Sorghum is the main raw material used to make Chinese Baijiu. However, different varieties can be difficult to distinguish quickly and accurately, making rapid quality screening a challenge.

A team led by Prof. WANG Qi from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, along with Luzhou Laojiao Co., Ltd, developed two data-fusion methods for rapid and accurate identification of brewing sorghum varieties. The studies were published in Microwave and Optical Technology Letters and Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy.

The first method combines information on key components in sorghum with conventional near-infrared (NIR) spectral analysis. Tested on more than 20,000 sorghum grains, this method achieved an accuracy of 87.86% and an F1-score of 89.99%, outperforming conventional identification methods.

The other method combines NIR spectroscopy with machine vision. By using both spectral data and images of sorghum kernels, it enables the two types of information to complement each other in identifying different varieties. Tested on six representative sorghum varieties, this method achieved 98.88% accuracy and a Macro-F1 score of 98.74%, outperforming methods based on either spectral or image information alone.

Both methods were tested with the team's self-developed high-throughput detection device. This study offers a practical way to rapidly screen and sort brewing sorghum varieties, and could help improve raw-material quality control in the Baijiu industry.