.2 5.7 80.0 Vivid 7.4 18.9 -6.49 26.2 7.4 96.9 Twist 4.2 22.0 -11.29 26.2 4.2 99.7

Figure 4.33 Dose-response curves for S. tritici (protectant), Experiments 3, 4 & 5, 2001

Opus

0

5

10

15

20

25

30

% S

. tri

tici

Amistar

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

5

10

15

20

25

30Caramba

0

5

10

15

20

25

30

Acanto

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

Vivid

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

Flamenco

0

5

10

15

20

25

30

Twist

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

69

Table 4.34 Parameter estimates for fitted dose response curves for S. tritici (eradicant)

Experiments 3, 4 & 5, 2001

Parameter estimates


Mean R2

adjusted

Opus 4.5 25.4 -3.22 29.9 5.5 96.6 Proline 7.9 22.0 -2.56 29.9 9.6 98.8 Caramba 7.8 22.1 -3.46 29.9 8.5 87.9 Flamenco 10.3 19.7 -3.4 29.9 10.9 97.6 Amistar 15.9 14.0 -6.36 29.9 16.0 97.1 Acanto 10.2 19.7 -4.34 29.9 10.4 95.4 Vivid 5.4 24.5 -6.47 29.9 5.5 96.9 Twist 9.8 20.2 -20 29.9 9.8 97.7

Figure 4.34 Dose-response curves for S. tritici (eradicant), Experiments 3, 4 & 5, 2001

Opus

0

5

10

15

20

25

30

% S

. tri

tici

Amistar

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

5

10

15

20

25

30Caramba

0

5

10

15

20

25

30

Acanto

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

Vivid

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

Flamenco

0

5

10

15

20

25

30

Twist

0

5

10

15

20

25

30

0 0.5 1 1.5 2

Dose

70


Experiment 11, 2002

Parameter estimates


Mean R2

adjusted

Opus 0.7 14.0 -4.33 14.8 0.9 78.6 Proline 0.6 14.2 -12.09 14.8 0.6 67.5 Fandango 0.4 14.3 -7.15 14.8 0.5 72.4 Flamenco 1.0 13.8 -6.25 14.8 1.1 95.1 Amistar 0.8 14.0 -1.6 14.8 3.6 98.1 Acanto 0.9 13.8 -3.34 14.8 1.4 93.0 Vivid 0.3 14.5 -15.45 14.8 0.3 80.9 Twist 0.1 14.7 -9.42 14.8 0.1 99.4

Figure 4.35 Dose-response curves for S. tritici (protectant), Experiment 11, 2002

Opus

0

5

10

15

20

% S

. tri

tici

Amistar

0

5

10

15

20

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

5

10

15

20Fandango

0

5

10

15

20

Acanto

0

5

10

15

20

0 0.5 1 1.5 2

Dose

Vivid

0

5

10

15

20

0 0.5 1 1.5 2

Dose

Flamenco

0

5

10

15

20

Twist

0

5

10

15

20

0 0.5 1 1.5 2

Dose

71


Experiment 11, 2002

Parameter estimates


Mean R2

adjusted

Opus 3.3 42.6 -5.86 45.9 3.5 81.9 Proline 5.8 40.1 -7.03 45.9 5.9 95.5 Fandango 4.3 41.7 -5.00 45.9 4.6 99.2 Flamenco 3.9 42.0 -6.28 45.9 4.0 70.7 Amistar 12.2 33.8 -2.65 45.9 14.6 93.5 Acanto 7.5 38.4 -5.27 45.9 7.7 84.6 Vivid 3.0 42.9 -9.79 45.9 3.0 88.1 Twist 3.8 42.1 -7.23 45.9 3.9 82.0

Figure 4.36 Dose-response curves for S. tritici (eradicant), Experiment 11, 2002

Opus

0

10

20

30

40

50

% S

. tri

tici

Amistar

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

10

20

30

40

50Fandango

0

10

20

30

40

50

Acanto

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Vivid

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Flamenco

0

10

20

30

40

50

Twist

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

72


Experiments 15, 17 & 19, 2003

Parameter estimates


Mean R2

adjusted

Opus 9.5 23.4 -2.12 32.9 12.3 93.9 Proline 4.7 28.2 -3.27 32.9 5.8 93.7 Vivid 14.4 18.5 -4.8 32.9 14.6 23.6 Vivid + Opus 5.7 27.2 -4.0 32.9 6.2 93.8 Acanto 19.8 13.1 -6.98 32.9 19.8 7.8 Fandango 5.0 27.9 -3.3 32.9 6.1 92.9 Swift 11.4 21.5 -6.0 32.9 11.5 75.6 Swift + Opus 4.6 28.3 -4.8 32.9 4.9 84.2


Opus

0

10

20

30

40

50

% S

. tri

tici

Acanto

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

10

20

30

40

50Vivid

0

10

20

30

40

50

Fandango

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Swift

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Vivid + Opus

0

10

20

30

40

50

Swift + Opus

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

73


Experiments 15, 17 & 19, 2003

Parameter estimates


Mean R2

adjusted

Opus 8.4 56.7 -2.11 65.2 15.3 91.2 Proline 8.1 57.1 -2.85 65.2 11.4 79.5 Vivid 28.6 36.6 -2.36 65.2 32.1 77.9 Vivid + Opus 4.4 60.8 -3.91 65.2 5.6 97.0 Acanto 45.8 19.4 -2.22 65.2 47.9 74.9 Fandango 12.0 53.2 -3.42 65.2 13.7 87.4 Swift 19.9 45.3 -0.92 65.2 38.0 91.7 Swift + Opus 5.9 59.2 -4.43 65.2 6.6 81.2


Opus

0

10

20

30

40

50

60

70

% S

. tri

tici

Acanto

0

10

20

30

40

50

60

70

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

10

20

30

40

50

60

70Vivid

0

10

20

30

40

50

60

70

Fandango

0

10

20

30

40

50

60

70

0 0.5 1 1.5 2

Dose

Swift

0

10

20

30

40

50

60

70

0 0.5 1 1.5 2

Dose

Vivid + Opus

0

10

20

30

40

50

60

70

Swift + Opus

0

10

20

30

40

50

60

70

0 0.5 1 1.5 2

Dose

74


Experiments 22, 24 & 26, 2004

Parameter estimates


Mean R2

adjusted

Opus 3.0 21.0 -5.2 23.9 3.1 93.0 Proline 2.1 21.9 -4.8 23.9 2.2 98.6 Vivid 18.1 5.9 -1.6 23.9 19.2 29.6 Vivid + Opus 4.0 19.9 -14.7 23.9 4.0 97.2 Charisma 4.7 19.3 -1.4 23.9 9.5 80.3 Bravo 5.9 18.1 -1.9 23.9 8.5 89.5 Fandango 2.3 21.6 -5.4 23.9 2.4 94.1 Swift 19.8 4.2 -11.2 23.9 19.8 45.8 Swift + Opus 4.8 19.1 -16.0 23.9 4.8 96.7 Tracker 3.4 20.5 -4.5 23.9 3.7 98.7


Opus

0

10

20

30

40

50

% S

. tri

tici

Bravo

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

10

20

30

40

50Vivid

0

10

20

30

40

50

Fandango

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Swift

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Vivid + Opus

0

10

20

30

40

50Charisma

0

10

20

30

40

50

Swift + Opus

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Tracker

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

75


Experiments 22, 24 & 26, 2003

Parameter estimates


Mean R2

adjusted

Opus 8.9 33.2 -2.0 42.1 13.5 96.5 Proline 11.5 30.6 -2.5 42.1 14.0 94.6 Vivid 33.3 8.8 -16.0 42.1 33.3 61.9 Vivid + Opus 15.2 26.9 -16.0 42.1 15.2 95.1 Charisma 15.5 26.6 -1.0 42.1 25.0 92.0 Bravo 23.5 18.7 -3.8 42.1 23.9 93.5 Fandango 9.6 32.5 -2.2 42.1 13.3 99.9 Swift 34.0 8.2 -16.0 42.1 34.0 85.7 Swift + Opus 15.5 26.7 -7.9 42.1 15.5 97.3 Tracker 14.3 27.8 -2.5 42.1 16.6 99.3


Opus

0

10

20

30

40

50

% S

. tri

tici

Bravo

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

% S

. tri

tici

Proline

0

10

20

30

40

50Vivid

0

10

20

30

40

50

Fandango

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Swift

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Vivid + Opus

0

10

20

30

40

50Charisma

0

10

20

30

40

50

Swift + Opus

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

Tracker

0

10

20

30

40

50

0 0.5 1 1.5 2

Dose

76

The contrast in activity of the strobilurin fungicides during the period of the experiments, due to the appearance

of fungicide-resistant strains in the population, is striking. This is illustrated in figures 4.40 and 4.41 which

clearly show the loss of protectant and eradicant activity of Vivid (pyraclostrobin) over the period 2002-2004.

