GE NETIC VARI ABIL ITY, COR RE LA TION AND PATH ANAL Y SIS FOR MUTAGENIC M
2POP U LA TION IN CHILLI
B.V. Tembhurne andB. Belabadevi
De part ment of Ge net ics and Plant Breed ing, UAS, Raichur (Karnataka) E-mail :[email protected]
ABSTRACT
Sixty four genotypes of chilli were evaluated to study the genetic variability as well as association for 11 growth and fruit characters along with four quantitative characters. There was significant variation among the genotypes and considerable amount of genetic variability exists for yield and its components studied in M2 mutant population. Least
difference between genotypic and phenotypic variance indicating environmental influence for expression of most of the traits. High heritability estimates with high genetic advance as per cent mean observed for characters like number of secondary branches/plant, number of fruits/plant, fruit length, number of seeds/fruit and fruit yield/plant revealed that these characters are under the control of additive gene action. Plant height, number of fruits/plant, fruit weight/fruit, fruit length and fruit diameter were highly associated with dry fruit yield/plant. Estimates of path analysis reveals that fruit weight/fruit, number of fruits/plant, leaf area and number of secondary branches/plant were the four factors that extends the greatest influence both directly and indirectly upon the dry fruit yield/plant, these four traits were important components that involved dry fruit yield/plant. However, number of primary branches/plant, fruit length and number of seeds/fruit were relatively unimportant. The genotype B. dabbi recorded highest colour value of 196.38 (ASTA) and oleoresin content of 15.92%. Genotype JCH-42 recorded highest capsaicin of 0.38 (SHU) and ascorbic acid of 102.28 mg/g. However, oleoresin content was more in genotype B. dabbi (15.92%).
Key words : Ge netic vari abil ity, cor re la tion, path anal y sis, mutagenic pop u la tion, chilli.
Chilli is one of the most important vegetable cum spice crops in India. In spite of its high nutritive value, well acceptability among consumers and wide range of genetic variability, the optimum productivity in chilli still remain to be achieved. Therefore, much concerted efforts are necessary to improve its yield and yield attributes. Genetic variability for economic traits is the pre-requisite for any successful breeding programme as the degree of response to selection depends on the quantum of variability. In any crop, yield being a complex character influenced by many of its contributing characters controlled by polygene and the environmental factors. So, an understanding of genetics of yield and its component traits, association between each component trait and yield is necessary for planning effective selection procedure in developing high yielding genotypes. However, the inheritance of quantitative traits is often influenced by variation in other characters which may be due to pleiotropy or genetic linkage. Hence, knowledge of association between yield and its attributes obtained through estimation of genotypic and phenotypic correlation helps in determining the extent of improvement that could be brought about in the characters and also in selecting suitable genotypes.
Mutation breeding is recognised as one of the driving force of evolution. It’s relatively quicker method for improvement of various crop species. It is an important tool to create variability for quantitatively inherited traits in different plants and is considered as an alternative
method to increase genetic variability in plant breeding (1). Mutation breeding often used to correct defects in cultivar which has a set of good agronomic characteristics (2). Chemical mutagens such as Ethyl Methane Sulphonate (EMS), Di Methyl Sulphate (DMS), Sodium Azide (SA) and certain base substitution and nitrous compounds appear to induce higher proportions of point mutations than chromosomal aberrations. The present study was, therefore, undertaken to determine the extent of genetic variability for important growth and fruit characters to yield as well as to determine interrelation-ship among the characters and their direct and indirect effects on yield of chilli.
MATERIALS AND METHODS
genotypes for different characters were tested for significance using analysis of variance. Genotypic Coefficient of Variation (GCV) and Phenotypic Coefficient of Variation (PCV) were estimated as per (5). Heritability (h2) and Genetic Advance (GA) were estimated according to (6) and (7) respectively, correlation was computed by using the formula given by (8) and path analysis was done by (9).
