Authentication of sibiu salami based on chemometric analysis of spectral data

UNIVERSITY POLITEHNICA OF BUCHAREST THE FACULTY OF APPLIED CHEMISTRY AND MATERIALS SCIENCE FOOD CHEMISTRY MASTER AUTHENTICATION OF SIBIU SALAMI BASED ON CHEMOMETRIC ANALYSIS OF SPECTRAL DATA SUPERVISOR S.l.dr.ing Cristina TODASCA MASTER STUDENT Tuan NGUYEN THUONG BUCHAREST 2017 Acknowledgements My sincere appreciation to the scholarship agreement between the government of the socialist republic of Vietnam and the government of Romanian has been extremely beneficial for me My great thanks go to the Faculty of Applied Chemistry and Materials Science University Politehnica of Bucharest I express my deepest gratitude to my supervisor Ms Cristina TODASCA, for her support, motivation and help during my thesis work The last important word, I would like to remember and thank my family for striving hard to provide a good education for me and always encouraging me to continue my studies Contents LITERATURE REVIEW 1.1 Studies on different sausage products 1.1.1 Studies on Sibiu Salami 1.1.2 The studies on other dry-cured salami produced abroad 1.2 Analytical methods used for composition sausage/salami products measurement 14 1.2.1 Fatty acid profile analysis of dry-cured sausages by a gas chromatography-mass spectrometric (GC-MS) technique was used 14 1.2.2 Fatty acid profile analysis dry-cured sausages, salami by NIR/NIRS/NIT system technique was used 18 1.2.1 Fatty acid profile analysis dry-cured sausages, salami by NMR system technique was used 21 ORIGINAL RESULTS AND DISCUSSIONS 29 2.1 Objectives 29 2.2 Collection of the relevant samples of Sibiu Salami and other dry cured salami produced in Romania 29 2.3 Fat extraction from salami samples 31 2.4 GC-MS analysis of the extracted 32 2.5 FT-IR analysis of the extracted fat 35 2.6 NMR analysis of the extracted fat 37 2.7 Chemometric analysis of the spectral data (PCA, AHC) 41 2.7.1 Agglomerative Hierarchical Clustering (AHC) 2.7.2 Principal Component Analysis (PCA) 42 43 INSTRUMENTS AND METHODS 45 3.1 Fat extraction – Soxhlet procedure 45 3.2 Transesterification procedure for obtaining FAME 47 3.3 GC-MS Analysis 47 3.4 FT-IR Analysis 48 3.5 NMR Analysis 48 CONCLUSION 49 REFERENCES 52 LIST OF ABBRFVIATION H-NMR: hydrogen nuclear magnetic resonance spectroscopy AHC Agglomerative hierarchical clustering EFA: Essential fatty acids FA: fatty acid FAME: fatty acid methyl ester FT-IR: fourier transform infrared spectroscopy GC-MS: gas chromatography-mass spectrometry NIT: near infrared transmittance spectroscopy NMR: nuclear magnetic resonance spectroscopy PCA: Principal component analysis PGI: Protected geographical indication SFA: Saturated fatty acids TE: Trolox equivalent UFA: Unsaturated fatty acids INTRODUCTION The sausage products are present in many countries throughout the years has become an indispensable dish for many families There are some countries in Europe such as Germany, France, Italy, Romanian, Spain, Denmark and some countries in Asia such us Korea, China with long tradition of salami production In general, salami can be defined as products made by selecting, chopping, and mixing meat and fat, mixed with seasoning, spices, and authorized additives, that are then ripened and dried (cured) and, sometimes, smoked However, regional traditions, environmental variations, family recipes, and other factors have rise to a wide range of fermented salami, and it can be said that there are almost as many types of salami as there are geographical regions This is also attested in the report were they compare fatty acid composition of salami from different countries and their nutritional implications [19] In some studies, reveal that, in the processing of sausage they have added additional ingredients such as olive oil, lard, spices This change affects the amount and type of fatty acids found in salami The studies determined the amount of fatty acids in the product enables us to test and refine new methods to improve the quality of products Today, along with the development of science and technical capabilities, we could use a variety of methods and different analysis system for fatty acid content analysing in salami The main analysis system known as a gas chromatography-mass spectrometry (GC-MS) technique, near infrared spectroscopy technology (NIR), near infrared transmittance (NIT) spectroscopy, nuclear