Processing Characteristics and Sensory Attributes of Bacon Manufactured From Seven Value-Added Cuts of Beef
Bibliographic record
Abstract
ObjectivesThere is great opportunity for the beef industry to add value to cuts that are currently marketed as low value cuts (i.e., cuts from the chuck, round, and flank/plate). The objective was to evaluate the processing characteristics and sensory attributes of bacon manufactured from seven different cuts of beef.Materials and MethodsThe seven cuts evaluated included the brisket (IMPS#120), the clod heart (IMPS#114E; divided horizontally into two halves; referenced as the wide half or silverskin side and the narrow half or non-silverskin side), the flank (IMPS#193), the outside flat (IMPS#171B), and the short plate (IMPS#121A; broken down into the deboned short rib half and the navel half). The cuts were injected using a standard commercial bacon cure (water, salt, corn syrup solids, sodium phosphate, sodium erythorbate, sodium nitrate, sodium bicarbonate, and glycerin; Herman Laue Spice Company Inc.; Uxbridge, Ontario, Canada) to a targeted rested pump uptake of approximately 20% (± 3%). The injected cuts were cooked to an internal temperature of 62°C in a smokehouse (ScottPec, Guelph, Ontario). Following cooking, cuts were cooled to 4°C and then sliced into 4.0 mm slices using a deli slicer. Slices were vacuum packaged, boxed, and stored at 4°C for zero, thirty, sixty, or ninety days. Following the allotted storage period, slices were stored at –20°C until evaluation of sensory attributes and cooking loss. Slices were cooked at 204°C for 15 min in a convection oven. Processing characteristics were conducted in six or seven replications for each cut. Sensory evaluation was conducted on three randomly selected samples for each cut at each of the four storage times (the same samples within each cut was used at each storage time). Processing data were analyzed using PROC GLIMMIX of SAS (v9.4) with fixed effect of cut and random effect of replication. A trained descriptive sensory panel of 6–8 panelists evaluated the differences in oxidative flavor and aroma (using a 4-pt nominal scale), and differences in beef flavor intensity, muscle fiber toughness, and connective tissue amount (using magnitude estimation). Sensory data were analyzed as repeated measures using PROC GLIMMIX of SAS (v9.4) with fixed effect of cut, storage day, and their interaction, and random effects of session, panelist, and replication.ResultsAs expected, dimensions and processing weights differed (P < 0.01) among cuts. Rested pump uptake was not different (P = 0.29) among cuts. Smokehouse yield was greater (P < 0.05) for the brisket, outside flat, and short plate (both halves) compared with the clod heart (both halves) and flank. Bacon slice cooking loss and sensory characteristics are presented in Table 4.ConclusionOverall, this research indicated that a variety of beef cuts can be used to manufacture beef bacon. The differences in sensory properties that were quantified in this study, allow manufacturers to tailor their cut selection to the sensory properties most valued by their consumers. All cuts exhibited oxidative stability when stored up to 90 d.Table 4Bacon slice cooking loss and sensory analysis of bacon manufactured with different beef cuts. Main effects of cut after 0, 30, 60, and 90 d of storage
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".