Comparative analysis of drop mass variance for manual and automatic delivery of large-scale eye drop poultry vaccine.

The delivery of ocular vaccines in the poultry industry is a crucial challenge, where manual eye-drop administration is prone to user-dependent variation. This leads to significant vaccine waste, increased labor costs, and potential health risks to animals. Employing robust statistical modeling, we aimed to compare a novel automated dropper apparatus against conventional methods under various influencing factors. Through multi-linear regression, we identified dispensing angle and inconsistent manual pressure as primary sources of drop mass variability in conventional systems. For flat-tip droppers, decreasing the dispensing angle led to smaller drops, while for round-tips, a tilted position (45°) altered drop mass significantly due to lateral wetting. We also demonstrated that remaining volume of the bottle could not explain the variability in drop mass, evidenced by near-zero R-squared values in regression models regardless of preparation or dispensing rate. The automated dropper exhibited superior performance, reducing drop mass standard deviation by 1.32 to 1.23 mg compared to manual methods ensuring both consistent dosing and minimizing waste. These lower standard deviations were particularly noticeable when compared to alternative dispensing techniques. These findings underscore the potential of automated systems to enhance accuracy and consistency in large-scale eye-drop poultry vaccine delivery.