COMBINING ABILITY AND HERITABILITY ESTIMATES OF MAIN AGRONOMIC CHARACTERS IN RAPESEED BREEDING LINES
USING LINE × TESTER ANALYSIS
Valiollah Rameeh*
Agriculture and Natural Resources Research Centre of Mazandran, Sari, Iran
Abstract: To estimate the general and specific combining ability (GCA and
SCA) effects of plant height, yield components, seed yield and oil content, three testers and six lines of spring type of rapeseed varieties were crossed using line × tester fashion. Significant mean squares of parents and crosses for all the traits indicated significant genetic variation among the parents and their F1 crosses.
Significant mean squares of parents vs crosses revealed significant average heterosis for all the traits except seeds per pod, 1000-seed weight and oil content. High narrow-sense heritability estimates for all the traits except seeds per pod, indicating the importance of additive genetic effects for these traits. Due to more importance of additive genetic effects for most of the traits, only a few of the crosses exhibited significant SCA effects. A significant positive correlation between seed yield and some of yield components including pods on main axis, pods per plant and 1000-seed weight indicates that these traits can be used as suitable selection criteria for improving of seed yield. The crosses including Opt × R01, RG06 × R01, RG06 × R08 and RGS3 × R08 with 3241.91, 3213.68, 3334.28 and 3237.45 kg ha-1 of seed yield detected as prior combinations for improving of this trait and all of these combinations had also positive SCA effect for this trait.
Key words: genetic variation, oil content, line × tester, seed yield.
Introduction
Rapeseed (Brassica napus L.) is one of the most important edible oilseed crops in the world, as well as a major potential source for protein meals (Diepenbrock, 2000; Wang, 2005). Its production in the world ranks second only to soybean (Glycine max L.). Seed yield of rapeseed is a quantitative trait, which is largely influenced by the different environmental conditions and hence in the most of the cases it has low heritability (Habekotte, 1997; Diepenbrock, 2000; Zhang and Zhu, 2006; Wang et al., 2007; Rameeh, 2010). The exploitation of genetic variability in any crop species is considered to be critical for making further
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genetic improvement in seed yield, as well as other economically important traits (Mahmood et al., 2003; Wang et al., 2010; Rameeh et al., 2012). Inter and intra
Brassica species crosses are suitable ways to make genetic variations and develop
the new varieties (Qian et al., 2007; Amiri-Oghana et al., 2009). In rapeseed breeding program for hybrid and open pollinated varieties, general and specific combining ability effects (GCA and SCA) are important indicators of the potential of inbred lines in hybrid combinations. To incorporate desirable characters to maximize economic yields, the knowledge of combining ability is valuable to get information on selection of parents and nature of gene actions involved. The variance for GCA includes the additive portion of the total variance, whereas that for SCA includes the non-additive portion of the total variance, arising largely from dominance and epistatic deviations (Malik et al., 2004; Teklwold and Becker, 2005; Variath et al., 2009). Information and exact study of combining ability can be useful in regard to selection of breeding methods and selection of lines for hybrid combination (Nassimi et al., 2006; Rameeh, 2011). Due to the numerous theoretical and practical advantages of this method, in recent years the choice of parental forms on the basis of combining ability has been extended. Genetic gain of
Brassica requires certain information regarding the nature of combining ability of
parents available for use in the hybridization program. Most of previous studies on combining abilities have shown significant GCA and SCA effects for yield and its component characters. These results indicate that both additive and non-additive gene actions are important in the inheritance of these traits (Yadav et al., 2005; Akbar et al., 2008; Huang et al., 2010; Singh et al., 2010). Variability of results indicated clearly that the inheritance patterns of plant traits imparting yield vary with the genetic material and the climatic vagaries that suggested exploring the genetic information about the present material before performing selection. Since different genetic materials display different genetic parameters, the objectives of the present study were therefore to examine the combining ability patterns of selected rapeseed (Brassica napus L.) genotypes in a line × tester analysis, to assess genetic parameters of some agronomic traits and oil content using a mixed model and to identify candidates for promising hybrid combinations.
