ICAR National Bureau of Soil Survey and Land Use Planning

Nāgpur, India

ICAR National Bureau of Soil Survey and Land Use Planning

Nāgpur, India
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Vasu D.,ICAR National Bureau of Soil Survey and land Use Planning | Singh S.K.,ICAR National Bureau of Soil Survey and land Use Planning | Sahu N.,ICAR National Bureau of Soil Survey and land Use Planning | Tiwary P.,ICAR National Bureau of Soil Survey and land Use Planning | And 5 more authors.
Soil and Tillage Research | Year: 2017

Crop productivity under rainfed farming systems in India is low due to poor water and nutrient management. The available small scale information of soil nutrients is inadequate to effectively manage individual farms held by small and marginal farmers. Large scale spatial variability assessment using grid sampling method is a feasible option to identify critical nutrient deficiency zones. The present study was conducted in a part of semi-arid tropical Deccan plateau region, India, to assess the spatial variability of soil pH, organic carbon (OC), soil available nitrogen (N), phosphorus (P), potassium (K) and sulphur (S). A total of 1508 composite samples (0–15 cm) were collected by adopting 325 × 325 m grid interval (one sample for 10 ha area) and they were analysed for soil fertility parameters. Coefficient of variation (CV) indicated that OC, N, P, K and S were high in heterogeneity (CV > 35%). Moreover, pH, P, K and S were non-normally distributed and log transformation produced normalised dataset. The semivariogram parameters (nugget to sill ratio, range and slope) indicated that the spatial distribution of soil properties were inconsistent. The spatial variability of parameters were mapped by ordinary kriging using exponential (pH and OC) and spherical (N, P, K and S) models selected based on root mean square error (RMSE) and r2 values. Multi-nutrient deficiencies were observed in most parts of the study area and N was acutely deficient. Farm level nutrient availability status was derived from spatial variability maps and critical nutrient deficiency zones were identified. Nutrient management recommendations based on soil test results were delivered to farmers for adopting need based variable rate of fertilizer application. The generated maps can serve as an effective tool for farm managers and policy makers in site specific nutrient management. © 2017 Elsevier B.V.


Reza S.K.,ICAR National Bureau of Soil Survey and Land Use Planning | Nayak D.C.,ICAR National Bureau of Soil Survey and Land Use Planning | Mukhopadhyay S.,ICAR National Bureau of Soil Survey and Land Use Planning | Chattopadhyay T.,ICAR National Bureau of Soil Survey and Land Use Planning | Singh S.K.,ICAR National Bureau of Soil Survey and Land Use Planning
Archives of Agronomy and Soil Science | Year: 2017

Alluvial soils constitute significant portion of cultivated land in India and it contributes towards food grain production predominantly. The objectives of this study were to assess the spatial variability of soil pH, organic carbon (OC), available (mineralizable) nitrogen (N), available phosphorus (P), available potassium (K) and available zinc (Zn) of alluvial floodplain soils of Kadwa block, Katihar district, Bihar, India. A total of 85 soil samples, representative of the plough layer (0–25 cm depth from surface) were randomly collected from the study area. The values of soil pH, OC, N, P, K and Zn varied from4.4 to 8.4, 0.20% to 1.20%, 141 to 474, 2.2 to 68.2, 107 to 903 kg ha–1 and 0.22 to 1.10 mg kg–1, respectively. The coefficient of variation value was highest for available P (94.3%) and lowest for soil pH (11.3%). Spherical model was found to be the best fit for N, P and Zn contents, while exponential model was the best fit for OC, and Gaussian model was the best-fit model for pH and K. The nugget/sill ratio indicates that except pH and available K all other soil properties were moderately spatially dependent (25–57%). Soil properties exhibited different distribution pattern. It was observed that the use of geostatistical method could accurately generate the spatial variability maps of soil nutrients in alluvial soils. © 2017 Informa UK Limited, trading as Taylor & Francis Group


Dharumarajan S.,Regional Center | Hegde R.,Regional Center | Singh S.K.,ICAR National Bureau of Soil Survey and Land Use Planning
Geoderma Regional | Year: 2017

