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Kantalop Kavunlarda (Cucumis melo L. subsp. melo. var cantalupensis Naudin) Verim Bileşenleri, Erken Olgunluk ve Toplam Suda Çözünür Kuru Maddenin Genetik Analizi

Year 2014, , 79 - 86, 01.03.2014
https://doi.org/10.29133/yyutbd.235919

Abstract

Analysis of genetic main effects and genotype×environment interaction effects for quantitative traits of cantaloupe were conducted based on a genetic model containing additive-dominance and their interactions with environments. A set of 21 diallel F hybrids and their parents were evaluated during two the springs of 2011 and 2012. The average weights per fruit, (WT), maturity (DM), flesh thickness (F), total soluble solids content (TSS) and total fruit yield (TY) were measured. The additive genetic variance component was significant for WT, F, DM and TSS, the dominance genetic variance for WT, TY, DM and TSS. However, dominance×year interaction was significant for all traits under investigation except for TSS. Additive gene effects were most important with respect to WT, F, DM and TSS, while genetic dominance effects mainly controlled TY. The parent, Dastjerdi had the highest additive effect for WT and DM, while the parents, Tiltorogh and Savei had the highest additive effects for F and TSS, respectively. Tiltorogh×Savei and Rishbaba×Tiltorogh was the best specific combiner for the traits, WT, F and TY. Favorable heterosis over the better parent heterobeltiosis was found for TY. Thus, there is the potential to generate superior cultivars in segregate generation and hybrid production.

References

  • Abderrahmane A, Zhu J (2001). Diallel analysis for inbred lines involving genotype× environment interaction effects on additive-dominance genetic model. J. Biol. Sci. 1: 704-707.
  • Allard R (1956). The analysis of genetic-environmental interactions by means of diallel crosses. Genetics 41: 305-318.
  • Allard RW, Bradshaw AD (1964). Implications of genotype-environmental interactions in applied plant breeding. Crop Sci. 4: 503-508.
  • Bhella HS (1985). Response of muskmelon to within-row plant spacing. Proc. Ind. Acad. Sci. 94: 99-100. Chen G, Zhu J 2003. QGA Station 1.0. Software for Classical Quantitative Genetics. Institute of Bioinformatics, Zhejiang University, China.
  • Feyzian E, Dehghani H, Rezai AM, Jalali-Javaran M (2009). Diallel cross analysis for maturity and yieldrelated traits in melon (Cucumis melo L.). Euphytica 168: 215-223.
  • Gardner CO, Eberhart SA (1966). Analysis and interpretation of the variety cross diallel and related populations. Biometrics 439-452.
  • Griffing B (1956). Concept of general and specific combining ability in relation to diallel crossing systems. Australian Journal of Biological Sciences 9: 463-493.
  • Hallauer AR, Miranda JB (1988). Quantitative genetics in maize breeding. Iowa State Univ. Press, Ames, IA.8
  • Hartley HO, Rao J (1967). Maximum-likelihood estimation for the mixed analysis of variance model. Biometrika 54: 93-108.
  • Hayman BI (1954). The theory and analysis of diallel crosses. Genetics 39: 789.
  • Kalb TJ, Davis DW (1984). Evaluation of combining ability, heterosis, and genetic variance for fruit quality characteristics in bush muskmelon. J. Amer. Soc. Hort. Sci. 109: 411-415.
  • Kerje T, Grum M (2000). The origin of melon, Cucumis melo L.: a review of the literature. Eucarpia Meeting on Cucurbit Genetics and Breeding, Pp. 37-44.
  • Kultur F, Harrison HC, Staub JE (2001). Spacing and genotype affect fruit sugar concentration, yield, and fruit size of muskmelon. HortScience 36: 274-278.
  • Lippert L, Legg P (1972). Diallel analyses for yield and maturity characteristics in muskmelon cultivars. J. Amer. Soc. Hort. Sci. 97: 87-90.
  • Lippert LF, Hall MO (1982). Heritabilities and correlations in muskmelon from parent-offspring regression analyses. J. Amer. Soc. Hort. Sci. 107: 217-221.
  • Miller R (1974). The jackknife-a review. Biometrika 61: 1-15.
  • Radhakrishna CR (1971). Estimation of variance and covariance components-MINQUE theory. J. Mult. Anal. 1: 257-275.
  • Rao CR (1970). Estimation of heteroscedastic variances in linear models. J. Amer. Stat. Assoc. 65: 1611
  • Sebastian P, Schaefer H, Telford IR, Renner SS (2010). Cucumber (Cucumis sativus L.) and melon (C. melo L.) have numerous wild relatives in Asia and Australia, and the sister species of melon is from Australia. Proc. of the Nation. Acad. Sci., USA 107: 14269-14273.
  • Yan W, Kang MS (2002). GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists, CRC.
  • Zalapa JE, Staub JE, McCreight JD (2006). Generation means analysis of plant architectural traits and fruit yield in melon. Plant Breed. 125: 482-487.
  • Zalapa JE, Staub JE, McCreight JD (2008). Variance component analysis of plant architectural traits and fruit yield in melon. Euphytica 162: 129-143.
  • Zhu J (1992). Mixed model approaches for estimating genetic variances and covariances. J. Biomath. 7: 1Zhu J (1993). Mixed model approaches for estimating genetic covariances between two traits with unequal design matrices. J. Biomath. 8: 24-30.
  • Zhu J, Weir BS (1994a). Analysis of cytoplasmic and maternal effects. II. Genetic models for triploid endosperms. Theor. Appl. Genet. 89: 160-166.
  • Zhu J, Weir BS (1994b). Analysis of cytoplasmic and maternal effects I. A genetic model for diploid plant seeds and animals. Theor. Appl. Genet. 89: 153-159.
  • Zhu J, Weir BS (1996). Mixed model approaches for diallel analysis based on a bio-model. Genet. Res. 68: 233-240.
  • Zhu J, Weir BS (1998). Mixed model approaches for genetic analysis of quantitative traits. Proceedings of the International Conference on Mathematical Biology,Singapore, Pp. 321-330.

