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HPTLC can easily deal with complex and diverse food matrices. It is used for quality control purposes, to screen for food contaminants, and to test for additives.

The analytical challenges of food, feed and related products are immense. One of the problematic aspects is the complexity and diversity of matrices in which analytes are to be determined. The term “Food” means any edible or potable substance containing any nourishing constituents such as carbohydrates, fats, proteins, vitamins and essential minerals, which sustain life, promote growth, provide energy, etc. With HPTLC food ingredients can easily be analyzed. To ensure food safety contaminants have to be excluded. Contaminants in food are defined as “any substance not intentionally added to food, which is present in such food as a result of the production, manufacture, processing, preparation, treatment, packing, packaging, transport or holding of such food or as a result of environmental contamination” (Codex Alimentarius, Codex Standard 193-1995). More dramatic impact may even be seen by intentionally added food additives based on fraud like melamine in milk. For food control and food safety robust and cost-effective high-throughput methods to analyze contaminants in different types of food matrices are needed. HPTLC is in many cases able to deal with high matrix loaded samples. Sample preparation can be minimized because of the single use of the HPTLC plates. That and the ability to treat multiple samples in parallel on the same plate allows high sample throughput at low costs per sample. CAMAG’s HPTLC systems are designed to meet the experts needs for successful analysis and quantification of various types of impurities in food (e.g. mycotoxins, antibiotics, pesticide residues, contaminants migrated into food from packaging, illegal dyes, etc.) and active ingredients (e.g. vitamins, antioxidants, etc.). The same aspects are valid for the analysis of feed samples.

HPTLC is well suited for rapid and easy identification of oil samples as shown in the first case study “Identification of fixed oils by HPTLC”. Based on the USP general chapter ‹202›; CAMAG developed an HPTLC method for the identification of those oils. All vegetable oils are termed “fixed oils” in the USP-NF (United States Pharmacopeia-National Formulary). The term “fixed oils” distinguishes them from the relatively volatile petrochemical oils and essential oils. Fixed oils are obtained by expression or extraction. Their consistency varies with temperature. Some are liquid (oils), others are semisolid (fats), and still others are solid (tallows) at ambient temperature.

Another current topic of public discussion also seen in developing countries is obesity. The daily consumption of carbohydrates, particularly sugar has been correlated with this problem. Low or no calorie sweeteners have therefore become increasingly popular. One of those is Stevia rebaudiana and its sweet steviol glycosides. Since December 2011, steviol glycosides have been permitted for use as food additive and sweetener in the EU. For steviol glycosides (E 960) a daily intake of up to 4 mg/kg body weight, expressed as steviol equivalent, was defined as acceptable.

Prof. Dr. Gertrud Morlock and her team at Justus Liebig University Giessen in Germany have developed analytical tools for Stevia in various food matrices, illustrated in the second case study ”Quantitative determination of steviol glycosides”. In another case study of Gerda Morlock and Ines Klingelhoefer, the detection of estrogen active compounds in beer by HPTLC direct bioautography is shown. HPTLC bioautography combines bioassays with chromatography. By the help of the planar Yeast Estrogen Screen (pYES) endocrine active compounds (EACs) can be sensitively detected in food samples and water, down to the very low µg/kg range. EACs, including estrone and estriol, can effect the endocrine system due to their binding to the human estrogen receptor. The pYES offers a non-target based screening method for this class of substance.

Equip your lab with CAMAG instruments and analytical software, and profit from our freely available methods to solve your analytical tasks in the field of food science.

Case Studies

Matching CBS articles

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  • The fingerprint of biopolymers (polysaccharides)
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Matching methods

  • A-132.1 – Quantification of piperine in black pepper fruit (Piper nigrum L.) and test for minimum content (MCT) of piperine (> 3% Ph. Eur.)
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