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This work addresses the production of biopesticides based on natural endophytic bacteria isolated from Quercus suber L. Artificial neural networks were used to maximize the percentage of inhibition triggered by the antifungal activity of bioactive compounds produced by Bacillus amyloliquefaciens. The active compounds, produced in liquid cultures, inhibited the growth of 15 fungi and exhibited a broader spectrum of antifungal activity against surface contaminant fungi, blue stain fungi, and phytopathogenic fungi. A 19-7-6-1 neural network was selected to predict the percentage of inhibition produced by antifungal bioactive compounds. A good match among the observed and predicted values was obtained with the R<jats:sup>2<\/jats:sup>values varying between 0.9965\u20130.9971 and 0.9974\u20130.9989 for training and test sets. The 19-7-6-1 neural network was used to establish the dilution rates that maximize the production of antifungal bioactive compounds, namely, 0.25 h<jats:sup>\u22121<\/jats:sup>for surface contaminant fungi, 0.45 h<jats:sup>\u22121<\/jats:sup>for blue stain fungi, and between 0.30 and 0.40 h<jats:sup>\u22121<\/jats:sup>for phytopathogenic fungi. Artificial neural networks show great potential in the modelling and optimization of these bioprocesses.<\/jats:p>","DOI":"10.1139\/cjfr-2013-0142","type":"journal-article","created":{"date-parts":[[2013,8,13]],"date-time":"2013-08-13T21:42:22Z","timestamp":1376430142000},"page":"985-992","source":"Crossref","is-referenced-by-count":10,"title":["Prediction of bioactive compound activity against wood contaminant fungi using artificial neural networks"],"prefix":"10.1139","volume":"43","author":[{"given":"Henrique","family":"Vicente","sequence":"first","affiliation":[{"name":"Departamento de Qu\u00edmica e Centro de Qu\u00edmica de \u00c9vora, Escola de Ci\u00eancias e Tecnologia, Universidade de \u00c9vora, Rua Rom\u00e3o Ramalho, 59, 7000-671 \u00c9vora, Portugal."}]},{"given":"Jos\u00e9 C.","family":"Roseiro","sequence":"additional","affiliation":[{"name":"Unidade de Bioenergia, Laborat\u00f3rio Nacional de Energia e Geologia, Estrada do Pa\u00e7o do Lumiar, 22, 1649-038 Lisboa, Portugal."}]},{"given":"Jos\u00e9 M.","family":"Arteiro","sequence":"additional","affiliation":[{"name":"Departamento de Qu\u00edmica e Centro de Qu\u00edmica de \u00c9vora, Escola de Ci\u00eancias e Tecnologia, Universidade de \u00c9vora, Rua Rom\u00e3o Ramalho, 59, 7000-671 \u00c9vora, Portugal."}]},{"given":"Jos\u00e9","family":"Neves","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica, Escola de Engenharia, Universidade do Minho, Campus de Gualtar, 4710-057 Braga, Portugal."}]},{"given":"A. 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