Título:	Metallophytic plant species in nickel deposits in Goiás: predictive modeling with random forest.
Autoria:	MIRANDA, Z. de J. G. FELÍCIO, A. S. G. MALAQUIAS, J. V. VILELA, M. de F. ANDRADE, L. R. M. de
Afiliação:	ZENILTON DE JESUS GAYOSO MIRANDA BRASIL, CPAC; ADÂMARA SANTOS GONÇALVES FELÍCIO, UNIVERSIDADE DE SÃO PAULO; JUACI VITORIA MALAQUIAS, CPAC; MARINA DE FATIMA VILELA, CPAC; LEIDE ROVENIA MIRANDA DE ANDRADE, CPAC.
Ano de publicação:	2025
Referência:	In: INTERNATIONAL CONFERENCE ON NATURAL SCIENCES & BIOTECHNOLOGY: KLIMENT'S DAYS, 2025, Sófia. Book of abstracts [...]. Sófia: [s. n.], 2025.
Páginas:	p. 74.
Conteúdo:	The search for new energy sources to replace oil has driven technological change and stimulated the development of low-carbon technologies. However, the scarcity of essential mineral resources required for this transition remains a barrier. In this context, the use of metallophytic plant species has gained relevance for multiple purposes, including phytomining, phytoextraction, and phytoremediation. In Brazil, knowledge about the potential of these species is still incipient. This study applied the Random Forest algorithm to identify a set of plant species that may serve as indicators of environments with nickel (Ni) deposits, based on correlations between environmental variables and the occurrence of species in these areas.
NAL Thesaurus:	Nickel Phytoremediation
Palavras-chave:	Random forest Modelling Phytomining Phytoextraction
Tipo do material:	Resumo em anais e proceedings
Acesso:	openAccess
Aparece nas coleções:	Resumo em anais de congresso (CPAC)