Potato tubers naturally contain a number of defense substances, some of which are of major concern for food safety. Among these substances are the glycoalkaloids and calystegines. We have here analyzed levels of glycoalkaloids (α-chaconine and α-solanine) and calystegines (A₃, B₂, and B₄) in potato tubers subjected to mechanical wounding, light exposure, or elevated temperature: stress treatments that are known or anticipated to induce glycoalkaloid levels. Basal glycoalkaloid levels in tubers varied between potato cultivars. Wounding and light exposure, but not heat, increased tuber glycoalkaloid levels, and the relative response differed among the cultivars. Also, calystegine levels varied between cultivars, with calystegine B4 showing the most marked variation. However, the total calystegine level was not affected by wounding or light exposure. The results demonstrate a strong variation among potato cultivars with regard to postharvest glycoalkaloid increases, and they suggest that the biosynthesis of glycoalkaloids and calystegines occurs independently of each other.

The rapidly growing demand for organic food requires the availability of analytical tools enabling their authentication. Recently, metabolomic fingerprinting/profiling has been demonstrated as a challenging option for a comprehensive characterisation of small molecules occurring in plants, since their pattern may reflect the impact of various external factors. In a two-year pilot study, concerned with the classification of organic versus conventional crops, ambient mass spectrometry consisting of a direct analysis in real time (DART) ion source and a time-of-flight mass spectrometer (TOFMS) was employed. This novel methodology was tested on 40 tomato and 24 pepper samples grown under specified conditions. To calculate statistical models, the obtained data (mass spectra) were processed by the principal component analysis (PCA) followed by linear discriminant analysis (LDA). The results from the positive ionisation mode enabled better differentiation between organic and conventional samples than the results from the negative mode. In this case, the recognition ability obtained by LDA was 97.5% for tomato and 100% for pepper samples and the prediction abilities were above 80% for both sample sets. The results suggest that the year of production had stronger influence on the metabolomic fingerprints compared with the type of farming (organic versus conventional). In any case, DART-TOFMS is a promising tool for rapid screening of samples. Establishing comprehensive (multi-sample) long-term databases may further help to improve the quality of statistical classification models.

Within this study, a new method enabling monitoring of various estrogenic substances potentially occurring in milk and dairy products was proposed. Groups of compounds fairly differing in physico-chemical properties and biological activity were analyzed: four natural estrogens, four synthetic estrogens, five mycoestrogens, and nine phytoestrogens. Since they may pass into milk mainly in glucuronated and sulfated forms, an enzymatic hydrolysis was involved prior to the extraction based on the QuEChERS methodology. For the purification of the organic extract, a dispersive solid-phase extraction (d-SPE) with sorbent C18 was applied. The final analysis was performed by ultra-high-performance liquid chromatography (UHPLC) coupled with triple quadrupole tandem mass spectrometry (MS/MS). Method recovery ranged from 70 to 120% with a relative standard deviation (RSD) value lower than 20% and limits of quantification (LOQs) in the range of 0.02-0.60 μg/L (0.2-6.0 μg/kg dry weight) and 0.02-0.90 μg/kg (0.2-6.0 μg/kg dry weight) for milk and yogurt, respectively. The new procedure was applied for the investigation of estrogenic compounds in 11 milk samples and 13 yogurt samples from a Czech retail market. Mainly phytoestrogens were found in the studied samples. The most abundant compounds were equol and enterolactone representing 40-90% of all estrogens. The total content of phytoestrogens (free and bound) was in the range of 149-3870 μg/kg dry weight. This amount is approximately 20 times higher compared to non-bound estrogens.

This study focused on the detection and quantification of organic micelle-type nanoparticles (NPs) with polysorbate components (polysorbate 20 and polysorbate 80) in their micelle shells that could be used to load biologically active compounds into fruit juice. Several advanced analytical techniques were applied in the stepwise method development strategy used. In the first phase, a system consisting of ultrahigh-performance liquid chromatography employing a size exclusion column coupled with an evaporative light scattering detector (UHPLC-SEC-ELSD) was used for the fractionation of micelle assemblies from other, lower molecular weight sample components. The limit of detection (LoD) of these polysorbate micelles in spiked apple juice was 500 μg mL(-1). After this screening step, mass spectrometric (MS) detection was utilized to confirm the presence of polysorbates in the detected micelles. Two alternative MS techniques were tested: (i) ambient high-resolution mass spectrometry employing a direct analysis in real time ion source coupled with an Orbitrap MS analyzer (DART-Orbitrap MS) enabled fast and simple detection of the polysorbates present in the samples, with a lowest calibration level (LCL) of 1000 μg mL(-1); (ii) ultrahigh-performance reversed-phase liquid chromatography coupled with high-resolution time-of-flight mass spectrometry (UHPLC-HRTOF-MS) provided highly selective and sensitive detection and quantification of polysorbates with an LCL of 0.5 μg mL(-1).

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