Merv Probert
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Merv Probert has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Bianca Das
The School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072 Australia
1 shared publication - Birthe Katharina Paul
Tropical Forages Program, International Center for Tropical Agriculture (CIAT), Nairobi, Kenya
1 shared publication - Daniel Rodriguez
Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Gatton campus, Gatton, Queensland, Australia
1 shared publication - Job Kihara
International Center for Tropical Agriculture (CIAT) Nairobi Kenya
1 shared publication - Mario Herrero
Cornell University
1 shared publication - Neil I. Huth
CSIRO, Toowoomba, Australia
1 shared publication
Latest Publications
- Open Access
- 30 December 2019
- Published by MDPI AG in Proceedings
- Vol. 36 (1) , 13
Drivers of Phosphorus Efficiency in Tropical and Subtropical Cropping Systems
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.
- 30 December 2019
- Published by MDPI AG in Proceedings
- Vol. 36 (1) , 13
Open AccessDrivers of Phosphorus Efficiency in Tropical and Subtropical Cropping Systems
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.