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Pinus wallichiana, commonly known as the Himalayan blue pine, holds significant ecological and economic importance in the northwestern Himalayan region. Understanding the genetic traits and variability within its seedling population is essential for sustainable forest management and conservation efforts. This study aimed to quantify and assess the genetic traits of Pinus wallichiana seedlings within a nursery environment situated in the northwestern Himalayas. Our research involved the collection and analysis of data from a representative sample of Pinus wallichiana seedlings from different sites in Himachal Pradesh in 2019–2020. Results revealed a diverse genetic pool with notable heritability for key traits, highlighting the potential for selective breeding and genetic improvement programs. Furthermore, our findings provide valuable insights into the adaptation and resilience of Pinus wallichiana to changing environmental conditions, which is crucial for addressing the challenges posed by climate change. The quantification of genetic traits in this study not only enhances our understanding of the species but also offers practical applications for forest managers and policymakers in the region. This research contributes to the broader context of forest genetics and underscores the importance of genetic conservation efforts for the sustainable management of Pinus wallichiana in the northwestern Himalayas.
Silviculture and Forest Management Division, Forest Research Institute, Dehradun, Uttarakhand, India
Rajesh Monga
Clean Development Mechanism, KBSCertification Services, Faridabad, Haryana, India
*Address all correspondence to: amanjambh59@gmail.com, dr.amanjambh@gmail.com
1. Introduction
The Himalayan coniferous forests hold great importance due to their contributions in terms of timber resources, non-wood forest products, grazing areas, and the provision of habitats for endangered species. The Western Himalayan subalpine conifer forests, which cover an approximate area of 39,700 km2 across India, Nepal, Pakistan, and Afghanistan, are primarily characterized by the presence of four dominant tree species. These species include Pinus wallichiana (blue pine), Pinus gerardiana (Chilgoza pine), Abies pindrow (fir), and Picea smithiana (spruce) [1]. The blue pine, a large evergreen tree, is widely distributed throughout the Himalayan region. In the country of Bhutan, the growth of this particular entity occurs at an elevation of 3400 m.a.s.l. [2, 3]. Seeds play a crucial role in the perpetuation of a species, although the likelihood of seed germination is frequently unknown and challenging to predict. The natural regeneration of many coniferous tree species is mostly dependent on seed-based mechanisms. Seeds, however, exhibit considerable variations, potentially attributable to variations in altitudinal ranges, necessitating the collection of seeds from different elevations [4]. The process of evaluating genetic parameters for qualities in Pinus wallichiana seedlings within a nursery entails examining several genetic and environmental factors that contribute to the observed variations in traits.
Genetic parameters offer valuable insights into several aspects of genetic features, including their heritability, genetic connection, and potential for selective breeding. In the field of quantitative genetics, the idea of heritability is crucial because it enables us to determine how much selection influences traits and how likely it is that breeding will pass those traits down to subsequent generations. The heritability of qualities determines the degree to which they are transmitted through successive generations [5]. However, it is important to note that solely relying on heritability estimates does not offer a comprehensive understanding of the degree to which development might be influenced by selection. Estimates of heritability alone do not show how much growth can be expected from selection. High genetic advance along with high heritability offers the most effective condition for selection of specific traits [6]. To what extent a trait improves in response to a certain selection pressure can be thought of as a genetic advance [7]. Genotype-phenotype analyses are indispensable for estimating the strength of associations between traits. Researchers can gain a better understanding of the relationships between various traits and how selection may affect them by studying genotype and phenotype correlations [8]. This knowledge allows for a more comprehensive understanding of the factors that contribute to growth and the potential impact of breeding on future generations. Additionally, examining these correlations can help identify any potential limitations or constraints in breeding programs that may affect the transmission of desired traits. The objectives of the present study encompass a comprehensive investigation into several key aspects: Our objective is to conduct a rigorous comparative analysis of the growth parameters exhibited by Pinus wallichiana seedlings collected from diverse altitudinal zones. This analysis will be carried out under real-world field conditions following a thorough nursery screening process by examining factors such as height, diameter, and foliage characteristics and then estimating the genetic parameters of Pinus wallichiana; we seek to quantify and assess the genetic diversity within the studied population. This aspect of the study is pivotal for understanding the species’ genetic makeup, heritability of important traits, and the potential for genetic improvement and conservation efforts.
