Effect of sweetclover cultivars and management practices on following weed infestations and wheat yield
Bibliographic record
Abstract
There is a renewed interest, especially among organic growers, in using either white sweetclover (Melilotus alba Desr.) or yellow sweetclover [M. officinalis (L.) Lam.] as cover crops. Sweetclover cultivars and tillage practices have changed since these crops were widely used as cover crops in the first half of the 20th century. Experiments were initiated in 1999, 2000, and 2002 to compare the effect of high- and low-coumarin cultivars and crop termination methods on weed suppression, available soil N, moisture conservation and following crop yield. Weed suppression was usually more effective when sweetclover residues were left on the surface than when removed as hay. Sweetclover termination at 70% bloom was often more effective in suppressing weeds than termination at the bud stage. In the summer and fall after termination, surface residues of Yukon, a high-coumarin and drought-tolerant cultivar, reduced lamb’s-quarters (Chenopodium album L.) density by > 80% compared with the no sweetclover check and essentially eliminated flixweed [Descurainia Sophia (L). Webb]. In the following spring, Yukon reduced kochia [Kochia scoparia (L.) Schrad.] density by > 80% and wild oat (Avena fatua L.) biomass by > 30% compared with the no sweetclover check. There was no difference in available N for a following crop between treatments with surface residue and cultivated fallow. Available soil moisture was about 10 mm less after the highest yielding sweetclover cultivars than after cultivated fallow, but subsequent wheat yield was not reduced. Maximum wheat yields were obtained after Yukon and Arctic sweetclover were grown as cover crops. It may be possible for organic growers to manage weeds with sweetclover in a reduced tillage system that leaves most of the plant residues on the soil surface. Key words: Cover crop, weed suppression, allelopathy, nitrogen, soil moisture
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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".