magnetic resonance spectroscopy (1H-NMR) Itself every method of analysis have its own advantages and disadvantages Some method has dominant time benefits others have lower costs of analysis Hence, researchers continue to drive improvements in analytical methods for fatty acid, to provide accurate process analysis, saving time and chemicals, as well as lower the cost of analysis for each sample Fermented salami is products that before consumption passes through a more or less prolonged process of drying and ripening Sibiu Salami is a famous Romanian fermented dry salami, produced mainly from pork meat and pork back-fat The mix is stuffed into natural casings and then smoked, dried and ripened There is a wide variety of dry-cured salami produced in Romania, the most appreciated is Sibiu Salami, because of the special taste A similar production procedure is applied for obtaining Dacia, Banatean and Sinaia Salamis They different mainly is the taste and some of them in the production receipt Romania has a tradition of over 100 years in producing „„Sibiu Salami‟‟, known as „„Salam de Sibiu‟‟ which has been registered as a “protected geographical indication” (PGI) labelled product in the European Union The Sibiu salami‟s producers have already made export to promote this product outside the country The aim of this thesis was to develop a method for authentication of Sibiu Salami against other meat products of its class, using spectral data combined with chemometrical analysis The GC-MS and NMR spectral data have been used as data base for chemometric analysis LITERATURE REVIEW The issue of product quality is one of the top concern in salami products now There were many countries were different quality problems of dry-cured salami were noticed The studies about the ingredients and the analysis methods were conducted Each study has its advantages and significance of its own, overall analysis of the composition and content of fatty acids in the salami is now improved and very interesting 1.1 Studies on different sausage products Salami is a type of cured sausage consisting of fermented and air-dried meat, typically beef or pork Historically, salami was popular among southern and central European peasants because it stores at room temperature for up to 40 days once cut, supplementing a potentially meager or inconsistent supply of fresh meat Countries and regions across Europe make their own traditional varieties of salami 1.1.1 Studies on Sibiu Salami Sibiu Salami, in Romania known as „„Salam de Sibiu‟‟ is a Romanian deli made with pork's meat, pork's fat, salt and condiments Sibiu Salami are considered as a luxury food Traditional sausages-dried salami is meat products that are part of the traditional daily diet, and also highly valued in modern life with an increasing demand Sausage recipes were developed that took advantage of what people had The differences between the various types of dry-cured salami are due to the kind of meat they contain the proportion of lean to fat, spices, and the fineness or coarseness of the grind is what distinguishes one regional Salami from another Fermented salami are products that before consumption passes through a more or less prolonged process of dry and ripening Dry salami is made from different types of meat which are mainly made from pork In Romania, there are some studies related to salami composition but not much The results showed that GC-MS is a suitable method for quantitative determination of fatty acid in different meat products [1, 2,] The composition and content of fatty acids in dry salami have been reported in many researches nationwide In a research in Romania, the authors mainly studied in the composition and content of fatty acids in dry salami The content of different fatty acids in sausage as such as myristic acid (C14:0), palmitoleic acid (C16:1), palmitic acid (C16:0), oleic acid (C18:1), linoleic acid (C18:2), stearic acid, arachidonic acid and saturated fatty acids (SFA); unsaturated fatty acids (UFA): essential fatty acids (EFA) The beef meat and the mixture of a sausage meat were compared Research results show the content of different fatty acids in beef meat and sausage Percentage of the fatty acid of beef meat in respective with sausage meat: myristic acid (C14:1) 0.84- 0.09; palmitoleic acid (C16:1) 1.21 - 0.43; palmitic acid (C16:0) 13.46 - 8.47.; oleic acid (C18:1) 22.7 - 28.54; linoleic acid (C18:2) 0.49 - 6.08; stearic acid 11.97 - 8.88 and saturated fatty acids (SFA) 26.28 - 17.44; unsaturated fatty acids (UFA) 24.30 - 35.05: essential fatty acids (EFA) 1.7 - 7.51 It is interesting to observe that unsaturated fatty acids (UFA) in the sausage mixture is higher than in beef meat and also the total saturated fatty acids (SFA) are higher in beef meat then in the sausage mixture The changes in fatty acid composition was also mentioned in other studies [119] In another research Dacia sausage (a Romanian fermented dry sausage, produced from raw pork, salt, pepper, garlic, species, additives and starter culture) was analysis The meat mix is stuffed into natural casings and then smoked, dried and ripened During the ripening of fermented sausages, various changes take place, leading to the final characteristics of the sausage Lipids are abundant in fermented meat products and their changes influence the aroma and the flavor of the final product One of many indicators that concern the composition, nutritional and content in fatty acids [3, 4] During the manufacture of Dacia sausage, there was an increase in all of the free fatty acids, with oleic (C18:1) and linoleic (C18:2) being the main fatty acids released The greatest increase in levels of these fatty acids took place during the drying-ripening stage Adding vegetal oil in smoked and boiled salami resulted in increasing both nutritional value and the protection against oxidation [4] This study has introduced a new meat product, boiled-smoked salami with an addition of sea buckthorn vegetable oil (Hippophaë rhamnosides L.) and walnut oil (Juglans Regia L) in order to improve PUFAs/SFAs and ω-6/ω-3 ratios The vegetable oils have been added for reducing the saturated fatty acids and to increase the poly- and mono - unsaturated fatty acids content Some chemical characteristics of the salami samples were analyzed by NIR spectrophotometry (FoodScan), the antioxidant capacity by photochemical instrument and fatty acids content by GC-MS The fatty acids were determined at 4, 11 and 18 days from processing at refrigeration temperature The lipid profile (g fatty acids/100g fatty acids), the vitamin E content (mg /100g fatty acids) and the antioxidant capacity (µmol TE /g fat) offer information about the nutritive value of the salami with vegetable oils added, respectively, changing in the lipid content and its profile during the storage The results of this study showed that adding vegetal oil in smoked and boiled salami resulted in increasing both nutritional value and the protection against oxidation Regarding the nutritional value, the sample prepared with walnut oil had the highest PUFAs content comparing with the sample obtained with sea buckthorn oil that showed higher MUFAs and α-tocopherol values The presence of sea buckthorn oil in salami, in relevant ratio, may cause a 10-day delay of the oxidative processes due to moderate PUFAs and higher antioxidant compounds content The back-fat sample registered a content of 41.43% of saturated fatty acids, with the palmitic acid as predominant (25.93%) A large percentage of PUFAs was found in walnut oil 73.49g/100g fatty acids, according to the literature values (69.55 ± 0.03 up to 75.54 ± 0.51) (Arimboor & al.) More MUFAs was found in the sea buckthorn oil, 57.25 g/100g fatty acids, higher than the values found in the literature (52.823-54.32%) (Tahira Fatima & al.) Palmitic acid is 36.7% higher in sea buckthorn oil compared to the walnut oil and approximately 50% lower than in meat and back fat The main MUFA acid, the oleic acid, had the highest value in the sea buckthorn oil (70% compared to the walnut oil and 28% compared to the average value of meat and fat) From the above findings, in the current situation, research is focusing on the nutritional composition and quality of dried sausage One of the criteria evaluated are most interested is that the fatty acid composition in dry sausages which are primarily implemented on the system GC-MS analysis This approach is in tune with the trend of research on dry sausage and countries around the world with the advantages of using modern analytical systems 1.1.2 The studies on other dry-cured salami produced abroad In regard to salami, it is thought that the name is derived from Latin words “salsiccia” and “salumen” In Europe, the main countries