Received: 17 November 2019 Revised: 11 March 2020 Accepted: 20 March 2020

DOI: 10.1111/jtxs.12523

RESEARCH ARTICLE

Using shear force, sarcomere length, particle size, collagen

content, and protein solubility metrics to predict consumer
acceptance of aged beef tenderness

Benjamin W. B. Holman1,2 | Damian Collins3 | Ashleigh K. Kilgannon1,2 |

David L. Hopkins1,2

1
Centre for Red Meat and Sheep
Development, NSW Department of Primary Abstract
Industries, Cowra, New South Wales, Australia In this study, the relationship between sensory evaluation and several objective met-
2
Graham Centre for Agricultural Innovation,
rics of beef tenderness was tested. Objective metrics included shear force, sarcomere
NSW Department of Primary Industries,
Charles Sturt University, Wagga Wagga, New length, collagen content, myofibrillar, and sarcoplasmic protein solubility and particle
South Wales, Australia
size analysis. These results were compared to consumer panel scores of tenderness
3
Elizabeth Macarthur Agricultural Institute,
NSW Department of Primary Industries, for the same aged beef striploin (longissimus lumborum muscle) samples. There was
Menangle, New South Wales, Australia found to be a significant relationship between sarcomere length, shear force, and par-

Correspondence ticle size with tenderness scores. Collagen content and protein solubilities were not
Benjamin W. B. Holman, Centre for Red Meat associated to tenderness scores (p > 0.05). Sarcomere length contributions for
and Sheep Development, NSW Department of
Primary Industries, Cowra, NSW 2794, explaining tenderness variation were overlapped by the contributions of shear force
Australia. (collinearity). Independent models demonstrated that the lower 95% confidence
Email: benjamin.holman@dpi.nsw.gov.au
interval of the fitted regression line exceeded 50% acceptance of tenderness when
Funding information shear force values <42.6 N and when particle size values <198 μm. We can recom-
Charles Sturt University; NSW Department of
Primary Industries; Australian Meat Processor mend these as thresholds for consumer acceptance of beef tenderness, although
Corporation (AMPC) considerations of sample type, analytical methodology, and consumer demographics
should be made prior to their adoption. This provision was based on the variation in
tenderness scores evident between individual panelists and experimental striploins.

KEYWORDS

collagen, consumer threshold, particle size, protein solubility, sarcomere length, shear force,
tenderness

1 | I N T RO DU CT I O N Likewise, when surveyed, consumers will often rank tenderness as a

very important factor that exceeds the contributions of other sensory
Tenderness is the ease by which a consumer can cut, bite and masti- attributes in terms of their influence on overall beef liking and a cus-
cate meat, and it underpins much of a consumer's sensory response tomer's decision to purchase (Holman, van de Ven, Mao, Coombs, &
and satisfaction with a beef product. This relationship has been well Hopkins, 2017; Miller et al., 2001). The tenderness of beef is impacted
established (Platter et al., 2003; Shackelford, Morgan, Savell, & by intrinsic and extrinsic factors. Intrinsic factors include muscle fiber
Cross, 1991), with past research demonstrating that customers will structure, type and dimensions, the distribution of connective tissue
preferentially purchase beef guaranteed as tender over other tender- and fatty deposits, and its susceptibility to post-mortem degradation;
ness categories (Miller, Carr, Ramsey, Crockett, & Hoover, 2001). extrinsic factors include cut or muscle selection, preparation method
(degree of doneness), and a plethora of production, processing and
This article was published on AA publication on: 07 April 2020 preservation effects (Hopkins, 2017). To understand these and

J Texture Stud. 2020;1–8. wileyonlinelibrary.com/journal/jtxs © 2020 Wiley Periodicals, Inc. 1

