Fresh Fruit Bunch (FFB) grading represents a critical intervention point for enhancing oil palm productivity and sustainability. This qualitative literature review synthesizes empirical evidence from 2020 to 2026 to examine the effectiveness of FFB grading implementation in improving both oil extraction rates and product quality. Through a thematic analysis of peer-reviewed publications and technical reports, this study identifies seven key themes: FFB grading as a productivity determinant; technological evolution from manual to automated systems; precision in ripeness classification; impacts of processing delays; economic viability considerations; drivers of sustainability certification; and challenges of smallholder inclusion. Findings reveal that automated grading systems can achieve 8-12% improvements in oil extraction rates compared to baseline manual practices, with deep learning technologies demonstrating over 95% classification accuracy. However, adoption barriers persist, particularly for smallholder producers who constitute a significant portion of global production. The review synthesizes mechanistic pathways linking grading accuracy to productivity outcomes, evaluates e
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