MétaCan
Menu
Back to cohort
Record W1562828167 · doi:10.5376/tgg.2011.02.0001

SSR Mapping for Locus Conferring on the Triple-Spikelet Trait of the Tibetan Triple-spikelet Wheat (<i>Triticum aestivum</i> L. concv. <i>tripletum</i>)

2012· article· en· W1562828167 on OpenAlexvenueno aff
Jun Li, Q. Wang, Wei HuiTing, Xiaorong Hu, Wuyun Yang

Bibliographic record

VenueTriticeae Genomics and Genetics · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsLocus (genetics)TraitBiologyAgronomyGeneticsGeneComputer science

Abstract

fetched live from OpenAlex

Tibetan triple-spikelet wheat is an unique common wheat landrace in Tibet region of China, which has special triple spikelet trait with supernumerary spikelets and florets. Molecular Mapping the control gene locus conferring on triple spikelet trait and mining the closely linked markers would be facilitate high-yield wheat breeding by marker-assisted selection approach. In this study, derived lines TTSW-5 from Tibetan triple spikelet wheat and common-spikelet wheat, Jian 3 and Chuanmai 55, were used to construct the F 2 populations for , phenotypic analysis and SSR genotyping. Genetic analysis of phenotypic traits showed that triple spikelet trait of Tibetan triple spikelet wheat are controlled by two independent recessive gene loci. One QTL linked to the triple spikelet trait was detected on the chromosome 2A by using F 2 population from TTSW-5/Jian 3 combination and SSR markers, the targeted locus was located within SSR markers, Xgwm275 and Xgwm122, the genetic distance between two markers is 6.6CM with LOD value 6.19,  which can be explained 33.1% phenotypic variation,  The detected locus tentatively named as qTS2A -1 . We speculated that qTS2A -1 locus might be one of dominant loci for controlling the triple spikelet trait , Therefore, SSR markers, Xgwm275 and Xgwm122, might  be used as assisted selection markers for triple spikelet trait in high-yield breeding program.

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 categoriesMeta-epidemiology (narrow)
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 score0.907
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.032
GPT teacher head0.229
Teacher spread0.197 · 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.

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

Citations10
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueTriticeae Genomics and GeneticsSame topicWheat and Barley Genetics and PathologyFrench-language works237,207