Comprehensive Approaches in Rehabilitating Salt Affected Soils: A Review on Indian Perspective
Bibliographic record
Abstract
Land, a non-renewable resource, is central to all primary production system. Increasing pressure of populationgrowth, economic development, climate change, land use changes, and environmental pollutionlead to different types of land degradation including salinization. Salt affected soils are normally uncultivated, uninhabited bare lands with poor quality and suffer from different stress conditions. These soils are generally not conducive for regeneration of vegetation. Salt affected soils are usually barren but potentially productive. Rehabilitation includes control of extension of salt affected soils, its reclamation, stabilization and eco-restoration. The rehabilitation of these lands is common through chemical means and engineering approaches. Extension of salt affected soils is controlled by utilizing the resource on sustainable basis. Good quality irrigation water and sufficient drainage facility accompanying with other physical measures help in reclamation of soil. Chemical reclamation requires different types of amendments for different soils. Biological reclamation of salt affected soil is more important from stabilization of soil quality and eco-restoration points of view. Selection of salt tolerant plants and crops are very important for cultivation in salt affected soils. Improved production systems including horticultural, pastoral, agri-horticultural, silvi-pastoral, silvi-cultural, agroforestry are the components of integrated farming system in bio-saline agriculture. The judicious use of the reclaimed lands for different production purposes and restoration of quality of soil through people’s participation in rehabilitative work is the way to get out of problem of salt affected soil.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".