The Synthetic Apple Collection (SyntAC) is a suite of three synthetic datasets (Synthetic A, B, and C) designed to advance computer vision applications in precision agriculture. SyntAC provides a scalable and cost-effective alternative to manually annotated real-world imagery. The collection was generated using a fully procedural pipeline in Blender and Unreal Engine 5, with each tier (A → C) progressively refined to align scene composition and annotation geometry with high-performing real-world benchmarks.