Combined Effect of Ultrasound and Low-Heat Treatments on E. coli in Liquid Egg Products and Analysis of the Inducted Structural Alterations by NIR Spectroscopy.

In this study, sonication with mild heat treatment was used to reduce the E. coli count in inoculated liquid whole egg, egg yolk and albumen. Ultrasonic equipment (20/40 kHz, 180/300 W) has been used for 30/60 min with a 55 °C water bath. The combination of sonication and low-heat treatment was able to reduce the concentration of E. coli from 5-log CFU × mL-1 below 10 CFU × mL-1 at 300 W, 40 kHz and 60 min of sonication in liquid egg products. The 60 min treatment was able to reduce the E. coli concentration below 10 CFU × mL-1 in the case of egg yolk regardless of the applied frequency, absorbed power or applied energy dose. The 30 min treatment of sonication and heating was able to reduce significantly the number of E. coli in the egg products, as well. Our results showed that sonication with mild heat treatment can be a useful technique to decrease the number of microorganisms in liquid egg products to a very low level. Near-infrared spectroscopy was used to investigate structural changes in the samples, induced by the combined treatment. Principal component analysis showed that this method can alter the C-H, C-N, -OH and -NH bonds in these egg products.

Revealing the Effect of Heat Treatment on the Spectral Pattern of Unifloral Honeys Using Aquaphotomics.

In this study we aimed to investigate the effect of heat treatment on the spectral pattern of honey using near infrared spectroscopy (NIRS). For the research, sunflower, bastard indigo, and acacia honeys were collected from entrusted beekeepers. The honeys were not subject to any treatment before. Samples were treated at 40 °C, 60 °C, 80 °C, and 100 °C for 60, 120, 180, and 240 min. This resulted in 17 levels, including the untreated control samples. The 5-hydroxymethylfurfural (HMF) content of the honeys was determined using the Winkler method. NIRS spectra were recorded using a handheld instrument. Data analysis was performed using ANOVA for the HMF content and multivariate analysis for the NIRS data. For the latter, PCA, PCA-LDA, and PLSR models were built (using the 1300-1600 nm spectral range) and the wavelengths presenting the greatest change induced by the perturbations of temperature and time intervals were collected systematically, based on the difference spectra and the weights of the models. The most contributing wavelengths were used to visualize the spectral pattern changes on the aquagrams in the specific water matrix coordinates. Our results showed that the heat treatment highly contributed to the formation of free or less bonded water, however, the changes in the spectral pattern highly depended on the crystallization phase and the honey type.

Development of a Novel Acoustic Spectroscopy Method for Detection of Eggshell Cracks.

Non-destructive testing (NDT) for eggshell faults is highly important for the egg industry, as cracked eggs account for around 3% of total production. The most commonly used method at present, candling, is labor intensive, while computer vision systems are expensive and complicated. In this paper, we present a simple, yet efficient, novel method for eggshell crack detection by acoustic spectroscopy. Altogether, 693 sound recordings were evaluated by different classification methods. The results show a cross-validated 2.1% total classification error, with only 0.87% false positive rate, which is the crucial metric for fresh eggs. Adapting the developed method to an industrial setting may lead to a reliable, fast and cost-effective detection method.

Determining Sonication Effect on E. coli in Liquid Egg, Egg Yolk and Albumen and Inspecting Structural Property Changes by Near-Infrared Spectra.

In this study, liquid egg, albumen, and egg yolk were artificially inoculated with E. coli. Ultrasound equipment (20/40 kHz, 180/300 W; 30/45/60 min) with a circulation cooling system was used to lower the colony forming units (CFU) of E. coli samples. Frequency, absorbed power, energy dose, and duration of sonication showed a significant impact on E. coli with 0.5 log CFU/mL in albumen, 0.7 log CFU/mL in yolk and 0.5 log CFU/mL decrease at 40 kHz and 6.9 W absorbed power level. Significant linear correlation (p < 0.001) was observed between the energy dose of sonication and the decrease of E. coli. The results showed that sonication can be a useful tool as a supplementary method to reduce the number of microorganism in egg products. With near-infrared (NIR) spectra analysis we were able to detect the structural changes of the egg samples, due to ultrasonic treatment. Principal component analysis (PCA) showed that sonication can alter C-H, C-N, -OH and N-H bonds in egg. The aquagrams showed that sonication can alter the properties of H2O structure in egg products. The observed data showed that the absorbance of free water (1412 nm), water molecules with one (1440 nm), two (1462 nm), three (1472 nm) and four (1488 nm) hydrogen bonds, water solvation shell (1452 nm) and strongly bonded water (1512 nm) of the egg samples have been changed during ultrasonic treatment.

