| 000 | 03447nab|a22004097a|4500 | ||
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| 001 | 69514 | ||
| 003 | MX-TxCIM | ||
| 005 | 20251215135521.0 | ||
| 008 | 2511112025|||||ne ||p|op||||00||0|eng|dd | ||
| 024 | 8 | _ahttp://dx.doi.org/10.2139/ssrn.5345569 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 1 |
_aNdegwa, M.K. _8001713077 _gSustainable Agrifood Systems _91681 |
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| 245 | 1 | 0 | _aIs newer better? The effect of varietal age on real-world maize yield in Kenya |
| 260 |
_aNetherlands : _bElsevier, _c2025. |
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| 500 | _aPreprint | ||
| 500 | _aOpen Access | ||
| 520 | _aMaize varietal turnover is widely promoted across Sub-Saharan Africa to improve crop productivity and increase food security, yet its impact on yields remains poorly understood amid heterogeneous agroecological and socioeconomic conditions. This study quantifies the yield effects of varietal age in Kenya using a three-wave panel survey (2023-2024) of 4,160 smallholder households across Kenya. Using entropy balancing and weighted regression models to isolate the effect of varietal age on maize yield, we find a strong and consistent relationship between varietal age and yield. New varieties yield 147 kg/ha more than old ones in the long rains and 91 kg/ha more in the short rains. Finer age categorization reveals that switching to ultra-new varieties (0-5 years) delivers the highest gains-360 kg/ha over ultra-old varieties (21+ years) in the long rains and 269 kg/ha in the short rains. These findings suggest that slow varietal turnover carries significant opportunity costs in the form of forgone yield gains. While farmers generally perceive new varieties favorably-particularly for yield potential, early maturity and grain quality-concerns around labor intensity and resilience remain, potentially dampening adoption. Providing farmers with clear, locally relevant performance data and opportunities for on-farm experimentation can help shift perceptions and support wider uptake. Policies and programs that expand access to newer, better-performing varieties and strengthen seed quality assurance are essential for translating genetic gains into productivity improvements across Kenya's bimodal maize | ||
| 546 | _aText in English | ||
| 591 | _aNyangau, P.N. : No CIMMYT Affiliation | ||
| 597 |
_aClimate adaptation & mitigation _aNutrition, health & food security _aPoverty reduction, livelihoods & jobs _bMarket Intelligence _bSeed Equal _cResilient Agrifood Systems _cGenetic Innovation _dBill & Melinda Gates Foundation (BMGF) _uhttps://hdl.handle.net/10568/178118 _fBreeding for Tomorrow |
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| 650 | 7 |
_aEntropy _2AGROVOC _940511 |
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| 650 | 7 |
_aSmallholders _2AGROVOC _91763 |
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| 650 | 7 |
_aMaize _2AGROVOC _91173 |
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| 650 | 7 |
_aYield gap _2AGROVOC _91356 |
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| 650 | 7 |
_aSenses _2AGROVOC _938065 |
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| 650 | 7 |
_aFertilizers _2AGROVOC _91111 |
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| 651 | 7 |
_aKenya _2AGROVOC _93783 |
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| 700 | 1 |
_8001715648 _aNyangau, P.N. _gSustainable Agrifood Systems _938256 |
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| 700 | 1 |
_aKariuki, S.W. _8N1706368 _gIntegrated Development Program _gSustainable Agrifood Systems _96403 |
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| 700 | 1 |
_aDebello, M.J. _gSustainable Agrifood Systems _8INT3210 _9903 |
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| 700 | 1 |
_aMichelson, H.C. _931389 |
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| 700 | 1 |
_aCairns, J.E. _gGlobal Maize Program _8INT2948 _9879 |
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| 773 | 0 |
_tSocial Science Research Network (SSRN) _gIn press _dNetherlands : Elsevier, 2025 |
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| 856 | 4 |
_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/36067 |
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| 942 |
_cJA _n0 _2ddc |
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_c69514 _d69506 |
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