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How to colour a flower: on the optical
principles of flower coloration
Casper J. van der Kooi1,3, J. Theo M. Elzenga2, Marten Staal2
and Doekele G. Stavenga1
Research
Cite this article: van der Kooi CJ, Elzenga
JTM, Staal M, Stavenga DG. 2016 How to
colour a flower: on the optical principles of
flower coloration. Proc. R. Soc. B 283:
20160429.
http://dx.doi.org/10.1098/rspb.2016.0429
Received: 25 February 2016
Accepted: 11 April 2016
Subject Areas:
biophysics, ecology, plant science
Keywords:
absorbance, anatomy, pollination, pigment,
reflectance, vision model
1
Department of Computational Physics, and 2Department of Plant Ecophysiology, University of Groningen,
Groningen, The Netherlands
3
Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
CJvdK, 0000-0003-0613-7633; DGS, 0000-0002-2518-6177
The coloration of flowers is due to the wavelength-selective absorption by pigments of light backscattered by structures inside the petals. We investigated
the optical properties of flowers using (micro)spectrophotometry and anatomical methods. To assess the contribution of different structures to the overall
visual signal of flowers, we used an optical model, where a petal is considered
as a stack of differently pigmented and structured layers and we interpreted
the visual signals of the model petals with insect vision models. We show
that the reflectance depends, in addition to the pigmentation, on the petal’s
thickness and the inhomogeneity of its interior. We find large between-species
differences in floral pigments, pigment concentration and localization, as well
as floral interior structure. The fractions of reflected and transmitted light are
remarkably similar between the studied species, suggesting common selective
pressures of pollinator visual systems. Our optical model highlights that pigment localization crucially determines the efficiency of pigmentary filtering
and thereby the chromatic contrast and saturation of the visual signal.
The strongest visual signal occurs with deposition of pigments only on the
side of viewing. Our systematic approach and optical modelling open new
perspectives on the virtues of flower colour.
1. Introduction
Author for correspondence:
Casper J. van der Kooi
e-mail: [email protected]
Electronic supplementary material is available
at http://dx.doi.org/10.1098/rspb.2016.0429 or
via http://rspb.royalsocietypublishing.org.
Plants attract pollinators by displaying distinctly coloured flowers [1–4]. The role
of flower colours in pollination has been studied in many experiments, providing
valuable insight into the complex nature of plant–pollinator interactions [3,5].
Accordingly, for numerous flowers the coloration, characterized by their reflectance spectrum, has been reported (e.g. [6–10]), but the optics, i.e. the complex
interaction of light with the inner components of flowers, has so far received
much less attention. A quantitative understanding of flower coloration is, nonetheless, important in order to comprehend the ecology and evolution of visual
signalling of flowers, as it aids in our understanding of the proximate aspects
underlying floral visual signals.
Flower coloration is due to the combined effect of wavelength-selective absorption by pigments and light scattering by the petal interior [11–14]. The reflected
light in the wavelength ranges complementary to the pigment’s absorption band
determines the flower’s hue and saturation. Backscattering of light occurs at the irregularly structured inner petal components (e.g. the vacuoles and air spaces;
figure 1). Flower coloration is thus the combined effect of the pigment absorption
spectrum, scattering structures, and flower thickness, yet the relative contribution
of these different aspects to the overall visual signal of flowers is poorly understood.
In this study, we illustrate and quantify different aspects of flower coloration
with the aim of determining the common optical principles of flower coloration.
We first provide an overview of the general optical characteristics of flowers,
i.e. the fractions of reflected, transmitted, and absorbed light, flower absorbance
spectra and types of pigment localization. To understand the functional consequences of different pigment localizations and amounts of scattering, we applied
our recently developed optical model that treats a petal as a stack of layers, with
& 2016 The Author(s) Published by the Royal Society. All rights reserved.
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I
Rs
ad
(b) Floral anatomy
ab
T
Figure 1. Simplified diagram of the propagation of incident light (I) in a petal.
