A predictive model for timing herbicide application of the nonpredictable root parasite Orobanche sp

1
A predictive model for timing herbicide
application of the non-predictable root parasite
Orobanche spp.Hanan EizenbergDepartment of
Weed Research and Phytopathology, Newe Yaar
Research Center, Israel
2
Hanan Eizenberg 1997 MSc studies at the Inst. of
Plant Science and Genetics, Faculty of Agric.,
Food and Environ. Science, The Hebrew University
of Jerusalem, Rehovot, Israel 2001 PhD studies
at the Inst. of Plant Science and Genetics,
Faculty of Agric., Food and Environ. Science,
The Hebrew University of Jerusalem, Rehovot,
Israel 2001- 2003- Post-doc, Dept. of Crop and
Soil Science, Oregon State University,
Corvallis, Oregon, USA
3
2003- to date Research Scientist, in the
Department of Plant Pathology and Weed Research,
Newe Ya'ar Research Center, Agric. Res. Org.
(ARO), Israel. Research topics Modeling and
precision agriculture focusing on chemical
control of troublesome weeds in vegetable, field
crops and flowers Optimization of chemical
control of weeds in major crops Orobanche
resistant varieties.
4
Clover broomrape (O. minor)
5
Sunflower field
6
(No Transcript)
7
(No Transcript)
8
Underground stages
Seed
Tubercle
Attachment
D.M. Joel
9
Aboveground stage
Underground stages
Flower

D.M. Joel
D.M. Joel
10
Why is Orobanche control complicated?

• The parasite is connected to the host
• Systemic herbicides may be metabolized by the
  host
• In most cases we do not know the infestation level

11
Why is Orobanche control complicated?

• The parasite continuously germinates throughout
  the season
• Photosynthesis Inhibitors cannot be used due to
  the absence of the relevant target enzymes

12
Post-planting herbicide application
13
Points for discussion - I

• Site specific weed management in the root
  parasite Orobanche spp.
• May it possible?
• Yes it may possible!
• First stage is developing model for Orobanche
  control

14

• Objectives
• To develop a predictive model for small broomrape
  parasitism in red clover based on growing degree
  days
• To develop a model for timing herbicide
  applications based on the parasitism model

15
HypothesisThe parasitism of Orobanche is
temperature related
16
Linke et al., 1991 O. crenata Lentil van
Hezewijk, 1994 O. crenata faba
bean lentil Mesa-Garcia, 1986 O.
crenata faba bean Castejon Manoz et al., 1993 O.
cumana sunflower Ter Borg, 1986 O.
crenata faba bean Sauerborn et al., 1989 O.
crenata lentil O. cumana sunflower Gordon
Ish Shalom, 1994 O. cumana sunflower Eizenberg
et al., 1998 O. aegyptiaca tomato Eizenberg et
al., 2001 O. aegyptiaca carrot O. crenata
carrot Eizenberg et al., 2003 O.
aegyptiaca sunflower O. cumana Sunflower Eiz
enberg et al., 2004 O. minor red clover
17
Materials and methods
18
S1
S1
S2
S3
S4
19
(No Transcript)
20
Mini-rhizotron system
21
(No Transcript)
22
Four light bulbs
23
70 cm
40 cm
10 cm
24
(No Transcript)
25
(No Transcript)
26
(No Transcript)
27
(No Transcript)
28
120 GDD D 20 cm
180 GDD D 20 cm
29
300 GDD D 30 cm
Foliar application of 10 ml ha-1 Cadre
(imazapic 240 g a. i. l-1)
360 GDD D 30 cm
30
120 GDD D 20 cm
240 GDD D 20 cm
Foliar application of 10 ml ha-1 Cadre
(imazapic 240 g a. i. l-1)
180 GDD D 20 cm
300 GDD D 20 cm
31
Growing degree days (GDD)
GDD ?Tmax Tmin) / 2 - Tbase
Tbase (tested) 0, 1, 2, .., 10
Red clover Tbase 0 Tomato Tbase
0 Sunflower Tbase 4
32
Y number of broomrape attachments a represents
the upper asymptote (maximum) x0 represents the
GDD when Y is 50 of maximum (median) b
represents the slope at x0
33
Small broomrape parasitism related to GDD
Small broomrape plant-1
S1 (Y 1.06/(1 (x / 736.88))-8.70) R2
0.99 S2 (Y 1.06/(1 (x / 886.53))-8.26) R2
0.99 S3 (Y 1.04/(1 (x / 1152.94))-9.74) R2
0.99 S4 (Y 0.72/(1 (x / 1357.87))-11.40) R2
0.99
Growing degree days
34
Attachment size correlated to GDD
Number
1850
1650
1450
Attachment size (mm)
1250
GDD
1050
850
35
Red clover biomass related to GDD
Non-infested red clover
Clover dry weight (g plant-1)
Small broomrape-infested red clover
Growing degree days
36
Broomrape stage distribution related to GDD
Small broomrape
GDD
37
Small broomrape infection related to GDD
Growing degree days
Days from January 1st
38
ImazamoxImidazolinones- ALS inhibitorsPRE or
POST applications in soybean
39
(No Transcript)
40
1200 GDD 10 g ha-1
1200 GDD 20 g ha-1
1200 GDD 30 g ha-1
1200 GDD 40 g ha-1
41
1600 GDD 10 g ha-1
1600 GDD 40 g ha-1
1600 GDD 40 g ha-1
42
A minimal herbicide rate model for O. minor
control (95)
Imazamox rate (g/ha)
Growing degree days
43

• Conclusions
• Broomrape parasitism is
• Temperature correlated
• The parasitism stages are predictable
• Optimizing herbicide applications enable to
  reduces rates

44
What do we need for integrating the model into
SSWM approach?
45
Points for discussion - II

• Estimating the spatial distribution of Orobanche
  infestation in the field
• Detecting physiological factors in the host that
  affected by the parasitism as a predicting tools
  in the underground stages of the parasite
• Using GIS with data from previous years

46
Further studies Integrating the model into SSPM
approach
47
Thanks for your attention
48
(No Transcript)