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Record W3047438227 · doi:10.1111/ppl.13181

Root membrane lipids as potential biomarkers to discriminate silage‐corn genotypes cultivated on podzolic soils in boreal climate

2020· article· en· W3047438227 on OpenAlexaff
Muhammad Nadeem, Raymond Thomas, Oludoyin Adeseun Adigun, Charles F. Manful, Jiaxu Wu, Thu Huong Pham, Xinbiao Zhu, Lakshman Galagedara, Mumtaz Cheema

Bibliographic record

VenuePhysiologia Plantarum · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceMemorial University of Newfoundland
Fundersnot available
KeywordsSilageBiologyLipidomicsAgronomyFood scienceBotanyBiochemistry

Abstract

fetched live from OpenAlex

Root membrane lipids are important biomolecules determining plant's ability to adapt to different growing environmental or climatic conditions. Herein, we demonstrate the potential use of root membrane lipids as biomarkers to discriminate silage-corn genotypes based on herbicide and insect/pest resistance genetic traits when cultivated on podzolic soils under short growing and moderately warm summer season in boreal climate. Lipids in root membranes of field grown silage-corn genotypes were previously quantified at crop maturity by ultra-high-performance liquid chromatography-hydrophilic interaction chromatography-heated electrospray ionization mass spectrometry. The lipid identified and quantified in silage-corn roots were phospholipids, glycolipids and sphingolipids. Following hierarchical cluster analysis, three groups of membrane lipids were observed to be very effective in segregating the five silage-corn genotypes. The first group consisted of hexosylceramide (HexCer), phosphatidylcholine (PC) and phosphatidylinositol (PI). The second group consisted of lysophosphatidic acid (LPA16:0) and lysophosphatidylcholine (LPC16:0), while the third group consisted of 37 molecular species from observed lipids (phospholipids, glycolipids, sphingolipids). Partial least squares-discriminant analysis (PLS-DA) based on 37 membrane lipid species, as well as principal component analysis using the variables important in projection derived from the PLS-DA segregated the five silage-corn genotypes into three groups according to their pesticide/herbicide resistant traits. This study is second to none using root lipidomics in discriminating different silage-corn genotypes based on their herbicide and insect/pest resistance genetic traits for cultivation in boreal climates. The segregated genotypes possess three different genetic traits for herbicide and insect/pest resistance including VT Double Pro (VT2P), VT Triple Pro Roundup Ready (VT3P/RR) and Roundup Ready-2 corn (RR2). These findings demonstrate that root membrane lipids could serve as appropriate chemical biosignatures to identify silage-corn genotypes based on herbicide and insect/pest resistance genetic traits suitable for cultivation in boreal climates.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.234
Teacher spread0.223 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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