Heliyon 7 (2021) e07940
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Heliyon
journal homepage: www.cell.com/heliyon
Research article
Evaluation of growth and yield traits in rice genotypes using
multivariate analysis
Jiban Shrestha *, Sudeep Subedi, Ujjawal Kumar Singh Kushwaha, Bidhya Maharjan
Nepal Agricultural Research Council, National Plant Breeding and Genetics Research Centre, Khumaltar, Lalitpur, Nepal
A R T I C L E I N F O
A B S T R A C T
Keywords:
Clusters
Grain yield
Plant height
Rice
Rice (Oryza sativa L.) is the first staple crop in terms of production and area of cultivation in Nepal. The amount of
genetic variability is important factor in identifying suitable genotypes in rice breeding programs. This study was
conducted in Khumaltar, Lalitpur, Nepal during rainy seasons of 2018 and 2019. Forty rice genotypes were
planted in Alpha Lattice Design with two replications to determine the genetic diversity among them. The rice
genotypes were grouped into 7 clusters based on growth and yield traits. The traits sucnamely plant height,
panicle length, number of tillers/plant and grain yield were found highly significant (p < 0.01). Rice genotypes
NR 10676-B-1-3-3-3 produced the highest yield (5.65 t/ha), followed by NR10410-89-3-2-1-1 (5.54 t/ha). The
highest distance between cluster centroids (83.51) was found in the cluster 2 (Bange Masino, Hansa raj, Indrabeli,
NR 11178-B-B-6-1, NR 11368-B-B-17, Pokhreli Jethobudho, Pokhreli Masino), and cluster 4 (IR73008-136-2-2-3,
IR74052-95-3-2) indicating genetic dissimilarity among the genotypes which can be utilized in a hybrid breeding
programme. Genotypes of cluster 2 had the highest grain yield (4.97 t/ha). The results of this study suggest that
genotypes grouped in cluster 2 can be grown for higher grain production in mid-hills of Nepal.
1. Introduction
Rice (Oryza sativa L.) is one of the leading staple food crops, feeding over
half of the world's population (Ricepedia, 2020; USDA, 2020). In Asia, it is
grown to the tune of 90% of the world's supply (Paranthaman et al., 2009). In
Nepal rice is the first staple food crop, contributing significantly to the
country's economy and supplying a substantial share of people's livelihoods.
It is grown on 1.49 million hectares with a total yield of 5.61 million tons and
a productivity of 3.76 t/ha in Nepal (CBS, 2018). Development of rice varieties with enhanced yield potential is a objective in rice breeding program
in Nepal. A number of varieties of rice have been developed and adapted in
the different agro-ecosystems of the country (Joshi, 2017). Breeders use
different methods for identifying superior rice varieites; among these
methods, multivariate analysis is the most commonly used approach for
assessing genetic variability. To maintain high productivity levels, genetic
diversity is essential (Tripathi et al., 2013). When it comes to selecting the
right kind of parents for a hybridization programme, it is the most important
tool for a plant breeder. The use of genetic divergence to select parents for a
successful hybridization and breeding program is a smart idea (Vivekananda
and Subramanian, 1993). According to Kwon et al. (2002), identifying
parents based on divergence study is more beneficial for any breeding
program. The measurement of genetic diversity across and within groups or
clusters is critical for the right selection of parents in the rice breeding
program (Murty and Arunachalam, 1966). According to Singh and
Chaudhary (1977), the identification of traits responsible for genetic variation among populations can help in the selection of varied parents for
hybridization programs. Cluster analysis with Euclidean distance is a valuable statistical approach for determining the genetic diversity of germplasm
collections in terms of the traits taken collectively. Many researchers had
successfully used agro-morphological characters to classify and estimate
diversity in a variety of rice using multivariate analyses (Nachimuthu et al.,
2014; Ravikumar et al., 2015). The objectives of this study were to determine the degree of diversity and to identify potential genotypes for rice
hybridization based on morphological traits.
2. Materials and methods
2.1. Plant materials
Forty rice genotypes were selected and used in this study. The source
of genotypes was National Plant Breeding and Genetics Research Centre
(NPBGRC), Khumaltar, Lalitpur, Nepal.
* Corresponding author.
E-mail address: jibshrestha@gmail.com (J. Shrestha).
https://doi.org/10.1016/j.heliyon.2021.e07940
Received 15 June 2021; Received in revised form 30 August 2021; Accepted 2 September 2021
2405-8440/© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
J. Shrestha et al.
Heliyon 7 (2021) e07940
Table 1. Meteorological data of the experimental location in 2018.
