Understanding beef flavour and overall liking traits using two different methods for determination of thiobarbituric acid reactive substance (TBARS)

Understanding beef flavour and overall liking traits using two different methods for determination of thiobarbituric acid reactive substance (TBARS)

Accepted Manuscript Understanding beef flavour and overall liking traits using two different methods for determination of thiobarbituric acid reactive...

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Accepted Manuscript Understanding beef flavour and overall liking traits using two different methods for determination of thiobarbituric acid reactive substance (TBARS)

Yimin Zhang, Benjamin W.B. Holman, Eric N. Ponnampalam, Matthew G. Kerr, Kristy L. Bailes, Ashleigh K. Kilgannon, Damian Collins, David L. Hopkins PII: DOI: Reference:

S0309-1740(18)30774-5 https://doi.org/10.1016/j.meatsci.2018.11.018 MESC 7730

To appear in:

Meat Science

Received date: Revised date: Accepted date:

3 August 2018 19 November 2018 19 November 2018

Please cite this article as: Yimin Zhang, Benjamin W.B. Holman, Eric N. Ponnampalam, Matthew G. Kerr, Kristy L. Bailes, Ashleigh K. Kilgannon, Damian Collins, David L. Hopkins , Understanding beef flavour and overall liking traits using two different methods for determination of thiobarbituric acid reactive substance (TBARS). Mesc (2018), https://doi.org/10.1016/j.meatsci.2018.11.018

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ACCEPTED MANUSCRIPT Understanding beef flavour and overall liking traits using two different methods for determination of thiobarbituric acid reactive substance (TBARS)

Yimin Zhanga,b, Benjamin W. B. Holmanb,c,*, Eric N. Ponnampalamd, Matthew G. Kerrd,

Lab of Beef Processing and Quality Control, College of Food Science and Engineering,

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a

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Kristy L. Bailese, Ashleigh K. Kilgannonb,c, Damian Collinsf, David L. Hopkinsa,b,c

Shandong Agricultural University, Taian, Shandong, 271018, PR China; Centre for Red Meat and Sheep Development, NSW Department of Primary Industries,

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c

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Cowra NSW 2794, Australia;

Graham Centre for Agricultural Innovation, NSW Department of Primary Industries &

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Charles Sturt University, Wagga Wagga NSW 2650, Australia; Animal Production Science, Agriculture Victoria, Department of Economic Development,

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Jobs, Transport and Resources, Bundoora VIC 3083, Australia; e

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Wagga Wagga Agricultural Institute, NSW Department of Primary Industries, Wagga Wagga NSW 2650, Australia;

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Elizabeth Macarthur Agricultural Institute, NSW Department of Primary Industries, Menangle NSW 2568, Australia.

*Corresponding author. Email address: [email protected] (B.W.B. Holman)

ACCEPTED MANUSCRIPT ABSTRACT Two extraction methods were applied to measure the thiobarbituric acid reactive substances (TBARS) values of vacuum packaged grass-fed beef steaks that were aged under four temperatures and five different time interval combinations to capture a range in lipid oxidation. The relationships between TBARS values and consumer assessment of flavour

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liking, flavour intensity and overall liking, were examined. M1 values had a normal

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distribution (0.02 to 2.55 mg MDA/kg), whereas M2 had a skewed distribution with the majority of the values < 1.0 mg MDA/kg and the maximum value being 10.72 mg MDA/kg.

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No relationship was found between these methods. Interestingly, there were no significant

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effects of TBARS value on the sensory results, irrespective of the method used. This suggests that untrained consumers cannot detect abnormal flavour development due to high levels of

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lipid oxidation (TBARS) as indicated by the TBARS test, and are therefore undiscouraged

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when tasting these beef samples.

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Keywords: TBARS; beef flavour; threshold; lipid oxidation; untrained consumer panel

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1.

Introduction The degree of lipid oxidation in meat and processed meat products is often quantified

using a thiobarbituric acid reactive substance (TBARS) assay. In practice, this assay has also been used to provide insight into the eating quality and shelf-life characteristics of beef.