These data clearly show the rapid decline in performance of the strobilurin fungicides against S. tritici during

this period.

2002 2003 2004

Figure 4.41 Dose-response curves for S. tritici (protectant) over period 2002-2004

2002 2003 2004

Figure 4.42 Dose-response curves for S. tritici (eradicant) over period 2002-2004

77


Table 4.41 Parameter estimates for fitted dose response curves for green leaf area Experiment 22, 2004

Parameter estimates


Mean R2

adjusted

Opus 71.0 -61.5 -1.3 9.6 53.6 99.3 Bravo 18.2 -8.6 -16.0 9.6 18.2 94.8 Vivid 21.9 -12.3 -16.0 9.6 21.9 86.9 Swift 72.2 -62.6 -1.1 9.6 51.5 96.1 Vivid+Opus 86.0 -76.4 -0.7 9.6 46.7 91.6 Swift+Opus 14.5 -4.9 -16.0 9.6 14.5 51.2 Charisma 44.8 -35.2 -16.0 9.6 44.8 94.8 Proline 34.1 -24.5 -16.0 9.6 34.1 84.7 Fandango 56.8 -47.2 -0.5 9.6 27.9 98.7 Tracker 51.2 -41.6 -1.9 9.6 45.2 93.4 HGCA9 14.2 -4.7 -16.0 9.6 14.2 84.6

Figure 4.43 Dose-response curves for green leaf area, experiment 22, 2004

Opus

0

10

20

30

40

50

60

70

80

90

GLA

(%)

Bravo

0

10

20

30

40

50

60

70

80

90Vivid

0

10

20

30

40

50

60

70

80

90

Vivid+Opus

0

10

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2

Dose

GLA

(%)

Swift+Opus

0

10

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2

Dose

Charisma

0

10

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2

Dose

Tracker

0

10

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2

Dose

GLA

(%)

Fandango

0

10

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2

Dose

Proline

0

10

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2

Dose

Swift

0

10

20

30

40

50

60

70

80

90

HGCA9

0

10

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2

Dose

78

Table 4.42 Parameter estimates for fitted dose response curves for green leaf area Experiment 24, 2004

Parameter estimates


Mean R2

adjusted


Figure 4.44 Dose-response curves for green leaf area, experiment 24, 2004

Opus

40

50

60

70

80

90

100

GLA

(%)

Bravo

40

50

60

70

80

90

100Vivid

40

50

60

70

80

90

100

Vivid+Opus

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

GLA

(%)

Swift+Opus

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Charisma

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Tracker

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

GLA

(%)

Fandango

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Proline

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Swift

40

50

60

70

80

90

100

HGCA9

40

50

60

70

80

90

100

0 0.5 1 1.5 2

Dose

79

4.3.3 Specific weight


Parameter estimates


Mean R2

adjusted

Opus 70.1 -1.1 -1.58 69.0 69.9 4.8

Amistar 70.2 -1.1 -1.68 69.0 70.0 36.37

Twist 70.3 -1.3 -20.00 69.0 70.3 48.85

Acanto 70.5 -1.4 -3.38 69.0 70.4 58.98

Vivid 72.5 -3.4 -0.45 69.0 70.3 92.23

Proline 71.8 -2.8 -0.62 69.0 70.3 97.04

Caramba 69.6 -0.5 -20.00 69.0 69.6 19.05

Flamenco 69.9 -0.9 -10.10 69.0 69.9 51.54


Opus

68

69

70

71

72

Sp. W

t (kg

/hl)

Vivid

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Sp. W

t (kg

/hl)

Amistar

68

69

70

71

72

Twist

68

69

70

71

72

Proline

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Caramba

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Acanto

68

69

70

71

72

Flamenco

68

69

70

71

72

0 0.5 1 1.5 2

Dose

80


Parameter estimates


Mean R2

adjusted

Opus 73.2 -0.5 -4.46 72.7 73.2 -0.6

Amistar 73.0 -0.3 -20.00 72.7 73.0 -50.0

Twist 74.2 -1.5 -0.36 72.7 73.2 82.9

Acanto 73.1 -0.4 -7.74 72.7 73.1 -49.3

Vivid 73.1 -0.4 -1.45 72.7 73.0 -4.2

Proline 73.2 -0.5 -20.00 72.7 73.2 -50.0

Caramba 73.2 -0.5 -5.20 72.7 73.2 -20.4

Flamenco 73.1 -0.4 -20.00 72.7 73.1 -50.0


Opus

71

72

73

74

Sp.

Wt (

kg/h

l)

Vivid

71

72

73

74

0 0.5 1 1.5 2

Dose

Sp.

Wt (

kg/h

l)

Amistar

71

72

73

74Twist

71

72

73

74

Proline

71

72

73

74

0 0.5 1 1.5 2

Dose

Caramba

71

72

73

74

0 0.5 1 1.5 2

Dose

Acanto

71

72

73

74

Flamenco

71

72

73

74

0 0.5 1 1.5 2

Dose

81


Parameter estimates


Mean R2

adjusted

Opus 75.7 -2.8 -2.71 73.0 75.5 62.2

Proline 75.4 -2.4 -1.71 73.0 74.9 94.8

Acanto 74.3 -1.3 -3.24 73.0 74.2 -40.5

Vivid 74.0 -1.1 -7.65 73.0 74.0 42.0

Fandango 75.4 -2.5 -4.51 73.0 75.4 48.6

Swift 75.4 -2.4 -2.04 73.0 75.1 2.7

Vivid+Opus 76.0 -3.0 -5.52 73.0 75.9 46.8

Swift+Opus 76.3 -3.3 -3.86 73.0 76.2 70.8


Opus

72

73

74

75

76

77

Sp

Wt.(

kg/h

l)

Fandango

72

73

74

75

76

77

0 0.5 1 1.5 2

Dose

Sp W

t.(kg

/hl)

Proline

72

73

74

75

76

77Acanto

72

73

74

75

76

77

Swift

72

73

74

75

76

77

0 0.5 1 1.5 2

Dose

Vivid+Opus

72

73

74

75

76

77

0 0.5 1 1.5 2

Dose

Vivid

72

73

74

75

76

77

Swift+Opus

72

73

74

75

76

77

0 0.5 1 1.5 2

Dose

82

Table 4.4 6 Parameter estimates for fitted dose response curves for specific weight, Experiment 17, 2003

Parameter estimates


Mean R2

adjusted

Opus 71.4 -1.4 -2.26 70.0 71.3 74.77

Proline 71.7 -1.7 -16.81 70.0 71.7 92.1

Acanto 70.8 -0.8 -20.00 70.0 70.8 48.88

Vivid 71.9 -1.8 -0.83 70.0 71.1 32.31

Fandango 71.7 -1.7 -20.00 70.0 71.7 75.09

Swift 71.4 -1.4 -20.00 70.0 71.4 44.4

Vivid+Opus 71.8 -1.8 -20.00 70.0 71.8 47.85

Swift+Opus 71.3 -1.3 -3.65 70.0 71.3 75.04


Opus

69

70

71

72

73

Sp

Wt.(

kg/h

l)

