| 000 | 03243nab a22003257a 4500 | ||
|---|---|---|---|
| 999 |
_c59101 _d59093 |
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| 001 | 59101 | ||
| 003 | MX-TxCIM | ||
| 005 | 20250808020847.0 | ||
| 008 | 180124b2017 ne |||p| p||| 00| 0 eng d | ||
| 024 | 8 | _ahttps://doi.org/10.1016/j.agrformet.2017.08.023 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 1 |
_96746 _aSeyoum, S. |
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| 245 | 1 | 0 | _aCharacterising production environments for maize in eastern and southern Africa using the APSIM Model |
| 260 |
_aAmsterdam, Netherlands : _bElsevier, _c2017. |
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| 500 | _aPeer review | ||
| 520 | _aMaize 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. | ||
| 526 |
_aMCRP _bFP3 |
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| 546 | _aText in English | ||
| 650 | 7 |
_aMaize _gAGROVOC _2 _91173 |
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| 650 | 7 |
_aCropping systems _gAGROVOC _2 _91068 |
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| 651 | 7 |
_91954 _aSouthern Africa _2AGROVOC |
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| 700 | 1 |
_96747 _aChauhan, Y. |
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| 700 | 1 |
_96748 _aRachaputi, R. |
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| 700 | 1 |
_96749 _aFekybelu, S. |
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| 700 | 1 |
_aPrasanna, B.M. _gGlobal Maize Program _gBorlaug Institute for South Asia _8INT3057 _9887 |
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| 773 | 0 |
_gv. 247, p. 445-453 _tAgricultural and Forest Meteorology _wu444454 |
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| 856 | 4 |
_yAccess only for CIMMYT Staff _uhttp://libcatalog.cimmyt.org/Download/cis/59101.pdf |
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| 942 |
_2ddc _cJA _n0 |
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