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Record W4389224091 · doi:10.1038/s41467-023-42991-z

Soybean reduced internode 1 determines internode length and improves grain yield at dense planting

2023· article· en· W4389224091 on OpenAlexaff
Shichen Li, Zhihui Sun, Qing Sang, Chao Qin, Lingping Kong, Xin Huang, Huan Liu, Tong Su, Haiyang Li, Milan He, Chao Fang, Lingshuang Wang, Shuangrong Liu, Bin Liu, Baohui Liu, Xiangdong Fu, Fanjiang Kong

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsInstitute of Genetics
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsSowingYield (engineering)Grain yieldAgronomyBiologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Major cereal crops have benefitted from Green Revolution traits such as shorter and more compact plants that permit high-density planting, but soybean has remained relatively overlooked. To balance ideal soybean yield with plant height under dense planting, shortening of internodes without reducing the number of nodes and pods is desired. Here, we characterized a short-internode soybean mutant, reduced internode 1 (rin1). Partial loss of SUPPRESSOR OF PHYA 105 3a (SPA3a) underlies rin1. RIN1 physically interacts with two homologs of ELONGATED HYPOCOTYL 5 (HY5), STF1 and STF2, to promote their degradation. RIN1 regulates gibberellin metabolism to control internode development through a STF1/STF2-GA2ox7 regulatory module. In field trials, rin1 significantly enhances grain yield under high-density planting conditions comparing to its wild type of elite cultivar. rin1 mutants therefore could serve as valuable resources for improving grain yield under high-density cultivation and in soybean-maize intercropping systems.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.302

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 science0.0010.001
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 head0.039
GPT teacher head0.274
Teacher spread0.234 · 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

Citations47
Published2023
Admission routes1
Has abstractyes

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