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Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Cerrados. |
Data corrente: |
25/02/2022 |
Data da última atualização: |
25/02/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
KOTHARI, K.; BATTISTI, R.; BOOTE, K. J.; ARCHONTOULIS, S. V.; CONFALONE, A.; CONSTANTIN, J.; CUADRA, S. V.; DEBAEKE, P.; FAYE, B.; GRANT, B.; HOOGENBOOM, G.; JING, Q.; VAN DER LAAN, M.; SILVA, F. A. M. da; MARIN, F. R.; NEHBANDANI, A.; NENDEL, C.; PURCELL, L. C.; QIAN, B.; RUANE, A. C.; SCHOVING, C.; SILVA, E. H. F. M.; SMITH, W.; SOLTANI, A.; SRIVASTAVA, A.; VIEIRA JÚNIOR, N. A.; SLONE, S.; SALMERÓN, M. |
Afiliação: |
KRITIKA KOTHARI, UNIVERSITY OF KENTUCKY; RAFAEL BATTISTI, UFG; KENNETH J. BOOTE, UNIVERSITY OF FLORIDA; SOTIRIOS V. ARCHONTOULIS, IOWA STATE UNIVERSITY; ADRIANA CONFALONE, UNIVERSIDAD NACIONAL DEL CENTRO DE LA PROVINCIA DE BUENOS AIRES; JULIE CONSTANTIN, UNIVERSITÉ DE TOULOUSE; SANTIAGO VIANNA CUADRA, CNPTIA; PHILIPPE DEBAEKE, UNIVERSITÉ DE TOULOUSE; BABACAR FAYE, INSTITUT DE RECHERCHE POUR LE D ́EVELOPPEMENT (IRD) ESPACE-DEV; BRIAN GRANT, AGRICULTURE AND AGRI-FOOD CANADA; GERRIT HOOGENBOOM, UNIVERSITY OF FLORIDA; QI JING, AGRICULTURE AND AGRI-FOOD CANADA; MICHAEL VAN DER LAAN, UNIVERSITY OF PRETORIA; FERNANDO ANTONIO MACENA DA SILVA, CPAC; FÁBIO RICARDO MARIN, ESALQ/USP; ALIREZA NEHBANDANI, GORGAN UNIVERSITY OF AGRICULTURAL SCIENCES AND NATURAL RESOURCE; CLAAS NENDEL, University of PotsdaM, Leibniz Centre for Agricultural Landscape ResearcH; LARRY C. PURCELL, UNIVERSITY OF ARKANSAS; BUDONG QIAN, AGRICULTURE AND AGRI-FOOD CANADA; ALEX C. RUANE, NASA GODDARD INSTITUTE FOR SPACE STUDIES; CÉLINE SCHOVING, UNIVERSITÉ DE TOULOUSE, TERRES INOVIA; EVANDRO H. F. M. SILVA, ESALQ/USP; WARD SMITH, AGRICULTURE AND AGRI-FOOD CANADA; AFSHIN SOLTANI, GORGAN UNIVERSITY OF AGRICULTURAL SCIENCES AND NATURAL RE-SOURCES; AMIT SRIVASTAVA, UNIVERSITY OF BONN; NILSON A. VIEIRA JÚNIOR, ESALQ/USP; STACEY SLONE, UNIVERSITY OF KENTUCKY; MONTSERRAT SALMERÓN, UNIVERSITY OF KENTUCKY. |
Título: |
Are soybean models ready for climate change food impact assessments? |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
European Journal of Agronomy, v. 135, 126482, Apr. 2022. |
DOI: |
https://doi.org/10.1016/j.eja.2022.126482 |
Idioma: |
Inglês |
Conteúdo: |
Abstract. An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models. MenosAbstract. An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield res... Mostrar Tudo |
Palavras-Chave: |
AgMIP; Agricultural Model Intercomparison and Improvement Project; Impacto das mudanças climáticas; Legume model; Model calibration; Model ensemble; Modelos de soja; Temperature Atmospheric CO2 concentration. |
Thesagro: |
Glycine Max; Soja; Temperatura. |
Thesaurus Nal: |
Models; Soybeans; Temperature. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/232002/1/AP-Soybean-models-2022.pdf
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Marc: |
LEADER 04032naa a2200625 a 4500 001 2140426 005 2022-02-25 008 2022 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1016/j.eja.2022.126482$2DOI 100 1 $aKOTHARI, K. 245 $aAre soybean models ready for climate change food impact assessments?$h[electronic resource] 260 $c2022 520 $aAbstract. An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models. 650 $aModels 650 $aSoybeans 650 $aTemperature 650 $aGlycine Max 650 $aSoja 650 $aTemperatura 653 $aAgMIP 653 $aAgricultural Model Intercomparison and Improvement Project 653 $aImpacto das mudanças climáticas 653 $aLegume model 653 $aModel calibration 653 $aModel ensemble 653 $aModelos de soja 653 $aTemperature Atmospheric CO2 concentration 700 1 $aBATTISTI, R. 700 1 $aBOOTE, K. J. 700 1 $aARCHONTOULIS, S. V. 700 1 $aCONFALONE, A. 700 1 $aCONSTANTIN, J. 700 1 $aCUADRA, S. V. 700 1 $aDEBAEKE, P. 700 1 $aFAYE, B. 700 1 $aGRANT, B. 700 1 $aHOOGENBOOM, G. 700 1 $aJING, Q. 700 1 $aVAN DER LAAN, M. 700 1 $aSILVA, F. A. M. da 700 1 $aMARIN, F. R. 700 1 $aNEHBANDANI, A. 700 1 $aNENDEL, C. 700 1 $aPURCELL, L. C. 700 1 $aQIAN, B. 700 1 $aRUANE, A. C. 700 1 $aSCHOVING, C. 700 1 $aSILVA, E. H. F. M. 700 1 $aSMITH, W. 700 1 $aSOLTANI, A. 700 1 $aSRIVASTAVA, A. 700 1 $aVIEIRA JÚNIOR, N. A. 700 1 $aSLONE, S. 700 1 $aSALMERÓN, M. 773 $tEuropean Journal of Agronomy$gv. 135, 126482, Apr. 2022.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Registro Completo
Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
10/06/2015 |
Data da última atualização: |
27/09/2017 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 3 |
Autoria: |
