emergence trap for monitoring the cranberry tipworm dasineura oxycoccana in quebec

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Emergence trap for monitoring the cranberry tipworm Dasineura oxycoccana in Quebec. Annabelle Firlej, Jean-Pierre Deland & Daniel Cormier . Cranberry tipworm Dasineura oxyccocana. Diptera pest presents in North-America Attacks shoots of cranberry and provokes gall - PowerPoint PPT Presentation

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Emergence trap for monitoring the cranberry tipworm Dasineura oxycoccana in Quebec

Annabelle Firlej, Jean-Pierre Deland & Daniel Cormier

Cranberry tipworm Dasineura oxyccocana

• Diptera pest presents in North-America • Attacks shoots of cranberry and provokes gall• In blueberry: blueberry gall midge but reproductive isolation

(Cook, 2011)

Photo: CETAQ

Cranberry tipworm Dasineura oxyccocana

• 25% of the field in Quebec with damage• In general upright damaged produces 50% less fruits (Le

Duc 2010)• When infested by the 3rd generation: 33% of fruiting buds

are recovered the next year (Le Duc 2010)

Photo: CETAQ

Scouting

• Current scouting: 100 shoot observed under binocular = time consuming!

• Need for adult scouting to better predict egg population, generation and spraying date

• MOVENTO 240 SC registered, application after flowering at egg hatching

• Different methods tested or under development for monitoring adults (Sarzinsky & Liburd, 2003, talk of S. Fitzpatrick)

Monitoring in blueberry of Florida

• Emergence trap developed for blueberry gall midge in blueberry rabbiteye (Roubos & Liburd 2010)

Emergence traps developed in Quebec

Petri dish trap (P1) Plate trap (P2)

Objectives and set up1. Which trap perform better?2. Are adults populations

correlated with eggs or larvae populations?

3. Where to set up the trap?4. Is the scouting with a trap

more costly (labor)

Objectives and set up1. Which trap perform better?2. Are adults populations

correlated with eggs or larvae populations?

3. Where to set up the trap?4. Is the scouting with a trap

more costly (labor)

• 3 farms• 9 fields• 15 weeks of sampling• 2 traps• 12 of each traps

Objectives and set up1. Which trap perform better?2. Are adults populations

correlated with eggs or larvae populations?

3. Where to set up the trap?4. Is the scouting with a trap

more costly (labor)

• 3 farms• 9 fields• 15 weeks of sampling• 2 traps• 12 of each traps

Objectives and set up1. Which trap perform better?2. Are adults populations

correlated with eggs or larvae populations?

3. Where to set up the trap?4. Is the scouting with a trap

more costly (labor)

• 3 farms• 9 fields• 15 weeks of sampling• 2 traps• 12 of each traps

Photo: CETAQ

Are adults populations correlated with eggs or larvae populations?

Farm Stage P1 P2

1 egg 0.74223<.0001

0.74077<.0001

larva 0.86582<.0001

0.88196<.0001

2 egg 0.71212<.0001

0.71867<.0001

larva 0.82630<.0001

0.85291<.0001

3 egg 0.413170.0065

0.437170.0038

larva 0.543630.0002

0.472280.0016

Spearman correlation

1. Which trap perform better?2. Are adults populations

correlated with eggs or larvae populations?

3. Where to set up the trap?4. Is the scouting with a trap

more costly (labor)

In summer 2013

• Petri dish trap• 12 farms• 12 traps in each field• Early may to September• HOBO loggers

1. Which trap perform better?2. Are adults populations

correlated with eggs or larvae populations?

3. Where to set up the trap?4. Is the scouting with a trap

more costly (labor)

Analyzing time of labor

0:00

0:07

0:14

0:21

0:28

0:36

0:43

0:34:42 0:23:49 0:22:28

Traditional scout -ing

field trap sam-pling+ binocular identification

field trap sampling + field identifi-cation

Tim

e (m

in)

a

b

b

ANOVAP<0.0001

Analyzing error du to technique used

Under binocular with magnifying glass0

2

4

6

8

10

12

14

16

7.9 8.3

Num

ber o

f D. o

xyco

ccan

a

ANOVAP>0.05

aa

Conclusion

• Petri dish efficient to capture adults• Good correlation with eggs but better with larvae• Appears less costly in time of labor• Data integration in forecasting model predicting eggs and

larvae generation.

Gaétan Bourgeois Scientist in Bioclimatology and Modelling

Acknowledgements

• Franz Vanoosthuyse (IRDA)• Jonathan Veilleux (IRDA)• Students from CETAQ and IRDA• Growers from Quebec

• Funding:

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