Increasing Crop Production Based on Data Mining Concepts

International Journal of Computer Science and Engineering
© 2018 by SSRG - IJCSE Journal
Volume 5 Issue 10
Year of Publication : 2018
Authors : Revathi.S, Akash.P, KarthiSankar M, B.Keerthana, S.Ashwini

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How to Cite?

Revathi.S, Akash.P, KarthiSankar M, B.Keerthana, S.Ashwini, "Increasing Crop Production Based on Data Mining Concepts," SSRG International Journal of Computer Science and Engineering , vol. 5,  no. 10, pp. 3-6, 2018. Crossref, https://doi.org/10.14445/23488387/IJCSE-V5I10P102

Abstract:

Effective crop management is based on selecting suitable crops based on soil properties in certain region. Data mining algorithms and their application plays a vital role in the domain of agriculture. Most of the crops are preferred based on the physical and chemical properties of soil to achieve the successful crop management which leads to the higher yield performance. This work surveys and analyzes soil properties in existing research with respect to the following areas:1. Main objective of the research, 2.Soil parameters, 3.Data mining technique or algorithm, 4.Performance analysis of existing works. The main focus is on the application of data mining techniques in agricultural field and also the process of discovering the knowledge in from soil database. It also explores the various chemical and physical properties of soil in agricultural land.

Keywords:

Data mining techniques, knowledge discovery, Crop management, higher yield, Soil properties

References:

[1] Shakil Ahamed, A.T.M.; Mahmood, N.T.; Hossain, N.; Kabir, M.T.; Das, K.; Rahman, F.; Rahman, R.M., "Applying data mining techniques to predict annual yield of major crops and recommend planting different crops in different districts in Bangladesh," in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2015 16th IEEE/ACIS International Conference on , vol., no., pp.1-6, 1-3 June 2015 doi: 10.1109/SNPD.2015.7176185 
[2] Yi-Ping Wang. Yuvan Shen. “Identifying and characterizing yield limiting soil factors with the aid of remote sensing and data mining techniques”, Precision Agriculture, 2015, Vol. 16(1), pp. 99-118 doi: 10.1007/s11119-014-9365-6 
[3] R.A.Viscarra Rossel, T.Behrens. “Using data mining to model and interpret soil diffuse reflectance spectra”, Geoderma, 2010, Vol. 158, pp. 46-54 doi: 10.1016/j.geoderma.2009.12.025 
[4] H.Borman, “Assessing the soil texture –specific sensitivity of simulated soil moisture to projected climate change by SVAT modeling”,Geoderma, 2012, Vol. 185-186, pp. 73-83 doi: 10.1016/j.geoderma.2012.03.021 
[5] Cecile Gomez, Phillipe Lagacherce, Guillaume Coulouma, “Regional predictions of eight common soil properties and their spatial structures from hyper spectral Vis-NIR data”,Geoderma, 2012, Vol. 189-190, pp.176-185 doi: 10.1016/j.geoderma.2012.05.023 
[6] S.M. Bateni, D.-S. Jeng, S.M. Mortazavi Naeini, “Estimating soil thermal properties from sequences of land surface temperature using hybrid genetic algorithm-finite difference method”, Engineering Applications of Artificial Intelligence, 2012, Vol. 25, pp. 1425-1436 doi: 10.1016/j.engappai.2012.02.017 
[7] Johan Arvidsson, Aron Westlin, Fredrik Sörensson, “Working depth in non-inversion tillage-effects on soil physical properties and crop yield in Swedish field experiments”, Soil and Tillage Research, 2013, Vol. 126, pp. 259-266. doi: 10.1016/j.still.2012.08.010 
[8] Adriana Pereira da Silva, Adriana Pereira, Letícia Carlos Babujia, Julio Cezar Franchini, Ricardo Ralisch, Mariangela Hungria, and Maria de Fátima Guimarães. "Soil structure and its influence on microbial biomass in different soil and crop management systems." Soil and Tillage Research, 2014, Vol. 142, pp. 42-53 doi: 10.1016/j.still.2014.04.006 
[9] M.E.Holzman, R. Rivas, M.C. Piccolo,“Estimating soil moisture and the relationship with crop yield using surface temperature and vegetation index” International Journal of Applied Earth Observation and Geoinformation, 2014, Vol. 28, pp.181-192 doi: 10.1016/j.jag.2013.12.006 
[10] N.Nassi o Di Nasso, M.V. Lasorella, N. Roncucci, E. Bonari ,“ Soil texture and crop management affect switchgrass (Panicum virgatum L.) productivity in the Mediterranean”, Industrial Crops and Products 2015, Vol. 65, pp. 21-26 doi: 10.1016/j.indcrop.2014.11.017 
[11] Sara Marinari, Roberto Mancinelli, Paola Brunetti, Enio Campiglia,“Soil quality, microbial functions and tomato yield under cover crop mulching in the Mediterranean environment”, Soil and Tillage Research , 2015, Vol. 145, pp. 20-28 doi: 10.1016/j.still.2014.08.002