Fatty acid and fatty acid methyl ester analysis can be applied to various industries.
In the field of food nutrition and food chemistry, GC and LC analysis of fatty acids and their methyl ester derivatives (FAME) are important tools for fat characterization.
In the chemical industry, fatty acid methyl esters are important chemical raw materials. FAME obtained from the methyl esterification of vegetable oils or other oils are popular for biodiesel fuels. There are differences in composition and content of biodiesel made from raw materials of different sources. An accurate understanding of the composition and content of mixed fatty acid methyl esters is helpful for the quality control of biodiesel and subsequent products.
The fatty acid components commonly contained in microbial cell structure have a high degree of homology with microbial DNA, and various microbes have their characteristic cellular fatty acid fingerprints. Analyzing the phospholipid fatty acid on the cell membrane of microorganisms can promote the detection and identification of microbial diversity and the study of microbial diversity.
Creative Proteomics has established a fatty acid methyl ester analysis platform, using LC-MS/MS and GC-MS/MS technologies to achieve efficient and accurate composition and quantitative analysis of fatty acid methyl esters.
Methyl butyrate (C4:0) | Methyl 9-cis-tetradecenoate(C14:1n5) | Methyl oleate (C18:1n9c) | Methyl cis-11,14-eicosadienoate (C20:2n6) | Methyl cis-13,16-docosadienoate (C22:2n6) |
Methyl caproate (C6:0) | Methyl pentadecanoate (C15:0) | Methyl oleate (C18:1n9t) | Methyl cis 8,11,14-eicosatrienoate (C20:3n6) | DHA methyl ester (C22:6n3) |
Methyl caprylate (C8:0) | Methyl cis-10-pentadecenoate (C15:1n5) | Methyl linoleate (C18: 2n6c) | Methyl cis-11,14,17-eicosatrienoate (C20:3n3) | Methyl tridecanoate (C23:0) |
Methyl decanoate (C10:0) | Methyl palmitate (C16:0) | Trans-linoleic acid methyl ester (C18: 2n6t) | Methyl arachidonic acid (C20:4n6) | Methyl lignocerate (methyl tetracosanoate) (C24:0) |
Methyl undecanoate (C11:0) | Methyl palmitoleate (C16:1n7) | Methyl γ-linolenate (C18:3n6) | Cis-5,8,11,14,17-eicosapentaenoic acid methyl ester (C20:5n3) | Methyl tetradecenoate (C24:1n9) |
Methyl laurate (C12:0) | Methyl heptadecanoate (C17:0) | Methyl α-linolenate (C18:3n3) | Methyl Eicosanate (C21:0) | |
Methyl tridecanoate (C13:0) | Methyl cis-10-heptadecenoate (C17:1n7) | Methyl arachidate (methyl eicosanate) (C20:0) | Methyl behenate (C22:0) | |
Methyl myristate (C14:0) | Methyl stearate (C18:0) | Methyl cis-11-eicosenoate (C20:1) | Methyl parasinate (C22:1n9) |
At Creative Proteomics, we offer Fatty Acid Methyl Ester (FAME) analysis services utilizing advanced analytical techniques and state-of-the-art instrumentation. FAME analysis is a critical component of various applications, including food industry quality control, biodiesel production, and lipidomics research.
