Multispectral imaging flow cytometry for spatio-temporal pollen trait variation measurements of insect-pollinated plants

Study of spatio-temporal pollen trait variation measurements of four insect-pollinated plants
Conclusion:
AI-driven pollen image recognition grows, but application to real-world samples is still challenging. Our study investigates spatial and temporal variations in pollen traits of 64,001 pollen of four species showing species-specific trait variations. Multiple diverse samples improve classification reliability, emphasizing the significance of variation in AI-based pollen identification. All pollen images were manually checked for quality and the fcs-Files derived stem only from pollen which are quality-checked.