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The effects of season and post-transport rest on alpaca (Vicunga pacos) meat quality
Meat Science 159 (2020) 107935
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The effects of season and post-transport rest on alpaca (Vicunga pacos) meat quality
T
⁎
Tamara E. Biffina, , David L. Hopkinsb, Russell D. Busha, Evelyn Halla, Melanie A. Smitha a b
The University of Sydney, School of Veterinary Science, Faculty of Science, 425 Werombi Road, Camden, NSW 2570, Australia NSW Department of Primary Industries, Centre for Red Meat and Sheep Development, Cowra, NSW 2794, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: Alpaca Pasture Season Resting period Lairage Meat quality
The effects of season (summer, autumn, winter and spring) and post-transportation rest on alpaca meat quality were investigated in 160 castrated male alpacas (23 ± 1 month of age) over a 12 month period. Twice per season, animals were randomly allocated to consignment groups of 20, transported 4 h to slaughter and allocated to either of two treatment groups: (1) overnight lairage pre slaughter (Direct) and (2) seven day rest period with access to feed pre slaughter (Rested). At slaughter, blood was collected for the analysis of plasma cortisol and a longissimus core sample obtain pre rigor for glycogen content determination. Alpaca muscle moisture loss increased through summer and spring in the longissimus thoracics. Seasonal differences did not reflect pasture seasonality or muscle glycogen content. Resting alpacas for 7 days pre-slaughter reduced muscle glycogen content and tenderness. Drip loss and purge was greater for rested animals indicating that resting alpacas post transport is not advantageous to alpaca meat quality.
1. Introduction Rapid growth within the Australian alpaca industry has increased interest in alpaca meat as a viable alternative to traditional fibre production. This has driven research into alpaca muscle biochemistry and meat quality. Given the initial paucity of information relating to Australian alpaca carcases and a limited industry scale, studies have primarily focused on post slaughter components such as carcase and muscle composition, salable meat yield, suitable processing techniques and product ageing (Smith et al., 2017; Smith, Bush, Thomson, & Hopkins, 2015; Smith, Bush, van de Ven, & Hopkins, 2016). Such research has been fundamental in establishing a framework for the development of a competitive alpaca meat market. However, the factors influencing meat quality are multifaceted (Cheng & Sun, 2008; McPhail, Stark, Ball, & Warner, 2014) with past studies identifying a limited understanding of the effects of seasonality, transport and lairage stress on alpaca meat quality. It is commonly understood that stress endured during mustering, transport and lairage of beef cattle can lead to undesirably dark cutting and dry meat (Warriss, 1990). This occurs through the pre-slaughter utilisation of glycogen, resulting in an increased ultimate muscle pH. Resting livestock with access to feed after exposure to stressors, such as transportation, can allow physiological recovery and has been shown to improve meat quality traits such as pH, fresh colour, water holding ⁎
capacity and sensory characteristics in multiple species, including cattle and pigs (Mcveigh, Tarrant, & Harrington, 1979; Salmi et al., 2012; Warriss, Kestin, Brown, & Wilkins, 1984). Alpaca meat research to date has indicated a large variation in muscle glycogen concentration at the point of slaughter ranging from 45.5 mmol/kg (Biffin, Smith, Bush, Collins, & Hopkins, 2018) to 73.8 mmol/kg (Smith, Bush, van de Ven, & Hopkins, 2017), with values falling well below those expected to limit muscle pH decline in other red meat species (Warriss, 1990). Therefore, there may be the potential for an improvement in the consistency of alpaca meat quality if resting post transport allows for the re-establishment of glycogen reserves pre-slaughter. In addition, seasons (summer, autumn, winter, spring) have been shown to have significant impacts on both beef and lamb quality through exposure to heat and cold stress, and nutritional variability (Knee, Cummins, Walker, & Warner, 2004; McPhail et al., 2014). Little is known in relation to seasonal effects on alpaca meat quality. It is evident that product quality varies, but it is unknown if this is due to genetics, seasonality or a combination thereof (Biffin, Smith, Bush, Collins, & Hopkins, 2019). Through the investigation of season induced pre-slaughter stressors and nutritional seasonality on alpacas, an appreciation of the resultant effects on meat quality within the species can be gained and thereby managed accordingly. The current study aimed to report variation in alpaca quality traits across seasons (summer, autumn, winter and spring) and to determine the feasibility of a 7-day
Corresponding author. E-mail address: tamara.biffi[email protected] (T.E. Biffin).
https://doi.org/10.1016/j.meatsci.2019.107935 Received 12 August 2019; Received in revised form 2 September 2019; Accepted 2 September 2019 Available online 02 September 2019 0309-1740/ Crown Copyright © 2019 Published by Elsevier Ltd. All rights reserved.
Meat Science 159 (2020) 107935
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Pasture samples were collected at 0, 3 and 6 weeks prior to each transportation day for qualitative (dry matter, DM; crude protein, CP; metabolisable energy, ME; neutral detergent fibre, NDF and acid detergent fibre, ADF) analysis. Sample collection occurred up to 6 weeks from the slaughter date in order to evaluate the presence of a rising, falling or neutral plane of nutrition. Twenty representative 30 cm × 30 cm (900 cm2) quadrants were sampled across the paddocks in which the animals were grazed in the lead up to transportation (3 separate paddocks in total, recorded as paddock 1, 2 and 3 for inclusion within statistical analysis). Quadrants were cut from ground level, pooled and a fresh pasture weight recorded at the point of collection. On several occasions, pasture within some quadrants was deemed too short and sparse for animal grazing. This was noted and utilised as an indicator of pasture availability, with the number of quadrants containing pasture of desirable grazing length expressed as a percentage of total quadrant number. Pasture samples were then frozen at −20 °C until subsequent analysis.
rest period under commercial pre-slaughter conditions to allow for recovery from 4 h of transportation. 2. Materials and methods 2.1. Experimental design A total of 160 castrated male alpacas (23 ± 1 month of age), averaging a live weight (LW) of 62 kgs, were transported to slaughter over a 12 month period (January 2017 to December 2017). Animals were moved using a single axle tray truck fitted with a standard commercial stock crate (7.2 × 2.5 × 2.0 m, L × W × H) in two groups of 20 per season (summer, autumn, winter and spring), resulting in 2 replicates per season across the year. Animals were randomly allocated to a location within the stock crate, either a front or rear pen (2.4 × 2.5 × 2.0 m, L × W × H; n = 10 animals per pen), for 4 h transportation to a commercial camelid certified abattoir on the south coast of New South Wales (35.19°S, 150.26°E, elevation of 15 m). The truck, transportation route and driver were standardized for all consignment groups. The route comprised a mixture of sealed highway, unsealed gravel, residential areas and tight bends across the 4 h trip from farm to abattoir, a reflection of the current commercial transport route to slaughter. Immediately following transport, animals were allocated to one of two treatment groups with ad lib access to water:
2.3. Pasture analysis Prior to analysis, pooled samples from each collection week were freeze dried and ground to a 1 mm particle size. Sample analysis was performed in duplicate for analytical dry matter, neutral detergent fibre (NDF), acid detergent fibre (ADF) and crude protein (CP) following the official methods of analysis protocols (AOAC, 2005). The NDF and ADF analysis was performed as described by Van Soest (1963), modified for an automated Ankom 200 Fibre Analyser and F57 filter bags (A2000 ANKOM Technologies, New York, USA). Sample nitrogen (N) content was quantified by the Kjeldahl method (method 984.13; AOAC, 2005) using a Leco-428 Analyser (Michigan, USA) and the CP content then calculated using the conversion factor CP = N x 6.25 (McDonald, Edwards, Greenhalgh, & Morgan, 2002). Pasture metabolisable energy (ME) was determined from the fibre and nitrogen content of pasture using methods previously described by NSW Agriculture (1983) and Oddy, Robards, and Low (1983). Calculations were as follows:
1) Overnight (15 ± 1 h) lairage pre slaughter (n = 80) 2) Seven day rest period with access to feed pre slaughter (n = 80) In order to account for potential variation in transport stressors as a result of the separate within truck locations, animals were allocated to treatments in a way that ensured equal numbers from both the front and rear pens were assigned to each lairage treatment (n = 5 animals per pen directed to one of the two treatment groups). The 7-day rest period was selected to best align with commercial practice, and research in beef cattle where a 7 day rest period overcame adverse effects to meat quality following exposure to a stressor (Mcveigh et al., 1979; Warriss et al., 1984).
DDM% = 83.58–0.824 (ADF%) + 2.62 (N%)
2.2. On-farm
ME (MJ/kgDM) = 0.17 (DDM%)–2
Animals were randomly selected from a large commercial meat herd (approximately 600 head) on the southern tablelands of NSW (34.14°S, 149.27°E, elevation of 741 m) one day prior to each transportation day. A subsection of the larger herd was mustered into drafting yards with the use of an integrated laneway system and all-terrain vehicle. Animals were drafted through yards and into a forcing pen and race on the basis of good visual health, age requirements (23 ± 1 months), breed (Huacaya) and time off shears (> 4 weeks). Animals meeting these requirements were then moved individually into a crush (retraining stall) for the evaluation of LW and body condition score (BCS; 1 to 5 scale with 0.25 unit increments; Keinprecht et al., 2016). Radio frequency identification (RFID) tags were used to identify individuals and LW and BCS measurements recorded using Gallagher™ Weigh Scales and Livestock Manager TSi 2 Data Recorder technology (Gallagher Group Limited, Epping VIC, Australia). Animals were then held (18 ± 1 h) on pasture adjacent to yards until subsequent loading the following day, through the yards to which animals were accustomed. Animals were exposed to a temperate Australian climate on farm. Annual daily minimum/maximum temperatures for the district average 11/25, 6/19, 4/11 and 5/18 °C through summer, autumn, winter and spring respectively. The district from which animals were sourced experiences an average annual rainfall of 860 mm and relative humidity of 77% (ranging from 68 to 86%, on average, across the year; Bureau of Meteorology, 2019a). Average district temperature and humidity across the trial year remained within annual averages, with rainfall falling just below average (807 mm for 2017; Bureau of Meteorology, 2019a).
