Phenotypic Diversity Analysis of Lens culinaris Medik. Accessions for Selection of Superior Genotypes

Abstract

Knowledge of genetic diversity in lentil is imperative for selection of parental genotypes that could yield heterotic combinations. The aim of the present study was to investigate the genetic diversity among 43 diverse lentil genotypes to identify complementary and unique genotypes for breeding programmes. Field experimentation was carried out in two winter seasons (2019–2020 and 2020–2021) in Hisar (29°10′ N, 75°46′ E) using randomized block design (RBD) with three replications. The chi-square test analysis showed significant genotypic variation for qualitative traits. There was substantial genetic variation among the genotypes for most quantitative traits, connoting the need to exploit a high degree of genetic variation through selection. Multiple-trait selection would also be beneficial, as seed yield was positively associated with most quantitative traits. The principal component analysis recognized seed yield (SY), days to 50% flowering (DTF), days to maturity (DTM), number of pods per plant (NPP), number of primary branches (NPB), plant height (PH) and biological yield (BY) as target traits that prominently described variation within lentil genotypes. The cluster analysis discriminated the lentil genotypes into five discrete clusters. Cluster III and V were the most distant groups, implying wider diversity among the genotypes of these groups. Furthermore, cluster analysis identified genotypes IPL 316, LH 17-19, LH 18-04, LH 17-17, IPL 81 and Pant L-8 as high-yielding genotypes, while L 4717 was identified as an early-maturing genotype. Therefore, to obtain a broad spectrum of early-maturing high-yielding segregants, the selected genotypes may serve as superior parental lines for structuring breeding strategies.

Full text

Citation: Sharma, R.; Chaudhary, L.;
Kumar, M.; Yadav, R.; Devi, U.; A.;
Kumar, V. Phenotypic Diversity
Analysis of Lens culinaris Medik.
Accessions for Selection of Superior
Genotypes. Sustainability 2022,14,
5982. https://doi.org/10.3390/
su14105982
Academic Editor: Khalid
Rehman Hakeem
Received: 12 February 2022
Accepted: 11 May 2022
Published: 14 May 2022
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sustainability
Article
Phenotypic Diversity Analysis of Lens culinaris Medik.
Accessions for Selection of Superior Genotypes
Rajat Sharma , Lakshmi Chaudhary * , Mukesh Kumar , Rajesh Yadav, Uma Devi, Amit and Vinay Kumar
Department of Genetics & Plant Breeding, CCS Haryana Agricultural University, Hisar 125004, India;
rajatsharma1917@gmail.com (R.S.); mukeshsaini@hau.ac.in (M.K.); rajeshyadav65@rediffmail.com (R.Y.);
umakansal0010@hau.ac.in (U.D.); amitkutubpur58341@gmail.com (A.); kumar.vinay51012@gmail.com (V.K.)
*Correspondence: lakshmi_gpb@hau.ac.in; Tel.: +91-97293-24350
Abstract:
Knowledge of genetic diversity in lentil is imperative for selection of parental genotypes
that could yield heterotic combinations. The aim of the present study was to investigate the genetic
diversity among 43 diverse lentil genotypes to identify complementary and unique genotypes for
breeding programmes. Field experimentation was carried out in two winter seasons (2019–2020 and
2020–2021) in Hisar (29
◦
10
0
N, 75
◦
46
0
E) using randomized block design (RBD) with three replications.
The chi-square test analysis showed significant genotypic variation for qualitative traits. There was
substantial genetic variation among the genotypes for most quantitative traits, connoting the need
to exploit a high degree of genetic variation through selection. Multiple-trait selection would also
be beneficial, as seed yield was positively associated with most quantitative traits. The principal
component analysis recognized seed yield (SY), days to 50% flowering (DTF), days to maturity (DTM),
number of pods per plant (NPP), number of primary branches (NPB), plant height (PH) and biological
yield (BY) as target traits that prominently described variation within lentil genotypes. The cluster
analysis discriminated the lentil genotypes into five discrete clusters. Cluster III and V were the
most distant groups, implying wider diversity among the genotypes of these groups. Furthermore,
cluster analysis identified genotypes IPL 316, LH 17-19, LH 18-04, LH 17-17, IPL 81 and Pant L-8 as
high-yielding genotypes, while L 4717 was identified as an early-maturing genotype. Therefore, to
obtain a broad spectrum of early-maturing high-yielding segregants, the selected genotypes may
serve as superior parental lines for structuring breeding strategies.
Keywords:
agronomic performance; cluster analysis; high temperature; lentil; morphological traits;
principal component analysis; seed yield; trait relationship
1. Introduction
Lentil (Lens culinaris Medik. ssp. culinaris, 2n = 2x = 14) is the earliest domesticated
grain legume and originated from L. culinaris Medik. ssp. orientalis in the Fertile Crescent
of Eastern Asia [
1
]. It is the principal cool-season grain legume of the Indian subcontinent,
North America, Middle East, Oceania, North Africa and Sub-Saharan Africa, grown for
its nutritious lens-shaped seed. Its contribution to semi-arid ecologies is crucial due to its
ability to yield a substantial return in marginal areas. It also has the capacity to resist the
risks, especially drought stress, that are common in dryland farming [
2
]. It is crucial for
human and animal nutrition, as well as improving soil health. Lentil seed is a rich source of
protein (third-highest after soybean and hemp), soluble and insoluble fibre, minerals (K, Ca,
Zn, Fe, P) and vitamins (thiamine, niacin and riboflavin) for balanced human nutrition [
3
,
4
].
Furthermore, due to its high lysine and tryptophan content, its consumption with cereals
provides the perfect complementary amino acid profile for human consumption. Its ability
to fix atmospheric nitrogen through symbiosis with Rhizobium leguminosarum and sequester
carbon improves soil nutrient status and soil health [5].
Lentil accounts for 8% of global pulses production [
6
]. Its production is 5.73 million
tons, which are yielded from 4.80 million hectares. Canada has become the dominant
Sustainability 2022,14, 5982. https://doi.org/10.3390/su14105982 https://www.mdpi.com/journal/sustainability

Sustainability 2022,14, 5982 2 of 19
player in lentil production, accounting for about 38% of world production, followed by
India and Australia [
7
]. Globally, lentils grew by 39% in production and over 100% in
productivity from 1994 to 2019, with the majority of the growth taking place in Canada,
India and Turkey [
7
]. In India, lentil occupies 1.30 million hectares with the production
of 1.10 million tons [
8
]. The average productivity of lentil in India is 847 kg/ha, which is
quite low as compared to the world average productivity of 1195 kg ha
−1
[
7
]. The possible
major constraints behind the yield gap include drought and heat stress, insect pests and
diseases and a paucity of suitable cultivars for specific adaptation. Lentil production
and productivity can be enhanced by breeding and deploying improved cultivars. The
availability of adequate genetic variation is critical for the development of farmer- and
market-driven superior lentil cultivars.
The narrow genetic base and high genotype
×
environment interactions serve as
a bottleneck in the quest for tailoring high-yielding and stress-resilient cultivars of lentil.
Reportedly, lentil accessions across India have exhibited relatively low levels of genetic
diversity [
9
]. The continuous artificial selection and breeding with a primary focus on a few
targeted traits to satisfy the ever-increasing demand has resulted in a lack of heterogeneity in
the lentil primary gene pool [
10
]. A limited number of superior landraces and cultivars were
repeatedly used as parental lines in hybridization programmes. Kumar et al. [
11
] reported
that 30% of the genetic base in 35 Indian cultivars was contributed by only ten parental lines.
Therefore, introgression of diverse and exotic genotypes has been recommended [
12
,
13
].
Through gene recombination and coherent selection, the genetic base of the primary gene
pool of lentil could be widened. However, hybridization of exotic macrosperma lentils
having late flowering with indigenous germplasm was not feasible on a vast scale due to
cross-incompatibility until Precoz was found. Precoz, an Argentinian cultivar, was the first
identified early-flowering macrosperma exotic germplasm that contributed to seed size
and rust resistance [11,13].
Therefore, the development of locally adapted and high-yielding lentil cultivars re-
quires a range of diverse genotypes to be used in breeding programmes to incorporate
various traits as per the needs of farmers and end consumers [
14
]. The wild gene pool
of lentil can serve as a potent source of genetic diversity that can be recombined with
established local cultivars to broaden the genetic base and improve economic traits [
15
,
16
].
The genetic diversity among the genotypes is a valuable source of genes for breeding
programmes, building new farming systems, diversifying production and producing new
high-quality goods [
17
]. Recently, a photothermal model [
14
] and a multi-trait stability
index [
18
] have been used to identify potential genotypes for lentil research and improve-
ment. However, knowledge of genetic diversity aids in the selection of parental genotypes
from random populations, and estimating the possibilities of heterotic combinations before
starting crossing programmes can save time and resources if the levels and patterns of
genetic diversity are accurately estimated [
19
]. Hence, the objective of the present study
was to evaluate the genetic diversity among the promising lentil genotypes cultivated
across India to identify unique, high-yielding and complementary genotypes for future
utilization in breeding programmes.
2. Materials and Methods
2.1. Plant Materials and Study Location
The study investigated 43 lentil genotypes, encompassing 33 promising released
cultivars, nine advanced breeding lines and one exotic genotype (Table 1), which were
procured from the Indian Institute of Pulses Research (IIPR), Kanpur, and the Depart-
ment of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural
University (CCS HAU), Hisar. The field experiments were conducted on research farms of
Pulses Section, Department of Genetics and Plant Breeding, CCS HAU, Hisar, during the
2019–2020
and 2020–2021 Rabi cropping seasons. The research site is in a subtropical region
with a dry environment characterized by extremely hot summers, chilly winters and little
rainfall. The meteorological conditions (temperature and rainfall) that prevailed during

