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Record W2900266758 · doi:10.5539/jas.v10n12p171

Genetics of Resistance in F2 Soybean Populations for Adzuki Bean Bruchid (Callosobruchus chinensis)

2018· article· en· W2900266758 on OpenAlexvenueno aff
Ulemu M. Msiska, Mehari Gebremedhn Hailay, Belay Weldekidan Miesho, Angele Ibanda, Phinehas Tukamuhabwa, Samuel Kyamanywa, Thomas Odong, Patrick Rubaihayo

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsPEST analysisDiallel crossBiologyInfestationCallosobruchus chinensisMating designCallosobruchus maculatusGenotypeHorticultureRandomized block designVeterinary medicineGeneHybridGeneticsMedicine

Abstract

fetched live from OpenAlex

Adzuki bean bruchid (Callosobruchus chinensis) is a significant pest of soybean in Uganda. To sustainably manage this pest, utilization of resistant soybean varieties is the key solution. Development of resistant varieties needs knowledge on modes of inheritance which is crucial in selection of parent materials. To identify parents, a study was initiated to determine the gene action and mode of inheritance of resistance to bruchids in soybean. Nine parental lines were crossed in a full-diallel at Makerere University Agricultural Institute, Uganda. The generated F1s were advanced to F2 and seeds were evaluated for response to bruchid infestation in a randomised complete block design. Ten seeds were infested with 10 randomly selected unsexed 1-3 day old bruchids. Genotypes showed significant differences in seed weight loss (swl), adult bruchid emergence (ABE) and Dobie susceptibility index (DSI) indicating that these parameters could be used to screen genotypes in genetic analysis. Mean squares of general combining ability (GCA) were significant (P < 0.05) for swl, DSI and number of ABE from the F2 seeds indicating additive gene action. Susceptibility parameters ABE and DSI showed significant specific combining ability (SCA) indicating non-additive gene action. Resistance was influenced by maternal effects indicating that direction of the cross was important. Genotypes S-Line 9.2 and S-Line 13.2A showed negative significant GCA effects for at least two of the susceptibility parameters indicating that they were the best parents for bruchid resistance breeding. The study established that additive, non additive and maternal effects governed the gene expression in soybean resistance to bruchids.

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 score0.922
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.032
GPT teacher head0.264
Teacher spread0.232 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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