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Asian Journal of Applied Sciences

Year: 2020 | Volume: 13 | Issue: 2 | Page No.: 84-93
DOI: 10.3923/ajaps.2020.84.93
Evaluation of Mutant Silkworm Genetic Resources for Important Morphological and Quantitative Characters
G. Lokesh , M. Maheswari, Ritwika Sur Chaudhuri, D.S. Somaprakash, S. Sekar and R.K. Mishra

Abstract: Background and Objective: Genetic diversity and variability in the population are pre-requisite for the crop improvement programme. Collection and maintenance of genetic diversity is a fundamental component in long-term management strategies for genetic improvement of silkworm. The silkworms mutant were evaluated for morphological characters and rearing traits during two crop seasons i.e., winter and summer to analyze the performance and to identify better mutant accessions. Materials and Methods: Total 23 mutant silkworm accessions were considered for the study, the important morphological characters during egg, larva and cocoon stages were recorded and compared with the catalogue data. Total 12 important silkworm quantitative traits were studied and analysed using multi trait analysis package to identify better accessions. Results: Significant amount of variations were observed among different accessions for different traits. Among 23 mutant silkworms 08 were qualified in the cumulative Evaluation Index (EI) (>50). The cluster analysis showed heterogeneity among the silkworm accessions based on the grouping. The Principal Component Analysis (PCA) indicated the grouping of 06 mutants along with commercially important silkworm races Multivoltine Pure Mysore (PM) and bivoltine (CSR-2). Conclusion: Since these genotypes were considered most suitable for basic genetic studies rather its usefulness in silk production. The correlation studies using PCA revealed that some of the mutant silkworms conserved in the germplasm showed on par with commercially important silkworm races and can be used to explore the combining ability studies for further commercial exploitation.

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How to cite this article
G. Lokesh, M. Maheswari, Ritwika Sur Chaudhuri, D.S. Somaprakash, S. Sekar and R.K. Mishra, 2020. Evaluation of Mutant Silkworm Genetic Resources for Important Morphological and Quantitative Characters. Asian Journal of Applied Sciences, 13: 84-93.

Keywords: evaluation, germplasm, genetic resources, Silkworm, mutant, Bombyx mori and genotypes

INTRODUCTION

Study about genetic diversity are an important tool that enables breeders to make good selection of parents to ensure genetic variability. Heterosis between genotypes is often enhanced when the two parents are genetically diverse1. The silkworm Bombyx mori. L is one of most important economic insect species which is exploited for the production of natural silk. The species has wide distribution found both in temperate as well as tropical regions with greater genetic diversity in morpho-biochemical and biometric characters2. It has been estimated that, more than 3000 silkworm strains are available worldwide which developed through breeding3,4. The temperate silkworm strains generally have Uni and bi-voltinism are quantitatively as well as qualitatively superior races compared to tropical polyvoltine silkworm races. On the other hand polyvoltines are better in terms of survival rate, hardiness and resistance to biotic and abiotic challenges5. The silkworms has been used as a model for genetic studies because of its large size, ease of rearing in laboratory and short life cycle. The existence of more than hundreds of geographical races and genetically improved strains used for commercial silk production which differ not only qualitative traits but also in quantitative traits such as body size, feeding duration, thermal tolerance and disease resistance. These traits remain to be subjected to systematic analysis using modern genetic tools6.

The principal aims of crop improvement is to develop silkworm breeds with superior multiple traits including improved silk productivity, adaptability, disease tolerance and other commercially important characters. Before any breeding tasks, it is imperative to understand the behavior, performance in different life stages and quality and quantity of the silk produced by the silkworm breed/race which is pre-requisite for the selection as parents. The domesticated mulberry silkworm, Bombyx mori L. represents itself as various mutants evolved both from spontaneous and induced mutation. These mutants are maintained by fanciers and breeders in the closed line culture system for many years and serve as a basic tool for genetic analyses including phylogenetic, physiological, ethological, biochemical and molecular studies since systematic linkage studies have been successfully carried out7. More than 400 mutations have been mapped corresponding to 230 genes with 28 linkage groups8-10. The mutant silkworm races shows different phenotypic characters, such as variation in egg color, larval duration, larval marking, cocoon shape, cocoon color and hemolymph colour. Morphological characterization has direct or indirect relation with various quantitative and qualitative traits11. These races also show wide diversity in the yield, economic parameters and exhibit considerable variations for several heritable characters viz., egg colour, larval markings, cocoon colour and cocoon shape. Further, morphological traits along with correlation parameters help to identify and group similar performing germplasm for effective conservation in the gene bank. As the mutant silkworm genetic stocks, it is possible to use directly in silkworm breeding for evolving new races12 and characterizations of morphological mutant traits were utilized as a basic tool for genetic analysis and were used to study the genetic diversity and distance among the population. In current research, the performance of mutant silkworm genetic resources conserved in the centre are evaluated for 11 rearing and grainage parameters and also compared with the popular commercially exploited bivoltine silkworm race to examine its potentialities for commercial cocoon production.

MATERIALS AND METHODS

Study area: The present study was conducted during 2018-2019 at Central Sericultural Germplasm Resources Centre (CSGRC), Hosur, Tamilnadu state, India.