Sustainability 2022,14, 5982 3 of 19
the two cropping seasons were recorded according the procedure given by Khichar and
Niwas [
20
]. Since cropping season 2020–2021 had considerably higher daytime (maximum)
temperatures throughout and after blooming up to maturity, as well as significantly lower
cumulative rainfall when compared with cropping season 2019–2020, both seasons were
identified as separate environments for evaluating the genotypes (Figure 1).
Sustainability 2022, 14, x FOR PEER REVIEW 4 of 19
Figure 1. Comparison of weather parameters across two years. Max = maximum temperature, Min
= minimum temperature, °C = degree Celsius, mm = millimetre.
2.2. Experimental Design and Data Collection
The experiment was laid out in randomized block design (RBD) with three replica-
tions. Each genotype was planted on a plot comprising six rows. The rows were 4 m long
and 0.30 m apart, resulting in a plot size of 7.2 m2. All recommended agronomic practices
were followed for lentil production [21]. List of different qualitative and quantitative traits
for which data were collected is presented in Table 2. Qualitative characterization was
done according to lentil descriptors of the Protection of Plant Varieties and Farmers’
Rights Act (PPV and FRA) [22].
Table 2. Descriptors for the lentil qualitative and quantitative traits as per PPV and FRA.
Traits Code Description
Qualitative Traits
Foliage: Intensity of green colour FGC 1 = light, 2 = medium, 3 = dark
Stem: Anthocyanin colouration SAC 1 = absent, 9 = present
Time of flowering TF 3 = early (<60 days), 5 = medium (60–80 days), 7 = late (>80 days)
Leaf: Pubescence LP 1 = absent, 9 = present
Leaflet: Size LS 3 = small, 5 = medium, 7 = large
Plant: Growth habit PGH 1 = erect (compact), 3 = semi-erect, 5 = horizontal (spreading)
Flower: Colour of standard FSC 1 = white, 2 = pink, 3 = blue, 4 = violet
Tallness TL 3 = short (<40 cm), 5 = medium (40–60 cm), 7 = long (>60 cm)
Pod: Anthocyanin colouration PAC 1 = absent, 9 = present
Seed: Size SS 3 = small (<2 g), 5 = medium (2.0–2.5 g), 7 = large (2.51–3.0 g), 9 = very large (>3.0 g)
Seed: Testa colour STC 1 = green, 2 = grey, 3 = pink, 4 = brown, 5 = black
Seed: Testa mottling STM 1 = absent, 3 = present
Cotyledon: Colour CC 1 = yellow, 2 = olive green, 3 = orange
Quantitative Traits
Days to 50% flowering DTF Number of days from sowing to stage when 50% plants in the plot had at least one
fully opened flower
Figure 1.
Comparison of weather parameters across two years. Max = maximum temperature,
Min = minimum temperature, ◦C = degree Celsius, mm = millimetre.
Table 1. Description of the lentil genotypes used in the study.
S.No. Genotype Pedigree Type of Material Source/Origin
1 RVL 11-6 JL 3 ×DPL 62 Cultivar RVSKVV, Sehore
2 RVL 13-5 JL 3 ×DPL 62 Cultivar RVSKVV, Sehore
3 RVL 31 Local selection from Shajapur, MP Cultivar RVSKVV, Sehore
4 RVL 13-7 JL 1 ×Black Masra Cultivar RVSKVV, Sehore
5 JL 3 Land race selection from Sagar, MP Cultivar JNKVV, Jabalpur
6 HUL 57 Mutant of HUL 11 Cultivar BHU, Varanasi
7 Kota Masoor-2 LL 1049 ×RKL 11 Cultivar AUK, Rajasthan
8 Kota Masoor-1 KLB 339 ×SL 94-09 Cultivar AUK, Rajasthan
9 RLG 5 Selection from local germplasm Cultivar RARI, Durgapura
10 L 4727 Sehore 74-3 ×Precoz Cultivar IARI, New Delhi
11 L 4717 ILL 7617 ×91516 Cultivar IARI, New Delhi
12 L 4147 (L 3875 ×P4) ×PKVL 1 Cultivar IARI, New Delhi
13 L 4076 PL 234 ×PL 639 Cultivar IARI, New Delhi
14 LH 89-48 (HM-1) K 75 ×L 4076 Cultivar CCS HAU, Hisar
15 LH 84-8 (Sapna) L9-12 ×JLS-2 Cultivar CCS HAU, Hisar
16 LH 82-6 (Garima) Pusa 2 ×No.- 4 Cultivar CCS HAU, Hisar
17 LL 699 PL 639 ×PL 77-2 Cultivar PAU, Ludhiana
18 LL 1373 IPL 406 ×FLIP 2004-7L Cultivar PAU, Ludhiana
19 LL 931 LH 90-103 ×LL 608 Cultivar PAU, Ludhiana
20 DPL 15 PL 406 ×L 4076 Cultivar IIPR, Kanpur
21 DPL 62 JLS 1 ×LG 171 Cultivar IIPR, Kanpur
22 IPL 81 K 75 ×PL 639 Cultivar IIPR, Kanpur
23 IPL 406 DPL 35 ×EC 157634/382 Cultivar IIPR, Kanpur

Sustainability 2022,14, 5982 4 of 19
Table 1. Cont.
S.No. Genotype Pedigree Type of Material Source/Origin
24 IPL 316 Sehore 74-3 ×DPL 58 Cultivar IIPR, Kanpur
25 IPL 220 (DPL 44 ×DPL 62) ×DPL 58 Cultivar IIPR, Kanpur
26 WBL 77 ILL 7723 ×BL ×84176 Cultivar Berhampore, WB
27 Pant L 7 L-4076 ×DPL 15 Cultivar GBPUA&T, Pantnagar
28 Pant L 8 DPL 59 ×IPL 105 Cultivar GBPUA&T, Pantnagar
29 Narender Masoor 1 Precoz ×PL 406 Cultivar NDUAT, Faizabad
30 Narender Masoor 2 Variety identified at AICRP’s workshop Cultivar NDUAT, Faizabad
31 LH 16-01 Selection from RKL 605-3 Breeding line CCS HAU, Hisar
32 LH 17-16 LH 07-26 ×PL 01 Breeding line CCS HAU, Hisar
33 LH 17-17 LH 07-26 ×PL 01 Breeding line CCS HAU, Hisar
34 LH 17-18 LH 07-26 ×PL 01 Breeding line CCS HAU, Hisar
35 LH 17-19 LH 07-26 ×PL 01 Breeding line CCS HAU, Hisar
36 LH 18-04 LH 07-26 ×PL 01 Breeding line CCS HAU, Hisar
37 LH 18-05 LH 07-26 ×PL 01 Breeding line CCS HAU, Hisar
38 Pant Lentil 01 PL 04 ×DPL 55 Breeding line GBPUA&T, Pantnagar
39 PL 02 PL 04 ×DPL 55 Cultivar GBPUA&T, Pantnagar
40 PL 04 UPL 175 ×(PL 184 ×P 288) Cultivar GBPUA&T, Pantnagar
41 Precoz Argentina cultivar Cultivar ICARDA, Syria
42 IPL 315 PL 4 ×DPL 62 Cultivar IIPR, Kanpur
43 DPL 58 PL 639 ×Precoz Breeding line IIPR, Kanpur
2.2. Experimental Design and Data Collection
The experiment was laid out in randomized block design (RBD) with three replications.
Each genotype was planted on a plot comprising six rows. The rows were 4 m long and
0.30 m apart, resulting in a plot size of 7.2 m
2
. All recommended agronomic practices were
followed for lentil production [
21
]. List of different qualitative and quantitative traits for
which data were collected is presented in Table 2. Qualitative characterization was done
according to lentil descriptors of the Protection of Plant Varieties and Farmers’ Rights Act
(PPV and FRA) [22].
Table 2. Descriptors for the lentil qualitative and quantitative traits as per PPV and FRA.
Traits Code Description
Qualitative Traits
Foliage: Intensity of green colour FGC 1 = light, 2 = medium, 3 = dark
Stem: Anthocyanin colouration SAC 1 = absent, 9 = present
Time of flowering TF 3 = early (<60 days), 5 = medium (60–80 days), 7 = late (>80 days)
Leaf: Pubescence LP 1 = absent, 9 = present
Leaflet: Size LS 3 = small, 5 = medium, 7 = large
Plant: Growth habit PGH 1 = erect (compact), 3 = semi-erect, 5 = horizontal (spreading)
Flower: Colour of standard FSC 1 = white, 2 = pink, 3 = blue, 4 = violet
Tallness TL 3 = short (<40 cm), 5 = medium (40–60 cm), 7 = long (>60 cm)
Pod: Anthocyanin colouration PAC 1 = absent, 9 = present
Seed: Size SS
3 = small (<2 g), 5 = medium (2.0–2.5 g), 7 = large (2.51–3.0 g), 9 = very large (>3.0 g)
Seed: Testa colour STC 1 = green, 2 = grey, 3 = pink, 4 = brown, 5 = black
Seed: Testa mottling STM 1 = absent, 3 = present
Cotyledon: Colour CC 1 = yellow, 2 = olive green, 3 = orange

