Abstract
Spotted-wing drosophila (Drosophila suzukii; SWD) is an invasive pest in the United States that is responsible for significant economic damage to soft-skinned fruit and berries worldwide. SWD uses a wide variety of cultivated and wild fruit for reproduction. Host suitability may depend on physical and chemical factors of the fruit, with a positive correlation of SWD oviposition and larval development generally associated with soluble sugar content, softer fruit, and higher pH, and a negative correlation of oviposition with fruit firmness. Variety selection is an important tool for integrated pest management, but few studies have reported host suitability across varieties within a single cultivated crop species for SWD. In this study, we investigated SWD oviposition and larval development in five half-high blueberry cultivars, Chippewa, Northblue, Northland, Patriot, and Polaris, using no-choice and two-choice laboratory bioassays. Using a host potential index, our results showed that Chippewa was the most preferred cultivar for oviposition as measured in the number of eggs laid per fruit, and Polaris was the least preferred. The inverse was true for larval development, with a higher survival rate and adult emergence in ‘Polaris’ than in ‘Chippewa’. There was a negative relationship between fruit firmness and oviposition and a positive correlation between pH and larval development. The results of this study indicate that cultivar selection for half-high blueberries may be a promising integrated pest management (IPM) tool, although further research under field conditions is needed for validation.
Spotted-wing drosophila (Drosophila suzukii; SWD) is an invasive insect in North America, South America, and Europe, and it is a significant pest to soft-skinned fruit and berries in these regions (Calabria et al. 2012; Deprá et al. 2014; Hauser 2011). Female SWD possess a serrated ovipositor, allowing them to deposit eggs inside ripe and ripening fruit (Atallah et al. 2014). After hatching from eggs, the larvae proceed to feed on the interior of the fruit, rendering it unmarketable (Walsh et al. 2011). SWD exhibit host use plasticity and use a wide variety of cultivated and wild fruit for reproduction (Bellamy et al. 2013; Lee et al. 2011).
Since SWD was first detected in the United States in 2008, numerous management tactics have been investigated and can contribute to an integrated pest management program for SWD (Tait et al. 2021). To combat SWD infestations, insecticide application (Gullickson et al. 2019; Haviland and Beers 2012; Sial et al. 2019; Van Timmeren and Isaacs 2013), increasing harvest frequency (Diepenbrock et al. 2017; Leach et al. 2018), exclusion netting (Cormier et al. 2015; Ebbenga et al. 2019; Leach et al. 2016; Rogers et al. 2016), and field sanitation and trapping programs (Hampton et al. 2014; Leach et al. 2018) have been researched and implemented, thus contributing to increased production costs (Farnsworth et al. 2017).
The economic impact of SWD on fruit crops varies by crop and region (Tait et al. 2021). Early research estimated that revenue losses from SWD infestations on raspberries, blackberries, blueberries, and strawberries are more than $500 million per year in California, Oregon, and Washington combined (Bolda et al. 2010; Walsh et al. 2011). However, more recent research found that SWD caused only $39.8 million in revenue losses for California raspberries between 2009 and 2014 (Farnsworth et al. 2017). For wild blueberries in Maine, which are likely more comparable in market size to that of the Upper Midwest, SWD infestations were found to cause revenue losses ranging from $1.1 to $6.9 million per year (Yeh et al. 2020). In Minnesota alone, raspberry losses caused by SWD in 2017 ranged from 2% to 100% for different farms, with the median yield loss equal to 20% and valued at approximately $2.36 million in sales (Digiacomo et al. 2019). The economic impact of SWD on blueberries in the Upper Midwest may be lower than that on raspberries because SWD prefers to oviposit in raspberries (Bellamy et al. 2013).
Cultivar selection has not been fully evaluated as an IPM strategy for SWD despite evidence of its efficacy against arthropod pests in several horticultural production settings. For example, Hampton et al. (2014) conducted a study of high-bush blueberry (V. corymbosum L.) cultivar susceptibility to SWD and found that rates of SWD infestation differed among cultivars (Hampton et al. 2014). Specifically, earlier-ripening cultivars had lower SWD infestations than later-ripening cultivars (Hampton et al. 2014). Similarly, Kamiyama and Geudot (2019) investigated the susceptibility of different tart cherry (Prunus cerasus L.) cultivars and found that the number of eggs and adults that emerged from tart cherry depended on the ripening state and cultivar interactions. Fruit of some cherry cultivars were more susceptible at the ripening or ripe stage compared with the unripe stage. Intriguingly, one cultivar, Kántorjánosi, had the most SWD oviposition, but it was among the lowest for adult emergence (Kamiyama and Guedot 2019). Finally, among mapping populations of strawberries, research has shown a positive correlation between methyl anthranilate and SWD oviposition preference (Bräcker et al. 2020).