By pursuing these objectives, our research aims to provide a comprehensive understanding of how altitude influences the growth patterns of Pinus wallichiana seedlings while also shedding light on the genetic underpinnings of this ecologically and economically significant tree species.
Experimental site: The experiment was carried out during the years 2019–2020 at the forest nursery, Department of Silviculture and Agroforestry, Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan, Himachal Pradesh, India. In 2019–2020, a study in Himachal Pradesh to gather seeds from various altitudinal ranges 1800–2100 (A1), 2100–2400 (A2), 2400–2700 (A3), and > 2700 (A4) m.a.s.l. [9]. The nursery location is situated at a height of 1200 m.a.s.l. in the northwestern region of the Himalayas, between the latitudes of 30°51′ N and longitudes of 76°11′ E. The experimental site exhibits topographical variations, including elevations, depressions, and a gradual incline in the southeastern direction. The region has a diverse range of temperatures, spanning from a minimum of 1°C during the winter season to a maximum of 33°C in the months of May and June, which are characterized as the peak of summer. The yearly precipitation ranges from 0 to 342 mm, with the highest amount occurring during the monsoon season, which typically spans from July to September.
Sample collection: Cones were collected from five phenotypically superior trees located in different sites of Himachal Pradesh (Figure 1). These trees displayed exceptional esthetic qualities and were selected based on a minimum distance of 100 m between each other. The mature cones of Pinus wallichiana were obtained from phenotypical superior trees in the intermediate stage of their life cycle and exhibited overall good health.
Figure 1.
Study area map.
Prior to being sown, the seeds underwent a 60-day period of storage in a trench that consisted of discrete layers of sand and moss, which facilitated the process of breaking dormancy. Then, the 75 seeds per replication were subsequently seeded directly into root trainers that were filled with deodar forest soil mixed with FYM (Farmyard manure) at a ratio of 2:1. These root trainers were placed in polyhouse for 6 months and then in open nursery for hardening of the seedlings.
Design followed: Randomized Block Design.
Number of Replication: Three.
Parameters: The observations (Table 1) were documented in seedlings that were 12 months old (final week of December). For calculation of genetic parameter irrespective of altitude, 60 plants were selected 5 plants per treatment, and for altitudinal effect, 15 plants per altitude were selected for data calculation.
Traits
Method used
Germination (%)
GP=Number of healthy seeds germinatedNumber of seeds sownX100
Germination Capacity (%)
The cumulative number of seeds that germinated during the 28 days of test period plus the number of viable seeds at the end of the test expressed in percentage.
Germination Energy (%)
GE=Number of healthy seeds germinated upto the time of peak germinationNumber of seeds sownX100
Germination Speed
GV=∑DGSNXGPx10 Where DGS = Daily germination speed = Cumulative germination per cent/Number of test days. N = Frequency or number of DGS during the test GP = Germination per cent at the end of the test
Germination Value
GS=∑i=1nnumber of newly germinated seedsnumber of days since sowing
Seedling Height (cm)
It was measured with the help of a meter scale in centimeter from leading shoot tip to the collar region of the seedling at the ground surface.
Collar Diameter (mm)
The diameter of seedling was recorded in millimeters with the help of a digital Vernier caliper.
Needle Area (cm2)
The projected leaf area was determined on CI-202 Leaf Area Meter.
Root Length (cm)
The root length was measured with the help of using a digital caliper (Mitutoyo Absolute) from the cut base to the tip of the taproot.
Seedling Dry Weight (gm)
Total seedling dry weight was obtained by summing up root and shoot dry weight in gram.
Survival (%)
SP=Total percent germinationNumber of seeds germinated in the that seed source×100
Table 1.
Germination and growth parameters measured in the nursery.