2.4. Lairage component Upon arrival at the abattoir, 5 animals from each truck pen were selected at random and placed into lairage (lairage; n = 10) at a density sufficient to meet Australian standards (0.32 to 0.58 m2 for livestock weighing 50 to 100 kg; Edge, 2009). Animals were provided with ad lib access to water for the duration of lairage. Undercover lairage pens were situated adjacent to forcing pens for the processing facility, approximately 50 m from the knocking box. The remainder of the animals were directed toward a holding paddock (averaging 0.23 acres) where they were held for 7 days prior to slaughter (rested; n = 10) with ad lib access to feed (coastal pasture and/or oaten hay) and water until being placed into lairage the afternoon prior to processing (15 ± 1 h pre slaughter). This was repeated for each of the 8 groups, generating 16 slaughter weeks across the year and two replicates within each season. The processing facility experiences a temperate climate with average daily minimum/maximum temperatures of 17/24, 14/21, 9/17 and 13/21 °C through summer, autumn, winter and spring respectively, average annual rainfall of 1096.9 mm and relative humidity of 70% (ranging from 60 to 80%, on average, across the year; Bureau of Meteorology, 2019b). Temperature, humidity and rainfall across the trial year (2017) reflected these annual averages (2017; Bureau of Meteorology, 2019b). 2
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(FLUOstar OPTIMA, BMG, Labtechnologies, Victoria, Australia) in order to calculate total glycogen concentration of each sample. Ultimate pH analysis was performed using methods outlined by De Brito et al. (2016). Briefly, 1 g of frozen aged sample was homogenised in an iodoacetate buffer (5 mM iodoacetate/150 mM KC; Dransfield, Etherington, & Taylor, 1992) and suspended in a water bath at 22 °C. Ultimate pH was determined as the average of duplicate measures using a temperature and pH meter (Model smartCHEMC-CP, TPS Ltd., Queensland, AUS) calibrated at 22 °C in pH 4.01 and 6.86 buffers.
2.5. Carcase processing The alpacas were slaughtered and dressed under commercial conditions, as previously outlined Smith et al. (2016). Briefly, a conventional captive bolt was used to render animals insensible, followed by exsanguination through severing of the jugular veins and carotid arteries. At this point blood from each animal was collected into prelabelled 10 mL BD lithium heparin vacutainers® (REF 367526, Becton Dickinson, Plymouth, UK) and placed on ice. Immediately following exsanguination, animals were immobilized to prevent excess kicking during carcase dressing procedures. Prior to entering chillers, a glycogen core sample was collected from the right side of each carcase in the caudal region of the longissimus lumborum (LL, shortloin section of the loin). Core samples were snap frozen in liquid nitrogen and stored at −80 °C prior to analysis.
2.8.2. Fresh colour A fresh surface was cut on LT samples 24 h post-mortem and allowed to bloom at chiller ambient temperature (6–7 °C) for 40 min, after which time the meat colour was measured using a Minolta Chroma (model CR400, Osaka, Japan). The chromameter was set to the L*, a*, b* system using illuminate D65, an observer angle of 2°, with an aperture size of 5.0 mm and a closed cone. The chromameter was calibrated using a standardized white tile prior to measurement, and three measurements were taken across the face of the LT for each sample.
2.6. Blood cortisol assay Blood samples were centrifuged for 15 min at 3500 rpm using a portable benchtop centrifuge (SkySpin™ CM-6MT, ELMI laboratory equipment, Riga, Latvia) 2 h post-collection to obtain blood plasma for the determination of cortisol concentration. Plasma was pipetted into a separate 5 mL sterile tube (SKU: P5016SL, TechnoPlas, SA, Australia) and stored at −20 °C until subsequent analysis. Plasma samples were thawed, prepared and cortisol concentration (μg/dL) determined using a commercially available radio-immunoassay kit (Coat-A-Count Cortisol RIA; Siemens Pty Ltd., Los Angeles, CA, USA).
2.8.3. Shear force Frozen samples were prepared and cooked for shear force analysis as described by Hopkins and Thompson (2001). Shear force blocks were randomly allocated to one of 8 cook batches. The allocation was constrained in such way that ensured equal representation from each slaughter week and each season across the batches. Shear force was measured as the average of 6 peak force recordings across each muscle block using a Lloyd (Model LRX, Lloyd instruments, Hampshire UK) texture analyser fitted with a Warner Bratzler shear v blade.
2.7. Sample collection and measurements After chilling for 24 h, carcases were weighed to obtain a cold carcase weight (CCW) and the pH and temperature of the LL was recorded. The pH and temperature were measured using a hand held pH meter with temperature compensation (WB-80, winTPS Pty. Ltd., Brisbane, AUS), a polypropylene spear-type gel electrode (Ionode IJ 44) and cylindrical stainless steel probe attachment. Carcases were then broken down for sample collection. The longissimus thoracis et lumborum was removed from the right hand side of each carcase, prepared into the longissimus thoracic (LT; rack section of the loin) and vacuum packaged for transport after a fresh colour measurement was performed on the LL at the 12th/13th rib. Samples were transported at an average temperature and humidity of 6.0 °C and 85.6%, respectively, for 3 h to a laboratory for sample preparation. Moving cranially along the LT from the 12th/13th rib, toward the 4th rib, approximately 90 g was removed for ageing and weighed for purge, followed by one 60 g sample for drip loss analysis. Drip loss sample preparation is outlined below and followed methods adapted by Logan, Bush, Biffin, Hopkins, and Smith (2019) for alpaca. The remaining muscle was diced, placed into 50 mL tubes and frozen at −20 °C for intramuscular fat (IMF) analysis. After 10 days ageing (3.0 °C and 83.3% humidity), the 90 g blocks were weighed to obtain post ageing weights and prepared into one 65 g block for shear force (SF) analysis and one 5 g sample for ultimate pH (pHu) assessment. Shear force and pHu samples were frozen at −20 °C until subsequent analysis.
2.8.4. Drip loss Drip loss was evaluated using the ‘EZ’ method and following the protocol adapted by Logan et al. (2019) for alpaca. The 60 g drip loss block was trimmed to 2.5 cm in length. From this, two core samples were cut parallel to the muscle fibre using a purpose built cylindrical (2.5 cm diameter) muscle corer. These samples were weighed to 3 decimal places and placed within specialised EZ drip loss containers. All samples were placed within a rack, in the same chiller for 48 h at an average temperature of 3.3 °C and average humidity of 83%. After 48 h, the residual drip was removed from samples with paper towel and samples were individually weighed to 3 decimal places to obtain postdrip weights. 2.8.5. Purge and cooking loss Purge was calculated from the pre and post age (10 d) weight of the 90 g aged LT sample, and expressed as a percentage of the pre-age weight. Cooking loss was calculated as a percentage of the pre-cook weight on all shear force blocks, using the pre-cook frozen weight and post cook weight as outlined by Hopkins and Thompson (2001). 2.8.6. Intramuscular fat (IMF) Prior to analysis, samples were freeze dried and ground using a FOSS Knifetech™1095 mill and stored (−20 °C) until analysis. The IMF analysis was conducted using methods described by Hopkins et al. (2014). In brief, 3 g of freeze dried and ground muscle sample was extracted with 85 mL hexane for 80 min, in a FOSS Soxtec 2050 machine. Samples were then removed, dried (30 min and 105 °C) and weighed.
2.8. Meat quality testing 2.8.1. Glycogen and ultimate pH For the determination of glycogen content, 1 g of frozen LL sample was incubated in 10 mL of Milli-Q water for 5 min at 100 °C, homogenised (two bursts of 15 s at 22,000 rpm) and then centrifuged (Model CPR, Beckman Instruments, CA, USA) for 15 min at 3500 rpm (De Brito et al., 2016). The supernatant from each sample was plated in duplicate and compared to glycogen standards using the colorimetric protocol detailed by the commercial glycogen assay kit (Sigma-Aldrich, MO, USA). Absorbance was measured at 570 nm using a micro-plate reader
2.8.7. Statistical analysis Animal live weight, body condition score and muscle IMF were analysed separately using Linear Mixed Model (LMM) analysis in Genstat 18th edition (VSN International Ltd., Hertfordshire, UK) with fixed terms for season (summer, autumn, winter, spring) and trip number (1 to 8). The model included animal ID as a random term. For the analysis of pasture quality, individual traits (ME, CP, DDM, 3
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minimal detectable assay level of 0.2 μg/dL.
NDF, ADF and availability) were investigated through separate LMMs. Fixed effects included season and trip number. The model contained a random term for paddock number (1, 2 or 3), as well as week number from slaughter (0, 3 or 6) nested within paddock number to account for the repeated measure. Multiple LMMs were generated for the analysis of meat quality traits including CCW, evaporative loss, fresh colour, glycogen, pHu, drip loss, purge, cooking loss and shear force, as well as plasma cortisol. Each trait was analysed individually and full models included fixed effects for constant + season + lairage treatment (direct vs rested) + trip number (1 to 8) + pen number (1 or 2) + an interaction term for season × lairage treatment. With the exception of muscle shear force, the season × lairage interaction term was dropped from all models on the basis of non-significance at the P < .05 level using a stepwise backward elimination. Trip number and pen number were also removed from the final model based on non-significance. For the analysis of evaporative loss, CCW was added to the model as a covariate. Random terms for all models included carcase and slaughter number. Additional random terms for batch number and test date were added to the plasma cortisol, pHu, shear force and cooking loss models. Chiller temperature was included as a random term within the CCW, evaporative loss, drip loss and purge models. Model based predicted means, standard errors, P–values and LSDs were extracted from all LMMs for reporting.
3.4. Carcase traits Cold carcase weights were lowest in spring, while being statistically similar to winter weights, and highest in autumn (Table 2). There was a significant relationship between CCWs and evaporative loss. There was no variation in carcase evaporative loss across season (Table 2) or between lairage treatments throughout the year (3.7 ± 0.22 and 3.3 ± 0.22 for direct and rested respectively). 3.5. Meat quality testing 3.5.1. Glycogen and pH Within the current study, glycogen was lower (P = .008) in muscles of animals slaughtered in autumn and winter (Table 2). Glycogen levels varied significantly between direct and rested animals, with rested animals exhibiting muscle glycogen content of 6.6 mmol/kg lower, on average, than animals sent direct (at 42.4 and 49.0 mmol/kg respectively). There was no effect of season on LL pHu (Table 2). Likewise pHu was unaffected by resting treatments, averaging 5.6 ( ± 0.05) across the year and resting groups.
3. Results
3.5.2. Fresh colour Alpaca LT fresh colour did not change across season or as a result of resting, with the exception of decreased (P = .007) redness in spring. Fresh colour parameters averaged across season and resting period were 39.4 ( ± 1.13), 15.7 ( ± 0.71), 7.7 ( ± 0.33) for L* (lightness), a* (redness) and b* (yellowness) respectively.
