Pork detection in binary meat mixtures and some commercial food products using conventional and real-time PCR techniques

Food Chemistry 219 (2017) 54–60

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Food Chemistry journal homepage: www.elsevier.com/locate/foodchem

Pork detection in binary meat mixtures and some commercial food products using conventional and real-time PCR techniques Hassan A. Al-Kahtani a, Elsayed A. Ismail a,b, Mohammed Asif Ahmed a,⇑ a b

Food Science & Nutrition Dept., College of Food & Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia Department of Food Science, Faculty of Agriculture, Benha University, Benha 13518, Egypt

a r t i c l e

i n f o

Article history: Received 31 May 2015 Received in revised form 28 August 2016 Accepted 16 September 2016 Available online 17 September 2016 Chemical compounds studied in this article: Agarose (PubChem CID: 11966311) Ethidium bromide (PubChem CID: 14710) TAE buffer (PubChem CID: 21257724)

a b s t r a c t Pork DNA was detected in meat mixtures using both conventional PCR and real-time PCR (RT-PCR). Thirty meat mixtures containing beef, chicken, camel, rabbit, goat and sheep with varying percentage of pork (0%, 1%, 5%, 10%, and 20%) and 75 commercial food products, were analyzed using conventional and RT-PCR to determine the presence of pork DNA. Pork DNA standard curves and cycle threshold (Ct) values were used for quantification. The detection limits for pork DNA in the mixtures were 0.22, 0.047, 0.048, 0.0000037, 0.015 ng/ll respectively. Unlike conventional PCR, RT-PCR detected pork DNA in nine processed food samples [chicken sausages (2), chicken luncheon (2), turkey meat loaf, milk chocolate with soft nougat, jelly, cake, and candies] at pork DNA concentrations of 0.0001 ng/ll or less. Ó 2016 Elsevier Ltd. All rights reserved.

Keywords: Meat mixtures Real time PCR Pork adulteration Commercial food products

1. Introduction Authenticity is an important criterion for food safety and quality. Foods with Halal or Kosher certification are readily accepted by Muslim and Jewish consumers to whom consumption of pork and its derivatives in any product is prohibited Regenstein, Chaudry, and Regenstein (2003). It is assumed that Halal or Kosher foods are wholesome, as specified by religious texts, but also are hygienic and safe to eat, and that certification protects against fraud and adulteration Ebbeca and Thomsen (1991). Muslims are expected to account for 30% of the world’s population by the year 2025 Farouk et al. (2006). The Halal food market currently accounts for as much as 12% of the global trade in agro-food products CPH World Media (2016). There are various analytical methods that have been used to detect pork adulteration in mixed meat samples and/or identify meat from other animal species as contaminants. These include high-performance liquid chromatography Toorop, Murch, and Ball (1997), electrophoretic techniques Özgun-Arun and Ugur

⇑ Corresponding author. E-mail address: [email protected] (M. Asif Ahmed). http://dx.doi.org/10.1016/j.foodchem.2016.09.108 0308-8146/Ó 2016 Elsevier Ltd. All rights reserved.

(2000), enzyme-linked immunosorbent assays Hajmeer, Cliver, and Provost (2003), Doi, Watanabe, Shibata, and Tanabe (2009) and Fourier transform infrared (FTIR) spectroscopy Hashim et al. (2010), Rohamn, Sismindari, and Che Man (2011). In recent years, significant attention has been turned toward DNA-based approaches, which have proven to be reliable, sensitive and rapid for many aspects of food authentication. Among them, the polymerase chain reaction (PCR) is undoubtedly the most common technique used to trace the origin (animal species) of the contaminating meat Calvo, Osta, and Zaragoza (2002), Tasara, Sandra, and Roger (2005), Aida, Che Man, Raha, and Son (2007), Tanabe et al. (2007), Kesmen, Gulluce, Sahin, and Yetim (2009), Palmieri, Bozza, and Giongo (2009), Köppel, Ruf, and Rentsch (2011), Cai, Gu, Scanlan, Ramatlapeng, and Lively (2012), Kesmen, Yetiman, Sahin, and Yetim (2012). The detection of pork and its derivatives in processed food products has been a challenge to researchers, food processors, food regulators and food industry due to the lack of reliable methods. The aim of this study was to demonstrate the capacity of PCR to detect pork in some animal meat mixtures containing pork, and the possible presence of pork DNA in some commercially processed foods from local markets in Riyadh, Saudi Arabia. Part of this work was presented at the 17th World Congress of Food Science and Technology (IUFoST) AL-Kahtani and Ismail (2014).