Sustainability 2022,14, 5982 5 of 19
Table 2. Cont.
Traits Code Description
Quantitative Traits
Days to 50% flowering DTF Number of days from sowing to stage when 50% plants in the plot had at least one
fully opened flower
Days to maturity DTM Number of days from sowing until when 75% of the plants in a plot had reached
physiological maturity
Plant height (cm) PH Height of five randomly selected and tagged plants in cm from ground level to the
tip of the plant.
Number of pods per plant NPP The average number of fully matured seed-bearing pods from five randomly
selected and tagged plants
Number of primary branches NPB The average number of branches shooting out of base from five randomly selected
and tagged plants
Number of fruiting branches NFB The average number of branches bearing fully matured pods from five randomly
selected and tagged plants
Seeds per pod SP The average number of seed per pods taken from 10 randomly selected and
tagged pods
100-seed weight HSW Weight of a random sample of 100 seeds
Biological yield per plot (kg) BY Weight of the total dry biomass produced above ground
Harvest index (%) HI Ratio of seed yield to total dry biomass
Seed yield per plot (kg) SY Weight of seed harvested in a plot
2.3. Statistical Analysis
Data collected for qualitative traits (Table 2) were analysed for frequency distribution
and chi-square test analysis. The quantitative data for each variable were tested for analysis
of variance (ANOVA) to determine variability among genotypes. Subsequently, data
were pooled across season for further analysis. To assess trait relationships and identify
influential components among 11 quantitative traits, Pearson’s correlation coefficient and
Principal component analysis (PCA) were analysed. The city block (Manhattan) distance
was further used for the construction of dendrogram following unweighted pair-group
method with arithmetic-average (UPGMA)-based hierarchical clustering of genotypes.
IBM SPSS Statistics version 26 was used to conduct the above-mentioned analyses on data
gathered for qualitative and quantitative traits.
3. Results
3.1. Evaluation of Genotypes Based on Qualitative Traits
Almost all assessed qualitative traits, such as foliage green colour intensity, stem
anthocyanin colouration, leaflet size, growth habit, flower standard colour, tallness and
seed traits, exhibited significant variations among the genotypes (Table 3). However,
significant variations were not found for time of flowering and two qualitative traits:
leaf pubescence and pod anthocyanin colouration did not yield any variation, and hence
chi-square test could not be performed. Morphological trait variations observed in lentil
genotypes are also depicted in Figures 2and 3. A large proportion of genotypes (58.1%)
were late-flowering, while 41.9% of genotypes were medium-flowering and none of the
genotypes were early-flowering (Table 3). About 76.9% of genotypes were semi-erect, while
23.3% of genotypes were erect in growth habits (Table 3, Figure 2). The majority of the
genotypes (79.1%) had medium plant height, while 20.9% had short plant height (Table 3,
Figure 3). About 44.2% genotypes had medium seed size, and the rest of the genotypes had
large, small and very large seed size at 25.6%, 18.6% and 11.6%, respectively (Table 3). Grey
seed test colour was found in a high proportion of genotypes (44.2%), followed by brown

Sustainability 2022,14, 5982 6 of 19
(37.2%), green (9.3%), pink (7.0%) and black (2.3%) (Table 3, Figure 3). The most common
cotyledon colour was orange, as it was exhibited by 93.0% of the genotypes (Table 3).
Sustainability 2022, 14, x FOR PEER REVIEW 6 of 19
Figure 2. Morphological trait variation observed in lentil genotypes across two years. (A) Foliage:
Intensity of green colour (light, medium and dark). (B) Stem: Anthocyanin colouration (present and
absent). (C) Plant: Growth habit (erect and semi-erect). (D) Leaflet size (small, medium and large).
Figure 3. Morphological trait variation observed in lentil genotypes across two years. (A) Flower:
Colour of standard (violet and white). (B) Seed: Testa mottling (present and absent). (C) Seed: Testa
colour (brown, grey, pink, green and black). (D) Tallness (short and medium).
Figure 2.
Morphological trait variation observed in lentil genotypes across two years. (
A
) Foliage:
Intensity of green colour (light, medium and dark). (
B
) Stem: Anthocyanin colouration (present and
absent). (C) Plant: Growth habit (erect and semi-erect). (D) Leaflet size (small, medium and large).
Sustainability 2022, 14, x FOR PEER REVIEW 6 of 19
Figure 2. Morphological trait variation observed in lentil genotypes across two years. (A) Foliage:
Intensity of green colour (light, medium and dark). (B) Stem: Anthocyanin colouration (present and
absent). (C) Plant: Growth habit (erect and semi-erect). (D) Leaflet size (small, medium and large).
Figure 3. Morphological trait variation observed in lentil genotypes across two years. (A) Flower:
Colour of standard (violet and white). (B) Seed: Testa mottling (present and absent). (C) Seed: Testa
colour (brown, grey, pink, green and black). (D) Tallness (short and medium).
Figure 3.
Morphological trait variation observed in lentil genotypes across two years. (
A
) Flower:
Colour of standard (violet and white). (
B
) Seed: Testa mottling (present and absent). (
C
) Seed: Testa
colour (brown, grey, pink, green and black). (D) Tallness (short and medium).

Sustainability 2022,14, 5982 7 of 19
Table 3. Distribution of phenotypic classes and significance tests among qualitative traits.
Trait State Frequency (%) DF Chi-Sqaure Genotypes
Foliage: Intensity
of green colour
Light 25.6
221.256 ***
RVL 31, RVL 13-7, JL 3, L 4727, LL 1373, DPL 62, WBL 77, LH
18-05, Pant Lentil 1, PL 02, Precoz
Medium 65.1
RVL 11-6, RVL 13-5, HUL 57, Kota Masoor-2, Kota Masoor-1,
RLG 5, L 4717, L 4076, LH 84-8, LL 699, LL 931, DPL 15, IPL 81,
IPL 316, IPL 220, Pant L -7, Pant L -8, Narender Masoor 1,
Narender Masoor 2, LH 16-01, LH 17-16, LH 17-17, LH 17-18,
LH 17-19, LH 18-04, PL 04, IPL 315, DPL 58
Dark 9.3 L 4147, LH 89-48, LH 82-6, IPL 406
Stem: Anthocyanin
colouration
Absent 83.7
119.558 ***
RVL 11-6, RVL 31, RVL 13-7, JL 3, HUL 57, Kota Masoor-2, RLG
5, L 4727, L 4717, L 4147, L 4076, LH 89-48, LH 84-8, LH 82-6,
LL 699, LL 1373, LL 931, DPL 15, DPL 62, IPL 81, IPL 406, IPL
316, WBL 77, Narender Masoor 2, LH 16-01, LH 17-16, LH
17-17, LH 17-18, LH 17-19, LH 18-04, LH 18-05, Pant Lentil 1,
PL 02, PL 04, Precoz, DPL 58
Present 16.3 RVL 13-5, Kota Masoor-1, IPL 220, Pant L -7, Pant L -8,
Narender Masoor 1, IPL 315
Time of flowering
Medium
(60–80 days) 41.9
11.140
RVL 11-6, RVL 13-5, RVL 31, RVL 13-7, JL 3, HUL 57, Kota
Masoor-2, Kota Masoor-1, RLG 5, L 4727, L 4717, DPL 15, DPL
62, IPL 220, WBL 77, Pant L -7, Pant Lentil 1, PL 02
Late
(>80 days) 58.1
L 4147, L 4076, LH 89-48, LH 84-8, LH 82-6, LL 699, LL 1373, LL
931, IPL 81, IPL 406, IPL 316, Pant L -8, Narender Masoor 1,
Narender Masoor 2, LH 16-01, LH 17-16, LH 17-17, LH 17-18,
LH 17-19, LH 18-04, LH 18-05, PL 04, Precoz, IPL 315, DPL 58
Leaflet: Size
Small 14
213.163 **
RVL 31, RVL 13-7, IPL 220, Pant L -8, Pant Lentil 1, PL 04
Medium 58.1
RVL 11-6, RVL 13-5, JL 3, RLG 5, L 4727, L 4717, L 4147, LH
89-48, LL 699, DPL 15, DPL 62, IPL 81, IPL 316, WBL 77, Pant L
-7, Narender Masoor 1, Narender Masoor 2, LH 16-01, LH 17-18,
LH 17-19, LH 18-05, PL 02, Precoz, IPL 315, DPL 58
Large 27.9 HUL 57, Kota Masoor-2, Kota Masoor-1, L 4076, LH 84-8, LH
82-6, LL 1373, LL 931, IPL 406, LH 17-16, LH 17-17, LH 18-04
Plant: Growth
habit
Erect (<30◦) 23.3
112.302 ***
RVL 13-7, RLG 5, L 4717, L 4147, LH 89-48, LL 699, Pant L -8,
LH 17-16, LH 18-04, IPL 315
Semi- erect
(30◦–60◦)76.9
RVL 11-6, RVL 13-5, RVL 31, JL 3, HUL 57, Kota Masoor-2, Kota
Masoor-1, L 4727, L 4076, LH 84-8, LH 82-6, LL 1373, LL 931,
DPL 15, DPL 62, IPL 81, IPL 406, IPL 316, IPL 220, WBL 77,
Pant L -7, Narender Masoor 1, Narender Masoor 2, LH 16-01,
LH 17-17, LH 17-18, LH 17-19, LH 18-05, Pant Lentil 1, PL 02,
PL 04, Precoz, DPL 58
Flower: Colour
of standard
Violet 90.7 128.488 ***
RVL 11-6, RVL 31, RVL 13-7, JL 3, HUL 57, Kota Masoor-2, Kota
Masoor-1, RLG 5, L 4727, L 4717, L 4147, L 4076, LH 89-48, LH
84-8, LH 82-6, LL 699, RVL 13-5, LL 1373, IPL 406, LL 931, DPL
15, DPL 62, IPL 81, IPL 316, IPL 220, Pant L -7, Pant L -8,
Narender Masoor 1, Narender Masoor 2, LH 16-01, LH 17-16,
LH 17-17, LH 17-18, LH 17-19, LH 18-04, LH 18-05, PL 04, IPL
315, DPL 58
White 9.3 PL 02, WBL 77, Pant Lentil 1, Precoz
Tallness
Short (<40 cm) 20.9
114.535 ***
RVL 31, RVL 13-7, JL 3, L 4717, L 4147, Narender Masoor 1,
Pant Lentil 1, PL 02, Precoz
Medium
(40–60 cm) 79.1
RVL 11-6, RVL 13-5, HUL 57, Kota Masoor-2, Kota Masoor-1,
RLG 5, L 4727, L 4076, LH 89-48, LH 84-8, LH 82-6, LL 699, LL
1373, LL 931, DPL 15, DPL 62, IPL 81, IPL 406, IPL 316, IPL 220,
WBL 77, Pant L -7, Pant L -8, Narender Masoor 2, LH 16-01, LH
17-16, LH 17-17, LH 17-18, LH 17-19, LH 18-04, LH 18-05, PL 04,
IPL 315, DPL 58
Seed: Size Small (<2.0 g) 18.6 3 10.116 * HUL 57, L 4717, L 4147, LH 89-48, IPL 220, WBL 77, Pant L -8,
Narender Masoor 2

