Discrimination of commercial cheeses from fatty acid profiles and phytosterol contents obtained by GC and PCA

A Comparative Analysis on the Environmental Impact of Selected Methods for Determining the Profile of Fatty Acids in Cheese

The fatty acid profile of cheese influences its sensory parameters, such as color, texture, or flavor. Examining the fatty acid profile also helps to assess the nutritional value of the cheese that is being tested. However, the determination of fatty acids in cheese samples is a multi-stage and time-consuming task. In addition, large amounts of toxic organic solvents are used to prepare samples for analysis purposes. This paper presents the results of a study to determine the fatty acid profile of yellow cheese samples. Six different methods of sample preparation were compared for analysis purposes. The profile of fatty acids was determined using gas chromatography with flame ionization detection (GC-FID). The study showed significant differences (p > 0.05) in the resulting fatty acid profile between the methods used. It was found that the most reliable fatty acid profile results were obtained using methods derived from the Folch method. In addition, tools such as the Analytical Eco-Scale tool and the Analytical Greenness Metric for Sample Preparation (AGREEprep) tool were used to assess the greenness of the methods used. In the case of the Analytical Eco-Scale tool, all six methods scored 'acceptable green analysis' with scores ranging from 61 to 73. However, an evaluation of methods using the AGREEprep metric showed that the results of the methods (0.13-0.27) did not show the "greenness" of the analytical methods.

Real Time Monitoring of Wine Vinegar Supply Chain through MOX Sensors

Vinegar is a fermented product that is appreciated world-wide. It can be obtained from different kinds of matrices. Specifically, it is a solution of acetic acid produced by a two stage fermentation process. The first is an alcoholic fermentation, where the sugars are converted in ethanol and lower metabolites by the yeast action, generally Saccharomyces cerevisiae. This was performed through a technique that is expanding more and more, the so-called "pied de cuve". The second step is an acetic fermentation where acetic acid bacteria (AAB) action causes the conversion of ethanol into acetic acid. Overall, the aim of this research is to follow wine vinegar production step by step through the volatiloma analysis by metal oxide semiconductor MOX sensors developed by Nano Sensor Systems S.r.l. This work is based on wine vinegar monitored from the grape must to the formed vinegar. The monitoring lasted 4 months and the analyses were carried out with a new generation of Electronic Nose (EN) engineered by Nano Sensor Systems S.r.l., called Small Sensor Systems Plus (S3+), equipped with an array of six gas MOX sensors with different sensing layers each. In particular, real-time monitoring made it possible to follow and to differentiate each step of the vinegar production. The principal component analysis (PCA) method was the statistical multivariate analysis utilized to process the dataset obtained from the sensors. A closer look to PCA graphs affirms how the sensors were able to cluster the production steps in a chronologically correct manner.

A New Kind of Chemical Nanosensors for Discrimination of Espresso Coffee

There are different methods to extract and brew coffee, therefore, coffee processing is an important factor and should be studied in detail. Herein, coffee was brewed by means of a new espresso professional coffee machine, using coffee powder or portioned coffee (capsule). Four different kinds of coffees (Biologico, Dolce, Deciso, Guatemala) were investigated with and without capsules and the goal was to classify the volatiloma of each one by Small Sensor System (S3). The response of the semiconductor metal oxide sensors (MOX) of S3 where recorded, for all 288 replicates and after normalization ∆R/R0 was extracted as a feature. PCA analysis was used to compare and differentiate the same kind of coffee sample with and without a capsule. It could be concluded that the coffee capsules affect the quality, changing on the flavor profile of espresso coffee when extracted different methods confirming the use of s3 device as a rapid and user-friendly tool in the food quality control chain.

Content of Health-Promoting Fatty Acids in Commercial Sheep, Cow and Goat Cheeses

The study aimed to examine samples of different market original sheep cow and goat cheeses, in respect of the content and profile of FA with special emphasis on health-promoting FA. The content of fatty acids in the examined cheeses was highly differentiated and depended on the sort and type of cheese. The content of fatty acid groups in milk fat varied within the limits: SFA, 55.2–67.2%; SCSFA, 10.9–23.4%; BCFA, 1.6–2.9%; MUFA, 15.2–23.4%; PUFA, 1.9–4.3%; trans-MUFA, 1.8–6.0%; and CLA, 1.0–3.1%. From among the examined cheeses, the seasonal sheep cheeses (Oscypek) and mountain cow cheeses were characterized by the highest content of health-promoting fatty acids. The content of health-promoting fatty acids in the fat fraction of these cheeses was CLA 2.1–3.1%, trans-MUFA 3.5–6%, BCFA 2.7–2.9%, and SCSFA 12–18%.

