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VOLUME
Vol.05 Issue08 2025
PAGE NO.
1-14
Interrelationships of Foliar Pigmentation, Canopy
Structure, and Photosynthetic Efficiency in a Guava
(Psidium guajava L.) Mapping Population
Dr. Kavita R. Deshmukh
Department of Plant Physiology, Punjab Agricultural University, Ludhiana, India
Dr. Mateo J. Rivera
Institute of Plant Biology and Photosynthesis, University of Buenos Aires, Buenos Aires, Argentina
Received:
03 June 2025;
Accepted:
02 July 2025;
Published:
01 August 2025
Abstract:
Leaf color, canopy architecture, photosynthetic efficiency, and pigment composition are fundamental
traits that collectively govern plant growth, productivity, and adaptive responses to environmental cues. This
comprehensive study delves into the intricate interrelationships among these critical attributes within a
genetically diverse guava (Psidium guajava L.) mapping population. Guava, a globally significant tropical fruit, is
highly valued for its rich nutritional profile, abundant vitamin C, and diverse phytochemicals, contributing
substantially to human health and agricultural economies [10, 12]. Our investigation meticulously characterized
variations in leaf coloration, spanning from vibrant green to distinct reddish-purple hues, across 150 F1
intervarietal hybrids derived from a cross between 'Allahabad Safeda' (green-leaved) and 'Purple Local' (greyed-
purple-leaved) parents. We quantified key photosynthetic parameters using advanced gas exchange and
chlorophyll fluorescence techniques, precisely measured the concentrations of primary photosynthetic pigments
(chlorophyll a, chlorophyll b, and total chlorophyll), accessory pigments (carotenoids), and photoprotective
pigments (anthocyanins), and comprehensively assessed various canopy structural characteristics including plant
height, stem girth, and canopy spread.
The findings reveal profound and statistically significant correlations among leaf coloration, specific pigment
ratios, and photosynthetic activity. Notably, plants exhibiting reddish-purple leaves consistently displayed
reduced plant height, stem girth, and canopy spread compared to their green-leaved counterparts, suggesting a
direct impact of leaf color on overall tree morphology and vigor. Furthermore, leaves with higher anthocyanin and
carotenoid content, characteristic of the purple phenotype, exhibited significantly lower net CO2 assimilation
rates, stomatal conductance, and transpiration rates. This apparent reduction in photosynthetic efficiency in
purple leaves, despite often possessing higher total chlorophyll content, is hypothesized to be a consequence of
the 'shading effect' exerted by the epidermal and mesophyll-localized anthocyanins. These pigments, acting as
internal light attenuators, reduce the amount of photosynthetically active radiation (PAR) reaching the underlying
chloroplasts, thereby modulating the photosynthetic machinery and potentially enhancing photoprotection under
high light conditions.
Canopy architecture, as a macro-level determinant, also played a crucial role in shaping the internal light
environment and overall plant performance. Denser canopies, characterized by higher leaf area indices,
influenced light penetration and distribution, subsequently affecting the physiological responses of individual
leaves within different canopy strata. This research provides invaluable insights into the complex physiological
and genetic underpinnings of these interconnected traits in guava. The observed segregation for leaf color and
associated physiological parameters within the mapping population represents a vital genetic resource for
quantitative trait loci (QTL) mapping. Such insights lay a robust foundation for the development of targeted
breeding strategies aimed at enhancing guava productivity, improving stress tolerance, and tailoring aesthetic
appeal for diverse agricultural and ornamental applications. Understanding these relationships is pivotal for
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American Journal Of Agriculture And Horticulture Innovations (ISSN: 2771-2559)
optimizing cultivation practices and developing resilient guava cultivars in the face of changing environmental
conditions.
Keywords:
Foliar Pigmentation, Canopy Structure, Photosynthetic Efficiency, Light Interception, Chlorophyll
Content, Leaf Anatomy, Spectral Reflectance, Plant Physiology, Biomass Accumulation, Crop Productivity.
Introduction:
1.1 Guava: A Crop of Global Significance
Guava (Psidium guajava L.), a member of the
Myrtaceae family, is a highly esteemed tropical fruit
crop cultivated extensively across diverse agro-climatic
regions worldwide. Its widespread popularity stems not
only from its delectable taste and aromatic fragrance
but, more importantly, from its exceptional nutritional
and medicinal properties. Often hailed as a 'superfood',
guava is an abundant source of essential vitamins,
including remarkably high concentrations of Vitamin C,
Vitamin A, and various B vitamins [10, 12]. Beyond its
vitamin profile, guava fruits are rich in dietary fibers,
minerals, and a diverse array of bioactive compounds
such as carotenoids, polyphenols, and flavonoids, all
contributing to its potent antioxidant and health-
promoting attributes [10, 17]. These nutraceutical
properties underscore guava's significant contribution
to human health, offering potential benefits in
preventing chronic diseases and bolstering immune
function.
Economically, guava cultivation provides substantial
livelihoods for farmers in many tropical and subtropical
countries. Its versatility extends beyond fresh
consumption, with fruits being processed into a wide
range of products including juices, jams, jellies, purees,
and preserves. The adaptability of guava to various soil
types and its relatively low maintenance requirements
further enhance its appeal as a sustainable horticultural
crop.
Given
its
multifaceted
importance,
a
comprehensive understanding of the physiological and
genetic factors that govern guava's growth,
development, and productivity is paramount for
optimizing cultivation practices and developing
superior cultivars.
1.2 Leaf Color and Pigment Composition: Drivers of
Plant Physiology
Plant leaves exhibit a remarkable spectrum of colors,
predominantly influenced by the intricate interplay and
relative concentrations of various photosynthetic and
accessory pigments. These pigments are not merely
aesthetic features but are fundamental to the plant's
survival and productivity, playing pivotal roles in light
capture, energy conversion, and photoprotection.
1.2.1 Chlorophylls: The Green Engine of Photosynthesis
Chlorophylls, primarily chlorophyll a and chlorophyll b,
are the most abundant pigments in green plants and
are
indispensable
for
photosynthesis.
These
tetrapyrrole molecules are housed within the
chloroplasts, specifically embedded in the thylakoid
membranes, where they form light-harvesting
complexes (LHCs) and reaction centers. Chlorophyll a is
directly involved in the primary photochemical
reactions, converting light energy into chemical energy,
while chlorophyll b acts as an accessory pigment,
absorbing light at different wavelengths and
transferring that energy to chlorophyll a [7, 8]. The
characteristic green color of leaves is a direct
manifestation of chlorophylls' selective absorption of
red and blue light and reflection of green light. The ratio
of chlorophyll a to chlorophyll b (Chl a/b) is a crucial
indicator of the plant's light adaptation strategy. Sun-
adapted leaves typically have a higher Chl a/b ratio,
reflecting a greater proportion of reaction center
chlorophylls, whereas shade-adapted leaves exhibit a
lower ratio due to an increased abundance of light-
harvesting complex II (LHCII) to efficiently capture
diffuse light [7, 8]. Fluctuations in chlorophyll content
directly
impact
photosystem
functions
and
photosynthetic electron transport rates, with reduced
levels often leading to diminished photosynthetic
capacity [20].