Months
Maximum Temperature
(oC)
Minimum Temperature
(oC)
Rainfall
(mm)
July
28.1
20.8
387.3
August
27.7
20.5
322.0
September
28.4
19.2
53.2
October
25.9
11.8
0
November
22.8
6.9
0
December
18.5
3.6
Table 3. Mean values of various growth and yield traits of 40 rice genotypes at
Khumaltar, Lalitpur in 2018.
0.9
(Source: NARC, 2019)
Table 2. Meteorological data of the experimental location in 2019.
Months
Maximum Temperature
(oC)
Minimum Temperature
(oC)
Rainfall
(mm)
July
27.9
20.6
446.1
August
29.2
20.9
172.8
Genotypes
Plant height
(cm)
Panicle length
(cm)
No. of tillers/
plant
Grain yield
(t/ha)
08FAN10
96.00
23.50
14.00
5.25
Aanga
94.00
20.50
15.00
4.48
Bange masino
172.50
22.25
10.00
4.40
Basmati-370
110.50
25.50
11.00
3.40
Hansa raj
166.50
22.00
14.00
4.05
3.72
Himali
120.00
21.00
13.00
Indrabeli
166.00
26.50
13.00
3.35
IR 87751-20-4-42
100.00
25.70
10.00
5.27
IR 87759-1-2-2-11
101.00
26.20
11.00
5.10
IR 88968-2-1-1-2
97.50
26.90
12.00
4.93
IR67017
91.00
26.50
11.00
4.68
IR70422-95-1-1
97.50
21.00
12.00
3.10
84.50
22.70
14.00
2.80
September
27.0
19.5
239.9
IR73008-136-22-3
October
26.0
14.4
3.0
IR74052-95-3-2
85.00
25.00
16.00
3.54
November
24.1
10.1
0
92.00
26.50
13.00
3.59
December
18.2
3.5
29.2
IR77512-128-21-2
(Source: NARC, 2020)
2.2. Experimental site
These experiments were carried out in the research field of National
Plant Breeding and Genetics Research Centre, Khumaltar, Laltipur,
Nepal. It is located at 27 400 000 N latitude, 85 200 000 E longitude, and
altitude of 1350 m above sea level (NARC, 2018). The soil of the research
plot is clayey loam.
2.3. Climatic data
The climatic data during the experimental periods (2018 and 2019)
are given in Table 1 and Table 2.
2.4. Experimental design and cultural practices
Forty rice genotypes were planted in the first week of July 2018 and
2019. The rice genotypes were evaluated in Alpha lattice design with two
replications. Rice was planted at a spacing of 20 cm 15 cm. The area of
the plot was 6 m2. The fertilizers at a rate of 100:40:40 N:P:K [(nitrogen
(N), phosphorus (P) and potassium (K)]/ha was applied via Urea, Diammonium Phosphate DAP, and Muriate of Potash (MOP). kg/ha. As a
base dose, the full dosages of P2O5 and K2O, as well as half of the dose of
N, were utilized, and the remaining 50% nitrogenous fertilizer was
divided into two halves. The first was applied during the tillering stage,
and the second was during the booting step. Other cultural practices were
carried out according to guidelines provided by the National Rice
Research Program, Hardinath, Dhanusha, Nepal.
IR77512-2-1-2-2
102.50
26.70
13.00
4.34
IR775-39-80-2-22
93.50
22.00
14.00
4.82
Lalka basmati
107.00
26.50
14.00
3.57
NR 10676-B-1-33-3
128.50
25.00
16.00
5.55
NR 11130-B-B-B3-3
145.00
26.50
10.00
5.00
NR 11133-B-B-B23-2
139.00
26.50
9.00
4.81
NR 11142-B-B-B9
145.00
27.75
7.00
4.82
NR 11156-B-B-10
137.50
23.30
9.00
4.40
NR 11178-B-B-61
164.50
26.20
9.00
5.39
NR 11182-B-12
132.00
26.50
15.00
5.30
NR 11182-B-21
96.50
21.00
9.00
4.19
NR 11196-B-3-3
167.50
30.80
8.00
4.94
NR 11281-B-B-11
143.00
26.90
9.00
5.08
NR 11367-B-B-10
151.50
25.40
9.00
4.47
NR 11368-B-B-17
168.50
26.75
8.00
4.48
NR 11374-B-B-11
123.50
21.30
14.00
4.71
NR 11410-B-B-9
149.00
26.70
7.00
5.39
NR10410-89-3-21-1
129.00
26.50
15.00
5.54
Pokhreli Basmati
151.50
26.50
13.00
4.20
Pokhreli
Jethobudho
172.45
24.25
9.00
3.56
Pokhreli Masino
180.00
23.20
9.00
3.56
Sali dhan
125.00
27.20
8.00
3.10
Sugandha-2
110.00
23.50
11.00
2.89
Sugandha-3
97.50
24.00
12.00
4.96
2.5. Data recording and analysis
Sunaulo
Sughandha
102.50
22.50
16.00
2.30
Plant height, panicle length, number of tillers/plant, and grain yield
were recorded. The grain yield was calculated using the formula adopted
by Poudel (1995) and Shrestha et al. (2020a) (Eq. 1).
