Published

2017-01-01

Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO

Nivel de fertilización en el uso del agua y la producción de maíz (Zea maiz L.) en Colombia - un ejercicio de modelación AquaCrop-FAO

DOI:

https://doi.org/10.15446/agron.colomb.v35n1.61428

Keywords:

water consumption, evapotranspiration, biomass, yield (en)
Consumo agua, evapotranspiración, biomasa, rendimiento (es)

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Authors

  • Javier García A. Universidad de Nariño
  • Gerhard Fischer Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Agrarias - Departamento de Agronomía https://orcid.org/0000-0001-8101-0507
  • Nestor Riaño H. Universidad de Manizales
The effect of the amount of fertilization applied to the corn variety 'ICA V-156' (white grain) was calibrated and validated with the simulator AquaCrop in Cerete (Cordoba, Colombia) at an altitude of 20 m. The fertilization level determined factors related to biomass production, the harvest index, yield and water use, and potential evapotranspiration (Eto). The basic information which calibrated and validated the model came from research conducted in different altitudes in maize growing areas in Colombia. Unexpectedly, the water shortages occurred during the growing season, which the modelling had not considered. Levels of 90 to 60% of fertilization were applied to the crop according to the analysis of the evaluated soil. The information was subjected to an analysis of variance; the results showed that the level of fertilization affected the formation of biomass, harvest index and yield, as well as, the use of water during the growing season. The ETo values were extreme at 0.9 and 7.3 mm day-1. Likewise the total biomass production was 4.64% less at the level of 90 and 25.04% less at 60% fertilization, as compared to the biomass measurements in the field. Similarly, the harvest index was 32.3 and 29.8% for the 90 and 60% levels of fertilization, respectively; on the other hand the grain yield was not affected by the highest level (90%), whereas when the reduction in fertilization was 40%, a decrease of 14.335% in the grain yield was obtained. In addition, per m3 of water 18.87 and 23.02 kg of grain for the fertilization levels of 60 and 90% were formed, respectively.

Calibrado y validado el modelo AquaCrop para maíz 'ICA V-156' (grano blanco), en Cereté (Córdoba, Colombia) a una altitud de 20 msnm, se determinó el efecto del nivel de fertilización, en la producción de biomasa, índice de cosecha; rendimiento y uso del agua, en la cual se tuvo en cuenta la evapotranspiración potencial (Eto). La información básica con la que se calibró y validó el modelo, provenía de trabajos de investigación realizados en altitudes diferentes, en zonas productoras de maíz en Colombia. La modelación partió del supuesto de no tener déficit de agua, durante el desarrollo del cultivo, como efectivamente sucedió. Se evaluaron dos niveles, que comprendían el 90 y 60% de la fertilización, enfrentados a la fertilización aplicada al cultivo de acuerdo con el análisis de suelos. El nivel de fertilización afectó la formación de biomasa, índice de cosecha y rendimiento, así mismo, el uso del agua y el ciclo del cultivo. La determinación de la ETo mostró valores extremos de 0,9 y 7,3 mm diarios. La producción de biomasa total fue 4,64% menor para el nivel del 90% y de 25,04% para el 60% de fertilización, en comparación con la medida en campo. El índice de cosecha fue de 32,3 y de 29,8%, para los niveles 90 y 60% de fertilización, respectivamente, de otra parte el rendimiento de grano no se resintió para el mayor nivel (90%), mientras que cuando la reducción en la fertilización fue del 40%, se obtuvo una disminución de 14,335% en el grano. Se formaron 18,87 kg de grano por m3 de agua para el nivel de fertilización del 60% y 23,02 kg para el 90%.

References

Abedinpour, M., A. Sarangi, T.B.S. Rajput, M. Singh, H. Pathak, and T. Ahmad. 2012. Performance evaluation of AquaCrop model for maize crop in a semi-arid environment. Agr. Water Manag. 110, 55-66. Doi: 10.1016/j.agwat.2012.04.001

Baldocchi, D.D. and K.B. Wilson. 2001. Modeling CO2 and water vapor exchange of a temperate broad leaved forest across hourly to decadal time scales. Ecol. Model. 142, 155-184. Doi: 10.1016/S0304-3800(01)00287-3