that produce salami are Romania, Germany (Tesco German Salami 125G, Salami pepper Germany), Italy (Cremona salami, Nduja, Calabrese salami), Spain (Iberian Salami, Serrano Ham D.O Teruel) France (Saucisson sec-200g, Garlic cervelat, Chorizo-200g), and Hungary (Bende Teli Hungarian Style Salami) The amount produced is of “several hundred million kg per year.” Worldwide, there are many different versions of sausages, each with its own cultural and flavour profiles For example, due to immigration to North America, European settlers brought many traditions, including fermented meats such as bologna or pepperoni Similar types of sausages are found in the Middle East, where various meats such as beef, lamb, and mutton are used, or in China where “Lap Cheong”, translated as “intestines stuffed in the winter” is usually pork Likewise, in Eastern Figure 2.6.3 Dendrogram of analysis the fat from salami samples by NMR The AHC results show a similarity between the Sibiu and Sinaia samples which cluster in a group, different from Banatean, Dacia and sample pork back fat Figure 2.6.4 Correlations between variables and factors 39 The intensity of the signal from the NMR spectra was subjected to the PCA analysis Figure 2.6.4 shows the variables were almost concentrated in one area, F1 and F2 explained up to 92.02% of total variance, 82.79% being explained by F1 and 9.25% by F2 Almost all variables have an important role, aside from ld which is less important than the other variables Figure 2.6.5 Score representation for F1 and F2 analysis factors obtained by PCA Results revealed that Salam Dacia-producer separates out because it contains beef and pork meat plus a maturation process as shown in Figure 2.6.5 The samples of Banatean salamis, from all producers, showed a tendency to cluster As well Sibiu and Sinaia samples tend to cluster, mainly because the row material is similar, the only difference is given by the maturation process Therefore, we can conclude that the maturation process does not produce an important change in the FAP of the fat 40 extracted from the samples The most important changes in the FAP is given by recipe of the product type of meat and ingredients ratio 2.7 Chemometric analysis of the spectral data (PCA, AHC) Chemometrics is the use of mathematical and statistical methods to improve the understanding of chemical information and to correlate quality parameters or physical properties Patterns in the data are modeled, these models can then be routinely applied to future data in order to predict the same quality parameters The result of the chemometrics approach is gaining efficiency in assessing product quality It can lead to more efficient laboratory practices or automated quality control systems The only requirements are an appropriate instrument and software to interpret the patterns in the data Chemometrics software is designed to recognize patterns in virtually any type of multidimensional analytical data Chemometrics can be used to speed methods development and make routine the use of statistical models for data analysis The science of chemometrics gives spectroscopists many efficient ways to solve the calibration problem for analysis of spectral data Chemometrics can be used to enhance methods development and make routine use of statistical models for data analysis In conclusion, Chemometrics is the bridge between connecting the state of a chemical system to the measurements of the system It has become an essential part in the modern chemical and biomedical industries Chemometrics software has been widely used by product development scientists, process engineers, PAT specialists, and QA/QC scientists to build reliable model, ensure product quality In the current thesis, the XLSAT addin software was used to analysis the spectral data 41 2.7.1 Agglomerative Hierarchical Clustering (AHC) AHC is one of the most popular clustering methods Available in Excel using the XLSTAT statistical software Agglomerative Hierarchical Clustering (AHC) is a clustering (or classification) method which has the following advantages: It works from the dissimilarities between the objects to be grouped together A type of dissimilarity can be suited to the subject studied and the nature of the data One of the results is the dendrogram which shows the progressive grouping of the data It is then possible to gain an idea of a suitable