Abstract

We evaluated the effect of postharvest cold storage temperature (0.0–2.2°C) and duration (3–5 d) on pupal emergence of single life stage populations of laboratory-generated Drosophila suzukii (Matsumura) and mixed-age populations collected in the field from blackberries, blueberries, strawberries, and raspberries. For field-infested fruit, cold storage at any temperature and duration resulted in less pupal emergence compared with the control held at 20°C, but D. suzukii subjected to higher temperatures and shorter storage durations in caneberries had higher survival. When a single life stage of D. suzukii was exposed to cold storage, pupal emergence was significantly reduced across all fruit types held at 0°C and for most life stages and fruit types held at 1.5 and 2.2°C, dependent on the substrate. Freshly laid eggs exposed to cold storage produced the lowest pupal emergence. Our results suggest using cold storage treatment is an effective postharvest management strategy for small-fruit growers to use on-farm as part of an integrated program to manage D. suzukii infestation. An economic assessment was made to examine the profit implications of an investment in cold storage units to counter pest pressure. Results suggest that investment in a cold storage unit would breakeven in about 4 yr. On farms that already have cold storage installed, we estimated a $0.11/kg decrease in blueberry market price for holding fruit for 3 d. Together, this cost assessment will provide growers with the knowledge to make decisions based on infestation risk and the seasonal sale price of blueberries.

The prevalence of invasive species around the world is increasing due to greater global shipping of goods (Westphal et al. 2008, Hulme 2009). Originally from east Asia, Drosophila suzukii (Matsumura), or spotted-wing drosophila, is believed to be one such species, first detected in North America and Europe in 2008 (Dreves et al. 2009, Calabria et al. 2012, Cini et al. 2012), and South America in 2014 (Deprá et al. 2014). Drosophila suzukii differs from other members of its genus in that its terminal abdominal segment is adapted to serve as a serrated, heavily sclerotized ovipositor used to lay eggs just under the skin surface of ripening soft-skinned small fruit (Atallah et al. 2014). Quality control checks conducted by fruit wholesale marketers most commonly use visual inspection and salt extraction, where ripe fruit is placed in a salt-water solution to draw out any living larvae (Van Timmeren et al. 2017). There is zero tolerance for any larvae found in fruit by purchasers (Bruck et al. 2011, Van Timmeren and Isaacs 2013).

Drosophila suzukii management relies on insecticide application (Bruck et al. 2011, Van Timmeren and Isaacs 2013) but also integrates other preharvest strategies such as pruning to reduce humid microclimate within the fruiting plant structure (Diepenbrock and Burrack 2017), adult trapping to detect fly presence and abundance (Landolt et al. 2012, Burrack et al. 2015), and thorough and frequent picking to reduce the time fruit are exposed to egg laying flies (Diepenbrock and Burrack 2017). Despite this suite of practices, growers still routinely experience D. suzukii infestation, particularly in preferred hosts such as blackberries and raspberries and in fruit which ripen late in the growing season (Diepenbrock et al. 2017). There is also increasing concern about insecticide resistance in D. suzukii on the West Coast of the United States (Smirle et al. 2017, Gress and Zalom 2019).

Because of their protected feeding niche and small size, it is possible for eggs and small larvae to remain undetected in harvested fruit, risking potential detection by purchasers or resulting in further spread. Postharvest handling practices have the potential to affect these immature D. suzukii and to potentially salvage a crop with low-level infestation as part of an integrated pest management program. Postharvest strategies for other internally feeding fruit pests include irradiation (Follett et al. 2007, 2014; Kiran et al. 2019), chemical treatment (Zettler and Arthur 2000, Walse et al. 2012), heat treatment (Jacobi et al. 2001, Wang et al. 2006), or cold storage (Sharp 1993, Dentener et al. 1997, Saour et al. 2012), and these have been used successfully in controlling codling moth (Wang et al. 2006), Bactrocera fruit fly (Hoa et al. 2006), and coffee berry borer beetle (Kiran et al. 2019). Cold storage as a postharvest practice is usually applied to crops that themselves tolerate extended cold storage periods and is often associated with quarantine and phytosanitary measures (Sharp 1993, Dentener et al. 1997, Kim et al. 2018), though it can also make up part of an integrated pest management system as in potatoes (Saour et al. 2012). Recent studies have suggested the use of cold storage as part of a pest management system for D. suzukii in blueberries and raspberries (Aly et al. 2017).

Drosophilidae as a group are highly susceptible to cold temperatures (Strachan et al. 2011). An evolutionary study across Drosophilidae found that chill susceptibility is likely the ancestral state based on its widespread distribution within this group of vinegar flies based on their Afro-tropical origins from which they have only recently diverged (Rajamohan and Sinclair 2008, Strachan et al. 2011). Additional studies showed that subjecting Drosophila melanogaster larvae to zero and subzero temperatures causes high levels of mortality (Lee et al. 1987; Czajka and Lee 1990; Rajamohan and Sinclair 2008, 2009; Koštál et al. 2011). A significant amount of research has focused on the mechanism of cold shock and adaptations in D. melanogaster (Rako and Hoffmann, 2006, Yi et al. 2007, Rajamohan and Sinclair 2008, Koštál et al. 2011). Recent work has addressed cold hardiness of adult winter-adapted (wintermorph) D. suzukii (Jakobs et al. 2015; Stephens et al. 2015; Wallingford and Loeb, 2016; Stockton et al. 2018, 2019). When similar phenotypic plasticity was induced in third-instar larvae of D. suzukii, the larvae remained chill-susceptible and died at temperatures above freezing (Jakobs et al. 2017). Our work differs in that we harness this chill-susceptible biology in an applied setting by using cold storage postharvest treatment on non cold-acclimatized immature D. suzukii, similar to those that may be present in harvested fruit.

