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.
Trang 1Evaluation and predictive modeling the effects of spice extracts
on raw chicken meat stored at different temperatures
K Radha krishnana, S Babuskina, P Azhagu Saravana Babua, M Sivarajanb, M Sukumara,⇑
a
Centre for Biotechnology, A.C Tech., Anna University, Chennai 25, India
b
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 Highestlmaxand LPD (lag phase duration) values were obtained for Enterobacteriaceae in T-SA
(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
there-fore 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
poten-tial to be applied as food preservatives Essenpoten-tial oils and other
extracts from plants, herbs and spices and some of their
constituents, have shown antimicrobial activity against different
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 car-vacrol are identified as the major chemical components responsi-ble 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, antibac-terial 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 pre-dict 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 deter-mining its storage life Mathematical models fulfill the research gap on the inactivation kinetics of natural antimicrobial extracts
http://dx.doi.org/10.1016/j.jfoodeng.2015.05.021
0260-8774/Ó 2015 Elsevier Ltd All rights reserved.
⇑ Corresponding author.
E-mail address: sukumaractech@gmail.com (M Sukumar).
Contents lists available atScienceDirect
Journal of Food Engineering
j o u r n a l h o m e p a g e : w w w e l s e v i e r c o m / l o c a t e / j f o o d e n g
Trang 2on 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,land 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
extrac-tor 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
trans-ferred through insulated polystyrene boxes to the laboratory
within 1 h of production Fresh meat samples were obtained
sepa-rately 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 colony-forming units (CFU) were counted and the results expressed in log-arithmic 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 R 2
NC Total viable count 0.659 7.33 8.96 0.96
Lactic acid bacteria 0.470 6.81 7.95 0.97 Enterobacteriaceae 0.609 7.18 7.15 0.95
PC Total viable count 0.579 7.27 8.68 0.94
Lactic acid bacteria 0.380 6.72 7.59 0.95 Enterobacteriaceae 0.515 7.06 6.78 0.98 T-SA Total viable count 0.306 7.02 7.61 0.97
Lactic acid bacteria 0.239 6.51 6.95 0.98 Enterobacteriaceae 0.465 6.99 6.57 0.95 T-CC Total viable count 0.389 7.11 7.95 0.97
Lactic acid bacteria 0.251 6.56 7.01 0.96 Enterobacteriaceae 0.391 6.88 6.24 0.98 T-OV Total viable count 0.364 7.09 7.85 0.99
Lactic acid bacteria 0.242 6.54 6.97 0.93 Enterobacteriaceae 0.454 6.98 6.52 0.95 T-SA–CC Total viable count 0.283 7.00 7.49 0.98
Lactic acid bacteria 0.192 6.47 6.72 0.95 Enterobacteriaceae 0.413 6.91 6.34 0.97 T-SA–OV Total viable count 0.352 7.07 7.81 0.94
Lactic acid bacteria 0.206 6.49 6.79 0.96 Enterobacteriaceae 0.400 6.89 6.28 0.97 T-CC–OV Total viable count 0.390 7.11 7.96 0.98
Lactic acid bacteria 0.192 6.47 6.75 0.97 Enterobacteriaceae 0.360 6.82 6.09 0.98 T-SA–CC–OV Total viable count 0.251 6.96 7.35 0.97
Lactic acid bacteria 0.137 6.36 6.42 0.97 Enterobacteriaceae 0.350 6.79 6.04 0.98
lmax : (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g 1 )).
