MétaCan
Menu
Back to cohort
Record W3048738466 · doi:10.21273/hortsci15196-20

Overnight Supplemental Blue, Rather than Far-red, Light Improves Microgreen Yield and Appearance Quality without Compromising Nutritional Quality during Winter Greenhouse Production

2020· article· en· W3048738466 on OpenAlexaffabout
Qinglu Ying, Yun Kong, Youbin Zheng

Bibliographic record

VenueHortScience · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBrassicaGreenhouseCropBiologyHorticultureChlorophyllYield (engineering)CarotenoidLight intensityFar-redCotyledonBotanyAgronomyRed light

Abstract

fetched live from OpenAlex

To determine whether supplemental blue light (B) or far-red light (FR) overnight can promote microgreen elongation to facilitate machine harvesting and improve microgreen quality and yield, two common microgreen species, mustard ( Brassica juncea ) and arugula ( Eruca sativa ), were grown in a greenhouse in Guelph, Ontario, Canada, during January 2019. Low-intensity (14 μmol·m −2 ·s −1 ) B or FR was applied to microgreens overnight from 1730 hr to 0630 hr , and no supplemental lighting (D) was used as a control. After 2 weeks of light treatments, B compared to D promoted stem elongation by 16% and 10%, respectively, and increased crop yield by 32% and 29%, respectively, in mustard and arugula. B compared to D also increased the cotyledon area in mustard and leaf mass per area in arugula and enhanced cotyledon color in both species despite having no effects on total chlorophyll, carotenoid, and phenolic contents. However, FR did not increase stem length or fresh weight compared with D, reduced plant height compared with B in both species, and reduced the cotyledon area in arugula. FR, compared with D and B, reduced the stem diameter and phytochemical contents of both species. Therefore, low-intensity B can be applied overnight for winter greenhouse microgreen production because of its beneficial effects on appearance quality and crop yield without negatively affecting nutritional quality.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.428

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 communication0.0000.001
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 head0.031
GPT teacher head0.255
Teacher spread0.224 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueHortScienceSame topicLight effects on plantsFrench-language works237,207