Fiber cell development and fiber yield of flax (Linum usitatissimum L.) affected by the seasonal temperature pattern
Bibliographic record
Abstract
Du, G.-H., Liu, F.-H. and Rowland, G. 2015. Fiber cell development and fiber yield of flax (Linum usitatissimum L.) affected by the seasonal temperature pattern. Can. J. Plant Sci. 95: 1215-1220. Three fiber flax cultivars ‘Ariane’, ‘Argos’ and ‘Viking’ were cultured in growth chambers under three seasonal temperature patterns (STPs) [parabolic (P), anti-parabolic (AP) and quasi-horizontal (QH) configurations]. The effect of STP was studied on fiber cell development and on fiber yield. The results indicated that, compared with the quasi-horizontal seasonal temperature pattern (QH-STP), the size of fiber cell cavity (SFCC) and fiber content (FC) decreased under parabolic seasonal temperature pattern (P-STP). However, the size of fiber cell (SFC) and SFCC decreased, but the number of fiber cells per bundle (NFCB) increased under anti-parabolic seasonal temperature pattern (AP-STP). Moreover, there was a significant positive correlation between fiber weight (FW) and width of fiber bundle (WFB), also between FC and NFCB. Considering the response of fiber flax cultivars to the different STPs, ‘Ariane’ had smaller SFC and SFCC, thinner thickness of fiber cell wall (TFCW) under AP-STP, and smaller SFCC and thicker TFCW under P-STP than under QH-STP, while ‘Argos’ had smaller SFC and SFCC, and higher NFCB under AP-STP, and smaller SFC under P-STP than under QH-STP. However, STPs had little effect on the fiber cell development of ‘Viking’. All three cultivars had high FC under AP-STP than under P-STP. These observations indicate that the fiber cell development and fiber yield of flax were related to the STP and suggest that AP-STP are the most favorable temperature conditions for fiber flax growth.
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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".