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Record W3127645913 · doi:10.5376/mp.2020.11.0004

Effects of <i>Tilletia foetida</i> on Activities of Three Defense Enzymes in Wheat

2020· article· en· W3127645913 on OpenAlexvenueno aff
Ting He, Taiguo Liu, Wanquan Chen, Qingyun Guo, Li Gao

Bibliographic record

VenueMolecular Pathogens · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsCatalasePoint of deliveryCultivarBiologyPeroxidaseSuperoxide dismutaseEnzymeEnzyme assayPlant disease resistanceAgronomyHorticultureBotanyBiochemistryGene

Abstract

fetched live from OpenAlex

To reveal the effect of  Tilletia foetida  (Wallr.) Liro on defense enzymes activities in wheat stems, leaves and ears, the cultivar 'Dongxuan 3' highly sensitive to wheat common bunt and 'Yinong 18 / Lankao Aizao 8' highly resistant to wheat dwarf bunt were used as test materials to study the activities of catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) after 0~6 days of infection by the  Tilletia foetida . The results showed that the activities of defense enzymes of the two wheat varieties were significantly increased. Except for the increase of CAT activity in the leaves of susceptible varieties, the activities of POD and SOD in stems and spikes of resistant varieties were higher than those of susceptible varieties, and the enzyme activities of resistant varieties lasted for a long time and the change range was more gentle. The activity of defense enzyme in the leaves of the two cultivars was higher than that in the stems and spikes, CAT and POD activity in the spikes showed the earliest peak of enzyme activity. All the three kinds of defense enzymes were correlated with disease resistance of wheat, which could provide theoretical basis for breeding resistance to common bunt of wheat.

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 score0.041
Threshold uncertainty score0.370

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 head0.191
Teacher spread0.180 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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