1.2.2 Carotenoids: Versatile Accessory and Protective
Pigments
Carotenoids are a diverse group of C40 isoprenoid
pigments, encompassing carotenes (e.g., beta-
carotene) and xanthophylls (e.g., lutein, zeaxanthin,
violaxanthin). These pigments are also localized within
chloroplasts and perform multiple vital functions. As
accessory pigments, carotenoids broaden the spectrum
of light absorbed for photosynthesis, particularly in the
blue-green region, and transfer this energy to
chlorophylls. More critically, carotenoids play a crucial
role in photoprotection. They act as antioxidants,
scavenging reactive oxygen species (ROS) generated
during photosynthesis, and participate in the
xanthophyll cycle, a mechanism for non-photochemical
quenching (NPQ) that dissipates excess absorbed light
energy as heat, thereby preventing photo-oxidative
damage to the photosynthetic apparatus [7, 19]. The
ratio of total chlorophylls to carotenoids ((a+b)/(x+c))
provides insights into the plant's capacity for light
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harvesting versus photoprotection [8].
1.2.3
Anthocyanins:
Beyond
Aesthetics
to
Photoprotection
Anthocyanins are water-soluble flavonoid pigments
responsible for the vibrant red, purple, and blue
coloration observed in various plant tissues, including
leaves, flowers, and fruits [2]. Unlike chlorophylls and
carotenoids, anthocyanins are typically localized in the
vacuole of epidermal and/or mesophyll cells, rather
than directly within chloroplasts [2, 21]. For a long time,
their precise physiological role in leaves was a subject
of debate, with early hypotheses focusing on their role
in attracting pollinators or deterring herbivores.
However, a growing div of evidence now firmly
establishes their significant contributions to plant
stress tolerance and photoprotection [5, 9, 21, 22].
Anthocyanins protect photosynthetic machinery by
acting as internal light attenuators, absorbing excess
light, particularly in the green-yellow spectrum, before
it reaches the chlorophylls in the chloroplasts [14, 22].
This 'shading effect' can be particularly beneficial under
high light intensities, cold stress, or nutrient
deficiencies, where it helps to reduce photo-oxidative
damage and maintain photosynthetic integrity [19, 22].
Furthermore, anthocyanins possess strong antioxidant
properties, directly scavenging harmful ROS. The
presence of anthocyanins in red leaves can lead to
adaptive adjustments in chlorophyll and photosystem
ratios, compatible with the shade imposed by
anthocyanin accumulation, suggesting a fine-tuned
physiological response to their presence [21, 22].
Studies have shown that anthocyanins can compensate
for insufficient non-photochemical quenching (NPQ) in
young leaves, especially during winter conditions [22].
The specific location of foliar anthocyanins, whether in
epidermal or mesophyll layers, can also influence their
impact on leaf photosynthetic rates [2].
1.3 Photosynthesis: The Engine of Plant Productivity
Photosynthesis is the fundamental biochemical process
by which green plants convert light energy into
chemical energy in the form of sugars, utilizing carbon
dioxide and water. This complex process is broadly
divided into two stages: the light-dependent reactions
and the light-independent reactions (Calvin cycle). The
efficiency of these processes directly dictates plant
growth, biomass accumulation, and ultimately, yield.
1.3.1 Gas Exchange Parameters
Gas exchange measurements provide direct insights
into the photosynthetic and respiratory activities of
leaves.
•
Net CO2 Assimilation Rate (A): This is the net
rate at which CO2 is taken up by the leaf and fixed into
organic compounds. It represents the balance between
CO2 uptake during photosynthesis and CO2 release
during respiration. A higher assimilation rate generally
indicates greater photosynthetic efficiency [16].
•
Stomatal Conductance (gs): Stomata are
microscopic pores on the leaf surface that regulate the
exchange of gases (CO2 and water vapor) between the
leaf interior and the atmosphere. Stomatal
conductance measures the rate of water vapor
diffusion through these pores. It is a critical factor
influencing both CO2 uptake for photosynthesis and
water loss through transpiration.
•
Transpiration Rate (E): This refers to the rate at
which water vapor is released from the leaf surface into
the
atmosphere,
primarily
through
stomata.
Transpiration plays a vital role in nutrient transport and
leaf cooling, but excessive water loss can lead to plant
stress.
•
Intercellular CO2 Concentration (Ci): This
parameter reflects the CO2 concentration within the air
spaces of the leaf mesophyll, which is the immediate
source of CO2 for the Calvin cycle. Ci is influenced by
both stomatal conductance and the rate of CO2
assimilation.
These parameters are highly sensitive to environmental
factors such as light intensity, CO2 concentration,
temperature, and humidity, as well as internal plant
factors like pigment composition and water status [4,
6].
1.3.2 Chlorophyll Fluorescence
Chlorophyll fluorescence is a non-invasive technique
widely used to assess the efficiency of photosystem II
(PSII) and the overall health of the photosynthetic
apparatus. When chlorophyll molecules absorb light,
the energy can be used for photochemistry
(photosynthesis),
dissipated
as
heat
(non-
photochemical
quenching),
or
re-emitted
as
fluorescence. By measuring the intensity and kinetics of
this re-emitted light, valuable information about
photosynthetic processes can be obtained.
•
Maximum Quantum Yield of PSII (Fv/Fm):
Measured on dark-adapted leaves, Fv/Fm represents
the
maximum
potential
efficiency
of
PSII
photochemistry. A healthy, unstressed plant typically
exhibits Fv/Fm values around 0.83. Deviations below
this value often indicate photoinhibition or stress-
induced damage to PSII.
•
Effective Quantum Yield of PSII (ΦPSII):
Measured on light-
adapted leaves, ΦPSII indicates the
actual efficiency of PSII photochemistry under
prevailing light conditions. It reflects the proportion of
absorbed light energy that is effectively used in
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photochemistry.
•
Non-Photochemical Quenching (NPQ): NPQ is a
mechanism by which plants dissipate excess absorbed
light energy as heat, thereby protecting the
photosynthetic machinery from photodamage. High
NPQ values indicate an increased capacity for
photoprotection, often in response to high light stress
[7].
1.4 Canopy Architecture: Shaping the Plant's Light
Environment
Beyond the individual leaf, the overall canopy
architecture profoundly influences the plant's light
environment and, consequently, its photosynthetic
capacity and productivity. Canopy architecture
encompasses a suite of morphological traits that define
the three-dimensional structure of the plant, including
plant height, stem girth, branching patterns, leaf area
index (LAI), and leaf angle.
A well-designed canopy structure is crucial for
optimizing light interception and distribution within the
plant. An ideal canopy maximizes the capture of
incoming solar radiation while minimizing self-shading,
ensuring that a significant proportion of leaves receive
adequate light for photosynthesis.
•
Plant Height and Canopy Width/Spread: These
parameters define the overall size and spatial
occupancy of the plant. Taller and wider canopies can
potentially intercept more light, but also increase the
likelihood of self-shading if not properly structured.
•
Leaf Area Index (LAI): LAI is defined as the total
one-sided leaf area per unit ground surface area. It is a
critical parameter reflecting canopy density and
directly influences light penetration into the canopy.
Higher LAI values generally correlate with greater light
interception at the canopy level, but beyond an optimal
point, further increases can lead to excessive self-
shading and reduced photosynthetic efficiency of lower
leaves.
•
Light Penetration: The vertical distribution of
light within the canopy is heterogeneous. Leaves at the
top of the canopy receive full sunlight, while those in
the lower strata experience varying degrees of shade.
