FOOD PROCESSING


Food processing is a natural application for thermal imaging. Pre-cooked meats are an increasingly popular convenience for busy consumers. Cereals, pastries and snack foods all require precise baking protocols. In these food applications and many others, large volumes of food product must be cooked or baked with precision.

The Competing Boundaries of Safety, Quality and Economy
Process engineers constantly face the competing boundaries imposed by safety, product quality, and economy. Safety requires that the all parts of a food product be maintained above a threshold temperature for a specific time period to kill potentially dangerous bacteria. However, if the temperature is raised too high or the time period is excessive,the product becomes dry and overdone -- an unacceptable product quality. Production economy dictates that the line move rapidly to achieve targeted volumes and that the oven operate at a minimum temperature to reduce fuel expenses. The daily economies of production are tempered by the realization that a single safety violation may have disastrous economic and moral consequences for the entire corporation. Likewise, a brief lapse in product quality may undo years of accomplishment in a competitive marketplace.

Factors Impacting Product Temperatures
Thermal imaging provides the measurement capability to safely and economically achieve a product of high quality. Thermal imaging provides the ability to constantly monitor the temperatures of the product itself. Sophisticated oven and belt controls are valuable, but it is the product temperatures that are most critical. Product temperatures may vary significantly due to such parameters as:
1) oven temperature;
2) belt speed;
3) product volume;
4) product composition;
5) start-up conditions; and
6) product separation or placement.

A Distribution of Product Temperatures
As they exit an oven, products typically have a range or distribution of temperatures throughout their surface and volume. This distribution of temperatures is influenced by the numerous factors listed above. Those who measure the ¡®temperature¡¯ (singular) of a product with a single thermometer may be surprised to see the temperature variations evident in a thermal image. A thermal image is equivalent to an array of thousands of temperature probes placed over the surface of the product with the resulting data organized in the format of an image. A distribution of temperatures, instead of a single product temperature, is supported by common observations such as cookies with burnt edges and semi-liquid centers. Since safety, quality and economic concerns apply to all parts of the product, it is valuable to measure temperatures throughout the product.

Once the temperature distributions are measured, the process can be managed and optimized. If the distribution of temperatures is too wide, perhaps the belt speed may be reduced slightly to permit all parts of the product to achieve the desired temperature. Conversely, if the distribution is narrow, the belt speed may be increased while still maintaining product safety and quality.

Figure 1. shows a series of thermal images of chocolate chip cookies after they were removed from a common kitchen oven. The upper left image in Figure 1 shows the cookies on a tray. The color bar to the right indicates the temperature (degrees Farenheit) of the image colors. The upper right image shows the product image extracted from the background tray. The lower left image shows a 3D representation of only the cookie temperatures. The lower right graph shows the temperature distributions of only the cookies and not the background. (The analysis and processing were provided by Cardiowave, Inc.)

Figures 2 and 3 shows thermal images of bacon strips at two different times after the strips were removed from a microwave oven. The variations in temperature are evident, as are the cooling effects from Figure 2 to Figure 3.

Strengths of Thermal Imaging for Food Processing Applications
Thermal imaging technology, in its basic form, provides accurate measurements of surface temperatures. This is ideally suited for measuring products such as chips or bacon because of their thin profile. The calibrated images from a radiometric, infrared camera work well without further processing.

For products with substantial thickness, the surface temperatures may be used as an input into a mathematical model describing the thermal properties of the product. With such a model, volumetric thermal properties and statistical analyses may be extended to many additional products. With sufficient post-processing power, these measurements may be made in real-time.

Infrared Image

 

Infrared Image

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Infrared Image

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