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Soil loss tolerance limit (SLTL) is the maximum amount of soil which can be removed annually before the long-term soil productivity is adversely affected. In many situations, the establishment of a SLTL is intended to provide basic information for the maintenance of soil productivity, which becomes one of the foci of the sustainability of agricultural land use. In India a default soil loss tolerance limit of 11.2 Mg ha-1 yr -1 is followed for planning soil conservation activities. The objective of this study is to provide a methodology to estimate quantitative SLTLs for suggesting suitable soil conservation measures. The assessment framework used follows three basic steps; viz. indicator selection, indicator interpretation and integration into a soil quality (SQ) index value. A quantitative model was used to integrate potential soil indicators such as saturated hydraulic conductivity, bulk density, soil erodibility, organic carbon and pH to assess soil resistibility to erosion. Scaling functions were used to convert soil parameters to a unitless 0 to 1 scale. Normalized values of all these soil parameters were then multiplied by assigned weights based on relative importance and sensitivity analysis. Soils were grouped into 1, 2, and 3 depending on overall additive score. A general guideline developed by the USDA-Natural Resource Conservation Service (NRCS) was followed, with certain modifications in depth categories, for estimation of SLTLs. The model was tested on 14.86 Mha of land in northern India comprising of the states of Punjab, Haryana and Himachal Pradesh. SLTLs varied from 2.5 to 12.5 Mg ha-1 yr -1 compared to the single value applied earlier. [ABSTRACT FROM AUTHOR]

Land evaluation is carried out to assess the suitability of land for a specific use. Land evaluation procedures focus increasingly on the use of quantitative procedures to enhance the qualitative interpretation of land resource surveys. Conventional Boolean retrieval of soil survey data and logical models for assessing land suitability, treat both spatial units and attribute value ranges as exactly specifiable quantities. They ignore the continuous nature of soil and landscape variation and uncertainties in measurement, which may result in the failure to correctly classify sites that just fail to match strictly defined requirements. The objective of this article is to apply fuzzy model to land suitability evaluation for major crops in the 15 benchmark sites of the Indo- Gangetic Plains (IGP) and 17 benchmark sites of the black soil regions (BSR). Minimum datasets of land characteristics considered relevant to rice and wheat in the IGP and cotton and soybean in the BSR were identified to enhance pragmatic value of land evaluation. The use of fuzzy model is intuitive, robust and helpful for land suitability evaluation and classification, especially in applications in which subtle differences in land characteristics are of a major interest, such as development of threshold values of land characteristics. [ABSTRACT FROM AUTHOR]

The articles presented in this special section emanated from the researches of consortium members of the National Agricultural Innovative Project (NAIP, Component 4) of the Indian Council of Agricultural Research (ICAR), New Delhi. These researches have helped develop a soil information system (SIS). In view of the changing scenario all over the world, the need of the hour is to get assistance from a host of researchers specialized in soils, crops, geology, geography and information technology to make proper use of the datasets. Equipped with the essential knowledge of data storage and retrieval for management recommendations, these experts should be able to address the issues of land degradation, biodiversity, food security, climate change and ultimately arrive at an appropriate agricultural land-use planning. Moreover, as the natural resource information is an essential prerequisite for monitoring and predicting global environmental change with special reference to climate and land use options, the SIS needs to be a dynamic exercise to accommodate temporal datasets, so that subsequently it should result in the evolution of the soil information technology. The database developed through this NAIP would serve as an example of the usefulness of the Consortium and the research initiative of ICAR involving experts from different fields to find out the potentials of the soils of humid and semi-arid bioclimatic systems of the country [ABSTRACT FROM AUTHOR]

Crop simulation models have emerged as powerful tools for estimating yield gaps, forecasting production of agricultural crops and analysing the impact of climate change. In this study, the genetic coefficients for Bt hybrids established from field experiments were used in the InfoCrop-cotton model, which was calibrated and validated earlier to simulate the cotton production under different agro-climatic conditions. The model simulated results for Bt hybrids were satisfactory with an R2 value of 0.55 (n = 22), d value of 0.85 and a root mean square error of 277 kg ha-1, which was 11.2% of the mean observed. Relative yield index (RYI) defined as the ratio between simulated rainfed (water-limited) yield to potential yield, was identified as a robust land quality index for rainfed cotton. RYI was derived for 16 representative benchmark (BM) locations of the black soil region from long-term simulation results of InfoCrop-cotton model (based on 11-40 years of weather data). The model could satisfactorily capture subtle differences in soil variables and weather patterns prevalent in the BM locations spread over 16 agro-ecological sub-regions (AESRs) resulting in a wide range of mean simulated rainfed cotton yields (482-4393 kg ha-1). The BM soils were ranked for their suitability for cotton cultivation based on RYI. The RYI of black soils (vertisols) ranged from 0.07 in Nimone to 0.80 in Panjari representing AESR (6.1) and AESR (10.2) respectively, suggesting that Panjri soils are better suited for rainfed cotton. [ABSTRACT FROM AUTHOR]

Current status of land/soil resources of the Indo- Gangetic Plains (IGP) is analysed to highlight the issues that need to be tackled in near future for sustained agricultural productivity. There are intraregional variations in soil properties, cropping systems; status of land usage, groundwater utilization and irrigation development which vary across the subregions besides demographies. Framework for land use policy is suggested that includes acquisition of farm-level data, detailing capability of each unit to support a chosen land use, assess infrastructural support required to meet the projected challenges and finally develop skilled manpower to effectively monitor the dynamics of land use changes. [ABSTRACT FROM AUTHOR]

