MétaCan
Menu
Back to cohort
Record W4388529155 · doi:10.1093/jas/skad281.657

PSVII-22 Effect of Trimming External Fat Before Cooking on Palatability and Calorie Content of Beef Ribeye Steaks

2023· article· en· W4388529155 on OpenAlexaffabout
Ó. López-Campos, Patricia L.A. Leighton, Sophie Zawadski, Rhona Thacker, Bryden Schmidt, Haley Scott, lacey Hudson, N. Prieto

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPalatabilityFood scienceLow calorieLongissimus dorsiLongissimusLongissimus ThoracisMathematicsAnimal scienceChemistryBiologyTenderness

Abstract

fetched live from OpenAlex

Abstract Consumer concerns about excess dietary fat have increased the practice of removing external fat from beef steaks prior to cooking. This practice, however, may be detrimental to meat eating quality. The objective of this study was to determine the effects of removing the external fat before cooking on the eating quality and calorie content of ribeye steaks. Twenty longissimus thoracis muscles with Canada AAA (n = 10) and AA (n = 10) quality grades (equivalent to USDA Choice and Select, respectively) were obtained from a federally inspected commercial slaughter plant, vacuum packaged and transported under refrigerated conditions to the Lacombe Research and Development Centre (Agriculture and Agri-Food Canada). After an average of 28 d of ageing, the muscles were removed from the vacuum packaging and fabricated into four 2.54-cm steaks. One-half of the steaks were trimmed to 0.635 cm of external fat (cap on). The remaining steaks were completely trimmed of external and seam (kernel) fats (cap off), and the longissimus and spinalis dorsi muscles were combined with butcher’s twine. Steaks were cooked on an electric grill to an endpoint temperature of 74 °C. Subsequently, descriptive sensory analyses were performed by a 10-member trained meat evaluation panel and calorie analyses were conducted. Results: Compared with muscles of AA steaks cooked with cap off, the AA steaks cooked with cap on had longissimus with greater initial and sustained juiciness (P < 0.01) and a tendency towards a smaller proportion of panelists detecting livery off-flavor (P = 0.058) and mealy texture (P = 0.071), and spinalis with a tendency towards fewer panelists detecting unidentified off-flavors (P = 0.096) and spongy texture (P = 0.096). When cooking the AAA steaks with cap on, the longissimus had a decreased frequency of panelists detecting ‘other’ off-flavors (i.e., burnt, rancid, barnyard, stale; P < 0.05) and mushy texture (P < 0.05) and tended to have less off-flavor intensities (P = 0.083), whereas the spinalis had greater beef flavor intensity and desirability (P < 0.05) and fewer panelists tending to detect ‘other’ off-flavors (i.e., burnt, fatty, oily, rancid; P = 0.052), compared with steaks cooked with cap off. The more pronounced flavor effects in the spinalis compared with the longissimus of AAA steaks cooked with cap on could be due to the spinalis having greater endpoint temperatures than the longissimus muscles, which probably caused more Maillard reactions and more efficient fat melting. Regardless of the quality grade and muscle type, cooking steaks with cap on did not increase the calorie content (P > 0.10). Overall, cooking ribeye steaks with external fat had positive effects on juiciness, flavor and texture without increasing the calorie content compared with steaks cooked without external fat. Educating consumers on the benefits of maintaining the external fat while cooking will improve the eating experience of Canadian beef.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.000

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 head0.057
GPT teacher head0.292
Teacher spread0.236 · 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 designObservational
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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Animal ScienceSame topicMeat and Animal Product QualityFrench-language works237,207