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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., (© 2024. The Author(s).)

Oat is an important crop in Nordic countries both for feed and human consumption. Maintaining a high level of genetic diversity is essential for both breeding and agronomy. A panel of 94 oat accessions was used in this study, including 24 museum accessions over 100- to 120-year old and 70 genebank accessions from mainly Nordic countries and Germany, covering different breeding periods. Sixty-one polymorphic SSR, 201 AFLP and 1056 DArT markers were used to evaluate the past and present genetic diversity of the Nordic gene pool. Norwegian accessions showed the highest diversity, followed by Swedish and Finnish, with German accessions the least diverse. In addition, the Nordic accessions appeared to be highly interrelated and distinct from the German, reflecting a frequent germplasm exchange and interbreeding among Nordic countries. A significant loss of diversity happened at the transition from landraces and old cultivars to modern cultivars. Modern oat originated from only a segment of the landraces and left the remainder, especially black oat, unused. However, no significant overall diversity reduction was found during modern breeding periods, although fluctuation of diversity indices was observed. The narrow genetic basis of the modern Nordic gene pool calls for increasing genetic diversity through cultivar introduction and prebreeding based on neglected sources like the Nordic black oat.