Application of multivariate data analysis for food quality investigations: An example-based review

These days, large multivariate data sets are common in the food research area. This is not surprising as food quality, which is important for consumers, and its changes are the result of a complex interplay of multiple compounds and reactions. In order to comprehensively extract information from these data sets, proper data analysis tools should be applied. The application of multivariate data analysis (MVDA) is therefore highly recommended. However, at present the use of MVDA for food quality investigations is not yet fully explored. This paper focusses on a number of MVDA methods (PCA (Principal Component Analysis), PLS (Partial Least Squares Regression), PARAFAC (Parallel Factor Analysis) and ASCA (ANOVA Simultaneous Component Analysis)) useful for food quality investigations. The terminology, main steps and the theoretical basis of each method will be explained. As this is an example-based review, each method was applied on the same experimental data set to give the reader an idea about each selected MVDA method and to make a comparison between the outcomes. Numerous MVDA methods are available in literature. Which method to select depends on the data set and objective. PCA should be the first choice for data exploration of two-dimensional data. For predictive purposes, PLS is the most appropriate method. Given an underlying experimental design, ASCA takes into account both the relation between the different variables and the design factors. In case of a multi-way data set, PARAFAC can be used for data exploration. While these methods have already proven their value in research, there is a need to further explore their potential to investigate the complex interplay of compounds and reactions contributing to food quality. With this work we would like to encourage food scientists with no or limited knowledge of MVDA to get some first insights into the selected methods.

Alteration of fatty acid profile of milk in Holstein cows fed Bacillus coagulans as probiotic: a field study

BACKGROUND

Probiotics may improve milk quality and the general health status of animals.

AIMS

The effects of dietary Bacillus coagulans PRM101 on milk components, milk fatty acids (FA), and some health indicators of dairy cows were investigated.

METHODS

The probiotic was added to the feed of 12 Holstein cows (2 g/cow: 2 × 1011 CFU/cow) for 63 days compared to a control group fed on the basal ration (n=11). Milk and blood samples were taken on days 0, 21, 42, and 63.

RESULTS

The yields of milk and energy corrected milk (ECM; computed from milk weight and its fat and protein content) decreased linearly and similarly (P=0.60) in both groups. The treatment cows, however, showed quadratic increases in the weights of milk (P=0.03) and ECM (P=0.04) at d42 of the study. Energy corrected milk (d42, P<0.05) and crude protein content of milk (d42, P<0.05; d63, P<0.1) were higher in the cows receiving the probiotic. The proportions of heptadecanoic (C17:0; P=0.002) and linoleic (C18:2; P=0.077) acids in milk fat (g/100 g fat) were higher in the treatment cows on d63. Milk total antioxidant capacity (TAC), malondialdehyde (MDA), and similarly, amyloid A (AA) and haptoglobin (Hp) of milk and blood were not affected. Total antioxidant capacity and MDA were negatively correlated in the control group (r=-0.669, P=0.005). Heptadecanoic acid correlated negatively with milk MDA (r=-0.611, P=0.035) and positively (r=0.591, P=0.043) with serum Hp in the treatment cows.

CONCLUSION

Dietary B. coagulans PRM101 may improve the proportions of C17:0 and C18:2 FA in milk. Some improvements in milk protein and the health status of the cows may also be anticipated.

Determination of milk fat authenticity in ultra-filtered white cheese by using Raman spectroscopy with multivariate data analysis

Cheese is one of the most widely consumed food products in the world. However, the increasing demand for nutritionally enhanced or functional products by the cheese industry has created new approaches that partially or fully replace milk fat. With this, new methods of adulteration have also been noted, potentially leading to these fully/partially-replaced products being offered as cheese. In this study, Raman spectroscopy was used to determine origins of fats in margarine, corn, and palm oils present in white and ultra-filtered cheese samples. Raman spectra were evaluated with partial least square-discriminant (PLS-DA) and PLS to identify fat/oil origins and adulteration ratios. The coefficients of determination and limits of detection for margarine, and corn and palm oil adulteration were found to be 0.990, 0.993, 0.991 and 3.38%, 3.36% and 3.59%, respectively.