number of classes into which the data can be grouped The synthesis of results on both systems GCMS and NMR has once again considered the accuracy of the analytical results Figure 2.7.1 Dendrogram of analysis the fat from salami samples by GC-MS and NMR According to the Figure 2.7.1 we found these samples were classified into four main categories C1, C2, C3 and C4 Inside, at the clusters C1 and C2 were the simple pork back-fat samples 42 2.7.2 Principal Component Analysis (PCA) Principal Component Analysis (PCA): is one of the most frequently used multivariate data analysis methods It is a projection method as it projects observations from a p-dimensional space with p variables to a k-dimensional space (where k < p) so as to conserve the maximum amount of information (information is measured here through the total variance of the dataset) from the initial dimensions PCA dimensions are also called axes or Factors If the information associated with the first or axes represents a sufficient percentage of the total variability of the scatter plot, the observations could be represented on a or 3-dimensional chart, thus making interpretation much easier (PCA) Recognize patterns in data: outliers, trends, groups… Transformation of the numbers into pictures by using principal component analysis (scores) X is an n samples (observation) by y variable (spectral variable) matrix The GC-MS with 1H-NMR data were subjected to the PCA analysis Figure 2.7.2 Correlations between variables and factors The F1 and F2 factors explain 73.81% of the system variable The variables have similar importance for the system, except for palmitoleic or ld owes 43 Figure 2.7.3 The representation of the scores for F1/F2 The results showed in Figure 2.7.3 prove that Salam Sibiu formes a separate group from other types of dry-cured salami The sample pork back fat separates completely from the fat extracted from the salami Therefor, Using the spectral information obtained from GC-MS combined with the ones from 1H-NMR, a good data base is obtained for authentication of Sibiu Salami against similar products produced in Romania These results are a good base for authentication of Sibiu Salami against other similar products on the enlarged EU markets or even international ones 44 INSTRUMENTS AND METHODS 3.1 Fat extraction – Soxhlet procedure Because of commercial regulations, it is important for foods producers to be able to report fat/lipids content in their products It is also important, in several industries, to closely monitor the fat content since it affects the quality or value of the product Soxhlet extraction is one of the most commonly used methods for determination of total fat This is mainly because it is simple to use it and it is the officially recognized method for a wide range of fat content determinations Nowadays improved extraction techniques tend to be more accurate and more generally applicable and can therefore often replace the old standard method for official analysis of many food materials The “Soxhlet” method described here is recognised by the Association of Official Analytical Chemists (AOAC) as the standard method for crude fat analysis The Soxhlet method for determining crude fat content is a lengthy process requiring up to a day for a single analysis The solvent extraction step alone takes six hours The method is therefore not favoured for routine testing purposes in the meat industry, rather it is used as a standard reference method As well as being used to determine the fat content of meat and meat products, the Soxhlet method can be used to determine the fat content of meat meal In the case of meat meal, the Soxhlet method is often the method of choice as a routine test Before the solvent extraction step can begin the sample must be dried Often a moisture analysis is required as well as a fat analysis and this can be achieved by accurately weighting the sample after drying and before extraction, as well as before drying If a moisture analysis is not required, the sample need only be weighed before drying and again after solvent extraction In either case the sample must be weighed accurately on an analytical balance at each stage of the analysis Procedure:  Rinse all glassware with petroleum spirit, drain, dry in an oven at 1020C for 30 and cool in a desiccator  Accurately weigh 10 g of salami into the thimble Insert the thimble