Previous studies of the effects of potential postharvest cold storage temperature and duration have been conducted on D. suzukii and demonstrated that cold temperatures (1.1, 3.9, and 5.0°C) and longer durations (up to 72 h) may result in longer developmental times and decreased survivorship (Aly et al. 2017). This study focused on testing flies in artificial diet at all temperatures and durations and then focused on only the coldest temperature and maximum duration to test in sound blueberry and raspberry fruits (Aly et al. 2017). Results from the study by Aly et al. showed that cold storage had potential to decrease survivorship of D. suzukii within the two berry types tested but did not include other small fruits attacked by D. suzukii. This study also did not achieve total mortality of D. suzukii within fruit. We expanded on this work to assess colder temperatures and longer durations for each blueberries, strawberries, blackberries, and raspberries. Additionally, we harvested infested fruit from fields that putatively had a mixture of immature D. suzukii stages and subjected that fruit to storage at the same temperatures and durations. Together, these results further inform recommendations for postharvest cold storage practices for fruit potentially infested with D. suzukii.

Materials and Methods

Single Life Stage Comparisons

Insects used for single life stage comparison experiments were derived from a colony first started in 2010 from D. suzukii collected at Upper Mountain Research Station near Laurel Springs, NC. Since that time, wild D. suzukii have been periodically added to the colony to maintain genetic diversity. This colony is raised on a cornmeal-based diet (Hardin et al. 2015) and maintained at 20°C, 65% humidity with a 12 (L:D) h cycle. All flies used for this experiment were between 4 and 11 d old to ensure reproductive maturity. Laboratory infestation was conducted under the same temperature and humidity conditions as used for the colony.

We purchased organically grown strawberries, blueberries, blackberries, and raspberries for use in single life stage comparison experiments and infested them the same day of purchase. Pesticides certified for use in organic cropping systems have shorter residual activity and are less likely to confound laboratory experiments. Fruit were placed in eight separate 0.3 m × 0.3 m × 0.3 m mesh cages (BioQuip Collapsible Cage 1450B, Rancho Dominguez, CA) and exposed to 200–250 mixed sex, reproductively mature D. suzukii for 6 h for caneberries and 12 h for blueberries and strawberries, based on host suitability, to ensure a thorough infestation. Fruit sufficient for the necessary replication were placed in cages and later subdivided and randomly assigned to treatment groups after a sample of fruit were observed under a stereomicroscope to confirm sufficient egg presence after adult exposure.

Following infestation, fruit were placed into plastic rectangular containers with mesh bottoms to allow juice from fruit decay to drain out. Each container was considered a treatment replicate, and each treatment was replicated four times except for the strawberry 2.2°C treatment, which was replicated three times due to low infestation rates. Strawberry treatments had 100-g fruit per container. Blueberry treatments had 50 g/container, and caneberry treatments received 40 g/container. Depending on the size of the fruit, this was between 4 and 7 strawberries, approximately 40 blueberries, or 8–12 blackberries or raspberries per container.

Fruit were then held at 20°C until >90% of immature D. suzukii reached the target life stage (durations indicated in Tables 36) based on preliminary experiments in which fruit was infested and held at 20°C (see Supp Material [online only]). In these preliminary experiments, we dissected 8–10 pieces of infested fruit daily and recorded the stage of all immature D. suzukii present.

Target life stages were egg (immediately following infestation), old egg (1- or 2-d-old eggs depending on fruit type), first-instar larvae, second-instar larvae, and third-instar larvae. Old-egg treatments were established to determine the effect of egg age following preliminary experiments indicating significant variability between egg and first instar. Once fruit within a container were determined to have reached the desired life stage, that treatment was placed into cold storage. Fruit were exposed to 0°C or either 1.5°C (caneberries) or 2.2°C (blueberries and strawberries) for either 3, 4, or 5 d, after which time, samples were returned to 20°C until larvae within completed development and checked every other day for pupal emergence to determine survivorship. The difference in temperature for caneberries versus strawberries and blueberries was based on availability of cold storage units. A HOBO data logger was set inside the cold storage units to monitor temperature.

All pupae were removed and held till adult emergence. For all treatments, four replicates of fruit were subjected to infestation by the same age flies at the same time and then held at 20°C until pupal emergence as a control.

Field-Infested Assay

We sought to determine the effect of postharvest cold storage on survivorship of mixed-age natural fly infestations. Fruit were collected from untreated plantings at North Carolina State University and North Carolina Department of Agriculture and Consumer Services research stations (Table 1). After collection, fruit was immediately placed in plastic rectangular containers with a mesh bottom to allow liquid to drain. Then, fruit was directly transferred into cold storage at 0 or 2.2°C for 3, 4, or 5 d. A HOBO data logger was set inside the cold storage units to monitor temperature.

Table 1.

