CSIRO PUBLISHING

Functional Plant Biology, 2009, 36, 874–879

www.publish.csiro.au/journals/fpb

3D monitoring spatio–temporal effects of herbicide
on a whole plant using combined range and chlorophyll a
ﬂuorescence imaging
Atsumi Konishi A,B, Akira Eguchi A, Fumiki Hosoi A and Kenji Omasa A,CA

Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1,
Bunkyo-ku, Tokyo 113-8657, Japan.
B
Present address: Marine Farm, Yanmar Co., Ltd, 3286 Itoharu, Musashi-machi, Kunisaki-city,
Oita 873-0421, Japan.
C
Corresponding author. Email: aomasa@mail.ecc.u-tokyo.ac.jp
This paper originates from a presentation at the 1st International Plant Phenomics Symposium,
Canberra, Australia, April 2009.

Abstract. Spatio–temporal effects of herbicide including 3-(3,4 dichlorophenyl)-1,1-dimethylurea (DCMU) on a wholemelon (Cucumis melo L.) plant were three-dimensionally monitored using combined range and chlorophyll a ﬂuorescenceimaging. The herbicide was treated to soil in a pot and the changes in chlorophyll a ﬂuorescence images of the plant were
captured over time. The time series of chlorophyll ﬂuorescence images were combined with 3D polygon model of the wholeplant taken by a high-resolution portable scanning lidar. From the produced 3D chlorophyll ﬂuorescence model, it wasobserved that the increase of chlorophyll ﬂuorescence appeared along veins of leaves and gradually expanded to mesophylls.
In addition, it was found by detailed analysis of the images that the invisible herbicide injury on the mature leaves occurredearlier and more severely than on the young and old leaves. The distance from veins, whole leaf area and leaf inclinationinﬂuenced the extent of the injury within the leaves. These results indicated difference in uptake of herbicide in the plant fromsoil depends on structural parameters of leaves and the microenvironments as well as leaf age. The ﬁndings showed that 3D
monitoring using combined range and chlorophyll a ﬂuorescence imaging can be utilised for understanding spatio-temporalchanges of herbicide effects on a whole plant.
Additional keywords: herbicide uptake, spatio-temporal change, three-dimensional imaging.

Introduction
Imaging techniques have been widely used for plant function
analysis from cells to whole plants (e.g. Omasa 1990; Govindjee
and Nedbal 2000; Häder 2000; Omasa et al. 2002; Jonesand Morison 2007). Two-dimensional (2D) imaging techniquessuch as multispectral and hyperspectral imaging, thermal imaging,and ﬂuorescence imaging allow non-destructive detection ofphotosynthesis, transpiration, stomatal response, and substancesin leaves. Digital imaging of chlorophyll ﬂuorescence quenchingis one of the leading methods used to assess photosynthetic
activities in leaves (e.g. Omasa et al. 1987; Daley et al. 1989;
Genty and Meyer 1995; Oxborough 2004) and at cellular levels(e.g. Oxborough and Baker 1997). Combined chlorophyll
ﬂuorescence and thermal imaging is useful for analysis ofrelationships between photochemical and non-photochemical
quenching and stomatal response (e.g. Chaerle et al. 2003;
Omasa and Takayama 2003).
Three-dimensional (3D) structure of plants has a great
inﬂuence on plant functioning and the microenvironments(Ross 1981; Jones 1983; Campbell and Norman 1989). For
 CSIRO 2009

example, leaf temperature and microenvironments such as
light intensity, air current, air temperature, humidity, and CO2
concentration differ three-dimensionally in each site surrounding/inside the leaves of a whole plant. The leaf position and distancefrom leaf veins affect water status and stomatal aperture.
Moreover, the stomata change size and aperture depending tocell age and physiological conditions in each leaf site.
Consequently, the ﬂuxes of water vapour and carbon dioxide(CO2) through the boundary layer and stomata vary with eachleaf site. And, it plays an important role in sustaining plant
functioning such as transpiration and photosynthesis.
Two-dimensional imaging techniques are useful for plant
function analysis. However, they are still not enough toinvestigate relationships between 3D structure and plant
functioning. Three-dimensional imaging of in situ leaves,tissues and cells improve our understanding of plant function
and response to environmental stimuli (Häder 2000; Schurr et al.
2006; Omasa et al. 2007). Concerning chlorophyll ﬂuorescenceimaging for photosynthesis analysis, 3D surface microscopy(Rolfe and Scholes 2002; Endo and Omasa 2007) and10.1071/FP09108

