Quantification of soil quality index using pedo-morphological data of alluvial soils of indo-gangetic plains, India. Issue 7 (7th June 2023)

• Record Type: Journal Article
• Authors: Reza, S.K.; Alam, N.M.; Mukhopadhyay, S.; Nayak, D.C.; Sahoo, A.K.; Singh, S.K.; Dwivedi, B.S.; Maurya, D.; Mukhopadhyay, J.
• Is Part Of: Archives of agronomy and soil science. Volume 69:Issue 7(2023)
• Page Start: 1129
• Page End: 1145
• Publication Date: 2023-06-07
• Subjects: Alluvial soils -- pedo-morphological properties -- categorical principal component analysis (CATPCA) -- optimal scaling -- morphological soil quality index (MSQI); Horticulture -- Periodicals; Soils -- Periodicals; 630.5
• DOI: 10.1080/03650340.2022.2067982
• Languages: English
• ISSNs: 0365-0340

Abstract

ABSTRACT: This study aimed to evaluate pedo-morphological properties to quantify the soil quality of alluvial soils in Indo-Gangetic Plains, India. In total, 241 geo-referenced soil profiles were collected representing four major landforms. The optimal scaling method was used to transform the categorical variables into numerical variables and the minimum datasets (MDS) were identified by categorical principal component analysis (CATPCA). Structure type and grade, texture class was highly loaded in PC 1 and explained about 36% of the variability. Four variables e.g. texture class, root quantity, structure size and hue were selected as MDS with 44%, 23%, 18% and 15% contribution to morphological soil quality index (MSQI), respectively. The MSQI of the study area varied 0.437–0.986 for surface and 0.110–0.989 for the sub-surface soils. The MSQI of alluvial landforms followed the sequence of old alluvial plain > young alluvial plain > meander plain > flood plain, respectively. The correlations of the selected pedo-morphological indicators were conducted and they were validated with laboratory data. In conclusion, landform-specific soil quality indicators were appropriate for the evaluation and monitoring of alluvial soils and MDS identified in this study could be effectively used to evaluate soil quality in a similar landscape with limited data.