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Record W3115920709

Susceptibility of fungi, mainly chocolate spot (botrytis fabae sard.), to gamma irradiation in the faba bean crop (vicia faba l.)

2021· article· en· W3115920709 on OpenAlexaff
Jesús Mao Estanislao Aguilar-Luna, Salvador López-López, Juan Manuel Loeza-Corte

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsVicia fabaSowingCropBiologyHorticultureGamma irradiationAgronomyIrradiation
DOInot available

Abstract

fetched live from OpenAlex

Fungi cause considerable losses in the faba bean crop in many regions of the world. The aim of the current research was to \nevaluate the susceptibility of faba bean to fungi, mainly chocolate spot, and its effect on yield, using seeds exposed to gamma \nirradiation. Faba bean seeds were cultivated in three regions: Hidalgo, Puebla and Tlaxcala, Mexico; the seeds were irradiated \nwith a dose rate of 4.90 Gy·min-1 \nusing a Gammacell 220 irradiator. The irradiation doses were 0, 20, 40, 60, 80, 160, 250 and \n350 Gy of gamma rays with 60Co radioisotopes. The irradiated seeds showed acceptable germination (75.70 %) without visible \ndamages, and survival was 53.62 % until 118 days after sowing. When unirradiated seed was used, the susceptibility of the crop \ncould reach 60 % and the disease severity up to 34 %, with a disease progress rate of 0.006 units·day-1 \n. The 40 Gy dose offered \nthe best response to control the disease; up to 58.80 g of dry weight was obtained for every 100 seeds and a production of \n4,442 kg·ha-1 \n. In faba bean crop, up to 77 % of the variation in yield was due to severity of fungi, mainly the chocolate spot.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes1
Has abstractyes

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Same venueDialnet (Universidad de la Rioja)Same topicGenetic and Environmental Crop StudiesFrench-language works237,207