Content uploaded by Ekram Hussain
Author content
All content in this area was uploaded by Ekram Hussain on Feb 15, 2022
Content may be subject to copyright.
Vol. 14(1), pp. 12-20, January-March 2022
DOI: 10.5897/JPBCS2021.0990
Article Number: 304868068694
ISSN 2006-9758
Copyright ©2022
Author(s) retain the copyright of this article
http://www.academicjournals.org/JPBCS
Journal of Plant Breeding and Crop
Science
Full Length Research Paper
Assessment of genetic variability, diversity, and
identification of promising lines in linseed germplasm
for harnessing genetic gain in central plain of the
Indian subcontinent
Mohammad Ekram Hussain1*, Vinod Kumar Goyal1, Pronob J Paul2, Yuvraj Yadav3,
Uday Chandra Jha4 and Prabhat K. Moitra1
1Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P, India.
2International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, TS, India.
3Department of Agriculture and Forestry, Tulsa Institute, Deharadun, U.K, India.
4ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India.
Received 2 January, 2022; Accepted 17 January, 2022
Linseed (Linum usitatissimum L.), cultivated in more than 60 countries, is grown for fiber and oilseed
worldwide. Here effort was made to assess the genetic variability in linseed germplasm and identify
some promising lines used as parents in the linseed hybridization program. The study was designed
with a total of 82 germplasm and a national check in RCBD for genetic variability for 11 agronomic
traits. In this study, a considerable variation was observed for all the studied traits by using PCA
analysis. It was also found that single plant yield, number of seeds per capsule, and number of
capsules are ideal for linseed improvement through the selection in central India. Few high yielding
accessions such as RL-10129 and Padmini showed maximum diversity with the popular variety T-397,
and can be used in the hybridization program. Similarly, we identified a few potential accessions such
as NDL-2013-03, EC-41741, Ruchi, EC-704, RL-10129 to be used as parents in the breeding program.
Key words: Genetic variability, linseed, genetic diversity, genetic gain, cluster, PCA.
INTRODUCTION
Linseed or flax, (2n=30 and genome size of ~370 Mb), is
the only species of agricultural significance within the
Linaceae family of 14 genera and 200 species (Wang et
al., 2012; Diederichsen and Richards, 2003). This self-
pollinated crop has been cultivated for centuries primarily
for its seed oil (linseed) or stem fibers (flax), or both
(Zohary, 1999). Linseed provides raw materials for food,
medicine, and textiles, and has been of great importance
to human civilization and development for more than
8,000 years (Van and Bakker, 1975). Crop evolutionists
consider linseed domestication to have existed in the old
world, including the modern-day countries Egypt,
*Corresponding author. E-mail: ekram.hussain12@gmail.com.
Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution
License 4.0 International License
Palestine, Israel, Iraq, Syria, Turkey, Iran, Lebanon,
Cyprus, and Jordan (Fu, 2011) and then spread to
Switzerland and Germany 5000 years ago in Europe
(Barber, 1991). Evidence suggests that the crop was also
grown in China and India, at least 5,000 years ago
(Cullis, 2007).
Linseed oil is remarkable for its health benefits primarily
attributed to its high content of dietary fiber (20-25%) and
omega-3 alpha-linolenic acid (45-65%) (Green and
Marshall, 1981; Rabetafika et al., 2011). Given its
impressive drying properties, it is also a prerequisite for
its use as an industrial product (Cullis, 2007).
Nonetheless, flax fiber is used as a valuable raw material
for textiles, threads, and wrapping materials, and its straw
used to manufacture different forms of cigarette papers,
currency notes, and the wooden component used as a
biomass energy source (Rowland, 1998). To increase the
linoleic acid content in eggs and meat, the various farms
include linseed as animal feed (Simmons et al., 2011).
Globally, Kazakhstan, Canada, Russia, China, India,
USA, Ethiopia, France, and the UK are the primary
linseed cultivation and producing nations. Kazakhstan is
the world's largest linseed producer (0.93 Mtonnes),
followed by Canada, and India (0.17 Mtonnes) ranks 5th
in the category (FAOSTAT, 2018). In India, under
marginal and rainfed conditions, linseed is grown
predominantly as an industrial oilseed crop covering an
area of 0.32 million ha with a production of 0.174 million
tons compared to 3.26 million ha worldwide which
produces 3.182 tons. India's productivity is considered
very poor at 543.8 kg/ha compared to the world average
yield of 975.1 kg/ha and the average yields for the UK
(1720 kg/ha), USA (1516.8 kg/ha), Canada (1497 kg/ha),
China (1308.6 kg/ha), Kazakhstan (866.9 kg/ha), which
are the top producers for this crop (FAOSTAT, 2018).
