Development of predictive models using Data Mining techniques to detect borer infestation (Diatraea saccharalis) in sugarcane culture | Zendy

Nádia Vieira Ribeiro | Zendy; Luiz Henrique Antunes Rodrigues | Zendy; Monique Pires Gravina de Oliveira | Zendy; Felipe Ferreira Bocca | Zendy

Open Access

Development of predictive models using Data Mining techniques to detect borer infestation (Diatraea saccharalis) in sugarcane culture

Author(s) -

Nádia Vieira Ribeiro,

Luiz Henrique Antunes Rodrigues,

Monique Pires Gravina de Oliveira,

Felipe Ferreira Bocca

Publication year - 2017

Publication title -

anais do congresso de iniciação científica da unicamp

Language(s) - English

Resource type - Conference proceedings

ISSN - 2447-5114

DOI - 10.19146/pibic-2017-78232

Subject(s) - diatraea saccharalis , infestation , microbiology and biotechnology , biology , botany , pest analysis

Borer infestation (Diatraea saccharalis) is one of the main concerns in the sugarcane crop because it affects productivity directly and negatively. In order to find alternatives that minimize these damages, the objective of this work is to develop predictive models using data mining tools to predict the infestation of the borer in the sugarcane crop.

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