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Some previous studies have suggested TBARS limits in beef for consumer acceptance. For

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example, Campo et al. (2016), considered the limiting threshold of TBARS values for the acceptability of oxidised beef as ~ 2.0 mg malondialdehyde (MDA) per kg; however,

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McKenna et al. (2005) adopted 1.0 mg MDA/kg as an arbitrary threshold; while, Hughes,

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McPhail, Kearney, Clarke, & Warner, (2015) found TBARS levels between 2.60 and 3.11 mg MDA/kg in long term aged beef striploins were still acceptable to consumers.

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These inconsistent outcomes may be the result of beef sample variation, the TBARS determination methods used, amount of sample used or the type of panels/consumer groups

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utilised for sensory assessment. Different protocols for TBARS determination in food and

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food products have been reviewed (Ghani, Barril, Bedgood, & Prenzler, 2017; Guillén-Sans & Guzmán-Chozas, 1998) and highlights the frequent and substantial differences between

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TBARS methods employed in different studies. Ganhão, Estévez, & Morcuende, (2011) grouped the TBARS methods applied in meat research into four categories; 1. Direct heating

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with added TBA solution, followed by TBA-MDA extraction using butanol; 2. MDA determination using the extracted lipid fraction from samples; 3. Aqueous acid extracts of samples (extraction method, EM) to quantify MDA; and 4. MDA determined using steam distillation (distillation methods, DM). The latter two categorises have greater prominence. Yet, both the aforementioned McKenna et al. (2005) and Campo et al. (2006) studies used DM and prescribed different thresholds for consumer acceptability (~ 50% difference). By contrast, there is a paucity of information for the consumer threshold based on TBARS values

ACCEPTED MANUSCRIPT in beef when the EM is applied. This is noteworthy since, this method has been proposed to be the most suitable method for determining lipid oxidation level in meat due to the absence of a heat treatment step, as well as its rapid determination without distillation that better facilitates the analysis of large numbers of samples (Estévez et al., 2009; Ganhão et al., 2011). In the present study, two different TBARS extraction methods were compared, with an

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objective to establish the relationship between TBARS values and aged beef sensory traits

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based on untrained panellists. Using this, we aimed to establish a TBARS threshold for

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consumer acceptance. Materials and methods

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2.1. Sample source

To capture a range of TBARS levels, beef samples were sourced from an investigation

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into the effects of time-temperature combinations on the rate of ageing. In brief, this involved a total of 40 grass-fed beef M. longissimus lumborum (LL) being selected at random from the

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boning room of a commercial Australian abattoir on two separate visits (20 per visit) to

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permit chronological replication. These were divided into eight equal portions (n = 320), individually vacuum-packaged and assigned to one of 72 time-temperature combinations

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(TTC) – the allocation was balanced by LL and portion location within LL (n = 4 per TTC). TTCs included three temperature settings (3.6± 1.7 °C, 5.8 ± 1.0°C, 6.6 ± 1.8°C) and control

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(2.6 ± 3.1°C and 0.8 ± 1.2 °C); and five time intervals (6, 8, 10 or 12 d and control) applied so that temperature control units (TCU) held samples at a constant temperature throughout a time interval, and only one temperature variation was permitted within their assigned total time period. The control TTC refers to a total of 32 LL portions held in duplicate temperature control units for 14 d at ~ 1 °C to replicate commercial practice. At the completion of their TTC, sample sections were removed and frozen (– 25 °C) to be analysed for TBARS content and organoleptic quality traits.

ACCEPTED MANUSCRIPT 2.2. Thiobarbituric acid reactive substances (TBARS) determination Both methods required the absorbance to be measured at 532 nm using a benchtop spectrophotometer (AMR-100 Microplate Reader, Hangzhou Allsheng Instruments Ltd., PRC), and reported their results as mg malondialdehyde (MDA) per kg LL. Technical duplicates were also used for each method.

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Method 1 (M1): Adapted from Hopkins et al., (2014) so that ~ 100 mg samples which

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were obtained from about 10 g minced beef from each sample to represent the entire sample

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profile (exterior and interior location), were prepared with care to avoid obvious connective tissue and fat deposits. These were then homogenised using micro-tube pestles with 500.0 µL

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radio-immunoprecipitation assay (RIPA) buffer (RIPA Buffer Concentrate, Cayman Chemicals™ Ltd., Michigan, USA). Following this the sample extraction was in accordance

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to OXI-tek TBARS Assay Kit Technical Bulletin (Enzo® Life Science Inc., New York, USA). This involved the addition of 100 µL SDS solution and 2.5 mL TBARS/Buffer

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Reagent to each sample that was then incubated at ~ 95 °C for 1 h. Samples were then cooled

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to room temperature in an ice bath, centrifuged and the supernatant then analysed. Method 2 (M2): Using the Witte, Krause, & Bailey (1970) method, ~ 10 g intact

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samples were obtained as per M1, so as to represent the entire sample profile (exterior and interior location) and prepared with care to avoid obvious connective tissue and fat deposits.