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Table 3. Cont.
Trait State Frequency (%) DF Chi-Sqaure Genotypes
Medium
(2.0–2.5 g) 44.2
RVL 11-6, RVL 31, RVL 13-7, JL 3, Kota Masoor-2, Kota
Masoor-1, L 4727, LH 84-8, LL 699, Narend-er Masoor 1, LH
16-01, LH 17-16, LH 17-17, LH 18-04, LH 18-05, Pant Lentil 1,
PL 02, PL 04, IPL 315
Large
(2.6–3.0 g) 25.6
RLG 5, L 4076, LH 82-6, LL 931, DPL 15, IPL 81, IPL 316, Pant L
-7, LH 17-18, LH 17-19, DPL 58
Very large
(>3.0 g) 11.6 RVL 13-5, LL 1373, DPL 62, IPL 406, Precoz
Seed: Testa colour
Green 9.3
431.767 ***
IPL 406, Pant Lentil 1, PL 02, Precoz
Grey 44.2
RVL 31, Kota Masoor-1, RLG 5, L 4727, L 4717, L 4147, L 4076,
DPL 62, IPL 220, WBL 77, Pant L -7, LH 16-01, LH 17-16, LH
17-17, LH 17-18, LH 17-19, LH 18-04, IPL 315, DPL 58
Pink 7.0 RVL 13-5, LH 1373, PL 04
Brown 37.2
RVL 11-6, JL 3, HUL 57, Kota Masoor-2, LH 89-48, LH 84-8, LH
82-6, LL 699, LL 931, DPL 15, IPL 81, IPL 316, Pant L -8,
Narender Masoor 1, Narender Masoor 2, LH 18-05
Black 2.3 RVL 13-7
Seed: Testa
mottling
Present 83.7
119.558 ***
RVL 11-6, RVL 31, RVL 13-7, JL 3, HUL 57, Kota Masoor-2, Kota
Masoor-1, RLG 5, L 4727, L 4717, L 4147, L 4076, LH 89-48, LH
84-8, LH 82-6, LL 699, LL 931, DPL 15, DPL 62, IPL 81, IPL 316,
IPL 220, WBL 77, Pant L -7, Pant L -8, Narender Masoor 1,
Narender Masoor 2, LH 16-01, LH 17-16, LH 17-17, LH 17-18,
LH 17-19, LH 18-04, LH 18-05, IPL 315, DPL 58
Absent 16.3 RVL 13-5, LL 1373, IPL 406, Pant Lentil 1, PL 02, PL 04, Precoz
Cotyledon: Colour
Olive green 7.0
131.837 ***
Pant Lentil 1, PL 02, Precoz
Orange 93.0
RVL 11-6, RVL 13-5, RVL 31, RVL 13-7, JL 3, HUL 57, Kota
Masoor-2, Kota Masoor-1, RLG 5, L 4727, L 4717, L 4147, L 4076,
LH 89-48, LH 84-8, LH 82-6, LL 699, LL 1373, LL 931, DPL 15,
DPL 62, IPL 81, IPL 406, IPL 316, IPL 220, WBL 77, Pant L -7,
Pant L -8, Narender Masoor 1, Narender Masoor 2, LH 16-01,
LH 17-16, LH 17-17, LH 17-18, LH 17-19, LH 18-04, LH 18-05,
PL 04, IPL 315, DPL 58
DF = degrees of freedom. *, ** and *** = significance at 0.05, 0.01 and 0.001 levels, respectively.
3.2. Genotype and Genotype ×Environment Variations Based on Quantitative Traits
The analysis of variance (ANOVA) for eleven quantitative traits exhibited highly
significant differences (p< 0.001) among all the genotypes under study (Table 4). The
variation across the seasons was also significant (p< 0.001) for almost all the traits except
number of pods per plant (NPP) and hundred-seed weight (HSW). The genotype
×
season
interactions had significant (p< 0.001) effect on all the assessed traits except seeds per pod
(SP) (Table 4).
Table 4.
Mean squares of analysis of variance for seed yield and its components measured in 43 lentil
genotypes across two years.
Source of Variation DF DTF DTM PH NPP NPB NFB SP HSW BY HI SY
Season 1 1138.62 *** 8104.33 *** 1635.08 *** 253.02 ns 0.92 *** 1634.58*** 0.07 * 4,912,248.06 ns 113.34 *** 5858.33 *** 1.15 ***
Replication 2 7.41 * 22.96 *** 3.93ns 39.51 ns 0.07 ns 3.13 ns 0.03 ns 0.04 ns 0.99 ** 32.66 ns 0.07**
Genotype 42 62.46 *** 63.64 *** 216.71 *** 1037.55 *** 0.43*** 25.49 *** 0.19 *** 1.15 *** 1.52 *** 84.06 *** 0.19 ***
Genotype ×Season 42 7.78*** 35.19 *** 68.99 *** 712.40 *** 0.32 *** 14.49 *** 0.01 ns 0.09 *** 0.40 *** 42.35 *** 0.08 ***
Error 170 1.57 2.73 7.44 85.62 0.05 3 0.01 0.03 0.13 12.7 0.01
DF = degrees of freedom, DTF = Days to 50% flowering, DTM = Days to maturity, PH = Plant height (cm),
NPP = Number of pods per plant,
NPB = Number of primary branches, NFB = Number of fruiting branches,
SP = Seeds per pod
, HSW = 100-seed weight (g), BY = Biological yield per plot (kg), HI = Harvest index (%),
SY = Seed yield per plot (kg). *, ** and *** = significance at 0.05, 0.01 and 0.001 levels, respectively.
3.3. Mean Performance of Lentil Genotypes across the Environments
As shown in Tables 5and S1, genotype WBL 77 was the earliest to attain 50% flowering
at 73 days, which was followed by L 4717 at 74.3 days and IPL 220 at 75 days. However,

