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Evaluation and predictive modeling the effects of spice extracts on raw chicken meat stored at different temperatures
Journal of Food Engineering 166 (2015) 29–37
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Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng
Evaluation and predictive modeling the effects of spice extracts on raw chicken meat stored at different temperatures K. Radha krishnan a, S. Babuskin a, P. Azhagu Saravana Babu a, M. Sivarajan b, M. Sukumar a,⇑ a b
Centre for Biotechnology, A.C. Tech., Anna University, Chennai 25, India Chemical Engineering Division, Central Leather Research Institute, Chennai 20, India
a r t i c l e
i n f o
Article history: Received 5 March 2015 Received in revised form 13 May 2015 Accepted 14 May 2015 Available online 15 May 2015 Keywords: Modeling Raw meat Shelf life Gompertz model Predictive microbiology Microbial growth
a b s t r a c t In the present study, the anti-microbial and anti-oxidant effects of Syzygium aromaticum (SA), Cinnamomum cassia (CC) and Origanum vulgare (OV) on the shelf life of raw chicken meat stored at different temperatures (4, 10, 15 and 20 °C ± 1) were studied. Gompertz model was used to model the microbial growth using the data from microbial analysis of meat samples. Arrhenius equation was applied to understand the effect of storage temperature on the specific growth rate (l) and lag phase duration. Highest lmax and LPD (lag phase duration) values were obtained for Enterobacteriaceae in T-SA (Treatment with 1% S. aromaticum extract) samples stored at 4 °C. The lmax values of T-SA–CC–OV (Treatment with 0.33% S. aromaticum extract + 0.33% C. cassia extract + 0.33% O. vulgare extract) samples were found to be low at all the tested temperatures and especially at 4 °C with better color values and lower TBARS (Thiobarbituric acid reactive substances) values than the other samples. The best preservative effects were achieved with the combination of spice extracts. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Meat is a very popular food commodity around the world due to its low cost of production, low fat content, high nutritional value and distinct flavor (Barbut, 2002; Patsias et al., 2008). The diverse nutrient composition of meat makes it an ideal environment for the growth and propagation of meat spoilage micro-organisms and common food-borne pathogens (Zhou et al., 2010). It is therefore essential that adequate preservation technologies are needed to extend the shelf life of perishable meat products which is a major concern for the meat industries (Wang et al., 2004). Lipid oxidation and microbial growth during storage can be reduced by applying antioxidant and antimicrobial agents to the meat products, leading to a retardation of spoilage, an extension of shelf-life, and a maintenance of quality and safety (Devatkal and Naveena, 2010). Therefore, there has been increasing interest in alternative additives from natural sources (Sebranek et al., 2005) which has gradually provided impetus to eliminating synthetic preservatives in food (McCarthy et al., 2001). Naturally occurring antimicrobial compounds have good potential to be applied as food preservatives. Essential oils and other extracts from plants, herbs and spices and some of their constituents, have shown antimicrobial activity against different ⇑ Corresponding author. E-mail address: [email protected] (M. Sukumar). http://dx.doi.org/10.1016/j.jfoodeng.2015.05.021 0260-8774/Ó 2015 Elsevier Ltd. All rights reserved.
food pathogens and spoilage microorganisms (Bakkali et al., 2008; Burt, 2004; Holley and Patel, 2005). Spices have been employed since ancient times as flavoring and preservative agents for food, but the research on the spice extracts has been initiated in the last decade for their compounds exerting antimicrobial and antioxidant activities (Sagdic et al., 2003). The clove, cinnamon and oregano are considered as the most common spices and herbs with strong antimicrobial activity. Their essential oils containing chemical compounds such as eugenol, cinnamaldehyde and carvacrol are identified as the major chemical components responsible for exerting antimicrobial activity (Wei and Shibamoto, 2010; El-Massry et al., 2008; Kordali et al., 2008; Zawirska-Wojtasiak and Wasowicz, 2009). Some studies reported that there is a highly positive linear relationship between antioxidant activity, antibacterial activity and total phenolic content in some spices and herbs (Shan et al., 2007, 2005). Determination of shelf life with traditional microbiological tests is expensive and time-consuming. An alternative is the concept of predictive microbiology, which uses mathematical models to predict the bacterial growth as a function of environmental factors such as temperature, pH and aw (Cayre et al., 2005; McMeekin et al., 1987). It allows us to quantify and to predict the rate of growth of microorganisms under environmental conditions with the intention of assuring the hygienic quality of food, thus determining its storage life. Mathematical models fulfill the research gap on the inactivation kinetics of natural antimicrobial extracts
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
on microorganisms inoculated in food products. One of the more frequently used models is that of Gompertz with parameters such as lag phase duration (LPD), maximum population density (MPD), growth rate (l) and the activation energy (El). The objective of the present work was to model the shelf life of raw chicken meat based on the microbiological analysis and to determine the effect of temperature on the kinetic parameters such as LPD, MPD, l and El. 2. Materials and methods 2.1. Materials Dried spices of clove (Syzygium aromaticum), cinnamon (Cinnamomum cassia) and oregano (Origanum vulgare) were obtained from Nuts and Spices Super market, Chennai, India. 2.2. Chemicals and reagents Butylated hydroxytoluene (BHT), thiobarbituric acid (TBA) and trichloroacetic acid (TCA) were supplied by Sigma-Aldrich Chemicals, Germany. Methanol, Plate Count Agar (PCA), Violet Red Bile Glucose (VRBG) agar, Buffered Peptone Water, de Man Rogosa and Sharpe (MRS) agar was purchased from Merck, Darmstadt, Germany. 2.3. Preparation of extracts Spices were grounded using mixer grinder (Preethi ChefPro model, Indian make) and sieved well using vertical vibratory sieve shaker (Labortechnik Gmbh, Ilmenau) for 20 min in order to obtain particles of same size. Extraction was performed in soxhlet extractor by contacting solvent and sample at a constant temperature, which could ensure solvent reflux (78–80 °C). Samples of 50 g were placed into a round-bottomed flask filled with 2500 mL ethanol (solid–solvent ratio of 1:50) connected at the top to a cooler and extraction was carried out for 5–6 h. The extracts were filtered through Whatman filter paper No. 1 (Whatman International, Ltd.,) and concentrated using a rotary evaporator. Finally spice extracts were dissolved in water in the ratio of 1:10 (w/v) for further studies. 2.4. Application of spice extracts in meat samples Raw chicken breast meat (70.1 g/100 g moisture, 22.9 g/100 g protein, 2.1 g/100 g fat content) were purchased from local meat market (Chennai, Tamil Nadu, India). Meat samples were transferred through insulated polystyrene boxes to the laboratory within 1 h of production. Fresh meat samples were obtained separately for each of the replications. The meat samples were cut into pieces of 25 g, thickness 0.8 cm and treatment was performed as follows: 1. NC (negative control – without any additive), 2. PC (positive control with 0.02% BHA – Butylated hydroxyanisole), 3. T-SA (Treatment with 1% S. aromaticum extract), 4. T-CC (Treatment with 1% C. cassia extract), 5. T-OV (Treatment with 1% O. vulgare extract), 6. T-SA–CC (Treatment with 0.5% S. aromaticum extract + 0.5% C. cassia extract), 7. T-SA–OV (Treatment with 0.5% S. aromaticum extract + 0.5% O. vulgare extract), 8. T-CC–OV (Treatment with 0.5% C. cassia extract + 0.5% O. vulgare extract), 9. T-SA–CC–OV (Treatment with 0.33% S. aromaticum extract + 0.33% C. cassia extract + 0.33% O. vulgare extract). Meat samples were stored at 4, 10, 15 and 20 °C ± 1 and microbial counts, color values and TBARS (Thiobarbituric acid reactive substances) values were determined during the storage period. Samples stored at 4 °C were analyzed after 1, 2, 4, 6, 10, 15 and 20 days; those stored at
10 °C after, 1, 2, 4, 6 and 10 days; the ones at 15 °C after 1, 2, 4, and 6 days of storage and samples stored at 20 °C were analyzed after 1, 2 and 4 days. At these two last temperatures analyzes were carried out for fewer days because of the greater rate of decay of the meat. All the analyzes were performed in triplicate. 2.5. Microbial analysis For the microbiological assays, a representative of 10 g meat sample was withdrawn and homogenized (Model PT-MR-2100, Kinematica AG, Switzerland) aseptically using 90 mL 0.1% peptone water and serial dilutions were made using 0.1% sterile peptone water. Total Viable Count (TVC) was determined on PCA agar by incubating plates at 37 °C for 24 h. Lactic Acid Bacteria (LAB) were counted on MRS Agar plates and incubated at 30 °C for 72 h. Total Enterobacteriaceae were counted on VRBG plates and incubated at 37 °C for 24 h. After incubation, plates having 25–250 colonyforming units (CFU) were counted and the results expressed in logarithmic of colony-forming units per gram of meat (log CFU/g). 2.6. Mathematical modeling of bacterial growth Modified Gompertz equation was used to generate the bacterial growth curves by data fitting (Zwietering et al., 1991) and Eq. (1)
Table 1 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of Total Viable Count (TVC), Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 4 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.659 0.470 0.609
7.33 6.81 7.18
8.96 7.95 7.15
0.96 0.97 0.95
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.579 0.380 0.515
7.27 6.72 7.06
8.68 7.59 6.78
0.94 0.95 0.98
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
0.306 0.239 0.465
7.02 6.51 6.99
7.61 6.95 6.57
0.97 0.98 0.95
T-CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.389 0.251 0.391
7.11 6.56 6.88
7.95 7.01 6.24
0.97 0.96 0.98
T-OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.364 0.242 0.454
7.09 6.54 6.98
7.85 6.97 6.52
0.99 0.93 0.95
T-SA–CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.283 0.192 0.413
7.00 6.47 6.91
7.49 6.72 6.34
0.98 0.95 0.97
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.352 0.206 0.400
7.07 6.49 6.89
7.81 6.79 6.28
0.94 0.96 0.97
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.390 0.192 0.360
7.11 6.47 6.82
7.96 6.75 6.09
0.98 0.97 0.98
T-SA–CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.251 0.137 0.350
6.96 6.36 6.79
7.35 6.42 6.04
0.97 0.97 0.98
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37 Table 2 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of Total Viable Count (TVC), Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 10 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.779 0.710 1.249
4.56 4.36 4.63
8.62 7.81 7.91
0.98 0.97 0.98
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.669 0.441 0.688
4.51 3.69 3.87
8.31 7.68 7.42
0.97 0.94 0.98
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
0.501 0.289 0.530
4.43 3.50 3.69
7.81 7.02 6.79
0.98 0.95 0.97
T-CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.548 0.314 0.552
4.45 3.54 3.72
7.95 7.15 6.88
0.95 0.97 0.96
T-OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.515 0.331 0.560
4.44 3.56 3.73
7.85 7.21 6.91
0.96 0.95 0.93
Total viable count Lactic acid bacteria Enterobacteriaceae
0.453 0.231 0.449
4.40 3.41 3.57
7.66 6.74 6.45
0.99 0.96 0.97
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.460 0.254 0.456
4.41 3.45 3.59
7.68 6.85 6.48
0.98 0.95 0.96
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.501 0.268 0.486
4.43 3.47 3.63
7.81 6.92 6.61
0.99 0.95 0.96
Total viable count Lactic acid bacteria Enterobacteriaceae
0.410 0.181 0.440
4.38 3.33 3.55
7.52 6.48 6.41
0.98 0.99 0.96
T-SA–CC
T-SA–CC–OV
ln l ¼ ln A El =RT
ð3Þ
El values for each type of bacteria were calculated by plotting the values of ln l vs. 1/T. Zwietering et al. (1991) modified the extended Ratkowsky model to describe the lag time as a function of temperature. The effect of temperature on LPD reflects how the adaptation period of microorganisms to their new environment changes with temperature. In this regard, the adaptation rate can be considered as the reciprocal of LPD (Li and Torres, 1993), and was modeled using an Arrhenius type model
1=LPD ¼ D expðE1=LPD =RTÞ
ð4Þ 1
where D is a pre exponential factor (days ), E1/LPD is the activation energy (kJ mol1), R is the gas constant 8.31 (J (K mol)1) and T is the temperature in (K). The activation energy E1/LPD can be considered as the sensitivity of the microorganisms to temperature change
lnð1=LPDÞ ¼ ln D ðE1=LPD =RTÞ
ð5Þ
2.7. Color values The color of raw chicken patties was evaluated using a HunterLab UltraScan VIS color spectrophotometer (Hunter
Table 3 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of Total Viable Count (TVC), Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 15 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.595 1.182 2.059
2.32 2.17 2.13
8.85 7.81 7.89
0.98 0.96 0.98
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.474 1.101 1.701
2.31 2.16 2.08
8.68 7.68 7.39
0.97 0.96 0.97
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
0.970 0.766 1.307
2.24 2.09 2.00
7.91 7.10 6.79
0.96 0.93 0.95
T-CC
has been used to estimate the response variables (lag phase duration, maximal growth rate and maximum population density).
