ABSTRACT
Background and Objectives: Potatoes (Solanum tuberosum), as starchy plants, have been highly esteemed for their rich supply of nutrients. Numerous studies have investigated the potential health benefits of potatoes and explored potential solutions. Among these considerations, the discussion regarding microbial contaminants has remained an important topic. Materials and Methods: The present study used cold atmospheric plasma (CAP) to evaluate the microbial quality (including mesophilic and psychrotrophic bacteria and mold and yeasts) of raw potato slices during a 14-day storage period. To achieve this goal, the duration of CAP exposure was set at 5, 10, and 15 min, utilizing an electric voltage of 60 kV and a specific frequency of 20 kHz. Results: The findings revealed the effectiveness of CAP pre-treatment in inhibiting microbial growth over the 14 days when compared to the control sample (untreated sample), with a statistically significant difference (P < 0.05). Moreover, with an extension of the CAP exposure duration to 15 min, there was a significant reduction in the logarithmic count of mesophilic, psychrotrophic microorganisms, molds, and yeasts (4.95, 2.85, and 2.22CFU/g, respectively) in comparison to the control groups (7.5, 5.62, and 5.5CFU/g) on days 0, 7, and 14 of the storage periods (P < 0.05). Conclusion: The results of this study highlight the potential of CAP pre-treatment on reducing the microbial load in raw potato slices prior to frying, which could potentially influence the overall quality of potato-based products.
ABSTRACT
This study investigated the impact of 60 kV Cold Atmospheric Plasma (CAP) pretreatment for varying durations (5, 10, and 15 min) on potato strip characteristics before and after frying, emphasizing oil uptake, acrylamide formation. Potato samples treated with cap showed significantly better physicochemical characteristics. Scanning electron microscopy revealed deformation of cell wall due to CAP treatment. Fourier-transform infrared spectroscopy indicated structural changes, while X-ray diffraction analysis suggested that starch remained amorphous state in CAP-pretreated samples. Post-frying, CAP-treated potato strips exhibited altered oil distribution with reduced absorption, possibly due to microstructural changes. CAP substantially reduced acrylamide formation during frying by degrading asparagine and inactivating amylase. CAP affected strip color, with increased brightness and decreased redness and yellowness after 14 days. Sensory evaluation showed no significant difference, with prolonged CAP-treated strips receiving higher overall acceptability scores. These findings highlight CAP as a non-thermal technology to enhance fried potato product quality and safety.
ABSTRACT
BACKGROUND: The adulteration of milk by hazardous chemicals like surfactants has recently increased. It conceals the quality of the product to gain profit. As milk and milk-based products are consumed by many people, novel analytical procedures are needed to detect these adulterants. This study focused on Fourier-transform infrared (FTIR) spectroscopy equipped with an attenuated total reflection (ATR) accessory, and near-infrared (NIR) spectroscopy for the determination of milk-surfactant adulteration using a genetic algorithm (GA) coupled with multivariate methods. The model surfactant was sodium dodecyl sulfate (SDS), and its concentration varied from 1.94-19.4 gkg-1 in adulterated samples. RESULTS: Prominent peaks in the spectral range of 5500-6400 cm-1 , 1160-1260 cm-1 and 1049-1080 cm-1 may correspond to the sulfonate group in SDS. A genetic algorithm could significantly reduce the number of variables to almost one third by selecting the specific wavenumber region. Principal component analysis (PCA) for ATR and NIR data indicated separate clusters of samples in terms of the concentration level of SDS (P ≤ 0.05). Partial least squares regression (PLSR) was used to determine the maximum R2 value for ATR and NIR data for calibration, cross-validation and prediction, which were 0.980, 0.972, 0.980, and 0.970, 0.937, and 0.956 respectively. The results showed apparent differences between unadulterated and adulterated samples using partial least squares-discriminant analysis (PLS-DA), which was validated by the permutation test. CONCLUSION: The results clearly show the successful application of the proposed methods with multivariate analysis in the selection of variables, classification, clustering, and identification of the adulterant in amounts as low as 1.94 gkg-1 in milk. © 2020 Society of Chemical Industry.
