Abstract
Agronomic and agricultural research in East Morocco depends on time and space evolution of the soil, which is an important factor, otherwise, limiting plant cover.
Thus, a chemical and physicochemical soil study was assisted by advanced techniques such as data mining. Today, data exploitation on a global scale is used in a large number of vast agribusiness operating areas. Products of computer operating systems and specific domain data extrapolation are applicable across the disciplines; however they are still relatively new on agriculture.
This work aims to evaluate the feasibility of the conversion of wheat crops into olive crops, based on the evaluation of the soil’s ability of the region to withstand the conversion, which is an axis of the Green Morocco Plan for the horizon of 2020.
This paper presents our approach to soil data analysis in order to determine the usefulness of the execution of this strategy, in the eastern of Morocco and its corresponding results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kumar A., Kannathasan, N.: A survey on data mining and pattern recognition techniques for soil data mining. IJCSI. Int. J. Comput. Sci. Issues 8(3) (2011)
Vigneau, E., Qannari, E.M., Sahmer, K., Ladiray, D.: Classification de variables autour de composantes latentes. Revue de statistique appliquée 54(1), 27–45 (2006)
Cunningham, S., Holmes, G.: Developing innovative applications in agriculture using data mining. Department of Computer Science University of Waikato Hamilton, New Zealand, Technical report (1999)
Vamanan, R., Ramar, K.: Classification of agricultural land soils a data mining approach. Int. J. Comput. Sci. Eng. 3 (2011). ISSN: 0975-3397
Bhargavi, P., Jyothi, S.: Soil classification using data mining techniques: a comparative study. Int. J. Eng. Trends Technol. 2, 55 (2011)
Dougherty, J., Kohavi, R., Sahami, M.: Supervised and unsupervised discretization of continuous features (1995)
Découpages en classes et discrétisation, Gilles Hunault, Université d’Angers
Nakache, J.P., Confais, J.: Approche Pragmatique de la Classification, TECHNIP, chapitre 9, pp. 219–239 (2005)
Tanagra Tutoriels: Association rules (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Belabed, I., Alaoui, M.T., Belabed, A., Alaoui, Y.T. (2017). Analysis of Soil Data from Eastern of Morocco Based on Data Mining Process. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10209. Springer, Cham. https://doi.org/10.1007/978-3-319-56154-7_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-56154-7_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-56153-0
Online ISBN: 978-3-319-56154-7
eBook Packages: Computer ScienceComputer Science (R0)