SPME-GC-MS and Multivariate Analysis of Sensory Properties of Cheese in a Sack Matured with Probiotic Starter Cultures

RESEARCH BACKGROUND

Cheese in a sack is a traditional cheese produced in Croatia. Types of cheese with similar production technology are made in other countries but chemical and microbiological composition varies between regions. Traditionally, cheese in a sack is produced without the addition of starter cultures. Addition of beneficial probiotic cultures to numerous dairy products has documented advantages. Effects that the addition of probiotic bacteria to traditional cheese have on aroma compounds and sensory properties have not been fully investigated. The aim of this study is to determine the sensory properties and differences in the aromatic profiles between cheese samples ripened in a lambskin sack, produced traditionally without the addition of any starter culture, or with the addition of probiotic bacteria.

EXPERIMENTAL APPROACH

In this study, cheese in a sack was produced with the addition of probiotic cultures Lactobacillus plantarum B and L. lactis ssp. lactis S1. During ripening volatile aroma compounds were analysed with a solid-phase microextraction gas chromatography-mass spectrometry. Sensory properties were evaluated by trained tasters who are familiar with the traditional taste of the cheese from a sack. The results of aroma composition and taste scores were then compared using factorial and principal component analyses.

RESULTS AND CONCLUSIONS

Chromatography showed differences in the composition of aroma compounds and the sensory properties between the cheese produced with Lactobacillus starter cultures and the control cheese, traditionally produced without a starter culture. The addition of probiotic cultures L. plantarum B and L. lactis ssp. lactis S1 resulted in products with better sensory properties and chemical profile of volatile aromatic compounds.

NOVELTY AND SCIENTIFIC CONTRIBUTION

This study investigates the usage of naturally present probiotic cultures as starter cultures in cheese in a sack production. Their effects on aroma profiles and sensory characteristics have been compared for the first time using factorial and principal component analyses.

Chemometric Analysis of Fatty Acids Profile of Ripening Chesses

The number of different types of cheese worldwide exceeds 4000 and dairy fat, composed of about 400 fatty acids (FA), is one of the most complex dietary fats. Cheeses are valuable sources of different bioactive FA, i.e., conjugated FA (CFA). The aim of present study was to determine FA profile of commercially available ripening cheeses, with the special emphasis on CFA profile. Multivariate analyses (cluster analysis (CA), principal component Analysis (PCA), and linear discriminant analysis (LDA)) of chromatographic data have been proposed as an objective approach for evaluation and data interpretation. CA enabled the differentiation of ripening cheeses from fresh cheeses and processed cheeses. PCA allowed to differentiate some types of ripening cheese whereas proposed LDA model, based on 22 analyzed FA, enabled assessing cheeses type with average predictive sensitivities of 86.5%. Results of present study clearly demonstrated that FA and CFA content may not only contribute to overall nutritional characteristics of cheese but also, when coupled with chemometric techniques, may be used as chemical biomarkers for assessing the origin and/or the type of ripening cheeses and the confirmation of their authenticity, which is of utmost importance for consumers.

Analysis of Nitraria Tangutourum Bobr-Derived Fatty Acids with HPLC-FLD-Coupled Online Mass Spectrometry

Fatty acids (FAs) are basic components in plants. The pharmacological significance of FAs has attracted attentions of nutritionists and pharmaceutists. Sensitive and accurate detection of FAs is of great importance. In the present study, a pre-column derivatization and online mass spectrometry-based qualitative and quantitative analysis of FAs was developed. Nineteen main FAs were derivatized by 2-(7-methyl-1H-pyrazolo-[3,4-b]quinoline-1-yl)ethyl-4-methyl benzenesulfonate (NMP) and separated on reversed-phase Hypersil BDS C8 column with gradient elution. All FAs showed excellent linear responses with correlation coefficients more than 0.9996. The method obtained LOQs between 0.93 ng/mL and 5.64 ng/mL. FA derivatives were identified by both retention time and protonated molecular ion corresponding to m/z [M + H]⁺. A comparative study based on FA contents in peel and pulp, seeds and leaves of Nitraria tangutourum Bobr (NTB) from different geographical origins was performed with the established method. Results indicated that NTB were rich in FAs, and the types and contents of FAs varied among tissues. On the other hand, the same tissue of NTB from different geographical areas differed in the content, but not in type, of FAs.

