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Record W6886917692 · doi:10.15454/xyndvb

Primary metabolite analyses on seeds of two Camelina sativa genotypes cultivated for five consecutive years

2021· dataset· en· W6886917692 on OpenAlexaboutno aff

Bibliographic record

VenueRecherche Data Gouv France · 2021
Typedataset
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsnot available
Fundersnot available
KeywordsCamelinaCamelina sativaCultivarRandomized block designGerminationHybridPrimary metaboliteMetaboliteBolting

Abstract

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Samples collection: six genotype of camelina were grown at the experimental farm of Bologna University (Italy) located in Cadriano (Bologna, Italy, 44°30′N, 11°23′E, 32 m a.s.l.) during five consecutive years (2015 - 2019). The six tested genotypes were: OMEGA (University of Poznan, Poland), WUR (Wageningen University and Research, The Netherlands), and 787-08, 789-02 and 887 cultivars (Smart Earth Camelina, Saskatoon, Canada). Camelina was sown each year in late winter/early spring accordingly to the specific meteorological conditions. The same agronomic management for all the trials was adopted consisting in typical tillage system (ploughing + harrowing), a seeding rate of 500 seeds m-2, no irrigation, a top-dressing fertilization with N (50 kg N ha-1, as urea at bolting stage), with no pest, disease nor weed chemical control. The experimental design was a randomized complete block with 3 or 4 replicates depending on the year. Representative seed samples from individual plots were cleaned and used for omic analyses. Only OMEGA and 789-02 seeds were used for GC-MS primary metabolite analyses. Extraction: Metabolites were extracted from 60 mg of camelina dry mature seeds. Briefly, 1 mL of MeOH: Methyl-tert-butyl: H2O (1:3:1), conserved at 4°C, and 200 ng of Apigenin (used as internal standard) were added to each sample, which were then homogenized in 2ml tubes using a FastPrep instrument (1 min, 14,000 rpm). The mixtures were then shaken for 30 min at 4ºC using a ThermoMixer™ C (Eppendorf), placed in an ice cooled ultrasonication bath for 15 min and centrifuged for 1 min at the maximum speed to remove debris. The extracted samples were then transferred in new tubes containing 650 mL of MeOH: water (1:3), previously placed at -20ºC. The mixtures were centrifuged for 1 min at 14,000 rpm. The addition of MeOH: water (1:3) and the centrifugation led to a led to a phase separation, providing the upper organic phase, containing the lipids, a lower aqueous phase, containing the polar and semi- polar metabolites, and a pellet of starch and proteins. The phase containing the polar and semi-polar metabolites was dried down in a SpeedVac vacuum concentrator (o/n) and resuspended in 200 μL of ULC/MS grade water (Biosolve). Primary Metabolites: GC-MS data analysis and processing: For GC-MS analyses and data processing, 150µl of the extraction solution were taken and dry in a Speed-Vac evaporator for 2 h at 30°C before adding 10 µL of 20 mg.mL-1 methoxyamine in pyridine to the samples. The reaction was performed for 90 min at 30°C under continuous shaking in an Eppendorf thermomixer. 90 µL N-methyl-N-trimethylsilyl- trifluoroacetamide (MSTFA) (Regis Technologies, Morton Grove, IL, USA) were then added and the reaction continued for 30 min at 37°C. After cooling, all the samples were transferred to an Agilent vial for injection. At 4 h after derivatization, 1 µL of sample was injected in splitless mode on an Agilent 7890B gas chromatograph coupled to an Agilent 5977A mass spectrometer. The column was an Rxi-5SilMS from Restek (30 m with 10 m Integra-Guard column). An injection in split mode with a ratio of 1:30 was systematically performed for saturated compounds quantification. Oven temperature ramp was 60°C for 1 min then 10°C min-1 to 325°C for 10 min. Helium constant flow was 1.1 mL.min-1. Temperatures were the following: injector: 250°C, transfer line: 290°C, source: 230°C and quadrupole 150°C. The quadrupole mass spectrometer was switched on after a 5.90 min solvent delay time, scanning from 50 to 600 m/z. Absolute retention times were locked to the internal standard d27-myristic acid using the RTL system provided in Agilent’s Masshunter software. Retention time locking reduces run-to-run retention time variation. Samples were randomized. A fatty acid methyl esters mix (C8, C9, C10, C12, C14, C16, C18, C20, C22, C24, C26, C28, C30) was injected at the beginning of analysis for external RI calibration. The Agilent Fiehn GC/MS Metabolomics RTL Library (version June 2008) was employed for metabolite identifications. Peak areas determined with the Masshunter Quantitative Analysis (Agilent Technologies, Santa Clara, CA, USA) in splitless and split 30 modes. Resulting areas were compiled into one single MS Excel file for comparison. Peak areas were normalized to Ribitol and Dry Weight. A total of 92 unique metabolites were identified are expressed in arbitrary units (semi-quantitative determination).

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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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.492
GPT teacher head0.541
Teacher spread0.049 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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