Spatially Based Whole-Farm Integrated Crop Management (ICM) Systems for Northeast Highbush Blueberry Production

Final Report for LNE08-273

Project Type: Research and Education
Funds awarded in 2008: $180,000.00
Projected End Date: 12/31/2012
Region: Northeast
State: New Jersey
Project Leader:
Expand All

Project Information

Summary:

This three-year project focused on implementing Geographic Information System (GIS)-based whole farm management and reduce-risk practices, referred to as Integrated Crop Management (ICM) programs, in blueberry farms in New Jersey, with a specific performance target of increasing their adoption in eight farms accounting for 1500 acres of the state’s blueberry production.

More than 100 blueberry growers from the mid-Atlantic U.S. were trained each year on blueberry pest biology, IPM, and reduced-risk practices through meetings, workshops, farm visits, and on-farm demonstrations. Movement of blueberry maggot flies, a major pest of blueberries in the U.S., was assessed by releasing marked flies and revealed that blueberry maggot fly movement is restricted to 180 ft within a 2-day period.

The spatial distribution of blueberry maggot flies was also determined to better target insecticide applications using a novel, large-scale monitoring approach that combined GIS with reduced-risk tactics. Other key blueberry insect pests, such as oriental beetle, and sharp-nosed leafhoppers, were also intensively monitored in ICM farms. It was found that the distribution of blueberry maggot flies is significantly higher in fields close to the forest than in interior fields, whereas populations of sharp-nosed leafhoppers and oriental beetle are irregularly distributed. Within farms, blueberry maggot distribution was significantly higher in fields surrounded by forest and lower in fields with no forest border, indicating possible invasion of flies from outside hosts. Upland forest edges were the most predictable source of blueberry maggot flies in fields surrounded by forest.

On some farms, flies were trapped inside blueberry fields, indicating the presence of resident populations. In these cases, high blueberry maggot numbers on traps were usually associated with the late-season variety Elliott. This information was used to identify high-risk areas for blueberry maggot infestation. Consequently, participating blueberry growers used this information to treat specific fields or parts of a field with insecticides rather than treating the entire farm. This led to a reduction in the number of insecticide applications, amounts of active ingredients and cost in some years.

During the project period, the percentage of users of reduced-risk products among New Jersey blueberry growers increased by 57%, from 60% of growers (15 out of 25) to 94% (37 out of 39). Similarly, there was an increase among growers from other Mid-Atlantic regions (Pennsylvania, Maryland, and New York) that either used or considered using reduced-risk pesticides in their blueberry farms, from 27% of growers (8 out of 30) to 66% (10 out of 15).

Introduction:

The distribution of insect populations in agricultural farms is often determined by local differences in factors such as the surrounding landscape, nesting or overwintering sites, food sources, climate, oviposition or mating preferences, among others. Agricultural farms are often surrounded by a diverse landscape i.e. farms are located adjacent to forest, open fields, other crops, or to neighboring farms having similar crops. These ecological features are potential sources of inter and intra-field variability on pest pressure within farms.

For example, the intensity of insect infestation may vary among fields depending on their distance from forest edges or surrounding vegetation. The surrounding habitats can not only serve as reservoirs for pests due to the presence of alternative host plants but also a source for the pests’ natural enemies. Thus, the surrounding landscape could be critical for the spatial distribution of pests in agricultural fields.

In the U.S., blueberries are produced in ecologically and environmentally sensitive areas characterized by porous soils with high water tables. In New Jersey, highbush blueberries are grown in an ecologically-important forest region known as the Pinelands, which serves as a fresh water source for 2.6 million people (NJDEP 2003). A complex of native and exotic insect pests attack blueberries in this region.

In New Jersey and other eastern and mid-western states, the blueberry maggot (Rhagoletis mendax Curran) is considered the most economically important pest of commercially grown highbush blueberries (Vaccinium corymbosum L.). Wild ericaceous plants growing naturally in the Pinelands serve as alternative hosts for R. mendax. Adults emerge from overwintering pupae and oviposit on ripening blueberries. The larvae feed inside the berries making damaged fruit unmarketable. Late-instar larvae leave the fruit to pupate in the soil. Flies often migrate from wild hosts into commercial blueberry fields from June through September. Besides R. mendax, blueberries are attacked by other key insect pests such as the cranberry fruitworm, oriental beetle, and sharp-nosed leaf hoppers.

Blueberry marketing standards have a zero tolerance for many insects and diseases, so significant pesticide use is common. Due to its high value, zero tolerance of insect infestation for fresh fruit market, and a strict export protocol, contamination of harvested fruit by insects can result in rejected loads and lower market prices. While growers have embraced integrated pest management concepts, actual practices often result in overuse of pesticides based on limited information of actual needs. For instance, to protect fruit and plant injury, and to minimize the risk of crop rejection, organophosphate and carbamate insecticides have historically been used to control insect pests of blueberries (Drummond 2006, Wise et al. 2006).

In recent years, integrated pest management (IPM) programs have been implemented on blueberry farms to protect fruits from direct feeding damage by insects. However, elimination or future phase-out plans for certain key broad spectrum insecticides (organophosphates and carbamates) by the Food Quality Protection Act (FQPA), combined with the high cost of newly available reduced-risk insecticides, have limited pest control options for blueberry growers. IPM programs for blueberries based on individual field management can maintain high fruit quality and greatly reduce applications of conventional insecticides to control pest problems; however, these programs may result in high management costs and thus hinder the widespread adoption of IPM.