Consumption of dairy products in relation to the presence of clinical knee osteoarthritis: The Maastricht Study

PURPOSE

Observational studies showed inverse associations between milk consumption and knee osteoarthritis (knee OA). There is lack of information on the role of specific dairy product categories. We explored the association between dairy consumption and the presence of knee osteoarthritis in 3010 individuals aged 40-75 years participating in The Maastricht Study.

METHODS

The presence of knee OA was defined according to a slightly modified version of the American College of Rheumatology (ACR) clinical classification criteria. Data on dairy consumption were appraised by a 253-item FFQ covering 47 dairy products with categorization on fat content, fermentation or dairy type. Multivariable logistic regression analyses were performed to estimate odd ratios (ORs) and 95% confidence intervals (95%CI), while correcting for relevant factors.

RESULTS

427 (14%) participants were classified as having knee OA. Significant inverse associations were observed between the presence of knee OA and intake of full-fat dairy and Dutch, primarily semi-hard, cheese, with OR for the highest compared to the lowest tertile of intake of 0.68 (95%CI 0.50-0.92) for full-fat dairy, and 0.75 (95%CI 0.56-0.99) for Dutch cheese. No significant associations were found for other dairy product categories.

CONCLUSION

In this Dutch population, higher intake of full-fat dairy and Dutch cheese, but not milk, was cross-sectionally associated with the lower presence of knee OA. Prospective studies need to assess the relationship between dairy consumption, and in particular semi-hard cheeses, with incident knee OA.

Application of electronic nose for determination of Slovak cheese authentication based on aroma profile

Electronic nose with sensors is used in many industries and for various applications such as quality control, process monitoring, shelf life evaluation, origin or authenticity assessment. The aim of this work was to investigate the electronic nose with FID detectors applicability for characterization of steamed cheese and for the assessment of steamed cheese quality decay during storage. Samples of smoked and unsmoked steamed cheese varieties from 5 Slovak enterprises concerning different regions of Slovakia were analysed. Data from aroma profiles were processed by statistical technique PCA. Compounds like acetaldehyde, 1-propanal, propanoic acid, ethyl hexanoate, furfural, butan-2-one, isovaleric acid, 1-hexanol or α-pinene were determined as significant flavours in fresh steamed cheese samples. In the current study, no significant differences in aroma profiles between fresh and stored cheese samples were confirmed. Thus, differences in main odour substances composition of steamed cheese varieties, obtained from various producers in several geographic regions of Slovakia, were minor.

Modeling of rheological characteristics of the fermented dairy products obtained by novel and traditional starter cultures

Tree different fermented dairy products obtained by conventional and non-conventional starter cultures were investigated in this paper. Textural and rheological characteristics as well as chemical composition during 21 days of storage were analysed and subsequent data processing was performed by principal component analysis. The analysis of samples` flow behaviour was focused on their time dependent properties. Parameters of Power law model described flow behaviour of samples depended on used starter culture and days of storage. The Power law model was applied successfully to describe the flow of the fermented milk, which had characteristics of shear thinning and non-Newtonian fluid behaviour.

Modern analytical methods for the detection of food fraud and adulteration by food category

This review provides current information on the analytical methods used to identify food adulteration in the six most adulterated food categories: animal origin and seafood, oils and fats, beverages, spices and sweet foods (e.g. honey), grain-based food, and others (organic food and dietary supplements). The analytical techniques (both conventional and emerging) used to identify adulteration in these six food categories involve sensory, physicochemical, DNA-based, chromatographic and spectroscopic methods, and have been combined with chemometrics, making these techniques more convenient and effective for the analysis of a broad variety of food products. Despite recent advances, the need remains for suitably sensitive and widely applicable methodologies that encompass all the various aspects of food adulteration. © 2017 Society of Chemical Industry.