Cultivar differences in host fruit suitability may depend on the physical and chemical factors of the fruit. Lee et al. (2011) reported positive correlations for SWD oviposition and larval development associated with soluble sugar content, softer fruit, and higher pH, and a negative correlation between oviposition and fruit firmness. Regarding table grapes (Vitis sp.), cultivars with higher sugar and lower acidity were more susceptible to SWD infestation (Ioriatti et al. 2015). In contrast, Ebbenga et al. (2021) observed successful SWD larval establishment in only six of the 34 cold-hardy grape varieties assessed in Minnesota, with some having less than 1% of berries infested. The diversity of SWD infestation results among highbush blueberries, tart cherries, and grapes suggests that there are differences among other fruit crops as well. Bellamy et al. (2013) developed a host potential index (HPI) to evaluate SWD preference and suitability among seven cultivated fruits. The HPI ranks fruits based on how often SWD selected them when compared with different fruit options. The number of times SWD selects a potential host compared with an alternative host is used to determine the preference proportions for that choice. The preference proportion values are averaged when the potential host has been tested against all the other hosts. This allows researchers to compare one cultivar to all others, rather than as an individual pairwise comparison, for example, to determine the most preferred host when host A is weakly preferred over host B, host B is weakly preferred over host C, but host C is strongly preferred over host A. Although Bellamy et al. (2013) did not investigate cultivar differences, this method may provide a valuable tool for determining SWD preferences among cultivars of a single fruit species.
Blueberries can be infested by SWD, but several studies suggest that SWD prefers other fruits, such as strawberries and raspberries over blueberries (Abraham et al. 2015; Bellamy et al. 2013; Lee et al. 2011b). Half-high blueberries (Vaccinium corymbosum/V. angustifolium), which are hybrid varieties of high-bush and low-bush blueberries (V. angustifolium Ait.), are popular in cold-climate regions because of their increased winterhardiness and greater yields compared with low-bush plants (Finn and Luby 1992). Early-ripening cultivars of high-bush blueberry can be harvested before SWD begin to oviposit, thus avoiding fruit damage (Hampton et al. 2014). The amount of SWD found on a Minnesota farm in half-high ‘Polaris’ was low for the first 3 weeks of harvest before 17 July, and significantly higher for the last 2 weeks of harvest (24 Jul and 30 Jul) (Gullickson, unpublished data). These data are similar to what was observed during previous research (Gullickson et al. 2020), but data for cultivar preference, phenological overlap of fruit development, and SWD oviposition timing for other half-high cultivars are lacking.
The objectives of this research were to determine the host preferences and suitability of different cultivars of half-high blueberries for SWD and whether SWD preference or suitability was correlated to the chemical (pH, total soluble solids) and physical (firmness) properties of the fruit. We hypothesized that there would be differences in SWD host preference and quality among the cultivars, and that differences may be explained by fruit physical and chemical properties. This information may contribute to the body of IPM research of SWD and provide growers with information about half-high blueberry cultivar preference and suitability for SWD.
Materials and Methods
Host no-choice assays.
Blueberries were harvested from the Sand Plain Research Farm of the University of Minnesota in Becker, MN (45°23′36.42″N, 93°52′36.3″W) and included five cultivars, Chippewa, Northblue, Northland, Patriot, and Polaris, with three replications or bushes of each cultivar chosen. Branches with berry clusters in the green–pink stage were netted for protection from SWD infestation and left to ripen in the field. Mature, bagged fruit was harvested from each plant. This was repeated twice for two harvests, 23 Jun and 6 Jul 2018. Individual berries were placed in lidded 37-mL containers (Frontier Agricultural Sciences, Newark, DE, USA) along with mated 3- to 5-day-old adult SWD (five male and five female) and kept in a growth chamber at 23 to 25 °C with a 16-h light and 8-h dark photoperiod and 47% relative humidity. Adults were removed after 24 h, and the number of eggs per fruit was counted. Individual berries were returned to their 37-mL containers and the growth chamber for an additional 14 d; thereafter, the numbers of larvae, pupae, and adult flies were counted and recorded for each sample. The survival rate was calculated based on the number of adult SWD at the end of 14 d divided by the number of eggs counted at 24 h, similar to the methods described by Aly et al. (2017).
Host choice assays.
In 2019, a series of two-choice tests between the aforementioned blueberry cultivars was conducted to determine relative preference in a choice setting. Individual berries were weighed to control for berry size, and only berries of the same weight were used for comparisons. Choice arenas consisted of two three-berry samples. Three berries of the same cultivar were placed in a clear 36-mL container (Frontier Scientific, Newark, DE, USA) labeled with the sample identifier, and two of these samples were placed in 946-mL semi-transparent plastic deli containers with lids (Choice Paper Company, Brooklyn, New York, NY, USA). Five mated female and five male SWD were introduced to the choice arenas, and flies had equal access to the three-berry samples. Each pairwise comparison combination of cultivars was replicated five times on two dates, providing choice comparisons between all berry cultivars (111 pairings per cultivar, except for Northland, which had 84 pairings because of lower fruit availability). After 24 h, adult fly preference (i.e., flies observed at 24 h after introduction as physically present on berries of a particular cultivar) was recorded, and adults were removed from the containers. The number of eggs was counted in individual berries.
