<p>Potato tuber dormancy and sprouting are critical postharvest physiological processes that strongly influence storage stability, processing quality, and marketability. However, postharvest sprouting remains a persistent problem, reducing tuber quality and its physicochemical properties. Accurate prediction and monitoring of dormancy and sprouting are therefore critical for long-term storage. This review provides an overview of destructive and non-destructive analytical methods developed for potato dormancy prediction and sprouting detection. Conventional destructive methods, such as biochemical and enzymatic assays, offer high precision but are labour-intensive and unsuitable for large-scale applications. In contrast, non-destructive technologies, including digital, multispectral, hyperspectral, and thermal imaging, have shown great potential for rapid, accurate, and automated quality monitoring. Recent studies have demonstrated the capability of multispectral and hyperspectral imaging systems, often coupled with advanced machine learning and deep learning algorithms, to classify and detect sprouting stages with accuracies exceeding 90%. However, dormancy prediction research remains minimal. Thermal imaging, which can detect temperature variations associated with metabolic activity during bud initiation, remains an unexplored yet promising tool for early dormancy detection. Moreover, most existing imaging-based studies have been confined to laboratory environments and require scaling to industrial conditions using real-time line-scan systems and high-speed processing algorithms. The review concludes that integrating spectral, thermal, and digital imaging with machine learning and data fusion frameworks could provide a comprehensive, non-destructive approach for dormancy prediction and sprouting detection. Such advancements will enable real-time quality monitoring, optimize sprout suppressant application, and enhance postharvest management to ensure the sustainable storage and supply of high-quality potatoes.</p>