Sustainability 2022,14, 5982 9 of 19
genotype L 4717 was earliest to attain maturity at 112.3 days, followed by L 4727 at
117.1 days and RVL 11-6 at 119.3 days. Pant L-8 was the latest genotype to flower at
85.5 days, while DPL 15 was the latest to mature at 128.1 days. The mean DTF and DTM
were 79 and 124.3 days, respectively (Tables 5and S1). The mean plant height of test
genotypes was 44 cm, and it varied from 27.7 cm to 53.6 cm (Tables 5and S1). The shortest
genotype across the seasons was L 4717. The tallest genotypes, with plant height exceeding
50 cm, were RLG 5, LH 18-05, LH 82-6, IPL 81, LH 17-19, LH 17-17 and LH 18-04. The
mean number of pods per plant of the test genotypes was 115 (Tables 5and S1). The
most productive genotypes, with high number of pods per plant, were LH 17-19, IPL 316,
Pant L-8 and Pant L -7 with 140.1, 139.9, 131.7 and 131.1, respectively. The mean number
of primary branches varies from 2.4 to 3.53, with mean value for test genotypes of 2.93
(Tables 6and S1). Genotypes DPL 58, LH 17-19 and LH 18-04 were the best performing
genotypes with 3.53, 3.53 and 3.47 primary branches per plant, respectively. There was
a wide variation in number of fruiting branches, ranging from 11.3 to 20.6, with mean value
of 15.9 (Tables 6and S1). The highest numbers of fruiting branches per plant were 20.6, 20.1,
19.3 and 18.3, observed on the genotypes LL 1373, DPL 62, HUL 57 and LH 84-8, in that
order. The genotype
×
season interaction effects were non-significant for number of seeds
per pod. The mean number of seeds per pod was 1.64. The hundred-seed weight varied
from 1.7 to 3.5 g/100 seed (Tables 6and S1). Genotypes LL 1373, Precoz, IPL 406, DPL 62
and RVL 13-5 expressed the highest HSW:
3.0 g/100 seed
. The mean value of biological
yield per plot of the test genotypes was 3.224 kg (Tables 7and S1). The mean harvest index
(%) varied from 28.9 to 44.2%, with a grand mean of 34.6% (Tables 7and S1). The highest
harvest index was achieved by genotype L 4717 (44.2%), which is followed by LH 18-04
(43.5%) and LH 17-19 (40.4%). There was a marked genetic difference for seed yield per
plot ranging from 0.606 to 1.373 kg/plot with a mean of 1.072 kg/plot. Genotypes IPL 316,
LH 18-04 and LH 17-19 were the best-performing genotypes, with mean seed yield of 1.373,
1.347 and 1.301 kg/plot. The lowest yield response was recorded for genotypes RVL 13-7
and RVL 31, with seed yield less than 0.8 kg/plot.
Table 5.
Mean performance for days to 50% flowering, days to maturity, plant height and number
of pods per plant among the ten best- and five worst-performing genotypes after assessing 43 lentil
genotypes across two years.
Genotype
DTF
Genotype
DTM
Genotype
PH
Genotype
NPP
Y1 Y2 Mean Y1 Y2 Mean Y1 Y2 Mean Y1 Y2 Mean
Top Ten Genotypes
WBL 77 75.3 70.7 73 L 4717 116.0 108.7 112.3 RLG 5 50.5 56.7 53.6 LH 17-19 123.1 157.1 140.1
L 4717 78.3 70.3 74.3 L 4727 122.3 112.0 117.1 LH 18-05 54.1 50.5 52.4 IPL 316 144.2 135.5 139.9
Kota
Masoor-2 76.3 73.0 74.7 RVL 11-6 122.3 116.3 119.3 LH 82-6 48.3 55.8 52.1 Pant L -8 136.4 127.0 131.7
IPL 220 78.3 71.7 75 RVL 31 120.7 118.3 119.5 IPL 81 58.5 45.5 52.0 Pant L -7 118.9 143.3 131.1
JL 3 76.0 74.0 75 WBL 77 123.7 116.0 119.8 LH 17-19 53.0 49.1 51.1 LH 17-17 125.4 133.5 129.5
RVL 31 76.7 74.0 75.3 RVL 13-7 119.3 121.0 120.1 LH 17-17 57.5 44.1 50.8 LH 17-18 113.8 141.3 127.6
RVL 13-7 77.0 74.3 75.7 JL 3 121.7 119.7 120.7 LH 18-04 50.2 50.4 50.3 IPL 81 126.2 128.2 127.2
Kota
Masoor-1 77.7 74.0 75.8 Pant L -7 127.3 114.7 121 LH 84-8 52.3 47.6 49.9 LH 18-04 128.5 125.8 127.1
L 4727 79.0 72.7 75.8 PL 04 125.3 117.7 121.5 RVL 13-5 53.1 46.1 49.7 LH 18-05 119.9 131.4 125.7
Pant L -7 78.0 73.7 75.8 Precoz 127.7 117.7 122.7 IPL 406 55.9 42.1 49.1 RVL 31 105.5 140.9 123.2
Bottom Five Genotypes
LH 17-16 85.7 80.0 82.83 LH 17-17 135.7 119.0 127.3 Narender
Masoor 1 39.5 37.5 38.5 Pant
Lentil 1 108.6 81.9 95.3
LH 82-6 84.7 83.7 84.17 LL 931 134.0 121.0 127.5 JL 3 39.2 33.3 36.3 JL 3 105.0 75.5 90.3
L 4147 85.3 84.0 84.67 IPL 81 134.3 121.0 127.7 Precoz 30.7 29.0 29.87 L 4717 98.9 79.6 89.3
LL 699 86.7 84.3 85.5 PL 02 134.3 121.3 127.8 RVL 13-7 32.7 25.4 29.03 L 4727 91.8 85.6 88.7
Pant L -8 86.0 85.0 85.5 DPL 15 135.3 121.0 128.1 L 4717 32.1 23.2 27.67 RVL 13-7 95.8 71.2 83.5
Mean 81.1 76.9 79.0 Mean 129.9 118.7 124.3 Mean 46.5 41.4 44.0 Mean 114.3 112.3 113.3
STD 3.46 3.64 4.12 STD 5.23 3.00 7.05 STD 7.02 7.38 7.62 STD 15.45 21.21 18.54
SE (m) 0.30 0.32 0.26 SE (m) 0.46 0.26 0.44 SE (m) 0.62 0.65 0.47 SE (m) 1.36 1.87 1.15
CV (%) 4.3 4.7 5.2 CV (%) 4.0 2.5 5.7 CV (%) 15.1 17.8 17.3 CV (%) 13.5 18.9 16.4
STD = standard deviation, SE (m) = standard error (mean), CV = coefficient of variation, Y1 = year 1 (
2019–2020
),
Y2 = year 2 (2020–2021), DTF = Days to 50% flowering, DTM = Days to maturity, PH = Plant height (cm),
NPP = Number of pods per plant.

