RETRACTACIÓN: Sistema difuso para la recomendación de planes de fertilización en ganadería de leche

Jorge Eliecer Giraldo Plaza; Luis Fernando Londoño Franco; Carlos Alberto Perez Buelvas; Eddie Yacir Alvarez Alabanes

doi:10.21500/20275846.6030

Submitted: 2022-07-26

Published: 2023-05-20

DOI: 10.21500/20275846.6030

Fuzzy system for the recommendation of fertilization plans in dairy farming

Jorge Eliecer Giraldo Plaza

Docente

Luis Fernando Londoño Franco

Carlos Alberto Perez Buelvas

Eddie Yacir Alvarez Alabanes

View/Download

PDF (Español (España))

FLIP

Dimensions

PlumX

Doi

https://doi.org/10.21500/20275846.6030

Issue: Vol. 14 No. 1 (2023): Ingenierías USBMed

How to Cite

Giraldo Plaza, J. E., Londoño Franco, L. F., Perez Buelvas, C. A., & Alvarez Alabanes, E. Y. (2023). Fuzzy system for the recommendation of fertilization plans in dairy farming. Ingenierías USBmed, 14(1), 14–21. https://doi.org/10.21500/20275846.6030

More Citation Formats

ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver

Download Citation

Endnote/Zotero/Mendeley (RIS) BibTeX

License terms ▼

This journal provides immediately free access to its contents under the principle that make available the research results for free to the public, helps for a greater global exchange of knowledge.

Therefore, the journal invokes the Creative Commons 4.0

License attributions: Recognition – Non-commertial - Share equal. Commercial use and distribution of original or derivative works are not permitted and must be done with a equal license as the one that regulate the original work.

Abstract

Fertilization plans for soils and grasslands consist of establishing physicochemical factors that improve its characteristics. This paper aims the fuzzy recommendation system design for fertilization plans. Initially, a characterization of the variables for a precise soil fertilization is made, determining those that generate greater affectation from the correlation between them. Thus, we define the input and output of fuzzy sets, as well as the membership functions and linguistic variables about ideal ranges in low, medium and high productions according to the extraction of macronutrients. The main result is a general scheme of an intelligent recommendation system based on fuzzy logic, which shows that the use of Industry 4.0 technologies has potential applications for control and management in the dairy farming

Keywords:

Dairy Farming

Fuzzy System

Fertilization Plan

Recommendation

References

[1] Torres Rozo, J. S. Protocolo sobre la atención del puerperio en el ganado bovino del complejo agroindustrial de Tizayuca en su estado actual, Hidalgo, México (Doctoral dissertation, Universidad Cooperativa de Colombia, Facultad de Ciencias de la Salud, Medicina Veterinaría y Zootecnia, Bucaramanga). 2020.

[2] IAEA. Gestión de la tierra y el agua. Organismo internacional de energía atómica, alimentación y agricultura. 2020. Recuperado el 7 enero en: https://www.iaea.org/es/temas/mejora-de-la-fertilidad-del-suelo#:~:text=La%20fertilidad%20del%20suelo%20es,inorg%C3%A1nicos%20que%20nutran%20el%20suelo.

[3] Martínez-España, R., Bueno-Crespo, A., Soto, J., Janik, L. J., & Soriano-Disla, J. M. (2019). Developing an intelligent system for the prediction of soil properties with a portable mid-infrared instrument. Biosystems Engineering, 177, 101-108.

[4] Bodake, K., Ghate, R., Doshi, H., Jadhav, P., & Tarle, B. (2018). Soil based fertilizer recommendation system using Internet of Things. MVP J. Eng. Sci, 1, 13-19.

[5] Konaté, J., Diarra, A. G., Diarra, S. O., & Diallo, A. (2020). Syragri: A recommender system for agriculture in Mali. Information, 11(12), 561.

[6] Jaiswal, S., Kharade, T., Kotambe, N., & Shinde, S. (2020). Collaborative recommendation system for agriculture sector. In ITM web of conferences (Vol. 32, p. 03034). EDP Sciences.

[7] Jadhav, M., Kolambe, N., Jain, S., & Chaudhari, S. (2021, May). Farming made easy using machine learning. In 2021 2nd International Conference for Emerging Technology (INCET) (pp. 1-5). IEEE.

[8] Heiß, A., Paraforos, D. S., Sharipov, G. M., & Griepentrog, H. W. (2020). Modelling and Simulation of a Fuzzy System for Site-Specific Nitrogen Fertilization. IFAC-PapersOnLine, 53(2), 15790-15795.

[9] Rajeswari, A. M., Anushiya, A. S., Fathima, K. S. A., Priya, S. S., & Mathumithaa, N. (2020, June). Fuzzy Decision Support System for Recommendation of Crop Cultivation based on Soil Type. In 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184) (pp. 768-773). IEEE.

[10] Haban, J. J. I., Puno, J. C. V., Bandala, A. A., Billones, R. K., Dadios, E. P., & Sybingco, E. (2020, November). Soil Fertilizer Recommendation System using Fuzzy Logic. In 2020 IEEE REGION 10 CONFERENCE (TENCON) (pp. 1171-1175). IEEE.

[11] De, A., & Singh, S. P. (2021). Analysis of fuzzy applications in the agri-supply chain: A literature review. Journal of Cleaner Production, 283, 124577.

[12] Samir Kouro R. y Rodrigo Musalem R. Técnicas modernas en automática. Control mediante lógica difusa. Universidad Técnica Federico Santa María. 2002. Recuperado de: http://www2.elo.utfsm.cl/~elo377/documentos/Fuzzy.pdf

[13] Giraldo E. Caracterización de variables para una fertilización precisa de suelos y praderas en ganadería de leche, un estudio técnico de campo para la sugerencia de un sistema de recomendación. Proyecto en curso, Politécnico Colombiano Jaime Isaza Cadavid, Unpublished. 2022.

[14] Montoya C. J. Evaluación de la Adopción Tecnológica de los Sistemas Silvopastoriles en el Municipio San Pedro de los Milagros – Antioquia. UNAD, Medellín. 2021. Recuperado el 28 enero https://repository.unad.edu.co/bitstream/handle/10596/39194/cjmontoyav.pdf?sequence=3&isAllowed=y.

[15] Echeverri J., Aristizabal M., Moreno F. y Bedoya Alejandra. Diseño de un sistema difuso para valoración de aportes en sistemas colaborativos. Rev. ing. univ. Medellín 11(20). 2012.