Phenological and productive response of white maize to climate change in andean conditions
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Amiri, E., Irmak, S. and Araji, H., 2022. Assessment of CERES-Maize model in simulating maize growth, yield and soil water content under rainfed, limited and full irrigation. Agricultural Water Management, 259, p. 107271. https://doi.org/10.1016/j.agwat.2021.107271
Andrade, F.H., Uhart, S.A. and Cirilo, A., 1993. Temperature affects radiation use efficiency in maize. Field Crops Research, 32(1–2), pp. 17-25. https://doi.org/10.1016/0378-4290(93)90018-I
Araya, A., Hoogenboom, G., Luedeling, E., Hadgu, KM, Kisekka, I. and Martorano, LG., 2015. Assessment of maize growth and yield using crop models under present and future climate in southwestern Ethiopia. Agricultural and Forest Meteorology, 214, pp. 252-265. https://doi.org/10.1016/j.agrformet.2015.08.259
Araya, A., Kisekka, I., Lin, X., Prasad, PV, Gowda, PH, Rice, C. and Andales, A., 2017. Evaluating the impact of future climate change on irrigated maize production in Kansas. Climate Risk Management, 17, pp. 139-154. https://doi.org/10.1016/j.crm.2017.08.001
Arteaga, L., and Burbano, J., 2018. Efectos del cambio climático: Una mirada al Campo. Revista de Ciencias Agrícolas, 35(2), pp. 79-91. https://doi.org/10.22267/rcia.183502.93
Badu-Apraku, B., Hunter, R.B. and Tollenaar, M., 1983. Effect of temperature during grain filling on whole plant and grain yield in maize (Zea mays L.). Canadian Journal of Plant Science, 63(2), pp. 357-363. https://doi.org/10.4141/cjps83-040
Beltrán-Tolosa, L.M., Navarro-Racines, C., Pradhan, P., Cruz-Garcia, G.S., Solis, R. and Quintero, M., 2020. Action needed for staple crops in the Andean-Amazon foothills because of climate change. Mitigation and Adaptation Strategies for Global Change, 25, pp. 1103–1127. https://doi.org/10.1007/s11027-020-09923-4
Capa-Morocho, M., Rodríguez-Fonseca, B. and Ruiz-Ramos, M. (2016), El Niño influence on potential maize yield in Iberian Peninsula. International Journal of Climatology, 36, pp. 1313-1330. https://doi.org/10.1002/joc.4426
Castro, I. and Hétier, J. M., 2015. Modelización y experimentación agronómica. Tierras Llaneras de Venezuela… tierras de buena esperanza. 1ra ed. Venezuela: Consejo de Publicaciones de la Universidad de Los Andes. https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers15-12/010065645.pdf
Castro, L. M., Calvas, B., Hildebrandt, P. and Knoke, T., 2013. Avoiding the loss of shade coffee plantations: how to derive conservation payments for risk-averse land-users. Agroforestry Systems, 87(2), pp. 331-347. https://doi.org/10.1007/s10457-012-9554-0
Clarke D., T. Hess, D Haro-Monteagudo, M.A. Semenov, J W Knox, 2021. Assessing future drought risks and wheat yield losses in England, Agricultural and Forest Meteorology, 297, p. 108248. https://doi.org/10.1016/j.agrformet.2020.108248
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H., and Buontempo, C., 2020. WFDE5: bias adjusted ERA5 reanalysis data for impact studies, Earth System Science Data Discussions, 2020, pp. 1–32. https://doi.org/10.5194/essd-2020-28
Echarte, L. et al., 2013. Grain Yield Determination and Resource Use Efficiency in Maize Hybrids Released in Different Decades. Agricultural Chemistry, InTech. https://doi.org/10.5772/55287
ESPAC., 2024. Tabulados de la Encuesta de Superficie y producción Agropecuaria Continua. Instituto Nacional de Estadística y Censos. https://www.ecuadorencifras.gob.ec/estadisticas-agropecuarias-2/
Fahad S., Bajwa AA, Nazir U., Anjum SA, Farooq A., Zohaib A., Sadia S., Nasim W., Adkins S., Saud S. and Huang, J., 2017. Crop production under drought and heat stress: plant responses and management options. Frontiers in Plant Science, 8, p. 1147. https://doi.org/10.3389/fpls.2017.01147
Feleke, H. G., Savage, M. J. and Tesfaye, K. 2021. Calibration and validation of APSIM–Maize, DSSAT CERES–Maize and AquaCrop models for Ethiopian tropical environments. South African Journal of Plant and Soil, 38(1), pp. 36–51. https://doi.org/10.1080/02571862.2020.1837271