This yield disparity may be due to low yield potential or
lack of optimum agro-technological practices or a
combination of both, and due to lack of availability of
improved varieties in line with varied agro-climatic
conditions (Singh et al., 2016).
The production of high-yielding varieties becomes the
top priority to address the low yield levels; and
improvement in any crop depends upon the accessibility
of a wide range of genetic diversity. The development of
a new variety depends primarily on selecting diverse
populations with a broad genetic base. Identifying
promising genotypes is very useful when breeding from
initial parent lines to the final release of the variety.
Modern linseed improvement has, however, lagged
behind other oilseed crops, such as soybean and brassica
oils.
The introduction of new germplasm is needed to
broaden the genetic base and rejuvenate the breeding
stocks.
Yield, a complex polygenic trait, is influenced by a large
number of factors. The assessment of genetic variability
for linseed accessions would constitute a better resource
Hussain et al. 13
and direction for better germplasm utilization in linseed
genetic improvement.
The present study was, therefore, conducted to
evaluate the variability present in the linseed germplasm
for the central part of the Indian subcontinent and
patterns of the interrelationship between different traits
and important selection parameters.
MATERIALS AND METHODS
Plant materials and phenotyping
The experimental materials consisted of a collection of 82
accessions of linseed for the present study. We laid the field
experiment during the post rainy season of 2015-16 at Seed
Breeding Farm, Department of Plant Breeding and Genetics,
College of Agriculture, Jabalpur, M.P. India. All India Coordinated
Research Project (AICRP) on linseed based at Regional
Agricultural Research Station, Sagar, M.P., India, provided the seed
materials for this study. We planned the experiment in Randomized
Complete Block Design (RCBD) with 2 replications in 2.5 m long 2-
row plot spaced 30 cm apart and plant to plant distance of 10 cm.
All the recommended agronomic practices were strictly followed to
raise a healthy crop. We collected the data on 11 agronomic traits,
viz; days to flowering (DF), days to maturity (DM), plant height (PH),
no. of primary branches (NPB), no. of secondary branches (NSB),
no. of capsule per plant (NCP), no. of seed per capsule (NSC),
1000-seed weight (TSW), harvest index (HI), and seed yield per
plant (SYP). Five competitive plants were selected randomly from
each entry for recording observation.
Statistical analysis
For agronomic traits, best linear unbiased predictors (BLUPs) were
obtained, and the range and mean were calculated based on
BLUPs. In GenStat 15, phenotypic correlations were estimated for
the determination of trait associations. Path analysis was performed
to estimate the direct effect of the traits towards grain yield using R
Version 3.5.3 (R Project for Statistical Computing,
http://www.rproject.org/) (R Core Team, 2018). To avoid the
multicollinearity issues, independent traits biological yield per plant
(BM) was excluded while performing path analysis. Based on
agronomic traits, the Euclidean dissimilarity matrix was constructed
using the R package cluster (Patterson and Thompson, 1971);
thereafter, the accessions were clustered following Ward's method.
The most diverse accession pairs were identified based on the
Euclidean distance matrix for potential use as parents in linseed
crossing programs.
RESULTS AND DISCUSSION
Variance components, genetic parameters, and trait
variability
The REML analysis showed significant variations among
linseed germplasm (σ2g) for all the 11 agronomic traits
indicating considerable variability among the linseed
germplasm. The phenotypic coefficient of variation (PCV)
values of all the traits was higher than the corresponding
genotypic coefficient of variation (GCV). Eight traits
14 J. Plant Breed. Crop Sci.
showed large phenotypic and genotypic variations, with
PCV and GCV values greater than 10% (Table 1). Three
traits had PCV exceeding 30%; four ranged from 20 to
30%, one has 11.17%, and 3 less than 10%. SYP and
NCP had the largest PCV and GCV values of (34.80,
29.95%, and 31.95, 29.65%), respectively. Broad sense
heritability was found high for all the traits studied (68.26
- 98.78%). Genetic advance as a percentage of mean
was found highest for the number of capsules per plant
(56.67%) followed by SYP (53.11%), BM (48.71%), and
NSB (46.99%).