Selecting individuals with optimal phenotypic expression is essential in the process of improving a trait. The developmental traits are the result of a combination of genetic and environmental variables. The computation of variability estimates and genetic parameters was performed for a range of seedling characteristics. The statistical measures of coefficient of variation and analysis of variance were computed for the phenotypic, genotypic, and environmental variations (Table 2). The study also involved the calculation of heritability estimates (in the broad sense), genetic advance (at a selection intensity of 5%), and genetic gain (expressed as a percentage of the mean). GCV and PCV can be categorized into three groups based on their magnitudes: low (less than 10%), moderate (10–20%), and high (more than 20%).
Sr. No.
Parameter name
Symbol
Calculation
Description
1.
Genotypic variance
Vg
Mt−MeR×100
Mt = Mean sum of square due to treatment Me = Mean sum of square due to error R = Number of replications. X = Mean of the character K = Selection intensity at 5 percent, which is equal to 2.06
2.
Phenotypic variance
Vp
Vg + Ve
3.
Environmental variance
Ve
Me
4.
Phenotypic coefficient of variation
PCV (%)
√VpX×100
5.
Genotypic coefficient of variance
GCV (%)
√VgX×100
6.
Environmental coefficient of variance
ECV (%)
√VeX×100
7.
Heritability in broad sense
h2 (%)
VgVp
8.
Genetic advance
GA
K. √VP* h2
9.
Genetic gain/Genetic advance as percent of mean
GG
GAX×100
Table 2.
Genetic parameters calculation methods.
Statistical analysis: The data obtained from the field experiment was subjected to analysis using the analysis of variance (ANOVA) approach using OPSTAT software (http://opstat.pythonanywhere.com/) and MS Excel, which is commonly employed for examining the effects of two factors at p-value (0.05). The analysis of variance (ANOVA) procedures were used to test for significant effect of treatments (Table 3).
Source of variation
Degree of freedom
Sum of squares
Mean sum of squares
F. Cal.
Replications
(r-1)
Sr
Srr−1=Mr
Mr/Me
Genotype
(g-1)
Sg
Stg−1=Mt
Mg/Me
Error
(r-1) (g-1)
Srg
Ser−1g−1=Me
Total
(rg-1)
S(rg-1)
Table 3.
Statistical analysis of the measured germination and growth traits.
Where r = Number of replications, g = Number of genotypes/Plant number, and M = Mean sum of square.
The calculated “F” values were compared with the tabulated “F” values at 5 percent level of significance. If the calculated value is higher than the tabulated value, it will be considered significant. Critical difference (CD) for comparing the means of any two treatments will be calculated as: SE (d)= ± (2Me/r) 1/2
Critical Difference (CD) = SE (d) × t (5%) value at error degrees of freedom. The calculation of predicted genetic advance at a selection intensity of 5 percent was performed using the formulas discussed in Table 2 [10], taking into account genotypic and phenotypic variances, environmental variances, and coefficients of variability.
3.1 Assessment of genotypic and phenotypic variability in nursery seedlings
The study aimed to assess the variability in germination and seedling growth characteristics among different seed sources, taking into account both genetic and environmental factors. A sample of five mother trees was used for cone and seed collection, and the results are presented in Table 4.
Traits
Variance
Coefficient of variance
HBS
GA
GAPM
CD (0.05)
EV
GV
PV
ECV
PCV
GCV
GC
6.29
75.6
81.9
4.04
14.6
14.0
0.92
17.1
27.6
1.96
GP
7.56
70.1
77.6
4.61
14.8
14.0
0.90
16.3
27.3
2.15
GE
2.80
4.37
7.18
4.88
7.81
6.10
0.61
3.35
9.76
1.31
GV
0.20
3.41
3.61
3.20
13.7
13.3
0.95
3.68
26.5
0.35
GS
0.10
0.74
0.84
10.3
29.1
27.2
0.88
1.65
52.3
0.25
SH
0.73
3.31
4.04
8.72
20.5
18.5
0.82
3.37
34.4
0.67
CD
0.06
1.16
1.21
8.13
37.9
37.0
0.95
2.15
74.2
0.18
NA
12.4
25.7
38.1
10.2
17.9
14.7
0.67
8.52
24.8
2.15
RL
7.59
16.8
24.4
17.4
31.2
25.9
0.69
6.97
44.1
2.75
SDW
0.01
0.04
0.05
24.3
49.1
42.6
0.75
0.34
75.9
0.09
SP
28.9
62.5
91.4
11.3
20.2
16.7
0.68
13.4
28.3
4.20
Table 4.