2 HOLMAN ET AL.

treatment effects of these on beef tenderness, researchers can use we aimed to establish instrumental thresholds to describe the limits of
subjective methods for sensory evaluation. acceptable tenderness.
Sensory evaluation allows meat scientists to quantify the tender-
ness (or toughness) of beef from actual consumer feedback; that is,
people are recruited to sample beef and score their perception of its 2 | M A T E R I A L S A N D M ET H O D S
eating quality traits viz. tenderness. Participants in sensory evaluation
may be trained to provide greater discrimination between trait scores 2.1 | Sample resource
than say, untrained participants who are often used to provide better
insight into the reactions of a broader population of beef consumers. To represent a range of tenderness profiles, data were sourced from
This method of tenderness appraisal is important, but is somewhat an existing database of objective metrics and corresponding sensory
limited by its logistical complexity and associated costs. Consequently, evaluation scores (Table 1). This was captured in an investigation of
proxy objective metrics of tenderness have been developed which different temperature–time combination (TTC) effects on aged beef
often are more simple, inexpensive and rapid—relative to sensory quality traits (Holman et al., 2019; Kilgannon et al., 2019), and conse-
evaluation, albeit dependent on the metric and method employed quently we acknowledge any protocol or statistical similarities to
(Holman, Fowler, & Hopkins, 2016). Although others exist, objective these former studies. It was the intention to provide a brief overview
metrics for tenderness common to meat science include shear force, of tenderness metrics and consumer panel protocols used herein so as
sarcomere length, particle size analysis, collagen content, and protein to provide context to this current study.
solubility (Hopkins, 2017). Alone, these objective metrics do not per- A total of 20 beef striploins (longissimus lumborum muscles) were
mit the researcher or reader to interpret results in terms of a con- selected from the boning room of a commercial Australian abattoir. These
sumer's satisfaction with beef tenderness. As a result, thresholds were divided into eight equal portions (160), weighed and individually vac-
indicative of consumer acceptance of beef tenderness have been uum packaged. As pairs within striploin, portions were assigned to TTCs.
recommended. TTCs were designed so that samples were held at a constant temperature
Several examples of consumer acceptance thresholds available to over each time period and there was at most one variation in temperature
interpret objective metrics include; Destefanis, Brugiapaglia, Barge, within a sample's combined (total) time period. Hence, three temperatures
and Dal Molin (2008) compared the shear force data from 60 beef loin (3, 5, and 7 C) and five time periods (4, 6, 8, 10, and 12 days) resulted in
samples with their untrained panel sensory responses to propose 72 different TTC. TTCs were applied within Temperature Control Units
42.9 N as a limit for tenderness; Huffman et al. (1996) used at home (TCU; CR-80DZ WAECO, Dometic Ltd., AUS), each set to one of the
testing, with participants instructed, but not monitored in beef steak experimental temperatures. Control samples were held for 14 days at
preparation, to find that consumers could discriminate between shear ~1 C across duplicate TCU (n = 8 per TCU). At the completion of each
force differences of 0.5 kg (4.9 N); and Platter et al. (2003) used an TTC, samples were sectioned and stored frozen (−25 C) until analysis.
untrained consumer panel that was selected to represent the demo- This design was repeated so that the study was replicated, chronologically,
graphics of the United States, to find shear force values <4.4 kg so that a total of 40 striploins and 320 sample portions were tested.
(43.2 N) as the limit for acceptable tenderness. Illustrated by these
studies and supported with a review of literature, it was apparent that
the 'shear force' was primarily used to understand consumer scores of 2.2 | Sensory evaluation
tenderness. Furthermore, there is a paucity of thresholds that use
other objective metrics to describe consumer acceptance of beef ten- Microbial testing was undertaken prior to any sensory appraisal and
derness. In response, this study aimed to quantify the relationship all samples considered unsafe (CSIRO, 1995) were replaced with safe,
between sensory evaluation results and objective metrics used as a nonexperimental samples so as to maintain sensory panel design. The
proxy for tenderness—including shear force, sarcomere length, protein sensory panel design was modified from Thompson et al. (2005). This
solubility, particle size, and collagen content. From these relationships, mandated that five sample slices were prepared from each sample,

