The proportion of narrow fibers during early development predicts the diameter, fineness, and other quality traits of mature cotton fiber (Gossypium spp.)
Bibliographic record
Abstract
Cotton fiber is an exceptionally long and strong outgrowth of the seed epidermis and the world’s most important textile material. To maintain the competitiveness of this renewable resource with synthetic fiber, the quality of the fiber typically produced by Gossypium hirsutum L. needs to be improved. For instance, fiber with lower fineness (or linear density) is preferred for the highest quality textiles. Based on prior research, we hypothesized that the proportion of narrow fibers early in development predicts the fineness of mature fiber. The hypothesis was supported by the currently reported analysis of 161 historical G. hirsutum accessions grown in the field along with two accessions of G. barbadense L., the species producing the highest quality fiber. Computer vision was used to estimate the proportion of narrow fibers three days after flowering, and mature fiber from the same field plots was analyzed by the High Volume Instrument (HVI) and the Automated Fiber Information System (AFIS). Linear regression analysis showed that a higher average proportion of young, narrow fibers was correlated with several improved qualities of mature fibers, including lower average fineness and diameter. Other analyses, including cooperative breeding trial data from multiple locations, demonstrated that there is genetic control on the narrow fiber proportion. The extent that environmental and other factors influence fiber shape proportions will need further exploration. We propose that consistently breeding for a higher proportion of narrow fibers in modern G. hirsutum cultivars would improve the quality of the G. hirsutum fiber crop.
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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 | 0.000 |
| 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".