Material and Methods
Six spring rapeseed (Brassica napus L.) genotypes including Opt, RW, 19H, RG06, Sarigol and RGS3 as lines were crossed with three spring testers including R01, R08 and R020 based on line × tester crossing scheme during 2010-2011. Eighteen F1 hybrids along with their parents were grown in a randomized complete
cm apart. The distance between plants in each row was 5 cm resulting in approximately 300 plants per plot, which was sufficient for F1 genetic analysis.
The soil classified as a deep loam soil (Typic Xerofluents,USDA classification) contained an average of 280 g clay kg-1,560 g silt kg-1, 160 g sand kg-1, and 22.4 g organic matter kg-1 with a pH of 7.3. Soil samples were found to have 45 kg ha-1 (mineral N in theupper 30-cm profile). Fertilizers were applied at the rates of 100 : 50 : 90 kg ha-1 of N : P : K, respectively. All the plant protection measures were adopted to make the crop free from insects. Seed yield (adjusted to kg/ha) was recorded based on two middle rows of each plot. The data were recorded from ten randomly competitive selected plants of each entry of each replication for plant height, pods on main axis, pods per plant, seeds per pod, and 1000-seed weight. Oil content was estimated by using nuclear magnetic resonance spectrometry (Madson, 1976).
Data for the genotypes were subjected to line × tester analysis (Mather and Jinks, 1982) to estimate GCA and SCA. A t-testwas used to test whether the GCA and SCA effects were differentfrom 0. Narrow-sense heritability estimates of the traits and Pearson coefficient correlation between the traits were calculated.
Results and Discussion
Line × tester analysis
Table 1. Mean squares (MS) from ANOVA, narrow-sense heritability and components of variability for plant height, yield components, seed yield and oil content of rapeseed (Brassica napus L.) genotypes based on line × tester fashion.
Source of
variance df
MS
Plant height
Pods on main
axis
Pods per plant
Seeds per pod
1000- seed weight
Seed yield
Oil content
Replication 2 1158.20** 840.42** 1606.62** 158.16** 0.27** 275545.0* 3.43** Treatment 26 279.34** 1457.06** 420.22** 18.60** 0.17** 417220.1** 13.26** Parents 8 428.71** 52.28** 859.78** 26.73** 0.136** 491032.4* 16.67** Parents vs crosses 1 333.37** 36565.5** 1977.56** 0.65 0.051 2429541.7** 0.09 Crosses 17 205.87** 52.93** 121.76** 15.83* 0.193** 264113.1** 12.43** Lines 5 499.95** 101.66** 42.32 19.52* 0.340** 559781.4* 15.91** Testers 2 94.46 17.22 61.56 8.20 0.004 92944.5 22.08** Line x tester 10 81.11* 35.70 173.52** 15.51 0.158** 150512.7 8.76** Error 52 35.81 12.76 27.14 3.93 0.002 97770.7 0.83 Heritability 0.88 0.70 0.45 0.26 0.52 0.79 0.67 Variations due to lines 0.71 0.56 0.10 0.36 0.51 0.62 0.38 Variations due to testers 0.05 0.04 0.06 0.06 0.0 0.04 0.21 Variations due to lines ×
testers 0.23 0.40 0.84 0.58 0.48 0.34 0.41
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, ** Significant at p<0.05 and 0.01, respectively.