Host potential index.
A modification of the host potential index created by Bellamy et al. (2013) was used to determine SWD host preferences and developmental suitability of different blueberry cultivars in both no-choice and two-choice settings. An example of calculating choice scores (C-scores) for SWD oviposition preference among five blueberry cultivars is provided in the Supplemental Methods. Preference proportions were determined, and then C-scores were calculated (Supplemental Table S1 and Supplemental Methods) to assign ranks (1–5 in order of most to least preferred) (Supplemental Table S2) to each cultivar following the methods described previously (Bellamy et al. 2013).
Fruit quality measurements.
Fruit firmness, measured as force in grams required to puncture the exocarp, used in host choice assays was measured in 2018–19 using a handheld FDK-32 penetrometer (Wagner Instruments, Greenwich, CT, USA) equipped with a 3-mm probe. Five different berries from each cultivar were tested at each harvest. A subsample of 250 g of harvested berries was homogenized and filtered through cheesecloth to obtain blueberry fruit juice for up to five samples for the total soluble solids (SS) and pH measurements. Three SS measurements were performed for each sample using a PAL-1 digital refractometer (Atago USA, Inc., Bellevue, WA, USA). The pH was also measured in 20 mL of this same juice for each subsample using an electronic pH and electrical conductivity meter (model mw802; Milwaukee Electronics, Milwaukee, WI, USA).
Statistical analyses.
Host no-choice oviposition data were assessed for normality of residuals before analysis using R statistical software (R Core Team 2020). Host no-choice oviposition data were analyzed with a negative binomial distribution, followed by an analysis of variance (ANOVA) and Tukey post hoc test using the MASS, car, and emmeans R packages (Fox and Weisberg 2019; Lenth 2022; Venables and Ripley 2002). The host choice data were only used to calculate C-scores and determine host preference rankings for the HPI equation (Eq. [1]).
The average HPI was determined based on mean HPI values (Eq. [1]) from our no-choice and two-choice measurements, excluding larval survival. The averageHPI assumes that oviposition preference, adult preference, and no-choice measurements are equally important for SWD host-finding decisions. To address this assumption, 30-iteration bootstrap-simulated weights for each HPI value for each cultivar were used to consider variations in weighting for each of the measurements (i.e., in case oviposition preference is a greater driver of behavior than adult preference). Three weighting values from a uniform distribution where the sum of the weighting values equaled 1 were randomly selected for Eq. [1]. Then, the mean HPI and 95% confidence interval for the simulated data were calculated. Data were analyzed using R Statistical Software (R Core Team 2020).
For blueberry fruit quality (firmness, SS, and pH) measurements, data fit the assumptions of normality; therefore, a one-way ANOVA followed by Tukey post hoc tests were used to determine differences in firmness among cultivars and between years. The 2018 data for SS was the only data measurement that was not normally distributed; therefore, a nonparametric Kruskal-Wallis test was used to determine whether there were differences in SS between years. A linear model was used to analyze the relationship between blueberry fruit firmness and the amount of SWD oviposition (number of eggs per berry), as well as the relationship between blueberry fruit pH and larval survival (proportion of eggs that reached adulthood).
Results
Host no-choice assays.
In the no-choice study, the number of SWD eggs laid in blueberries at 24 h after adult exposure was significantly different among cultivars (χ2 = 10.83; degrees of freedom = 4; P = 0.028). However, the Tukey post hoc analysis revealed no significant difference in the number of eggs at α = 0.05 (Table 1). ‘Northblue’ berries had the greatest number of eggs and ‘Polaris’ berries had the fewest number of eggs, but these differences were not significant. The five cultivars differed significantly in numbers of larvae, pupae, and adults 14 d after SWD exposure (χ2 = 13.76; degrees of freedom = 4; P = 0.008). ‘Patriot’ berries had the greatest number of SWD; its number of SWD was significantly different from that of ‘Northland’ berries, which had the lowest number of SWD. Berries of the other three cultivars had intermediate numbers of SWD; however, their numbers of SWD were not significantly different from those of Northland or Patriot (Table 1).
Host potential index (HPI) values of five cultivars of northern half-high blueberry (Vaccinium sp.) harvested from the Sand Plains Research Farm in Becker, MN, in 2018–19. Higher HPI values indicate spotted-wing drosophila (SWD), Drosophila suzukii (Matsumura), had a greater preference for the cultivar. Oviposition was measured as the number of eggs observed 24 h after mated pairs of adult SWD were introduced to berries. Total numbers of larvae, pupae, and adults were counted after 14 d of SWD introduction. In the two-choice tests, preference values were the average proportion of times that the cultivar had more oviposition, adult preference, and larval survival compared with other cultivars.