Short communication: Discrimination between retail bovine milks with different fat contents using chemometrics and fatty acid profiling

We used a multivariate chemometric approach to differentiate or associate retail bovine milks with different fat contents and non-dairy beverages, using fatty acid profiles and statistical analysis. We collected samples of bovine milk (whole, semi-skim, and skim; n = 62) and non-dairy beverages (n = 27), and we analyzed them using gas-liquid chromatography. Principal component analysis of the fatty acid data yielded 3 significant principal components, which accounted for 72% of the total variance in the data set. Principal component 1 was related to saturated fatty acids (C4:0, C6:0, C8:0, C12:0, C14:0, C17:0, and C18:0) and monounsaturated fatty acids (C14:1 cis-9, C16:1 cis-9, C17:1 cis-9, and C18:1 trans-11); whole milk samples were clearly differentiated from the rest using this principal component. Principal component 2 differentiated semi-skim milk samples by n-3 fatty acid content (C20:3n-3, C20:5n-3, and C22:6n-3). Principal component 3 was related to C18:2 trans-9,trans-12 and C20:4n-6, and its lower scores were observed in skim milk and non-dairy beverages. A cluster analysis yielded 3 groups: group 1 consisted of only whole milk samples, group 2 was represented mainly by semi-skim milks, and group 3 included skim milk and non-dairy beverages. Overall, the present study showed that a multivariate chemometric approach is a useful tool for differentiating or associating retail bovine milks and non-dairy beverages using their fatty acid profile.

Methodologies for the Characterization of the Quality of Dairy Products

The growing interest of consumers in food quality and safety issues has contributed to the increasing demand for sensitive and rapid analytical technologies. Physicochemical, textural, sensory, etc., methods have been used to evaluate the quality and authenticity of milk and dairy products. Despite the importance of these standard methods, they are expensive and time consuming. Recently, spectroscopic methods have shown great potential due to speed of analysis, minimal sample preparation, high repeatability, low cost, and, most of all, the fact that these techniques are noninvasive and nondestructive and, therefore, could be applied to any on-line monitoring system. This chapter gave examples of the application of the most commonly traditional methods for the determination of the quality of milk and dairy products. A special focus is devoted to the use of infrared and fluorescence spectroscopies for the evaluation of the quality of dairy products.

Rapid and sensitive screening of some acidic micronutrients in infant foods by HPLC with fluorescent detector

BACKGROUND

Currently, commercially prepared complementary foods have become an important part of the diet of many infants and toddlers. But the method for simultaneous analysis of different types of micronutrient remains poorly investigated, which hinders the rapid and comprehensive quality control of infant foods. In the presented study, we first tried to employ the fluorescence labeling strategy combined with high-performance liquid chromatography-fluorescence detection for simultaneous determination of some acidic micronutrients including biotin, nicotinic acid, linolenic acid, eicosapentaenoic acid, docosahexaenoic acid, arachidonic acid and linoleic acid in infant foods.

RESULTS

2-(5-Benzoacridine) ethyl-p-toluenesulfonate was used as the fluorescence labeling reagent for simultaneous labeling of the seven components. The labeling conditions were optimized systematically by response surface methodology. The correlation coefficients for the calibration curves of the tested compounds ranged from 0.9991 to 0.9998. Limits of detection were in the range of 1.99-3.05 nmol L(-1) . Relative standard deviation values of retention time and peak area of seven compounds were less than 0.05% and 0.75%, respectively. The intra- and inter-day precision was in the range of 1.81-3.80% and 3.21-4.30%, respectively. When applied to analysis of several infant foods it showed good applicability.

CONCLUSION

The developed method has been proven to be simple, inexpensive, selective, sensitive, accurate and reliable for analysis of some acidic micronutrients in infant foodstuffs. Furthermore, this developed method also has powerful potential in the analysis of many other complementary foodstuffs. © 2015 Society of Chemical Industry.

Detection for Non-Milk Fat in Dairy Product by Gas Chromatography

The aim of this study was to evaluate the potential use of fatty acids, triacylglycerols, and cholesterol in the detection of adulterated milk fat. The fatty acid, triacylglycerol, and cholesterol profiles of the mixtures of milk and non-milk fat (adulteration ratios of 10%, 30%, 50%, 70%, and 90%) were analyzed by gas chromatography. The results showed that concentrations of the fatty acids with oleic acid (C18:1n9c) and linoleic acid (C18:2n6c), triglycerides with C52 and C54, and cholesterol detected are proportional to the adulteration ratios remarkably. Oleic acid (C18:1n9c), linoleic acid (C18:2n6c), C52, and C54 were lower in pure milk fat than in adulterated mixtures. In contrast, pure milk has a higher cholesterol concentration than all adulterated mixtures (adulteration concentration in the range 10-90%). Thus, we suggest that oleic acid (C18:1n9c), linoleic acid (C18:2n6c), C52, C54, and cholesterol are suitable indicators and can be used as biomarkers to rapidly detect adulterated milk fat by gas chromatography. This study is expected to provide basic data for adulteration and material usage. Moreover, this new approach can detect the presence of foreign oils and fats in the milk fat of cheese and can find application in related studies.

