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Record W1857337246

Vibrational Spectroscopic Investigation of Biomolecular Responses of Carbohydrate Structure to Moisture and Dry Heating in Soybean Seed (Glycine max)

2012· article· en· W1857337246 on OpenAlexafffund
Samadi Samadi, Peiqiang Yu

Bibliographic record

VenueAnimal Production (Faculty of Animal Science, Jenderal Soedirman University) · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlycineMoistureCarbohydrateChemistryAgronomyBiologyBiochemistryOrganic chemistryAmino acid
DOInot available

Abstract

fetched live from OpenAlex

Abstract. The objective of this experiment was to investigate carbohydrate structures of seed tissue affected by different heat processing methods using infrared vibrational molecular spectroscopy. In this study, soybean seeds (two different harvested years; 2008 and 2010) were used as a model to investigate the alteration of inherent structure carbohydrate due to heat treatments. Structural characteristics of the bands in typical infrared molecular spectrum were studied in the region at ca. 1452-1188 cm-1 related to cellulosic and hemicellulosic compounds and the region at ca. 1193-881 cm-1, related to total CHO. Multivariate molecular spectral analyses: Hierarchical cluster analysis (CLA) and principal components analysis (PCA) were applied to identify heat-induced changes of molecular spectral profiles. Treatments used in this study were raw soybean seeds as control, autoclaved soybean seeds at 120°C for 1 h (HT-1: wet heating) and dry roasted soybean seeds at 120°C for 1 h (HT-2: dry heating). The results showed that the heat treatments did not change spectral profiles of cellulosic, hemicellulosic and total CHO. Based on spectral analysis, CLA and PCA also did not produce any alterations among different treatments in original spectra at cellulosic, hemicellulosic and total CHO regions. In conclusion, the molecular spectral technique with multivariate spectral technique can be considered as a research tool to investigate the magnitude of heat-induced change in carbohydrate molecular structure and other biopolymers in feeds, seed and plant tissues. These techniques could be used in the food and feed industry in which, losing or changing carbohydrate molecular chemistry was able to be detected in rapidly without any destruction and chemical hazardous. Further studies are needed to understand the trend in structural changes by heating with increasing temperature and time of exposure. Keywords: carbohydrate molecular, heat processing, molecular spectroscopy, soybean seed, feeds Animal Production 14(1):23-31, January 2012

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 score0.417
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.230
Teacher spread0.208 · 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

Citations2
Published2012
Admission routes2
Has abstractyes

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