TIBA, C.; REIS, R. J. dos R.; COSTA, J. C. E. da; AZEVEDO, V. W. B.; ABREU, J. F.; ALVES, M. A. S.; GUIMARAES, D. P.; PORTO, M. A. D. |
Afiliação: |
DANIEL PEREIRA GUIMARAES, CNPMS. |
Título: |
Siting study of solar thermoelectric plants in the State of Minas Gerais. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Journal of Geographic Information System, v. 6, p. 423-439, 2014. |
DOI: |
10.4236/jgis.2014.65037 |
Idioma: |
Inglês |
Conteúdo: |
The generation of heliothermal electricity has received increasing attention throughout the world in countries such as Spain, the USA, Germany and many others. In Brazil, this type of energy generation in the form of large projects (above 80 MW) remains unexplored. However, it is known that in the country, there are extensive areas of normal direct irradiation with high intensity and a low seasonality factor, especially in the semiarid regions in Brazil, mainly the North and Northeast of Minas Gerais. Moreover, these Minas Gerais regions have other significant characteristics for the installation of these plants: proximity to transmission lines, flatness, the fact that the respective vegetation is not endangered, a suitable land use profile (availability of land not used in agriculture), low wind speed, low population density, and, most recently, an increase in the demand for local electric energy due to the economic growth above the Brazilian average rate. Furthermore, the introduction of solar plants in that region, due to its distributed nature, will bring development and growth to the region (normally poor) by generating employment and income. This article presents a study of the optimal location of thermoelectric plants in the semiarid regions of Minas Gerais, conducted with Geographical Information System (GIS) technology. GIS consists of a set of specialised resources that allow the manipulation of spatial data, bringing efficiency and agility in the identification of suitable places for the installation of solar plants, while simultaneously enabling the consideration of future scenarios for energy planning, with its respective impact, costs and benefits. The study has identified very promising solar irradiation levels for the electric generation by solar energy, whether thermoelectric or photovoltaic, reaching an annual solar irradiation of 2700 kWh/m² in the summer and in the range of 2200 - 2400 kWh/m² on an annual basis. This area includes a vast region in the North/Northeast of the state, which also has continuous and flat regions, with slopes inferior to 3%; in addition, high-quality hydro resources are abundant and well distributed. Furthermore, the Minas Gerais region has few areas with high agriculture profile and reduced quantity of protected units. Therefore, generally speaking, the coverage of the transmission lines in that region is suitable. Considering the most relevant aspects mentioned before, and taking as a reference the micro-region limits defined by the IBGE, the following micro-regions were classified as the most promising ones: 1) Janaúba, 2) Januária, 3) Pirapora and Unaí, 4) Pirapora and Paracatu, 5) Curvelo and Três Marias, and 6) Patrocínio and Araxá. Finally, it is important to highlight that this potential might be explored gradually in the medium term, with the shortage of other supply sources, the scale up and readiness of such technologies, as well as the creation of a complex solar-wind-hydro system that leverages the strong complementarity of such resources, as has been observed. MenosThe generation of heliothermal electricity has received increasing attention throughout the world in countries such as Spain, the USA, Germany and many others. In Brazil, this type of energy generation in the form of large projects (above 80 MW) remains unexplored. However, it is known that in the country, there are extensive areas of normal direct irradiation with high intensity and a low seasonality factor, especially in the semiarid regions in Brazil, mainly the North and Northeast of Minas Gerais. Moreover, these Minas Gerais regions have other significant characteristics for the installation of these plants: proximity to transmission lines, flatness, the fact that the respective vegetation is not endangered, a suitable land use profile (availability of land not used in agriculture), low wind speed, low population density, and, most recently, an increase in the demand for local electric energy due to the economic growth above the Brazilian average rate. Furthermore, the introduction of solar plants in that region, due to its distributed nature, will bring development and growth to the region (normally poor) by generating employment and income. This article presents a study of the optimal location of thermoelectric plants in the semiarid regions of Minas Gerais, conducted with Geographical Information System (GIS) technology. GIS consists of a set of specialised resources that allow the manipulation of spatial data, bringing efficiency and agility in the identification of... Mostrar Tudo |
