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

  • Viviane Ribas Pereira
  • Danillo Roberto Pereira
  • Kátia Cristina de Melo Tavares Vieira
  • Vitor Pereira Ribas
  • Carlos José Leopoldo Constantino
  • Patrícia Alexandra Antunes
  • Ana Paula Alves FavaretoEmail author
Research Article


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−1day (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.


Fungicide Reproduction Spermatozoa Rat Raman spectroscopy Artificial intelligence 



This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

Grant support

University of Western São Paulo (UNOESTE). FAPESP (2013/14262-7 and 2014/11410-8) and CNPq.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Abd-Alrahman SH, Elhalwagy ME, Kotb GA, Farid H, Farag AA, Draz HM, Isa AM, Sabico S (2014) Exposure to difenoconazole, diclofop-methyl alone and combination alters oxidative stress and biochemical parameters in albino rats. Int J Clin Exp Med 7:3637–3646Google Scholar
  2. Albuquerque VHC, Nunes TM, Pereira DR, Luz E.J, Menotti D, Papa JP, Tavares JMRS (2018) Robust automated cardiac arrhythmia detection in ECG beat signals. Neural Comput Appl 29:679-693. CrossRefGoogle Scholar
  3. Amaral S, Da Costa R, Wübbeling F, Redmann K, Schlatt S (2018) Raman micro-espectroscopy analysis of different sperm regions: a species comparison. Mol Hum Reprod 24:185–202. CrossRefGoogle Scholar
  4. Aroca RF, Alvarez-Puebla RA, Pieczonka N, Sanchez-Cortez S, Garcia-Ramos JV (2005) Surface-enhanced Raman Scattering em colloidal nanostructures. Adv Colloid Interf Sci 116:45–6146. CrossRefGoogle Scholar
  5. Baskin II (2018) Machine Learning Methods in Computational Toxicology. Methods Mol Biol 1800:119–139. CrossRefGoogle Scholar
  6. Baştanlar Y, Ozuysal M (2014) Introduction to machine learning. Methods Mol Biol 1107:105–128. CrossRefGoogle Scholar
  7. Chang CC, Lin CJ (2011) LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol 2:1–27 Software available at CrossRefGoogle Scholar
  8. Chen J, Xiao HJ, Qi T, Chen DL, Long HM, Liu SH (2015) Rare earths exposure and male infertility: the injury mechanism study of rare earths on male mice and human sperm. Environ Sci Pollut Res 22:2076–2086. CrossRefGoogle Scholar
  9. Clegg ED, Perreault SD, Klinefelter GR (2001) Assessment of Male reproductive toxicology. In: Wallace H (ed) Principles and methods of toxicology, 4th edn. Taylor & Francis, Philadelphia, pp 1263–1299Google Scholar
  10. Costa NO, Vieira ML, Sgarioni VP (2015) Evalution of the reproductive toxicity of fungicide prppiconazole in male rats. Toxicol 335:55–61. CrossRefGoogle Scholar
  11. Dong X, Zhang L, Chen M, Yang Z, Zuo Z, Wang C (2018) Exposure to difenoconazole inhibits reproductive ability in male marine medaka (Oryzias melastigma). J Environ Sci 63:126–132. CrossRefGoogle Scholar
  12. El-Medany AH, Hagar HH (2002) Effect of fluconazole on the fertility of male rabbits. Arzneimittelforschung 52:636–640. CrossRefGoogle Scholar
  13. Fernandes GS, Arena AC, Fernandez CD, Mercadante A, Barbisan LF, Kempinas WG (2007) Reproductive effects in male rats exposed to diuron. Reprod Toxicol 23(1):106–112. CrossRefGoogle Scholar
  14. Filler R (1993) Methods for evaluation of rat epididymal sperm morphology. In: Chapin RE, Heindel JH (eds) Methods in toxicology: Male reproductive toxicology. Academic Press, San Diego, pp 334–343CrossRefGoogle Scholar
  15. Garrett C, Liu DY, Baker HWG (1997) Selectivity of the human sperm-zona pellucida binding process to sperm head morphometry. Fertil Steril 67:362–371. CrossRefGoogle Scholar