Fandango

69

70

71

72

73

0 0.5 1 1.5 2

Dose

Sp W

t.(kg

/hl)

Proline

69

70

71

72

73Acanto

69

70

71

72

73

Swift

69

70

71

72

73

0 0.5 1 1.5 2

Dose

Vivid+Opus

69

70

71

72

73

0 0.5 1 1.5 2

Dose

Vivid

69

70

71

72

73

Swift+Opus

69

70

71

72

73

0 0.5 1 1.5 2

Dose

83


Parameter estimates


Mean R2

adjusted

Opus 74.4 -3.9 -2.40 70.5 74.1 78.1

Proline 132.6 -62.1 -0.06 70.5 74.0 73.7

Acanto response curve not fitted

Vivid response curve not fitted

Fandango 75.8 -5.3 -1.84 70.5 75.0 96.5

Swift 71.0 -0.5 -0.95 70.5 70.8 -34.6

Vivid+Opus 77.4 -6.9 -1.70 70.5 76.2 38.7

Swift+Opus 76.7 -6.2 -3.03 70.5 76.4 42.0


Opus

6869707172737475767778

Sp

Wt.(

kg/h

l)

Fandango

6869707172737475767778

0 0.5 1 1.5 2

Dose

Sp W

t.(kg

/hl)

Proline

6869707172737475767778

Acanto

6869707172737475767778

DATA NOTFITTED

Swift

6869707172737475767778

0 0.5 1 1.5 2

Dose

Vivid+Opus

6869707172737475767778

0 0.5 1 1.5 2

Dose

Vivid

6869707172737475767778

DATA NOTFITTED

Swift+Opus

6869707172737475767778

0 0.5 1 1.5 2

Dose

84


Parameter estimates


Mean R2

adjusted



Opus

64

65

66

67

68

69

70

Sp W

t.(kg

/hl)

Bravo

64

65

66

67

68

69

70Vivid

64

65

66

67

68

69

70Swift

64

65

66

67

68

69

70

Vivid+Opus

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Sp W

t.(kg

/hl)

Swift+Opus

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Charisma

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Tracker

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Sp.

Wt.(

kg/h

l)

Fandango

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Proline

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

HGCA9

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

85


Parameter estimates


Mean R2

adjusted

Opus 68.9 -1.0 -0.7 67.9 68.4 13.8 Bravo 67.9 0.0 16.0 67.9 67.9 25.6 Vivid 69.0 -1.1 0.2 67.9 67.7 -91.9 Swift 67.4 0.5 -16.0 67.9 67.4 77 Vivid+Opus 68.8 -0.8 -4.1 67.9 68.8 58.2 Swift+Opus 68.3 -0.3 -16.0 67.9 68.3 47.1 Charisma 67.9 0.0 0.7 67.9 68.0 -31.1 Proline 68.4 -0.4 -16.0 67.9 68.4 -26.8 Fandango 70.1 -2.1 -0.3 67.9 68.5 72.9 Tracker 70.3 -2.4 0.1 67.9 67.7 -27.5 HGCA9 68.3 -0.4 0.1 67.9 67.9 -63.1


Opus

64

65

66

67

68

69

70

Sp

Wt.(

kg/h

l)

Bravo

64

65

66

67

68

69

70Vivid

64

65

66

67

68

69

70

Vivid+Opus

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Sp W

t.(kg

/hl)

Swift+Opus

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Charisma

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Tracker

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Sp. W

t.(kg

/hl)

Fandango

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Proline

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

Swift

64

65

66

67

68

69

70

HGCA9

64

65

66

67

68

69

70

0 0.5 1 1.5 2

Dose

86


Parameter estimates


Mean R2

adjusted

Opus 73.0 -1.3 -16.0 71.7 73.0 68.6 Bravo 75.5 -3.8 -0.3 71.7 72.6 77.5 Vivid 70.4 1.4 -16.0 71.7 70.4 40.8 Swift 73.7 -1.9 0.3 71.7 71.1 19.6 Vivid+Opus 73.1 -1.3 -3.3 71.7 73.0 85.6 Swift+Opus 73.7 -2.0 -4.4 71.7 73.7 97.8 Charisma 75.5 -3.8 -0.3 71.7 72.7 -33.3 Proline 74.3 -2.6 -0.7 71.7 73.1 41 Fandango 74.3 -2.6 -2.1 71.7 74.0 40.3 Tracker 73.8 -2.1 -3.2 71.7 73.7 40.5 HGCA9 70.1 1.6 -0.3 71.7 71.4 21.3


Opus

70

71

72

73

74

75

Sp

Wt.(

kg/h

l)

Bravo

70

71

72

73

74

75Vivid

70

71

72

73

74

75

Vivid+Opus

70

71

72

73

74

75

0 0.5 1 1.5 2

Dose

Sp

Wt.(

kg/h

l)

Swift+Opus

70

71

72

73

74

75

0 0.5 1 1.5 2

Dose

Charisma

70

71

72

73

74

75

0 0.5 1 1.5 2

Dose

Tracker

70

71

72

73

74

75

0 0.5 1 1.5 2

Dose

Sp. W

t.(kg

/hl)

Fandango

70

71

72

73

74

75

0 0.5 1 1.5 2

Dose

Proline

70

71

72

73

74

75

0 0.5 1 1.5 2

Dose

Swift

70

71

72

73

74

75

HGCA9

70

71

72

73

74

75

0 0.5 1 1.5 2

Dose

87

4.3.4 Yield


Parameter estimates


Mean R2

adjusted

Opus 9.9 -0.8 -3.33 9.1 9.9 10.0

Amistar 9.8 -0.7 -2.26 9.1 9.8 17.5

Twist 9.7 -0.6 -20.00 9.1 9.7 -50.0

Acanto 10.3 -1.2 -2.70 9.1 10.2 77.8

Vivid 10.1 -1.0 -6.02 9.1 10.1 88.9

Proline 10.4 -1.3 -1.42 9.1 10.1 37.8

Caramba 9.9 -0.8 -19.45 9.1 9.9 -50.0

Flamenco 9.8 -0.7 -1.50 9.1 9.6 60.6


Opus

8

9

10

11

Yie

ld t/

ha

Vivid

8

9

10

11

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Amistar

8

9

10

11

Twist

8

9

10

11

Proline

8

9

10

11

0 0.5 1 1.5 2

Dose

Caramba

8

9

10

11

0 0.5 1 1.5 2

Dose

Acanto

8

9

10

11

Flamenco

8

9

10

11

0 0.5 1 1.5 2

Dose

88


Parameter estimates


Mean R2

adjusted

Opus 10.0 -0.6 -20.00 9.4 10.0 -50.0 Amistar 10.5 -3.1 -0.18 9.4 9.9 76.5 Twist 10.3 -0.9 -10.17 9.4 10.3 -17.2 Acanto 10.3 -0.9 -0.96 9.4 10.0 15.8 Vivid 10.1 -0.7 -20.00 9.4 10.1 -50.0 Proline 10.3 -0.9 -6.79 9.4 10.3 -25.4 Caramba 10.1 -0.7 -2.05 9.4 10.0 29.4 Flamenco 10.2 -0.8 -1.62 9.4 10.0 76.8


