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Record W2754595400 · doi:10.5539/jas.v9n10p189

Trinexapac-Ethyl Causes Stimulatory Effect on the Initial Growth of Eucalyptus urograndis Clones

2017· article· en· W2754595400 on OpenAlexvenueno aff
Allan Lopes Bacha, Pedro de Figueiredo Rocha Barbosa Martins, Willians César Carrega, P. L. da C. A. Alves, Rinaldo César de Paula

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsnot available
FundersUniversidade Estadual Paulista
Keywordsclone (Java method)BiologyEucalyptusHorticultureBotanyRandomized block designGeneGenetics

Abstract

fetched live from OpenAlex

Eucalyptus plants are sensitive to stress factors in the initial growth phase. The plant growth regulator trinexapac-ethyl can provide gains to eucalyptus plants, a phenomenon known as hormesis. Thus, the aim of this work was to evaluate the effect of trinexapac-ethyl on the initial growth of two Eucalyptus urograndis clones (Clone 1 = I-144 and Clone 2 = 1407). The experiment was performed during 90 days after planting (DAP) of eucalyptus, in 100 L pots, with a randomized complete block design. The treatments were arranged in a 2 × 3 factorial scheme, with two eucalyptus clones and three trinexapac-ethyl doses (0, 30 and 60 g i.a. ha-1), with four replications. Fortnightly, plants height and stem diameter were evaluated. At 90 DAP, the leaf area and plants dry matter (DM) were evaluated. Clone 1 obtained leaf area and total DM 53% and 58% larger than Clone 2, respectively. The higher dose of trinexapac-ethyl provided mean gains of 30% in stem DM and total DM in Clone 1. For Clone 2, both doses of the product caused mean gains of 70% in stem DM, leaf DM and total DM. In conclusion, trinexapac-ethyl has a positive effect on the initial growth of E. urograndis, Clones I-144 and 1407. Clone I-144 showed higher growth than Clone 1407, regardless trinexapac-ethyl application. However, the Clone 1407 obtained more expressive gains with the application of trinexapac-ethyl, compared to Clone I-144.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.271
Teacher spread0.240 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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