Group Title: Research report (North Florida Research and Education Center (Quincy, Fla.))
Title: Investigation of soybean stress from defoliating pests southern region
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 Material Information
Title: Investigation of soybean stress from defoliating pests southern region
Series Title: Research report (North Florida Research and Education Center (Quincy, Fla.))
Physical Description: 23 pages : ill. ; 28 cm.
Language: English
Creator: Teare, I. D ( Iwan Dale ), 1931-
North Florida Research and Education Center (Quincy, Fla.)
Publisher: North Florida Experiment Station
Place of Publication: Quincy Fla
Publication Date: 1991
Subject: Soybean -- Effect of pesticides on   ( lcsh )
Defoliation   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
Bibliography: Includes bibliographical references.
Statement of Responsibility: I.D. Teare ... et al..
General Note: Cover title.
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Bibliographic ID: UF00066090
Volume ID: VID00001
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 71154433

Full Text

Investigation of Soybean Stress from Defoliating Pests:
Southern Region

I. D. Teare, J. E. Funderburk, L. G. Higley, A. J. Mueller, and T. P. Mack

Central Science

APRp12 1931

North Florida Res. and Educ. Ctr., Univ. of Fla., Quincy, Fla. 32351; Univ. of
Nebraska, Lincoln, NE 68583; Dept. of Entomol., Univ. of Arkansas,
Fayetteville, AR 72701; Dept. of Zoology, Univ. of Alabama, Auburn Univ.,
Auburn Univ, AL 36849. -R~eitch-NF-'91Z-2.J

L 1

~ 3 dr~t




Defoliation by insect pests is a major stress of soybean in the Southern
Region. Quantifying physiological responses of soybean to defoliation is
essential for understanding how insect defoliation reduces soybean yields.
Indeed, defoliators comprise the most abundant and diverse guild of insects
that attack soybean in the U. S. (Turnipseed and Kogan 1976). Understanding
the relationship between defoliation and plant responses, such as yield is
essential for better pest management.
Researchers have long recognized the importance of defoliating pests to
soybean, and over the past 40 years more than 50 research articles have
addressed soybean defoliation (Ostlie 1984). However, despite this volume of
research, long standing questions regarding defoliation on soybean persists.
Often results from different studies do not agree, possibly because of
differences in environment or methodology. For example, hail simulation
studies, with injury imposed on a single day, clearly do not simulate injury
by defoliating insects (Ostlie 1984). But even where actual insects or
appropriate simulation techniques are used, reported relationships between
defoliation by insects and yield vary greatly (Ostlie 1984). Nor are soybean
compensatory responses to defoliation well documented. Fundamentally, no
clear understanding of the physiological effects of defoliation on soybean has
yet emerged.
Research on simulation techniques has established requirements for
simulating insect defoliation (Ostlie 1984). So it is possible to precisely
imposed and quantify injury while avoiding confounding effects associated with
some other techniques. Simulated injury can be easily related to insect
numbers for a variety of defoliating species. New instrumentation, such as
leaf area meters, line quantum sensors, and portable photosynthesis meters,
allow precise, rapid measurements of important physiological parameters.
Previous research often examined percent defoliation, however, 50%
defoliation of a large soybean canopy is unlikely to produce the same response
as 50% defoliation of a small canopy. We believe the light interception
hypothesis (that the principal physiological effect of defoliation is to
reduce light interception by soybean canopies) may account for much of the
variability between defoliation and yield losses reported in the literature.
Further, this hypothesis may provide a model for defoliation effects in many
systems, not only soybean. Aspects of this hypothesis have been previously
proposed by some researchers (Johnson 1987, Waggoner and Berger 1987), but it
has not been tested as we propose. One previous study (Ingram et al. 1981)
did include light interception effects of defoliation, but this was peripheral
to the major direction of the study and cannot be used to test the light
interception hypothesis. In our previous research we observed that over 80%
of the variability in yield from defoliation could be explained by differences
in light interception. Consequently, we are optimistic that this hypothesis
may provide a powerful model for understanding how insect defoliation impacts
Even if the light interception hypothesis is correct, it would be naive to
think that defoliation does not influence other plant parameters. Therefore,
the proposed study will examine a variety of additional responses besides
light interception. Growth and yield parameters, and compensatory mechanisms
all will be considered. For example, our previous research demonstrated that
compensation to defoliation occurs through delayed leaf senescence and altered
leaf photosynthesis rates. This array of compensatory responses have not been
previously reported from soybean.
Among the significant scientific benefits of this research is establishing
a physiological model for soybean defoliation that also may be applicable to

