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A comparison of two open-source crop simulation models for a potato crop
Comparación de dos modelos de simulación de cultivo de código abierto para un cultivo de papa
DOI:
https://doi.org/10.15446/agron.colomb.v38n3.82525Keywords:
crop modelling, crop yield, agrometeorology, Solanum tuberosum L. (en)modelización de cultivos, rendimiento de cultivos, agrometeorología, Solanum tuberosum L. (es)
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An open-source model is a model that makes it possible to modify the source code. This tool can be a great advantage for the user since it allows changing or modifying some of the background theory of the model. World Food Studies (WOFOST) and AquaCropOS open-source crop models were compared using field recorded data. Both models are free open-source tools that allow evaluating the impacts of climate and water on agriculture. The objective of this research was to assess the model’s efficiency in simulating the yield and above-ground biomass formation of a potato crop on the Cundiboyacense plateau. WOFOST simulates biomass accumulation in the crop organs using partitioning of assimilates to establish the biomass fraction that turns into yield. AquaCropOS simulates total above-ground biomass accumulation using crop water productivity (WP) and considers the Harvest Index (HI) to calculate yield formation. Crop modules for both models were built using information recorded in previous studies by other authors; those works performed a physiological and phenological characterization of some potato varieties. It was found that the WOFOST model simulates yield formation better than AquaCropOS; despite that, AquaCropOS simulates total above-ground biomass better than WOFOST. However, AquaCropOS was as efficient as WOFOST in simulating yield formation.
Un modelo de código abierto permite modificar el código fuente. Esto puede ser una gran ventaja para el usuario, pues permite modificar o cambiar parte de la teoría en la que se sustenta el modelo. Los modelos de código abierto WOFOST y AquaCropOS fueron comparados usando información medida en campo. Ambos modelos son herramientas gratuitas de código abierto que permiten evaluar los impactos del clima y el agua en la agricultura. El objetivo de esta investigación fue evaluar la eficiencia de los modelos para simular el rendimiento y la formación de acumulación de biomasa sobre el suelo para un cultivo de papa en el altiplano cundiboyacense. WOFOST simula la acumulación de biomasa en los órganos del cultivo utilizando la partición de asimilados para establecer la fracción de biomasa que va al rendimiento. AquaCropOS simula la acumulación total de biomasa sobre el suelo usando la productividad de agua del cultivo (PA) y tiene en cuenta el índice de cosecha (IC) para calcular la formación del rendimiento. Los módulos de cultivo para ambos modelos fueron construidos usando información recolectada en estudios previos hechos por otros autores; estos trabajos hicieron una caracterización fisiológica y fenológica de algunas variedades de papa. Se encontró que el modelo WOFOST simula la formación del rendimiento mejor que AquaCropOS; a pesar de esto, AquaCropOS simula la acumulación total de biomasa sobre el suelo mejor que WOFOST. Sin embargo, AquaCropOS fue tan eficiente como WOFOST simulando la formación del rendimiento.
References
Boogaard, H., C. Van Diepen, R. Rötter, J. Cabrera, and Van Laar. 2014. WOFOST Control Centre 2.1 and WOFOST 7.1.7. Wageningen University and Research Centre, Wageningen, Netherlands.
Condori, B., A. de la Casa, A. Mazetti, R. Peres, S. Olarte, E. Jerez, N. Clavijo, D. Rodríguez, B. Gómez, I. Trebejo, F. Vilaró, C. García, L. Sarmiento, J. Rodríguez, and M. van den Berg. 2016. Modelación de la papa en Latinoamérica: estado del arte y base de datos para parametrización. Publications Office of the European Union, Luxembourg. Doi: 10.2788/520167
Confalonieri, R., Acutis, M., Bellocchi, G. and Donatelli, M. 2009. Multi-metric evaluation of the models WARM, CropSyst, and WOFOST for rice. Ecol. Model. 220(11), 1395-1410. Doi: 10.1016/j.ecolmodel.2009.02.017
Cortés, C., J. Bernal, E. Díaz, and F. Méndez. 2013. Uso del modelo AquaCrop para estimar rendimientos para el cultivo de papa en los departamentos de Cundinamarca y Boyacá. FAO, Colombia.