A considerable variation in flowering time was observed
(42 - 69 days) in the germplasms. Four genotypes
showed early flowering than popular check variety T-397,
which flowered in 51 days. The study found a
considerable variation amongst the germplasm for PH
(45.94 - 82.91). Similarly, the number of capsules per
plant was much higher in the germplasm (up to 66
capsules per plant, e.g. Rashmi) compared to T-397 (33
capsules per plant).
Correlation analysis
Correlation analysis showed no association between
phenological traits viz., (0.05), and DF (0.07) with SYP.
Similarly, PH also showed no correlation (r=0.18) with
SYP. On the other hand, both NPB (r=0.48**) and NSB
(r=0.59**) showed a significant positive correlation with
SYP. The NCP emerged as one of the most important
indirect traits for selecting a high yielding line as it
showed a correlation (r=0.79**) on SYP. Similarly, BM
also showed its importance in determining seed yield with
a correlation value (r=0.82**). TSW and HI showed a
significantly high correlation with SYP (r=0.28** and r=
0.45**, respectively) (Figure 1). Among the yield
contributing traits, NPB had a significant correlation
(r=0.40**) with NSB. Similarly, branches per plant, e.g.
NPB (r= 0.44**) and NSB (r=0.68**), showed a significant
positive correlation with the NCP.
Principal component analysis
The principal component analysis was performed based
on predicted means (BLUPs) for the quantitative traits of
linseed. Out of 11, only four principal components (PCs)
exhibited more than 1.00 eigenvalue and showed about
79% of the total phenotypic variability (Table 2). The PC1
had the highest variability (34.11%) followed by PC2
(20.39%), PC3 (14.01%) and PC4 (10.50%) for traits.
The first two principal components accounted for
(54.51%) of total phenotypic variability. The PC1
explained 34.11% for the first axis, and PC2 explained
20.39% for the second axis. SYP, BM, NCP, NSB, NPB,
NSC were the main contributing traits in PC1. In contrast,
PH, DM, and DF contributed to PC2 (Figure 2).
Cluster analysis
The hierarchical cluster analysis following Ward's method
resulted in 10 clusters (Table 3 and Figure 3). Cluster 3
was the largest cluster consisting of 25 lines, followed by
cluster 2 (10 lines) and cluster 5 (10 lines). Cluster 6 had
only three genotypes, all high yielding lines, EC-41741,
NDL-2013-03, and Shikha.
All early flowering and maturing lines, e.g., EC-704,
EX313-23, FRW-9, and RLC-140, were grouped into
cluster 7 (flowering 42.69 - 47.61 and maturity 85.7 -
104.5). Cluster 9 had the highest cluster mean for SYP
(2.76 g) followed by cluster 6 (2.14 g) and cluster 10
(2.12 g), whereas cluster 9 had the highest NCP (57.16)
followed by cluster 10 (47.13). Cluster 4 exhibited the
lowest means for SYP (~1.07 g) and NCP (~29.84)
(Table 3). The popular check variety (T-397) was grouped
into cluster 3.
The Euclidean distance matrix identified the most
diverse genotypes among the linseed germplasm and the
most similar and diverse genotypes to the popular variety
(T-397). Rashmi was the most diverse (8.6) than T-397,
while SLS-95 (1.8) was the most similar genotype with T-
397. Among the 82 genotypes, the most diverse pair of
accessions was RL-10129 and Padmini, with a distance
of 11.02. The top 10 most diverse pairs of accession are
listed in Table 3.
