Flower number is the primary determinant of yield in pyrethrum (Tanacetum cineariifolium). Traditional estimates of flower numbers use physical harvesting of flowers, which is time consuming, destructive, and complicated. The precision of flower number estimates may be highly influenced by spatial heterogeneity of plant density and vigor. Here, we examined the potential for digital image analysis to enable rapid, nondestructive assessment of flower number. This technique involved removal of pixels with color profiles not typical of the disc florets of pyrethrum. Particle counting was then performed using defined size and shape parameters to estimate flower numbers. Estimates of flower number based on image analyses were correlated with physical harvests of flowers, with estimates representing about an average of 32% of total flower numbers present within a sampling unit. This relationship was consistent across all observed flower densities. Covariate analysis indicated that occurrences of crop lodging and over mature flower canopies had significant, detrimental effects on system predictions. Pyrethrum flowers were spatially aggregated within fields with the degree of aggregation greatest at the lowest flower densities. Based on modeled flower distributions, eight quadrats (0.49-m2 sampling unit) were sufficient to achieve a cv of 0.1 in a 600-m2 plot area in all but the lowest flower densities. The utility of this approach for biomass assessment in pyrethrum and other Compositae is discussed.