INTRODUCTIONThe Russian Federation strategy to improve thequality of food products until 2030 prioritizes researchin the field of quality management.Today, the problem of food adulteration is ofparticular concern. Food manufacturers are increasinglyreplacing expensive raw materials, such as good qualitybeef, with cheaper poultry. According to the publicreport “Consumer Protection in the Russian Federationin 2017”, Rospotrebnadzor (Russian Federal Service forSurveillance on Consumer Rights Protection and HumanWellbeing) detected 3410 adulterated products out of310 000 inspected food samples [1]. In 2018, the volumesof rejected meat, poultry, and their products doubledcompared to 2017. In particular, Rospotrebnadzorrejected 519 batches of meat and meat productsweighing 3509 kg (compared to 459 batches of1685 kg in 2017) and 168 batches of poultry, eggs,and their products weighing 1951 kg (compared to159 batches of 975 kg in 2017).Research Article DOI: http://doi.org/10.21603/2308-4057-2020-1-98-106Open Access Available online at http://jfrm.ru/en/Methodology for identification and quantificationof chicken meat in food productsMariya A. Pleskacheva1 , Marina P. Artamonova2 , Elena V. Litvinova2, * ,Mariia A. Gergel1 , Ekaterina E. Davydova31 The Russian State Center for Animal Feed and Drug Standardization and Quality, Moscow, Russia2 Moscow State University of Food Productions, Moscow, Russia3 The Center for Strategic Planning and Management of Medical and Biological Health Risks, Moscow, Russia* e-mail: illusionse@mail.ruReceived December 20, 2019; Accepted in revised form January 13, 2020; Published March 31, 2020Abstract:Introduction. The problem of food adulteration is highly relevant today. Food manufacturers are increasingly replacing expensive rawmaterials with cheaper poultry. We aimed to develop an effective method for identification and quantification of chicken meat and eggproducts in multicomponent meat systems using real-time PCR.Study objects and methods. We studied native animal tissue, namely that of chicken, pork, beef, turkey, quail, duck, horse meat, rabbit,sheep, and goat. Standard samples were taken from pure fresh chicken muscle tissue. We also used raw, boiled, and powdered chickeneggs. For a semiquantitative analysis of chicken mass in the sample, we compared the threshold cycle (Сt) of chicken DNA and thethreshold cycles of calibration samples. To ensure the absence of PCR inhibition, we used an internal control sample which wentthrough all the stages of analysis, starting with DNA extraction.Results and discussion. We developed a methodology to qualitatively determine the content of chicken tissue in the productand distinguish between the presence of egg products and contamination on the production line. The method for chicken DNAidentification showed 100% specificity. This genetic material was detected in the range of 0.1% to 0.01% of chicken meat in thesample. The efficiency of the duplex PCR system for chicken DNA detection was more than 95% (3.38 on the Green slope channeland 3.45 on the Yellow slope channel). The analytical sensitivity of the primers was 40 copies/reaction.Conclusion. Our methodology is suitable for analyzing multicomponent food products, raw materials, feed, and feed additives.It can identify the content of chicken meat at a concentration of up to 1%, as well as distinguish egg impurities from contaminationof various origin. PCR allows differentiation between chicken meat and egg products.Keywords: Multicomponent products, canned food, chicken meat, egg melange, PCR, adulteration, sausagesPlease cite this article in press as: Pleskacheva MA, Artamonova MP, Litvinova EV, Gergel MA, Davydova EE. Methodology foridentification and quantification of chicken meat in food products. Foods and Raw Materials. 2020;8(1):98–106. DOI: http://doi.org/10.21603/2308-4057-2020-1-98-106.99Pleskacheva M.A. et al. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 98–106Species identification of meat and meat products isbecoming more important due to increased internationaltrade and labeling rules introduced in many countries.Morphological and anatomical characteristics areused to identify fresh and unprocessed meat. However,processed meat loses its characteristic morphologicalfeatures, which creates favorable conditions foradulteration, namely for replacing one type of meatwith another, less valuable type. Poultry – a cheaperraw material compared to pork, beef or other meats –is often used to adulterate products, both semi-finishedand finished. Especially difficult is species identificationof multicomponent products containing several types ofmeat, egg impurities, various food additives, enzymepreparations, as well as products subjected to rigorousmechanical or thermal processing, such as cannedfoods and pastes [2–7]. According to Rospotrebnadzor,most violations of the technical standards in 2018 weredetected in canned meat and sausages [1].At the moment, the Russian Federation has nomethod for quantifying the content of chicken and/or egg melange in food products and isolating possiblecontamination on the production line.Scientific literature reports numerous methods forqualitative identification of meat species [8–11]I. A groupof scientists from Gorbatov’s Federal Scientific Centerfor Food Systems and the National Center for FishingProducts Safety attempted to identify egg melange at the30th PCR cycle [12, 13]. However, there were no dataon the quantitative identification of impurities [14, 15].Therefore, we need to develop a quantitative methodfor identifying ingredients in the analyzed products toprevent producers from replacing a specified contentof meat with cheaper raw materials and to distinguishbetween adulteration and inevitable contamination inproduction [16–20].The highly sensitive PCR method can reveal eventrace amounts of meat ingredients, which are essentiallytechnical impurities. However, in order to distinguish aminor technical impurity from intentional adulteration,we need a methodology for a quantitative or semiquantitativeevaluation of meat, for example, chicken, infood products [20–38].Therefore, we aimed to develop an effective methodfor identification and quantification of chicken meat andegg products in multicomponent meat systems using thereal-time PCR.STUDY OBJECTS AND METHODSOur objects of study included native animal tissuepurchased in retail chain stores (chicken, pork, beef,turkey, quail, duck, horse meat, rabbit, sheep, and goat)or obtained at the Russian State Center for AnimalFeed and Drug Standardization and Quality, MoscowI MU А 1/022 Sekvenirovanie fragmentov mitokhondrialʹnogogenoma zhivotnykh i ryb dlya opredeleniya vidovoy prinadlezhnostimyasa v odnokomponentnoy produktsii [MU А 1/022 Sequencingfragments of the mitochondrial genome of animals and fish todetermine meat species in mono-component products].(mink, cat, and dog). Pure fresh chicken muscle tissuewas used as standard samples. The species identityof all the materials was confirmed by the SangerDNA sequencing method based on the standard CytBgene [3]. In addition, we used raw, boiled, and powderedchicken eggs.We used only certified equipment, materials,reagents, and utensils.The tests were conducted using the followingmethods:– taking laboratory samples from different productgroups (State Standard 31904-2012II);– adsorption DNA extraction based on silicon dioxide(State Standard R 56140-2014III);– guanidine-chloroform-based DNA extraction (StateStandard R ISO 21571-2014IV). This method can purifyDNA from fatty and protein impurities, reduce theinhibition of the reaction, and eliminate the influence offood additives on the final result (it also works well withegg impurities);– real-time polymerase chain reaction withhybridization-fluorescence detection (State StandardISO 22119-2013V);– evaluation of metrological characteristics of