Structural and Chemical Attributes of Soil Inorganic Fractions for Environmental Characterization in the Brazilian Semiarid Region
Bibliographic record
Abstract
Soil structure affects plant growth factors in agroecosystems. The relationships of these factors with soil texture and chemical attributes are important to differentiate environments. The objective of this work was to evaluate the relationship of soil structural attributes with physical and chemical attributes of different soils to differentiate environments, using multivariate statistics. The research was carried out in the Terra da Esperança Settlement Project, in Governador Dix-Sept Rosado, RN, semiarid region of Brazil. Ten soil profiles were evaluated: Haplustepts in a conventional area (1CA); Haplustepts in a collective area with (2CA); Haplustepts in an agroecological area with native forest (3AGRO); Eutrustox in a native forest (4NF); Calciustolls in a conventional area of pasture (5CAP); Haplustepts in a native forest (6NF); Haplustepts in an native forest (7NF); Usticfluvents in a permanent conservation area with Licania rigida (8PPA); Haplustepts in a native forest (9MN); and Haplustepts in a collective area with Spondias spp. (10SP). Ten soil samples were collected and analyzed by horizons in volumetric rings and in soil blocks (aggregate analysis), with three replications. Structural, physical, and chemical attributes were evaluated. The data were subjected to multivariate statistical analysis, using correlation matrix, cluster analysis, and factorial analysis considering the factors as principal components. According to the factorial analysis, Factor 1 (F1) and Factor 2 (F2)—F1 consisting of clay, Ca2+, Na+, sum of bases, and base saturation (V), and F2 consisting of cation exchange capacity (CEC), total organic carbon, macroporosity, particle density, K+, and microporosity—were essential to differentiate the environments. The cluster analysis formed four groups. The structural groups showed greater similarity, denoting the relationship between source material and land use, followed by the chemical groups P, K+, CEC, Ca2+, V, and pH for the Calciustolls; the structural weighted mean diameter, geometric mean diameter, soil aggregates larger than 2 mm, plasticity index, and plasticity limit for the Eutrustox; and the physical and chemical attributes EC, Na+, Silt, macroporosity, total calculated porosity, aluminum saturation, total sand, volumetric moisture, Mg2+ and particle density for the Haplustepts and the Usticfluvents. The clay fraction presented correlation with chemical attributes (F1) for the distinction of soil classes and land uses. The soil classes presented eutrophic character (V ≥ 50%) as a function of the Na+ and Ca2+ contents, including the Eutrustox (4NF), despite its lower contents when compared to the other soil classes. This is a local peculiarity due to the climatic pattern of the Brazilian semiarid region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".