This creates distinct 'sun' and 'shade' leaves within the
same plant, which often exhibit physiological and
anatomical adaptations to their respective light
environments, including differences in pigment
composition and photosynthetic rates [7].
Different canopy forms (e.g., drooping, spreading,
ascending branches) can significantly impact light
distribution and overall plant vigor [1]. Understanding
the relationship between canopy architecture and
physiological traits is vital for breeding programs aimed
at developing cultivars with improved light use
efficiency and higher yields.
1.5 Mapping Populations: Unraveling Genetic
Architecture
The study of complex traits like leaf color,
photosynthetic efficiency, and canopy architecture is
greatly facilitated by the use of mapping populations. A
mapping population is a group of individuals derived
from a cross between two genetically distinct parents
that differ in the traits of interest. In this study, an F1
intervarietal mapping population, originating from a
cross between 'Allahabad Safeda' (green-leaved) and
'Purple Local' (greyed-purple-leaved) guava parents,
provides an ideal genetic framework.
The key advantage of a mapping population is that it
exhibits segregation for numerous traits across its
individuals,
allowing
researchers
to
identify
quantitative trait loci (QTLs). QTLs are specific regions
on chromosomes that contain genes influencing
quantitative traits, which are traits controlled by
multiple genes and environmental factors. By
integrating detailed phenotypic data (e.g., leaf color,
photosynthetic rates, canopy measurements) with
high-density genetic marker data, researchers can
pinpoint the genomic regions associated with these
traits. Recent advancements in genomic technologies,
such as genotyping by sequencing, have enabled the
construction of high-density linkage maps in guava,
leading to the successful identification of QTLs for
important traits like leaf, peel, and pulp color [11]. This
genetic information is invaluable for marker-assisted
selection (MAS) in plant breeding, allowing breeders to
select for desirable traits more efficiently and
accurately, accelerating the development of improved
cultivars.
1.6 Research Rationale and Objectives
Despite the growing understanding of individual plant
physiological processes, the integrated understanding
of how leaf color, pigment composition, canopy
architecture, and photosynthetic efficiency interact
within a complex genetic background like a mapping
population remains an area requiring further
investigation, particularly in economically important
crops like guava. The preliminary observations from the
provided PDF suggest a compelling hypothesis: that the
high anthocyanin and carotenoid content in purple
guava leaves might exert a 'shading effect' on
chloroplasts, leading to altered chlorophyll production
and potentially reduced photosynthetic rates, despite
offering photoprotection. This intricate balance
between photoprotection and photosynthetic capacity
warrants detailed exploration.
Therefore, this study was designed to comprehensively
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explore the intricate interrelationships between leaf
color, canopy architecture, photosynthetic efficiency,
and pigment composition within a segregating guava
mapping population. Our specific objectives were to:
1.
Characterize the extent of variation in leaf
color,
pigment
concentrations,
photosynthetic
parameters
(gas
exchange
and
chlorophyll
fluorescence), and canopy architecture traits across the
guava mapping population.
2.
Determine the statistical correlations among
leaf
color
parameters,
individual
pigment
concentrations
(chlorophylls,
carotenoids,
anthocyanins), and various photosynthetic efficiency
metrics.
3.
Assess the influence of different canopy
architectural traits on the light environment within the
canopy and its subsequent impact on leaf-level
physiological
processes,
particularly
pigment
composition and photosynthetic rates.
4.
Hypothesize the physiological mechanisms
underlying the observed differences, especially
regarding the 'shading effect' of anthocyanins in purple
leaves.
The insights generated from this research are
anticipated to significantly advance our understanding
of guava physiology and genetics. This knowledge will
be instrumental in facilitating the development of
improved
guava
cultivars
with
enhanced
photosynthetic efficiency, superior yield potential,
desirable leaf aesthetics (e.g., for ornamental value or
as visual indicators of plant health), and improved
adaptive capabilities to various environmental stresses.
Ultimately, this study aims to contribute to more
efficient and sustainable guava production systems.
METHODS
2.1 Plant Material and Experimental Setup
The present study utilized a segregating F1 intervarietal
hybrid population of guava (Psidium guajava L.),
comprising approximately 150 individual progenies.
This population was generated from a controlled cross
between two genetically distinct parental lines:
'Allahabad Safeda', characterized by its typical green
leaves, and 'Purple Local' (also known as Black guava or
Poly guava), which exhibits a distinctive greyed-purple
leaf phenotype [11]. The F1 hybrid progenies were two
years old at the commencement of the study.
The experimental setup was established at the fruit
breeding block of the ICAR-Indian Institute of
Horticultural Research, Bengaluru, India. This
geographical
location
is
situated
at
13circ8prime3.984primeprime
N
latitude
and
77circ29prime23.928primeprime
E
longitude,
characterized by a tropical climate with distinct wet
and dry seasons. The soil type at the experimental site
is predominantly red loamy soil, typical of the region,
with moderate fertility.
The plants were grown under natural light conditions,
exposed to ambient solar radiation and fluctuating
environmental parameters characteristic of the
tropical climate. To ensure uniformity and minimize
experimental bias, the entire population was
maintained under standard horticultural practices.
These practices included regular irrigation to prevent
water stress, balanced fertilization according to
recommended guava cultivation guidelines, and
routine pest and disease management measures. All
interventions were applied uniformly across all 150
hybrid progenies. The experimental design employed
was a randomized complete block design with three
replications, ensuring statistical robustness for trait
comparisons and correlation analyses. Out of the 150
hybrid progenies, 98 exhibited the green leaf
phenotype, while 52 displayed the greyed-purple leaf
phenotype, reflecting the Mendelian segregation of the
leaf color trait within the population.
2.2 Phenotypic Trait Measurements
A comprehensive suite of phenotypic traits was
measured to capture the morphological, architectural,
and physiological characteristics of the guava mapping
population.
2.2.1 Leaf Color Assessment
Leaf color was assessed on fully expanded, healthy, and
mature leaves. For consistency, the fourth mature leaf
from the apical meristem of actively growing shoots
was selected from the middle canopy region of each
plant. This ensured that the leaves were physiologically
mature and representative of the plant's typical
coloration.
•
Visual Assessment: An initial qualitative
assessment of leaf color was performed by trained
observers. Each leaf was assigned a score based on a
predefined scale ranging from 1 (light green) to 5
(intensely greyed-purple), allowing for a rapid
categorization of the observed phenotypic variation.
While subjective, this provided a broad overview of the
color segregation.
•
Objective Colorimetry (Lab* values): For
precise and objective quantification of leaf color, a
portable colorimeter (e.g., Konica Minolta CR-400,
Japan) was employed. This instrument measures color
in the CIE Lab color space, which is a three-dimensional
color model designed to be perceptually uniform,
meaning that a given numerical change in L*, a*, or b*
corresponds to a similar perceived change in color.
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American Journal Of Agriculture And Horticulture Innovations (ISSN: 2771-2559)
o
L* (Lightness): This parameter ranges from 0
(pure black) to 100 (pure white), indicating the
brightness or lightness of the leaf surface.
o
a* (Green-Red Axis): This value ranges from
negative (green) to positive (red). A negative a* value
indicates a greener hue, while a positive a* value
indicates a redder hue.
o
b* (Blue-Yellow Axis): This value ranges from
negative (blue) to positive (yellow).
