The amount of microplastics (MPs) present in marine ecosystems are a growing concern, with potential impacts on human health because they are associated with an increase in the ecotoxicity of certain foods, such as fish. As a result, there has been a growing interest in developing effective methods for the analysis of MPs in marine waters. Traditional methods for MP analysis involve visual inspection and manual sorting, which can be time-consuming and subject to human error. However, novel methods have been developed that offer more efficient and accurate analyses. One such method is based on spectroscopy, such as Fourier transform infrared spectroscopy (FTIR). Another method involves the use of fluorescent dyes, which can selectively bind to microplastics and allow for their detection under UV light. Additionally, machine learning approaches have been developed to analyze large volumes of water samples for MP detection and classification. These methods involve the use of specialized algorithms that can identify and classify MPs based on their size, shape, and texture. Overall, these novel methods offer more efficient and accurate analyses of MPs in marine waters, which is essential for understanding the extent and impacts of MP pollution and for developing effective mitigation strategies. However, there is still a need for continued research and development to optimize these methods and improve their sensitivity and accuracy.

Strawberries (Fragaria x ananassa Duch. cv. ‘Albion’) were harvested at two stages of ripeness (75% vs. 100%) and their physicochemical, sensory, toxicological, and bioactive properties were evaluated before and after processing into juice. The fresh fruits and their by-products were also evaluated. During processing into juice, the color change was higher in the fully ripe fruits, confirming the encouraging prospects for using the less ripe strawberries for processing. The analysis of heavy metals (Cu, Zn, Ni, As, Cd, Pb) was carried out, and in juice and by-product samples of 100% maturity, only Pb was higher than the MDK. Of the 566 pesticides analyzed, only cyprodinil was found in the by-products of the strawberries at 75% maturity, while pyrimethanil was detected in all samples. Fresh strawberries of both ripeness levels were rated similarly to the corresponding juices for all sensory attributes studied, indicating that sensory perception was not affected by processing. However, ripeness was found to be an important factor influencing most sensory attributes. The by-products were the materials with the highest levels of all bioactive compounds. Considering all quality parameters evaluated, the chemometric evaluation confirms the suitability of 75% ripe strawberries for processing into functional juice, which could be important for the juice industry.

The beneficial health effects of cheese as a source of bioactive compounds with antioxidant, antimicrobial, anti-inflammatory, immunomodulatory, and analgesic effects are well known. The aim of this study is to determine the presence of pesticide residues and heavy metals in 79 cheese samples from small farms in Croatia. The samples were analyzed over a period of three years for the quality parameters of fat, protein, dry matter, salt, and pH to determine whether metrological conditions affect the quality of cheese and to test the correlation between the variables in different types of cheese. A total of 509 pesticide residues were analyzed using liquid and gas chromatography with tandem mass spectrometry. Piperonyl butoxide was found in two samples. Inductively coupled plasma with mass spectrometry was used for a metal content analysis, and Cd, Cr, Mn, Ni, and Pb were found in the range of <0.005–0.012 mg kg⁻¹, <0.02–0.84 mg kg⁻¹, 0.031–1.128 mg kg⁻¹, <0.03–0.67 mg kg⁻¹, and <0.01–0.12 mg kg⁻¹, respectively. Cd was detected in just three samples. Mn was found in all analyzed samples. All tested samples complied with EU regulations and directives, and at the point of analysis, none posed a direct health risk for consumers. Sustainability on small farms could be ensured with the responsible use of pesticides and through a consistent and reliable supply of fresh, high-quality milk.

The strawberry (genus Fragaria) is a plant from the rose family (Rosaceae). As the fruits are likely to be picked mechanically, they are grown close to consumption centers. The aim of this work was to develop a suitable method for detecting as many molecules as possible in order to be able to distinguish between different strawberry cultivars and geographical origins in the future. Whole strawberries of the “Albion” cultivar, grown in the Jagodica Purgerica region of Zagreb, were used. Gas chromatography-mass spectrometry (GC-MS) in SCAN mode was used to analyze the aroma profile and to determine the proportion of individual components. The samples were prepared and analyzed using the solid-phase microextraction method (SPME). The impact of SPME fiber selection and GC column type was investigated, as well as sample weight, ionic strength, agitation temperature, and sampling time. A higher ionic strength was achieved by adding a 20% NaCl solution to the sample. The aroma profile of the studied strawberry cultivar consisted of furanone, esters, aldehydes, and carboxylic acids. Optimal results were achieved by adjusting the ionic strength during 15 min of extraction and incubation. The individual compounds were identified using NIST, Wiley libraries, and the “area normalization” method.