A STRATEGY TO MOTIVATE FRESHMAN AGRONOMY STUDENTS FOR THE USE OF APPLIED COMPUTING TECHNOLOGY

Authors

João E. M. Perea Martins Computer Science Department, School of Sciences (FC), São Paulo State University (UNESP), Bauru-SP, Brazil
Eduardo Oyanedel Dirección General de Investigación y Postgrado, Universidad Viña del Mar, Viña del Mar, Chile.
Manuel Flores Cabrales Escuela de Ciencias Agrícolas y Veterinarias, Universidad Viña del Mar, Viña del Mar, Chile.
Edvaldo José Scoton Agronomic Engineering Departament, Sagrado Coração University Center (UNISAGRADO), Bauru-SP, Brazil,

Keywords:

Mathematical processing, temperature map, Greenhouse

Abstract

This work objective is to propose a class activity that combines technological and agricultural aspects with the purpose of motivating freshmen students of agronomy to think about the use of computing technology applications in the agricultural area. The methodology was based on a 2-hour practical class in a computer lab where the students, most with no previous knowledge, use mathematical processing software to generate a color map of the temperature variation inside a greenhouse. This article shows step by step activity design, which can facilitate its reproduction even by professors without knowledge in this area of computing. Finally, this work proves qualitatively and quantitatively that its results were satisfactory to motivate the students to learn more about applied technology.

References

Burrows, Andrea C. et al. (2021), Finding spaces: Teacher education technology competencies (TETCs). Education Sciences, 11(11), 733

Kotrlik, Joe W. et al. (2000), Information technology related professional development needs of Louisiana agriscience teachers. Journal of Agricultural Education, 41(1), 18-29

Kersaint, Gladis, 2007. Toward technology integration in mathematics education: A technology-integration course planning assignment. Contemporary Issues in Technology and Teacher Education, 7(4), 256-278

Choab, Noureddine et al. 2019. Review on greenhouse microclimate and application: Design parameters, thermal modeling and simulation, climate controlling technologies, Solar Energy, 191, Doi: https://doi.org/10.1016/j.solener.2019.08.042.

Hasan, O. Z. et al. 2009, The efficiency of fan-pad cooling system in greenhouse and building up of internal greenhouse temperature map. African Journal of Biotechnology, 8(20)

Bojacá, C. R. et al. 2009, Analysis of greenhouse air temperature distribution using geostatistical methods. Transactions of the ASABE, 52(3), 957-968

Barbosa, R. Z.; Perea Martins, J. E. M. 2018, Design of a wireless sensor network for greenhouses temperature analysis. Irriga, 1(1), 132-138.

Ferrante, antonio; mariani, luigi. Agronomic management for enhancing plant tolerance to abiotic stresses: High and low values of temperature, light intensity, and relative humidity. Horticulturae, 4(3), 21, 2018.

Nievola, Catarina C. et al. Rapid responses of plants to temperature changes. Temperature, 4(4), 371-405, 2017.

Sandhu S. S. et al, Chap. 7 Heat Stress in Field Crops: Impact and Management Approaches, in Advances in Crop Environment Interaction, Editors: Dhawan, A. K. et al, Springer Singapore, ISBN:9789811318610, 2018.

Hussain, S., Khaliq, A., Ali, B., Hussain, H.A., Qadir, T., Hussain, S. Temperature Extremes: Impact on Rice Growth and Development. In: Plant Abiotic Stress Tolerance, editors Hasanuzzaman, M et al. Springer, Cham. https://doi.org/10.1007/978-3-030-06118-0_6, 2019

Bhattacharya, A. Physiological Processes in Plants Under Low Temperature Stress. Singapura, Springer Singapore Ed., ISBN 978-981-16-9037-2, https://doi.org/10.1007/978-981-16-9037-2, 2022.

World Meteorological Organization (WMO). Guide to Meteorological Instruments and Methods of Observation. WMO Geneva, Switzerland. DOI: http://dx.doi.org/10.25607/OBP-432, 2014 Edition, updated in 2017

Maclean, Ilya M et al. On the measurement of microclimate. Methods in Ecology and Evolution, 12(8), 1397-1410, 2021.

Burt, S.; de Podesta, M. Response times of meteorological air temperature sensors, Quarterly Journal of the Royal Meteorological Society, 146, 2789–2800. https://doi.org/10.1002/qj.3817, 2020.

Pirsa, S. Chemeresistive. Chap 6 - Gas Sensors Based on Conducting polymer, in Handbook of research on nanoelectronic sensor modeling and applications. IGI Global, Editors Ahmadi, M. T. el al. 2016

Qiwen S. et al. High resolution, fast response fiber-optic temperature sensor with reduced end conduction effect, Optical Letters. 45, 6094-6097, 2020

Liu R, He L, Cao M, Sun Z, Zhu R, Li Y. Flexible Temperature Sensors. Frontiers in Chemistry, 9, doi: 10.3389/fchem.2021.539678, 2021.

Andreas Stahel, “Octave and Matlab for Engineers”, Bern University of Applied Sciences, Biel-Switzerland, licensed under a Creative Commons Attribution, 2020

Miguel, J. MATLAB Handbook with Applications to Mathematics, Science, Engineering, and Finance. Chapman and Hall/CRC Ed., 2019.

Hansen, J. S. "GNU Octave - Beginner's Guide", Packt Publishing Ltd.,Birmingham, UK.ISBN 978-1-849513-32-6, 2011

Lodovico, Jerry. The Genius Code: The Twelve Pillars of Creative Genius. iUniverse Ed. USA, ISBN 9780595452040, 2008.

Goldblatt, Joe. Special Events: A New Generation and the Next Frontier. Wiley Ed. UK, ISBN 9780470449875, 2010.

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Published

2023-08-21

How to Cite

João E. M. Perea Martins, Eduardo Oyanedel, Manuel Flores Cabrales, & Edvaldo José Scoton. (2023). A STRATEGY TO MOTIVATE FRESHMAN AGRONOMY STUDENTS FOR THE USE OF APPLIED COMPUTING TECHNOLOGY. European Journal of Agricultural and Rural Education, 4(8), 4-13. Retrieved from https://scholarzest.com/index.php/ejare/article/view/3794