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Table 6.
Mean performance for number of primary branches, number of fruiting branches, seeds per
pod and 100-seed weight among the ten best- and five worst-performing genotypes after assessing
43 lentil genotypes across two years.
Genotype
NPB
Genotype
NFB
Genotype
SP
Genotype
HSW
Y1 Y2 Mean Y1 Y2 Mean Y1 Y2 Mean Y1 Y2 Mean
Top Ten Genotypes
DPL 58 3.87 3.20 3.53 LL 1373 25.9 15.2 20.6 HUL 57 1.90 1.97 1.93 LL 1373 3.54 3.47 3.50
LH 17-19 3.40 3.67 3.53 DPL 62 22.4 17.8 20.1 Narender
Masoor 2 1.87 1.97 1.92 Precoz 3.34 3.44 3.39
LH 18-04 3.73 3.20 3.47 HUL 57 21.9 16.7 19.3 IPL 81 1.90 1.87 1.88 IPL 406 3.48 3.11 3.30
RVL 11-6 3.87 2.87 3.37 LH 84-8 22.3 14.2 18.3 LH 17-16 1.93 1.83 1.88 DPL 62 3.23 3.03 3.13
LL 699 3.07 3.53 3.3 IPL 81 22.7 13.8 18.2 Pant L -8 1.83 1.87 1.85 RVL 13-5 3.20 2.90 3.05
Kota
Masoor-2 3.67 2.87 3.27 L 4147 21.7 14.5 18.2 LH 17-19 1.83 1.87 1.85 Pant L -7 2.67 2.93 2.80
L 4147 3.20 3.13 3.17 IPL 316 18.7 17.3 18.0 WBL 77 1.83 1.87 1.85 DPL 58 2.76 2.72 2.74
LH 17-17 2.93 3.33 3.13 LH 16-01 20.6 15.1 17.9 L 4147 1.83 1.83 1.83 DPL 15 2.79 2.64 2.72
IPL 220 3.33 2.87 3.1 Pant L -8 23.7 11.9 17.8 LL 931 1.80 1.87 1.83 LL 931 2.81 2.55 2.68
IPL 316 2.93 3.20 3.07 LH 18-05 19.3 15.6 17.5 RVL 11-6 1.73 1.87 1.8 LH 82-6 2.83 2.52 2.67
Bottom Five Genotypes
LL 931 2.47 2.67 2.57 IPL 406 16.1 10.8 13.5 LH 17-18 1.40 1.43 1.42 L 4717 1.68 1.91 1.79
LL 1373 2.40 2.67 2.53 Pant
Lentil 1 14.2 11.0 12.6 RVL 13-7 1.40 1.23 1.32 IPL 220 1.80 1.65 1.73
L 4727 2.40 2.67 2.53 Precoz 11.9 12.3 12.1 LH 17-17 1.33 1.27 1.3 L 4147 1.69 1.75 1.72
RVL 13-7 2.60 2.47 2.53 LH 89-48 13.8 10.0 11.9 IPL 406 1.23 1.33 1.28 Narender
Masoor 2 1.70 1.73 1.71
PL 02 2.27 2.47 2.37 L 4717 12.5 10.0 11.3 Pant L -7 1.23 1.27 1.25 Pant L -8 1.74 1.67 1.7
Mean 2.99 2.87 2.93 Mean 18.4 13.4 15.9 Mean 1.62 1.65 1.64 Mean 2.46 2.46 2.46
STD 0.45 0.35 0.40 STD 3.37 2.41 3.86 STD 0.20 0.20 0.20 STD 0.50 0.52 0.47
SE (m) 0.04 0.03 0.03 SE (m) 0.30 0.21 0.24 SE (m) 0.02 0.02 0.01 SE (m) 0.04 0.05 0.03
CV (%) 14.9 12.2 13.8 CV (%) 18.3 18.0 24.3 CV (%) 12.6 12.2 12.4 CV (%) 20.1 21.1 19.1
STD = standard deviation, SE (m) = standard error (mean), CV = coefficient of variation, Y1 = year 1 (2019–2020),
Y2 = year 2 (2020–2021), NPB = Number of primary branches, NFB = Number of fruiting branches, SP = Seeds per
pod, HSW = 100-seed weight (g).
Table 7.
Mean performance for biological yield, harvest index and seed yield among the ten best-
and five worst-performing genotypes after assessing 43 lentil genotypes across two years.
Genotype BY Genotype HI Genotype SY
Y1 Y2 Mean Y1 Y2 Mean Y1 Y2 Mean
Top Ten Genotypes
LL 931 4.740 3.450 4.096 L 4717 45.4 43.1 44.2 IPL 316 1.429 1.316 1.373
DPL 15 5.237 2.756 3.996 LH 18-04 38.1 48.9 43.5 LH 18-04 1.410 1.283 1.347
IPL 316 4.757 3.187 3.972 LH 17-19 33.8 47.0 40.4 LH 17-19 1.297 1.304 1.301
DPL 62 4.683 3.186 3.935 Kota Masoor-2 36.4 43.7 40.0 LL 699 1.293 1.294 1.294
IPL 81 4.977 2.831 3.905 LH 17-18 33.2 46.4 39.8 LH 84-8 1.337 1.243 1.290
L 4147 4.447 3.264 3.855 WBL 77 38.0 39.4 38.7 LH 82-6 1.298 1.261 1.280
LH 82-6 4.387 3.197 3.79 LH 17-17 34.4 41.7 38.1 Kota Masoor-2 1.521 0.966 1.244
RLG 5 4.163 3.115 3.638 Pant L -7 33.0 42.3 37.6 Pant L -8 1.292 1.192 1.242
L 4076 4.120 3.076 3.599 LH 84-8 32.2 42.9 37.6 IPL 81 1.301 1.131 1.216
IPL 315 4.463 2.718 3.592 Kota Masoor-1 31.3 43.8 37.6 IPL 220 1.381 1.036 1.209
Bottom Five Genotypes
Precoz 2.673 2.512 2.593 LL 1373 22.5 37.3 29.9 L 4727 0.902 0.732 0.817
RVL 11-6 3.313 1.861 2.588 Pant Lentil 1 31.7 28.1 29.9 Precoz 0.796 0.825 0.811
RVL 31 2.977 1.870 2.423 L 4727 27.6 31.5 29.53 JL 3 0.933 0.685 0.809
L 4717 2.673 1.728 2.201 LH 18-05 26.5 31.9 29.17 RVL 31 0.777 0.709 0.743
RVL 13-7 2.217 1.762 1.991 LL 931 21.1 36.7 28.9 RVL 13-7 0.651 0.560 0.606
Mean 3.887 2.561 3.224 Mean 29.8 39.3 34.6 Mean 1.138 1.005 1.072
STD 0.74 0.52 0.92 STD 5.61 5.24 7.22 STD 0.22 0.23 0.24
SE (m) 0.07 0.05 0.06 SE (m) 0.49 0.46 0.45 SE (m) 0.02 0.02 0.01
CV (%) 19.0 20.2 28.5 CV (%) 18.8 13.3 20.9 CV (%) 19.2 23.3 22.0
STD = standard deviation, SE (m) = standard error (mean), CV = coefficient of variation, Y1 = year 1 (2019–2020),
Y2 = year 2 (2020–2021), BY = Biological yield per plot (kg), HI = Harvest index (%), SY = Seed yield per plot (kg).

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3.4. Interrelations among Agro-Morphological Traits
Positive correlation was observed among most of the traits (Table 8). DTF had sig-
nificant positive association with DTM, PH, NPP, BY and SY (p< 0.01). Similarly, NPB
exhibited positive correlation with PH, NPP, HI and SY (p< 0.01). Assessed traits revealed
a variable degree of relationships with seed yield. SY was highly significantly (p< 0.01) and
positively correlated with DTF, DTM, PH, NPP, NPB, BY and HI. SY and BY exhibited the
strongest correlation (r = 0.77, p< 0.01). However, SY exhibited weak negative correlation
with HSW (r =
−
0.18). Moreover, HSW had significant negative relationship with SP
(r = −0.45, p< 0.01).
Table 8.
Phenotypic correlation coefficients among the eleven quantitative traits of 43 lentil genotypes.
Trait DTF DTM PH NPP NPB NFB SP HSW BY HI SY
DTF 1
DTM 0.482 ** 1
PH 0.434 ** 0.672 ** 1
NPP 0.398 ** 0.464 ** 0.529 ** 1
NPB 0.334 * 0.245 0.460 ** 0.455 ** 1
NFB 0.365 * 0.424 ** 0.391 ** 0.458 ** 0.234 1
SP 0.253 0.094 0.059 0.208 0.220 0.249 1
HSW −0.027 0.230 0.159 0.002 −0.180 0.132 −0.445 ** 1
BY 0.417 ** 0.677 ** 0.608 ** 0.455 ** 0.289 0.541 ** 0.277 0.119 1
HI 0.024 −0.191 0.040 0.279 0.390** −0.181 0.038 −0.0393 ** −0.189 1
SY 0.414 ** 0.517 ** 0.574 ** 0.600 ** 0.548** 0.344 * 0.256 −0.175 0.765 ** 0.467 ** 1
** Correlation significant at p= 0.01, * Correlation significant at p= 0.05 (2-tailed), DTF = Days to 50% flowering,
DTM = Days to maturity, PH = Plant height (cm), NPP = Number of pods per plant, NPB = Number of primary
branches, NFB = Number of fruiting branches, SP = Seeds per pod, HSW = 100-seed weight (g), BY = Biological
yield per plot (kg), HI = Harvest index (%), SY = Seed yield per plot (kg).
3.5. Principal Component Analysis
The principal component analysis (PCA) was performed to obtain a better under-
standing of sources of variance among lentil genotypes. PCA reduces the number of traits
influencing the maximum percentage of total variance. Of the 11 principal components
(PCs) produced, only first three PCs are discussed, as their eigen values were more than
one. A total of 67.5% variation was explained by the first three PCs (Table 9). PC1 explained
39.2% of total variation and was positively influenced by BY (0.89), DTM (0.79), NFB (0.72),
PH (0.70), SY (0.64), DTF (0.63) and NPP (0.59). PC2 added 16.8% of total variation, and
the traits HI, NPB and SY were the highest contributors, with contributions of 0.88, 0.62
and 0.57, respectively. The third PC explained 11.5% of total variation, SP was the only
major positive contributor with PC loading of 0.84, and HSW was the only major negative
contributor with PC loading of −0.75.
Table 9.
Eigen values, eigen vectors and proportion of variation accounted for by first three princi-
pal components.
Trait
Dimension
1 2 3
BY 0.891 −0.028 0.092
DTM 0.793 0.038 −0.165
NFB 0.723 −0.067 0.212
PH 0.706 0.342 −0.328
SY 0.647 0.567 0.102
DTF 0.637 0.157 0.153
NPP 0.597 0.475 −0.028
HI −0.183 0.881 0.127
NPB 0.373 0.622 0.096
SP 0.258 −0.033 0.843
HSW 0.176 −0.372 −0.755

