Spectral Signatures of Immature Lucilia sericata (Meigen) (Diptera: Calliphoridae).
Hyperspectral remote sensing is an innovative technology with applications in many sciences and is a non-destructive method that may offer more precise aging within development stages. Hyperspectral reflectance measurements from the anterior, midsection, and posterior ofLucilia sericata(Meigen) larvae and pupae were conducted daily from samples of the developing insects beginning at second instar. Only midsection measurements were conducted on second instar larvae due to their size, to ensure that the measurement was not of reflective surroundings. Once measured, all insects were washed with deionized water, blotted with filter paper, and re-measured. Daily age prediction during the post-feeding stage was not impacted by the unwashed insect measurements and was best predicted based on posterior measurements. The second and third instar larvae, which move about their food source, had different contributing coefficients to the functional regression model for the hyperspectral measurements of the washed compared with unwashed specimens. Although washing did not affect the daily prediction within these stages, it is still encouraged in order to decrease the effect of food source on spectral reflectance. Days within the intra-puparial period were best predicted based on anterior measurements and were not well distinguished from one another in the first few days based on midsection and posterior measurements.
School of Criminology, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. jwarren@sfu.ca.
Jodie-A
JA
Warren
Department of Statistics and Actuarial Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. ganderso@sfu.ca.
T D Pulindu
TD
Ratnasekera
Department of Statistics and Actuarial Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. pratnase@sfu.ca.
David A
DA
Campbell
School of Criminology, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. dac5@sfu.ca.
Gail S
GS
Anderson
Lucilia sericata; coefficient; functional regression; hyperspectral; reflectance; remote sensing; wavelength