Research procedure: Silkworm Bombyx mori mutant genetic resources which were collected and maintained at CSGRC, India are selected (Table 1) for the evaluation of important morphological characters, rearing parameters and grainage performance as per the standard descriptor (Table 2, 3). The rearing of 23 silkworm mutant accessions was conducted during June-July and December-January. Three replications of each mutant accession were maintained in a separate 2’×3’ Plastic perforated trays arranged on rearing stand. The rearing was conducted as per the Standard silkworm rearing procedure13 and Standard Operational Procedure for conservation of silkworm germplasm. G-2 mulberry variety for chawki rearing and V-1 mulberry variety leaves was used for rearing of late age silkworms. The morphological data was collected based on the physical observation and compared with passport data available at the centre. The data for 12 important rearing and grainage parameters was collected for 5 years (2 crops/year). Mutant silkworm data was compared with commercially important mutivoltine (PM) and bivoltine (CSR-2) silkworm breeds using PCA analysis for better understanding of the possibilities of mutant silkworms for commercial exploitation.

Statistical analysis: Mean data of 5 years for 23 mutants from 12 important quantitative characters were considered. The number of rearing conducted during the period was treated as replications.

Table 1: List of mutant silkworm germplasm maintained at CSGRC, Hosur, India
Acc. No.
National accession number
Name of the race
BBE-0306
NBAII-CSG---0000306
TMS-12
BBE-0307
NBAII-CSG---0000307
TMS-14
BBE-0308
NBAII-CSG---0000308
TMS-32
BBE-0309
NBAII-CSG---0000309
TMS-33
BBE-0310
NBAII-CSG---0000310
TMS-35
BBE-0311
NBAII-CSG---0000311
TMS-38
BBE-0312
NBAII-CSG---0000312
TMS-61
BBE-0313
NBAII-CSG---0000313
TMS-62
BBE-0314
NBAII-CSG---0000314
TMS-64
BBE-0315
NBAII-CSG---0000315
TMS-65
BBE-0316
NBAII-CSG---0000316
TMS-66
BBE-0317
NBAII-CSG---0000317
TMS-67
BBE-0318
NBAII-CSG---0000318
TMS-75
BBE-0319
NBAII-CSG---0000319
TMS-82
BBE-0320
NBAII-CSG---0000320
TMS-2
BBE-0321
NBAII-CSG---0000321
TMS-17
BBE-0322
NBAII-CSG---0000322
TMS-31
BBE-0323
NBAII-CSG---0000323
TMS-69
BBE-0331
NBAII-CSG---0000331
TMS-34
BBE-0333
NBAII-CSG---0000333
OD-Translucent
BBE-0390
NBAII-CSG---0000390
TMS-04
BBE-0391
NBAII-CSG---0000391
TMS-13
BBE-0392
NBAII-CSG---0000392
TMS-18
BBE: Bombyx mori bivoltine exotic, NBAII: National bureau of agriculturally important insect, CSG: Central sericultural germplasm, TMS: Mutant silkworm


Table 2: Parameters for the evaluation of mutant silkworm germplasm during rearing and grainage
Parameters
Fecundity (No.s)
Hatching (%)
Weight of grown larvae (g)
Total larval duration (h)
5th Instar larval duration (h)
Effective Rate of Rearing (ERR) by no.
ERR by wt. (kg)
Pupation rate (%)
Single cocoon weight (g)
Single shell weight (g)
Shell ratio (%)


Table 3: Descriptor for important morphological characters of mutant silkworm germplasm
Egg Cocoon Larva
Egg colour Cocoon colour Larval markings
Egg Shape Cocoon shape Body colour of 5th instar larva
Nature of constriction Nature of integument

Multivariate analysis was conducted to analyze the variability in the parameters among different accession. WINDOWSTAT statistical package was used for ANOVA to compare the performance of the accessions in two different seasons. PAST3 statistical software package was used for Principal Component Analysis (PCA) to compare the mutant accessions with commercially important silkworm races and to generate cluster grouping.

RESULTS AND DISCUSSION

The evaluation of morphological characters of the mutant silkworm genetic resources in the present study was recorded in egg, larva and cocoon stages and compared with the catalogue data (Table 4). The present observations are on par with the catalogue data which is maintained at the Silkworm Germplasm Information System (SGIS). Maintenance of original characters of the silkworm genotypes over the generations is one of the prime objectives of the silkworm germplasm.

Quantitative trait analysis: The data of 23 mutant accessions recorded for 5 years was analyzed for 12 important characters showed significant variations among different mutant genotypes which were evident from the calculation of Coefficient Variation (CV%). The higher variability was recorded with single shell weight, minimum value recorded 0.097 g in BBE-0318 and maximum recorded in BBE-0392 (0.217 g). In contrast, lower variations recorded in total larval duration 533.85 h in BBE-0309 and 566.4 h in BBE-0391 (Table 5). The multiple trait evaluation indices assessment of all the accessions by taking into consideration of all the parameters recorded in Table 5. High variability was observed in the parameters such as fecundity (10.158), larval weight (16.687), survivability /ERR by weight (11.76), cocoon weight (12.47), shell weight (23.49) and SR% (13.17) recorded significant variations among the mutant silkworm genotypes conserved in the germplasm (Table 6).

