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Elevated Ultraviolet-B Radiation Reduces Concentrations of Isoflavones and Phenolic Compounds in Soybean Seeds

2010· article· en· W2123455092 on OpenAlex
E. H. Kim, Philippe Séguin, J. E. Lee, C. G. Yoon, Hyun‐Kon Song, Jae Kyoun Ahn, Ill‐Min Chung

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

VenueJournal of Agronomy and Crop Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsMcGill University
Fundersnot available
KeywordsIsoflavonesChemistryFood scienceUltravioletAgronomyBiochemistryBiology

Abstract

fetched live from OpenAlex

The gradual disruption of the ozone layer in the stratosphere has resulted in increased exposure of plants to ultraviolet-B (UV-B, 280–315 nm) radiation. UV-B radiation is known to affect crop growth and quality negatively. A study was conducted to determine the impact of elevated UV-B radiation levels on the isoflavones and phenolic compound concentrations of seven soybean varieties. UV-B radiation significantly reduced the concentration of most isoflavones and phenolic compounds in soybean seeds. Exposure to elevated UV-B levels overall resulted in 35 % reduction in total isoflavones and 31 % in phenolic compounds concentrations. The effect on individual isoflavones and phenolic compounds depended on the compound and variety, but UV-B overwhelmingly reduced concentrations. This study suggests that increased UV-B radiation negatively impacted soybean quality by reducing the concentration of compounds that have health-beneficial properties.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.133

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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