3.1. Pasture analysis Pasture availability (indicated by the percentage of grass of desirable grazing length) and quality varied across the year (Table 1). Spring pasture was of highest (P < .001) quality as judged by CP, ME and DDM, and winter pasture of lowest (P < .001) availability, while summer and autumn pastures had similar quality and pasture availability.
3.5.3. Shear force and intramuscular fat (IMF) There was an interaction between season and resting treatment (P = .032). The effect was such that SF values for muscle of animals sent direct to slaughter in any season, with the exception of autumn, were lower than product from rested animals (Fig. 1). Longissimus thoracis IMF did not change (P = .11; Table 2) across the year or between consignment groups. Intramuscular fat averaged 1.3 ( ± 0.08) % across seasons.
3.2. On-farm Animal live weight averaged 61.6 ± 0.07 kg across the year, ranging from an average of 57.8 ± 1.59 kg (spring) to 64.1 ± 1.59 kg (autumn). With the exception of transport group 6 (winter; 54.0 ± 2.25 kg), animal live weight did not vary across trip groups. Body condition score also did not vary across trips or season, with animals retaining an average BCS of 2.75 ± 0.03 across the year. 3.3. Blood cortisol
3.5.4. Drip loss Drip loss was higher in the summer (P = .026) compared to other seasons (Table 2). The resting treatment also tended (P = .055) to increase drip loss percentage, averaging 2.5 ± 0.15% while muscle from animals sent direct to slaughter averaged 2.1 ± 0.15%.
Blood plasma cortisol levels did not vary across season or resting treatments (P = .61 and .11 respectively). Plasma cortisol, averaged across season and lairage treatments was 1.05 μg/dL at the point of slaughter. A high number (51 out of 160) of samples fell below the
3.5.5. Purge and cooking loss Purge loss was greater in the summer than in the other seasons (Table 2). Product from animals sent direct to slaughter lost significantly less (P = .02) moisture than animals that were rested. There
Table 1 Predicted means ± standard error across season for pasture qualitative traits. Traits include; sample size (n), dry matter (DM), digestible dry matter (DDM), desirable grazing length (i.e. of a length that can be physically grazed by the animal; average % across quadrants), crude protein (CP), metabolisable energy (ME), acid detergent fibre (ADF) and neutral detergent fibre (NDF). Means are averaged across trip group, collection week and paddock number. Trait DM (%) DDM (%) Grass of desirable grazing length (%) CP (%) ME (MJ/kg DM) ADF (%) NDF (%)
Winter (n = 6)
Spring (n = 6)
b
30 71 88 20 10 25 45
43 ± 12.2 62 ± 1.2b 60 ± 7.1b 18 ± 0.8a 9 ± 0.2b 36 ± 1.3b 52 ± 1.4b
± ± ± ± ± ± ±
ab
14.6 1.2a 7.3a 0.8a 0.2a 1.3a 1.4a
Summer (n = 5) c
66 ± 12.3 52 ± 1.4c 100 ± 7.7a 8 ± 1.0b 7 ± 0.2c 42 ± 1.5c 65 ± 1.6c
Autumn (n = 6) 72 ± 11.1c 50 ± 1.2c 96 ± 6.9a 8 ± 0.8b 6 ± 0.2c 46 ± 1.3c 67 ± 1.4c
Significant differences between means denoted by superscripts. All superscripts were generated on an individual trait by season level. Superscripts are not applicable to means in different rows. 4
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Table 2 Sample size (n) and predicted means ± standard error across seasons for alpaca cold carcase weight (CCW), evaporative loss, ultimate pH (pHu), fresh colour (lightness, L*; redness, a* and; yellowness, b*), intramuscular fat (IMF), drip loss, purge, and cooking loss in the alpaca longissimus thoracis. Trait
Winter (n = 40)
Spring (n = 40)
Summer (n = 40)
Autumn (n = 40)
CCW (kg) Evaporative loss (%) Glycogen (mmol/kg) pHu Fresh colour L* a* b* IMF (%) Drip loss (%) Purge (%) Cooking loss (%)
32.0 ± 0.79ab 3.6 ± 0.31a 42.8 ± 2.77ab 5.6 ± 0.04a
30.3 ± 0.79a 3.2 ± 0.31a 52.9 ± 2.77a 5.5 ± 0.05a
33.1 ± 0.79bc 3.1 ± 0.31a 49.9 ± 2.77a 5.5 ± 0.05a
34.5 ± 0.79c 3.9 ± 0.31a 37.1 ± 2.77b 5.6 ± 0.05a
38.4 ± 0.67a 15.9 ± 0.68a 7.2 ± 0.45a 1.02 ± 0.16a 2.2 ± 0.21a 7.7 ± 0.38b 21.9 ± 0.51a
40.5 ± 0.78a 12.6 ± 0.79b 8.0 ± 0.53a 1.75 ± 0.16a 2.3 ± 0.21a 8.6 ± 0.38bc 20.6 ± 0.51a
40.1 ± 0.67a 17.1 ± 0.68a 8.1 ± 0.45a 1.21 ± 0.16a 2.9 ± 0.21b 9.3 ± 0.38c 20.6 ± 0.51a
38.6 ± 0.67a 17.1 ± 0.68a 7.7 ± 0.45a 1.18 ± 0.16a 1.8 ± 0.21a 6.5 ± 0.38a 20.4 ± 0.51a
Significant differences between means denoted by superscripts. All superscripts were generated on an individual trait by season level. Superscripts are not applicable to means in different rows.
90
78.4a
80
Shear force (N)
70
65.6bc
73.2ab 65.5bc
57.1c
60
requirements were being met across all seasons. Furthermore, this may explain why the seasonal variation in muscle glycogen content was only minimal, despite fluctuations in feed quality and availability under the same transportation and lairage stressors. The variation in CCW across season can be aligned to animal LW differences, with LW and CCW both highest in autumn and lowest in spring. However, animal LW and CCW trends did not tend to follow increases or decreases in pasture quality. Given that animal BCS remained constant across consignment groups, these differences in weight may simply reflect the variation in animal frame size. For future research, the evaluation of animal frame scores prior to transportation may be advantageous in explaining animal and carcase weight variation when weight changes are not supported by differences in BCS. Evaporative loss percentages ranged from 3 to 4% of the initial hot carcase weight across the year which is in line with past alpaca research (Smith et al., 2015) and is toward the higher end of that observed for beef and lamb (1–3%; James & James, 2002). This is to be expected given the lean nature of alpaca carcases when compared to beef and lamb. There was a significant negative relationship between CCW and evaporative loss, with reduced evaporative loss at greater carcase weights. For every kg increase in CCW across the sampled range, evaporative loss was reduced by 0.06 units, resulting in an evaporative loss of 3.2% at a CCW of 38–40 kg, down from 3.8% at CCW of 28–30 kg. These results indicate an advantage to slaughtering alpacas at heavier weights in order to minimise carcase moisture loss. Glycogen levels varied significantly between direct and rested animals, with rested animals exhibiting lower muscle glycogen content. This could have resulted from increased stressors within the novel resting environment, as well as the change in nutrition from the southern tablelands to the south coast across the year. As plasma cortisol levels were low and did not vary between resting groups at the point of slaughter, glycogen differences more likely reflect the changing nutritional base and a reduced feed intake through the resting period (Ferguson, Daly, Gardner, & Tume, 2008). Autumn values for muscle glycogen within the current study are the lowest reported to date for alpacas managed under Australian conditions, at 37 ( ± 2.8) mmol/kg, with past research reporting values of 45.5 mmol/kg (Biffin et al., 2018) and 73.8 mmol/kg (Smith et al. 2017). These values remain well below that reported as potentially limiting to beef and lamb pH decline (Pethick & Rowe, 1996; Warriss, 1990). Biffin et al. (2018) indicated that a glycogen concentration beyond the lower threshold of 45 mmol/kg reported for other red meat species, will still result in a desirable pHu within alpaca. The current study supports this notion with an average pHu of 5.6 achieved within a glycogen concentration range of 37 mmol/kg to 53 mmol/kg. Furthermore, there were no changes to pHu across the year or due to resting treatments within the current study despite significant variation in
73.0ab 64.0bc 58.2c
50
Direct
40
Rested
30 20 10 0 Winter
Spring
Summer
Autumn
Fig. 1. Shear force values within the alpaca longissimus thoracis across season and lairage treatments (n = 20). Significant differences between means denoted by superscripts.
was no seasonal effect (P = .22) on cooking loss percentage (Table 2). Product from rested animals tended to have higher cooking loss than product from animals sent direct (21.4 ± 0.36% and 20.3 ± 0.36% respectively). 4. Discussion Pasture growth followed a traditional annual trend where summer and autumn pastures were of higher fibre content and lower digestible dry matter (DDM; though ample availability). This was followed by pasture availability dropping off toward the end of autumn and increasing again through spring (Table 1). Spring pastures exhibited the highest CP (%), ME (MJ/kg DM) and DDM (%) at the same level of availability provided through summer and spring. This aids in explaining the slightly greater muscle glycogen content exhibited by animals processed through spring. Importantly, it should be noted that despite significant variation in quality across seasons, nutrient availability throughout the year still met the maintenance requirements for 62 kg male alpacas, > 12 months old (~6.74 MJ ME/day, 8% - 10% CP and 0.6–1.1 kg daily DMI depending on feed quality) (Cebra, Anderson, Tibary, Saun, & Johnson, 2014; National Research Council, 2007; San Martin & Bryant, 1989). When considering animal activity level during grazing and the fibre content of pastures through summer and into autumn, nutrient intake may have been limited in these seasons given that ME and CP fell toward the lower end of maintenance requirements. However, animal LW was greater through autumn and lowest in spring on the higher quality pasture. This, combined with the lack of observed variation in animal BCS across season, indicates that nutritional 5
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consignment groups in future may aid in explaining some of this variation. Resting alpacas for 7 days pre-slaughter had a negative effect on meat quality, with reduced muscle glycogen content and tenderness. Moisture loss in the form of drip and purge was greater for rested animals when compared to product of animals sent direct to slaughter. Therefore, there is no advantage to resting animals for 7 days post transport on alpaca meat quality.
