The Effects of Light, Rehilling, and Mulching on Greenshoulder and Internal Greening in Carrots
Bibliographic record
Abstract
Greenshoulder (GS) and internal greening (IG) in carrots (Daucus carota var. sativus) affect root appearance and can lead to significant economic loss. Experiments were conducted to quantify the critical light intensity that may trigger greening by exposing carrot hypocotyls to different light intensities. Chlorophyll a, b, and total chlorophyll were measured. The effects of rehilling on GS and IG were measured in a 2‐yr field study with eight treatments imposed at various stages of growth. Another experiment to confirm the effects of rehilling by etiolating various genotypes was also conducted. Leaf area index, internal and external greening, and IG length were measured. Increasing light intensity enhanced chlorophyll a and b linearly and significantly. The highest amount of chlorophyll a, b, and total chlorophyll accumulation in hypocotyl occurred at the highest light intensity tested (320 μmol m−2 s−1). Rehilling reduced GS and IG significantly. However, the response varied significantly between seasons. In 2002, rehilling once at the early vegetative stage, initial bulking stage, or active bulking stage was effective in reducing GS and IG. In the 2003 field study, rehilling once at each of the three stages reduced GS and IG. Compared with the control, rehilling reduced GS by 10 to 21% and IG by 13 to 20%. Among the cultivars tested, mulching reduced GS only for Magno. The results suggest that GS and IG are induced at the hypoctoyl stage and that rehilling could reduce GS and IG considerably; however, the etiolation response appears to be genotype specific.
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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) | 0.001 | 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".