Total viable count Lactic acid bacteria Enterobacteriaceae
1.031 0.793 1.363
2.25 2.10 2.02
8.01 7.15 6.88
0.98 0.97 0.97
T-OV
LPD t þ1 logðCFUÞ ¼ K þ D exp exp lmax 2:7182 A
Total viable count Lactic acid bacteria Enterobacteriaceae
1.019 0.827 1.381
2.24 2.11 2.02
7.99 7.21 6.91
0.99 0.98 0.97
T-SA–CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.793 0.579 1.107
2.21 2.05 1.96
7.61 6.74 6.45
0.99 0.96 0.97
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.856 0.634 1.124
2.22 2.06 1.96
7.72 6.85 6.48
0.98 0.96 0.97
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.940 0.670 1.200
2.24 2.07 1.98
7.86 6.92 6.61
0.96 0.96 0.98
T-SA–CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.726 0.453 1.018
2.20 2.01 1.93
7.49 6.48 6.29
0.96 0.97 0.97
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
ð1Þ where K is the initial bacterial count (log CFU/g); D is the increase in log CFU/g between time 0 and the maximum population density achieved at the stationary phase; lmax is the maximal growth rate (Dlog (CFU/g)/day); LPD is the lag phase duration (days); and t is the storage time (days). The maximum population density MPD (log (CFU g1)) is calculated by adding the values of K and A. The goodness of the fit was assessed by the R2 value. Arrhenius equation was applied to understand the effect of storage temperature on the specific growth rate (l),
l ¼ A expðEl =RTÞ
ð2Þ 1
1
where A is a pre exponential factor (log (CFU g ) days ), El is the activation energy (kJ mol1), R is the gas constant 8.31 (J (K mol)1) and T is the temperature (K). The sensitivity of the microorganisms to temperature change can be considered as the activation energy El and calculated using Eq. (3)
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
Table 4 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of total viable count, Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 20 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
2.050 1.705 2.987
1.05 0.93 0.99
8.56 7.79 7.77
0.96 0.97 0.97
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.875 1.567 2.707
1.04 0.92 0.97
8.39 7.64 7.51
0.98 0.98 0.97
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
1.267 1.144 2.109
1.00 0.88 0.92
7.74 7.15 6.91
0.96 0.98 0.97
T-CC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.215 1.193 2.016
1.00 0.89 0.91
7.68 7.21 6.81
0.99 0.98 0.98
T-OV
Total viable count Lactic acid bacteria Enterobacteriaceae
1.241 1.260 2.063
1.01 0.92 0.91
7.71 7.29 6.86
0.99 0.97 0.96
T-SA–CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.971 0.938 1.748
0.89 0.86 0.89
7.39 6.89 6.51
0.95 0.96 0.98
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
1.070 0.953 1.809
0.99 0.86 0.89
7.51 6.91 6.58
0.96 0.96 0.93
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
1.020 0.915 1.844
0.98 0.86 0.90
7.45 6.86 6.62
0.98 0.96 0.97
T-SA–CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.737 0.659 1.595
0.96 0.83 0.87
7.09 6.51 6.33
0.97 0.95 0.96
Associates Laboratory Inc., Reston, VA, USA). Color was described as L⁄ (lightness), a⁄ (redness), and b⁄ (yellowness) color space values. A Chroma meter was standardized with a standard white plate (L⁄ = 93.80, a⁄ = 0.3157 and b⁄ = 0.3319). Measurements were made perpendicular to the patty surface at five different locations per sample and mean values (L⁄, a⁄, and b⁄) from the samples were analyzed. From the measured values, hue (h⁄) and chroma (C⁄) were calculated as following (Mastromatteo et al., 2009):
Hue ¼
b a
Chroma ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 a2 þ b
ð6Þ
2.8. Thiobarbituric acid reactive substances (TBARS) value Meat samples were analyzed for Thiobarbituric acid reactive substances (TBARS) as per the method described by Du and Ahn (2002). Five grams of meat was homogenized with 15 mL of deionized distilled water. 1 mL of the meat homogenate was transferred to a test tube and 50 lL of butylated hydroxytoluene (7.2%) and 2 mL of thiobarbituric acid (TBA)–trichloroacetic acid (TCA) (15 mM TBA–15% TCA) were added. The mixture was vortexed and then incubated in a boiling water bath for 15 min to develop color. Then samples were subjected to cooling for 10 min, vortexed again, and centrifuged for 15 min at 2500g. The absorbance of the resulting supernatant solution was determined at 531 nm against a blank containing 1 mL of deionized water and 2 mL of TBA–TCA solution. The amount of TBARS was expressed as milligrams of malondialdehyde per kilogram of meat.
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
2.9. Statistical analysis The data were obtained from independent experiments with repetition, and the means were obtained from the triplicates. The data observed were subjected to analysis of variance (ANOVA) with significance levels of 0.05 using a statistical package (SYSTAT Inc. 1990, version 5.0, U.S.A.) for comparing the counts obtained from treated sample and its control for all the experiments.
Table 5 Application of Arrhenius model to evaluate the effect of temperature on lag phase duration and specific growth rate for total viable count, lactic acid bacteria and Enterobacteriaceae. Sample
E1 1/LPD (kJ/mol) Total viable count
R2
E1 1/LPD (kJ/mol) Lactic acid bacteria
R2
E1 1/LPD (kJ/mol) Enterobacteriaceae
R2
NC PC T-SA T-CC T-OV T-SA–CC T-SA–OV T-CC–OV T-SA–CC–OV
32.93 33.23 34.71 34.78 34.72 35.54 35.16 35.17 35.17
0.93 0.94 0.94 0.95 0.93 0.94 0.93 0.93 0.95
37.56 37.52 39.02 38.89 38.55 40.12 39.97 40.19 41.75
0.95 0.95 0.93 0.94 0.96 0.95 0.96 0.94 0.95
35.79 36.14 38.10 38.39 38.30 39.62 39.33 39.04 40.47
0.95 0.93 0.94 0.95 0.94 0.94 0.96 0.95 0.96
Sample
El1 (kJ/mol) Total viable count
R2
El1 (kJ/mol) Lactic acid bacteria
R2
El1 (kJ/mol) Enterobacteriaceae
R2
NC PC T-SA T-CC T-OV T-SA–CC T-SA–OV T-CC–OV T-SA-CC–OV
51.84 54.31 62.04 51.59 54.87 54.34 50.13 44.60 48.95
0.93 0.91 0.96 0.96 0.97 0.98 0.96 0.93 0.93
55.52 64.97 71.39 70.42 73.92 71.08 69.22 69.44 70.96
0.94 0.91 0.92 0.94 0.95 0.92 0.93 0.94 0.94
67.49 74.11 68.13 73.25 68.47 65.43 68.00 73.20 67.83
0.98 0.95 0.91 0.96 0.93 0.90 0.91 0.95 0.94
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37 Table 6 Color parameters of raw chicken meat samples stored at different temperatures (4, 10, 15 and 20 °C). Sample
Days
4 °C
10 °C
15 °C
20 °C
Hue
Chroma
Hue
Chroma
Hue
Chroma
Hue
Chroma
NC
0 1 2 4 6 10 15 20
1.68a,A 1.71a,A 1.75a,A 1.86a,A 1.92a,A 1.93a,A 1.94a,A 1.96a,A
16.92a,A 16.77a,A 16.56a,A 16.69b,A 16.05a,A 15.59c,A 15.72a,A 15.39a,A
1.67a,A 1.66a,A 1.73a,A 1.77a,B 1.81a,B 1.86a – –
17.02a,B 16.74a,A 16.72a,A 16.44a,B 16.19a,A 15.75a,A – –
1.69a,A 1.82b,B 1.79a,A 1.75b,B 1.88a,A – – –
16.83a,C 16.59a,B 15.60a,B 14.14a,C 14.71a,B – – –
1.68a,A 1.78a,B 1.69b,B 1.83a,A – – – –
16.87a,A 16.90b,C 15.70a,B 15.11a,D – – – –
PC
0 1 2 4 6 10 15 20
1.68a,A 1.75a,A 1.70b,A 1.89a,A 1.95a,A 1.98a,A 1.97a,A 2.01a,A
16.92a,A 16.82a,A 16.52a,A 16.29a,A 16.38b,A 15.84a,A 15.23a,A 15.06a,A
1.67a,A 1.70a,A 1.74b,A 1.70a,B 1.76a,B 1.88a,A – –
17.02a,B 16.63a,A 16.61a,A 16.48a,A 15.99a,B 15.60a,A – –
1.69a,A 1.74a,A 1.56c,B 1.84a,A 1.87a,A – – –
16.83a,C 16.36a,B 15.84a,B 14.92a,B 14.39a,C – – –
1.68a,A 1.75a,A 1.71b,A 1.90a,A – – – –
16.87a,A 16.19a,C 15.52a,C 14.82a,B – – – –
T-SA
0 1 2 4 6 10 15 20
1.68a,A 1.72a,A 1.74a,A 1.79a,A 1.80a,A 1.82a,A 1.89a,A 1.88a,A
16.93a,A 16.78a,A 16.70a,A 16.81b,A 16.69a,A 16.50a,A 16.28a,A 16.02a,A
1.67a,A 1.72a,A 1.70b,A 1.76a,A 1.76a,A 1.81a,A – –
17.02a,B 16.67a,A 16.84a,A 16.80a,A 16.54a,A 16.20a,B – –
1.69a,A 1.66a,A 1.69c,A 1.80a,A 1.80d,A – – –
16.83a,C 16.70a,A 16.11a,B 15.63a,B 15.18a,B – – –
1.68a,A 1.75a 1.68b,A 1.80a,A – – – –
16.87a,A 16.29a,B 15.46a,C 15.69b,B – – – –
T-CC
0 1 2 4 6 10 15 20
1.68a,A 1.74a,A 1.77a,A 1.69b,A 1.79a,A 1.87a,A 1.93a,A 1.97a,A
16.92a,A 16.85a,A 16.87a,A 16.93c,A 16.49a,A 16.68c,A 16.50a,A 16.30a,A
1.68a,A 1.72a,A 1.75a,A 1.72b,A 1.79a,A 1.81a,A – –
17.02a,B 16.89a,A 16.68a,A 16.66b,B 16.37a,A 15.89a,B – –
1.69a,A 1.70a,A 1.65e,B 1.77a,A 1.85a,A – – –
16.83a,C 16.39a,B 15.92a,B 15.47a,C 14.99a,B – – –
1.68a,A 1.79a,A 1.83a,A 1.74c,A – – – –
16.87a,A 16.30a,B 15.74a,B 15.24a,C – – – –
T-OV
0 1 2 4 6 10 15 20
1.68a,A 1.76a,A 1.80a,A 1.83a,A 1.80b,A 1.84a,A 1.93c,A 1.89a,A
16.92a,A 16.65b,A 16.80a,A 16.55a,A 16.55a,A 16.21a,A 15.90a,A 15.80a,A
1.67a,A 1.66a,A 1.70a,A 1.75a,A 1.82a,A 1.87a,A – –
17.02a,B 17.17c,B 16.93a,A 16.71a,A 16.21a,A 15.97a,A – –
1.69a,A 1.71a,A 1.75a,A 1.76a,A 1.81a,A – – –
16.83a,C 16.45a,C 16.06a,B 15.51a,B 15.03a,B – – –
1.68a,A 1.64d,A 1.76a,A 1.84a,A – – – –
16.87a,A 16.67a,C 15.05c,C 15.29a,B – – – –
T-SA–CC
0 1 2 4 6 10 15 20
1.68a,A 1.71a,A 1.74a,A 1.74a,A 1.69b,A 1.84a,A 1.85a,A 1.90a,A
16.92a,A 16.93a,A 16.97c,A 16.84a,A 16.82a,A 16.59a,A 16.40a,A 16.14a,A
1.67a,A 1.61c,A 1.68a,A 1.69a,A 1.76a,A 1.80a,A – –
17.02a,B 16.93a,A 16.95c,A 16.62a,A16.58a,A 16.32a,A – –
1.69a,A 1.71a,A 1.64c,A 1.77a,A 1.79a,A – – –
16.83a,C 16.44a,A 16.17a,B 15.64a,B 15.34a,B – – –
1.68a,A 1.70a,A 1.65d,A 1.77a,A – – – –
16.87a,A 15.94a,B 16.44d,C 15.68a,B – – – –
T-SA–OV
0 1 2 4 6 10 15 20
1.68a,A 1.67a,A 1.70a,A 1.77a,A 1.84a,A 1.84a,A 1.87a,A 1.90a,A
16.92a,A 17.01c,A 16.94a,A 16.93a,A 16.70a,A 16.42a,A 16.23a,A 16.03a,A
1.67a,A 1.67a,A 1.67a,A 1.72a,A 1.81a,A 1.82a,A – –
17.02a,B 17.04a,A 16.76a,A 16.42a,B 16.33a,B 16.08a,B – –
1.69a,A 1.74a,A 1.75a,A 1.81a,A 1.86a,A – – –
16.83a,C 16.50a,B 16.00a,B 15.55a,B 15.34a,C – – –
1.68a,A 1.74a,A 1.80a,A 1.81a,A – – – –
16.87a,A 16.35a,B 15.97a,B 15.67a,B – – – –
T-CC–OV
0 1 2 4 6 10 15 20
1.68a,A 1.71a,A 1.78a,A 1.81a,A 1.86a,A 1.87a,A 1.92a,A 1.92a,A
16.92a,A 17.00c,A 16.96a,A 16.92c,A 16.60a,A 16.34a,A 16.41d,A 16.11a,A
1.67a,A 1.75a,A 1.71b,A 1.74a,A 1.74a,A 1.80a,A – –
17.02a,B 16.98a,A 16.93a,A 16.81a,A 16.50a,A 16.12a,A – –
1.69a,A 1.70a,A 1.74a,A 1.76a,A 1.80a,A – – –
16.83a,C 16.53a,B 16.09a,B 15.62a,B 15.11a,B – – –
1.68a,A 1.73a,A 1.60e,B 1.80a,A – – – –
16.87a,A 16.60a,B 15.99a,B 15.55a,B – – – –
