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Record W4285999448 · doi:10.1139/cjps-2021-0273

Effects of decreasing photoperiod on cold acclimation of asparagus seedlings

2022· article· en· W4285999448 on OpenAlexafffundvenueabout
William Short, David J. Wolyn

Bibliographic record

VenueCanadian Journal of Plant Science · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhytochemical Studies and Bioactivities
Canadian institutionsUniversity of Guelph
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsAsparagusphotoperiodismBiologyFructanDormancyShootHorticultureCultivarHerbaceous plantAcclimatizationBotanyProlinePerennial plantSucroseGermination

Abstract

fetched live from OpenAlex

Cold acclimation is a vital process for surviving subzero temperatures in asparagus ( Asparagus officinalis L.). A winter hardy cultivar, “Guelph Millennium” (GM), cold acclimates, senesces, and develops freezing tolerance earlier in the fall compared to “UC157” (UC), a cultivar adapted to warm climates. Decreasing photoperiod can induce timely senescence and freezing tolerance in both woody and herbaceous perennials, although its effects on asparagus are unclear. The objectives of this research were to study the effects of daylength and cold, and their interaction, on the induction of freezing tolerance in asparagus. Seedlings of GM and UC were subjected to four treatments: constant (15.5 h) or decreasing (15.5–14 h) photoperiods with either high (23 °C) or low (11 °C) temperatures. Decreasing daylengths did not impact the acquisition of freezing tolerance at either temperature. For UC, low temperature accompanied by decreasing photoperiod diminished root:shoot ratio and increased crown water percentage, which are both indicators of reduced dormancy. A decreasing photoperiod and high temperature increased crown fructan (total and high-molecular weight) and decreased glucose and proline concentrations in GM compared to UC. These results suggest that decreasing daylengths, similar to those occurring in late summer in Southern Ontario, may be a signal for crown metabolite partitioning. This effect may be a contributing factor to the timely senescence and cold acclimation seen in GM compared to UC.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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 designBench or experimental
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

Citations0
Published2022
Admission routes4
Has abstractyes

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