GM
125.90
24.88
12.00
4.33
SEM
6.51
1.93
0.96
0.28
P value
<.001
<0.001
<.001
<.001
kg
ð100MÞPlotyield ðkgÞ10000m2
Grainyield
at12%moisture¼
ha
ð10012ÞNetplotarea; m2
(1)
CV(%)
5.17
7.75
8.28
6.40
LSD (0.05)
13.21
3.91
1.94
0.56
GM: Grand mean, SEM: Standard error of mean, CV: Coefficient of variation, LSD:
Least significant difference.
Where, M is the grain moisture content in percentage.
2
J. Shrestha et al.
Heliyon 7 (2021) e07940
Table 4. Mean values of various growth and yield traits of 40 rice genotypes at
Khumaltar, Lalitpur in 2019.
Table 5. Combined mean values over years (2018 and 2019) of various growth
and yield traits of 40 rice genotypes at Khumaltar, Lalitpur.
Genotypes
Plant height
(cm)
Panicle length
(cm)
No. of tillers/
plant
Grain yield
(t/ha)
Genotypes
Plant height
(cm)
Panicle length
(cm)
No. of tillers/
plant
Grain yield
(t/ha)
08FAN10
93
26.5
12.00
5.25
08FAN10
94.5
25
13.00
5.25
Aanga
92.5
24
11.00
4.4
Aanga
93.25
22.25
13.00
4.44
Bange masino
174.5
24.5
7.00
4.8
Bange masino
173.5
23.38
9.00
4.6
Basmati-370
124
32.5
9.00
3.8
Basmati-370
117.25
29
10.00
3.6
Hansa raj
167.5
23.5
10.00
4.1
Hansa raj
167
22.75
12.00
4.08
Himali
118
24.5
9.00
3.72
Himali
119
22.75
11.00
3.72
Indrabeli
170.5
26
12.00
3.35
Indrabeli
168.25
26.25
12.00
3.35
IR 87751-20-4-42
108
28
9.00
5.27
IR 87751-20-4-42
104
26.85
10.00
5.27
IR 87759-1-2-2-11
104.5
31.5
10.00
5.42
IR 87759-1-2-2-11
102.75
28.6
10.00
5.26
IR 88968-2-1-1-2
107.5
26.5
11.00
4.93
IR 88968-2-1-1-2
102.5
26.7
12.00
4.93
IR67017
95.5
26.5
10.00
4.68
IR67017
93.25
26.5
10.00
4.68
IR70422-95-1-1
96.5
24.5
11.00
3.45
IR70422-95-1-1
97
22.75
11.00
3.28
IR73008-136-22-3
88.5
23
8.00
2.8
IR73008-136-22-3
86.5
22.85
11.00
2.8
IR74052-95-3-2
89.7
25
9.00
3.04
IR74052-95-3-2
87.35
25
12.00
3.29
IR77512-128-21-2
102.5
25.5
11.00
3.59
IR77512-128-21-2
97.25
26
12.00
3.59
IR77512-2-1-2-2
108.5
24
15.00
4.34
IR77512-2-1-2-2
105.5
25.6
14.00
4.34
IR775-39-80-2-22
97.5
26
13.00
4.82
IR775-39-80-2-22
95.5
24
13.00
4.82
Lalka basmati
107
25.5
14.00
3.57
Lalka basmati
107
26
14.00
3.57
NR 10676-B-1-33-3
133
26.5
13.00
5.76
NR 10676-B-1-33-3
130.75
25.75
15.00
5.65
NR 11130-B-B-B3-3
148
25.5
8.00
5.05
NR 11130-B-B-B3-3
146.5
26
9.00
5.02
NR 11133-B-B-B23-2
141.5
30.5
11.00
4.81
NR 11133-B-B-B23-2
140.25
28.5
10.00
4.81
NR 11142-B-B-B9
151.5
29
11.00
4.8
NR 11142-B-B-B9
148.25
28.38
9.00
4.81
NR 11156-B-B-10
144
24.5
7.00
4.65
NR 11156-B-B-10
140.75
23.9
8.00
4.53
NR 11178-B-B-61
164.5
30.5
7.00
5.11
NR 11178-B-B-61
164.5
28.35
8.00
5.25
NR 11182-B-12
134
25.5
13.00
5.42
NR 11182-B-12
133
26
14.00
5.36
NR 11182-B-21
102
21
7.00
4.19
NR 11182-B-21
99.25
21
8.00
4.19
NR 11196-B-3-3
166.5
31
6.00
5.43
NR 11196-B-3-3
167
30.9
7.00
5.18
NR 11281-B-B-11
147
27
7.00
4.78
NR 11281-B-B-11
145
26.95
8.00
4.93
NR 11367-B-B-10
155
29.5
6.00
4.47
NR 11367-B-B-10
153.25
27.45
7.00
4.47
NR 11368-B-B-17
170
28.5
6.00
4.48
NR 11368-B-B-17
169.25
27.63
7.00
4.48
NR 11374-B-B-11
127
24
11.00
4.71
NR 11374-B-B-11
125.25
22.65
12.00
4.71
NR 11410-B-B-9
147.5
25.5
5.00
4.97
NR 11410-B-B-9
148.25
26.1
6.00
5.18
NR10410-89-3-21-1
136
25.5
13.00
5.54
NR10410-89-3-21-1
132.5
26
14.00
5.54
Pokhreli Basmati
160
25.5
11.00
4.2
Pokhreli Basmati
155.75
26
12.00
4.2
Pokhreli
Jethobudho
180.5
26.5
6.00
3.56
Pokhreli
Jethobudho
176.5
25.38
8.00
3.56
Pokhreli Masino
173.5
28
7.00
3.56
Pokhreli Masino
176.75
25.6
8.00
3.56
Sali dhan
133.5
25
5.00
3.6
Sali dhan
129.25
26.1
7.00
3.35
Sugandha-2
112.2
26
9.00
2.46
Sugandha-2
111.1
24.75
10.00
2.67
Sugandha-3
105.5
25
9.00
4.96
Sugandha-3
101.5
24.5
11.00
4.96
Sunaulo
Sughandha
103
26
14.00
2.6
Sunaulo
Sughandha
102.75
24.25
15.00
2.45
Grand mean
129.54
26.34
10.00
4.36
Grand mean
127.72
25.61
11.00
4.34
SEM
7.37
2.46
1.88
0.4
SEM
4.47
1.68
2.01
0.27
P value
<.001
0.01
<.001
<.001
P value
<.001
<.001
<0.001
<.001
CV%
5.69
9.35
19.56
9.21
CV%
4.95
9.29
18.96
8.73
LSD (0.05)
14.97
5
3.86
0.82
LSD (0.05)
8.86
3.33
2.82
0.53
GM: Grand mean, SEM: Standard error of mean, CV: Coefficient of variation, LSD:
Least significant difference.
GM: Grand mean, SEM: Standard error of mean, CV: Coefficient of variation, LSD:
Least significant difference.
3
J. Shrestha et al.
Heliyon 7 (2021) e07940
Table 6. Grouping of 40 rice genotypes by Euclidean Method.
Cluster1
Cluster 2
Cluster3
Cluster4
Cluster5
Cluster6
IR 87751-20-4-4-2,
Bange masino,
Basmati-370,
IR73008-136-2-2-3,
NR 10676-B-1-3-3-3,
NR 11130-B-B-B-3-3,
Cluster7
NR 11367-B-B-10,
IR 87759-1-2-2-1-1,
Hansa raj,
Himali,
IR74052-95-3-2
NR 11182-B-12,
NR 11133-B-B-B-23-2,
Pokhreli Basmati
IR 88968-2-1-1-2,
Indrabeli,
NR 11374-B-B-11,
NR10410-89-3-2-1-1,
NR 11142-B-B-B-9,
IR67017,
NR 11178-B-B-6-1,
Sugandha-2
Sali dhan
NR 11156-B-B-10,
IR70422-95-1-1,
NR 11368-B-B-17,
NR 11281-B-B-11,
IR77512-128-2-1-2,
Pokhreli Jethobudho,
NR 11410-B-B-9
IR77512-2-1-2-2,
Pokhreli Masino
IR775-39-80-2-2-2,
Lalka basmati,
NR 11182-B-21,
NR 11196-B-3-3,
Sugandha-3,
Sunaulo Sughandha
ruled by the genotypes' genetic make-up, which is based on the number
of internodes and length of internodes (Rahman et al., 2018).