TABLE 1 Summary statistics for the

Objective metric Mean SD Range (min–max) Median
objective metrics used to represent a
Sarcomere length, μm 1.75 0.17 1.41–2.52 1.72 range of beef striploin (longissimus
Total collagen, mg/g DM 11.4 5.0 4.5–59.9 10.4 lumborum muscle) tenderness profiles
Soluble collagen, mg/g DM 2.6 1.7 0.9–17.0 2.0
Shear force, N 36.8 11.9 13.3–83.5 34.3
Sarcoplasmic protein, mg/g 14.9 3.0 7.6–25.2 14.7
Myofibrillar protein, mg/g 17.8 4.7 1.2–33.1 17.5
Particle size, μm 142.3 55.2 47.5–334.3 127.8

Abbreviations: DM, dry matter; max, maximum; min, minimum.

HOLMAN ET AL. 3

each sample should be tasted by 10 different panelists, and each pan- TABLE 2 The demographic information for the untrained
elist should taste only eight samples to limit their response fatigue. consumer panels (n = 373) recruited for sensory evaluation of aged
beef striploin (longissimus lumborum muscle)
Consequently, a total of 20 sensory panel sessions that consisted of
20 panelists was required to test all experimental samples. However, Panelists
(%)
“no shows” resulted in 373 volunteer panelists attending sensory ses-
Age, years
sions and each sample therefore being tasted by at least six individual
18–25 28
panelists. It should be noted that all panelists were untrained. The
26–30 11
demographic information of these panelists is shown in Table 2.
31–39 11
For each sensory panel session, the assigned frozen sample slices
40–55 23
were thawed (~12 hr at 4–5 C) and then cooked at 220 ± 15 C until
55+ 27
their internal temperature reached 71 C using a clam shell grill (GR-
Sex
4A, Cuisinart Griddler, East Windsor). All temperatures were con-
Male 47
firmed using a HACCP infrared thermometer (model 8,838, AZ Instru-
Female 53
ment Corp., Taichung City, TAI). Samples were cooked in batches of
Smoking status
10 which were immediately cut into halves so that these could be
Yes 7
served at a consistent temperature to the allocated panelist, this ser-
No 90
vice took approximately 2 min from the grill to the panelist. Panelists
Occupation
first received a nonexperiment sample to ensure their comprehension
Tradesperson 5
of documentation requirements and protocol instructions. These were
Professional 33
then followed by experimental samples, which were provided in a
Sales and personal service 5
monadic sequence. Panelists then recorded their scores for sample
Technical 5
tenderness on a 100 mm line scale which was anchored with the
Laborer 2
labels “not tender” and “extremely tender”—this allowed their
Farmer 7
responses to be quantified out of a 100, with higher responses indica-
Homemaker 3
tive of higher tenderness scores. Panelists cleansed their palate
Student 21
between each sample evaluation with dry water crackers and water.
Administration 9

Retired 7
Red meat consumption
2.3 | Objective metrics
Daily 7
4–5 times per week 30
2.3.1 | Shear force
2–3 times per week 41
Weekly 15
Vacuum packaged and frozen shear force sample blocks (mean ± SD:
Fortnightly 3
57.6 ± 5.4 g) were submerged in a 71 C water bath for 35 min before
Monthly 2
being placed into cold water, so as to halt the cooking process
Less often 1
(Hopkins, Toohey, Warner, Kerr, & van de Ven, 2010). These were
Attitude to red meat
then removed from their packaging, patted dry with paper towel, and
I enjoy red meat, it is an important part of my diet 48
held refrigerated for ~12 hr at 4–5 C, prior to analysis. Cuboidal strips
I like red meat, it is a regular part of my diet 37
were removed from each cooked sample block (cross-sectional area:
2 I do eat some red meat although it would not worry me if I did 13
1 cm ) and these tested using a Warner-Bratzler vee-shaped blade
not
attached to a texture analyzer (model LRX, Lloyd Instruments, Hamp-
I rarely/never eat red meat 1
shire, UK) set with a 200 mm/min crosshead speed. The cutting line
Preferred level of doneness
was positioned perpendicular to the muscle fiber orientation, and
Rare 25
avoiding obvious fatty and connective tissue deposits. Peak SF was
Medium 59
then recorded for six technical replicates (Holman, Alvarenga, van de
Well done 12
Ven, & Hopkins, 2015) and the average expressed in Newtons (N).
Annual household income
Less than AUD$45,000 23
Between AUD$45,000 and $80,000 26
2.3.2 | Sarcomere length
More than AUD$80,000 48

