Machine learning-based estimation of leaf chlorophyll content in greenhouse-grown muskmelon using portable hyperspectral reflectance measurements

Abstract

Abstract has not been obtained from indexed metadata or an accessible article page.

Plant phenotyping relevance

携帯型ハイパースペクトル測定と機械学習により、葉のクロロフィル含量という植物形質を推定する手法が題名上の中心であるため。

Code and data availability

The paper's hyperspectral reflectance dataset (392 muskmelon leaf samples) and analysis code are not publicly deposited; the authors state data are available only on request.

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