The Influence of Heat Analysis on the Hatching Rate of Lucilia Sericata (Diptera: Calliphoridae) Eggs Using Polynomial Regression Method

This study examines the effects of temperature on the hatching rates of Lucilia sericata, a species important for forensic entomology and medical biology. Using a polynomial regression approach, we investigated the relationship between extreme thermal conditions and egg emergence rates to provide insights that could enhance applications in postmortem interval (PMI) estimation and ecological modeling. Eggs were subjected to controlled temperature treatments ranging from $0^\circ\mathrm{C}$ to $41^\circ\mathrm{C}$ at $1^\circ\mathrm{C}$ intervals, maintaining 45% relative humidity. Observations were conducted at 24, 48, and 72-hour intervals, with additional incubation at $30^\circ\mathrm{C}$ for those subjected to extreme temperatures. Findings revealed no larval emergence at temperatures below $10^\circ\mathrm{C}$ or above $40^\circ\mathrm{C}$. However, within a $14^\circ\mathrm{C}$ to $38^\circ\mathrm{C}$ range, hatching rates reached their peak at $28^\circ\mathrm{C}$ (89.7%), indicating optimal developmental conditions. Our polynomial regression model demonstrated a high degree of accuracy ($R^2 > 0.70$) in predicting hatching rates across varying temperatures, thus establishing a predictive framework for forensic and ecological applications. The results emphasize the potential for this thermal modeling approach to enhance forensic entomological practices by providing refined developmental timelines for L. sericata, a species widely used in PMI estimation. The findings also underscore the species’ ecological sensitivity to temperature fluctuations, which may inform future ecological distribution models.