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Table 9. Cont.
Trait
Dimension
1 2 3
Eigen value 4.308 1.847 1.268
Variance % 39.2 16.8 11.5
Cumulative 39.2 56.0 67.5
For trait code description, refer to Table 2.
Three groups of characters were identified on the basis of trait biplot, as shown in
Figure 4. The first group was composed of NPB, SY, NPP, PH, DTF and DTM, which
showed positive association with the first two PCs. The second group was negatively
correlated with PC2 and comprised BY, NFB, SP and HSW. The third group contained HI
that was negatively correlated with PC1. Furthermore, traits such as NPB, NPP, PH, DTF,
DTM, BY, NFB and SY were positively correlated to each other, since vectors of these traits
were in the same direction and formed acute angles between each other. However, HSW
was negatively associated with SY, as depicted by the obtuse angle between them.
Sustainability 2022, 14, x FOR PEER REVIEW 12 of 19
Three groups of characters were identified on the basis of trait biplot, as shown in
Figure 4. The first group was composed of NPB, SY, NPP, PH, DTF and DTM, which
showed positive association with the first two PCs. The second group was negatively cor-
related with PC2 and comprised BY, NFB, SP and HSW. The third group contained HI
that was negatively correlated with PC1. Furthermore, traits such as NPB, NPP, PH, DTF,
DTM, BY, NFB and SY were positively correlated to each other, since vectors of these traits
were in the same direction and formed acute angles between each other. However, HSW
was negatively associated with SY, as depicted by the obtuse angle between them.
Figure 4. Trait biplot ordination depicting the association among quantitative traits in 43 lentil geno-
types assessed across two years. For trait code and genotype description, refer to Tables 1 and 2.
3.6. Cluster Analysis
Eleven agro-morphological traits delineated 43 lentil genotypes into five major clus-
ters. From Table 10 and Figure 5, it is clearly evident that Cluster I was the largest (28
genotypes) group. Clusters III and IV contained 10 and 3 genotypes, respectively. Cluster
II as well as Cluster V were the smallest groups, containing one genotype each. The allo-
cation of genotypes into different clusters was not specific, as clusters consisted of a mix-
ture of cultivars and advanced breeding lines. However, Precoz, the only exotic cultivar,
was solely placed in Cluster II. The minimum inter-cluster distance was 36.40 units be-
tween Cluster I and II (Table 11). Cluster III and Cluster V were the most diverse groups,
with 94.69 units inter-cluster distance. Furthermore, the maximum intra-cluster distance
was recorded in Cluster I (24.85 units), while minimum intra-cluster distance was found
in Cluster IV, which congregated three genotypes (Table 11). Cluster III had the highest
mean values for six traits (Table 12): DTM (125.07 days), PH (47.50 cm), NPP (130.28), NPB
(3.08), NFB (16.42) and SY (1.15 kg). The second group (Cluster II) included the highest
average for three traits: DTF (80.67 days), SP (1.67) and HSW (3.39 g). On the contrary,
Cluster V recorded the lowest mean values for the traits DTF (74.33 days), DTM (112.33),
PH (27.67 cm), NPB (2.63), NFB (11.25), HSW (1.79 g) and BY (2.20 kg). However, Cluster
V revealed the highest average for HI (44.25%).
Figure 4.
Trait biplot ordination depicting the association among quantitative traits in 43 lentil
genotypes assessed across two years. For trait code and genotype description, refer to Tables 1and 2.
3.6. Cluster Analysis
Eleven agro-morphological traits delineated 43 lentil genotypes into five major clusters.
From Table 10 and Figure 5, it is clearly evident that Cluster I was the largest (28 genotypes)
group. Clusters III and IV contained 10 and 3 genotypes, respectively. Cluster II as well
as Cluster V were the smallest groups, containing one genotype each. The allocation of
genotypes into different clusters was not specific, as clusters consisted of a mixture of
cultivars and advanced breeding lines. However, Precoz, the only exotic cultivar, was solely
placed in Cluster II. The minimum inter-cluster distance was 36.40 units between Cluster I
and II (Table 11). Cluster III and Cluster V were the most diverse groups, with 94.69 units
inter-cluster distance. Furthermore, the maximum intra-cluster distance was recorded in
Cluster I (24.85 units), while minimum intra-cluster distance was found in Cluster IV, which
congregated three genotypes (Table 11). Cluster III had the highest mean values for six
traits (Table 12): DTM (125.07 days), PH (47.50 cm), NPP (130.28), NPB (3.08), NFB (16.42)

Sustainability 2022,14, 5982 13 of 19
and SY (1.15 kg). The second group (Cluster II) included the highest average for three
traits: DTF (80.67 days), SP (1.67) and HSW (3.39 g). On the contrary, Cluster V recorded
the lowest mean values for the traits DTF (74.33 days), DTM (112.33), PH (27.67 cm), NPB
(2.63), NFB (11.25), HSW (1.79 g) and BY (2.20 kg). However, Cluster V revealed the highest
average for HI (44.25%).
Sustainability 2022, 14, x FOR PEER REVIEW 13 of 19
Figure 5. Hierarchical clustering depicting genetic similarity matrix of 43 lentil genotypes evaluated
across two years.
Figure 5.
Hierarchical clustering depicting genetic similarity matrix of 43 lentil genotypes evaluated
across two years.

Sustainability 2022,14, 5982 14 of 19
Table 10.
Grouping of 43 lentil genotypes into different clusters using between-group method when
evaluated for eleven quantitative traits.
Cluster No. of Genotypes Name of Genotypes
Cluster I 28
RVL 11-6, RVL 13-5, HUL 57, Kota Masoor-2, Kota
Masoor-1, RLG 5, L 4147, L 4076, LH 89-48, LH 84-8, LH
82-6, LL 699, LL 1373, LL 931, DPL 15, DPL 62, IPL 406,
IPL 220, WBL 77, Narender Masoor 1, Narender Masoor
2, LH 16-01, LH 17-16, Pant Lentil 1, PL 02, PL 04, IPL
315, DPL 58
Cluster II 1 Precoz
Cluster III 10 RVL 31, IPL 81, IPL 316, Pant L -7, Pant L -8, LH 17-17,
LH 17-18, LH 17-19, LH 18-04, LH 18-05
Cluster IV 3 RVL 13-7, JL 3, L 4727
Cluster V 1 L 4717
Table 11. Inter- and intra-cluster (diagonal) distance for 43 genotypes of lentil.
Cluster I II III IV V
I 24.85
II 36.40 -
III 39.14 57.22 23.72
IV 50.29 41.33 75.41 13.61
V 74.02 54.13 94.69 37.46 -
Table 12.
Mean values of 11 quantitative traits for five clusters revealed by cluster analysis among
43 lentil genotypes.
Cluster DTF DTM PH (cm) NPP NPB NFB SP HSW (g) BY (kg) HI (%) SY (kg)
I 79.13 125.07 44.63 111.01 2.93 16.18 1.67 2.45 3.36 33.97 1.09
II 80.67 122.67 29.85 108.58 2.73 12.12 1.67 3.39 2.59 31.47 0.81
III 80.10 125.07 47.50 130.28 3.08 16.42 1.60 2.49 3.24 36.73 1.15
IV 75.50 119.33 36.01 87.48 2.64 14.62 1.46 2.46 2.50 30.69 0.74
V 74.33 112.33 27.67 89.25 2.63 11.25 1.60 1.79 2.20 44.25 0.96
DTF = Days to 50% flowering, DTM = Days to maturity, PH = Plant height (cm), NPP = Number of pods per plant,
NPB = Number of primary branches, NFB = Number of fruiting branches, SP = Seeds per pod, HSW = 100-seed
weight (g), BY = Biological yield per plot (kg), HI = Harvest index (%), SY = Seed yield per plot (kg).
4. Discussion
With limited availability of genetic variability in the primary gene pool of lentil, selec-
tion of superior and complementary genotypes may be used effectively to aid in varietal
development as per the needs of farmers and consumers. Knowledge of genetic diversity
assists in the selection of parental genotypes from random populations and enables the es-
tablishment of heterotic groups. The present study assessed 43 lentil genotypes across two
cropping seasons to evaluate the extent of genetic diversity and inter-relatedness among
traits and to select potential genotypes with good complementation to develop transgres-
sive segregates. The genotypes exhibited significant variation in qualitative traits (Table 3),
which connotes the presence of important genetic variation in test genotypes that fosters
morphological variation. Similar findings have been reported by Gaad et al. [
23
], who
found significant variation in qualitative traits among lentil accessions procured for Algeria,
ICARDA and USDA genebanks. The heterogeneity in morphological traits such as plant
height, growth habit and seed traits is important for tailoring cultivars that meet farmers’
needs. For instance, breeding cultivars adapted for mechanical harvesting require screening
of genotypes with tall stature and erect or semi-erect growth habit. Since tallness and erect
growth habit are among the traits, in addition to non-lodging and even ripening, to be in-
corporated into genotypes to assist harvest mechanization [
24
]. However,
Jawad et al. [25]
reported that genotypes suitable for mechanized harvesting are low yielders and thus