Acanto

8

9

10

11

Flamenco

8

9

10

11

0 0.5 1 1.5 2

Dose

Opus

8

9

10

11

Yie

ld t/

ha

Vivid

8

9

10

11

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Amistar

8

9

10

11

Twist

8

9

10

11

Proline

8

9

10

11

0 0.5 1 1.5 2

Dose

Caramba

8

9

10

11

0 0.5 1 1.5 2

Dose

89


Parameter estimates


Mean R2

adjusted

Opus 7.2 -2.2 -2.99 5.1 7.1 65.4

Amistar 6.4 -1.3 -7.27 5.1 6.4 -43.7

Twist 8.2 -3.1 -4.17 5.1 8.1 77.4

Proline 7.5 -2.5 -3.26 5.1 7.4 92.0

Flamenco 7.3 -2.2 -2.08 5.1 7.0 43.8

Acanto 6.9 -1.9 -2.38 5.1 6.8 73.3

Vivid 7.5 -2.5 -6.24 5.1 7.5 26.7

Fandango 8.2 -3.1 -1.99 5.1 7.8 94.2


Opus

5

6

7

8

9

Yiel

d t/h

a

Flamenco

5

6

7

8

9

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Amistar

5

6

7

8

9

Twist

5

6

7

8

9

Acanto

5

6

7

8

9

0 0.5 1 1.5 2

Dose

Vivid

5

6

7

8

9

0 0.5 1 1.5 2

Dose

Proline

5

6

7

8

9

Fandango

5

6

7

8

9

0 0.5 1 1.5 2

Dose

90


Parameter estimates


Mean R2

adjusted

Opus 10.0 -1.1 -2.52 8.9 9.9 99.2

Proline 10.1 -1.2 -1.79 8.9 9.9 97.3

Acanto 9.5 -0.6 -3.06 8.9 9.5 89.3

Vivid 9.6 -0.7 -3.54 8.9 9.6 45.5

Fandango 10.3 -1.4 -2.11 8.9 10.2 86.3

Swift 9.6 -0.6 -20.00 8.9 9.6 -50.0

Vivid+Opus 10.3 -1.4 -3.99 8.9 10.3 77.3

Swift+Opus 10.5 -1.6 -2.95 8.9 10.5 88.0


Opus

8

9

10

11

Yie

ld t/

ha

Fandango

8

9

10

11

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Proline

8

9

10

11

Swift

8

9

10

11

0 0.5 1 1.5 2

Dose

Vivid+Opus

8

9

10

11

0 0.5 1 1.5 2

Dose

Acanto

8

9

10

11

Swift+Opus

8

9

10

11

0 0.5 1 1.5 2

Dose

Vivid

8

9

10

11

0 0.5 1 1.5 2

91


Parameter estimates


Mean R2

adjusted

Opus 9.4 -0.8 -2.64 8.7 9.4 65.86

Proline 9.9 -1.2 -4.68 8.7 9.8 87.16

Acanto 9.0 -0.4 -2.85 8.7 9.0 7.91

Vivid 9.4 -0.7 -3.16 8.7 9.3 65.87

Fandango 9.9 -1.2 -2.65 8.7 9.8 84.04

Swift 9.5 -0.8 -20.00 8.7 9.5 33.91

Vivid+Opus 9.5 -0.9 -9.37 8.7 9.5 93.75

Swift+Opus 10.1 -1.4 -1.62 8.7 9.8 88.53


Opus

8

9

10

11

Yie

ld t/

ha

Fandango

8

9

10

11

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Proline

8

9

10

11

Swift

8

9

10

11

0 0.5 1 1.5 2

Dose

Vivid+Opus

8

9

10

11

0 0.5 1 1.5 2

Dose

Acanto

8

9

10

11

Swift+Opus

8

9

10

11

0 0.5 1 1.5 2

Dose

Vivid

8

9

10

11

0 0.5 1 1.5 2

92


Parameter estimates


Mean R2

adjusted

Opus 6.2 -1.5 -1.57 4.7 5.9 85.3

Proline 7.3 -2.7 -1.05 4.7 6.4 98.6

Acanto 4.7 0.0 0.65 4.7 4.7 -45.9

Vivid 6.5 -1.8 -0.30 4.7 5.1 82.1

Fandango 6.8 -2.1 -1.83 4.7 6.4 73.9

Swift 5.2 -0.5 -1.65 4.7 5.1 0.6

Vivid+Opus 7.9 -3.2 -1.28 4.7 7.0 98.1

Swift+Opus 7.2 -2.5 -1.70 4.7 6.7 74.6


Opus

4

5

6

7

8

Yie

ld t/

ha

Fandango

4

5

6

7

8

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Proline

4

5

6

7

8

Swift

4

5

6

7

8

0 0.5 1 1.5 2

Dose

Vivid+Opus

4

5

6

7

8

0 0.5 1 1.5 2

Dose

Acanto

4

5

6

7

8

Swift+Opus

4

5

6

7

8

0 0.5 1 1.5 2

Dose

Vivid

4

5

6

7

8

0 0.5 1 1.5 2

93


Parameter estimates


Mean R2

adjusted

Opus 10.1 -2.3 -1.9 7.8 9.7 98.6 Bravo 9.1 -1.3 -0.5 7.8 8.3 95.5 Vivid 8.5 -0.7 -0.2 7.8 7.9 55.9 Swift 7.9 -0.1 -0.1 7.8 7.8 -56.9 Vivid+Opus 9.4 -1.6 -16.0 7.8 9.4 96.5 Swift+Opus 9.4 -1.6 -12.8 7.8 9.4 99.3 Charisma 9.5 -1.7 -0.7 7.8 8.6 99.4 Proline 10.1 -2.3 -2.3 7.8 9.8 97.6 Fandango 10.6 -2.8 -1.2 7.8 9.8 87.2 Tracker 10.0 -2.3 -2.7 7.8 9.9 96.7 HGCA9 9.0 -1.2 -0.2 7.8 8.0 16.3


HGCA9

7

8

9

10

11Opus

7

8

9

10

11

Yie

ld t/

ha

Bravo

7

8

9

10

11Vivid

7

8

9

10

11

Tracker

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Fandango

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Proline

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Vivid+Opus

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Swift+Opus

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Charisma

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Swift

7

8

9

10

11

0 0.5 1 1.5 2

Dose

94


Parameter estimates


Mean R2

adjusted

Opus 11.4 -2.1 -0.4 9.2 9.9 60.9 Bravo 9.7 -0.5 -0.3 9.2 9.3 64.7 Vivid 9.0 0.3 -2.9 9.2 9.0 -29.7 Swift 8.4 0.8 -4.3 9.2 8.4 40.9 Vivid+Opus 9.9 -0.7 -9.2 9.2 9.9 87 Swift+Opus 8.3 0.9 0.2 9.2 9.4 -194.5 Charisma 9.0 0.2 -0.1 9.2 9.2 -68.5 Proline 10.8 -1.6 -1.0 9.2 10.2 66.8 Fandango 10.9 -1.7 -0.2 9.2 9.5 -4.6 Tracker 9.4 -0.2 -4.2 9.2 9.4 -22.9 HGCA9 8.8 0.4 -16.0 9.2 8.8 38.9


Opus

7

8

9

10

11

Yiel

d t/h

a

Bravo

7

8

9

10

11Vivid

7

8

9

10

11

Vivid+Opus

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Swift+Opus

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Charisma

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Tracker

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Fandango

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Proline

7

8

9

10

11

0 0.5 1 1.5 2

Dose

HGCA9

7

8

9

10

11

Sw ift

7

8

9

10

11

0 0.5 1 1.5 2

Dose

95


Parameter estimates


Mean R2

adjusted

Opus 10.0 -2.2 -2.3 7.9 9.8 99.8 Bravo 9.3 -1.4 -1.8 7.9 9.1 94 Vivid 8.3 -0.5 -2.7 7.9 8.3 50.2 Swift 8.4 -0.5 -6.0 7.9 8.4 52.5 Vivid+Opus 9.7 -1.9 -3.2 7.9 9.6 94.7 Swift+Opus 9.8 -2.0 -12.4 7.9 9.8 94.8 Charisma 9.1 -1.3 -0.8 7.9 8.6 50.4 Proline 10.6 -2.8 -1.0 7.9 9.6 98.2 Fandango 9.6 -1.8 -4.5 7.9 9.6 94.4 Tracker 10.4 -2.5 -1.9 7.9 10.0 99.9 HGCA9 8.5 -0.6 -16.0 7.9 8.5 37.6


