MétaCan
Menu
Back to cohort
Record W4281707150 · doi:10.3390/agronomy12061371

Biological Response of Triticum aestivum L. to the Abiotic Stress Induced by Winemaking Waste

2022· article· en· W4281707150 on OpenAlexfundno aff
Silvica Padureanu, Antoanela Patraș

Bibliographic record

VenueAgronomy · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsnot available
FundersAgence Universitaire de la FrancophonieEuropean Commission
KeywordsWinemakingGerminationAbiotic stressMicronucleus testHorticultureAbiotic componentMitotic indexBiologyBotanyFood scienceChemistryMitosisToxicity

Abstract

fetched live from OpenAlex

The winemaking waste (grape marc) can be beneficial if it is used in food, pharmaceutical industry, and medicine. However, studies reported that some concentrations of grape marc extracts may induce negative effects on animals. The present study was conducted in order to research if the grape marc induces abiotic stress with serious negative implications on plants. For this purpose, wheat grains were treated for 48 h with 0.025%, 0.05%, 0.1% and 0.2% aqueous extracts of Merlot and Sauvignon blanc grape marc. Grains germination rate and cytogenetic parameters were investigated. The germination rate decreased moderately compared to the control in all treatments. The investigated cytogenetic parameters were: mitotic index (MI) and genetic abnormalities (bridges, fragments, associations between bridges and fragments, multipolar ana-telophases, micronuclei). As the grape marc concentration increases, the germination rate and mitotic index decrease moderately, while the percent of cells with chromosomal aberrations and micronuclei increases. Treatments with Merlot grape marc extract induced a higher percent of genetic abnormalities. The results prove from a genetic point of view that the winemaking waste induces abiotic stress on wheat (and probably, on other plants) and it should be depleted in polyphenols before storing on fields. Possible use of unprocessed grape marc could be as bio-herbicide.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.205

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 head0.017
GPT teacher head0.241
Teacher spread0.225 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAgronomySame topicPlant tissue culture and regenerationFrench-language works237,207