Detection of plant oil addition to cheese by synchronous fluorescence spectroscopy

The fraudulent addition of plant oils during the manufacturing of hard cheeses is a real issue for the dairy industry. Considering the importance of monitoring adulterations of genuine cheeses, the potential of fluorescence spectroscopy for the detection of cheese adulteration with plant oils was investigated. Synchronous fluorescence spectra were collected within the range of 240 to 700 nm with different wavelength intervals. The lowest detection limits of adulteration, 3.0 and 4.4%, respectively, were observed for the application of wavelength intervals of 60 and 80 nm. Multiple linear regression models were used to calculate the level of adulteration, with the lowest root mean square error of prediction and root mean square error of cross validation equalling 1.5 and 1.8%, respectively, for the measurement acquired at the wavelength interval of 60 nm. Lower classification errors were obtained for the successive projections algorithm-linear discriminant analysis (SPA-LDA) rather than for the principal component analysis (PCA)-LDA method. The lowest classification error rates equalled 3.8% (∆λ = 10 and 30 nm) and 0.0% (∆λ = 60 nm) for the PCA-LDA and SPA-LDA classification methods, respectively. The applied technique is useful for detecting the addition of plant fat to hard cheese.

Determination of the Authenticity of Dairy Products on the Basis of Fatty Acids and Triacylglycerols Content using GC Analysis

Milk fat is an important food component, and plays a significant role in the economics, functional nutrition, and chemical properties of dairy products. Dairy products also contain nutritional resources and essential fatty acids (FAs). Because of the increasing demand for dairy products, milk fat is a common target in economic fraud. Specifically, milk fat is often replaced with cheaper or readily available vegetable oils or animal fats. In this study, a method for the discrimination of milk fat was developed, using FAs profiles, and triacylglycerols (TGs) profiles. A total of 11 samples were evaluated: four milk fats (MK), four vegetable oils (VG), two pork lards (PL), and one beef tallow (BT). Gas chromathgraphy analysis were performed, to monitor the FAs content and TGs composition in MK, VG, PL, and BT. The result showed that qualitative determination of the MK of samples adulterated with different vegetable oils and animal fats was possible by a visual comparision of FAs, using C14:0, C16:0, C18:1n9c, C18:0, and C18:2n6c, and of TGs, using C36, C38, C40, C50, C52, and C54 profiles. Overall, the objective of this study was to evaluate the potential of the use of FAs and TGs in the detection of adulterated milk fat, and accordingly characterize the samples by the adulterant oil source, and level of adulteration. Also, based on this preliminary investigation, the usefulness of this approach could be tested for other oils in the future.

Multivariate statistical analysis treatment of DSC thermal properties for animal fat adulteration

The adulteration of edible fats is a kind of fraud that impairs the physical and chemical features of the original lipid materials. It has been detected in various food, pharmaceutical and cosmeceutical products. Differential scanning calorimetry (DSC) is the robust thermo-analytical machine that permits to fingerprint the primary crystallisation of triacylglycerols (TAGs) molecules and their transition behaviours. The aims of this study was to assess the cross-contamination caused by lard concentration of 0.5-5% in the mixture systems containing beef tallow (BT) and chicken fat (CF) separately. TAGs species of pure and adulterated lipids in relation to their crystallisation and melting parameters were studied using principal components analysis (PCA). The results showed that by using the heating profiles the discrimination of LD from BT and CF was very clear even at low dose of less than 1%. Same observation was depicted from the crystallisation profiles of BT adulterated by LD doses ranging from 0.1% to 1% and from 2% to 5%, respectively. Furthermore, CF adulterated with LD did not exhibit clear changes on its crystallisation profiles. Consequently, DSC coupled with PCA is one of the techniques that might use to monitor and differentiate the minimum adulteration levels caused by LD in different animal fats.