Optimized near infrared reflectance model based on preprocessing selection strategy for rapid analysis of 2-acetyl-1-pyrroline content in rice flour

The chemical compound 2-acetyl-1-pyrroline (2-AP) is a major contributor to the fragrance of rice. This report presents the first efforts towards determining the quantities of 2-AP in rice by grating-based visible–near-infrared reflectance spectroscopy using a diverse set of rice varieties. Calibration models generated by preprocessing treatments using Design of Experiment (DoE) and ‘one-variable-at-atime’ (OVAT) methods were compared and optimized. A modified partial least squares model with “2, 3, 1, 1”/SNV and 174 variables yielded a coefficient of determination for calibration values of 0.978. The results showed that a DoE-based preprocessing selection could efficiently and accurately optimize 2-AP calibration models, with advantages over OVAT. The findings of this study provide high-throughput screening technology for high-precision fragrance quality breeding, monitoring and control in the rice industry. The method demonstrated here also has potential for application in many other disciplines, including identification of plant fragrances and quality control of cereal products. • Vis-NIRS was capable of accurate quantifying 2-acetyl-1-pyrroline in diverse rice samples. • DoE preprocessing methods accurately constructed Vis-NIRS calibration equations. • The long-NIR spectroscopic region was critical for successfully establishing the 2-AP model. • Using Vis-NIRS in HTS proved to be a valuable tool in rice breeding and the food industry.