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2. Materials and methods 2.1. Preparation of meat mixtures Authentic canned pork luncheon meat (Product of Denmark) was purchased in Kuala Lumpur (Malaysia). Locally produced fresh cooked camel, cooked mutton and goat, and canned beef and chicken were purchased from supermarkets in Riyadh (Saudi Arabia). Fresh rabbit was purchased from a local market and cooked in our laboratory. Mixtures of these meats were spiked with 0%, 1%, 5%, 10% and 20% (w/w) pork, prepared using a warring blender (Blender 8008, Connecticut, USA) to a final weight of 100 g. To prevent any cross-contamination each mixture was processed separately using a different blender container. The mixtures of meat were immediately stored at
18 °C until DNA extraction. 2.2. Commercial processed food products Seventy-five commercial food samples were collected from local markets in Riyadh, Saudi Arabia and coded appropriately. The product description and country of origin were recorded. The food products included 30 processed meat samples, comprising beef luncheon meat, corned beef, sausages, minced beef, chicken luncheon meat, hot dogs, chicken franks, and turkey franks, 26 food products with gelatin listed on their label, comprising jelly, marshmallow, chewing gum, candies, and cake, 8 samples of cheese and ice cream, 6 samples of chocolates and burger samples from 5 franchised restaurants (Chicken Breast Fillet, Burger Chicken, Burger Tower Chicken, Succulent Piece of Chicken in a corn meal topped bun, and Chicken Big Mac). Samples were stored at
18 °C after purchase until DNA extraction. 2.3. Genomic DNA extraction DNA extraction from 2 g of meat mixtures and food samples was carried out using the DNeasyÒ mericon food kit (Qiagen, Hilden, Germany). Extraction process was conducted according to the manufacturer’s instructions. DNA concentration was estimated by UV absorption spectrophotometer at 260 nm wavelength Heptinstall and Rapley (2002).

Table 1 Specificity and sensitivity (detection limit) for pork DNA in different binary meat mixtures. Binary Meat mixtures

Ct value

Log of Conc.

Conc. (ng/ll)

Beef+ 1% pork 5% pork 10% pork 20% pork 100% pork

23.9 24.26 22.78 19.09 16.4

5.356372186 5.240426423 5.717092338 6.90553641 7.771908918

0.227143 0.17394 0.521303 8.053784 59.15616

Chicken+ 1% pork 5% pork 10% pork 20% pork 100% pork

ND 22.22 19.61 19.15 16.4

ND 5.897452414 6.738059197 6.886212116 7.771908918

ND 0.78886 5.470789 7.694847 59.15616

Camel+ 1% pork 5% pork 10% pork 20% pork 100% pork

26 23.81 20.29 18.91 16.4

4.680021901 5.385358627 6.519050533 6.963509292 7.771908918

0.047863 0.242829 3.304076 9.193905 59.15616

Rabbit+ 1% pork 5% pork 10% pork 20% pork 100% pork

25.97 20.47 18.91 18.13 16.4

4.689684048 6.461077651 6.963509292 7.214725112 7.771908918

0.048944 2.891346 9.193905 16.39457 59.15616

Goat+ 1% pork 5% pork 10% pork 20% pork 100% pork

38.74 20.27 19.71 19.42 16.4

0.576830172 6.525491964 6.70585204 6.799252794 7.771908918

3.77E-06 0.335351 5.076916 6.296511 59.15616

Sheep+ 1% pork 5% pork 10% pork 20% pork 100% pork

27.52 20.65 19.71 18.74 16.4

4.190473123 6.40310477 6.70585204 7.018261458 7.771908918

0.015505 2.52988 5.07984 10.42942 59.15616

DNA fragments in the agarose gel were visualized and photographed using a Gel Doc system (Syngene, Cambridge, UK). 2.6. Real-time PCR

