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Record W1991993569 · doi:10.1021/jf101412y

Chemical Profiling of Lentil (Lens culinaris Medik.) Cultivars and Isolation of Compounds

2010· article· en· W1991993569 on OpenAlexaff
Apollinaire Tsopmo, Alister D. Muir

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsAgriculture and Agri-Food CanadaCarleton University
Fundersnot available
KeywordsMethanolChemistryCultivarChromatographyHigh-performance liquid chromatographyArbutinBotanyBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

A high-performance liquid chromatography method was developed to obtain fingerprints of secondary metabolites of 12 lentil cultivars grown under the same environmental condition. Extracts (100% methanol and methanol-water (1:1)) were analyzed by RP-HPLC. Full photodiode array (191-360 nm) data were collected and used for cluster analysis. Methanol and methanol-water extracts showed slightly different clustering patterns. In the dendogram of methanol extracts, CDC Richlea appeared as an isolated group, whereas Indianhead was the isolated group in methanol-water extracts. The cultivar CDC Milestone was selected for further evaluation because of the presence of three peaks (8.9, 16.7, and 32.7 min) that were absent in other cultivars or present in very small amounts. Chromatographic separations of the methanol extract afforded several compounds including the novel 4-chloro-1H-indole-3-N-methylacetamide (13) as well as itaconic acid (3), arbutin (5), gentisic acid 5-O-[beta-d-apiofuranosyl-(1-->2)-beta-d-xylopyranoside] (9), and (6S,7Z,9R)-9-hydroxymegastigma-4,7-dien-3-one-9-O-beta-d-apiofuranosyl-(1-->2)-beta-d-glucopyranoside (14), which are described for the first time from lentils. Structures were determined by high-resolution NMR experiments.

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 score0.317
Threshold uncertainty score0.132

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 head0.010
GPT teacher head0.182
Teacher spread0.172 · 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

Citations42
Published2010
Admission routes1
Has abstractyes

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