Sustaining soil and land quality under intensive land use and fast economic development is a major challenge for improving crop productivity in the developing world. Assessment of soil and land quality indicators is necessary to evaluate the degradation status and changing trends of different land use and management interventions. During the last four decades, the Indo-Gangetic Plains (IGP) which covers an area of about 52.01 m ha has been the major food producing region of the country. However at present, the yield of crops in IGP has stagnated; one of the major reasons being deterioration of soil and land quality. The present article deals with the estimation of soil and land quality indicators of IGP, so that, proper soil and land management measures can be taken up to restore and improve the soil health. Use of principal component analysis is detailed to derive the minimum dataset or indicators for soil quality. The article also describes spatial distribution of soil and land quality with respect to major crops of IGP. [ABSTRACT FROM AUTHOR]

Five benchmark soils, namely Fatehpur (Punjab) and Haldi (Uttarakhand) non-sodic soils, Zarifa Viran (Haryana), Sakit and Itwa sodic soils (Uttar Pradesh) representing Trans, Upper, Middle and Central Indo- Gangetic Plains (IGP) were revisited for studying the morphological, physical and chemical properties of soils at low and high management levels to monitor changes in soil properties due to the impact of landuse as well as management levels. The results indicate an increase in bulk density (BD) below the plough layer, and build up of organic carbon (OC) and decline in pH in surface layers of Zarifa Viran, Sakit and Itwa sodic soils under high management. The concentration of carbonates and bicarbonates in sodic soils decreased due to adaptation of rice-wheat system. The build-up of OC and decrease of pH in surface soils under rice- wheat system enhanced the soil health. Increase in BD in subsurface soils, however, is a cause of concern for sustaining rice-wheat cropping system. Soil management interventions such as tillage, conservation agriculture and alternate cropping system have been suggested for improved soil health and productivity. [ABSTRACT FROM AUTHOR]

The present study documents the biological properties of the black soil region (BSR) of India in terms of culturable microbial population. Besides surface microbial population, subsurface population of individual soil horizons is described to improve the soil information system. An effort has been made to study the depth-wise distribution and factors (bioclimates, cropping systems, land use, management practices and soil properties) influencing the microbial population in the soils of the selected benchmark spots representing different agro-ecological sub-regions of BSR. The microbial population declined with depth and maximum activity was recorded within 0-30 cm soil depth. The average microbial population (log10 cfu g-1) in different bioclimates is in decreasing order of SHm > SHd > SAd > arid. Within cropping systems, legumebased system recorded higher microbial population (6.12 log10 cfu g-1) followed by cereal-based system (6.09 log10 cfu g-1). The mean microbial population in different cropping systems in decreasing order is legume > cereal > sugarcane > cotton. Significantly higher (P < 0.05) microbial population has been recorded in high management (6.20 log10 cfu g-1) and irrigated agrosystems (6.33 log10 cfu g-1) compared to low management (6.12 log10 cfu g-1) and rainfed agrosystems (6.17 log10 cfu g-1). The pooled analysis of data inclusive of bioclimates, cropping systems, land use, management practices, and edaphic factors indicates that microbial population is positively influenced by clay, fine clay, water content, electrical conductivity, organic carbon, cation exchange capacity and base saturation, whereas bulk density, pH, calcium carbonate and exchangeable magnesium percentage have a negative effect on the microbial population. [ABSTRACT FROM AUTHOR]

Understanding the physical quality of soil that influences its hydraulic behaviour helps in formulating appropriate water management strategies for sustainable crop production. Saturated hydraulic conductivity (Ks) is a key factor governing the hydraulic properties of soils. Ks can be estimated through various techniques. In the present article we have developed and validated the regression models to predict Ks of the soils of the Indo-Gangetic Plains (IGP) and the black soil regions (BSR) under different bioclimatic systems. While particle size distribution was found to be a key factor to predict Ks of the BSR soils, organic carbon was found useful for the IGP soils. Moreover, the models for Ks of both soils were strengthened by putting in CaCO3 and exchangeable sodium percentage content. It seems there is ample scope to study the interaction process for revising Ks to desired levels through management practices in these two important food-growing zones. An index of soil physical quality, derived from the inflection points of the soil moisture characteristic curves could well explain the impact of management practices on soil physical quality. [ABSTRACT FROM AUTHOR]

In recent years, georeferenced soil information system has gained significance in agricultural land-use planning and monitoring the changes in soil properties/ soil quality induced by land-use changes. The spatiotemporal information on saturated hydraulic conductivity (sHC) and soil water retention-release behaviour is essential for proper crop and land-use planning. The sHC greatly influences the drainage process and soil water retention-release behaviour, ultimately affecting the crop growth and yield. However, sHC and water retention are not measured in a routine soil survey and are generally estimated from easily measurable soil parameters through pedotransfer functions (PTFs). In the present study, PTFs for sHC and water retention were developed separately for the soils of two food-growing zones of India (the Indo-Gangetic Plains (IGP) and the black soil region (BSR)). For the IGP soils, sHC is affected by the increased subsoil bulk density due to intensive cultivation. In BSR, presence of Na+ and Mg++ ions affects the drainage and water retention of the soils. Therefore, these soil parameters were considered while developing the PTFs using stepwise regression technique in SPSS. The validation of PTFs was found to be satisfactory with low RMSE values and high model efficiency. [ABSTRACT FROM AUTHOR]