Determining Fat and Oil in Food Using the ORACLE

Wet chemistry techniques have been traditionally used for testing fat and moisture in foodstuff samples, but these techniques are laborious, time consuming and usually involve hazardous solvents and skilled Technicians. While many rapid techniques such as FT-NIR, FT-IR, NIR and TD-NMR have been developed, none of these have been universally accepted due to the need for often extensive calibration development and maintenance.

The ORACLE, a rapid time-domain NMR (TD-NMR) instrument, is based on advanced technology that makes it possible to directly determine the oil and fat content in foodstuffs. The ORACLE is different from other rapid techniques because it can completely isolate the detection of fat in complex matrices and thus remove the necessity for calibration development. The instrument can also be combined with a SMART 6 moisture/solids analyzer to achieve rapid solids/moisture and fat testing.

A range of 11 samples were obtained and studied in order to show how the ORACLE and SMART 6 can reliably and accurately determine the moisture and fat content present in dairy samples. The samples were carefully chosen to represent both matrix types and relative component concentrations.

Key Benefits of ORACLE

• Rapid (less than 5 minutes for fat and moisture)
• Direct technique, requiring no calibration
• Better repeatability than reference methods
• Bulk measurement (insensitive to granularity and color)

Robot and high capacity heater blocks (100 positions) with ORACLE

Experiment

In order to complete each analysis, the samples were first pre-dried on the SMART 6 (ca. 3 – 4 minutes) and subsequently prepared for analysis in the ORACLE instrument. After the samples were inserted into the ORACLE magnet, they were quickly conditioned (30 seconds) using the QuikPrep™ before NMR analysis (35 seconds). The size of the samples ranged between 2 and 3 g. Each sample was analyzed at least in duplicate for the reference analyses (AOAC approved methods), and at least 5 times for the SMART 6-ORACLE analyses.

Note: High-throughput analyses can be enabled through the use of batch automation using an optional robot and high capacity heater blocks (100 positions).

Results and Discussion

Table 1 shows the accuracy of the ORACLE and SMART 6 results, where comparison is made between the average reference results and the average of the ORACLE and SMART 6 results. It was observed that the average difference ranged from 0.01 to 0.15% for fat and from 0.01 to 0.29% for solids/moisture. Table 2 shows repeatability, where the standard deviations ranged from 0.01 to 0.12% for fat and from 0.01 to 0.11 % for solids/ moisture.

Conclusion

The above results demonstrate that the SMART 6 – ORACLE can reliably determine the fat as well as moisture/solids content present in dairy samples, and also with an accuracy that closely matches with the reference methods. Further, there are also inherent repeatability benefits over the reference methods, which are prone to errors because of a strong reliance on many experimental factors (for example, temperature, solvent composition, extraction time, etc.).

Table 1. Accuracy

Table 2. Repeatability

This information has been sourced, reviewed and adapted from materials provided by CEM Corporation.

For more information on this source, please visit CEM Corporation.