Soil Chemical Changes under Irrigated Mango Production in the Central São Francisco River Valley, Brazil
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Irrigated areas in Brazil's Central São Francisco River Valley have experienced declines in productivity, which may be a reflection of changes in soil chemical properties due to management. This study was conducted to compare the chemical composition of soil solutions and cation exchange complexes in a five-year-old grove of irrigated mango (Mangifera indica L. cv. Tommy Atkins) with that of an adjacent clearing in the native caatinga vegetation. A detailed physiographic characterization of the area revealed a subsurface rock layer, which was more undulating than the current land surface, and identified the presence of a very saline and sodic (1045 microS cm(-1), sodium adsorption ratio [SAR] = 5.19) ground water table. While changes in concentrations of Ca, Mg, and K could be attributed to direct management inputs (fertilization and liming with dolomite), increases in Na suggested average annual capillary rise from the ground water table of 28 L m(-2). Accordingly, soil salinity levels appeared to be more dependent on surface elevation than the elevation of the rock layer or sediment thickness. The apparent influence of land surface curvature on water redistribution and the solution chemistry was more pronounced under irrigated mango production. In general, salinity levels had doubled in the mango grove and nearly tripled under the canopies, after only five years of irrigation. Though critical saline or sodic conditions were not encountered, the changes observed indicate a need for more adequate monitoring and management of water and salt inputs despite the excellent water quality of the São Francisco River.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it