The number of tillers per plant varied from NR 11410-B-B-9 (6) to
Sunaulo sugandha (15) (Table 5). The diversity in the genetic makeup of
the variety is the cause of the variability in the number of effective tillers
per plant. Ramasamy et al. (1987) reported a similar result, stating that
varietal variation affected the quantity of tillers. Rice grain yield is
heavily influenced by tillering ability. Too few tillers result in fewer
panicles, whereas too many tillers result in high tiller mortality, undersized panicles, poor grain filling, and reduced grain yield (Peng et al.,
1994). Productive tillers are one of the most important yield components,
as the final yield is mostly determined by the number of panicles bearing
tillers per unit area (Roy et al., 2014).
The panicle length ranged from NR 11182-B-21 (21 cm) to NR 11196B-3-3 (30.9 cm) (Table 5). At various trials of rice evaluation in Khumaltar, Lalitpur, Nepal, there was a fluctuation in the number of viable
grains per panicle (NPBGRC, 2020). One of the most critical yields
determining features is the number of viable grains per panicle. Gravois
and McNew (1993) found that full viable grains per panicle had a
beneficial direct effect on rice yield. Grain yield ranged from 2.45 t/ha
(Sunaulo Sugandha) to 5.65 t/ha (NR10676-B-3-3-3) (Table 5). Rice
Data collected on various growths, yield, and yield components were
processed by using Excel 2010 and subjected to Analysis of Variance
(ANOVA) by using Genstat 13.2. The treatment means were compared by
the Least Significant Difference (LSD) test at 5% level (Gomez and
Gomez, 1984). The collected data were subjected to multivariable analysis was done using the statistical software packages of Minitab ver.14
(Mohammadi and Prasanna, 2003). The data was submitted to Average
Linkage cluster analysis based on mean Euclidean distances and similarity index (Sneath and Sokal, 1973).
3. Results and discussion
All evaluated rice genotypes were found highly significant (p < 0.01)
for plant height, panicle length, number of tillers/plant, and grain yield
(Table 3, Table 4, and Table 5). The plant height varied from IR73008136-2-2-3 (86.50 cm) to Bange masino (173.5 cm) (Table 5). Rasheed
et al. (2002) found similar results for plant height variation in rice genotypes. Plant height is an important growth parameter for any crop
since it defines or alters yield contributing traits, which in turn gives
grain production (Reddy and Redd, 1997). It is a complicated trait that is
the result of various genetically controlled elements, most of which are
Dendrogram
Average Linkage, Euclidean Distance
Similarity
45.12
63.41
81.71
100.00
j i
i
i
i
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S 76 1 0 1 3
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1 75 5 8 9 S 75 a o 0 8 74 a i h
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0 12 14 11 -B 1 1 1 3 h r
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6 R 41 1
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1 3 1 11 R 1 33 1 1 o k
0
R
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NR 8 8 7 IR
N
0
77
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P
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7
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R
R R
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R N NR
IR IR
IR
IR
R
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N
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N
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N
R
N
N
Genotypes
Figure 1. Dendrogram of 40 rice genotypes using Euclidean Method.
4
J. Shrestha et al.
Heliyon 7 (2021) e07940
Table 7. Cluster mean for four characters of 40 rice genotypes.
Variable
Cluster1
Cluster2
Cluster3
Cluster4
Cluster5
Cluster6
Cluster7
Grand centroid
Plant height
99.71
170.34
118.15
86.92
131.37
144.83
154.5
127.71
Panicle length
25
26.27
24.78
23.92
25.96
26.63
26.72
25.6
No. of tillers/plant
12.00
9.00
11.00
12.00
12.00
8.00
10.00
11.00
Grain yield
4.35
4.97
3.67
3.04
4.87
4.25
4.33
4.34
Masino) and cluster 4 (IR73008-136-2-2-3, IR74052-95-3-2) (83.51)
indicating genetic dissimilarity (Table 9). Anandan et al. (2011) and Latif
et al. (2011) both found similar results in rice. Yadav et al. (2011),
Vennila et al. (2011), and Latif et al. (2011) proposed using distantly
placed cluster genotypes in hybridization programs to get a wide spectrum of variation among genotypes (2011).
