Combined analysis of categorical and numerical descriptors of Australian groundnut accessions using nonlinear principal component analysis

Kroonenberg, P.M., Harch, B.D., Basford, K.E., & Cruickshank, A. (1997) Combined analysis of categorical and numerical descriptors of Australian groundnut accessions using nonlinear principal component analysis. Journal of Agricultural, Biological and Environmental statistics, 2(3), pp. 294-312.

View at publisher (open access)

Abstract

For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

Impact and interest:

8 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 72779
Item Type: Journal Article
Refereed: Yes
Additional Information: Cited By (since 1996):7
Export Date: 26 May 2014
Source: Scopus
Additional URLs:
Keywords: Arachis hypogaea L., Genetic diversity, Mixture of data types, Oleic-linoleic ratio, Ordinal data, Ordination
ISSN: 1085-7117
Divisions: Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 12 Jun 2014 23:39
Last Modified: 08 Jun 2015 23:03

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page