An alternative is to develop farm-wide spatially-based IPM programs where insecticides are applied only in “hot-spot” areas i.e., areas of high insect abundance. Development, delivery, and adoption of sustainable spatially based whole-farm Integrated Crop Management (ICM) programs for highbush blueberries have the potential to significantly reduce pesticide use, improve pesticide recommendations, reduce management costs, and increase adoption of reduced-risk practices.

Blueberry pest abundance can vary by two orders of magnitude (spatially and temporally) between fields within a single farm. Knowledge on the spatial distribution of pest populations in relation to the surrounding agro-ecosystem could help improve current IPM practices in blueberries. These practices could include spatially-based monitoring of pest populations, and can thus apply precision agriculture for pest management to reduce insecticide use and achieve cost-effective IPM practices. Adoption of new management protocols are facilitated when growers better understand the economic consequences of such decisions.

In this study, the overall impact of a change from standard pest management programs (STD) to ICM employing reduced-risk tactics was evaluated using a technique called partial budgeting. Partial budgeting is a farm management technique used to examine the profitability of incremental changes in production technologies, the size or scale of operation, or the product mix. A partial budget contains only those income and cost items that change if the proposed change is undertaken. Only the changes in income and expenses are used for a partial budget analysis, not the total values. The final result is an estimate of the increase or decrease in income attributable to the change. Decreased revenues and increased costs are subtracted from increased revenues and decreased costs to identify the net effect of the change. The changes in profitability calculated using partial budgeting will allow blueberry growers to better gauge the impact of adoption of ICM practices on the cash-flow and profitability of their own operations.

The main objective of the present project was to determine the distribution and spatial movement of insect pests within blueberry farms using Geographic Information System (GIS). In this study, we combined GIS-based monitoring and geo-spatial analysis for a key pest of blueberries, the blueberry maggot. The implications of this spatially-based IPM program were assessed by geo-statistical analysis and mapping pest distribution across fields. Outcomes of the spatially based IPM programs were measured by the reduction on the number insecticide applications, amount of active ingredient (a.i)/acre, and management costs.

Performance Target:

Objective 1: Determine the distribution and spatial movement of pests and their natural enemies within whole farm using Geographic Information System (GIS). Over three years (2009-2011), eight participating growers used spatially-precise pesticide applications based on pest distribution.

Objective 2: Study the spatial movement of insects into fields. A mark-release-recapture study was conducted to study movement of blueberry maggot flies.

Objective 3: Develop and evaluate new reduced-risk practices for pest control. A study was conducted to evaluate a new pheromone formulation of oriental beetle for mating disruption called SPLAT. We are working with the manufacturing company (ISCA Technologies Inc.) towards registration of this formulation.

Objective 4: Demonstrate and train growers on whole-farm ICM-based practices.

Objective 5: Measure adoption of whole-farm ICM-based practices and their economic impact. Six surveys were conducted during the project period to understand the grower’s adoption of reduced-risk insecticides in their farms. Growers’ pesticide use records for four New Jersey growers using ICM-based IPM programs were collected in 2009-2011. Data were spatially analyzed to provide information on insecticide use patterns, amount of active ingredient, and cost of insecticides for individual blueberry fields. Management costs were compared between ICM programs and grower standard (STD) programs. Costs of spray materials and scouting were calculated for each program.

Performance Targets

Through this project, eight New Jersey blueberry growers implemented ICM-based whole farm management practices in their farms. Over 20 growers used border insecticide treatments, target-specific insecticide applications, and timely applications based on economic thresholds. More than 100 blueberry growers from New Jersey, Pennsylvania, Maryland, and other neighboring states were yearly trained on reduced-risk pest management practices for blueberries. From grower surveys, there was a 57% increase on grower users of reduced-risk products. ICM programs had a significant impact on reducing the number of pesticide applications and the cost of spray materials. On average ICM resulted in reduced production cost of between $ 75 and $ 118 per acre annually.

Cooperators

Click linked name(s) to expand
  • Anne DeMarsay
  • Kathleen Demchak
  • Jayson Harper
  • Agenor Mafra-Neto
  • Bradley Majek
  • Jan Meneley
  • Peter Oudemans
  • Gary Pavlis
  • Dean Polk

Research

Materials and methods:

Objective 1: Determine the distribution and spatial movement of pests and their natural enemies within whole farm using Geographic Information System (GIS)

The Farms: Spatially-based whole farm integrated pest management programs, referred to as Intensive Crop Management (ICM), were established in eight blueberry farms covering 1500 acres of blueberry fields in Burlington and Atlantic Counties in New Jersey. Farm size varied between 30 to 637 acres. All farms contained at least one of three major blueberry cultivars: Duke, an early season cultivar; Bluecrop, a mid-season cultivar, and Elliott, a late season cultivar. Out of the eight farms, four ICM farms were paired with four farms having standard management programs. These paired farms were under the same grower’s management such that each paired site had one farm was under intensive monitoring program (“ICM” farm) and another under standard monitoring program (“Standard” farm). We used paired farms for measuring the outcome (pesticide use pattern, a.i/acre, and cost/acre) of ICM and standard programs. The other four unpaired farms were under an ICM program only.