measurementprocedures (RIS 61-2010VI);– certification of measurement procedures (StateStandard R 8.563-2009VII).When sampling and preparing test samples, wetook measures to prevent the seeding of environmentalobjects in line with State Standard 8756.0-70VIIIand State Standard 31719-2012IX. The samples werehomogenized and 0.05 g weighed, placed in a 1.5 cmEppendorf type disposable microcentrifuge tube,labeled, and used to isolate DNA.Three sets of samples were prepared in duplicate.The first set was not subjected to heat treatment. Thesamples of the second set were mixed with 100 mm3II State Standard 31904-2012. Food products. Methods of sampling formicrobiological analyses. Moscow: Standartinform; 2014. 8 p.III State Standard R 56140-2014. Medicine biological remedies forveterinary use. Polymerase chain reaction for the Mycoplasma DNAdetection. Moscow: Standartinform; 2015. 12 p.IV State Standard R ISO 21571-2014. Foodstuffs. Methods of analysisfor the detection of genetically modified organisms and derivedproducts. Nucleic acid extraction. Moscow: Standartinform; 2016. 46 p.V State Standard ISO 22119-2013. Microbiology of food and animalfeeding stuffs. Real-time polymerase chain reaction (PCR) forthe detection of food-borne pathogens. General requirements anddefinitions. Moscow: Standartinform; 2014. 15 p.VI RIS 61-2010. State system for ensuring the uniformity ofmeasurements. Accuracy, trueness and precision measures of theprocedures for quantitative chemical analysis. Methods of evaluation.Moscow: Standartinform; 2013. 62 p.VII State Standard R 8.563-2009. State system for ensuring theuniformity of measurements. Procedures of measurements. Moscow:Standartinform; 2011. 20 p.VIII State Standard 8756.0-70. Canned food products. Sampling andpreparation of samples for test. Moscow: Standartinform; 2010. 8 p.IX State Standard 31719-2012. Foodstuffs and feed. Rapid methodof identification of raw composition (molecular). Moscow:Standartinform; 2014. 24 p.100Pleskacheva M.A. et al. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 98–106of water and heated at 99°С on a Termite solid-statethermostat (DNA-Technology, Russia) for 30 min. Thethird set was sampled in quadruplicate and autoclaved at110°C and 0.5 atm. for 30 min and an hour, respectively.For the purity of the experiment, we used chickenmuscle tissue (breast fillet and drumstick), parenchymaland hollow internal organs (kidney, heart, liver), skinand cartilage, as well as minced pork meat containing1% and 10% chicken.Since chicken eggs are widely used in the foodindustry, we had to determine their effect on thePCR results. For this, we analyzed raw, boiled andpowdered eggs, as well as pancake flour. In addition, weinvestigated 20% egg in minced pork, 10% raw egg inwater, and 10% egg in minced chicken. A model panelwas made from the above samples.To eliminate the likelihood of PCR inhibition,we used an internal control sample (ICS) which wasadded to each test sample starting from the DNAextraction stage.DNA was extracted by the sorbent methodrecommended by State Standard R 52723-2007X, using astandard set of DNA-Sorb-S reagents (Central ResearchInstitute of Epidemiology, Russia). A number ofexperiments performed with the extracted DNA showedthat a 100% chicken content (whether fillet, hollowand parenchymal internal organs or connective tissue)produced a threshold cycle (Ct) ≤ 15, whereas 10% and1% chicken contents in minced meat produced Ct ≤ 18and Ct ≤ 21, respectively. There is a correlation with theICS detection. When egg is present, the values decreaseto Ct ≥ 23 and the ICS also drops to Ct ≥ 28 due toinhibition (Ct ≥ 24 with no inhibitors). DNA is obviouslyless degraded in a pure product (raw and boiled egg)than in egg powder, but Ct is inversely related: Ct ≥ 27and Ct ≥ 20 for the egg powder sample and the ICS,respectively; Ct ≥ 30 and Ct ≥ 28 for the raw and boiledegg sample and the ICS, respectively.Thus, we can conclude