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Record W4402072600 · doi:10.5376/mpb.2024.15.0017

Autotetraploid Rice Hybrids: Overcoming Sterility Barriers for Enhanced Heterosis

2024· article· en· W4402072600 on OpenAlexvenueno aff
Qian Zhu, Xiaoling Zhang, Hui Zhang, Juan Li, Chunli Wang, Dongsun Lee, Lijuan Chen

Bibliographic record

VenueMolecular Plant Breeding · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRice Cultivation and Yield Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsSterilityHeterosisBiologyHybridBiotechnologyInterspecific hybridizationGeneticsAgronomy

Abstract

fetched live from OpenAlex

Autotetraploid rice, developed through whole genome duplication of diploid rice, offers potential advantages such as larger grains, higher nutrient content, and increased resistance. However, its low fertility has been a significant barrier to its commercial viability. Recent advancements have focused on understanding and overcoming the sterility issues in autotetraploid rice hybrids to harness their heterosis potential. The development of high-fertility tetraploid rice lines and the application of molecular breeding techniques have shown promise in improving hybrid performance. This study synthesizes the genetic mechanisms underlying the low fertility of autotetraploid rice and its F 1  hybrids from both cytological and molecular biological perspectives. It introduces the main types of high-fertility tetraploid rice and the latest research progress. Lastly, the study proposes ideas for future research on exploiting the heterosis of high-fertility autotetraploid rice, aiming to provide insights for polyploid rice breeding.

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)0.000
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 score0.022
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.230
Teacher spread0.206 · 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
Published2024
Admission routes1
Has abstractyes

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