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Record W2321179605 · doi:10.1021/jf4012517

Synchrotron-Based Microspectroscopic Study on the Effects of Heat Treatments on Cotyledon Tissues in Yellow-Type Canola (Brassica) Seeds

2013· article· en· W2321179605 on OpenAlexafffund
Peiqiang Yu, Katerina Theodoridou, Hangshu Xin, Pei‐Yu Huang, Yao-Chang Lee, Bayden R. Wood

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsUniversity of Saskatchewan
FundersBrookhaven National LaboratoryUniversity of Saskatchewan
KeywordsCanolaBrassicaCotyledonSynchrotronBiologyChemistryBotanyAgronomyHorticulturePhysics

Abstract

fetched live from OpenAlex

Synchrotron-based infrared (IR) microspectroscopy is able to reveal structural features of biomaterials within intact tissue at both cellular and molecular levels. Heat-related treatments have been used to improve nutrient availability of canola seeds and meal. However, hitherto, there has been no study on the sensitivity and response of each layer in canola seeds to heat-related treatments. It is not known which layer (epiderm/mucllage, spermoderm, endosperm, or cotyledon) is the most sensitive to heat when heat treatment is applied to the seeds. Traditional wet chemical analysis is unable to answer such questions. The objective of this study is to use synchrotron IR microspectroscopy with multivariate molecular spectral analyses as a research tool to study heat treatment effects in a fast way on the structural changes in cotyledon tissues of yellow-type canola (Brassica) seeds among raw (treatment code "A"), wet heating (autoclaving at 121 °C for 60 min, treatment code "B"), and dry heating (dry roasting at 120 °C for 60 min, treatment code "C"). The hypothesis of this study was that different heat treatments have different heat penetration abilities on cotyledon tissues in yellow-type canola seeds. The multivariate analytical tools principal component analysis (PCA) and agglomerative hierarchal cluster analysis (AHCA) were applied to investigate variance and groupings within the spectral data set [whole spectral range of ca. 4000-650 cm(-1), spectral range of ca. 1300-900 cm(-1) (cellulose or saccarides), spectral range of ca. 1800-1500 cm(-1) (secondary structures of protein) and spectral range of ca. 1500-1300 cm(-1) (bending motion of methylene and methyl group; this change is consistent with the change in the range of ca. 3000-2800 cm(-1))]. The results showed that there were no clear cluster and groups formed in the cotyledon tissues among the three treatments (A, B, and C). There were no clear distinguished responses of the cotyledon tissues to different types of heat treatments using multivariate molecular spectral analyses. The results indicate that the cotyledon tissues might not be sufficiently penetrated by both heat treatments (autoclaving and dry roasting) under the specified conditions. A future study is needed to analyze individual functional group band intensity among the treatments using univariate molecular spectral analysis to confirm multivariate PCA and cluster analyses.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 head0.004
GPT teacher head0.209
Teacher spread0.205 · 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

Citations8
Published2013
Admission routes2
Has abstractyes

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