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Record W2082878455 · doi:10.2527/jas.2013-7210

A noncalibration spectroscopic method to estimate ether extract and fatty acid digestibility of feed and its validation with flaxseed and field pea in pigs1

2014· article· en· W2082878455 on OpenAlexaff
L. F. Wang, M. L. Swift, R. T. Zijlstra

Bibliographic record

VenueJournal of Animal Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsAgriculture Food and Rural DevelopmentUniversity of Alberta
Fundersnot available
KeywordsChemistryFecesFood scienceField peaFatty acidChromatographyAnimal scienceBiochemistryBiology

Abstract

fetched live from OpenAlex

Digestibility of ether extract (EE) or fatty acids (FA) is traditionally measured by chemical analyses for EE or GLC methods for FA combined with marker concentration in diet and digesta or feces. Digestibility of EE or FA may be predicted by marker concentrations and spectral analyses of diet and digesta or feces. On the basis of Beer's law, a noncalibration spectroscopic method, which used functional group digestibility (FGD) determined with marker concentration and peak intensity of spectra of diets and undigested residues (digesta or feces), was developed to predict the apparent ileal digestibility (AID) of total FA and apparent total tract digestibility (ATTD) of EE. To validate, 4 diets containing 30% flaxseed and field pea coextruded with 4 extruder treatments and a wheat and soybean basal diet with predetermined AID of total FA and ATTD of EE were used. Samples of ingredients, diets, and freeze-dried digesta and feces were scanned on a Fourier transform infrared (FT-IR) instrument with a single-reflection attenuated total reflection (ATR) accessory. The intensity of either the methylene (CH2) antisymmetric stretching peak at 2,923 cm(-1) (R(2) = 0.90, P < 0.01) or the symmetric stretching peak at 2,852 cm(-1) (R(2) = 0.86, P < 0.01) of ingredients, diet, and digesta spectra was related strongly to the concentration of total FA. The AID of total FA of diets measured using GLC was predicted by the spectroscopic method using FGD at 2,923 and 2,852 cm(-1) (R(2) = 0.75, P < 0.01) with a bias of 0.54 (SD = 3.78%) and -1.35 (SD = 3.74%), respectively. The accumulated peak intensity in the region between 1,766 and 1,695 cm(-1) of spectra was related to EE concentration in ingredients and diets (R(2) = 0.61, P = 0.01) and feces (R(2) = 0.88, P < 0.01). The relation was improved by using second-derivative spectra of the sum of peak intensities at 1,743 and 1,710 cm(-1) for ingredients and diets (R(2) = 0.90, P = 0.01) and at 1,735 and 1,710 cm(-1) for feces (R(2) = 0.92, P < 0.01). The ATTD of EE of test diets determined with proximate analysis was estimated by the FGD of nonderivative spectra with or without baseline (R(2) = 0.90, P < 0.01) with a bias of 3.15 (SD = 3.14%) and 3.50 (SD = 3.24%), respectively. In conclusion, instead of using GLC methods or predictions based on calibrations, the AID of total FA and ATTD of EE can also be estimated directly from ATR FT-IR spectra, provided the ratio of marker in the diet and undigested residue is known.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.310
Teacher spread0.287 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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