If you want to know how your food is coming along, sample it. That’s as true in a factory as it is in a kitchen.
Analytical testing is basically a combination of detection, for safety, and measurement, for quality. Detection ensures that everything that’s in a food or beverage is supposed to be there; measurement ensures that it’s there in the right proportions.
A variety of analysis techniques are available, depending on what has to be measured or detected, how fast and how precisely. Options include benchtop or in-line equipment, destructive or non-destructive, wet or dry, light-based or electromagnetic, and many more variations.
One of the most important variables in sample analysis is how fast it has to be done, which usually depends on how often samples have to be taken to comply with a given set of GMPs. Generally speaking, destructive techniques, like loss-on drying or titration with acids or other chemicals, are slow and expensive but highly accurate. Indirect non-destructive techniques, like exposure to infrared light or magnetic pulses, are faster but often not as authoritative.
It’s common to use destructive tests as a preliminary technique to calibrate non-destructive ones, for example to determine a product’s optimal infrared profile. The non-destructive technique, whether benchtop or in-line, then becomes the norm.
Moisture is one of the most frequently tested parameters in food, and it can be measured in a variety of ways. One of the most common preliminary destructive tests for moisture is loss-on drying. A food sample is heated to drive moisture out. The difference between the sample’s weight before and after heating is expressed as a percentage; this is taken as the product’s percentage of moisture.
Loss-on drying has some drawbacks. Heat can make some kinds of food lose other volatile components, like fat, in addition to water. The test is also time-consuming, usually taking at least an hour, and sometimes three or more. Faster equipment is available. Ametek Brookfield markets a rapid loss-on drying system that cuts testing to 10 minutes by continuously weighing the sample and ending the test as soon as the weight loss abates.
Another common preliminary destructive test is the Karl Fischer method, named for the chemist who developed it in the early 1940s. It basically uses chemicals that, when combined, consume water; moisture can be extrapolated from the amount of time this process, called titration, takes when a test sample is introduced. Karl Fischer titration is able to measure moisture with a 1% margin of accuracy. However, it’s relatively expensive and uses toxic chemicals that must be disposed of properly.
Another titration-based test is even older: the Kjeldahl method, developed in the late 19th century by a Danish brewer. It gauges the protein content of products like milk by breaking it down with acids to free its nitrogen. Most of the nitrogen content comes from protein; the amount of liberated nitrogen, measured through titration, indicates the proportion of protein.
Seeing the light
Destructive methods set benchmarks, but everyday analysis usually gets done by fast, non-destructive test methods. These typically expose product, either samples or the main product flow, to a form of energy, like light or electromagnetic pulses. The interplay of this energy with the product indicates the amount of moisture, fat, protein, salt and other substances present.
The most common non-destructive tests involve low-frequency, high-wavelength light. This method, known as spectroscopy, analyzes how such light is altered when it passes through a food sample and/or reflects off its surface. Spectroscopy takes various forms, depending mainly on the light’s wavelength; different wavelengths are suited to different purposes.
One of the most common such methods is near infrared spectroscopy (NIR), which uses light with wavelengths between 800 and 2,500 nanometers. NIR is fast, usually taking less than a minute per sample, and versatile. It’s used in many different foods for a wide variety of parameters.
“While moisture is our major focus, we also supply analyzers for the continuous online measurement of protein, fat/oil, sugar, seasonings, caffeine and other constituents/elements that absorb the NIR beam,” says Adrian Fordham, president of MoistTech.
Doing multiple measurements at one time is a major plus for NIR. “Another NIR advantage for food companies is the ability to measure more than moisture with one instrument,” says John Bogart, managing director of Kett US. “As an example, moisture, fat/oil, protein, ash (as a residual), sugar, fiber, water activity and other components can be simultaneously measured. This substantially reduces capital expenditures and ‘people time’ requirements.”
Another light-based analysis method is Fourier Transform Infrared (FTIR). Its basic difference from NIR is that it uses higher-wavelength light, between 2,500 and 25,000 nanometers. This longer wavelength yields a stronger signal, making FTIR more accurate and specific. However, it also limits its penetrating power, making it best suited to liquids and to samples with less than 20% total solids. NIR’s shorter wavelength enables it to penetrate a sample to a depth of up to 2cm, making it better suited for solid samples.