The purpose of the study is to map the spatial variation of major soil properties in Bukkarayasamudrum mandal of Anantapur district, India using Random Forest model. The study area is divided into different Physiographic Land Units (PLU) based on landform, landuse and slope. Random Forest model (RFM) was developed based on field survey data of 116 surface samples (0–30 cm) representing all major PLU units of the study area. RFM is neither sensitive to over fitting nor to noise features and has capacity to handle large datasets. High resolution satellite imagery (IRS LISS IV data- 3 bands), terrain attributes such as elevation, slope, aspect, topographic wetness index, topographic position index, plan & profile curvature, Multi-resolution index of valley bottom flatness and Multi-resolution ridge top flatness, Vegetation factors like NDVI, EVI and land use land cover (LULC) are used as covariates along with legacy soil data of 1:50,000 scale. The predicted organic carbon, pH and EC ranged from 0.24–1.03%, 6.9–9.0, 0.11–0.97 dsm− 1 respectively. The model performance was evaluated based on Coefficient of determination (R2) and Lin's Concordance coefficient (CCC). The model performed well with R2 and CCC values of 0.23 and 0.38 for SOC, 0.30 and 0.37 for pH, and 0.62 and 0.70 for EC respectively. Variable importance ranking of RFM model showed that EVI and NDVI are the most important predictors for organic carbon whereas drainage and NDVI for EC and pH respectively. This technique can be applied to similar landscapes with more observations to refine the spatial resolution of soil properties. © 2017 Elsevier B.V.


Vasu D.,ICAR National Bureau of Soil Survey and Land Use Planning | Singh S.K.,ICAR National Bureau of Soil Survey and Land Use Planning | Tiwary P.,ICAR National Bureau of Soil Survey and Land Use Planning | Chandran P.,ICAR National Bureau of Soil Survey and Land Use Planning | And 2 more authors.
Soil Research | Year: 2017

Knowledge of soil-landform relationships helps in understanding the dominant pedogenic processes causing variations in soil properties within and between landforms. In this study, we investigated how major pedogenic processes in three landform positions of the semi-arid Deccan Plateau (India) have led to current plant yield-limiting soil properties. For this, we characterised 26 pedons from three landforms-piedmont, alluvial plain and valley-and performed factor analysis on the dataset. As the frequency distribution of the dataset was highly skewed for most of the soil properties, landform-wise partition and log-transformation were performed before studying soil variability within landforms. Results indicated that two factors explained 56, 71 and 64% of variability in soil properties in piedmonts, alluvial plains and valleys, respectively. The major soils in lower piedmonts (Typic Haplustalfs and Typic Rhodustalfs) were spatially associated with Vertisols (Sodic Haplusterts) occurring in alluvial plains and valleys. The soil properties in alluvial plains and valleys (Vertic Haplustepts, Sodic Haplusterts and Typic Ustifluvents) were modified due to regressive pedogenic processes. These soils were characterised by high pH (8.5-9.8), exchangeable sodium percentage (16.5-46.6) and poor saturated hydraulic conductivity (<1cmh-1). Subsoil sodicity induced by the presence of pedogenic calcium carbonate impaired the hydraulic conductivity. Subsoil sodicity and poor saturated hydraulic conductivity were identified as major yield-limiting soil properties. The relationships found between specific soil properties, surface and subsurface horizons, and position in the landscape helped to determine the dominant pedogenic processes and how these influenced current soil properties and their effects on crop yield. © 2017 CSIRO.


Selvaraj S.,Fujian Agriculture and forestry University | Duraisamy V.,ICAR National Bureau of Soil Survey and Land Use Planning | Guo F.,Fujian Agriculture and forestry University | Ma X.,Fujian Agriculture and forestry University
Geoderma | Year: 2017

Tree plantations contribute towards balancing global carbon (C) and nitrogen (N) cycles, with the C:N ratio being a key factor determining soil fertility in plantations. In the present study, we investigated how the management practices of Chinese fir (Cunninghamia lanceolata) plantations affect soil organic carbon (SOC), C:N ratio and soil quality. We assessed how these soil properties vary for stands of (1) different ages (up to 97 years) within the same rotation and (2) similar ages but in different rotations (up to four). Soil samples were collected and analysed from incremental depths (0–20, 20–40, 40–60, 60–80, and 80–100 cm). Continuous replanting of Chinese fir at the same site caused SOC stock and C:N ratio to decline after the second rotation. SOC stock (0–100 cm) decreased by 3, 3.6, and 14.3% between the first and second, second and third, and third and fourth rotations, respectively. The SOC concentration and C:N ratio declined from 21- to 40-year-old stands, and then increased in the 97-year-old stand throughout all soil depths. The stratification ratio (SR) index of SOC stock showed that continuous cultivation causes soil quality to decrease with increasing rotation cycle. Approximately 35–45% of equivalent soil mass SOC stocks were distributed in the upper soil layer (0–20 cm) in stands of all ages, indicating more organic C accumulation in the surface layer compared to subsurface layers (> 20 cm). In conclusion, we recommend that (1) cutting cycles of the stands should be increased from 20 to 25 years (current practice) to ~ 30 years of age and (2) plantations should only be cultivated to the second rotation to maintain site productivity, which would maximise both the ecological and economic value of this practice to the environment. © 2017 Elsevier B.V.