Site Selection: Farms were selected based on three geo-spatial and landscape features: amount of forest, open fields, other crops (non- R. mendax host), and other blueberry fields surrounding the farms (Figure 1; Table 1). Before the season started, farms were digitally mapped by individual fields with a Trimble hand held GPS device (GeoXT 2005 series). Metafiles were created with information for each field on geographic coordinates, acreage, cultivar, surrounding landscape, and types of forest undercover. Traps baited with ammonium acetate for monitoring blueberry maggot flies were placed every 2.5 acres within each farm. Each monitoring trap position was geo-referenced as point source data. At each station, numbers were monitored twice per week. Data were spatially analyzed by geo-statistics and geo-spatial analysis using ArcGIS-9.3 software. Growers were provided with spatially referenced pest distribution maps and recommendations on when, where, and what to treat were given to these growers on a weekly basis.

Data collection: Traps for individual insect species were digitally marked as point source data. Digital maps were differentially corrected and exported to the desktop computer (GPS Pathfinder Office 3.10) for further spatial analysis. High resolution orthophotograph (image) for individual farms and surrounding areas were downloaded from the New Jersey Department of Environmental Protection (NJDEP) information warehouse (http://www.nj.gov/dep/gis). Geospatial data were analyzed by ArcGIS 9.0 software (Arc Editor version 9.3). During 2006-2008, blueberry maggot flies were intensively monitored in three farms located in Atlantic Co., New Jersey. In 2009 we extended this monitoring program to eight farms (6 farms in Atlantic Co., and 2 farms in Burlington Co.). Adult blueberry maggot flies were monitored by using ammonium acetate baited yellow sticky traps. One third of the traps were placed at the border of the farms, while the rest of the traps were placed inside the farms; thus, farms with longer peripheral line especially smaller farms had higher number of traps in border areas compared to the number of traps inside the fields. Farms under standard monitoring programs had fewer numbers of traps (approximately one tenth of the ICM farms). Traps were changed every 15 days. Blueberry maggot traps were monitored twice a week starting the first week of June until the second week of September. Number of adults captured per trap per week was calculated. Traps were categorized by “border” or “inside” based on their position within farms.

This project also monitored for other economically-important pests of blueberries such as sharp-nosed leafhopper, cranberry fruitworm, and oriental beetle. These pests were monitored using pheromone traps (cranberry fruitworm and oriental beetle) or yellow sticky traps (sharp-nosed leafhoppers) placed in all eight farms used for the blueberry maggot study. These traps were checked weekly and data were collected from 2009-2011.

In 2010 and 2011, 524 and 361 terminals were collected, respectively, from ICM and STD farms, and the number of aphids and parasitized aphids were assessed. Terminals were collected in early and late June from Duke, Bluecrop, and Elliott cultivars.

Data analysis: Adult blueberry maggot abundance is expressed here as the number of adults captured per Pherocon AM traps per week. Spatial distribution of weekly adult captures was measured over the 485 trapping points in the eight experimental farms. Spatial analysis methods used in this study were: spatial autocorrelation, hot spot analysis, semivariogram and kriging. Data for other pests were not subjected to geospatial analysis because the numbers of traps per farm too small or the number of individuals captured per trap per week was not significant to perform spatial analysis. However, we conducted a general analysis on these data and the results are shown below. We used analysis of variance (ANOVA) to test for differences in aphid parasitism among blueberry cultivars and between management programs (ICM vs STD).

Objective 2: Study the spatial movement of insects into fields
A mark-release-recapture study was performed inside a high tunnel and in an abandoned blueberry field in New Jersey. The first experiment was established in a 45.72 m x 6.0 m tunnel set at the forest edge and extended inside the field parallel to blueberry rows. This experiment investigated adult blueberry maggot migration from wooded areas to blueberry fields. Subsequent experiments were done in an open field so that the released flies represent a resident blueberry maggot population. In all experiments the maximum flight distance and dispersal of flies in a given period of time were measured.

Several hours prior to release, 6-10 day old starved adult blueberry maggot flies were chilled for 5 minutes to facilitate the marking process. Polyethylene bags were dusted with small amounts of ultraviolet Day-GLO powder. Flies were then placed inside the dusted bags. Marked flies were released in the morning. Flies were first released outside the field on 28-Jun, 4-Jul, and 6-Jul at the rate of 200 flies per release date. Another three releases were done at the edge of a field on 30-Jun, 2-Jul, and 10-Jul at the rate of 200 flies per release. Under the open field release experiment, a total of 3183 flies were released on 30-Jun, 7-Jul, 13-Jul, and 5-Aug. Different color GLO powders were used to mark the flies to avoid contamination with previous releases and natural populations. For experiments done in the tunnel, two Pherocon AM traps (great Lakes IPM, Vestaburg, MI) were placed at 0.5 m and 1.5 m height at every 9.12 m intervals from the release points up to 91.4 m. For the open field release experiment, a grid of 48 traps (7 traps x 7 traps) at a distance of 10 m from each other was set at the center of the field. No traps were located in the center of the grid, which was the release point of marked flies. Traps were inspected for flies at 2, 4, 6, 12, 24, and 48 hrs after being released. Captured flies were examined in-situ and in the lab using a hand lens and microscope, respectively. Weather information was obtained from a HOBO unit placed inside the tunnel and from the weather station at the Rutgers Marucci Center for blueberry/cranberry research and extension in Chatsworth, New Jersey. No precipitation was recorded during the experiments and the temperature varied between 22-24 ºC. The average distance a recaptured fly traveled was determined using the distance between the trap and the release point. Since the on-field releases were captured in a grid of traps, travel distances were transformed into a linear model to compare with the tunnel data. Dispersal data were obtained from the proportion captured flies at each trap distance.

