Artificial intelligence and machine vision are increasingly popular within food supply chains for automated decision making in quality grading and disease identification.

Animal pollination enhances a third of global food production, yet the roles of pollinator, pollen, and cultivar identity in shaping crop quality, such as nutritional, sensory, and marketing value, are underexplored. Crop quality often depends on pollinator movement patterns, which vary with cultivar selection and spatial arrangement, pollen donor identity, and landscape context. Transfer of the right pollen between cultivars may fail, as pollen is often not transported far, even by highly dispersive pollinators, reducing cross-pollination and crop quality. Both pollinator identity and complementary spatiotemporal activity of diverse pollinators can shape crop quality. Here, we argue that promoting crop quality needs better understanding of species-specific pollinator behaviour and cultivar distribution patterns, rather than only focusing on enhancing pollinator densities.