Table 8. Different statistics of Euclidean distance and cluster analysis of 40 rice
genotypes.
Cluster
No. of
genotypes
Within cluster
sum of squares
Average distance
from centroid
Maximum distance
from centroid
Cluster1
14
390.3
5.04
7.66
Cluster2
8
236.37
5.27
6.57
Cluster3
4
133.67
5.34
7.63
Cluster4
2
3.56
1.33
1.33
Cluster5
4
53.66
3.24
6.16
Cluster6
6
89.06
3.48
5.18
Cluster7
2
15.02
2.74
2.74
4. Conclusion
The cluster analysis showed the presence of genetic diversity in the
evaluated genotypes. The highest distance between cluster centroids was
found in cluster 2 and cluster 4 indicating genetic dissimilarity. Crosses
between parents belonging to the most diverse clusters would be expected to show the maximum heterosis. Rice genotypes NR 10676-B-1-33-3 was found the highest yielder followed by NR10410-89-3-2-1-1 and
NR 11182-B-12. These genotypes are promising rice genotypes and grain
production can be maximized by growing these genotypes.
genotypes NR 10676-B-1-3-3-3 (5.65 t/ha) produced the highest yield,
followed by NR10410-89-3-2-1-1 (5.54 t/ha) (Table 3). There was also a
lot of variation in grain production across the twelve coarse rice genotypes (Zahid et al., 2005). Significant diversity in agro-morphological
traits was reported in rice genotypes by Worede et al. (2014), Shrestha
et al. (2020b), and Shrestha et al. (2021).
The 40 rice genotypes were grouped in 7 clusters based on growth
and yield traits (Table 6, Figure 1). Fifty-eight rice varieties grouped into
four clusters based on 18 morphological characters in a study by
Ahmadikhah et al. (2008). Rahman et al. (2011) also divided 21 rice
varieties into five clusters based on 14 physiological traits. Similar results
were also reported by Yadav et al. (2011) and Anandan et al. (2011) in
rice.
Genotypes of cluster 2 had the highest plant height (170.34 cm) and
the highest grain yield (4.97 t/ha) whereas genotypes of cluster 4 had the
lowest plant height (86.92 cm) and the lowest grain yield (3.04 t/ha)
(Table 7). Similar results were obtained by Chakma et al. (2012).
The maximum distance of cluster 1 from centroids was 7.66 and the
minimum distance of cluster 4 (1.33) (Table 8). Caldo et al. (1996a) used
33 qualitative and quantitative parameters to estimate a range of
Euclidean distance ranging from 2.23 to 16.71 with a mean of 7.55 for 78
improved rice genotypes. Caldo et al. (1996b) used 41 attributes to
generate Euclidean distance estimates ranging from 3.97-17.38 with a
mean of 8.80 in a separate investigation of 81 ancestral lines of
Philippines current rice genotypes. Chakma et al. (2012) discovered
similar results.
Distance between cluster centroids ranged from 9.78 to 83.49
(Table 9). The lowest distance between cluster centroids was found in the
cluster 6 and cluster 7 (9.78) indicating genetic similarity and the highest
was found in the cluster 2 (Bange Masino, Hansa raj, Indrabeli, NR
11178-B-B-6-1, NR 11368-B-B-17, Pokhreli Jethobudho, Pokhreli
Declarations
Author contribution statement
Jiban Shrestha; Sudeep Subedi; Ujjawal Kumar Singh Kushwaha;
Bidhya Maharjan: Conceived and designed the experiments; Performed
the experiments; Analyzed and interpreted the data; Wrote the paper.
Funding statement
This work was supported by National Plant Breeding and Genetics
Research Centre, NARC, Khumaltar, Lalitpur, Nepal.
Data availability statement
Data will be made available on request.
Declaration of interests statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
Table 9. Distances between cluster centroids in 40 rice genotypes.
Cluster1
Cluster1
Cluster2
Cluster2
Cluster3
Cluster4
Cluster5
Cluster6
Cluster7
70.7
18.49
12.9
31.68
45.3
54.86
52.24
Cluster3
Cluster4
83.51
39.13
25.52
15.86
31.26
13.45
26.88
36.42
44.54
Cluster5
58.11
67.68
14.11
23.31
Cluster6
9.78
Cluster7
-
5
J. Shrestha et al.
Heliyon 7 (2021) e07940
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