glycogen content across season and between resting groups. Therefore, these findings further support that of Biffin et al. (2018), that a glycogen concentration of approximately 45 to 46 mmol/kg is not limiting to pH decline in alpaca and is sufficient to meet a desired pHu of 5.5 to 5.6 (Biffin et al., 2018; Smith, Bush, van de Ven, Hall, et al., 2017). Alpaca fresh colour within the current study fell toward the higher end of the spectrum for L*, a* and b* when compared to previously reported values for non-electrically stimulated alpaca carcases (Biffin et al., 2019), yet remained below that reported for all colour parameters in lamb (Khliji, van de Ven, Lamb, Lanza, & Hopkins, 2010). Redness (a*) values in spring were lower than in any other season. It is possible that this change reflected glycogen levels being highest through spring. Immonen, Ruusunen, and Puolanne (2000) indicated that as residual glycogen concentration increased within beef longissimus, redness values decreased. However, glycogen differences within the current study were not as great as that observed by Immonen et al. (2000). Further research would be required to determine if this difference in redness relates to season and glycogen availability or more so genetic variation between consignment groups. The interaction between seasonality and resting treatments influenced muscle SF, such that within each season excluding autumn, resting negatively impacted product tenderness (Fig. 1). There was a trend toward improved SF with resting in autumn. However autumn resting values did not differ significantly from those of animals sent direct to slaughter, indicating that despite season, resting will tend to negatively affect muscle SF in alpaca's which is an important finding. Further work to explain the reason for this finding could be warranted, but from a practical perspective it provides a clear message to alpaca processors that to maximize tenderness alpacas should not be exposed to lengthy lairage periods. The seasonality of alpaca moisture loss, characterized in the current study by elevated spring and summer DL % and purge %, as well as increased DL % and purge % when resting animals, may reflect variation in animal hydration or events occurring early in post-mortem chilling. Muscle pH is known to have a negative correlation with pork drip loss as a greater amount of water will be bound within meat fibres at a higher pH (Hertog-Meischke, van Laack, & Smulders, 1997; Prevolnik, Čandek-Potokar, Novič, & Škorjanc, 2009). However, pHu within the current study did not vary across season or resting treatments. Further research is required to fully understand the underlying mechanism for these moisture loss findings. At the commercial level, the increases in product moisture loss during spring and summer, and as a result of resting, would result in reduced value on a $/kg basis. Intramuscular fat averaged 1.3 ( ± 0.08) % across seasons, which is higher than values previously reported for Australian alpacas (0.58–0.66%; Smith, Bush, van de Ven, Hall, et al., 2017; Smith et al., 2017). However, it is evident that alpaca IMF remains well below the IMF % reported for other red meat species, with grass fed beef reported to contain on average 5% IMF (Scollan et al., 2006) and lamb 4–5% (Hopkins, Hegarty, Walker, & Pethick, 2006). The current study demonstrates that despite the variation in nutritional base between consignment groups, product IMF did not change. This indicates that there may be a significant genetic influence over animal to animal and consignment group variation in IMF %.
Declaration of Competing Interest The authors acknowledge there is no conflict of interest. Acknowledgments This project was funded by AgriFutures Australia (PRJ-010045) and Illawarra Prime Alpaca. The authors would like to thank Mr. Matthew Kerr, NSW DPI, and Miss Bridgette Logan, the University of Sydney, for their immeasurable assistance across the sampling year; the staff of Milton district meats for their time; and all volunteers that gave up their time to assist with sample collections. References AOAC (2005). Offical Methods of Analysis (18 ed.). Gaithersburg, Maryland, USA: Association of Official Analytical Chemists (AOAC). Biffin, T., Smith, M., Bush, R., Collins, D., & Hopkins, D. (2018). The effect of combining tenderstretching and electrical stimulation on alpaca (Vicugna pacos) meat tenderness and eating quality. Meat Science, 145, 127–136. https://doi.org/10.1016/j.meatsci. 2018.06.002. Biffin, T., Smith, M., Bush, R., Collins, D., & Hopkins, D. (2019). The effect of electrical stimulation and tenderstretching on colour and oxidation traits of alpaca (Vicunga pacos) meat. Meat Science, 156, 125–130. https://doi.org/10.1016/j.meatsci.2019. 05.026. Bureau of Meteorology (2019a). Climate statistics for Australian locations (site 070025). Australian Government Bureau of Meteorology. Retrieved 19/08/2019, from http:// www.bom.gov.au/climate/averages/tables/cw_070025.shtml. Bureau of Meteorology (2019b). Climate statistics for Australian locations (site 069138). Australian Government Bureau of Meteorology. Retrieved 19/08/2019, from http:// www.bom.gov.au/climate/averages/tables/cw_069138.shtml. Cebra, C., Anderson, D. E., Tibary, A., Van Saun, R. J., & Johnson, L. W. (2014). Llama and alpaca care: Medicine, surgery, reproduction, nutrition, and herd health (1st ed.). (St. Louis: MO, Chapter 9). Cheng, Q., & Sun, D. (2008). Factors affecting the water holding capacity of red meat products: A review of recent research advances. Critical Reviews in Food Science and Nutrition, 48, 137–159. https://doi.org/10.1080/10408390601177647. De Brito, G., McGrath, S., Holman, B., Friend, M., Fowler, S., van de Ven, R., & Hopkins, D. (2016). The effect of forage type on lamb carcass traits, meat quality and sensory traits. Meat Science, 119, 95–101. https://doi.org/10.1016/j.meatsci.2016.04.030. Dransfield, E., Etherington, D. J., & Taylor, M. A. J. (1992). Modelling post-mortem tenderisation: 11. Enzyme changes during storage of electrically stimulated and nonstimulated beef. Meat Science, 31, 75–84. Edge, M. (2009). Industry animal welfare standards for livestock processing establishments preparing meat for human consumption. Meat and Livestock Australia Ltd.. Retrieved 26/08/2019 from https://aawcs.com.au/wp-content/uploads/2019/03/33024_ MLA_ind_Welfare_V4.pdf. Ferguson, D., Daly, B., Gardner, G., & Tume, R. (2008). Effect of glycogen concentration and form on the response to electrical stimulation and rate of post-mortem glycolysis in ovine muscle. Meat Science, 78, 202–210. https://doi.org/10.1016/j.meatsci.2007. 06.003. Hertog-Meischke, M. J. A., van Laack, R. J. L. M., & Smulders, F. J. M. (1997). The waterholding capacity of fresh meat. Veterinary Quarterly, 19(4), 175–181. Hopkins, D. L., Clayton, E. H., Lamb, T. A., van de Ven, R. J., Refshauge, G., Kerr, M. J., & Ponnampalam, E. N. (2014). The impact of supplementing lambs with algae on growth, meat traits and oxidative status. Meat Science, 98, 135–141. https://doi.org/ 10.1016/j.meatsci.2014.05.016. Hopkins, D., Hegarty, R., Walker, P., & Pethick, D. (2006). Relationship between animal age, intramuscular fat, cooking loss, pH, shear force and eating quality of aged meat from sheep. Australian Journal of Experimental Agriculture, 46, 879–884. https://doi. org/10.1071/EA05311. Hopkins, D., & Thompson, J. (2001). The relationship between tenderness, proteolysis, muscle contraction and dissociation of actomyosin. Meat Science, 57, 1–12. https:// doi.org/10.1016/S0309-1740(00)00065–6. Immonen, K., Ruusunen, M., & Puolanne, E. (2000). Some effects of residual glycogen concentration on the physical and sensory quality of normal pH beef. Meat Science, 55, 33–38. https://doi.org/10.1016/S0309-1740(99)00122-9. James, S. J., & James, C. (2002). Meat refrigeration. Cambridge: Woodhead Publishing Ltd (Chapter 5).
5. Conclusion Alpaca meat quality varied across the year, with increased moisture loss through summer and spring and a trend toward improved summer tenderness. However, this variation did not reflect nutritional quality or changes to muscle glycogen content. Supporting past literature, it can be concluded that low muscle glycogen content (of ~45 mmol/kg) is not limiting to alpaca pHu. It is possible that additional biochemical and genetic processes not considered within the scope of the current research are contributing to alpaca meat quality variation across seasons. Research that incorporates the genetic evaluation of different 6
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using artificial neural networks. Meat Science, 83, 405–411. Salmi, B., Trefan, L., Bünger, L., Doeschl-Wilson, A., Bidanel, J. P., Terlouw, C., & Larzul, C. (2012). Bayesian meta-analysis of the effect of fasting, transport and lairage times on four attributes of pork meat quality. Meat Science, 90, 584–598. San Martin, F., & Bryant, F. (1989). Nutrition of domesticated South American llamas and alpacas. Small Ruminant Research, 2(3), 191–216. https://doi.org/10.1016/09214488(89)90001-1. Scollan, N., Hocquette, J., Nuernberg, K., Dannenberger, D., Richardson, I., & Moloney, A. (2006). Innovations in beef production systems that enhance the nutritional and health value of beef lipids and their relationship with meat quality. Meat Science, 74, 17–33. https://doi.org/10.1016/j.meatsci.2006.05.002. Smith, M., Bush, R., Thomson, P., & Hopkins, D. (2015). Carcass traits and saleable meat yield of alpacas (Vicugna pacos) in Australia. Meat Science, 107, 1–11. https://doi.org/ 10.1016/j.meatsci.2015.04.003. Smith, M., Bush, R., van de Ven, R., Hall, E., Greenwood, P., & Hopkins, D. (2017). The impact of gender and age on the nutritional parameters of alpaca (Vicugna pacos) meat, colour stability and fat traits. Meat Science, 123, 21–28. https://doi.org/10. 1016/j.meatsci.2016.08.012. Smith, M., Bush, R., van de Ven, R., & Hopkins, D. (2016). Effect of electrical stimulation and ageing period on alpaca (Vicugna pacos) meat and eating quality. Meat Science, 111, 38–46. https://doi.org/10.1016/j.meatsci.2015.08.013. Smith, M., Bush, R., van de Ven, R., & Hopkins, D. (2017). The combined effects of grain supplementation and tenderstretching on alpaca (Vicugna pacos) meat quality. Meat Science, 125, 53–60. https://doi.org/10.1016/j.meatsci.2016.11.015. Van Soest, P. J (1963). Use of detergents in the analysis of fibrous feeds. II. A rapid method for the determination of fibre and lignin. Journal of the Association of Official Agricultural Chemists, 46(5), 829–835. Warriss, P. D. (1990). The handling of cattle pre-slaughter and its effects on carcass and meat quality. Applied Animal Behaviour Science, 28, 171–186. Warriss, P., Kestin, S., Brown, S., & Wilkins, L. (1984). The time required for recovery from mixing stress in young bulls and the prevention of dark cutting beef. Meat Science, 10, 53–68. https://doi.org/10.1016/0309-1740(84)90031-7.
