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Record W4283722390 · doi:10.5713/ab.22.0076

Quantitation of relationship and development of nutrient prediction with vibrational molecular structure spectral profiles of feedstocks and co-products from canola bio-oil processing

2022· article· en· W4283722390 on OpenAlexafffundabout
Alessandra M. R. C. B. de Oliveira, Peiqiang Yu

Bibliographic record

VenueAnimal Bioscience · 2022
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsUniversity of Saskatchewan
FundersTianjin Agricultural UniversityCanola Council of CanadaWestern Grains Research FoundationUniversity of SaskatchewanSaskatchewan Forage NetworkNatural Sciences and Engineering Research Council of CanadaSaskatchewan Canola Development Commission
KeywordsCanolaCarbohydrateChemistryNutrientFood scienceBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: This program aimed to reveal the association of feed intrinsic molecular structure with nutrient supply to animals from canola feedstocks and co-products from bio-oil processing. The special objective of this study was to quantify the relationship between molecular spectral feature and nutrient availability and develop nutrient prediction equation with vibrational molecular structure spectral profiles. METHODS: The samples of feedstock (canola oil seeds) and co-products (meals and pellets) from different bio-oil processing plants in Canada (CA) and China (CH) were submitted to this molecular spectroscopic technique and their protein and carbohydrate related molecular spectral features were associated with the nutritional results obtained through the conventional methods of analyses for chemical and nutrient profiles, rumen degradable and intestinal digestible parameters. RESULTS: The results showed that the spectral structural carbohydrates spectral peak area (ca. 1,487.8 to 1,190.8 cm-1) was the carbohydrate structure that was most significant when related to various carbohydrate parameters of canola meals (p<0.05, r>0.50). And spectral total carbohydrate area (ca. 1,198.5 to 934.3 cm-1) was most significant when studying the various carbohydrate parameters of canola seeds (p<0.05, r>0.50). The spectral amide structures (ca. 1,721.2 to 1,480.1 cm-1) were related to a few chemical and nutrient profiles, Cornell Net Carbohydrate and Protein System (CNCPS) fractions, truly absorbable nutrient supply based on the Dutch protein system (DVE/OEB), and NRC systems, and intestinal in vitro protein-related parameters in co-products (canola meals). Besides the spectral amide structures, α-helix height (ca. 1,650.8 to 1,643.1 cm-1) and β-sheet height (ca. 1,633.4 to 1,625.7 cm-1), and the ratio between them have shown to be related to many protein-related parameters in feedstock (canola oil seeds). Multiregression analysis resulted in moderate to high R2 values for some protein related equations for feedstock (canola seeds). Protein related equations for canola meals and carbohydrate related equations for canola meals and seeds resulted in weak R2 and low p values (p<0.05). CONCLUSION: In conclusion, the attenuated total reflectance Fourier transform infrared spectroscopy vibrational molecular spectroscopy can be a useful resource to predict carbohydrate and protein-relates nutritional aspects of canola seeds and meals.

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 score0.014
Threshold uncertainty score0.264

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 head0.018
GPT teacher head0.253
Teacher spread0.235 · 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

Citations1
Published2022
Admission routes3
Has abstractyes

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