Application of artificial neural networks to analyze the emergence of soybean seeds after applying herbal treatments
Journal Title: Journal of Research and Applications in Agricultural Engineering (ISSN 1642-686X) - Year 2018, Vol 63, Issue 4
Abstract
The aim of the following work is to indicate factors which significantly affect the emergence of selected soybean varieties after application of natural herbal extracts based on - Levisticum officinale L., Ribes nigrum L., Matricaria chamomilla L., as wet seed treatments using two methods of treatment. The research material included seeds treated for 24 hours in macerats, decoctions and infusions made from the above herb species as well as untreated seeds, seeded together with preparations in point application. Untreated seeds were used as the control group. The experiment was being conducted for 16 days in a greenhouse facility belonging to the COBORU Experimental Station for Variety Testing in Karzniczka. The assessed parameter referred to the percentage of soybean seedlings emergence ability determined based on the number of emerged plants. Indication of the importance of factors in shaping soybean emergence and considering their rank was possible due to the sensitivity analysis of the generated neural network with the MLP architecture 4:4-13-5-1:1 with two hidden layers. All analyzed factors of the experiment significantly shaped the ability of soybean emergence, with the following order: cultivar, application method, herb species from which the extract was made, form of preparation.
Authors and Affiliations
Gniewko Niedbała, Magdalena Piekutowska, Janina Rudowicz-Nawrocka, Mariusz Adamski, Tomasz Wojciechowski, Marcin Herkowiak, Agnieszka Szparaga, Aneta Czechowska-Kosacka
Keywords
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