other crops. Compensatory responses to defoliation are not well documented or
understood (particularly photosynthetic responses); therefore, this study
would significantly advance our knowledge of plant compensation to
defoliation. Ultimately, a better understanding of compensatory mechanisms
may open up new avenues for work in plant breeding and genetic engineering to
reduce the impact of plant pests.
The practical consequences of this situation are that calculated economic
injury levels (EILs) and economic thresholds (ETs) for soybean pests differ
widely among insects and across states. It seems unlikely that
defoliation/soybean response relationships are really as variable as existing
thresholds suggest. Rather, these thresholds probably reflect our present
uncertainty in how defoliation physiologically impacts soybean. Consequently,
to some degree our existing thresholds are suspect. Moreover, the lack of
more definitive understandings of how soybeans response to defoliation
impedes the implementation of more advanced decision tools, such as multiple
species EILs (Hutchins et al. 1988, Pegido et al. 1989). This latter
limitation is especially important in the south where soybean defoliators
usually occur as a complex of species.
In 1988, four participating states (Florida, Iowa, Nebraska, and Ohio)
began a limited two year study focusing on physiological effects of insect
defoliation to soybean. For the first time, common experimental procedures
and methodologists were employed in different states allowing direct
comparisons. Moreover, whereas many previous studies had related percent
defoliation to subsequent yield loss, this investigation tried to use more
physiologically meaningful evaluations. Although this research will be
valuable in producing more accurate economic thresholds for some defoliating
insects, only defoliation at reproductive stage R3 was examined, so the
practical uses of the research are somewhat limited.
Other major practical benefits of this research will be precise yield loss
relationships necessary for calculating ETs and EILs. Additionally,
information from this study will be crucial for more accurately characterizing
defoliation in plant growth simulation models. Finally, our results will
allow the calculation of multiple species EILs for all major defoliating
insects of soybean. Consequently, this research can produce well-established,
state-of-the-art decision tools needed for soybean pest management.
The objectives of this study are to: 1) To characterise effects of
simulated insect defoliation on soybean physiology, 2) To determine how yield
responses to defoliation can be explained by reductions in canopy light
interception (through reductions in leaf area below the critical leaf area
index), 3) To determine how response to defoliation at different reproductive
stages differ, how responses to sequential defoliation at two stages differ
from defoliation at a single stage, and how responses to simulated insect
defoliation (through time) differ from responses to defoliation on one day,
4) To characterize mechanisms of soybean compensation to defoliation, partic-
ularly delayed leaf senescence and altered leaf photosynthesis, 5) To compare
responses at different sites (states) and responses to determinate and
indeterminate soybean growth habits (if the study is conducted nationally), 6)
To describe defoliation/yield loss relationships for calculating single and
multiple species EILs for defoliating insect pests of soybean.