Genetic parameters analysis of the Pinus wallichiana seedlings, irrespective of altitudinal ranges.
The data in Table 4 indicate significant variation (p-value ≤0.05) in various characteristics among the seed sources. Notably, the survival rate, needle area, root length, and germination rate exhibited the highest levels of environmental diversity. This suggests that these traits are particularly influenced by environmental conditions. The study also revealed substantial variability in both genotypic and phenotypic characteristics, with germination capacity and plant survival showing the most significant variation. Additionally, the coefficient of variation for environmental, phenotypic, and genotypic components showed higher values for the dry weight of seedlings, indicating that this trait is influenced by a combination of genetic and environmental factors. On the other hand, collar diameter and germination value displayed the highest levels of broad-sense heritability, indicating a strong genetic component in these traits. Genetic advance and genetic gain were most prominent in germination capacity and germination percentage, whereas dry weight of seedlings and collar diameter showed the greatest potential for genetic improvement.
3.2 Assessment of genotypic and phenotypic variability across altitudinal gradients in nursery seedlings
Table 5 presents data illustrating significant variations (p-value ≤0.05) in germination and growth parameters across different altitudinal ranges. Environmental variance was notably high in survival percentage at altitude A4, highlighting the influence of altitude on this particular trait. Altitude A2 exhibited the highest genotypic and phenotypic variations in germination percentage, indicating the significance of altitude in shaping these characteristics. Furthermore, the coefficients of variance for environmental, genotypic, and phenotypic components were highest for the dry weight of seedlings at altitude A3, suggesting that this trait is influenced by both genetic and environmental factors, particularly at this altitude. Collar diameter at altitude A4 displayed the greatest degree of heritability, emphasizing the strong genetic influence on this trait. Needle area at altitude A1 also showed a high level of heredity. The study revealed that altitude A2 had the most significant genetic enhancement in germination percentage compared to other altitudes, while the most substantial genetic improvement was observed in the dry weight of seedlings at altitude A1. The disparity between phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) across all traits underscores the interplay between genetic and environmental factors in shaping these characteristics. This study highlights the pronounced influence of environmental factors in the A1 altitudinal range on seedling growth and development, emphasizing the importance of considering both genetic and environmental elements in the analysis of these traits.
