No abstract

A sequential strategy was proposed to detect adulterants in milk using a mid-infrared spectroscopy and soft independent modelling of class analogy technique. Models were set with low target levels of adulterations including formaldehyde (0.074g.L), hydrogen peroxide (21.0g.L), bicarbonate (4.0g.L), carbonate (4.0g.L), chloride (5.0g.L), citrate (6.5g.L), hydroxide (4.0g.L), hypochlorite (0.2g.L), starch (5.0g.L), sucrose (5.4g.L) and water (150g.L). In the first step, a one-class model was developed with unadulterated samples, providing 93.1% sensitivity. Four poorly assigned adulterants were discarded for the following step (multi-class modelling). Then, in the second step, a multi-class model, which considered unadulterated and formaldehyde-, hydrogen peroxide-, citrate-, hydroxide- and starch-adulterated samples was implemented, providing 82% correct classifications, 17% inconclusive classifications and 1% misclassifications. The proposed strategy was considered efficient as a screening approach since it would reduce the number of samples subjected to confirmatory analysis, time, costs and errors.

Simple modifications in classical methods for detection of milk adulteration were validated with significant performance improvement.

No abstract

Neutralization with alkaline compounds is one of the most common adulterations in milk. The rosolic acid method is a classical test widely used in different countries for detection of neutralizers in milk. The official and a modified version were validated in a single laboratory validation process considering four adulterants: sodium bicarbonate(BI), sodium carbonate(CA), sodium hydroxide(HY) and sodium citrate(CI). The modified version, which presented better performance was selected for interlaboratory validation. In this process, samples of raw milk with acidities of 0.19% were neutralized with different concentrations of BI, CA, HY and C and tested for homogeneity and stability. Eight laboratories, which represented different sectors of the milk production chain, received and analysed these samples. The collaborative trial results confirmed the method performance, although sensitivity and precision were inferior to those obtained in the intralaboratory process, demonstrating its applications and limitations

No abstract

Food safety is recognized as a main requirement for consumers, food industries, and official laboratories. Here, we present the optimization and screening qualitative validation of two multianalyte methods in bovine muscle tissues by ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry with an Orbitrap-type analyzer, operated with a heated ionization source in positive and negative mode. This aims for not only the simultaneous detection of veterinary drugs regulated in Brazil but also the prospection of antimicrobials not yet monitored. Two different sample preparation procedures were applied: method A—generic solid-liquid extraction with 0.1% formic acid (v/v) in an aqueous solution of EDTA 0.1% (w/v)—acetonitrile-methanol (1:1:1, v/v/v), followed by an additional ultrasound-assisted extraction and method B—QuEChERS. In both procedures, selectivity showed satisfactory conformity. From a detection capability (CCβ) equivalent to ½ the maximum residue limit, >34% of the analyte resulted in a false positive rate of <5%, preponderant by the QuEChERS method, which exhibited a higher yield of the sample. The results showed the potential application of both procedures in the routine analysis of foods by official laboratories, enabling the expansion of this methodological portfolio as well as its analytical scopes, thus optimizing the control of residues of veterinary drugs in the country.