2.4. Conventional PCR Conventional polymerase chain reaction (PCR) was performed in a Labnet thermal cycler (Labnet international, Inc. Edison, NJ, USA). The primers, Sus Fw (50 –CTACATAAGAATATC CACCAC–30 ) and Sus Rv (50 –ACATTGTGGGATCTTCTAGGT–30 ) and Pg Fv (50 –CTA CATAAGAATATCCACCAC–30 ) and Pg Rv (50 –AGCCTACACCACAGCCA CAG–30 ), were used for conventional PCR (Tasara et al., 2005). The PCR reaction mixture consisted of 26 ll deionised water, 1 ll (10 pmol) primer1, 1 ll (10 pmol) primer2, and 20 ll PCR master-mix. The PCR conditions used were an initial denaturation at 95 °C for 3 min followed by 30 cycles of denaturation at 98 °C for 15 s, annealing at 55 °C for 15 s, elongation at 72 °C for 30 s, final elongation at 72 °C for 5 min, and hold at 4 °C. (Fw = Forward, Rv = Reverse). 2.5. Agarose gel electrophoresis Analysis of PCR amplicons was performed using agarose gel electrophoresis. Agarose gel (1.5%) was prepared by dissolving the appropriate quantities of agarose in 1x TAE buffer (pH 8.0) in a microwave oven. Ethidium bromide stock solution was added directly to molten agarose at a concentration of 0.5 lg/ml before pouring the gel. The electrophoretic samples were mixed with 6x loading buffer before loading onto the gel. After electrophoresis,

The DNA was amplified in a Rotor-Gene Q (Qiagen, 40724 Hilden, Germany) thermal cycler, using MericonTM Plant and Animal identification assays kit, catalogue number-292013 (Qiagen, Hilden, Germany) according to MericonTM instructions. Briefly 10 ll of the extracted DNA and 10 ll of the reconstituted MericonTM assay with 45 numbers of cycles. Initial activation at 95 °C for 5 min, denaturation at 95 °C for 15 s, annealing at 60 °C for 15 s, and extension was at 72 °C for 10 s. Reactions were replicated twice per experiment and experiments were replicated three times to verify the positive results. 2.7. Sensitivity of PCR Determination of the detection limit for pork DNA was carried out using the RT-PCR as described above. The minimum quantities of DNA detected are listed in Table 1 and described as the limits of detection (LOD). 3. Results and discussion 3.1. Conventional PCR for Pork meat mixtures The agarose gel images of PCR products, obtained from conventional PCR reactions using two species-specific primers for pork

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detection in meat mixtures, are shown in Fig. 1. PCR amplification for pork DNA yielded a band of 290 bp in all meat mixtures containing pork with no cross reactivity with other meat species. The other primer pair, Pg Fw and Pg Rv (target gene: Pre-1 Sine element), yielded a band of 134 bp in all meat mixtures irrespective of the pork presence Fig. 1B. Therefore, this primer pair was not specific to pork DNA and cross-reacted with beef, chicken, camel, rabbit, goat, and sheep DNA, so it was not used in subsequent experiments. 3.2. Real time PCR amplification for pork meat mixtures The specificity analysis yielded a quantification cycle (Cq) of around 15 for 100% pork and negative results for other meat species. The analysis of cooked meat mixtures by RT-PCR demonstrated the specificity and sensitivity of the assay for pork detection over the conventional PCR. The analysis, detected pork at 1–20% in all meat mixtures with only one exception, of 1% pork-chicken where the 1% pork was not detected – see Fig. 2. Beef mixtures tested positive for pork using RT-PCR and had Ct values of

