Accurate prediction of sugarcane yield using a random forest algorithm
Crossref DOI link: https://doi.org/10.1007/s13593-016-0364-z
Published Online: 2016-04-19
Published Print: 2016-06
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Everingham, Yvette
Sexton, Justin
Skocaj, Danielle
Inman-Bamber, Geoff
Funding for this research was provided by:
Sugar Research Australia (2014/024)
Text and Data Mining valid from 2016-04-19