Designing Cropping Systems to Improve the Management of the Invasive Weed Phalaris minor Retz.
Bibliographic record
Abstract
Because cropping systems can greatly affect the establishment and spread of alien species populations, the design of cropping systems to control invasive weeds is an important approach for invasive species management in agro-ecosystems to avoid excessive increases in other control measures such as herbicides. The annual weed Phalaris minor Retz. (P. minor) is one of the most troublesome invasive weed species of winter crops in Yunnan Province, China, but the development of cropping systems for ecological control of this weed have received limited research attention. Here, we studied seed dormancy, germination characteristics and reproductive responses of P. minor to various cropping systems to show how cropping systems could be better designed to control P. minor in China. Our research showed that cropping systems significantly affected seed dormancy in submerged paddy fields. Phalaris minor seed remained dormant and the germination rates (less than 10%) were significantly lower (p < 0.05) than in maize fields and dry, bare soil conditions. Wheat, faba bean and rapeseed crops had no significant influence (p < 0.05) on the seed germination rate of P. minor, but increasing soil depth significantly decreased (p < 0.05) the germination rate and germination index of this weed. Total biomass, spike biomass, spike number and seed number of P. minor were significantly reduced (p < 0.05) with increasing proportions of the three crops (wheat, faba bean and rapeseed), with rapeseed having the strongest inhibition effects among the three crops. The reproductive allocation and reproductive investment of P. minor were also significantly reduced (p < 0.05) in mixed culture with wheat and rapeseed. With increasing proportions of wheat or rapeseed, the specific leaf area of P. minor significantly increased (p < 0.05), but the reverse was true for leaf area and specific leaf weight. Moreover, the net photosynthetic rate, stomatal conductance and transpiration rate for P. minor also decreased significantly (p < 0.05) when grown with wheat or rapeseed. These results suggest that optimal cropping systems design could involve planting rapeseed in conjunction with deep plowing and planting rice (continuous submergence underwater) in summer. Such a system could reduce the field populations and seed bank of P. minor, thus providing a sustainable and environmentally friendly means of suppressing P. minor.
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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 | 0.000 | 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 | 0.000 |
| 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 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".