Root growth of containerized lodgepole pine seedlings in response to <i>Ascophyllum nodosum</i> extract application during nursery culture
Bibliographic record
Abstract
MacDonald, J. E., Hacking, J., Weng, Y. and Norrie, J. 2012. Root growth of containerized lodgepole pine seedlings in response to Ascophyllum nodosum extract application during nursery culture. Can. J. Plant Sci. 92: 1207–1212. Vigorous root growth immediately after spring planting is crucial to ensure a well-developed root system before the occurrence of drought events associated with climate change. The objective of this study was to enhance spring root growth of containerized lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.) seedlings. Seedling culture began in April. In September, seedlings were root drenched with an extract of the brown marine alga Ascophyllum nodosum (L.) Le Jolis in finisher fertilizer at rates of 1:750, 1:500, and 1:250. Finisher fertilizer alone served as control. Applications were made three or six times. Seedling culture continued until lifting in December, and then seedlings were freezer stored. Frequency of application had no effect on root growth, whereas rate of application had a significant effect. Compared with control, the 1:750, 1:500, and 1:250 rates significantly reduced total length of the root system in mid October. After overwintering and growing under favorable environmental conditions for 21 d, the 1:500 rate significantly increased the total number of white roots, as well as the number of both short and long white roots. These results suggest that application of Ascophyllum nodosum extract may be a valuable nursery practice to increase spring root growth, thereby enhancing drought resistance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".