A small part of the incident light is reflected by the surface (Rs) of the adaxial side
of the petal (ad), but reflections and refractions inside the petal at the boundaries
of irregularly arranged components of the mesophyll layer (ml) result in diffusely
scattered light from the interior (Ri). The light that is not reflected or absorbed is
transmitted (T ) through the abaxial side (ab) of the petal.
each layer having specific absorption and scattering characteristics [14]. The optical properties of each individual layer (e.g.
the epidermal and mesophyll layers; figure 1) are calculated
using the Kubelka–Munk theory for absorbing and scattering
media [15]. The Kubelka–Munk model has proved to be
useful in modelling plant leaf optics as well as artificial materials
such as dyes and paints [15,16]. Although the Beer–Lambert law
yields the transmittance of a homogeneous, pigmented medium
with negligible scattering, the Kubelka–Munk theory [15] incorporates scattering and accordingly yields the medium’s
transmittance as well as reflectance. Using a calculation procedure for a stack of layers [16–18] and parameters based on
real flowers, we show that the overall reflectance of a petal can
be calculated with the Kubelka–Munk-layer-stack model; with
increasing thickness and inhomogeneity (due to cell walls, air
holes, or amyloplasts) a petal’s transmittance decreases while
the reflectance increases. The differences in reflectance spectra
due to changes in pigment localizations and optical properties
are interpreted with models for bee vision.
2. Material and methods
(a) Plant material, photography, and spectrophotometry
Flower samples of randomly chosen species were obtained from
meadows and roadsides around Groningen and the Botanical
Garden in Haren, The Netherlands, or were grown from seeds
(obtained from the Botanical Garden of Nijmegen, The Netherlands and De Bolster, Epe, The Netherlands). Flowers were
photographed with a Nikon D70 digital camera equipped with
an F Micro-Nikkor (60 mm, f2.8) macro objective (Nikon, Tokyo,
Japan). Petal details were photographed with an Olympus
SZX16 stereomicroscope equipped with an Olympus DP70 digital
camera (Olympus, Tokyo, Japan) or a Zeiss Universal Microscope
Thickness values were measured for floral elements from at least
two plants using a caliper. We placed a piece (one petal/ligule
for small flowers or a 1 cm2 piece for large flowers) of the element
in between two cover glasses and measured the thickness at five
points. For a subset of species, the thickness measurements
obtained with the caliper were verified using the Zeiss microscope
yielding similar results (see the electronic supplementary material).
The pigment distribution within the floral elements was examined
via cross sections of flower pieces. We embedded small pieces of
the flower in a 6% solution of agarose (Duchefa, Haarlem, The
Netherlands) at a temperature near the point of solidification
(approx. 558C). The sections were cut using a sharp razor blade
and immediately examined with the Zeiss microscope using the
Olympus 20 (NA 0.45) objective.
(c) Modelling petal reflectance and transmittance
We modelled the reflectance and transmittance of the petals by
considering a petal as a stack of absorbing and scattering
layers [14]. In this optical model, we combined the Kubelka –
Munk theory [15] with a calculation procedure for a stack of
absorbing and reflecting layers [16 – 18]. The model allows calculating the effect of scattering of the individual petal layers and
the petal as a whole on the transmittance and reflectance.
Although the Kubelka – Munk theory was developed for diffuse
light, and the illumination applied in the integrating sphere
was directional, we assume that the incident light becomes
readily diffuse, owing to the highly irregular flower surfaces
and interiors found in virtually all species [11 – 14,19,20].
In our optical model, the scattering parameter of a layer, S*,
plays a central role. This is the scattering coefficient, S
(i.e. the scattering per unit thickness), times the layer thickness,
d: S* ¼ Sd. In the case that absorption is negligible, we assumed
for all petal layers a wavelength-independent scattering coefficient
that was uniform for the different layers of the flower. It should be
noted, however, that the scattering coefficient is expected to be
higher for pigmented layers than for unpigmented layers, because
pigment granules (and possibly other high refractive index
materials) increase the inhomogeneity [14]. Provided the pigment
concentration is the same for different models, the scattering parameter of a stack of pigmented and unpigmented layers can
nonetheless be calculated using the weighted average of the different layers. Hence, the scattering parameters considered in the
models are similar as those found in real flowers (see below).