Table 4: Morphological characters of mutant silkworm genetic resources
Name of Egg Larva Cocoon
Acc. No. the race Colour Shape Marking Colour Integument Colour Shape Constriction
BBE-0306 TMS-12 White Ellipsoidal Marked Mixed Opaque White Elongated Faint
BBE-0307 TMS-14 Creamish white Ellipsoidal Plain Pale red Opaque Greenish white Elongated Faint
BBE-0308 TMS-32 White Ellipsoidal Plain White Opaque White Elongated Faint
BBE-0309 TMS-33 White Ellipsoidal Marked Dirty Opaque White Elongated Faint
BBE-0310 TMS-35 White Ellipsoidal Plain Light yellow Opaque White Elongated Nil
BBE-0311 TMS-38 Light yellow Oval Marked Brown Opaque Flesh Elongated Faint
BBE-0312 TMS-61 Brownish red Ellipsoidal Faint marked Light yellow Opaque White Elongated Faint
BBE-0313 TMS-62 White Oval Marked White Opaque Yellow Elongated Faint
BBE-0314 TMS-64 White Ellipsoidal Marked Yellow Translucent White Elongated Nil
BBE-0315 TMS-65 White Ellipsoidal Marked Brown yellow Translucent Chrome yellow Elongated Faint
BBE-0316 TMS-66 Creamish white Ellipsoidal Marked White Opaque Yellow Elongated deep
BBE-0317 TMS-67 Creamish white Ellipsoidal Plain Light yellow Opaque Flesh Elongated Nil
BBE-0318 TMS-75 White with red tint Ellipsoidal Plain White Semi-translucent White Elongated Faint
BBE-0319 TMS-82 Creamish white Ellipsoidal Plain White Opaque White Elongated Nil
BBE-0320 TMS-2 White Ellipsoidal Marked White Opaque White Elongated Faint
BBE-0321 TMS-17 White Ellipsoidal Plain Light yellow Opaque White Elongated Faint
BBE-0322 TMS-31 Creamish white Ellipsoidal Marked Light yellow Opaque Chrome yellow Elongated Deep
BBE-0323 TMS-69 White Ellipsoidal Marked Light yellow Opaque White Elongated Faint
BBE-0331 TMS-34 White Ellipsoidal Marked White Opaque White Elongated Faint
BBE-0333 OD-Translu White Ellipsoidal Marked White Translucent White Elongated Faint
BBE-0390 TMS-04 White Ellipsoidal Marked White Opaque White Elongated Faint
BBE-0391 TMS-13 White Ellipsoidal Marked White Opaque White Elongated Faint
BBE-0392 TMS-18 White Ellipsoidal Marked White Opaque White Elongated deep