Sample sarcomere length was determined using thin slices (thickness: Note: The nonresponses have resulted in percentage summations not
equating to 100%, within categories.
<1 mm) removed parallel to the muscle fiber, placed onto glass slides
4 HOLMAN ET AL.

and analyzed using a laser light diffraction unit in accordance to sarcomere length, collagen content, protein solubility, and particle size)
Bouton, Carrol, Harris, and Shorthose (1973). The average of five and taste order as fixed effects; as well as the random effects of animal
technical replicates was then reported as μm. (striploin/portion/slice + slice), sensory (repeat/sensory evaluation
session/panelist + repeat/sensory evaluation session/panelist × taste
order), and striploin/portion × panelist. To improve the robustness of
2.3.3 | Collagen content the regression models and reduce the undue influence of outlying
observations, a logarithmic transformation was applied to both total
The total collagen content was determined using 1.00 ± 0.03 mg of freeze- and soluble collagen content data, and a square-root transformations
dried and ground beef samples, hydrolysed overnight with sulfuric acid to sarcomere length and shear force values. To determine an optimal
(3.5 M). The hydrolysate was then diluted with water and sodium hydroxide model for tenderness (sensory evaluation scores), a forward stepwise
(2 M). The soluble collagen content was determined using ~1.5 mg freeze- regression approach was used. This tested all predictors (objective
dried and ground beef samples, cooked for 2 hr in 10.0 ml water, cen- metrics) individually, the most significant predictor was then added to
trifuged, and the supernatant then hydrolysed with sulfuric acid (3.5 M). the model, and the subsequent predictors were added in turn until no
The hydroxyproline content of both preparations was quantified as per further predictors were significant. The level of significance was set at
Starkey, Geesink, Oddy, and Hopkins (2015) using an oxidant solution, color the 5% level, where p < .05 is considered to be significant.
reagent and measuring sample absorbance at 558 nm with a benchtop
spectrophotometer. All results were expressed as mg per g of dry matter.
3 | RE SU LT S