1445-4408/09/110874

3D imaging the effects of herbicide on a whole plant

Functional Plant Biology

confocal laser scanning microscopy (Omasa et al. 2009) havebeen developed. For whole plant analysis, we have recently
developed a new 3D imaging system, combining 3D range
lidar and chlorophyll ﬂuorescence imaging (Omasa et al.
2007). In present study, we have therefore applied this system
to 3D monitoring and analysis of spatio–temporal effects ofherbicide added to soil of a whole plant.
Materials and methods
Plant material
Melon (Cucumis melo L.) seedlings were grown in pots (10 cm
diameter, 10 cm high) in a growth chamber for ~4 weeks after
germination. The plants were illuminated for 12 h each daywith ﬂuorescent lights at photosynthesis photon ﬂux (PPF) of
200 mmol m–2 s–1. Air temperature was 26.5C during the day
and 24C at night. Relative humidity was 70% during the day
and 90% at night. The pots were ﬁlled with artiﬁcial soil
(mixture of vermiculite and perlite, 2 : 1, v/v). Plants werewatered daily with a nutrient solution (1 : 1000 dilution of
HYPONeX, HYPONeX Japan Corp., Japan).
Herbicide treatment
The herbicide Nekosogi-ace (Rainbow Chemical, Co., Ltd,
Japan), containing 6.0% 3-(3,4 dichlorophenyl)-1,1dimethylurea (DCMU) was used in the experiment. The
herbicide of 10 g L–1 (water solubility of DCMU at 25C is
0.18 mM) dissolved in water was treated to the plant soil in the(a)Portablescanning lidar

3D point cloud data875

pot before chlorophyll ﬂuorescence imaging. The concentration
was within normal use in the ﬁeld.
Combined range and chlorophyll ﬂuorescenceimaging system
Figure 1 shows (a) a combined range and (b) chlorophyll a
ﬂuorescence imaging system. In Fig. 1a, a high-resolution
portable scanning lidar (modiﬁed type of TDS-130 L, Pulstec
Industrial Co., Ltd, Japan) was used for the 3D range imaging of
a whole plant. The lidar is based on the light-probe method(trigonometry), and is able to obtain 3D point cloud range dataof the plant. The accuracy of range measurement was 0.5 mm at a
distance of 3.5 m. The spatial resolution was 1.7 mm to y-axis and1.2 mm to x-axis. In Fig. 1b, a metal halide lamp equipped with ashort pass heat absorbing ﬁlter (LS-M180, Sumita Optical Glass,Inc., Japan) was used as actinic light of the wavelength from
400 nm to 700 nm for photosynthesis. An actinic light illuminatedthe whole plant through ﬁbre optics and lens from above.
The optical ﬁbre exit is set as the whole plant can be
uniformly illuminated. PPFs on the lowest and highest leaves
were 130 and 160 mmol m–2 s–1, respectively. Chlorophyll a
ﬂuorescence images were captured at 640 horizontal  480
vertical pixels per ﬂame with 8-bit (0–255) resolution from theabove using a cooled charge-coupled device (CCD) camera(C5985, Hamamatsu Photonics, K.K., Japan) equipped with aband pass ﬁlter (MIF-W, central wavelength = 755 nm and halfband width = 8 nm, Optical Coatings Japan Co., Ltd, Japan) andanalysed by a computer.

