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Record W4396514081 · doi:10.1080/14620316.2024.2345894

Amber LEDs outperform red, blue, and red-blue-amber LEDs for lettuce

2024· article· en· W4396514081 on OpenAlexafffund
S. Venkata Reddy, Lucas McCartney, Bo-Sen Wu, Philip Wiredu Addo, Sarah MacPherson, Mark Lefsrud

Bibliographic record

VenueThe Journal of Horticultural Science and Biotechnology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBlue lightLight-emitting diodeRed lightHorticultureArtificial lightYield (engineering)Monochromatic colorFar-redChemistryBotanyBiologyMaterials scienceOpticsOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Debate persists on light in controlled environment agriculture.To dissect the effects of conventionally used wavelengths on a crop and provide new information to this expanding food production sector, this study investigated the effects of monochromatic and combined red, blue, and amber light on lettuce growth with increasing light intensities (up to 1300 molm -2 sec -1 ) for 18 days with a 16 hd -1 .Under amber light at PPFDs ranging from 500 to 700 molm -2 sec -1 , fresh mass displayed a 33.3% greater yield when compared to red light at the same PPFD.Suppressed growth was observed with either red or amber alone at high PPFD (>800 molm -2 sec -1 ).Blue light was the least productive of the four treatments, yet lettuce plant growth was not suppressed at high intensities.No growth suppression was observed for lettuce plants grown under combined red-blue-amber light at high intensities, and these plants exhibited greater biomass yield than blue light alone.Varied degrees of pigmentation occurred under each light treatment, yet bleaching was only observed in plants grown under amber light alone at PPFD above 1000 molm -2 sec -1 .Findings present novel plant responses to high intensity light, setting precedence for future experiments aimed at expanding the use of LEDs in horticulture.

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)0.002
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 score0.246
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.013
GPT teacher head0.235
Teacher spread0.223 · 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

Citations10
Published2024
Admission routes2
Has abstractyes

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