Multivariate distinguishing of phenotypically similar groups of genotypes in a winter wheat (Triticum aestivum L.) working germplasm collection
Joanna Ukalska
joanna_ukalska@sggw.edu.plZakład Biometrii, Katedra Ekonometrii i Statystyki, Szkoła Główna Gospodarstwa Wiejskiego (Poland)
Krzysztof Ukalski
Zakład Biometrii, Katedra Ekonometrii i Statystyki, Szkoła Główna Gospodarstwa Wiejskiego (Poland)
Tadeusz Śmiałowski
Zakład Roślin Zbożowych, Instytut Hodowli i Aklimatyzacji Roślin w Krakowie (Poland)
Abstract
The investigations were conducted on part of winter wheat working collection from the Plant Breeding and Acclimatization Institute, the Department of Cereals Crops in Cracow. Fifty-one genotypes (cultivars and clones) were evaluated in the years 1999–2002. Yield structure traits and susceptibility to the most important winter wheat diseases were assessed. The aim of the study was to classify the genotypes into homogeneous groups (clusters), identify the traits having the highest discriminative power in separating these groups, and characterize the genotypic diversity of the distinguished clusters for the examined traits. Hierarchical cluster analysis was carried out using Ward’s procedure and squared Euclidean distance. The final number of groups (clusters) was obtained on the basis of the pseudo t2 statistic which indicating a possibility to classify the genotypes in 3, 5 or 8 groups. For each division the MANOVA and Canonical Variable Analysis (CVA) were carried out on the basis of Mahalanobis distance. Finally, the genotypes were classified into five homogeneous groups, which including 4 to 22 objects. The three first canonical variables accounted for 82% of the total variation between groups. The following traits were found to have the highest discriminative power: plant height, lodging score, 1000-grain weight, weight per spike, number of grains per spike, number of days to heading, powdery mildew score and protein content.
Keywords:
Triticum aestivum L., canonical variable analysis, cluster analysis, germplasm collection, multivariate analysis of variance, phenotypic diversityReferences
Caliński T., Harabasz J. 1974. A dendrite method for cluster analysis. Comm. Stat. 3: 1 — 27.
Google Scholar
Cooper M., Woodruff D. R., Phillips I. G., Basford K. E., Gilmour A. R. 2001. Genotype-by-management interactions for grain yield and grain protein concentration of wheat. Field Crops Research 69: 47 — 67.
Google Scholar
Crossa J., Bellon M. R., Franco J. 2002. Quantitative method for classifying farmers using socioeconomic variables In: Quantitative analysis of data from participatory methods in plant breeding. Bellon M. R., Reeves J. (Eds), CIMMYT, Mexico: 113 — 127.
Google Scholar
Crossa J., Franco J. 2004. Statistical methods for classifying genotypes. Euphytica 137: 19 — 37.
Google Scholar
Duda, R. O., Hart P. E. 1973. Pattern classification and science analysis, New York: John Wiley & Sons, Inc.
Google Scholar
Harch B. D., Basford K. E., DeLacy I. H., Lawrence P. K. 1997. The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection I. Two-way quantitative data. Euphytica 95: 27 — 38.
Google Scholar
Khattree R., Naik D. N. 2000. Multivariate data reduction and discrimination with SAS software. SAS Institute Inc., Cary, NC.
Google Scholar
Krzanowski W. J. 1988. Principles of multivariate analysis: a users perspective. Oxford Univ. Press, Oxford: 563 pp.
Google Scholar
Mazurkiewicz B., Struś M. 1997. Kolekcje pszenicy ozimej jako czynnik postępu hodowlanego. Biul. IHAR 204: 81 — 97.
Google Scholar
Mohammadi S. A., Prasanna M. 2003. Analysis of genetic diversity in crop plants -salient statistical tools and considerations. Crop Sci. 43: 1235 — 1248.
Google Scholar
Sarle W. S. 1983. Cubic Clustering Criterion, SAS Technical Report A-108, Cary, NC: SAS Institute Inc.
Google Scholar
SAS/STAT User's Guide, Version 8.2. 2002. SAS Institute, Cary, NC.