Genetic Analysis of Yield Components, Early Maturity and Total Soluble Solids in Cantaloupe (Cucumis melo L. subsp. melo var cantalupensis Naudin

Year 2014, , 79 - 86, 01.03.2014
https://doi.org/10.29133/yyutbd.235919

Abstract

Kantalop kavunlarda kantitatif özellikler için genetik ana bileşenler ve genotip-çevre etkileşimi etkilerinin analizi eklemeli-dominans genetik modelleme ve bunların çevre ile etkileşimlerini içeren bir genetik modele dayalı olarak gerçekleştirilmiştir. Yirmibir (21) adet diallel Fmelez ve ebeveynlerini içeren bir set 2011 ve 2012 yıllarında iki yıl incelenmiştir. Ortalama meyve ağırlığı (OMA), olgunluk (O), meyve eti kalınlığı (MEK), toplam suda çözünür kuru madde (SÇKM) ve toplam meyve verimi (TMV) ölçüm ve gözlemleri yapılmıştır. Eklemeli genetik varyans bileşeni, OMA, MEK, O ve SÇKM bakımından istastistiki olarak önemli bulunurken, dominans gentik varyans bileşeni, OMA, TMV, O ve SÇKM ibakımından istastistiki olarak önemli bulunmuştur. Bununla birlikte, dominans-yıl etkileşimi SÇKM hariç bütün incelenen özellikler bakımından istastistiki olarak önemli çıkmıştır. Eklemeli gen etkisi özellikle OMA, MEK, O ve SÇKM bakımından en önemli olarak bulunurken, dominans gen etkisi başlıca TMV’yi kontrol etmiştir. Ebeveynlerden Dastjerdi OMA ve O bakımından en yüksek eklemeli gen etkisine sahip olurken, ebeveynlerden Tiltorogh ve Savei, MEK ve SÇKM bakımından en yüksek eklemeli gen etkisine sahip olmuşlardır. OMA, MEK ve TMV bakımından en iyi özel kombinasyonlara Tiltorogh×Savei ve Rishbaba×Tiltorogh sahip olmuştur. TMV bakımından en iyi ebeveyni geçen olumlu heterobeltiosis gözlenmiştir. Bu yüzden, açılım gösteren jenerasyonlarda ve hibrit üretiminde üstün özelliklere sahip çeşitlerin geliştirilmesi potansiyeli bulunmaktadır.

