The dynamics of silk emergence in maize (Zea mays L.) determine the number of silks available for pollination. Simulation models that use flowering characteristics to predict kernel set have proven to be an important tool for improving inbred management in seed corn production fields. However, the time needed to generate the inputs that they require might prevent their use. We recently developed a new technique to estimate the dynamics of silk exsertion based on the perimeter of the silk bouquet. Our objectives were to extend this technique to estimate exserted silk numbers for six commercial inbred lines grown under typical seed production conditions, and to determine the minimum number of measurements needed to quantify their silking dynamics reliably. The correlation between the perimeter and silk number was consistently high across all the genotypes, explaining on average 99% of the variability in silk numbers. The average estimate error for silk exsertion was 2.6% when silks were sampled on four dates during silk exsertion. As the number of sampling dates decreased, the error estimate increased to 17.8%. Using a single regression model pooled across inbreds, the error estimate was about 10.1%. The technique is well suited to use in genotype characterization and modeling. The results indicate that the dynamic of silk exsertion can be estimated quickly and accurately under field conditions.