Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-23T02:18:20.921Z Has data issue: false hasContentIssue false
  • English
  • Français

Intra-cultivar variation in cotton: response to single-plant yield selection at low density

Published online by Cambridge University Press:  12 August 2010

I. S. TOKATLIDIS ,
C. TSIKRIKONI ,
A. S. LITHOURGIDIS ,
J. T. TSIALTAS  and
C. TZANTARMAS
I. S. TOKATLIDIS*
Affiliation:
Department of Agricultural Development, Democritus University of Thrace, 68200 Orestiada, Greece
C. TSIKRIKONI
Affiliation:
Department of Agricultural Development, Democritus University of Thrace, 68200 Orestiada, Greece
A. S. LITHOURGIDIS
Affiliation:
Department of Agronomy, Aristotle University Farm of Thessaloniki, 57001 Thermi, Greece
J. T. TSIALTAS
Affiliation:
Cotton and Industrial Plants Institute, NAGREF, 57400 Sindos, Greece
C. TZANTARMAS
Affiliation:
Department of Agricultural Development, Democritus University of Thrace, 68200 Orestiada, Greece
*
*To whom all correspondence should be addressed. E-mail: [email protected]; [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

In a 5-year study (2004–2008), the possibility of exploiting intra-cultivar variation in cotton (Gossypium hirsutum L.) was investigated. Honeycomb single-plant selection for seedcotton yield was employed within three cultivars at a low density of 1·15 plants/m2. First- and second-generation progeny lines (1GPLs and 2GPLs) were evaluated for seedcotton yield at low density at three sites, whereas third-generation progeny lines (3GPLs) were tested at the crop density of 10 plants/m2 across two sites and 2 years. Significant differentiation for seedcotton yield was discovered within cultivar (cvar) Christina and cvar Corona at both low and crop densities, and within cvar Flora at low density. In addition, significant intra-cultivar heterogeneity for fibre quality properties was found at crop density. The 1GPLs and 2GPLs grown at low density showed increases in seedcotton yield of 16 and 19%, respectively, in cvar Christina, and of 2·6 and 3·7%, respectively, in cvar Corona. In cvar Flora, the 1GPLs and 2GPLs yielded 10 and 3·3% lower than the mother cultivar, respectively. When grown at standard crop density, across sites and years, 12 and 5·2% higher yield was obtained by the Christina-derived 3GPLs and the Corona-derived 3GPLs, respectively, when compared with the original cultivars. These results provide evidence that elite cultivars are not homogeneous but rather heterogeneous material, within which selections can be made to maintain or improve uniformity and further improve desirable agronomic traits.