Keinprecht, H., Pichler, M., Pothmann, H., Huber, J., Iwersen, M., & Drillich, M. (2016). Short term repeatability of body fat thickness measurement and body condition scoring in sheep as assessed by a relatively small number of assessors. Small Ruminant Research, 139, 30–38. https://doi.org/10.1016/j.smallrumres.2016.05.001. Khliji, S., van de Ven, R., Lamb, T. A., Lanza, M., & Hopkins, D. L. (2010). Relationship between consumer ranking of lamb colour and objective measures of colour. Meat Science, 85(2), 224–229. https://doi.org/10.1016/j.meatsci.2010.01.002. Knee, B., Cummins, L., Walker, P., & Warner, R. (2004). Seasonal variation in muscle glycogen in beef steers. Animal Production Science, 44, 729–734. Logan, B., Bush, R., Biffin, T., Hopkins, D., & Smith, M. (2019). Measurement of drip loss in alpaca (Vicugna pacos) meat using different techniques and sample weights. Meat Science, 151, 1–3. https://doi.org/10.1016/j.meatsci.2018.12.012. McDonald, P., Edwards, R. A., Greenhalgh, J. F. D., & Morgan, C. A. (2002). Animal nutrition (6th ed.). Essex, UK: Peasons Education Limited. McPhail, N., Stark, J., Ball, A., & Warner, R. (2014). Factors influencing the occurrence of high ultimate pH in three muscles of lamb carcasses in Australia. Animal Production Science, 54, 1853–1859. Mcveigh, J., Tarrant, P., & Harrington, M. (1979). Influence of behavioural stress on bovine skeletal muscle glycogen content [proceedings]. Biochemical Society Transactions, 7, 539–541. https://doi.org/10.1042/bst0070539. NSW Agriculture (1983). Summary of Feed Composition. Glenfield: Nutrition and Feeds Evaluation Unit. National Research Council (2007). Nutrient requirements of small ruminants: Sheep, goats, cervids, and new world camelids. National Academy of Sciences. Retrieved from http:// search.proquest.com/docview/1820736917/. Oddy, V. H., Robards, G. E., & Low, S. G. (1983). Prediction of in vivo digestibility of ruminant feeds from fibre and nitrogen content. Paper presented at the proc 2nd international conference of the International Network of Feeds Information Centres. Pethick, D. W., & Rowe, J. B. (1996). The effect of nutrition and exercise in carcass parameters and the level of glycogen in skeletal muscle of Merino sheep. Australian Journal of Agricultural Research, 47, 525–537. Prevolnik, M., Čandek-Potokar, M., Novič, M., & Škorjanc, D. (2009). An attempt to predict pork drip loss from pH and colour measurements or near infrared spectra
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The effects of season and post-transport rest on alpaca (Vicunga pacos) meat quality
T
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Tamara E. Biffina, , David L. Hopkinsb, Russell D. Busha, Evelyn Halla, Melanie A. Smitha a b
The University of Sydney, School of Veterinary Science, Faculty of Science, 425 Werombi Road, Camden, NSW 2570, Australia NSW Department of Primary Industries, Centre for Red Meat and Sheep Development, Cowra, NSW 2794, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: Alpaca Pasture Season Resting period Lairage Meat quality
The effects of season (summer, autumn, winter and spring) and post-transportation rest on alpaca meat quality were investigated in 160 castrated male alpacas (23 ± 1 month of age) over a 12 month period. Twice per season, animals were randomly allocated to consignment groups of 20, transported 4 h to slaughter and allocated to either of two treatment groups: (1) overnight lairage pre slaughter (Direct) and (2) seven day rest period with access to feed pre slaughter (Rested). At slaughter, blood was collected for the analysis of plasma cortisol and a longissimus core sample obtain pre rigor for glycogen content determination. Alpaca muscle moisture loss increased through summer and spring in the longissimus thoracics. Seasonal differences did not reflect pasture seasonality or muscle glycogen content. Resting alpacas for 7 days pre-slaughter reduced muscle glycogen content and tenderness. Drip loss and purge was greater for rested animals indicating that resting alpacas post transport is not advantageous to alpaca meat quality.
1. Introduction Rapid growth within the Australian alpaca industry has increased interest in alpaca meat as a viable alternative to traditional fibre production. This has driven research into alpaca muscle biochemistry and meat quality. Given the initial paucity of information relating to Australian alpaca carcases and a limited industry scale, studies have primarily focused on post slaughter components such as carcase and muscle composition, salable meat yield, suitable processing techniques and product ageing (Smith et al., 2017; Smith, Bush, Thomson, & Hopkins, 2015; Smith, Bush, van de Ven, & Hopkins, 2016). Such research has been fundamental in establishing a framework for the development of a competitive alpaca meat market. However, the factors influencing meat quality are multifaceted (Cheng & Sun, 2008; McPhail, Stark, Ball, & Warner, 2014) with past studies identifying a limited understanding of the effects of seasonality, transport and lairage stress on alpaca meat quality. It is commonly understood that stress endured during mustering, transport and lairage of beef cattle can lead to undesirably dark cutting and dry meat (Warriss, 1990). This occurs through the pre-slaughter utilisation of glycogen, resulting in an increased ultimate muscle pH. Resting livestock with access to feed after exposure to stressors, such as transportation, can allow physiological recovery and has been shown to improve meat quality traits such as pH, fresh colour, water holding ⁎
capacity and sensory characteristics in multiple species, including cattle and pigs (Mcveigh, Tarrant, & Harrington, 1979; Salmi et al., 2012; Warriss, Kestin, Brown, & Wilkins, 1984). Alpaca meat research to date has indicated a large variation in muscle glycogen concentration at the point of slaughter ranging from 45.5 mmol/kg (Biffin, Smith, Bush, Collins, & Hopkins, 2018) to 73.8 mmol/kg (Smith, Bush, van de Ven, & Hopkins, 2017), with values falling well below those expected to limit muscle pH decline in other red meat species (Warriss, 1990). Therefore, there may be the potential for an improvement in the consistency of alpaca meat quality if resting post transport allows for the re-establishment of glycogen reserves pre-slaughter. In addition, seasons (summer, autumn, winter, spring) have been shown to have significant impacts on both beef and lamb quality through exposure to heat and cold stress, and nutritional variability (Knee, Cummins, Walker, & Warner, 2004; McPhail et al., 2014). Little is known in relation to seasonal effects on alpaca meat quality. It is evident that product quality varies, but it is unknown if this is due to genetics, seasonality or a combination thereof (Biffin, Smith, Bush, Collins, & Hopkins, 2019). Through the investigation of season induced pre-slaughter stressors and nutritional seasonality on alpacas, an appreciation of the resultant effects on meat quality within the species can be gained and thereby managed accordingly. The current study aimed to report variation in alpaca quality traits across seasons (summer, autumn, winter and spring) and to determine the feasibility of a 7-day
Corresponding author. E-mail address: tamara.biffi[email protected] (T.E. Biffin).
https://doi.org/10.1016/j.meatsci.2019.107935 Received 12 August 2019; Received in revised form 2 September 2019; Accepted 2 September 2019 Available online 02 September 2019 0309-1740/ Crown Copyright © 2019 Published by Elsevier Ltd. All rights reserved.
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Pasture samples were collected at 0, 3 and 6 weeks prior to each transportation day for qualitative (dry matter, DM; crude protein, CP; metabolisable energy, ME; neutral detergent fibre, NDF and acid detergent fibre, ADF) analysis. Sample collection occurred up to 6 weeks from the slaughter date in order to evaluate the presence of a rising, falling or neutral plane of nutrition. Twenty representative 30 cm × 30 cm (900 cm2) quadrants were sampled across the paddocks in which the animals were grazed in the lead up to transportation (3 separate paddocks in total, recorded as paddock 1, 2 and 3 for inclusion within statistical analysis). Quadrants were cut from ground level, pooled and a fresh pasture weight recorded at the point of collection. On several occasions, pasture within some quadrants was deemed too short and sparse for animal grazing. This was noted and utilised as an indicator of pasture availability, with the number of quadrants containing pasture of desirable grazing length expressed as a percentage of total quadrant number. Pasture samples were then frozen at −20 °C until subsequent analysis.
rest period under commercial pre-slaughter conditions to allow for recovery from 4 h of transportation. 2. Materials and methods 2.1. Experimental design A total of 160 castrated male alpacas (23 ± 1 month of age), averaging a live weight (LW) of 62 kgs, were transported to slaughter over a 12 month period (January 2017 to December 2017). Animals were moved using a single axle tray truck fitted with a standard commercial stock crate (7.2 × 2.5 × 2.0 m, L × W × H) in two groups of 20 per season (summer, autumn, winter and spring), resulting in 2 replicates per season across the year. Animals were randomly allocated to a location within the stock crate, either a front or rear pen (2.4 × 2.5 × 2.0 m, L × W × H; n = 10 animals per pen), for 4 h transportation to a commercial camelid certified abattoir on the south coast of New South Wales (35.19°S, 150.26°E, elevation of 15 m). The truck, transportation route and driver were standardized for all consignment groups. The route comprised a mixture of sealed highway, unsealed gravel, residential areas and tight bends across the 4 h trip from farm to abattoir, a reflection of the current commercial transport route to slaughter. Immediately following transport, animals were allocated to one of two treatment groups with ad lib access to water:
2.3. Pasture analysis Prior to analysis, pooled samples from each collection week were freeze dried and ground to a 1 mm particle size. Sample analysis was performed in duplicate for analytical dry matter, neutral detergent fibre (NDF), acid detergent fibre (ADF) and crude protein (CP) following the official methods of analysis protocols (AOAC, 2005). The NDF and ADF analysis was performed as described by Van Soest (1963), modified for an automated Ankom 200 Fibre Analyser and F57 filter bags (A2000 ANKOM Technologies, New York, USA). Sample nitrogen (N) content was quantified by the Kjeldahl method (method 984.13; AOAC, 2005) using a Leco-428 Analyser (Michigan, USA) and the CP content then calculated using the conversion factor CP = N x 6.25 (McDonald, Edwards, Greenhalgh, & Morgan, 2002). Pasture metabolisable energy (ME) was determined from the fibre and nitrogen content of pasture using methods previously described by NSW Agriculture (1983) and Oddy, Robards, and Low (1983). Calculations were as follows:
1) Overnight (15 ± 1 h) lairage pre slaughter (n = 80) 2) Seven day rest period with access to feed pre slaughter (n = 80) In order to account for potential variation in transport stressors as a result of the separate within truck locations, animals were allocated to treatments in a way that ensured equal numbers from both the front and rear pens were assigned to each lairage treatment (n = 5 animals per pen directed to one of the two treatment groups). The 7-day rest period was selected to best align with commercial practice, and research in beef cattle where a 7 day rest period overcame adverse effects to meat quality following exposure to a stressor (Mcveigh et al., 1979; Warriss et al., 1984).
