Fatty acid profile as an indicator of larval host for adult drosophila suzukii

Authors: WIMAN, NIK - Oregon State University; ANDREWS, HEATHER - Oregon State University; RUDOLPH, ERICA - Oregon State University; Lee, Jana; Choi, Man-Yeon

Submitted to: Insects
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/31/2020
Publication Date: 11/3/2020
Citation: Wiman, N.G., Andrews, H., Rudolph, E., Lee, J.C., Choi, M.Y. 2020. Fatty acid profile as an indicator of larval host for adult drosophila suzukii. Insects. 11(11). Article 752. https://doi.org/10.3390/insects11110752.
DOI: https://doi.org/10.3390/insects11110752

Interpretive Summary: Spotted-wing drosophila (SWD) is an economic pest of fruit crops. Management relies on killing adult females with insecticides to prevent damage resulting from egg laying and larval development. Fruits from crop and non-crop plants are used by the flies for reproduction at different times of the year, and knowledge of SWD seasonal plant use and movement could be helpful. SWD have been tracked for movement with various marking methodologies, including protein, dyes, and powder. In this study, we report on the potential to use the fatty acid profiles of adults SWD to determine what they fed on as larvae, and to use larval diet as an internal marker for adult flies in release-recapture experiments. Insects are limited in the ability to synthesize fatty acids and may acquire them through diet. Oftentimes, lipids acquired in the larval stage carry over to the adult stage. We tested the ability of a machine learning algorithm to discriminate adult SWD reared from susceptible small fruit crops (blueberry, strawberry, blackberry and raspberry) and laboratory diet based on the fatty acid profile of adult flies. We found that fatty acid components in adult flies were significantly different when flies were reared on different hosts, and the machine learning algorithm was highly successful in correctly classifying flies according to their larval host based on fatty acid profile.

Technical Abstract: Drosophila suzukii is a severe economic invasive pest of soft-skinned fruit crops. Management of this pest relies on killing gravid adult female flies with insecticides to prevent damage resulting from oviposition and larval development. Fruits from cultivated and uncultivated host plants are used by the flies for reproduction at different times of the year, and knowledge of D. suzukii seasonal host plant use and movement patterns could be better exploited to protect vulnerable crops. Various marking methodologies for tracking movement patterns of D. suzukii across different landscape scales have been used to better understand movement and habitat use of the pest. In this study, we report on potential to determine larval host for adult D. suzukii using their fatty acid profile or signature, and to use larval diet as an internal marker for adult flies in release-recapture experiments. Fatty acids can pass efficiently through trophic levels unmodified, and insects are constrained in the ability to synthesize fatty acids and may acquire them through diet. In many holometabolous insects, lipids acquired in the larval stage carry over to the adult stage. We tested the ability of a machine learning algorithm to discriminate adult D. suzukii reared from susceptible small fruit crops (blueberry, strawberry, blackberry and raspberry) and laboratory diet based on the fatty acid profile of adult flies. We found that fatty acid components in adult flies were significantly different when flies were reared on different hosts, and the machine learning algorithm was highly successful in correctly classifying flies according to their larval host based on fatty acid profile.