Anil Kumar K.S.,Regional Center | Kalaiselvi B.,Regional Center | Sujata K.,Regional Center | Nair K.M.,Regional Center | Singh S.K.,ICAR National Bureau of Soil Survey and Land Use Planning
Clay Research | Year: 2016

Influence of climatic variations on characteristics of red and lateritic soils formed towards west and east of Western Ghats spread over Kerala and Karnataka was studied by selecting nine pedons, 6 in Kerala and 3 in Karnataka. The formation of diverse group of soils could be attributed to the effect of topography, vegetation and climate leading to various pedogenic processes. Variation in soil characteristics and land qualities are attributed to total, frequency and distribution of rainfall, potential evapo-transpiration, which have significantly influenced the active pedogenic processes and results in profound changes in soil characteristics. The soil constraints due to climatic influence can be reduced through effective management practices. © 2016, Clay Minerals Society of India. All rights reserved.


Sharma R.P.,ICAR National Bureau of Soil Survey and Land Use Planning | Singh R.S.,ICAR National Bureau of Soil Survey and Land Use Planning | Singh S.K.,ICAR National Bureau of Soil Survey and Land Use Planning | Obi Reddy G.P.,ICAR National Bureau of Soil Survey and Land Use Planning
Journal of Agriculture and Environment for International Development | Year: 2016

Geographically, the Rajasthan is the largest state of India. The mapping of degraded and wasteland, its distribution and district base statistics are very important for land resource assessment and management. This paper deals with the status of land degradation affecting different kind of soils and under different management options. The study further illustrates the regional example of the Bhilwara district. The pressure on land resources has increased manifold with the increasing human and animal population. Western part of Rajasthan is severely affected by wind erosion (56%) and south-eastern part is affected by water erosion (42%) and salinity and sodicity (2%) affected area is scattered throughout the state. The area is characterised by a marked temperature range with strong diurnal variations, a typical phenomenon of the warm-dry continental climate. Desertification ranks among the greatest environmental challenge for the ecosystems in this region, and twelve districts of Rajasthan are already affected by severe desertification. Wind erosion is the major cause of soil degradation in western Rajasthan, whereas water erosion affects mostly south and eastern Rajasthan.


Vasu D.,ICAR National Bureau of Soil Survey and Land Use Planning | Singh S.K.,ICAR National Bureau of Soil Survey and Land Use Planning | Ray S.K.,Regional Center | Duraisami V.P.,Tamil Nadu Agricultural University | And 4 more authors.
Geoderma | Year: 2016

Assessment of soil quality index (SQI) using only the surface soil properties provides an incomplete information as the crop productivity is influenced by both surface and subsurface properties, with the latter being inherently linked to pedogenic processes. Two different SQIs were estimated for soil surface (0–15 cm) and control section (0–100 cm) using soil profile data of six identified soil series in part of semi-arid tropical (SAT) Deccan plateau and correlated with crop yield. Principal component analysis (PCA) and expert opinion (EO) methods were used for selecting minimum soil data set (MDS). Additive and weighted index methods were compared for SQI estimation. SQI obtained showed variation as PCA and EO methods produced different results. In general, weighted index SQIs were better correlated with crop yield than the additive index SQIs for both PCA and EO methods. EO derived weighted index SQI were comparable for both surface and control section except for few cases and consistent in their correlation with the crop yield, indicating its better performance as compared to PCA. Reason is that the PCA is a data dimension reduction technique whereas EO method is primarily conceived by the experts on cause-effect relationship of soil properties (such as hydraulic conductivity, CaCO3 and exchangeable sodium percentage) that are influenced by regressive pedogenic processes in SAT environments. Results showed that consideration of both surface and control section soil properties helps in establishing a good relationship between soil functions and management goal. In addition, it also satisfies the need to integrate both surface and subsurface soil information for soil quality assessment. © 2016 Elsevier B.V.