Baldocchi, D.D., K.B. Wilson, and L. Gu. 2002. How the environment, canopy structure and canopy physiological functioning influence carbon, water and energy fluxes of a temperate broad-leaved deciduous forest and assessment with the biophysical model CANOAK. Tree Physiol. 22, 1065-1077. Doi: 10.1093/treephys/22.15-16.1065

Biazin, B. and L. Stroosnijder. 2012. To tie or not to tie ridges for water conservation in Rift Valley drylands of Ethiopia. Soil Tillage Res. 124, 83-94. Doi: 10.1016/j.still.2012.05.006

Bowman, W.D. 1989. The relations chip between leaf water status, gas exchange, and spectral reflectance in cotton leaves, remote sensing of environment. Remote Sensing Environ. 30(3), 249-255. Doi: 10.1016/0034-4257(89)90066-7

Breton, O.M., V.K.S. Morris, and V.E. Mendez. 2012. Cultivation of maize landraces by small-scale shade coffee farmers in western El Salvador. Agric. Syst. 111, 63-74. Doi: 10.1016/j.agsy.2012.05.005

Cantor, F., J.R. Cure, and A.M. Orozco. 1995. Simulation and growth Gypsophyla paniculata var. Perfect, including the effect of vernalization. In: Abstracts Network Meeting of the International Biometric Society for Central America, the Caribbean, Colombia and Venezuela.11-15 June, 1995. Santa Marta, Colombia.

Ceccato, P., S. Flasse, S. Tarantola, S. Jacquemoud, and J.M. Gregoire. 2001. Detecting vegetation leaf water content using reflectance in the optical domain. Remote Sensing Environ. 77(1), 22-33. Doi: 10.1016/S0034-4257(01)00191-2

Chuvieco, S.E. 2002. Environmental remote sensing. The earth observation from space. Ariel Science, Barcelona, Spain.

FAO. 2006. Crop evapotranspiration. Guidelines for determining water requirements of crops. FAO Irrigation and Drainage Study No. 56. FAO, Rome.

Fageria, N.K., V.C. Baligar, and R.B. Clark. 2005. Physiology of crop production. The Haword Press, New York, NY, USA.

Fallas, R., F. Bertsch, C. Echandi, and C. Henriquez. 2011. Characterization of development and nutrient absorption hybrid corn HC-57. Agron. Costar. 35(2), 33-47.

Fenalce. 2012. Cerealistas indicators 2011-2012 A. Economic Department, National Federation of Grain and Legumes Growers. In: Congreso Nacional Cerealista. 28-29 June, 2012. Monteria, Colombia.

Fenalce. 2013. Corn technology in Colombia. Growers National Federation of Cereals and Pulses. In: www.fenalce.org; consulted: November, 2014.

Fernandez, J.F., F. Moreno, J.M. Murillo, J.A. Cayuela, B.E. Fernandez, and F. Cabrera. 1996. Water use and yield of maize with two levels of nitrogen fertilization in SW Spain. Agric. Water Manag. 29, 215-233. Doi: 10.1016/0378-3774(95)01192-7

Gambin, B.L., L. Borras, and M.E. Otegui. 2006. Source-sink relations and kernel weight differences in maize temperate hybrids. Field Crops Res. 95, 316-326. Doi: 10.1016/j.fcr.2005.04.002

Garcia A., J. 2014. Comparison of simulation models and CREFT AquaCrop under Colombian conditions as a tool for decisionmaking and support corn production. PhD thesis. Faculty of Agricultural Sciences, National University of Colombia, Bogota, Colombia.

Garcia A., J., N. Riano, and S. Magnitskiy. 2014. Simulation of corn (Zea mays L.) production in different agricultural zones of Colombia using the AquaCrop model. Agron. Colomb. 32(3), 358-366. Doi: 10.15446/agron.colomb.v32n3.45939

Garcia-Vila, M. and E. Fereres. 2012. Combining the simulation crop model AquaCrop with an economic model for the optimization of irrigation management at farm level. Eur. J. Agron. 36, 21-31. Doi: 10.1016/j.eja.2011.08.003

Garcia, A., L.C. Guerra, and G. Hoogenboom. 2008. Impact of generated solar radiation on simulated crop growth and yield. Ecol. Model. 210, 312-326. Doi: 10.1016/j.ecolmodel.2007.08.003