(d) Vision models
The reflectance spectra of differently pigmented model
flowers were interpreted with a bee-subjective view applying
Proc. R. Soc. B 283: 20160429
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Ri
(Zeiss, Oberkochen, Germany) with a Mueller DCM510 camera
(Mueller Optronic, Erfurt, Germany).
We measured the reflectance and transmittance of the floral
elements with an integrating sphere (for equipment details,
see [14]). The dominant coloured flower areas were mounted
with the display side (generally the adaxial surface) facing the
detector. For reflectance measurements, the floral element was
close to perpendicular, directionally illuminated from within the
sphere. For transmittance measurements, the petal was perpendicularly illuminated from outside the sphere via an optical fibre.
Several measurements were taken from floral elements of two to
five plants; for flowers of the same species, the shape of the spectra
was virtually constant and the amplitude varied only a few per
cent. The combined averaged reflectance (R) and transmittance
(T ) of the flowers yielded the absorptance A ¼ 1 2 (R þ T ).
Absorbance spectra of floral elements immersed in water were
measured with a microspectrophotometer (MSP), as in [14].
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species name
R
s.d. R
d (mm)
s.d. d (mm)
S*
S (mm21)
Apiaceae
Astrantia major
0.36
0.01
246
21
0.56
2.28
4.7
11.1
Apocynaceae
Asteraceae
Vinca minor
Cichorium intybus
0.48
0.37
0.01
0.01
222
146
44
53
0.92
0.59
4.16
4.04
13.2
6.3
10.1
8.9
Balsaminaceae
Impatiens glandulifera
0.39
0.05
127
16
0.64
5.03
9.8
6.7
Balsaminaceae
Boraginaceae
Impatiens parviflora
Borago officinalis
0.36
0.32
0.02
0.01
164
162
17
23
0.56
0.47
3.43
2.91
7.5
8.2
4.1
6.6
Boraginaceae
Brassicaceae
Echium vulgare
Eruca sativa
0.20
0.43
0.02
0.05
209
119
58
23
0.25
0.75
1.19
6.30
6.4
6.6
5.4
4.7
Caryophyllaceae
Silene dioica
0.42
0.03
102
17
0.72
7.08
6.4
8.6
Caryophyllaceae
Cleomaceae
Silene latifolia ssp. alba
Cleome spinosa
0.47
0.43
0.02
0.01
200
184
38
17
0.89
0.75
4.44
4.11
12.8
20.4
9.1
9.6
Colchicaceae
Convolvulaceae
Colchicum autumnale
Convolvulus sepium
0.46
0.33
0.00
0.01
327
128
58
17
0.85
0.49
2.61
3.85
11.1
4.7
11.3
11.1
Fabaceae
Fabaceae
Lathyrus pratensis
Phaseolus coccineus
0.24
0.41
0.01
0.02
162
379
38
17
0.32
0.69
1.95
1.83
6.6
11.1
10.0
8.9
Geraniaceae
Geranium robertianum
0.47
0.01
100
26
0.89
8.84
11.9
8.0
Hypericaceae
Hypericaceae
Hypericum calycinum
Hypericum perforatum
0.46
0.44
0.05
0.00
254
180
75
34
0.85
0.79
3.36
4.37
10.7
15.6
10.0
10.4
Lamiaceae
Malvaceae
Salvia guarantica
Hibiscus trionum
0.26
0.35
0.00
0.01
109
186
22
22
0.35
0.54
3.23
2.90
8.4
8.4
10.3
14.0
Malvaceae
Malva moschata
0.31
0.01
146
30
0.45
3.08
5.6
5.2
Malvaceae
Nymphaceae
Malva sylvestris
Nuphar lutea
0.28
0.45
0.03
0.03
139
419
36
71
0.39
0.82
2.79
1.95
7.8
10.5
6.5
15.0
Onagraceae
Onagraceae
Epilobium hirsutum
Oenothera biennis
0.30
0.45
0.02
0.03
96
220
17
75
0.43
0.82
4.48
3.73
9.3
9.3
7.4
8.8
Onagraceae
Onagraceae
Oenothera glazioviana
Oenothera lindheimeri
0.46
0.43
0.02
0.01
190
154
85
46
0.85
0.75
4.48
4.89
8.9
7.5
7.6
11.1
Papaveraceae
Chelidonium majus
0.37
0.02
98
29
0.59
6.02
14.6
10.7
Papaveraceae
Plantaginaceae
Papaver rhoeas
Linaria vulgaris
0.31
0.32
0.01
0.01
75
97
12
48
0.45
0.47
5.99
4.85
10.3
7.4
15.1
9.6
Ranunculaceae
Rosaceae
Caltha palustris
Geum urbanum
0.49
0.44
0.01
0.03
304
104
65