Opus

7

8

9

10

11

Yie

ld t/

ha

Bravo

7

8

9

10

11Vivid

7

8

9

10

11

Vivid+Opus

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Swift+Opus

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Charisma

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Tracker

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Fandango

7

8

9

10

11

0 0.5 1 1.5 2

Dose

Proline

7

8

9

10

11

0 0.5 1 1.5 2

Dose

HGCA9

7

8

9

10

11

Swift

7

8

9

10

11

0 0.5 1 1.5 2

Dose

96

4.4 Brown rust experiments

4.4.1 Disease Control

The standard azole (Opus) gave very good control of brown rust at half dose. The new azole, Proline, was

markedly weaker against brown rust. The addition of fluoxastrobin to prothioconazole (in Fandango) improved

brown rust control over the prothioconazole alone. Flamenco gave moderate control of brown rust. The

strobilurin fungicides, Acanto, Amistar, Twist and Vivid, all gave good control of brown rust. Vivid gave the

highest level of control.

4.4.2 Green Leaf Area

Green leaf area retention was not always closely linked with disease control. Opus and Tracker gave the highest

green leaf areas and good disease control. In contrast, the strobilurins (Acanto, Amistar, Twist and Vivid) gave

good disease control but this was not reflected in green leaf area or yield. This may be due to the effects of

other diseases such as S. tritici which were also present in the experiments, particularly in 2004.

4.4.3. Yield

Yield was not always related to control of brown rust. This was particularly true in 2004 when S. tritici was

also present in the experiment. Resistance to the strobilurins in S. tritici was widespread at high levels in 2004

and so the strobilurins would contribute less to the control of this disease, whereas the control of brown rust was

not affected.

97

Table 4.60 Parameter estimates for fitted dose response curves for brown rust, Experiment 10, 2002

Parameter estimates


Mean R2

adjusted

Opus 0.1 13.9 -6.82 14.1 0.2 86.7

Amistar 1.2 12.9 -3.82 14.1 1.4 68.0

Twist 1.2 12.8 -5.9 14.1 1.3 73.9

Proline 2.8 11.3 -2.02 14.1 4.3 92.6

Flamenco 0.7 13.3 -3.8 14.1 1.0 91.0

Acanto 0.3 13.7 -4.18 14.1 0.6 91.9

Vivid 0.4 13.6 -6.12 14.1 0.4 84.8

Fandango 0.4 13.7 -5.8 14.1 0.4 76.6

Opus

0

5

10

15

% B

row

n ru

st

Proline

0

5

10

15

Vivid

0

5

10

15

Amistar

0

5

10

15

Acanto

0

5

10

15

0 0.5 1 1.5 2

Dose

% B

row

n ru

st

Fandango

0

5

10

15

0 0.5 1 1.5 2

Dose

Twist

0

5

10

15

0 0.5 1 1.5 2

Dose

Flamenco

0

5

10

15

0 0.5 1 1.5 2

Dose

Figure 4.62 Dose response curves for brown rust control (eradicant), experiment 10, 2002

98

Table 4.61 Parameter estimates for fitted dose response curves for brown rust, Experiment 10, 2002

Parameter estimates


Mean R2

adjusted

Opus 4.4 26.3 -4.15 30.7 4.8 72

Amistar 4.0 26.7 -1.63 30.7 9.2 60

Twist 4.7 26.0 -1.27 30.7 12.0 74

Proline 13.7 17.0 -1.91 30.7 16.2 51

Flamenco 4.5 26.2 -1.77 30.7 8.9 98

Acanto 1.9 28.8 -1.69 30.7 7.2 97

Vivid 4.7 26.0 -3.48 30.7 5.5 75

Fandango 5.5 25.2 -2.93 30.7 6.8 75

Figure 4.63 Dose response curves for brown rust control (protectant), experiment 10, 2002

Opus

0

5

10

15

20

25

30

35

% B

row

n ru

st

Flamenco

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2

Dose

% B

row

n ru

st

Amistar

0

5

10

15

20

25

30

35

Twist

0

5

10

15

20

25

30

35

Acanto

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2

Dose

Vivid

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2

Dose

Proline

0

5

10

15

20

25

30

35

Fandango

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2

Dose

99


Parameter estimates


Mean R2

adjusted

Opus 8.2 -1.8 -3.74 6.4 8.2 84.87

Amistar 8.0 -1.5 -4.15 6.4 7.9 95.45

Twist 8.1 -1.7 -4.35 6.4 8.0 98.38

Proline 8.2 -1.7 -0.56 6.4 7.2 55.77

Flamenco 7.4 -1.0 -3.49 6.4 7.4 71.74

Acanto 7.8 -1.4 -7.59 6.4 7.8 91.85

Vivid 8.3 -1.9 -5.47 6.4 8.3 94.77

Fandango 8.1 -1.6 -4.51 6.4 8.0 86.80

Figure 4.64 Dose response curves for yield, experiment 10, 2002

Opus

6

7

8

9

Yiel

d t/h

a

Flamenco

6

7

8

9

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Amistar

6

7

8

9

Twist

6

7

8

9

Acanto

6

7

8

9

0 0.5 1 1.5 2

Dose

Vivid

6

7

8

9

0 0.5 1 1.5 2

Dose

Proline

6

7

8

9

Fandango

6

7

8

9

0 0.5 1 1.5 2

Dose

100


Parameter estimates


Mean R2

adjusted

Opus 77.5 -2.4 -3.82 75.2 77.5 89.7

Amistar 77.6 -2.5 -2.09 75.2 77.3 72.1

Twist 77.8 -2.6 -3.67 75.2 77.7 93.1

Proline 77.4 -2.2 -1.86 75.2 77.0 73.5

Flamenco 78.0 -2.8 -2.2 75.2 77.7 94.5

Acanto 77.9 -2.7 -2.62 75.2 77.7 94.2

Vivid 77.6 -2.4 -20 75.2 77.6 -50.0

Fandango 77.8 -2.6 -3.92 75.2 77.7 58.3

Figure 4.65 Dose response curves for specific weight, experiment 10, 2002

Opus

75

76

77

78

Sp.

Wt (

kg/h

l)

Flamenco

75

76

77

78

0 0.5 1 1.5 2

Dose

Sp. W

t (kg

/hl)

Amistar

75

76

77

78

Twist

75

76

77

78

Acanto

75

76

77

78

0 0.5 1 1.5 2

Dose

Vivid

75

76

77

78

0 0.5 1 1.5 2

Dose

Proline

75

76

77

78

Fandango

75

76

77

78

0 0.5 1 1.5 2

Dose

101

Table 4.64 Parameter estimates for fitted dose response curves for brown rust, Experiment 23 , 2004

Parameter estimates


Mean R2

adjusted

Opus 0.3 8.3 -4.9 8.5 0.3 94.0 Amistar 0.0 8.5 -3.5 8.5 0.2 98.9 Vivid 0.9 7.6 -5.5 8.5 0.9 80.7 Proline 3.6 4.9 -16.0 8.5 3.6 90.9 Fandango 0.9 7.6 -3.6 8.5 1.2 89.1 Swift 0.1 8.4 -4.4 8.5 0.2 95.8 Charisma 0.7 7.8 -2.1 8.5 1.7 85.7 Tracker 0.1 8.4 -4.3 8.5 0.2 88.6 HGCA9 6.7 1.8 -2.7 8.5 6.9 27.2

Figure 4.66 Dose response curves for brown rust control (eradicant), experiment 23, 2004