Soybean were grown on a Norfolk loamy sand (fine, loamy, siliceous thermic
typic Kandiudult) with a pH of 5.5 and 1.5 percent organic matter in 1990 at
the North Fla. Res. and Educ. Ctr. at Quincy, FL.
The experimental area was bottom plowed 3 May 1990 and fertilized at a
rate of 15# N/acre, 45# P/acre and 90# K/acre on 20 May 1990. Weed control
consisted of a preplant treatment of Treflan 4E at 0.75 Ib Ai/acre on 17 May
1990, postemergence treatment of Classic at 0.5 oz Ai/acre plus Tackle at 0.5
lb Ai/acre on 25 June 1990, and a cultivation with a rolling cultivator on 2
July 1990.
A 2-row cone planter was used to plant Braxton soybean in eight row plots
7 meters long and with 30 cm between rows at a rate of 26 seeds per row-m on
11 June 1990. Row orientation is north-south. Final soybean plant density
will be 25 plants/row-m (soybean may be over-planted and thinned to provide
uniform plant spacing). Soybean cultivar used was Braxton in southern states.
Insecticides used were Dimilin at 0.5 oz Ai/acre plus Dipel at 1 Ib/acre
on 9 Sept 90; Dimilin at 0.5 oz Ai/acre plus Assini at 0.025 oz Ai/acre on 16
Oct 90.
The experimental design for\'soil treatments and for yield was a randomized
complete block containing four replications. Yield estimates each year were
determined for all 11 defoliation treatments. The effects of defoliation
treatments on soybean yield, light interception and photosynthesis were
evaluated by using ANOVA, subsequent treatment comparisons, and regression.
Treatments consist of 4 defoliation patterns (simulated insect defoliation
at stage R2, R4, R2R4, three levels within each pattern (defoliation to
produce a leaf area index of 3.5, 2.5, and 1.5 at late R4), and an
undefoliated check. Defoliation levels will be chosen based on the measured
leaf area index (LAI) at late Rl/early R2 and the projected LAI at R4 based on
the R4 measurement. Defoliation levels will be chosen to provide final LAIs
after defoliation (R4) that include values above, at, and below the critical
LAI (the LAI value at which 95% of incident light is intercepted by a plant
canopy, estimated to be ca. 3.5 for soybean). Consequently, specific levels
of defoliation may vary between locations, but all locations will provide
defoliation treatments that span the critical LAI. Soybean will be defoliated
by leaflet, and leaf areas of all leaflets removed will be measured.
Defoliation will be limited to the upper two thirds of the canopy, but may
extend into the lower canopy if necessary for high defoliation levels. The
center 4 row-m of the two middle rows will be defoliated. Undefoliated plots
will receive comparable handling (walking in plots and "fondling" plants) as
defoliated plots (to allow for compaction during defoliation and affects of
touching plants). Areas adjacent to the defoliated region (border rows and
ends of plots) will be sham defoliated (stripping leaflets without quantifying
area removed) to approximately the same level as the defoliated area. Border
areas should be sham defoliated during the last 8 days of the simulation (when
most of the defoliation is occurring), specifically on days 8 and 12.
Treatments will be color coded with stakes or wood lath and flags to minimize
potential errors in leaf picking.
Target LAI's (3.5, 2.5, and 1.5) were chosen to provide discrete
reductions in light interception based a critical LAI of ca. 3.5. The
undefoliated check will provide a treatment above the critical LAI. Because
the defoliation levels depend on these target LAIs at late R4, an estimate of
the R4 LAI is needed. The LAI at R4 is likely to be 1-2 units greater than
the LAI at late Rl/early R2 (when defoliation is initiated for certain
treatments); therefore, the LAI at R4 will be approximately by the measured
LAI at late Rl/early R2 + 2. Treatments will be imposed by removing a given

amount of leaf area (leaflets) based on the difference in projected LAIs and
the target LAIs. For the R2+4 sequential defoliation treatments, the total
leaf area to be removed will be calculated and half removed at R2 and half
removed at R4 (so that total leaf area removed is the same as in the R2 and R4
treatments). The amount of leaf area removed is likely to differ between
states; however, the resulting treatments (LAI levels and corresponding levels
of light interception) will be comparable. For comparison, the percent
defoliation per treatment to achieve the target LAI can be calculated from the
[(projected LAI target LAI)/projected LAI]*100

