Developing a growing degree day model to guide integrated pest management of Eucosma giganteana, a pest of a novel perennial oilseed crop

Authors: SCRIBNER, HAZEL - Animal And Plant Health Inspection Service (APHIS); MURRELL, EBONY - The Land Institute; CHEREMOND, NERVAH - The Land Institute; Abshire, Jennifer; CASTALDI, JOSEPH - Kansas State University; ZHU, KUN YAN - Kansas State University; Morrison Iii, William

Submitted to: Journal of Economic Entomology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/31/2025
Publication Date: N/A
Citation: N/A

Interpretive Summary: Yellow silflower is being domesticated as an alternate oilseed crop to sunflower in Kansas. Eucosma giganteana, or the giant Eucosma moth, is a pest on yellow silflower, and a major limiting factor to the development and commercialization of the new crop. A key challenge towards preventing damage caused by this moth is knowing when they are active in the field. Our objectives were to determine when moths become active in spring, then use that knowledge to develop a model to estimate first appearance of moths in the field, peak of flight activity, and end of flight activity. We determined that insects become active at 17°C and that it takes about 1608, 1872, and 2947 growing degree days for initial moth appearance, peak flight, and end of flight. Ultimately, the model was able to accurately predict moth emergence in the field during 2024. We anticipate the model will continue to provide accurate predictions for the coming years, which would allow for improved timing of pest management practices to be implemented.

Technical Abstract: Eucosma giganteana, or the giant Eucosma moth, is a specialist pest on Silphium spp. including Silphium integrifolium. This pest is currently one of the major limiting factors to the development and commercialization of S. integrifolium in Kansas as a more sustainable oilseed alternative within its native range. One of the factors making E. giganteana difficult to manage is the lack of knowledge about when pest management tactics should be applied for maximum effect. To aid with proper timing, our objectives were to determine a lower activity threshold, then use it to develop a growing degree day model to estimate important phenological events in the life history of adult E. giganteana in the field. In addition, we found a good fit between the actual phenological events for E. giganteana from 2020, 2023, and 2024 and the predicted phenological events from trapping data collected in 2019 in Salina Kansas. The lower activity threshold was determined to be 17°C using a series of environmental chamber experiments with overwintering E. giganteana larvae. Furthermore, we found a significant correlation between predicted growing degree days for phenological events in 2019 and the actual degree day measurements for those events in subsequent years. Finally, the model was able to accurately predict adult E. giganteana emergence in the field during 2024. We anticipate the model will continue to provide accurate predictions for the coming years, which would allow for improved timing of pest management practices for E. giganteana to be implemented.