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Record W2979161531 · doi:10.1111/pbr.12751

Male sterility in soybean: Occurrence, molecular basis and utilization

2019· article· en· W2979161531 on OpenAlexaff
Jiajia Li, Muhammad Azhar Nadeem, Genlou Sun, Xiaobo Wang, Lijuan Qiu

Bibliographic record

VenuePlant Breeding · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsSaint Mary's University
FundersPostdoctoral Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsBiologyHeterosisCytoplasmic male sterilitySterilityBiotechnologyTraitHybrid seedAgricultureBreeding programCloning (programming)AgronomyGeneticsHybridCultivarComputer science

Abstract

fetched live from OpenAlex

Abstract In plants, male sterility (MS) is a specific breeding target trait. With the advancements in agriculture, utilization of heterosis breeding in hybrid production through MS lines has become the main breeding tool of various cross‐pollinated and even self‐pollinated crops. Soybean is an essential source of oil and protein; however, the low yield is a major factor limiting its development. Soybean MS mainly comprises cytoplasmic‐nuclear MS and nuclear/genic MS (NMS/GMS), which can effectively utilize heterosis to improve soybean yield. This review outlines the recent research progress on the development of new genetically MS lines, exploring the underlying molecular mechanism of MS, identification and cloning of MS and fertility restoration genes, and the application of MS lines. We further discussed and prospected the future developmental scenario direction of the soybean MS, based on the previous studies of other crops sterility system. Moreover, this review also provides comprehensive information for better application of MS to soybean breeding programme.

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 score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.021
GPT teacher head0.239
Teacher spread0.218 · 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

Citations26
Published2019
Admission routes1
Has abstractyes

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