DDM% = 83.58–0.824 (ADF%) + 2.62 (N%)
2.2. On-farm
ME (MJ/kgDM) = 0.17 (DDM%)–2
Animals were randomly selected from a large commercial meat herd (approximately 600 head) on the southern tablelands of NSW (34.14°S, 149.27°E, elevation of 741 m) one day prior to each transportation day. A subsection of the larger herd was mustered into drafting yards with the use of an integrated laneway system and all-terrain vehicle. Animals were drafted through yards and into a forcing pen and race on the basis of good visual health, age requirements (23 ± 1 months), breed (Huacaya) and time off shears (> 4 weeks). Animals meeting these requirements were then moved individually into a crush (retraining stall) for the evaluation of LW and body condition score (BCS; 1 to 5 scale with 0.25 unit increments; Keinprecht et al., 2016). Radio frequency identification (RFID) tags were used to identify individuals and LW and BCS measurements recorded using Gallagher™ Weigh Scales and Livestock Manager TSi 2 Data Recorder technology (Gallagher Group Limited, Epping VIC, Australia). Animals were then held (18 ± 1 h) on pasture adjacent to yards until subsequent loading the following day, through the yards to which animals were accustomed. Animals were exposed to a temperate Australian climate on farm. Annual daily minimum/maximum temperatures for the district average 11/25, 6/19, 4/11 and 5/18 °C through summer, autumn, winter and spring respectively. The district from which animals were sourced experiences an average annual rainfall of 860 mm and relative humidity of 77% (ranging from 68 to 86%, on average, across the year; Bureau of Meteorology, 2019a). Average district temperature and humidity across the trial year remained within annual averages, with rainfall falling just below average (807 mm for 2017; Bureau of Meteorology, 2019a).
2.4. Lairage component Upon arrival at the abattoir, 5 animals from each truck pen were selected at random and placed into lairage (lairage; n = 10) at a density sufficient to meet Australian standards (0.32 to 0.58 m2 for livestock weighing 50 to 100 kg; Edge, 2009). Animals were provided with ad lib access to water for the duration of lairage. Undercover lairage pens were situated adjacent to forcing pens for the processing facility, approximately 50 m from the knocking box. The remainder of the animals were directed toward a holding paddock (averaging 0.23 acres) where they were held for 7 days prior to slaughter (rested; n = 10) with ad lib access to feed (coastal pasture and/or oaten hay) and water until being placed into lairage the afternoon prior to processing (15 ± 1 h pre slaughter). This was repeated for each of the 8 groups, generating 16 slaughter weeks across the year and two replicates within each season. The processing facility experiences a temperate climate with average daily minimum/maximum temperatures of 17/24, 14/21, 9/17 and 13/21 °C through summer, autumn, winter and spring respectively, average annual rainfall of 1096.9 mm and relative humidity of 70% (ranging from 60 to 80%, on average, across the year; Bureau of Meteorology, 2019b). Temperature, humidity and rainfall across the trial year (2017) reflected these annual averages (2017; Bureau of Meteorology, 2019b). 2
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(FLUOstar OPTIMA, BMG, Labtechnologies, Victoria, Australia) in order to calculate total glycogen concentration of each sample. Ultimate pH analysis was performed using methods outlined by De Brito et al. (2016). Briefly, 1 g of frozen aged sample was homogenised in an iodoacetate buffer (5 mM iodoacetate/150 mM KC; Dransfield, Etherington, & Taylor, 1992) and suspended in a water bath at 22 °C. Ultimate pH was determined as the average of duplicate measures using a temperature and pH meter (Model smartCHEMC-CP, TPS Ltd., Queensland, AUS) calibrated at 22 °C in pH 4.01 and 6.86 buffers.
2.5. Carcase processing The alpacas were slaughtered and dressed under commercial conditions, as previously outlined Smith et al. (2016). Briefly, a conventional captive bolt was used to render animals insensible, followed by exsanguination through severing of the jugular veins and carotid arteries. At this point blood from each animal was collected into prelabelled 10 mL BD lithium heparin vacutainers® (REF 367526, Becton Dickinson, Plymouth, UK) and placed on ice. Immediately following exsanguination, animals were immobilized to prevent excess kicking during carcase dressing procedures. Prior to entering chillers, a glycogen core sample was collected from the right side of each carcase in the caudal region of the longissimus lumborum (LL, shortloin section of the loin). Core samples were snap frozen in liquid nitrogen and stored at −80 °C prior to analysis.
2.8.2. Fresh colour A fresh surface was cut on LT samples 24 h post-mortem and allowed to bloom at chiller ambient temperature (6–7 °C) for 40 min, after which time the meat colour was measured using a Minolta Chroma (model CR400, Osaka, Japan). The chromameter was set to the L*, a*, b* system using illuminate D65, an observer angle of 2°, with an aperture size of 5.0 mm and a closed cone. The chromameter was calibrated using a standardized white tile prior to measurement, and three measurements were taken across the face of the LT for each sample.
2.6. Blood cortisol assay Blood samples were centrifuged for 15 min at 3500 rpm using a portable benchtop centrifuge (SkySpin™ CM-6MT, ELMI laboratory equipment, Riga, Latvia) 2 h post-collection to obtain blood plasma for the determination of cortisol concentration. Plasma was pipetted into a separate 5 mL sterile tube (SKU: P5016SL, TechnoPlas, SA, Australia) and stored at −20 °C until subsequent analysis. Plasma samples were thawed, prepared and cortisol concentration (μg/dL) determined using a commercially available radio-immunoassay kit (Coat-A-Count Cortisol RIA; Siemens Pty Ltd., Los Angeles, CA, USA).
2.8.3. Shear force Frozen samples were prepared and cooked for shear force analysis as described by Hopkins and Thompson (2001). Shear force blocks were randomly allocated to one of 8 cook batches. The allocation was constrained in such way that ensured equal representation from each slaughter week and each season across the batches. Shear force was measured as the average of 6 peak force recordings across each muscle block using a Lloyd (Model LRX, Lloyd instruments, Hampshire UK) texture analyser fitted with a Warner Bratzler shear v blade.
2.7. Sample collection and measurements After chilling for 24 h, carcases were weighed to obtain a cold carcase weight (CCW) and the pH and temperature of the LL was recorded. The pH and temperature were measured using a hand held pH meter with temperature compensation (WB-80, winTPS Pty. Ltd., Brisbane, AUS), a polypropylene spear-type gel electrode (Ionode IJ 44) and cylindrical stainless steel probe attachment. Carcases were then broken down for sample collection. The longissimus thoracis et lumborum was removed from the right hand side of each carcase, prepared into the longissimus thoracic (LT; rack section of the loin) and vacuum packaged for transport after a fresh colour measurement was performed on the LL at the 12th/13th rib. Samples were transported at an average temperature and humidity of 6.0 °C and 85.6%, respectively, for 3 h to a laboratory for sample preparation. Moving cranially along the LT from the 12th/13th rib, toward the 4th rib, approximately 90 g was removed for ageing and weighed for purge, followed by one 60 g sample for drip loss analysis. Drip loss sample preparation is outlined below and followed methods adapted by Logan, Bush, Biffin, Hopkins, and Smith (2019) for alpaca. The remaining muscle was diced, placed into 50 mL tubes and frozen at −20 °C for intramuscular fat (IMF) analysis. After 10 days ageing (3.0 °C and 83.3% humidity), the 90 g blocks were weighed to obtain post ageing weights and prepared into one 65 g block for shear force (SF) analysis and one 5 g sample for ultimate pH (pHu) assessment. Shear force and pHu samples were frozen at −20 °C until subsequent analysis.
2.8.4. Drip loss Drip loss was evaluated using the ‘EZ’ method and following the protocol adapted by Logan et al. (2019) for alpaca. The 60 g drip loss block was trimmed to 2.5 cm in length. From this, two core samples were cut parallel to the muscle fibre using a purpose built cylindrical (2.5 cm diameter) muscle corer. These samples were weighed to 3 decimal places and placed within specialised EZ drip loss containers. All samples were placed within a rack, in the same chiller for 48 h at an average temperature of 3.3 °C and average humidity of 83%. After 48 h, the residual drip was removed from samples with paper towel and samples were individually weighed to 3 decimal places to obtain postdrip weights. 2.8.5. Purge and cooking loss Purge was calculated from the pre and post age (10 d) weight of the 90 g aged LT sample, and expressed as a percentage of the pre-age weight. Cooking loss was calculated as a percentage of the pre-cook weight on all shear force blocks, using the pre-cook frozen weight and post cook weight as outlined by Hopkins and Thompson (2001). 2.8.6. Intramuscular fat (IMF) Prior to analysis, samples were freeze dried and ground using a FOSS Knifetech™1095 mill and stored (−20 °C) until analysis. The IMF analysis was conducted using methods described by Hopkins et al. (2014). In brief, 3 g of freeze dried and ground muscle sample was extracted with 85 mL hexane for 80 min, in a FOSS Soxtec 2050 machine. Samples were then removed, dried (30 min and 105 °C) and weighed.
2.8. Meat quality testing 2.8.1. Glycogen and ultimate pH For the determination of glycogen content, 1 g of frozen LL sample was incubated in 10 mL of Milli-Q water for 5 min at 100 °C, homogenised (two bursts of 15 s at 22,000 rpm) and then centrifuged (Model CPR, Beckman Instruments, CA, USA) for 15 min at 3500 rpm (De Brito et al., 2016). The supernatant from each sample was plated in duplicate and compared to glycogen standards using the colorimetric protocol detailed by the commercial glycogen assay kit (Sigma-Aldrich, MO, USA). Absorbance was measured at 570 nm using a micro-plate reader
2.8.7. Statistical analysis Animal live weight, body condition score and muscle IMF were analysed separately using Linear Mixed Model (LMM) analysis in Genstat 18th edition (VSN International Ltd., Hertfordshire, UK) with fixed terms for season (summer, autumn, winter, spring) and trip number (1 to 8). The model included animal ID as a random term. For the analysis of pasture quality, individual traits (ME, CP, DDM, 3
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minimal detectable assay level of 0.2 μg/dL.