Figarola, L. A., Ghersa, F., Castro, R. and Ferraro, D. O., 2020. Automatización del Modelo de Simulación de Cultivos DSSAT para Evaluar el Desempeño Productivo Bajo Distintas Estrategias de Manejo y Escenarios Ambientales. In: XII Congreso de AgroInformática (CAI 2020)-JAIIO 49 (Modalidad virtual). http://sedici.unlp.edu.ar/handle/10915/115512
García Montero, P. 2023. El cambio climático: posibles impactos en la agricultura en el contexto de América Latina y Venezuela. Agroalimentaria Journal-Revista Agroalimentaria, 28(55), pp. 167-189. https://doi.org/10.22004/ag.econ.338827
Gerald, N., Rosegrant, M. W., Koo, J., Robertson, R., Sulser, T., Zhu, T. and Lee, D., 2009. Cambio Climático El impacto en la agricultura y los costos de adaptación. International Food Policy Research Institute. https://doi.org/10.2499/0896295370
Gobezie, A., Ademe, D., and Sharma, L. K., 2025. CERES-Maize (DSSAT) Model Applications for Maize Nutrient Management Across Agroecological Zones: A Systematic Review. Plants, 14(5), p. 661. https://doi.org/10.3390/plants14050661
González, D., Rodríguez, O., Florido, R., Vázquez, R. and Socorro, M., 2022. Determinación de parámetros para la calibración del modelo DSSAT en el cultivo del maíz. Ingeniería Agrícola, 12(4). https://www.redalyc.org/journal/5862/586272874006/html/
Groundswell International, 2024. Indigenous Farming Systems in Ecuador: Lessons for Adapting to Climate Change. https://www.groundswellinternational.org/blog/indigenous-farming-techniques-ecuador-lessons-adapt-climate-change/
Hoogenboom, G., CH Porter, KJ Boote, V. Shelia, P.W. Wilkens, U. Singh, J.W. White, S. Asseng, J.I. Lizaso, L.P. Moreno, W. Pavan, R. Ogoshi, L.A. Hunt, G.Y. Tsuji and J.W. Jones., 2019. El ecosistema de modelado de cultivos DSSAT. En: p.173-216 [KJ Boote, editor] Avances en el modelado de cultivos para una agricultura sostenible. Burleigh Dodds Science Publishing, Cambridge, Reino Unido. https://dx.doi.org/10.19103/AS.2019.0061.10
Hoogenboom, G., CH Porter, V. Shelia, KJ Boote, U. Singh, W. Pavan, FAA Oliveira, LP Moreno-Cadena, TB Ferreira, JW White, JI Lizaso, DNL Pequeno, BA Kimball, PD Alderman, KR Thorp, SV Cuadra, MS Vianna, FJ Villalobos, WD Batchelor, S. Asseng, MR Jones, A. Hopf, HB Dias, A. Jintrawet, R. Jaikla, E. Memic, LA Hunt and JW Jones. 2024. Sistema de Apoyo a la Decisión para la Transferencia de Agrotecnología (DSSAT) Versión 4.8.5. Fundación DSSAT, Gainesville, Florida, Estados Unidos. https://www.dssat.net
Hoogenboom, G., et al., 2010. The Decision Support System for Agrotechnology Transfer (DSSAT), Version 4. 5 [CD-ROM]. University of Hawaii, Honolulu, Hawaii.
Hoogenboom, G., Wilkens, P.W., Thornton, P.K., Jones, J.W., Hunt, L.A. and Imamura, D.T., 1999. Decision support system for agrotechnology transfer v3.5. In: Hoogenboom, G., Wilkens, P.W., Tsuji, G.Y. (Eds.), DSSAT version 3, vol. 4 (ISBN 1-886684-04-9). University of Hawaii, Honolulu, HI, pp. 1-36.
Hultgren, A., Carleton, T., Delgado, M., Gergel, D. R., Greenstone, M., Houser, T., Hsiang, S., Jina, A., Kopp, R., Malevich, S., McCusker, K., Mayer, T., Nath, I., Rising, J., Rode, A. and Yuan, J., 2025. Impacts of climate change on global agriculture accounting for adaptation. Nature, 642, pp. 644-652. https://doi.org/10.1038/s41586-025-09085-w
INAMHI, Instituto Nacional de Meteorología e Hidrología del Ecuador. 2024. Biblioteca: anuarios meteorológicos. https://www.inamhi.gob.ec/biblioteca/
ISIMIP, Inter-Sectoral Impact Model Intercomparison Project., 2024. ISIMIP Repository. https://data.isimip.org/search/tree/ISIMIP3b/InputData/climate/atmosphere/
Issifou Moumouni, Y., Kindjinou, T., Adougan, B., Hounkanrin, B., Koumassi, H., Ezin, A. V., Yabi, I., and Ogouwale, E., 2022. Impact of climate change on the dynamics of soybean (Glycine max) (L.) Merr. production areas in the second agricultural development pole of the Sudanian region of Benin (West Africa). Legume Science, 4(3). https://doi.org/10.1002/leg3.135
Jones, C. A., and Kiniry, J. R., 1986. CERES-Maize: A Simulation Model of Maize Growth and Development. Texas A&M University Press, Texas, First edition, p. 194.