Google Scholar
Searle S. R. 1987. Linear models for unbalanced data. J. Wiley & Sons, New York.
Google Scholar
Śmiałowski T. 2005. Ocena rodów pszenicy ozimej z polskiej hodowli w doświadczeniach przedrejestrowych w roku 2004. Biul. IHAR 235: 13 — 22.
Google Scholar
Ukalski K., Ukalska J., Śmiałowski T., Mądry W. 2008. Badanie zmienności i współzależności cech użytkowych w kolekcji roboczej pszenicy ozimej (Triticum aestivum L.) za pomocą metod wielowymiarowych. Część I. Korelacje fenotypowe i genotypowe. Biul. IHAR 249: 35 — 43.
Google Scholar
Ukalska J., Ukalski K., Śmiałowski T., Mądry W. 2008. Badanie zmienności i współzależności cech użytkowych w kolekcji roboczej pszenicy ozimej (Triticum aestivum L.) za pomocą metod wielowymiarowych. Część II. Analiza składowych głównych na podstawie macierzy korelacji fenotypowych i genotypowych. Biul. IHAR 249: 45 — 57.
Google Scholar
Ward J. H. jr. 1963. Hierarchical grouping to optimize an objective function. J. Am. Statist. Assoc. 58: 236 — 244.
Google Scholar
Węgrzyn S. 1988. Ocena postępu hodowlanego pszenicy ozimej na podstawie wyników doświadczeń hodowlanych. Prace badawcze grupy problemowej. IHAR, Radzików: 15 — 28.
Google Scholar
Węgrzyn S., Mazurkiewicz B., Kuc I. 1992. Zmienność wybranych cech w kolekcji pszenicy ozimej. Biul. IHAR 181/182: 23 — 30.
Google Scholar
Wojas T., Węgrzyn S., Śmiałowski T. 2001. Uwarunkowania genetyczne oraz współzależność plonu i wybranych cech użytkowych pszenicy ozimej (Triticum aestivum L.) Biul. IHAR 218/219: 39 — 48.
Google Scholar
Authors
Joanna Ukalskajoanna_ukalska@sggw.edu.pl
Zakład Biometrii, Katedra Ekonometrii i Statystyki, Szkoła Główna Gospodarstwa Wiejskiego Poland
Authors
Krzysztof UkalskiZakład Biometrii, Katedra Ekonometrii i Statystyki, Szkoła Główna Gospodarstwa Wiejskiego Poland
Authors
Tadeusz ŚmiałowskiZakład Roślin Zbożowych, Instytut Hodowli i Aklimatyzacji Roślin w Krakowie Poland
Statistics
Abstract views: 29PDF downloads: 38
License
Copyright (c) 2009 Joanna Ukalska, Krzysztof Ukalski, Tadeusz Śmiałowski
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Upon submitting the article, the Authors grant the Publisher a non-exclusive and free license to use the article for an indefinite period of time throughout the world in the following fields of use:
- Production and reproduction of copies of the article using a specific technique, including printing and digital technology.
- Placing on the market, lending or renting the original or copies of the article.
- Public performance, exhibition, display, reproduction, broadcasting and re-broadcasting, as well as making the article publicly available in such a way that everyone can access it at a place and time of their choice.
- Including the article in a collective work.
- Uploading an article in electronic form to electronic platforms or otherwise introducing an article in electronic form to the Internet or other network.
- Dissemination of the article in electronic form on the Internet or other network, in collective work as well as independently.
- Making the article available in an electronic version in such a way that everyone can access it at a place and time of their choice, in particular via the Internet.
Authors by sending a request for publication:
- They consent to the publication of the article in the journal,
- They agree to give the publication a DOI (Digital Object Identifier),
- They undertake to comply with the publishing house's code of ethics in accordance with the guidelines of the Committee on Publication Ethics (COPE), (http://ihar.edu.pl/biblioteka_i_wydawnictwa.php),
- They consent to the articles being made available in electronic form under the CC BY-SA 4.0 license, in open access,
- They agree to send article metadata to commercial and non-commercial journal indexing databases.
