Image-Based Phenotyping for Non-Destructive In Situ Rice (<i>Oryza sativa</i> L.) Tiller Counting Using Proximal Sensing.

Yamagishi, Yuki; Kato, Yoichiro; Ninomiya, Seishi; Guo, Wei

Image-Based Phenotyping for Non-Destructive In Situ Rice (Oryza sativa L.) Tiller Counting Using Proximal Sensing.

Yamagishi, Yuki; Kato, Yoichiro; Ninomiya, Seishi; Guo, Wei.

Afiliação

Yamagishi Y; Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.
Kato Y; Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.
Ninomiya S; Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.
Guo W; Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.

Sensors (Basel) ; 22(15)2022 Jul 25.

Article em En | MEDLINE | ID: mdl-35898050

Assuntos

Oryza; Grão Comestível; Processamento de Imagem Assistida por Computador; Folhas de Planta

Palavras-chave

image analysis; plant phenotyping; synchronous emergence of leaf and tiller theory

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Oryza Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Japão

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