Identification of promising lines
Five genotypes flowered significantly earlier (42-49) than
T-397 (51 days). In comparison with T-397 (~1.8 g), 18
genotypes (out of 82 genotypes) had significantly higher
SYP (~1.89 - 3.43 g) (Table 4). Besides, many
germplasms were significantly better than T-397 in terms
of PH (57 lines ranging from 61.83 - 82.91 cm), NCP (31
lines ranging from 34.92 - 65.91), and TSW (32 lines with
6.32 - 8.91 g). Twenty-eight lines also showed a
significantly higher number of primary branches (3-4)
compared to T-397 (2) (Table 4). Eighteen promising
high-yielding lines (~1.89-3.43 g) which performed better
than the popular variety (T-397), were identified (Table
5). Remarkably, one genotype, EC-704, was early
flowering (47 days) having high SYP (1.91g) compared to
best check T-397. Seven genotypes viz., NDL-2013-03,
RL-10135, RLC-140, RL-10121, EC-41741, LC-54 and
Ruchi showed the highest TSW (~8.39 - 8.91 g), which is
one of the most important traits considering linseed
improvement. Similarly, NDL-2013-03, EC-41741, Ruchi,
EC-704, and RL-10129 showed bold seeded genotypes
having high seed yield per plant.
DISCUSSION
In the present study, we observed a large genetic
Hussain et al. 15
Table 1. Summary statistics and different genetic parameters for various traits in Linseed germplasm evaluated during post rainy season
2015-16 at JNKVV, Jabalpur, India.
Trait
Genotypic variance
SE
Mean
Range
GCV
PCV
H2
GA%
DF
16.33**
2.61
53.96 ± 5.252
42- 69
7.44
7.55
98.3
15.29
DM
33.01**
5.25
105.7 ±16.33
85-127
5.43
5.46
98.78
11.13
PH (cm)
46.25**
8.34
64.93 ± 8.34
45.94-82.91
10.47
11.17
87.81
20.21
NPB
0.2**
0.05
2.46± 0.05
1.8-3.5
19.08
23
68.26
32.47
NSB
7.85**
1.44
11.46 ± 1.44
7.25-19.44
24.53
26.38
86.46
46.99
NCP
104.16**
19.2
34.61± 19.2
19.94-65.91
8.62
8.93
86.08
56.67
NSC
0.41**
0.07
7.5 ± 0.07
6-8.7
29.65
31.95
93.22
17.15
TSW(g)
1.65**
0.27
6.06±0.27
4.23-8.9
21.21
21.69
95.59
42.72
BM(g)
2.56**
0.553
6.003±0.553
3.325-11.615
26.85
30.49
77.54
48.71
HI
30.02**
6.42
28.18±6.42
16.89-43.79
19.47
22.39
75.61
34.89
SYP(g)
0.25**
0.05
1.68±0.05
0.92-3.433
29.95
34.8
74.07
53.11
**, * Significant at P ≤ 0.01 and P ≤ 0.05, respectively. DF: days to flowering, DM: Days to maturity, PH: Plant height, NPB: No. of primary branches,
NSB: No. of secondary branches, NCP: No. of capsule per plant, NSC: No. of seed per capsule, TSW: 1000 seed weight, HI: Harvest index, SYP:
Seed yield per plant. GCV: Genotypic coefficient of variation, PCV: Phenotypic coefficient of variation, GA %: Genetic advance as percent of mean,
H2: Broad sense heritability
Figure 1. Correlation analysis of various agronomic in Linseed accessions at JNKVV, Jabalpur, India. Significant at P
≤ 0.01; *Significant at P ≤ 0.05. No. of primary branches (NPB), No. of secondary branches (NSB), No. of capsules
per plant (NCP), and Biological yield per plant (BM) were positively associated with seed yield per plant (SYP). On
the other hand, no correlation of days to flowering (DF) and days to maturity (DM) was found with seed yield per
plant. PH: Plant height, NSC: No. of seed per capsule, TSW: 1000 seed weight, HI: Harvest index.
16 J. Plant Breed. Crop Sci.
Table 2. Table Direct (in bold) and indirect effects of nine traits on seed yield per plant in Linseed germplasm during post rainy season 2015-
16 at JNKVV, Jabalpur, India.