Table 5: Performance of mutant silkworm accessions for 12 important quantitative characters in mean, range with CV (%)
Hatching
Larval
Yld/10000
Yld/10000
Pupa
Cocoon
Coco/100
Fecundity
(%)
weight (g)
Tld
Vld
(No.)
(Wt)
(%)
wt.
Shell wt.
SR (%)
dfl
BBE-0306
Average
402.150
94.379
26.462
542.850
124.550
9666.150
11.530
90.912
1.155
0.176
15.257
44.256
Min.-Max.
341-494
87-98.4
19.9-31.9
480-624
90-168
8767-9942
8.4-14.9
71.8-98
0.9-1.3
0.12-0.28
12.01-20.8
26.8-64
CV (%)
13.194
3.440
12.600
8.580
17.900
3.100
17.400
6.700
13.960
23.600
15.400
22.900
BBE-0307
Average
351.250
92.622
23.459
549.900
131.400
9727.600
11.370
94.038
1.146
0.161
14.082
42.320
Min.-Max.
261-439
80.8-98
16.9-28.6
486-624
90-168
9300-9929
9-15.4
91.05-96.9
0.95-1.37
0.12-0.23
11.8-17.4
33.3-61.65
CV (%)
14.150
4.010
13.800
8.200
18.400
1.900
14.800
1.800
12.300
18.130
9.440
14.600
BBE-0308
Average
315.925
93.018
21.001
540.350
122.150
9575.250
8.245
90.985
0.928
0.115
12.512
29.351
Min.-Max.
181-450
67.6-98.4
12.3-28.8
480-628
90-168
8233-9925
5.8-11.7
79.3-98.36
0.59-1.23
0.05-0.15
9.45-15.8
14.06-41.2
CV (%)
23.900
6.870
25.700
9.300
21.300
5.200
21.400
6.300
24.050
26.800
11.900
24.200
BBE-0309
Average
353.350
93.916
21.686
533.850
115.550
9531.900
8.815
92.272
0.942
0.122
13.049
32.759
Min.-Max.
262-438
81.7-97.2
16.5-25.8
456-624
88-168
7967-9960
7-11.01
76.3-98.04
0.69-1.23
0.08-0.15
11.1-14.4
24-43.8
CV (%)
12.150
4.120
13.800
9.500
21.140
5.500
11.060
5.800
16.600
17.300
7.600
15.200
BBE-0310
Average
267.900
88.706
20.416
553.150
130.550
9561.750
9.945
87.189
0.975
0.122
12.589
35.607
Min.-Max.
116-367
77.4-98
14.9-26.3
480-624
84-168
8867-9960
7.8-13
46.4-97.6
0.813-1.26
0.09-0.15
10.8-14.2
19.8-49.6
CV (%)
25.500
7.500
14.400
7.500
20.300
2.900
14.500
14.900
15.220
15.900
7.240
20.270
BBE-0311
Average
304.850
90.396
23.254
539.15
121.150
9623.250
9.955
92.480
0.993
0.121
12.281
36.498
Min.-Max.
196-460
71.5-97
17.2-31.2
480-624
84-168
9233-9968
7.2-13.3
85.4-97.4
0.76-1.22
0.08-0.15
10.50-14.7
13.5-55.94
CV (%)
25.300
8.650
17.800
8.600
19.800
2.400
15.100
4.200
14.330
17.160
9.880
25.900
BBE-0312
Average
354.450
90.496
17.001
537.200
120.650
9605.700
8.070
91.705
0.837
0.103
12.461
29.379
Min.-Max.
177-630
75-99
12.5-24.8
480-624
90-168
8767-9928
6-10.4
86-95.1
0.60-1.17
0.06-0.14
9.60-15.70
19.65-41.57
CV (%)
33.900
7.390
20.000
8.800
18.400
3.300
16.400
3.400
24.040
22.290
12.200
19.050
BBE-0313
Average
318.000
87.566
21.701
545.050
130.200
9631.900
9.930
92.101
1.007
0.117
11.664
37.258
Min.-Max.
163-449
68.3-65.6
16.7-26.2
486-624
90-168
9000-9957
8.2-13.1
75-98.8
0.82-1.16
0.09-0.14
9.5-13.2
28.52-51.4
CV (%)
25.500
10.400
12.800
7.700
18.400
2.600
14.800
5.800
11.070
14.550
8.300
17.610
BBE-0314
Average
353.364
93.990
20.238
550.136
133.227
9512.409
9.569
90.770
0.970
0.121
12.48
35.598
Min.-Max.
248-487
88.6-98
16.2-25.5
486-624
90-168
8267-9915
6.7-16.3
76.6-98
0.8-1.3
0.09-0.18
10.7-14.7
23.4-65.3
CV (%)
18.740
2.900
13.800
7.600
16.900
4.660
22.300
6.100
18.040
19.210
9.500
27.660
BBE-0315
Average
347.650
95.025
21.210
545.000
129.400
9583.900
9.915
90.418
0.947
0.113
11.905
38.344
Min.-Max.
247-452
88.3-98
14.3-26.2
486-624
90-168
8200-9936
6.3-17.2
78.6-96.3
0.78-1.17
0.08-0.18
10.05-17.4
25.3-68.80
CV (%)
16.480
3.000
16.100
7.600
18.300
3.900
29.500
4.900
14.300
21.770
13.600
31.820
BBE-0316
Average
291.650
88.249
18.548
552.200
132.100
9585.850
9.065
87.876
0.930
0.102
10.760
34.818
Min.-Max.
184-518
78.3-97
12.1-26.5
486-624
90-168
8933-9942
7.1-11
70.7-97.3
0.73-1.17
0.06-0.16
8.0-15.0
28.5-42.17
CV (%)
28.700
7.800
23.600
8.200
18.300
2.900
13.600
8.100
17.100
33.030
19.090
12.860
BBE-0317
Average
308.350
91.253
19.188
536.800
120.200
9557.650
7.938
90.242
0.881
0.111
12.586
28.933
Min.-Max.
201-428
78.6-99
15.2-36.3
486-600
90-168
8133-9964
4.8-10.5
79.3-96.7
0.66-1.21
0.08-0.22
10.12-18.5
13.15-38.5
CV (%)
22.900
7.200
23.160
6.300
20.000
4.100
18.300
5.120
19.770
32.400
16.290
22.250
BBE-0318
Average
296.650
92.094
16.653
538.600
124.400
9657.150
8.430
93.279
0.799
0.097
11.967
30.204
Min.-Max.
208-415
72.1-98
13.0-26.5
480-624
90-168
9233-9955
6.1-11
86.6-97.7
0.57-1.16
0.06-0.19
10.1-18.3
17.5-44.2
CV (%)
23.900
7.800
21.700
8.700
18.200
2.200
18.600
3.500
22.500
33.900
15.960
24.740
BBE-0319
Average
381.900
94.934
26.119
535.950
119.400
9660.500
9.725
92.661
1.058
0.137
13.015
36.791
Min.-Max.
330-493
90.9-98
18.3-32.3
480-624
90-168
9000-9999
7.5-11.7
84.8-99.5
0.88-1.18
0.1-0.16
10.8-15.6
27.3-46.7
CV (%)
10.940
2.200
13.600
8.800
20.500
2.650
11.200
4.300
8.700
13.330
11.500
16.660
BBE-0320
Average
343.600
95.201
26.347
535.750
119.200
9660.050
10.215
91.618
1.090
0.149
13.720
39.150
Min.-Max.
266-432
82.6-99
19.4-32.2
480-624
90-168
9133-9946
7.2-14.2
83.7-97
0.86-1.25
0.17-0.21
10.7-17.6
25.4-56.9
CV (%)
14.840
4.100
11.800
8.800
20.700
2.060
16.700
4.050
11.190
18.200
11.260
21.110
BBE-0321
Average
312.850
88.678
21.296
536.100
119.300
9624.750
9.800
90.656
0.961
0.124
13.025
36.278
Min.-Max.
217-414
56.6-99
16.2-25.8
480-624
84-168
9300-9900
7.2-16.1
80.3-98
0.71-1.19
0.07-0.15
10.2-19.1
24.3-64.3
CV (%)
15.250
15.900
15.320
8.900
20.900
1.800
25.800
4.500
16.600
20.860
15.590
30.800
BBE-0322
Average
315.150
88.492
19.201
547.600
130.750
9748.250
8.225
93.596
0.874
0.106
12.207
29.768
Min.-Max.
218-405
71.3-98
12.8-24.2
480-624
84-168
9300-9932
5.9-10.4
80.8-97
0.63-1.17
0.06-0.14
9.39-14.2
23.6-36.3
CV (%)
18.900
8.800
17.900
7.900
18.500
1.700
15.700
4.060
18.300
19.800
10.350
11.760
BBE-0323
Average
367.950
91.863
23.549
541.000
125.400
9672.650
10.570
91.640
1.031
0.136
17.983
39.154
Min.-Max.
230-474
77.2-98
17.3-26.8
480-624
84-168
9200-9967
8.8-12.4
72.7-98
0.51-1.28
0.08-0.19
10.48-13.9
29.8-48
CV (%)
17.610
5.500
10.300
8.900
17.900
2.150
11.600
5.900
18.100
20.670
12.900
11.630
BBE-0331
Average
276.200
87.113
20.165
545.750
129.550
9551.550
8.370
89.537
0.910
0.112
12.425
30.465
Min.-Max.
151-445
61.4-96
12.2-23.8
480-624
84-168
8533-9965
7-10.7
60-97
0.74-1.19
0.08-0.15
10.01-14.1
19.65-42.7
CV (%)
27.870
11.800
14.300
7.800
19.000
3.800
10.700
11.200
14.700
15.900
8.750
17.180
BBE-0333
Average
363.150
94.671
24.559
543.500
122.100
9696.950
9.770
94.151
1.047
0.141
13.600
34.952
Min.-Max.
128-530
88.8-99
19.2-28.5
480-624
84-168
9400-9967
7.6-12.3
88.5-98
0.88-1.17
0.10-0.18
8.8-17.8
11.3-49.1
CV (%)
28.630
3.260
12.600
8.100
19.400
2.050
11.600
3.200
10.050
18.730
18.280
25.130
BBE-0390
Average
348.667
96.348
24.795
536.000
144.000
8914.167
7.950
87.667
1.202
0.178
14.857
27.224
Min.-Max.
300-435
94-98
20.6-31.9
504-576
120-168
8367-9233
5.1-9.8
83.6-92
1.17-1.22
0.15-0.22
12.7-19.2
16.2-30.8
CV (%)
13.260
1.500
22.118
6.100
14.900
3.500
21.200
3.900
1.370
18.000
19.150
20.670
BBE-0391
Average
356.900
92.924
28.915
566.400
147.600
9367.100
10.405
92.120
1.167
0.189
16.326
34.434
Min.-Max.
306-397
89-95
23-35
504-624
120-168
8933-9935
9.4-12.1
85-98
0.95-1.26
0.15-0.22
12.4-17.9
29.8-38.5
CV (%)
7.815
2.700
16.100
9.100
13.300
3.800
8.200
4.8
10.300
14.900
13.340
8.150
BBE-0392
Average
341.300
94.148
31.995
542.400
143.900
9354.100
11.350
91.670
1.307
0.217
16.612
35.639
Min.-Max.
315-374
85.3-97.8
24.5-39.35
504-624
108-168
8633-9933
9.4-12.8
83-98
1.2-1.46
0.15-0.26
13.12
30.5-41
CV (%)
4.53
3.9
15.4
8.6
16.2
4.5
11.01
5.2
7.4
15.77
18.426
12.12


