Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods

• Published in: Environmental science and pollution research international 2019-12, Vol.26 (34), p.35253-35265
• Main Authors: Pereira, Viviane Ribas, Pereira, Danillo Roberto, de Melo Tavares Vieira, Kátia Cristina, Ribas, Vitor Pereira, Constantino, Carlos José Leopoldo, Antunes, Patrícia Alexandra, Favareto, Ana Paula Alves
• Format: Article
• Language: English
• Subjects: Agricultural practices; Algorithms; Animals; Aquatic Pollution; Artificial intelligence; Artificial neural networks; Atmospheric Protection/Air Quality Control/Air Pollution; Classification; Difenoconazole; Dioxolanes - toxicity; DNA Damage; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental science; Epididymis; Epididymis - drug effects; Exposure; Fungicides; Fungicides, Industrial - toxicity; Learning algorithms; Learning theory; Machine Learning; Male; Neural networks; Parameters; Pattern recognition; Performance evaluation; Pesticides; Raman spectra; Rats; Rats, Wistar; Research Article; Spectrum Analysis, Raman; Sperm; Sperm Count; Sperm Motility - drug effects; Spermatozoa; Spermatozoa - drug effects; Support Vector Machine; Support vector machines; Testis - drug effects; Toxicity Tests; Triazoles - toxicity; Viability; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-019-06407-0

Difenoconazole is a fungicide extensively used in agriculture. The aim of this study was to evaluate the effects of difenoconazole fungicide on the sperm quality of rats. Wistar rats were divided into four groups: control and exposed to 5 (D5), 10 (D10), or 50 mg −1 kg bw −1 day (D50) of difenoconazole for 30 days, by gavage. Classical sperm parameters and surface-enhanced Raman scattering (SERS) were performed. Progressive motility, acrosomal integrity, and percentage of morphologically normal spermatozoa were reduced in the D10 and D50 groups in comparison with the control group. Sperm viability was reduced only in the D50 group. Sperm number in the testis and caput/corpus epididymis and daily sperm production were reduced in the three exposed groups. SERS measurements showed changes in the spectra of spermatozoa from D50 group, suggesting DNA damage. In addition, machine learning (ML) methods were used to evaluate the performance of three classification algorithms (artificial neural network—ANN, K-nearest neighbors—K-NN, and support vector machine—SVM) in the identification task of the groups exposed to difenoconazole. The results obtained by ML algorithms were very promising with accuracy ≥ 90% and validated the hypothesis of the exposure to difenoconazole reduces sperm quality. In conclusion, exposure of rats to different doses of the fungicide difenoconazole may impair sperm quality, with a recognizable classification pattern of exposure groups.