Objective 3: Develop and evaluate new reduced-risk practices for pest control
A study was conducted in two commercial blueberry farms in Atlantic Co., New Jersey, to evaluate the efficacy of the following treatments: 1) SPLAT® OrB (1% (Z)-7-tetradecen-2-one) applied as 250 1 g dollops/ha; 2) SPLAT OrB® (1% (Z)-7-tetradecen-2-one) applied as 500 1 g dollops/ha; and 3) Non-pheromone treated control plot. SPLAT OrB was applied by hand to wooden posts (15 cm × 1.5 cm plant labels; Gempler’s) using a caulking gun (Newborn X-lite) modified to deliver 1 g dollops of material. Pheromone treatments were applied in 1 ha plots using an evenly-spaced grid among blueberry bushes. Plots were separated by at least 50 m. Treatments within blocks were assigned to plots in a complete randomized block design; with treatments replicated three times (one replicate per block). SPLAT was applied on June 3. All fields received the grower’s standard fungicide and insecticide programs, but no applications of imidacloprid were made during the study. Pheromone-treated wooden posts and dispensers were removed from fields at the completion of the study. The following methods described below were used to assess treatment efficacy.

Trap shut-down. This method measured the number of male oriental beetles captured in pheromone-baited traps. In each plot, three Japanese beetle sex pheromone traps (Trécé) baited with 300 ?g of (Z)-7-tetradecen-2-one were placed and monitored weekly to determine male populations. Traps were installed on June 10 and lures were replaced every three weeks.

ANOVA was used to test for differences in trap shut-down among treatments.

Objective 4: Demonstrate and train growers on whole-farm ICM-based practices
Each year (2009-2011), approximately 50 blueberry growers mainly from New Jersey listened to presentations given by the project leaders at the Blueberry Open House (Hammonton, New Jersey). During the project period (2009-2011), the investigators also organized a session on Blueberry IPM for the Mid-Atlantic Fruit and Vegetable Convention at Hershey, PA. A grower survey was conducted at each of these meetings. See project “Impacts/Outcomes” below for results of these surveys.

Verification: Measure adoption of whole-farm ICM-based practices and their economic impact
At the end of each season (2009-2011), pesticide use records were collected for the four paired farms for comparison of the ICM and standard (STD) programs. Data were entered into the Rutgers AgroTrak software, a Geographic Information System (GIS)-based data management program, to analyze spatial information of insecticide use patterns such as number of insecticide applications, amount of active ingredient, and cost of insecticides for individual fields and seasonal cultivars such as early, mid-season, and late maturing cultivars.

Research results and discussion:

Objective 1: Determine the distribution and spatial movement of pests within whole farm using Geographic Information System (GIS)

The total blueberry cultivation under the eight farms used in this study covered about 1200 acres. Figure 2 A-H summarizes the data on blueberry maggot captured in traps at each of the eight farms during early, mid, and late growing seasons in New Jersey in 2009-2010.

Among the farms with forest boundaries, traps near the forest captured significantly higher number of blueberry maggot flies than traps placed inside blueberry fields. There is a positive relationship between trap captures and the proportion of forest area surrounding the farms. As the proportion of forest area increased the number of blueberry maggot capture per trap increased significantly (Figures 3 and 4). Overall farms surrounded by mixed landscape (i.e. forest, vegetables, and open fields) had lower number of blueberry maggot populations than farms surrounded by only forest boundaries. However, in a mixed landscape farm, blueberry maggot population distribution was biased near the fields with forest than the fields with other crops or open fields. Farms surrounded by other blueberry farms had low numbers of blueberry maggot flies compared to farms with forest and mixed landscape boundaries. In these farms no significant differences were found in number of adult captures between traps in border versus inside fields (P = 0.28 and 0.56 for farms 7 and 8, respectively). Overall, traps set on field borders adjacent to forest captured significantly higher (P = 0.02) numbers of blueberry maggot flies than traps adjacent to open space or other blueberry farms (Figure 3).

Influence of seasonality and cultivar on blueberry maggot abundance:
In some instance, our study found resident blueberry maggot populations in traps located inside blueberry farms. Spatial analysis revealed that there is a cultivar effect on the abundance of blueberry maggot flies. The resident blueberry maggot populations were most associated with the late blueberry cultivar “Elliott” (Figure 5). This cultivar produces ripening fruits at the end of the blueberry season. Occasionally, growers do not harvest the entire fruit load from these bushes due to labor availability or market costs, and thus allow the unpicked fruit to rotten in the field. Rotting berries in fields can create an optimum habitat for harboring late-season blueberry maggot resident populations.

Hot-spot identification
Identification of hot spots is crucial for implementing an spatially-based Integrated Pest Management (IPM) program. Hot-spot management can reduce the overall cost of pest management as well as encourage growers to apply reduced-risk insecticides to target-specific, high risk areas instead of using whole-farm insecticide treatments. Our spatial analysis showed that high risk areas do exist for blueberry maggot flies in blueberry farms in New Jersey (Figure 6A-D), and that they can be defined spatially. We revealed that most of the high-risk areas are near to the forest area (Figure 7). In some cases, high risk areas were identified as fields of the later-season cultivar Elliott.