Host choice assays.
Oviposition and adult preference proportions among cultivars, C-scores, and calculated HPI values for each cultivar from the two-choice study are reported in Table 1. Patriot berries had the highest proportion of oviposition; however, based on the performance of all cultivars in a two-choice pairing (i.e., the C-score), SWD preferred to oviposit the most in Chippewa berries and the least in Polaris berries. In contrast, based on C-score results, adult SWD preferred ‘Polaris’ berries the most and ‘Patriot’ berries the least. ‘Chippewa’ and ‘Northland’ berries had lower adult SWD preference rates than ‘Polaris’ and ‘Patriot’ berries. Polaris berries had the greatest proportion (HPI = 303) of larval survival in the two-choice assay compared with the other cultivars, and Chippewa berries had the lowest proportion of larvae surviving to adulthood (HPI = 232).
Regarding the observed data, SWD least preferred ‘Northland’ berries (averageHPI = 246), whereas ‘Chippewa’ berries had the highest averageHPI score of 274.3. Regarding the simulated data, ‘Northland’ berries remained the least preferred by SWD and had an HPI 95% confidence interval of 245.55 to 248.3, and ‘Chippewa’ berries remained the most preferred, with an HPI 95% confidence interval of 271.26 to 277.95 (Fig. 1).
Simulated host potential index (HPI) values (30 simulated HPI values) for five northern half-high blueberry (Vaccinium sp.) cultivars. Red dashed lines indicate the mean HPI value for the cultivar. Red dotted lines illustrate the 95% confidence intervals (2 * SEM). Higher HPI values correspond to a greater preference by spotted-wing drosophila.
Citation: HortScience 58, 6; 10.21273/HORTSCI17097-23
Fruit quality.
The fruit characteristics of blueberry cultivars used in host choice assays were evaluated in 2018 and 2019. Year had a significant effect on fruit firmness, with fruit being firmer in 2018 than in 2019 (P < 0.0001) (Table 2). Firmness was also significantly different among cultivars (P = 0.009). ‘Polaris’ had the firmest fruit and was significantly different from the least firm ‘Northblue’. Fruit of the three remaining cultivars were not different from those of either Polaris or Northblue. Year did not influence fruit SS (P = 0.333). Additionally, fruit SS were not significantly different among cultivars (P = 0.792). Year had a significant effect on fruit pH, with fruit being less acidic in 2019 than in 2018 (P = 0.026). pH was also significantly different among cultivars (P < 0.0001), with Polaris fruit being significantly less acidic than those of the other four cultivars.
Mean (±SE) fruit firmness, total soluble solids (SS), and pH of fruit of five cultivars of half-high blueberry (Vaccinium sp.). Fruits were harvested in 2018–19 from the Sand Plains Research Farm in Becker, MN. Five replicate berries were measured for berry firmness (gf/mm2) for each cultivar. Five 250-g berry samples were juiced per cultivar, and aliquots of juice were used for SS (°Brix) and pH determinations.
There was a statistically significant negative relationship between blueberry fruit firmness and the amount of SWD oviposition (Fig. 2A) (adjusted R2 = 0.26; P = 0.0067). The number of eggs laid per blueberry decreased by a factor of 0.066 per unit increase of fruit firmness. Additionally, there was a statistically significant relationship between blueberry fruit pH and larval survival (proportion of eggs that reached adulthood) (Fig. 2B) (adjusted R2 = 0.20; P = 0.030). The proportion of eggs that survived to adulthood increased by a factor of 0.287 for every unit increase in blueberry fruit pH.
The effect of blueberry (Vaccinium sp.) fruit quality on spotted-wing drosophila (SWD), Drosophila suzukii (Matsumura) host suitability. (A) The amount of SWD oviposition (number of eggs/berry) as a function of blueberry fruit firmness (g force/mm2) (adjusted R2 = 0.2572; P = 0.007). Berries were harvested from the Sand Plains Research Farm in Becker, MN, and fruit firmness was measured on five berries of each cultivar. Other berries from the same harvests were used for host choice assays in which mated pairs of SWD were introduced to individual berries. (B) The proportion of SWD eggs that reached adulthood as a function of blueberry fruit pH (adjusted R2 = 0.1961; P = 0.030). Fruit pH was measured on 20 mL juice samples obtained from 250 g of berries. Mated pairs of SWD adults were introduced to individual berries, removed after 24 h, and counted after 14 d.
Citation: HortScience 58, 6; 10.21273/HORTSCI17097-23
Discussion
Cultivar selection is a useful tool for IPM, but few studies have reported host quality and preference across cultivars within a single cultivated crop species for SWD. In this study, we investigated SWD oviposition and larval development in five half-high blueberry cultivars, Chippewa, Northblue, Northland, Patriot, and Polaris, using no-choice and two-choice laboratory bioassays. We used the HPI developed by Bellamy et al. (2013) because it allows for comparisons across multiple hosts. Additionally, the HPI can include multiple variables of preference, such as oviposition and adult preference. Based on HPI, our results showed that Chippewa was the most preferred cultivar for oviposition measured in the number of eggs laid per fruit, and that Polaris was the least preferred in the two-choice tests. The inverse was true for larval development, with a higher survival rate and adult emergence in fruit of ‘Polaris’ than ‘Chippewa’, possibly indicating that intraspecific competition for host resources was occurring in ‘Chippewa’ fruit (Bezerra Da Silva et al. 2019).
The HPI values and preference ranks were generally consistent with direct measures of SWD cultivar preference, but there were some exceptions. For instance, ‘Patriot’ had a lower ranking (ranking of 2) than ‘Chippewa’ (ranking of 1) for the two-choice oviposition measurement, even though it had a higher preference probability than the direct measure (0.57 vs. 0.50). This was because SWD strongly preferred to oviposit in Patriot than in some cultivars, whereas SWD only moderately preferred Chippewa to all of the cultivars besides Patriot (see Supplemental Methods). Another aspect of the HPI that influenced the final result was the adult preference; Patriot was the least preferred cultivar and Chippewa was moderately preferred. These examples highlight the limitations of relying solely on pairwise comparisons and suggest that multichoice tests including all cultivars could provide a more comprehensive understanding of SWD preferences, although controlling for berry size and harvest date may be more challenging as the number of cultivars increase. The difference in SWD behavior preferences may be attributable to factors such as fruit volatiles (Keesey et al. 2015), microorganisms (Hamby et al. 2012), or macronutrient content (Silva-Soares et al. 2017), which could indicate whether a host is more suitable for ovipositing or foraging. Future studies could investigate whether differences exist among these blueberry cultivars, and whether they are correlated with SWD host suitability.
Blueberry characteristics that have been reported to affect SWD preferences include fruit flesh firmness and SS content (Lee et al. 2016). In fact, we observed a negative relationship between fruit firmness and oviposition and a positive correlation between pH and larval development. This supports previous laboratory and field experiment results observed by Lee et al. (2016), who found that SWD were more likely to oviposit as penetration force values decreased, and that pH increased in high-bush and rabbiteye blueberry fruit. The total SS content was less reliably related to oviposition probability than penetration force and pH (Lee et al. 2016). In two-choice assays involving blueberries, chokecherries, lingonberries, raspberries, and sea buckthorn fruit, Little et al. (2017) found that, considering all types of fruit and their characteristics, SWD preferred fruit with lower total SS content and lower pH. Of the half-high blueberries used in our comparisons, ‘Northland’ was the least and ‘Chippewa’ the most preferred by SWD (Table 1). These cultivars did not differ in firmness, total SS, or pH in 2018–19 (Table 2), suggesting that some other fruit characteristics, such as penetration force (not measured during this study), may influence SWD oviposition preference in half-high blueberries.
One physical characteristic that may have influenced SWD oviposition preference in the 2018 no-choice assay was berry size. Although fruits with similar weights were selected in the two-choice tests to minimize the influence of size between the two cultivars, berries from each cultivar in the no-choice test were randomly selected. A shortcoming of this study is that berry diameter was not controlled because we prioritized maximizing the number of replications and controlling for harvest date rather than diameter. This could have resulted in differences in SWD oviposition based on fruit size (e.g., larger fruits could have had more eggs) and potentially biased our results in the no-choice test. Studies suggest that fruit size is likely to influence oviposition, but reported data are lacking (Lee et al. 2016; Young et al. 2018).
SWD adults were observed on Polaris more than other cultivars despite this cultivar having the lowest amount of oviposition in the two-choice experiment. This may be because of differences in the quality of the fruits or volatile cues associated with the fruit. Cloonan et al. (2018) reported that female SWD attraction cues differ based on whether the individual is seeking food, mates, or an oviposition substrate. Future research could investigate microbial communities on the exterior of the fruit or metabolite differences among the berries with gas chromatography–mass spectroscopy to determine what role these characteristics may have in host-seeking behavior or larval nutrition (Deans and Hutchison 2021).
Conclusion
Our results showed that Chippewa was the most preferred cultivar for SWD oviposition as measured by the number of eggs laid per fruit, and Polaris was the least preferred. The inverse was true for larval development, with a higher survival rate and adult emergence in ‘Polaris’ than ‘Chippewa’, indicating that competition for host resources was occurring in ‘Chippewa’. As expected, there was an overall negative relationship between fruit firmness and oviposition and a positive correlation between pH and larval development. The results of this study indicate that cultivar selection for half-high blueberries may be a promising IPM tool; however, further research under field conditions is needed for validation.
References Cited
Abraham J, Zhang A, Angeli S, Abubeker S, Michel C, Feng Y & Rodriguez-Saona C. 2015 Behavioral and antennal responses of Drosophila suzukii (Diptera: Drosophilidae) to volatiles from fruit extracts Environ Entomol. 44 356 367 https://doi.org/10.1093/ee/nvv013
Aly MFK, Kraus DA & Burrack HJ. 2017 Effects of postharvest cold storage on the development and survival of immature Drosophila suzukii (Diptera: Drosophilidae) in artificial diet and fruit J Econ Entomol. 110 87 93 https://doi.org/10.1093/jee/tow289
Atallah J, Teixeira L, Salazar R, Zaragoza G & Kopp A. 2014 The making of a pest: The evolution of a fruit-penetrating ovipositor in Drosophila suzukii and related species Proc Biol Sci. 281 1 9 https://doi.org/10.1098/rspb.2013.2840
Bellamy DE, Sisterson MS & Walse SS. 2013 Quantifying host potentials: Indexing postharvest fresh fruits for spotted wing drosophila, Drosophila suzukii PLoS One. 8 https://doi.org/10.1371/journal.pone.0061227
Bezerra Da Silva CS, Park KR, Blood RA & Walton VM. 2019 Intraspecific competition affects the pupation behavior of spotted-wing drosophila (Drosophila suzukii) Sci Rep. 9 1 9 https://doi.org/10.1038/s41598-019-44248-6
Bolda MP, Goodhue RE & Zalom FG. 2010 Spotted wing drosophila: Potential economic impact of a newly established pest Agric. Resour. Econ. Updat. Univ. California. Giannini Found. 13 5 8 https://doi.org/10.1016/j.jff.2015.04.027
Bräcker LB, Gong X, Schmid C, Dawid C, Ulrich D, Phung T, Leonhard A, Ainsworth J, Olbricht K, Parniske M & Gompel N. 2020 A strawberry accession with elevated methyl anthranilate fruit concentration is naturally resistant to the pest fly Drosophila suzukii PLoS One. 15 e0234040 https://doi.org/10.1371/journal.pone.0234040
Calabria G, Máca J, Bächli G, Serra L & Pascual M. 2012 First records of the potential pest species Drosophila suzukii (Diptera: Drosophilidae) in Europe J Appl Entomol. 136 139 147 https://doi.org/10.1111/j.1439-0418.2010.01583.x
Cloonan KR, Abraham J, Angeli S, Syed Z & Rodriguez-Saona C. 2018 Advances in the chemical ecology of the spotted wing drosophila (Drosophila suzukii) and its applications J Chem Ecol. 44 922 939 https://doi.org/10.1007/s10886-018-1000-y
Cormier D, Veilleux J & Firlej A. 2015 Exclusion net to control spotted wing drosophila in blueberry fields IOBC WPRS Bull. 109 181 184
Deans C & Hutchison WD. 2021 The Protein Paradox: Elucidating the complex nutritional ecology of the invasive berry pest, spotted-wing drosophila (Diptera: Drosophila suzukii) Front. Insect Sci. 1 1 7 https://doi.org/10.3389/finsc.2021.787169
Deprá M, Poppe JL, Schmitz HJ, De Toni DC & Valente VLS. 2014 The first records of the invasive pest Drosophila suzukii in the South American continent J Pest Sci. 87 379 383 https://doi.org/10.1007/s10340-014-0591-5
Diepenbrock LM, Hardin JA & Burrack HJ. 2017 Season-long programs for control of Drosophila suzukii in southeastern U.S. blackberries Crop Prot. 98 149 156 https://doi.org/10.1016/j.cropro.2017.03.022
Digiacomo G, Hadrich J, Hutchison WD, Peterson H & Rogers M. 2019 Economic impact of spotted wing drosophila (Diptera: Drosophilidae) yield loss on Minnesota raspberry farms: A grower survey J Integr Pest Manag. 10 https://doi.org/10.1093/jipm/pmz006
Ebbenga DN, Burkness EC, Clark MD & Hutchison WD. 2021 Risk of spotted-wing drosophila injury and associated increases in acetic acid in Minnesota winegrapes Am J Enol Viticult. 72 106 112 https://doi.org/10.5344/ajev.2020.20008
Ebbenga DN, Burkness EC & Hutchison WD. 2019 Evaluation of exclusion netting for spotted-wing drosophila (Diptera: Drosophilidae) management in Minnesota wine grapes J Econ Entomol. 143 1 8 https://doi.org/10.1093/jee/toz143
Farnsworth D, Hamby KA, Bolda M, Goodhue RE, Williams JC & Zalom FG. 2017 Economic analysis of revenue losses and control costs associated with the spotted wing drosophila, Drosophila suzukii (Matsumura), in the California raspberry industry Pest Manag Sci. 73 1083 1090 https://doi.org/10.1002/ps.4497
Finn CE & Luby JJ. 1992 Inheritance of fruit quality traits in blueberry J Am Soc Hortic Sci. 117 617 621 https://doi.org/10.21273/jashs.117.4.617
Fox J & Weisberg S. 2019 An R companion to applied regression 3rd ed Sage Thousand Oaks, CA
Gullickson M, Hodge CF, Hegeman A & Rogers M. 2020 Deterrent effects of essential oils on spotted-wing drosophila (Drosophila suzukii): Implications for organic management in berry crops Insects. 11 1 12 https://doi.org/10.3390/insects11080536
Gullickson MG, Rogers MA, Burkness EC & Hutchison WD. 2019 Efficacy of organic and conventional insecticides for Drosophila suzukii when combined with erythritol, a non-nutritive feeding stimulant Crop Prot. 125 https://doi.org/10.1016/j.cropro.2019.104878
Hamby KA, Hernández A, Boundy-Mills K & Zalom FG. 2012 Associations of yeasts with spotted-wing Drosophila (Drosophila suzukii; Diptera: Drosophilidae) in cherries and raspberries Appl Environ Microbiol. 78 4869 4873 https://doi.org/10.1128/AEM.00841-12
Hampton E, Koski C, Barsoian O, Faubert H, Cowles RS & Alm SR. 2014 Use of early ripening cultivars to avoid infestation and mass trapping to manage Drosophila suzukii (Diptera: Drosophilidae) in Vaccinium corymbosum (Ericales: Ericaceae) J Econ Entomol. 107 1849 1857 https://doi.org/10.1603/EC14232
Hauser M. 2011 A historic account of the invasion of Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) in the continental United States, with remarks on their identification Pest Manag Sci. 67 1352 1357 https://doi.org/10.1002/ps.2265
Haviland DR & Beers EH. 2012 Chemical control programs for Drosophila suzukii that comply with international limitations on pesticide residues for exported sweet cherries J Integr Pest Manag. 3 1 6 https://doi.org/10.1603/IPM11034
Ioriatti C, Walton V, Dalton D, Anfora G, Grassi A, Maistri S & Mazzoni V. 2015 Drosophila suzukii (Diptera: Drosophilidae) and its potential impact to wine grapes during harvest in two cool climate wine grape production regions J Econ Entomol 108 1148 1155 https://doi.org/10.1093/jee/tov042
Kamiyama MT & Guedot C. 2019 Varietal and developmental susceptibility of tart cherry (Rosales: Rosaceae) to Drosophila suzukii (Diptera: Drosophilidae) J Econ Entomol. 112 1789 1797 https://doi.org/10.1093/jee/toz102
Keesey IW, Knaden M & Hansson BS. 2015 Olfactory specialization in Drosophila suzukii supports an ecological shift in host preference from rotten to fresh fruit J Chem Ecol. 41 121 128 https://doi.org/10.1007/s10886-015-0544-3
Leach H, Moses J, Hanson E, Fanning P & Isaacs R. 2018 Rapid harvest schedules and fruit removal as non-chemical approaches for managing spotted wing drosophila J Pest Sci. 91 1 8 https://doi.org/10.1007/s10340-017-0873-9
Leach H, Van Timmeren S & Isaacs R. 2016 Exclusion netting delays and reduces Drosophila suzukii (Diptera: Drosophilidae) infestation in raspberries J Econ Entomol. 109 2151 2158 https://doi.org/10.1093/jee/tow157
Lee JC, Bruck DJ, Curry H, Edwards D, Haviland DR, Van Steenwyk RA & Yorgey BM. 2011 The susceptibility of small fruits and cherries to the spotted-wing drosophila, Drosophila suzukii Pest Manag Sci. 67 1358 1367 https://doi.org/10.1002/ps.2225
Lee JC, Dalton DT, Swoboda-Bhattarai KA, Bruck DJ, Burrack HJ, Strik BC, Woltz JM & Walton VM. 2016 Characterization and manipulation of fruit susceptibility to Drosophila suzukii J Pest Sci. 89 771 780 https://doi.org/10.1007/s10340-015-0692-9
Lenth RV. 2022 emmeans: Estimated marginal means, aka least-squares means R package version 1.7.3
Little CM, Chapman TW, Moreau DL & Hillier NK. 2017 Susceptibility of selected boreal fruits and berries to the invasive pest Drosophila suzukii (Diptera: Drosophilidae) Pest Manag Sci. 73 160 166 https://doi.org/10.1002/ps.4366
R Core Team 2020 R: A language and environment for statistical computing
Rogers MA, Burkness EC & Hutchison WD. 2016 Evaluation of high tunnels for management of Drosophila suzukii in fall-bearing red raspberries: Potential for reducing insecticide use J Pest Sci. 89 815 821 https://doi.org/10.1007/s10340-016-0731-1
Sial AA, Roubos CR, Gautam BK, Fanning PD, Van Timmeren S, Spies J, Petran A, Rogers MA, Liburd OE, Little BA, Curry S & Isaacs R. 2019 Evaluation of organic insecticides for management of spotted-wing drosophila (Drosophila suzukii) in berry crops J Appl Entomol. 143 593 608 https://doi.org/10.1111/jen.12629
