Rapid Non-Destructive Detection of Rice Seed Vigor via Terahertz Spectroscopy

Rice seed vigor significantly impacts yield, making the selection of high-vigor seeds crucial for agricultural production. Traditional methods for assessing seed vigor are time-consuming and destructive. This study aimed to develop a rapid, non-destructive method for evaluating rice seed vigor using terahertz spectroscopy. Rice seeds with varying vigor levels were prepared through high-temperature and high-humidity aging and classified into high-, low-, and non-vigorous groups based on germination performance. Terahertz transmission imaging (0.1–3 THz) was conducted on 420 seeds, and spectral data were preprocessed using several advanced data processing techniques, including competitive adaptive reweighting (CARS), uninformative variable elimination (UVE), and principal component analysis (PCA). Three chemometric models, namely random forest (RF), K-nearest neighbors (KNN), and partial least squares–discriminant analysis (PLS-DA), were established. The model based on CARS-KNN after band selection achieved the highest prediction accuracy of 97.14%. The results indicate that terahertz spectroscopy combined with band selection methods provides a reliable, non-destructive approach for rice seed vigor assessment, offering significant potential for agricultural quality control.