T-SA–CC–OV
0 1 2 4 6
1.68a,A 1.75b,A 1.73a,A 1.75a,A 1.68c,A
16.93a,A 16.89a,A 16.84a,A 17.05c,A 16.82a,A
1.67a,A 1.66a,A 1.67d,A 1.70a,A 1.73a,A
17.02a,B 17.09d,A 16.88a,A 16.57a,B 16.62a,A
1.69a,A 1.70a,A 1.63b,A 1.74a,A 1.78a,A
16.83a,C 16.49a,B 16.29a,B 15.93a,C 15.70a,B
1.68a,A 1.69a,A 1.72a,A 1.74a,A –
16.87a,A 16.12a,B 16.58a,B 15.90a,C –
(continued on next page)
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
Table 6 (continued) Sample
Days
10 15 20 a–c
4 °C
10 °C
15 °C
20 °C
Hue
Chroma
Hue
Chroma
Hue
Chroma
Hue
Chroma
1.77a,A 1.82a,A 1.92a,A
16.51a,A 16.43a,A 16.22a,A
1.76a,A – –
16.44a,A – –
– – –
– – –
– – –
– – –
Means with the same superscript within same row do not differ significantly (p > 0.05). Means with the same superscript within same column do not differ significantly (p > 0.05).
A–E
3. Results and discussion 3.1. Mathematical modeling of microbial growth in raw chicken meat under different storage temperatures Raw chicken meat samples treated with spice extracts (T-SA, T-CC, T-OV, T-SA–CC, T-SA–OV, T-CC–OV and T-SA–CC–OV) along with control samples (PC and NC) were stored at 4, 10, 15 and 20 °C. The changes in Total Viable Counts (TVC), Lactic Acid Bacteria (LAB) counts and Enterobacteriaceae counts were monitored. Gompertz modified function was used to describe the growth of microbial populations at each temperature (Zwietering et al., 1991). A good agreement was observed between the model and the experimental data. Growth parameters such as lag phase duration (LPD), maximum population density (MPD) and maximal growth rate (lmax), obtained by the model, with their respective standard error and the coefficient of determination (R2) were calculated and presented in Tables 1–4 for different storage temperatures 4, 10, 15 and 20 °C. In all cases, the ANOVA analysis shows significant differences (p < 0.05) in the microbial counts. The LPD values of control samples (NC and PC) were varied between 0.921 and 7.331 days for TVC, LAB and Enterobacteriaceae from 4 °C to 20 °C. In the case of TVC, LPD ranged between 0.891 and 7.111 days for the spice treated meat samples at the temperature range from 4 °C to 20 °C. The LPD values of LAB ranged between 0.831 and 6.561 days for meat samples treated with spice extracts at the studied temperatures. The values of LPD were in the range from 0.871 to 6.991 for Enterobacteriaceae from 4 °C to 20 °C. It is quite clearly visible that with the increase of the storage temperature of raw meat, the LPD values were decreased. For Enterobacteriaceae, the highest LPD value was shown by the T-SA samples stored at 4 °C, while lower values were displayed by T-SA–CC–OV samples stored at 20 °C. For the control samples (NC and PC) the MPD values were varied in between 6.78 and 8.96 log CFU g1 for TVC, LAB and Enterobacteriaceae at temperature ranging from 4 °C to 20 °C. The MPD values of TVC ranged between 7.09 and 8.01 for the spice treated meat samples in the studied temperatures from 4 °C to 20 °C. In the case of LAB, MPD values were in the range from 6.42 to 7.29 log CFU g1 from 4 °C to 20 °C. The values of MPD for Enterobacteriaceae, ranged between 6.04 and 6.91 log CFU g1 at the storage temperature range from 4 °C to 20 °C. In all cases, the increase in temperature showed an increase in the maximal growth rate (lmax). In the control samples (NC and PC) stored at 4 °C, the lmax values were observed as follows for TVC, LAB and Enterobacteriaceae 0.659 and 0.579, 0.470 and 0.380, 0.609 and 0.515 respectively. The lmax values were found as follows 0.779 and 0.669, 0.710 and 0.441, 1.249 and 0.688 respectively for TVC, LAB and Enterobacteriaceae for the control samples (NC and PC) stored at 10 °C. At 15 °C, the lmax values of control samples (PC and NC) were recorded as 1.595 and 1.474, 1.182 and 1.101, 2.059 and 1.701 for TVC, LAB and Enterobacteriaceae respectively. At 20 °C, the values of lmax were observed as 2.050 and 1.875, 1.705 and 1.567, 2.987 and 2.707
for TVC, LAB and Enterobacteriaceae respectively for NC and PC samples. In meat samples treated with spice extracts, the lmax values were found to be in the range between 0.251 and 0.390 at 4 °C, 0.410 and 0.548 at 10 °C, 0.726 and 1.031 at 15 °C and 0.737 and 1.267 at 20 °C for TVC. The lmax values of LAB ranged between 0.137 and 0.251 at 4 °C and 0.181 and 0.331 at 10 °C. When the temperature increased to 15 °C, the lmax values were increased and they were in the range of 0.453–0.827 and 0.659–1.260 at 20 °C. The values of lmax for Enterobacteriaceae, ranged between 0.350 and 0.465 at 4 °C, 0.440 and 0.560 at 10 °C, 1.018 and 1.381 at 15 °C and 1.595 and 2.109 at 20 °C. Based on the obtained results from the meat samples treated with spice extracts, highest lmax values were obtained for Enterobacteriaceae in the meat samples at various temperatures, particularly for T-SA samples stored at 20 °C. Under controlled environmental conditions, only one species of the microflora is often responsible for spoilage (specific spoilage organism – SSO) in raw meat. The spoilage becomes evident when the spoilage reaches certain level by the SSO and/or its microbial metabolic product (Limbo et al., 2010). From the data, it was evident that Enterobacteriaceae had higher rates of growth than LAB at all four temperatures. Lactic acid bacteria was the microorganism that showed the lowest lmax values in the meat samples at different temperatures, especially in T-SA–CC–OV samples stored at 4 °C. It may be due to the stronger antimicrobial activity shown by mixed spice extracts when compared with their respective individual activity (Djenane et al., 2003). The strong antimicrobial effect of the combination of S. aromaticum, C. cassia and O. vulgare extracts observed in the present study could be a result of synergistic actions of specific compounds present in the mixed spice extracts. Synergistic inhibitory effects on food-borne bacteria had been observed when spice extracts were combined (Dufour et al., 2003; Radha krishnan et al., 2014a). The antimicrobial activities of phenolic compounds in the spice extracts may involve multiple modes of action (Lambert et al., 2001). For example, phenolic compounds can degrade the cell wall, disrupt the cytoplasmic membrane, cause leakage of cellular components, change fatty acid and phospholipid constituents, influence the synthesis of DNA and RNA and destroy protein translocation (Shan et al., 2007). The exact target(s) for natural antimicrobials are often not known or well defined, as it is difficult to identify a specific action site where many interacting reactions take place simultaneously. 3.2. Effect of temperature on specific growth rate (l) and lag phase duration The values of El were calculated by plotting ln l vs. 1/T for each type of bacteria. The results obtained along with the coefficients of regression for the three types of microorganisms studied were presented in Table 5. From the results it was found that the lactic acid bacteria showed the higher El value than the values shown by Enterobacteriaceae in the meat samples. The highest El value for LAB was observed in the meat samples treated with O. vulgare
35
K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37 Table 7 TBARS values of raw chicken meat samples stored at different temperatures (4, 10, 15 and 20 °C). Sample
Days
4 °C
10 °C
15 °C
a,A
a,A
a,A
20 °C
NC
0 1 2 4 6 10 15 20
0.72 0.85a,A 0.99a,A 0.94b,A 1.29a,A 1.41a,A 1.58a,A 1.88a,A
0.72 1.09a,A 1.33a,A 1.71a,A 1.91a,A 2.31a,A – –
0.72 1.29a,A 1.59a,A 1.97a,A 2.45a,A – – –
0.72a,A 1.39a,A 1.77a,A 2.29a,A – – – –
PC
0 1 2 4 6 10 15 20
0.72a,A 0.96b,A 1.02a,B 1.29a,B 1.19b,B 1.97a,B 1.82c,B 2.12a,B
0.72a,A 1.25a,B 1.49a,B 1.87a,A 2.38a,B 2.62a,B – –
0.72a,A 1.37a,B 1.78a,B 2.21a,B 2.54a,A – – –
0.72a,A 1.51a,B 1.99a,B 2.41a,B – – – –
T-SA
0 1 2 4 6 10 15 20
0.72a,A 0.63c,B 0.92a,A 1.02a,A 1.29a,A 1.49a,A 1.71a,C 1.86a,A
0.72a,A 0.96a,C 1.12a,C 1.46a,B 1.79a,A 2.01a,C – –
0.72a,A 1.26a,A 1.69a,B 1.86a,C 2.10a,B – – –
0.72a,A 1.35a,A 1.78a,A 2.11a,C – – – –
T-CC
0 1 2 4 6 10 15 20
0.72a,A 0.85a,B 0.74b,C 1.11a,A 1.35a,A 1.53a,A 1.74a,C 1.79a,A
0.72a,A 1.02a,A 1.39a,A 1.21a,C 1.71a,C 1.99a,C – –
0.72a,A 1.21a,A 1.94a,C 1.81b,C 2.14a,B – – –
0.72a,A 1.29a,C 1.65a,C 1.98a,D – – – –
T-OV
0 1 2 4 6 10 15 20
0.72a,A 0.92a,B 0.71b,C 1.06a,A 1.38a,A 1.29c,C 1.61a,A 1.81a,A
0.72a,A 1.29a,B 1.25b,A 1.74a,A 1.69c,C 2.04a,C – –
0.72a,A 1.29a,A 1.49a,D 1.76a,C 2.19a,B – – –
0.72a,A 1.41a,A 1.72a,A 2.05a,C – – – –
T-SA–CC
0 1 2 4 6 10 15 20
0.72a,A 0.84a,A 0.91a,A 1.09a,A 1.41a,A 1.34b,C 1.44a,D 1.59a,C
0.72a,A 1.08a,A 1.28a,D 1.25b,C 1.78a,A 1.91a,C – –
0.72a,A 1.19a,A 1.41a,D 1.68a,D 2.04a,C – – –
0.72a,A 1.32a,C 1.59a,C 1.89a,E – – – –
T-SA–OV
0 1 2 4 6 10 15 20
0.72a,A 0.81a,A 0.83a,D 1.05a,A 1.32a,A 1.24b,C 1.41a,D 1.68a,C
0.72a,A 0.97a,C 1.08a,C 1.49a,B 1.41b,D 1.94a,C – –
0.72a,A 1.09a,C 1.39a,D 1.69a,D 2.01a,C – – –
0.72a,A 1.48a,B 1.68a,C 1.95a,D – – – –
T-CC–OV
0 1 2 4 6 10 15 20
0.72a,A 0.85a,A 0.74b,C 1.08a,A 1.32a,A 1.27c,C 1.41a,D 1.56a,C
0.72a,A 1.01a,A 1.14a,C 1.24a,C 1.45a,D 1.82a,D – –
0.72a,A 1.21a,A 1.70a,B 1.61b,D 1.98a,C – – –
0.72a,A 1.36a,A 1.74a,A 1.98a,D – – – –
T-SA–CC–OV
0 1 2 4
0.72a,A 0.69c,B 0.79b,C 0.91a,A
0.72a,A 1.02a,A 1.26a,B 1.24b,C
0.72a,A 1.06a,C 1.48a,D 1.39a,E
0.72a,A 1.33a,C 1.61a,C 1.79a,E (continued on next page)
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
Table 7 (continued) Sample
a–c A–E
Days
4 °C
10 °C
15 °C
20 °C
6 10 15 20
1.11a,C 1.25a,C 1.38a,D 1.48a,C
1.37a,D 1.75a,D – –
1.83a,D – – –
– – – –
Means with the same superscript within same row do not differ significantly (p > 0.05). Means with the same superscript within same column do not differ significantly (p > 0.05).