Defoliation will be imposed to approximate insect injury. Ideally, daily
injury rates and duration should be based on temperature driven consumption
and development models. However, because temperature driven models would
result in substantial differences in injury rates among locations, standard
durations and injury rates will be employed at all sites. Many soybean
defoliators have larval development times for the latter developmental stages
(when >90% of consumption occurs) of approximately two weeks, at temperatures
commonly occurring in mid to late summer. Consequently, defoliation will be
imposed over 12 days (possibly, Monday of week 1 to Friday of week 2).
Defoliation will occur at soybean stages R2 and R4 (depending on treatment)
which corresponds with the injury phenology for may soybean defoliators.
Daily defoliation rates depend on stage specific consumption rates. In
brief, to simulate insect feeding we need to estimate what proportion of the
total defoliation required should occur on each day. The rationale behind the
values chosen is as follows. For this study, two aspects of development and
consumption are pertinent. First, proportion of total larval consumption in a
stage, and second, duration of developmental time in a stage. To determine
the proportion of the total defoliation that should occur in each larval
stage, an estimate of proportion of total consumption by stage is needed.
Published data on this question indicate that the proportion of total
consumption by instars are: GCW 1-2=2%, 3-4=8%, 5-6=90% (Hammond et al.,
1979b); SBL 1-2=1%, 3-4=9%, 5-6=90% (Boldt et al., 1975); and VBC 1-2=3%,
304=5%, 5-6=92% (Boldt et al., 1975). Because so little defoliation occurs in
the first two larval stages (<3%), for this study we will consider defoliation
only during the latter stages. Specifically, we estimate the proportion of
defoliation by stage as 3-4=10%, and 5-6=90%. The second question is duration
of development time in a stage. Literature data on green cloverworm (GCW),
corn earworm (CEW), soybean looper (SBL), and velvetbean caterpillar (VBC)
were used to determine appropriate values for this study. The proportion of
time spent in various instars ae: GCW 1-2=29%, 3-4=26%, 5-6=45% (Hammond et
al., 1979a); SBL 1-2=26%, 3-4=31%, 5-6=43% (Boldt et al., 1975); and CEW
1-2=23%, 3-4=25%, 5-6=52% (Boldt et al., (1975). Based on these values, an
appropriate estimate of time spent in each stage is 1-2=25%, 3-4=25%, and
5-6=50%. We will estimate development through stages 3-6 as requiring 12
days. Therefore, the ratio of development times (25%:50% or 1:2) gives the
number of days spent in each stage; specifically, stages 3-4=4 days and stages
5-6=8 days. Consequently, to provide an appropriate simulation of a
lepidopteran defoliator of soybean (combining consumption and development
data), we will impose injury over 12 days with 2.5% of the total defoliation
occurring on each of the first 4 days and 11.25% occurring on each of the last
8 days. Although designed to simulate lepidopteran defoliation patterns, this
simulation also is suitable for other species (such as bean leaf beetle and
grasshoppers). For adult defoliating insect (like beetles) the increasing
defoliation rates simulate an increasing pest population rather than
increasing consumption per individual pest.

