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Use of Principal Factor Analysis in the Study of Three Stem Termination Types of Soybean by P. J. Bramel; P. N. Hinz; D. E. Green; R. M. Shibles is a Agricultural and Biological Sciences article available to read on EtoBox.
What is Use of Principal Factor Analysis in the Study of Three Stem Termination Types of Soybean about?
The study was conducted to identify plant characters associated with seed yield in close soybean plant spacings . Lines selected from two F 6 soybean populations in the F I p generation segregating for degree of stem termination were grown in two locations . Traits measured included lengths of developmental stage, plant and canopy height, number of nodes, lodging at different stages, raceme lengths, and number of nodes and branch number of nodes . One problem in analyzing data and drawing conclusions from such a study is related to the complex nature of the interrelationships of a large number of traits . Another, not unrelated problem, involves the calculation of multiple-regression equations with multicolinearities . Because of these problems, factor analysis was used to study the correlation matrix to identify sets of variables related to the same biological concept or function . The variables within sets were determined for each stem termination type, and measurements of these variables were standardized . Means were calculated by using the sum of the standardized variables for each set . Multiple regression was used to study the relationships between sets as the independent va
Who reads Use of Principal Factor Analysis in the Study of Three Stem Termination Types of Soybean?
It is typically read by researchers, students, and practitioners in Agricultural and Biological Sciences.
- Author
- P. J. Bramel; P. N. Hinz; D. E. Green; R. M. Shibles
- Publisher
- Springer; Springer-Verlag; Kluwer Academic Publishers; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 0014-2336)
- Published
- 1984
- Language
- EN
- Field
- Agricultural and Biological Sciences (Life Sciences)