Explorando el estado del arte de la labranza y su impacto en la calidad del suelo y la productividad agrícola: Una revisión crítica de los últimos 20 años
Bibliographic record
Abstract
Tillage has been a fundamental pillar in the establishment and evolution of agriculture over time. However, its impact on soil quality and agricultural productivity has received significant attention due to environmental challenges and the need for sustainable agriculture. This study assessed the state of the art on tillage practices and their influence on soil quality and agricultural productivity over the last 20 years, through an analysis of 92 articles from the Web of Science database. The results reveal a growing interest in the topic in the last decade, with notable contributions from the United States, China, Brazil, Canada, and India, focusing on conservation systems and their relationship with soil quality, organic matter, and agricultural productivity. The most frequently evaluated indicators include physical parameters (bulk density, penetration resistance, aggregates, porosity), chemical parameters (nitrogen, phosphorus, potassium, pH), and biological parameters (organic carbon, microbial biomass, enzymatic activities). The review suggests that conservation tillage systems tend to improve soil quality and crop productivity. However, some studies present contradictory results regarding soil physical quality and productivity, attributable to intrinsic factors. To better understand the impacts of tillage practices, it is crucial to conduct national-level research that considers the edaphoclimatic requirements of different crops, in order to identify the conditions under which conservation systems are most efficient for more sustainable and resilient agriculture.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".