Means and general combining abilities of the parents
Table 2. Means of parents for plant height, yield components, seed yield and oil content. Parents Plant height (cm) Pods on main axis Pods per plant Seeds per pod 1000-seed weight (g) Seed yield (kg ha-1)
Oil content
(%)
Testers
1 - R01 151.46 29.82 127.96 18.83 3.62 2559.23 45.16 2 - R08 142.03 33.64 123.52 25.54 3.35 2166.64 41.19 3 - R020 143.74 41.16 114.59 18.49 3.85 2902.01 45.32
Lines
4 - Opt 133.81 37.27 133.29 22.86 3.80 2554.64 46.30 5 - RW 155.91 35.59 138.70 26.47 3.44 2934.24 40.30 6 - 19H 135.33 31.10 116.56 23.24 3.63 3132.64 43.15 7 - RG06 128.84 33.13 104.20 19.56 3.55 2212.31 45.36 8 - Sarigol 116.28 27.11 82.12 19.24 3.37 1897.32 46.43 9 - RGS3 142.25 35.10 114.19 22.79 3.95 2658.67 41.51 LSD (α=0.05) 9.97 5.95 8.68 3.30 0.24 520.82 1.52 LSD (α=0.01) 13.44 8.02 11.70 4.45 0.32 702.09 2.05
Opt, 19H and RG06 with significant positive GCA effects of 1000-seed weight were good combiners for this trait. The high mean values of seed yield belonged to 19H, RW and R020. R08 from the testers and also Opt and RG06 from the lines were good combiners for breeding this trait. The high mean values of oil content were detected in R01, R020, Opt, RG06 and Sarigol. Opt and RG06 had significant positive GCA effects on oil content, therefore these genotypes were superior combiners. Similarly, significant GCA effects were reported for pods per main axis, pods per plant, length of pod, number of seeds per pod, 1000-seed weight and seed yield in B. napus (Rameeh, 2010; Sabaghnia et al., 2010).
Table 3. Estimates of GCA effects for plant height, yield components, seed yield and oil content of rapeseed (Brassica napus L.) genotypes based on line × tester fashion.
Parents Plant height Pods on main axis Pods per plant Seeds per pod 1000-seed weight Seed yield Oil content Testers
1 - R01 -0.09 -0.03 -0.51 -0.07 -0.003 -23.44 0.11 2 - R08 -0.71 -0.31 -0.18 -0.18 -0.003 24.43 0.30 3 - R020 0.81 0.34 0.69 0.25 0.006 -0.99 -0.41*
Lines
4 - Opt 1.49 0.53 -0.29 -0.84* 0.041* 105.53* 0.34* 5 - RW -0.58 -1.62* -0.75 0.54 -0.032 -52.41 -0.34* 6 - 19H 1.79 0.14 0.52 -0.07 0.051* -70.26 0.28 7 - RG06 -3.94** 1.73* 1.01 0.43 0.050* 83.72 0.43* 8 - Sarigol 2.72* -0.55 -0.77 -0.11 -0.115** -90.34 -0.70** 9 - RGS3 -1.48 -0.23 0.28 0.05 0.004 23.75 -0.02 S.E. GCA (tester) 0.92 0.55 0.80 0.30 0.02 47.91 0.14 S.E. GCA (line) 1.30 0.77 1.13 0.43 0.03 67.75 0.20
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Meansand specific combining abilities of the crosses
The lowest genetic variation (0.23) which indicates the lowest genetic diversity of line × tester was detected for plant height (Table 1). The mean values of the crosses for all the traits are presented in Table 4. Low mean values of plant height allow them to be tolerant of lodging, therefore the cross combinations including RG06 × R01, RG06 × R020, RW × R08, RGS3 × R08 with 128.81, 128.54, 133.99 and 133.29 cm of plant height were suitable combinations. Crosses RW × R08, 19H × R01 and RG06 × R020 with significant negative SCA effects were preferred for improving plant height (Table 5).
Table 4. Means of the crosses for plant height, yield components, seed yield and oil content.