Fruit sourcing and method preparation

Fruit typeDate collectedLocationFruit per replicateNumber of replicates per treatmentExposure temperatures
Strawberries14 June 2018Central Crops Research Station, Clayton, NC10 berries40°C, 2.2°C
Blueberries30 July 2018Sandhills Research Station, Jackson Springs, NC15 berries40°C, 2.2°C
Blackberries19 July 2018Piedmont Research Station, Salisbury, NC15 berries40°C, 2.2°C
Raspberries11 Sept. 2018Upper Mountain Research Station, Laurel Springs, NC14 ga32.2°C
Fruit typeDate collectedLocationFruit per replicateNumber of replicates per treatmentExposure temperatures
Strawberries14 June 2018Central Crops Research Station, Clayton, NC10 berries40°C, 2.2°C
Blueberries30 July 2018Sandhills Research Station, Jackson Springs, NC15 berries40°C, 2.2°C
Blackberries19 July 2018Piedmont Research Station, Salisbury, NC15 berries40°C, 2.2°C
Raspberries11 Sept. 2018Upper Mountain Research Station, Laurel Springs, NC14 ga32.2°C

aDue to fragile nature of highly infested raspberries, we divided samples based on mass rather than fruit number.

Table 1.

Fruit sourcing and method preparation

Fruit typeDate collectedLocationFruit per replicateNumber of replicates per treatmentExposure temperatures
Strawberries14 June 2018Central Crops Research Station, Clayton, NC10 berries40°C, 2.2°C
Blueberries30 July 2018Sandhills Research Station, Jackson Springs, NC15 berries40°C, 2.2°C
Blackberries19 July 2018Piedmont Research Station, Salisbury, NC15 berries40°C, 2.2°C
Raspberries11 Sept. 2018Upper Mountain Research Station, Laurel Springs, NC14 ga32.2°C
Fruit typeDate collectedLocationFruit per replicateNumber of replicates per treatmentExposure temperatures
Strawberries14 June 2018Central Crops Research Station, Clayton, NC10 berries40°C, 2.2°C
Blueberries30 July 2018Sandhills Research Station, Jackson Springs, NC15 berries40°C, 2.2°C
Blackberries19 July 2018Piedmont Research Station, Salisbury, NC15 berries40°C, 2.2°C
Raspberries11 Sept. 2018Upper Mountain Research Station, Laurel Springs, NC14 ga32.2°C

aDue to fragile nature of highly infested raspberries, we divided samples based on mass rather than fruit number.

After cold storage, fruit were returned to 20°C to allow any surviving larvae to develop until pupation. Containers were checked every other day, and pupae were removed and placed into a Petri dish with a damp paper towel until adults emerged. We differentiated pupae of other Drosophila species by breathing tubes and did not count non-D. suzukii pupae.

Statistical Analyses

We analyzed survival data using a mixed model analysis of variance via SAS v 9.4, and all data conformed to the necessary assumptions. Treatments were defined as the berry type held at its specific temperature and duration. Due to constraints of cold storage unit size, each temperature treatment was included separately with its own control. Treatment was considered an independent variable, and replication was considered a random effect. Means were separated using a Tukey–Kramer test.

Economic Assessment

We performed an economic assessment on the investment of postharvest cooling for a typical rabbiteye, or late season, blueberry farm in North Carolina with 40.5 hectares (100 acres). The parameters used in the analysis are the following. Based on Sanford and Hendrickson (2015) and interviews of industry experts, the one-time investment cost of the facility was estimated at $23,000, with an annual operation cost including additional labor and electricity at $5,000, and we assumed the facility has a life span of 20 yr. The yield and other production costs were retrieved from existing crop budgets (Safley et al. 2006). We assumed the grower harvests a total of 14 times in the season. Each harvest was set at 3 d apart and spans from late May to late June. The assumption of a 3-d harvest interval is based on hand harvesting across the whole farm. Given that North Carolina growers face fluctuating market prices, we specified a linear regression model to estimate the price change during the harvest cycle using the average farmgate price from 2015 to 2018 (U.S. Department of Agriculture 2019; n = 270). The regression was performed by using the statistical software Stata.

We divided the production season into early, mid, and late season, which corresponds to three risk levels (low, medium, and high) of getting a rejection from the fresh market due to D. suzukii infestation. In the early season, there is little pest pressure, so we assumed the rejection rate is 1% only, and cooling decreased the risk to 0%. In the midseason, we assumed a 5% rejection rate and that cooling could decrease the risk to 1%. In simulating the late season, in which growers observe the highest pest pressure, cooling for 5 d at 0°C brought the rejection rate from 15 to 5% based on the data input from the above cold storage project. We also ran a separate scenario in which the pest pressure is higher throughout the season. In this high pest-pressure scenario, at the first half of the season, the grower faces medium risk of getting rejection due to D. suzukii infestation. The grower then faces a high risk of rejection at the second half of the season. See Table 2 for a full list of inputs.

Table 2.

Baseline parameters of the economic assessment of a typical farm in North Carolina

Production characteristics
 Farm size40.5 hectares
 Annual yield5,044 kg per hectare
 Yield per harvest (over a total of  14 harvests per season)360 kg per hectare
 Annual production expenses$18,214 per hectare
Cold storage related
 One-time investment cost$23,000
 Additional operation cost$5,000 per yr
 Life span of equipment20 yr
Risk of rejection during harvesting cycle
 Low risk (early season), without cooling1%
 Low risk (early season), with cooling0%
 Medium risk (midseason), without cooling5%
 Medium risk (midseason), with cooling1%
 High risk (late season), without cooling15%
 High risk (late season), with cooling5%
Production characteristics
 Farm size40.5 hectares
 Annual yield5,044 kg per hectare
 Yield per harvest (over a total of  14 harvests per season)360 kg per hectare
 Annual production expenses$18,214 per hectare
Cold storage related
 One-time investment cost$23,000
 Additional operation cost$5,000 per yr
 Life span of equipment20 yr
Risk of rejection during harvesting cycle
 Low risk (early season), without cooling1%
 Low risk (early season), with cooling0%
 Medium risk (midseason), without cooling5%
 Medium risk (midseason), with cooling1%
 High risk (late season), without cooling15%
 High risk (late season), with cooling5%

Cold storage-related costs are based on Sanford and Hendrickson (2015) and interviews of industry experts. Other parameters are estimated from the crop budgets (Safley et al. 2006) and based on the cold storage experiment.