(b)

Metal halide lampwith short pass filter
Cooled CCD camera withband pass filter

Exclusion of noises

Registration

Polygonisation
ComputerComputer
Herbicide-treatedplant

Herbicide-treatedplant
3D polygon model

Chlorophyll fluorescence image

Texture mapping

3D chlorophyll fluorescence modelFig. 1. (a) Combined range and (b) chlorophyll ﬂuorescence imaging system and diagrammatic illustration of procedures for 3D chlorophyll
ﬂuorescence modelling of a whole plant. Procedure (a) represents the method of 3D lidar imaging. Procedure (b) represents the method ofchlorophyll a ﬂuorescence imaging. The images taken by the procedures (a) and (b) are combined by the texture-mapping technique.

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Measurement and analysis of herbicide effects
After a whole plant was acclimated for 1 h under an actinic light,
the steady-state chlorophyll a ﬂuorescence image of all leaves ofthe plant was captured from one point above the plant (Fig. 1b).
Thereafter, Nekosogi-ace water solution including the particles
was poured into the soil around the roots in the pot. Chlorophyll a
ﬂuorescence images were intermittently captured at ~1/30 s every
hour during a 5-h period after the herbicide treatment. Natural
colour images were taken from different positions as JPEG
image of 1600 horizontal  1200 vertical pixels with a digital
camera (Power Shot Pro1, Canon, Japan) just after the ﬁnal
chlorophyll ﬂuorescence imaging. Spike-noises on thechlorophyll ﬂuorescence images were eliminated by a medianﬁlter with the mask size of 3  3. 3D point cloud range data of
the whole plant was measured with the lidar after the chlorophyll
ﬂuorescence measurements. The lidar measurements wereconducted from four measuring points surrounding the plant toconstruct a complex 3D range image of all leaves without
blind areas. The measurement time was a few minutes at eachmeasuring point. The lidar data obtained from different measuring
points were co-registered into the same orthogonal coordinates.
Thereafter, the point cloud data was converted into a trianglepolygon image after noise exclusion, thus 3D range surfaces ofleaves were expressed as irregular triangle meshes determineduniquely by arrangement of each point. Consequently, each leaf wascreated as a polygon shell in the 3D polygon model (3D range
image). Laplacian smoothing was used to smooth polygon meshes.
A sequence of chlorophyll ﬂuorescence images before
and after the herbicide treatment and natural colour images
taken after chlorophyll ﬂuorescence measurements were
mapped on the lidar-derived 3D polygon model of the wholeplant by a texture-mapping technique (Heckbert 1986). The
texture-mapping technique is widely applied as a method foradding surface texture to a computer-generated 3D polygon
model. Digital 2D images like natural colour and chlorophyll
ﬂuorescence images are useable as the texture surface. Throughthe correspondence of the coordinates of 2D image to 3D polygon
model, the information of 2D image is automatically mapped
onto each polygon shell of the 3D polygon model. An accurate
selection of the corresponding points between 2D and 3D images
is of great importance to produce the complex texture mapping
image of the plant. The corresponding points were then chosenfrom distinctive points on each leaf (e.g. the axils and edges).
Subsequently, accurate 3D natural colour and 3D chlorophyll
ﬂuorescence models were constructed.
Leaf area was automatically calculated by summating areas of
all polygons in each polygon shell, i.e. each leaf of 3D polygon
model. The percentage of injured area, in which the chlorophyll
ﬂuorescence intensity exceeded the maximum value at each leaf
site 1 h after the herbicide treatment, to whole area of each leaf wascalculated from 3D chlorophyll ﬂuorescence model. The meanvalue of leaf inclination and the standard deviation (s.d.) wereobtained from 3D polygon model by averaging the values of
50 polygons selected randomly on the whole leaf.
Results
Three-dimensional natural colour model of a potted melon plant
was produced by combining 2D natural colour images with aA. Konishi et al.

