Group Title: Research paper (North Florida Research and Education Center (Quincy, Fla.))
Title: Investigation of soybean stress from defoliating pests
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 Material Information
Title: Investigation of soybean stress from defoliating pests
Series Title: Research paper (North Florida Research and Education Center (Quincy, Fla.))
Physical Description: 15 pages : ill. ; 28 cm.
Language: English
Creator: Teare, I. D ( Iwan Dale ), 1931-
Funderburk, J. E ( Joseph E. ), 1954-
Higley, Leon G
North Florida Research and Education Center (Quincy, Fla.)
Publisher: North Florida Research and Education Center
Place of Publication: Quincy Fla
Publication Date: 1992
Subject: Soybean -- Effect of pesticides on   ( lcsh )
Soybean -- Florida   ( lcsh )
Defoliation   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
Bibliography: Includes bibliographical reference (p. 15).
Statement of Responsibility: I.D. Teare, J.E. Funderburk, and L.G. Higley.
General Note: Cover title.
 Record Information
Bibliographic ID: UF00066095
Volume ID: VID00001
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 71171791

Full Text


Investigation of Soybean Stress from Defoliating Pests:

I. D. Teare, J. E. Funderburk, and L. G. Higley

Central Science
DEC 2 8 19S2

University of Florida

North Florida Res. and
Nebraska, Lincoln, NE

Educ. Ctr., Univ. of Fla., Quincy,, Fla.
68583. Research NF-92-2.

32351; Univ. of


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 understanding of

the physiological effects of defoliation on soybean has yet emerged.

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.

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, Pedigo et al. 1989). This latter limitation is especially

important in the south where soybean defoliators usually occur as a complex of

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

soybeans. Consequently, this research can produce well-established, state-of-

the-art decision tools needed for soybean pest management.

The objectives of this study are: 1) To characterize 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, particularly 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 Kandidult) 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 lb 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


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 2 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

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. 305

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-mm 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 stages 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 formula:

[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 many 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%, 3-4=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 are: GCW 1-

2=29%, 3-4=26%, 5-6=45% (Hammond 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=5-%. 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 discrepancies 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 cm2) 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, 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) --:-- BI (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, unifoliate 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 RI, 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 measurement.

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.



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).

The 1991 rainfall for the soybean growing season was 28 inches. Rainfall

distribution was heavy in the early part of the season, but was dry during the

R5 and R6 reproductive stage (Fig. 1).

The quantitative effect of drought on soybean in relation to defoliation

period is shown as a function of 1990 stomatal resistance (RS) in Fig. 2).

Stomatal resistances were statistically significant for defoliation treatments

(F=2.57; df=7,21; P<0.05). Stomatal resistances (RS) were significantly

different in 1991. Defoliation at the R2 stage resulted in RS differences at the

R5 sampling date and defoliation at the R4 stage resulted in RS differences at

the R4 and R5 stage.


Seed weight in 1990 was highly correlated with pod weight (R2 = 0.997) in

relation to defoliation treatment. Defoliation intensity is ranked in relation

to 1990 seed weight in Fig. 3 to order the integrated effect of defoliation

treatments [defoliation intensity = () LAI, soybean physiological stage,

duration] for that year. One check was 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. The

1991 defoliation intensity needs to be reordered in relation to 1991 seed weight.

The 1991 data seems to follow original hypothesis and 1990 and 1991


- -

SC0 -
So4 o T O C
". c. .

., ., i .....,A J .. e., A ,,, ,, ....J l J ,,,.,J ,,,,. .,,,,t,, ,,...,,,,..,,,,

145 155 165 175 185 195 205 215 225 235 245 255 265



275 285 295 305 315 325


* I .,i I


i .1ii,

. I I .

155 165 175 185 195 205 215 225 235 245 255 265 275

285 295 305 315 325

Fig. 1. Rainfall (inches) and soybean
phenological stages during the soybean
growing season in relation to Julian days
(June thru Oct); 1990, 1991.

Mm ..ltMlll i.l mtffm^WTWTm rr. .r ..m-nTrrr.M . n iii ..... ....

Soybean Physiological Stage


8 ---


2- -.
4 .-. ...