Table 6: Parameter-wise variability analysis in mean values of 23 mutant silkworm accessions
Parameters
Average
Minimum
Maximum
SD
SE
CV (%)
Fecundity
0333.618
0267.900
0402.150
033.889
07.225
10.158
Hatching (%)
0092.004
0087.113
0096.348
002.792
00.595
3.034
Larval Wt_10
0022.511
0016.653
0031.995
003.757
00.801
16.687
Larval duration total
0543.247
0533.850
0566.400
007.597
01.620
1.398
Larval duration 5th Instar
0127.684
0115.550
0147.600
008.566
01.826
6.709
Yield/ No.)
9568.284
8914.167
9748.250
172.017
36.674
1.798
Yld/10000(Wt)
0009.529
0007.938
0011.530
001.121
00.239
11.765
Pupa %
0091.286
0087.189
0094.151
001.890
00.403
2.071
Cocoon
0001.007
0000.799
0001.307
000.126
00.027
12.47
Shell
0000.133
0000.097
0000.217
000.031
00.007
23.49
SR %
0013.364
0010.760
0017.983
001.760
00.375
13.172
Cocoon/100dfl
0034.747
0027.224
0044.256
004.441
00.947
12.781
SR: Shell ratio, CV: Cumulative variance


Table 7: Top performing mutant silkworm accessions with cumulative evaluation index value (>50)
Fec
Hat
Wt_10
ERR
ERR
Pupa
Cocoon
Shell
SR
Cocoon
No. of
Acc. No.
(No.)
(%)
larvae
(No.)
(Wt)
(%)
wt. (g)
wt. (g)
(%)
yield/100 dfl
CEI
qualified traits
Rank
BBE-0306
70.22
58.51
60.52
55.69
67.85
48.02
61.79
63.57
60.75
71.41
61.83
9.00
I
BBE-0392
52.27
57.68
75.25
37.55
66.25
52.03
73.94
76.63
68.46
52.01
61.21
9.00
II
BBE-0307
55.20
52.22
52.52
59.26
66.43
64.56
61.07
58.69
54.08
67.05
59.11
10.00
III
BBE-0391
56.87
53.30
67.05
38.30
57.82
54.41
62.79
67.80
66.83
49.30
57.45
8.00
IV
BBE-0323
60.13
49.49
52.76
56.07
59.29
51.87
51.89
50.83
76.24
59.92
56.85
9.00
V
BBE-0320
52.95
61.45
60.21
55.33
56.12
51.76
56.63
55.03
52.02
59.91
56.14
10.00
VI
BBE-0319
64.25
60.50
59.60
55.36
51.75
57.27
54.08
51.01
48.02
54.60
55.64
9.00
VII
BBE-0333
58.71
59.55
55.45
57.48
52.15
65.15
53.18
52.24
51.35
50.46
55.57
10.00
VIII
SR: Shell ratio