extracts (T-OV). The highest El value for Enterobacteriaceae was recorded in the T-CC samples. The high R2 values show an Arrhenius dependence on temperature both for LAB and Enterobacteriaceae. Concerning the effect of temperature on lag phase duration and specific growth rate, the higher El values of LAB indicated that their growth was affected more by temperature shifts than the growth of Enterobacteriaceae. The values of E1/LPD for each type of bacteria were obtained by plotting ln1/LPD vs. 1/T and the values were presented in Table 5. From the observed data, it was noticed that lactic acid bacteria showed higher E1/LPD values than values shown by Enterobacteriaceae and the highest E1/LPD was found in the T-SA– CC–OV samples. As like LAB, the highest E1/LPD value for Enterobacteriaceae was also observed in the T-SA–CC–OV samples. 3.3. Color values The color of fresh meat is one of the main factors as consumers use discoloration as an indicator of freshness and wholesomeness for its acceptability (Mancini and Hunt, 2005). Lightness (L⁄), redness (a⁄) and yellowness (b⁄) of meat samples with or without added spice extracts (not shown in table) were measured and these values were used to calculate chroma and hue index values (Table 6). The lightness (L⁄) values of meat samples were altered slightly by the addition of spice extracts at all storage temperatures. L⁄ values of meat samples treated with spice extracts were found to be increased during the storage period. However, L⁄ values of both control samples (PC and NC) gradually decreased and showed lower values at the end of the storage period. In all samples redness (a⁄ values) declined incrementally as the storage time progressed but red color of the control sample faded very rapidly. The redness of the control samples (PC and NC) decreased significantly while that of spice treated meat samples decreased slightly during storage. Several authors have studied the effect of different antioxidants on the color of meat and meat products (Higgins et al., 1998; Lee et al., 1998; Radha krishnan et al., 2014b) and have reported that meat oxidation decreases a⁄ values. To some extent, the present study revealed the protective effects of spice extracts against the decrease in a⁄ values in raw meat during storage. The yellowness (b⁄ values) values of all meat samples followed a pattern similar to a⁄ values. The b⁄ values were decreased during storage at different temperatures. The Hue index values of all meat samples were found to be increased gradually during the storage at different temperatures. The increase in of Hue index depended on the storage temperature and time as reported by many authors (Akarpat et al., 2008; Georgantelis et al., 2007). The increase in Hue index may be due to the gradual oxidation of myoglobin and accumulation of metmyoglobin with time (Mancini and Hunt, 2005; Ruiz de Huidobro et al., 2003). The chroma values of all meat samples were gradually decreased during storage at different temperatures as it depend on the redness (a⁄) and yellowness (b⁄) values. As both values decreased during storage at different temperatures the chroma values also decreased when moving from 4 °C to 20 °C.
3.4. TBARS values Lipid oxidation was analyzed in raw meat samples using the TBARS distillation method (Table 7). The TBARS method has been widely used to estimate the degree of lipid oxidation in meat products. TBARS are produced through second stage autooxidation during which peroxides are oxidized to aldehydes and ketones (e.g., MDA – Malondialdehyde). Table 7 shows the effect of spice extracts on TBARS values of raw meat samples during storage at different temperatures. These results indicate that spice extracts were effective in lowering the TBARS values of meat samples when compared to control samples (NC and PC). The increase in TBARS values of all the spice treated samples was slow and remained low during their storage period than the control samples. In general, storage time has a significant influence on the development of lipid oxidation in meat samples, resulting in extensive increases in TBARS values during the storage period. The TBARS values of all the treatment samples were considerably lower than the control on all days and the treatment with combined spice extracts (T-SA–CC–OV) suppressed lipid oxidation more than the other spice treated samples, indicating the high protective effect against lipid oxidation in raw meat. The effect of spice extracts may be related to its phenolic constituents. The phenolic compounds are of great interest as they have biochemical and pharmacological effects including anticarcinogenic and antioxidant effects (Doshi et al., 2006). Several studies have reported on the relationship between phenolic content and antioxidant activity (Velioglu et al., 1998; Wong et al., 1995).
4. Conclusion In the present work the individual and simultaneous effects of S. aromaticum (SA), C. cassia (CC) and O. vulgare (OV) extracts on raw chicken meat were studied by analyzing microbial counts, color values and TBARS values; the effects of temperature (4, 10, 15 and 20 °C) were considered as an important factor. Gompertz derived parameters were determined in order to compare the effects of temperatures on microbial growth. In all cases, the increase in temperature showed an increase in the maximal growth rate (lmax). From the results, it was observed that the meat samples treated with spice extracts had highest lmax values for Enterobacteriaceae at various temperatures and particularly for T-SA samples stored at 20 °C, when compared with LAB counts. In the case of lactic acid bacteria, it showed the lowest lmax values in the meat samples, especially in T-SA–CC–OV samples stored at 4 °C. The effect of temperature on specific microbial growth and lag phase duration values were modeled through Arrhenius equation, determining the corresponding activation energies. Lactic acid bacteria showed the highest value of activation energy (El) for the specific growth rate in raw chicken meat samples treated with O. vulgare extracts (T-OV) and the highest values of activation energy for the adaptation period (E1/LPD) were found for Enterobacteriaceae in the T-SA–CC–OV samples.
K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
The results from the present study showed that the combination of spice extracts (SA + CC + OV) can be used as an alternate preservative to synthetic preservatives in raw chicken meat to improve and increase the hygiene quality of the chicken meat. Acknowledgment The first author sincerely express his greatest gratitude to Department of Biotechnology, New Delhi, India for the award of Junior Research Fellowship under ‘‘Enhancing research capacity and initiating integrated M.Tech programme in the area of Food Science and Technology’’. References Akarpat, A., Turhan, S., Ustun, N.S., 2008. Effects of hot-water extracts from myrtle, rosemary, nettle and lemon balm leaves on lipid oxidation and color of beef patties during frozen storage. J. Food Process. Preserv. 32, 117–132. Bakkali, F., Averbeck, S., Averbeck, D., Idaomar, M., 2008. Biological effects of essential oils – a review. Food Chem. Toxicol. 46, 446–475. Barbut, S., 2002. Poultry Products Processing. An Industry Guide. CRC Press, London. Burt, S., 2004. Essential oils: their antibacterial properties and potential applications in foods – a review. Int. J. Food Microbiol. 94, 223–253. Cayre, M.E., Garro, O., Vignolo, G., 2005. Effect of storage temperature and gas permeability of packaging film on the growth of lactic acid bacteria and Brochothrix thermosphacta in cooked meat emulsions. Food Microbiol. 22 (6), 505–512. Devatkal, S.K., Naveena, B.M., 2010. Effect of salt, kinnow and pomegranate fruit byproduct powders on color and oxidative stability of raw ground goat meat during refrigerated storage. Meat Sci. 85 (2), 306–311. Djenane, D., Sanchez-Escalante, A., Beltran, J.A., Roncalés, P., 2003. Extension of the shelf life of beef steaks packaged in a modified atmosphere by treatment with rosemary and displayed under UV-free lighting. Meat Sci. 64 (4), 417–426. Doshi, P., Adsule, P., Banerjee, K., 2006. Phenolic composition and antioxidant activity in grapevine parts and berries (Vitis vinifera L.) cv. Kishmish chornyi (Sharad Seedless) during maturation. Int. J. Food Sci. Technol. 41 (1), 1–9. Du, M., Ahn, D.U., 2002. Effect of antioxidants on the quality of irradiated sausages prepared with turkey thigh meat. Poult. Sci. 81, 1251–1256. Dufour, M., Simmonds, R.S., Bremer, P.J., 2003. Development of a method to quantify in vitro the synergistic activity of natural antimicrobials. Int. J. Food Microbiol. 85, 249–258. El-Massry, K.F., Farouk, A., Abou-Zeid, M., 2008. Free radical scavenging activity and lipoxygenase inhibition of rosemary (Rosmarinus officinalis L.) volatile oil. J. Essent. Oil Bear. Plants 11 (5), 536–543. Georgantelis, D., Blekas, G., Katikou, P., Ambrosiadis, I., Fletouris, D.J., 2007. Effect of rosemary extract, chitosan and a-tocopherol on lipid oxidation and color stability during frozen storage of beef burgers. Meat Sci. 75, 256–264. Higgins, F.M., Kerry, J.P., Buckley, D.J., Morrisey, P.A., 1998. Effect of dietary atocopheryl acetate supplementation on a-tocopherol distribution in raw turkey muscles and its effect on the storage stability of cooked turkey meat. Meat Sci. 37, 373–383. Holley, R.A., Patel, D., 2005. Improvement in shelf-life and safety of perishable foods by plant essential oils and smoke antimicrobials. Food Microbiol. 4, 273–292. Kordali, S., Cakir, A., Ozer, H., Cakmakci, R., Kesdek, M., Mete, E., 2008. Antifungal, phytotoxic and insecticidal properties of essential oil isolated from Turkish Origanum acutidens and its three components, carvacrol, thymol and p-cymene. Bioresour. Technol. 99 (18), 8788–8795. Lambert, R.J.W., Skandamis, P.N., Coote, P.J., Nychas, G.J., 2001. A study of the minimum inhibitory concentration and mode of action of oregano essential oil, thymol and carvacrol. J. Appl. Microbiol. 91 (3), 453–462.
