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Record W2076078714 · doi:10.1080/17450390600679017

An emerging method for rapid characterization of feed structures and feed component matrix at a cellular leveland relation to feed quality and nutritive value

2006· review· en· W2076078714 on OpenAlex
Peiqiang Yu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArchives of Animal Nutrition · 2006
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsChemical compositionMatrix (chemical analysis)Fourier transform infrared spectroscopyCharacterization (materials science)Biological systemChemistrySynchrotronComponent (thermodynamics)Chemical imagingAnimal feedFood scienceBiochemical engineeringBiotechnologyChemical engineeringMaterials scienceComputer scienceNanotechnologyBiologyChromatographyArtificial intelligenceOrganic chemistry

Abstract

fetched live from OpenAlex

Feed quality, feed characteristics, nutrient utilization and digestive behaviour are closely related to: (i) total feed composition, (ii) feed intrinsic structures, and (iii) biological component matrix (such as protein to starch matrix, protein to carbohydrate matrix). Conventional "wet" chemical analysis can determine total chemical composition, but fails to detect the feed intrinsic structures and biological component matrix due to destruction of feed samples during the processing for chemical analysis and the "wet" chemical analysis cannot link structural information to chemical information within intact feed tissue. Recently, advanced synchrotron-based Fourier transform infrared (FTIR) microspectroscopy has been developed as a non-destructive and non-invasive structural-chemical analytical technique. This technique can link chemical information to structural information of biological samples within intact tissue within cellular dimensions. It can provide four kinds of information simultaneously: tissue composition, tissue structure, tissue chemistry and tissue environment. However, this novel technique has been found mainly for medical science research, extremely rare for feed science and nutrition research. The objective of this review article was to illustrate synchrotron-based FTIR microspectroscopy as a novel research tool for rapid characterization of feed structures at a cellular level and for detection of chemical features and molecular chemical make-up of feed biological component matrix and nutrient interaction. The emphasis of this article was to show that feed structural-chemical features at a cellular level are closely related to feed characteristics, feed quality and nutritive value in animals. The synchrotron-based technology will provide us with a greater understanding of the plant-animal interface.

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.

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: Review · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.060
GPT teacher head0.347
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