Crosses
Plant height (cm)
Pods on main
axis
Pods per plant
Seeds per pod
1000-seed weight
(g)
Seed yield (kg ha-1)
Oil content
(%) 1 - Opt × R01 145.29 36.87 133.58 20.17 3.84 3241.91 46.61 2 - Opt × R08 145.60 35.89 119.50 16.14 3.50 3075.29 47.41 3 - Opt × R020 151.99 41.66 127.48 21.23 4.09 3407.32 40.59 4 - RW × R01 146.42 29.71 127.40 22.20 3.54 2746.16 42.03 5 - RW × R08 133.99 28.22 123.47 20.57 3.72 2613.95 43.62 6 - RW × R020 143.86 37.12 125.52 27.17 3.52 2942.98 42.91 7 - 19H × R01 141.61 38.62 122.30 21.86 4.11 2302.04 43.61 8 - 19H × R08 151.28 37.82 120.52 22.10 3.76 3003.01 45.27 9 - 19H × R020 152.67 34.42 145.02 20.53 3.65 2837.31 45.27 10 - RG06 × R01 128.81 41.26 127.32 23.96 3.54 3213.68 45.30 11 - RG06 × R08 136.63 41.84 137.50 23.86 4.13 3334.28 46.56 12 - RG06 × R020 128.54 42.13 127.43 21.20 3.85 2980.28 43.62 13 - Sarigol × R01 152.84 39.86 123.19 20.17 3.45 2636.75 42.24 14 - Sarigol × R08 145.31 33.06 129.66 20.46 3.23 2725.27 41.21 15 - Sarigol × R020 155.76 31.81 123.38 23.51 3.36 2599.69 41.85 16 - RGS3 × R01 142.27 32.48 123.39 20.62 3.60 2986.98 45.34 17 - RGS3 × R08 133.29 36.84 132.45 23.82 3.75 3237.45 44.57 18 - RGS3 × R020 140.61 38.25 129.83 21.11 3.75 2764.06 41.53 LSD (α=0.05) 9.97 5.95 8.68 3.30 0.24 520.82 1.52 LSD (α=0.01) 13.44 8.02 11.70 4.45 0.32 702.09 2.05
high means of pods per plant were determined as superior combinations and also most of these crosses had significant positive SCA effects of this trait. RW × R020, RG06 × R01, RG06 × R08, Sarigol × R020 and RGS3 × R08 had high mean values of seeds per pod. RW × R020 had only significant positive SCA effect for this trait and both parents of this combination had also significant positive GCA effect on the trait. Opt × R020, 19H × R01 and RG06 × R020 with 4.09, 4.11 and 4.13 g of 1000-seed weight were superior combinations for improving this trait. Most of these crosses had at least one parent with significant positive GCA effect for 1000-seed weight. Opt × R020 and RG06 × R08 had positive SCA effect of 1000-1000-seed weight. Superior combinations for seed yield were Opt × R01, RG06 × R01, RG06 × R08 and RGS3 × R08 with 3241.91, 3213.68, 3334.28 and 3237.45 kg ha-1, respectively and all of the combinations had also positive SCA effects of this trait. Most of combinations with high mean values of oil content had at least one parent with significant positive GCA effect of this trait. Opt × R08 had only significant positive SCA effect for oil content. Most previous studies on combining abilities have shown significant GCA and SCA effects on yield and its component characters. These results indicated that both additive and non-additive gene actions were important in the inheritance of these traits (Yadav et al., 2005; Akbar et al., 2008; Huang et al., 2010; Singh et al., 2010).
Table 5. Estimates of SCA effects for plant height, yield components, seed yield and oil content of rapeseed (Brassica napus L.) genotypes based on line × tester fashion.
Crosses Plant height
Pods on main axis
Pods per plant
Seeds per pod
1000-seed weight
Seed yield
Oil content 1 - Opt × R01 -0.69 -0.40 3.14** 0.40 0.01 23.58 0.47 2 - Opt × R08 -0.13 -0.44 -1.79 -0.83 -0.10** -79.84 0.54* 3 - Opt × R020 0.64 0.83 -1.35 0.43 0.09** 56.26 -1.02** 4 - RW × R01 1.76 -0.63 1.54 -0.30 -0.02 16.26 -0.38 5 - RW × R08 -1.93* -0.84 0.00 -0.73 0.04 -75.68 -0.05 6 - RW × R020 -0.01 1.47** -1.54 1.03* -0.03 59.42 0.43
7 - 19H × R01 -2.21* 0.58 -1.43 0.19 0.09 -113.92* -0.48
8 - 19H × R08 1.47 0.60 -2.25** 0.38 -0.02 71.86 -0.12 9 - 19H × R020 0.56 -1.18 3.69** -0.57 -0.07* 42.05 0.60** 10 - RG06 × R01 -0.74 -0.13 -1.43 0.39 -0.10** 35.98 -0.06 11 - RG06 × R08 2.31* 0.34 -2.25** 0.47 0.10** 28.30 0.16 12 - RG06 × R020 -1.75* -0.21 3.69** -0.85 0.01 -64.28 -0.10 13 - Sarigol × R01 0.61 1.68** -0.25 -0.33 0.04 17.72 0.05 14 - Sarigol × R08 -1.45 -0.30 2.91** -0.12 -0.04 -0.64 -0.49** 15 - Sarigol × R020 0.66 -1.37 -2.67** 0.46 0.01 -17.08 0.44
16 - RGS3 × R01 1.28 -1.10 0.15 -0.34 -0.03 20.38 0.40 17 - RGS3 × R08 -1.26 0.64 2.08* 0.84 0.02 56.00 -0.05 18 - RGS3 × R020 -0.19 0.46 -2.24* -0.50 0.01 - 76.38 -0.35
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Table 6. Pearson coefficients of correlation forthe studied traits.