Accurately finding some components, like fat, sometimes requires a more penetrating analysis technique. One of the most common is nuclear magnetic resonance (NMR), which involves sending electromagnetic pulses through a sample. The pulses excite the protons of the sample’s fat molecules, allowing them to be detected as they “relax.”
A type of NMR known as time-domain (TD-NMR) can be used as a complementary technique to near infrared spectroscopy. TD-NMR is useful for applications where there is a portion of the sample that is liquid and a portion that is a solid, says Dean Roberts, director of market development for applied spectroscopy in North America for Bruker Optics.
CEM Corp. markets the Oracle, an NMR-based analyzer that can determine fat content in 30 seconds without being calibrated through a wet chemical method. The Genesis, which won an innovation award from the Institute of Food Technologists in 2017, can analyze fat content in meats, dairy, powders and processed foods ranging from cheese to noodles.
NMR can look for other substances, like sugars and proteins, that make up a food’s chemical profile. Deviations from this profile are a sign that something is wrong with the food or it’s not what it purports to be. Bruker has a line of NMR analytical equipment that can verify, for example, that juice was actually made from Valencia oranges, or that olive oil is really extra-virgin, or that honey hasn’t been “spiked” with high-fructose corn syrup.
In fact, detecting things in food that shouldn’t be there – whether accidentally or deliberately introduced – is a potentially important function of analytical test equipment. But this capability has been largely underutilized, Roberts says. “I don’t see too many customers actually willing to spend the money, particularly for adulteration, unless they get that as part of an overall analysis package.”
Detection of contaminants can be divided into non-targeted, which looks for anything that doesn’t belong, and targeted, which looks for a specific substance. Spectroscopy, especially NIR, is more suited to non-targeted detection.
Both methods have an advantage over some of the common “wet” chemical methods when it comes to certain adulterants. Urea and melamine, its derivative, have been implicated in scandals involving contaminated ingredients originating in China that have been used in protein-rich products like baby formula and pet food. Because melamine, like protein, is high in nitrogen, it can fool tests like the Kjeldahl that gauge protein by measuring nitrogen content; spectroscopy can distinguish the two.
What’s your line?
Two fundamental aspects of analytical test equipment are where and how often to use it. The basic options are: benchtop, sometimes called at-line, where samples are taken to devices in a lab or other dedicated testing area; on-line, which involves testing on the plant floor, either with a handheld device or by diverting samples systematically into a side stream; and in-line, which means continuous measurement of the actual product stream.
In-line testing is the most accurate option, especially in processes with high fluctuations. It also can be used for automated process control, for example to adjust parameters like temperature or oven dwell time to meet moisture targets. But in-line testing is more expensive than benchtop and often less versatile, able to focus on only one or two parameters.
“Food producers with many products or a smaller budget can benefit from at-line analysis since one benchtop sensor can be configured to measure dozens of products with no additional hardware,” says Bonnie Woods, marketing coordinator for Process Sensors Corp. “Companies looking to automate their process, get real-time data and reduce operator dependency benefit from in-line analysis.”
It comes down to speed versus comprehensiveness, says Naimish Sardesai, business development and segment marketing manager for food, feed and beverages at tec5usa.
“Benchtop analysis is a gold standard, but it can be a slow and expensive process,” Sardesai warns. “The biggest drawback of this technique is that by the time you receive the qualitative results of the products, they may have already been packaged. The users of online spectroscopy may have to give up precision and number of variables of analysis to some extent but [it] boils down to only what is necessary for the process.”
One important consideration for in-line analysis is proper placement of the probes for consistent contact with the product, Roberts says. For instance, a probe in a liquid stream should not be placed near a pump that’s prone to cavitation, because the air bubbles introduced into the stream could interfere with the reading.
Using the right analytical test equipment for the right parameters can go a long way toward ensuring that food is both good-tasting and safe. That’s a test every food processor wants to pass.