9
0.96
0.79
3.16
7.54
17.6
16.5
13.8
12.2
Solanaceae
Browallia americana
0.42
0.02
172
24
0.72
4.21
14.8
11.0
Solanaceae
Solanaceae
Nicotiana tabacum
Nolana paradoxa
0.40
0.40
0.01
0.01
210
139
23
58
0.67
0.67
3.18
4.80
3.2
8.3
9.8
7.2
Solanaceae
Solanaceae
Petunia nyctaginiflora
Physalis philadelphica
0.38
0.25
0.04
0.01
200
132
48
27
0.61
0.33
3.07
2.52
12.3
8.6
11.6
6.4
Solanaceae
Solanum trisectum
0.25
0.05
326
90
0.33
1.02
6.6
5.4
Tropaeolaceae
Tropaelum majus
0.46
0.02
228
26
0.85
3.73
23.2
9.5
the receptor noise-limited (RNL) [21,22] and colour hexagon
(CH) [23] model, which have been applied in many previous
studies (e.g. [7 – 9,24,25]). We used measured bee photoreceptor sensitivity spectra [26] and the daylight spectrum
D65. (See the electronic supplementary material for more
details about the insect vision models.)
JND R
JND T
3. Results
(a) Reflectance, transmittance, and absorptance of
flowers
We investigated the flowers of 39 plant species from 23 angiosperm families (table 1; electronic supplementary material,
Proc. R. Soc. B 283: 20160429
family
3
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Table 1. Parameters of floral elements from different species and families. R, reflectance value at 800 nm; d: thickness; s.d., standard deviation; S*, scattering
parameter; S, scattering coefficient; just noticeable differences (JND) R and JND T, perceptual distance in JND of the reflectance and transmittance spectra
against a green background, calculated using the RNL model.
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1.0
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reflect/transmit/absorptance
(a)
0.8
0.6
0.4
0.2
0
300
400
500
600
700
800
300
400
500
600
700
800
300
400
500
600
700
800
300
600
400
500
wavelength (nm)
700
800
reflect/transmit/absorptance
Proc. R. Soc. B 283: 20160429
(b) 1.0
0.8
0.6
0.4
0.2
0
reflect/transmit/absorptance
(c) 1.0
0.8
0.6
0.4
0.2
0
reflect/transmit/absorptance
(d) 1.0
0.8
0.6
0.4
0.2
0
Figure 2. Spectral characteristics of four differently coloured flowers. (a) Hibiscus trionum, (b) Borago officinalis, (c) Oenothera biennis, and (d) Papaver rhoeas. The
transmittance (T, red curves) and reflectance (R, green curves) spectra of single petals were measured with an integrating sphere, and the absorptance (blue curves)
was calculated from A ¼ 1 – (R þ T ).
figure S1). Figure 2 presents the spectra of four differentcoloured exemplary flowers. Flowers that appear white to the
human eye always had a low UV reflectance (figure 1a; electronic supplementary material, figure S2; see also [10,27]). The
blue, yellow, and red flowers yielded a high reflectance in the
short-, medium-, and long-wavelength ranges, respectively,
and occasionally featured an additional high ultraviolet
(UV) reflectance (figure 1; electronic supplementary material,
figure S1). For both the long- and short-wavelength ranges,
the transmittance was often higher than the reflectance
(figure 2; electronic supplementary material, figure S1;
table 1). The colour contrast calculated with the reflectance
and transmittance spectra greatly varied between species,
likely due to differences in absorption by pigments (table 1).
Interestingly, the absorptance spectrum of many yellow flowers
had a minor, yet consistent peak at approximately 660 nm, presumably due to the presence of a-chlorophyll (figure 1c;
electronic supplementary material, figure S1).