lidar-derived 3D polygon model. Different views of 3D natural
colour model were shown in Fig. 2. The leaves from ﬁrst (lowest)
to ﬁfth (highest) positions are indicated as numbers 1 to 5, inFig. 2a, b, respectively. Circles, squares and triangles marked on
the leaves in Fig. 2a, b correspond to the bases of each leaf. The
produced models allowed 3D observation of shape, colour andtexture of a whole plant from any points of view. All leaves
inclined from the base to the tip, and especially the ﬁrst and second
leaves, which were older and looked somewhat more yellow thanthe other leaves, had steep slants. The visible injury was notobserved in the 3D natural colour model at 5 h after the herbicide
treatment.
Changes in 3D chlorophyll ﬂuorescence intensity images froma 3D model view are shown in Fig. 3a–f, which correspond tobefore and at 1, 2, 3, 4 and 5 h after the herbicide treatment.
Chlorophyll ﬂuorescence intensity was uniformly distributed on
all the leaves before the herbicide treatment (Fig. 3a). After
herbicide treatment, increase in chlorophyll ﬂuorescenceintensity was observed slightly at the base of some leaves at
1 h (Fig. 3b). Increase in chlorophyll ﬂuorescence intensity was
also seen along main veins of leaves, except the ﬁfth leaf, at
2 h (Fig. 3c). Thereafter, the increase gradually expanded tomesophylls of all leaves (Fig. 3d–f ). The expansion was moresigniﬁcantly observed on the third and the fourth leaves than otherleaves (Fig. 3c–f ); however, it was least visible on the ﬁfth leaf, at
which the increase was hardly observed until 3 h after the
herbicide treatment (Fig. 3f ).
The earliest response site of chlorophyll ﬂuorescence intensity
is at the base of each leaf. Therefore, changes in chlorophyll
ﬂuorescence intensity were shown at leaf base sites marked inFig. 2 after the herbicide treatment (Fig. 4). Before herbicide
treatment, intensity of all sites was between 45 and 55 within
an intensity range of 0 to 255 (8 bit). Changes in chlorophyll
ﬂuorescence intensity gradually appeared at the sites on the ﬁrst
to fourth leaves after 1 h of treatment. The intensity increases atthe sites on third and fourth leaves were steeper than those at sites
on the ﬁrst and second leaves. The chlorophyll ﬂuorescenceintensity on third and fourth leaves reached around 160 at 5 h,while the ﬁrst and second leaves were ~110 at 5 h. The intensity on
the ﬁfth leaf did not signiﬁcantly change until 3 h, but increased
to 95 at 5 h.
Differences in leaf area, leaf inclination and percentage of
injured area to whole area of each leaf at 5 h after herbicide
treatment were obtained from the 3D chlorophyll ﬂuorescencemodel including the 3D polygon model (Fig. 5). The percentage
of injured area distributed from 20.6 to 85.9%. The injuries ofthird and fourth leaves were very large and the percentages were
85.9% and 82.6%, respectively. The percentages of other leaves
were below 50%, and especially those of the second and ﬁfth
leaves were 20.9% and 20.6%, respectively. The mean value of
inclination from ﬁrst to ﬁfth leaves were 42.4 (s.d. = 15.1), 50.3
(16.7), 28.2 (12.2), 34.9 (7.3) and 28.5 (11.4) in degree,
respectively. The ﬁrst and second leaves had large inclinationin comparison with the others. The leaf area ranged from 56 to
298 cm2. The leaf areas of ﬁrst, third and forth leaves were over
200 cm2 but those of the second and ﬁfth leaves were 127 cm2and
56 cm2, respectively. In particular, the ﬁfth leaf was extremely
small and immature. As shown in Fig. 6, there was a positive
linear correlation (R2 = 0.72, adjusted R2 = 0.63, P = 0.068 in

3D imaging the effects of herbicide on a whole plant(a)Functional Plant Biology

(b)

5

5

3
3

4
4

2

2
1
1

Fig. 2. Three-dimensional natural colour model of a melon (Cucumis
melo L.) plant constructed by mapping natural colour images taken at 5 hafter herbicide (Nekosogi-ace, including DCMU) treatment on the lidarderived 3D polygon model. (a) and (b) are 3D images from different view
points. The ﬁrst to ﬁfth leaves are indicated by the number 1 to 5. Open circle,
ﬁlled circle, open triangle, ﬁlled triangle and open square marked on theleaves represent bases of ﬁrst to ﬁfth leaves.

