In today’s time, consumers are highly quality oriented. Specifically for honey, which is extracted from the natural resources like honeycombs of beehive, buckwheat, etc., and chances of bacteria and fungi growth in honey are pretty high. Honey may also contain reclining endospores of bacteria that can transmute into a toxin-producing bacteria, leading to severe illness and in some cases, even death. Therefore, safety, nutritional value, functionality, and aesthetics like color, texture, flavor, and appearance of honey carries high priority standards for us before its consumption. Hence, it duty bounds the Quality Assurance teams to monitor the quality and standard of honey well before they extend its reach to the consumers.
In the market, variant options are available that cater the need of testing the honey quality. But EST Inc.’s zNose® is a highly advanced technology that uses the chromatogram approach as well as the spectral approach to carry out rapid aroma profiling of honey. Two experiments were carried out for at-line flavor quality control and off-flavor assessment. Sugar solutions were included in the tests because of their resemblance with honey and as they are often mentioned as mimics for honey in adulteration practices.
In experiment 1, the samples of three different honey varieties, buckwheat, clover, and orange blossom were used, and ten independent samples were analyzed for each honey variety and sugar solution. In experiment 2, samples of six different honey varieties, buckwheat, clover, orange blossom, black locust, mint, and carrot, from different geographical origin, were compared to the honeys used in the first experiment. Also, ten independent samples per honey variety and sugar solution were measured.
As the zNose® is a combination of a sensor based detection and a regular GC analysis, the data resulting from the zNose® measurements were thus approached in two different ways:
With the chromatogram approach, PCA analysis on the total dataset of all relative peak areas of three honey types (buckwheat, clover, and orange blossom) and two sugar solutions (beet invert and cane invert) resulted in a separation between all products with PC1 and PC2 explaining 90% of the total variance.
In the spectral approach, both the negative and positive values in first derivative plots of all honey samples and sugar solutions were included in the PCA analysis, which initially, did not lead to a good separation. Only the aroma fingerprint of buckwheat appeared distinct enough to be separated from the rest in a PCA plot with PC1 and PC2 explaining 80% of the total variance.
In the chromatogram approach, the twelve most abundant honey volatiles were selected and used directly as explanatory variables in the discriminant analysis. This model showed a good classification performance. All but one of the sixteen external validation samples were classified from the carrot honey in the group of the clover honey.
In case of the corrected spectral data, it was not possible to use the full spectra directly to perform the discriminant analysis as the number of variables exceeded the number of observations and resulted in an overfit. Data reduction techniques like principal components or canonical variable analysis were applied and visually discriminated all honey samples and sugar solutions. Results obtained indicated that the validation measurements coincide with the corresponding calibration measurements, except for one carrot honey validation observation, which is classified among the clover honey observations. Thus, it corresponds to a 94% correctly classified external validation samples.
Therefore, EST Inc.’s zNose® is capable of discriminating not only the aroma of the different honey varieties but also, adulterant sugars from pure honey samples. Hence, proves to be a fast aroma fingerprinting technique that carries the aroma profiling of honey within a minute with speed, accuracy and precision. As the quality of food products carries high priority standards for the consumers, zNose® comes out to be the one-stop solution for the Quality Assurance teams to check the quality and standard of honey well, before it reaches consumers.
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