2.3.4 | Protein solubility In Table 3, it is shown that shear force (p < .001) had a negative rela-
tionship with tenderness, wherein increased shear force values
Protein solubility was determined using a protocol modified from reflected decreased tenderness scores. Particle size (p < .001) also had
Farouk and Swan (1998). For this method, ~25 mg beef samples were a negative relationship with tenderness, but accounted for less of the
homogenized in 200.0 μl buffer (25 mM KH2PO4), and then held these variation in tenderness than did shear force values. Sarcomere length
refrigerated overnight (4–5 C) before centrifugation and ascertaining (p = .030) instead had a positive relationship with tenderness scores
the protein content of the supernatant with a Bicinchoninic Acid Kit as increased sarcomere length results were indicative of increased
for Protein Determination (BCA1, Sigma-Aldrich Pty. Ltd., Missouri) beef tenderness. No other objective measures were found to have a
and a benchtop spectrophotometer set to measure absorbance at relationship with tenderness (p > .05).
560 nm. The average of technical duplicates was the total protein sol- When the objective metrics for tenderness were modeled to pre-
ubility expressed as mg protein per g. Sarcoplasmic protein solubility dict tenderness scores, shear force was found to be the best predictor
was assessed using this same method and a sarcoplasmic buffer (p < .001; Step 1), followed by particle size (p = .034; Step 2), and then
(1.1 M KI, 0.1 M KH2PO4). Myofibrillar protein solubility was calcu- no further objective metrics were significant after these two metrics
lated as the difference between total and sarcoplasmic protein solubil- were included (Table 3). It should be noted that when shear force and
ity, this was then expressed as mg protein per g of sample. particle size were fitted into the same model, the coefficients were
only slightly lower than if these were fitted independently
(coefficient ± SE: −5.48 ± 0.65 [shear force] and −0.04 ± 0.01 [parti-
2.3.5 | Particle size cle size] versus −5.18 ± 0.67 [shear force] and −0.03 ± 0.01 [particle
size], respectively). When we plotted these independent models, it
The particle size of beef samples was quantified using the protocol of
Karumendu, van de Ven, Kerr, Lanza, and Hopkins (2009). This homoge-
TABLE 3 The level of significance (p value) for objective metrics
nized ~1 g samples at 16,000 rpm (series X10/25, Ystral Homogenizer,
used to predict tenderness scores using a forward stepwise regression
GER), with 20.0 ml of buffer (0.1 M KCl, 1 mM EDTA [di-sodium], 25 mM model
potassium phosphate) balanced to have pH 7 at 4 C. Samples were then
p Values
added drop-wise to a laser diffraction particle size analyzer (model CPR,
Beckman Instruments, California) with a water connection and set per the Objective metric Step one Step two Step three
technical, instrument instructions (Beckman Coulter, 2011). Technical Sarcomere length .030 .663 .640
duplicates were tested, and their mean PS diameter reported as μm. Total collagen .566 .926 .927
Soluble collagen .803 .734 .752
Shear force <.001 – –
2.4 | Statistical analysis
Sarcoplasmic protein .150 .190 .172
Myofibrillar protein .598 .479 .339
Data were analyzed in asreml (Butler, 2009) under R (R Core
Particle size <.001 .034 –
Team, 2018). The model included the objective metrics (shear force,
HOLMAN ET AL. 5

F I G U R E 1 The fitted relationship

of sensory evaluation tenderness
scores with shear force values
(squareroot scale) for aged beef
striploin (longissimus lumborum
muscle) samples. This is shown as a
solid black line (with 95% confidence
intervals included as dotted lines)
overlaid on the raw data (light gray
unfilled dots) and mean tenderness
scores per sample (solid gray dots)

was observed that the lower 95% confidence internal of the fitted tenderness as a result of their quantification of muscle shortening,
regression line exceeds 50% acceptability of tenderness when shear structural protein proteolysis and/or the resistance of muscle fibers
force values <42.6 (Figure 1) and when particle size values <198 and connective tissues to physical disruption—all of which are funda-
(Figure 2). These same figures show the variation evident between mental contributors to tenderness (Starkey et al., 2015). It was inter-
individual panelist tenderness scores when evaluating the same sam- esting to note that shear force contributions to predict tenderness
ple with the same objective metric value. overlapped that of sarcomere length, in the present study. This sug-
gests collinearity between the measures and consequently, as shear
force provided a better predictor for tenderness, it can be used to
4 | DISCUSSION benchmark the tenderness requirements of consumers.
Beef with shear force values >42.6 N were found to be unaccept-
There were significant relationships identified between sarcomere able to the majority of consumers, in this study. This reflects the rec-
length, shear force, and particle size with beef tenderness rankings, ommendations of previous research, which investigated other
with shear force found to be the best predictor. Based on the pre- population demographics. Platter et al. (2003) used an untrained con-
dominance of these metrics in meat studies, this outcome was not sumer panel that was selected to represent the demographics of the
unexpected. Indeed, past research supports the relationship between United States and found shear force values <4.4 kg (43.2 N) as the
these laboratory metrics and sensory panel tenderness data, as well as limit for consumer acceptance. This was also based on a 50% confi-
each other (Purchas, 2014). For example, Battaglia et al. (2019) dence level. Liang et al. (2016) tested consumers from different loca-
reported that sarcomere length and shear force were both correlated tions within the Shandong province of China to find that striploin
with tenderness, even when different methods were used viz. slice or shear force values <41.4 N were considered to be tender. This thresh-
Warner-Bratzler shear force and laser diffraction or microscopic- old was established using samples with a range of shear force values
based sarcomere lengths. Sarcomere length was also observed as hav- (26.5–58.4 N) that were found to have a positive association with
ing a strong, positive association with sensory tenderness (Rhee, consumer tenderness scores (R2 = 0.64). Rodas-Gonzalez, Huerta-
Wheeler, Shackelford, & Koohmaraie, 2004; Smulders, Marsh, Swartz, Leidenz, Jerez-Timaure, and Miller (2009) concluded that ribeye steak
Russell, & Hoenecke, 1990). These metrics provide insight into shear force values from 41.4 to 39.6 N were indicative of the
6 HOLMAN ET AL.