in a Soxhlet liquid/solid extractor (Figure 3.1) 45  Accurately weigh a clean, dry 250 mL round bottom flash and put about 90 mL of petroleum spirit into the flask  Assemble the extraction unit over either an electric heating mantle or a water bath Heat the solvent in the flask until it boils Adjust the heat source so that solvent drips from condenser into the sample chamber at the rate of about drops per second  Continue the extraction for hours Remove the extraction unit from the heat source and detach the extractor and condenser Replace the flask on the heat source and evaporate off the solvent (The solvent may be distilled and recovered)  Weight of empty flask (g) = W1 Weight of flask and extracted fat (g) = W2 Weight of sample = S % Crude fat = (W2 – W1) x 100/ S Figure 3.1 Soxhlet extraction apparatus 46 3.2 Transesterification procedure for obtaining FAME Weigh 0.5 gram of fat sample into a small flask, add 0.9ml NaOH/MeOH (1g NaOH add 100ml MeOH) solution Operating under a well-ventilated fume hood provided with a water scrubbing system, and heat using the electric heater control the heating so as to limit the production of foam in the flask Keep the mixture boiling gently in 10 minute Avoid local overheating and avoid heating the flask above the surface of the liquid contents Then add 0.1ml BF3 in MeOH solution 25% and 0.75ml MeOH solution Keep the mixture boiling gently in 10 minutes again Cool the mixture in air to room temperature Quantitatively transfer the liquid contents into a 10ml one-mark separatory funnel Then, add 0.75ml CH2Cl2 solution and 4ml of water Shake in minute, wait for partitioning Separates of the resulting two phases Extracting the lower layer (The organic phase), add more CH2Cl2 into upper layer (aqueous phase) and it again Add MgSO4 to absorb water in the organic phase (it is very important to GCMS) 3.3 GC-MS Analysis The standard mixture of 37 fatty acids methyl esters (Supelco™ 37 Component FAME Mix) used for the gas-chromatographic analyses was used as standard The gas-chromatograms of the fatty acid methyl esters mixtures were recorded on an Agilent Technologies model 7890A instrument coupled with an Agilent Technologies model 5975 C VL, provided with Triple Axis MSD Detector and Agilent auto-sampler The separation into components was made on a capillary column specially designed for the FAME analysis (Supelco SPTM 2560, with the following characteristics: 100 m length, 0.25 mm inner diameter, 0.2 μm film thickness) The ready for injection solutions were prepared in CH2Cl2 of HPLC purity grade 47 Fatty acids identification was made by comparing the retention time for each peak with those of a standard mixture of 37 fatty acid methyl esters (SupelcoTM 37 Component FAME Mix) In the standard mixture the exact concentration of each component is known Both standard mixture and each of the fatty acid methyl esters of the analysed salami fat were chromatographically separated under the same conditions, using the same temperature program (oven initial temperature 140 ºC to final temperature 240 ºC, heating rate ºC/min.), injection volume µL, split rate 100:1, carrier gas He, according to the Supelco specifications, total analysis time 55 minutes The calibration of the signals was made by taking into account the concentration of each component of the standard mixture, correlated with the detector‟s response 3.4 FT-IR Analysis FT-IR spectra were recorded on a Bruker Equinox 55 Spectrometer, with horizontal device for attenuated reflectance and zinc selenite crystal, on a spectral window ranging from 4000 to 600 cm-1, at a spectral resolution of cm-1 Spectra were recorded without any sample preparation and were processed with OPUS 5.5 program Differentiation of the samples was performed using the relative intensity of absorption bands The area between 3050 and 4000 cm-1 was eliminated from the study because it contains information which is not relevant for oils discrimination (water absorbance) and it is also a source of noise in the spectrum The spectral region used ranges in the interval 1800-650 cm-1; each IR spectrum was represented as a vector 3.5 NMR Analysis The 1H-NMR spectra of the fat extracted from salami were recorded on a Bruker Avance III 400 spectrometer, operating at 9.4 Tesla, corresponding to the resonance frequency of 400.13 MHz for the 1H nucleus, equipped with a direct