MétaCan
Menu
Back to cohort
Record W2128151414

ASCORBIC ACID OF SEEDS AND PROTEINS OF LEAVES AS BIOCHEMICAL MARKERS FOR RESISTANCE OF FLAX TO POWDERY MILDEW DISEASE

2012· article· en· W2128151414 on OpenAlexaboutno aff
Aly A. Aly, Heba I. Mohamed, Kamel A. Abd–Elsalam

Bibliographic record

VenueRomanian Agricultural Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Plant Science, Crop Management
Canadian institutionsnot available
Fundersnot available
KeywordsPowdery mildewCultivarAscorbic acidMalondialdehydeHorticultureLipid peroxidationStepwise regressionPeroxidaseBiologyAntioxidantChemistryBotanyVeterinary medicineBiochemistryEnzymeMedicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

A field trial was conducted in 2009/2010 and 2010/2011 growing seasons at Giza Agricultural Research Station to evaluate powdery mildew (PM) severity on 15 flax cultivars. In general, the tested cultivars could be divided into six distinct groups, i.e., highly susceptible (Corland and C.I. 2008), susceptible (Sofie and Marylin), moderately susceptible (Giza 8, Sakha 1, Giza 7, and Marshall), moderately resistant (Cass and Clay), resistant (Koto, Dakota, Wilden, and Bombay), and highly resistant (Ottawa 770B). The cultivars showed considerable variation in PM severity ranged from 8.05 on Ottawa 770 B to 97.02% on Cortland. Total free amino acids, total soluble proteins, total phenols, antioxidant enzymes (peroxidase and polyphenoloxidase), ascorbic acid, tocopherol, and malondialdehyde (MDA), as indicator of lipid peroxidation, were determined in uninfected seeds and in uninfected leaves of the tested cultivars. Pearson’s correlation coefficient was calculated to measure the degree of association between PM severity and each component in linseeds or in leaves. All components, except free amino acids in linseeds and MDA in leaves, showed significant (P<0.05) or highly significant (P<0.01) negative correlation with PM severity. Free amino acids in linseeds were not correlated with PM severity, while MDA in leaves was positively correlated (P<0.01). Data for PM severity and level or activity of each component were entered into a computerized stepwise multiple regression analysis. Using the predictors supplied by stepwise regression, two one-factor models were constructed to predict PM severity. These models showed that PM severity differences were due largely to ascorbic acid of seeds and proteins of leaves, which accounted for 58.46 and 77.15%, respectively of the total variation in PM severity. The results of the present study suggest that ascorbic acid in uninfected seeds or total proteins in uninfected leaves can be used as biochemical markers to predict PM resistance in flax.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.285
Teacher spread0.250 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueRomanian Agricultural ResearchSame topicAgriculture, Plant Science, Crop ManagementFrench-language works237,207