Temperature, Sowing and Harvest Dates, and Yield Potential of Maize in the Southwestern US

Myoung, Boksoon; Kim, Seung Hee; Stack, D.; Kim, Jin-Won; Kafatos, Menas

doi:10.1016/j.proenv.2015.07.207

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“…The planting date of maize was sensitive to climate change and variability. The effect of planting date on maize yields under various temperature regimes in the SWUS was studied by Myoung et al (2015). The study findings showed that maize planted earlier would give higher yield due to the length of the growing season in cold mountainous regions.…”

Section: Impact Of Climate Change On Maize Yield Using Dssat Ceres-mamentioning

confidence: 99%

“…The study findings showed that maize planted earlier would give higher yield due to the length of the growing season in cold mountainous regions. In mountainous regions, there are warmer than normal conditions during the planting period, and this tended to advance the planting date which resulted in increased maize yield (Myoung et al, 2015). Furthermore, in warmer low laying altitudes, yields were less correlated with dates of planting.…”

Section: Impact Of Climate Change On Maize Yield Using Dssat Ceres-mamentioning

confidence: 99%

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Climate change impact on maize (Zea mays L.) yield using crop simulation and statistical downscaling models: A review

Chisanga¹,

Phiri²,

Chinene³

2017

Sci. Res. Essays

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Review of literature related to the impact of climate change on maize (Zea mays L.) yield using Global Climate Models (GCMs), statistical downscaling, and crop simulation (APSIM-maize-and-CERES-maize models) models are discussed. GCMs can simulate the current and future climatic scenarios. Crop yield projections using crop models require climate inputs at higher spatial resolution than that provided by GCMs. The computationally inexpensive statistical downscaling technique is widely used for this translation. Studies on regional climate modeling have mostly focused on Southern Africa and West Africa, with very few studies in Zambia. Additionally, the integrated use of climate and crop models have received relatively less attention in Africa compared to other parts of the world. Conversely, the AgMIP protocols have been implemented in Sub-Saharan Africa (SSA) (Ethiopia, Kenya, Tanzania, Uganda and South Africa) and South Asia (SA) (Sri Lanka). In Zambia, however, the protocols have not been applied at either regional or local scale. Applying crop and statistical downscaling models requires calibration and validation, and these are crucial for correct climate and crop simulation. The review shows that although uncertainties exist in the design of models, and parameters, soil, climate and management options, the climate would adversely affect maize yield production in SSA. The potential effect of climate change on maize production can be studied using crop models such as agricultural production simulator (APSIM) and decision support system for agrotechnology (DSSAT) models. There is need to use integrated assessment modeling to study future climate impact on maize yield. The assessment is essential for long-term planning in food security and in developing adaptation and mitigation strategies in the face of climate variability and change.

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Section: Impact Of Climate Change On Maize Yield Using Dssat Ceres-mamentioning

confidence: 99%

Section: Impact Of Climate Change On Maize Yield Using Dssat Ceres-mamentioning

confidence: 99%

Climate change impact on maize (Zea mays L.) yield using crop simulation and statistical downscaling models: A review

Chisanga¹,

Phiri²,

Chinene³

2017

Sci. Res. Essays

View full text Add to dashboard Cite

show abstract

Temperature, Sowing and Harvest Dates, and Yield Potential of Maize in the Southwestern US

Cited by 1 publication

References 0 publications

Climate change impact on maize (Zea mays L.) yield using crop simulation and statistical downscaling models: A review

Climate change impact on maize (Zea mays L.) yield using crop simulation and statistical downscaling models: A review

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