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Transitioning from Hand to Machine Harvesting of Blueberries for Fresh Market

Blueberry production acreage in the U.S. is expanding. Across the country, commercial blueberry growers are increasingly using over-the-row (OTR) mechanical harvesters (MH) to pick their blueberries for fresh market (Figure 1). Growers everywhere are experiencing difficulties in finding sufficient labor for hand harvest operations and due to the rising costs of labor. Harvesting blueberries with OTR harvesters can significantly reduce the overall cost of harvesting to a fraction of that needed for hand harvesting (HH) and workers needed for harvest operations from about 500 hours of labor per acre per year to as little as three hours of labor per acre per year. However, compared to hand harvesting, OTR harvesting causes more berry loss due to falling on the ground and green/red berries are harvested along with ripe, blue fruit.

Detailed field testing of OTR harvesters for picking blueberries for the fresh market was conducted nearly 30 years ago in Michigan. That research in South Haven, Mich. evaluated the quality of blueberries harvested by hand and by four rotary and slapper harvesters that were used by growers at that time to harvest blueberries for processing. MH blueberries were sorted at the packinghouse (Figure 2).

Figure 2. Mechanical harvesting detaches unripe green fruit and clusters that must be sorted out on the grading line.

The most significant findings were a high percentage of detached blueberries had impact damage (Figure 3) and more than 20% of detached blueberries fell on the ground. The bruise damage was attributed to iImpact to the fruit created by the rapid actions of shaking rods and detached berries landing on the hard catching surface. Those studies revealed that blueberries harvested by the machines had a high percentage of blueberries with more than 20% of sliced surface area showing bruise damage (Figure 3 and 4). Also, MH blueberries were much softer compared to hand harvested fruit. Their conclusion was that MH blueberries should not be cold-stored for more than two weeks while HH blueberries could go in controlled atmosphere storage for six weeks and air-shipped to Europe in excellent condition.

Figure 3. Bruise damage caused by mechanical harvesting makes the flesh dark and soft. Half of these berries have excessive bruising.
Figure 4. Sliced examples of mechanically harvested blueberries. From left to right: Fruit with no internal bruise as indicated by no large discolored tissue; Fruit with impact damage at the stem end as indicated by discoloration inside the seed core; Fruit exhibiting damaged area from impact force to that triangular shaped, discolored section; and Discolored area has been highlighted in purple with SketchAndCalc program to calculate bruised area as 17% of the total cut surface area.

Soon after, USDA engineers developed an experimental harvester called the V45 harvester designed specifically to harvest fresh-market blueberries. It used a direct-drive shaker with an angled, double-spike-drum, a unique cane dividing and positioning system to push the canes out diagonally and cushioned catching surfaces to harvest fruit with minimum damage. With the V45 harvester design, the detached blueberries dropped less than 15 inches onto a soft neoprene sheet glued to a hard catch plate and soft sheet over the conveyor belt.

These soft surfaces reduced impact force on the fruit detached by the V45 harvester. However, gluing a soft surface onto a hard surface has proven to show little reduction in bruise damage when harvesting is performed with conventional harvesters with two vertical drum shakers and berries falling more than 30 inches. Only five V45 harvesters were sold by the now defunct B.E.I Inc. (South Haven, Mich.), although it was thought to have good fruit selectivity (low green fruit removal) compared to slapper models, little ground loss (fruiting cane pushed away from the crown) and superior quality over existing commercial harvesters at the time with two vertical drum shakers and either a metal or hard plastic catch surface.

Sometimes, the fruit harvested by the V45 harvester had quality as good as commercially HH fruit. Its limitations were: 1) It needed to be driven much slower to avoid damaging bushes; 2) It could not harvest trellised rows or those with overhead sprinklers; and 3) It could not harvest all varieties, especially those with stiff, upright canes like ‘Jersey’ and many rabbiteye cultivars. The Fulcrum harvester made by A&B Packing Equipment (Lawrence, Mich.) has features like those of the V45 harvester.

In the last ten years or so, U.S. blueberry farmers targeting the fresh market have been facing challenging economic situations (e.g., rising cost of hand picking, shrinking labor force, global competition, etc.) They and other specialty crop farmers have a greater interest in using automation and OTR machines to harvest their crop. The authors of this article have participated in different aspects of machine harvesting and sorting of blueberries to reduce the amount of internal bruise damage and in packing line sorting technology and damage detection systems to improve the quality of packed fruit. Several blueberry MH manufacturers (e.g., Oxbo International, Lynden, Wash.; A&B Packing Equipment, Lawrence, Mich.; BSK, Serbia; and FineFields, the Netherlands) have put more efforts devoted to developing MH systems that would impart low or no bruise damage so that fruits can be packed for fresh market. Following is a summary of recent developments in MH.


Bruised Berries from Mechanical Harvesting

Most OTR harvesters currently available are better suited for harvesting processed blueberries because they can cause excessive fruit damage. However, OTR machines have been used to pick blueberries for fresh market. In these instances, the fruit should be packed and transported to consumers as quickly as possible. When blueberries are HH, typically the picker gently picks ripe fruit selectively. In Chile and China, for example, ripe berries are picked individually to obtain high fresh quality.