(b) Scattering in flower petals
Despite the great differences in peak absorption of the pigments, we found that pigment absorption was always
negligible in the long-wavelength range (i.e. above 800 nm;
figures 2 and 3; electronic supplementary material, figure S1).
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From the reflectance and transmittance spectra, the absorptance
spectra can be derived. These do not reliably represent the pigment absorption spectra, because scattering inside the petal
distort the latter spectra. A more accurate way is to measure
the absorbance of the floral element in a refractive index-matching fluid with a MSP. This revealed the presence of a diverse set
of pigments (figure 3). The white area of the Hibiscus trionum
petals yielded an absorbance spectrum with a high, narrowband peak in the (ultra-)violet wavelength range. The yellow
Oenothera biennis flowers featured an absorbance spectrum
similar to that of b-carotene, the flowers of P. rhoeas show a pigment with a broad-band absorption spectrum with maximal
absorption at approximately 500 nm, and the spectra of the
blue flowers of Borago officinalis and Cichorium intybus indicated
the presence of very similar pigments, but with about a threefold difference in absorbance (figure 3; see also figure 2b and
electronic supplementary material, figure S1a). An extreme
case of dense pigmentation is the deeply red-coloured proximal
area of H. trionum petals (absorbance peak value approx. 2.5;
electronic supplementary material, figure S2).
(d) Localization of floral pigments
Previous studies showed that the localization of floral pigments
varies among plant species [12,13]. Generally, pigments can be
localized throughout the floral elements in three ways
(figure 4): (i) the pigment is rather evenly distributed
absorbance
1.5
1.0
0.5
0
400
500
600
wavelength (nm)
700
Figure 3. Absorbance spectra of petals in water measured with a MSP. Ht,
Hibiscus trionum; Bo, Borago officinalis; Ci, Cichorium intybus; Ob, Oenothera
biennis; Pr, Papaver rhoeas.
throughout the petal (e.g. O. biennis, figure 4a), (ii) the upper
and lower epidermises are pigmented, whereas the layer in
between (mesophyll or starch layer) is unpigmented (e.g. Phaseolus coccineus, figure 4b), (iii) the pigment is asymmetrically
localized in only one of the two epidermises (e.g. Browallia
americana, figure 4c). The functional implications of the
different pigment localizations will be discussed below.
(e) Modelling flower optics
The Kubelka–Munk-layer-stack model (Material and methods;
[14]) was used to illustrate the consequences of different
pigment localizations and scattering parameters on flower
coloration. For the model petal, we assumed a thickness of
0.25 mm and a scattering coefficient S ¼ 4 mm21, hence a scattering parameter S* ¼ 1. These values are similar to those
found in real flowers (table 1). We considered five different
cases, all having an equal amount of blue-absorbing carotenoid
pigment. In all five cases, the long-wavelength reflectance was
50%. Since for transmission the pigment localization is unimportant, the model yields identical transmittance spectra for
the different types of pigmentation, i.e. a low transmittance
in the blue and a distinct peak in the UV. The flowers’ reflectance spectra, however, strongly depended on the
localization of the pigment (figure 5a). In case 1, the pigment
was homogeneously distributed throughout the petal, resulting in a fairly high UV reflectance and a more moderate
reflectance in the blue wavelength range (figure 5a). In case 2,
an equal amount of pigment was distributed in the upper
and lower 0.05 mm of the petal, yielding a reflectance spectrum
similar to case 1, but with slightly lower UV and blue reflectance (figure 5a). In case 3, the pigment was located only in
the top 0.05 mm of the petal, which resulted in a low reflectance
in the UV and a very low reflectance in the blue wavelength
range. The reflectance of the lower side of this model petal
(as in case 4; figure 5a), however, is virtually wavelength independent, because the light is backscattered before it reaches the
pigmented layer. Similarly, the hypothetical case of pigment
localized only in the mesophyll layer also showed a weak
modulation of the reflected light (case 5; figure 5a).