References

  • Abderrahmane A, Zhu J (2001). Diallel analysis for inbred lines involving genotype× environment interaction effects on additive-dominance genetic model. J. Biol. Sci. 1: 704-707.
  • Allard R (1956). The analysis of genetic-environmental interactions by means of diallel crosses. Genetics 41: 305-318.
  • Allard RW, Bradshaw AD (1964). Implications of genotype-environmental interactions in applied plant breeding. Crop Sci. 4: 503-508.
  • Bhella HS (1985). Response of muskmelon to within-row plant spacing. Proc. Ind. Acad. Sci. 94: 99-100. Chen G, Zhu J 2003. QGA Station 1.0. Software for Classical Quantitative Genetics. Institute of Bioinformatics, Zhejiang University, China.
  • Feyzian E, Dehghani H, Rezai AM, Jalali-Javaran M (2009). Diallel cross analysis for maturity and yieldrelated traits in melon (Cucumis melo L.). Euphytica 168: 215-223.
  • Gardner CO, Eberhart SA (1966). Analysis and interpretation of the variety cross diallel and related populations. Biometrics 439-452.
  • Griffing B (1956). Concept of general and specific combining ability in relation to diallel crossing systems. Australian Journal of Biological Sciences 9: 463-493.
  • Hallauer AR, Miranda JB (1988). Quantitative genetics in maize breeding. Iowa State Univ. Press, Ames, IA.8
  • Hartley HO, Rao J (1967). Maximum-likelihood estimation for the mixed analysis of variance model. Biometrika 54: 93-108.
  • Hayman BI (1954). The theory and analysis of diallel crosses. Genetics 39: 789.
  • Kalb TJ, Davis DW (1984). Evaluation of combining ability, heterosis, and genetic variance for fruit quality characteristics in bush muskmelon. J. Amer. Soc. Hort. Sci. 109: 411-415.
  • Kerje T, Grum M (2000). The origin of melon, Cucumis melo L.: a review of the literature. Eucarpia Meeting on Cucurbit Genetics and Breeding, Pp. 37-44.
  • Kultur F, Harrison HC, Staub JE (2001). Spacing and genotype affect fruit sugar concentration, yield, and fruit size of muskmelon. HortScience 36: 274-278.
  • Lippert L, Legg P (1972). Diallel analyses for yield and maturity characteristics in muskmelon cultivars. J. Amer. Soc. Hort. Sci. 97: 87-90.
  • Lippert LF, Hall MO (1982). Heritabilities and correlations in muskmelon from parent-offspring regression analyses. J. Amer. Soc. Hort. Sci. 107: 217-221.
  • Miller R (1974). The jackknife-a review. Biometrika 61: 1-15.
  • Radhakrishna CR (1971). Estimation of variance and covariance components-MINQUE theory. J. Mult. Anal. 1: 257-275.
  • Rao CR (1970). Estimation of heteroscedastic variances in linear models. J. Amer. Stat. Assoc. 65: 1611
  • Sebastian P, Schaefer H, Telford IR, Renner SS (2010). Cucumber (Cucumis sativus L.) and melon (C. melo L.) have numerous wild relatives in Asia and Australia, and the sister species of melon is from Australia. Proc. of the Nation. Acad. Sci., USA 107: 14269-14273.
  • Yan W, Kang MS (2002). GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists, CRC.
  • Zalapa JE, Staub JE, McCreight JD (2006). Generation means analysis of plant architectural traits and fruit yield in melon. Plant Breed. 125: 482-487.
  • Zalapa JE, Staub JE, McCreight JD (2008). Variance component analysis of plant architectural traits and fruit yield in melon. Euphytica 162: 129-143.
  • Zhu J (1992). Mixed model approaches for estimating genetic variances and covariances. J. Biomath. 7: 1Zhu J (1993). Mixed model approaches for estimating genetic covariances between two traits with unequal design matrices. J. Biomath. 8: 24-30.
  • Zhu J, Weir BS (1994a). Analysis of cytoplasmic and maternal effects. II. Genetic models for triploid endosperms. Theor. Appl. Genet. 89: 160-166.
  • Zhu J, Weir BS (1994b). Analysis of cytoplasmic and maternal effects I. A genetic model for diploid plant seeds and animals. Theor. Appl. Genet. 89: 153-159.
  • Zhu J, Weir BS (1996). Mixed model approaches for diallel analysis based on a bio-model. Genet. Res. 68: 233-240.
  • Zhu J, Weir BS (1998). Mixed model approaches for genetic analysis of quantitative traits. Proceedings of the International Conference on Mathematical Biology,Singapore, Pp. 321-330.
There are 27 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

R. Mohammadı This is me

H. Dehghanı This is me

G. Karımzadeh This is me

Publication Date March 1, 2014
Published in Issue Year 2014

Cite

APA Mohammadı, R., Dehghanı, H., & Karımzadeh, G. (2014). Genetic Analysis of Yield Components, Early Maturity and Total Soluble Solids in Cantaloupe (Cucumis melo L. subsp. melo var cantalupensis Naudin. Yuzuncu Yıl University Journal of Agricultural Sciences, 24(1), 79-86. https://doi.org/10.29133/yyutbd.235919

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