Application of artificial neural networks to classify Avena fatua and Avena sterilis based on seed traits: insights from European Avena populations primarily from the Balkan Region.

BACKGROUND: Avena fatua and A. sterilis are challenging to distinguish due to their strong similarities. However, Artificial Neural Networks (ANN) can effectively extract patterns and identify these species. We measured seed traits of Avena species from 122 locations across the Balkans and from some populations from southern, western, and central Europe (total over 22 000 seeds). The inputs for the ANN model included seed mass, size, color, hairiness, and placement of the awn attachment on the lemma. RESULTS: The ANN model achieved high classification accuracy for A. fatua and A. sterilis (R2 > 0.99, RASE < 0.0003) with no misclassification. Incorporating geographic coordinates as inputs also resulted in successful classification (R2 > 0.99, RASE < 0.000001) with no misclassification. This highlights the significant influence of geographic coordinates on the occurrence of Avena species. The models revealed hidden relationships between morphological traits that are not easily detectable through traditional statistical methods. For example, seed color can be partially predicted by other seed traits combined with geographic coordinates. When comparing the two species, A. fatua predominantly had the lemma attachment point in the upper half, while A. sterilis had it in the lower half. A. sterilis exhibited slightly longer seeds and hairs than A. fatua, while seed hairiness and mass were similar in both species. A. fatua populations primarily had brown, light brown, and black colors, while A. sterilis populations had black, brown, and yellow colors. CONCLUSIONS: Distinguishing A. fatua from A. sterilis based solely on individual characteristics is challenging due to their shared traits and considerable variability of traits within each species. However, it is possible to classify these species by combining multiple seed traits. This approach also has significant potential for exploring relationships among different traits that are typically difficult to assess using conventional methods.

Phenolic Compounds and Bioactivity of Healthy and Infected Grapevine Leaf Extracts from Red Varieties Merlot and Vranac (Vitis vinifera L.).

We investigated the phenolic composition, radical scavenging activity, and antimicrobial activity of grapevine leaf extracts from two red grape varieties, Vranac and Merlot (Vitis vinifera L.). The extracts were prepared from healthy grapevine leaves and those infected by Plasmopara viticola (downy mildew). The phenolic composition of the grapevine leaf extracts was determined using spectrophotometric assays and reverse-phase high performance liquid chromatography (RP-HPLC). The radical scavenging activity of grapevine leaf extracts was determined by the 2,2-diphenyl-1-picrylhydrazyl assay, and their antimicrobial activity was determined by microwell dilution tests. The total phenolic content was higher in healthy grapevine leaf extracts than in infected grapevine leaf extracts. The RP-HPLC analysis detected significant amounts of flavonols, phenolic acids, and flavan-3-ols, and small amounts of stilbenes in the grapevine leaf extracts. Compared with the infected grapevine leaf extracts, the healthy grapevine leaf extracts were richer in flavonols, phenolic acids, and flavan-3-ols, but had lower stilbenes contents. All extracts showed strong free radical scavenging activity, which was strongly correlated with the total phenolic content (R(2) = 0.978). The extracts showed a stronger antimicrobial activity towards Gram-positive bacterial strains than towards Gram-negative bacterial strains and yeast. The phenolic compounds in grapevine leaves were responsible for their strong radical scavenging and antimicrobial activities. Together, these results demonstrate that grapevine leaves have high nutritional value and can be used as a fresh food and to prepare extracts that can be used as additives in food and medicines.

Fitness Costs of Insecure Romantic Attachment: The Role of Reproductive Motivation and Long-Term Mating.

Attachment styles are frequently viewed from within the evolutionary conceptual framework; however, their associations with evolutionary fitness are very rarely empirically explored. In the present research (N = 448), we analyzed the relations between romantic attachment (anxiety and avoidance) and various fitness indicators in Serbian adults: matting patterns (short and long-term mating), reproductive motivation, reproductive success (age of first birth, number of children, and grandchildren), and kin care (care for biological relatives in general and care for children). Congruent negative associations between insecure styles and fitness outcomes were found: this is particularly true for avoidance, which is negatively related to long-term mating, reproductive motivation, number of children, and kin care. Furthermore, the data showed that reproductive motivation and long-term mating may mediate the links between avoidance and the number of children. Anxiety was negatively related to reproductive motivation and the number of children; this attachment style was also negatively associated with care for children, but only in males. The present data suggest that secure romantic bonding may be evolutionary adaptive; the obtained results contradict some evolutionary theories that assume that insecure attachment has some adaptive benefits as well. Findings provide new insights into the role of romantic attachment in the behavioral ecology of pair bonding.