19.09, 22.78, 24.26 and 23.90 for beef meat containing 20, 10, 5 and 1% pork, respectively. The results of this test establish the reliability of the assay for detecting pork at different levels. 3.3. Linearity and sensitivity of the assay for pork DNA The linearity and sensitivity of the detection system used in this study were determined using serial dilutions of pork genomic DNA extracted from cooked pork, starting with 100 ng of DNA. The Ct values were plotted against the logarithms of DNA concentrations to create the standard curve for pork DNA. Linearity was observed for pork DNA over six orders of magnitude Fig. 3. The correlation between Ct values and log concentrations of pork template DNA showed a regression coefficient of 0.9953, indicating the possibility of a linear relationship between the Ct values and DNA concentrations in the range 100 ng to 0.001 ng pork DNA. Values could be observed even as low as 0.001 ng target DNA (corresponding to 0.001%), suggesting the detection limit of pure pork DNA using RT-PCR was 0.001%. Similar results were reported by Kesmen et al. (2012) who found that the TaqMan probe assays

Fig. 1. Agarose gel (2%) electrophoresis of PCR products for meat mixtures containing pork using pork primers. A: (Fw) CTACATAAGAATATCCACCACA and (Rv) ACATTGTGGGATCTTCTAGGT. B: (Fw) GACTAGGAACCATGAGGTTGCG and (Rv) AGCCTACACCACAGCCACAG. M: DNA ladder 100 bp. Lanes 1–5: Beef mixed with 0, 1, 5, 10, 20% pork. Lane 6–10: Chicken meat mixed with 0, 1, 5, 10, 20% pork. Lane 11–15: Camel meat mixed with 0, 1, 5, 10, 20% pork. Lane 16–20: Rabbit meat mixed with 0, 1, 5, 10, 20% pork. Lane 21–25: Goat meat mixed with 0, 1, 5, 10, 20% pork. Lane 25–30: Sheep meat mixed with 0, 1, 5, 10, 20% pork. Lane P: pork as a positive control. Lane N: negative control.

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Fig. 2. PCR amplification plot for meats containing pork. A: Beef; B: Chicken; C: Camel; D: Rabbit; E: Goat; F: Sheep. Curves in the green channel are above a preset threshold indicating the presence of target DNA in the sample and a successful PCR.

allowed the detection of 0.001% chicken and turkey in meat mixtures prepared by mixing chicken and turkey with beef at different levels (0.001–10%). Ali, Hashim, Dhahi et al. (2012) and Ali, Hashim, Mustafa et al. (2012) reported pork contaminant levels ranging from 100 to 0.01% could be detected with RT-PCR efficiency (E) of 93.8% and a correlation coefficient (R2) of 0.991. Tanabe et al. (2007) constructed a pork DNA standard curve with a calculated (R2) of 0.994 in the range of 0.001–100%. 3.4. Specificity and sensitivity (detection limit-LOD) for pork DNA in meat mixtures Pork DNA concentrations were determined using standard curve (Fig. 3) and Ct values in all the meat mixtures are shown in Table 2. The detection limits of pork DNA in all the meat mix-

tures were 0.22, 0.047, 0.048, 0.0000037, 0.015 ng/ll in porkbeef, pork-camel, pork-rabbit, pork-goat, and pork-sheep meat mixtures, respectively (Table 1). Conventional PCR focused on detection and specificity for pork DNA, using the PCR primers that amplified a 290-bp fragment without any cross reactivity and a 134-bp fragment with crossreactivity with all meat species (Fig. 1A & B). The primer pair from the 12S rRNA-tRNA Val gene produced a 290-bp PCR amplicon and was very specific for pork DNA detection in the meat mixtures, as compared to the primer pair Pg Fw and Pg Rv (target gene: Pre-1 Sine element). These results are in agreement with those obtained by Tasara, Sandra, and Roger (2005), Dalmasso et al. (2004) and S ß akalar, Abasiyanik, Bektik, and Tayyrov (2012). Walker, Hughes, Anders, Shewale, and Sinha (2003) reported that the designed primer pair Pg Fw and Pg Rv (target gene: Pre-1 Sine element) had no