Table 2.

Baseline parameters of the economic assessment of a typical farm in North Carolina

Production characteristics
 Farm size40.5 hectares
 Annual yield5,044 kg per hectare
 Yield per harvest (over a total of  14 harvests per season)360 kg per hectare
 Annual production expenses$18,214 per hectare
Cold storage related
 One-time investment cost$23,000
 Additional operation cost$5,000 per yr
 Life span of equipment20 yr
Risk of rejection during harvesting cycle
 Low risk (early season), without cooling1%
 Low risk (early season), with cooling0%
 Medium risk (midseason), without cooling5%
 Medium risk (midseason), with cooling1%
 High risk (late season), without cooling15%
 High risk (late season), with cooling5%
Production characteristics
 Farm size40.5 hectares
 Annual yield5,044 kg per hectare
 Yield per harvest (over a total of  14 harvests per season)360 kg per hectare
 Annual production expenses$18,214 per hectare
Cold storage related
 One-time investment cost$23,000
 Additional operation cost$5,000 per yr
 Life span of equipment20 yr
Risk of rejection during harvesting cycle
 Low risk (early season), without cooling1%
 Low risk (early season), with cooling0%
 Medium risk (midseason), without cooling5%
 Medium risk (midseason), with cooling1%
 High risk (late season), without cooling15%
 High risk (late season), with cooling5%

Cold storage-related costs are based on Sanford and Hendrickson (2015) and interviews of industry experts. Other parameters are estimated from the crop budgets (Safley et al. 2006) and based on the cold storage experiment.

Table 3.

Single life stage comparison mean surviving pupae in raspberry

Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control57c54.25c
Egg (0)720.5a3.75a
960a2a
1200a1.25a
Old egg (1)728.25a15.5b
964.5a5.25ab
1200a0.25a
First instar (3)72 h21.25b1.75a
962.5a0.25a
1200.5a0a
Second instar (4)721.5a4.25a
960a2.25a
1200a1.5a
Third instar (6)722.5a4.75a
960.25a3.75a
1200a3a
F53.24F12.26
df15, 45df15, 45
P<0.0001P<0.0001
Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control57c54.25c
Egg (0)720.5a3.75a
960a2a
1200a1.25a
Old egg (1)728.25a15.5b
964.5a5.25ab
1200a0.25a
First instar (3)72 h21.25b1.75a
962.5a0.25a
1200.5a0a
Second instar (4)721.5a4.25a
960a2.25a
1200a1.5a
Third instar (6)722.5a4.75a
960.25a3.75a
1200a3a
F53.24F12.26
df15, 45df15, 45
P<0.0001P<0.0001

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α = 0.05).

Table 3.

Single life stage comparison mean surviving pupae in raspberry

Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control57c54.25c
Egg (0)720.5a3.75a
960a2a
1200a1.25a
Old egg (1)728.25a15.5b
964.5a5.25ab
1200a0.25a
First instar (3)72 h21.25b1.75a
962.5a0.25a
1200.5a0a
Second instar (4)721.5a4.25a
960a2.25a
1200a1.5a
Third instar (6)722.5a4.75a
960.25a3.75a
1200a3a
F53.24F12.26
df15, 45df15, 45
P<0.0001P<0.0001
Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control57c54.25c
Egg (0)720.5a3.75a
960a2a
1200a1.25a
Old egg (1)728.25a15.5b
964.5a5.25ab
1200a0.25a
First instar (3)72 h21.25b1.75a
962.5a0.25a
1200.5a0a
Second instar (4)721.5a4.25a
960a2.25a
1200a1.5a
Third instar (6)722.5a4.75a
960.25a3.75a
1200a3a
F53.24F12.26
df15, 45df15, 45
P<0.0001P<0.0001

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α = 0.05).

Table 4.

Single life stage comparison mean surviving pupae in blackberry

Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control56c41.75d
Egg (0)720.5a1.5a
960.75a0.25a
1200.5a0a
Old egg (1)724.5a11.53c
960.75a5.12abc
1200.5a0.65abc
First instar (3)724.75a3.25abc
962.25a1.25ab
1200a0.5a
Second instar (4)722.25a1.65abc
960a1.44abc
1200a1.35abc
Third instar (6)725.5a2.87abc
961.5a2.56abc
1200a1.5ab
F74.53F8.31
df15, 45df15, 45
P<0.0001P<0.0001
Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control56c41.75d
Egg (0)720.5a1.5a
960.75a0.25a
1200.5a0a
Old egg (1)724.5a11.53c
960.75a5.12abc
1200.5a0.65abc
First instar (3)724.75a3.25abc
962.25a1.25ab
1200a0.5a
Second instar (4)722.25a1.65abc
960a1.44abc
1200a1.35abc
Third instar (6)725.5a2.87abc
961.5a2.56abc
1200a1.5ab
F74.53F8.31
df15, 45df15, 45
P<0.0001P<0.0001

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α  = 0.05).

Table 4.

Single life stage comparison mean surviving pupae in blackberry

Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control56c41.75d
Egg (0)720.5a1.5a
960.75a0.25a
1200.5a0a
Old egg (1)724.5a11.53c
960.75a5.12abc
1200.5a0.65abc
First instar (3)724.75a3.25abc
962.25a1.25ab
1200a0.5a
Second instar (4)722.25a1.65abc
960a1.44abc
1200a1.35abc
Third instar (6)725.5a2.87abc
961.5a2.56abc
1200a1.5ab
F74.53F8.31
df15, 45df15, 45
P<0.0001P<0.0001
Target life stage (age in days)Exposure duration (h)0°C1.5°C
Control56c41.75d
Egg (0)720.5a1.5a
960.75a0.25a
1200.5a0a
Old egg (1)724.5a11.53c
960.75a5.12abc
1200.5a0.65abc
First instar (3)724.75a3.25abc
962.25a1.25ab
1200a0.5a
Second instar (4)722.25a1.65abc
960a1.44abc
1200a1.35abc
Third instar (6)725.5a2.87abc
961.5a2.56abc
1200a1.5ab
F74.53F8.31
df15, 45df15, 45
P<0.0001P<0.0001

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α  = 0.05).

Table 5.

Single life stage comparison mean surviving pupae in strawberry

Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control93c22c
Egg (0)722.5a2.67a
960a1a
1200a0a
Old egg (2)7219ab11ab
968.75a7ab
1200a8ab
First instar (3)7230.75b12.33ab
9616ab3.67a
1203a3.67a
Second instar (5)727.25a12.33ab
960.75a0.33a
1200a2.0a
Third instar (7)726.75a2a
962.333a4.33a
1200a3.33a
F38.24F3.16
df15,44df15, 30
P<0.0001P0.0035
Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control93c22c
Egg (0)722.5a2.67a
960a1a
1200a0a
Old egg (2)7219ab11ab
968.75a7ab
1200a8ab
First instar (3)7230.75b12.33ab
9616ab3.67a
1203a3.67a
Second instar (5)727.25a12.33ab
960.75a0.33a
1200a2.0a
Third instar (7)726.75a2a
962.333a4.33a
1200a3.33a
F38.24F3.16
df15,44df15, 30
P<0.0001P0.0035

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α  = 0.05).

Table 5.

Single life stage comparison mean surviving pupae in strawberry

Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control93c22c
Egg (0)722.5a2.67a
960a1a
1200a0a
Old egg (2)7219ab11ab
968.75a7ab
1200a8ab
First instar (3)7230.75b12.33ab
9616ab3.67a
1203a3.67a
Second instar (5)727.25a12.33ab
960.75a0.33a
1200a2.0a
Third instar (7)726.75a2a
962.333a4.33a
1200a3.33a
F38.24F3.16
df15,44df15, 30
P<0.0001P0.0035
Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control93c22c
Egg (0)722.5a2.67a
960a1a
1200a0a
Old egg (2)7219ab11ab
968.75a7ab
1200a8ab
First instar (3)7230.75b12.33ab
9616ab3.67a
1203a3.67a
Second instar (5)727.25a12.33ab
960.75a0.33a
1200a2.0a
Third instar (7)726.75a2a
962.333a4.33a
1200a3.33a
F38.24F3.16
df15,44df15, 30
P<0.0001P0.0035

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α  = 0.05).

Table 6.

Single life stage comparison mean surviving pupae in blueberry

Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control32.75c31.5c
Egg (0)720.5a0a
960a0.25a
1200a0a
Old egg (2)7210ab17.75bc
962.5a14ab
1200.75a10ab
First instar (3)727.5ab8ab
963a8.75ab
1200.5a4.25a
Second instar (5)728.5ab12.25ab
966ab4.5a
1200.25a4.5a
Third instar (7)7216.5b18.75bc
968.75ab12.25ab
1201.25a4a
F10.89F9.61
df15, 45df15, 45
P<0.0001P<0.0001
Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control32.75c31.5c
Egg (0)720.5a0a
960a0.25a
1200a0a
Old egg (2)7210ab17.75bc
962.5a14ab
1200.75a10ab
First instar (3)727.5ab8ab
963a8.75ab
1200.5a4.25a
Second instar (5)728.5ab12.25ab
966ab4.5a
1200.25a4.5a
Third instar (7)7216.5b18.75bc
968.75ab12.25ab
1201.25a4a
F10.89F9.61
df15, 45df15, 45
P<0.0001P<0.0001

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α = 0.05).

Table 6.

Single life stage comparison mean surviving pupae in blueberry

Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control32.75c31.5c
Egg (0)720.5a0a
960a0.25a
1200a0a
Old egg (2)7210ab17.75bc
962.5a14ab
1200.75a10ab
First instar (3)727.5ab8ab
963a8.75ab
1200.5a4.25a
Second instar (5)728.5ab12.25ab
966ab4.5a
1200.25a4.5a
Third instar (7)7216.5b18.75bc
968.75ab12.25ab
1201.25a4a
F10.89F9.61
df15, 45df15, 45
P<0.0001P<0.0001
Target life stage (age in days)Exposure duration (h)0°C2.2°C
Control32.75c31.5c
Egg (0)720.5a0a
960a0.25a
1200a0a
Old egg (2)7210ab17.75bc
962.5a14ab
1200.75a10ab
First instar (3)727.5ab8ab
963a8.75ab
1200.5a4.25a
Second instar (5)728.5ab12.25ab
966ab4.5a
1200.25a4.5a
Third instar (7)7216.5b18.75bc
968.75ab12.25ab
1201.25a4a
F10.89F9.61
df15, 45df15, 45
P<0.0001P<0.0001

Values within a column followed by the same letter are not significantly different via mean comparison with the Tukey–Kramer adjustment (α = 0.05).

