The Role of NMR in Food Production

Solid fat content, or SFC in short, is considered a critical quality control parameter for edible oils utilized in the confectionery, bakery, and margarine sectors. But conventional techniques for determining the precise SFC in edible oils and fats are not only slow but also inaccurate.

By contrast, nuclear magnetic resonance (NMR) can redefine the way individuals conform to official standards and help identify accurate SFC in edible oils and fats.

Improving Health and the Taste Experience

Food production is bound by numerous regulations developed to ensure the health and safety of the consumer. But advice and legislation regarding fat profiles change constantly as researchers come to terms with the advantages or drawbacks of specific substances.

Trans fats are an excellent example of a substance that was earlier assumed to be beneficial. However, people are now aware that these fats can actually increase the risk of coronary artery disease. In order to reduce trans fats, the product has to be reformulated without compromising on the properties that tempt consumers to purchase it.

In particular, SFC plays a major role in how food feels and tastes. “Mouthfeel” is one of the most vital aspects of how people perceive food, and this mostly had to do with the types of fat utilized in the products.

People of a specific age might recall the old advertising slogan—“the milk chocolate melts in your mouth, not in your hands.” That is one way where SFC plays a role—by establishing the melting profiles of numerous edible oils utilized in confectionery.

At the other end of the scale, the same SFC helps to identify the temperatures at which food can be stored. This helps to retain the quality and safety aspects of the food all through its production and distribution. Hence, SFC plays an important role in how food is produced and stored, and also how it is made healthier and tastier.

As a result, the precise measurement of the SFC represents a major part of the food production process. Conventionally, a thermo-analytical technique called dilatometry would be used for measuring the expansion or shrinkage of materials over a regulated temperature system. But this method is considered cumbersome, inaccurate, and slow. Hence, several laboratories and companies have switched to NMR to establish the accurate levels of SFC in any specified product.

A Simple, Speedy Process

The NMR measurement process is simple. After the samples are melted and cooled to zero temperature for an hour, each of them is heated to the correct temperature. Subsequently, an eight-second picture is taken of both the liquid and solid signals from the NMR Free Induction Decay (FID) of the sample. The samples are measured for every temperature of interest, until a complete melting profile has been achieved for every sample.

That is the reason why NMR has been the preferred technique for the food sector for many years, but it can be very difficult to find the right device. While the process may seem to be easy, the related technical equipment and software also play a major role.

The MQC+23 NMR analyzer available from Oxford Instruments strives to wrap everything that might be needed by a laboratory into a single sleek package. The analyzer includes an SFC calibration, analysis, and reporting software that guides users via the measurement process, and keeps a record of measurement temperatures and sample identification.

The built-in Solid Fat Reporter software makes it possible to examine, plot, and export the data to other programs and to generate melting profile curves. All these processes are helped by instructions in English, German, French, Japanese, Chinese or Spanish.

The advanced software enables users to accurately measure the varying fat profiles as temperatures increase, without any scope for human errors. The same NMR software and device can also be employed for other measurements, like oil and/or fat content in food.

Why MQC+?

The NMR technique offers a clean, rapid, and reliable solution for analyzing SFC in edible oils. It offers a more effective method to achieve precise results without the need for extensive training.

If users want to track the SFC content of edible oils, the MQC+23 NMR analyzer from Oxford Instruments offers a user-friendly and fully compliant solution with a compact benchtop footprint.

To arrange a demonstration and see how Oxford Instruments’ novel measurement solutions can enhance their operation, users can contact one of the company’s expert team members.

This information has been sourced, reviewed and adapted from materials provided by Oxford Instruments Magnetic Resonance.

For more information on this source, please visit Oxford Instruments Magnetic Resonance.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Oxford Instruments Magnetic Resonance. (2023, March 14). The Role of NMR in Food Production. AZoM. Retrieved on November 21, 2024 from https://www.azom.com/article.aspx?ArticleID=18567.

  • MLA

    Oxford Instruments Magnetic Resonance. "The Role of NMR in Food Production". AZoM. 21 November 2024. <https://www.azom.com/article.aspx?ArticleID=18567>.

  • Chicago

    Oxford Instruments Magnetic Resonance. "The Role of NMR in Food Production". AZoM. https://www.azom.com/article.aspx?ArticleID=18567. (accessed November 21, 2024).

  • Harvard

    Oxford Instruments Magnetic Resonance. 2023. The Role of NMR in Food Production. AZoM, viewed 21 November 2024, https://www.azom.com/article.aspx?ArticleID=18567.

Ask A Question

Do you have a question you'd like to ask regarding this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.