Forecasting the seasonal phenology of Agrotis ipsilon in Oregon grass seed and vegetable agroecosystems
(Lepidoptera: Noctuidae) is a significant pest in Oregon grass seed and vegetable production systems. Effective management of this species relies on timely foliar insecticide applications targeting immature larvae before crop damage is observed. Regionally specific phenological models serve as a cri...
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Veröffentlicht in: | Frontiers in insect science 2024, Vol.4, p.1505524 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | (Lepidoptera: Noctuidae) is a significant pest in Oregon grass seed and vegetable production systems. Effective management of this species relies on timely foliar insecticide applications targeting immature
larvae before crop damage is observed. Regionally specific phenological models serve as a critical component of effective areawide pest management plans to inform the timing of pest monitoring and management action. Seasonal modeling of
phenology is complicated by their migratory behavior and limited knowledge of temperature-dependent development on affected crop hosts. Growth chamber experiments at five constant temperatures (12 to 32°C) were conducted to determine the temperature-dependent development of
life stages on an artificial and perennial ryegrass diet. The completion of one
generation (egg-to-adult) required 658.71 ± 31.49, 601.98 ± 16.01, 648.47 ± 21.35 degree days with a base temperature threshold of 9.8°C for artificial diet, perennial ryegrass diet, and across both diet types, respectively. The timing of migrant adults was predicted with surface air temperature using non-linear regression with
abundance data collected from pheromone-baited traps in 77 total commercial grass seed (n = 57) and vegetable (n = 20) production fields across 19 sampling years (1996 to 2023). Developmental parameters and predictions of adult arrival were used to develop general and grass seed specific phenology model projections for
populations in Oregon. Regionally validated phenology models can be incorporated into decision support tools to forecast the spatiotemporal occurrence of crop-damaging life stages of priority insect pests. |
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ISSN: | 2673-8600 2673-8600 |
DOI: | 10.3389/finsc.2024.1505524 |