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Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng
Evaluation and predictive modeling the effects of spice extracts on raw chicken meat stored at different temperatures K. Radha krishnan a, S. Babuskin a, P. Azhagu Saravana Babu a, M. Sivarajan b, M. Sukumar a,⇑ a b
Centre for Biotechnology, A.C. Tech., Anna University, Chennai 25, India Chemical Engineering Division, Central Leather Research Institute, Chennai 20, India
a r t i c l e
i n f o
Article history: Received 5 March 2015 Received in revised form 13 May 2015 Accepted 14 May 2015 Available online 15 May 2015 Keywords: Modeling Raw meat Shelf life Gompertz model Predictive microbiology Microbial growth
a b s t r a c t In the present study, the anti-microbial and anti-oxidant effects of Syzygium aromaticum (SA), Cinnamomum cassia (CC) and Origanum vulgare (OV) on the shelf life of raw chicken meat stored at different temperatures (4, 10, 15 and 20 °C ± 1) were studied. Gompertz model was used to model the microbial growth using the data from microbial analysis of meat samples. Arrhenius equation was applied to understand the effect of storage temperature on the specific growth rate (l) and lag phase duration. Highest lmax and LPD (lag phase duration) values were obtained for Enterobacteriaceae in T-SA (Treatment with 1% S. aromaticum extract) samples stored at 4 °C. The lmax values of T-SA–CC–OV (Treatment with 0.33% S. aromaticum extract + 0.33% C. cassia extract + 0.33% O. vulgare extract) samples were found to be low at all the tested temperatures and especially at 4 °C with better color values and lower TBARS (Thiobarbituric acid reactive substances) values than the other samples. The best preservative effects were achieved with the combination of spice extracts. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Meat is a very popular food commodity around the world due to its low cost of production, low fat content, high nutritional value and distinct flavor (Barbut, 2002; Patsias et al., 2008). The diverse nutrient composition of meat makes it an ideal environment for the growth and propagation of meat spoilage micro-organisms and common food-borne pathogens (Zhou et al., 2010). It is therefore essential that adequate preservation technologies are needed to extend the shelf life of perishable meat products which is a major concern for the meat industries (Wang et al., 2004). Lipid oxidation and microbial growth during storage can be reduced by applying antioxidant and antimicrobial agents to the meat products, leading to a retardation of spoilage, an extension of shelf-life, and a maintenance of quality and safety (Devatkal and Naveena, 2010). Therefore, there has been increasing interest in alternative additives from natural sources (Sebranek et al., 2005) which has gradually provided impetus to eliminating synthetic preservatives in food (McCarthy et al., 2001). Naturally occurring antimicrobial compounds have good potential to be applied as food preservatives. Essential oils and other extracts from plants, herbs and spices and some of their constituents, have shown antimicrobial activity against different ⇑ Corresponding author. E-mail address: [email protected] (M. Sukumar). http://dx.doi.org/10.1016/j.jfoodeng.2015.05.021 0260-8774/Ó 2015 Elsevier Ltd. All rights reserved.
food pathogens and spoilage microorganisms (Bakkali et al., 2008; Burt, 2004; Holley and Patel, 2005). Spices have been employed since ancient times as flavoring and preservative agents for food, but the research on the spice extracts has been initiated in the last decade for their compounds exerting antimicrobial and antioxidant activities (Sagdic et al., 2003). The clove, cinnamon and oregano are considered as the most common spices and herbs with strong antimicrobial activity. Their essential oils containing chemical compounds such as eugenol, cinnamaldehyde and carvacrol are identified as the major chemical components responsible for exerting antimicrobial activity (Wei and Shibamoto, 2010; El-Massry et al., 2008; Kordali et al., 2008; Zawirska-Wojtasiak and Wasowicz, 2009). Some studies reported that there is a highly positive linear relationship between antioxidant activity, antibacterial activity and total phenolic content in some spices and herbs (Shan et al., 2007, 2005). Determination of shelf life with traditional microbiological tests is expensive and time-consuming. An alternative is the concept of predictive microbiology, which uses mathematical models to predict the bacterial growth as a function of environmental factors such as temperature, pH and aw (Cayre et al., 2005; McMeekin et al., 1987). It allows us to quantify and to predict the rate of growth of microorganisms under environmental conditions with the intention of assuring the hygienic quality of food, thus determining its storage life. Mathematical models fulfill the research gap on the inactivation kinetics of natural antimicrobial extracts
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
on microorganisms inoculated in food products. One of the more frequently used models is that of Gompertz with parameters such as lag phase duration (LPD), maximum population density (MPD), growth rate (l) and the activation energy (El). The objective of the present work was to model the shelf life of raw chicken meat based on the microbiological analysis and to determine the effect of temperature on the kinetic parameters such as LPD, MPD, l and El. 2. Materials and methods 2.1. Materials Dried spices of clove (Syzygium aromaticum), cinnamon (Cinnamomum cassia) and oregano (Origanum vulgare) were obtained from Nuts and Spices Super market, Chennai, India. 2.2. Chemicals and reagents Butylated hydroxytoluene (BHT), thiobarbituric acid (TBA) and trichloroacetic acid (TCA) were supplied by Sigma-Aldrich Chemicals, Germany. Methanol, Plate Count Agar (PCA), Violet Red Bile Glucose (VRBG) agar, Buffered Peptone Water, de Man Rogosa and Sharpe (MRS) agar was purchased from Merck, Darmstadt, Germany. 2.3. Preparation of extracts Spices were grounded using mixer grinder (Preethi ChefPro model, Indian make) and sieved well using vertical vibratory sieve shaker (Labortechnik Gmbh, Ilmenau) for 20 min in order to obtain particles of same size. Extraction was performed in soxhlet extractor by contacting solvent and sample at a constant temperature, which could ensure solvent reflux (78–80 °C). Samples of 50 g were placed into a round-bottomed flask filled with 2500 mL ethanol (solid–solvent ratio of 1:50) connected at the top to a cooler and extraction was carried out for 5–6 h. The extracts were filtered through Whatman filter paper No. 1 (Whatman International, Ltd.,) and concentrated using a rotary evaporator. Finally spice extracts were dissolved in water in the ratio of 1:10 (w/v) for further studies. 2.4. Application of spice extracts in meat samples Raw chicken breast meat (70.1 g/100 g moisture, 22.9 g/100 g protein, 2.1 g/100 g fat content) were purchased from local meat market (Chennai, Tamil Nadu, India). Meat samples were transferred through insulated polystyrene boxes to the laboratory within 1 h of production. Fresh meat samples were obtained separately for each of the replications. The meat samples were cut into pieces of 25 g, thickness 0.8 cm and treatment was performed as follows: 1. NC (negative control – without any additive), 2. PC (positive control with 0.02% BHA – Butylated hydroxyanisole), 3. T-SA (Treatment with 1% S. aromaticum extract), 4. T-CC (Treatment with 1% C. cassia extract), 5. T-OV (Treatment with 1% O. vulgare extract), 6. T-SA–CC (Treatment with 0.5% S. aromaticum extract + 0.5% C. cassia extract), 7. T-SA–OV (Treatment with 0.5% S. aromaticum extract + 0.5% O. vulgare extract), 8. T-CC–OV (Treatment with 0.5% C. cassia extract + 0.5% O. vulgare extract), 9. T-SA–CC–OV (Treatment with 0.33% S. aromaticum extract + 0.33% C. cassia extract + 0.33% O. vulgare extract). Meat samples were stored at 4, 10, 15 and 20 °C ± 1 and microbial counts, color values and TBARS (Thiobarbituric acid reactive substances) values were determined during the storage period. Samples stored at 4 °C were analyzed after 1, 2, 4, 6, 10, 15 and 20 days; those stored at
10 °C after, 1, 2, 4, 6 and 10 days; the ones at 15 °C after 1, 2, 4, and 6 days of storage and samples stored at 20 °C were analyzed after 1, 2 and 4 days. At these two last temperatures analyzes were carried out for fewer days because of the greater rate of decay of the meat. All the analyzes were performed in triplicate. 2.5. Microbial analysis For the microbiological assays, a representative of 10 g meat sample was withdrawn and homogenized (Model PT-MR-2100, Kinematica AG, Switzerland) aseptically using 90 mL 0.1% peptone water and serial dilutions were made using 0.1% sterile peptone water. Total Viable Count (TVC) was determined on PCA agar by incubating plates at 37 °C for 24 h. Lactic Acid Bacteria (LAB) were counted on MRS Agar plates and incubated at 30 °C for 72 h. Total Enterobacteriaceae were counted on VRBG plates and incubated at 37 °C for 24 h. After incubation, plates having 25–250 colonyforming units (CFU) were counted and the results expressed in logarithmic of colony-forming units per gram of meat (log CFU/g). 2.6. Mathematical modeling of bacterial growth Modified Gompertz equation was used to generate the bacterial growth curves by data fitting (Zwietering et al., 1991) and Eq. (1)
Table 1 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of Total Viable Count (TVC), Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 4 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.659 0.470 0.609
7.33 6.81 7.18
8.96 7.95 7.15
0.96 0.97 0.95
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.579 0.380 0.515
7.27 6.72 7.06
8.68 7.59 6.78
0.94 0.95 0.98
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
0.306 0.239 0.465
7.02 6.51 6.99
7.61 6.95 6.57
0.97 0.98 0.95
T-CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.389 0.251 0.391
7.11 6.56 6.88
7.95 7.01 6.24
0.97 0.96 0.98
T-OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.364 0.242 0.454
7.09 6.54 6.98
7.85 6.97 6.52
0.99 0.93 0.95
T-SA–CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.283 0.192 0.413
7.00 6.47 6.91
7.49 6.72 6.34
0.98 0.95 0.97
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.352 0.206 0.400
7.07 6.49 6.89
7.81 6.79 6.28
0.94 0.96 0.97
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.390 0.192 0.360
7.11 6.47 6.82
7.96 6.75 6.09
0.98 0.97 0.98
T-SA–CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.251 0.137 0.350
6.96 6.36 6.79
7.35 6.42 6.04
0.97 0.97 0.98
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37 Table 2 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of Total Viable Count (TVC), Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 10 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.779 0.710 1.249
4.56 4.36 4.63
8.62 7.81 7.91
0.98 0.97 0.98
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.669 0.441 0.688
4.51 3.69 3.87
8.31 7.68 7.42
0.97 0.94 0.98
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
0.501 0.289 0.530
4.43 3.50 3.69
7.81 7.02 6.79
0.98 0.95 0.97
T-CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.548 0.314 0.552
4.45 3.54 3.72
7.95 7.15 6.88
0.95 0.97 0.96
T-OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.515 0.331 0.560
4.44 3.56 3.73
7.85 7.21 6.91
0.96 0.95 0.93
Total viable count Lactic acid bacteria Enterobacteriaceae
0.453 0.231 0.449
4.40 3.41 3.57
7.66 6.74 6.45
0.99 0.96 0.97
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.460 0.254 0.456
4.41 3.45 3.59
7.68 6.85 6.48
0.98 0.95 0.96
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.501 0.268 0.486
4.43 3.47 3.63
7.81 6.92 6.61
0.99 0.95 0.96
Total viable count Lactic acid bacteria Enterobacteriaceae
0.410 0.181 0.440
4.38 3.33 3.55
7.52 6.48 6.41
0.98 0.99 0.96
T-SA–CC
T-SA–CC–OV
ln l ¼ ln A El =RT
ð3Þ
El values for each type of bacteria were calculated by plotting the values of ln l vs. 1/T. Zwietering et al. (1991) modified the extended Ratkowsky model to describe the lag time as a function of temperature. The effect of temperature on LPD reflects how the adaptation period of microorganisms to their new environment changes with temperature. In this regard, the adaptation rate can be considered as the reciprocal of LPD (Li and Torres, 1993), and was modeled using an Arrhenius type model
1=LPD ¼ D expðE1=LPD =RTÞ
ð4Þ 1
where D is a pre exponential factor (days ), E1/LPD is the activation energy (kJ mol1), R is the gas constant 8.31 (J (K mol)1) and T is the temperature in (K). The activation energy E1/LPD can be considered as the sensitivity of the microorganisms to temperature change
lnð1=LPDÞ ¼ ln D ðE1=LPD =RTÞ
ð5Þ
2.7. Color values The color of raw chicken patties was evaluated using a HunterLab UltraScan VIS color spectrophotometer (Hunter
Table 3 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of Total Viable Count (TVC), Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 15 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.595 1.182 2.059
2.32 2.17 2.13
8.85 7.81 7.89
0.98 0.96 0.98
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.474 1.101 1.701
2.31 2.16 2.08
8.68 7.68 7.39
0.97 0.96 0.97
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
0.970 0.766 1.307
2.24 2.09 2.00
7.91 7.10 6.79
0.96 0.93 0.95
T-CC
has been used to estimate the response variables (lag phase duration, maximal growth rate and maximum population density).
