Rapid Evaluation of Wheat Quality Using Near-Infrared Spectroscopy and Chemometrics

Strategic Insights -

Researchers at the National Wheat Improvement Centre have developed a method for rapidly evaluating the quality of bread wheat using near-infrared spectroscopy and chemometrics. This breakthrough has significant implications for the food industry and wheat breeding programs, enabling the selection of high-quality varieties. The study used a dataset of 1082 representative samples to develop calibration models for key rheological properties of dough in wheat. The results demonstrated strong predictive capabilities for Farinograph water absorption and high accuracy in qualitative analysis for other characteristics.

Key Takeaways:

  • The study used a dataset of 1082 representative samples to develop calibration models for key rheological properties of dough in wheat.
  • The partial least squares regression model for Farinograph water absorption demonstrated strong predictive capabilities (Rc = 0.92, Rv = 0.90, and RPD = 3.20).
  • The developed NIR models provided an efficient method for evaluating wheat quality in food processing and wheat breeding.
  • Qualitative analysis was feasible for other characteristics with high accuracy ranging from 80.23% to 94.27%.
  • The study has significant implications for the food industry and wheat breeding programs, enabling the selection of high-quality varieties.
  • The National Wheat Improvement Centre has developed a method for rapidly evaluating wheat quality using near-infrared spectroscopy and chemometrics.
  • The research was led by Lei Li and included contributions from Zihui Zhao, Wenduan Li, Yuanyuan Tian, Yan Zhang, Yong Zhang, Maria Itria Ibba, Zhonghu He, Yuanfeng Hao, and Wenfei Tian.

Statistics:

  • 1082 representative samples were used to develop calibration models for key rheological properties of dough in wheat.
  • The partial least squares regression model for Farinograph water absorption achieved a correlation coefficient (Rc) of 0.92 and a regression coefficient (Rv) of 0.90.
  • The root mean square error of prediction (RPD) for Farinograph water absorption was 3.20.
  • Qualitative analysis had a high accuracy ranging from 80.23% to 94.27% for different characteristics.

Sources:

  • Rapid evaluation of Farinograph and Extensograph characteristics in bread wheat using near-infrared spectroscopy and chemometrics. Food Research International, 2025;218:116915.