Trait
DF
DM
PH
NPB
NSB
NCP
NSC
TSW
HI
SYP
DF
0.164
-0.106
0.003
0.004
-0.014
0.037
0.018
-0.024
-0.012
0.070
DM
0.153
-0.113
0.003
0.006
-0.006
0.043
0.020
-0.022
-0.034
0.050
PH
0.054
-0.045
0.009
0.009
0.034
0.192
0.020
-0.028
-0.064
0.180
NPB
0.010
-0.010
0.001
0.065
0.064
0.273
0.041
0.002
0.003
0.450
NSB
-0.015
0.005
0.002
0.026
0.161
0.422
-0.004
-0.007
0.000
0.590
NCP
0.010
-0.008
0.003
0.029
0.109
0.620
0.023
-0.002
0.006
0.790
NSC
0.016
-0.012
0.001
0.015
-0.003
0.081
0.180
-0.052
0.055
0.280
TSW
-0.018
0.011
-0.001
0.001
-0.005
-0.006
-0.043
0.217
0.134
0.290
HI
-0.007
0.012
-0.002
0.001
0.000
0.012
0.032
0.096
0.305
0.450
Residual effect: 0.128. DF: days to flowering, DM: Days to maturity, PH: Plant height, NPB: No. of primary branches, NSB: No. of secondary
branches, NCP: No. of capsule per plant, NSC: No. of seed per capsule, TSW: 1000 seed weight, HI: Harvest index, SYP: Seed yield per plant.
Figure 2. Projection of 10 quantitative characters on the first two components (axis 1 and axis 2) of the PCA.
DF: days to flowering, DM: Days to maturity, PH: Plant height, NPB: No. of primary branches, NSB: No. of
secondary branches, NCP: No. of capsule per plant, NSC: No. of seed per capsule, TSW: 1000 seed weight, HI:
Harvest index, SYP: Seed yield per plant.
Hussain et al. 17
Table 3. Top ten most diverse lines, most similar and diverse lines in relation to the popular linseed variety, T-397.
S/N
Pairs of accessions showing
maximum diversity
Diversity
Accessions showing
maximum diversity
with 'T-397'
Maximum
Diversity
Accessions showing
minimum diversity with
'T-397'
Minimum
diversity
1
RL-10129
Padmini
11.02
Rashmi
8.61
SLS-91
1.80
2
Rashmi
Padmini
10.42
RL-10129
7.93
R-7
2.15
3
EX13-23
Rashmi
10.71
BAU-11-08
6.80
LCK-1213
2.27
4
RLC-140
Rashmi
10.75
KL-241
6.77
EC-1066
2.28
5
BAU-1007-12
EX313-23
10.40
BAU-06-05
6.65
EC-41628
2.37
6
BAU-11-08
EX313-23
10.58
LCK-1214
6.44
EC-1645
2.49
7
RL-10121
RL-10129
10.46
SLS-95
6.24
C12006
2.54
8
RL-10129
KL-241
10.43
Padmini
6.00
SLS-92
2.56
9
RL 10129
EX313-23
10.32
Kastika
5.96
LMS-2011-91
2.57
10
EX-313-23
BAU-06-05
10.40
PKDL-133
5.78
FR-11
2.60
Figure 3. Cluster diagram depicting different clusters formed from 83 Linseed germplasms following Ward's method based on
agronomic traits.
18 J. Plant Breed. Crop Sci.
Table 4. Identification of promising trait-specific lines in Linseed germplasm.
Trait
Number of lines significantly better than T-397 (range)
T-397
Top five performing lines against mega cultivar T-397 (range)
DF
5 (42-49)
51
EX313-23, FRW-9, RLC-140, EC-704, LCK-1213 (42-49)
PH (cm)
57 (61.83-82.91)
61
BAU-06-05, PKDL-62, Kastika, Rashmi, Shikha (71.75-77.86)
NPB
28(2.52-3.51)
2.48
Rashmi, Kastika, SLS-95, BAU-06-05, RL-10175 (2.83-3.5)
NCP
31(34.92-65.91)
32.94
Rashmi, SLS-95, RL-10129, Kastika, GS-64 (52.48-65.91)
TSW (g)
32(6.32-8.39)
6.3
Ruchi, EC-704, RL-10129, LAXMI-27, Rashmi (6.7- 8.39)
SYP (g)
18(1.89-3.43)
1.77
RL-10129, SLS-95, Rashmi, Laxmi-27, GS-64(2.25-3.43)
DF: days to flowering, PH: Plant height, NPB: No. of primary branches, NCP: No. of capsule per plant, TSW: 1000 seed weight, SYP: Seed yield per
plant.
Table 5. Performance of 18 promising high-yielding Linseed germplasm for important agronomic traits.