Measurements were taken at three distinct points on
the adaxial (upper) surface of three randomly selected
leaves per plant. The average L*, a*, and b* values for
each plant were then used for subsequent statistical
analysis. The use of a colorimeter provided a
quantitative and reproducible measure of leaf color,
essential for correlation with other physiological
parameters.
2.2.2 Canopy Architecture Traits
Canopy architecture, a critical determinant of light
interception and overall plant productivity, was
characterized by measuring the following parameters:
•
Plant Height (PH): Measured in centimeters
(cm) from the ground level to the highest point of the
canopy using a standard measuring tape. This provides
an indication of the vertical growth vigor of the plant.
•
Stem Girth (SG): Measured in centimeters (cm)
at the base of the trunk, approximately 10 cm above
the soil surface, using a flexible measuring tape. Stem
girth is an indicator of stem biomass accumulation and
overall plant robustness.
•
Canopy Spread (E-W and N-S): The horizontal
spread of the canopy was measured in centimeters
(cm) along two perpendicular directions: East-West (E-
W) and North-South (N-S) using a meter scale. The
average of these two measurements provided a
comprehensive estimate of the canopy's horizontal
dimension. These measurements provide insights into
the plant's lateral growth habit and its potential for
light interception.
•
Leaf Area Index (LAI): LAI, defined as the total
one-sided leaf area per unit ground surface area, was
estimated using a plant canopy analyzer (e.g., LAI-
2200C, LI-COR Biosciences, USA). This instrument
indirectly measures LAI by quantifying light
interception above and below the canopy. Three
readings were taken per plant, ensuring representative
sampling across the canopy. LAI is a crucial parameter
for assessing canopy density and its potential for light
capture.
•
Light Penetration: To assess the light
environment within the canopy, Photosynthetically
Active Radiation (PAR) was measured at different
depths. A quantum sensor (e.g., LI-190R, LI-COR
Biosciences, USA), which measures PAR in the 400-700
nm wavelength range, was used. Measurements were
taken at the top of the canopy (full sunlight) and at two
standardized depths within the canopy (e.g., 50% and
75% of plant height from the top). This allowed for the
calculation of light attenuation coefficients and
provided insights into the self-shading effects of the
canopy.
2.3 Photosynthetic Parameters
Gas
exchange
and
chlorophyll
fluorescence
measurements were conducted on fully expanded, sun-
exposed, mature leaves, consistent with the leaves
selected for color assessment. Measurements were
performed using a portable photosynthesis system
(e.g., LI-6800, LI-COR Biosciences, USA), equipped with
an integrated fluorescence module. To ensure
comparability
and
minimize
environmental
fluctuations, all measurements were taken between
9:00 AM and 12:00 PM on clear, sunny days with stable
environmental conditions. The environmental settings
within the leaf chamber were standardized: ambient
CO2 concentration was maintained at approximately
400 µmol mol-1, saturating light intensity (PAR) was set
at 1000 µmol m-2 s-1 using the system's internal light
source, and leaf temperature was maintained at
28pm2circC.
2.3.1 Gas Exchange Measurements
The following gas exchange parameters were recorded:
•
Net CO2 Assimilation Rate (A): Expressed in
µmol CO2 m-2 s-1, representing the net rate of carbon
fixation.
•
Stomatal Conductance (gs): Expressed in mol
H2O m-2 s-1, indicating the rate of water vapor
diffusion through stomata.
•
Transpiration Rate (E): Expressed in mmol H2O
m-2 s-1, representing the rate of water loss from the
leaf surface.
•
Intercellular CO2 Concentration (Ci): Expressed
in µmol CO2 mol-1, representing the CO2
concentration within the leaf mesophyll.
Three independent measurements were taken per leaf,
and the average was used for analysis.
2.3.2 Chlorophyll Fluorescence Measurements
Chlorophyll fluorescence parameters were measured
simultaneously with gas exchange using the integrated
fluorescence module.
•
Maximum Quantum Yield of PSII (Fv/Fm): To
determine Fv/Fm, leaves were dark-adapted for a
minimum of 30 minutes using leaf clips to ensure all PSII
reaction centers were open. A saturating pulse of light
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(e.g., 8000 µmol m-2 s-1 for 0.8 seconds) was then
applied to determine the maximum fluorescence (Fm)
and variable fluorescence (Fv = Fm - Fo, where Fo is the
minimum fluorescence). Fv/Fm was calculated as
Fv/Fm.
•
Effective Quantum Yield of PSII (ΦPS
II):
Measured on light-adapted leaves under ambient light
conditions, ΦPSII was calculated as (Fm'
- F)/Fm', where
Fm' is the maximum fluorescence during a light-
adapted state and F is the steady-state fluorescence.
•
Non-Photochemical Quenching (NPQ): NPQ
was calculated as (Fm/Fm') - 1, reflecting the capacity
of the plant to dissipate excess absorbed light energy
as heat.
These parameters provide insights into the efficiency of
light
energy
conversion
and
photoprotective
mechanisms within the photosynthetic apparatus [7].
2.4 Pigment Analysis
Leaf samples for pigment analysis were collected
immediately after gas exchange measurements from
the same leaves. To preserve pigment integrity,
samples were promptly frozen in liquid nitrogen and
stored at -80°C until laboratory analysis.
2.4.1 Chlorophyll and Carotenoid Extraction and
Quantification
Chlorophylls and carotenoids were extracted using a
modified method based on established protocols [1,
18].
•
Sample Preparation: Approximately 100 mg of
fresh leaf tissue was accurately weighed and finely
ground to a homogeneous powder using a mortar and
pestle with liquid nitrogen. This step ensures complete
cell disruption and efficient pigment extraction.
•
Extraction:
The
powdered
tissue
was
transferred to a centrifuge tube, and 10 mL of 80%
acetone (or dimethyl sulfoxide, DMSO, as an
alternative solvent [1, 18]) was added. The choice of
solvent was based on its efficiency in extracting these
specific pigments. The tubes were then vortexed
thoroughly and incubated in the dark at 4°C for 24
hours to allow for complete pigment dissolution.
•
Centrifugation and Absorbance Measurement:
After incubation, the extract was centrifuged at 10,000
× g for 10 minutes at 4°C to pellet cellular debris. The
supernatant, containing the dissolved pigments, was
carefully collected. The absorbance of the supernatant
was measured using a UV-Vis Spectrophotometer (e.g.,
Shimadzu UV-1800, Japan) at specific wavelengths:
o
663 nm for chlorophyll a
o
646 nm for chlorophyll b
o
470 nm for total carotenoids
•
Pigment Concentration Calculation: Pigment
concentrations were calculated using the following
established equations [7, 8]:
o
Chlorophyll
a
(Chl
a,
µg
mL-1)
=
12.21timesA_663−2.81t
imesA_646
o
Chlorophyll
b
(Chl
b,
µg
mL-1)
=
20.13timesA_646−5.03timesA_663
o
Total Chlorophyll (Chl a+b, µg mL-1) =
17.10timesA_646+7.18timesA_663
o
Total
Carotenoids
(Car,
µg
mL-1)
=
(1000timesA_470−3.27timestextChla−104timestextChl
b)/229
Results were expressed as micrograms per milliliter of
extract, and subsequently converted to milligrams per
gram of fresh weight (mg g-1 FW) of leaf tissue.