  16. Goetz AK, Ren H, Schmid JE, Blystone CR, Thillainadarajah I, Best DS, Nichols HP, Strader LF, Wolf DC, Narotsky MG, Rockett JC, Dix DJ (2006) Disruption of testosterone homeostasis as a mode of action for the reproductive toxicity of triazole fungicides in the male rat. Toxicol Sci 95:227–239. CrossRefGoogle Scholar
  17. Grabar KC, Freeman RG, Hommer MB, Natan MJ (1995) Preparation and characterization monolayers. Anal Chem 67:735–743. CrossRefGoogle Scholar
  18. Hall P, Park BU, Samworth RJ (2008) Choice of neighbor order in nearest-neighbor classification. Ann Stat 6(5):2135–2152. CrossRefGoogle Scholar
  19. Haykin S (1999) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall, New JerseyGoogle Scholar
  20. Hinfray N, Porcher JM, Brion F (2006) Inhibition of rainbow trout (Oncorhynchus mykiss) P450 aromatase activities in brain and ovarian microsomes by various environmental substances. Comp Biochem Physiol C Toxicol Pharmacol 144:252–262. CrossRefGoogle Scholar
  21. Hossain MS, Johannisson A, Wallgren M, Nagy S, Siqueira AP, Rodriguez-Martinez H (2011) Flow cytometry for the assessment of animal sperm integrity and functionality: state of the art. Asian J Androl 13:406–419. CrossRefGoogle Scholar
  22. Huang ZF, Chen XW, Chen G, Chen JH, Wang J, Lin JK, Zeng H, Chen R (2013) Characterization and differentiation of normal and abnormal spermatozoa via micro-Raman spectroscopy. Laser Phys Lett 10:1–6. CrossRefGoogle Scholar
  23. Huang S, Yan W, Liu M, Hu J (2016) Detection of difenoconazole pesticides in packchoi by surface-enhanced Raman scaterring spectroscopy coupled with gold nanoparticles. Anal Methods 8:4755–4761. CrossRefGoogle Scholar
  24. Huser T, Orme CA, Hollars CW, Corzett MH, Balhorn R (2009) Raman spectroscopy of DNA packaging in individual human sperm cells distinguishes normal from abnormal cells. J Biophotonics 2(5):322–332. CrossRefGoogle Scholar
  25. Jankowska M, Łozowicka B, Kaczyński P (2019) Comprehensive toxicological study over 160 processing factors of pesticides in selected fruit and vegetables after water, mechanical and thermal processing treatments and their application to human health risk assessment. Sci Total Environ 652:1156–1167. CrossRefGoogle Scholar
  26. Khaki A, Khaki AA, Hajhosseini L, Golzar FS, Ainehchi N (2014) The anti-oxidant effects of ginger and cinnamon on spermatogenesis dys-function of diabetes rats. Afr J Tradit Complement Altern Med 11(4):1–8. CrossRefGoogle Scholar
  27. Lang T, Dechant M, Sanchez V, Wistuba J, Boiani M, Pilatz A, Stammler A, Middendorff R, Schuler G, Bhushan S, Tchatalbachev S, Wübbeling F, Burger M, Chakraborty T, Mallidis C, Meinhardt A (2013) Structural and functional integrity of spermatozoa is compromised as a consequence of acute uropathogenic e.coli-associated epididymitis. Biol Reprod 89:1–10. CrossRefGoogle Scholar
  28. Latiff KA, Bakar NKA, Isa NM (2010) Preliminary study of difenoconazole residues in rice paddy watersheds. Malays J Sci 29:73–79. CrossRefGoogle Scholar
  29. Li N, Chen D, Xu Y, Liu S, Zhang H (2014) Confocal Raman micro-spectroscopy for rapid and label-free detection of maleic acid-induced variations in human sperm. Biomedical Opt Express 5:1690–1699. CrossRefGoogle Scholar
  30. Li F, Fan D, Wang H, Yang H, Li W, Tang Y, Liu G (2017) In silico prediction of pesticide aquatic toxicity with chemical category approaches. Toxicol Res (Camb) 6(6):831–842. CrossRefGoogle Scholar
  31. Liu R, Madore M, Glover KP, Feasel MG, Wallqvist A (2018) Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity. Toxicol Sci 164(2):512–526. CrossRefGoogle Scholar