Genotype
DF
PH
NPB
NSB
NCP
TSW
SYP
BAU-06-05
68.25
71.75
3.103
10.36
36.38
6.046
1.907
EC-41741
55.47
59.42
2.42
12.53
31.39
8.679
2.203
EC-704
47.61
62.27
2.454
10.19
30.7
7.848
1.914
GS-64
56.46
63.32
2.83
14.95
52.48
4.616
2.259
Kastika
52.52
74.26
3.445
14.86
54.72
5.907
2.229
LAXMI-27
55.47
68.37
2.625
16.48
47.92
6.916
2.596
NDL-2013-03
56.46
59.99
1.874
9.41
33.2
8.918
2.233
PKDL-141
52.52
68.15
2.489
15.55
49.64
5.979
2.188
PKDL-62
51.54
71.93
2.489
14.6
49.38
5.352
2.011
Rashmi
54.49
74.43
3.513
19.36
65.91
6.767
2.855
RL-10129
53.51
71.97
3.445
19.44
55.23
7.628
3.433
RL-10175
54.49
70.52
2.83
12.18
48.78
6.289
1.922
Ruchi
55.47
65.17
2.215
12.18
37.5
8.393
1.988
Shikha
55.47
77.86
2.625
7.25
34.32
6.375
2.011
SLS-91
50.56
59.29
2.625
10.88
43.01
5.639
1.892
SLS-95
56.46
61.04
3.172
14.86
56.78
6.586
3.033
SLS-97
52.52
63.1
1.805
15.12
50.24
6.892
2.218
SLS-98
53.51
71.67
2.762
15.03
49.04
5.41
2.185
T-397
50.56
60.6
2.352
9.85
32.94
6.194
1.77
DF: days to flowering, PH: Plant height, NPB: No. of primary branches, NSB: No. of secondary branches, NCP: No. of capsule per plant, TSW:
1000 seed weight, HI: Harvest index, SYP: Seed yield per plant.
variation for all the important agronomic traits viz—DF,
DM, PH, NCP, TSW, and SYP. High GCV and PCV
values for the NPB, BM, and SYP indicates selection will
be rewarding for these traits (Tyagi et al., 2014; Reddy et
al., 2013; Mirza et al., 2011; Tadesse et al., 2010). The
traits ~ SYP, NSC, NCP showed high heritability along
with high genetic advance. This fact suggests that
additive gene action controls the traits, and simple
selection for these traits may be successful (Payasi et al.,
2000; Naik and Satapathy, 2002; Muhammad et al.,
2003; Awasthi and Rao, 2005; Vardhan and Rao, 2006;
Iqbal et al., 2013).
The study revealed no correlation between TSW and
the NCP. The absence of any correlation between TSW
and the NCP indicates an excellent opportunity for
independent improvement of the NSC and seed size. As
there was no correlation between DM and BM, it means
there were early maturing high yielding lines, listing some
early and high yielding lines. e.g. EC-704 and SLS-91.
Since there was no association between PH and SYP,
there would be no benefit of PH when deciding on grain
yield in linseed.
The linseed breeders can use traits such as NPB, NSB,
NCP, NSC, TSW, and BM as an indirect selection
criterion for enhancing grain yield as these showed a
significant positive association with grain yield.
Furthermore, independent improvement of the traits~
NSC and NCP is possible with no correlation between
them (Pal et al., 2000; Chimurkar et al., 2001; Bhosle,
2002; Naik and Satapathy, 2002; Akbar et al., 2003;
Bhosle and Rao, 2005; Vardhan and Rao, 2006).Based
on the cluster analysis, genotypes from Cluster V and
Cluster VIII can be utilized in future hybrid programs for
the highest grain yield as they had the highest mean
value for the NSC and TSW. The utilization of germplasm
and the source of genetic diversity occur periodically to
meet the changing needs of improved crop varieties.
Besides, there must be significant variation for economic
traits in the germplasm for productive utilization following
recombination breeding or selection. Optimal parental
diversity is much needed to obtain superior genotypes to
recover transgressive segregants (Griffing and Lindstrom,
1954; Moll et al., 1962). The genetic diversity of selected
parents does not always rely on factors such as
geographic diversity per place of release or degree of
ploidy.
Therefore, the classification of germplasm for genetic
divergence should be based on second statistical
methods, such as D2 statistics and cluster analysis, to
identify suitable and diverse genotypes. Cluster analysis
categorize lines into distinct groups/clusters where
genotypes in different clusters are more diverse than in a
cluster (Ward, 1963) and are useful in selecting the most
diverse genotypes to be used as parents in crossing
programs. Besides, knowledge about the similarity/
dissimilarity between accessions and check cultivars is
vital for the efficient use of the accessions in hybridization
programs.
