Characterising production environments for maize in eastern and southern Africa using the APSIM Model

Seyoum, Solomon, Chauhan, Yash, Rachaputi, Rao, Fekybelu, Solomon and Prasanna, Boddupalli (2017) Characterising production environments for maize in eastern and southern Africa using the APSIM Model. Agricultural and Forest Meteorology, 247 445-453. doi:10.1016/j.agrformet.2017.08.023


Author Seyoum, Solomon
Chauhan, Yash
Rachaputi, Rao
Fekybelu, Solomon
Prasanna, Boddupalli
Title Characterising production environments for maize in eastern and southern Africa using the APSIM Model
Journal name Agricultural and Forest Meteorology   Check publisher's open access policy
ISSN 0168-1923
1873-2240
Publication date 2017-12-15
Year available 2017
Sub-type Article (original research)
DOI 10.1016/j.agrformet.2017.08.023
Open Access Status Not yet assessed
Volume 247
Start page 445
End page 453
Total pages 9
Place of publication Amsterdam, The Netherlands
Publisher Elsevier
Language eng
Subject 1107 Forestry
2306 Global and Planetary Change
1102 Agronomy and Crop Science
1902 Atmospheric Science
Abstract Maize is a staple food crop in eastern and southern Africa with significant contribution for food security of this vast region. Efforts to breed superior maize cultivars for the region are challenged by high genotype x environment interactions arising mainly due to variable soil moisture supply caused by high temporal and spatial variability in rainfall. Information on major drought patterns and their frequencies, which can assist in dealing with such interactions in the region, however, is not available. The objectives of this study were therefore to (i) identify major drought patterns and their frequencies, (ii) identify iso-environments based on the similarity of drought patterns and (iii) explore scope for yield improvement through optimising genotype and management in various drought patterns. We used the well validated APSIM model to characterise major drought patterns and their frequencies experienced by maize cropping systems in the target population of environments spread across six countries of the region including Ethiopia, Kenya, Tanzania, Malawi, Mozambique and Zimbabwe. The data-base used for the model simulations consisted of 35 locations, 17–86 years of daily climate records and three cultivars. The dynamic changes in water supply-demand ratio in each season was simulated against the thermal time for each cultivar across the 35 locations and clustering analysis was used to cluster the major drought patterns. The analysis identified four major drought patterns characterised by low-stress, mid-season drought, late terminal drought and early-terminal drought patterns, occurring at 46%, 11%, 22% and 21% of the years, respectively. The frequencies of these patterns varied in relation to locations, genotypes and management. Yield reduction of up to 80% was observed for early terminal drought compared with low-stress drought pattern. There was significant scope for yield improvement through manipulating genotype and management. These results have important implications for germplasm enhancement and deployment over similar environments in the region.
Keyword APSIM
Drought pattern
Eastern and southern Africa
Environmental characterization
Zea mays L.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Alliance for Agriculture and Food Innovation
 
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Created: Fri, 10 Nov 2017, 09:03:41 EST