Total viable count Lactic acid bacteria Enterobacteriaceae
1.031 0.793 1.363
2.25 2.10 2.02
8.01 7.15 6.88
0.98 0.97 0.97
T-OV
LPD t þ1 logðCFUÞ ¼ K þ D exp exp lmax 2:7182 A
Total viable count Lactic acid bacteria Enterobacteriaceae
1.019 0.827 1.381
2.24 2.11 2.02
7.99 7.21 6.91
0.99 0.98 0.97
T-SA–CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.793 0.579 1.107
2.21 2.05 1.96
7.61 6.74 6.45
0.99 0.96 0.97
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.856 0.634 1.124
2.22 2.06 1.96
7.72 6.85 6.48
0.98 0.96 0.97
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.940 0.670 1.200
2.24 2.07 1.98
7.86 6.92 6.61
0.96 0.96 0.98
T-SA–CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.726 0.453 1.018
2.20 2.01 1.93
7.49 6.48 6.29
0.96 0.97 0.97
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
ð1Þ where K is the initial bacterial count (log CFU/g); D is the increase in log CFU/g between time 0 and the maximum population density achieved at the stationary phase; lmax is the maximal growth rate (Dlog (CFU/g)/day); LPD is the lag phase duration (days); and t is the storage time (days). The maximum population density MPD (log (CFU g1)) is calculated by adding the values of K and A. The goodness of the fit was assessed by the R2 value. Arrhenius equation was applied to understand the effect of storage temperature on the specific growth rate (l),
l ¼ A expðEl =RTÞ
ð2Þ 1
1
where A is a pre exponential factor (log (CFU g ) days ), El is the activation energy (kJ mol1), R is the gas constant 8.31 (J (K mol)1) and T is the temperature (K). The sensitivity of the microorganisms to temperature change can be considered as the activation energy El and calculated using Eq. (3)
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
32
K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
Table 4 Maximal growth rate (lmax), lag phase duration (LPD) and maximum population density (MPD) obtained by the Gompertz equation of total viable count, Lactic Acid Bacteria (LAB) and Enterobacteriaceae counts for raw chicken meat samples stored at 20 °C. Sample
Microorganisms
lmax
LPD
MPD
R2
NC
Total viable count Lactic acid bacteria Enterobacteriaceae
2.050 1.705 2.987
1.05 0.93 0.99
8.56 7.79 7.77
0.96 0.97 0.97
PC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.875 1.567 2.707
1.04 0.92 0.97
8.39 7.64 7.51
0.98 0.98 0.97
T-SA
Total viable count Lactic acid bacteria Enterobacteriaceae
1.267 1.144 2.109
1.00 0.88 0.92
7.74 7.15 6.91
0.96 0.98 0.97
T-CC
Total viable count Lactic acid bacteria Enterobacteriaceae
1.215 1.193 2.016
1.00 0.89 0.91
7.68 7.21 6.81
0.99 0.98 0.98
T-OV
Total viable count Lactic acid bacteria Enterobacteriaceae
1.241 1.260 2.063
1.01 0.92 0.91
7.71 7.29 6.86
0.99 0.97 0.96
T-SA–CC
Total viable count Lactic acid bacteria Enterobacteriaceae
0.971 0.938 1.748
0.89 0.86 0.89
7.39 6.89 6.51
0.95 0.96 0.98
T-SA–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
1.070 0.953 1.809
0.99 0.86 0.89
7.51 6.91 6.58
0.96 0.96 0.93
T-CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
1.020 0.915 1.844
0.98 0.86 0.90
7.45 6.86 6.62
0.98 0.96 0.97
T-SA–CC–OV
Total viable count Lactic acid bacteria Enterobacteriaceae
0.737 0.659 1.595
0.96 0.83 0.87
7.09 6.51 6.33
0.97 0.95 0.96
Associates Laboratory Inc., Reston, VA, USA). Color was described as L⁄ (lightness), a⁄ (redness), and b⁄ (yellowness) color space values. A Chroma meter was standardized with a standard white plate (L⁄ = 93.80, a⁄ = 0.3157 and b⁄ = 0.3319). Measurements were made perpendicular to the patty surface at five different locations per sample and mean values (L⁄, a⁄, and b⁄) from the samples were analyzed. From the measured values, hue (h⁄) and chroma (C⁄) were calculated as following (Mastromatteo et al., 2009):
Hue ¼
b a
Chroma ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 a2 þ b
ð6Þ
2.8. Thiobarbituric acid reactive substances (TBARS) value Meat samples were analyzed for Thiobarbituric acid reactive substances (TBARS) as per the method described by Du and Ahn (2002). Five grams of meat was homogenized with 15 mL of deionized distilled water. 1 mL of the meat homogenate was transferred to a test tube and 50 lL of butylated hydroxytoluene (7.2%) and 2 mL of thiobarbituric acid (TBA)–trichloroacetic acid (TCA) (15 mM TBA–15% TCA) were added. The mixture was vortexed and then incubated in a boiling water bath for 15 min to develop color. Then samples were subjected to cooling for 10 min, vortexed again, and centrifuged for 15 min at 2500g. The absorbance of the resulting supernatant solution was determined at 531 nm against a blank containing 1 mL of deionized water and 2 mL of TBA–TCA solution. The amount of TBARS was expressed as milligrams of malondialdehyde per kilogram of meat.
lmax: (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g1)). NC – negative control; no extract; PC – positive control with 0.02% BHT; T-SA – Treatment with Syzygium aromaticum extract (1% v/w); T-CC – Treatment with Cinnamomum cassia (1% v/w); T-OV – Treatment with Origanum vulgare extract (1% v/w); T-SA–CC – Treatment with Syzygium aromaticum (0.5% v/w) + Cinnamomum cassia (0.5% v/w); T-SA–OV – Treatment with Syzygium aromaticum (0.5% v/w) + Origanum vulgare (0.5% v/w); T-CC–OV – Treatment with Cinnamomum cassia (0.5% v/w) + Origanum vulgare (0.5% v/w) and T-W-SA + T-W-CC + T-W-OV – Treatment with Syzygium aromaticum (0.33% v/w) + Cinnamomum cassia (0.33% v/w) + Origanum vulgare (0.33% v/w).
2.9. Statistical analysis The data were obtained from independent experiments with repetition, and the means were obtained from the triplicates. The data observed were subjected to analysis of variance (ANOVA) with significance levels of 0.05 using a statistical package (SYSTAT Inc. 1990, version 5.0, U.S.A.) for comparing the counts obtained from treated sample and its control for all the experiments.