Lange, S., 2019. Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1. 0). Geoscientific Model Development, 12(7), pp. 3055-3070. https://doi.org/10.5194/gmd-12-3055-2019
Lange, S., 2020. ISIMIP3BASD v2.4.1, https://doi.org/10.5281/zenodo.3898426
Lin, Y., Wu, W., and Ge, Q., 2014. CERES-Maize model-based simulation of climate change impacts on maize yields and potential adaptive measures in Heilongjiang Province, China. Journal of the Science of Food and Agriculture, 95 (14), pp. 2838-2849. https://doi.org/10.1002/jsfa.7024
Liu, Y., Qin, Y., Ge, Q., Dai, J. and Chen, Q. 2017. Responses and sensitivities of maize phenology to climate change from 1981 to 2009 in Henan Province, China. Journal of Geographical Sciences, 27(9), pp. 1072–1084. https://doi.org/10.1007/s11442-017-1422-4
Lopez, G., Gaiser, T., Ewert, F. and Srivastava, A. 2021. Effects of recent climate change on maize yield in Southwest Ecuador. Atmosphere, 12(3), p. 299. https://doi.org/10.3390/atmos12030299
Lozano-Povis, A., Alvarez-Montalván, C.E. and Moggiano, N. 2021. El cambio climático en los Andes y su impacto en la agricultura: una revisión sistemática. Scientia Agropecuaria, 12(1), pp. 101–108. https://doi.org/10.17268/sci.agropecu.2021.012
Medina, S., Cruz, W. and Cuellar, J. 2019. First maize AquaCrop modeling for adaptation to climate change for Andean and arid zones production. INIA Perú. https://app.ingemmet.gob.pe/biblioteca/pdf/TGS-23.pdf
Moreno, J. and Pintado, P., 2013. INIAP 103 “Mishqui Sara”: Nueva variedad de maíz blanco harinoso para consumo humano [Ficha técnica]. Instituto Nacional de Investigaciones Agropecuarias (INIAP), Estación Experimental del Austro, Programa de Maíz. https://repositorio.iniap.gob.ec/bitstream/41000/2342/1/FT3.pdf
Muchow, R.C., Sinclair, T.R. and Bennett, J.M., 1990. Temperature and Solar Radiation Effects on Potential Maize Yield across Locations. Agronomy. Journal, 82(2), pp. 338-343. https://doi.org/10.2134/agronj1990.00021962008200020033x
Na Li, Yating Zhao, Jinsheng Han, Qiliang Yang, Jiaping Liang, Xiaogang Liu, Yazhou Wang, Zhengzhong Huang. 2024. Impacts of future climate change on rice yield based on crop model simulation—A meta-analysis. Science of The Total Environment, 949, p. 175038. https://doi.org/10.1016/j.scitotenv.2024.175038
Noriega-Navarrete, P., Rubel, J. L., Salazar, R. and López-Cruz; I., 2021. Revisión: Modelos de crecimiento y rendimiento de maíz en escenarios de cambio climático. Revista Mexicana de Ciencias Agrícolas, 12(1), pp. 127-140. https://doi.org/10.29312/remexca.v12i1.2552
Ogallo, L.A., Boulahya, M.S. and Keane, T., 2000. Applications of seasonal to interannual climate prediction in agricultural planning and operations. Agricultural and Forest Meteorology, 103(1–2), pp. 159-166. https://doi.org/10.1016/S0168-1923(00)00109-X
Ojeda, W., Sifuentes, E., Íñiguez, M., and Montero, M. 2011. Impacto del cambio climático en el desarrollo y requerimientos hídricos de los cultivos. Agrociencia, 45(1), pp. 1-11. https://www.scielo.org.mx/pdf/agro/v45n1/v45n1a1.pdf
Parra, R. 2023. Assessment of Land Surface Schemes from the WRF-Chem for Atmospheric Modeling in the Andean Region of Ecuador. Atmosphere, 14(3), pp. 508. https://doi.org/10.3390/atmos14030508
Plomitallo, V. and Selicati, R.E., 2023. Thermal index-based phenology models for maize: A review. International Journal of Agricultural Science and Food Technology. 5(2), pp. 138–141. https://doi.org/10.33545/2664844X.2023.v5.i2b.184
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O’Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A., Cuaresma, J. C., Kc, S., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., and Tavoni, M., 2017. Las trayectorias socioeconómicas compartidas y sus implicaciones en la energía, el uso del suelo y las emisiones de gases de efecto invernadero: Una visión general. Cambio Ambiental Global, 42, pp. 153-168. https://doi.org/10.1016/j.gloenvcha.2016.05.009
