Assessment of Single and Multivariate Soil Quality Indices in the Part of Sarab Plain Agricultural Lands (East Azerbaijan Province)

Document Type : Research Article

Authors

1 Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.

2 Department of Soil and Water Research, East Azerbaijan Agricultural and Natural Resources Research and Education Center, Agricultural Research,Education and Extension Organization (AREEO), Tabriz, Iran.

Abstract

Background and Objectives
Soil quality concept was initiated for the realization and strengthening of soil sustainable management particularly for sustained yield production as early as 1990 decade. At the time it was a qualitative concept but later evolved and expressed in quantitative term as soil quality index (SQI). Briefly, it is based on selecting soil properties (referred as indicators) that attribute to general soil wellness or particular soil function (e.g. yield production, nutrient cycling, carbon sequestration etc.), assigning an appropriate score (0 to 1) for each indicator and integrating (averaging) the scores and expressing the outcome as SQI. Substantial researches have been carried out on various aspects of the issue including indicators selection, their scoring, and score integration. However most of them have been generally-oriented or generally-purposed meaning that no particular or specific goal(s) has been in mind of the investigator. The SQI has often been determined by using the total available data (TDS) or a minimum set of data (MDS), hear after would be referred as multivariate based SQI. In the present study, we also investigated S-index, relative bulk density (RBD) and least limiting water range (LLWR) by referring to them as a single variable quality index. The assessment of those multi and single variable based SQI in relation to winter wheat yield production was the major goal of the present research.
 
Methodology
In this research two types of indicator scoring functions (linear and non-linear) were applied to both TDS and MDS (identified by principle component analysis) to determine each selected indicator score. The scores were integrated as their simple average, weighed average, Nemero and scaled average methods. The corresponding quality indices were designated as SQISA, SQIWA, SQIN, and SQIc, respectively. Considering the single based quality indices, SD was determined using S-index proposed by Dexter, RBD according to Jones and LLWR according to da Silva et al. The pertinent parameters were obtained from soil water release and soil penetration resistance curves determined at 173 sites and wheat grain yield was recorded at all sites as well.
 
Results
Linear and non-linear indicator scorings led to SQIs ranging from 0.28 to 0.53 being significantly different at 5% probability level. The four applied score integration methods also yielded statistically significant (p<0.05) SQIs. For TDS, SQISC showed the highest quality index of 0.45 while for MDS, SQIWA was the highest (0.45). The results clearly indicated significant interaction between scoring (linear and non-linear) and score integration methods for both TDS and MDS. On the basis of SQIWA, at about 70% of the 173 studied locations, soil quality was graded as low or poor which is in accordance with low grain yield obtained at nearly 65% of those locations. This implies the potential applicability of SQIWA for wheat yield assessment at the studied area. Single variable based quality indices (SD, RBD, LLWR) were significantly (p<0.01) correlated to SQIs, meaning that instead of set of variables (TDS or MDS), a single variable (e.g. RBD) may be adequate for soil quality assessment. Among the single variable indices, the LLWR showed the highest correlation (r = 0.55**) with wheat yield. The RBD stood at the second place indicating its high adequacy for the soil quality assessment in relation to wheat yield.
 
Conclusion
Strongly significant (p<0.005) correlation between MDS-based SQIs with those TDS-based ones along with low cost and less time needed for obtaining MDS (%clay, AWC, pH, Pav., and Mnav. in the present study) in comparison to TDS (17 variables) indicated that the SQIs based on MDS may be preferred especially if periodic SQI assessment in the studied area is desired. Among the single variable based quality indices, the LLWR showed the highest correlation with grain yield indicating its potential applicability for soil quality assessment in relation to yield. Generalization of this finding needs more investigations. In the present study, accessibility to the biological soil variables which may attribute to SQIs was unfortunately impossible; their inclusion in SQIs assessment for the area would be much valuable. It was also implicitly assumed that no water stress has been occurred during the active growth period for the crop in the studied area which again needs to be considered in future investigations.
Author Contributions
Conceptualization, M. R. N. and S. R. G.; methodology, M. R. N. and S. R. G.; software, R. H. and D. Z.; validation, S. R. G. and R.  H.; formal analysis, S. R. G. and M. R. N.; investigation, S. R. G.; resources, S. R. G. and R. H.; data curation, S. R. G. and R. H.; writing- original data preparation, S. R. G.; writing-review and editing, M. R. N. and D. Z.; visualization, S. R. G.; supervision, M. R. N.; project administration, M. R. N. and D. Z.; funding acquisition, M. R. N. and S. R. G.  All authors have read and agreed to the published version of the manuscript.
 
Data Availability Statement
Data is available on reasonable request from the authors.
 
Acknowledgements
The authors are thankful to the University of Tabriz for financial supports.
 
Conflict of interest
The authors declare no conflict of interest.
 
Ethical considerations
The authors avoided data fabrication, falsification, plagiarism, and misconduct.

Keywords

Main Subjects

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Journal of Soil and Plant Science
Volume 35, Issue 1
June 2025
Pages 31-50

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