Table 5 Application of Arrhenius model to evaluate the effect of temperature on lag phase duration and specific growth rate for total viable count, lactic acid bacteria and Enterobacteriaceae. Sample
E1 1/LPD (kJ/mol) Total viable count
R2
E1 1/LPD (kJ/mol) Lactic acid bacteria
R2
E1 1/LPD (kJ/mol) Enterobacteriaceae
R2
NC PC T-SA T-CC T-OV T-SA–CC T-SA–OV T-CC–OV T-SA–CC–OV
32.93 33.23 34.71 34.78 34.72 35.54 35.16 35.17 35.17
0.93 0.94 0.94 0.95 0.93 0.94 0.93 0.93 0.95
37.56 37.52 39.02 38.89 38.55 40.12 39.97 40.19 41.75
0.95 0.95 0.93 0.94 0.96 0.95 0.96 0.94 0.95
35.79 36.14 38.10 38.39 38.30 39.62 39.33 39.04 40.47
0.95 0.93 0.94 0.95 0.94 0.94 0.96 0.95 0.96
Sample
El1 (kJ/mol) Total viable count
R2
El1 (kJ/mol) Lactic acid bacteria
R2
El1 (kJ/mol) Enterobacteriaceae
R2
NC PC T-SA T-CC T-OV T-SA–CC T-SA–OV T-CC–OV T-SA-CC–OV
51.84 54.31 62.04 51.59 54.87 54.34 50.13 44.60 48.95
0.93 0.91 0.96 0.96 0.97 0.98 0.96 0.93 0.93
55.52 64.97 71.39 70.42 73.92 71.08 69.22 69.44 70.96
0.94 0.91 0.92 0.94 0.95 0.92 0.93 0.94 0.94
67.49 74.11 68.13 73.25 68.47 65.43 68.00 73.20 67.83
0.98 0.95 0.91 0.96 0.93 0.90 0.91 0.95 0.94
33
K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37 Table 6 Color parameters of raw chicken meat samples stored at different temperatures (4, 10, 15 and 20 °C). Sample
Days
4 °C
10 °C
15 °C
20 °C
Hue
Chroma
Hue
Chroma
Hue
Chroma
Hue
Chroma
NC
0 1 2 4 6 10 15 20
1.68a,A 1.71a,A 1.75a,A 1.86a,A 1.92a,A 1.93a,A 1.94a,A 1.96a,A
16.92a,A 16.77a,A 16.56a,A 16.69b,A 16.05a,A 15.59c,A 15.72a,A 15.39a,A
1.67a,A 1.66a,A 1.73a,A 1.77a,B 1.81a,B 1.86a – –
17.02a,B 16.74a,A 16.72a,A 16.44a,B 16.19a,A 15.75a,A – –
1.69a,A 1.82b,B 1.79a,A 1.75b,B 1.88a,A – – –
16.83a,C 16.59a,B 15.60a,B 14.14a,C 14.71a,B – – –
1.68a,A 1.78a,B 1.69b,B 1.83a,A – – – –
16.87a,A 16.90b,C 15.70a,B 15.11a,D – – – –
PC
0 1 2 4 6 10 15 20
1.68a,A 1.75a,A 1.70b,A 1.89a,A 1.95a,A 1.98a,A 1.97a,A 2.01a,A
16.92a,A 16.82a,A 16.52a,A 16.29a,A 16.38b,A 15.84a,A 15.23a,A 15.06a,A
1.67a,A 1.70a,A 1.74b,A 1.70a,B 1.76a,B 1.88a,A – –
17.02a,B 16.63a,A 16.61a,A 16.48a,A 15.99a,B 15.60a,A – –
1.69a,A 1.74a,A 1.56c,B 1.84a,A 1.87a,A – – –
16.83a,C 16.36a,B 15.84a,B 14.92a,B 14.39a,C – – –
1.68a,A 1.75a,A 1.71b,A 1.90a,A – – – –
16.87a,A 16.19a,C 15.52a,C 14.82a,B – – – –
T-SA
0 1 2 4 6 10 15 20
1.68a,A 1.72a,A 1.74a,A 1.79a,A 1.80a,A 1.82a,A 1.89a,A 1.88a,A
16.93a,A 16.78a,A 16.70a,A 16.81b,A 16.69a,A 16.50a,A 16.28a,A 16.02a,A
1.67a,A 1.72a,A 1.70b,A 1.76a,A 1.76a,A 1.81a,A – –
17.02a,B 16.67a,A 16.84a,A 16.80a,A 16.54a,A 16.20a,B – –
1.69a,A 1.66a,A 1.69c,A 1.80a,A 1.80d,A – – –
16.83a,C 16.70a,A 16.11a,B 15.63a,B 15.18a,B – – –
1.68a,A 1.75a 1.68b,A 1.80a,A – – – –
16.87a,A 16.29a,B 15.46a,C 15.69b,B – – – –
T-CC
0 1 2 4 6 10 15 20
1.68a,A 1.74a,A 1.77a,A 1.69b,A 1.79a,A 1.87a,A 1.93a,A 1.97a,A
16.92a,A 16.85a,A 16.87a,A 16.93c,A 16.49a,A 16.68c,A 16.50a,A 16.30a,A
1.68a,A 1.72a,A 1.75a,A 1.72b,A 1.79a,A 1.81a,A – –
17.02a,B 16.89a,A 16.68a,A 16.66b,B 16.37a,A 15.89a,B – –
1.69a,A 1.70a,A 1.65e,B 1.77a,A 1.85a,A – – –
16.83a,C 16.39a,B 15.92a,B 15.47a,C 14.99a,B – – –
1.68a,A 1.79a,A 1.83a,A 1.74c,A – – – –
16.87a,A 16.30a,B 15.74a,B 15.24a,C – – – –
T-OV
0 1 2 4 6 10 15 20
1.68a,A 1.76a,A 1.80a,A 1.83a,A 1.80b,A 1.84a,A 1.93c,A 1.89a,A
16.92a,A 16.65b,A 16.80a,A 16.55a,A 16.55a,A 16.21a,A 15.90a,A 15.80a,A
1.67a,A 1.66a,A 1.70a,A 1.75a,A 1.82a,A 1.87a,A – –
17.02a,B 17.17c,B 16.93a,A 16.71a,A 16.21a,A 15.97a,A – –
1.69a,A 1.71a,A 1.75a,A 1.76a,A 1.81a,A – – –
16.83a,C 16.45a,C 16.06a,B 15.51a,B 15.03a,B – – –
1.68a,A 1.64d,A 1.76a,A 1.84a,A – – – –
16.87a,A 16.67a,C 15.05c,C 15.29a,B – – – –
T-SA–CC
0 1 2 4 6 10 15 20
1.68a,A 1.71a,A 1.74a,A 1.74a,A 1.69b,A 1.84a,A 1.85a,A 1.90a,A
16.92a,A 16.93a,A 16.97c,A 16.84a,A 16.82a,A 16.59a,A 16.40a,A 16.14a,A
1.67a,A 1.61c,A 1.68a,A 1.69a,A 1.76a,A 1.80a,A – –
17.02a,B 16.93a,A 16.95c,A 16.62a,A16.58a,A 16.32a,A – –
1.69a,A 1.71a,A 1.64c,A 1.77a,A 1.79a,A – – –
16.83a,C 16.44a,A 16.17a,B 15.64a,B 15.34a,B – – –
1.68a,A 1.70a,A 1.65d,A 1.77a,A – – – –
16.87a,A 15.94a,B 16.44d,C 15.68a,B – – – –
T-SA–OV
0 1 2 4 6 10 15 20
1.68a,A 1.67a,A 1.70a,A 1.77a,A 1.84a,A 1.84a,A 1.87a,A 1.90a,A
16.92a,A 17.01c,A 16.94a,A 16.93a,A 16.70a,A 16.42a,A 16.23a,A 16.03a,A
1.67a,A 1.67a,A 1.67a,A 1.72a,A 1.81a,A 1.82a,A – –
17.02a,B 17.04a,A 16.76a,A 16.42a,B 16.33a,B 16.08a,B – –
1.69a,A 1.74a,A 1.75a,A 1.81a,A 1.86a,A – – –
16.83a,C 16.50a,B 16.00a,B 15.55a,B 15.34a,C – – –
1.68a,A 1.74a,A 1.80a,A 1.81a,A – – – –
16.87a,A 16.35a,B 15.97a,B 15.67a,B – – – –
T-CC–OV
0 1 2 4 6 10 15 20
1.68a,A 1.71a,A 1.78a,A 1.81a,A 1.86a,A 1.87a,A 1.92a,A 1.92a,A
16.92a,A 17.00c,A 16.96a,A 16.92c,A 16.60a,A 16.34a,A 16.41d,A 16.11a,A
1.67a,A 1.75a,A 1.71b,A 1.74a,A 1.74a,A 1.80a,A – –
17.02a,B 16.98a,A 16.93a,A 16.81a,A 16.50a,A 16.12a,A – –
1.69a,A 1.70a,A 1.74a,A 1.76a,A 1.80a,A – – –
16.83a,C 16.53a,B 16.09a,B 15.62a,B 15.11a,B – – –
1.68a,A 1.73a,A 1.60e,B 1.80a,A – – – –
16.87a,A 16.60a,B 15.99a,B 15.55a,B – – – –
T-SA–CC–OV
0 1 2 4 6
1.68a,A 1.75b,A 1.73a,A 1.75a,A 1.68c,A
16.93a,A 16.89a,A 16.84a,A 17.05c,A 16.82a,A
1.67a,A 1.66a,A 1.67d,A 1.70a,A 1.73a,A
17.02a,B 17.09d,A 16.88a,A 16.57a,B 16.62a,A
1.69a,A 1.70a,A 1.63b,A 1.74a,A 1.78a,A
16.83a,C 16.49a,B 16.29a,B 15.93a,C 15.70a,B
1.68a,A 1.69a,A 1.72a,A 1.74a,A –
16.87a,A 16.12a,B 16.58a,B 15.90a,C –
(continued on next page)
34
K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
Table 6 (continued) Sample
Days
10 15 20 a–c
4 °C
10 °C
15 °C
20 °C
Hue
Chroma
Hue
Chroma
Hue
Chroma
Hue
Chroma
1.77a,A 1.82a,A 1.92a,A
16.51a,A 16.43a,A 16.22a,A
1.76a,A – –
16.44a,A – –
– – –
– – –
– – –
– – –
Means with the same superscript within same row do not differ significantly (p > 0.05). Means with the same superscript within same column do not differ significantly (p > 0.05).
A–E
3. Results and discussion 3.1. Mathematical modeling of microbial growth in raw chicken meat under different storage temperatures Raw chicken meat samples treated with spice extracts (T-SA, T-CC, T-OV, T-SA–CC, T-SA–OV, T-CC–OV and T-SA–CC–OV) along with control samples (PC and NC) were stored at 4, 10, 15 and 20 °C. The changes in Total Viable Counts (TVC), Lactic Acid Bacteria (LAB) counts and Enterobacteriaceae counts were monitored. Gompertz modified function was used to describe the growth of microbial populations at each temperature (Zwietering et al., 1991). A good agreement was observed between the model and the experimental data. Growth parameters such as lag phase duration (LPD), maximum population density (MPD) and maximal growth rate (lmax), obtained by the model, with their respective standard error and the coefficient of determination (R2) were calculated and presented in Tables 1–4 for different storage temperatures 4, 10, 15 and 20 °C. In all cases, the ANOVA analysis shows significant differences (p < 0.05) in the microbial counts. The LPD values of control samples (NC and PC) were varied between 0.921 and 7.331 days for TVC, LAB and Enterobacteriaceae from 4 °C to 20 °C. In the case of TVC, LPD ranged between 0.891 and 7.111 days for the spice treated meat samples at the temperature range from 4 °C to 20 °C. The LPD values of LAB ranged between 0.831 and 6.561 days for meat samples treated with spice extracts at the studied temperatures. The values of LPD were in the range from 0.871 to 6.991 for Enterobacteriaceae from 4 °C to 20 °C. It is quite clearly visible that with the increase of the storage temperature of raw meat, the LPD values were decreased. For Enterobacteriaceae, the highest LPD value was shown by the T-SA samples stored at 4 °C, while lower values were displayed by T-SA–CC–OV samples stored at 20 °C. For the control samples (NC and PC) the MPD values were varied in between 6.78 and 8.96 log CFU g1 for TVC, LAB and Enterobacteriaceae at temperature ranging from 4 °C to 20 °C. The MPD values of TVC ranged between 7.09 and 8.01 for the spice treated meat samples in the studied temperatures from 4 °C to 20 °C. In the case of LAB, MPD values were in the range from 6.42 to 7.29 log CFU g1 from 4 °C to 20 °C. The values of MPD for Enterobacteriaceae, ranged between 6.04 and 6.91 log CFU g1 at the storage temperature range from 4 °C to 20 °C. In all cases, the increase in temperature showed an increase in the maximal growth rate (lmax). In the control samples (NC and PC) stored at 4 °C, the lmax values were observed as follows for TVC, LAB and Enterobacteriaceae 0.659 and 0.579, 0.470 and 0.380, 0.609 and 0.515 respectively. The lmax values were found as follows 0.779 and 0.669, 0.710 and 0.441, 1.249 and 0.688 respectively for TVC, LAB and Enterobacteriaceae for the control samples (NC and PC) stored at 10 °C. At 15 °C, the lmax values of control samples (PC and NC) were recorded as 1.595 and 1.474, 1.182 and 1.101, 2.059 and 1.701 for TVC, LAB and Enterobacteriaceae respectively. At 20 °C, the values of lmax were observed as 2.050 and 1.875, 1.705 and 1.567, 2.987 and 2.707
for TVC, LAB and Enterobacteriaceae respectively for NC and PC samples. In meat samples treated with spice extracts, the lmax values were found to be in the range between 0.251 and 0.390 at 4 °C, 0.410 and 0.548 at 10 °C, 0.726 and 1.031 at 15 °C and 0.737 and 1.267 at 20 °C for TVC. The lmax values of LAB ranged between 0.137 and 0.251 at 4 °C and 0.181 and 0.331 at 10 °C. When the temperature increased to 15 °C, the lmax values were increased and they were in the range of 0.453–0.827 and 0.659–1.260 at 20 °C. The values of lmax for Enterobacteriaceae, ranged between 0.350 and 0.465 at 4 °C, 0.440 and 0.560 at 10 °C, 1.018 and 1.381 at 15 °C and 1.595 and 2.109 at 20 °C. Based on the obtained results from the meat samples treated with spice extracts, highest lmax values were obtained for Enterobacteriaceae in the meat samples at various temperatures, particularly for T-SA samples stored at 20 °C. Under controlled environmental conditions, only one species of the microflora is often responsible for spoilage (specific spoilage organism – SSO) in raw meat. The spoilage becomes evident when the spoilage reaches certain level by the SSO and/or its microbial metabolic product (Limbo et al., 2010). From the data, it was evident that Enterobacteriaceae had higher rates of growth than LAB at all four temperatures. Lactic acid bacteria was the microorganism that showed the lowest lmax values in the meat samples at different temperatures, especially in T-SA–CC–OV samples stored at 4 °C. It may be due to the stronger antimicrobial activity shown by mixed spice extracts when compared with their respective individual activity (Djenane et al., 2003). The strong antimicrobial effect of the combination of S. aromaticum, C. cassia and O. vulgare extracts observed in the present study could be a result of synergistic actions of specific compounds present in the mixed spice extracts. Synergistic inhibitory effects on food-borne bacteria had been observed when spice extracts were combined (Dufour et al., 2003; Radha krishnan et al., 2014a). The antimicrobial activities of phenolic compounds in the spice extracts may involve multiple modes of action (Lambert et al., 2001). For example, phenolic compounds can degrade the cell wall, disrupt the cytoplasmic membrane, cause leakage of cellular components, change fatty acid and phospholipid constituents, influence the synthesis of DNA and RNA and destroy protein translocation (Shan et al., 2007). The exact target(s) for natural antimicrobials are often not known or well defined, as it is difficult to identify a specific action site where many interacting reactions take place simultaneously. 