All calculations of total leaf area to be removed, of % of this total leaf
area to be removed each day per plot, of the conversion of leaf area to be
removed to leaflets to be removed, and of defoliation summaries are provided
by a computer program, DEFOL (written by L. G. Higley for this project). To
adjust for possible discrepanices between projected and actual leaf area
removed, all leaf area removed/plot/day must be quantified and entered into
the program to allow for daily adjustments. The program will output leaf
areas and numbers of leaflets to be removed for each plot on each day. Leaf
area to be removed is based on target defoliation levels, appropriate injury
rate, and previously removed leaf area. Leaflets to be removed are calculated
from leaf area to be removed and a user-supplied estimate of average leaflet
size on the first day. Subsequently, the program calculates the average
leaflet size based on number of leaflets removed and measured leaf areas.
Because the defoliation levels are based on projected LAIs at R4, it is
important to have an idea of actual LAIs during defoliation so that
adjustments can be made if the projections are greatly in error. Measures of
plant leaf area will be available from plant samples taken immediately before
the defoliation period, which provide a measure of the actual LAIs. (To
convert a mean plant leaf area into an LAI for 76 cm rows and 25 plants/row-m,
multiply the plant leaf area (in cm ) by 0.00329). Records of total leaf area
actually removed (by plot) will be maintained to calculate actual defoliation
at end of the defoliation period.
Light interception will be measured in the plant canopy weekly from R3 to
R6 to include measures at each reproductive stage. A line quantum sensor, 76
cm long, will be centered across the row and a measure of photosynthetically
active radiation (PAR) will be obtained. Measurement will be made for each of
the two center rows of each plot. Additionally, a measurement will be made
outside the plots, in full sun, for each block, to indicate PAR with 0% light
interception. All measurements will be taken within one hour of solar noon.
Individual plant samples (for growth analysis) will be taken at ca. weekly
intervals at R2, R3, R4, R5, and R6. For each sample date 3 plants/plot will
be removed, using a stratified random sampling procedure. Plants will be
bagged, labeled by treatment/block, and returned to the laboratory for
measurements. Immediately prior to defoliation at R2, plants will be randomly
selected from any of the 1.5 m areas on either end of the two center rows. On
all other dates plants will be selected randomly from any of the 1 m sections
at the end the 4 m defoliated regions of the two center rows. Once a section
is sampled additional samples will not be taken from the same region, and the
center 2 m of the 2 center rows will not be sampled for growth analysis. The
R3 sample will be taken immediately after R2 defoliation and the R5 sample
immediately after the R4 defoliation. At harvest, individual plant samples (3
plants/ plot) will be taken from the center 2 m of the middle 2 rows. After
individual plant samples are obtained, all remaining plants in the defoliated,
4 m, middle two rows will be harvested to provide plot yield. The appropriate
sampling pattern is indicated below (note that sections B and C are the
defoliated areas):

Individual Plant Growth Samples R2 section A; R3, R4, R5, R6 section B1-B4
Individual Plant Yield Samples section C; Plot Yield section B & C

- A (1.5 m) -:- B1 (1 m) -:- C (2 m) -:- B2 (1 m) -:- A (1.5 m) --
- A (1.5 m) -:- B3 (1 m) -:- C (2 m) -:- B4 (1 m) -:- A (1.5 m) -

Variable measured for growth analysis are: height (measure from
cotyledonary node), vegetative stage, reproductive stage, branches, nodes,
lowest leaf-bearing node (cotyledonary node=l, unifoliolate node = 2, etc),
leaves, flowers, pods, leaf area, leaf dry weight, support (stem and petiole)
dry weight, and pod dry weight.
Variables measured for yield analysis (individual plant yield) are: 0
seeded pods, 1 seeded pods, 2 seeded pods, 3 seeded pods, 4 seeded pods, pod
dry weight (with seeds), seed dry weight, and support (stem) dry weight.
Variables measured for plot yield are yield and percent moisture.
Insecticide (Bacillus thuringiensis or other) will be applied as needed to
avoid confounding with natural insect injury. Fungicide benomyll or other)
will be applied at recommended rates at ca. R1 to avoid confounding effects of
disease, if necessary. As much'as possible only minimal pesticide application
will be made to avoid confounding effects.
Additional data to be maintained include agronomic practices herbicide
treatments, tillage, fungicides; soil factors soil type, soil pH, % organic
matter; weather data daily maximum and minimum temperatures, daily rainfall;
and important dates planting date, emergence date (80% emergence), sampling
dates for growth, light, individual yield, and plot yield. Other data may be
collected as necessary or indicated.
In specific states (Arkansas and Florida in the south, Iowa and Nebraska
in the north, and others if equipment can be located) photosynthesis measures
will be taken weekly, from R1, to examine the soybean compensation to
defoliation through altered leaf photosynthesis. Leaflets at ca. nodes 6, 9,
and 12 will be marked, and photosynthetic rates monitored before, during, and
after defoliation. Leaflets on at least two plants per plot will be measured.
Measurements will be made in full sunlight at comparable times for each
Individual investigators are encouraged to conduct their own data analysis
as desired, however, data analysis by and across locations will be conducted
at Florida. For the national study data will be collated and analyzed at
Nebraska. Analysis will include calculation of variables for classical growth
analysis and for yield component analysis. Statistical procedures used will
include analysis of variance and regression techniques. All data were
subjected to analysis of variance. When the F test was significant, multiple
range tests were applied.