that raw and boiled eggscontain PCR-inhibiting substances. The presence of10% raw eggs in minced chicken leads to ICS Ct ≥ 27versus ICS Ct ≤ 21 for 100% minced chicken. It isimpossible to evaluate the results when the reaction is sostrongly inhibited. Therefore, we chose a different DNAextraction method described by Minaev et al. [2]. Forthis, we used a SORB-GMO-B kit (Syntol, Russia) inaccordance with the manufacturer’s recommendations.The PCR results are shown in Table 1. As we can see,the ICS threshold cycle values indicate insignificantinhibition of the reaction, confirming the right choice ofthe DNA isolation method.We selected those primers and probes thatfluoresce to the target DNA of chicken and the ICSin the Green and Yellow channels. The solutionsX State Standard R 52723-2007. Foodstuffs and feeds. Rapidmethod of identification of raw composition (molecular). Moscow:Standartinform; 2007. 22 p.of direct and reverse PCR primers and a probe at aknown molar concentration were diluted to a workingmolar concentration of 6 μmol/dm3 a nd 3 μ mol/dm3,respectively. For PCR, we used a dNTF solution (Syntol,Russia), a PCR buffer-Flu and TaqF DNA polymerase(Central Research Institute of Epidemiology, Russia).The DNA extracted from each test sample wasanalyzed in at least two replicates. For amplificationcontrol reactions, we used recombinant plasmids basedon the pAL-2 vector (solutions of plasmid DNA at aconcentration of 0.01 mg/dm3) as positive reactioncontrols. They were a plasmid containing a chickenDNA fragment (pCh) and a plasmid of the internalcontrol sample (pICS).For real-time PCR, we used Rotor-Gene Q amplifiers(QIAGEN, Germany) and Rotor-Gene 6000 amplifiers(Corbett Research Pty Ltd., Australia). We programmedthe device according to the operating instructions andoptimized the PCR-RT conditions for the duplex format.The primer annealing temperature was 60°С, with aPCR total temperature profile of 40 cycles.RESULTS AND DISCUSSIONThe PCR results for the model meat systems beforeand after heat treatment (at various temperatures) arepresented in Table 1. The Background Threshold wasset at 15% and the Threshold was 0.05. We interpretedthe results based on the presence (or absence) of theintersection between the fluorescence curve and athreshold line set at an appropriate level. The conditionsfor analysis were as follows: for a positive PCR control,the threshold cycle values of Ct < 26 were present in theGreen and Yellow channels; for a negative extractioncontrol and a negative PCR control, the threshold cyclevalues were absent in all the channels; the thresholdcycle value for the ICS was not lower than Ct ≤ 24 forqualitative determination, since higher values indicatePCR inhibition.As we can see in Table 1, all the raw samplescontaining meat or offal (including extremely lowconcentrations) were identified at no later than the 19thcycle; egg impurities, no earlier than the 25th cycle; andegg powder and pancake flour, at the 29–30th cycle.Interestingly, pure chicken meat, whether fillet or offal,was identified at no later than the 14th cycle, whileconnective tissue, no later than the 17th cycle. Thechicken contents of 10% and 1% produced Ct ≤ 15 andCt ≤ 19, respectively. These results allowed us toconclude that:– Ct < 15 indicated over 10% chicken in the test sample;– Ct < 19 indicated over 1% chicken or highconcentrations of connective tissue in the test sample.This conclusion makes it impossible to quantify thechicken content at this stage of the study. However,it leaves a possibility of a semi-quantitative analysis,whose result can be expressed as “chicken content atleast N%”.101Pleskacheva M.A. et al. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 98–106The heat-treated samples containing meat or offal(including extremely low concentrations, up to 1%)were identified at no later than the 21st cycle and eggimpurities, no earlier than the 21st cycle. A 10% chickencontent in minced meat produced Ct ≤ 17, whereas1% chicken showed Ct ≤ 21. From these results, weconcluded that Ct < 21 indicated more than 1% chickenin the test sample.The autoclaved samples containing chicken meator offal were identified at no later than the 17th cycle,whereas the samples with extremely low concentrationsof chicken meat (up to 1%) and egg impurities, no laterthan the 26th cycle. The chicken contents of 10% and1% resulted in Ct ≤ 21 and Ct ≤ 25, respectively. Thus,the detection of Ct < 25 indicated over 1% chickenin the test sample.Next, we proceeded to the development of a semiquantitativemethod for determining chicken meat infood products, since a quantitative method was notpossible due to the equality of cycles for the 10% mincedchicken samples and the connective tissue samples.As adulterating a product with less than 1% meat (1 gchicken meat per 1 kg of product) seems impractical,we decided that the methodology should allow usto determine the content of chicken in the productin relation to several threshold values of calibrationsamples, namely:– “at least 1%” if Ct 10% < sample’s Ct ≤ Ct 1%;– “at least 10%” if Ct 50% < sample’s Ct ≤ Ct 10%;– “high content” if the sample’s Ct ≤ Ct 50%;– “low DNA, possible egg presence” if the sample’sCt > Ct 1%.Further, we evaluated the following criteria:sensitivity and specificity of the primers, detectionlimits, and a range of values for calibration samplesand internal control samples. Each experiment wasperformed by two different researchers, at differenttimes, with reagents of different series, on differentamplifiers of the same type. Each sample was tested induplicate.To assess the specificity of PCR, we created a panelof DNA samples isolated from chicken, pork, beef,Table 1 PCR results for model samplesProduct Weight content, % Threshold cycle of the model sample (chicken meat content)Not heat-treated 99°С, 30 min 110°С, 0.5 atm., 1 hMinced breast 100 12.67 13.54 16.26Minced drumstick 100 12.54 13.39 14.62Minced liver 100 11.92 13.01 15.52Minced kidneys 100 12.15 13.83 16.01Minced heart 100 11.64 13.88 15.04Cartilage 100 14.97 16.81 19.23Skin 100 16.04 18.16 22.08Minced chicken breast and pork 10 14.26 16.44 20.34Minced chicken breast and pork 1 18.26 20.16 25.72Liquid egg 100 24.29 26.89 29.05Liquid egg 10 33.40 32.99 –Minced pork and egg 20% egg 22.00 22.81 25.91Minced chicken breast and egg 10% egg 13.29 14.91 16.91Chicken ovalbumin (egg powder) 100 27.65 29.34 –Pancake flour 4%* 28.95 30.06 –* The average amount of egg powder in 12 formulationsFigure 1 Specificity assessment of the chicken identification methodology(а) Chicken meat DNA, Yellow (b) ICS, GreenNorm. fluoresc.Cycle0.50.40.30.20.1Threshold5 10 15 20 25 30 35 40Norm. fluoresc.Cycle0.300.250.200.150.100.050.00 5 10 15 20 25 30 35 40Threshold102Pleskacheva M.A. et al. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 98–106Table 2 Specificity assessment of the duplex PCR system for chicken identificationExpected amplification result Actual amplification result, threshold cycle values, Сt ± SD NameReplicate № 1 Replicate № 2 of sampleFAM, ICS Yellow, chicken FAM, ICS Yellow, chicken FAM, ICS Yellow, chicken+ + 21.66 ± 0.05 12.76 ± 0.18 21.61 ± 0.10 13.46 ± 0.01 chicken+ – + – + – pork+ – + – + – beef+ – + – + – goat+ – + – + – mink+ – + – + – turkey+ – + – + – quail+ – + – + – duck+ – + – + – horse+ – + – + – rabbit+ – + – + – cat+ – + – + – dog+ – + – + – sheep+ – + – + – Ci*– – – – – – –C**Table 3 Sensitivity of the duplex PCR system(initial concentration of plasmid DNA – 4 ng/μL)Number of genomiccopies in the reactionСt ± SD,Yellow (chicken)Сt ± SD,Green (ICS)20 000 23.16 ± 0.10 24.41 ± 0.152 000 26.87 ± 0.10 28.19 ± 0.05200 30.58 ± 0.56 32.01 ± 0.1820 34.00 ± 0.79 35.29 ± 1.072 – –Table 4 PCR results for LOD determinationChicken DNAcontent, %Threshold cycleCt ± SD for rawand cooked productsThresholdcycleCt ± SDChicken(Yellow)ICS(Green)Chicken(Yellow)ICS(Green)10 16.06 ± 0.11 23.15 ± 0.03 24.03 ± 0.12 23.15 ± 0.041.0 19.16 ± 0.03 23.18 ± 0.20 26.15 ± 0.02 23.18 ± 0.190.1 21.84 ± 0.28 23.02 ± 0.01 28.73 ± 0.29 23.02 ± 0.020.01 24.56 ± 0.01 23.25 ± 0.03 30.35 ± 0.02 23.25 ± 0.020.001 26.56 ± 0.23 22.29 ± 0.03 32.46 ± 0.19 22.29 ± 0.04turkey, quail, duck, horse, mink, rabbit, cat, dog, goat,and sheep. The results are shown in Fig. 1 and Table 2.Within the proposed panel, the chicken DNAidentification methodology showed 100% specificity:we observed the ICS amplification only on the Greenchannel and the target chicken DNA on the Yellowchannel.The assessment of the control panel for validationconfirmed a 100% convergence of the results.To determine the analytical sensitivity of theprimers, we isolated DNA from a sample of 100%chicken meat and prepared a series of 10-fold dilutions.The maximum dilution was determined which allowedreproducible (in duplicate) detection of DNA.In addition, we used plasmid DNA solutions at aspecified concentration containing a cloned chickengene fragment and a ICS fragment. Two series often-fold dilutions were prepared in a TE buffer withvarious concentrations: series № 1 – pICS plasmidDNA solution; series № 2 – pCh plasmid DNA solution.The initial concentration of plasmid DNA in eachseries was 4 ng/μL, which corresponds to ~ 20 000 genomiccopies in PCR (5 μL of a DNA solution for a25 μL reaction). The results are presented in Table 3.To determine the absolute limit of detection (LOD)at which the PCR method is able to detect and quantifychicken genetic material, we performed 10 PCRs,with 5, 10, 20, and 40 genomic copies of chicken DNAin each. Our PCR methodology detected chicken evenin the strongest dilution, with only five genomic copiesin the PCR.To determine the limit of detection of chicken andegg products in multicomponent raw and heat-treatedproducts, we used a number of model samples preparedin two replicates and containing 10, 1.0, 0.1, 0.01, and0.001% chicken in minced pork (isolated DNA). Thesamples were preliminarily cooked at 99°С for 30 min.To determine the LOD of chicken and egg products incanned foods, the model samples were autoclaved at110°C and 0.5 atm. The minimum chicken content inminced pork was determined, at which chicken DNAwas reproducibly (in duplicate) detected. The results areshown in Table 4.* Ci – isolation control (shows the absence of inhibition at the stage of DNA isolation)** –C – negative PCR control (shows the purity of the reaction, mixes, and the laminar, as well as the absence of contamination)103Pleskacheva M.A. et al. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 98–106Table 5 Constancy of Ct ranges for calibration samplesSeries Calibration sample’s CtCooked for 30 min at 99°C Autoclaved for 60 min at 0.5 atm1% 10% 50% 1% 10% 50%1 18.97 18.68 16.08 16.21 13.85 13.91 27.92 27.89 24.05 23.99 19.74 19.852 19.63 19.70 15.84 16.02 11.78 12.13 25.34 25.40 24.63 24.52 20.04 20.213 19.34 19.55 17.04 17.15 13.81 13.89 27.83 27.95 22.16 22.03 19.10 19.034 19.22 19.43 17.54 17.66 13.77 13.98 26.45 26.53 22.25 22.15 20.93 20.845 19.93 20.15 14.50 14.37 12.88 13.00 27.27 27.17 23.69 23.45 21.52 21.686 18.29 18.52 16.32 16.45 12.70 12.96 25.77 25.89 24.67 24.77 19.66 19.767 18.04 18.19 15.52 15.63 13.84 13.79 25.05 25.30 22.16 22.26 19.76 19.828 19.71 19.59 16.96 16.67 13.55 13.75 25.58 25.41 22.25 22.05 19.34 19.119 19.94 20.17 14.43 14.87 12.67 12.56 26.90 26.99 23.70 23.84 20.81 20.9410 20.40 20.62 14.03 14.25 13.02 13.17 27.60 27.52 24.71 24.66 21.70 21.6411 18.01 18.14 16.47 16.44 11.99 12.21 25.53 25.64 22.86 23.02 21.45 21.1512 20.78 20.84 15.33 15.66 12.40 12.23 26.15 26.45 24.35 24.23 20.93 21.0313 20.96 20.86 17.83 17.64 12.56 12.71 25.74 26.03 22.88 23.09 21.63 21.7214 20.85 20.91 17.98 17.83 12.83 13.01 27.14 27.33 24.64 24.98 21.12 21.2315 20.21 20.16 15.25 15.44 13.34 13.43 26.59 26.84 24.10 24.28 21.84 21.92Maximum, Ct 20.96 20.91 17.98 17.83 13.85 13.98 27.92 27.89 24.71 