The Column
Food carbohydrate content is routinely analyzed to ensure food quality and taste. Over the years many analytical techniques, including thin-layer chromatography (TLC), enzymatic analysis, and gas liquid chromatography (GLC), have been developed that allow qualitative and quantitative analysis of sugars, organic acids, and alcohol in food. Amongst these, ion‑moderated partitioning high performance liquid chromatography (HPLC) has emerged as a very valuable tool and has been used in thousands of published studies. This article describes the various considerations for selecting and optimizing the use of ion-moderated partitioning HPLC analytical columns for carbohydrate analysis in various types of food samples.
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Payal Khandelwal, Mona Chin, and Anna Quinlan, Bio-Rad Laboratories, Hercules, California, USA
Food carbohydrate content is routinely analyzed to ensure food quality and taste. Over the years many analytical techniques, including thin-layer chromatography (TLC), enzymatic analysis, and gas liquid chromatography (GLC), have been developed that allow qualitative and quantitative analysis of sugars, organic acids, and alcohol in food. Amongst these, ionâmoderated partitioning high performance liquid chromatography (HPLC) has emerged as a very valuable tool and has been used in thousands of published studies. This article describes the various considerations for selecting and optimizing the use of ion-moderated partitioning HPLC analytical columns for carbohydrate analysis in various types of food samples.
Ion-moderated partitioning is a high performance liquid chromatography (HPLC) separation technique that can involve ion exclusion, ion exchange, ligand exchange, size-exclusion, reversed phase, or normal phase partitioning, depending on the base bead of the selected chromatography resin. This type of resin, however, predominantly takes advantage of ion exchange, which separates analytes based on charge, and ion exclusion, which separates molecules of interest by polarity or repulsion (1). For this reason, ionâmoderated partitioning chromatography is often referred to as ion chromatography (IC).
Carbohydrate separation is followed by detection on the HPLC system. Detection options include electrochemical detectors (ED), such as conductivity or pulsed amperometric detectors, and in some cases mass spectrometry (MS). The most commonly used detection systems for IC are ultraviolet–visible (UV–vis) or refractive index (RI) detectors.
The Importance of IC in the Food Industry
IC was first used to reduce the hardness of water during the industrial revolution in Europe. Since then, it has been in use for a wide variety of analytes in the pharmaceutical industry and for environmental, agricultural, and biotechnological applications, and biofuel. This analytical tool has also become crucial to the food industry’s efforts to meet increased demands from the FDA and from consumers. IC has been used to demonstrate food safety, meet mandatory and voluntary government standards, ensure quality control of raw materials as well as final products, provide nutrition labels, and identify ingredients (2). In addition, IC is used for continuous R&D efforts in food development and testing.
In the past decade, this has led to the inclusion of chapters on ion chromatography in the United States Pharmacopeia–National Formulary (USP–NF). Many USP–NF test procedures and assays are now available for the identification and quantification of proteins, organic acids, carbohydrates, sugar alcohols, and other analytes that are important factors in the food and wine industry.
Selecting a Suitable Analytical Column
For certain analytes, published USP protocols are available and should be followed. For analytes that do not have an existing protocol, several factors must be considered to select the HPLC analytical column that provides the best resolution for a particular application. Some important considerations are:
Minimal sample preparation is needed before a sample is loaded onto an ionâmoderated partitioning HPLC column. Usually simple filtration through a 0.45 µm filter suffices. Derivitization is not required here, in contrast to affinity purification.
To prolong the life of IC columns, guard columns are an option. These are smaller versions of the column, which are placed before the main column to absorb components that may foul or damage the main column.
Optimizing the Analysis
After selecting the appropriate analytical column, it is crucial to optimize run conditions. Multiple factors in the run condition can affect the analyte resolution:
USP Classification
The USP has classified different IC resins into numbers such as L17, L19, L22, L34, and L58. These designations are referred to by the USP–NF as well as other international agencies such as the Food and Agriculture Organization (FAO), Food Chemicals Codex (FCC), and European Pharmacopoeia (Ph. Eur.). Resins appropriate for carbohydrate analysis are classified as seen in Table 1.
Applications of IC Columns in the Food Industry
The food industry is driven by narrow profit margins and requires large production volumes and rapid product turnover. IC has been used for many different applications to support this industry.
Carbohydrate analysis of fermentable sugars (using USP L19 columns) in raw materials, such as corn, directly influences the price of sugar product. Marginal mistakes in determining the sugar composition of corn products can result in significant price variation when translated into thousands of pounds of corn. Sugar profile determination can also help identify food spoilage or degradation by microbes, by detecting sugar byproducts released from microbial metabolism. These quick quality controls of raw materials help food manufacturers save considerable costs.
The dairy industry relies on carbohydrate analysis for flavour studies and nutritional assessments. USP L34 is used to assess and quantify different sweeteners added to or naturally occurring in yogurt, milk, and lactose reduced milk. Figure 3 shows the carbohydrate profile for different flavours of yogurt. The three different flavours show different sugar contents and quantities. Such information helps food manufacturers develop food content and nutrition labelling.
Fermentation analysis of carbohydrates and organic acids is routinely performed by the beer and wine industries. USP L17 columns can separate both these species. USP L19 columns are good for quantitating sugar alcohols in fermentation products (Figure 4). Either column can be paired with an RI monitor to detect carbohydrates, glycerol, and alcohol resulting from fermentation, and a UV monitor to detect carboxylic acids, volatile fatty acids, and other fermentation byproducts. Ethanol and glycerol content of wine are not only excellent indicators of fermentation progression, but they can also be used to predict the quality of the final product. Glycerol content, for example, correlates with the smoothness of the wine.
Sugar and organic acid analysis not only applies to process control and spoilage detection or the detection of food additives, but it can also be used to determine vitamin content and nutritional quality. A common application is the detection of vitamin C (ascorbic acid), which occurs naturally in many food products and is also used as a supplement in fortified foods and drinks. Vitamin C is affected most by food processing and is therefore monitored throughout the process to measure its depletion. It can also be an indicator of the depletion of other nutrients. Vitamin C levels are assessed for fruits and vegetables sold in all forms, fresh, frozen, or canned.
Conclusion
As applications for IC in the food industry have grown, an increasing number of varying HPLC options are available. To take full advantage of this powerful analytical technique, it is important to understand how subtle differences in IC columns or methods can impact column performance. By following the general considerations outlined in this article, IC can be used as a powerful tool to ensure food safety and quality and meet the requirement set forth by the FDA and other food regulation agencies.
References
Payal Khandelwal, Ph.D., is a Global Product Manager for Protein Purification at Bio-Rad Laboratories.
Mona Chin is a Global Product Manager for Protein Purification Business at BioâRad Laboratories.
Anna Quinlan, Ph.D., is Editorial Manager at Bio-Rad Laboratories.
E-mail: Payal_Khandelwal@Bio-Rad.comWebsite:www.Bio-Rad.com
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