(f ) The bee visual system
We calculated the relative excitations of the set of bee photoreceptors by daylight and the reflectance spectra of the five
Proc. R. Soc. B 283: 20160429
(c) Absorption of light by different pigment
concentrations
5
Ht
Bo
Ci
Ob
Pr
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The reflectance in the long-wavelength range thus is solely
determined by the flowers’ scattering structures. The lowest
reflectance value was obtained for the flowers of Echium vulgare
(20%) and the highest reflectance value was for the flowers of
Caltha palustris (49%) (electronic supplementary material,
figure S1; table 1).
In order to quantitatively assess the scattering of flowers,
we heuristically considered the petals as a single, homogeneously diffusing plate and we neglected the surface
reflections, as these are generally very small, i.e. only a few
per cent [11,14]. When the absorption is negligible (i.e. at wavelengths more than 800 nm), the scattering parameter S* follows
from the reflectance value, R: S* ¼ R/(1 2 R) [14]. Accordingly, the lowest and highest scattering parameters were
obtained for the flowers of E. vulgare and C. palustris, respectively. The flowers’ thickness value, d, was more variable and
ranged from 75 mm (Papaver rhoeas) to 419 mm (Nuphar lutea;
table 1). The scattering coefficient (S ¼ S*/d) is a measure of
the inhomogeneity of the flower’s interior and was found to
vary considerably between species (table 1). The flowers of
Solanum trisectum, which have a reflectance value R ¼ 0.25
and thickness d ¼ 0.33 mm, yielded the lowest scattering coefficient, S ¼ 1.0 mm21. The small thickness (d ¼ 0.075 mm) and
fairly high reflectance (R ¼ 0.31) of P. rhoeas flowers yielded a
high scattering coefficient of S ¼ 6.0 mm21. The scattering coefficient was even higher for flowers of Geranium robertianum,
which were slightly thicker (d ¼ 0.10 mm) but considerably
brighter (R ¼ 0.47), resulting in a very high scattering coefficient
of S ¼ 8.8 mm21. In other words, the moderately thick flowers
of S. trisectum are inefficient reflectors and the flowers of
P. rhoeas and G. robertianum, which consist of only a few cell
layers, are very efficient reflectors.
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(a)
(b)
(c)
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model flowers (figure 5). The overall hue of the model petals
was yellow, hence the strongest excitation always occurred in
the green photoreceptor, but the excitation of the UV and
blue photoreceptors distinctly varied between the different
pigment localizations (figure 5c). The very weakly modulated
reflectance spectra of cases 4 and 5 (figure 5a) resulted in a
high excitation of the UV and blue photoreceptors but excitation of these photoreceptors was considerably less for a
homogeneous (case 1) as well as symmetrical (case 2) pigmentation. The excitation of the UV and blue photoreceptors was
very low for the spectrum of the model petal where pigment
is only localized at the side of viewing (case 3, figure 5a), showing that this type of pigment localization yields a visual signal
with the highest saturation. The saturation of the transmitted
light is slightly lower than that created by the reflected light
in case 3, because the peak in the UV is slightly higher for
the transmitted light.
We interpreted the visual signal of the model spectra
of figure 5a against that of a green background with a beesubjective view using the RNL [21,22] model for insect vision
(figure 5c, inset; electronic supplementary material, table S1).
The model’s results showed that the colour contrast of the
flower against a green background increases when the spectral
modulation of the reflected light increases, i.e. when absorption in the blue wavelength range increases. Consequently,
the spectra of figure 5a yield colour contrast values that are
low for the asymmetrical pigmentation observed from the
unpigmented side as well as for the case where pigment only
occurs in the mesophyll layer. The colour contrast is more moderate for homogeneous and symmetrical pigmentation, and
very high when pigments occur only at the side of viewing
(figure 5c, inset). For the transmission signal, the modulation
of the spectrum is also strong, but not as strong as when the
pigments only occur at the side of viewing. Clearly, symmetrical and homogeneous pigment localizations yield a moderately
distinct coloration from a green background, whereas pigment
localization solely at the display side provides the highest
colour contrast. Using the CH model [23], very similar perceptual differences between the types of pigment localization were
obtained, that is, both models showed low- or high-contrast
values for specific spectra, as shown by the ratio of values normalized to the mean that is always close to 1 (electronic
supplementary material, table S1).
