Open Access   Article Go Back

Complex analysis of classified of Soil parameters and its relationship identification using PCA

M.V.Mawale 1 , V.N.Chavan 2

  1. Dept of Computer Science. Adarsha Science,J.B.Arts & Birla Commerce Mahavidyalaya,SGBAU Amravati University, Dhamangaon Rly,India.
  2. Dept. Of Computer Science &IT, Seth Kesarimal Porwal College, Kamptee, Nagpur M.S.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-4 , Page no. 61-70, Apr-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i4.6170

Online published on Apr 30, 2018

Copyright © M.V.Mawale, V.N.Chavan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: M.V.Mawale, V.N.Chavan, “Complex analysis of classified of Soil parameters and its relationship identification using PCA,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.61-70, 2018.

MLA Style Citation: M.V.Mawale, V.N.Chavan "Complex analysis of classified of Soil parameters and its relationship identification using PCA." International Journal of Computer Sciences and Engineering 6.4 (2018): 61-70.

APA Style Citation: M.V.Mawale, V.N.Chavan, (2018). Complex analysis of classified of Soil parameters and its relationship identification using PCA. International Journal of Computer Sciences and Engineering, 6(4), 61-70.

BibTex Style Citation:
@article{_2018,
author = {M.V.Mawale, V.N.Chavan},
title = {Complex analysis of classified of Soil parameters and its relationship identification using PCA},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2018},
volume = {6},
Issue = {4},
month = {4},
year = {2018},
issn = {2347-2693},
pages = {61-70},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1846},
doi = {https://doi.org/10.26438/ijcse/v6i4.6170}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i4.6170}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1846
TI - Complex analysis of classified of Soil parameters and its relationship identification using PCA
T2 - International Journal of Computer Sciences and Engineering
AU - M.V.Mawale, V.N.Chavan
PY - 2018
DA - 2018/04/30
PB - IJCSE, Indore, INDIA
SP - 61-70
IS - 4
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
1058 722 downloads 373 downloads
  
  
           

Abstract

This study was carried out to predict meaningful information from large data set of soil parameters and representation in graphical manner to make its clear understanding This analysis help in determining role of dependent variable and independent variable in the system and their relationships, their dependability for designing any prediction system. A field study is carried out to collect information for assessing soil parameter. Soil parameters analysis is done on 902 soil samples collected from KrushiVighan Kendra, Ghatkhed, Amravati. The values of C, N, P, K, Mg, C, Fe, Cu, Zn, B, Mo, Lime, Saline, CEC, Mn, OM and pH of soil sample collected for the year 2011-2012 and 2012-2013 andPrinciple Component Analysis (PCA) is used to predict these soil parameters as a dependent and independent parameter that have direct/indirect effects on productivity.

Key-Words / Index Term

complex analysis.soilparameter,Principle Component Analysis,Cu_copper, Fe_iron; ; K_potassium; Mn_manganese; OC_organic content: P_ phosphorus; Zn_zinc.

References

[1] Kevin Mc-Sweeney, Sabine Grunwald,,Soil Morphology, Classification, and Mapping, University of Wisconsin- Madison , 1999
[2] R. M. Larka, S. R. Kaffkab, D. L. Corwinca, Multi-resolution analysis of data on electrical conductivity of soil using wavelets, Journal of Hydrology Vol. 272, pp 276–290, 2003
[3] Abdi. H. & Williams L. J., Principal component analysis, Wiley Interdisciplinary Reviews Computational Statistics, Vol. 2, pp. 433– 459, 2010.
[4] Ali Salehi1 and G. ZahediAmiri, Study of Physical and Chemical Soil Properties Variations Using Principal Component Analysis Method in the Forest, North of Iran, Caspian J. Env. Sci. Vol. 3 No. 2, pp. 131-137, 2005.
[5] A Xing Zhu,Feng Qi,Amanda Moore,James E Burt,Prediction of soil properties using membership values Geoderma, Vol.158, pp.199–206, 2010.
[6] P. Bhargavi , Dr. S. Jyothi, Soil Classification Using Data Mining Techniques:A Comparative Study, International Journal of Engineering Trends and Technology- July to Aug,Vol.2, Issue 1,pp.55-59,2011.
[7] M. Kumar & A. L. Babel, Available Micronutrient Status and Their Relationship with Soil Properties of Jhunjhunu Tehsil, District Jhunjhunu, Rajasthan, India, Journal of Agricultural Science, Vol 3, No 2, pp 102-118, 2011.
[8] J.O. Ogunwole, E.N. O. Iwuafor, N.M. Eche, J. Diels, Effect of organic and inorganic soil amendments on soil physical and chemical properties in a west africa savanna agroecosystem,Tropical and Subtropical Agroecosystems, Vol. 12, No. 2, pp. 247-255, 2010.
[9] A.Akbarzadeh,R.Taghizadeh,Mehrjardi H. Rahimi Lake & H.Ramezanpour,Application of artificial intelligence in modeling of soil properties,Enviromental Research Journal Vol.3,No.2,pp.19-24,2009.