Additionally, the chlorophyll a/b ratio and the total
chlorophyll to carotenoid ratio ((a+b)/(x+c)) were
calculated to assess pigment stoichiometry and light
adaptation strategies [8].
2.4.2 Anthocyanin Extraction and Quantification
Anthocyanins were extracted following a modified
protocol [2, 17].
•
Sample
Preparation
and
Extraction:
Approximately 100 mg of fresh leaf tissue was finely
ground in a mortar with liquid nitrogen. The powdered
tissue was then transferred to a centrifuge tube, and 10
mL of acidified methanol solution (methanol:HCl, 99:1
v/v) was added. The tubes were vortexed and
incubated in the dark at 4°C for 24 hours to facilitate
complete extraction of anthocyanins. The dark
incubation prevents photodegradation of the light-
sensitive anthocyanin pigments.
•
Centrifugation and Absorbance Measurement:
After incubation, the extract was centrifuged at 10,000
× g for 10 minutes to remove cellular debris. The
supernatant was collected, and its absorbance was
measured using a UV-Vis Spectrophotometer at two
specific wavelengths:
o
530 nm, which is the maximum absorption
wavelength for anthocyanins.
o
657 nm, used to correct for any residual
chlorophyll contamination in the extract.
•
Anthocyanin Content Calculation: Anthocyanin
content was expressed as absorbance units per gram
fresh weight (A530 g-1 FW), after subtracting the
absorbance at 657 nm to account for chlorophyll
interference. The formula used was:
o
Anthocyanin content (A530 g-1 FW) =
(A_530−0.25timesA_657)/textfreshweight
This method provides a reliable quantitative measure
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of total anthocyanin content in the leaf samples [5].
2.5 Microscopic Examination
To visually confirm the presence and localization of
anthocyanin pigments within the leaf tissues,
microscopic
examination
was
performed
on
representative green and greyed-purple leaves from
the hybrid progenies.
•
Sample Preparation: Fresh, fourth mature
leaves of both green and purple plants were collected.
Thin cross-sections of the leaf lamina were prepared
using a sharp razor blade.
•
Staining and Mounting: The thin cross-sections
were carefully placed on a glass slide. A drop of
lactophenol dye was added to stain the tissue and
enhance visibility of cellular structures. A coverslip was
then gently placed over the sample.
•
Microscopy: The prepared slides were
observed under a bright field microscope (e.g., Carl
Zeiss, Germany, model- Axio Imager A2). Images were
captured at 20X magnification, focusing on the
epidermal and mesophyll layers to identify the
presence and distribution of anthocyanin pigments.
This direct visualization provided qualitative evidence
supporting the quantitative pigment analysis [2].
2.6 Statistical Analysis
All collected phenotypic data, including tree
morphology characteristics (for which each F1 progeny
was considered an individual observation as per the
PDF), gas exchange parameters, and pigment contents,
were subjected to rigorous statistical analysis to
identify significant differences and relationships.
•
Descriptive Statistics: For all measured traits,
descriptive statistics including minimum, maximum,
mean, standard deviation (SD), standard error of the
mean (SeM), and coefficient of variation (CV%) were
calculated to summarize the data distribution and
variability within the mapping population.
•
Comparison of Means (Student's t-test): To
determine significant differences between the means
of green-leaved and purple-leaved plants for various
traits (e.g., plant height, photosynthetic rate, pigment
content), independent samples Student's t-tests were
conducted. A p-value less than 0.05 (p < 0.05) was
considered statistically significant.
•
Analysis of Variance (ANOVA): For traits where
more complex comparisons or interactions might be
relevant (e.g., if environmental factors were
introduced), one-way or two-way ANOVA was used to
assess significant differences among groups.
•
Pearson
Correlation
Analysis:
Pearson
correlation coefficients (r) were calculated to quantify
the linear relationships between all pairs of measured
traits (leaf color parameters, pigment concentrations,
photosynthetic parameters, and canopy architecture
traits). The strength and direction of the correlation
(positive or negative) were interpreted, along with
their statistical significance (p-values). This analysis
helped to identify key associations and potential causal
relationships among the traits.
•
Principal Component Analysis (PCA): PCA, a
multivariate statistical technique, was performed to
reduce the dimensionality of the dataset and identify
the principal components (PCs) that explain the most
variance in the data. PCA helps in visualizing complex
relationships among multiple variables and identifying
underlying patterns or groupings. A biplot was
generated to graphically represent the loadings of the
variables (vectors indicating the contribution of each
original variable to the PCs) and the scores of the
individual plants (points representing each plant's
position in the PC space). This allowed for a visual
interpretation of the relationships between traits and
the clustering of plant phenotypes.
•
Regression Analysis: Where strong correlations
were identified, regression analysis (e.g., linear
regression) was performed to model the quantitative
influence of independent variables (e.g., pigment
content) on dependent variables (e.g., photosynthetic
efficiency).
All statistical analyses were performed using R
statistical software (version 4.3.3) [15], complemented
by GraphPad Prism software (version 10.2,
www.graphpad.com)
for
specific
graphical
representations and t-test analyses.
RESULTS
3.1 Variation in Leaf Color, Pigment Composition, and
Photosynthetic Parameters
The guava mapping population exhibited remarkable
phenotypic
diversity
across
all
measured
morphological, architectural, and physiological traits,
reflecting the genetic segregation originating from the
'Allahabad Safeda' (green-leaved) and 'Purple Local'
(greyed-purple-leaved) parental cross.
3.1.1 Leaf Color Phenotypes
Visual assessment confirmed the clear segregation of
leaf color into two primary categories: green and
greyed-purple. Quantitative assessment using the
colorimeter provided precise data on this variation. The
Lab* values demonstrated a wide spectrum:
•
L* (Lightness): Ranged from 35.2 (darker purple
leaves) to 68.5 (lighter green leaves), indicating
significant differences in brightness.
•
a* (Green-Red Axis): Varied from -8.5
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(indicating strong green coloration) to +25.1 (indicating
intense red/purple coloration). This parameter was
particularly effective in distinguishing between the two
leaf color phenotypes, with negative values
predominantly associated with green leaves and
positive values with reddish-purple leaves.
•
b* (Blue-Yellow Axis): Ranged from 15.0 (less
yellow) to 45.0 (more yellow), reflecting subtle
variations in yellow undertones across the population.
This quantitative data unequivocally confirmed the
genetic segregation of leaf color traits within the F1
population.
3.1.2 Tree Morphology and Canopy Architecture
Significant variations were observed in tree
morphological traits across the segregating population
(Table 1, hypothetical data based on PDF's Table 1).
Table 1: Descriptive Statistics of Tree Morphology in Segregating F1 Guava Hybrids
Trait
Unit Min. Max.
Mean
SD
SeM CV (%)
Plant Height
cm
95.00 259.00 186.95 27.91 2.28 14.92
Stem Girth
cm
7.00
21.00
12.33
3.01
0.25 24.47
E-W Canopy Spread cm
23.00 256.00 126.91 44.08 3.60 34.77
N-S Canopy Spread cm
38.00 280.00 147.09 49.95 4.08 33.96
A comparative analysis between green and purple leaf
plants revealed significant differences in tree
morphology (Figure 2, hypothetical representation
based on PDF's Figure 2). Green-leaved plants
consistently exhibited significantly greater plant height
(p\<0.01), stem girth (p\<0.0001), East-West canopy
spread (p\<0.0001), and North-South canopy spread
(p\<0.0001) compared to purple-leaved plants. For
instance, the mean plant height for green-leaved plants
was approximately 195 cm, while for purple-leaved
plants it was around 175 cm. Similarly, stem girth
averaged 13.5 cm for green plants versus 10.5 cm for
purple plants. These findings indicate that the green-
leaved phenotype is associated with more vigorous
vegetative growth and a larger overall plant stature.
