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.

Autor: Oveisi M; Department of Agronomy and Plant Breeding, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran., Sikuljak D; Institute for Plant Protection and Environment, Belgrade, Serbia., Anđelković AA; Institute for Plant Protection and Environment, Belgrade, Serbia., Bozic D; Faculty of Agriculture, University of Belgrade, Belgrade, Serbia., Trkulja N; Institute for Plant Protection and Environment, Belgrade, Serbia., Piri R; Department of Agronomy and Plant Breeding, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran., Poczai P; Botany and Mycology Unit, Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland. peter.poczai@helsinki.fi., Vrbnicanin S; Faculty of Agriculture, University of Belgrade, Belgrade, Serbia. sava@agrif.bg.ac.rs.
Jazyk: angličtina
Zdroj: BMC plant biology [BMC Plant Biol] 2024 Jun 12; Vol. 24 (1), pp. 537. Date of Electronic Publication: 2024 Jun 12.
DOI: 10.1186/s12870-024-05266-3
Abstrakt: 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).)
Databáze: MEDLINE
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