Wind Tunnel and Field Evaluation of Trapping Efficiency of Semiochemical Baited Camera-Traps for Capturing Codling Moth (Lepidoptera: Tortricidae).

Sex pheromone baited monitoring traps are a critical tool for integrated pest management decisions against many insects, particularly codling moths (Cydia pomonella L.). The addition of cameras for remote monitoring has the potential to enhance the usefulness of these important tools. However, changes in trap design could potentially alter plume structure and trapping efficiency of these new traps. Here we look at several trap configurations designed to optimize the capture of codling moths in traps equipped with cameras. We found that, in both wind tunnel and field trials, camera equipped triangle traps and camera equipped rectangle traps (both V1 and V2) caught codling moths equivalent to a standard 'delta' style trap. While catch was unaffected, altering our rectangular trap opening from 4 to 8 cm (V1 and V2, respectively) decreased frequency of moths contacting the front of trap and increased the frequency of moths flying directly into the trap. We show that these novel camera equipped semiochemical-baited traps catch equivalent to the industry standard white delta trap.

High-resolution weather network reveals a high spatial variability in air temperature in the Central valley of California with implications for crop and pest management.

Weather is the most important driver of crop development. However, spatial variability in weather makes it hard to obtain reliable high resolution datasets across large areas. Most growers rely on data from a single station that can be up to 50km away to make decisions about irrigation, pest management and penology-associated cultural practices at the block level. In this regard, we hypothesize that kriging a large network of weather stations can improve thermal time data quality compared to using the closest station. This study aims to explore the spatial variability in California's Central Valley and what is the relationship between the density of weather stations used and the error in the measurement of temperature related metrics and derived models. For this purpose, we used temperature records from January 1st 2020 to March 1st 2021 collected by the California Irrigation Management Information System (CIMIS) and a system of 731 weather stations placed above the canopy of trees in commercial orchards (in-orchard). We observed large discrepancies (>300 GDDTb0) in thermal time accumulation between using an interpolation of all stations available and just using the closest CIMIS station. Our data suggests these differences are not systematic bias but true differences in mesoclimate. Similar results were observed for chill accumulation in areas especially prone to not meeting pistachio chill requirements where the discrepancies between using the site-specific in-orchard weather station network and not using them were up to 10 CP. The use of this high resolution network of weather stations revealed spatial patterns in grape, almond, pistachio and pests phenology not reported before. Whereas previous studies have been focused on predictions at the county or state or regional level, our data suggests that a finer resolution can result in major improvements in the quality of data crucial for crop decision making.