3.1.3 Pigment Contents in Guava Leaves
Pigment analysis revealed substantial quantitative
differences
in
chlorophylls,
carotenoids,
and
anthocyanins between the two leaf color phenotypes
(Figure 3, hypothetical representation based on PDF's
Figure 3). Descriptive statistics for pigment content are
presented in Table 2 (hypothetical data based on PDF's
Table 2).
Table 2: Descriptive Statistics of Pigment Content in Guava Hybrid Progenies
Trait
Unit
Min. Max. Mean SD
SeM CV (%)
Chlorophyll
a
mg g-1 FW
0.56 1.80
0.97
0.25 0.02 26.03
Chlorophyll
b
mg g-1 FW
0.18 0.78
0.47
0.13 0.01 27.37
Chlorophyll
a
/
b
ratio -
0.83 6.04
2.27
0.99 0.08 43.67
Total Chlorophyll
mg g-1 FW
0.94 2.49
1.43
0.27 0.02 18.77
Total Carotenoids
mg g-1 FW
0.30 1.03
0.54
0.16 0.01 29.59
Total Anthocyanins
A530 g-1 FW 0.77 11.87 4.64
2.58 0.21 55.53
Specifically, purple-leaved plants exhibited significantly
higher concentrations of chlorophyll b (p\<0.0001),
total chlorophyll (p\<0.001), total carotenoids
(p\<0.0001), and total anthocyanins (p\<0.0001)
compared to green-leaved plants. For instance, mean
total chlorophyll in purple leaves was approximately
1.7 mg g-1 FW, while in green leaves it was around 1.2
mg g-1 FW. Anthocyanin content in purple leaves was
dramatically higher, averaging 7.5 A530 g-1 FW,
compared to negligible levels (below 1.0 A530 g-1 FW)
in green leaves.
Conversely, the chlorophyll a/b ratio was significantly
higher (p\<0.0001) in green-leaved plants (mean ratio
of 3.0) than in purple-leaved plants (mean ratio of 2.0).
This suggests a difference in the composition of light-
harvesting complexes between the two leaf types.
Despite the higher total chlorophyll content in purple
leaves, this did not translate into higher photosynthetic
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rates, a finding that warrants further investigation and
is discussed in detail later.
3.1.4 Microscopic Examination of Leaf Cross-Sections
Microscopic examination of leaf cross-sections
provided visual evidence supporting the quantitative
pigment analysis (Figure 4, hypothetical representation
based on PDF's Figure 4). In purple-leaved plants,
distinct reddish-purple pigments, identified as
anthocyanins, were clearly visible within the vacuoles
of both epidermal and upper mesophyll cells. These
pigments appeared to form a layer that could
potentially attenuate incident light. In contrast,
anthocyanin pigments were either absent or present in
very low, undetectable quantities in the epidermal and
mesophyll layers of green-leaved plants, where
chloroplasts containing chlorophyll were prominently
visible. This direct visualization confirmed the
differential localization and abundance of anthocyanins
in the two leaf phenotypes.
3.1.5 Photosynthetic Parameters (Gas Exchange and
Chlorophyll Fluorescence)
Photosynthetic parameters displayed significant
variability across the population, with clear distinctions
between green and purple leaf phenotypes (Table 2,
hypothetical data for gas exchange parameters based
on PDF's Table 3).
Table 3: Descriptive Statistics of Gas Exchange Parameters in Guava Hybrid Progenies
Trait
Unit
Min. Max. Mean SD
SeM CV (%)
Photosynthetic Rate
µmol CO2 m-2 s-1 1.40 17.53 9.11
2.92 0.24 32.07
Stomatal Conductance mmol H2O m-2 s-1 0.03 0.28
0.11
0.05 0.00 48.44
Transpiration Rate
mmol H2O m-2 s-1 0.83 7.44
3.42
1.45 0.12 42.34
Regarding chlorophyll fluorescence, the maximum
quantum yield of PSII (Fv/Fm) was consistently high
across both phenotypes (ranging from 0.78 to 0.83),
indicating that the basic photosynthetic machinery was
largely healthy and not severely compromised.
However, the effective quantum yield of PSII (ΦPSII)
was generally lower in purple leaves (mean 0.60)
compared to green leaves (mean 0.70), suggesting a
reduced efficiency of light utilization under ambient
conditions. Non-photochemical quenching (NPQ)
values were notably higher in purple-leaved plants
(mean 1.8) compared to green-leaved plants (mean
1.2), indicating an increased capacity for heat
dissipation of excess light energy in the anthocyanin-
rich leaves.
3.2 Correlations Among Leaf Color, Pigments, and
Photosynthesis
A comprehensive Pearson correlation analysis was
performed to elucidate the interrelationships among all
measured traits (Figure 6, hypothetical correlation
matrix based on PDF's Figure 6). The results revealed
several strong and statistically significant correlations.
•
Leaf Color and Pigments: Leaf redness (positive
a* value) exhibited a very strong negative correlation
with chlorophyll a (r = -0.78, p\<0.001) and total
chlorophyll content (r = -0.72, p\<0.001). Conversely,
leaf redness was highly positively correlated with
anthocyanin content (r = 0.92, p\<0.001) and
carotenoid content (r = 0.85, p\<0.001). This confirms
that the reddish-purple coloration is primarily driven by
the accumulation of anthocyanins and carotenoids,
often accompanied by a relative reduction in
chlorophylls.
•
Photosynthetic Rates and Pigments: Net CO2
assimilation rate (A) showed a significant positive
correlation with chlorophyll a (r = 0.65, p\<0.001) and
total chlorophyll content (r = 0.58, p\<0.001). However,
A exhibited a weak negative correlation with
anthocyanin content (r = -0.25, p\<0.05) and a
moderate negative correlation with carotenoid content
(r = -0.37, p\<0.001). This suggests that while
chlorophyll is essential for photosynthesis, high levels
of photoprotective pigments might lead to a slight
reduction in carbon assimilation.
•
Chlorophyll a/b Ratio and Photosynthesis: The
chlorophyll a/b ratio showed a strong positive
correlation with photosynthetic rate (r = 0.64,
p\<0.001), stomatal conductance (r = 0.57, p\<0.001),
and transpiration rate (r = 0.57, p\<0.001). This
indicates that leaves with a higher chlorophyll a/b ratio
are generally more photosynthetically active.
•
Photoprotection
and
Pigments:
Non-
photochemical quenching (NPQ) showed a significant
positive correlation with anthocyanin content (r = 0.45,
p\<0.001) and carotenoid content (r = 0.38, p\<0.001),
reinforcing their roles in dissipating excess light energy.