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%
Trang 3has been used to estimate the response variables (lag phase
dura-tion, maximal growth rate and maximum population density)
logðCFUÞ ¼ K þ D exp exp lmax 2:7182
LPD t A
þ 1
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;lmaxis 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 R2value
Arrhenius equation was applied to understand the effect of
stor-age temperature on the specific growth rate (l),
l¼ A expðEl=RTÞ ð2Þ
where A is a pre exponential factor (log (CFU g1) days1), Elis 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 Eland calculated using
Eq.(3)
lnl¼ ln A El=RT ð3Þ
Elvalues for each type of bacteria were calculated by plotting the values of lnlvs 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 tem-perature 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
where D is a pre exponential factor (days1), E1/LPDis 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/LPDcan be consid-ered 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 R 2
NC Total viable count 1.595 2.32 8.85 0.98
Lactic acid bacteria 1.182 2.17 7.81 0.96 Enterobacteriaceae 2.059 2.13 7.89 0.98
PC Total viable count 1.474 2.31 8.68 0.97
Lactic acid bacteria 1.101 2.16 7.68 0.96 Enterobacteriaceae 1.701 2.08 7.39 0.97 T-SA Total viable count 0.970 2.24 7.91 0.96
Lactic acid bacteria 0.766 2.09 7.10 0.93 Enterobacteriaceae 1.307 2.00 6.79 0.95 T-CC Total viable count 1.031 2.25 8.01 0.98
Lactic acid bacteria 0.793 2.10 7.15 0.97 Enterobacteriaceae 1.363 2.02 6.88 0.97 T-OV Total viable count 1.019 2.24 7.99 0.99
Lactic acid bacteria 0.827 2.11 7.21 0.98 Enterobacteriaceae 1.381 2.02 6.91 0.97 T-SA–CC Total viable count 0.793 2.21 7.61 0.99
Lactic acid bacteria 0.579 2.05 6.74 0.96 Enterobacteriaceae 1.107 1.96 6.45 0.97 T-SA–OV Total viable count 0.856 2.22 7.72 0.98
Lactic acid bacteria 0.634 2.06 6.85 0.96 Enterobacteriaceae 1.124 1.96 6.48 0.97 T-CC–OV Total viable count 0.940 2.24 7.86 0.96
Lactic acid bacteria 0.670 2.07 6.92 0.96 Enterobacteriaceae 1.200 1.98 6.61 0.98 T-SA–CC–OV Total viable count 0.726 2.20 7.49 0.96
Lactic acid bacteria 0.453 2.01 6.48 0.97 Enterobacteriaceae 1.018 1.93 6.29 0.97
lmax : (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g 1 )).
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%
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 R 2
NC Total viable count 0.779 4.56 8.62 0.98
Lactic acid bacteria 0.710 4.36 7.81 0.97
Enterobacteriaceae 1.249 4.63 7.91 0.98
PC Total viable count 0.669 4.51 8.31 0.97
Lactic acid bacteria 0.441 3.69 7.68 0.94
Enterobacteriaceae 0.688 3.87 7.42 0.98
T-SA Total viable count 0.501 4.43 7.81 0.98
Lactic acid bacteria 0.289 3.50 7.02 0.95
Enterobacteriaceae 0.530 3.69 6.79 0.97
T-CC Total viable count 0.548 4.45 7.95 0.95
Lactic acid bacteria 0.314 3.54 7.15 0.97
Enterobacteriaceae 0.552 3.72 6.88 0.96
T-OV Total viable count 0.515 4.44 7.85 0.96
Lactic acid bacteria 0.331 3.56 7.21 0.95
Enterobacteriaceae 0.560 3.73 6.91 0.93
T-SA–CC Total viable count 0.453 4.40 7.66 0.99
Lactic acid bacteria 0.231 3.41 6.74 0.96
Enterobacteriaceae 0.449 3.57 6.45 0.97
T-SA–OV Total viable count 0.460 4.41 7.68 0.98
Lactic acid bacteria 0.254 3.45 6.85 0.95
Enterobacteriaceae 0.456 3.59 6.48 0.96
T-CC–OV Total viable count 0.501 4.43 7.81 0.99
Lactic acid bacteria 0.268 3.47 6.92 0.95
Enterobacteriaceae 0.486 3.63 6.61 0.96
T-SA–CC–OV Total viable count 0.410 4.38 7.52 0.98
Lactic acid bacteria 0.181 3.33 6.48 0.99
Enterobacteriaceae 0.440 3.55 6.41 0.96
lmax : (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g 1 )).
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).
