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Record W2892590085 · doi:10.23986/afsci.70780

Ion beam irradiation mutagenesis in rye (Secale cereale L.), linseed (Linum usitatissimum L.) and faba bean (Vicia faba L.)

2018· article· en· W2892590085 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAgricultural and Food Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Genetic and Mutation Studies
Canadian institutionsUniversity of Saskatchewan
FundersJyväskylän YliopistoHelsingin Yliopisto
KeywordsSecaleVicia fabaIrradiationBiologyMutation breedingIon beamGerminationCropInflorescenceHorticultureAgronomyMutantIonChemistryBiochemistry

Abstract

fetched live from OpenAlex

Ion beam irradiation is a potential tool for inducing novel mutations in plants. We chose three crop species (rye, linseed, and faba bean) to determine the potential of nitrogen ion beam irradiation for inducing mutations. We tested ion beam irradiation with nitrogen ions at six different fluencies (5×105, 1×106, 5×106, 1×107, 5×107, and 1×108 N-ion cm-2) on dry grains. The three studied crop species had different sensitivities to the irradiation. Increased doses of ion irradiation had more effect on survival than on germination. Rye seedlings had the lowest survival rate at high doses of irradiation and significantly higher off-type plant phenotypes than the other two species. In M1 seedlings, stunted growth, failure to complete the plant life cycle and chlorophyll mutants were observed in all three species. Terminal-inflorescence mutations and sectional chimeras in faba bean were observed in the M2 generation. We conclude that ion beam irradiation is an effective tool for mutation breeding of diverse crop species when the appropriate dose is defined.

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.

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 score0.948
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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