24.98 21.84 21.92Minimum, Ct 18.01 18.14 14.03 14.25 11.78 12.13 25.05 25.30 22.16 22.03 19.10 19.03SD 0.94 0.93 1.20 1.10 0.65 0.63 0.92 0.88 0.98 1.02 0.91 0.93RSD 4.81 4.70 7.49 6.82 5.02 4.84 3.47 3.33 4.16 4.34 4.40 4.50* SD – standard deviation, RSD – relative standard deviationThe limit of detection for chicken DNA ranged from0.1 to 0.001% of the chicken content in the sample.The methodology should allow us to assess thecontent of chicken and egg products in food productsrelative to several selected threshold values ofcalibration samples. To prepare calibration samples ofvarious compositions for the semi-quantitative analysisof raw and cooked products, we mixed 100% mincedchicken meat with 100% minced pork (1%, 10%, and50% chicken) and heated at 99°C for 30 min.We decided to evaluate both cooked and rawproducts in relation to the values of heat-treatedcalibrators, since fresh chicken meat was used toprepare model samples of raw products, which cannotbe guaranteed by product manufacturers. Moreover,samples for analysis do not always get delivered to thelaboratory directly, bypassing the stages of storageor freezing, which increases the likelihood of DNAdegradation. The calibration samples for cannedproducts were autoclaved at 110°C and 0.5 atm. Theuniformity coefficient of the calibrators was 0.99 (99%).To confirm the constancy of the calibrators’ Ctranges, we performed a series of tests. In particular,we studied 15 series of calibration samples preparedon different days, by different people, each in tworeplicates. For each series, we determined the minimumand maximum values of the threshold cycle on theYellow-chicken channel, a standard deviation, and arelative standard deviation. The results are presentedin Table 5.As a result, we selected the following threshold cyclevalues on the “Yellow-Chicken DNA” channel for thecalibrators of:– raw products and those subjected to light heattreatment: 18 ≤ Ct 1% < 21; 14 ≤ Ct 10% < 18;Ct 50% < 14;– autoclaved products (canned food): 25 ≤ Ct 1% < 28;22 ≤ Ct 10% < 25; Ct 50% < 22.Also, a threshold cycle value of at least Ct ≤ 24 waschosen as acceptable on the “Green-ICS” channel forthe calibrators (Ctics 1%, Ctics 10%, Ctics 50%) and thenegative control sample.CONCLUSIONWe developed a method (certified methodology)for a semi-quantitative assessment of chicken contentin multicomponent food systems of varying degreesof heat and mechanical treatment: raw, heat-treated,canned, finely ground, and homogenized. Having testedvarious DNA extraction methods, we concluded thatthe guanidine-chloroform method reduces the contentof PCR-inhibiting substances compared to the sorptionmethod.Our methodology was tested on model samples,as well as product samples from retail stores, toexclude the possibility of PCR inhibition by foodadditives, stabilizers, emulsifiers, etc. With PCR,we can distinguish between chicken meat and eggproducts in raw and cooked products (over 21 cycles),as well as canned foods (over 28 cycles). Our resultssuggest that this methodology is suitable for analyzing104Pleskacheva M.A. et al. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 98–106multicomponent food products, raw materials, feeds, andfeed additives. In addition, it can identify the contentof chicken meat at a concentration of up to 1%, as wellas detect egg impurities and contamination of variousorigins.Taking into account the current need fordistinguishing adulteration from the inevitablecontamination on the production line, as well aspreventing adulteration of expensive raw materialswith chicken meat by introducing egg products, webelieve that our methodology could make a significantcontribution to the production of high-quality foods.CONTRIBUTIONEach of the authors was directly involved in thedevelopment, testing, and validation of the abovemethodology, as well as in writing this article.CONFLICT OF INTERESTThe authors state that there is no conflict of interest.