ABSTRACT The labor shortage and high wages in the tea industry have prompted a shift from manual (fine) plucking to non‐selective (coarse) shear plucking machinery. While this transition addresses the labor issue, it introduces a new challenge of effectively separating buds with multiple leaves from those with one or two leaves to produce high‐quality tea. Currently, a comprehensive review on fresh tea leaf grading is unavailable and therefore, this review was undertaken to provide the technologies used in fresh tea leaves grading. This review focuses on fresh tea leaf grading, specifically examining machinery and their working mechanisms that have addressed the challenges associated with coarse plucking and improved tea quality. Traditionally, leaf grading was carried out by trained personnel, but this process was time‐consuming and had low throughput. To overcome these challenges, conventional machinery was developed with mesh sieving and pneumatic separation mechanisms. While these machines provided high throughput, they also increased the damage level to tea leaves and decreased the precision of grading, thereby reducing tea quality. Consequently, intelligent graders utilizing computer vision (CV) and artificial intelligence (AI) were developed. These intelligent graders improved precision and minimized damage levels but exhibited a low throughput of 3–5 kg/h of tea leaves. At this capacity, these machines are not suitable for industrial purposes and require further enhancements to increase throughput and meet industrial demands.
Gunaratnam Abhiram (2026) studied this question.