2 t -- i

215 220 225 230 235 240 245 250 255

260 265 270

1.2 -

0.9 --

0.6 ----- --

0.3 --- -

210 215 220 225 230 236 240 245 250 255 260 265

Fig. 2. Soybean stomatal resistance (SR) in
relation to defoliation period [R2 (top)
and R4 (bottom)], drought (fig.l), date,
and soybean physiological stage. Top =
R2, Bottom = R4; Defoliation level:
Control = *, 3.5 = +, 2.5 = *, 1.5 = D.
Left = 1990 and right = 1991.

illustrations need to be reordered in relation to 1991. Note the 1991 R2

defoliation intensities order themselves correctly and are the least affected by


Ranking the LAI intensity [LAI intensity = () 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 1990 LAI intensity was

3.5=2.5=1.5, R4 ranking was 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 for 1990 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 for 1990 and 1991 are shown

in Fig. 4. In 1990 and 1991, total number of seeds/plant was most closely

related to number of two seeded pods. Total number of seeds/plant was less

affected by one seeded pods/plant and three seeded pods/plant. The number of

pods with zero seed (Fig. 5) are of less interest. The controls in 1990 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. The 1991 need to be reordered the same as in Fig.

3, but R4-2.5, R4-1.5, and R2R4-1.5 had significantly more 0-seeded pods.


be b bed

Scdf cddef

e f

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


abc abe

bec be c
^'"~ ^^ C

ck ck R2' R2R4 R2 R2 R2R4 R2R4 R4 R4 R4
3.5 .3.5 2.5' 1.5 2.5 1.5 3.5 1.5 2.5

Defoliation Intensity

Fig. 3. Seed weight per soybean plant in relation
to yield for ranking defoliation
intensity of defoliation treatments.
Left = 1990 and right = 1991. Note
magnitude increase for y axis in 1991.




-X- 1 Seed Pod (gr)

50--2__ "Z..Seed. Pod-(g)--
S04- 3 Seed Pod (gr)

4 -




R2 -R2R4 R2 R2 R2R4 R2R4. R4 R4 R4 ck ck R2 R2R4 "R2 R2 R2R4 R2R4 R4 R4 R4
3.5 3.5 2.5 1.5 2.5 1.5 3.5 1.5 2.5 3.5 3.5 2.5 1.5 2.5 1.5 3.5 1.5 2.5

Defoliation Intensity

Fig. 4. Mean number of pods with one, two and
three seeds in relation to defoliation
intensity and total number of pods per
plant. Left = 1990 and right = 1991.
Note magnitude increase for y axis in


0 I I
ck Ck R2 R2R4 R2 R2 R2R4 R2R4 R4 R4 R4
3.5 3.5 2.5 1.5 2.5 1.5 3.5 1.5 2.5

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

Defoliation Intensity

Fig. 5. Mean number of pods with zero seeds in
relation to defoliation intensity. Left
= 1990 and right = 1991. Note magnitude
increase for y axis in 1991.

ck ck


Defoliation treatments reduced the PIPAR absorbed by the soybean canopy

(Fig. 6). Even with drought between R4 and R6, soybean plants increased leaf

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

Defoliation treatment in 1991 for R2-R4 and R4 defoliation reduced PIRAR

after defoliation at the R5 and R6 stage.


Defoliation in 1990 at R2 seemed to increase photosynthesis (Fig. 7, top).

Photosynthesis was greatest for 1.5>2.5>3.5
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. Following drought at Julian day 247, photosynthesis for R4

defoliation 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.

Photosynthesis in 1991 decreased with time when defoliated at the R2 stage

because of the high leaf area over time that covered the preselected

photosynthesis leaves. The R4 defoliation had some reduction in photosynthesis

after defoliation.

Soybean Physiological Stage

R2 R3 R4 R5 R6



0.9 ------

0.6 -.. .

0.3 -



g -- _..


20 ------- -- ---- i ---

215 220 225 230 235 240 245 250 255 260 265 270

.9 -


0 I I
205 210 215 220 225 230 235 240 245 260 255 260 265 270

Fig. 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 = *, 1.5 = D. Left = 1990 and right
= 1991.

Defoliation Defoliation
1.2 -. -- -- ..

0.9 --- -- --

0.6 -

0.3 --. --.. .



R3 R4

R5 R6

0.4 -


0.8 -

0.4 ---


0.2 ------ -

Soybean Physiological Stage

R2 R3 R4 R6 R6


o o
a 25-

20 -- ......... .- --

I 1



U .
215 220 225 230 235 240 245 250 255 260 265 270





50 .- .. .. .- -
.0 ... ----4~-- -


210 215 220 225 230 235 240 245 250 255 260 265

Fig. 7. Soybean photosynthesis (I 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 = *, 1.5 = D. Left = 1990 and right
= 1991.


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. 1975. Lepidopteran pests of
soybean: consumption of soybean foliage and pods and development time. J.
Econ. Entomol. 68:480-482.

Hammond, R. B., L. P. Pedigo, and F. L. Poston. 1979a. Green cloverworm leaf
consumption on greenhouse and field 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
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