Traits Plant
height
Pods on main axis
Pods per plant
Seeds per pod
1000-seed weight
Seed yield
Oil content Plant height 1
Pods on main axis 0.09 1
Pods on main axis 0.52** 0.38* 1
Seeds per pod 0.07 0.14 0.34 1
1000-seed weight -0.06 0.55** 0.21 0.04 1
Seed yield 0.25 0.54** 0.57** 0.14 0.38* 1
Oil content -0.41* 0.03 -0.17 -0.46* 0.18 0.08 1
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, ** Significant at p<0.05 and 0.01, respectively.
Conclusion
In general, pods on main axis, pods per plant and 1000-seed weight were significantly correlated with seed yield, indicating that these traits can be used as good selection criteria for improving of seed yield. Parents vs crosses as indicators of average heterosis were significant for plant height, pods on main axis, pods per plant and seed yield. Most of variations of the traits in the genotypes were related to lines and their crosses. Among the yield components, pods on main axis and 1000-seed weight were more heritable than the others.
Acknowledgements
The author wishes to thank Agricultural and Natural Resources Research Center of Mazandaran and Seed and Plant Improvement Institute (SPII) for providing genetic materials and facilities for conducting the experiment.
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OCENE KOMBINACIONE SPOSOBNOSTI I HERITABILNOSTI GLAVNIH AGRONOMSKIH OSOBINA KOD LINIJA DOBIJENIH
OPLEMENJIVANJEM ULJANE REPICE KORIŠĆENJEM ANALIZE LINIJA × TESTER
Valiollah Rameeh*
Istraživački centar za poljoprivredne i prirodne resurse u Mazandranu, Sari, Iran
R e z i m e
U cilju ocenjivanja uticaja opšte i posebne kombinacione sposobnosti (GCA i SCA) visine biljke, komponenti prinosa, prinosa semena i sadržaja ulja, tri testera i
šest linija prolećnog tipa sorti uljane repice su ukršteni korišćenjem metode linija ×
tester. Značajni srednji kvadrati roditelja i hibrida za sve osobine su pokazali
značajnu genetsku varijaciju među roditeljima i njihovim F1 hibridima. Značajni
srednji kvadrati roditelja u odnosu na hibride su pokazali značajan prosečan heterozis za sve osobine osim broja semena po mahuni, mase 1000 semena i sadržaja ulja. Visoke ocene heritabilnosti u užem smislu za sve osobine osim broja semena po mahuni, ukazuju na značaj aditivnih genetskih efekata za ove osobine. Zbog većeg značaja aditivnih genetičkih efekata na većinu osobina, samo nekoliko hibrida je pokazalo značajne SCA uticaje. Značajna pozitivna korelacija između prinosa semena i nekih komponenti prinosa uključujući broj mahuna na glavnoj osi, broj mahuna po biljci i masu 1000 semena ukazuje na to da se ove osobine mogu koristiti kao pogodni selekcioni kriterijumi za poboljšanje prinosa semena. Hibridi Opt × R01, RG06 × R01, RG06 × R08 i RGS3 × R08 sa prinosom semena od 3241,91; 3213,68; 3334,28 i 3237,45 kg ha-1 su uočeni kao prethodne kombinacije za poboljšanje ove osobine, a sve ove kombinacije imale su takođe pozitivan SCA uticaj na ovu osobinu.
Ključne reči: genetska varijacija, sadržaj ulja, linija × tester, prinos semena.
Primljeno: 25. aprila 2013. Odobreno: 3. juna 2013.
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