Feasibility of bioplastic mulch systems to stimulate early seed germination and plant growth for corn silage hybrids
Bibliographic record
Abstract
Beres, B. L. and Stevenson, F. C. 2015. Feasibility of bioplastic mulch systems to stimulate early seed germination and plant growth for corn silage hybrids. Can. J. Plant Sci. 95: 1229–1234. A study was conducted at Vauxhall and Lethbridge, Alberta, Canada, in 2006 and 2007 to determine if covering corn (Zea mays L.) seed rows with bioplastic mulch accelerates growth and improves yield. Each site (location by year combination) included all factorial combinations of three seeding rates (64 000, 74 000, and 84 000 kernels ha −1 ), two Pioneer ® corn hybrids [39J26 at 2350 corn heat units (CHU), high vigour; and Roundup Ready ® 38K46 at 2775 CHU; low vigour], and seedbed preparation (1), bioplastic mulch covering each seed row, (2) same bioplastic system but removed 3 wk post-planting, or (3) no plastic covering. The use of a bioplastic mulch decreased days to anthesis and silking, and the removal of plastic often decreased days to anthesis a further day or two. Application and subsequent removal of plastic from corn rows always increased corn plant height relative to plots without plastic. However, the use of plastic without removal limited weed control, causing increased weed weight by 0.3–0.5 Mg ha −1 at the three sites. A yield reduction of 5–9 Mg ha −1 occurred with plastic mulch vs. no plastic applied or plastic removed at Vauxhall in 2006 (High CHU hybrid) and at Lethbridge in 2007 (both hybrids). Otherwise, yield was not affected with plastic applied vs. no plastic. Removal of the plastic offers accelerated plant growth and proper timing of weed removal, but the feasibility in a corn silage system at recommended sowing dates is questionable due to logistics at planting and increased costs. The system would provide earlier harvest dates for silage or grain systems, which lessens the risk of frost effects in fall.
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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 | 0.001 | 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".