De Wit, A. 2018a. PCSE: the Python crop simulation environment. URL: https://pcse.readthedocs.io/en/stable/ (accessed 5 February 2019).
De Wit, A. 2018b. WOFOST Crop Parameters. URL: https://github.com/ajwdewit/WOFOST_crop_parameters (accessed 24 January 2019).
De Wit, A., H. Boogaard, D. Fumagalli, S. Janssen, R. Knapen, D. van Kraalingen, I. Supit, R. van der Wijngaart, and K. van Diepen. 2019. 25 years of the WOFOST cropping systems model. Agric. Syst. 168, 154-167. Doi: 10.1016/j.agsy.2018.06.018
Foster, T., N. Brozović, A.P. Butler, C.M.U. Neale, D. Raes, P. Steduto, E. Fereres, and T.C. Hsiao. 2017. AquaCrop-OS: an open source version of FAO’s crop water productivity model. Agr. Water Manage. 181, 18-22. Doi: 10.1016/j.agwat.2016.11.015
Graeff, S., J. Link, J. Binder, and W. Claupein. 2012. Crop models as decision support systems in crop production. pp. 3-27. In: Sharma, P. (ed.). Crop production technologies. InTech, Shangai, China. Doi: 10.5772/28976
Huang, X., G. Huang, C. Yu, S. Ni, and L. Yu. 2017. A multiple crop model ensemble for improving broad-scale yield prediction using Bayesian model averaging. Field Crops Res. 211, 114-124. Doi: 10.1016/j.fcr.2017.06.011
IGAC. 2000. Estudio general de suelos y zonificación de tierras del Departamento de Cundinamarca. IGAC, Bogota.
Marcelis, L.F., E. Heuvelink, and J. Goudriaan. 1998. Modelling biomass production and yield of horticultural crops: a review. Sci. Hortic. 74(1-2), 83-111. Doi: 10.1016/s0304-4238(98)00083-1
Ñústez, C., M. Santos, and M. Segura. 2009. Acumulación y distribución de materia seca de cuatro variedades de papa (Solanum tuberosum L.) en Zipaquirá, Cundinamarca (Colombia). Rev. Fac. Nac. Agron. Medellín 62(1), 4823-4834.
Raes, D., P. Steduto, T. Hsiao, and E. Fereres. 2018. Chapter 3 - Calculation procedures. AquaCrop Version 6.0-6.1 Reference manual. FAO, Rome.
Rosenzweig, C., J. Jones, J. Hatfield, J. Antle, A. Ruane, and C. Mutter. 2015. The agricultural model intercomparison and improvement project: phase I - Activities by a global community of science. pp. 3-24. In: Ronsenzweig, C. and D. Hillel (eds.). Handbook of climate change and agroecosystems. Imperial College Press, London. Doi: 10.1142/9781783265640_0001
Teh, C. 2006. Introduction to mathematical modeling of crop growth: how the equations are derived and assembled into a computer model. Brown Walker Press, Boca Raton, USA.
Todorovic, M., R. Albrizio, L. Zivotic, M. Abi Saab, C. Stöckle, and P. Steduto. 2009. Assessment of AquaCrop, CropSyst, and WOFOST models in the simulation of sunflower growth under different water regimes. Agron. J. 101(3), 509-521. Doi: 10.2134/agronj2008.0166s
Valbuena, R., G. Roveda, A. Bolaños, J. Zapata, C. Medina, P. Almanza, and P. Porras. 2010. Escalas fenológicas de las variedades de papa Parda Pastusa, Diacol Capiro y Criolla “Yema de Huevo” en las zonas productoras de Cundinamarca, Boyacá, Nariño y Antioquia. Corpoica, Produmedios, Bogota.
Van Genuchten, M.T., J. Simunek, F.J. Leji, and M. Sejna. 1998. RETC, version 6.0. Code for quantifying the hydraulic functions of unsaturated soils. US Salinity Laboratory, USDA, Riverside, USA.
Wallach, D., D. Makowski, J. Jones, and F. Brun. 2014. Working with dynamic crop models: methods, tools and examples for agriculture and environment. 2nd ed. Elsevier, San Diego, USA. Doi: 10.1016/C2011-0-06987-9
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