Quality evaluation of Keemun black tea by fusing data obtained from near-infrared reflectance spectroscopy and computer vision sensors.

Song, Yan; Wang, Xiaozhong; Xie, Hanlei; Li, Luqing; Ning, Jingming; Zhang, Zhengzhu

Song, Yan; Wang, Xiaozhong; Xie, Hanlei; Li, Luqing; Ning, Jingming; Zhang, Zhengzhu.

Afiliação

Song Y; School of Engineering, Anhui Agricultural University, Hefei 230036, China.
Wang X; School of Engineering, Anhui Agricultural University, Hefei 230036, China.
Xie H; School of Engineering, Anhui Agricultural University, Hefei 230036, China.
Li L; State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China.
Ning J; State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China. Electronic address: ningjm1998009@163.com.
Zhang Z; State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China.

Spectrochim Acta A Mol Biomol Spectrosc ; 252: 119522, 2021 May 05.

Article em En | MEDLINE | ID: mdl-33582437

Assuntos

Camellia sinensis; Chá; Computadores; Folhas de Planta; Espectroscopia de Luz Próxima ao Infravermelho

Palavras-chave

Computer vision system; Convolutional neural network; Feature fusion; Keemun black tea; Near-infrared reflectance spectroscopy; Quality identification

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Chá / Camellia sinensis Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo

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PubMed Links

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Chá / Camellia sinensis Idioma: En Ano de publicação: 2021 Tipo de documento: Article