Analytical Technique | Description |
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Gas Chromatography (GC) | Gas chromatography is the most common method for FAME analysis. It involves separating and quantifying FAME compounds using a gas chromatograph, often with a Flame Ionization Detector (FID). The FAMEs are vaporized and passed through a capillary column where they are separated based on their chemical properties and then detected. |
High-Performance Liquid Chromatography (HPLC) | HPLC is an alternative to GC for FAME analysis. It separates and quantifies FAMEs using a liquid chromatograph, typically with a UV or fluorescence detector. It is particularly useful for polar FAMEs. |
Mass Spectrometry (MS) | Mass spectrometry can be coupled with GC or HPLC to identify and quantify FAMEs. It provides detailed structural information based on the mass-to-charge ratio of the compounds. |
Fourier Transform Infrared Spectroscopy (FTIR) | FTIR spectroscopy can be used to identify functional groups in FAMEs by measuring the absorption of infrared light. It's suitable for qualitative analysis and is often used to confirm FAME presence. |
Nuclear Magnetic Resonance (NMR) | NMR can provide detailed structural information about FAMEs. It is not as common as GC or HPLC but is valuable for in-depth structural analysis. |
Thin-Layer Chromatography (TLC) | TLC is a simple and cost-effective method for separating FAMEs based on their physical properties. It's often used for quick qualitative analysis and to check the purity of FAME samples. |
Gravimetric Analysis | Gravimetric analysis involves the separation of FAMEs from a sample and their quantification based on changes in mass during the chemical reaction. It's useful for determining FAME content. |
Spectrophotometry | Spectrophotometric methods can be used to measure FAME content based on the absorption of specific wavelengths of light. These methods are often used in conjunction with other techniques for quantitative analysis. |
Titration | Acid-base titration methods can be used to quantify FAME content by measuring the amount of acid or base required to neutralize the FAMEs. This is particularly relevant for biodiesel quality assessment. |
A typical workflow of mass spectrometry-based lipidomics (Wang et al., 2019)
Requirement | Specification | Details |
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Sample Type | Vegetable Oils (Soybean, Canola, Olive), Animal Fats (Beef Tallow, Pork Lard), Dairy Products (Butter, Cheese), Seafood (Fish Oil, Krill Oil), Algal Oil, Biodiesel, Microbial Cultures, Human Body Fluids (Serum, Plasma, Breast Milk), Animal Tissues (Chicken, Beef, Pork) | A wide range of sample types, covering food, biological, bodily fluids, microbial cultures, and animal tissues |
Sample Size | 5 grams (for solid samples), 10 mL (for liquid samples), 1 mL (for bodily fluids), 5 grams (for animal tissues) | Quantity of sample required for analysis |
Extraction Solvent | Methanol or Hexane | Choice of solvents for FAME extraction |
Reaction Temperature | 70°C | Temperature at which the reaction occurs |
Gas Chromatograph (GC) Method | GC-FID or GC-MS | Analysis methods with FID or Mass Spectrometry detection |
Column Type | Capillary Column | Type of GC column used for separation |
Column Temperature | 200°C | Temperature of the GC column during analysis |
Detection Limits | ≤ 0.05% | Low detection limits to ensure precision |
FAME Profile | C16:0, C18:1, C18:2, C18:3, etc. | Specific fatty acids of interest |
Delivery time: 2-4 weeks
Creative Proteomics has many years of experience in lipidomics analysis services, and enjoys a good reputation in supporting the detection and quantification of various lipids. Based on a highly stable, reproducible and highly sensitive separation, characterization, identification and quantitative analysis system, we provide reliable, fast and cost-effective fatty acid methyl ester analysis services. If you have other substances you want to test or other questions, please contact us.
Case: Discrimination and Quantification of Lard Adulteration in Olive Oil Using GC-MS Metabolomics Approach
Background
The study addresses the pressing issue of food adulteration, specifically the adulteration of olive oil with lard. The quality and authenticity of food products are paramount due to their significant impact on health and the economy. As a complex mixture, food requires reliable methods for assessing quality and authenticity. Foodomics, particularly metabolomics, has emerged as a discipline for studying food and nutrition domains through omics technologies.
Samples
Technical Methods:
The study employed Gas Chromatography-Mass Spectrometry (GC-MS) for the analysis of FAMEs. Several key technical steps were involved, including:
Results:
Discriminant markers for distinguishing between olive oil and lard, such as methyl palmitate, methyl oleate, and methyl stearate.
Clear differentiation between pure olive oils and lards in PCA score plots.
A quantification method to detect and quantify lard adulteration in olive oil.
Evaluation of adulterated samples even at low lard percentages (5%) using Euclidean distance.
The potential for applying the method to investigate the authenticity of various animal fats and vegetable oils in different food products and cosmetics.
PCA score plot and Euclidean distance plot for adulteration samples. ((d2 - d1) was difference distances between adulterated samplespure olive oil (d2) and adulterated samples- pure lard (d1))
The changes in FAME composition of olive oil adulterated with different levels of lard (Color figure available online)
Reference
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