Results

In most treatments, cold exposure significantly reduced the number of surviving D. suzukii (Tables 36). Different life stages differed in their tolerance to cold storage in laboratory experiments. In general, the old-egg and first-instar treatments had the highest survivorship at shorter durations, followed by third-instar treatments (Tables 36). Emergence was lowest in freshly laid eggs across in all fruit types (Tables 36). We compared the sex ratio of surviving adult flies to determine whether cold storage had differential impact on the sexes, but there was no significant effect of treatment (F = 1.08; df = 9, 15; P = 0.4307). Therefore, we analyzed only pupal count data.

Stage-Specific Survival Following Cold Storage

Raspberries

The number of surviving pupae was significantly lower across all life stages and durations held at 0°C than in respective controls, with one notable exception. First instars held for 3 d had significantly more surviving pupae than all other treatments, yet survival was still lower than the control (Table 3).

Fewer surviving pupae resulted from all immature D. suzukii stages in raspberries held at 1.5°C when compared with the control. There were no significant differences among durations for egg, first-instar, second-instar, and third-instar life stages. Old-egg treatments had fewer surviving pupae following exposure to 1.5°C for 5 or 4 d than the shorter duration of 3 d (Table 3).

Blackberries

Numbers of surviving pupae in all blackberry treatments held at 0°C were significantly different from the controls (Table 4). There were differences among treatments exposed to 1.5°C with blackberries. All treatments differed significantly from the control. Eggs exposed to 1.5°C for any duration had the lowest number of surviving pupae. A similar number of eggs survived to pupae as for all other life stages held at 3, 4, and 5 d except the old-egg stage. Eggs grouped with days 4 and 5 in old-egg stage, but not with 3 d (Table 4).

Larvae exposed as first instars to 1.5°C exhibited more complex results where often longer durations and colder temperatures were needed to minimize emergence of pupae. Old-egg treatments held for 3 d had the highest rate of survivorship and were not significantly different from old-egg treatments held 4 and 5 d, first-instar treatments held 3 d, all cold storage second-instar treatments, and third-instar treatments held 4 and 5 d (Table 4).

Strawberries

Temperatures during lab-infested strawberry experiments were held at 0°C in a unit holding the temperature quite tightly and in one that fluctuated around 0 ± 0.5°C. This small temperature fluctuation appears to have no significant effect on the survivorship of D. suzukii (F = 30.16; df = 24, 71; P < 0.0001), so we therefore pooled data for analyses.

The number of surviving pupae was similar across all 0°C storage durations for egg, second-instar, and third-instar treatments (Table 5). In the old-egg treatment, emergence was lower than the control after 3 d at 0°C but lowest after 4 and 5 d. Similarly, for first instars, surviving pupae were lowest after 5 d and higher at 3 and 4 d (Table 5).

At 2.2°C, the old-egg treatment did not significantly differ from 20°C controls for any of the durations listed. Similarly, in the 2.2°C treatment, holding first- and second-instar larvae for only 3 d did not result in significantly reduced emergence in pupae from the control, but when those same treatments were held for longer durations (either 4 and 5 d), the pupal emergence was significantly lower than the control with no difference between the two durations (Table 5).

Blueberries

The number of surviving pupae in D. suzukii exposed to 0°C as eggs, old eggs, first instars, and second instars at all durations was statistically similar (Table 6). However, for all life stages, pupal counts for shorter treatment durations were also statistically similar to treatments with the highest pupal counts following cold storage, namely, the third-instar stage held for 3 d and freshly laid eggs treatments. Despite the high survivorship in the third instar treatment held for only 3 days, the 4- and 5-d durations both resulted in similar pupal numbers when compared with 4- and 5-d treatments for all other life stages.

In general, the 2.2°C treatments had higher proportion of survivorship compared with the control than the 0°C treatments. Two of the 2.2°C treatments did not significantly differ from the control, old eggs, and first instars held for 3 d. The lowest number of surviving pupae was observed in all egg, first- and second-instar treatments, and 4- and 5-d treatments of old-egg and third-instar treatments (Table 6).

Field-Infested Fruit

Initial infestation rate as measured by pupation in control field-infested fruit varied dramatically by substrate. Blueberry infestation was lowest, ranging from 0 to 4 pupae from 15 berries (Fig. 1a). One to 13 D. suzukii were present in our samples of 10 strawberries per replicate (Fig. 1b). Field-infested control blackberries had pupal emergence from 11 to 28 pupae per 15 berries (Fig. 1c). Field-infested raspberries had the highest infestation rate with control treatment for raspberries ranging from 263 to 318 pupae from 14 g of raspberry across the three replicates (Fig. 1d).

Fig. 1.

Mean ± SE D. suzukii emergence from field infested fruit held at cold storage temperatures as compared to control fruit held at 20°C. Values for a given fruit type indicated by the same letter are not significantly different via comparison using the Tukey-Kramer adjustment, α = 0.05.