NDF, ADF and availability) were investigated through separate LMMs. Fixed effects included season and trip number. The model contained a random term for paddock number (1, 2 or 3), as well as week number from slaughter (0, 3 or 6) nested within paddock number to account for the repeated measure. Multiple LMMs were generated for the analysis of meat quality traits including CCW, evaporative loss, fresh colour, glycogen, pHu, drip loss, purge, cooking loss and shear force, as well as plasma cortisol. Each trait was analysed individually and full models included fixed effects for constant + season + lairage treatment (direct vs rested) + trip number (1 to 8) + pen number (1 or 2) + an interaction term for season × lairage treatment. With the exception of muscle shear force, the season × lairage interaction term was dropped from all models on the basis of non-significance at the P < .05 level using a stepwise backward elimination. Trip number and pen number were also removed from the final model based on non-significance. For the analysis of evaporative loss, CCW was added to the model as a covariate. Random terms for all models included carcase and slaughter number. Additional random terms for batch number and test date were added to the plasma cortisol, pHu, shear force and cooking loss models. Chiller temperature was included as a random term within the CCW, evaporative loss, drip loss and purge models. Model based predicted means, standard errors, P–values and LSDs were extracted from all LMMs for reporting.
3.4. Carcase traits Cold carcase weights were lowest in spring, while being statistically similar to winter weights, and highest in autumn (Table 2). There was a significant relationship between CCWs and evaporative loss. There was no variation in carcase evaporative loss across season (Table 2) or between lairage treatments throughout the year (3.7 ± 0.22 and 3.3 ± 0.22 for direct and rested respectively). 3.5. Meat quality testing 3.5.1. Glycogen and pH Within the current study, glycogen was lower (P = .008) in muscles of animals slaughtered in autumn and winter (Table 2). Glycogen levels varied significantly between direct and rested animals, with rested animals exhibiting muscle glycogen content of 6.6 mmol/kg lower, on average, than animals sent direct (at 42.4 and 49.0 mmol/kg respectively). There was no effect of season on LL pHu (Table 2). Likewise pHu was unaffected by resting treatments, averaging 5.6 ( ± 0.05) across the year and resting groups.
3. Results
3.5.2. Fresh colour Alpaca LT fresh colour did not change across season or as a result of resting, with the exception of decreased (P = .007) redness in spring. Fresh colour parameters averaged across season and resting period were 39.4 ( ± 1.13), 15.7 ( ± 0.71), 7.7 ( ± 0.33) for L* (lightness), a* (redness) and b* (yellowness) respectively.
3.1. Pasture analysis Pasture availability (indicated by the percentage of grass of desirable grazing length) and quality varied across the year (Table 1). Spring pasture was of highest (P < .001) quality as judged by CP, ME and DDM, and winter pasture of lowest (P < .001) availability, while summer and autumn pastures had similar quality and pasture availability.
3.5.3. Shear force and intramuscular fat (IMF) There was an interaction between season and resting treatment (P = .032). The effect was such that SF values for muscle of animals sent direct to slaughter in any season, with the exception of autumn, were lower than product from rested animals (Fig. 1). Longissimus thoracis IMF did not change (P = .11; Table 2) across the year or between consignment groups. Intramuscular fat averaged 1.3 ( ± 0.08) % across seasons.
3.2. On-farm Animal live weight averaged 61.6 ± 0.07 kg across the year, ranging from an average of 57.8 ± 1.59 kg (spring) to 64.1 ± 1.59 kg (autumn). With the exception of transport group 6 (winter; 54.0 ± 2.25 kg), animal live weight did not vary across trip groups. Body condition score also did not vary across trips or season, with animals retaining an average BCS of 2.75 ± 0.03 across the year. 3.3. Blood cortisol
3.5.4. Drip loss Drip loss was higher in the summer (P = .026) compared to other seasons (Table 2). The resting treatment also tended (P = .055) to increase drip loss percentage, averaging 2.5 ± 0.15% while muscle from animals sent direct to slaughter averaged 2.1 ± 0.15%.
Blood plasma cortisol levels did not vary across season or resting treatments (P = .61 and .11 respectively). Plasma cortisol, averaged across season and lairage treatments was 1.05 μg/dL at the point of slaughter. A high number (51 out of 160) of samples fell below the
3.5.5. Purge and cooking loss Purge loss was greater in the summer than in the other seasons (Table 2). Product from animals sent direct to slaughter lost significantly less (P = .02) moisture than animals that were rested. There
Table 1 Predicted means ± standard error across season for pasture qualitative traits. Traits include; sample size (n), dry matter (DM), digestible dry matter (DDM), desirable grazing length (i.e. of a length that can be physically grazed by the animal; average % across quadrants), crude protein (CP), metabolisable energy (ME), acid detergent fibre (ADF) and neutral detergent fibre (NDF). Means are averaged across trip group, collection week and paddock number. Trait DM (%) DDM (%) Grass of desirable grazing length (%) CP (%) ME (MJ/kg DM) ADF (%) NDF (%)
Winter (n = 6)
Spring (n = 6)
b
30 71 88 20 10 25 45
43 ± 12.2 62 ± 1.2b 60 ± 7.1b 18 ± 0.8a 9 ± 0.2b 36 ± 1.3b 52 ± 1.4b
± ± ± ± ± ± ±
ab
14.6 1.2a 7.3a 0.8a 0.2a 1.3a 1.4a
Summer (n = 5) c
66 ± 12.3 52 ± 1.4c 100 ± 7.7a 8 ± 1.0b 7 ± 0.2c 42 ± 1.5c 65 ± 1.6c
Autumn (n = 6) 72 ± 11.1c 50 ± 1.2c 96 ± 6.9a 8 ± 0.8b 6 ± 0.2c 46 ± 1.3c 67 ± 1.4c
Significant differences between means denoted by superscripts. All superscripts were generated on an individual trait by season level. Superscripts are not applicable to means in different rows. 4
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Table 2 Sample size (n) and predicted means ± standard error across seasons for alpaca cold carcase weight (CCW), evaporative loss, ultimate pH (pHu), fresh colour (lightness, L*; redness, a* and; yellowness, b*), intramuscular fat (IMF), drip loss, purge, and cooking loss in the alpaca longissimus thoracis. Trait
Winter (n = 40)
Spring (n = 40)
Summer (n = 40)
Autumn (n = 40)
CCW (kg) Evaporative loss (%) Glycogen (mmol/kg) pHu Fresh colour L* a* b* IMF (%) Drip loss (%) Purge (%) Cooking loss (%)
32.0 ± 0.79ab 3.6 ± 0.31a 42.8 ± 2.77ab 5.6 ± 0.04a
30.3 ± 0.79a 3.2 ± 0.31a 52.9 ± 2.77a 5.5 ± 0.05a
33.1 ± 0.79bc 3.1 ± 0.31a 49.9 ± 2.77a 5.5 ± 0.05a
34.5 ± 0.79c 3.9 ± 0.31a 37.1 ± 2.77b 5.6 ± 0.05a
38.4 ± 0.67a 15.9 ± 0.68a 7.2 ± 0.45a 1.02 ± 0.16a 2.2 ± 0.21a 7.7 ± 0.38b 21.9 ± 0.51a
40.5 ± 0.78a 12.6 ± 0.79b 8.0 ± 0.53a 1.75 ± 0.16a 2.3 ± 0.21a 8.6 ± 0.38bc 20.6 ± 0.51a
40.1 ± 0.67a 17.1 ± 0.68a 8.1 ± 0.45a 1.21 ± 0.16a 2.9 ± 0.21b 9.3 ± 0.38c 20.6 ± 0.51a
38.6 ± 0.67a 17.1 ± 0.68a 7.7 ± 0.45a 1.18 ± 0.16a 1.8 ± 0.21a 6.5 ± 0.38a 20.4 ± 0.51a
Significant differences between means denoted by superscripts. All superscripts were generated on an individual trait by season level. Superscripts are not applicable to means in different rows.
90
78.4a
80
Shear force (N)
70
65.6bc
73.2ab 65.5bc
57.1c
60
requirements were being met across all seasons. Furthermore, this may explain why the seasonal variation in muscle glycogen content was only minimal, despite fluctuations in feed quality and availability under the same transportation and lairage stressors. The variation in CCW across season can be aligned to animal LW differences, with LW and CCW both highest in autumn and lowest in spring. However, animal LW and CCW trends did not tend to follow increases or decreases in pasture quality. Given that animal BCS remained constant across consignment groups, these differences in weight may simply reflect the variation in animal frame size. For future research, the evaluation of animal frame scores prior to transportation may be advantageous in explaining animal and carcase weight variation when weight changes are not supported by differences in BCS. Evaporative loss percentages ranged from 3 to 4% of the initial hot carcase weight across the year which is in line with past alpaca research (Smith et al., 2015) and is toward the higher end of that observed for beef and lamb (1–3%; James & James, 2002). This is to be expected given the lean nature of alpaca carcases when compared to beef and lamb. There was a significant negative relationship between CCW and evaporative loss, with reduced evaporative loss at greater carcase weights. For every kg increase in CCW across the sampled range, evaporative loss was reduced by 0.06 units, resulting in an evaporative loss of 3.2% at a CCW of 38–40 kg, down from 3.8% at CCW of 28–30 kg. These results indicate an advantage to slaughtering alpacas at heavier weights in order to minimise carcase moisture loss. Glycogen levels varied significantly between direct and rested animals, with rested animals exhibiting lower muscle glycogen content. This could have resulted from increased stressors within the novel resting environment, as well as the change in nutrition from the southern tablelands to the south coast across the year. As plasma cortisol levels were low and did not vary between resting groups at the point of slaughter, glycogen differences more likely reflect the changing nutritional base and a reduced feed intake through the resting period (Ferguson, Daly, Gardner, & Tume, 2008). Autumn values for muscle glycogen within the current study are the lowest reported to date for alpacas managed under Australian conditions, at 37 ( ± 2.8) mmol/kg, with past research reporting values of 45.5 mmol/kg (Biffin et al., 2018) and 73.8 mmol/kg (Smith et al. 2017). These values remain well below that reported as potentially limiting to beef and lamb pH decline (Pethick & Rowe, 1996; Warriss, 1990). Biffin et al. (2018) indicated that a glycogen concentration beyond the lower threshold of 45 mmol/kg reported for other red meat species, will still result in a desirable pHu within alpaca. The current study supports this notion with an average pHu of 5.6 achieved within a glycogen concentration range of 37 mmol/kg to 53 mmol/kg. Furthermore, there were no changes to pHu across the year or due to resting treatments within the current study despite significant variation in
73.0ab 64.0bc 58.2c
50
Direct
40
Rested
30 20 10 0 Winter
Spring
Summer
Autumn
Fig. 1. Shear force values within the alpaca longissimus thoracis across season and lairage treatments (n = 20). Significant differences between means denoted by superscripts.
