The oil content and fatty acid composition of total lipids (TLs) and main lipid classes (NLs- neutral and PLs- polar lipids) in seeds of two wild Sambucus species (S. nigra and S. ebulus) from Transylvania (Romania) were determined by capillary gas chromatography (GC-MS). In addition, the positional distribution of fatty acids in seed triacylglycerols (TAGs) was determined by hydrolysis with pancreatic lipase. The seeds were found to be rich in fat (22.40–24.90 g/100g) with high amounts of polyunsaturated fatty acids (PUFAs) ranging from 68.96% (S. ebulus) to 75.15% (S. nigra). High ratios of PUFAs/SFAs (saturated fatty acids), ranging from 7.06 (S. nigra) to 7.64 (S. ebulus), and low ratios of n-6/n-3, ranging from 0.84 (S. nigra) to 1.51 (S. ebulus), were determined in both oils. The lipid classes/subclasses analyzed (PLs, MAGs—monoacylglycerols, DAGs—diacylglycerols, FFAs—free fatty acids, TAGs and SEs—sterol esters) were separated and identified using thin-layer chromatography. The fatty acid compositions of the TAG fractions were practically identical to the profiles of TLs, with the same dominating fatty acids in both analyzed species. SEs and FFAs, were characterized by high proportions of SFAs. The sn-2 position of TAGs was esterified predominantly with linoleic acid (43.56% for S. nigra and 50.41% for S. ebulus).

The overall yield and sugar content of sugar beet (Beta vulgaris L.) were determined by the genotype and its interaction with the environment. This study aimed to analyze the interaction of 23 genotypes with different environmental conditions during two growing seasons. To estimate the variance of genotypes, environment, and genotype function of the environment, the R 3.5.1 software package was used. In addition, the multivariate stability method was used to explain the G (genotype) × E (environment) interaction based on the GGE (Genotype plus Genotype-by-Environment) and AMMI (additive main effects and multiplicative interaction) biplots. The AMMI ASV (AMMI stability value) and biplot analysis revealed that only two genotypes (G10 and G11) showed higher values for yield and sugar content and production compared to the other genotypes. The AMMI ASV analysis also showed that the environment significantly influenced the sugar beet yield, sugar content, and sugar production, which were the descriptors for production in this study.

Danube Delta (DD), an ecologically vulnerable site, together with fish populations, which are significant food resources, are largely exposed to heavy metal contamination. This study was developed in the Babina–Cernovca sector of DD in September 2023. Zinc (Zn), and iron (Fe) were identified in water, while copper (Cu), iron (Fe), and manganese (Mn) were in sediments (mud). Proximate composition of the muscle tissues of eight fish species identified in the area was assessed. The muscle was also tested to identify heavy metals contamination. The contamination degree was assessed using bioaccumulation and bioconcentrations factors. The relation between nutritional parameters and metals was tested using bivariate and multivariate analyses. Samples were analyzed by specific laboratory tests, and data were processed using ANOVA, Spearman correlation, Principal Component Analysis (PCA), and hierarchical clustering. S. erythrophthalmus, C. gibelio, and A. alburnus have the highest metal bioaccumulation capacity, exhibiting species-specific accumulation patterns. PCA and clustering analysis reflect the influence of species and environmental factors on heavy metal accumulation in fish tissue. The study integrates the heavy metals content with nutritional parameters in fish muscular tissue, using bivariate and multivariate analysis for assessing fish vulnerability to heavy metals exposure in the Danube River.