detection four nuclei probe head and field gradients on z axis Samples were analysed in mm NMR tubes (Wilmad 507) The chemical shifts are reported in ppm, using the TMS as internal standard 48 Typical parameters for 1H-NMR spectra were: 45° pulse, 2.05 s acquisition times, 6.4 KHz spectral window, 16 scans, 26 K data points The FID was not processed prior to Fourier transformation The average acquisition time of the 1H-NMR spectra was approximately minutes The samples were prepared by dissolving the fat in CDCl3 with a dilution of 0.2:0.8 (V/V) CONCLUSION The successful authentication of Sibiu Salami based on chemometric analysis of spectral data brought the precise and useful in the analysis of fatty acids Used spectral information obtained by means of (GC-MS, IR and NMR) spectroscopic methods and analysed through chemometric methods A literature review regarding the analytical methods used for chemical composition and authentication of sausage/salami products was accomplished There were four groups of samples collected: Sibiu, Dacia, Banatean and Sinaia salamis The results of 1H-NMR analysis of the fat extracted could conclude that the maturation process does not produce an important change in the FAP of the fat extracted from the samples The most important changes in the FAP is given by recipe of the product type of meat and ingredients ratio Using the spectral information obtained from GC-MS combined with the ones from 1H-NMR, a good data base is obtained for authentication of Sibiu Salami against similar products produced in Romania These results are a good base for authentication of Sibiu Salami against other similar products on the enlarged EU markets or even international ones 49 List of Tables Table 1.1 The content of different fatty acids in beef meat and various sausages [1,11,13] 15 Table 1.2 Fatty acid composition (of total fatty acids) of the milano-type salamis manufactured in different European countries [19] 25 Table 1.3 Common Saturated Fatty Acids 28 Table 2.1 The main ingredients of the relevant dry cured salami 31 List of Figures Figure 1.1 High-resolution 1H-NMR spectra of TLE (total lipid extract), FAME (fatty acid methy ester), and FFA (free fatty acid) recorded for the analysis of ‘soppressata dolce’ 22 Figure 2.4.1 The concentration of the fatty acids obtained thought the GC-MS analysis were used in the chemometric 32 Figure 2.4.2 Dendrogram for the fat extracted from salami samples and analysed on FAME at GC-MS 32 Figure 2.4.3 Correlations between variables and factors 33 Figure 2.4.4 Score representation for F1 and F2 analysis factors obtained by PCA 34 Figure 2.5.1 FT-IR spectral 35 Figure 2.5.2 Dendrogram of analysis the fat from salami samples by FT-IR 36 Figure 2.5.3 Score representation for F1 and F2 analysis factors obtained by PCA 36 Figure 2.6.1 1H-NMR spectra of Sibiu Salami (red colour) and pork back fat (blue colour) 37 50 Figure 2.6.2 1H-NMR spectral of the four type of dry cured salami analised (1- Sibiu salami, 2Dacia salami, 3- Banatean salami, 4- Sinaia salami) 38 Figure 2.6.3 Dendrogram of analysis the fat from salami samples by NMR 39 Figure 2.6.4 Correlations between variables and factors 39 Figure 2.6.5 Score representation for F1 and F2 analysis factors obtained by PCA 40 Figure 2.7.1 Dendrogram of analysis the fat from salami samples by GC-MS and NMR 42 Figure 2.7.2 Correlations between variables and factors 43 Figure 2.7.3 The representation of the scores for F1/F2 44 Figure 3.1 Soxhlet extraction apparatus 46 51 REFERENCES C Pop, L Bara, E Horj, A Iordache, C Laslo, M Culea “Determination of Free Fatty Acids in Sausage Meat” Bulletin UASVM Agriculture, 2010, 67(2), 1-5 A.M.C Simion, J Carballo, P Alexe “Lipolytical changes in Dacia sausage, a Romanian dry cured sausage” Journal 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successful authentication of Sibiu Salami based on chemometric analysis of spectral data brought the precise and useful in the analysis of fatty acids... FT-IR analysis of the extracted fat Activity 5: NMR analysis of the extracted fat Activity 6: Chemometric analysis of the spectral data 2.2 Collection of the relevant samples of Sibiu Salami. .. method for authentication of Sibiu Salami against other meat products of its class, using spectral data combined with chemometrical analysis The GC-MS and NMR spectral data have been used as data base