  32. Mallidis C, Wistuba J, Bleisteiner B, Damm OS, Gross P, Wübbeling F, Fallnich C, Burger M, Schlatt S (2011) In situ visualization of damaged DNA in human sperm by Raman microspectroscopy. Hum Reprod 26:1641–1649. CrossRefGoogle Scholar
  33. Menkveld R, Rhemrev JP, Franken DR, Vermeiden JP, Kruger TF (1996) Acrosomal morphology as a novel criterion for male fertility diagnosis: relation with acrosin activity, morphology (strict criteria), and fertilization in vitro. Fertil Steril 65:637–644. CrossRefGoogle Scholar
  34. Monod G, Rime H, Bobe J, Jalabert B (2004) Agonistic effect of imidazole and triazole fungicides on in vitro oocyte maturation in rainbow trout (Oncorhynchus mykiss). Mar Environ Res 58:143–146. CrossRefGoogle Scholar
  35. Mu X, Chai T, Wang K, Zhang J, Zhu L, Li X, Wang C (2015) Occurrence and origin of sensitivity toward difenoconazole in zebrafish (Danio reio) during different life stages. Aquat Toxicol 160:57–68. CrossRefGoogle Scholar
  36. Nissen S (2003) Implementation of a Fast Artificial Neural Network Library (FANN). Department of Computer Science University of Copenhagen (DIKU). Software available at
  37. Papa JP, Falcão AX, Suzuki CTN (2009) Supervised pattern classification based on optimum-path forest. Int J Imaging Syst Technol 19:120–131. CrossRefGoogle Scholar
  38. Patel VL, Shortliffe EH, Stefanelli M, Szolovits P, Berthold MR, Bellazzi R, Abu-Hanna A (2009) The coming of age of artificial intelligence in medicine. Artif Intell Med 46(1):5–17. CrossRefGoogle Scholar
  39. Pereira CR, Pereira DR, Silva FA, Masieiro JP, Weber SA, Hook C, Papa JP (2016) A new computer vision-based approach to aid the diagnosis of Parkinson's disease. Comput Methods Prog Biomed 136:79–88. CrossRefGoogle Scholar
  40. Pope CE, Zhang YZ, Dresser BL (1991) A simple staining method for evaluating acrossomal status of cat spermatozoa. J Zoo Wildl Med 22(1):87–95. CrossRefGoogle Scholar
  41. Reuveni M, Sheglov D (2002) Effects of azoxystrobin, difenoconazole, polyoxin B (polar) and trifloxystrobin on germination and growth of Alternaria alternata and decay in red delicious apple fruit. Crop Prot 21:951–955. CrossRefGoogle Scholar
  42. Robb GW, Amann RP, Killian GJ (1978) Daily sperm production and epididymal sperm reserves of pubertal and adult rats. J Reprod Fertil 54(1):103–107. CrossRefGoogle Scholar
  43. Sanchez VB, Redmann K, Wistuba J, Wübbeling F, Burger M, Oldenhof H, Wolkers WF, Kliesch S, Schlatt S, Mallidis C (2012) Oxidative DNA damage in human sperm can be detected by Raman microspectroscopy. Fertil Steril 98:1124–1129. CrossRefGoogle Scholar
  44. Satapornvanit K, Baird DJ, Little DC, Tayloe GJ (2004) Risks of pesticide use in aquatic ecosystems adjacent to mixed vegetable and monocrop fruit growing areas in Thailand. Australas J 10:85–95Google Scholar
  45. Schölkopf B, Smola A (2002) Learning with Kernels. MIT Press, CambridgeGoogle Scholar
  46. Seed J, Chapin RE, Clegg ED, Dostal LA, Foote RH, Hurtt ME, Klinefelter GR, Makris SL, Perreault SD, Schrader S, Seyler D, Sprando R, Treinen KA, Veeramachaneni DN, Wise LD (1996) Methods for assessing sperm motility, morphology, and counts in the rat, rabbit, and dog: a consensus report. ILSI risk science institute expert working group on sperm evaluation. Reprod Toxicol 10(3):237–244. CrossRefGoogle Scholar
  47. Shivanoor SMS, David M (2015) Fourier transform infrared (FT-IR) study on cyanide induced biochemical and structural changes in rat sperm. Toxicol Rep 2:1347–1356. CrossRefGoogle Scholar
  48. Souza LP, Faroni LRD, Heleno FF, Pinto FG, Queiroz MELR, Prates LHF (2019) Difenoconazole and linuron dissipation kinetics in carrots under open-field conditions. Ecotoxicol Environ Saf 168:479–485. CrossRefGoogle Scholar