Trang 4Associates Laboratory Inc., Reston, VA, USA) Color was described
as L⁄(lightness), a⁄(redness), and b⁄(yellowness) color space val-ues 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 ¼b
a Chroma ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
a2þ b2
q
ð6Þ
2.8 Thiobarbituric acid reactive substances (TBARS) value Meat samples were analyzed for Thiobarbituric acid reactive substances (TBARS) as per the method described byDu and Ahn (2002) Five grams of meat was homogenized with 15 mL of deion-ized distilled water 1 mL of the meat homogenate was transferred
to a test tube and 50lL 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
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 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 R 2
NC Total viable count 2.050 1.05 8.56 0.96
Lactic acid bacteria 1.705 0.93 7.79 0.97
Enterobacteriaceae 2.987 0.99 7.77 0.97
PC Total viable count 1.875 1.04 8.39 0.98
Lactic acid bacteria 1.567 0.92 7.64 0.98
Enterobacteriaceae 2.707 0.97 7.51 0.97
T-SA Total viable count 1.267 1.00 7.74 0.96
Lactic acid bacteria 1.144 0.88 7.15 0.98
Enterobacteriaceae 2.109 0.92 6.91 0.97
T-CC Total viable count 1.215 1.00 7.68 0.99
Lactic acid bacteria 1.193 0.89 7.21 0.98
Enterobacteriaceae 2.016 0.91 6.81 0.98
T-OV Total viable count 1.241 1.01 7.71 0.99
Lactic acid bacteria 1.260 0.92 7.29 0.97
Enterobacteriaceae 2.063 0.91 6.86 0.96
T-SA–CC Total viable count 0.971 0.89 7.39 0.95
Lactic acid bacteria 0.938 0.86 6.89 0.96
Enterobacteriaceae 1.748 0.89 6.51 0.98
T-SA–OV Total viable count 1.070 0.99 7.51 0.96
Lactic acid bacteria 0.953 0.86 6.91 0.96
Enterobacteriaceae 1.809 0.89 6.58 0.93
T-CC–OV Total viable count 1.020 0.98 7.45 0.98
Lactic acid bacteria 0.915 0.86 6.86 0.96
Enterobacteriaceae 1.844 0.90 6.62 0.97
T-SA–CC–OV Total viable count 0.737 0.96 7.09 0.97
Lactic acid bacteria 0.659 0.83 6.51 0.95
Enterobacteriaceae 1.595 0.87 6.33 0.96
lmax : (Dlog (CFU/g)/day); LPD: days; MPD: (log (CFU g 1 )).
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).
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.
E 1/LPD1 (kJ/mol) R 2
E 1/LPD1 (kJ/mol) R 2
El 1
El 1
Trang 5Table 6
Color parameters of raw chicken meat samples stored at different temperatures (4, 10, 15 and 20 °C).
16.92 a,A
1.67 a,A
17.02 a,B
1.69 a,A
16.83 a,C
1.68 a,A
16.87 a,A
1 1.71 a,A
16.77 a,A
1.66 a,A
16.74 a,A
1.82 b,B
16.59 a,B
1.78 a,B
16.90 b,C
2 1.75 a,A 16.56 a,A 1.73 a,A 16.72 a,A 1.79 a,A 15.60 a,B 1.69 b,B 15.70 a,B
4 1.86 a,A 16.69 b,A 1.77 a,B 16.44 a,B 1.75 b,B 14.14 a,C 1.83 a,A 15.11 a,D
6 1.92 a,A
16.05 a,A
1.81 a,B
16.19 a,A
1.88 a,A
14.71 a,B
10 1.93 a,A
15.59 c,A
1.86 a
15.75 a,A
15 1.94 a,A
15.72 a,A
20 1.96 a,A
15.39 a,A
16.92 a,A
1.67 a,A
17.02 a,B
1.69 a,A
16.83 a,C
1.68 a,A
16.87 a,A
1 1.75 a,A
16.82 a,A
1.70 a,A
16.63 a,A
1.74 a,A
16.36 a,B
1.75 a,A
16.19 a,C
16.52 a,A
1.74 b,A
16.61 a,A
1.56 c,B
15.84 a,B
1.71 b,A
15.52 a,C
4 1.89 a,A
16.29 a,A
1.70 a,B
16.48 a,A
1.84 a,A
14.92 a,B
1.90 a,A
14.82 a,B
6 1.95 a,A
16.38 b,A
1.76 a,B
15.99 a,B
1.87 a,A
14.39 a,C
15 1.97 a,A
15.23 a,A
20 2.01 a,A
15.06 a,A
16.93 a,A
1.67 a,A
17.02 a,B
1.69 a,A
16.83 a,C
1.68 a,A
16.87 a,A
1 1.72 a,A 16.78 a,A 1.72 a,A 16.67 a,A 1.66 a,A 16.70 a,A 1.75 a 16.29 a,B
2 1.74 a,A 16.70 a,A 1.70 b,A 16.84 a,A 1.69 c,A 16.11 a,B 1.68 b,A 15.46 a,C
4 1.79 a,A
16.81 b,A
1.76 a,A
16.80 a,A
1.80 a,A
15.63 a,B
1.80 a,A
15.69 b,B
6 1.80 a,A
16.69 a,A
1.76 a,A
16.54 a,A
1.80 d,A
15.18 a,B
10 1.82 a,A
16.50 a,A
1.81 a,A
16.20 a,B
15 1.89 a,A
16.28 a,A
20 1.88 a,A
16.02 a,A
16.92 a,A
1.68 a,A
17.02 a,B
1.69 a,A
16.83 a,C
1.68 a,A
16.87 a,A
1 1.74 a,A
16.85 a,A
1.72 a,A
16.89 a,A
1.70 a,A
16.39 a,B
1.79 a,A
16.30 a,B
2 1.77 a,A
16.87 a,A
1.75 a,A
16.68 a,A
1.65 e,B
15.92 a,B
1.83 a,A
15.74 a,B
16.93 c,A
1.72 b,A
16.66 b,B
1.77 a,A
15.47 a,C
1.74 c,A
15.24 a,C
15 1.93 a,A
16.50 a,A
20 1.97 a,A
16.30 a,A
1 1.76 a,A 16.65 b,A 1.66 a,A 17.17 c,B 1.71 a,A 16.45 a,C 1.64 d,A 16.67 a,C
2 1.80 a,A
16.80 a,A
1.70 a,A
16.93 a,A
