Key points are not available for this paper at this time.
Spices are widely valued for their unique flavors and bioactive properties, but ensuring authenticity, quality, and safety remains challenging due to adulteration, geographic variability, and complex composition. Analytical methods, such as spectroscopy, chromatography, and electronic sensors, offer insights but often face limitations in cost, scalability, and real-time application. Artificial intelligence (AI) provides a data-driven solution, enabling rapid and accurate assessment through machine learning, deep learning, and computer vision for origin identification, adulteration detection, quality evaluation, and flavor profiling. Complementary technologies, including IoT and blockchain, further enhance traceability and intelligent supply chain management. This review also discusses key technical challenges, such as limited datasets, model interpretability, and integration of domain knowledge, alongside emerging innovations addressing these issues. Overall, AI offers significant potential to standardize spice quality evaluation, safeguard authenticity, and drive intelligent, efficient production across the spice industry.
Lu et al. (2025) studied this question.