  49. Sun C, Cang T, Wang Z, Wang X, Yu R, Wang Q, Zhao X (2015) Degradation of three fungicides following application on strawberry and a risk assessment of their toxicity under greenhouse conditions. Environ Monit Assess 187:303. CrossRefGoogle Scholar
  50. Szpyrka E, Walorczyk S (2017) Dissipation of difenoconazole in apples used for production of baby food. J Environ Sci Health B 52(2):131–137. CrossRefGoogle Scholar
  51. Talari ACS, Movasaghi Z, Rehman S, Rehman I (2015) Raman Spectroscopy of Biological Tissues. Appl Spectrosc Rev 50:46–111. CrossRefGoogle Scholar
  52. Taxvig C, Hass U, Axelstad M, Dalgaard M, Boberg J, Andeasen HR, Vinggaard AM (2007) Endocrine-disrupting activities in vivo of the fungicides tebuconazole and epoxiconazole. Toxicol Sci 100:464–473. CrossRefGoogle Scholar
  53. Teng M, Qi S, Zhu W, Wang Y, Wang D, Dong K, Wang C (2018) Effects of the bioconcentration and parental transfer of environmentally relevant concentrations of difenoconazole on endocrine disruption in zebrafish (Danio rerio). Environ Pollut 233:208–217. CrossRefGoogle Scholar
  54. Thom E, Ottow JCG, Benckiser G (1997) Degradation of the fungicide difenoconazole in a silt loam soil as affected by pretreatment and organic amendment. Environ Pollut 96:409–414. CrossRefGoogle Scholar
  55. Tomiazzi J, Judai MA, Nai GA, Pereira DR, Antunes PA, Favareto APA (2018) Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms. Environ Sci Pollut Res Int 25(2):1259–1269. CrossRefGoogle Scholar
  56. Tully DB, Bao W, Goetz AK, Blystone CR, Ren H, Schmid JE, Strader LF, Wood CR, Best DS, Narotsky MG, Wolf DC, Rockett JC, Dix DJ (2006) Gene expression profiling in liver and testis of rats to characterize the toxicity of triazole fungicides. Toxicol Appl Pharmacol 215:260–273. CrossRefGoogle Scholar
  57. Vargas TS, Salustriano NA, Klein B, Romão W, Silva SRCD, Wagner R, Scherer R (2018) Fungicides in red wines produced in South America. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 35(11):2135–2144. CrossRefGoogle Scholar
  58. Wang K, Wu JX, Zhang HY (2012) Dissipation of difenoconazole in rice, paddy soil, and paddy water under field conditions. Ecotoxicol Environ Saf 86:111–115. CrossRefGoogle Scholar
  59. WHO (1999) Laboratory manual for the examination of human semen and sperm-cervical mucus interaction, 4th edn. Cambridge University Press, United Kingdom 128p. 4th 20manual.pdf Accessed 15 fev 2017Google Scholar
  60. Yang JD, Liu SH, Liao MH, Chen RM, Liu PY, Ueng TH (2018) Effects of tebuconazole on cytochrome P450 enzymes, oxidative stress, and endocrine disruption in male rats. Environ Toxicol 33(899):907. CrossRefGoogle Scholar
  61. Yilmaz A, Ari S, Kocabiçak U (2016) Risk analysis of lung cancer and effects of stress level on cancer risk through neuro-fuzzy model. Comput Methods Prog Biomed 137:35–46. doi: Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Viviane Ribas Pereira
    • 1
  • Danillo Roberto Pereira
    • 1
  • Kátia Cristina de Melo Tavares Vieira
    • 1
  • Vitor Pereira Ribas
    • 2
  • Carlos José Leopoldo Constantino
    • 3
  • Patrícia Alexandra Antunes
    • 2
  • Ana Paula Alves Favareto
    • 1
    Email author
  1. 1.Graduate Program in Environment and Regional DevelopmentUniversity of Western São Paulo – UNOESTEPresidente PrudenteBrazil
  2. 2.College of Science, Letters and Education from Presidente Prudente – FACLEPPUniversity of Western São Paulo – UNOESTEPresidente PrudenteBrazil
  3. 3.School of Technology and Applied Sciences, São Paulo State University (UNESP), Campus Presidente PrudentePresidente PrudenteBrazil

Personalised recommendations