Including diverse accession in the hybridization, the
program is very beneficial as this leads to new and useful
recombinants used as variety. Based on yield and
phenological traits, the cluster analysis grouped 82 lines
into 10 clusters wherein similar accessions were in the
same cluster. Hence, this would make the selection
process easy for the breeders to choose trait-specific and
diverse accession for use in a breeding program. Apart
from this, a few accessions such as RL-10129 and
Padmini showing maximum diversity with the popular
variety (T-397), have been identified for breeding
programs to develop new cultivars.
To understand the potential of this germplasm in
improving cultivated linseed, we compared the
performance of these lines with the popular check variety
T-397. In this study, apart from identifying 18 highly
significant promising lines, we have observed many trait-
specific significant lines. We identified many lines having
early flowering, bold seeded, a higher number of primary
branches as well as capsules per plant. Based on this,
the breeder can select trait-specific significant lines and
can be used in crop improvement breeding program as
per the necessity. Besides, we found early flowering lines
too, e.g., EX313-23, FRW-9, and RLC-140, which can be
used in breeding programs for earliness trait. Similarly,
we can use lines having a higher NCP for breeding
promising lines in linseed. Remarkably, the high yielding
and early flowering genotype EC-704 signifies there will
be no yield trade-offs while breeding for early high-
Hussain et al. 19
yielding lines from this selection.
Conclusion
This study on evaluation of linseed germplasms for
variability and identification of promising lines revealed
considerable genetic variation in the studied location.
High genetic gain for this crop would be possible in this
region with the improvement of traits such as single plant
yield, number of capsules per plant, and seed per
capsule. This study identified some lines, viz: NDL-2013-
03, EC-41741, EC-704 and RL-10129 that have the
potential to be used as parents in breeding programs and
released as a variety (es) after evaluation across multi-
location over the years. Also, utilizing those lines as
parents in hybridization programs would diversify the
current germplasm available. The high yielding lines
should also be evaluated for its flax content and linoleic
acid for further use in the breeding program.
CONFLICT OF INTERESTS
The authors have not declared any conflict of interests.
ACKNOWLEDGEMENTS
The funding support provided by the Jwahar Lal Nehru
Krishi Vishwavidyalaya (JNKVV) is duly appreciated.
REFERENCES
Akbar M, Mahmood T, Anwar M, Ali M, Shafiq M, Salim J (2003).
Linseed improvement through genetic variability, correlation and path
coefficient analysis. International Journal of Agriculture
Biology 5(3):303-305.
Awasthi SK, Rao SS (2005). Selection parameters for yield and its
components in linseed (Linum usitatissimum L.). Indian Journal of
Genetics 65(4):323-324.
Barber EJW (1991). The Development of Cloth in the Neolithic and
Bronze Ages with Special Reference to the Aegean.
Bhosle AB (2002). Diallel Cross Analysis in Linseed (Linum
usitatissimum L.) with F2 population. M.Sc Thesis. Indira Gandhi
Krishi Vishwavidyalaya, Raipur.
Bhosle AB, Rao SS (2005). Estimation of genetic components of
variation in F2 generation in Linseed (Linum usitatissimum L.).
Journal of Agricultural Issues 10(1):39-42.
Chimurkar HC, Patil S, Rathod DR (2001). Character association
studies in linseed (Linum usitatissimum L.). Annals of Plant
Physiology 15(1):72-76.
Cullis C (2007). Flax: genome mapping and molecular breeding in
plants. Springer, Berlin.
Diederichsen A, Richards K (2003). Cultivated flax and the genus Linum
L.: Taxonomy and germplasm conservation. In: Flax (). CRC Press.
pp. 34-66.
FAOSTAT (2018): Food and Agriculture Organization of the United
Nations Database. (Rome, Italy: Food and Agriculture Organization).
Available at: http://faostat.fao.org/database.
Fu YB (2011) Genetic evidence for early flax domestication with
capsular dehiscence. Genetic Resources and Crop Evolution 58(8):
20 J. Plant Breed. Crop Sci.
1119-1128.