Gates, D.M., H.J. Keegan, J.C. Schleter, and V.R. Weidner. 1965. Spectral properties of plants. Appl. Optics 4, 11-20. Doi: 10.1364/AO.4.000011

Geerts, S. and D. Raes. 2009. Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas. Agr. Water Manag. 96, 1275-1284. Doi: 10.1016/j.agwat.2009.04.009

Geerts, S., D. Raes, and M. Garcia. 2010. Using AquaCrop to derive deficit irrigation schedules. Agr. Water Manag. 98, 213-216. Doi: 10.1016/j.agwat.2010.07.003

Goetz, S.J., S.D. Prince, S.N. Goward, M.M. Thawley, and J. Small. 1999. Satellite remote sensing of primary production: an improved production efficiency modeling approach. Ecol. Model. 122, 239-255. Doi: 10.1016/S0304-3800(99)00140-4

Hsiao, T.C., L. Heng, P. Steduto, B. Rojas-Lara, D. Raes, and E. Fereres. 2009. AquaCrop-The FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agron. J. 101(3), 448-459. Doi: 10.2134/agronj2008.0218s

Jones, J.W., G. Hoogenboom, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, and P.W. Wilkens. 2003. The DSSAT cropping system model. Eur. J. Agron.18, 235-265. Doi: 10.1016/S1161-0301(02)00107-7

Lopez-Mata, E., J.M. Tarjuelo, J.A. de Juan, R. Ballesteros, and A. Dominguez. 2010. Effect of irrigation uniformity on the

profitability of crops. Agric. Water Manag. 98, 190-198. Doi: 10.1016/j.agwat.2010.08.006

Li, L., G. Luoa, X. Chena, Y. Li, G. Xu, H. Xu, and J. Bai. 2011. Modelling evapotranspiration in a Central Asian desert ecosystem. Ecol. Model. 222, 3680- 3691. Doi: 10.1016/j.ecolmodel.2011.09.002

Liu, G., M. Hafeez, Y. Liu, D. Xua, and C. Vote. 2012. A novel method to convert daytime evapotranspiration into daily evapotranspiration based on variable canopy resistance. J. Hydrol. 414-415, 278-283. Doi: 10.1016/j.jhydrol.2011.10.042

Ma, L, T.J. Trout, L.R. Ahuja, W.C. Bausch, S.A. Saseendran, R.W. Malone, and D.C. Nielsen. 2012. Calibrating RZWQM2 model for maize responses to deficit irrigation. Agr. Water Manag. 103, 140-149. Doi: 10.1016/j.agwat.2011.11.005

Martins, J.D, G.C. Rodrigues, P. Paredes, R. Carlesso, Z.B. Oliveira, A.E. Knies, M.T. Petry, and L.S. Pereira. 2013. Dual crop coefficients for maize in southern Brazil: Model testing for sprinkler and drip irrigation and mulched soil. Biosyst. Eng. 115, 291-310. Doi: 10.1016/j.biosystemseng.2013.03.016

Melgar, R.J., J. Lavandera, M. Torres D., and L. Ventimiglia. 2001. Response to fertilization with boron and zinc in intensive corn production systems. Cienc. Suelo 19(2), 109-114.

Negrete, F., J. Morales, A.J. Lopez, and A.M. Martinez. 2004. Final report project “Comprehensive technical assistance in the cultivation of corn for Caribbean ecoregion”. Corpoica, C.I. Turipana, Cerete, Colombia.

Odhiambo, L.O. and S. Irmak. 2012. Evaluation of the impact of surface residue cover on single and dual crop coefficient for estimating soybean actual evapotranspiration. Agr. Water Manag. 104, 221-234. Doi: 10.1016/j.agwat.2011.12.021

Ospina, J.G. 2006. DSSAT validation model in different agroecological conditions of Colombia, a tool to optimize management practices maize (Zea mays L.). M.Sc. thesis. Faculty of Agricultural Sciences, National University of Colombia, Medellin, Colombia.

OECD/FAO. 2011. Agricultural outlook 2011-2020. Doi: 10.1787/agr_outlook-2011-en

Paliwal, R.L. 2001. Morphology of tropical maize. Corn in the tropics. Improvement and production. Collection FAO Plant Production and Protection. In: http: //www.fao.org/DOCREP; consulted: August, 2015.