ALT
GC
GP
GE
GV
GS
SH
CD
NA
RL
SDW
SP
EV
A1
5.12
3.28
0.59
0.07
0.05
0.87
0.04
0.47
13.9
0.01
14.4
A2
5.48
4.06
0.80
0.22
0.12
0.35
0.07
12.9
4.87
0.01
13.2
A3
4.04
3.48
3.27
0.14
0.07
0.39
0.07
9.83
3.20
0.02
31.4
A4
2.49
0.85
2.46
0.32
0.08
0.35
0.01
1.97
2.95
0.01
34.5
PV
A1
14.1
17.5
1.20
0.35
0.17
0.87
0.15
43.7
22.3
0.05
20.8
A2
79.1
81.3
8.18
4.23
0.69
4.86
1.03
43.7
12.6
0.04
14.8
A3
22.5
15.1
4.98
1.07
0.99
1.25
0.73
17.8
4.17
0.08
58.0
A4
13.1
6.96
5.89
7.57
1.45
3.00
2.85
13.8
9.18
0.03
58.9
GV
A1
8.94
14.2
0.61
0.27
0.12
NA
0.11
43.2
8.48
0.04
6.42
A2
73.6
77.3
7.38
4.01
0.57
4.50
0.96
30.8
7.75
0.03
1.60
A3
18.4
11.6
1.71
0.93
0.92
0.86
0.67
7.95
0.97
0.06
26.6
A4
10.6
6.11
3.43
7.25
1.37
2.64
2.83
11.8
6.23
0.02
24.4
ECV
A1
3.12
2.61
2.20
1.87
6.37
7.92
7.56
1.82
17.6
18.7
6.56
A2
3.66
3.26
2.48
3.30
10.9
6.67
10.1
10.1
13.8
23.8
7.27
A3
3.51
3.38
5.45
2.60
8.84
6.34
8.15
9.97
12.8
27.0
13.4
A4
2.90
1.77
4.75
4.46
9.50
6.81
3.52
4.23
14.3
25.7
14.7
PCV
A1
5.17
6.01
3.14
4.06
12.1
7.90
14.5
17.6
22.3
52.0
7.89
A2
13.9
14.6
7.92
14.61
25.7
24.7
38.9
18.6
22.2
42.4
7.70
A3
8.28
7.05
6.73
7.28
33.2
11.3
27.2
13.4
14.6
56.9
18.2
A4
6.66
5.06
7.35
21.57
41.0
19.9
52.5
11.2
25.2
40.3
19.2
GCV
A1
4.12
5.42
2.23
3.61
10.2
NA
12.3
17.5
13.8
48.5
4.38
A2
13.4
14.2
7.52
14.2
23.3
23.8
37.6
15.6
17.4
35.1
2.53
A3
7.50
6.18
3.94
6.79
32.0
9.38
25.9
8.96
7.02
50.1
12.3
A4
5.99
4.74
5.61
21.10
39.8
18.6
52.4
10.4
20.8
31.1
12.3
HBS
A1
0.64
0.81
0.51
0.79
0.72
NA
0.73
0.99
0.38
0.87
0.31
A2
0.93
0.95
0.90
0.95
0.82
0.93
0.93
0.71
0.61
0.69
0.11
A3
0.82
0.77
0.34
0.87
0.93
0.69
0.91
0.45
0.23
0.77
0.46
A4
0.81
0.88
0.58
0.96
0.95
0.88
1.00
0.86
0.68
0.59
0.41
GA
A1
4.91
6.99
1.14
0.96
0.62
NA
0.57
13.5
3.69
0.40
2.90
A2
17.1
17.7
5.31
4.02
1.40
4.21
1.95
9.60
4.50
0.28
0.86
A3
8.01
6.16
1.58
1.86
1.91
1.58
1.60
3.88
0.98
0.46
7.20
A4
6.03
4.77
2.91
5.43
2.34
3.15
3.46
6.56
4.24
0.20
6.56
GAPM
A1
6.77
10.1
3.28
6.59
17.9
NA
21.7
35.8
17.4
93.2
5.02
A2
26.6
28.6
14.7
28.6
43.5
47.3
74.7
27.1
28.1
59.9
1.72
A3
14.0
11.18
4.76
13.1
63.5
16.0
50.9
12.3
6.97
90.8
17.2
A4
11.1
9.16
8.82
42.5
79.8
36.1
107
19.8
35.2
49.3
16.4
p-value (0.05)
A1
<0.0001
<0.0001
0.0008
<0.0001
<0.0001
0.4957
<0.0001
<0.0001
0.0092
<0.0001
0.0269
A2
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.2344
A3
<0.0001
<0.0001
0.0163
<0.0001
<0.0001
<0.0001
<0.0001
0.0027
0.0709
0.05
0.0021
A4
<0.0001
<0.0001
0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.005
CD (0.05)
A1
3.14
2.52
1.07
0.38
0.31
1.30
0.28
5.18
0.95
0.11
5.27
A2
3.25
2.80
1.25
0.65
0.49
0.83
0.37
3.07
4.98
0.15
5.05
A3
1.61
1.50
1.45
0.30
0.21
0.50
0.21
1.44
2.52
0.11
4.49
A4
2.19
1.28
2.18
0.79
0.39
0.82
0.16
2.39
1.95
0.14
8.16
Table 5.
