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Effective Control of Pythium and Brown Patch Diseases of Cool

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Effective Control of Pythium and Brown Patch Diseases of Cool-Season Turfgrasses Bruce B. Clarke Rutgers University, New Brunswick, New Jersey USA
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Effective Control of Pythium and Brown Patch

Diseases of Cool-Season Turfgrasses

Bruce B. Clarke

Rutgers University,

New Brunswick, New Jersey USA

Diseases Caused by Pythium

Damping-off of seedlings

Pythium blight of foliage

Pythium root rot, dysfunction

Pythium Blight

• Causal Agent(s): Pythium aphanidermatum and

other Pythium species such as P. myriotylum, P.

graminicola ,P. arrhenomanes, and P. ultimum

• Hosts / Occurrence: All turfgrasses are susceptible

with the cool-season grasses - creeping bentgrass,

annual bluegrass and Kentucky bluegrass - being

the most.

Pythium Blight

• Causal Agent(s): Pythium aphanidermatum and

other Pythium species such as P. myriotylum, P.

graminicola ,P. arrhenomanes, and P. ultimum

• Hosts / Occurrence: All turfgrasses are susceptible

with the cool-season grasses - creeping bentgrass,

annual bluegrass and Kentucky bluegrass - being

the most.

Pythium Blight

Symptoms on Leaves

small (2.5-10 cm), bronzed, water-soaked

patches a with slippery or slimy feeling

when rubbed between the fingers

white-gray “cobwebby” mycelium may be

present with humidity is high

symptoms may occur in streaks,

sometimes with water draining channels

Mycellium and oospores of Pythium ultimum

Pythium zoospore infecting turfgrass root

Pythium Blight

Most likely to occur when temperatures

exceed 29 0C (day) and 20 0C (night) and

when the relative humidity is high.

Typically occurs between June and

September

High soil salinity favors

increased susceptibility

High fertility generally favors

increased disease

Low soil moisture preceding abundant

rainfall and high temperatures

Conditions Favoring Pythium Blight

■ Maintain adequate soil moisture

■ Reduce seed rates (spring and summer)

■ Soil pH in a more acid range

■ Balanced fertility

■ Leach salts if they accumulate to high levels

■ Reduce leaf wetness

Pythium Blight Cultural Control

Chemical Control of Pythium Blight

I Phenylamides :

Subdue MAXX (spray and seed treatment)

II Phosphonates :

Alliette Signature

III Strobilurins :

Heritage MAXX, Compass, Insignia

IV Acylamine: benalaxyl

(New QiL Chemistry – cyazofamid)

Pythium Blight Control: 2007 Penn State University

Treatments and Product Appl.rates

Azoxystrobin 0.62 kg ai/ha Trifloxystrobin 0.31 kg ai/ha

Pyraclostrobin 0.55 kg ai/ha Untreated --- ---

Mike Fidanza

% B

ligh

ted

Tu

rf

● Agrostis stolonifera (fairway – 1.143 cm

● Bellewood Golf Course, North Coventry, PA.

(Penn State University, State College, PA USA - Mike Fidanza)

Percent Pythium blight – Aug. 24, 2007 (21 Days after treatment)

b b b

a

Control of Pythium Blight on Lolium : Rutgers 2005

% turf area infested

Trt and rate / 1000 ft2 Sch. 13 Jun 30 Jun 25 Jul

metalaxyl 0.37 kg ai/ha 14 day 7.3 a 3.0 ab 0.0 a

Propamocarb 2.2 kg ai/ha 14 day 0.0 a 1.0 a 0.0 a

Fosetyl-Al 9.8 kg ai/ha 14 day 0.8 a 0.0 a 3.8 ab

Pyraclostrobin 0.55 kg ai/ha 14 day 0.0 a 0.0 a 0.0 a

Azoxystrobin (WG) 0.31 kg ai/ha 14 day 0.0 a 0.0 a 0.3 a

Azoxystrobin (WG) 0.62 kg ai/ha 21 day 0.0 a 1.3 a 11.3 c

Azoxystrobin (ME) 0.62 kg ai/ha 21 day 0.0 a 4.5 b 10.0 c

Untreated check - 7.8 b 24.3 c 32.7 e

Control of Pythium Blight with Selected Fungicides

on Perennial Ryegrass : Rutgers 2010

Treatments applied in 4 gal water/M on a 14-day interval beginning on 18-June to 23-July.

