Analytical Validation Studies Research Articles

RAPID HIGH PERFORMANCE LIQUID CHROMATOGRAPHIC DETECTION OF FUROSINE (ε‐N‐2‐FUROYLMETHYL‐L‐LYSINE) IN YOGURT AND CHEESE MARKETED IN TURKEY*

ABSTRACT Furosine (ε‐N‐2‐furoylmethyl‐L‐lysine) content determination in the yogurt and different cheese types (pickled white, kasar, processed, canned tulum, blue‐veined and mozzarella cheeses) marketed in Turkey was performed using ion‐pair reversed‐phase high performance liquid chromatography (RP‐HPLC). Calibration study (R2 = 0.9999), analytical method validation and recovery studies gave satisfactory results. The lowest furosine values were observed in pickled white cheeses (5.35 ± 0.01 to 7.28 ± 0.02 mg/100 g protein). All cheeses except pickled white showed furosine values between 182.16 ± 0.12 (canned tulum) and 261.32 ± 0.10 mg/100 g protein (ripened kasar). The highest content of furosine was observed in whole yogurt (316.47 ± 0.17 mg/100 g protein) which could be because of severe heat treatment and the addition of milk powder during the manufacturing process. The method provides a rapid, reproducible and accurate determination of this Amadori compound (ε‐deoxy‐fructosyl‐lysine) in yogurt and cheese samples.

Using validation data for ISO measurement uncertainty estimationPart 1. Principles of an approach using cause and effect analysis

A strategy for reconciling the information requirements of formal measurement uncertainty estimation principles with data generated from classical analytical method validation studies is described in detail. The approach involves a detailed analysis of influence factors on the analytical results, employing cause and effect analysis, followed by a formal reconciliation stage. The methodology is shown to be consistent with the principles outlined in the ISO Guide to the Expression of Uncertainty in Measurement (GUM), given representative data. Any relevant data may be used, including those obtained from classical validation studies. The relationship between classical validation studies and ISO GUM uncertainty estimation is discussed briefly; it is concluded that the two methodologies are equivalent, subject to additional allowance for terms held constant during validation experiments.