Your browser doesn't support javascript.
loading
Research on detection of potato varieties based on spectral imaging analytical algorithm.
Li, You; Chen, Zhaoqing; Zhang, Fenyun; Wei, Zhenbo; Huang, Yun; Chen, Changqing; Zheng, Yurui; Wei, Qiquan; Sun, Hongwei; Chen, Fengnong.
Afiliación
  • Li Y; School of Automation, Hangzhou Dianzi University, Hanzhou, Zhejiang Province 310018, China.
  • Chen Z; School of Automation, Hangzhou Dianzi University, Hanzhou, Zhejiang Province 310018, China.
  • Zhang F; School of Automation, Hangzhou Dianzi University, Hanzhou, Zhejiang Province 310018, China.
  • Wei Z; College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang Province 310058, China.
  • Huang Y; Jinhua Academy of Agricultural Sciences, Jinhua, Zhejiang Province 321017, China.
  • Chen C; Jinhua Academy of Agricultural Sciences, Jinhua, Zhejiang Province 321017, China.
  • Zheng Y; School of Automation, Hangzhou Dianzi University, Hanzhou, Zhejiang Province 310018, China.
  • Wei Q; School of Automation, Hangzhou Dianzi University, Hanzhou, Zhejiang Province 310018, China.
  • Sun H; School of Automation, Hangzhou Dianzi University, Hanzhou, Zhejiang Province 310018, China. Electronic address: sunhongwei@hdu.edu.cn.
  • Chen F; School of Automation, Hangzhou Dianzi University, Hanzhou, Zhejiang Province 310018, China. Electronic address: fnchen@hdu.edu.cn.
Spectrochim Acta A Mol Biomol Spectrosc ; 311: 123966, 2024 Apr 15.
Article en En | MEDLINE | ID: mdl-38335591
ABSTRACT
Potatoes are popular among consumers due to their high yield and delicious taste. However, due to the numerous varieties of potatoes, different varieties are suitable for different processing methods. Therefore, it is necessary to distinguish varieties after harvest to meet the needs of processing enterprises and consumers. In this study, a new visible-near-infrared spectroscopic analysis method was proposed, which can achieve detection of five potato varieties. The method measures the transmission and reflection spectra of potatoes using a spectral acquisition system, encodes one-dimensional spectra into two-dimensional images using Gramian Angular Summation Field (GASF), Gramian Angular Difference Field (GADF), Markov Transition Field (MTF) and Recurrence Plot (RP), and improves the coordinated attention mechanism module and embeds the improved module into the ConvNeXt V2 model to build the ConvNeXt V2-CAP model for potato variety classification. The results show that compared with directly using one-dimensional classification models, image encoding of spectral data for classification greatly improves the accuracy. Among them, the best accuracy of 99.54% is achieved by using GADF image encoding of transmission spectra combined with the ConvNeXt V2-CAP model for classification, which is 16.28% higher than the highest accuracy of the one-dimensional classification model. The CAP attention mechanism module improves the performance of the model, especially when the dataset is small. When the training set is reduced to 150 images, the accuracy of the model is improved by 2.33% compared to the original model. Therefore, it is feasible to classify potato varieties using visible-near infrared spectroscopy and image encoding technology.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Spectrochim Acta A Mol Biomol Spectrosc Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Spectrochim Acta A Mol Biomol Spectrosc Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido