Sample preparation for the analysis of flavors and off-flavors in foods.

Department of Health and Human Services, Food and Drug Administration, National Center for Toxicological Research, Jefferson, AR 72079, USA.
Journal of Chromatography A (Impact Factor: 4.61). 07/2000; 880(1-2):3-33. DOI: 10.1016/S0021-9673(00)00318-6
Source: PubMed

ABSTRACT Off-flavors in foods may originate from environmental pollutants, the growth of microorganisms, oxidation of lipids, or endogenous enzymatic decomposition in the foods. The chromatographic analysis of flavors and off-flavors in foods usually requires that the samples first be processed to remove as many interfering compounds as possible. For analysis of foods by gas chromatography (GC), sample preparation may include mincing, homogenation, centrifugation, distillation, simple solvent extraction, supercritical fluid extraction, pressurized-fluid extraction, microwave-assisted extraction, Soxhlet extraction, or methylation. For high-performance liquid chromatography of amines in fish, cheese, sausage and olive oil or aldehydes in fruit juice, sample preparation may include solvent extraction and derivatization. Headspace GC analysis of orange juice, fish, dehydrated potatoes, and milk requires almost no sample preparation. Purge-and-trap GC analysis of dairy products, seafoods, and garlic may require heating, microwave-mediated distillation, purging the sample with inert gases and trapping the analytes with Tenax or C18, thermal desorption, cryofocusing, or elution with ethyl acetate. Solid-phase microextraction GC analysis of spices, milk and fish can involve microwave-mediated distillation, and usually requires adsorption on poly(dimethyl)siloxane or electrodeposition on fibers followed by thermal desorption. For short-path thermal desorption GC analysis of spices, herbs, coffee, peanuts, candy, mushrooms, beverages, olive oil, honey, and milk, samples are placed in a glass-lined stainless steel thermal desorption tube, which is purged with helium and then heated gradually to desorb the volatiles for analysis. Few of the methods that are available for analysis of food flavors and off-flavors can be described simultaneously as cheap, easy and good.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The use of herbal teas, infusions or tisanes in folk medicine, medicinal phytotherapy as well as for food purposes is still very popular. In classical phytotherapy the active principles of herbal teas are often attributed to their volatile constituents. On the other hand, safety concerns could arise from volatiles as ingredients of infusions. In any case, information on the aromatic composition and volatile fraction of herbal teas is limited. There is a lack of qualitative and quantitative data on the volatile compounds in infusions as well as on the changes of volatile composition during the tea preparation process. For isolation of the volatile compounds from infusions several methods like liquid–liquid extraction, hydrodistillation or solid phase micro extraction have been used. Primarily, the composition has been determined by GC-FID or GC–MS analysis, in exceptional cases by HPLC-PDA or HPLC–MS analysis. The profile of the volatile fraction of herbal teas classified by chemical functionalities of the compounds (hydrocarbons, oxides, alcohols/ethers, aldehydes/ketones, acids/esters) differs from the profile of the corresponding genuine essential oil. Remarkable are losses of hydrocarbons in infusions. This review will cover the phytochemical research that has been carried out on the volatiles of herbal teas and will focus on results of the volatile fraction especially from rosemary (Rosmarinus officinalis), fennel (Foeniculum vulgare subsp. vulgare), lavender (Lavandula angustifolia), thyme (Thymus vulgaris) and chamomile (Matricaria recutita) infusions.
    Phytochemistry Reviews 01/2012; 11(2-3). · 4.15 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Beef quality characteristics can be measured by several physicochemical methods, but consumers usually evaluate beef quality by color or off-flavor. Thus, the detection of off-flavor can be an ultimate quality factor determining consumer purchases. Sensory off-flavor development (OFD) times, in this study, were statistically determined by logistic regression on the sensorial binomial responses for the presence and absence of off-flavor. Furthermore, a kinetic model was created to predict OFD time during beef storage and it was evaluated by comparing sensory and predicted OFD times under dynamic time-temperature conditions. The model was based on the OFD time corresponding to the reciprocal of the reaction constant (1/k). The temperature dependence of the OFD times could be expressed by an Arrhenius relationship. The model for OFD time was proven to be effective at predicting OFD time for several cuts of beef. Consequently, by using this new model, the OFD time of beef can be predicted from its time-temperature history during storage.
    Meat Science 03/2011; 88(4):712-7. · 2.75 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Volatile compounds in skim milk and nonstandardised milk subjected to instant infusion pasteurisation at 80°C, 100°C and 120°C were compared with raw milk, high temperature short time pasteurised milk and milk pasteurised at 85°C/30 s. The composition of volatile compounds differed between infusion pasteurisation treated samples and the reference pasteurisations. The sensory properties of skim milk subjected to instant infusion pasteurisation were described by negative attributes, such as cardboard sour and plastic flavours, which are not associated normally with fresh milk. Partial least squares modelling showed good correlation between the volatile compounds and the sensory properties, indicating the predictive and possible causal importance of the volatile compounds for the sensory characteristics.
    International Journal of Dairy Technology 01/2011; 64(1):34 - 44. · 1.18 Impact Factor

Full-text (2 Sources)

Available from
May 30, 2014