‘Palmer’ Mango Yield as Affected by Soil Class and Pedon Physicochemical Characteristics
Bibliographic record
Abstract
To evaluate the variation in ‘Palmer’ mango yield related to soil formation and soil physical and chemical properties, we studied a transect with 11 soil profiles, selected according to the altitude in a commercial orchard. Surface and subsurface diagnostic horizons were described up to two meters in depth. Soil depth, texture, structure, consistency, clay coating, cementation, and color of each horizon were morphologically determined. Undisturbed and disturbed samples were used to determine the soil total porosity, macroporosity, microporosity, density, saturated hydraulic conductivity, granulometry, total organic carbon, pH, sum of bases, and the contents of P, S, K, Na, Ca, Mg, Al, Fe, Mn, Cu, and Zn. The number of fruits (for production estimates), stem diameter, canopy area, and plant height were determined in four plants around each soil profile. Three classes of soil showed good suitability for mango cultivation: Argisol Red-Yellow Eutrophic typic, Cambisol Haplic Eutrophic Tb, and Latosol Red Yellow Eutrophic typic. The ‘Palmer’ mango yield was correlated with the K contents, sum of bases, and pH. The low yield was a result of the low K content associated with the presence of gravel.
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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 | 0.000 | 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) | 0.001 | 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".