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Record W1965025451 · doi:10.2135/cropsci2006.08.0517

The Effects of Light, Rehilling, and Mulching on Greenshoulder and Internal Greening in Carrots

2007· article· en· W1965025451 on OpenAlexafffund
P Ravi Shankar, Rajasekaran R. Lada, C. D. Caldwell, Samuel K. Asiedu, Azure Adams

Bibliographic record

VenueCrop Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsNova Scotia Department of Agriculture
FundersDepartment of Agriculture and Fisheries, Queensland GovernmentDalhousie UniversityOxford Frozen FoodsDepartment of Agriculture, Nova Scotia
KeywordsDaucus carotaGreeningEtiolationBiologyChlorophyllChlorophyll aHorticultureLight intensityHypocotylChlorophyll bCultivarBotanyBiochemistryPhysicsEcology

Abstract

fetched live from OpenAlex

Greenshoulder (GS) and internal greening (IG) in carrots ( Daucus carota var. s ativus ) 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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.236
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2007
Admission routes2
Has abstractyes

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