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Record W2956031388 · doi:10.5539/jas.v11n11p193

Adjusting the Minigrafting Technique Applied to Citrus by Using Rootstocks Grown in vitro

2019· article· en· W2956031388 on OpenAlexvenueno aff
Maria Inês S. Mendes, Antônio Sérgio de Souza, Maria Angélica Pereira de Carvalho Costa, W. dos S. Soares Filho, Abelmon da Silva Gesteira, Honorato P. Silva Neto

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanana Cultivation and Research
Canadian institutionsnot available
Fundersnot available
KeywordsRootstockCultivarHorticultureOrange (colour)BiologyBotany

Abstract

fetched live from OpenAlex

Techniques applied to promote citrus propagation are of extreme relevance, since they assure high yield rates, as well as high genetic and phytosanitary quality. The aim of the present research is to assess the vegetative growth and survival of citrus cultivars subjected to different rootstocks through minigrafting in order to generate identical to the parents. Minigrafting of apical segments (1 and 2 cm long) of ‘Clementine’ tangerine budded onto rootstocks of citrandarins ‘Indio’ and ‘Riverside’ and of the combination between varieties ‘Pera’ sweet orange, ‘Sunki Madarin’ tangerine and ‘Santa Cruz Rangpur’ lemon budded onto rootstocks of citrandarins ‘Indio’, HTR-069 and LRF × (LCR × TR)-005 were evaluated. Assessments were conducted in greenhouse 120 days after the experiment were installed. The use of 2cm long segments facilitates minigrafting adherence to smaller caudal apices. The rootstock of HTR-069 presented the best survival responses among the assessed crowns. Rootstock of citrandarin ‘Indio’ enabled the best crown length development and graft diameter. Based on the results, minigrafting can be a new option for citrus propagation.

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)0.002
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 score0.488
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.257
Teacher spread0.235 · 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
Published2019
Admission routes1
Has abstractyes

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