RESULTS AND DISCUSSION
All the 11 characters under study showed highly significant variation among the genotypes indicating their importance in the study of genetic variability. Estimates for the PCV and GCV, heritability in broad sense (h2) and GA as % of mean for these characters are presented in the Table-1.
Table-1 : Estimates of range, mean and different genetic parameters for yield, yield attributing traits of chilli mutants (M2 generation)
Characters Range Coefficient of variability Heritability
(%) broad sense
Expected genetic advance
@ 5%
Genetic advance % of mean
Min. Max. Mean. GCV PCV
PH 20.00 95.00 43.08 27.50 56.50 24.00 1.19 2.76
NPB 2.00 6.00 3.69 26.17 33.31 61.74 1.56 42.36
NSB 4.00 36.00 20.31 34.52 34.78 98.48 14.33 70.56
LA 7.60 24.60 13.74 19.83 27.61 51.63 4.03 29.36
NF 2.00 57.00 21.05 52.22 52.64 98.41 22.46 106.71
FW 0.25 4.70 0.83 47.76 40.05 1.42 0.10 11.73
FL 1.80 9.80 4.36 29.38 29.80 97.20 2.60 59.67
FD 7.40 18.35 12.73 14.38 16.84 72.51 3.20 25.15
NSD 5.00 142.0 54.02 99.07 99.09 99.95 110.21 204.02
TW 5.63 10.34 8.53 9.40 9.61 95.54 1.61 18.91
YLD 2.04 183.3 19.72 75.17 75.30 99.65 30.48 154.58
PH = Plant height (cm) NPB = Number of primary branches/plant NSB = Number of secondary branches/plant LA = Leaf area (cm2) NF = Number of fruits/plant FW = Fruit weight/fruit (g) FL = Fruit length (cm) FD = Fruit diameter (mm) NSD = Number of seeds/fruit
TW = Test weight (g) YLD = Fruit yield/plant (g)
Table-2 : Mean performance of chilli genotypes selected for quality analysis.
Sl. No. Genotypes Capsaicin (SHU) Ascorbic acid (g) Oleoresin (%) Color value (ASTA)
1. P3 T1-16 0.19 59.62 9.02 95.36
2. P3 T1-22 0.15 65.10 10.09 56.32
3. P3 T1-27 0.13 73.56 9.65 87.05
4. P3 T1-29 0.25 55.82 8.53 76.51
5. P3 T1-30 0.09 69.36 10.0 79.34
6. P3 T2-02 0.23 59.25 9.87 69.86
7. P3 T2-06 0.22 71.86 8.65 85.62
8. P3 T2-07 0.16 69.52 7.19 77.62
9. P3 T2-19 0.18 65.37 9.86 56.23
10. P3 T2-20 0.22 79.18 8.20 87.25
11. P3 T2-26 0.13 68.43 7.69 68.23
12. P3 T3-02 0.16 64.65 9.38 85.90
13. P3 T1-03 0.21 80.26 9.73 76.68
14. P3 T1-08 0.16 62.50 8.90 81.30
15. P3 T1-09 0.18 78.08 9.16 66.26
16. Indam 5 0.33 84.60 9.65 87.20
17. Sitara 0.22 99.23 9.86 98.56
18. 9608 × KA2 long 0.20 96.09 9.21 86.53
19. JCH-42 0.38 102.28 9.06 89.31
20. JCH-43 0.16 89.21 9.58 101.21
21. JCH-46 0.19 95.85 10.10 69.56
22. P3 0.18 56.23 8.00 55.30
23. B. DABBI 0.10 84.00 15.92 196.38
Mean 0.19 74.92 9.45 84.07
CV 5.137 1.535 2.460 0.499
CD @ 5% 0.025 2.380 0.488 0.867
Number of secondary branches/plant showed high heritability coupled with high genetic and phenotypic variance and also high genetic advance which indicates predominance of additive gene action; hence this trait is amenable for direct selection. The plant height showed low heritability coupled with low genetic advance making it lucid that non additive is predominant; hence this trait is less amenable for direct selection, but can be used for hybrid production. Further, low genetic advance for leaf area indicates non additive gene action for which the direction cannot be practiced. The number of primary branches exhibited high heritability coupled with low genetic advance as percentage mean showed the role of additive genes in the expression of the character which could be effectively improved upon selection. These