Opus

0

5

10

15

% B

row

n ru

st

Fandango

0

5

10

15

0 0.5 1 1.5 2

Dose

% B

row

n ru

st

Amistar

0

5

10

15Vivid

0

5

10

15

Swift

0

5

10

15

0 0.5 1 1.5 2

Dose

Charisma

0

5

10

15

0 0.5 1 1.5 2

Dose

HGCA9

0

5

10

15

0 0.5 1 1.5 2

Dose

% B

row

n ru

st

Proline

0

5

10

15

0 0.5 1 1.5 2

Dose

Tracker

0

5

10

15

0 0.5 1 1.5 2

Dose

102

Table 4.65 Parameter estimates for fitted dose response curves for GLA, Experiment 23, 2004

Parameter estimates


Mean R2

adjusted

Opus 93.95 -16.9 -2.26 77.05 92.18 87.62 Amistar 96.46 -19.41 -0.5 77.05 84.66 95.3 Vivid 88.82 -11.77 -2.62 77.05 87.96 89.04

Proline 90.83 -13.78 -5.79 77.05 90.79 77.55 Fandango 95.11 -18.06 -1.65 77.05 91.65 90.98

Swift 84.72 -7.67 -3.88 77.05 84.56 77.95 Charisma 90.01 -12.96 -1.43 77.05 86.9 93.72 Tracker 93.35 -16.3 -5.74 77.05 93.3 94.6 HGCA9 106.59 -29.54 -0.17 77.05 81.55 86.04

Figure 4.67 Dose response curves for GLA, experiment 23, 2004

Opus

60

70

80

90

100

% G

LA

Fandango

60

70

80

90

100

0 0.5 1 1.5 2

Dose

% G

LA

Amistar

60

70

80

90

100Vivid

60

70

80

90

100

Swift

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Charisma

60

70

80

90

100

0 0.5 1 1.5 2

Dose

HGCA9

60

70

80

90

100

0 0.5 1 1.5 2

Dose

% G

LA

Proline

60

70

80

90

100

0 0.5 1 1.5 2

Dose

Tracker

60

70

80

90

100

0 0.5 1 1.5 2

Dose

103


Parameter estimates


Mean R2

adjusted

Opus 8.3 -1.8 -0.3 6.6 7.0 78.8 Amistar 7.1 -0.5 -1.2 6.6 7.0 26.3 Vivid 7.1 -0.5 -14.1 6.6 7.1 55.2

Proline 7.3 -0.7 -0.9 6.6 7.0 81.7 Fandango 7.1 -0.6 -16.0 6.6 7.1 84.2

Swift 7.0 -0.4 -10.1 6.6 7.0 41.5 Charisma 6.8 -0.2 -16.0 6.6 6.8 7.8 Tracker 8.8 -2.3 -0.3 6.6 7.2 81.9 HGCA9 7.3 -0.7 -0.3 6.6 6.8 20.3


Opus

6

7

8

9

Yiel

d t/h

a

Fandango

6

7

8

9

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Amistar

6

7

8

9Vivid

6

7

8

9

Swift

6

7

8

9

0 0.5 1 1.5 2

Dose

Charisma

6

7

8

9

0 0.5 1 1.5 2

Dose

HGCA9

6

7

8

9

0 0.5 1 1.5 2

Dose

Yie

ld t/

ha

Proline

6

7

8

9

0 0.5 1 1.5 2

Dose

Tracker

6

7

8

9

0 0.5 1 1.5 2

Dose

104

4.5 Mildew experiments

4.5.1 Disease Control Much of the mildew data collected from these experiments represents a combination of eradicant and protectant

activity, with fungicides applied when mildew is already present at the time of application. Under these

conditions at experiment 25 in 2004, Fortress (a largely protectant fungicide) performed poorly. Flexity, Neon

and Tern gave good control of mildew, particularly at higher doses. The new azole, Proline, also gave good

control of mildew, particularly at higher doses. Opus gave some mildew control but was very weak at low

doses. Unix gave good control at high doses. Corbel was significantly poorer than Tern.

Experiment 23 in 2004 was aimed primarily at brown rust but useful data on mildew control were gathered. The

strobilurin fungicides Amistar, Swift and Vivid were all very weak against mildew, reflecting the high levels of

resistance to strobilurins present in the mildew population. Opus gave some useful control of mildew, as did

Proline. The addition of fluoxastrobin to prothioconazole (in Fandango) gave no additional activity against

mildew. Similarly, the addition of boscalid to epoxiconazole (in Tracker) gave no additional control of mildew

over Opus alone. Charisma gave little control of mildew.

4.5.2 Green Leaf Area

The effects of fungicides on mildew did not always reflect in improved green leaf areas. The relatively poor

control of mildew by Corbel, compared with Tern was clearly visible in the improvements in green leaf area

given by Tern but not by Corbel. Flexity, although giving good control of mildew, particularly at high rates, did

not have a marked effect on green leaf area.

Opus and Proline both gave some control of mildew and significant improvement in green leaf area, as did Neon

and Unix – reflecting their mildew control.

4.5.3 Specific Weight

Effects on specific weight largely matched effects on yield. The largest yield effects were usually associated

with improved specific weights.

105

Table 4.67 Parameter estimates for fitted dose response curves for mildew (protectant) Experiment 12, 2002

Parameter estimates


Mean R2

adjusted

Opus -3.7 6.4 -0.11 2.7 2.0 85.3 Proline 0.5 2.2 -2.05 2.7 0.8 98.8 Corbel 1.5 1.3 -20 2.7 1.5 -32.4 Tern 0.2 2.5 -2.5 2.7 0.4 99.5 Fortress 1.3 1.4 -20 2.7 1.3 60.3 Neon -1.5 4.2 -0.43 2.7 1.2 94.9 Unix 0.9 1.8 -2.68 2.7 1.0 71.7 Flexity + Corbel 0.4 2.3 -3.16 2.7 0.5 81.2

Figure 4.69 Dose-response curves for mildew (protectant), Experiment 12, 2002

Opus

0

1

2

3

4

5

% m

ildew

Fortress

0

1

2

3

4

5

0 0.5 1 1.5 2

Dose

% m

ildew

Proline

0

1

2

3

4

5Corbel

0

1

2

3

4

5

Neon

0

1

2

3

4

5

0 0.5 1 1.5 2

Dose

Unix

0

1

2

3

4

5

0 0.5 1 1.5 2

Dose

Tern

0

1

2

3

4

5

Flexity + Corbel

0

1

2

3

4

5

0 0.5 1 1.5 2

Dose

106


Parameter estimates


Mean R2

adjusted

Opus 4.3 -0.5 -0.94 3.8 4.1 -5.5 Proline 3.8 0.0 10.73 3.8 3.8 -27.2 Corbel 4.7 -0.9 -0.99 3.8 4.4 53.4 Tern 4.3 -0.4 -2.68 3.8 4.2 -30.5 Fortress 9.6 -5.8 -0.01 3.8 3.9 -24.7 Neon 14.4 -10.6 -0.05 3.8 4.3 57.9 Unix 4.8 -1.0 -0.61 3.8 4.3 63.2 Flexity + Corbel 5.0 -1.1 -0.75 3.8 4.4 80.0


Opus

3

3.5

4

4.5

5

Yiel

d t/h

a

Neon

3

3.5

4

4.5

5

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Corbel

3

3.5

4

4.5

5Unix

3

3.5

4

4.5

5

Proline

3

3.5

4

4.5

5

0 0.5 1 1.5 2

Dose

Tern

3

3.5

4

4.5

5

0 0.5 1 1.5 2

Dose

Fortress

3

3.5

4

4.5

5

Corbel+Flexity

3

3.5

4

4.5

5

0 0.5 1 1.5 2

Dose

107

Table 4.69 Parameter estimates for fitted dose response curves for mildew control, experiment 25, 2004

