MétaCan
Menu
Back to cohort
Record W4412683919 · doi:10.1080/19315260.2025.2538495

Effect of planting distance and spatial arrangement on different cultivars of romaine lettuce in a controlled hydroponic environment system

2025· article· en· W4412683919 on OpenAlexafffund
Eugene Roy Antony Samy, Olivia Mendelson, Naresh Kumar Arumugagounder Thangaraju, Sarah MacPherson, Philip Wiredu Addo

Bibliographic record

VenueInternational Journal of Vegetable Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLeaf Properties and Growth Measurement
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCultivarSowingHorticultureBiologyAgronomy

Abstract

fetched live from OpenAlex

Lettuce is a nutritious leafy vegetable, which is cultivated worldwide. This study investigated how planting distance and patterns (non-staggered and staggered) influence different cultivar responses of romaine lettuce (Lactuca sativa). Valley Heart exhibited a higher yield at lower spacing conditions than Breen. Increasing the distance from 6.3 to 8.8 cm increased fresh mass by 46% for non-staggered patterns and 46.1% for staggered patterns for Breen and 51.8% for non-staggered patterns and 62.4% for staggered patterns for Valley Heart. Dry mass increased by 41% for non-staggered patterns, 33.7% for staggered patterns, and 58.3% for non-staggered patterns for Breen and 35.2% for staggered patterns for Valley Heart by increasing the distance from 6.3 to 10.1 cm. The tallest plant heights of 31.8 ± 4.2 cm for Breen and 46.6 ± 0.4 cm for Valley Heart were observed with a non-staggered pattern at 6.3 cm. The highest internodal elongations of 2 ± 0.3 cm and 2.3 ± 0.3 cm were additionally observed with a 6.3-cm staggered distance for Breen and non-staggered distance for Valley Heart, respectively. The spacing pattern did not significantly influence the plant growth for both cultivars. These findings contribute to a better understanding of different cultivars’ responses to planting density in terms of plant growth.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.124

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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Vegetable ScienceSame topicLeaf Properties and Growth MeasurementFrench-language works237,207