findings are in confirmation with (10). All the fruit related characters viz. dry fruit weight, fruit length and number of seeds/fruit except fruit diametershowed high genotypic and phenotypic coefficients of variation. High estimates of co-efficients of variation for the above trait indicated wide range of variability. Narrow difference between phenotypic and genotypic co-efficients of variation were noticed for fruit diameter, where as strong correlation between the fruit weight to fruit length and number of seeds/fruit were noticed. Similar conclusions were presented by (11). Moderate phenotypic and genotypic co-efficient of variation, heritability and genetic advance were observed for fruit length and fruit weight. It indicates preponderance of both non-additive and additive gene Table-3 : Estimates of phenotypic correlation coefficient between fruit yield and its components in chilli mutants (M2 generation)
NPB NSB LA NF FW FL FD NSD TW YLD
PH 0.28** 0.53** 0.05 0.36** -0.06 0.10 -0.11 -0.00 -0.10 0.19**
NPB 0.41** -0.08 0.19** -0.03 0.01 -0.06 -0.03 -0.02 0.08
NSB -0.25** 0.14** -0.07 0.05 -0.08 0.04 -0.9 0.06
LA -0.05 0.82** 0.11 0.11 0.03 -0.01 0.07
NF 0.13* 0.18** -0.03 -0.01 -0.02 0.66**
FW 0.29** 0.37** 0.18** 0.05 0.64**
FL 0.06 0.04 0.14** 0.26**
FD 0.09* 0.21** 0.21**
NSD 0.15** 0.07
TW 0.02
YLD 1.00
*, **, Significant at 5 and 1% levels, respectively.
PH = Plant height (cm) NPB = Number of primary branches/plant NSB = Number of secondary branches/plant LA = Leaf area (cm2) NF = Number of fruits/plant FW = Fruit weight/fruit (g) FL = Fruit length (cm) FD = Fruit diameter (mm) NSD = Number of seeds/fruit
TW = Test weight (g) YLD = Fruit yield/plant (g)
Table-4 : Phenotypic path of different characters affecting fruit yield/plant in chilli mutant (M2 generation).
PH NPB NSB LA NF FW FL FD NSD TW
PH 0.0023 0.0007 0.0012 -0.0001 0.0009 -0.0001 0.0002 -0.0002 0.0000 -0.0002 NPB -0.0066 -0.0233 -0.0094 0.0018 -0.0044 0.0008 -0.0001 0.0014 0.0006 0.0005
NSB 0.0223 0.0176 0.0440 -0.0109 0.0059 -0.0029 0.0023 -0.0034 0.0016 -0.0040 LA -0.0031 -0.0046 -0.0150 0.0600 -0.0031 0.0049 0.0067 0.0063 0.0016 -0.0003 NF 0.2146 0.1122 0.0798 -0.0309 0.5193 0.0747 0.1045 -0.0178 0.0041 -0.0137 FW -0.0327 -0.0186 -0.0377 0.0464 0.0718 0.5681 0.1634 0.2112 0.1003 0.0277 FL -0.0013 -0.0001 -0.0007 -0.0015 -0.0024 -0.0039 -0.0136 -0.0008 -0.0005 -0.0019 FD -0.0017 -0.0010 -0.0013 0.0017 -0.0005 0.0061 0.0009 0.0163 0.0014 0.0033
NSD 0.0000 0.0010 -0.0014 -0.0011 -0.0003 -0.0070 -0.0014 -0.0034 -0.0394 -0.0060 TW -0.0018 -0.0004 -0.0017 -0.0001 -0.0004 0.0009 0.0026 0.0038 -0.0028 0.0190 Correlation with
fruit yield/plant
0.1927** 0.0829 0.0566 0.0649 0.6588** 0.6384** 0.2637** 0.2105** 0.0371 0.0202
Residual effect = 0.4963
PH = Plant height (cm) NPB = Number of primary branches/plant NSB = Number of secondary branches/plant LA = Leaf area (cm2) NF = Number of fruits/plant FW = Fruit weight/fruit (g) FL = Fruit length (cm) FD = Fruit diameter (mm) NSD = Number of seeds/fruit
action for fruit length and fruit weight and slow response to selection for fruit having less length.
