Microorganisms bioprospection and evaluation of their bioremediation potential in soils contaminated with indaziflam

• Grant number: 24/10738-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2024
• End date: November 30, 2025
• Field of knowledge: Biological Sciences - Microbiology - Applied Microbiology
• Principal Investigator: Paulo Renato Matos Lopes
• Grantee: Stefani Gabrieli Dias de Freitas
• Host Institution: Faculdade de Ciências Agrárias e Tecnológicas. Universidade Estadual Paulista (UNESP). Campus de Dracena. Dracena , SP, Brazil

Abstract

The presence of weeds represents one of the biggest losses in sugarcane cultivation and indaziflam is among the herbicides most used for their control. However, its molecule has a high potential for environmental impact due to its long persistence in the soil and high toxicity. Therefore, techniques to reduce the concentration of this herbicide and its potential environmental damage in soil is necessary. Thus, this proposal aims to bioprospect soil microorganisms and evaluate their efficiency in indaziflam biodegradation. Hence, soil samples will be collected in two different areas: (1) in sugarcane crops with a history of indaziflam application, and (2) in native forest without the presence of pesticides. The bioprospection process and the biodegradation evaluation of microbial isolates will use specific culture media and isolation techniques in classical protocols to identify and select the most efficient microorganisms in the herbicide metabolism. Microbial activity will be evaluated qualitatively (photographic records) and quantitatively (spectrophotometry) by colorimetric tests using the redox indicator 2,6-dichlorophenol-indophenol. Furthermore, a stage abroad is planned to perform molecular analyzes of isolated microorganisms with better results in the biodegradation of the indaziflam molecule. Statistical analyzes will be carried out using routines in the free software R by a broad statistical approach with mathematical modeling through the application of the Welch and Games-Howell tests and the Bayesian scale.