Qualitative Detection of Fungal Contamination in Paprika Powder

Effect of storage on bioactivity of an Algerian spice "paprika": optimization of phenolic extraction and study of antioxidant and antibacterial activities

The effect of different storage methods (ambient temperature (A), refrigeration at 4 °C (R) and freezing at - 18 °C (F)), on the phytochemistry of an Algerian spice (paprika powder), was assessed. The optimized extract was obtained under the optimum conditions of ultrasound-assisted extraction (UAE) using response surface methodology (RSM) coupled with a Box-Behnken Design (BBD). This extract was evaluated for its total phenolics content (TPC), total flavonoids content (TFC) and its antioxidant and antibacterial activities. Under the optimum conditions (5 min for the irradiation time, 40% for the amplitude, 80% for ethanol concentration and 50% for solid-liquid ratio) the TPC was 12.23 ± 1.01 mg Gallic Acid Equivalent/gram of Dried Powder (mg GAE/g DP) which is very close with experimental assay. The TPC are better preserved at A whereas TFC and the antioxidant activity at F, and the antibacterial activity depend on the storage methods and the strains tested.

Rapid identification of polypeptide from carbapenem-resistant and susceptible Escherichia coli via Orbitrap-MS and pattern recognition analyses

A rapid and accurate analytical method was established to identify CREC and CSEC. Orbitrap-MS was used to detect the polypeptide of CREC and CSEC strains, and MS data were analyzed by pattern recognition analyses such as hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). HCA based on the farthest distance method could well distinguish the two types of E. coli, and the cophenetic correlation coefficient of the farthest distance method was 0.901. Comparing the results of PCA, PLS-DA, and OPLS-DA, OPLS-DA exhibited the highest accuracy in predicting the CREC and CSEC strains. A total of 26 compounds were identified, and six of the compounds were the highly significant difference between the two types of strains. MS combined with pattern recognition can achieve a more comprehensive and efficient statistical analysis of complex biological samples.

Preparative and capillary isoelectric focusing for detection and identification of Aspergillus conidia in complex sample matrices

This study describes a new method for fast identification of highly hydrophobic conidia of Aspergillus species from both simple and complex matrices. The method is based on recently developed preparative isoelectric focusing in a cellulose-based separation medium which had to be modified with respect to the highly hydrophobic surface of the conidia. Although Aspergillus conidia are colored, their zones in the cellulose bed were indicated by colored isoelectric point markers. The isoelectric point values of Aspergillus conidia were determined by capillary isoelectric focusing. Preparative isoelectric focusing was successfully used for preconcentration of individual conidia of cultivated strains of Aspergillus niger, Aspergillus fumigatus, Aspergillus flavus, and Aspergillus parasiticus, and also for separation of the conidia in a mixture. Subsequently, red pepper powder and peanuts spiked with Aspergillus niger and Aspergillus flavus conidia, respectively, were used as complex matrices. The detection limit for identification of the conidia in these complex matrices is 10⁴ conidia mL^-1 . The presence of conidia in the focused zones was confirmed by their subsequent analysis by capillary isoelectric focusing. Their viability was confirmed by a cultivation of the conidia extracted from the collected fractions after preparative isoelectric focusing.