Hyperspectral wavelength selection for estimating chlorophyll content of muskmelon leaves

Quantifying chlorophyll content, an effective indicator of disease as well as nutritional and environmental stresses on plants, may enable optimal fertilization while managing crops. Hyperspectral remote-sensing is commonly used to estimate chlorophyll content. In this context, the process of variab...

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Detalhes bibliográficos

Principais autores:	Rei Sonobe, Yudai Sugimoto, Ryohei Kondo, Haruyuki Seki, Erika Sugiyama, Yoshikazu Kiriiwa, Katsumi Suzuki
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Taylor & Francis Group 2021-01-01
coleção:	European Journal of Remote Sensing
Assuntos:	chlorophyll content cucumis melo l. machine learning partial least square
Acesso em linha:	http://dx.doi.org/10.1080/22797254.2021.1964383
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