Color analysis of horticultural produces using hue spectra fingerprinting.

Color has great importance in agriculture due to its relationship with plant pigments and therefore, plant development and biochemical changes. Due to the trichromatic vision, instruments equipped with CCD or CMOS sensor represent color with the mixture of red, green and blue signals. These values are often transformed into HSL (hue, saturation, luminance) color space. Beyond average color of the visible surface area, histograms can represent color distribution. Interpretation of distribution can be challenging due to the information shared among histograms. Hue spectra fingerprinting offers color information suitable for analysis with common chemometric methods and easy to understand. Algorithm is presented with GNU Octave code.•Hue spectra is a histogram of hue angle over the captured scene but summarizes saturation instead of number of pixels. There are peaks of important colors, while others of low saturation disappear. Neutral backgrounds such as white, black or gray, are removed without the need of segmentation.•Color changes of fruits and vegetables are represented by displacement of color peaks. Since saturation is usually changing during ripening, storage and shelf life, peaks also change their shape by means of peak value and width.

Detection and Quantification of Tomato Paste Adulteration Using Conventional and Rapid Analytical Methods.

Tomato, and its concentrate are important food ingredients with outstanding gastronomic and industrial importance due to their unique organoleptic, dietary, and compositional properties. Various forms of food adulteration are often suspected in the different tomato-based products causing major economic and sometimes even health problems for the farmers, food industry and consumers. Near infrared (NIR) spectroscopy and electronic tongue (e-tongue) have been lauded as advanced, high sensitivity techniques for quality control. The aim of the present research was to detect and predict relatively low concentration of adulterants, such as paprika seed and corn starch (0.5, 1, 2, 5, 10%), sucrose and salt (0.5, 1, 2, 5%), in tomato paste using conventional (soluble solid content, consistency) and advanced analytical techniques (NIR spectroscopy, e-tongue). The results obtained with the conventional methods were analyzed with univariate statistics (ANOVA), while the data obtained with advanced analytical methods were analyzed with multivariate methods (Principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares regression (PLSR). The conventional methods were only able to detect adulteration at higher concentrations (5-10%). For NIRS and e-tongue, good accuracies were obtained, even in identifying minimal adulterant concentrations (0.5%). Comparatively, NIR spectroscopy proved to be easier to implement and more accurate during our evaluations, when the adulterant contents were estimated with R2 above 0.96 and root mean square error (RMSE) below 1%.

Factors Influencing the Long-Term Stability of Electronic Tongue and Application of Improved Drift Correction Methods.

Temperature, memory effect, and cross-contamination are suspected to contribute to drift in electronic tongue (e-tongue) sensors, therefore drift corrections are required. This paper aimed to assess the disturbing effects on the sensor signals during measurement with an Alpha Astree e-tongue and to develop drift correction techniques. Apple juice samples were measured at different temperatures. pH change of apple juice samples was measured to assess cross-contamination. Different sequential orders of model solutions and apple juice samples were applied to evaluate the memory effect. Model solutions corresponding to basic tastes and commercial apple juice samples were measured for six consecutive weeks to model drift of the sensor signals. Result showed that temperature, cross-contamination, and memory effect influenced the sensor signals. Three drift correction methods: additive drift correction based on all samples, additive drift correction based on reference samples, and multi sensor linear correction, were developed and compared to the component correction in literature through linear discriminant analysis (LDA). LDA analysis showed all the four methods were effective in reducing sensor drift in long-term measurements but the additive correction relative to the whole sample set gave the best results. The results could be explored for long-term measurements with the e-tongue.