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Record W3169344873 · doi:10.5539/jas.v13n7p55

Growth of Alfavaca-Cravo in Response to Different Levels of Shade and Tiririca Density

2021· article· en· W3169344873 on OpenAlexvenueno aff
Patricia Aparecida de Carvalho, Maria Juliana A. de Oliveira, Rafaela Aparecida A. de Almeida, Silvério de Paiva Freitas, Geraldo de Amaral Gravina

Bibliographic record

VenueJournal of Agricultural Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAllelopathy and phytotoxic interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCyperus rotundusOcimum gratissimumShadingContext (archaeology)WeedDry weightHorticultureBiologyCropAgronomyBotany

Abstract

fetched live from OpenAlex

The species Ocimum gratissimum L. is widely utilized in food, cosmetics, and folk medicine, and is also an important source of essential oils. Understanding its behavior in response to environmental conditions is of paramount importance to improving crop management methods. In this context, the following study aimed to evaluate the effects of shade, and of competition with weeds (Cyperus rotundus L.), on the growth of Ocimum gratissimum L. The experimental design adopted was randomized blocks, in a 5 × 5 factorial scheme, with 5 levels of shading (48%, 75%, 77%, 83% and 90%) and 5 densities of Cyperus rotundus L. (0, 5, 10, 15 and 20 per pot), with 4 repetitions. The variables analyzed were main stem height (MSH), diameter of stem base (DSB), number of leaves on the principal branch (NL), number of ramifications (NR), chlorophyll index of leaves (CIL), foliar area (FA), dry mass of the aerial part of the medicinal species (DMAPm), dry mass of the aerial part of the weed species (DMAPw) and essential oil content (EOC). The results demonstrate that the Ocimum gratissimum L. plants presented compatible tolerance responses to up to 70% shading, and that competition with Cyperus rotundus L. was detrimental in a density above 13 plants per pot in interaction with shading. The highest dry mass production and, consequently, the highest oil yield, were obtained from the 48% shading treatment.

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)0.001
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 score0.795
Threshold uncertainty score0.115

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.248
Teacher spread0.226 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

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