Green AG, Marshall DR (1981). Variation for oil quantity and quality in
linseed (Linum usitatissimum). Australian Journal of Agricultural
Research 32(4):599-607.
Griffing B, Lindstrom EW (1954). A Study of the Combining Abilities of
Corn Inbreds Having Varying Proportions of Corn Belt and Non-Corn
Belt Germ Plasm 1. Agronomy Journal 46(12):545-552.
Iqbal J, Hussain F, Ali M, Iqbal MS, Hussain K (2013). Trait association
of yield and yield components of linseed (Linum usitatissimum L.).
International Journal of Modern Agriculture 2(3):114-117.
Mirza MY, Khan MA, Akmal M, Mohmand AS, Nawaz MS, Nawaz N,
Ullah N (2011). Estimation of genetic parameters to formulate
selection strategy for increased yield in linseed. Pakistan Journal of
Agricultural Research 24:1-4.
Moll R, Salhuana WS, Robinson HF (1962). Heterosis and Genetic
Diversity in Variety Crosses of Maize. Crop Science 2(3):197-198.
Naik B, Satapathy P (2002). Selection strategy for improvement of seed
yield in late sown linseed. Research on Crops 3(3):599-605.
Pal SS, Gupta TR, Inderjit S (2000). Genetic determination of yield in
Linseed (Linum usitatissimum L.). Crop improvement 27(1):109-10.
Patterson HD, Thompson R (1971). Recovery of inter-block information
when block sizes are unequal. Biometrika 58(2):545–554.
Payasi SK, Bose US, Singh AK (2000). Pooled analysis of genetic
parameters in Linseed (Linum usitatissimum L.). Advances in Plant
Science 13(2):559-62.
R Core Team. (2018). R: a Language and Environment for
StatisticalComputing. R Foundation for Statistical Computing.
https://www.R-project.org
Rabetafika HN, Remoortel VV, Danthine S, Paquot M, Blecker C
(2011). Flaxseed proteins: food uses and health benefits.
International Journal of Food Science and Technology 46(4):221-228.
Reddy MP, Reddy BR, Arsul BT, Maheshwari JJ (2013). Character
association and path coefficient studies in linseed. International
Journal of Current Microbiology and Applied Science 2(9): 250-254
Rowland GG (1998). Growing flax: Production, management and
diagnostic guide. Flax Council of Canada and Saskatchewan Flax
Development Commission.
Simmons CA, Turk P, Beamer S, Jaczynski J, Semmens K, Matak KE
(2011). The effect of a flaxseed oil enhanced diet on the product
quality of farmed brook trout (Salvelinus fontinalis) fillets. Journal of
Food Science 76(1):S192–S197.
Singh N, Yadav KV, Kumar R, Kumar S, Yadav HK (2016) Genetic
variability and interrelationship among morphological and yield traits
in linseed (Linum usitatissimum L.). Genetika 48(3):881-892.
Tadesse T, Singh HA, Weyessa B (2010). Correlation and path
coefficient analysis among seed yield traits and oil content in
Ethiopian Linseed germplasm. International Journal of Sustainable
Crop Production 4(4):8-16.
Tyagi AK, Sharma MK, Mishra SK, Kumar R, Kumar P, Kerkhi SA
(2015). Evaluation of genetic divergence in Linseed (Linum
usitatissimum L.) Germplasm. Progressive Agriculture 15(1):128-33.
Van ZW, Bakker H (1975). Evidence for Linseed cultivation before 6000
BC. Journal of Archaeological Science 2 (3):215-9.
Vardhan KM, Rao SS (2006). Association analysis for seed yield and its
components in Linseed (Linum usitatissimum L.). Mysore Journal of
Agriculture Science 40(1):55-59.
Wang Z, Hobson N, Galindo L, Zhu S, Shi D, McDill J, Yang L, Hawkins
S, Neutelings G, Datla R (2012). The genome of flax (Linum
usitatissimum) assembled de novo from short shotgun sequence
reads. The Plant Journal 72 (3):461-473.
Ward JH (1963). Hierarchical Grouping to Optimize an Objective
Function. Journal of American Stastics and Association 58(4):236-
244.
Zohary D (1999). Monophyletic vs. polyphyletic origin of the crops on
which agriculture was founded in the Near East. Genetic Resources
and Crop Evolution 46(2):133-142.