Influence of Long-Term Storage on the Caking Properties Determined in Punch Test and Fungal Contamination of Potato Starch and Wheat Flour

The presented results are an attempt to identify the changes taking place during a punch test experiment and the development of fungal impurities of powdered food materials over long-term storage at 75% RH. The potato starch and wheat flour market has a large share of the global production of bulk materials. The growing interest in powdered food materials requires additional production expenditure. This is associated with an increase in storage time of the discussed product and providing it with the appropriate conditions. The samples of potato starch and wheat flour were stored in perforated containers in a climatic chamber at 75% humidity and 21 °C for five months and then samples were measured by a punch test in a Lloyd LRX materials testing machine. The graphs obtained in the potato starch punch test differed significantly from wheat flour. The thickening of potato starch was observed in the form of layers, while potato starch was uniformly thickened throughout the experiment. The conditions of 75% humidity and 21 °C can be described as the beginning of the caking process. In potato starch, linear sections were observed, which changed the length of their storage time and, additionally, was correlated with the appearance of fungal contamination. These results may suggest the influence of fungi on the phenomenon of bulk material caking.

The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods When Using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods

Food allergens present a significant health risk to the human population, so their presence must be monitored and controlled within food production environments. This is especially important for powdered food, which can contain nearly all known food allergens. Manufacturing is experiencing the fourth industrial revolution (Industry 4.0), which is the use of digital technologies, such as sensors, Internet of Things (IoT), artificial intelligence, and cloud computing, to improve the productivity, efficiency, and safety of manufacturing processes. This work studied the potential of small low-cost sensors and machine learning to identify different powdered foods which naturally contain allergens. The research utilised a near-infrared (NIR) sensor and measurements were performed on over 50 different powdered food materials. This work focussed on several measurement and data processing parameters, which must be determined when using these sensors. These included sensor light intensity, height between sensor and food sample, and the most suitable spectra pre-processing method. It was found that the K-nearest neighbour and linear discriminant analysis machine learning methods had the highest classification prediction accuracy for identifying samples containing allergens of all methods studied. The height between the sensor and the sample had a greater effect than the sensor light intensity and the classification models performed much better when the sensor was positioned closer to the sample with the highest light intensity. The spectra pre-processing methods, which had the largest positive impact on the classification prediction accuracy, were the standard normal variate (SNV) and multiplicative scattering correction (MSC) methods. It was found that with the optimal combination of sensor height, light intensity, and spectra pre-processing, a classification prediction accuracy of 100% could be achieved, making the technique suitable for use within production environments.

Improving Sensitivity in Raman Imaging for Thin Layered and Powdered Food Analysis Utilizing a Reflection Mirror

Raman imaging has been proven to be a powerful analytical technique for the characterization and visualization of chemical components in a range of products, particularly in the food and pharmaceutical industries. The conventional backscattering Raman imaging technique for the spatial analysis of a deep layer suffers from the presence of intense fluorescent and Raman signals originating from the surface layer which mask the weaker subsurface signals. Here, we demonstrated the application of a new reflection amplifying method using a background mirror as a sample holder to increase the Raman signals from a deep layer. The approach is conceptually demonstrated on enhancing the Raman signals from the subsurface layer. Results show that when bilayer samples are scanned on a reflection mirror, the average signals increase 1.62 times for the intense band at 476 cm−1 of starch powder, and average increases of 2.04 times (for the band at 672 cm−1) for a subsurface layer of high Raman sensitive melamine powder under a 1 mm thick teflon sheet. The method was then applied successfully to detect noninvasively the presence of small polystyrene pieces buried under a 2 mm thick layer of food powder (a case of powdered food adulteration) which otherwise are inaccessible to conventional backscattering Raman imaging. In addition, the increase in the Raman signal to noise ratio when measuring samples on a mirror is an important feature in many applications where high-throughput imaging is of interest. This concept is also applicable in an analogous manner to other disciplines, such as pharmaceutical where the Raman signals from deeper zones are typically, substantially diluted due to the interference from the surface layer.

Evaluation of Methods for Inoculating Dry Powder Foods with Salmonella enterica, Enterococcus faecium, or Cronobacter sakazakii

ABSTRACT Salmonella and Cronobacter are two bacteria of concern in powdered food ingredients with low water activity, due to their ability to remain viable for long periods of time. There is great interest in studying the survival of these bacteria in powdered foods, but discrepancies have been reported between broth-grown and lawn-grown bacterial cells and their thermal resistance and desiccation tolerance once inoculated onto powdered foods. The purpose of this study was to evaluate three different powdered food inoculation methods, two broth-grown and one lawn-grown. To evaluate these methods on three types of powdered food matrices, Salmonella enterica serovar Typhimurium LT2 (ATCC 700720), Salmonella surrogate Enterococcus faecium (NRRL B-2354), and Cronobacter sakazakii (ATCC 29544) were inoculated onto nonfat dry milk powder, organic soy flour, and all-purpose flour using one of the three previously developed inoculation methods. In the first broth-grown method, labeled broth-grown pelletized inoculation, a bacterial cell pellet was added to powdered foods directly and mixed with a sterile wooden stick. The second broth-grown method, labeled broth-grown spray inoculation, used a chromatography reagent sprayer to spray the bacterial cell suspension onto the powdered foods. The third inoculation method, lawn-grown liquid inoculation, made use of a spot inoculation and a stomacher to incorporate each bacterium into the powdered foods. Results indicated that the method of inoculation of each powder impacted repeatability and bacteria survivability postequilibration (4 to 6 days). Broth-grown spray inoculation, regardless of the powder and bacterium, resulted in the highest log reduction, with an average ∼1-log CFU/g reduction following equilibration. Broth-grown pelletized inoculation resulted in the second-highest log reduction (∼0.79 log CFU/g), and finally, lawn-grown liquid inoculation was the most stable inoculation method of the three, with ∼0.52-log CFU/g reduction. Overall, the results from this inoculation study demonstrate that inoculation methodologies impact the desiccation tolerance and homogeneity of C. sakazakii, E. faecium, and Salmonella Typhimurium LT2.