F-test) between leaf area and percentage of injured area. For
the relationship between leaf inclination and percentage of
injured area, the value of ﬁfth leaf were off from a negative
linear correlation (R2 = 0.94, adjusted R2 = 0.91, P = 0.031 in
F-test) among other leaves.
Discussion
A part of light energy absorbed by leaves is used forphotosynthetic electron transport, and the residual energy is

5

(a)

3

dissipated as heat and chlorophyll ﬂuorescence emissions(Govindjee 2004). Herbicides affect the photosynthetic
activities and leads to a change in the amount of dissipatedenergy. In the case of DCMU included in Nekosogi-ace, theeffect on leaves appears as an increase in steady-state chlorophyll
ﬂuorescence intensity, where the primary l electron receptor QAof photosystem II is not reoxidated and thus photosynthetic
electron transport is inhibited (Govindjee 2004). Therefore, theincrease in chlorophyll ﬂuorescence along the veins and the
expansion to mesophylls were caused by DCMU transportedwith transpiration ﬂow from the roots in the pot (Chaerle et al.
2003).
The affects of DCMU on chlorophyll ﬂuorescence intensities
were more signiﬁcant at the third and fourth leaves than those of
the ﬁrst, second and ﬁfth leaves (Figs 3, 4). It seems that the ﬁrst
and second leaves had already been senescent and the ﬁfth leaf
had still been immature seen as a slight yellow colour of theformers and insufﬁcient leaf development of the latter (Figs 2, 5).
That would have induced less stomatal opening and transpirationof the ﬁrst, second or ﬁfth leaves than those of the third and fourth
leaves, thus the effects of DCMU would have been observed
differently among leaves.
Transpiration ﬂow rates at the base and veins of each leaf
depend on whole leaf area and leaf conductance. Enlargements ofleaf area and leaf conductance would increase transpiration ﬂow
rate and consequently DCMU transport and injury caused by the
DCMU. The results of Fig. 6, especially the relationship between
leaf area and percentage of injured area, support this assumption.
Maximum stomatal conductance is strongly affected by growth
conditions and changes with leaf age. In general, the maximum
stomatal conductance of senescent and immature leaves becomes

(b)

(c)

(e)

(f )

High

2

1

Chlorophyll fluorescence intensity (rel.)

4

(d )

877

Low
Fig. 3. Changes in 3D chlorophyll ﬂuorescence intensity images from a view of the 3D model of the melon plant after
the herbicide treatment. The plant is the same as shown in Fig. 2. (a–f ) represent before and 1, 2, 3, 4 and 5 h after
herbicide treatment. Numbers 1 to 5 in Fig. 3a correspond to the ﬁrst to ﬁfth leaves. The 3D model was constructedby combining the 2D chlorophyll ﬂuorescence intensity images and the lidar-derived 3D polygon model.

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A. Konishi et al.

60

200

Leaf area ( 10 cm2)

1
160

Leaf inclination (degree)2

Leaf area and leaf inclination

Chl flourescence intensity (rel.)Site (leaf position)

3
120

4
5

80

40

40

5
20

0
0.0

1.0

2.0

3.0

4.0

5.0

Time (h)0Fig. 4. Changes in chlorophyll ﬂuorescence intensity at the bases of eachmelon leaf after the herbicide treatment. The sites of numbers 1 to 5 correspondto those in Fig. 2, respectively.

