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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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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 body 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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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 (ΦPSII): 
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_663−2.81timesA_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). 



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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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