Penman, H.L. 1948. Natural evapotranspiration from open water, bare soils, and grass. Proc. R. Soc. London 193(1032), 120-145. Doi: 10.1098/rspa.1948.0037

Penman, H.L. 1949. The dependence of transpiration on weather conditions. J. Soil Sci. 1, 74-89. Doi: 10.1111/j.1365-2389.1950.tb00720.x

Raes, D., P. Steduto, T.C.Hsiao, and E. Fereres. 2011. AquaCrop version 3.1plus: FAO cropwater productivity model to simulate yield response to water. Reference Manual. FAO, Rome.

Raes, D., P. Steduto, T.C.Hsiao, and E. Fereres. 2010. AquaCrop – The FAO crop model to simulate yield response to water. User Guide. Chapter 2. Version 3.1 plus. Reference Manual. FAO, Rome.

Reiko, I., N. Tatsuro, and O. Hiroyuki. 2010. Assessment of canopy photosynthetic capacity and estimation of GPP by using spectral vegetation indices and the light-response function in a larch forest. Agr. For. Meteor. 150, 389-398. Doi: 10.1016/j.agrformet.2009.12.009

Riano, H., N.M. Tangarife., O.I. Osorio, J.F. Giraldo, C.M. Ospina, D. Obando, L.F. Gomez, and L.F. Jaramillo. 2005. Growth model and carbon sequestration to forest species in the tropics. CREFT. V 1.0. National Federation of Coffee Growers of Colombia, National Development Corporation and Forest Development, Bogota.

Ruane, A.C., L.D. Cecil, R.M. Horton, R. Gordon, R. McCollum, D. Brown, B. Killough, R. Goldberg, A.P. Greeley, and C. Rosenzweig. 2011. Climate change impact uncertainties for maize in Panama: Farm information, climate projections, and yield sensitivities. Agr. For. Meteorol. 170, 132-145. Doi: 10.1016/j.agrformet.2011.10.015

Salemi, H., M.A. Soom, T.S. Lee, S.F. Mousavi, A. Ganji, and M.K. Yusoff. 2011. Application of AquaCrop model in deficit irrigation management of winter wheat in arid region. Afr. J. Agr. Res. 610, 2204-2215.

Sezen, S.M., A. Yazar, B. Kapur, and S. Tekinb. 2011. Comparison of drip and sprinkler irrigation strategies on sunflower seed and oil yield and quality under Mediterranean climatic conditions. Agric. Water Manag. 98, 1153-1161. Doi: 10.1016/j.agwat.2011.02.005

Singh, B.R. and D.P. Singh. 1995. Agronomic and physiological responses of sorghum, maize and pearl millet to irrigation. Field Crops Res. 42, 57-67. Doi: 10.1016/0378-4290(95)00025-L

Steduto, P., T.C. Hsiao, and E. Fereres. 2007. On the conservative behavior of biomass water productivity. Irrig. Sci. 25, 189-207. Doi: 10.1007/s00271-007-0064-1

Steduto, P., T.C. Hsiao, D. Raes, and E. Fereres. 2009. AquaCrop- The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agron. J. 101(3), 426-437. Doi: 10.2134/agronj2008.0139s

Steduto, P., D. Raes, T.C. Hsiao, E. Fereres, L.K. Heng, T.A. Howell, S.R. Evett, B.A. Rojas-Lara, H.J. Farahani, G. Izzi, T.Y. Oweis, S.P. Wani, and R. Albrizio. 2005. Resource use efficiency of field-grown sunflower, sorghum, wheat and chickpea. II. Water use efficiency and comparison with radiation use efficiency. Agric. For. Meteorol. 130, 269-281. Doi: 10.1016/j.agrformet.2005.04.003

Steduto, P., D. Raes, T.C. Hsiao, E. Fereres, L.K. Heng, T.A. Howell, S.R. Evett, B.A. Rojas-Lara, H.J. Farahani, G. Izzi, T.Y. Oweist, S.P. Wani, J. Hoogeveen, and S. Geerts. 2009. Concepts and applications of AquaCrop: The FAO crop water productivity model. pp. 175-191. In: Weixing, C., J.W. White, and E. Wang (eds.). Crop modeling and decision support. Springer, Berlin. Doi: 10.1007/978-3-642-01132-0_19