Qualities of chilli are judged commercially by its colour value. 23 genotypes were selected to evaluate the colour value. Among the 23 genotypes 11 genotypes registered greatest colour value than mean colour value. The genotype B.dabbi recorded highest colour value of 196.38 (ASTA) and genotype P3 registered 55.30 (ASTA). This is in conformity with findings of (12). As far the mean per se performance is related following top five best genotype were selected for further breeding programme (Table-2).
Ascorbic acid : JCH-42, Sitara, 9608 × KA2 long, JCH-46 and JCH-43
Capsaicin : JCH-42, Indam 5, P3 T1 -29, P3 T2-2 and P3 T2-20
Oleoresin : B. Dabbi, JCH-46, P3 T1-22, P3 T2-2 and P3 T2-19
Color value : B. Dabbi, JCH-43, Sitara, P3 T1-16 and JCH-42
Fruit yield had significant and positive correlation with number of fruits/plant, fruit weight/fruit, fruit diameter, fruit length and plant height. Fruit yield/plant and number of primary branches, number of secondary branches, leaf area showed positive correlation and high value of heritability and low genetic advance (Table-4). It indicates that number of primary branches, number of secondary branches and leaf area may not be suitable as selection criteria for improving yield. This conclusion is in contrast with (13) who had recorded positive significant correlation for these traits.
Plant height with number of primary branches, number of secondary branches and number of fruits/ plant recorded significant positive correlation and high heritability and moderate to low genetic advance suggests that there is preponderance of both additive and non additive gene action. Leaf area had significantly positive correlation with fruit weight/fruit at phenotypic correlation in addition to this strong genetic nature of heritability makes this character suitable for selection to improve the yield. This has to be further studied as to which effects are influencing more. Similar findings were made by (14). Dry fruit weight recorded significant positive correlation with all fruit related trait viz., fruit length, fruit diameter and number of seeds/fruit phenotypically.
In the present study out of 11 characters seven characters had positive and direct effect on fruit yield/ plant. The character viz., fruit weight/fruit had maximum positive direct effect on fruit yield/plant followed by number of fruit/plant, leaf area, number of secondary
branches/plant, test weight, fruit diameter and plant height. Similar results were obtained by (15). However, number of seeds/fruit had maximum negative and direct effect on fruit yield/plant followed by number of primary branches and fruit length. These results are in contrast with (16). The indirect effect of number of primary branches, leaf area, fruit weight/fruit, fruit length, fruit diameter and test weight via other characters was not considerable. Whereas, number of primary branches had lower direct effect on fruit yield/plant but highest positive indirect effect via leaf area, fruit weight and fruit diameter. While the indirect effect of number of fruits/plant via plant height, number of primary branches, number of secondary branches, fruit weight, fruit length and number of seeds/fruit was high and had positive effect (Table-5), similar results were obtained by (15).
CONCLUSION
It has been concluded from the present investigation that the characters like number of secondary branches/plant, number of fruits/plant, fruit length, number of seeds/fruit and fruit yield/plant are under the control of additive gene action. The characters like, plant height, number of fruits/ plant, fruit weight/fruit, fruit length and fruit diameter were highly associated with dry fruit yield/plant. However, fruit weight/fruit, number of fruits/plant, leaf area and number of secondary branches/plant were the four factors that extends the greatest influence both directly and indirectly upon the dry fruit yield/plant. These four traits were important components that involved dry fruit yield/plant. While, number of primary branches/plant, fruit length and number of seeds/fruit were relatively unimportant.
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