Multiple trait evaluation method is being utilized for testing large number of silkworm germplasm and based on the performance for important economic characters and promising genotypes are selected14-18. In the present study also the 23 mutant accessions were evaluated based on the multiple trait evaluation to understand the better performing accessions. More than 21 traits contribute to silk yield and there exists an inter-relationship between multiple traits in silkworm19. The precision of selection of breeds among many numbers of breeds can achieved through the evaluation index method that gives priority to all yield component traits20. Based on the performance of the silkworm genotypes, individual indices were calculated for each of the 10 parameters. Since in larval duration the desirability is lower values, hence this character was not considered for calculation of Evaluation Index (EI). The EI values were calculated for each of the genotype in all the 10 parameters and ranking was assigned based on the qualifying average EI-value>50. It was found that eight accessions such as BBE-0306 (EI = 61.83), BBE-0392, 0307, 0391, 0323, 0320, 0319 and 0333 (EI = 55.57) qualified the EI value >50 with 9-10 qualifying parameters in each accessions. Remaining accessions were also performed better but not qualified the bench mark of EI>50. In the recent past evaluation index method developed by Mano et al.21 has been utilized for short listing better performing silkworm genotypes/hybrids for commercial exploitation18,22 and the same has been utilized in the present study as well for evaluating 23 mutant silkworm Bombyx mori L. genotypes in respect of different traits viz., fecundity, hatching, larval weight, ERR by no. and ERR by Wt., Pupation, cocoon weight, shell weight, shell ratio, cocoon yield by number and by weight. The ranking was assigned to those genotypes which qualifies with Cumulative EI>50 (Table 7). Similar works also reported earlier wherein the identification of top performing silkworm breeds in different seasons was achieved23. Evaluation index is one such method that increases the precision of selection of breed among an array of breeds by a common index giving due to weight-age to all the yield component traits20.

Since, the rearing of mutant silkworms were conducted in two different seasons. The comparative analysis of the performance of these silkworms was made by ANOVA, which revealed significant difference between the seasons, between the accessions and between the accessions and the seasons. Highly significant values were recorded in the important commercial characters of the silkworm such as fecundity (p<0.01), survivability (p<0.01), cocoon weight (p<0.01), shell weight (p<0.05) and total cocoon yield (p<0.01). However, there was no significant difference in values were also recorded with larval duration, larval hatching and in shell ratio during the two seasons. However, the analysis of data indicates that all the genotypes utilized in the study vary significantly with respect to most of the parameters studied during winter and summer seasons (p<0.001, Confidence Distribution (CD) value 40.73).

Table 8: Mean performance of silkworm mutant accessions during winter season (December-January)
Wt_10
Yld/10000
Yld/10000
Pupa
Cocoon wt.
Shell wt.
Coco/100
Acc. No.
Fec (No.)
Hat (%)
larvae
Tld (h)
Vld (h)
(No.)
(Wt)
(%)
(g)
(g)
SR (%)
dfl
BBE-0306
406.2
94.64
25.922
575
130
9698
10.91
91.65
1.080
0.168
15.519
43.73
BBE-0307
357
93.34
23.834
584
139
9693
11.11
93.51
1.113
0.160
14.358
41.24
BBE-0308
300.9
91.13
19.483
577
132
9767
7.78
93.47
0.863
0.114
13.300
26.77
BBE-0309
354.5
93.50
20.272
570
124
9734
8.57
94.95
0.905
0.120
13.337
32.15
BBE-0310
262.6
88.54
19.666
581
136
9544
9.49
90.05
0.963
0.124
12.927
34.69
BBE-0311
306.7
92.17
22.012
573
128
9586
9.34
92.31
0.939
0.121
12.918
35.79
BBE-0312
402.6
90.74
16.771
573
128
9660
7.41
92.16
0.764
0.098
12.946
27.89
BBE-0313
323.2
87.10
21.133
577
135
9649
9.73
91.50
0.955
0.113
11.976
37.19
BBE-0314
350.9
93.41
19.830
580
137
9619
8.90
92.46
0.963
0.129
13.224
33.03
BBE-0315
347.9
94.63
20.072
576
136
9649
8.45
91.03
0.903
0.111
12.233
32.58
BBE-0316
329.5
89.78
17.910
586
134
9608
8.71
87.58
0.890
0.093
10.212
34.57
BBE-0317
338.5
91.62
17.678
562
122
9643
7.83
90.99
0.853
0.119
13.747
28.37
BBE-0318
300.9
93.28
16.916
572
128
9656
7.28
93.60
0.783
0.094
12.051
25.91
BBE-0319
385.1
95.45
25.554
571
126
9684
9.32
92.39
1.074
0.141
13.291
35.62
BBE-0320
368.7
96.37
24.931
571
126
9707
9.50
91.80
1.049
0.144
13.749
37.59
BBE-0321
304.8
89.95
20.665
572
127
9627
8.35
89.59
0.958
0.132
14.087
30.43
BBE-0322
311.8
87.56
19.370
582
137
9794
8.15
94.15
0.843
0.108
12.879
29.35
BBE-0323
407.9
92.59
22.685
578
134
9734
10.36
92.76
0.999
0.131
13.228
39.90
BBE-0331
295.7
91.10
19.517
577
136
9645
8.15
93.35
0.900
0.116
12.942
29.88
BBE-0333
408.2
94.56
24.019
572
132
9718
9.51
94.69
1.035
0.145
14.236
35.96
BBE-0390
396.5
95.20
31.846
576
144
8863
7.60
86.50
1.215
0.158
12.960
30.7
BBE-0391
367
92.81
30.325
588
156
9605
10.00
93.84
1.089
0.193
17.726
33.94
BBE-0392
351.7
92.92
32.600
588
156
9791
10.75
95.40
1.263
0.220
17.393
35.01
Mean
346.9
92.28
22.305
577
134
9638
9.01
92.16
0.974
0.133
13.532
33.58
Range
262.6-408.2
87.10-96.37
16.771-32.600
562-588
122- 156
8862- 9794
7.28-11.11
86.50-95.40
0.764-1.263
0.093-0.220
10.212-17.726
25.92-43.73
SD
41.891
2.501
4.515
6.363
8.763
180.772
1.134
2.201
0.127
0.031
1.622
4.612
CV
12.076
2.710
20.240
1.104
6.542
1.876
12.585
2.388
13.036
23.385
11.985
13.734
SR: Shell ratio