Biology and Management of

Pythium Root Rot

Bruce B. Clarke1 and Lane Tredway2

Rutgers University1and N C State University2 USA

Pythium Root Rot

Pathogen: Pythium aristosporum, P.

arrhenomanes, P. graminicola,

P.volutum; others

Grasses affected: All turfgrasses, but

primarily Agrostis stolonifera and Poa

annua

Root Rot Caused by Pythium species

• Pythium Root Rot

• Caused by an large number of Pythium species

• Occurs in poorly drained greens or during wet weather

• May develop at any time of year

• Symptoms usually in irregular patterns, sometimes in

spots or patches

• Responds well to standard Pythium fungicides

(metalaxyl)

Pythium

Root Rot

Pythium Root Rot

Pythium oospores

Pythium root rot reduces the plant’s ability to absorb water and nutrients

Kerns and Tredway

P. volutum P. torulosum Uninoculated Kerns and Tredway

Roots

Infected

with

Pythium

Root

Rot

August 5, 2004

Untreated pyraclostrobin (0.56 kg ai/ha)

Kerns and Tredway

Management of Pythium Root Rot

- Improve drainage, sunlight penetration

- Improve soil conditions; deep tine aerification

- Fungicides: contact fungicide drenches (avoid in high

heat…), followed by metalaxyl or fosetyl-Al

Rhizoctonia Blight (Brown Patch)

Causal Agent :

Rhizoctonia solani

Host :

Bentgrass Agrostis sp.

Ryegrass Lolium sp.

Fescue Festuca sp.

Relative Growth of a Cool-season Grass

/ Pathogen System

Conditions Favoring

Brown Patch

* Hot, Wet Weather

* High Humidity

* Excess Nitrogen

* Thatch Accumulation

Brown Patch of Cool-season

Turfgrasses: Disease Cycle

15-20 C - growth of fungus from

sclerotia or dead plant tissue

24-28 C - colonization of lower leaves in

turfgrass canopy (symptoms of

disease may not be apparent!)

28-32 C - colonization of upper leaves in

turfgrass canopy with symptoms

Environmental Parameters

Necessary for

Brown Patch Development

* RH >95% for 10 hours

* Minimum Air Temp. > 15 0C

* > 2.5 mm Rainfall within 36 hours

12 AM

6 AM

12 PM

6 PM

DEW AND

GUTTATION

WATER

DO NOT

IRRIGATE

LEAVES

DRY

DO NOT

IRRIGATE

Brown Patch of Cool-season

Turfgrasses Management

♦ Balanced fertility

♦ Improve air movement

♦ Decrease leaf wetness

♦ Correct subsurface

drainage problems

♦ Reduce thatch

♦ Avoid high N fertility

during periods of heat

stress

♦ Improved cultivars for

better disease and

heat stress

♦ Proper mowing Ht.

♦ Use of fungicides

NTEP Agrostis Greens Test Brown Patch Ratings, Stillwater, OK USA

6.2

6.46.6

6.8

7

7.27.4

7.6

7.88

8.2

L-93 A

-4A-1

G-2

Cen

tury

Cre

nsha

w

Pen

ncro

ss

a

LSD = 0.9 a

b

a

a

a

1 to 9, with 9=no disease, 1993 trial

a

Chemical Control of Brown Patch

I DMIs: tebuconazole, propiconazole

II Dicarboximide: iprodione

III QoIs: azoxystrobin, trifloxystrobin,

pyraclostrobin

IV Organic Phosphate: tolclofos-methyl

Control of Brown of Brown Patch on

Festuca arundinacea, Rutgers 1987

Treatments applied on 14-day interval beginning on 3 July,

Control of Brown of Brown Patch on

Agrostis stolonifera, Rutgers 1990

Treatments applied on 28-day interval beginning on 11 July, Rizolex 75W = Tochlofos-methyl 75W, Chipco 26019 2F = Iprodione 2F

Improving Disease Control using

Disease Predictive Models

R. Latin

Professor of Plant Pathology

Purdue University

Decisions regarding fungicide application

schedules may be based upon…

Calendar

Damage thresholds

Environmental-Based

Disease Predictive models

Factors Involved with Disease

Predictive Models Standard Factors

Air temperature

Relative Humidity

Rainfall/Irrigation

Soil Temperature

Others Factors

Dewpoint

Evapotranspiration

Leaf wetness

Degree Days Temp base 50

Environmental data

Data Processor

(computer in weather station

on golf course)

Disease

Prediction

Precip

Hours

Dew

RH

Air Temp

Weather-based systems collect environmental data and

process the data into usable information.

Important environment-based models

Diseases

– Dollar spot,

– Pythium blight

– Brown patch

– Gray leaf spot

– Anthracnose

(Cool season grasses)

Brown Patch (Bent)

1. Low air temp > 15 C (for two consecutive days)

2. RH > 95% for at least 10 hours

3. Rainfall/irrigation of at least 2.5 mm within the past 36 hr

Schumann, Clarke and Burpee, 2001

Predicting Pythium Blight

Hall et al – 1985 ( over predicts )

◆ Based on air temp during 24 hr period only

◆ Min temp > 20 0C < 18 hr = No risk

◆ Min temp > 20 0C > 18 hr < 24 hr = Mod risk

◆ Min temp > 20 0C > 24 hr = Severe risk

So In Conclusion:

For

- Calendar

- Weather-based

- Damage threshold

methods

Each has advantages and disadvantages. However,

weather based disease predictive models offer the

greatest opportunity to improve control and to

potentially reduce fungicide usage.


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