Parameter estimates


Mean R2

adjusted

Opus 1.4 12.9 -0.33 14.3 10.7 63.7

Corbel 6.0 8.3 -0.89 14.3 9.4 93.4

Unix -2.2 16.5 -0.61 14.3 6.8 93.3

Fortress 8.4 5.9 -16.0 14.3 8.4 71.1

Neon 2.1 12.2 -1.78 14.3 4.2 71.3

Proline 2.3 12.0 -1.9 14.3 4.1 85.3

Tern 4.1 10.2 -3.2 14.3 4.5 74.8

Flexity 3.8 10.5 -2.6 14.3 4.6 72.4

Figure 4.71 Dose response curves for mildew control, experiment 25, 2004

Opus

0

5

10

15

20

25

% M

ildew

Neon

0

5

10

15

20

25

0 0.5 1 1.5 2

Dose

% M

ildew

Corbel

0

5

10

15

20

25Unix

0

5

10

15

20

25

Proline

0

5

10

15

20

25

0 0.5 1 1.5 2

Dose

Tern

0

5

10

15

20

25

0 0.5 1 1.5 2

Dose

Fortress

0

5

10

15

20

25

Flexity

0

5

10

15

20

25

0 0.5 1 1.5 2

Dose

108

Table 4.70 Parameter estimates for fitted dose response curves for GLA, experiment 25, 2004

Parameter estimates


Mean R2

adjusted

Opus 96.1 -17.4 -0.4 78.6 84.8 79.2

Corbel 80.6 -1.9 -16.0 78.6 80.6 25.8

Unix 88.0 -9.3 -2.5 78.6 87.2 86.1

Fortress 84.3 -5.7 -6.4 78.6 84.3 58.5

Neon 88.8 -10.2 -1.6 78.6 86.7 79.4

Proline 90.6 -11.9 -1.6 78.6 88.2 97.5

Tern 89.3 -10.6 -2.1 78.6 87.9 97.7

Flexity 80.7 -2.1 -16.0 78.6 80.7 -10.8

Figure 4.72 Dose response curves for GLA, experiment 25, 2004

Opus

70

80

90

100

GLA

(%)

Neon

70

80

90

100

0 0.5 1 1.5 2

Dose

GLA

(%)

Corbel

70

80

90

100Unix

70

80

90

100

Proline

70

80

90

100

0 0.5 1 1.5 2

Dose

Tern

70

80

90

100

0 0.5 1 1.5 2

Dose

Fortress

70

80

90

100

Flexity

70

80

90

100

0 0.5 1 1.5 2

Dose

109

Table 4.71 Parameter estimates for fitted dose response curves for yield, experiment 25, 2004

Parameter estimates


Mean R2

adjusted

Opus 8.8 -3.1 -0.2 5.7 6.2 87.9

Corbel 6.4 -0.7 -1.1 5.7 6.2 49.7

Unix 5.5 0.2 -0.6 5.7 5.6 -32.6

Fortress 7.2 -1.5 -0.4 5.7 6.2 38.3

Neon 6.4 -0.7 -2.5 5.7 6.4 89.3

Proline 6.3 -0.6 -2.7 5.7 6.3 20.0

Tern 7.3 -1.6 -1.2 5.7 6.8 80.4

Flexity 6.6 -0.9 -1.8 5.7 6.5 20.3


Opus

5

6

7

8

Yie

ld t/

ha

Neon

5

6

7

8

0 0.5 1 1.5 2

Dose

Yiel

d t/h

a

Corbel

5

6

7

8Unix

5

6

7

8

Proline

5

6

7

8

0 0.5 1 1.5 2

Dose

Tern

5

6

7

8

0 0.5 1 1.5 2

Dose

Fortress

5

6

7

8

Flexity

5

6

7

8

0 0.5 1 1.5 2

Dose

110

Table 4.72 Parameter estimates for fitted dose response curves for specific weight, experiment 25, 2004

Parameter estimates


Mean R2

adjusted

Opus 71.0 -3.2 -0.3 67.8 68.7 50.8

Corbel 68.6 -0.7 -16.0 67.8 68.6 25.0

Unix 67.6 0.2 -0.3 67.8 67.8 -36.0

Fortress 70.7 -2.9 -0.7 67.8 69.2 80.9

Neon 69.6 -1.7 -1.2 67.8 69.0 78.1

Proline 69.6 -1.8 -1.2 67.8 69.1 83.9

Tern 70.4 -2.6 -2.1 67.8 70.1 88.5

Flexity 71.1 -3.2 -1.4 67.8 70.2 86.0

Figure 4.74 Dose response curves for specific weight, experiment 25, 2004

Opus

65

66

67

68

69

70

71

72

Sp

Wt.

Neon

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Sp

Wt.

Corbel

65

66

67

68

69

70

71

72Unix

65

66

67

68

69

70

71

72

Proline

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Tern

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

Fortress

65

66

67

68

69

70

71

72

Flexity

65

66

67

68

69

70

71

72

0 0.5 1 1.5 2

Dose

111

Table 4.73 Parameter estimates for fitted dose response curves for mildew, experiment 23, 2004

Parameter estimates


Mean R2

adjusted

Opus 2.4 6.9 -9.0 9.3 2.4 55.5

Amistar 4.1 5.2 -1.2 9.3 5.7 66.8

Vivid 5.4 3.9 -10.3 9.3 5.4 68.0

Proline 1.0 8.3 -2.2 9.3 1.9 73.0

Fandango 2.0 7.3 -2.0 9.3 3.0 82.5

Swift 6.1 3.2 -7.1 9.3 6.1 50.1

Charisma 3.1 6.2 -1.3 9.3 4.8 85.3

Tracker 2.5 6.8 -4.1 9.3 2.6 97.9

Figure 4.55 Dose response curves for mildew, experiment 23, 2004

N.B. At experiment 23, 2004, both brown rust and mildew were present. GLA and yield data relate to a

combination of brown rust and mildew control. See tables 4.65 and 4.66 for data on GLA and yield at this site.

Opus

0

5

10

15

% M

ildew

Fandango

0

5

10

15

0 0.5 1 1.5 2

Dose

% M

ildew

Amistar

0

5

10

15Vivid

0

5

10

15

Swift

0

5

10

15

0 0.5 1 1.5 2

Dose

Charisma

0

5

10

15

0 0.5 1 1.5 2

Dose

Proline

0

5

10

15

Tracker

0

5

10

15

0 0.5 1 1.5 2

Dose

112

5.0 CONCLUSIONS

• Robust, comparative dose-response data sets were gathered for the most widely used fungicides used on

wheat. This includes active ingredients from azole, morpholine, strobilurin, spiroketalamine,

benzamide and carboxanilide fungicide groups.

• Up to three years of data on fungicides launched in 2005 were gathered. These included boscalid (in

mixture with epoxiconazole in Tracker), dimoxystrobin (in mixture with epoxiconazole in Swing Gold),

fluoxastrobin (in mixture with prothioconazole in Fandango), metrafenone (Flexity) and

prothioconazole (Proline).

• The exponential function : y=a+be k dose described the range of dose-response variation across a wide

range of circumstances. The a, b and k parameters all have clear biological meaning.

• Fitted exponential curves describing the effect of fungicides on disease, green leaf area, yield and grain

quality typically explained a very high proportion (over 90%) of the variance in the data.

• The conclusions on individual treatments relate to single applications, applied under high disease

pressure, on a disease-susceptible variety. Where more resistant varieties are grown, disease pressure is

lower or the treatment forms part of a 2- or 3-spray programme, the appropriate dose will be lower.

This aspect of ‘Appropriate Dose’ is addressed in the new HGCA project No. 3026 Appropriate

Fungicide Dose sequences and mixtures in winter wheat according to disease risk

• Data on strobilurin performance against S. tritici clearly show a dramatic reduction in efficacy over the

period 2002 –2004. Despite measurements of the resistance allele (G143A) frequency indicating that

resistance levels were generally greater than 80% in 2004 there was still a measurable effect of

strobilurin fungicides against S. tritici.