Sun, J., L. Yang, Y. Wang, and D.R. Ort. 2009. FACE-ing the global change: Opportunities for improvement in photosynthetic radiation use efficiency and crop yield. Plant Sci. 177, 511-522. Doi: 10.1016/j.plantsci.2009.08.003

Taboada, M.A. and C.R. Alvarez. 2008. Root abundance of maize (Zea mays L.) in conventionally-tilled and zero-tilled soils of Argentina. Rev. Bras. Cienc. Solo 32, 769-779. Doi: 10.1590/S0100-06832008000200031

Trezza, R. 2008. Estimating reference evapotranspiration monthly in Venezuela. What method to use? Bioagro 20(2), 89-95.

USDA. 2012. USDA agricultural projections to 2022. U.S. Department of Agriculture, Interagency Agricultural Projections Committee, Washington DC, USA.

Vico, G. and A. Porporato. 2011. From rainfed agriculture to stressavoidance irrigation: I. A generalized irrigation scheme with stochastic soil moisture. Adv. Water Resour. 34, 263-271. Doi:10.1016/j.advwatres.2010.11.010

Wang, X. P.W. Gassman, R. Williams, S. Potter, and A.R. Kemanian. 2008. Modeling the impacts of soil management practices on runoff, sediment yield, maize productivity, and soil organic carbon using APEX. Soil Tillage Res. 101, 78-88. Doi: 10.1016/j. still.2008.07.014

Zhu, X.-G., Q. Song, and D.R. Ort. 2012. Elements of a dynamic systems model of canopy photosynthesis. Curr. Opin. Plant Biol. 15, 237-244. Doi: 10.1016/j.pbi.2012.01.010

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APA

García A., J., Fischer, G. and Riaño H., N. (2017). Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO. Agronomía Colombiana, 35(1), 68–74. https://doi.org/10.15446/agron.colomb.v35n1.61428

ACM

[1]
García A., J., Fischer, G. and Riaño H., N. 2017. Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO. Agronomía Colombiana. 35, 1 (Jan. 2017), 68–74. DOI:https://doi.org/10.15446/agron.colomb.v35n1.61428.

ACS

(1)
García A., J.; Fischer, G.; Riaño H., N. Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO. Agron. Colomb. 2017, 35, 68-74.

ABNT

GARCÍA A., J.; FISCHER, G.; RIAÑO H., N. Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO. Agronomía Colombiana, [S. l.], v. 35, n. 1, p. 68–74, 2017. DOI: 10.15446/agron.colomb.v35n1.61428. Disponível em: https://revistas.unal.edu.co/index.php/agrocol/article/view/61428. Acesso em: 24 apr. 2024.

Chicago

García A., Javier, Gerhard Fischer, and Nestor Riaño H. 2017. “Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO”. Agronomía Colombiana 35 (1):68-74. https://doi.org/10.15446/agron.colomb.v35n1.61428.

Harvard

García A., J., Fischer, G. and Riaño H., N. (2017) “Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO”, Agronomía Colombiana, 35(1), pp. 68–74. doi: 10.15446/agron.colomb.v35n1.61428.

IEEE

[1]
J. García A., G. Fischer, and N. Riaño H., “Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO”, Agron. Colomb., vol. 35, no. 1, pp. 68–74, Jan. 2017.

MLA

García A., J., G. Fischer, and N. Riaño H. “Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO”. Agronomía Colombiana, vol. 35, no. 1, Jan. 2017, pp. 68-74, doi:10.15446/agron.colomb.v35n1.61428.

Turabian

García A., Javier, Gerhard Fischer, and Nestor Riaño H. “Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO”. Agronomía Colombiana 35, no. 1 (January 1, 2017): 68–74. Accessed April 24, 2024. https://revistas.unal.edu.co/index.php/agrocol/article/view/61428.

Vancouver

1.
García A. J, Fischer G, Riaño H. N. Effect of fertilization level on water use and production of corn (Zea mays L.) in a cereal producing area in Colombia - a modeling exercise using AquaCrop-FAO. Agron. Colomb. [Internet]. 2017 Jan. 1 [cited 2024 Apr. 24];35(1):68-74. Available from: https://revistas.unal.edu.co/index.php/agrocol/article/view/61428

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