Pairwise comparisons of the different reflectance spectra
by the model petals yielded similar results: larger differences
in the fraction of blue light absorbed resulted in larger contrast
values (electronic supplementary material, table S1). The visual
signals of petals with homogeneous and symmetrical pigmentation are similar (figure 5), and a pairwise comparison yields
contrast values indeed below the threshold value for both
vision models (electronic supplementary material, table S1).
This shows that, although a symmetrical distribution of
pigments yields a slightly higher colour contrast with the background, for the chosen set of model parameters homogeneously
and symmetrically pigmented flowers are not visibly different.
We also tested the optical model with the same pigment
localizations and thickness value as before (d ¼ 0.25 mm) but
with a lower scattering parameter, S* ¼ 0.5 (electronic supplementary material, figure S3a), which is also commonly
found in real species (table 1). The obtained spectra, photoreceptor quantum catches, and colour contrast values were
similar to S* ¼ 1 (electronic supplementary material, figure
S3b; table S1), demonstrating that the pigment localization
also strongly determines the visual signal for petals with a
more moderately inhomogeneous interior.
4. Discussion
The plant kingdom encompasses a bewildering array of differently coloured flowers [3,6,10,13,27], with variations in
anatomy, pigments, and pigment localizations, but how these
differences contribute to the overall visual signal of flowers is
largely unknown. Absorption by pigments occurs in the (ultra)violet, short-, and medium-wavelength ranges, but not in the
long-wavelength range, i.e. above 800 nm (figures 1 and 2 and
electronic supplementary material, figure S1). Although the
long-wavelength reflectance is of no importance for visual signalling, because many flower-visiting insects, like bees, have
negligible spectral sensitivity above approximately 650 nm
[26], it can be used to quantify the amount of backscattering
by a petal, as it is fully determined by scattering structures.
We measured the floral reflectance and transmittance of
many species and found that the long-wavelength reflectance
was always between 20 and 50% (figure 2; electronic
supplementary material, figure S1; table 1). For both the
long- and short-wavelength ranges, the transmittance was
often higher than the reflectance (figure 2; electronic supplementary material, figure S1; table 1). This is somewhat
surprising, because the transmitted light will often not be
detected by foraging pollinators. In order for the transmittance
to be perceived by pollinators, the flower needs to be
Proc. R. Soc. B 283: 20160429
Figure 4. Localization of pigments in petals. (a) Oenothera biennis, (b) Phaseolus coccineus, and (c) Browallia americana. Scale bars, 50 mm.
Downloaded from http://rspb.royalsocietypublishing.org/ on June 16, 2017
(a)
1
2
3
4
5
reflectance
0.4
pigmentation
1
2
3
4
5
T
0.3
0.2
0.1
300
400
500
600
(b) 1.0
sensitivity
0.8
UV
B
G
0.6
0.4
0.2
0
relative excitation
(c) 1.0
0.8
0.6
300
400
500
wavelength (nm)
600
JND
1: 5.6
2: 7.0
3: 9.6
4: 5.0
5: 4.6
T: 9.2
0.4
0.2
0
UV
blue
receptor type
green
Figure 5. Different types of pigment localization of the model petal and
their visual signals. (a) Reflectance spectrum of five model petals (thickness
d ¼ 0.25 mm, scattering parameter S* ¼ 1) containing the same amount of
the blue-absorbing pigment of Oenothera biennis (figure 3), with pigment
homogeneously distributed (case 1), equally distributed in both a top and
bottom layer of 0.05 mm (case 2), existing in a 0.05 mm top or bottom
layer (case 3 and 4, respectively), and located only in the middle layer
(case 5); the transmittance spectrum (T ) is the same for all types of pigment
localization. (b) Normalized spectral sensitivities of the honeybee photoreceptors used in the vision models. UV, ultraviolet; B, blue; G, green.
(c) Bar plots of the relative excitation of the set of photoreceptors for the
spectra of the model petal with the different types of pigment localization
as shown in (a); inset: colour contrast values (in JND) using the RNL model.
positioned in between the pollinator and sun. Although this
may occur for flowers attached high on trees or under specific
circumstances, such as shortly after dawn or before sunset, in
the majority of cases, however, the sun is high in the sky so
that pollinators will perceive reflected light. The reflectance
and transmittance of the flower examples presented here are
similar to those found in flowers of other plant species [28–30].
