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Record W2902749205 · doi:10.20546/ijcmas.2018.711.236

Marker Trait Correlation Study for Fusarium wilt Resistance in Chickpea (Cicer arietinum)

2018· article· en· W2902749205 on OpenAlexaff
Vishal L Bagde, S. J. Gahukar, Amrapali A Akhare

Bibliographic record

VenueInternational Journal of Current Microbiology and Applied Sciences · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsFusarium wiltBiologyCultivarFusariumPopulationHorticultureVeterinary medicineTraitQuantitative trait locusAlleleFusarium oxysporumAgronomyGeneticsGeneMedicine

Abstract

fetched live from OpenAlex

The investigation was focused on transfer of the fusarium wilt resistance into elite cultivar. Screening of chickpea parents (ICC 506 EB and Vijay), 196 RIL’s (Obtained from ICRISAT, Hyderabad), F2and BC1F1 populations for fusarium wilt resistance were done by Pot culture method and wilt sick plot method. The BC1F1 segregated in 1:1 ratio for resistance and susceptibility and F2 progenies segregated in a ratio of 1 resistant and 3 susceptible. The RILs closely fit a 1:1 segregation ratio for resistance and susceptibility indicating that resistance to fusarium wilt was monogenic with the recessive allele conferring resistance to fusarium wilt in this population. The parents were screened with 43 SSR primers. 22 markers were identified polymorphic. The polymorphism ranged from 57.14 to 100.00 per cent. The PIC scores of SSR markers ranged between 0.0371 and 0.9226. The BC1F1 population screened with three polymorphic foreground markers (TR19, TA110 and GA16) and four polymorphic background markers (TS82, TA194, TA135 and TA 22). The reported markers linked to susceptibility and resistance proved their effectiveness and further can be exploited for maker assisted selection (MAS) of fusarium wilt resistance breeding in chickpea.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.267
Teacher spread0.241 · 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 designObservational
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

Citations3
Published2018
Admission routes1
Has abstractyes

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