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Proceedings
  • Abstract
  • Open Access

30 December 2019

Drivers of Phosphorus Efficiency in Tropical and Subtropical Cropping Systems †

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1
The School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072 Australia
2
Commonwealth Scientific Industrial Research Organisation (CSIRO), 306 Carmody Road, Brisbane, QLD 4067, Australia
3
International Centre for Tropical Agriculture (CIAT), ICIPE Duduville Campus, Kasarani 00621, Nairobi, Kenya
4
Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Brisbane, QLD 4072, Australia
This article belongs to the Proceedings The Third International Tropical Agriculture Conference (TROPAG 2019)

Abstract

Phosphorus (P) is an essential nutrient but is commonly limiting for food production in tropical and subtropical maize cropping. The efficiency of P fertiliser uptake is often low (5–30%) for various site-specific reasons and so identifying the drivers of P efficiency for different systems is important. We conducted a sensitivity analysis on the parameters of a well-established cropping systems model (APSIM) for a wide range of soil, crop and management factors to understand their influence on yield. The analysis was conducted for two contrasting maize cropping systems: (a) a high-input, large-scale commercial system in subtropical Queensland, Australia and (b) a low-input, small-holder system in tropical, western Kenya. In Queensland, yield was most sensitive to available P and mineral N supply, and the sensitivity of both increased with in-crop rainfall. Available P was also the most important parameter in Western Kenya, but N supply had much weaker influence due to higher levels of organic matter. Parameters controlling P sorption were more important than other soil parameters at both sites irrespective of seasonal conditions. In conclusion, these results suggest that efforts to improve efficiency of P use by plants need to account for interactions between water and N supply in environments where these are limiting. They also highlight a potential constraint to modelling of these systems as some of the most influential parameters are difficult to measure directly.

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