. . . . . . . ........




111IiltI I







0 I'

223 233 243 253 263
August September

I >



i I I 1 1 1 I IL' i f I l l li i l l f i i l li f f i i li f t il i f i

October November

1. Rainfall (inches) and soybean phenological stages during the soybean
growing season in relation to Julian days (June thru Oct), 1990.


I.. ill I I I

1.I ......


.. .. --. -- 1* ''I M* -- 1--



Weather must be discussed in relation to defoliation results for 1990 at

Quincy FL. The summer of 1990 was one of the driest on record. The average

rainfall for the soybean growing of the previous 10 year period was 26 inches

compared to 12 inches for 1990. Soybean were definitely stressed during this

period, particularly from the R4 to R6 stage (Fig. 1).

Soybean Physiological Stage
R2 R3 R4 R5 R6
Defoliation Defoliation




0 I I I I I I I I
215 220 225 230 235 240 245 250 255 260 265 270
2. Soybean stomatal resistance (SR) in relation to defoliation period [R2
(top) and R4 (bottom), drought (fig. 1), date, and soybean physiological
stage. Top = R2, Bottom = R4; Defoliation level: Control = ---, 3.5
= ----, 2.5 --i-, 1.5 = -.

The quantitative effect of drought on soybean in relation to defolation

period is shown as a function of stomatal resistance (RS) in Fig. 2. Stomatal

resistances were statistically significant for defoliation treatments (F=2.57;

df=7,21; P<0.05).


Seed weight was highly correlated with pod weight (R2=0.997) in relation

to defoliation treatment. Defoliation Intensity is ranked in relation to seed

weight in fig. 3 to order the integrated effect of defoliation treatments

[defoliation intensity = (f) LAI, soybean physiological stage, duration]. We

can't explain the significance between the two controls but the first check is

not significantly different from R2-3.5, R4-3.5, R2R4-3.5 as would be expected

if LAI 3.5 is truly the critical LAI.




ck ck R2R4 R4 R4 R2 R2 R2
3.5 2.5 3.5 3.5 2.5 1.5
Defoliation Intensity

3. Seed weight per soybean plant in relation to yield for
intensity of defoliation treatments.

R4 R2R4 R2R4
1.5 2.5 1.5

ranking defoliation

CO 18
< 16

- 14

CJ 12

ck .ck R2R4 R4 R4 R2 R2 R2
3.5 2.5 3.5 3.5 2.5 1.5
Defoliation Intensity

4. Mean number of pods with one, two and three
defoliation intensity and total number of pods per

R4 R2R4 R2R4
1.5 2.5 1.5

seeds in relation to


ck ck R2R4

R4 R2 R2 R2
3.5 3.5 2.5 1.5

Defoliation. Intensity

5. Mean number of pods with zero seeds in relation to defoliation intensity.

R4 R2R4
1.5 2.5


--..~ ~-. .. -....- ....l` .-~r.~:.r-.;. -.l.i' i .. ;.