Palavras-Chave: |
SIG; Thermoelectric solar plant. |
Thesagro: |
Energia solar; Sistema de Informação Geográfica. |
Thesaurus NAL: |
Geographic Information Systems; Solar energy. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/125197/1/Siting-study.pdf
|
Marc: |
LEADER 03959naa a2200289 a 4500 001 2017290 005 2017-09-27 008 2014 bl uuuu u00u1 u #d 024 7 $a10.4236/jgis.2014.65037$2DOI 100 1 $aTIBA, C. 245 $aSiting study of solar thermoelectric plants in the State of Minas Gerais.$h[electronic resource] 260 $c2014 520 $aThe generation of heliothermal electricity has received increasing attention throughout the world in countries such as Spain, the USA, Germany and many others. In Brazil, this type of energy generation in the form of large projects (above 80 MW) remains unexplored. However, it is known that in the country, there are extensive areas of normal direct irradiation with high intensity and a low seasonality factor, especially in the semiarid regions in Brazil, mainly the North and Northeast of Minas Gerais. Moreover, these Minas Gerais regions have other significant characteristics for the installation of these plants: proximity to transmission lines, flatness, the fact that the respective vegetation is not endangered, a suitable land use profile (availability of land not used in agriculture), low wind speed, low population density, and, most recently, an increase in the demand for local electric energy due to the economic growth above the Brazilian average rate. Furthermore, the introduction of solar plants in that region, due to its distributed nature, will bring development and growth to the region (normally poor) by generating employment and income. This article presents a study of the optimal location of thermoelectric plants in the semiarid regions of Minas Gerais, conducted with Geographical Information System (GIS) technology. GIS consists of a set of specialised resources that allow the manipulation of spatial data, bringing efficiency and agility in the identification of suitable places for the installation of solar plants, while simultaneously enabling the consideration of future scenarios for energy planning, with its respective impact, costs and benefits. The study has identified very promising solar irradiation levels for the electric generation by solar energy, whether thermoelectric or photovoltaic, reaching an annual solar irradiation of 2700 kWh/m² in the summer and in the range of 2200 - 2400 kWh/m² on an annual basis. This area includes a vast region in the North/Northeast of the state, which also has continuous and flat regions, with slopes inferior to 3%; in addition, high-quality hydro resources are abundant and well distributed. Furthermore, the Minas Gerais region has few areas with high agriculture profile and reduced quantity of protected units. Therefore, generally speaking, the coverage of the transmission lines in that region is suitable. Considering the most relevant aspects mentioned before, and taking as a reference the micro-region limits defined by the IBGE, the following micro-regions were classified as the most promising ones: 1) Janaúba, 2) Januária, 3) Pirapora and Unaí, 4) Pirapora and Paracatu, 5) Curvelo and Três Marias, and 6) Patrocínio and Araxá. Finally, it is important to highlight that this potential might be explored gradually in the medium term, with the shortage of other supply sources, the scale up and readiness of such technologies, as well as the creation of a complex solar-wind-hydro system that leverages the strong complementarity of such resources, as has been observed. 650 $aGeographic Information Systems 650 $aSolar energy 650 $aEnergia solar 650 $aSistema de Informação Geográfica 653 $aSIG 653 $aThermoelectric solar plant 700 1 $aREIS, R. J. dos R. 700 1 $aCOSTA, J. C. E. da 700 1 $aAZEVEDO, V. W. B. 700 1 $aABREU, J. F. 700 1 $aALVES, M. A. S. 700 1 $aGUIMARAES, D. P. 700 1 $aPORTO, M. A. D. 773 $tJournal of Geographic Information System$gv. 6, p. 423-439, 2014.
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