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Record W4380537788 · doi:10.2503/hortj.qh-052

Development and Evaluation of a New Source of Tolerance to Fusarium Wilt Race 1.2 in Melon

2023· article· en· W4380537788 on OpenAlexaff
Tomoko Ishikawa, Ryo Okada, M. Kuzuya, Kenji Kato, Yosuke Yoshioka

Bibliographic record

VenueThe Horticulture Journal · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsPlant Biotechnology Institute
Fundersnot available
KeywordsMelonFusarium wiltRace (biology)HorticultureBiologyFusarium oxysporumBotany

Abstract

fetched live from OpenAlex

Melon Fusarium wilt, caused by Fusarium oxysporum f. sp. melonis (Fom), is one of the most prevalent fungal diseases affecting melon (Cucumis melo L.). We aimed at finding an effective resource for breeding cultivars tolerant to Fom race 1.2, which includes pathotypes that cause yellowing (race 1.2y) and wilting (race 1.2w). We screened 294 melon accessions that originated mainly in Africa and Asia for tolerance to race 1.2y. The highest level of tolerance was observed in the Indian accession PI124550; one of the five PI124550 plants tested showed no disease symptoms. From this plant, a tolerant inbred line, YR01, was developed after seven rounds of selfing combined with selection for tolerance to race 1.2y. YR01 had a high level of tolerance not only to race 1.2y, but also to race 1.2w. It was more tolerant to race 1.2y than the tolerant reference control ‘Isabelle’ and was equally tolerant to race 1.2w. Analysis of F1 hybrids and an F2 population developed by crossing YR01 with susceptible ‘Earl’s Favorite Harukei 3’ suggested that YR01 had multiple recessive and dominant (or codominant) genes for tolerance to race 1.2y and one dominant gene for tolerance to race 1.2w. These results indicate that PI124550 and its derivative YR01 are a promising breeding material with novel genes conferring practically useful tolerance to both pathotypes of race 1.2.

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 score0.648
Threshold uncertainty score0.144

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 head0.022
GPT teacher head0.274
Teacher spread0.252 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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