Behavior model of average temperatures in the tomato crop (Solanum licopersicum)
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Abstract
Mathematics has continued to increase its presence in the sciences and in the economic sectors, in general. Along with information technologies, huge volumes of data are processed that facilitate analysis and serve for objective decision-making. The avoidance of agricultural risks is a task of the first order to safeguard food security and thus reducing the vegetative periods in crops is an effective strategy to achieve it. The work is carried out in the Babahoyo canton, Los Ríos province on obtaining behavior models of air temperatures that facilitate, through the application of Differential Calculation, obtaining the dates of maximum temperatures, which would allow obtaining the periods of higher temperatures. thermal supply to accelerate growth and development processes. The dates of maximum temperature were located around decade 7, between March 13 and 17, results of the sum of probabilities for 75%. The sums of temperatures obtained fluctuate in the range 2170 – 2266 Celsius Degrees that guarantee the acceleration of the vegetative period, since they have 100% of the sum of probabilities of being reached. Observe a management directed to the selection of the period of highest temperature will reduce the risks of pests and extreme events, in addition to reducing inputs in agricultural production, which will increase the sustainability of the system.
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References
Chandola, V.; Hui, D.; Gu, L.; Bhaduri, B. & Vatsavai, R. 2010. “Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data”. IEEE International Conference on Data Mining Workshops, Massachusetts Ave., NW Washington DC, United States: IEEE Computer Society, pp. 202-208, ISBN: 978-0-7695-4257-7. DOI: 10.1109/ICDMW.2010.143. Available:
Chávez Esponda, D.; Sabín, Y.; Toledo, V. & Jiménez, Y. 2013. “La Matemática: una herramienta aplicable a la Ingeniería Agrícola”. Revista Ciencias Técnicas Agropecuarias, 22(3): 81-84.
Costanza, R.; D’Arge, R.; de Groot, R.; Farberk, S.; Grasso, M.; Hannon, B.; Limburg, K.; Naeem, N. O’Neill, R.; Paruelo, J.; Raskin, R.; Suttonkk, P. & van den Belt, M. 1998. “The value of the world’s ecosystem services and natural capital”. Nature, 387: 253-260.
De Fina, A. & Ravelo, A., 1979. Climatología y fenología agrícolas. 3ra ed. Lugar: Editorial Universitaria de Buenos Aires (Eudeba), 354 p.
Delire, C.; Ngomanda, A. & Jolly, D. 2008. “Possible impacts of 21st century climate on vegetation in Central and West Africa”. Global and Planetary Change, 64(1): 3-15. DOI: 10.1016/j.gloplacha.2008.01.008.
Eldin, M., Rojas, O. 1983. A System of Agroclimatic Zoning to Evaluate Climatic Potential for Crop production. In: Cusak, D. F. (eds.). Agroclimatic Information for Development. Reviving the Green Revolution. Boulder, Colorado (USA), Westview, 83-91.
Elikana, J.; Bunting, P.; Hardy, A.; Roberts, O.; Giliba, R. & Silayo, D. 2020. “Modelling the impact of climate change on Tanzanian forest”. Diversity and Distributions,26: 1663-1686. Wiley. DOI: 10.1111/ddi.13152.
Jönson P. & Eklundh L. 2004. “TIMESAT— a program for analyzing time-series of satellite sensor data”. Computers & Geosciences 30(8): 833-845. https://doi.org/10.1016/j.cageo.2004.05.006.
Ortega, D. 2000. Perfeccionamiento de la enseñanza de la Matemática en la carrera de Agronomía. Tesis de Maestría en Pedagogía Aplicada a las Ciencias Agrícolas. Universidad Central “Marta Abreu” de Las Villas. Facultad de Matemática, Física y Computación. Departamento de Matemática, Cuba, 95 p.
Pan, S.; Dangal, S.; Tao, B.; Yang, J. & Tian, J. 2015. “Recent patterns of terrestrial net primary production in Africa influenced by multiple environmental changes”. Ecosystem Health and Sustainability, 1(5): 1-15. https://doi.org/10.1890/EHS14-0027.1.
Pan, S.; Tian, H.; Dangal, S.; Ouyang, Z.; Tao, B.; Ren, W.; Lu, Ch.; & Running, S. 2014. “Modeling and monitoring terrestrial primary production in a changing global environment: toward a multiscale synthesis of observation and simulation”. Advances in Meteorology, 2014(965936): 1-17, http://dx.doi.org/10.1155/2014/965936.
Plaza, L. 2011. “Modelamiento matemático de fenómenos cíclicos”. Scientia et Technica Año XVI, 48: 148 -150. Universidad Tecnológica de Pereira. ISSN 0122-1701.
Rodríguez, L. F. & Bermúdez, T. 1995. “Usos y aplicaciones de la simulación en la investigación agropecuaria”. Agronomía Colombiana, 12(2): 198-204.
San Martin, J.; Uña, J. & Tomeo, P. V. 2005. Ampliación de Matemáticas para Ciencias e Ingeniería. In: De la Fuente, C.; García, C. & Vicente, O. (eds.), Métodos Matemáticos. Madrid: Editorial THOMSON: 1-17, ISBN: 84-9732-288-6, Available:
Tiedenman, J. 2015. “Phenology and aboveground net primary productivity of panicum maximum pastoralist systems in the department of Moreno, Santiago del Estero, Argentina, derived from Modis NDVI”. Ecología Aplicada, 14(1): 27-39, ISSN 1726-2216, DOI:10.21704/rea.v14i1-2.79.
Vitousek, P. M.; Ehrlich, P. R.; Ehrlich, A. & Matson, P. A., 1986. “Human appropriation of the products of photosynthesis”. BioScience, 36(6): 368-373. ISSN: 0006-3568.
Yang, H.; Hu, D.; Xu, H. & Zhong, X. 2020. “Assessing the spatiotemporal variation of NPP and its response to driving factors in Anhui province, China”. Environmental Science and Pollution Research, 27: 14915-14932. https://doi.org/10.1007/s11356-020-08006-w.