Ranking the LAI intensity [LAI intensity = (f) LAI, soybean physiological

stage, and duration] in relation to seed yield for each soybean physiological

stage where defoliation occurred should indicate the severity of defoliation

treatments (R2, R4, R2R4) to soybean yield. R2 ranking of LAI intensity is

3.5=2.5=1.5, R4 ranking is 2.5=3.5>1.5, and R2R4 is 3.5>2.5=1.5; where > and

= shows significance and nonsignificance, respectively, at the 5% level of


Seed weight was less highly correlated with stem weight (R2=0.702) at the

more severe defoliation intensities (based on ranking in relation to seed

weight). The stem weights of the three most severe defoliation intensities

(R4-1.5, R2R4-1.5, R2-1.5) increased in contrast to a reduction in seed weight

(data not shown).


Number of one, two and three seeded pods/plant are shown in fig. 4 in

relation to defoliation intensity. Total number of seeds/plant was most

closely related to number of two seeded pods (R2=0.922). Total number of

seeds/plant was less affected by one seeded pods/plant (R2=0.437) and three

seeded pods/plant (R2=0.727). The number of pods with zero seed (fig. 5) are

of less interest, but controls had significantly more pods with zero seed than

all the defoliation treatments, which seems to indicate that limited

defoliation to the critical LAI promotes pod abortion in stressed soybean.


Defoliation at R2 seemed to increase photosynthesis (fig 6, top).

Photosynthesis was greatest for 1.5>2.5>3.5
Defoliation at R4 reduced photosynthesis of defoliation treatments below

the controls (fig. 3, bottom) on Julian day 236. For that day, photosynthesis

was greatest for the control>2.5>3.5=1.5


Soybean Physiological Stage
R2 'R3 R4 R5 R6

Defoliation Defoliation

SI i I I I I I 1


220 225 230 235 240 245 250

255 260 265


7. Soybean photosynthesis (u mol m-2 s-1) in relation to defoliation period
[R2 (top) and R4 (bottom)], drought (fig. 1), date, and soybean
physiological stage. Defoliation level: Control = --, 3.5 = -----, 2.5
= -v-, 1.5 --.















~. ~..:'.-; ~~
:- ...-... ........-.....' :-: ..~ .... ;... i: ... 'I'~"'."'~.- 1;.I`-

Following drought at Julian day 247, photosynthesis for R4 defolation was

greatest for 1.5>3.5>2.5>control. Photosynthesis for R2 defoliation on Julian

day 247 was similar, 1.5>2.5=3.5>control.


Defoliation treatments reduced the PIPAR absorbed by the soybean canopy

(fig. 7). Even with drought Between R4 and R6, soybean plants increased leaf

area after defoliation between R4 and R5 and increased PIPAR by canopy.

,..,.......... ...--, ...... -. e ,-. . -~. -:- :;.;.-. .~ :

Soybean Physiological Stage
R2 R3 R4 R5


CO 0.6

0 I I I I I I
215 220 225 230 235 240 245 250 255 260. 265 270
6. Proportion of intercepted photo-active-radiation (PIPAR) by soybean when
defoliated at R2 (top), R2+4 (middle), and R4 (bottom) in relation to
Julian days and physiological stage of growth. Defoliation level: Control
= --, 3.5 = ---, 2.5 = -X--, 1.5 = -0-.


Our thanks to E. Brown, Agric. Tech. IV; North Fla. Res. and Educ. Ctr.,
Univ. of Fla., Quincy FL; for data collection, computer processing, and data

Boldt, P. E., K. D. Biever, and C. M. Ignoffo.
soybean: consumption of soybean foliage and
Econ. Entomol. 68:480-482.

1975. Lepidopteran pests of
pods and development time. J.

Hammond, R. B., L. P. Pedigo, and F. L. Poston. 1979a. Green cloverworm leaf
consumption on greenhouse and filed soybean leaves and development of a
leaf-consumption model. J. Econ. Entomol. 72:714-717.