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These were homogenised for 45 s with 30.0 mL of chilled extraction solution that contained 20% trichloroacetic acid (TCA) and 2 M phosphoric acid. An additional 30.0 mL of chilled water was added before the solution was homogenised for a further 15 s and then filtered through Whatman’s No. 1 Filter Paper. Filtrate aliquots (2.0 mL) were mixed with 2.0 mL of 2-thiobarbituric acid (5 mM) and held overnight (~ 12 h) under darkness, at room temperature. 2.3. Untrained sensory panel evaluation

ACCEPTED MANUSCRIPT Human ethics approval was granted (Charles Sturt University Ethics Committee Protocol No. 400/2017/25) for an untrained consumer appraisal of beef sample sensory quality traits. The sensory panel design was modified from that described by Thompson et al., (2005) so that samples were randomly assigned to 20 sessions, each populated by 20 volunteer

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untrained panellists (n ≈ 400). Prior to testing, allocated samples were first thawed overnight

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(~ 12 h at 4-5 °C) and then cooked in batches of ten using a clam shell grill (GR-4A,

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Cuisinart™ Griddler, East Windsor, USA) set to 220 °C (observed mean ± standard deviation: 220 ± 15 °C). All temperatures were confirmed using a HACCP infrared

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thermometer (Model 8838, AZ Instrument Corp., Tiachun City, TAI). Samples were considered cooked when their internal temperatures achieved 71 °C, where after they were

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cut into halves which were individually served immediately to individual panellists. Panellists were limited to tasting eight samples per session to minimise ‘taster fatigue’. Consequently,

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each sample was evaluated by at least six, but no more than ten individual panellists whom

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provided feedback in terms of its ‘flavour liking’ (Dislike Extremely vs. Like Extremely) and ‘flavour intensity’ (Not intense vs. Very Intense). Responses were captured using

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corresponding 100 mm sliding scales. Panellist demographic and meat consumption habits were also recorded (Table 1).

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It should be noted that panellists were provided with ad libitum dry water crackers and water throughout a session and instructed to cleanse their palate between each tasting; a nonexperimental (blank) sample was provided prior to experimental samples to assure the correct documentation of their opinion. 2.4. Statistical analysis A linear mixed model was fitted in ASReml-R (Butler, 2009) to each sensory response, consisting of fixed effects of TBARS and taste order, and random effects of carcase,

ACCEPTED MANUSCRIPT carcase/portion/slice, slice, run/session/order, run by order, panellist and panellist by taste order effects, carcase/portion x panellist, and their interactions (where appropriate) with treatment. The notation "A/B" here refers to nested effects viz. A/B = A + A by B. 3.

Results and discussion

3.1.

Comparison of the methods for TBARS determination

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The results showed TBARS values determined by M1 ranged from 0.02 to 2.55 mg

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MDA/kg, with most of the data found between 1.0-1.5 mg MDA/kg (Fig. 1a). By contrast, values obtained using M2 ranged between 0.04-10.72 mg MDA/kg and the majority of the

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data were < 1.0 mg MDA/kg (Fig. 1b). No significant relationship was found between

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methods (Fig. 1c), even after M2 TBARS data were log transformed (log 10) (Fig. 1d). An important difference between two methods used in this study was the extraction

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condition: such as the temperature for the MDA-TBA reaction; samples in M1 were set at 95 °C for 60 min; and M2 samples were held at room temperature for 12 h overnight. The

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range of TBARS values in previous studies that used 100 °C for the MDA-TBA reaction

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were found consistent with that obtained from M1. For example, from 0.3 to 0.8 mg MDA/kg, with the MDA-TBA reacted at 100 °C for 40 min, (Lopacka, Poltorak, &