For long term pest management decisions, a critical question is whether these high risk or hot spot areas are consistent over time. To address this, we analyzed our blueberry maggot fly trap data collected between 2006 -2010 using the four largest blueberry farms in this study (farms 1, 4, 5, and 8) covering about 1100 acres. The results showed that the location of high risk areas remains fairly consistent across years and thus location of blueberry maggot populations is consistent over the years. However, the size (acreage) of the hot-spots varied among years. For example, in farm 4, the size of the hot spot in 2006 was small but increased in subsequent years (Figure 6B). In other instances the size of the hot-spots stayed consistent over the years; however, this was not the case for hot-spots on the Elliott cultivar that changed over the years (Figure 6C).

Influence of forest types on blueberry maggot abundance
As indicated previously, high number of blueberry maggot fly captures are associated with traps near the forest; however, not all the traps near forest borders captured high numbers of flies. In fact, some of the traps near the forest border captured number of flies as low as the numbers captured on the traps located deep inside fields. We used NJDEP land use-land cover raster data to categorize forest types adjacent to the farms. Forest near the farms’ perimeters were categorized under two types: upland forest and wetland forest.

Our data indicate that upland forest was a more predictable source of blueberry maggot flies as compared with wetland forest (Figures 8 and 9). These findings will help blueberry growers in New Jersey to monitor and manage blueberry maggot more intensively in fields adjacent to upland forest.

Prediction of blueberry maggot distribution
The interpolated surface map created from the several years of trap data from six of the blueberry farms revealed local hot spots. These hot spots (in red) are clearly located in blueberry fields adjacent to the forest or in fields of the late cultivar Elliott. The low-risk areas (in blue) are mostly located in the middle of farms or fields adjacent to open spaces or facing other blueberry farms (Figure 10). An understanding of the spatial dependence of blueberry maggot distribution is an important advantage for developing efficient monitoring programs. These maps will provide growers and IPM consultants visual information on potential blueberry maggot infestation. The interpolated surface maps could then be useful for blueberry maggot management programs to indicate the areas where infestation are more likely to occur and could more precisely determine areas in greater need for management intervention (Figure 11A-D).

Monitoring results for other key insect pests of blueberries

Sharp-nosed leafhopper
No clear distribution pattern was observed for populations of the sharp-nosed leafhopper within farms. Spatial distribution pattern showed that leafhopper populations are irregularly distributed across blueberry fields. However, the number of leafhoppers captured per week per trap varied greatly among fields within farms (Figure 12). No clear differences in leafhopper captures were observed between traps located along field borders compared to those inside the fields.

Cranberry fruitworm
Throughout this project, cranberry fruitworm populations were low in monitored blueberry farms; therefore, no clear distribution pattern was observed among farms or within farms (Figure 13). Out of the eight farms, only one farm (farm E) had noticeable numbers of cranberry fruitworm adults (> 3 per trap in some fields).

Oriental beetles
Oriental beetles appear to be evenly distributed among the fields (Figure 14). The number of oriental beetle captures per week per trap was not significantly different between traps placed on borders and traps inside the fields. Therefore, landscape composition does not appear to affect oriental beetle distribution in blueberry farms.

Aphid parasitism
Aphid parasitism ranged from 1.7% in 2011 to 7.7% in 2012. We found no effect of cultivar (P = 0.68), nor an effect of management program (ICM vs STD) (P = 0.338) on aphid parasitism.

Objective 2: Study the spatial movement of insects into fields.

The high tunnel mark-release-recapture study showed that irrespective of the release points either on field interior, forest border or field border, blueberry maggot flies flew as far as 180 ft. in 24 hours (Figure 15). When observed up to 48 hours, the distance traveled did not increase but the number of recaptured flies increased (Figure 16). The average distance flies can travel in 48 hours is about 68 ft. These results indicate that once adult flies enter a blueberry field from the surrounding landscape, flies tend to stay near the field border (about 7 rows).

Objective 3: Develop and evaluate new reduced-risk practices for pest control

Oriental beetle male captures were significantly lower in all plots treated with SPLAT, regardless of density, compared to captures in non-pheromone treated control plots (P < 0.001) (Table 2). Beetle captures in the control plots peaked during the second week of study, averaging 42 beetles per trap/day, followed by a steady decline until the eighth week of study, when captures recorded in control plots were similar to SPLAT-treated plot. Beetle captures remained consistently low (at or near zero) in all SPLAT-treated plots for the duration of the study. DI values varied only slightly from 88.67% to 89.45%, with no significant differences among treatments (Table 2). In light of the consistently low trap captures observed in all SPLAT-treated plots throughout the study, it would be reasonable to assume that sufficient control of oriental beetle could be achieved at the lesser point source density (250 dispensers/ha) which would be more advantageous from a cost perspective.

Objective 4: Demonstrate and train growers on whole-farm ICM-based practices

During the project period (2009-2011), the investigators organized workshops in Pennsylvania to train regional growers (outside of New Jersey) on blueberry IPM. In each year, about 30 growers and extension agents working on blueberries from Pennsylvania, Maryland, and New York attended these field workshops in September.

Eight growers in New Jersey participated in the GIS-based integrated pest management program. Two private meetings with each of the growers were held in March (before the start of the growing season) and November (after completion of the growing season) of 2009, 2010 and 2011. These meetings also provided growers’ inputs for future improvement of the project. In each year (2009-2011), these growers, as well as other interested growers, attended an annual training program on the use of Rutgers AgroTrak software, a grower friendly GIS-based crop management system. The training provided computer-based learning on the use of maps to record pest distribution, and thus better target insecticide applications, and to better organize pesticide records.

Verification: Measure adoption of whole-farm ICM-based practices and their economic impact.