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Fig. 3. Pork genomic DNA Standard curve where Ct was plotted against Log DNA concentration (pg/ml) of DNA standard solution. Ct represents the PCR cycle at which fluorescence reaches threshold value.

cross-reactivity with other meat species. In this study, the detection of 1% pork in meat mixtures is in agreement with the results reported by Rodriguez et al. (2004) and Calvo et al. (2002). Rodriquez et al. (2005) developed an RT-PCR method for porkbeef mixture, and the detection of pork was in the range of 0.5– 5%. Ali et al. (2012) described the specificity test with DNA from 11 different animal and fish mixtures that yielded a Ct of 15.5 ± 0.20 for the pork and negative results for the other meats. The specificity of oligonucleotides is one of the most important requirements for meat adulteration analysis; the chosen primer pair should hybridize only with the specific target sequence S ß akalar et al. (2012). 3.5. Conventional PCR for commercial food products The conventional PCR was not successful in detecting pork DNA in any of the commercial food products tested (Agarose gel electrophoresis of the PCR was not shown). The gel had no bands with the exception of positive controls. 3.6. Real-time PCR for commercial food products Unlike the conventional PCR, the RT-PCR detected pork DNA in nine out of the 75 commercial food samples. Five of the 30 processed meat samples and one of the six chocolate candy samples were found to contain pork DNA (Fig. 4A). The five processed meat samples that tested positive for pork DNA were two canned chicken luncheon meat, two canned chicken Vienna sausage, and one frozen turkey meat loaf. The Ct values were 34, 37.45, 36.86, 37.06 and 35.1 respectively. The Ct value of the only positive chocolate candy sample was 35.76 (Table 2). These results indicate that RT-PCR was more sensitive than the conventional PCR for the detection of pork adulteration in the samples tested. The PCR amplification and Ct values for burgers from some franchised

restaurants, and cheeses and ice cream from local markets are shown in Fig. 4A. None of these products was positive for pork DNA. Results of the analysis for commercial foods containing gelatin are shown in Fig. 4C and Table 2. Out of the 26 samples tested, only three samples were found to be positive for pork DNA. Ct values for three positive samples viz. jelly (label mentioning beef gelatin), cake (label mentioning bovine gelatin) and candies (with no gelatin mentioned in the label) were 35.92, 40.14 and 41.71 respectively. Concentration of pork DNA in samples positive for pork contamination were estimated using standard pork DNA curve (Fig. 3), and results are listed in Table 2. The pork DNA concentrations in all the positive samples were very low (60.0001 ng/lL). Such low amounts of pork DNA in commercial food products is likely to be as a result of cross-contamination in the production line rather than the deliberate adulteration of food products with pork. These results are in agreement with those of Kesmen, Yetiman, Sahin, and Yetim (2012), who found that RT-PCR could detect chicken and turkey DNA at 0.0001% (0.0001 ng DNA/lL), and the LOD of conventional PCR was 10 times less (0.001%) than that of the RT-PCR. Ulca, Balta, Çag˘ın, and Senyuva (2013) in a survey of 42 samples of Turkish meat products found four samples positive for pork DNA. Ali, Hashim, Mustafa et al. (2012) reported chicken-nuggets containing pork. Tanabe, Miyauchi, et al. (2007) and Tanabe, Hase, et al. (2007) concluded that the LOD for pork DNA using RT-PCR and conventional PCR were 0.0001% (10 fg/ll) and 1 pg/ ll, respectively. Calvo et al. (2002) developed swine-specific primers for detection of pork in raw and cooked meats, sausages, cured meat products, hamburgers and patties and found 1% pork in beef (heated and non-heated) and pork in duck using PCR. Kesmen et al. (2009) reported that Ct values of more than 30 indicate an LOD as low as 0.0001% in samples of cooked and raw meat mixtures. There are no acceptable levels of pork contamination specified by any regulatory authorities for Halal foods. Ulca et al. (2013) proposed 0.1% as a reasonable cut-off point. Gelatin extracted from animal skins, bones, and meat waste, is a significant raw material globally, and used in foods, capsules and cosmetics (Demirhan, Ulca, & Senyuva, 2011; Sahilah & Aminah, 2010). Two of the three samples (jelly and cake) that tested positive for pork DNA declared beef/bovine gelatin, whereas the third (candies) did not state the gelatin source in the ingredients. Stating an erroneous gelatin source or not declaring the gelatin source on the label can be fraudulent or (unintentionally) misleading. Demirhan et al. (2011) reported that two out of 11 retail products collected from Germany were found to contain pork gelatin with Ct values of 30.04 and 43. They also tested 32 samples from Turkey and one of those products (cake covered with gelatin) was positive with a Ct value of 36.3. Sahilah et al. (2012) found that 37.2% of tested pharmaceutical capsules contained pork DNA. Fraudulent labeling of products is common throughout the world Ali, Hashim, Dhahi et al. (2012) and Ali, Hashim, Mustafa et al. (2012), Doosti, Ghasemi, and Rahimi (2011), Doosti, Abbasi,

