Crop water use estimation of drip irrigated walnut using ANN and ANFIS models
Dökmen, Funda; Ahi, Yeşim; Köksal, Daniyal D.
Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM, publicado en Atmósfera, y cosechado de Revistas UNAM
dor_id: 4134805
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590.#.#.d: Los artículos enviados a la revista "Atmósfera", se juzgan por medio de un proceso de revisión por pares
510.0.#.a: Consejo Nacional de Ciencia y Tecnología (CONACyT); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Scientific Electronic Library Online (SciELO); SCOPUS, Web Of Science (WoS); SCImago Journal Rank (SJR)
561.#.#.u: https://www.atmosfera.unam.mx/
561.#.#.a: no
650.#.4.x: Físico Matemáticas y Ciencias de la Tierra
336.#.#.b: article
336.#.#.3: Artículo de Investigación
336.#.#.a: Artículo
351.#.#.6: https://www.revistascca.unam.mx/atm/index.php/atm/index
351.#.#.b: Atmósfera
351.#.#.a: Artículos
harvesting_group: RevistasUNAM
270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx
590.#.#.c: Open Journal Systems (OJS)
270.#.#.d: MX
270.1.#.d: México
590.#.#.b: Concentrador
883.#.#.u: https://revistas.unam.mx/catalogo/
883.#.#.a: Revistas UNAM
590.#.#.a: Coordinación de Difusión Cultural
883.#.#.1: https://www.publicaciones.unam.mx/
883.#.#.q: Dirección General de Publicaciones y Fomento Editorial
850.#.#.a: Universidad Nacional Autónoma de México
856.4.0.u: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/53149/46901
100.1.#.a: Dökmen, Funda; Ahi, Yeşim; Köksal, Daniyal D.
524.#.#.a: Dökmen, Funda, et al. (2023). Crop water use estimation of drip irrigated walnut using ANN and ANFIS models. Atmósfera; Vol. 37, 2023; 295-310. Recuperado de https://repositorio.unam.mx/contenidos/4134805
245.1.0.a: Crop water use estimation of drip irrigated walnut using ANN and ANFIS models
502.#.#.c: Universidad Nacional Autónoma de México
561.1.#.a: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
264.#.0.c: 2023
264.#.1.c: 2023-03-07
653.#.#.a: artificial intelligence; data analysis; evapotranspiration; semi-arid climate; irrigation
506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC 4.0 Internacional, https://creativecommons.org/licenses/by-nc/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico editora@atmosfera.unam.mx
884.#.#.k: https://www.revistascca.unam.mx/atm/index.php/atm/article/view/53149
001.#.#.#: 022.oai:ojs.pkp.sfu.ca:article/53149
041.#.7.h: eng
520.3.#.a: Walnut trees, as well as their fruits, represent an important sector of the agricultural industry and their cultivation significantly contributes to the global economy. Irrigation is a key factor in walnut cultivation and its most important problem is related to accurately estimating the need for irrigation water. Walnut water use was estimated in this study through artificial intelligence methods, namely artificial neural networks (ANN) and the adaptive neuro-fuzzy inference system (ANFIS) using meteorological data in western Turkey, which has semi-arid climatic conditions. Probabilistic scenarios based on maximum, minimum and average temperature, wind speed and sunshine hours over the period 2016-2019 were developed and tested with ANN and ANFIS to estimate walnut evapotranspiration. Results indicate that the optimum performance in the training and testing for ANN and ANFIS was obtained from the fourth scenario with R = 0.95 and two climate parameters: sunshine duration and mean temperature. Both ANN and ANFIS were able to predict crop water use obtaining a high correlation and the minimum number of climatic parameters. Nevertheless, the ANFIS model had a higher predictive capacity, with smaller MSE (0.36 for training and 0.29 for testing) compared to the ANN model.
773.1.#.t: Atmósfera; Vol. 37 (2023); 295-310
773.1.#.o: https://www.revistascca.unam.mx/atm/index.php/atm/index
022.#.#.a: ISSN electrónico: 2395-8812; ISSN impreso: 0187-6236
310.#.#.a: Trimestral
300.#.#.a: Páginas: 295-310
264.#.1.b: Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM
doi: https://doi.org/10.20937/ATM.53149
handle: 00e4f0cc7b56be17
harvesting_date: 2023-06-20 16:00:00.0
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file_creation_date: 2023-03-07 17:25:00.0
file_modification_date: 2023-03-07 17:25:01.0
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last_modified: 2023-06-20 16:00:00
license_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode.es
license_type: by-nc
Dökmen, Funda; Ahi, Yeşim; Köksal, Daniyal D.
Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM, publicado en Atmósfera, y cosechado de Revistas UNAM
Dökmen, Funda, et al. (2023). Crop water use estimation of drip irrigated walnut using ANN and ANFIS models. Atmósfera; Vol. 37, 2023; 295-310. Recuperado de https://repositorio.unam.mx/contenidos/4134805