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Spatial variability of sulphur fractions in soils of agro-climatic zone-II, Himachal Himalaya, India


Affiliations
1 Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India
2 Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India; Swami Vivekanand Govt. Utkrisht College, Department of Environment Science, Ghumarwin 174 021, India
3 Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India; School of Agricultural Sciences, Baddi University of Emerging Sciences and Technology, Solan 173 205, India
4 Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India; Krishi Vigyan Kendra Shimla, Dr YS Parmar University of Horticulture & Forestry, Nauni, Solan 171 207, India

Estimating spatial variability of soil nutrients and their fractions is important for understanding their dynamic distribution under various pools. The present study was carried out to examine the spatial distribution of soil sulphur (S) fractions in agro-climatic zone-II (mid hills sub-humid) of Himachal Himalaya, India. The data were analysed with a classical and geostatistical approaches. The soil organic carbon varies from 2.8 to 22 g/kg and the S-fractions are positively correlated with organic carbon. The total-S varies from 72.6 to 513.9 mg/kg with a mean value of 260.9 mg/kg. The descriptive analysis showed that the coefficient of variation ranged from 8.5% to 52.9%. Semivariogram modelling represents that the best-fitted model was exponential and the nugget-to-sill ratio {(C0/C0 + C)} explains the spatial dependency, suggesting a moderate spatial dependence. The principal component analysis represents the three principal components that explain the 91% variance in the dataset. The higher concentration of sulphur is well correlated with soil organic carbon. The present study provides information to understand sulphur dynamics through their partitioning among various pools for effective soil resource management.

Keywords

Geostatistics, GIS mapping, kriging technique, spatial variation, sulphur fractions.
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  • Spatial variability of sulphur fractions in soils of agro-climatic zone-II, Himachal Himalaya, India

Abstract Views: 11  | 

Authors

Deepika Suri
Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India
Vijay Kumar Sharma
Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India
Pardeep Kumar
Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India
Praveen Kumar
Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India; Swami Vivekanand Govt. Utkrisht College, Department of Environment Science, Ghumarwin 174 021, India
Munish Sharma
Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India; School of Agricultural Sciences, Baddi University of Emerging Sciences and Technology, Solan 173 205, India
Nagender Pal Butail
Department of Soil Science, CSK Himachal Pradesh Agricultural University, Palampur 176 062, India; Krishi Vigyan Kendra Shimla, Dr YS Parmar University of Horticulture & Forestry, Nauni, Solan 171 207, India

Abstract


Estimating spatial variability of soil nutrients and their fractions is important for understanding their dynamic distribution under various pools. The present study was carried out to examine the spatial distribution of soil sulphur (S) fractions in agro-climatic zone-II (mid hills sub-humid) of Himachal Himalaya, India. The data were analysed with a classical and geostatistical approaches. The soil organic carbon varies from 2.8 to 22 g/kg and the S-fractions are positively correlated with organic carbon. The total-S varies from 72.6 to 513.9 mg/kg with a mean value of 260.9 mg/kg. The descriptive analysis showed that the coefficient of variation ranged from 8.5% to 52.9%. Semivariogram modelling represents that the best-fitted model was exponential and the nugget-to-sill ratio {(C0/C0 + C)} explains the spatial dependency, suggesting a moderate spatial dependence. The principal component analysis represents the three principal components that explain the 91% variance in the dataset. The higher concentration of sulphur is well correlated with soil organic carbon. The present study provides information to understand sulphur dynamics through their partitioning among various pools for effective soil resource management.

Keywords


Geostatistics, GIS mapping, kriging technique, spatial variation, sulphur fractions.



DOI: https://doi.org/10.18520/cs%2Fv127%2Fi9%2F1083-1092