Toward identification of the risk group of food products: Chemometric assessment of heavy metals content in confectionery products

Cadmium, lead, mercury, and arsenic in fresh fruits and fruit products intended for human consumption in the Republic of Serbia, 2015-2017

The European Commission has established legislation for toxic metals in certain foodstuffs in order to protect public health already in 1993. After several amendments, new maximum levels for cadmium and lead in certain foods were set as per 30 and 31 August 2021 for lead and cadmium, respectively. The new Serbian Regulation on "maximum levels of certain contaminants in food" is fully harmonised with this European legislation. The concentrations of cadmium (Cd), lead (Pb), mercury (Hg), and arsenic (As) were determined in 832 samples of 39 species of fruits and processed fruits, collected during the period January 2015 to December 2017. Fruits and fruit products originated from 45 countries, including Serbia. Samples were analysed by inductively coupled plasma - optical emission spectrometry (ICP-OES). Concentrations of cadmium, lead, mercury, and arsenic in fruits and fruit products were compared to these maximum levels (MLs). Overall, measurable Cd, Pb, Hg, and As were found in 377 samples (45.3%). According to the former regulations, the maximum levels of Cd and Pb for analysed fruits and fruit products were exceeded in only 10 samples (1.20%; n = 832): Cd in 6 and Pb in 4 samples, but according to the latest regulations, the maximum levels of Cd and Pb for fruits were exceeded in 196 of the samples (23.9%; n = 820): Cd in 191 and Pb in 5 samples. The increase of ML exceedances shows that attention needs to be paid for compliance of food to the recent MLs for these metals.

From Sweet Corn By-Products to Carotenoid-Rich Encapsulates for Food Applications

In the present study, carotenoids were recovered from processing sweet corn by-products (SCB). The total carotenoid content determined in the SCB extract was 1.19 mg/100 g DW, and the principal carotenoids identified by the HPLC technique were zeaxanthin, β-cryptoxanthin and lutein. Freeze- and spray-drying techniques were applied for the encapsulation of SCB extract; for this purpose, four different wall materials were used: two proteins (soy and pea) and two carbohydrates (maltodextrin and inulin). The physicochemical characteristics of eight encapsulates were determined to assess their stability. The obtained results indicate that, by using the freeze-drying method, better water activity, moisture content as well as encapsulation efficiency were achieved. Spray-drying resulted in better flowing properties. All obtained encapsulates were microbiologically safe for food applications due to the fact that the obtained results are in agreement with the requirements for consumer safety, i.e., for further food applications and scale-up processes. Chemometric classification and ranking techniques were applied to observe potential grouping among the investigated encapsulates and to select the most favorable encapsulates regarding the used wall materials and encapsulation techniques for the assessment of sustainability in food products. The most suitable wall material and encapsulation technique for the assessment of sustainability in food products was produced by freeze-drying pea protein as a wall material (FDP).

Chemical and Biological Properties of Peach Pomace Encapsulates: Chemometric Modeling

Background: Bioactive compounds need to resist food processing, be released from the food matrix, and be bioaccessible in the gastrointestinal tract in order to provide health benefits. Bioactive compounds isolated from peach pomace (PP) were encapsulated using four different wall materials to improve their stability and to evaluate the effects of in vitro gastrointestinal digestion, as well as chemometric modeling among obtained encapsulates. Methods: Phenolics and carotenoids content, antioxidant, antihyperglycemic, anti-inflammatory, and cell growth activities were evaluated after gastric and intestinal digestion steps. Chemometrics classification analysis–principal component analysis and hierarchical cluster analysis revealed grouping among encapsulates. Results: The encapsulation of PP bioactive compounds showed a protective effect against pH changes and enzymatic activities along digestion, and thereby contributed to an increase in their bioaccessibility in gastric and intestinal fluids. Conclusions: The obtained results suggest protein and polysaccharide carriers and the freeze-drying technique, as an efficient method for the encapsulation of bioactives from PP, could find use in the food and pharmaceutical industry.

Prediction of mechanical extraction oil yield of new sunflower hybrids: artificial neural network model

BACKGROUND

Sunflower seeds are in the top five most abundant oilseeds in the world, as well as sunflower oil in the edible oils group. Recently, increasing attention has been paid to cold-pressed sunflower oil because less processing is involved and no solvent is used. The present study was carried out to investigate dimensions (length, width, thickness), firmness, general (moisture content and hull content, mass of 1000 seeds), gravimetric (true and bulk density, porosity) and geometric characteristics (equivalent diameter, surface area, seed volume, sphericity) of 20 new sunflower hybrid seeds. Steps to determine most of these parameters are quite simple and easy since the process does not require long time or special equipment.

RESULTS

Principal component analysis and cluster analysis confirmed differences in the mentioned characteristics between oily and confectionary sunflower hybrid seeds. One of the major differences between two groups of samples was in extraction oil yield. Mechanical extraction oil yield of the oily hybrid seeds was significantly (P ˂ 0.05) higher (from 68.72 ± 4.21% to 75.61 ± 1.99%) compared to confectionary hybrids (from 20.10 ± 2.82% to 39.91 ± 6.23%). Extraction oil yield values are known only after oil extraction.

CONCLUSION

Knowledge of the extraction oil yield value before the mechanical extraction enables better management of the process. By application of the artificial neural network approach, an optimal neural network model was developed. The developed model showed a good generalization capability to predict the mechanical extraction oil yield of new sunflower hybrids based on the experimental data, which was a main goal of this paper. © 2021 Society of Chemical Industry.