3.2. Effect of temperature on specific growth rate (l) and lag phase duration The values of El were calculated by plotting ln l vs. 1/T for each type of bacteria. The results obtained along with the coefficients of regression for the three types of microorganisms studied were presented in Table 5. From the results it was found that the lactic acid bacteria showed the higher El value than the values shown by Enterobacteriaceae in the meat samples. The highest El value for LAB was observed in the meat samples treated with O. vulgare
35
K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37 Table 7 TBARS values of raw chicken meat samples stored at different temperatures (4, 10, 15 and 20 °C). Sample
Days
4 °C
10 °C
15 °C
a,A
a,A
a,A
20 °C
NC
0 1 2 4 6 10 15 20
0.72 0.85a,A 0.99a,A 0.94b,A 1.29a,A 1.41a,A 1.58a,A 1.88a,A
0.72 1.09a,A 1.33a,A 1.71a,A 1.91a,A 2.31a,A – –
0.72 1.29a,A 1.59a,A 1.97a,A 2.45a,A – – –
0.72a,A 1.39a,A 1.77a,A 2.29a,A – – – –
PC
0 1 2 4 6 10 15 20
0.72a,A 0.96b,A 1.02a,B 1.29a,B 1.19b,B 1.97a,B 1.82c,B 2.12a,B
0.72a,A 1.25a,B 1.49a,B 1.87a,A 2.38a,B 2.62a,B – –
0.72a,A 1.37a,B 1.78a,B 2.21a,B 2.54a,A – – –
0.72a,A 1.51a,B 1.99a,B 2.41a,B – – – –
T-SA
0 1 2 4 6 10 15 20
0.72a,A 0.63c,B 0.92a,A 1.02a,A 1.29a,A 1.49a,A 1.71a,C 1.86a,A
0.72a,A 0.96a,C 1.12a,C 1.46a,B 1.79a,A 2.01a,C – –
0.72a,A 1.26a,A 1.69a,B 1.86a,C 2.10a,B – – –
0.72a,A 1.35a,A 1.78a,A 2.11a,C – – – –
T-CC
0 1 2 4 6 10 15 20
0.72a,A 0.85a,B 0.74b,C 1.11a,A 1.35a,A 1.53a,A 1.74a,C 1.79a,A
0.72a,A 1.02a,A 1.39a,A 1.21a,C 1.71a,C 1.99a,C – –
0.72a,A 1.21a,A 1.94a,C 1.81b,C 2.14a,B – – –
0.72a,A 1.29a,C 1.65a,C 1.98a,D – – – –
T-OV
0 1 2 4 6 10 15 20
0.72a,A 0.92a,B 0.71b,C 1.06a,A 1.38a,A 1.29c,C 1.61a,A 1.81a,A
0.72a,A 1.29a,B 1.25b,A 1.74a,A 1.69c,C 2.04a,C – –
0.72a,A 1.29a,A 1.49a,D 1.76a,C 2.19a,B – – –
0.72a,A 1.41a,A 1.72a,A 2.05a,C – – – –
T-SA–CC
0 1 2 4 6 10 15 20
0.72a,A 0.84a,A 0.91a,A 1.09a,A 1.41a,A 1.34b,C 1.44a,D 1.59a,C
0.72a,A 1.08a,A 1.28a,D 1.25b,C 1.78a,A 1.91a,C – –
0.72a,A 1.19a,A 1.41a,D 1.68a,D 2.04a,C – – –
0.72a,A 1.32a,C 1.59a,C 1.89a,E – – – –
T-SA–OV
0 1 2 4 6 10 15 20
0.72a,A 0.81a,A 0.83a,D 1.05a,A 1.32a,A 1.24b,C 1.41a,D 1.68a,C
0.72a,A 0.97a,C 1.08a,C 1.49a,B 1.41b,D 1.94a,C – –
0.72a,A 1.09a,C 1.39a,D 1.69a,D 2.01a,C – – –
0.72a,A 1.48a,B 1.68a,C 1.95a,D – – – –
T-CC–OV
0 1 2 4 6 10 15 20
0.72a,A 0.85a,A 0.74b,C 1.08a,A 1.32a,A 1.27c,C 1.41a,D 1.56a,C
0.72a,A 1.01a,A 1.14a,C 1.24a,C 1.45a,D 1.82a,D – –
0.72a,A 1.21a,A 1.70a,B 1.61b,D 1.98a,C – – –
0.72a,A 1.36a,A 1.74a,A 1.98a,D – – – –
T-SA–CC–OV
0 1 2 4
0.72a,A 0.69c,B 0.79b,C 0.91a,A
0.72a,A 1.02a,A 1.26a,B 1.24b,C
0.72a,A 1.06a,C 1.48a,D 1.39a,E
0.72a,A 1.33a,C 1.61a,C 1.79a,E (continued on next page)
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K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
Table 7 (continued) Sample
a–c A–E
Days
4 °C
10 °C
15 °C
20 °C
6 10 15 20
1.11a,C 1.25a,C 1.38a,D 1.48a,C
1.37a,D 1.75a,D – –
1.83a,D – – –
– – – –
Means with the same superscript within same row do not differ significantly (p > 0.05). Means with the same superscript within same column do not differ significantly (p > 0.05).
extracts (T-OV). The highest El value for Enterobacteriaceae was recorded in the T-CC samples. The high R2 values show an Arrhenius dependence on temperature both for LAB and Enterobacteriaceae. Concerning the effect of temperature on lag phase duration and specific growth rate, the higher El values of LAB indicated that their growth was affected more by temperature shifts than the growth of Enterobacteriaceae. The values of E1/LPD for each type of bacteria were obtained by plotting ln1/LPD vs. 1/T and the values were presented in Table 5. From the observed data, it was noticed that lactic acid bacteria showed higher E1/LPD values than values shown by Enterobacteriaceae and the highest E1/LPD was found in the T-SA– CC–OV samples. As like LAB, the highest E1/LPD value for Enterobacteriaceae was also observed in the T-SA–CC–OV samples. 3.3. Color values The color of fresh meat is one of the main factors as consumers use discoloration as an indicator of freshness and wholesomeness for its acceptability (Mancini and Hunt, 2005). Lightness (L⁄), redness (a⁄) and yellowness (b⁄) of meat samples with or without added spice extracts (not shown in table) were measured and these values were used to calculate chroma and hue index values (Table 6). The lightness (L⁄) values of meat samples were altered slightly by the addition of spice extracts at all storage temperatures. L⁄ values of meat samples treated with spice extracts were found to be increased during the storage period. However, L⁄ values of both control samples (PC and NC) gradually decreased and showed lower values at the end of the storage period. In all samples redness (a⁄ values) declined incrementally as the storage time progressed but red color of the control sample faded very rapidly. The redness of the control samples (PC and NC) decreased significantly while that of spice treated meat samples decreased slightly during storage. Several authors have studied the effect of different antioxidants on the color of meat and meat products (Higgins et al., 1998; Lee et al., 1998; Radha krishnan et al., 2014b) and have reported that meat oxidation decreases a⁄ values. To some extent, the present study revealed the protective effects of spice extracts against the decrease in a⁄ values in raw meat during storage. The yellowness (b⁄ values) values of all meat samples followed a pattern similar to a⁄ values. The b⁄ values were decreased during storage at different temperatures. The Hue index values of all meat samples were found to be increased gradually during the storage at different temperatures. The increase in of Hue index depended on the storage temperature and time as reported by many authors (Akarpat et al., 2008; Georgantelis et al., 2007). The increase in Hue index may be due to the gradual oxidation of myoglobin and accumulation of metmyoglobin with time (Mancini and Hunt, 2005; Ruiz de Huidobro et al., 2003). The chroma values of all meat samples were gradually decreased during storage at different temperatures as it depend on the redness (a⁄) and yellowness (b⁄) values. As both values decreased during storage at different temperatures the chroma values also decreased when moving from 4 °C to 20 °C.
3.4. TBARS values Lipid oxidation was analyzed in raw meat samples using the TBARS distillation method (Table 7). The TBARS method has been widely used to estimate the degree of lipid oxidation in meat products. TBARS are produced through second stage autooxidation during which peroxides are oxidized to aldehydes and ketones (e.g., MDA – Malondialdehyde). Table 7 shows the effect of spice extracts on TBARS values of raw meat samples during storage at different temperatures. These results indicate that spice extracts were effective in lowering the TBARS values of meat samples when compared to control samples (NC and PC). The increase in TBARS values of all the spice treated samples was slow and remained low during their storage period than the control samples. In general, storage time has a significant influence on the development of lipid oxidation in meat samples, resulting in extensive increases in TBARS values during the storage period. The TBARS values of all the treatment samples were considerably lower than the control on all days and the treatment with combined spice extracts (T-SA–CC–OV) suppressed lipid oxidation more than the other spice treated samples, indicating the high protective effect against lipid oxidation in raw meat. The effect of spice extracts may be related to its phenolic constituents. The phenolic compounds are of great interest as they have biochemical and pharmacological effects including anticarcinogenic and antioxidant effects (Doshi et al., 2006). Several studies have reported on the relationship between phenolic content and antioxidant activity (Velioglu et al., 1998; Wong et al., 1995).
4. Conclusion In the present work the individual and simultaneous effects of S. aromaticum (SA), C. cassia (CC) and O. vulgare (OV) extracts on raw chicken meat were studied by analyzing microbial counts, color values and TBARS values; the effects of temperature (4, 10, 15 and 20 °C) were considered as an important factor. Gompertz derived parameters were determined in order to compare the effects of temperatures on microbial growth. In all cases, the increase in temperature showed an increase in the maximal growth rate (lmax). From the results, it was observed that the meat samples treated with spice extracts had highest lmax values for Enterobacteriaceae at various temperatures and particularly for T-SA samples stored at 20 °C, when compared with LAB counts. In the case of lactic acid bacteria, it showed the lowest lmax values in the meat samples, especially in T-SA–CC–OV samples stored at 4 °C. The effect of temperature on specific microbial growth and lag phase duration values were modeled through Arrhenius equation, determining the corresponding activation energies. Lactic acid bacteria showed the highest value of activation energy (El) for the specific growth rate in raw chicken meat samples treated with O. vulgare extracts (T-OV) and the highest values of activation energy for the adaptation period (E1/LPD) were found for Enterobacteriaceae in the T-SA–CC–OV samples.
K. Radha krishnan et al. / Journal of Food Engineering 166 (2015) 29–37
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