SPME-MS-MVA

Marsili, R.T. (1999) SPME-MS-MVA as an electronic nose for the study of off-flavors in milk. J. Agric. Food Chem. 47 648-654. 

MarsUi, R.T. SPME-MS-MVA as a rapid technique for assessing oxidation off-flavors in foods. Adv. Expt. Med. Biol. 488, 89-100 (2001). 

One approach recently reported is referred to as SPME-MS-MVA (13,14). This technique uses solid-phase microextraction (SPME), mass spectrometry (MS), and multivariate analysis (MVA) as an e-nose system. A conventional GC/ MS analytical capillary column can be used at an elevated temperature in place of the short uncoated deactivated retention gap. Coelution of volatile components occurs, but this is of no concern when using the GC/MS as an e-nose. With this configuration, one can switch from using the GC/MS as an e-nose to a conventional GC/MS simply by changing the temperature program of the column. 

SPME-MS-MVA applications reported to date have used the Varian Saturn ion trap mass spectrometer and 75- J,m Carboxen/PDMS as the SPME fiber (13,14). In one study, for example, SPME-MS-MVA was used to classify various types of food samples according to the level of oxidized off-flavors they contained (14). Mass fragmentation data resulting from the unresolved food volatile components were subjected to MVA. The mass intensities from m/z 50 to m/z 150 were selected to perform MVA. PGA based on SPME-MS-MVA provided rapid differentiation of the following types of samples control soybean oil from oxidized soybean oil that was exposed to fluorescent light for various time periods control nondairy coffee creamer from complaint ( oxidized ) nondairy coffee creamer samples fresh boiled beef from boiled beef with various levels of warmed-over flavor (WOE) and control 2% reduced-fat milk samples from 2% reduced-fat milk samples abused by light or copper exposure. 

To illustrate the utility of SPME-MS-MVA for QC food applications, consider how it can be applied to monitoring the development of WOF in boiled beef. 

Figure 12 PCA scores plot of mass intensity data for fresh boiled beef and boiled beef refrigerated for 4 days and 6 days and then reheated. Analyses performed by SPME-MS-MVA.

Figure 12 shows that SPME-MS-MVA is capable of quickly identifying groups of samples with similar levels of WOF. 

Besides predicting categories for samples, MS e-nose instruments can also be used for determining a continuous property of samples. Continuous properties are modeled and predicted by regression methods. Details describing how SPME-MS-MVA has been used for predicting the shelf life of milk are described below (16). 

Recent advances in sample preparation techniques now make analysis of off-flavor metabolites simple, fast, accurate, and sensitive. With the SPME-MS-MVA technique, a mass intensity list representing all the volatiles in the milk sample is the basis for shelf-life prediction—not GC peak area data. SPME-MS-MVA prediction of processed milk shelf life is based on measurement of volatiles and semivolatiles present in milk after a pre-incubation period. 

SPME-MS-MVA shelf-life prediction models were developed for reduced-fat milk samples of known shelf life. Mass intensity lists were determined for 84 samples of reduced-fat milk. Sixty-four of these samples were used to develop a PLS calibration model, and 20 samples (a Model Validation Subset ) were randomly selected from the set of 84 total samples to evaluate how well the PLS model for reduced-fat milk could predict shelf life. 

Table 2 compares actual shelf life (determined by sensory evaluation) to predicted shelf life for the 20 PLS Model Validation Subset samples for reduced-fat milk. On average, the SPME-MS-MVA PLS model for reduced-fat milk predicted the shelf life with an accuracy of 0.62 days, with a correlation coefficient of 0.9801 and a range of -0.7 to 2.8 days. 

Predicted from SPME-MS-MVA data using PLS prediction models. 

Figure 13 Plot of predicted shelf life (based on PLS modeling) versus actual shelf life (based on sensory testing) for 64 samples used to prepare a PLS model for reduced-fat milk. Analyses performed by SPME-MS-MVA.

Preliminary results using SPME-MS-MVA as an electronic-nose system appear to give more accurate predictions of milk shelf life than most methods currently used to estimate milk shelf life. (See Table 4.) SPME-MS-MVA is also faster and easier to implement than other shelf-life prediction methods. Furthermore, SPME-MS-MVA has been shown to be useful for identifying samples with nonmicrobiological induced off-flavors and for determining the cause of off-flavors even when nonmicrobiological agents are involved. 

Over a 7-month period, SPME-MS-MVA has been shown to be an accurate technique for predicting the shelf life of reduced-fat milk. Despite the fact that during the testing period significant changes occurred with the mass spectrometer (replacement of the turbomolecular pump and replacement of the electron multiplier) and the fact that several different Carboxen/PDMS fibers were used, internal standard normalization with chlorobenzene allowed accurate prediction over the 7-month period. Long-term stability, a problem with many e-nose instruments based on solid-state sensors, does not appear to be a significant problem with MS-based e-nose instruments. 

SPME-MS-MVA has strong potential applications in the dairy industry for shelf-life prediction. Testing over a longer period of time and sampling from different production facilities should be conducted to confirm the accuracy of this new test as a predictor of shelf life. With a SPME autoinjector and minor test modifications, it would be possible to analyze one sample every five to seven minutes. The only labor required by the QC technician would be to pipette 3 mL of milk into a GC vial. 

Figure 14 illustrates a possible strategy for implementing SPME-MS-MVA in a dairy QC lab. A processed milk sample would first be analyzed in the dairy processing plant laboratory by SPME-MS-MVA to estimate shelf life as de-... 

Analyze pre-incubated milk at dairy Q.C. lab in processing plant using SPME-MS-MVA based on the low cost Varian Saturn 2100 equipped with a Combi PAL SPME autosampler... 

Figure 14 A strategy for using SPME-MS-MVA as a dairy QC screening tool. Rapid screening is performed using a GC/MS as an e-nose to estimate shelf life of fresh processed milk subsequent checking of suspect samples (i.e., those with unusually short shelf life) can be conducted with additional manipulation of the TIC GC/MS file by trained chemists (e.g., at a corporate research chemistry lab) without the need for retesting samples. MVA based on mass intensity data.

If the initial screening indicates a potential shelf life problem (for example, if SPME-MS-MVA predicted a shelf life of 10 days or less instead of the typical 15-17 days), then the chromatographic file (total ion chromatogram) could be subjected to further scmtiny in order to uncover the cause of the off-flavor. The .ms file, which contains all the information necessary to perform conventional MS identification of chromatographic peaks, could be e-mailed to a corporate research lab. The corporate lab could then perform more sophisticated analysis of the data. It could, for example, do further multivariate analysis investigations... 

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