was no seasonal effect (P = .22) on cooking loss percentage (Table 2). Product from rested animals tended to have higher cooking loss than product from animals sent direct (21.4 ± 0.36% and 20.3 ± 0.36% respectively). 4. Discussion Pasture growth followed a traditional annual trend where summer and autumn pastures were of higher fibre content and lower digestible dry matter (DDM; though ample availability). This was followed by pasture availability dropping off toward the end of autumn and increasing again through spring (Table 1). Spring pastures exhibited the highest CP (%), ME (MJ/kg DM) and DDM (%) at the same level of availability provided through summer and spring. This aids in explaining the slightly greater muscle glycogen content exhibited by animals processed through spring. Importantly, it should be noted that despite significant variation in quality across seasons, nutrient availability throughout the year still met the maintenance requirements for 62 kg male alpacas, > 12 months old (~6.74 MJ ME/day, 8% - 10% CP and 0.6–1.1 kg daily DMI depending on feed quality) (Cebra, Anderson, Tibary, Saun, & Johnson, 2014; National Research Council, 2007; San Martin & Bryant, 1989). When considering animal activity level during grazing and the fibre content of pastures through summer and into autumn, nutrient intake may have been limited in these seasons given that ME and CP fell toward the lower end of maintenance requirements. However, animal LW was greater through autumn and lowest in spring on the higher quality pasture. This, combined with the lack of observed variation in animal BCS across season, indicates that nutritional 5
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consignment groups in future may aid in explaining some of this variation. Resting alpacas for 7 days pre-slaughter had a negative effect on meat quality, with reduced muscle glycogen content and tenderness. Moisture loss in the form of drip and purge was greater for rested animals when compared to product of animals sent direct to slaughter. Therefore, there is no advantage to resting animals for 7 days post transport on alpaca meat quality.
glycogen content across season and between resting groups. Therefore, these findings further support that of Biffin et al. (2018), that a glycogen concentration of approximately 45 to 46 mmol/kg is not limiting to pH decline in alpaca and is sufficient to meet a desired pHu of 5.5 to 5.6 (Biffin et al., 2018; Smith, Bush, van de Ven, Hall, et al., 2017). Alpaca fresh colour within the current study fell toward the higher end of the spectrum for L*, a* and b* when compared to previously reported values for non-electrically stimulated alpaca carcases (Biffin et al., 2019), yet remained below that reported for all colour parameters in lamb (Khliji, van de Ven, Lamb, Lanza, & Hopkins, 2010). Redness (a*) values in spring were lower than in any other season. It is possible that this change reflected glycogen levels being highest through spring. Immonen, Ruusunen, and Puolanne (2000) indicated that as residual glycogen concentration increased within beef longissimus, redness values decreased. However, glycogen differences within the current study were not as great as that observed by Immonen et al. (2000). Further research would be required to determine if this difference in redness relates to season and glycogen availability or more so genetic variation between consignment groups. The interaction between seasonality and resting treatments influenced muscle SF, such that within each season excluding autumn, resting negatively impacted product tenderness (Fig. 1). There was a trend toward improved SF with resting in autumn. However autumn resting values did not differ significantly from those of animals sent direct to slaughter, indicating that despite season, resting will tend to negatively affect muscle SF in alpaca's which is an important finding. Further work to explain the reason for this finding could be warranted, but from a practical perspective it provides a clear message to alpaca processors that to maximize tenderness alpacas should not be exposed to lengthy lairage periods. The seasonality of alpaca moisture loss, characterized in the current study by elevated spring and summer DL % and purge %, as well as increased DL % and purge % when resting animals, may reflect variation in animal hydration or events occurring early in post-mortem chilling. Muscle pH is known to have a negative correlation with pork drip loss as a greater amount of water will be bound within meat fibres at a higher pH (Hertog-Meischke, van Laack, & Smulders, 1997; Prevolnik, Čandek-Potokar, Novič, & Škorjanc, 2009). However, pHu within the current study did not vary across season or resting treatments. Further research is required to fully understand the underlying mechanism for these moisture loss findings. At the commercial level, the increases in product moisture loss during spring and summer, and as a result of resting, would result in reduced value on a $/kg basis. Intramuscular fat averaged 1.3 ( ± 0.08) % across seasons, which is higher than values previously reported for Australian alpacas (0.58–0.66%; Smith, Bush, van de Ven, Hall, et al., 2017; Smith et al., 2017). However, it is evident that alpaca IMF remains well below the IMF % reported for other red meat species, with grass fed beef reported to contain on average 5% IMF (Scollan et al., 2006) and lamb 4–5% (Hopkins, Hegarty, Walker, & Pethick, 2006). The current study demonstrates that despite the variation in nutritional base between consignment groups, product IMF did not change. This indicates that there may be a significant genetic influence over animal to animal and consignment group variation in IMF %.
Declaration of Competing Interest The authors acknowledge there is no conflict of interest. Acknowledgments This project was funded by AgriFutures Australia (PRJ-010045) and Illawarra Prime Alpaca. The authors would like to thank Mr. Matthew Kerr, NSW DPI, and Miss Bridgette Logan, the University of Sydney, for their immeasurable assistance across the sampling year; the staff of Milton district meats for their time; and all volunteers that gave up their time to assist with sample collections. References AOAC (2005). Offical Methods of Analysis (18 ed.). Gaithersburg, Maryland, USA: Association of Official Analytical Chemists (AOAC). Biffin, T., Smith, M., Bush, R., Collins, D., & Hopkins, D. (2018). The effect of combining tenderstretching and electrical stimulation on alpaca (Vicugna pacos) meat tenderness and eating quality. Meat Science, 145, 127–136. https://doi.org/10.1016/j.meatsci. 2018.06.002. Biffin, T., Smith, M., Bush, R., Collins, D., & Hopkins, D. (2019). The effect of electrical stimulation and tenderstretching on colour and oxidation traits of alpaca (Vicunga pacos) meat. Meat Science, 156, 125–130. https://doi.org/10.1016/j.meatsci.2019. 05.026. Bureau of Meteorology (2019a). Climate statistics for Australian locations (site 070025). Australian Government Bureau of Meteorology. Retrieved 19/08/2019, from http:// www.bom.gov.au/climate/averages/tables/cw_070025.shtml. Bureau of Meteorology (2019b). Climate statistics for Australian locations (site 069138). Australian Government Bureau of Meteorology. Retrieved 19/08/2019, from http:// www.bom.gov.au/climate/averages/tables/cw_069138.shtml. Cebra, C., Anderson, D. E., Tibary, A., Van Saun, R. J., & Johnson, L. W. (2014). Llama and alpaca care: Medicine, surgery, reproduction, nutrition, and herd health (1st ed.). (St. Louis: MO, Chapter 9). Cheng, Q., & Sun, D. (2008). Factors affecting the water holding capacity of red meat products: A review of recent research advances. Critical Reviews in Food Science and Nutrition, 48, 137–159. https://doi.org/10.1080/10408390601177647. De Brito, G., McGrath, S., Holman, B., Friend, M., Fowler, S., van de Ven, R., & Hopkins, D. (2016). The effect of forage type on lamb carcass traits, meat quality and sensory traits. Meat Science, 119, 95–101. https://doi.org/10.1016/j.meatsci.2016.04.030. Dransfield, E., Etherington, D. J., & Taylor, M. A. J. (1992). Modelling post-mortem tenderisation: 11. Enzyme changes during storage of electrically stimulated and nonstimulated beef. Meat Science, 31, 75–84. Edge, M. (2009). Industry animal welfare standards for livestock processing establishments preparing meat for human consumption. Meat and Livestock Australia Ltd.. Retrieved 26/08/2019 from https://aawcs.com.au/wp-content/uploads/2019/03/33024_ MLA_ind_Welfare_V4.pdf. Ferguson, D., Daly, B., Gardner, G., & Tume, R. (2008). Effect of glycogen concentration and form on the response to electrical stimulation and rate of post-mortem glycolysis in ovine muscle. Meat Science, 78, 202–210. https://doi.org/10.1016/j.meatsci.2007. 06.003. Hertog-Meischke, M. J. A., van Laack, R. J. L. M., & Smulders, F. J. M. (1997). The waterholding capacity of fresh meat. Veterinary Quarterly, 19(4), 175–181. Hopkins, D. L., Clayton, E. H., Lamb, T. A., van de Ven, R. J., Refshauge, G., Kerr, M. J., & Ponnampalam, E. N. (2014). The impact of supplementing lambs with algae on growth, meat traits and oxidative status. Meat Science, 98, 135–141. https://doi.org/ 10.1016/j.meatsci.2014.05.016. Hopkins, D., Hegarty, R., Walker, P., & Pethick, D. (2006). Relationship between animal age, intramuscular fat, cooking loss, pH, shear force and eating quality of aged meat from sheep. Australian Journal of Experimental Agriculture, 46, 879–884. https://doi. org/10.1071/EA05311. Hopkins, D., & Thompson, J. (2001). The relationship between tenderness, proteolysis, muscle contraction and dissociation of actomyosin. Meat Science, 57, 1–12. https:// doi.org/10.1016/S0309-1740(00)00065–6. Immonen, K., Ruusunen, M., & Puolanne, E. (2000). Some effects of residual glycogen concentration on the physical and sensory quality of normal pH beef. Meat Science, 55, 33–38. https://doi.org/10.1016/S0309-1740(99)00122-9. James, S. J., & James, C. (2002). Meat refrigeration. Cambridge: Woodhead Publishing Ltd (Chapter 5).
5. Conclusion Alpaca meat quality varied across the year, with increased moisture loss through summer and spring and a trend toward improved summer tenderness. However, this variation did not reflect nutritional quality or changes to muscle glycogen content. Supporting past literature, it can be concluded that low muscle glycogen content (of ~45 mmol/kg) is not limiting to alpaca pHu. It is possible that additional biochemical and genetic processes not considered within the scope of the current research are contributing to alpaca meat quality variation across seasons. Research that incorporates the genetic evaluation of different 6
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