Genetic parameter analysis of germination and growth traits of Pinus wallichiana along different altitudinal ranges.
The findings of this study suggest that root length, survival percentage, and germination percentage were predominantly influenced by site-specific and environmental factors. While heredity plays a significant role, it is clear that site conditions exerted a greater influence on these traits. To gain a comprehensive understanding of the potential for selection in the studied material, it is essential to examine heritability and expected genetic gain together, as these factors collectively provide a more reliable and credible assessment [10]. Relying solely on heredity can be limiting, and incorporating both heritability estimates and genetic gain into predictions for the future selection of optimal genotypes offers a more advantageous approach [11].
Previous research on Grewia optiva [12] and Celtis australis [13] has documented higher heritability estimates and statistically significant genetic effects on seed weight increase. Furthermore, significant findings in Albizia chinensis [14], Celtis australis [13], and Pinus wallichiana [15] align with the outcome of our study, supporting the influence of genetics on these traits.
Our investigation revealed that genotypic coefficients of variance (GCV) were consistently higher than their corresponding phenotypic coefficients of variance (PCV), indicating that the genetic component played a more substantial role in trait variation at the genotypic level. This finding is in agreement with other studies, such as [16], who observed inter- and intraspecific genetic variation in seedling drought tolerance in different pine species. Similarly, [17] identified distinct patterns in loci associated with phenotypic traits in loblolly pine, suggesting a genetic basis for these traits. Genetic correlations tended to be higher than phenotypic correlations, indicating that phenotypic correlations can serve as fair estimates of their genetic counterparts in many scenarios [18]. Additionally, a negative genetic correlation between height growth and other traits in jack pine, emphasizing the importance of considering multiple traits in selection approaches [1]. GCV is a superior indicator of the genetic relationships among traits in pines [19].
This phenomenon may be attributed to genotype–environment interaction or the influence of environmental elements on trait expression. Our findings align with similar observations in full-sibling offspring of specifically chosen clones of Populus deltoides [20] and the outcomes of studies on willow clones [21], collectively suggesting that GCV provides a more accurate representation of genetic relationships among traits than PCV. The results of studies conducted by various scientists [11, 22, 23] are consistent with these findings. The observation of a notable level of agreement between phenotypic and genotypic coefficients of variation suggests substantial diversity in genotypes, indicating the potential for improvement in these specific characteristics. This underscores the importance of considering genotypic values when studying trait inheritance and selection in plant populations.
In conclusion, our research uncovers substantial genetic diversity within Pinus wallichiana genotypes. While environmental factors predominantly dictate survival rates, our study underscores the influential role of genetic and phenotypic variance, particularly in shaping germination capacity and, notably, germination percentage. Among these traits, germination percentage emerges as the most genetically diverse, suggesting its potential as a prime target for selective breeding initiatives. Furthermore, our findings highlight altitudes A1 and A2 as regions where heritability plays a prominent role in governing germination and growth traits, indicating their relative resilience to environmental influences within these altitudinal ranges. Consequently, focusing on trait improvement within the lower (1800–2100 m.a.s.l.) and mid-altitudinal (2100–2400 m.a.s.l.) zones appears strategically advantageous. The application of these insights in selective breeding holds promise for bolstering the adaptability and vitality of Pinus wallichiana populations. As we look ahead, our findings offer valuable guidance for sustainable forest management, conservation, and breeding programs, particularly in diverse altitudinal contexts, fostering the long-term resilience of this important species.
The authors express their gratitude for the help provided by Dr. YS Parmar, the Head of the Department of Silviculture and Agroforestry, University of Horticulture and Forestry, in relation to the current study.
ANOVA for growth traits in Pinus wallichiana Seedlings among different altitudinal range.
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Written By
Amanpreet Kaur and Rajesh Monga
Submitted: 16 August 2023Reviewed: 18 September 2023Published: 20 December 2023
Open access peer-reviewed chapter