Table 9: Mean performance of silkworm mutant accessions during summer season (June-July)
Wt_10
Yld/10000
Yld/10000
Pupa
Cocoon
Shell
Cocoon/
Acc. No.
Fec (No.)
Hat (%)
larvae
Tld (h)
Vld (h)
(No.)
(Wt)
(%)
wt (g)
wt (g)
SR (%)
100 dfl
BBE-0306
398.1
94.12
27
510
119
9635
12.15
90.18
1.23
0.184
14.994
44.779
BBE-0307
345.5
91.91
23.08
516
124
9762
11.63
94.57
1.178
0.161
13.806
43.395
BBE-0308
330.9
94.91
22.52
504
112
9384
8.71
88.5
0.993
0.117
11.724
31.935
BBE-0309
352.2
94.33
23.1
498
108
9330
9.06
89.59
0.978
0.123
12.76
33.372
BBE-0310
273.2
88.87
21.17
526
125
9579
10.4
84.32
0.986
0.12
12.251
36.529
BBE-0311
303
88.62
24.5
505
114
9661
10.57
92.65
1.047
0.122
11.644
37.207
BBE-0312
306.3
90.25
17.23
501
113
9551
8.73
91.25
0.91
0.109
11.975
30.869
BBE-0313
312.8
88.03
22.27
513
126
9615
10.13
92.7
1.06
0.12
11.353
37.327
BBE-0314
356.3
94.68
20.73
515
129
9385
10.37
88.74
0.979
0.112
11.587
38.677
BBE-0315
347.4
95.42
22.35
514
123
9519
11.38
89.8
0.991
0.115
11.576
44.106
BBE-0316
253.8
86.72
19.19
518
131
9564
9.42
88.17
0.971
0.111
11.308
35.066
BBE-0317
278.2
90.89
20.7
512
119
9472
8.05
89.5
0.909
0.103
11.426
29.492
BBE-0318
292.4
90.9
16.39
505
121
9658
9.58
92.96
0.815
0.099
11.884
34.494
BBE-0319
378.7
94.42
26.68
501
113
9637
10.13
92.93
1.042
0.133
12.739
37.962
BBE-0320
318.5
94.04
27.76
501
113
9613
10.93
91.44
1.131
0.155
13.691
40.709
BBE-0321
320.9
87.41
21.93
500
111
9623
11.25
91.72
0.964
0.116
11.962
42.128
BBE-0322
318.5
89.42
19.03
514
125
9703
8.299
93.04
0.905
0.104
11.534
30.189
BBE-0323
328
91.13
24.41
504
117
9612
10.78
90.52
1.062
0.141
22.737
38.409
BBE-0331
256.7
83.12
20.81
514
123
9458
8.59
85.73
0.92
0.109
11.908
31.054
BBE-0333
318.1
94.78
25.1
515
112
9676
10.03
93.61
1.059
0.136
12.965
33.938
BBE-0390
324.8
96.92
21.27
516
144
8940
8.125
88.25
1.196
0.189
15.805
25.486
BBE-0391
350.2
93
27.97
552
142
9209
10.675
90.97
1.22
0.187
15.392
34.761
BBE-0392
334.3
94.97
31.59
512
136
9063
11.75
89.18
1.337
0.215
16.092
36.06
Mean
321.68
91.69
22.9
512
122
9506
10.03
90.45
1.038
0.134
13.179
35.997
Range
253.80-398.10
83.12-96.92
16.39-31.59
498-552
107-144
8940-9761
8.05-12.15
84.32-94.57
0.815-1.337
0.099-0.215
11.308-22.737
25.486-44.779
SD
35.791
3.467
3.634
11.281
9.79
206.917
1.229
2.521
0.127
0.032
2.57
4.988
CV
11.126
3.781
15.865
2.205
8.045
2.177
12.253
2.787
12.193
24.198
19.499
13.856
SR: Shell ratio

Higher mean values were recorded for all the parameters during winter season (Table 8) compared to the multi-trait values recorded in the summer season (Table 9). This shows the favorable season for better expression of quantitative traits in mutant silkworm accessions. Since, these mutant silkworms are temperate in origin, the silkworm rearing performance always better due to congenial and less fluctuations in the environmental temperature during winter season (Table 10)24.