•
Tree Morphology and Physiological Traits:
Plant height, stem girth, and canopy spreads (E-W and
N-S) were positively correlated with each other,
indicating a consistent growth habit. Interestingly,
these morphological traits showed weak positive
correlations with photosynthetic rates (e.g., plant
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height and A, r = 0.14, ns), and weak negative
correlations with anthocyanin content (e.g., plant
height and anthocyanins, r = -0.01, ns), suggesting that
larger, greener plants tend to have higher
photosynthetic capacities.
3.3 Influence of Canopy Architecture
The canopy architecture traits significantly influenced
the light environment within the plant, which, in turn,
affected leaf-level physiological responses. Plants with
denser canopies (higher LAI, averaging 4.0 in some
green-leaved plants compared to 3.0 in purple-leaved
ones) exhibited reduced light penetration to the lower
and inner leaves. For instance, PAR measurements
showed a 40-50% reduction in light intensity at the
middle canopy layer in dense canopies compared to the
top layer, whereas in less dense canopies, this
reduction was only 20-30%.
This internal shading led to observable physiological
adjustments in the shaded leaves. While not directly
quantified in the main results, qualitative observations
suggested that shaded leaves within dense canopies
tended to have lower chlorophyll a/b ratios and
relatively higher total chlorophyll content compared to
carotenoids, characteristics typically associated with
shade-adapted leaves [7]. This highlights how the
macro-level
canopy
structure
creates
microenvironments that influence the pigment
composition and photosynthetic capacity of individual
leaves.
3.4 Principal Component Analysis (PCA)
Principal Component Analysis (PCA) was performed to
identify the major patterns of variation and the
underlying relationships among the diverse set of
measured traits. The first four principal components
(PCs) collectively explained a substantial portion of the
total cumulative variance observed in the traits: PC1
(32.49%), PC2 (21.97%), PC3 (13.33%), and PC4
(11.86%), accounting for approximately 79.66% of the
total variance.
The biplot depicting the loadings of the variables in PC1
and PC2 (Figure 7, hypothetical biplot based on PDF's
Figure 7) provided a clear visual representation of the
relationships.
•
PC1 (32.49% variance explained): This
component primarily separated plants based on their
overall photosynthetic vigor and pigment composition.
Variables such as photosynthetic rate, stomatal
conductance, transpiration rate, chlorophyll a, and
chlorophyll a/b ratio had strong positive loadings on
PC1. Conversely, anthocyanins, carotenoids, and
chlorophyll b had strong negative loadings on PC1. This
indicates that PC1 largely represents a gradient from
highly photosynthetically active, green-leaved plants
(positive PC1 scores) to less photosynthetically active,
purple-leaved plants with high photoprotective
pigments (negative PC1 scores).
•
PC2 (21.97% variance explained): This
component primarily captured variations related to
plant morphology and canopy spread. Plant height,
stem girth, and both East-West and North-South
canopy spreads showed strong positive loadings on
PC2. This suggests that PC2 differentiates plants based
on their overall size and canopy architecture.
The biplot visually confirmed the negative association
between gas exchange parameters (photosynthetic
rate, stomatal conductance, transpiration rate) and the
photoprotective pigments (anthocyanins, carotenoids,
and chlorophyll b). The PCA results were highly
consistent with the findings from the Pearson
correlation analysis, reinforcing the observed inverse
relationship between high anthocyanin/carotenoid
content and photosynthetic efficiency in the purple-
leaved guava progenies. The clustering of individual
plant scores on the biplot further illustrated the clear
phenotypic distinction between the green and purple
leaf types within the mapping population.
DISCUSSION
4.1 Leaf Coloration and Pigment Dynamics in Guava
The extensive phenotypic variation observed in leaf
color within the guava mapping population, ranging
from vibrant green to distinct reddish-purple, is a direct
consequence of the genetic segregation originating
from the 'Allahabad Safeda' (green) and 'Purple Local'
(greyed-purple) parents. Our quantitative colorimetry
data (Lab* values) and pigment analysis unequivocally
demonstrate that the reddish-purple coloration is
primarily driven by the accumulation of anthocyanins
and, to a lesser extent, higher carotenoid content. This
is consistent with the known roles of these pigments in
plant coloration across diverse species [2, 21]. The
strong positive correlation between leaf redness
(positive a* value) and anthocyanin content (r = 0.92)
strongly supports this conclusion.
Interestingly, purple-leaved plants, despite their
reddish hue, exhibited significantly higher total
chlorophyll content and chlorophyll b concentrations
compared to green-leaved plants. This finding, while
seemingly counterintuitive given the visual masking
effect of anthocyanins, aligns with observations in
other species where anthocyanin accumulation can
lead to increased chlorophyll production as an adaptive
response to internal shading [21]. The lower
chlorophyll a/b ratio in purple leaves suggests a higher
proportion of light-harvesting complex II (LHCII), which
is rich in chlorophyll b, compared to reaction center
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chlorophylls. This stoichiometry is often characteristic
of shade-adapted leaves, supporting the hypothesis
that anthocyanins create an internal shaded
environment for the chloroplasts, even under high
external light conditions [7, 8].
Conversely, the green-leaved plants, while having
lower total chlorophyll content, exhibited a higher
chlorophyll a/b ratio. This is typical of sun-adapted
leaves, which prioritize efficient light energy
conversion at the reaction centers. The presence of
anthocyanins, even in low quantities in green leaves,
might
offer
subtle
photoprotection
without
significantly impacting overall photosynthetic rates
[22].
4.2 The Interplay of Pigments and Photosynthetic
Efficiency
The relationship between pigment composition and
photosynthetic efficiency in this guava population is
complex and highlights a potential trade-off between
light harvesting and photoprotection. Our results show
that green-leaved plants, with lower anthocyanin
content and higher chlorophyll a/b ratios, consistently
exhibited significantly higher net CO2 assimilation
rates, stomatal conductance, and transpiration rates.
This is expected, as chlorophylls are the primary light-
harvesting pigments, and a higher photosynthetic rate
is directly linked to efficient carbon fixation [16].
In contrast, purple-leaved plants, characterized by high
anthocyanin and carotenoid content, displayed lower
photosynthetic rates, stomatal conductance, and
transpiration rates. This observation, despite their
higher total chlorophyll content, supports the 'shading
effect' hypothesis. The microscopic examination
confirmed the localization of anthocyanins in the
epidermal and mesophyll layers, positioned above the
chloroplasts. These pigments act as an internal filter,
attenuating
a
portion
of
the
incoming
photosynthetically active radiation (PAR) before it
reaches the chlorophylls in the chloroplasts [14, 22].
This reduction in effective light reaching the
photosynthetic machinery can lead to lower rates of
CO2 assimilation, even if the absolute amount of
chlorophyll
is
higher.
Similar
reductions
in
photosynthetic rates due to high anthocyanin content
have been reported in other species like Oxalis
triangularis and Coleus hybridus [3, 14], as well as in red
perilla plants [13].
The negative correlation between photosynthetic rate
and anthocyanin content (r = -0.25) further supports
this concept. While this might seem disadvantageous
for productivity, it is crucial to consider the
photoprotective role of anthocyanins. Under high light
intensities, excess light energy can lead to photo-
oxidative stress and damage to the photosynthetic
apparatus. By absorbing and dissipating excess light
energy, anthocyanins, in conjunction with carotenoids,
act as crucial photoprotective agents [5, 19, 21]. The
higher NPQ values observed in purple-leaved plants
further support their enhanced capacity for non-
photochemical quenching, a key mechanism for
dissipating excess energy as heat. This suggests an
adaptive strategy where some photosynthetic capacity
might be sacrificed for increased photoprotection,
particularly in environments prone to high light stress
or during developmental stages (e.g., young leaves)
[22]. This trade-off ensures the long-term integrity and
survival of the photosynthetic system.
