Design and Experiment of a Portable Near-Infrared Spectroscopy Device for Convenient Prediction of Leaf Chlorophyll Content.

Li, Longjie; Guo, Junxian; Wang, Qian; Wang, Jun; Liu, Ya; Shi, Yong

Li, Longjie; Guo, Junxian; Wang, Qian; Wang, Jun; Liu, Ya; Shi, Yong.

Afiliación

Li L; College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
Guo J; Key Laboratory of Xinjiang Intelligent Agricultural Equipment, Urumqi 830052, China.
Wang Q; College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
Wang J; College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
Liu Y; College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
Shi Y; College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Sensors (Basel) ; 23(20)2023 Oct 19.

Article en En | MEDLINE | ID: mdl-37896678

Asunto(s)

Clorofila; Espectroscopía Infrarroja Corta; Espectroscopía Infrarroja Corta/métodos; Análisis de los Mínimos Cuadrados; Clorofila/análisis; Hojas de la Planta/química; Agricultura

Palabras clave

Internet of Things technology; chlorophyll content prediction; data preprocessing; regression algorithms; spectral data analysis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Clorofila / Espectroscopía Infrarroja Corta Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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