Nutrient Cycling in Agroecosystems

, Volume 83, Issue 2, pp 163–178 | Cite as

A conceptual framework for determining economically optimal fertiliser use in oil palm plantations with factorial fertiliser trials

Research Article


The theory, and the statistics and mathematics of using factorial fertiliser trials to assist in making fertiliser recommendations for neighbouring commercial plantings is presented as a conceptual framework and in a format for practical application. As an example, the yield and leaf nutrient levels from a typical factorial fertiliser rate trial (nitrogen by potassium) were modelled using multiple linear regression and the resulting response surfaces used to determine the maximum agronomic yield and optimum economic yield and to calculate the requirement for ‘basal’ fertiliser. Leaf nutrient data in both the trial and commercial plantings was used to estimate the requirement for ‘corrective’ fertiliser, where necessary, to increase the leaf nutrient levels to the target leaf nutrient level for maximum yield. All the mathematics required can be incorporated into a spreadsheet calculator that uses costs (e.g. fertiliser) and prices (e.g. oil) to calculate optimum economic fertiliser application rates. Problems with extrapolating the results of fertiliser trials to commercial plantings can be overcome by matching each trial with a corresponding commercial planting domain.


Fertiliser response Regression models Economic optimum Oil palm Fertiliser nitrogen Fertiliser potassium Application rate 



This research was conducted while the author was employed by Papua New Guinea Oil Palm Research Association. The author wishes to thank Dr Hugh Foster for an introduction to the use of multiple linear regression as a method of analysing factorial trials; and Thomas Fairhurst for critically reviewing and improving the manuscript before submission. The author also wishes to thank staff of the Papua New Guinea Oil Palm Research Association and Milne Bay Estates for conducting and maintaining Trial 504.


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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Davies LaboratoryCSIRO Land and WaterTownsvilleAustralia

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