High throughput phenotyping of energy cane using uncrewed aircraft system (UAS) and machine learning

Accurate estimation of biomass in energy cane is essential for cultivar selection in breeding programs and biomass supply forecasting in bioenergy production. This study evaluated the integration of Uncrewed Aircraft System (UAS) based Light Detection and Ranging (lidar) and Red-Green-Blue Structure...

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מידע ביבליוגרפי

Principais autores:	Benjamin Ghansah, Ittipon Khuimphukhieo, Jorge Da Silva, Jose L.Landivar Scott, Oscar Fernández Montero, Jamie Foster, Hua Li, Michael J. Starek, Mahendra Bhandari
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Elsevier 2026-01-01
סדרה:	Industrial Crops and Products
נושאים:	Energy cane High throughput phenotyping (HTP) Uncrewed aircraft system (UAS) Light detection and ranging (lidar) Red-green-blue (RGB) Biomass
גישה מקוונת:	http://www.sciencedirect.com/science/article/pii/S0926669025019430
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!