Silva-Soares NF, Nogueira-Alves A, Baldade P & Mirth C. 2017 Adaptation to new nutritional environments: Larval performance, foraging decisions, and adult oviposition choices in Drosophila suzukii BMC Ecol. 17 1 13 https://doi.org/10.1186/s12898-017-0131-2
Tait G, Mermer S, Stockton D, Lee J, Avosani S, Abrieux A, Anfora G, Beers E, Biondi A, Burrack H, Cha D, Chiu JC, Choi MY, Cloonan K, Crava CM, Daane KM, Dalton DT, Diepenbrock L, Fanning P, Ganjisaffar F, Gómez MI, Gut L, Grassi A, Hamby K, Hoelmer KA, Ioriatti C, Isaacs R, Klick J, Kraft L, Loeb G, Rossi-Stacconi MV, Nieri R, Pfab F, Puppato S, Rendon D, Renkema J, Rodriguez-Saona C, Rogers M, Sassù F, Schöneberg T, Scott MJ, Seagraves M, Sial A, Van Timmeren S, Wallingford A, Wang X, Yeh DA, Zalom FG & Walton VM. 2021 Drosophila suzukii (Diptera: Drosophilidae): A decade of research towards a sustainable integrated pest management program J Econ Entomol. 114 1950 1974 https://doi.org/10.1093/jee/toab158
Van Timmeren S & Isaacs R. 2013 Control of spotted wing drosophila, Drosophila suzukii, by specific insecticides and by conventional and organic crop protection programs Crop Prot. 54 126 133 https://doi.org/10.1016/j.cropro.2013.08.003
Venables WN & Ripley BD. 2002 Modern applied statistics with S 4th ed Springer New York, NY, USA
Walsh DB, Bolda MP, Goodhue RE, Dreves AJ, Lee J, Bruck DJ, Walton VM, O’Neal SD & Zalom FG. 2011 Drosophila suzukii (Diptera: Drosophilidae): Invasive pest of ripening soft fruit expanding its geographic range and damage potential J Integr Pest Manag. 2 G1 G7 https://doi.org/10.1603/IPM10010
Yeh DA, Drummond FA, Gómez MI & Fan X. 2020 The economic impacts and management of spotted wing drosophila (Drosophila suzukii): The case of wild blueberries in Maine J Econ Entomol. 113 1262 1269 https://doi.org/10.1093/jee/toz360
Young Y, Buckiewicz N & Long TAF. 2018 Nutritional geometry and fitness consequences in Drosophila suzukii, the spotted-wing drosophila Ecol Evol. 8 2842 2851 https://doi.org/10.1002/ece3.3849
Supplemental Material S1.
Steps for calculating C-scores used for ranking blueberry cultivars (two-choice oviposition will be used as an example). This method is based on Bellamy et al. (2013).
Create a preference table for all the tested hosts with the number of times that host a was preferred over host b, host b was preferred over host a, and the number of times that there was equal preference. Columns are the a values and rows are the b values.
Apply Supplemental Eq. [1] to each tested host to determine the preference probability:
Supplemental equation 1: Aa = (Pa+0.5Ta)/n
Aa is the actual preference probability from the recorded data, Pa is the number of choice-pairs that the cultivar won, Ta is the number of ties between the two cultivars, and n is the number of choice-pairs.
The table reports the preference probabilities that the column blueberry variety was preferred over the row blueberry variety. The overall preference probability is the averaged preference probability for that variety.
Determine the calculation order for Eqs. [2] and [3] in steps 4 and 5, respectively. The calculation order is from the greatest preference probability to the lowest preference probability.
Calculate the expected preference.
Expected preference Supplemental Equation 2: Ea = 1/(1 + 10(Cb-Ca/400)). Cb is the C-score of host b and Ca is the C-score of host a. The expected preferences are determined as C-scores are calculated here. The initial C-score is 900.
Calculate C-scores for host 1.
Supplemental Equation 3
Calculate C-scores for host n
C-scores, ranks, and Host Potential Index (HPI) values for the oviposition preference of SWD for five blueberry cultivars:
Reference Cited
Bellamy DE, Sisterson MS & Walse SS. 2013 Quantifying host potentials: Indexing postharvest fresh fruits for spotted wing drosophila, Drosophila suzukii PLoS One. 8 4 https://doi.org/10.1371/journal.pone.0061227
C-scores and corresponding K-factors.
Host Potential Index.