In general, exposure to lower temperatures for longer periods of time (greater than 72 h and less than 2.2°C) resulted in the lowest levels of survivorship within all fruit types. Survivorship in cold-treated field-infested blueberries (F = 7.02; df = 6, 12; P = 0.0022) and strawberries (F = 9.70; df = 6, 18; P < 0.0001) was not significantly different between treatments, and all low temperature treatments differed from the control. In raspberries, survivorship was lowest in fruit held for 5 d at 2.2°C (F = 20.81; df = 3, 6; P = 0.0014). In field-infested blackberry, the emergence of D. suzukii in fruit held at 0°C for 4 or 5 d and 2.2°C for 5 d was similar, whereas emergence at higher temperatures and shorter durations was greater (F = 8.56; df = 6, 18; P = 0.0002).

Economic Assessment

The average initial blueberry price is $4.73/kg ($2.14/lb), with a significant decreasing trend of $0.036/kg each day according to the linear regression estimates (F = 110.95; df = 1, 268; P < 0.001; r2 = 0.29). Thus, if the blueberries are put into postharvest cooling for 3 d, the price is decreased by around $0.108/kg.

The estimated annual budget per hectare is summarized in Table 7. The estimated grower revenue change is calculated at an increase of $267 per hectare per year when the grower uses cooling (Table 7). Factoring in the additional maintenance and depreciation costs of the cooling facility, the additional profit of using cooling is estimated at $115 per hectare per year.

Table 7.

Results of the economic assessment

Initial blueberry market price$4.73 per kga
Estimated market price reduction every 3 d−$0.11 per kga
Estimated annual budget (per hectare)
 Revenue without cooling$19,113
 Revenue with cooling$19,380
 Other production expenses$18,214
 Additional costs for cooling
  Depreciation of the investment$28
  Additional operation cost$124
 Profit without cooling$899
 Profit with cooling$1,014
 Incremental profit with cooling$115
Initial blueberry market price$4.73 per kga
Estimated market price reduction every 3 d−$0.11 per kga
Estimated annual budget (per hectare)
 Revenue without cooling$19,113
 Revenue with cooling$19,380
 Other production expenses$18,214
 Additional costs for cooling
  Depreciation of the investment$28
  Additional operation cost$124
 Profit without cooling$899
 Profit with cooling$1,014
 Incremental profit with cooling$115

aSource: Parameter estimates from the linear regression model.

Table 7.

Results of the economic assessment

Initial blueberry market price$4.73 per kga
Estimated market price reduction every 3 d−$0.11 per kga
Estimated annual budget (per hectare)
 Revenue without cooling$19,113
 Revenue with cooling$19,380
 Other production expenses$18,214
 Additional costs for cooling
  Depreciation of the investment$28
  Additional operation cost$124
 Profit without cooling$899
 Profit with cooling$1,014
 Incremental profit with cooling$115
Initial blueberry market price$4.73 per kga
Estimated market price reduction every 3 d−$0.11 per kga
Estimated annual budget (per hectare)
 Revenue without cooling$19,113
 Revenue with cooling$19,380
 Other production expenses$18,214
 Additional costs for cooling
  Depreciation of the investment$28
  Additional operation cost$124
 Profit without cooling$899
 Profit with cooling$1,014
 Incremental profit with cooling$115

aSource: Parameter estimates from the linear regression model.

In addition to the annual budget, we calculate the accumulated cash flow which the investment is a lump-sum cost at the first year to analyze the time needed to recover the capital investment (Fig. 2). The breakeven point of investing in the cooling facility is at year 4.

Fig. 2.

A comparison of the accumulated cash flows for a typical North Carolina blueberry farm over 10 yr, with and without the cooling investment. The dash line indicates the baseline cash flow, whereas the solid line refers to the case with additional cooling investment at year 1. The differences between the two accumulated cash flows are indicated by the bars.

Furthermore, under a 5% annual discount factor, the net present value of the accumulated profit differences of using cooling is $88,756 for the farm over 20 yr. For the scenario with which grower faces a higher pest pressure year-round, the increase in profit of using cooling is estimated at $254 per hectare each year. Under the assumed conditions, the investment breaks even at the first year, and the net present value of the accumulated profit differences of using cooling is at $482,979 for the farm over 20 yr.

Discussion

Our results suggest that subjecting larval D. suzukii to cold temperatures directly affects their emergence within fruit but appears to be substrate-dependent. Differences are most distinct in fruit type on pupal emergence in field-infested fruit, which was held at the same temperature in the same cold storage unit, albeit at different yet often overlapping times. Although 3 d may be sufficient to reduce survival of different life stages of infestation within blueberry and strawberry, the maximum duration of 5 d may be required for minimal survivorship of larvae within caneberries. These soft-skinned, summer-ripening fruit are preferential hosts for D. suzukii. As such, there may be greater intraspecific larval competition within the wild-infested fruit causing larvae within to develop more quickly and achieve later-instar stages that also happen to provide greater adult emergence (first instar and third instar) rates after cold storage treatment. In general among treatments, longer, lower temperatures resulted in reduced survivorship of larvae into pupae, though total mortality was not reached for all treatments even at the lowest and longest duration tested. Different D. suzukii life stages exhibited different pupal survival following cold storage with freshly deposited eggs resulting in the lowest pupal counts. There is a significant difference in survivorship based on egg age (egg vs old egg) subjected to cold storage in some substrate and temperature treatments, despite the fact that these life stages are at times separated by only a day. This suggests that frequent harvest (Leach et al. 2018) combined with cold storage may be more effective when used together as part of an integrated pest management strategy.

