Microplastics in the agroecosystem: effects of plastic mulch film residues on the soil-plant system
Bibliographic record
Abstract
Due to the widely use of plastic mulch in agriculture, plastic residues in the soil are threatening soil quality. In this thesis, we assessed the effects of macro and micro sized plastic residues from polyethylene and biodegradable plastic mulch films on the soil-plant system, by investigating their effects on plant growth, rhizosphere microflora, soil physicochemical properties and soil functions.Overall, this thesis provided experimental evidence that plastic mulch film residues affected physical, chemical and biological processes in the soil-plant system. Despite the lack of knowledge, it is clear with the incipient evidence that both macroplastics and microplastics derived from LDPE and biodegradable plastic mulch films could be detrimental to agricultural productivity, soil biodiversity and soil biogeochemical cycles. Moreover, the insights developed during this PhD research are a valuable contribution to a framework for the systematic analysis of the effects of microplastics on the soil-plant system and a holistic approach to study interrelated physical, chemical and biological processes in the agroecosystem.
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 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".