Maps on the spatial distribution of number of insecticide applications (Figures 17-25) and amount of active ingredient (a.i) (Figures 26-34) for ICM and STD farms in 2009-2011 are shown in Figures 17-34. For 2009-2011, a summary of the number of insecticide applications for the three seasonal cultivars in the ICM and STD farms is shown in Table 3.

Grower adoption of pest management was remarkably influenced by adoption of the ICM-based program in blueberry farms. Among the four paired farms, one ICM farm used a lower number of insecticide applications in all three years of study compared with the STD farm (Figures 17B vs F, 23, and 31). The largest paired farm in our study applied considerably lower number of insecticides in the ICM farm than in the STD farm in 2009 (5.3 vs 8.3 applications for ICM and STD, respectively). However, in 2010 and 2011, the number of insecticide applications did not differ between ICM and STD farms. In 2010, the number of applications was 7.1 and 6.7 for ICM and STD farms, respectively. In 2011, the number of application was 7.3 and 7.5 for ICM and STD farms, respectively. The other two ICM growers had varied numbers of applications between years and between ICM and STD farms.

The amount of active ingredients (a.i.) applied per acre was also lower in ICM farms as comparison with STD farms. In 2009, the amounts of a.i. applied in ICM farms ranged between 1.44–5.00, 0.01-3.00, 1.5-4.0, and 0.5–2.5 lb/ac for fields in the four ICM farms. In contrast, the amount of applied a.i. was 3.00-6.00, 5.14, 1.5-4.4, and 1.5–3.50 lb/ac for the four STD farms in 2009. The cost of insecticides was also lower in ICM farms than the cost of insecticides in STD farms. Growers can apply pesticide treatments to individual fields or part of field based on the pest population abundance. The numbers of applications, amount of used a.i., and the cost of pest management could be reduced substantially by adopting intensive monitoring programs.

Participation Summary

Education

Educational approach:

Results of the project were presented at various scientific and grower meetings

List of outreach, trainings, and research presentations from 2009-2011

2011 Faruque U. Zaman. March 4, 2011. Geo-spatial analysis of insect pest distribution and management in blueberries. Department of Entomology, The Pennsylvania State University, University Park, PA 16802.

2011 Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, and Peter Oudemans. Landscape influence on blueberry maggot fly spatial distribution, Blueberry Open House, Hammonton, NJ. February 23, 2011.

2010 Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, and Peter Oudemans. An analysis of Blueberry maggot (Rhagoletis mendax) fly distribution in New Jersey blueberry. The 58th ESA Annual Meeting, December 12-16, 2010. San Diego, CA.

2010 Dean Polk, Faruque U. Zaman, Cesar Rodriguez-Saona, Peter Oudemans and Marilyn Hughes, The impact of spatial IPM on pesticide inputs in New Jersey blueberry production. The 58th ESA Annual Meeting, December 12-16, 2010. San Diego, CA.

2010 Faruque U. Zaman. December 3, 2010. The use of spatial analysis for pest management decision making in blueberries. Department of Entomology, Rutgers University, New Jersey.

2010 Faruque U. Zaman and Cesar Rodriguez-Saona. Blueberry IPM Training, Dymonds Farm, Luzerne, PA, September 20, 2010.

2010 Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, and Peter Oudemans. Where Are the Blueberry Maggots in Your Farms? Blueberry Open House, Hammonton, NJ. February 18, 2010

2010 Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, and Peter Oudemans. Impact of Intensive Monitoring in Blueberry Pest Management, Mid-Atlantic Fruit &amp; Vegetable Convention. Hershey, PA. February 2-4, 2010

2009 Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, Peter Oudemans, and Eugene Rizio., A GIS-based Insect Pest Management Program for Highbush Blueberries. The 57th ESA Annual Meeting, Indianapolis, Indiana. December 12-16, 2009.

2009 Dean Polk, Cesar Rodriguez-Saona, Faruque U. Zaman, Peter Oudemans, Eugene Rizio, and Marilyn Hughes., The Effect of a Spatially-Based Blueberry IPM Program on Grower Pesticide Use. The 57th ESA Annual Meeting, Indianapolis, Indiana. December 12-16, 2009.

2009 Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, and Peter Oudemans. Monitoring Insect Pests in Blueberries Using Spatially-based Methods. 85th Annual Cumberland-Shenandoah Fruit Workers Conference, VA, November 19-20, 2009.

2009 Faruque U. Zaman and Cesar Rodriguez-Saona. Principles of Blueberry IPM and roles of scouting Blueberry IPM Training, Perry Acres, Berks County, PA, September 21, 2009.

2009 Cesar Rodriguez-Saona. Blueberry Insect Pests and their Control. Mid-Atlantic Fruit and Vegetable Convention, Hershey Lodge and Convention Center, Hershey, PA. February 3-5, 2009

Publications (we anticipate at least 2 peer-reviewed publications in scientific journals from this project)

Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, and Peter Oudemans., Spatio-temporal distribution and movement of Rhagoletis mendax in highbush blueberries. (in progress)

Faruque U. Zaman, Cesar Rodriguez-Saona, Dean Polk, and Peter Oudemans., 2009. Monitoring Insect Pests in Blueberries Using Spatially-based Methods. Proceedings of the 85th Annual Cumberland-Shenandoah Fruit Workers Conference, Winchester, VA. November 19-20, 2009.

