Utility of multivariate analyses in examining foliage composition and soil nutrition in a factorial fertilizer experiment

Abstract

The data for this paper were derived from a previously reported field trial with Pinus radiata which was treated with fertilizer at planting and three subsequent occasions. The experiment tested factorial combinations of urea (n), dicalcium phosphate (p), gypsum (s) and potassium chloride plus trace elements (b).

At 5 years-of-age bole development was substantially increased by p alone, but p and n in combination increased growth further still. Urea, applied alone, had no, or retardive effects. Foliage concentrations of N, P, K, Ca, Mg, Fe and Mn were raised by p or n and p in combination, but Zn concentrations were not changed. Urea alone caused significantly lower Fe, Mg, Ca, and K concentrations in foliage.

The 16 fertilizer combinations created a series of diverse soil nutrient conditions. For the ameliorative treatments (p and np), soils were characterized by high levels of total P and N, and exchangeable NH ⁺₄ and Ca ²⁺ whereas soils treated with n alone had low levels of the cations Mg²⁺, Ca²⁺, and Na⁺, but higher A1³⁺. While not contributing to stem growth, the s and b treatments also formed unique soil nutrient concentrations; s induced appreciable increases in Ca²⁺ while b resulted in a 3.5-fold increase in K⁺.

Multivariate statistical analyses aided examination of the experimental data, whereas univariate analyses became cumbersome or repetitive, or gave no insight into individual contributions to overall variation. Eigenvalues extracted from discriminant analyses did provide this information, and ranked effects in order of importance. The effects of urea fertilizer on concentration of a number of elements in the foliage and on soil nutrient status were small but had marked effects on growth. It is envisaged that multivariate techniques can be utilized with other trial data, provided such experiments are soundly designed and adequately replicated.