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Record W4402541451 · doi:10.1093/jas/skae234.771

PSVII-20 Effect of starch content in the concentrate of finishing bison on meat nutritional composition, quality, and palatability

2024· article· en· W4402541451 on OpenAlexaffabout
N. Prieto, Ó. López-Campos, G.B. Penner, Gabriel O Ribeiro, Maite de Almeida, D. Moya

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of SaskatchewanAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPalatabilityFood scienceComposition (language)StarchBiologyChemistry

Abstract

fetched live from OpenAlex

Abstract According to the Saskatchewan Bison Association, in the last few years producers have not been able to fill the increasing demand for bison meat. Indeed, one of the main challenges faced by the bison industry is their ability to produce a consistent product in a relatively short period of time. Hence, it is necessary to optimize the productivity and profitability of feeding bison calves while ensuring the quality of the end product. This study aimed to evaluate the effects of different starch contents in the concentrate of finishing bison on meat nutritional composition, quality, and palatability. Yearling bison bulls [n = 48; commercial Wood × Plains, 435 ± 13.4 kg body weight (BW)] were homogenously distributed into 12 pens (4 bulls/pen) based on BW, and each pen randomly assigned (n = 6) to receive either a high- [51.4% dry matter basis (DM); n = 24 bison bulls) or moderate-starch (25.8% DM; n = 24 bison bulls) concentrate, alongside free access to water and grass hay bales. After 156 d of feeding, bison bulls were slaughtered in a commercial abattoir in AB, Canada. At 3 d postmortem, color values were measured at the ribeye between the 11 and 12th ribs. Subsequently, striploins from the left carcass sides were collected, weighed, vacuum packaged, and transported under refrigeration conditions to the AAFC-Lacombe Research and Development Centre, AB, Canada. On d 6 of ageing, striploins were unpacked and weighed to measure purge losses, and pH was collected. Subsequently, six 2.5-cm thick steaks were obtained for further nutritional analyses (minerals, cholesterol, vitamin B3, protein, fat, moisture, and fatty acids), shear force, color in retail display for 4 d, and descriptive sensory and flavor profile analyses performed by trained panelists. The dietary starch content did not affect the nutritional composition as well as the pH, 3-d color values, moisture losses, and shear force value of the bison meat (P > 0.1). However, the high-starch concentrate increased the meat luminosity (L*) after 4 d in retail display (P < 0.05) and initial and overall tenderness (P < 0.001), and decreased the amount of perceived connective tissue (P < 0.001). Additionally, spongy and rubbery textures were less frequently found by trained panelists in meat from bison fed a high-starch than a moderate-starch concentrate (P < 0.01 and 0.05, respectively). Regarding meat flavor, the high-starch concentrate decreased salty taste (P < 0.05) and burnt and livery aromas (P = 0.071 and 0.069, respectively) but increased metallic flavor (P < 0.01) and bitter taste (P = 0.076). In conclusion, the starch content in the concentrate of finishing bison did not affect the meat nutritional value. However, some positive effects on meat color and palatability were found when feeding bison a high-starch concentrate.

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 score0.005
Threshold uncertainty score0.010

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.121
GPT teacher head0.348
Teacher spread0.227 · 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
Published2024
Admission routes2
Has abstractyes

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