Guillermo R. Chantre

Associate Professor & Researcher UNS-CERZOS/CONICET Weed ecology & Management/ Weed modeling/ Decision Support Systems

Predicting field weed emergence with empirical models and soft computing techniques


Journal article


Jose Luis Gonzalez-Andujar, Guillermo R Chantre, C Morvillo, Anibal Manuel Blanco, Frank Forcella
Weed research, vol. 56, Wiley Online Library, 2016, pp. 415--423

DOI: https://doi.org/10.1111/wre.12223

View PDF
Cite

Cite

APA   Click to copy
Gonzalez-Andujar, J. L., Chantre, G. R., Morvillo, C., Blanco, A. M., & Forcella, F. (2016). Predicting field weed emergence with empirical models and soft computing techniques. Weed Research, 56, 415–423. https://doi.org/ https://doi.org/10.1111/wre.12223


Chicago/Turabian   Click to copy
Gonzalez-Andujar, Jose Luis, Guillermo R Chantre, C Morvillo, Anibal Manuel Blanco, and Frank Forcella. “Predicting Field Weed Emergence with Empirical Models and Soft Computing Techniques.” Weed research 56 (2016): 415–423.


MLA   Click to copy
Gonzalez-Andujar, Jose Luis, et al. “Predicting Field Weed Emergence with Empirical Models and Soft Computing Techniques.” Weed Research, vol. 56, Wiley Online Library, 2016, pp. 415–23, doi: https://doi.org/10.1111/wre.12223.


BibTeX   Click to copy

@article{gonzalez-andujar2016a,
  title = {Predicting field weed emergence with empirical models and soft computing techniques},
  year = {2016},
  journal = {Weed research},
  pages = {415--423},
  publisher = {Wiley Online Library},
  volume = {56},
  doi = { https://doi.org/10.1111/wre.12223},
  author = {Gonzalez-Andujar, Jose Luis and Chantre, Guillermo R and Morvillo, C and Blanco, Anibal Manuel and Forcella, Frank}
}


Share



Follow this website


You need to create an Owlstown account to follow this website.


Sign up

Already an Owlstown member?

Log in