APA   Click to copy
Chantre, G. R., Vigna, M. R., Renzi, J. P., & Blanco, A. M. (2018). A flexible and practical approach for real-time weed emergence prediction based on Artificial Neural Networks. Biosystems Engineering, 170, 51–60. https://doi.org/10.1016/j.biosystemseng.2018.03.014

Chicago/Turabian   Click to copy
Chantre, Guillermo R., Mario R. Vigna, Juan P. Renzi, and Aníbal M. Blanco. “A Flexible and Practical Approach for Real-Time Weed Emergence Prediction Based on Artificial Neural Networks.” Biosystems Engineering 170 (2018): 51–60.

MLA   Click to copy
Chantre, Guillermo R., et al. “A Flexible and Practical Approach for Real-Time Weed Emergence Prediction Based on Artificial Neural Networks.” Biosystems Engineering, vol. 170, 2018, pp. 51–60, doi:10.1016/j.biosystemseng.2018.03.014.

@article{chantre2018a,
  title = {A flexible and practical approach for real-time weed emergence prediction based on Artificial Neural Networks},
  year = {2018},
  journal = {Biosystems Engineering},
  pages = {51-60},
  volume = {170},
  doi = {10.1016/j.biosystemseng.2018.03.014},
  author = {Chantre, Guillermo R. and Vigna, Mario R. and Renzi, Juan P. and Blanco, Aníbal M.}
}