Table 2 Calculation of pork DNA concentration in commercial food products, which was tested positive for pork DNA by real time PCR. Code of Sample

Product Description

Ct- value

Log of Conc.

Conc.ng/ll

10 14 17 25 30 33 62 72 75

Chicken luncheon meat (canned) Chicken Vienna sausage (canned) Chicken Vienna sausage (canned) Turkey meat loaf (frozen) Chicken luncheon meat (canned) Milk chocolate with soft nougat Jelly(Beef gelatin) Cake(Beef gelatin) Candies(No gelatin labeled)

34 36.85 37.06 35.1 37.45 35.76 35.92 40.14 41.71

2.103449386 1.185545428 1.1179104 1.749170666 0.99230249 1.536603433 1.485071983 0.125929982 0.379722374

0.000127 0.000015 0.000013 0.000056 0.0000098 0.000034 0.000031 0.0000013 0.00000042

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Fig. 4. Real-time PCR amplification plot of commercial food products from local markets. A: Processed Meat and Chocolate Candies; B: Burgers, Cheese, and Ice Cream from Franchised Restaurants; C: Gelatin containing foods. Curves in the green channel are above a preset threshold indicating the presence of target DNA in the sample and a successful PCR.

and Ghorbani-Dalini (2011), Fajardo, González, Rojas, García, and Martín (2010). Food labeling regulations require accurate declaration of meat or gelatin source in food products on the labels, especially for ‘‘Halal” food products. Fraudulent labeling of meat products and adulteration of high priced meat with low cost meats make the identification of the meat species in processed meat products very important (Sakaridis, Ganopoulos, Argiriou, & Tsaftaris, 2013).

This study shows that detection of adulteration or contamination of commercial food products with pork derivatives by RTPCR is more accurate, reliable and sensitive compared to conventional PCR methods. Therefore, quality control laboratories could use RT-PCR for sensitive products including Halal. The presence of pork below 0.1% in meat products could be considered crosscontamination in the commercial production line rather than adulteration because such low levels are not financially rewarding.

