Biodegradable mulch films support root proliferation and yield in water-saving rice production
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Biodegradable mulch films enhanced the soil conditions in water-saving rice production. • Enhanced spatial distribution of the root system improved rice resistance to stunting. • Optimized root development contributed to rice productivity and sustainability with biodegradable mulch films. Water-saving rice systems must maintain yield targets while reducing water consumption. Applying biodegradable film to cover the soil surface reduces water loss through evapotranspiration, establishing a warmer, more humid microenvironment for rice growth compared to traditional paddy rice systems. This study examined soil water regimes for rice production in northeast China, comparing rice growth with and without biodegradable mulch film under continuous flooding, drip irrigation, and controlled irrigation conditions. The implementation of biodegradable mulch film elevated soil temperature and sustained soil moisture during early rice development. Continuous flooding with biodegradable mulch film yielded the highest rice production (9.4 Mg ha -1 ) and net profit of approximately 11,800 CNY ha -1 . Drip irrigation with biodegradable mulch film achieved maximum water efficiency, demonstrating the highest water productivity (1.25 kg m -3 ) and minimum water consumption (235 mm). Root length, weight, and surface area in the 0-40 cm soil layer exhibited positive correlations with water productivity, shoot dry matter, and yield, indicating that root morphological characteristics, particularly during the panicle initiation stage, enhanced rice production and water conservation. The findings demonstrate that biodegradable mulch film created favorable soil conditions for root proliferation, enabling higher yields in water-saving rice systems.
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.
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 | 0.000 | 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 | 0.001 |
| 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 it