Impact of effective microorganisms on weed infestation and yield of peppermint cultivated on muck-peat soil
Bibliographic record
Abstract
Peppermint (<em>Mentha ×piperita</em> L.) rootstock cuttings with 9–11 internodes were planted on April 10, 2014 in rows 50 cm apart and with 25-cm distance in the row, on well fertilized muck-peat soil containing 82.1% of organic matter with a pH of 5.9. Peppermint plants were sprayed once with an activated EM-1 preparation, then on two or three further occasions as follows: at 10 cm height (May 10), at branching stage (May 29), and during rapid growth (June 19). EM did not affect peppermint growth or yield. Yields of the fresh and dry herb were high (means: 15,563 and 2,661 kg ha<sup>−1</sup>, respectively) and characterized by a medium (1.85–1.90%) essential oil content in the dry herb. Twenty-nine compounds were identified in the oil and its main components were menthol (53.1–58.5%), menthone (14.6–16.8%), isomenthone (6.3–6.7%), menthyl acetate (4.0–5.0%), germacrene D (2.3–3.4%), ß-caryophyllene (1.8–2.4%), viridiflorol (1.5–2.3%), and 1,8-cyneole (0.3–3.7%). EM did not affect the content of essential oil in the dry herb or the oil composition (except for 1,8-cyneole). Thirty-four days after planting, 22 weed species grew in the experimental plots and the dominant were common meadow grass (<em>Poa pratensis</em> L.) accounting for 20% of total weed population, annual meadow grass (<em>Poa annua</em> L.) 17%, common chickweed [<em>Stellaria media</em> (L.) Vill.] 20%, creeping yellowcress [<em>Rorippa sylvestris</em> (L.) Besser] 8%, hairy galinsoga [<em>Galinsoga ciliata</em> (Raf.) S. F. Blake] 7%, gallant soldiers (<em>Galinsoga parviflora</em> Cav.) 6%, Canadian horseweed [<em>Conyza canadensis</em> (L.) Cronq.] 6%, common groundsel (<em>Senecio vulgaris</em> L.) 5%, and annual nettle (<em>Urtica urens</em> L.) 5%. Other species occurred sporadically. The total number and fresh weight of weeds growing on 1 m<sup>2</sup> were 412 and 246 g on plots treated with EM and 389 and 227 g on control plots, respectively, but the differences were not statistically significant.
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 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".