MétaCan
Menu
Back to cohort
Record W2029614849 · doi:10.1021/jf802192f

Metabolic Changes in Roots of the Oilseed Canola Infected with the Biotroph Plasmodiophora brassicae: Phytoalexins and Phytoanticipins

2008· article· en· W2029614849 on OpenAlexaff
M. Soledade C. Pedras, Qing‐An Zheng, Stephen E. Strelkov

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsUniversity of SaskatchewanUniversity of Alberta
Fundersnot available
KeywordsCanolaClubrootBrassicaBiologyMetabolitePhytoalexinAlternaria brassicaeBotanyHorticultureBiochemistry

Abstract

fetched live from OpenAlex

Analyses of metabolite production and accumulation in roots of canola ( Brassica napus L. spp. oleifera) infected with the phytopathogen Plasmodiophora brassicae (clubroot) allowed the identification of 45 metabolites. HPLC analysis corroborated by metabolite isolation and NMR spectroscopic data demonstrated for the first time that phytoalexins and phytoanticipins were produced in roots of canola infected with a soilborne biotroph. In addition, six new indolyl metabolites were identified, synthesized, and tested against three fungal pathogens of canola. Multivariate data analysis using principal component analysis (PCA) revealed distinct metabolic responses of canola to P. brassicae infection during a six-week period. At late harvest days (five and six weeks), a clear clustering was observed among samples of infected roots because of the higher concentration of phytoalexins, while higher concentration of phytoanticipins contributed to the differentiation between three and four weeks samples of infected and control roots. Altogether, the data shows that canola roots under biotrophic attack are able to produce a complex blend of phytoalexins and other antimicrobial metabolites as a defensive response and that the metabolic regulation of phytoanticipins and phytoalexins appeared to correlate with the infection period.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.122

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 head0.009
GPT teacher head0.173
Teacher spread0.164 · 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

Citations59
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicPlant Disease Resistance and GeneticsFrench-language works237,207