Table 10: ANOVA of seasonal variation in the performance of mutant silkworm accessions for different parameters
Acc. No.
Fec
Hat (%)
Wt_10 larvae
Tld
Vld
Yld/10000 (No.)
Season
96208.16***
67.34NS
73.77*
458074.46***
17868.89***
1817433.46***
Accession
14510.09***
86.99***
235.19***
553.29NS
536.06NS
598906.67***
Season x Accn
12239.27***
52.35NS
35.85***
663.11NS
203.07NS
252284.11***
Error
4293.44
37.7
13.58
494.99
386.82
86795.71
CD (S)
12.0111
1.125
0.675
4.078
3.605
54.007
CD (A)
40.733
3.817
2.291
13.831
12.227
183.147
CD (S X A)
57.606
5.398
3.239
19.559
17.291
259.009
Acc-No.
Yld/10000(Wt)
Pupa (%)
Cocoon wt
Shell wt
SR (%)
Cocoon/100dfl
Season
153.63***
166.03*
0.73***
0.004*
2.678NS
669.48***
Accession
16.52***
37.76NS
0.33***
0.018***
51.28**
242.94***
Season x Accn
6.60***
71.78***
0.04*
0.002***
27.96NS
115.969***
Error
2.47
28.49
0.02
0.001
25.05
48.05
CD (S)
0.288
0.978
0.027
0.005
0.917
1.271
CD (A)
0.976
3.318
0.091
0.017
3.111
4.309
CD (S X A)
1.381
4.692
0.129
0.024
4.4
6.094
Significance level: *p<0.05, **p<0.01, ***p<0.001, CD: Confidence distribution


Fig. 1: Cluster analysis based on all 12 parameters for 23 silkworm mutant accessions according to grouping from multivariate PAST

A detailed analysis was undertaken to test the efficacy of hierarchical agglomerative clustering (UPGMA method) in grouping the different mutant silkworm accessions based on quantitative trait analysis (Fig. 1). The results indicate that all the mutant accessions were grouped together in two major groups. Further, sub-grouping under these 2 groups highlights genetically different association with the differentiation of various groups. The cluster analysis provides scope for adopting a re-combinational breeding program using distant cluster members. Thus, the sub-grouping of high yielding bivoltine strains offers an opportunity to exploit the genetic differences between high yielding strains25,26. The clustering also indicates the possibility for recombining low and high-yielding members from genetically distant clusters. The results presented here establish its usefulness in realizing a better projection of the genetic difference between silkworm strains of different yield potentials27. Recently the cluster analysis of 369 bivoltine silkworm accessions was done using Ward’s minimum variance cluster analysis method for 11 economic traits revealed the diversity among the bivoltine genotypes that were grouped into 20 clusters based on the degree of variations28. The maintenance of heterogeneity in the germplasm is important and is necessary for better maintenance without any inbreeding depression29. The inclusion of genotypes of the same origin in different clusters clearly indicates the presence of considerable genetic diversity among the population used in this study.

The PCA was conducted for multivariate traits and analyzed for correlation of the performance of mutant silkworm accessions along with the commercially exploited silkworm races such as Bivoltine CSR-2 (BBI-0290) and Multivoltine Pure Mysore (PM) (BMI-0001) indicated that the performance of mutant accessions viz., BBE-0306, 0307, 0319, 0320, 0323 and 0333 are positively correlated with the performance of BBI-290 (CSR-2) and BMI-0001 (PM) and grouped under one group (Fig. 2). Whereas, accessions such as BBE-0308, 0310, 0314, 0316 and BBE-0317 are negatively correlated compared to the BBI-0290 and BMI-0001 and grouped separately. The grouping of silkworm genotypes indicates the higher similarity with respect to multiple traits30. Similarly, 6 mutant accessions showed similarity with CSR-2 and PM silkworm races for some of the commercially important characters. This indicates the possibilities of using mutant silkworm genetic resources for commercial exploitation through crop improvement programme.

Fig. 2: Comparative (PCA) analysis of 23 mutant silkworm accessions with commercially important silkworm races

CONCLUSION

The extent of variability among different genotypes is essential and is basis for the germplasm collection for their effective utilization in the future. The concerted efforts are utmost necessary for the characterization, evaluation and identification of trait specific genotypes using standard and reliable methods. The present study is an attempt to showcase the potentialities of the mutant silkworm accessions for their utilization in the commercial exploitation. Since these genotypes were considered most suitable for basic genetic studies rather its usefulness in silk production. The correlation studies using PCA with commercially important silkworm races PM and CSR-2 revealed that some of the mutant silkworms conserved in the germplasm can be used to explore the combining ability studies for further commercial exploitation.

SIGNIFICANCE STATEMENT

This study emphasizes the importance of the mutant silkworm germplasm and its proper maintenance for their sustainable utilization in the future. This study showcases the genetic potentialities of the mutant silkworm genetic resources which can be utilized by the silkworm breeders to develop trait specific breeds. Also, this study give a light on the efficient management of silkworm germplasm and also their evaluation to understand the genetic potentialities of silkworm genetic resources to exploit for commercial silk production through appropriate silkworm breeding strategies.

REFERENCES

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