The selective pressures—or the lack of them—imposed by
the visual ecology of pollinators may explain the virtual
absence of very weakly and strongly reflecting flowers. In
Proc. R. Soc. B 283: 20160429
0
7
rspb.royalsocietypublishing.org
0.5
order to provide a sufficiently coloured signal, flowers need
to reflect a minimum amount of light. The observed longwavelength reflectance minimum of 20% is presumably
sufficient to create a substantial modulation by pigments of
the reflected light. Conversely, the absence of flowers with a
long-wavelength reflectance of more than 50% suggests that a
higher value will not effectively enhance the visibility to pollinators. Indeed, the colour contrast values obtained for
reflectance and transmittance spectra of real flowers showed
great variation independent of the brightness (table 1), highlighting that the absorption by pigments is very important
for creating a distinct visual signal. Behavioural and psychophysiological experiments with diurnal insect pollinators
have shown that brightness of the visual signal may play a
role for long-distance detection of flowers [31,32], whereas
chromatic aspects are important for short-distance discrimination [24,33,34]. Extreme increases in floral brightness need
not necessarily be beneficial, however, because insect colour
vision generally adapts to intensity changes [35–37], a
phenomenon known as ‘colour constancy’ (reviewed in [38]).
The virtual absence of flowers with reflectance below or
above the 20–50% range hence suggests that flowers could
be physiologically limited to increase their scattering, and/or
that this range is sufficient to create distinct colours.
In order to obtain a quantitative measure of the inhomogeneity of the flower’s interior independent of the flower
thickness, we calculated the scattering coefficient. The
observed eightfold variation in the scattering coefficient as
well as in the thickness values between the investigated species
(table 1) illustrates that flowers of different species greatly differ
in their anatomy. The thickness of a flower is presumably correlated with the flower’s size, because thicker flowers will need
to have more mechanical strength. The amount of vacuoles,
amyloplasts, and cell walls in flowers varies considerably
amongst different species [12,18], comparable to what was previously found for leaves [39]. From this study, it is clear that
thin flowers are not necessarily dim flowers, that is, flowers
with very thin petals can—and maybe must—have a very
inhomogeneous interior to achieve sufficient light reflection
for luring pollinators.
The floral pigment selectively filters the backscattered
light (figure 2; electronic supplementary material, figure S1),
and increases in pigment concentration will result in more
absorption of light in a specific wavelength range (figure 3; electronic supplementary material, figure S2). Increases in pigment
concentration may, however, not always be an optimal strategy,
e.g. when pigment synthesis is energetically costly. Alternatively, deposition of pigments in specific layers can increase
the colour contrast (figures 4 and 5). Our modelling showed
that deposition of pigments exclusively in the middle mesophyll
layer is inefficient, because part of the light is backscattered
before it reaches the pigment. The resulting low contrast with
the background (figure 5c) may explain why it is almost never
found in real flowers [12]. Homogeneous or symmetrical pigment deposition in the epidermal layers causes similarly
coloured upper and lower sides of the flower but a rather moderate modulation of the spectrum and moderate contrast values
(figure 5c; electronic supplementary material, table S1). Pigment
deposition solely in the upper epidermal layer resulted in a
pigmented side that strongly contrasted with the green background, whereas the unpigmented side was weakly
discriminable from a green background (9.6 versus 5.0 JND
units; figure 5c). When viewed from the side of viewing, the
Downloaded from http://rspb.royalsocietypublishing.org/ on June 16, 2017
Data accessibility. The datasets supporting this article have been
uploaded as part of the electronic supplementary material.
Authors’ contributions. C.J.v.d.K., M.S., and D.G.S. performed measurements. C.J.v.d.K. and D.G.S. designed the study, carried out the
modelling and drafted the manuscript. All authors analysed the
results and contributed to the manuscript.
Competing interests. We have no competing interests.
Funding. This work was funded by EOARD/AFOSR grant no. FA865512-1-2053.
Acknowledgements. The authors gratefully acknowledge Hein Leertouwer
for assistance and two referees for valuable comments.
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