1.75 a,A
16.06 a,B
1.76 a,A
15.05 c,C
4 1.83 a,A
16.55 a,A
1.75 a,A
16.71 a,A
1.76 a,A
15.51 a,B
1.84 a,A
15.29 a,B
16.55 a,A
1.82 a,A
16.21 a,A
1.81 a,A
15.03 a,B
10 1.84 a,A
16.21 a,A
1.87 a,A
15.97 a,A
15 1.93 c,A
15.90 a,A
16.92 a,A
1.67 a,A
17.02 a,B
1.69 a,A
16.83 a,C
1.68 a,A
16.87 a,A
1 1.71 a,A
16.93 a,A
1.61 c,A
16.93 a,A
1.71 a,A
16.44 a,A
1.70 a,A
15.94 a,B
2 1.74 a,A
16.97 c,A
1.68 a,A
16.95 c,A
1.64 c,A
16.17 a,B
1.65 d,A
16.44 d,C
4 1.74 a,A 16.84 a,A 1.69 a,A 16.62 a,A 16.58 a,A 1.77 a,A 15.64 a,B 1.77 a,A 15.68 a,B
10 1.84 a,A
16.59 a,A
1.80 a,A
16.32 a,A
15 1.85 a,A
16.40 a,A
20 1.90 a,A
16.14 a,A
T-SA–OV 0 1.68 a,A 16.92 a,A 1.67 a,A 17.02 a,B 1.69 a,A 16.83 a,C 1.68 a,A 16.87 a,A
1 1.67 a,A
17.01 c,A
1.67 a,A
17.04 a,A
1.74 a,A
16.50 a,B
1.74 a,A
16.35 a,B
2 1.70 a,A
16.94 a,A
1.67 a,A
16.76 a,A
1.75 a,A
16.00 a,B
1.80 a,A
15.97 a,B
4 1.77 a,A
16.93 a,A
1.72 a,A
16.42 a,B
1.81 a,A
15.55 a,B
1.81 a,A
15.67 a,B
6 1.84 a,A
16.70 a,A
1.81 a,A
16.33 a,B
1.86 a,A
15.34 a,C
10 1.84 a,A
16.42 a,A
1.82 a,A
16.08 a,B
16.92 a,A
1.67 a,A
17.02 a,B
1.69 a,A
16.83 a,C
1.68 a,A
16.87 a,A
1 1.71 a,A
17.00 c,A
1.75 a,A
16.98 a,A
1.70 a,A
16.53 a,B
1.73 a,A
16.60 a,B
2 1.78 a,A
16.96 a,A
1.71 b,A
16.93 a,A
1.74 a,A
16.09 a,B
1.60 e,B
15.99 a,B
4 1.81 a,A 16.92 c,A 1.74 a,A 16.81 a,A 1.76 a,A 15.62 a,B 1.80 a,A 15.55 a,B
6 1.86 a,A
16.60 a,A
1.74 a,A
16.50 a,A
1.80 a,A
15.11 a,B
10 1.87 a,A
16.34 a,A
1.80 a,A
16.12 a,A
15 1.92 a,A
16.41 d,A
20 1.92 a,A
16.11 a,A
T-SA–CC–OV 0 1.68 a,A 16.93 a,A 1.67 a,A 17.02 a,B 1.69 a,A 16.83 a,C 1.68 a,A 16.87 a,A
16.89 a,A
1.66 a,A
17.09 d,A
1.70 a,A
16.49 a,B
1.69 a,A
16.12 a,B
2 1.73 a,A
16.84 a,A
1.67 d,A
16.88 a,A
1.63 b,A
16.29 a,B
1.72 a,A
16.58 a,B
4 1.75 a,A
17.05 c,A
1.70 a,A
16.57 a,B
1.74 a,A
15.93 a,C
1.74 a,A
15.90 a,C
6 1.68 c,A
16.82 a,A
1.73 a,A
16.62 a,A
1.78 a,A
15.70 a,B
(continued on next page)
Trang 63 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
moni-tored 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
cal-culated and presented inTables 1–4for different storage
tempera-tures 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 7.331days for TVC, LAB and
Enterobacteriaceae from 4 °C to 20 °C In the case of TVC, LPD
ran-ged between 0.891 and 7.111days for the spice treated meat
samples at the temperature range from 4 °C to 20 °C The LPD
val-ues of LAB ranged between 0.831and 6.561days for meat
sam-ples 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
var-ied 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 g1from 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, thelmaxvalues 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 Thelmaxvalues 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, thelmaxvalues 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 oflmaxwere
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 lmaxvalues 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 Thelmaxvalues 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, thelmax values were increased and they were in the range of 0.453–0.827 and 0.659–1.260 at
20 °C The values oflmaxfor 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 envi-ronmental 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 cer-tain 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 lowestlmaxvalues 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 com-bination 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 com-ponents, change fatty acid and phospholipid constituents, influ-ence 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 Elwere calculated by plotting lnlvs 1/T for each type of bacteria The results obtained along with the coefficients of regression for the three types of microorganisms studied were pre-sented inTable 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
Table 6 (continued)
10 1.77 a,A
16.51 a,A
1.76 a,A
16.44 a,A
15 1.82 a,A
16.43 a,A
a–c
Means with the same superscript within same row do not differ significantly (p > 0.05).