Reza S.K.,ICAR National Bureau of Soil Survey and Land Use Planning | Baruah U.,ICAR National Bureau of Soil Survey and Land Use Planning | Sarkar D.,ICAR National Bureau of Soil Survey and Land Use Planning | Singh S.K.,ICAR National Bureau of Soil Survey and Land Use Planning
Arabian Journal of Geosciences | Year: 2016

Soil properties like pH, organic carbon (OC), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) vary spatially from a field to a larger region scale and determine the soil fertility. This study addressed the spatial variability of soil properties in Brahmaputra plains, northeastern India using geostatistical method. For this, a total of 767 soil samples from a depth of 0–25 cm at an approximate interval of 1 km were collected over the entire Bongaigaon district of Assam. Data were analyzed both statistically and geostatistically on the basis of semivariogram. Soil properties showed large variability with greatest variation was observed in AP (86 %) where as the smallest variation was in pH (19 %). The semivariogram for all soil properties were best fitted by exponential models and showed a highest (2.7 km) range for OC and lowest (1.2 km) for AP. The nugget/sill ratio indicates a strong dependence for pH (12 %), moderate spatial dependence for available nutrients (53–72 %) and a weak spatial dependence for OC (77 %). Evaluation of spatial maps indicated that except for AN due to high root mean square error (61.8), kriging could successfully interpolate other soil properties. Soil pH highly negatively correlated with OC (−0.330**) and AN (−0.228**) and highly positive correlated with AP (0.334**) and AK (0.164**). A highly significant correlation was also found between OC and AN (0.490**). © 2016, Saudi Society for Geosciences.


Gajare A.S.,ICAR National Bureau of Soil Survey and Land Use Planning | Mandal D.K.,ICAR National Bureau of Soil Survey and Land Use Planning | Prasad J.,ICAR National Bureau of Soil Survey and Land Use Planning
Indian Journal of Agricultural Sciences | Year: 2016

Information on dynamics of soil organic carbon (SOC) in agricultural soils is important for sustained crop productivity, maintenance of soil health and alleviating the climate related stress. Researchers have found that oxidizable soil organic carbon (SOC) fractions are more important in maintaining the soil quality than total organic carbon (TOC). The SOC measured by Walkley and Black method is not sensitive to assess soil quality, but labile fractions of TOC is directly related to the soil productivity and quality. It is therefore, imperative to find out its quantum of SOC and fractions of TOC for better C management and carbon sequestration. In such an endeavour, a case study on carbon dynamics was undertaken for cotton-growing shrink-swell soils of Jalgaon district, Maharashtra, to quantify the SOC and its fractions in TOC and their interrelation with the crop yield. The surface (0-30 cm) soil samples (75) were collected from dominant cotton-growing shrink- swell soils in 2011-12 and analyzed for SOC, very labile carbon (VLC), labile carbon (LC), less labile C (LLC) and non-labile C (NLC). Factorial relationship between SOC with TOC and their relationship with crop yield was worked out. The result indicated that VLC, LC, LLC and NLC contributed to the tune of 15.33%, 11.85%, 51.15% and 21.07% of the TOC, respectively. The dichromate oxidizable SOC (y) was found linearly related to the TOC (x) by the equation, y = 0.782x + 0.025 (R2 = 0.932), indicating that oxidizable SOC comprised 78.2 % of the TOC, in other words, a correction factor of 1.278 (inverse of the slope of linear regression line) may be used to convert SOC values in shrink-swell soils of Jalgaon. The crop yield was closely related to the SOC (r = 0.642) compared to TOC (r = 0.610). Considering the maximum and minimum cotton yield, the threshold value and maximum value of SOC were worked out to be 5.688 and 8.312 g C/kg, respectively, reflecting the carbon sequestrations potential of soils. Among the different fractions, VLC was found to be well correlated (r = 0.512) with the crop productivity. The computed threshold and maximum value for VLC were 0.547 and 2.147 g C/kg, respectively. The study thus establishes that only 27.18 % of active carbon (VLC+LC) are important for the crop production in cotton- growing shrink-swell soils. © 2016, Indian Council of Agricultural Research. All rights reserved.

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