Name
Title | ||
|---|---|---|
Sugarcane yields prediction at the row level using a novel cross-validation approach to multi-year multispectral images |
Abstract | ||
|---|---|---|
•Determine a more accurate sugarcane growth stage for predicting sugarcane production than prior studies.•Improve the sugarcane yield prediction model by adding UAV data at the row level.•Identify the most predictive VIs for pre-harvest prediction.•Present the novel cross-validation method to assess sugarcane yield model. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.compag.2022.107024 | Computers and Electronics in Agriculture |
Keywords | DocType | Volume |
Sugarcane crop yield prediction,Unmanned aerial vehicle,Cross-validation,Normalized Difference RedEdge,Green–red normalized difference vegetation index | Journal | 198 |
ISSN | Citations | PageRank |
0168-1699 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sharareh Akbarian | 1 | 0 | 0.34 |
| Chengyuan Xu | 2 | 0 | 0.34 |
| Weijin Wang | 3 | 0 | 0.34 |
| Stephen Ginns | 4 | 0 | 0.34 |
| Samsung Lim | 5 | 68 | 12.02 |