Leaf area, leaf inclination andpercentage of injured area

120

Leaf area (×10 cm2)
Leaf inclination (degree)
Percentage of injured area (%)

80

40

0
1

2

3

5

4

5

Leaf position
Fig. 5. Differences in leaf area, leaf inclination and percentage of injured
area to whole area of each melon leaf 5 h after the herbicide treatment obtained
from 3D chlorophyll ﬂuorescence model (including 3D polygon model)
shown in Fig. 3. The vertical bar of leaf inclination is the standard
deviation (s.d.) of the values of 50 polygons selected randomly on thewhole leaf.

smaller than that of mature leaves (Jones 1983). Leaf shape andinclination change microenvironments such as light intensity andboundary layer conductance on the leaf (Ross 1981; Jones 1983;
Sinoquet et al. 1998). Consequently, the stomatal conductanceand the rates of transpiration ﬂow and DCMU transport differ at
each leaf site. In this experiment, the relationship between leaf
inclination and percentage of injured area showed a negative
linear correlation, except at the ﬁfth, immature leaf (Fig. 6).
Steady-state chlorophyll ﬂuorescence intensity increases
with increasing actinic light intensity (Omasa et al. 1987). In
this study, PPF of actinic light at the level on each leaf distributed
between 130 and 160 mmol m–2 s–1. The leaf inclination increased
difference in PPF on the leaves. Consequently, the chlorophyll
ﬂuorescence intensity before the herbicide treatment varied

0

20

40

60

80

100

Percentage of injured area
Fig. 6. Relationships between leaf area, leaf inclination and percentage of
injured melon leaf area obtained from Fig. 5.

between 44 and 59, and the difference was ~30%. Therefore,
the percentage of injured area, in which the chlorophyll
ﬂuorescence intensity exceeded the maximum value at eachleaf site during 1 h after the herbicide treatment, to whole areaof each leaf was used as a more-steady index of the injury.
Although this index was also affected by change in the leaf
inclination during the experiment, the extent was very small
because of little change in leaf inclination during the experiment.
It is difﬁcult to measure accurately whole areas, injured areas,and site inclination of in situ curved leaves using ordinary 2D
imaging. Therefore, 3D digitiser and stereo photogrammetry
techniques (e.g. Lang 1973; Herbert 1995; Sinoquet et al.
1998) have been developed for estimations of leaf area andleaf inclination. Recent advances in computer technology anddigital image sensors have made it possible to conduct more
prompt 3D modelling and analysis for the plant structuralparameters and growth responses (e.g. Ivanov et al. 1994;
Omasa 2000; Andersen et al. 2005; Biskup et al. 2007; Omasa
et al. 2007; Hosoi and Omasa 2009). Leaf ﬂuctuations caused
by wind during measurement affects accuracy of the 3D
polygon model (Biskup et al. 2007). However, the affect on
accuracy was very slight in the experiments (Fig. 2).
The present 3D chlorophyll ﬂuorescence model allowed
detection of spatio–temporal changes of physiologicalresponses relating to photosynthetic electron transport of theherbicide on a whole plant, in addition to herbicide transportwith transpiration ﬂow from roots to leaves. Consequently, it was
shown that the herbicide injury on the mature leaves was earlier
and more severe than on the young and old leaves. The distancefrom veins, leaf area and leaf inclination inﬂuenced the extent of
the injury within the leaves. These results indicate that differences
in uptake of herbicide in the plant from soil depend on structuralparameters of leaves and the microenvironments as well as leaf
age. The ﬁndings should be veriﬁed by more detail studies on
different growth stages and species. A possible advancement is tocombine lidar-derived 3D polygon models with thermal andspectral reﬂectance images as well as chlorophyll ﬂuorescence3D imaging the effects of herbicide on a whole plant

Functional Plant Biology

images (Omasa et al. 2007). Therefore, the 3D composite imaging
will increasingly improve our spatio–temporal understanding of
biotic activities of plants and their responses to environmental
stresses.
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Manuscript received 12 May 2009, accepted 24 August 2009http://www.publish.csiro.au/journals/fpb