Hammond, R. B., F. L. Poston, and L. P. Pedigo. 1979b. Growth of the. green
cloverworm and a thermal-unit system for development. Environ. Entomol.

Hutchins, S. H., L. G. Higley, and L. P. Pedigo. 1988. Injury-equivalency as
a basis for developing multiple-species economic injury levels. J. Econ.
Entomol. 81:1-8.

Ingram, K. T., D. C. Herzog, K. J. Boote, J. W. Jones, and C. S. Barfield.
1981. Effects of defoliating pests on soybean canopy CO2 exchange and
reproductive growth. Crop Sci. 21:961-968.

Johnson, K. B.

1987. Defoliation, disease, and growth: a reply.

Ostlie, K. R. 1984. Soybean transpiration, vegetative morphology, and yield
requirements following simulated and actual insect defoliation. Ph.D.
dissertation. Iowa State University, Ames, IA.

Pedigo, L. P., L. G. Higley, and P. M. Davis. 1989. Concepts and advances in
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(ed.) Proc. World Soybean Res. Conf. IV. Vol. III.

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L.T. Evans (ed.) Crop Physiology, some case histories. Cambridge Univ.
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Turnipseed, S. G., and M. Kogan.
Entomol. 21:247-282.

1976. Soybean entomology.

Annu. Rev.

Waggoner, P. E., and R. D. Berger. 1987. Defoliation, disease, and growth.
Phytopathol. 77:393-398.






8 a




0 I I I I I I I I I I

ck ck R2R4

R4 R4 R2
2.5 3.5 3.5

R2 R2
2.5 1.5




R4 R2R4
1.5 2.5


0) 60
) 45


6 35

r- 30 X

J 25



6 5 x

0 0

'. '.P ~ B

I X( X X
1 1 I t t I t t

ck ck R2R4 R4 R4 R2 R2 R2 R4 R2R4 R2R4
3.5 2.5 3.5 3.5 2.5 1.5 1.5 2.5 1.5
-- Total Pods -e- 2 Seeded Pod --- 1 Seeded Pod -- 3 Seeded Pod








n i I I I I I


ck R2R4 R4 R4 R2 R2 R2 R4 R2R4 R2R4
3.5 2.5 3.5 3.5 2.5 1.5 1.5 2.5 1.5
Defoliation Intensity

' : -;.-.......i.. ..... -.--. ;i; ;- .; .~;: -' ~~-;~. .:--: ` ":-::_1 `-~;--



.-... --.--;- -;--

. . . . . ` ..: .





CL: 12
CY) ab
6 bb



o I
ck ck R2R4 R4 R4 R2 R2 R2 R4 R2R4 R2R4
3.5 2.5 3.5 3.5 2.5 1.5 1.5 2.5 1.5
Defoliation Intensity

CO 50


C 25

0C 15

6 5

i l l l l ) l l ( l
I I I I I I 1

ck ck R2R4 R4 R4 R2 R2 R2 R4 R2R4 R2R4
3.5 2.5 3.5 3.5 2.5 1.5 1.5 2.5 1.5

-.- Total Pods -+- 2 Seeded Pod -x- 1 Seeded Pod -- 3 Seeded Pod







ck ck R2R4 R4 R4 R2 R2 R2 R4 R2R4 R2R4
3.5 2.5 3.5 3.5 2.5 1.5 1.5 2.5 1.5
Defoliation Intensity

. . . .,.. .

Soybean Physiological Stage
R2 R3 R4 R5 R6
Defoliation Defoliation




E 0
I 0 i i i
E 215 220 225 230 235 240 245 250 255 260 265 270 275 280 285

E CK -+- R2 3.5 R2 2.5 --R2 1.5
0. 5 Defoliation Defoliation





0 I I I I
215 220 225 230 235 240 245 250 255 260 265 270 275 280 285

CK -IR4 3.5 -*-R4 2.5 ---R4 1.5

'"' ~ "'

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