A–E
Means with the same superscript within same column do not differ significantly (p > 0.05).
Trang 7Table 7
TBARS values of raw chicken meat samples stored at different temperatures (4, 10, 15 and 20 °C).
0.72 a,A
0.72 a,A
0.72 a,A
1.09 a,A
1.29 a,A
1.39 a,A
1.71 a,A
1.97 a,A
2.29 a,A
1.91 a,A
2.45 a,A
–
2.31 a,A
0.72 a,A
0.72 a,A
0.72 a,A
1.25 a,B
1.37 a,B
1.51 a,B
1.49 a,B
1.78 a,B
1.99 a,B
1.87 a,A
2.21 a,B
2.41 a,B
0.72 a,A
0.72 a,A
0.72 a,A
1.46 a,B
1.86 a,C
2.11 a,C
1.79 a,A
2.10 a,B
–
2.01 a,C
0.72 a,A
0.72 a,A
0.72 a,A
1.02 a,A
1.21 a,A
1.29 a,C
1.39 a,A
1.94 a,C
1.65 a,C
1.21 a,C
1.81 b,C
1.98 a,D
1.25 b,A
1.49 a,D
1.72 a,A
1.74 a,A
1.76 a,C
2.05 a,C
1.69 c,C
2.19 a,B
–
2.04 a,C
0.72 a,A
0.72 a,A
0.72 a,A
1.08 a,A
1.19 a,A
1.32 a,C
1.28 a,D
1.41 a,D
1.59 a,C
1.91 a,C
0.97 a,C
1.09 a,C
1.48 a,B
1.08 a,C
1.39 a,D
1.68 a,C
1.49 a,B
1.69 a,D
1.95 a,D
1.41 b,D
2.01 a,C
–
1.94 a,C
0.72 a,A
0.72 a,A
0.72 a,A
1.01 a,A
1.21 a,A
1.36 a,A
1.45 a,D
1.98 a,C
–
1.82 a,D
0.72 a,A
0.72 a,A
0.72 a,A
1.02 a,A
1.06 a,C
1.33 a,C
1.26 a,B
1.48 a,D
1.61 a,C
1.24 b,C
1.39 a,E
1.79 a,E (continued on next page)
Trang 8extracts (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/LPDfor each type of bacteria were obtained by
plotting ln1/LPDvs 1/T and the values were presented inTable 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/LPDwas 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⁄),
red-ness (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
tempera-tures L⁄values of meat samples treated with spice extracts were
found to be increased during the storage period However, L⁄
val-ues 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
met-myoglobin 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
val-ues 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 prod-ucts TBARS are produced through second stage autooxidation dur-ing 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 gen-eral, 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 consider-ably 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 pro-tective 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 antioxi-dant 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 highestlmax values for Enterobacteriaceae at various temperatures and particu-larly for T-SA samples stored at 20 °C, when compared with LAB counts In the case of lactic acid bacteria, it showed the lowestlmax 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 bac-teria 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
Table 7 (continued)
1.37 a,D
1.83 a,D
–
a–c
Means with the same superscript within same row do not differ significantly (p > 0.05).
A–E
Means with the same superscript within same column do not differ significantly (p > 0.05).
Trang 9The results from the present study showed that the
combina-tion 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’’
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