Rodríguez, O., Florido, R., Hernández, N., Soto, F., Jeréz Mompié, E., González, D., and Vázquez, R., 2021. Simulación de estrategias de manejo a partir del modelo DSSAT para incrementar los rendimientos de un cultivar de maíz. Cuban Journal of Agricultural Science, 55(2), http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S2079-34802021000200008&lng=es&tlng=es
Rubel, F. and Kottek, M., 2010. Observed and projected climate shifts 1901-2100 depicted by world maps of the Köppen-Geiger climate classification. Meteorologische Zeitschrift, 19(2), pp. 135-141. https://doi.org/10.1127/0941-2948/2010/0430
Rugira, P., Ma, J., Zheng, L., Wu, C., and Liu, E., 2021. Application of DSSAT CERES-Maize to Identify the Optimum Irrigation Management and Sowing Dates on Improving Maize Yield in Northern China. Agronomy, 11(4), p. 674. https://doi.org/10.3390/agronomy11040674
Sanodiya, P., Tiwari, P., Gupta, Ch., 2023. Maize (Zea mays L.) -The future potential cereal crop of an indispensable significance in agro-forestry system. Maize Journal, 12(2), pp. 61-71.
Stewart, B. A., Thapa, S., Xue, Q., and Shrestha, R., 2018. Climate change effect on winter wheat (Triticum aestivum L.) yields in the US Great Plains. Journal of Soil and Water Conservation, 73(6), pp. 601-609. https://doi.org/10.2489/jswc.73.6.601
Wang, Z., Chen, J., Li, Y., Li, C., Zhang, L., and Chen, F., 2016. Effects of climate change and cultivar on summer maize phenology. International Journal of Plant Production, 10(4), pp. 509-526.
Wheeler, T.R., Craufurd, P.Q., Ellis, R.H., Porter, J.R. and Vara Prasad, P.V., 2000. Temperature variability and the yield of annual crops. Agriculture, Ecosystems & Environment, 82(1–3), pp. 159-167. https://doi.org/10.1016/S0167-8809(00)00224-3
Yánez, G., 2013. INIAP-103: "Mishqui Sara". Quito, Ecuador: INIAP, Estación Experimental Santa Catalina, Programa de Maíz. https://repositorio.iniap.gob.ec/bitstream/41000/2413/1/iniapsc337.pdf
Young, M. D., Ros, G. H., and de Vries, W., 2021. Impacts of agronomic measures on crop, soil, and environmental indicators: A review and synthesis of meta-analysis. Agriculture, Ecosystems & Environment, 319, p. 107551. https://doi.org/10.1016/j.agee.2021.107551
Yuan, X., Li, S., Chen, J., Yu, H., Yang, T,; Wang, C., Huang, S., Chen, H. and Ao, X., 2024. Impacts of Global Climate Change on Agricultural Production: A Comprehensive Review. Agronomy, 14, p. 1360. https://doi.org/10.3390/agronomy14071360
Yzarra, W. J., and Navarro, M. L., 2015. Ministerio del ambiente. Obtenido de Calibración y validación del modelo CERES MAIZE-DSSAT en la costa central: https://hdl.handle.net/20.500.12542/434
Zambrano, J.L., Velásquez, J., Peñaherrera, D., Sangoquiza, C., Cartagena, Y., Villacrés, E., Garcés, S., Ortíz, R., León, J., Campaña, D., López, V., Asaquibay, C., Nieto, M., Sanmartín G., Pintado, P., Yánez, C. and Racines, M., 2021. Guía para la producción sustentable de maíz en la Sierra ecuatoriana. INIAP, Manual No. 122. Quito, Ecuador. https://repositorio.iniap.gob.ec/bitstream/41000/5796/1/GUIA%20CULTIVO%20DE%20MAIZ%202021-1.pdf
Zhang N, Qu Y, Song Z, Chen Y, and Jiang J., 2022. Responses and sensitivities of maize phenology to climate change from 1971 to 2020 in Henan Province, China. Plos One, 17(1), p. e0262289. https://doi.org/10.1371/journal. pone.0262289
URN: http://www.revista.ccba.uady.mx/urn:ISSN:1870-0462-tsaes.v28i3.65012
DOI: http://dx.doi.org/10.56369/tsaes.6501
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