Modeling climate warming impacts on grain and forage sorghum yields in Argentina

Sorghum is the world’s fifth major cereal in terms of production and acreage. It is expected that its growth will be affected by the increase in air temperature, an important component of global climate change. Our objective was to use the Agricultural Land Management Alternatives with Numerical Ass...

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Otros Autores: Druille, Magdalena, Williams, Amber S., Torrecillas, Marcelo, Kim, Sumin, Meki, Norman, Kiniry, James R.
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Lenguaje:Inglés
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Acceso en línea:http://ri.agro.uba.ar/files/download/articulo/2020druille.pdf
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245 1 0 |a Modeling climate warming impacts on grain and forage sorghum yields in Argentina 
520 |a Sorghum is the world’s fifth major cereal in terms of production and acreage. It is expected that its growth will be affected by the increase in air temperature, an important component of global climate change. Our objective was to use the Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) model to (a) evaluate the impact of climate warming on forage and grain sorghum production in Argentina and (b) to analyze to what extent yield changes were associated with changes in water or nitrogen stress days. For model calibration, we used previous information related to the morpho-physiological characteristics of both sorghum types and several soil parameters. We then used multiyear field data of sorghum yields for model validation. Yield simulations were conducted under three possible climate change scenarios: 1, 2, and 4 °C increase in mean annual temperature. ALMANAC successfully simulated mean yields of forage and grain sorghum: root mean square error (RMSE): 2.6 and 1.0 Mg ha−1, respectively. Forage yield increased 0.53 Mg ha−1, and grain yield decreased 0.27 Mg ha−1 for each degree of increase in mean annual temperature. Yields of forage sorghum tended to be negatively associated with nitrogen stress (r = −0.94), while grain sorghum yield was negatively associated with water stress (r = −0.99). The information generated allows anticipating future changes in crop management and genetic improvement programs in order to reduce the yield vulnerability. 
650 |2 Agrovoc  |9 26 
653 |a PLANT GROWTH 
653 |a NITROGEN STRESS 
653 |a WATER STRESS 
653 |a CLIMATE CHANGE 
700 1 |9 29196  |a Druille, Magdalena  |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Forrajicultura. Buenos Aires, Argentina. 
700 1 |a Williams, Amber S.  |u U.S. Department of Agriculture - Agricultural Research Service (USDA-ARS), Grassland, Soil and Water Research Laboratory, Temple, USA.  |9 73129 
700 1 |a Torrecillas, Marcelo  |u Universidad Nacional de Lomas de Zamora. Facultad de Ciencias Agrarias, Lavallol, Buenos Aires, Argentina.  |9 73130 
700 1 |a Kim, Sumin  |u Oak Ridge Institute for Science and Education, Temple, USA.  |9 73131 
700 1 |a Meki, Norman  |u Texas AgriLife Research, Blackland Research and Extension Center. Temple, USA.  |9 73132 
700 1 |a Kiniry, James R.  |u U.S. Department of Agriculture - Agricultural Research Service (USDA-ARS), Grassland, Soil and Water Research Laboratory, Temple, USA.  |9 73133 
773 0 |t Agronomy  |g Vol.10, no.7 (2020). art.964, 13 p., grafs. 
856 |f 2020druille  |i En Internet  |q application/pdf  |u http://ri.agro.uba.ar/files/download/articulo/2020druille.pdf  |x ARTI202112 
856 |u https://www.mdpi.com/journal/agronomy  |z LINK AL EDITOR 
942 |c ARTICULO 
942 |c ENLINEA 
976 |a AAG