The use of multivariate statistical analysis and soil quality indices as tools to be included in regional management plans. A case study from the Mashhad Plain, Iran


  • J. Rodrigo-Comino PhD Student of Geography/ Estudiante de Doctorado de Geografía Universität Trier/University of Trier (Germany) Universidad de Málaga/University of Málaga (Spain)
  • A. Keshavarzi Laboratory of Remote Sensing and GIS, Department of Soil Science, University of Tehran
  • A. Bagherzadeh Department of Agriculture, Islamic Azad University
  • E.C. Brevik Department of Natural Sciences, Dickinson State University



soil properties, soil quality indicators, irrigation farming, semiarid area, land degradation, land management planning, Mashhad Plain, Iran


Several methods have been used to model reality and explain soil pedogenesis and evolution. However, there is a lack of information about which soil properties truly condition soil quality indicators and indices particularly at the pedon scale and at different soil depths to be used in land management planning. Thus, the main goals of this research were: i) to assess differences in soil properties (particle size, saturation point, bulk density, soil organic carbon, pH and electrical conductivity) at different soil depths (0-30 and 30-60 cm); ii) to check their statistical correlation with soil quality indicators (CEC, total N, Olsen-P, available K, exchangeable Na, calcium carbonate equivalent, Fe, Mn, Zn, and Cu); and, iii) to elaborate a soil quality index and maps for each soil layer. To achieve this, forty-eight soil samples were analysed in the laboratory and subjected to statistical analyses by ANOVA, Spearman Rank coefficients and Principal Component Analyses. Finally, a soil quality index was developed based on indicators of sensitivity. The study was conducted in a semiarid catchment in northeast Iran with irrigated farming and well-documented land degradation issues. We found that: i) organic carbon and bulk density were not similar in the topsoil and subsoil; ii) calcium carbonate and sand content conditioned organic carbon content and bulk density; iii) organic carbon showed the highest correlations with soil quality indicators; iv) particle size conditioned cation-exchange capacity; and, v) heavy metals such as Mn and Cu were highly correlated with organic carbon due to non-suitable agricultural practices. Based on the communality analysis to map of soil quality, CEC, Mn, Zn, and Cu had the highest weights (≥0.11) at both depths, coinciding with the same level of relevance in the multivariate analysis. Exchangeable Na, CaCO3, and Fe had the lowest weights (≤0.1) and N, P, and K had intermediate weights (0.1- 0.11). In general, the map of the soil quality index shows a lower soil quality in the subsoil increment than in the topsoil.


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Author Biography

J. Rodrigo-Comino, PhD Student of Geography/ Estudiante de Doctorado de Geografía Universität Trier/University of Trier (Germany) Universidad de Málaga/University of Málaga (Spain)

Licenciado en Geografía  por la Universidad de Málaga en el curso   2011-2012. Realizó el Trabajo Fin de Carrera (tesina) bajo la dirección   del Dr. Senciales titulado: “Los suelos de la provincia de Málaga:   Revisión en función de los criterios de la clasificación de FAO-WRB   (2006)”. También con él, ha publicado una serie de artículos   relacionados con cuestiones geomorfológicas en los Montes de Málaga o   las plataformas travertínicas. Ha participado en actividades de  Didáctica de la  Geografía con jóvenes preuniversitarios, publicando  resultados de esta  actividad en revistas de la Asociación de Geógrafos  Españoles junto con  el Dr. Delgado Peña. Está preparando la tesis  doctoral sobre procesos geomorfológicos en viñedos (Valle del Mosela y Axarquía),en colaboración con la Universidad de Trier (Alemania) con los profesores  Johannes Ries y Manuel Seeger y con el Departamento de Geografía de la Universidad de Málaga con los profesores José Damián Ruiz Sinoga y José María Senciales.


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How to Cite

Rodrigo-Comino J, Keshavarzi A, Bagherzadeh A, Brevik E. The use of multivariate statistical analysis and soil quality indices as tools to be included in regional management plans. A case study from the Mashhad Plain, Iran. CIG [Internet]. 2019 Sep. 4 [cited 2023 May 28];45(2):687-708. Available from: