Evaluating Alternative Host Plant Use of Spotted Wing Drosophila, Drosophila suzukii

Evaluating Alternative Host Plant Use of Spotted Wing Drosophila, Drosophila suzukii

Summary

Spotted wing drosophila (SWD), Drosophila suzukii, a native of Asia, has emerged as a devastating pest of soft fruits. Since its first detection in California in 2008, SWD has spread throughout the U.S. causing significant yield losses and increased pesticide use at an estimated cost approaching $1 billion annually. Unlike most Drosophila species, SWD females oviposit primarily in ripening fruits, presenting a major threat to U.S. fruit industries. The presence of SWD can be viewed as a “game changer” to raspberry and blueberry production, as they have historically required very few insecticides and have the highest infestations, with yield losses often reaching 100%. Currently SWD management consists of insecticide applications on a 4-5 day schedule. Increased chemical inputs add substantial new costs to growing operations and increased risks to surrounding ecosystems, leading to numerous growers abandoning these crops. A major challenge with invasive species is often our lack of fundamental knowledge about their biology, dispersal activity or phenology. Broadening our understanding of these fundamental knowledge gaps is critical to implementing and refining sufficient and effective monitoring and management practices.

To address this issue and provide alternatives to chemical controls this project will:

1. Identify and evaluate non-crop host plants.
2. Correlate seasonal phenology of crop and non-crop hosts with SWD populations, and pesticide application timing.
3. Evaluate the impact of exclusion on raspberry pollinations and fruit quality. (Performed by other laboratory, see objective 3 section descriptions)

Our ultimate goal is to provide growers with information to control SWD while maintain a high level of fruit quality without the overreliance on disruptive insecticides, improving the sustainability of crop production throughout the region, directly addressing all three NCR-SARE broad-based outcomes.

Objectives/Performance Targets

Objective 1. Alternative hosts will be determined using methods similar to what is described by Lee et. al. (2015). A minimum of three common Minnesota invasive fruiting plants that have been reported as potential alternative hosts for SWD include: exotic honeysuckles (Lonicera tartarica, L. morrowii), wild black raspberry (Rubus occidentalis), and buckthorn (Rhamnus and Frangula spp.). These will be identified near plots of known host crops (raspberry and/or blueberry) from a minimum of five locations separated by a minimum of 400 meters, in Minnesota. Fruits and flowers will be collected from the field sites and incubated in the laboratory to determine larval infestation rates. Fruit will be collected once a week throughout the summer for each species. All sites will be within a 50-m radius of a crop host location known to have SWD. If sampling of one host occurs at multiple sites, every effort will be made to collect those samples on the same day. Data collected from each site will include date, location, number of fruits or flowers collected per plant species, and the condition of the fruit (unripe, ripe, or overripe). Sampling of berries will involve clipping the stem of the berry to avoid breaking or damaging the fruit.

Individual fruits will be placed in 30 to 89 ml plastic cups depending on fruit size. Cups will be sealed with a screened lid to reduce fungal growth. In some cases, a small cotton swab or sand layer will be added to the bottom of the container to absorb moisture. Cups will be kept in the laboratory at 21± 1˚C. Fruit will be held for a maximum of 18 days, and will be examined daily for the presence of adults. The percent of fruit with emerging adult SWD ([number of infested fruit/total number of fruit] X 100) and number of larvae per berry will be recorded.

SWD adult populations will be monitored in the field using commercially available Pherocon SWD lures and traps (Trécé, Inc.). A minimum of two traps will be set up at each location. Traps will consist of dual lures hanging from the lid of a Pherocon trap baited with 150 ml of apple cider vinegar and 0.2 ml of unscented dish soap (Seventh Generation, Inc.). Trap catches will be collected weekly. Bait solution will be replaced and trap contents removed when traps are being serviced. Trap contents will be analyzed in the laboratory and the number of male and female SWD recorded for each trap using a stereomicroscope. Lures will be replaced every 4 weeks, according to the manufacturer recommendations (Trécé, Inc.).

Objective 2. Beginning in early spring, we recorded which hosts retained fruit throughout the winter. We will collect fruit that overwintered and examine them for infestation as described in objective 1. We will monitor both crop and non-crop hosts weekly and record the phenology for each throughout the season. This will also be done with crop hosts blueberry and raspberry. Phenology will be recorded based on: presence of flower buds, flowering, unripe fruit, ripe fruit, and overripe fruit. Presence of adult SWD will also be monitored and recorded using the commercially available Pherocon SWD lures and traps (Trécé, Inc.) as described in objective 1. Seasonal phenology will be compared with crop, non-crop, and SWD and examined for correlation. Defining the phenology of hosts and pest is important in understanding how the pest is able to move rapidly through the landscape.

Objective 3. This is the original described proposal for our third objective. Fifteen experimental plots (10’L x 17’W) have been established with two rows each of raspberries (cv. ‘Heritage’) at the UMN Outreach, Research and Extension (UMORE) Park near Rosemount, MN. Starting in May during each study year, each plot will be randomly assigned to one of three treatments (n = 5 replicates / treatment) in a randomized block design: (1) ‘open’, (2) ‘high tunnel’, and (3) ‘high tunnel + netting’. Small portable “Hanley-style” high tunnels have been constructed with 10’L x 17’W x 7.5’H frames (reduced-size of the design outlined in Hams 2009) and covered with plastic tarp. In addition, for plots in the ‘high tunnel + netting’ treatment, a layer of Reemay mesh (fine horticultural mesh that excludes SWD) will be attached to the exterior of the high tunnel and buried at the edges. Starting at the time of enclosure establishment, SWD adult population levels will be monitored using using commercially available Pherocon SWD lures and traps (Trécé, Inc.), checked weekly. Sampling for larvae will be performed weekly using fruit dunk flotation tests. Finally, given the potential for netting to affect fruit productivity through increased temperature, temperature will be recorded across the growing season using digital thermometers (LaCrosse Technology, LaCrosse, WI).

Accomplishments/Milestones

Objective 1 and 2. Alternative hosts have been identified at each sampling site within Minnesota. Hosts found to incur infestations include: wild black raspberry (Rubus occidentalis), exotic honeysuckle (Lonicera morrowii, and Lonicera tatrica), and buckthorn (Rhamnus cathartica l.). Hosts found to not incur infestations include: wild strawberry (Fragaria vesca), wild plum (Prunus americana), and wild gooseberry (Ribes cynosbati). Evidence from this study suggests honeysuckle to be a preferred host in the alternative host category, giving way to raspberry as a preferred crop host later in the season. Previously unknown, D. suzukii is utilizing more than just crop hosts in the environment.

Plant variety did significantly alter the percent of infested fruit (p<0.0001); (Fig. 1) as did the time of sample (p<0.0081), but there was no interaction between variety and time (p<0.134). There was a significant negative correlation between the percent of infested fruit and sample date (p<0.001) with significantly fewer berries infested with later samples (Fig. 2).

Plant variety also had a significant impact on the average number of larvae per fruit (p<0.0001) (Fig 3); however, we also found that there was a significant impact of sample date (p<0.038) as well as an interaction between sample date and variety (p<0.0001) (Fig. 4). When each sample date was evaluated significant differences were detected between varieties on seven sample dates (Table 2; Fig. 4). Finally There was a significant negative correlation between the average number of larvae per fruit and sample (p<0.0001) with significantly fewer larvae per berry in later samples (Fig. 5).

Objective 2. Phenology was successfully recorded for both summers 2015 and 2016 for alternative host plants, crop host plants, and D. suzukii infestations. Early season (e.g. May) contains did not contain any fruit available for infestation. Each year, honeysuckle was the first host to be infested. There is potential to use honeysuckle as either an early warning system, or a management option. To what extent are SWD using alternative hosts?

Of the eight potential alternative hosts sampled, five of them were recorded to contain infested fruit (Table. 3). Both Lonicera species acquired the highest levels of infestations, while Rhamnus cathartica l. sustained the least with 0.15% of fruit infested in year 2015 (Table. 3). All three potential crop hosts held infestations typically higher than the alternative hosts (Table. 4). Fragaria vesca, Prunus Americana, and Ribes spp. did not sustain any infestations; therefore it is probable they cannot act as hosts for D. suzukii.

Infestation rates significantly differed between host plant types with Tukey-Kramer HSD statistical analysis with three levels: A, B, and C. Both Lonicera species and Rubus ideaus sustained highest infestations in level A with no significant difference between them, but significant differences over levels B and C (p-values < 0.0001) (Fig. 5). Level B contains Vaccinium corumbosum, Sambucus canadensis, and Rubus occidentalis (Fig. 5). There were no significant differences between these three hosts, however significantly different between the other levels (p-values < 0.017) (Fig. 5). Cornus racemose was the least infested host and significantly different from all other species (p-value <0.017) (Fig. 5).

Differences between infestations of non-crop hosts by month were explored using the ANOVA framework in JMP 2013 ®. In May, only wild locations were available and sampled. Non-crop hosts in the farm locations were infested at significantly greater rate in June (p-value < 0.0001) (Fig. 6). No significant difference between farm nor wild locations in the non-crop host plants were observed for July and August (p-value = 0.9753 and 0.3298 respectively) (Fig. 6). The early season higher infestation rates could be the population which leads to large crop host infestations.

Differences were observed between infestation rates for each host plant type. Each year, 2015 and 2016, Lonicera morrowii developed infestations at least one week before any other plant type (Fig. 7 and 8). Observable shifts in preferred host each week can be observed over time, with the greatest infestation rates between weeks eight and thirteen (Fig. 7). Highest infestation rates are seen in two of the three crop hosts: Rubus ideas and Vaccinium corumbosum (Fig. 7).

Phenologies varied greatly between non-crop host plants. Typically the bud and flowers can be found at week 1 progressing at different speeds afterwards (Fig. 8).  Lonicera morrowii and Cornus racemosa developed ripe fruit starting week 3, however, Lonicera morrowii produced infestations in its ripe fruit during its first week of bearing ripe fruit, while Cornus racemosa did not incur infestations until two weeks later (Fig. 8). Rubus occidentalis was the only non-crop host to become infested in its blush berries (Fig. 8). Cornus racemosa produced two ripening periods for its phenology, thus providing two opportunities where ripe and over ripe fruit were infested outside of the typical phenologies (Fig. 8).

First infestations for Rubus idaeus, Vaccinium corymbosum, and Sambucus canadensis appear in weeks 4, 7, and 9 respectively (Fig. 9). Past week 12, Vaccinium corymbosum and Sambucus canadensis are the only available hosts, leading to high, and in Sambucus canadensis increasing, infestations of ripe and over ripe berries (Fig. 9). Infestations of green fruit were recorded for Rubus idaeus and Vaccinium corymbosum with Rubus ideaus also sustaining infestations in blush berries (Fig. 9).

This work has already lead to one peer reviewed publication, The phenology of infestations and the impacts of different varieties of cold hardy red raspberries on Drosophila suzukii (Advances in Entomology 4, 183-190).

Objective 3. Immediately before beginning our field work on objective three we learned that another group at the University of Minnesota was focusing on using high tunnels and exclusion netting to manage SWD (see Rogers et al. 2016), with promising results. However, rather than duplicating efforts, we chose to focus our efforts on evaluating modification in management and the potential development of insecticide resistance.

In part one of this project, we set up in a randomized complete block design at the University of Minnesota North Central Research and Outreach Center in Grand Rapids, MN. Treatments included an untreated control, current spray practice (pyrethroid/spinosyn rotation), and the high and low rate of a new formula (Harvanta powered by cycloprene). Plots were sprayed on either a 5 or 7 day spray schedule. The 5 day schedule was sampled with 10 berries per treatment every 3 and 5 days after treatment (DAT). The 7 day schedule was sampled with 10 berries per treatment every 3, 5, and 7 DAT. Berries were placed in individual cups and held for 3 days. A brown sugar water solution was made as described by Beers et. al. (date) and larvae were counted and recorded. A portion of the berries were held for 2 weeks to confirm SWD identification. An analysis of variance (ANOVA) was performed in JMP statistical software.

Two objectives for this study were to determine differences in the timing of insecticide sprays in the percent and number of larvae of SWD infestations and to evaluate the new diamide chemical in regards to current practices. In terms of the timing efficacy for infested berries, no significant differences were observed, however between the treatments there was a difference. For the number of larvae per berry, significant differences were observed. Both the current practice and diamide high rate was more effective at the 7-day spray schedule with p values of 0.0001 and 0.0004 respectively. No differences were observed between 5 and 7 day sprays for the diamide low rate, however it was very consistent. The control had significantly more larvae per berries than the other treatments.

Because this pest requires such intensive management, and is part of a group of insect that has a propensity to rapidly develop resistance to numerous insecticides we wanted to develop a diet-incorporated assay for baseline toxicity and resistance monitoring. We are currently working to develop this new diet incorporate lab assay. To date, lethal concentrations for the most commonly used insecticides for SWD are unknown. Starting with highest field labeled rates, serial dilutions will be used with adult flies being exposed to each treatment.

Bioassays are planned for this spring and summer, 2017. Treatments will include: untreated control, delegate, and mustang. These studies will also be replicated using diet-incorporated assays. LC50s will be calculated from the serial dilutions and diet incorporated assays. LC50s and 95% confidence limits from bioassays will be analyzed with standard porbit analysis. Abbott’s formula will be used to correct for control mortality greater than 15%. Once lethal concentrations are determined, cohorts of flies will be exposed to these concentrations. Surviving flies will be mated and re-exposed to LC50 concentrations of each insecticide. This process will continue through 10 generations ate which time LC50s will be reevaluated. Diet incorporated assay will also allow us to evaluate the sublethal impact of each insecticide (e.g. sex ratio, oviposition deterrence effects, ect.).Graphs and tables for report

Impacts and Contributions/Outcomes

Learning outcomes:

Action outcomes: