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Record W3158668449 · doi:10.1111/jpn.13551

Carbohydrates molecular structure profiles in relation to nutritional characteristics of newly developed low and normal tannin faba bean varieties in dairy cows analysed by using standard methods and the vibrational molecular spectroscopy (Ft/IR‐ATR)

2021· article· en· W3158668449 on OpenAlexafffundabout
María E. Rodríguez‐Espinosa, Víctor H. Guevara‐Oquendo, Peiqiang Yu

Bibliographic record

VenueJournal of Animal Physiology and Animal Nutrition · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
FundersGovernment of SaskatchewanNatural Sciences and Engineering Research Council of CanadaSaskatchewan Pulse Growers
KeywordsRumenTanninChemistryStarchFood scienceCondensed tanninDigestion (alchemy)Animal scienceAgronomyBiologyProanthocyanidinBiochemistryChromatographyAntioxidantFermentation

Abstract

fetched live from OpenAlex

Abstract To our knowledge, there was no study on interactive relationship between CHO molecular structure spectral profiles of newly developed cool‐season adapted faba bean and nutritional characteristics in ruminants. The aim of this study was to evaluate the impact of genotypes and tannin levels on the physicochemical and nutritional characteristics of faba bean as an alternative protein and energy source for ruminants and its relation to CHO molecular structure spectral profiles using vibrational molecular spectroscopy (Ft/IR‐ATR). Eight genotypes with two tannin levels (low and normal) grown at three different locations in Saskatchewan (CDC crop research fields) were analysed. Chemical analyses were performed using AOAC standards and energy was evaluated using NRC standards. Rumen degradation kinetics were determined using in situ dairy trial. Intestinal digestion was analysed by a modified three‐step in vitro technique with 12 h pre‐rumen incubation in dairy cows. Molecular spectral study was performed using Ft/IR–ATR, and the molecular structural features were analysed at ca. 4000–800 cm−1 using the Spectra ManagerII. CHO‐related functional groups were analysed with OMNIC 7.3. The results showed low‐tannin faba bean (LT) presented a highly significant difference (p < 0.05) on rumen bypass starch (BSt) compared to normal tannin faba bean (NT). On the other hand, NT had more total tract digested starch (TDST) compared to LT. No significant differences (p > 0.10) were observed for total digestible nutrients (TDN1x), metabolizable protein (MP), feed milk value (FMV) or rumen undegraded crude protein (RUP). Results showed differences in physicochemical characteristics among faba bean varieties; however, the predicted production performance was not different within faba bean genotypes. These outcomes suggest that faba bean can be used as nutritive ingredient for dairy cattle without a significant genotype or tannin level effect on metabolic characteristics. Results from vibrational spectroscopic study showed a higher ATR‐Ft/IR absorbance (p < 0.05) in NT on inherent structural CHO (STCHO), total CHO (TCHO) area and peaks (H_1015, H_1076, H_1145), and cellulosic compounds (CEC) to total CHO (TCHO) ratio. Significant correlations could be found between CHO spectral profiles and metabolic characteristics of faba bean, which indicates that structural spectral features of faba bean could be used to predict metabolic characteristics in ruminants.

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 score0.005
Threshold uncertainty score0.009

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 head0.271
Teacher spread0.260 · 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".

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Citations1
Published2021
Admission routes3
Has abstractyes

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