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Record W7117650796 · doi:10.3390/horticulturae12010043

Greenhouse Performance of Anemone and Ranunculus Under Northern Climates: Effects of Temperature, Vernalization, and Storage Organ Traits

2025· article· en· W7117650796 on OpenAlexafffund
Sara Benchaa, Line Lapointe

Bibliographic record

VenueHorticulturae · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFlowering Plant Growth and Cultivation
Canadian institutionsUniversité Laval
FundersMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsVernalizationBoltingPhenologyphotoperiodismSowingGreenhouseYield (engineering)

Abstract

fetched live from OpenAlex

Optimizing the growing conditions of Anemone coronaria and Ranunculus asiaticus for cut-flower production under northern greenhouse conditions requires a better understanding of the environmental and cultivation practices influencing emergence, flowering, and flower quality. This study evaluated the effect of storage organ reuse, along with vernalization conditions, growth temperature, growing season, and planting method (in-ground vs. containers) on plant phenology and flower yield and quality. Flower quantity and quality were unaffected by storage organ age, confirming that these organs can be stored and reused the following season. Vernalization at temperatures of 7 °C or 10 °C advanced flowering compared to warmer vernalization in all cultivars, and increased flower yield compared to non-vernalization. Growth under cool conditions (15/10 °C day/night) extended the production period and improved floral quality by promoting longer stems and delaying senescence. Short to moderate photoperiods (11–13 h in the winter vs. 15 h in the spring) and low light intensity, typical of winter, promoted stem elongation and marketable flower yield, whereas increasing photoperiod and temperature in late spring shorten the flowering period. Ground beds provided cooler and more buffered soil conditions, improving flowering duration and yield compared to container-grown plants during springtime. These findings highlight the importance of integrating temperature management, vernalization, and tailored cultivation practices to enhance flower quality, prolong the production, and improve sustainability of cut-flower production under northern climates in both species.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.152

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 head0.004
GPT teacher head0.170
Teacher spread0.167 · 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
Published2025
Admission routes2
Has abstractyes

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