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Acknowledgements This project was funded by the National Plan for Science, Technology and Innovation (MAARIFAH), King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia, Award number (10-ARG 1311-02). References Aida, A., Che Man, Y. B., Raha, A., & Son, R. (2007). Detection of pig derivatives in food products for halal authentication by polymerase chain reaction-restriction fragment length polymorphism. Journal of the Science of Food and Agriculture, 87, 569–572. Ali, M. E., Hashim, U., Dhahi, T. S., Mustafa, S., Che Man, Y. B., & Abdul-Latif, M. (2012). Analysis of pork adulteration in commercial burgers targeting porcinespecific mitochondrial cytochrome B gene by TaqMan probe real-time polymerase chain reaction. Food Analytical Methods, 5, 784–794. Ali, M. E., Hashim, U., Mustafa, S., Che Man, Y. B., Abdul-Latif, M., Islam, K. N., Bakar, Z. B. A., et al. (2012). TaqMan real-time polymerase chain reaction for the determination of pork adulteration in meat nuggets. Journal of Food and Nutrition Research, 51, 1–12. AL-Kahtani, H. A., & Ismail, E. A. (2014). Detection of Pork adulteration/contamination in meat mixtures and some commercial food products by conventional and Real-Time Polymerase Chain Reaction techniques. 17th World Congress of Food Science and Technology (IUFoST 2014). Cai, H., Gu, X., Scanlan, M., Ramatlapeng, D., & Lively, C. (2012). Real-time PCR assays for detection and quantitation of porcine and bovine DNA in gelatin mixtures and gelatin capsules. Journal of Food Composition and Analysis, 25, 83–87. Calvo, J. H., Osta, R., & Zaragoza, P. (2002). Quantitative PCR detection of pork in raw and heated ground beef and pate. Journal of Agricultural and Food Chemistry, 50, 5265–5267. CPH world media s.a.r.l., Lebanon, Food Industry, (2016). http://www. cphworldmedia.com/Industries/Food.aspx, Accessed 16-04-04. Dalmasso, A., Fontanella, E., Piatti, P., Civera, T., Rosati, S., & Bottero, M. T. (2004). A multiplex PCR assay for the identification of animal species in feedstuffs. Molecular Cell Probes, 18, 81–87. Demirhan, Y., Ulca, P., & Senyuva, H. Z. (2011). Detection of porcine DNA in gelatin and gelatin-containing processed food products Halal/Kosher authentication. Meat Science, 90, 686–689. Doi, H., Watanabe, E., Shibata, H., & Tanabe, S. (2009). A reliable enzyme linked immunosorbent assay for the determination of bovine and porcine gelatin in processed foods. Journal of Agricultural and Food Chemistry, 57, 1721–1726. Doosti, A., Abbasi, P., & Ghorbani-Dalini, S. (2011b). Fraud identification in fishmeal using polymerase chain reaction (PCR). African Journal of Biotechnology, 10(59), 12762–12765. Doosti, A., Ghasemi, D. P., & Rahimi, E. (2011a). Molecular assay to fraud identification of meat products. Journal of Food Science and Technology. http:// dx.doi.org/10.1007/s13197-011-0456-3. Ebbeca, J. K. F., & Thomsen, P. D. (1991). Species differentiation of heated meat products by DNA hybridization. Meat Science, 30, 221–234. Fajardo, V., González, I., Rojas, M., García, T., & Martín, R. (2010). A review of current PCR-based methodologies for the authentication of meats from game animal species. Trends in Food Science and Technology, 21(8), 408. Farouk, A., Batcha, M., Eng, B., Greiner, R., Salleh, H., Salleh, M., & Sirajudin, A. (2006). The use of a molecular technique for the detection of porcine ingredients in the Malaysian food market. Saudi Medical Journal, 27(9), 1397–1400. Hajmeer, M., Cliver, D. O., & Provost, R. (2003). Spinal cord tissue detection in comminuted beef: comparison of two immunological methods. Meat Science, 65, 757–763.