No milestones

Additional Project Outcomes

Project outcomes:

Impacts of Results/Outcomes

Training Sessions
In 2009, approximately 50 blueberry growers, mainly from New Jersey, attended presentations given by the project leaders at the Blueberry Open House (Hammonton, New Jersey) in February. A survey was conducted at this meeting. Among the 25 respondents, 15 of them were either using or considered using reduced-risk pesticides, which was 60% of the total respondents.

In 2010, about 45 blueberry growers from New Jersey attended presentations given by the project leaders at the Blueberry Open House (Hammonton, New Jersey) in February. A survey showed that among the 26 respondents, 19 of them were either using or considered using reduced-risk pesticides which is 73% of the respondents.

In 2011, a total of 40 blueberry growers from New Jersey attended the Blueberry Open House (Hammonton, New Jersey). A grower survey showed that among the 39 respondents, 33 of them were familiar with “reduced-risk” practices, which is about 87% of the respondent. About 37 of the respondent indicated to have used reduced-risk insecticides in their farm, which is about 94% of the respondents.

During the project period, the percentage of reduced-risk product users in New Jersey increased from 60% to 94%.

During the project period (2009-2011), the investigators organized a session on Blueberry IPM at the Mid-Atlantic Fruit and Vegetable Convention at Hershey, PA. About 100 growers attended these sessions. Each year a grower survey was conducted at the end of the session to understand the perception of Mid-Atlantic blueberry growers on reduced-risk practices.

In 2009, out of 30 respondents, 8 respondents either used or considered to be using reduced-risk pesticides in their blueberry farms, which is about 27% respondents. In 2010, among the 49 respondents, 29 either used or considered using reduced-risk pesticides in their blueberry farms, i.e., 60% of the respondents. In 2011, out of 15 respondents, 10 participants (66%) indicated that they had used reduced-risk insecticides in blueberries.

During the project period, there was a 39% increase among Mid-Atlantic growers that either used or considered using reduced-risk pesticides in their blueberry farms.

Workshops
During the 3-year project period (2009-2011), the investigators organized “Blueberry IPM” workshops in Pennsylvania to train regional blueberry growers (outside of New Jersey) about monitoring and management of blueberry pests. About 30 growers and extension agents working on blueberries in Pennsylvania attended these field workshops held each year in September. The “Blueberry IPM” workshop provided information and on-farm demonstrations on pest identification, scouting and monitoring techniques, and the use of reduced-risk pesticides. The workshops were organized by personnel from Rutgers University (SARE project leaders) in collaboration with co-PIs from Penn State University, and were held at commercial farms.

Each year (2009-2011), about seven growers attended an annual training program on the use of Rutgers AgroTrak software, a grower friendly GIS-based crop management system. The training provided computer-based learning on the use of maps to record pest distribution, and thus better target insecticide applications, and to better organize pesticide records. The GIS workshop was held at the Rutgers Marucci Center for Blueberry and Cranberry Research and Extension center at Chatsworth, New Jersey.

One-on-one mentoring
Eight growers in New Jersey participated in the GIS-based integrated pest management program. Two private meetings with each of these growers were held in March (before the start of the growing season) and in November (after completion of the growing season) of 2009, 2010 and 2011. These meetings provided grower inputs for future improvement of the project.

Outcomes
Under this project, eight blueberry growers used ICM-based whole farm pest management practices. We applied intensive pest monitoring to compare ICM programs with current standard programs. We studied the movement and distribution of pests in blueberry farms to better target pesticide applications. Our spatial analyses identified two potential sources of blueberry maggot flies in New Jersey blueberry farms. High numbers of blueberry maggot flies were found on traps close to the forest or inside or near Elliott fields (late cultivar). Results from our spatially-based intensive monitoring revealed that high risk areas do exist for some blueberry pests and these can be defined spatially. For example, blueberry maggot distribution was significantly higher in farms surrounded by forest and lower in farms with no forest border. Upland forest was a more predictable source of blueberry maggot flies than wetland forest. Our data show that growers can treat individual, high-risk fields within blueberry farms with insecticides instead of the more conventional cover sprays over the entire farm. Consequently, number of insecticide applications, amounts of active ingredients and cost can be reduced by using spatially-based IPM. This information may help adopt reduced-risk practices and benefit the environment. Therefore, landscape agriculture can be a useful tool to improve pest management and reduce costs.

Overall Project Assessment
All our project objectives were achieved in a timely manner. Participating growers from New Jersey, Pennsylvania, and Maryland were extremely satisfied with the outcomes from this project. Several practices developed under this proposal, such as ICM-based target-specific sprays and use of reduced-risk products, have already been adopted by several growers in New Jersey and neighboring states. Unfortunately, mating disruption for oriental beetle has not been used thus far in blueberries because a product has yet to become registered for this purpose. Through this project we worked with a manufacturing company and we are now expecting registration of a product in May-June 2012.

Economic Analysis

The objective of the economic analysis is to compare the cost of standard spray programs (STD) with those using more intensive scouting practices (ICM). To do this, the cost of spray materials, application costs, insect traps, and scouting time were estimated for each program. Spray records were evaluated for four growers who evaluated both ICM and STD pest management programs from 2009 through 2011. The STD data was obtained from 56 fields containing 256 acres. The ICM data was obtained from 141 fields containing 423 acres. The data includes both insecticide and fungicide data and application method.

