, Volume 151, Issue 3, pp 311–319 | Cite as

Genetic Combining Ability of Petal Shape in Garden Pansy (Viola × wittrockiana Gams) based on Image Analysis

  • Y. Yoshioka
  • H. Iwata
  • N. Hase
  • S. Matsuura
  • R. Ohsawa
  • S. NinomiyaEmail author
Original Article


Flower appearance is an important target for improvement in garden pansy (Viola × wittrockiana Gams). Flowers of this species consist of three petal types: inferior, lateral, and superior. By means of principal-components (PC) analysis of elliptic Fourier descriptors (EFDs), we estimated the general and specific combining abilities (GCA and SCA) of the floral characteristics of F1 progeny derived from diallel crosses of four inbred lines. The greatest variation in petal shape was explained by the aspect ratio (the first PC) in each petal type. The second or third PC of each petal type was associated with the curvatures of the various parts of the petal. The highly significant GCA effects indicate the importance of additive genetic variance in the transmission of parental petal characteristics to the progeny. The fact that the SCA mean squares were not significant for aspect ratio and petal area indicates that these characteristics of a single-cross progeny can be sufficiently predicted on the basis of GCA. Significant SCA effects were observed in the curvatures of the distal and proximal parts of lateral and superior petals. Correlation analyses indicated several associations between the shape elements of lateral and superior petals, suggesting that genes for these shape elements may be associated, linked, or pleiotropic in the parents used in this study. We successfully demonstrated the use of EFD–PCA to evaluate the petal shape of garden pansy, and of analyzing combining ability and correlations based on the PC scores of EFDs.


Combining ability Elliptic Fourier descriptor Floral variation Heritability Principal component analysis 



Elliptic Fourier descriptor


General combining ability


Petal area


Principal component


Principal-components analysis


Specific combining ability


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Baker RJ (1978) Issues in diallel analysis. Crop Sci 18:533–536CrossRefGoogle Scholar
  2. Du CG, Nelson LR, McDaniel ME (1999) Diallel analysis of gene effects conditioning resistance to Stagonospora nodorum (Berk.) in wheat. Crop Sci 9:686–690CrossRefGoogle Scholar
  3. Freeman H (1974) Computer processing of line drawing images. Comput Surv 6:57–97CrossRefGoogle Scholar
  4. Furuta N, Ninomiya S, Takahashi S, Ohmori H, Ukai Y (1995) Quantitative evaluation of soybean (Glycine max L., Merr.) leaflet shape by principal component scores based on elliptic Fourier descriptor. Breed Sci 45:315–320Google Scholar
  5. Griffing B (1956) Concept of general and specific combining ability in relation to diallel crossing systems. Austral J Biol Sci 9:463–493Google Scholar
  6. Horgan GW (2001) The statistical analysis of plant part appearance–a review. Comput Electron Agric 31:169–190CrossRefGoogle Scholar
  7. Iwata H, Nesumi H, Ninomiya S, Takano Y, Ukai Y (2002) The evaluation of genotype × environment interactions of citrus leaf morphology using image analysis and elliptic Fourier descriptors. Breed Sci 52:243–251CrossRefGoogle Scholar
  8. Iwata H, Niikura S, Matsuura S, Takano Y, Ukai Y (1998) Evaluation of variation of root shape of Japanese radish Raphanussativus L.) based on image analysis using elliptic Fourier descriptors. Euphytica 102:143–149CrossRefGoogle Scholar
  9. Iwata H, Ukai Y (2002) SHAPE: a computer program package for quantitative evaluation of biological shapes based on elliptic Fourier descriptors. J Hered 93:384–385PubMedCrossRefGoogle Scholar
  10. Krahl KH, Randle WM (1999) Genetics of floral longevity in petunia. HortScience 34:339–340Google Scholar
  11. Kuhl FP, Giardina CR (1982) Elliptic Fourier features of a closed contour. Comput Graphics Image Process 18:236–258CrossRefGoogle Scholar
  12. R Development Core Team (2005) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 27 Sept. 2005Google Scholar
  13. Rainey KM, Griffiths PD (2005) Diallel analysis of yield components of snap beans exposed to two temperature stress environments. Euphytica 142:43–53CrossRefGoogle Scholar
  14. Rohlf FJ, Archie JW (1984) A comparison of Fourier methods for the description of wing shape in mosquitoes (Diptera: Culicidae). Syst Zool 33:302–317CrossRefGoogle Scholar
  15. SAS Institute, Inc. (2000) JMP statistics and graphics guide, version 4. SAS Institute, Inc., Cary, NCGoogle Scholar
  16. Van der Meulen-Muisers JJM, van Oeveren JC, Jansen J, van Tuyl JM (1999) Genetic analysis of postharvest flower longevity in Asiatic hybrid lilies. Euphytica 107:149–157CrossRefGoogle Scholar
  17. Yamanaka N, Ninomiya S, Hoshi M, Tsubokura Y, Yano M, Nagamura Y, Sasaki T, Harada K (2001) An informative linkage map of soybean reveals QTLs for flowering time, leaflet morphology and regions of segregation distortion. DNA Res 8:61–72PubMedCrossRefGoogle Scholar
  18. Yoshioka Y, Iwata H, Ohsawa R, Ninomiya S (2004a). Analysis of petal shape variation of Primula sieboldii E. Morren by elliptic Fourier descriptors and principal component analysis. Ann Bot 94:657–664CrossRefGoogle Scholar
  19. Yoshioka Y, Iwata H, Ohsawa R, Ninomiya S (2004b) Quantitative evaluation of flower colour pattern by image analysis and principal component analysis of Primula sieboldii E. Morren. Euphytica 139:179–186CrossRefGoogle Scholar
  20. Yoshioka Y, Iwata H, Ohsawa R, Ninomiya S (2005) Quantitative evaluation of the petal shape variation in Primula sieboldii caused by breeding process in the last 300 years. Heredity 94:657–663PubMedCrossRefGoogle Scholar
  21. Yoshioka Y, Ohsawa R, Iwata H, Ninomiya S, Fukuta N (2006) Quantitative evaluation of petal shape and picotee colour pattern in lisianthus by image analysis. J Am Soc Hort Sci 131:261–266Google Scholar

Copyright information

© Springer Science + Business Media B.V. 2006

Authors and Affiliations

  • Y. Yoshioka
    • 1
  • H. Iwata
    • 2
  • N. Hase
    • 3
  • S. Matsuura
    • 3
  • R. Ohsawa
    • 1
  • S. Ninomiya
    • 4
    • 5
    Email author
  1. 1.Graduate School of Life and Environmental SciencesUniversity of TsukubaTsukubaJapan
  2. 2.Department of Information Science and TechnologyNational Agricultural Research CenterTsukubaJapan
  3. 3.Tohoku Seed CompanyUtsunomiyaJapan
  4. 4.Graduate School of Life and Environmental SciencesUniversity of TsukubaTsukubaJapan
  5. 5.Department of Information Science and TechnologyNational Agricultural Research CenterTsukubaJapan

Personalised recommendations