Type
Crops and Soils
Information
The Journal of Agricultural Science , Volume 149 , Issue 2 , April 2011 , pp. 197 - 204
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Batzios, D. P. & Roupakias, D. G. (1997). Honey: a microcomputer program for plant selection and analyses of the honeycomb designs. Crop Science 37, 744–747.CrossRefGoogle Scholar
Bolek, Y. (2006). Genetic variation among cotton (Gossypium hirsutum L.) cultivars for mote frequency. Journal of Agricultural Science, Cambridge 144, 327–331.CrossRefGoogle Scholar
Byth, D. E. & Weber, C. R. (1968). Effects of genetic heterogeneity within two soybean populations. I. Variability within environments and stability across environments. Crop Science 8, 44–47.CrossRefGoogle Scholar
Christakis, P. A. & Fasoulas, A. C. (2002). The effects of the genotype by environmental interaction on the fixation of heterosis in tomato. Journal of Agricultural Science, Cambridge 139, 55–60.CrossRefGoogle Scholar
Cullis, C. A. (2005). Mechanisms and control of rapid genomic changes in flax. Annals of Botany 95, 201–206.CrossRefGoogle ScholarPubMed
Dudley, J. W. & Lambert, R. J. (2004). 100 generations of selection for oil and protein in corn. Plant Breeding Reviews 24, 79–110.Google Scholar
Fasoula, D. A. (1990). Correlations between auto-, allo- and nil-competition and their implications in plant breeding. Euphytica 50, 57–62.CrossRefGoogle Scholar
Fasoula, V. A. & Boerma, H. R. (2007). Intra-cultivar variation for seed weight and other agronomic traits within three elite soybean cultivars. Crop Science 47, 367–373.CrossRefGoogle Scholar
Fasoula, D. A. & Fasoula, V. A. (1997). Competitive ability and plant breeding. Plant Breeding Reviews 14, 89–138.Google Scholar
Fasoula, V. A. & Fasoula, D. A. (2002). Principles underlying genetic improvement for high and stable crop yield potential. Field Crops Research 75, 191–209.CrossRefGoogle Scholar
Fasoulas, A. C. (2000). Building up resistance to Verticillium wilt in cotton through honeycomb breeding. In New Frontiers in Cotton Research. Proceedings of the 2nd World Cotton Research Conference, Athens, Greece, 6–12 September 1998 (Ed. Gillham, F. M.), pp. 120–124. Thessaloniki, Greece: P. Petridis Publishers.Google Scholar
Fasoulas, A. C. & Fasoula, V. A. (1995). Honeycomb selection designs. Plant Breeding Reviews 13, 87–139.CrossRefGoogle Scholar
Gethi, J. G., Labate, J. A., Lamkey, K. R., Smith, M. E. & Kresovich, S. (2002). SSR variation in important U.S. maize inbred lines. Crop Science 42, 951–957.CrossRefGoogle Scholar
Grogan, C. O. & Francis, C. A. (1972). Heterosis in inbred source crosses of maize (Zea mays L.). Crop Science 12, 729–730.CrossRefGoogle Scholar
Hao, J. J., Yu, S. X., Dong, Z. D., Fan, S. L., Ma, Q. X., Song, M. Z., & Yu, J. W. (2008). Quantitative inheritance of leaf morphological traits in upland cotton. Journal of Agricultural Science, Cambridge 146, 561–569.CrossRefGoogle Scholar
Laverack, G. K. (1994). Management of breeders seed production. Seed Science and Technology 22, 551–563.Google Scholar
Laverack, G. K. & Turner, M. R. (1995). Roguing seed crops for genetic purity: a review. Plant Varieties and Seeds 8, 29–45.Google Scholar
McClintock, B. (1984). The significance of the responses of the genome to challenge. Science 226, 792–801.CrossRefGoogle ScholarPubMed
Morgante, M., Brunner, S., Pea, G., Fengler, K., Zuccolo, A. & Rafalski, A. (2 005). Gene duplication and exon shuffling by helitron-like transposons generate intraspecies diversity in maize. Nature Genetics 37, 997–1002.CrossRefGoogle Scholar
Olufowote, J. O., Xu, Y., Chen, X., Park, W. D., Beachell, H. M., Dilday, R. H., Goto, M. & McCouch, S. R. (1997). Comparative evaluation of within-cultivar variation of rice (Oryza sativa L.) using microsatellite and RFLP markers. Genome 40, 370–378.CrossRefGoogle ScholarPubMed
Parlevliet, J. E. (2007). How to maintain improved cultivars. Euphytica 153, 353–362.CrossRefGoogle Scholar
Peng, S., Cassman, K. G., Virmani, S. S., Sheehy, J. & Khush, G. S. (1999). Yield potential trends of tropical rice since the release of IR8 and the challenge of increasing rice yield potential. Crop Science 39, 1552–1559.CrossRefGoogle Scholar
Rasmusson, D. C. & Phillips, R. L. (1997). Plant breeding progress and genetic diversity from de novo variation and elevated epistasis. Crop Science 37, 303–310.CrossRefGoogle Scholar
Saranga, Y., Jiang, C. -X., Wright, R. J., Yakir, D. & Paterson, A. H. (2004). Genetic dissection of cotton physiological responses to arid conditions and their inter-relationships with productivity. Plant, Cell and Environment 27, 263–277.CrossRefGoogle Scholar
Sprague, G. F., Russell, W. A. & Penny, L. H. (1960). Mutations affecting quantitative traits in the selfed progeny of doubled monoploid maize stocks. Genetics 45, 855–866.CrossRefGoogle ScholarPubMed
Tokatlidis, I. S. (2000). Variation within maize lines and hybrids in the absence of competition and relation between hybrid potential yield per plant with line traits. Journal of Agricultural Science, Cambridge 134, 391–398.CrossRefGoogle Scholar
Tokatlidis, I. S., Xynias, I. N., Tsialtas, J. T. & Papadopoulos, I. I. (2006). Single-plant selection at ultra-low density to improve stability of a bread wheat cultivar. Crop Science 46, 90–97.CrossRefGoogle Scholar
Tokatlidis, I. S., Tsikrikoni, C., Tsialtas, J. T., Lithourgidis, A. S. & Bebeli, P. J. (2008). Variability within cotton cultivars for yield, fibre quality and physiological traits. Journal of Agricultural Science, Cambridge 146, 483–490.CrossRefGoogle Scholar
Tokatlidis, I. S., Has, V., Mylonas, I., Has, I., Evgenidis, G., Melidis, V., Copandean, A. & Ninou, E. (2010). Density effects on environmental variance and expected response to selection in maize (Zea mays L.). Euphytica 174, 283–291.CrossRefGoogle Scholar
Tsialtas, J. T., Tokatlidis, I. S., Tsikrikoni, C. & Lithourgidis, A. S. (2008). Leaf carbon isotope discrimination, ash content and K relationships with seedcotton yield and lint quality in lines of Gossypium hirsutum L. Field Crops Research 107, 70–77.CrossRefGoogle Scholar
Xanthopoulos, F. P. & Kechagia, U. E. (2000). Natural crossing in cotton (Gossypium hirsutum L.). Australian Journal of Agricultural Research 51, 979–983.CrossRefGoogle Scholar
Zhang, Y. X., Gentzbittel, L., Vear, F. & Nicolas, P. (1995). Assessment of inter- and intra-inbred line variability in sunflower (Helianthus annuus) by RFLPs. Genome 38, 1040–1048.CrossRefGoogle ScholarPubMed