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Record W2953899394 · doi:10.5539/jas.v11n11p41

Identification of Double-Haploid Maize Plants One Generation After the Chromosomes Doubling

2019· article· en· W2953899394 on OpenAlexvenueno aff
Raquel Maria Oliveira Pires, B. G. Ribeiro, F. O. Bustamante, E. V. R. Von Pinho, Heloísa Oliveira dos Santos, Renzo Garcia Von Pinho

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoUniversidade Federal de LavrasCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsBiologyPloidyGene duplicationChromosomeDoubled haploidyGeneticsGene

Abstract

fetched live from OpenAlex

The objectives in the present work were to identify maize double haploids one generation after chromosome duplication through the evaluation of phenotypic characteristics in thr field, flow cytometry and molecular markers SSR. The seeds used in the present study were obtained from a cross between four simple hybrids (DKB393, GNS 3225, GNS 3264, GNS 3032) and the KEMS inducer of gymnogenetic haploidy, used as a male parent. Seeds from this crossing were selected according to the R-Navajo marker and those considered haploid, were submitted to two different chromosome duplication protocols. Plants that survived to the chromosome duplication protocols were acclimatized in greenhouse and later transplanted to the field. After self-fertilization of the DH0 plants, the DH1 seeds obtained were seeded in the field, divided into treatments according to the parental and duplication protocols. At the vegetative stage V4 of the DH1 seedlings, leaf tissue samples were collected to identify ploidy via flow cytometry and DNA analyzes using microsatellite markers. These results were confronted with the morphological characteristics of the future DH1 plants developed in the field, evaluated with the use of descriptive tools. Statistical analyzes were performed using the generalized linear modeling approach and the exploratory and inferential analyzes of datas, by the use of graphical resources, barplot and boxplot. For the analysis of variance, were used the Student-Newman-Keuls test, and the Pearson's correlations. It was not observed uniformity of phenotypic characteristics of plants subjected to duplication protocols in the field and the use of descriptive tools in the morphological analysis of adult maize plants must be done carefully to avoid the wrong classification of determined genotypes related to the ployd. Flow cytometry must be used as screening in the identification of possible DH´s and the molecular markers SSR can be used to prove the genetically inherited KEMS lineage and also to identify the double-haploid corn plants.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.226
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

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