Characterization and suitability evaluation of rice growing soils for sustainable land use planning using geographic information system (GIS)
Bibliographic record
Abstract
Ten typical representative pedons from rice growing soils of Tirupati revenue division, Chittoor, Andhra Pradesh were characterized for crop suitability evaluation by limitations methods using GIS. The soils were deep (>1.0 m), sandy clay loam to sandy loam texture and clay, silt and sand ranged from 13.6 to 45.4, 9.4 to 28.1 and 38.5 to 71.6 per cent. The bulk density ranged from 1.28 to 1.80 Mg m-3 and increased with depth. The water holding capacity ranged from 27.2 to 52.9 per cent and negatively correlated with sand (r = -0.863). The soils were neutral to strongly alkaline (7.32 to 9.32), non- saline to slightly saline (0.22 to 5.62 dS m-1) and low to high organic carbon (3.9-11.7 g kg-1). The cation exchange capacity, base saturation and ESP ranged from low to medium (9.24 to 29.24 cmol (p+) kg-1), medium to high (63.5 to 85.7%) and 0.15 to 16.75 per cent. The available N was low to medium (40.9 to 388.9 kg ha-1), available P2O5 and K2O were 6.5 to 178.6 kg ha-1 and 42.5 to 642.8 kg ha-1 (low to high). The available sulphur was 3.7 to 35.5 mg kg-1 and micro nutrients were sufficient except Zn in some soil profiles. Based on crop suitability evaluation, soils were highly suitable for groundnut, sunflower, sugarcane and finger millet cultivation with an area of 24068, 3898, 16303 and 16303 ha. representing 72.6, 11.2, 49.2 and 49.2, per cent. Moderately suitable for rice, maize, groundnut sunflower, sesame, sugarcane and finger millet cultivation with an area of 33144, 33144, 9066, 29246, 33144, 16840 and 16841 ha. representing 100, 100, 27.4, 88.8, 100, 50.8 and 50.8 per cent of study area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".