F I G U R E 2 The fitted relationship

of sensory evaluation tenderness
scores with particle size values
(squareroot scale) for aged beef
striploin (longissimus lumborum
muscle) samples. This is shown as a
solid black line (with 95% confidence
intervals included as dotted lines)
overlaid on the raw data (light gray
unfilled dots) and mean tenderness
scores per sample (solid gray dots)

transition from tough to tender beef, when evaluated by Venezuelan 5-week period. This was concluded to result from shear force
consumers. There is slight variation in these proposed thresholds, but reaching its minimum level of detection at a point when particle size
if we consider the capacity for consumers to discriminate between could still detect proteolysis. Proteolysis of structural proteins is fun-
shear force values there is sufficient crossover—with the shear force damental to tenderness, with higher levels of proteolytic degradation
limit at which consumers can detect tenderness variation proposed as associated with improved tenderness (Hopkins, 2017). These findings
ranging from 0.5 to 1 kg (4.9 to 9.8 N) (Huffman et al., 1996). The suggest that particle size can provide insight into beef tenderness and
comparability between tenderness thresholds developed using differ- would therefore be a useful metric to predict consumer acceptance.
ent populations is important as this buoys the concept that laboratory In response, this study demonstrated that beef with a particle size
metrics can be broadly interpreted to provide robust and easier (logis- <198 μm would be considered tender by consumers.
tically) means to evaluate samples, at least for the loin cut and pro- The background tenderness of meat is impacted by its connective
vided comparable shear force methods of determination are applied tissue concentration and extent of cross-linkages (Purchas, 2014), yet
(Hopkins, Lamb, Kerr, & van de Ven, 2013). it was observed that collagen content was not suitable to predict ten-
It was observed that particle size contributions to the prediction derness. This outcome was also shared by Hopkins, Allingham, Col-
of tenderness were “in addition” to the variation accounted for by grave, and van de Ven (2013) wherein no relationship between
shear force. This is of interest because other studies have reported sensory tenderness and shear force with collagen concentration was
strong correlations between particle size and shear force data, albeit identified in lamb meat. It is possible that collagen capacity to predict
with coefficients that are still indicative of a degree of variation tenderness is dependent on the muscle, as Starkey, Geesink, Collins,
(Karumendu et al., 2009; Lametsch, Knudsen, Ertbjerg, Oksbjerg, & Oddy, and Hopkins (2016) observed that soluble collagen impacted
Therkildsen, 2007; Ngapo, Barbare, Reynolds, & Mawson, 1999). on biceps femoris muscle tenderness, but not for longissimus or semi-
Hence, there is a degree of independence between these metrics in membranosus muscles. However, only the longissimus lumborum mus-
terms of their determination of meat tenderness. This concept was cle was evaluated in the present study. Furthermore, Jeremiah and
illustrated by Silva et al. (2018) when beef samples were observed to Martin (1981) did not observe any significant relationship between
have dissimilar particle size and shear force trends when tested over a collagen content or solubility with the shear force values of beef
HOLMAN ET AL. 7

