4.3 Article

Measurement of absorption and scattering properties of milk using a hyperspectral spatial frequency domain imaging system

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出版社

SPRINGER
DOI: 10.1007/s11694-021-01199-9

关键词

Hyperspectral; Spatial frequency domain imaging; Optical properties; Absorption; Reduced scattering; Milk

资金

  1. National Natural Science Fund of China [32071904]
  2. Natural Science Fund of Zhejiang Province [LY20C130008]
  3. Science Foundation of Zhejiang Sci-Tech Univ. (ZSTU) [16022177-Y]

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A line scan hyperspectral spatial frequency domain combined imaging system was developed for quantitative hyperspectral optical imaging in the spatial frequency domain in agricultural and food products. The system was calibrated using liquid phantoms and showed average errors in absorption and reduced scattering parameters of tissues. The system was used to analyze optical parameters of milk samples and showed correlation between fat and protein contents of milk with absorption and reduced scattering parameters. Future applications include milk quality evaluation and classification for agricultural products and foods.
In response to the research demand in spatial frequency domain techniques at continuous wavelengths in the field of agricultural and food products, a line scan hyperspectral spatial frequency domain combined imaging (LSH-SFDI) system was developed for quantitative hyperspectral optical imaging in the spatial frequency domain for detecting absorption (mu(a)) and reduced scattering (mu '(s)) parameters of tissues in the continuous spectral range. Systematic calibration of the LSH-SFDI system was performed using the configured liquid phantoms, and the average errors of mu(a) and mu '(s) at 56 wavelength bands between 450 and 740 nm were obtained as 9.24% and 6.08%, respectively. The optical parameters of milk were measured using the LSH-SFDI system, and the mu(a) and mu '(s) values of milk samples at continuous wavelengths were analyzed by linear regression with the fat and protein contents of the corresponding milk, and the final results verified the correlation between the fat content and mu '(s) and the protein content and mu(a) of milk. The developed system can be further used for milk quality evaluation and classification subsequently, as well as for other agricultural products and foods.

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