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Wierzbicka, 2016); and 0.40 to 1.38 mg MDA/kg, with the temperature at 100 °C for 10 min (Wills et al., 2017). It has been reported, that when the reaction temperature is decreased, the

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yield of the pink TBA-MDA compound increases and a longer reaction time is required (Botsoglou et al., 1994). In agreement, in this study, M2 resulted in a higher average TBARS value, with the mean and median values being 1.09 and 1.13, and 1.52 and 0.69 for M1 and M2, respectively. Other studies have reported a difference in TBARS values between methods may result from extraction reagent differences; such as in M1 when acetic acid is used, while in M2 when phosphoric acid and TCA is used instead; It also seems there is a large difference

ACCEPTED MANUSCRIPT between the pH of the two extraction solutions. Kerth & Rowe (2016) identified one of the problems when determining TBARS to be the amount and types of chemicals utilised. Grotta, Castellani, Palazzo, Haouet al., & Martino (2016) compared TBARS values of aged beef using extraction methods with different acids [trichloroacetic acid (TCA), hydrochloric acid (HCl) and perchloric acid (HClO4)] to find TBARS values were lowest if samples were

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extracted in TCA, and no difference was observed when extracted in HCl and HClO4,

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additionally; the extraction conditions employed in the study were 80 °C for 60 min. The absence of any relationship between TBARS values obtained from the two

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methods applied in our study was contrary to our initial thoughts that as the values from M1

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increased the values in M2 would also increase. This position was based on an observed regression correlation (0.845) between the TBARS values of meat samples, obtained from the

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distilled and extraction methods (Witte et al., 1970). However, in the current study, two data points observed in Fig.1c that were above 10 mg MDA/kg for M2 had corresponding data

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values between 1.0-1.5 mg MDA/kg for M1; while those five data points with values > 2.0

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mg MDA/kg for M1 had corresponding values below 0.5 mg MDA/kg for M2 (Fig. 1c). Most of the data from M2 which was < 1.0 mg MDA/kg corresponded to data ranging from 0.5-2.0

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mg/kg for M1. When M2 is log transformed (Fig. 1d), the scatter plot shows a ‘cloud of data’ with no distinct pattern. As a consequence there was no relationship between methods. The

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disparity might be caused by the amount of sample portion used and sample preparation, given that for M1 the sample weight was 0.1 g, and for M2 was 10.0 g. Potentially, using more sample could provide greater insight into the whole sample status, capturing the equidistribution of the intramuscular fat, compared to a more distinguishing smaller subsection focused on lean tissue type. This merits further consideration. 3.2.

Relationship between TBARS values and sensory traits The relationships between the TBARS values and consumer scores of overall liking,

ACCEPTED MANUSCRIPT intensity of flavour and the liking of flavour are shown in Fig. 2. From this, we observe that flavour liking and overall liking both slightly decreased as the TBARS values obtained from M1 increased (Fig. 2a and 2c), while the intensity of the flavour slightly increased as TBARS increased from 0 to 2.5 mg MDA/kg (Fig. 2b). All the three sensory traits slightly increased as the TBARS values obtained from M2 increased (Fig. 2d and 2e). Nonetheless, no

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significant association was found between TBARS values and the sensory results, regardless

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of the method used.

This finding differs from other research available in scientific literature. For instance,

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TBARS values were shown to be highly correlated (Spearman Rank Correlation rho = 0.89)

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with the rancid odour in ground cooked pork (Tarladgis, Watts, Younathan, & Dugan, 1960). Campo et al. (2006) found a significant relationship (rho = 0.84) between the TBARS values

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and the perception of beef rancidity. Resconi et al. (2018) reported the relationship between cooked meat flavour and TBARS values (r = 0.44, P < 0.001), and rancid flavour and

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TBARS values, which showed a higher correlation (r = 0.82, P < 0.001). It should be stressed

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however that these are simple correlations that cannot be used to draw conclusions about causation. Further, Insausti et al. (2001) established the relationship between TBARS values

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of beef and uncooked meat odour using stepwise multiple regression analysis (R2 = 0.68, P < 0.001). However, the sensory assessments in all these previous studies were all undertaken

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using trained panellists. Trained panellists are inherently more sensitive to organoleptic traits so that they can detect more subtle differences than their untrained counterparts. Nonetheless, the sensory science community has claimed that untrained consumers are capable of evaluating the sensory characteristics of products (Ares & Varela, 2017), and the results obtained from consumer panel can closely reflect the “house-in” feeling of the ‘general public’s mouths’. In the current study, a comparatively larger cohort of untrained consumers was used to provide confidence in their assessment that the flavour of aged beef was still

ACCEPTED MANUSCRIPT acceptable when the TBARS values of some samples were above 2.5 mg MDA/kg for M1 or above 10 mg MDA/kg for M2. Additionally, the “halo” effect might be considered when interpreting this sensory evaluation. The halo effect for a food product can be described as the evaluation of one character of a product being strongly impacted or biased by the perception of other traits (Larmond, 1977). Since the sensory traits measured in this study included

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tenderness and juiciness evaluations of meat, it is possible that the high scores for tenderness

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or juiciness could mitigate the negative effects of the flavour, and as a result, there was no significant difference of the flavour scores recorded by the consumers between samples with

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high or low TBARS values.

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Furthermore, in the studies mentioned above, samples were either ground or stored under high oxygen modified atmosphere, and as such were under conditions to accelerate the

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process of lipid oxidisation. In this study, the samples were vacuum packaged beef without exposure to oxygen, which might reduce the flavour intensity due to oxidation (Resconi et al.,

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2018). Additionally, the beef provided for the consumer panel was trimmed heavily, without

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any of the visible fat, which was consistent with the lean samples for TBARS determination, and the lipid oxidation results would only reflect the intramuscular fat. As found in this study,

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Greene & Cumuze (1982) also reported a large variation in the threshold levels of consumers and the correlations between TBARS values and consumer sensory oxidized flavour were

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low. This suggests it might not be possible to define a threshold value for TBARS of vacuum packaged beef using inexperienced consumers. 4.

Conclusion Based on the results and the limitations discussed herein, we suggest that beef remains

acceptable to consumers even when their TBARS values achieve levels of 2.5 mg MDA/kg or 10.0 mg MDA/kg when calculated using M1 and M2 respectively. Whether this remains true across other cooking methods or when trained sensory panellists are used must still be

ACCEPTED MANUSCRIPT confirmed. Acknowledgements We appreciate the support from the Australian Meat Processor Corporation (AMPC), New South Wales Department of Primary Industries (NSW DPI), and Shandong Agricultural University (SDAU). We also acknowledge the assistance of staff from the Graham Centre for

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Agricultural Innovation, Charles Sturt University and our abattoir collaborators.

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Conflict of Interest

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The authors declare no conflicts of interest.

ACCEPTED MANUSCRIPT Table 1 Demographic information collected from volunteers during consumer sensory testing, including red meat consumption habits. Demographic Categorises

Number of Respondents

Age 18-25

101

26-30

43

31-39

41 86

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40-55 55+

101

Unknown

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Sex Male

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Female Other Smoker

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Yes No Unknown

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Occupation Tradesperson Professional Administration

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Technical Labourer Farmer

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Sales and personal service

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201 172 1 28 338 8 23 128 35 11 17 6 24

Homemaker

11

Student

79

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Other

Unknown

36 4

Adults in Household

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1

51

2

222

3

49

4

24

5+

16

Unknown

11

Children in Household 0

256

1

57

2

29

3

21

4+

2

Unknown

8

ACCEPTED MANUSCRIPT Red Meat Consumption Frequency Daily

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4-5 times per week

111

2-3 times per week

155

Weekly

57

Fortnightly

10 8

Less often

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Never

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Unknown

4

I rarely/never eat red meat. Unknown Rare Medium

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Well Done Unknown Annual Income

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Unknown

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>$80000

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<$45000 $45000-$80000

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Level of Doneness

184

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Attitude to Red Meat I enjoy red meat. It's an important part of my diet. I like red meat. It's a regular part of my diet. I do eat some red meat although it would not worry me if I didn't.

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Monthly

136 48 2 3 96 231 44 3 85 99 180 9

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Estévez, M., Morcuende, D., & Ventanas, S. (2009). Determination of oxidation. Handbook of Muscle Foods Analysis (Vol. 13, pp. 221–239). CRC Press. Taylor & Francis Groups.

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