semitendinosus and longissimus muscles. Alternatively, the impact of acceptability to be established. These objective metric limits to
cooking or sample preparation could negate the contributions of colla- describe sensory evaluation will be useful to interpret meat research
gen to understand the consumer's perception of tenderness. This pre- within the context of the customer and consumer. Nevertheless, cau-
mise is somewhat supported by Bouton and Harris (1972) findings tion is recommended when applying these thresholds to other studies
that beef shear force values were aligned with myofibril properties because of the potential sources of variation from methodological,
more so, comparative to the connective tissue of cooked meat. sample type and consumer preference differences to those used
Similarly to collagen content, protein solubility was likewise found herein.
to be unsuitable for the prediction of beef tenderness, although it is
indicative of the post-mortem proteolysis of myofibrillar proteins and ACKNOWLEDG MENTS
has previously been included in the prediction of taste panel tenderness The authors acknowledge the financial support of the Australian Meat
scores and shear force results for beef (Dikeman, Tuma, & Processor Corporation (AMPC) and NSW Department of Primary
Beecher, 1971). This could be due to the somewhat limited range of Industries (NSW DPI). We are grateful for the contributions of the staff
protein solubilities included in the present study and this hampering the from these organizations, Charles Sturt University (CSU), the Graham
potential to identify a threshold for tenderness. Nevertheless, when Centre for Agricultural Innovation (GC) for participating in consumer
interpreting these findings, it is important to note the considerable vari- panels—specifically we thank Mr Matthew Kerr (NSW DPI), Dr Douglas
ation in the consumer rankings of beef tenderness, within samples. Silva (UFLA), Dr Yimin Zhang (SDAU), Prof. John Mawson (CSU),
A consumer's perception of beef sensory acceptability will Dr. Michael Campbell (CSU). In addition, the efforts of Dr Remy van de
depend on their individual preference, behavior and expectation Ven (NSW DPI) to the design of this study are also acknowledged.
(Font-i-Furnols & Guerrero, 2014). As such, we expect this to be the
basis for the variation in consumer rankings of tenderness observed ETHICAL STATEMENTS
herein, where the same sample may have been ranked as unaccept- Conflict of Interest: The authors declare no conflict of interest.
ably tough and very tender by different “tasters”. Another source of Ethical Review: Human ethics approval was granted (Charles Sturt
variation which merits consideration is the method for tenderness University Ethics Committee, 400/2017/25) for the sensory assess-
appraisal. This is because method selection will impact on the repre- ment of sample organoleptic qualities.
sentativeness of a laboratory based metric to consumer scores for Informed Consent: Informed consent was obtained from all study
tenderness—for example, method selection will impact on shear force participants.
(Holman et al., 2016) and likewise, the design or method of a sensory
panel assessment will impact on perceived tenderness as well as other AUTHOR CONTRIBU TIONS
sensory attributes (Torrico et al., 2018). Sources of variation highlight Design (David L. Hopkins, Benjamin W. B. Holman, and Damian Col-
a need for pragmatism when interpreting data against consumer lins), acquisition of data (Ashleigh K. Kilgannon and Benjamin W. B.
thresholds. They likewise may provide context to the alternative Holman), analysis (Damian Collins), interpretation and manuscript
benchmarks for acceptable tenderness proposed in other studies preparations (all authors).
(Aalhus, Jeremiah, Dugan, Larsen, & Gibson, 2004). That said—the pre-
sent study does demonstrate that, although laboratory based metrics OR CID
are proxy or surrogate outcomes to consumer panel assessment, they
Benjamin W. B. Holman https://orcid.org/0000-0002-8458-4511
are nonetheless useful to gleaming practical insight into beef
tenderness. RE FE RE NCE S
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(2004). Establishment of consumer thresholds for beef quality attri-
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