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Record W4221062515 · doi:10.1139/cjb-2021-0172

Pathogenesis-related gene (<i>PvPR1</i> and <i>PvPR2</i>) expression involved in <i>Meloidogyne incognita</i> parasitism and resistance reactions of common bean genotypes in host–nematode interactions

2022· article· en· W4221062515 on OpenAlexvenueno aff
Refik Bozbuğa, Vahdettin Çi̇ftçi̇, Mehmet Zahit Yeken, Mustafa İmren

Bibliographic record

VenueBotany · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyMeloidogyne incognitaNematodeTerra incognitaNematode infectionPhaseolusGenotypeGeneGene expressionHost (biology)Root-knot nematodeParasitismGeneticsBotanyEcology

Abstract

fetched live from OpenAlex

Pathogenesis-related (PR) genes are useful molecular markers, and gene expressions are activated in the reaction of plant-parasitic nematodes. Determining the PR gene expression and the resistance reaction of Phaseolus vulgaris L. genotypes against root-knot nematode are valuable for understanding plant–nematode interactions. However, resistance reactions of P. vulgaris genotypes and the gene expression of host–nematode interactions are not fully understood. Therefore, this study aimed to determine the expression of PR genes during the infection of Meloidogyne incognita on resistant and susceptible bean varieties at 1, 3, 5, and 7 days postinfection (dpi). The results revealed that one genotype gave a reaction as “immune”, and numerous genotypes were susceptible. The expression of PvPR1 and PvPR2 genes reached the highest peak at 1 dpi in nematode-infected immune plants, and the expression of PvPR1 reached 5 dpi in susceptible plants. In conclusion, PR genes involved in nematode resistance and parasitism and the immune common bean genotype have great potential in breeding programs and understanding the exact location of resistance on the gene map would be advantageous as future work.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.331

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 science0.0000.000
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 head0.013
GPT teacher head0.219
Teacher spread0.206 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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