• Analysis of data since 1994 indicate a significant reduction in activity of epoxiconazole (and by

inference, all other azole fungicides) against S. tritici. The observation of this effect in field trials has

been supported by laboratory-based data showing changes in the sensitivity of isolates of S. tritici.

• Information on these new products was published in the Wheat Disease Management Guide Update

2005 (published in February 2005) and on the HGCA web site as an interactive tool in March 2005.

113

• There were very substantial differences in dose-response curves between treatments. Significant

economic benefits would arise by using such data when selecting products and deciding on the dose to

apply.

Septoria tritici

• Opus (epoxiconazole) provided the most effective and consistent control of S. tritici.

• Tracker (a mixture of epoxiconazole and boscalid) gave equivalent control to epoxiconazole, despite

containing only 80% of the epoxiconazole dose in Opus.

• Proline (prothioconazole) gave control of S. tritici comparable to Opus.

• Fandango (prothioconazole plus fluoxastrobin) gave control of S. tritici comparable to Opus.

• Under high disease pressure, on a susceptible variety a three-quarter dose of Opus was needed for

consistent control.

• Compared with data from the mid 1990s there has been a clear loss of performance of the azoles against

S. tritici.

• The performance of strobilurins against S. tritici declined markedly during the period 2002-2004.

• Despite high levels of resistance to strobilurins in the S. tritici population at the start of 2004,

trifloxystrobin and pyraclostrobin both gave about 30% control of septoria in high disease pressure

situations.

Yellow rust

• The patterns of dose-response for yellow-rust control are substantially different from those for S. tritici.

The disease-control curves are very steep – i.e. the majority of the control of yellow rust is obtained

from the first quarter dose.

114

• Provided sprays are well timed, effective and consistent control of yellow rust can be obtained with

between a quarter and a half of the label-recommended dose.

• There is no evidence of any shift in activity of the triazoles against yellow rust since the mid 90s.

• The active ingredient prothioconazole (in Proline and Fandango) is slightly weak on yellow rust

compared with epoxiconazole. However, even in the very high disease-risk situations in these

experiments prothioconazole performed well.

• The strobilurins continue to be very effective against yellow rust. The addition of fluoxastrobin to

prothioconazole (in Fandango) eliminates the slight weakness of prothioconazole alone (as Proline).

Mildew

• There has been an almost complete loss of activity of the strobilurins against mildew during the course

of these experiments due to the development of resistance in the mildew population in the UK.

• There have been a number of new mildew fungicides introduced which has helped to compensate for

the loss of activity of the strobilurins. New active ingredients with specific activity against mildew

include metrafenone (Flexity), quinoxyfen (Fortress) and spiroxamine (Neon), all of which give good

control of the disease, particularly in when applied in a protectant situation.

Yield

• The full yield potential of disease-susceptible varieties such as Consort and Brigadier will not be

achieved in these experiments as only a single treatment is applied. Nevertheless, significant yield

responses were obtained in the experiments. Comparisons of full and untreated yields on Consort in

2004 showed a yield response of 1.1 t/ha for Opus, and 1.3 t/ha for Proline, Fandango and Tracker.

• The yield response to strobilurin treatment in these experiments is variable depending on the main

pathogens present and the resistance status of the S. tritici population. In 2001 and 2002 Vivid, on

average, gave yield responses 15-20% higher than Opus at S. tritici sites. In 2003 yield responses were

very similar but in 2004 Vivid treatment gave only 27% of the yield response of Opus treatment at

predominantly S. tritici sites.

• In brown rust experiments in 2002 yield responses to strobilurin treatment were often high because

additional control of S. tritici was obtained. This was not the case in 2004 when majority of the S. tritici

population was resistant to strobilurin fungicides.

115

• At septoria sites in 2004 yield responses to strobilurins were variable. At some sites no yield response

was obtained (Expt 24) but at others, (Expt 20) responses of 1.1 t/ha were achieved from a full dose of

Vivid. Some of this yield response is likely to be due to the control of other diseases such as brown rust

and S. nodorum but there was clearly significant control of S. tritici at some of these sites, despite very

high levels of resistance in the S. tritici population. The reasons for the variability in response to

strobilurin treatment at septoria sites are not fully understood although possible mechanisms are

discussed in a paper to be presented by W. S. Clark at the BCPC Conference – Crop Science &

Technology 2005 entitled “QoI resistance in Septoria tritici in the UK: implications for future use of

QoI fungicides”.

• In yellow rust experiments yield responses to low doses of fungicide were very large. In 2003 yield

responses to single applications at full label dose were on average 3.0 t/ha, with responses of 2.4 t/ha to

a quarter dose of Opus. In 2004 a yield response of 3.0t/ha was achieved from a single application of

one quarter of the label dose of Opus. A single full dose gave a yield response of over 3.5 t/ha. Vivid

and Swift gave yield responses of 1.5 t/ha to a quarter dose and 2.1 t/ha to a full dose. The recently

introduced products Fandango, Proline and Tracker all gave yield responses similar to Opus.

ACKNOWLEDGMENTS

These experiments were funded by the Home-Grown Cereals Authority. Thanks are due to the many

workers involved, including staff from ADAS, SAC and TAG who gathered the field data. Dr Anne

Ainsley, who carried out all of the statistical analysis, has our particular thanks.

116

APPENDIX 1

Active ingredient Example products

Azoxystrobin Amistar Boscalid In mixture with epoxiconazole as Tracker Bromuconazole Granit Carbendazim Various Chlorothalonil Bravo, various Cyproconazole Caddy, Fort Cyprodinil Unix Difenoconazole Plover Dimoxystrobin In mixture with epoxiconazole in Swing Gold Epoxiconazole Opus Fenbuconazole Kruga, Reward, Surpass Fenpropidin Tern Fenpropimorph Corbel Fluoxastrobin In mixture with prothioconazole as Fandango Fluquinconazole Flamenco Flusilazole Genie, Lyric, Sanction Flutriafol Pointer Kresoxim-methyl In mixtures with epoxiconazole in Landmark, Mantra, Opponent Metconazole Caramba Metrafenone Flexity Picoxystrobin Acanto Prochloraz Sportak, Poraz Propiconazole Barclay Bolt, Bumper, Tilt Prothioconazole Proline Pyraclostrobin Comet, Tucana, Vivid Quinoxyfen Erysto, Fortress Spiroxamine Neon, Torch Tebuconazole Folicur Tetraconazole Juggler Triadimenol Bayfidan Trifloxystrobin Twist, Swift

117

APPENDIX 2

Products Active ingredient

Acanto Picoxystrobin Amistar Azoxystrobin Bayfidan Triadimenol Bravo Chlorothalonil Bumper Propiconazole Caddy Cyproconazole Caramba Metconazole Comet Pyraclostrobin Corbel Fenpropimorph Erysto Quinoxyfen Fandango Fluoxastrobin + prothioconazole Flamenco Fluquinconazole Flexity Metrafenone Folicur Tebuconazole Fort Cyproconazole Fortress Quinoxyfen Genie Flusilazole Granit Bromuconazole Juggler Tetraconazole Kruga Fenbuconazole Landmark Kresoxim-methyl + epoxiconazole Lyric Flusilazole Mantra Kresoxim-methyl + epoxiconazole + fenpropimorph Neon Spiroxamine Opponent Kresoxim-methyl + epoxiconazole + pyraclostrobin Opus Epoxiconazole Plover Difenoconazole Pointer Flutriafol Poraz Prochloraz Proline Prothioconazole Reward Fenbuconazole Sanction Flusilazole Sportak Prochloraz Surpass Fenbuconazole Swift Trifloxystrobin Swing Gold Dimoxystrobin + epoxiconazole Tern Fenpropidin Tilt Propiconazole Torch Spiroxamine Tracker Boscalid + epoxiconazole Tucana Pyraclostrobin Twist Trifloxystrobin Unix Cyprodinil Vivid Pyraclostrobin

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