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The Component Analysis Approach to the Interpretation of Plant Analysis Data from Groundnuts and Sugar Cane

Published online by Cambridge University Press:  03 October 2008

D. A. Holland
D. A. Holland
Affiliation:
East Mailing Research Station, Kent, England
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Summary

Component analysis was applied to the interpretation of (a) leaf analyses from six similar groundnut fertilizer trials, and (b) the chemical composition of different parts (root, stem and successive leaves) of the sugar cane plant. For each of the groundnut trials it was found that approximately 60 per cent of the total variation in N, P, K, and Ca could be accounted for by two independent linear functions of the elements, representing the balance of N and K with Ca and the balance of N with P and K. The second of these functions was consistently affected by phosphorus applications. Yield was related to one or other function, according to trial, but never to them both. Throughout the sugar cane plant the elements N, P, K, Ca, and Mg were found to be distributed between the roots and the aerial parts, and between active photosynthetic and non-photosynthetic tissues. In both cases the result was a reasonable and consistent simplification of a considerable body of data, such as had not resulted from a series of univariate analyses of variance.

Type
Research Article
Information
Experimental Agriculture , Volume 4 , Issue 2 , April 1968 , pp. 179 - 185
Copyright
Copyright © Cambridge University Press 1968

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References

REFERENCES

Beaufils, E. R. (1956). Annales agron. 7, 205.Google Scholar
Holland, D. A. (1966). J. hort. Sci. 41, 311.CrossRefGoogle Scholar
Holland, D. A. (1967a). Oléagineaux 22, 307.Google Scholar
Holland, D. A. (1967b). (In preparation).Google Scholar
Kendall, M. G. (1957). A Course in Multivariate Analysis. London: Charles Griffin.Google Scholar
Lagatu, H. & Maume, L. (1926). Comp. Rend. Acad. Sc. 182, 653.Google Scholar
Moore, C. S. (1965). J. hort. Sci. 40, 133.CrossRefGoogle Scholar
Pearce, S. C. (1959). Rep. E. Mailing Res. Stn for 1958 73.Google Scholar
Pearce, S. C. & Holland, D. A. (1960). Appl. Statist. 9, 1.CrossRefGoogle Scholar
Pearce, S. C. & Holland, D. A. (1961). Biométrie-Praximétrie 2, 159.Google Scholar
Prévot, P. & Ollagnier, M. (1953). Oléagineux 8, 843.Google Scholar
Prévot, P. & Ollagnier, M. (1954). Plant Physiol. 29, 26.CrossRefGoogle Scholar
Prévot, P. & Ollagnier, M. (1955). Rep. XIVth Int. hort. Congr. 1382.Google Scholar
Prévot, P. & Ollagnier, M. (1961). Publ. Am. Inst. Biol. Sci. 8, 257.Google Scholar
Prévot, P. & Ollagnier, M. (1963). World Crops 15, 312.Google Scholar
Thomas, W. (1937). Plant Physiol. 12, 571.CrossRefGoogle Scholar
Thomas, W. (1938). Proc. Am. Soc. hort. Sci. 35, 269.Google Scholar