Hashim, D. M., Che Man, Y. B., Norakasha, R., Shuhaimi, M., Salmah, Y., & Syahariza, Z. A. (2010). Potential use of Fourier transform infrared spectroscopy for differentiation of bovine and porcine gelatins. Food Chemistry, 118, 856–860. Heptinstall, J., & Rapley, R. (2002). Spectrophotometric analysis of nucleic acids. In R. Rapley (Ed.), The nucleic acid protocols handbook (pp. 57–60). Totowa, NJ: Humana Press. Kesmen, Z., Gulluce, A., Sahin, F., & Yetim, H. (2009). Identification of meat species by TaqMan-based real-time PCR assay. Meat Science, 82, 444–449. Kesmen, Z., Yetiman, A. E., Sahin, F., & Yetim, H. (2012). Detection of chicken and turkey meat in meat mixtures by using real-time PCR assays. Journal of Food Science, 77(2), C167–C173. Köppel, R., Ruf, J., & Rentsch, J. (2011). Multiplex real-time PCR for the detection and quantification of DNA from beef, pork, horse and sheep. European Food Research and Technology, 232(1), 151–155. Özgun-Arun, O., & Ugur, M. (2000). Animal species determination in sausages using an SDS-PAGE technique. Archive für Lebensmittelhygiene, 51, 49–53. Palmieri, L., Bozza, E., & Giongo, L. (2009). Soft fruit traceability in food matrices using real-time PCR. Nutrients, 1, 316–328. Regenstein, J. M., Chaudry, M. M., & Regenstein, C. E. (2003). The kosher and halal food laws. Comprehensive Reviews in Food Science and Food Safety, 2, 111–127. Rodriguez, M. A., Garcia, T., Gonzalez, I., Asensio, L., Hernandez, P. E., & Martin, R. (2004). PCR identification of beef, sheep, goat and pork in raw and heat-treated meat mixtures. Journal of Food Properties, 67(1), 172–177. Rodriquez, M. A., Garcia, T., Gonzalez, I., Asensio, L., Mayoral, B., Lopez-Calleja, I., Hernandez, P. E., et al. (2005). TaqMan real-time PCR for the detection and quantitation of pork in meat mixtures. Meat Science, 70, 113–120. Rohamn, A., Sismindari, Erwanto Y., & Che Man, Y. B. (2011). Analysis of pork adulteration in beef meat ball using Fourier transform infrared (FTIR) spectroscopy. Meat Science, 88, 91–95. Sahilah, A.M., & Aminah, A. (2010). Halal Gelatin an overview: A Challenge for Muslims Globally. Seminar Antarabangsa IKRAB: Peradaban dan Kebudayaan Malaysia-Asia Barat. Held on 29–30 September, 2010. Bangunan Canselori. Universiti Kebangsaan Malaysia, Bangi. Sahilah, A. M., Fadly, M. L., Norrakiah, A. S., Aminah, A., Wan, A. W. M., Ma’aruf Khan, M.A., A. G., & Khan, M. A. (2012). Halal market surveillance of soft and hard gel capsules in pharmaceutical products using PCR and southern-hybridization on the biochip analysis. International Food Research Journal, 19(1), 371–375. S ß akalar, E., Abasiyanik, M. F., Bektik, E., & Tayyrov, A. (2012). Effect of heat processing on DNA quantification of meat. Journal of Food Science, 77(9), 40–44. Sakaridis, I., Ganopoulos, I., Argiriou, A., & Tsaftaris, A. (2013). A fast and accurate method for controlling the correct labeling of products containing buffalo meat using High Resolution Melting (HRM) analysis. Meat Science, 94, 84–88. Tanabe, S., Hase, M., Yano, T., Sato, M., Fujimaru, T., & Akiyama, H. (2007). A realtime quantitative PCR detection method for pork, chicken, beef, mutton, and horseflesh in foods. Bioscience, Biotechnology and Biochemistry, 71(12), 3131–3135. Tanabe, S., Miyauchi, E., Muneshige, A., Mio, K., Sato, C., & Sato, M. (2007). PCR method detecting pork in foods for verifying allergen labeling and identified hidden pork ingredients in processed foods. Bioscience, Biotechnology and Biochemistry, 71, 1663–1667. Tasara, T., Sandra, S., & Roger, S. (2005). Conventional and real-time PCR–based approaches for molecular detection and quantitation of bovine species material in edible gelatin. Journal of Food Protection, 68(11), 2420–2426. Toorop, R. M., Murch, S. J., & Ball, R. O. (1997). Development of a rapid and accurate method for separation and quantification of myofibrillar proteins in meat. Food Research International, 30, 619–627. _ & Senyuva, H. Z. (2013). Meat species identification and Ulca, P., Balta, H., Çag˘ın, I., Halal authentication using PCR analysis of raw and cooked traditional Turkish foods. Meat Science, 94, 280–284. Walker, J. A., Hughes, D. A., Anders, B. A., Shewale, J., & Sinha, S. K. (2003). Quantitative intra-short interspersed element PCR for species-specific DNA identification. Analytical Biochemistry, 316, 259–269.