Sustainability 2022,14, 5982 15 of 19
require hybridizing with high-yielding genotypes. The variation in lentil seed traits such
as seed testa colour and cotyledon colour also helps in recognizing genotypes preferred by
local farmers and consumers. For example, red lentils that have orange cotyledon colour are
preferred by farmers in South Asia [
26
]. This preference for red lentils is associated with the
fact that lentil is grown in South Asia as a winter crop, where temperature increases as crop
heads toward maturity, resulting in a shorter seed-filling period in which red lentils yield
higher than green lentils [
24
]. Similarly, Choudhary et al. [
27
] reported a preponderance
of red lentils genotypes with brown or grey testa colour and orange cotyledons in the
Indian subcontinent, indicating the farmers’ colour preference. Therefore, knowledge of
farmers’ and consumers’ preferences, the needs of mechanized harvesting and variation in
qualitative traits among the genotypes becomes useful for structuring appropriate breeding
objectives and thus suitable breeding programmes.
Being highly self-pollinated (out-crossing less than 0.08%) and inbreeding species,
presence of genetic variation is indispensable for improvement of quantitative traits in
lentil. The ANOVA for tested traits exhibited significant differences among the genotypes
(Table 4), highlighting the presence of an ample amount of genetic variation for exploita-
tion in future breeding programmes. The differences in genetic composition among the
genotypes are largely responsible for expressed genetic variation, which is imperative for
crop improvement [
28
]. Similar findings have been reported by many lentil researchers
for different traits [
29
]. The genotype performances were also not consistent across two
cropping seasons, as indicated by significant genotype and season interactions for most
of the quantitative traits (Table 4). Temperature and rainfall are among the elements that
influence phenotypic expression in the environment. Because of the strong effect of the
environment on phenotypic expression, genotype–phenotype correlation is known to be
reduced [
30
], making the identification of stable and superior genotypes more difficult.
Nevertheless, significant genotype
×
environment interactions affecting different quantita-
tive traits have been described previously for various legumes including lentil, pigeonpea
and cowpea [31–33].
In the present study, there was a significant difference in genotype performance for
seed yield and its attributing traits across the two cropping seasons. For the majority
of genotypes, days to maturity, seed yield, biological yield, plant height and number of
branches were considerably lower in cropping season 2020–2021 than in cropping season
2019–2020 (Tables 5–7). This was due to markedly higher daytime temperatures throughout
and after blooming up to maturity in cropping season 2020–2021, as well as significantly
lower cumulative rainfall when compared with cropping season 2019–2020 (Figure 1). High
temperatures post-flowering restrict vegetative growth, accelerate crop towards maturity
and thus ultimately reduce seed yield [
34
]. Furthermore, about 50% accumulation of
stem dry matter in lentil occurs after peak flowering [
35
]; thus, water deficits during the
reproductive and grain filling stages reduce biological yield and thereby substantially
decrease seed yield [
36
–
38
]. Similarly, Sehgal et al. [
39
] reported in their research about the
adverse effects of drought and heat stress at time of grain filling on seed yield in lentil.
In order to initiate an effective crop improvement program, knowledge of inter-trait
correlation among the traits is imperative. Directly selecting for complex traits such as yield,
which are expressed late, may end up making the selection process complicated and time-
consuming. Moreover, yield is a quantitatively inherited trait and is influenced by genetic
effects as well as genotype and environment interactions. Therefore, indirect selection is
preferred, because indirect character is considerably easier to quantify than direct character.
Hence, it’s a good idea to seek and employ strongly associated characters [
40
]. In the
present study, highly positively significant association of SY with DTF, DTM, PH, NPP,
NPB, BY and HI (p< 0.01) was observed (Table 8). In indeterminate legumes, seed yield
is a function of number of branches, number of pods, biological yield and proportion of
flowers that end up forming mature pods [
41
]. Multiple-trait selection is also feasible, as
most of the traits exhibit positive association. Thus, selection for these positively associated
yield-attributing traits could bring about sufficient gain in seed yield. Similar results

Sustainability 2022,14, 5982 16 of 19
have been reported by [
42
,
43
] in their studies. However, SY was found to be weakly and
negatively correlated with HSW, which may result in inefficient selection or low genetic
gain. Furthermore, HSW was found negatively associated with SP, but SP was positively
correlated with SY. A weak correlation between SY and HSW was also reported by [
44
,
45
].
Conversely, Sharma et al. [
29
] and Kumar et al. [
42
] reported a positive association between
HSW and SY. The significant positive correlation exhibited between DTF, DTM, PH and BY
suggests that indirect selection for earliness could be performed using plant height and
biological yield as reference traits. Since winter lentil, especially in South Asia, is frequently
exposed to terminal heat and drought stress, there is a need to develop short-duration
cultivars to mitigate yield losses [
46
]. The significant relationship between DTF, DTM, PH,
NPP, NPB, BY, HI and SY connotes that these quantitative traits would be a good index to
screen genotypes for higher grain yield. The genetic cause of notable association between
traits was likely attributable to the pleiotropic effect rather than linkage between the genes
controlling various characters [47].
The reduction of number of traits responsible for maximum variation and identification
of important traits with high variability among the genotypes was made possible by
using principal component analysis. In this study, there were considerable morphological
differences among the genotypes, as a few eigen vectors elucidated the majority of observed
variation (Table 9). The results further revealed that SY, DTF, DTM, NPP, NPB, PH and BY
were the most important traits due to their high contribution to PC1. This suggests that
selection should be performed for those genotypes that report high and desirable mean
performances for these targeted traits. These findings are in agreement with [
29
,
48
], who
found that the first three PCs accounted for the majority of variation and traits associated
with them were vital for crop improvement. Furthermore, the positive association between
SY, NPB, NPP, PH, DTF, DTM, BY and NFB was again confirmed by biplot ordination
(Figure 4), in which the angle between vectors of these correlated traits was acute. Therefore,
indirect selection for seed yield could be practised using these associated traits, as they also
exhibited high contribution to PCs.
UPGMA dendrogram delineated the lentil genotypes into five groups (Table 10,
Figure 5
), which further implied broad genetic diversity among the genotypes. How-
ever, the presence of cultivars and advanced breeding lines from different institutes across
India (from where genotypes were sourced) in each group could be attributed to the use of
a few superior parental lines in lentil breeding programmes. According to Kumar et al. [
11
],
ten parental lines contributed approximately 30% of the genetic base in 35 lentil cultivars.
In addition, Precoz, an exotic line, has been extensively used in recombination programmes
to broaden the genetic base of microsperma Indian germplasm since the 1990s. Precoz
was the first identified exotic macrosperma early-flowering genotype [
11
,
13
,
15
]. Mean
values of clusters connoted that Cluster III was outstanding due to highest trait values,
principally for NPP, NPB, NFB, PH and SY, while Cluster V was the earliest to flower
and mature and had highest mean performance for HI (Table 12). Moreover, Cluster III
and V were the most distant groups, implying wider diversity among the genotypes of
these groups (Table 11). Therefore, lentil breeders should choose genotypes from Cluster
III and V during breeding experiments to produce sufficient variability and screen out
transgressive segregants. The present findings are in agreement with previous works,
one of which reported that on the basis of 11 quantitative traits, 50 lentil accessions were
clustered into seven groups [
29
], while Maurya et al. [
49
] found that 74 lentil genotypes
were discriminated into nine different clusters based on 11 agro-morphological traits.
5. Conclusions
In current study, 43 lentil genotypes were examined for their diversity to identify
complementary and unique genotypes for lentil breeding programmes. The data obtained
showed that genotypes possessed a wide range of diversity for qualitative traits. The study
would also be beneficial for choosing appropriate genotypes with suitable plant types and
seed traits that align with the interests of farmers and consumers. There was substantial

Sustainability 2022,14, 5982 17 of 19
genetic variation among the genotypes and significant genotype
×
environment effects for
most traits, connoting the urgency of exploiting a high degree of genetic variation through
selection. Multiple-trait selection would be highly advantageous, as seed yield and most
other quantitative traits were positively and significantly correlated. The PCA analysis
recognized SY, DTF, DTM, NPP, NPB, PH and BY as target traits that prominently described
variation within lentil genotypes. Hence, these traits should serve as useful selection indices
for lentil improvement. The cluster analysis discriminated the lentil genotypes into five
discrete clusters and advocated for hybridization between genotypes present in Cluster
III and V to yield superior transgressive segregants. Since drought and heat stress are
frequent occurring phenomena due to global warming and climate change, the need to
develop early-maturing cultivar is inevitable. Therefore, to obtain a broad spectrum of
early-maturing high-yielding segregants, the genotypes IPL 316, LH 17-19, LH 18-04, LH
17-17, IPL 81 and Pant L-8 grouped in Cluster III with high mean performances for target
traits such as yield and its attributing traits should be hybridized with L 4717 (Cluster V),
which was the earliest to flowering and maturity. The results of the present study would
help to identify heterotic clusters and superior parents for structuring breeding strategies
to develop improved lentil cultivars.
Supplementary Materials:
The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/su14105982/s1, Table S1: Pooled mean performance of forty-
three genotypes of lentil for eleven characters.
Author Contributions:
Each author has participated sufficiently in the completion of this work. L.C.,
M.K. and R.Y. contributed to the experimental design, data analysis and review of manuscript. U.D.
contributed to methodology and visualization. R.S. implemented the experiment, analysed the data
and wrote up the manuscript. A. and V.K. contributed to data collection and visualization. All
authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Data Availability Statement: Data are contained within the article and Supplementary Materials.
Acknowledgments:
The authors acknowledge the station managers and technical staff of Pulses
Section, Department of Genetics and Plant Breeding, CCS HAU, for technical assistance and overall
support. All India Coordinated Projects (AICRP) on MULLaRP stationed at Indian Institute of Pulses
Research, Kanpur, are sincerely thanked for providing the genotypes used in the study. The authors
duly acknowledge the Department of Agricultural Meteorology for providing data for different
weather parameters.
Conflicts of Interest: The authors declare no conflict of interest.
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