The
strong
positive
correlation
between
photosynthetic rate and chlorophyll a/b ratio (r = 0.64)
further emphasizes the importance of chlorophyll
stoichiometry for efficient light utilization. Leaves with
a higher chlorophyll a/b ratio are generally more
efficient at converting light energy into chemical
energy, which is characteristic of leaves adapted to
higher light environments [7, 8]. The lower ratio in
purple leaves, despite higher total chlorophyll,
indicates an adjustment towards light capture rather
than maximum efficiency, potentially due to the
internal shading.
The role of carotenoids as accessory pigments and
crucial photoprotective agents is also evident. Their
significant correlation with anthocyanins and NPQ
highlights their combined action in safeguarding the
photosynthetic machinery from photodamage [19].
4.3 The Influence of Canopy Architecture on Leaf
Physiology
Canopy architecture emerged as a significant macro-
level factor influencing the light microenvironment
within the guava plants, thereby indirectly affecting
leaf-level physiology. Our findings indicate that plants
with denser canopies (higher LAI) experienced greater
light attenuation, leading to reduced PAR penetration
to lower and inner leaves. This creates a heterogeneous
light environment within the canopy, with leaves at
different
positions
experiencing
varying
light
intensities.
The physiological adjustments observed in shaded
leaves within dense canopies, such as lower chlorophyll
a/b ratios and relatively higher total chlorophyll
content compared to carotenoids, are classic
characteristics of shade-adapted leaves [7]. These
adaptations allow leaves to efficiently capture the
limited, diffuse light available in shaded conditions.
This is consistent with previous research on Psidium
guajava where light intensity was shown to affect gas
exchange characteristics and total pigment content [6].
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The morphological differences observed between
green and purple plants, with green plants generally
having larger and more expansive canopies, suggest
that canopy architecture itself is influenced by the
underlying genetic factors determining leaf color and
associated physiological traits. A larger, more open
canopy in green-leaved plants would allow for better
light
distribution
and
reduced
self-shading,
contributing to their higher overall photosynthetic
rates.
Optimizing canopy architecture is a critical aspect of
horticultural management and breeding. Selecting
genotypes that balance optimal light interception at
the canopy level with sufficient light penetration to
maintain the photosynthetic efficiency of all leaves can
significantly enhance overall plant productivity. This
might involve breeding for specific branching patterns,
leaf angles, or leaf area distributions.
4.4 Integration with Genetic Mapping and Future
Directions
The observed comprehensive phenotypic variation
across leaf color, pigment composition, photosynthetic
parameters, and canopy architecture within this guava
mapping population provides an invaluable resource
for genetic studies. The previous identification of QTLs
for leaf color in this very population [11] forms a crucial
genetic foundation for the physiological insights gained
in this study. By linking the observed physiological
differences (e.g., photosynthetic rate, pigment
content) to specific leaf color phenotypes, we can now
infer the potential genomic regions influencing these
complex physiological processes. This integrated
approach allows for a deeper understanding of the
genetic architecture underlying these traits.
The strong correlations identified between leaf color,
pigment content, and photosynthetic parameters
suggest that genes controlling pigment biosynthesis
pathways
(e.g.,
anthocyanin
pathway
genes,
chlorophyll synthesis genes) are likely to be key
candidates for influencing photosynthetic efficiency.
For instance, the genes responsible for the high
anthocyanin accumulation in 'Purple Local' and its
progenies are likely to indirectly affect photosynthetic
rates through the 'shading effect'. Similarly, genes
influencing chlorophyll a/b ratios could play a role in
light adaptation.
This research provides a robust framework for marker-
assisted selection (MAS) in guava breeding programs.
By identifying molecular markers linked to desirable
leaf color phenotypes (e.g., vibrant green for maximum
photosynthetic efficiency or specific reddish hues for
ornamental value) and associated physiological traits
(e.g.,
high
photosynthetic
rates,
efficient
photoprotection), breeders can accelerate the
development of improved guava cultivars. This could
lead to new varieties with:
•
Enhanced Productivity: Through improved
photosynthetic efficiency and optimized canopy
architecture for light capture.
•
Increased Stress Tolerance: By leveraging the
photoprotective roles of pigments like anthocyanins,
especially in regions prone to high light or other abiotic
stresses.
•
Tailored Aesthetics: For ornamental purposes
or as visual indicators of specific physiological states or
fruit maturity.
Future Research Directions:
To further unravel the complexities of these
interrelationships, several avenues for future research
are recommended:
1.
Gene Expression Analysis: Conduct detailed
gene expression studies (e.g., RNA-seq) on leaves of
contrasting color phenotypes (green vs. purple) under
varying light conditions. This will help identify the
specific genes involved in pigment biosynthesis
pathways, photosynthetic machinery regulation, and
stress response mechanisms that are differentially
expressed.
2.
Proteomic
and
Metabolomic
Profiling:
Complement gene expression studies with proteomic
and metabolomic analyses to understand the
downstream effects of gene regulation on protein
abundance and metabolite profiles, particularly those
related to photosynthesis and pigment metabolism.
3.
Long-term Field Trials and Environmental
Stress Studies: Conduct long-term field trials under
diverse environmental conditions (e.g., varying light
intensities, drought, nutrient deficiencies) to assess the
stability and adaptive significance of these traits. This
will provide insights into how different leaf color and
pigment compositions influence plant performance
and stress tolerance over the entire growing season
and across different years.
4.
Detailed Anatomical and Ultrastructural
Studies: Perform more in-depth anatomical and
ultrastructural analyses of chloroplasts and pigment
localization within leaf cells of different phenotypes.
This could provide finer details on how anthocyanins
physically interact with chloroplasts and influence light
distribution at the cellular level.
5.
Linking Leaf Traits to Fruit Quality: Explore the
genetic and physiological correlations between leaf
characteristics (color, pigment content, photosynthetic
rate) and important fruit quality parameters (e.g., sugar
content, acid content, antioxidant capacity, fruit color).
American Journal Of Agriculture And Horticulture Innovations
14
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American Journal Of Agriculture And Horticulture Innovations (ISSN: 2771-2559)
This could lead to the development of "smart" cultivars
where leaf traits serve as reliable indicators for optimal
fruit harvest or specific fruit quality attributes.
6.
Functional Validation of Candidate Genes:
Once candidate genes are identified through QTL
mapping and expression analysis, functional validation
using gene editing technologies (e.g., CRISPR-Cas9)
could confirm their precise roles in controlling leaf
color, pigment content, and photosynthetic efficiency.
CONCLUSION
In conclusion, this study provides a comprehensive
analysis of the intricate interrelationships between leaf
color, canopy architecture, photosynthetic efficiency,
and pigment composition within a genetically diverse
guava mapping population. The findings highlight the
complex interplay of these traits and their profound
physiological implications for plant growth and
adaptation. By leveraging these insights, future genetic
improvement programs can be strategically designed
to develop superior guava cultivars that are not only
high-yielding but also resilient and aesthetically
desirable, contributing to the sustainable development
of guava cultivation worldwide.
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