An unsupervised automatic measurement of wheat spike dimensions in dense 3D point clouds for field application

An accurate measurement of field-grown wheat traits, including spike number, dimension and volume are essential for crop phenotyping and yield analysis. A high-throughput method to image field-grown wheat in three dimensions is presented with an accompanying unsupervised measuring method to obtain i...

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Vydáno v:	Biosystems engineering Ročník 223; s. 103 - 114
Hlavní autoři:	Wang, Fuli, Li, Fengping, Mohan, Vishwanathan, Dudley, Richard, Gu, Dongbing, Bryant, Ruth
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.11.2022
Témata:	algorithms data collection k-means phenotype Point clouds Shape-fitting Unsupervised algorithm wheat Wheat phenotype k-means Unsupervised algorithm Wheat phenotype Shape-fitting Point clouds
ISSN:	1537-5110, 1537-5129
On-line přístup:	Získat plný text
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