The spatial distribution of the cost for individual fields in four paired growers (2009-2011) is shown in Figures 35-41). A comparison of the cost of insect traps and scouting for the ICM and STD management programs can be found in Table 4. Because of marketing standards and export regulations, both the ICM and STD programs have insect traps and scouting costs. The trap and scouting cost for the ICM management program were $3-$14/A higher per grower than for the STD program or $9.77/A higher on average. Although the ICM approach requires more traps and time, this represents a fairly minor increase in cost that could easily be recouped if the number of pesticide sprays can be reduced.

Because the grower data is not based on paired comparisons, the economic analysis was conducted using weighted means, with the spray data being weighted by the number of acres representing a given observation. In this way, the information derived from each field has a weight that is proportional to its size in the overall data set. This somewhat complicates the calculation of t-statistics for testing the differences between the means of the ICM and STD comparisons because the sample variances must be weighted before they are pooled.

A weighted mean (X*) is calculated by:

n n
X* = ? wi xi/ ? wi
i=1 i=1

The weighted variance (?2X*) is calculated by:
n n
?2X* = ? wi (xi - X* )2 / ? wi
i=1 i=1

The hypotheses to be tested are whether the differences in the weighted means for the number of applications and the cost of spray materials are equal to zero (Ho: X*ICM - X*STD = 0). Test statistics were calculated for comparisons of ICM and STD over all growers and cultivar maturities for each year, over all years and cultivar maturities for each grower, and for the entire data set. Comparisons of mean differences for individual growers for each year and cultivar maturity were not conducted because of problems relating to either lack of comparisons or insufficient degrees of freedom.

Data on the weighted average number of insecticide sprays for the ICM and STD management programs can be found in Table 5. Overall, the number of sprays was statistically less under the ICM program than under STD program in each year and for three of the four growers over the three years (Grower A actually showed a slight increase in the average number of sprays under ICM). As a group, the growers were able to reduce the number of insecticide sprays by an average of 2.4 sprays over the three years. The number of insecticide sprays was reduced the most during the 2009 season, but appeared to be on an increasing trajectory over the course of the study. Grower C was able to reduce the number of sprays the most, eliminating an average of 5.4 sprays annually over the three years. Given that typical application costs are in the range of $7-$10/A for boom sprayers, $12-$16 for airblast sprayers, and $20-$25 for aerial application, the additional cost of scouting under the ICM protocol can be justified in most cases on the basis of reduced application costs alone.

A comparison of the cost of insecticide materials for the ICM and STD management programs can be found in Table 6. In the case of most growers (except for grower A) there were significant cost savings from using ICM compared to STD. Overall, costs of spray materials under ICM averaged $48/A less annually compared to STD. Cost savings from reduced insecticide use averaged from $0 to $103/A annually during the three years of the study for the individual growers. It is apparent that despite higher scouting costs, the ICM program in general results in less applications and lower insecticide costs.

Data on the weighted average number of fungicide sprays for the ICM and STD management programs can be found in Table 7. Overall, the number of sprays was statistically less under the ICM program than under STD program in 2010 and 2011, but this was due to the impact of only one grower (Grower C). This grower was able to reduce fungicide applications by an average of 3.2 sprays annually over the course of the three years, while there was no statistical difference for the other three growers. The comparison of the cost of fungicide materials for the ICM and STD management programs in Table 8 shows similar results. Grower C reduced the average cost for fungicides by $74/A over the three years, while the other growers showed no statistical difference in fungicide costs. Although this is not as strong of evidence for cost reductions as for insecticides, it does indicate that reductions in applications and fungicide cost are possible for some growers under the ICM protocol. If only one grower in four could realize these savings, it would represent a major reduction in that individual’s production cost and a corresponding reduction in overall fungicide use in blueberry production.

Overall ICM appears to have a significant impact on reducing the number of pesticide applications and the cost of spray materials (Table 9). Taking into account the additional scouting costs and considering two application cost scenarios (low, $7/acre (boom sprayer) and high, $25/acre (aerial application)), on average ICM resulted in reduced production cost of between $75 and $118/A annually. Grower C realized the greatest savings of between $223 and $378/A. Three of the four growers had reduced production costs over the three years of study. Only Grower A experienced higher costs (an average of $5-$11/A annually), but this is a very modest increase in production costs. The benefits of adoption of technologies like ICM are often only realized in the long-term. With increasing pesticide, labor, and fuel costs the benefits of programs like ICM will likely increase in the future.

Farmer Adoption

Farmer adoption of reduced-risk pest management increased considerably after the initiation of the project. From grower surveys, there was a 34% increase on grower users of reduced-risk products. Regarding pest monitoring practices, about 1200 acres of blueberry cultivation are currently under a spatially-based intensive monitoring program. We expect an increase in the number of blueberry growers using spatially-based GIS monitoring as new tools become more user friendly.

Overall, the growers’ perception and understanding of spatially-based GIS monitoring tools for managing blueberry pests was very positive; however, there is the need for further training of growers, scouts, and IPM consultants on these technologies.

Assessment of Project Approach and Areas of Further Study:

Areas needing additional study

In 2011, blueberry growers in our region faced new pest challenges. Two new pests were found attacking blueberry farms in New Jersey. These are the Brown Marmorated Stink Bug and the Spotted Wing Drosophila. These newly invasive pests will likely change current IPM practices in our region. Most of the new reduced-risk products being adopted by our growers are not effective against these pests that are mainly controlled by broad-spectrum insecticides (organophosphates, carbamates, and pyrethroids). Knowledge of their spatial distribution within blueberry farms may help reduce the amount of broad-spectrum insecticide applications. These are areas in desperate need for future research.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.