MétaCan
Menu
Back to cohort
Record W2513289528 · doi:10.4236/ajps.2016.712150

The Effect of Nitrogen and Phosphorus Ratios and Electrical Conductivity on Plant Growth

2016· article· en· W2513289528 on OpenAlexaff
Laura Wiser, Theo J. Blom

Bibliographic record

VenueAmerican Journal of Plant Sciences · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPhosphorusPlant growthAmmoniumNitrogenNutrientAgronomyHorticultureChemistryBiologyBotanyEcology

Abstract

fetched live from OpenAlex

Environmental concerns surround the use of plant growth retardants (PGRs) for plant height control, and non-chemical alternatives to PGRs can be labor intensive and expensive. Macronutrient modification is a little-studied, yet potentially effective method of controlling plant height. A number of studies have suggested that phosphorus (P) limitation may restrict plant height. Anecdotal evidence also suggests that using nitrate (NO3-), rather than ammonium (NH4+), as the principal nitrogen (N) source may help control plant height. The primary objective of this study was to evaluate different ratios of NO3-/ NH4+, NO3-/P and NH4+/P as well as electrical conductivity (EC) on plant height and growth. This was tested in a hydroponic system using marigolds, sunflowers and tomatoes. Initially, different ratios were tested at an EC of 1.2 dS·m-1, followed by using the same ratios at four ECs (0.6, 1.2, 2.2 and 4.0 dS·m-1) as a second objective. Although ratios did, at times, limit plant height, responses were season and species dependent, suggesting that modifications in plant nutrition, at the ratios used in this study, may not effectively control plant height in hydroponic systems. More consistent, yet species specific, height control was achieved by increasing EC level.

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 score0.183
Threshold uncertainty score0.274

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 studies0.0000.001
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 head0.008
GPT teacher head0.200
Teacher spread0.192 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Plant SciencesSame topicPlant Growth and Agriculture TechniquesFrench-language works237,207