The difference in larval survivorship dependent on substrate may be because different fruit confer better cold tolerance due to their diet quality. Because cryoprotectants are made up of carbohydrates or amino acids, it is possible that the different fruit chemistry is affecting D. suzukii’s differential ability to survive cold storage conditions. Cryoprotectants are usually built up during cold acclimation periods, which were purposefully absent in our applied study (Enriquez et al. 2018), but this is an interesting topic for future research.

In our experiment, D. suzukii third-instar larvae were also more tolerant to cold storage treatment, and this may also be supported by other studies. Some experiments in other Drosophila species suggest that first-instar larvae may have superior adaptations to tolerate cooling as measured by the lower super cooling point of first-instar larvae compared with other stages (Strachan et al. 2011). Research on D. melanogaster shows that third-instar larvae may be more tolerant than other life stages to acute cold exposure (Rajamohan and Sinclair 2008).

Previous experiments by our group evaluated the effect of cold storage treatment on larval development time (in diet) and mortality in two fruit types (Aly et al. 2017). Our new observations build on this prior work to maximize mortality within four berry types as well as to look at mixed-larval life stage populations within untreated fields. The bulk of the experiments conducted here included D. suzukii laboratory lines that have been maintained since 2010 in a climate-controlled room at North Carolina State University. Notably, other authors working with D. melanogaster have found that laboratory based lines held without pressure to maintain cold tolerance nevertheless maintained comparable cold tolerance to wild-caught lines (Rajamohan and Sinclair 2008). Susceptibility to cold chilling appears to be a basal trait within the Drosophila and so may be highly conserved (Strachan et al. 2011), even among laboratory lines.

Infestation of blueberry and strawberry fruit in the field was lower than caneberries and is typical of the level of infestation that we see in untreated North Carolina blueberries (Diepenbrock et al. 2016). Caneberries ripen later in the season and are considered preferential hosts which led to higher infestation rates. Primocane-fruiting raspberries were collected in September, a couple months after most of the other berry samples, and had infestation rates typical for untreated raspberries, which ripen later in summer when D. suzukii populations in North Carolina are generally at their highest.

In the large body of work looking at cold shock and cold hardening in D. melanogaster, flies held for even 30 min at a cooler temperature become primed for colder, known lethal temperatures and are able to physiologically resist mortality at those lower thresholds (Lee et al. 1987, Czajka and Lee 1990). Clearly, then, it is important that commercial-scale fruit production not allow infested fruit to cool before subjecting it to cold storage. Forced air cooling, which imposes a faster drop in substrate temperature than other systems, may be necessary on a commercial scale to realize similar results to our experiments on small quantities of fruit which presumably cool quickly.

Cold storage is used for more than just pest management, and there are many publications detailing the quality of fruit after treatment. It is widely accepted that fruit quality of blueberries, blackberries, raspberries, and strawberries does not decline due to cold storage at 0°C, which is the suggested temperature for any cold storage treatment of these fruit types (Zhao 2007). Because fruits contain abundant soluble sugars, their freezing point is below 0°C (Zhao 2007). Extended duration in cold storage, which is usually measured in weeks and not days as in this experiment, may result in fruit drying and fruit firmness (Chiabrando et al. 2009). Despite the relatively short period of cold storage, loss of fruit mass due to dehydration of fruit within cold storage may result in lower fruit quality and may positively or negatively affect survivorship of D. suzukii. Future studies may seek to monitor humidity in cold storage treatments for live D. suzukii reduction. Additionally, there are concerns that cold storage may affect fruit nutrition and flavor. The quantity and quality of anthocyanins within the fruit may change due to extended durations within cold storage (Kalt et al. 1999, Connor et al. 2002, Reque et al. 2014). Most concerns over fruit deterioration in cold storage concern longer cold storage treatments than those used in these studies.

The results of this study provide evidence of cold storage being one of the viable postharvest control options for growers as well as information on the economics of the investing the on-farm cold storage facility. Although small growers in North Carolina may not already have an on-farm unit, we spoke to larger growers in the region and many have a cold storage unit to 1) remove field heat and 2) reduce fruit temperature to 1°C (34°F) before immediately shipping. Additionally, most growers said that they would have the capacity to hold that fruit for up to 5 d as necessary, though mentioned that is as much dependent on a strong organizational system and cold storage manager as the space. Some growers also rent out space by the pallet to smaller growers to use cold storage. Although the economic assessment presented here focuses on growers who do not already have on-farm cold storage, the analysis also provides insights for growers that already have cold storage unit. Per the parameters chosen in this study to create an example table (Tables 2 and 7), growers in North Carolina will see a $0.11/kg reduction in price for holding fruit up to 3 d. This assessment will allow growers to choose whether or not to hold fruit in preexisting cold storage units when faced with residual D. suzukii infestation after previous treatment fails due to higher than normal infestation or inability to maintain spray regimen during rain events.

Targeting cold susceptibility in many tropical and temperate pests may be one of the best ways to ensure that no live larvae survive to fresh market or, more importantly, to trading partner country. Cold storage is one of the easiest postharvest treatment options, which makes it attractive to implement over other potential treatments. Successful use of cold storage may also help reduce inputs during harvest, such as a final insecticide application, and would fit into a larger integrated pest management program for D. suzukii not only in the southeastern United States which this economic model has been designed for, but also in other major fruit-growing regions in the United States and around the world.

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Subject Editor: Dong H Cha
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