Soil and Root System Attributes of Forage Cactus under Different Management Practices in the Brazilian Semiarid
Bibliographic record
Abstract
Drylands cover 40% of the global surface and house more than 2 billion people. Drought-tolerant crops are becoming more important in these regions, not only to provide food, fodder, and energy, but also to sequester soil organic carbon. This study evaluated soil and root system attributes of forage cactus ‘Orelha de Elefante Mexicana’ (Opuntia stricta Haw.) managed using different agronomic practices in the Brazilian Semiarid. The experiment was established in June 2011 and the design was split-plot in a randomized complete blocks, where the main plot was the different planting density, and the subplots were the factorial arrangement between harvest frequency and harvest intensity. Soil samples were collected at 0 to 10 and 10 to 20 cm depths and response variables included root biomass, soil bulk density (BD), and soil carbon (C) and nitrogen (N) contents and stocks. Sampling occurred in August 2019, but for root biomass and soil BD analysis it also occurred in September 2021. There were no significant effects from management practices on root biomass at 0 to 10 and 10 to 20 cm depth (p > 0.05), with respective averages of 12.45 Mg ha−1 and 6.06 Mg ha−1. Soil BD was similar at 10 to 20 cm depth (p > 0.05) averaging 1.28 g cm−3. Soil organic carbon (SOC) stock varied with management and reached almost 100 Mg C ha−1 in the 0 to 20 cm layer, indicating the potential of cactus to store carbon. Plants with a more developed root system are more likely to survive the drought climatic condition; therefore, less dense plantings could result in more resilient plants for drier regions, but could potentially negatively affect biomass productivity per area.
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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 | 0.001 | 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".