Yin Shen | Wheats | Best Researcher Award

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Assoc Prof DrĀ Ā YinĀ Shen |Ā Wheats |Ā Best Researcher Award

Associate professor atĀ Ā Chongqing Medical University,Ā China

Yin Shen is a dedicated researcher specializing in the field of spectroscopy and its applications in material identification and analysis. Holding a strong academic background, Shen has contributed significantly to the advancement of analytical methods, particularly in the areas of terahertz spectroscopy combined with advanced algorithms.

Publication Profile:šŸŒŸšŸ‘Øā€šŸŽ“

šŸ”¬ Research Focus:

Yin Shen’s research focuses on the application of terahertz spectroscopy combined with advanced chemometric techniques in agricultural analysis, particularly in the domain of wheat quality assessment. With an emphasis on rapid identification of wheat origin, moisture determination, spectral signature analysis across different years, and impurity detection using terahertz spectral imaging and convolutional neural networks, Shen’s work addresses critical challenges in wheat production and quality control.

citations:

Yin Shen is a distinguished researcher with a focus on analytical chemistry and spectroscopy techniques, particularly in the agricultural domain. With 131 citations from 123 documents, Shen’s work has garnered significant attention within the scientific community.

Having authored 12 impactful documents, Shen’s research has contributed to advancements in the field. Their dedication to scientific inquiry is reflected in their h-index of 6, indicating a notable level of influence and recognition in their field.

Publications Top Notes

  1. “Rapid identification of producing area of wheat using terahertz spectroscopy combined with chemometrics” (Spectrochimica Acta – Part A: Molecular and Biomolecular Spectroscopy, 2022)
    • This study highlights the use of terahertz spectroscopy and chemometrics for rapid identification of wheat production areas, contributing to advancements in agricultural quality control.
  2. “Determination of wheat moisture using terahertz spectroscopy combined with the tabu search algorithm” (Analytical Methods, 2021)
    • Shen’s research demonstrates the efficacy of terahertz spectroscopy combined with the tabu search algorithm in accurately determining wheat moisture content, offering valuable insights for grain storage and management.
  3. “Study on Terahertz Time-domain Spectral Signatures of Wheat from Different Years” (Journal of Physics: Conference Series, 2021)
    • This conference paper explores terahertz time-domain spectral signatures of wheat across different years, providing valuable data for understanding variations in wheat composition over time.
  4. “Detection of impurities in wheat using terahertz spectral imaging and convolutional neural networks” (Computers and Electronics in Agriculture, 2021)
    • Shen’s research investigates the detection of impurities in wheat using terahertz spectral imaging and convolutional neural networks, offering innovative solutions for quality assessment in agricultural products.