In the Pacific Northwest and elsewhere in North America, ripe fruit is often harvested by rubbing fruit cluster or sometimes by “tickling” them between the thumb and index finger and catching the detached berries in the palm and then placing them in a small harvesting bucket. In contrast, MH involves the shaking of the entire bush with rapid action of shaking rods to move canes back and forth. The cane movement causes ripe berries that need less fruit removal force than green/red berries to be displaced from the fruit stem (pedicel) and fall onto catching surfaces. Experienced MH operators make slight adjustments on machine settings to obtain good selectivity (minimize green/red berry removal and maximize ripe fruit removal).

The blueberry bush can range from 3 to about 6 feet tall with fruit located from the tip of the canes to branches near the ground, which causes the berries located on the top part of bush to fall as much as 50 inches. When an OTR harvester picks blueberries and fruit falls from that height onto plastic catch plates and conveyor belts, one can hear berries hitting the hard catch surfaces.

Based on this simplified description of the blueberry MH process, it was apparent that the interaction between the machine and fruit should be better understood. To do this, we used a custom-made miniature electronic sphere called the BIRD (blueberry impact recording device developed at the University of Georgia) to measure the fruit impacts during MH process in 2010 and 2011. The BIRD sensor for this study weighed 14 g. The later version, BIRD II, was built to closely approximate the size and weight of a large blueberry (9/16-in diameter and weighed 6 g) (Figure 5).

Figure 5 . BIRD II (red sphere) connected with a 4-pin connector to a laptop to charge its internal battery, initiate impact measurements or download collected data to a laptop or mobile device.

Along with documenting fruit impacts with a BIRD, a closeup video camera recorded the harvesting to pinpoint critical control points where most impacts were created. The results showed that the drop to the plastic catch plates on the harvester accounted for over 30% of all impacts on the BIRD, followed by the drop from the grading belt on the harvester into an empty lug (20%). When the lug is filled with blueberries, fruit-to-fruit impacts occur, which are much lower than when the fruit fall into an empty lug.

Impacts created by the conveyor, including secondary bounce from the catch plates, and shaking rods combined for another 25% of recorded impacts. The remaining 25% of impacts that occurred before the sphere contacted the catch plate were classified as obscured impact events which could not be identified clearly from the video and were attributed to contact with the shaking rod, branches and the vertical tunnel panels. These measurements suggested that the most significant reduction in fruit impacts could be achieved by 1) Modifying the catch plates; 2) Reducing drop heights, either by restricting bush size, placing catching surfaces closer to the fruit or decreasing drop heights at other transition points; and 3) Placing softer surfaces at the transition points (e.g., at transfer points in the fruit handing equipment on the top of platform.)

The two parts of the impacts include the number of encounters between the sphere and different surfaces of the harvester and the magnitude of these impacts. In our study, the harvesting process was documented with video that recorded time-stamped impact events with the larger, heavier BIRD I sensor. Using these parameters, the OTR MH process was divided into four phases: Phase I (detachment and falling), Phase II (fruit hitting the catch plate/conveyor belt), Phase III (elevation from the conveyor/transfer belt to the top platform and conveyance through a trash blower) and Phase IV (dropping from the conveyor belt into the lug).

Results showed that for the rotary drum shaker, the BIRD sensor recorded an average of 18 impacts in Phases I to IV. During Phase I, it is assumed blueberries detached by fast-moving harvesting rods that shake left and right, impact branches as they fall and/or are flung out to the side panel. There were about five impact events in Phase I, but magnitudes of these impacts proved to be less significant than initially assumed. In Phase II, the BIRD contacted the catch plate and usually only one or two events were recorded. The magnitude of the impacts in Phase II was extremely high compared to impacts recorded in Phases I, III and IV. Our results strongly suggested that the high impact that the falling blueberries receive at the point of contact with the catch plate injures the fruit, resulting in fruit softening and larger bruise while the fruit is in storage (Figures 3 and 4).

Further analysis was performed by dropping the large, heavier BIRD I sensor onto a hard-plastic catch plate from different heights (6, 12, 24, 36 and 48 in) (Figure 6). As expected, the impact values (peak acceleration at impact (g) increased sharply linearly with increasing drop height, ranging from 280 g at 6 in to about 800 g at 48 in (data not shown). In subsequent studies, impact measurements were made using the smaller and lighter-weight BIRD II sphere by dropping onto soft surfaces created by placing cushioned padding on top of the hard plastic plates or by suspending the soft material (no hard surface underneath.)

Figure 6. The relationship between various contact surface materials and drop height. The impacts were collected with a BIRD II sphere dropped from different heights.

A wide range of impact values were obtained depending on the hardness of the catch plate (Figure 6). Impacts greater than 200 g were recorded on hard surfaces such as a stainless-steel sheet and a plastic catch plate even when the BIRD II was dropped from a height less than 30 cm (12 in). Gluing a soft surface to a hard surface reduced impact; however, this type of surface still created high impact above a one-foot drop height such that blueberries falling 30 inches onto such a surface would still be bruised. For example, the suspended foam sheet we used in our harvest-assist blueberry picking machine in 2017 generated less than 200 g even when the drop height was 42 in, but well above the 120 g at which ripe blueberries can be bruised by impact force. Only the netted fabric that acted like a hammock produced low enough impact force and kept the blueberries from getting bruised even when the fruit was dropped from a 48-in height. Thus, it was thought that replacing the hard, plastic fruit catching and collection surfaces with soft and durable catching surface materials and plate design features that prevent soft surface from contacting any hard surfaces underneath had the potential to improve the quality of MH blueberries and reduce bruise damage associated with high mechanical impact.

In terms of mechanical impact to blueberry fruit, our research has shown that bruise damage and the loss of firmness in MH fruit can be decreased by reducing space between blueberries on the bush and the catching surface to 12 inches in the case of hard plastic fruit catching surfaces or by modifying the fruit catching surfaces to create a softer fruit landing surface. Ideally, the fruit catching surface should not exceed 120 g impact even when the BIRD II is dropped from a height of 48 in (equivalent to the distance between the top of a large mature blueberry bush and catch plates on the harvester).

The design of soft surfaces can be achieved by either incorporating netted material or a soft “rubber” sheet with no hard surfaces beneath for catching the fruit (Takeda and Wolford, U.S. Patent No. 9,750,188 and the Oxbo SoftSurface kit). For example, even with a soft surface insert in a hollowed-out plexiglass catch plate, the margins of the plate contributed to more than 20% of the exposed surface area. In addition, catch plates on the harvester overlapped with adjacent plates and rested on top of another plate. The outline of the plate below another created about 10% additional hard surfaces.

When blueberries are HH, the packout is about 95% or better and fruit usually have little or no internal bruise damage (Table 1). The packout of MH blueberries is lower and typically ranges from 70% to slightly more than 80%. The remaining 20% consists of soft, overripe and immature green- and red-colored berries.

Table 1. Effect of catch surface (hard or soft) and drop height on internal bruise damage within one day of drop and after 14 days in cold storage (32 degrees F to 37 degrees F). Bruise damage is expressed as the percentage of cut surface area indicated by dark color (see Figure 4).

Commercial packing operations, for the most part, do not check for internal bruise damage in their MH blueberries. However, close inspections of MH blueberries packed into clamshells after sorting on commercial packing lines revealed berries were bruised (Figure 3, see page 4). Our studies evaluated different catch surface designs by inserting soft, flexible material to reduce internal bruise damage. We did record improvements in packout. However, neither the improvement in packout nor berry firmness approached that of HH fruit in the case of varieties Duke, Draper or southern highbush blueberry (SHB) Optimus even when they were harvested with OTR machines equipped with soft, flexible catch surfaces. The only exception to date has been the variety Last Call, where MH produced the quality approaching that of HH berries. MH of SHB Optimus produced higher-quality packout than other SHB varieties, such as Jewel, Star and Farthing, but even Optimus should not be cold-stored for more than one week. Our studies have shown that fresh market pack-out can be increased by installing a soft catch surface on the harvester, but the quality of HH blueberries has been better.


Cultivar Susceptibility

In a study conducted in Oregon, the susceptibility of 11 blueberry cultivars to impact damage was determined by dropping the fruit from 2-, 3-, and 4-foot heights onto a hard, plastic catch plate. Bruises developed more rapidly in rabbiteye cultivars (Ochlocknee, Powderblue and Overtime) than in northern highbush (NHB) and SHB cultivars. NHB cultivars Aurora, Cargo, Draper and Last Call had the least amount of bruising after two weeks in cold storage. Blue Ribbon, Legacy and Liberty had a moderate amount of bruising.

These studies showed that simulated drop tests are useful in determining the potential of varieties for long-term cold storage and, more importantly, their potential to MH for fresh market. In a study in 2020 in Oregon, Draper and Legacy were MH with two OTR Oxbo harvesters, one fitted with and the other without the SOFTSurface kit. To date, the challenge for Oxbo Corporation and other machine manufacturers has been to procure soft materials that meet food safety standards and are durable for harvesting blueberries.

The preliminary findings of this study were: 1) Machine harvesting with the SOFTSurface kit reduced fruit internal bruise damage in both Draper and Legacy fruits compared to those harvested with the unmodified OTR harvester as shown with a laboratory test (Table 1); 2) Draper and Legacy fruit harvested with the machine fitted with the SOFTSurface kit and sampled before sorting in the packing house were firmer compared to fruit harvested by the unmodified harvester; and 3) After one and two weeks in cold storage, there was no difference in firmness of berries harvested by machines fitted with and without the SOFTSurface kit.

We found that fruit firmness-based sorting by itself may not be a good predictor of berry quality when MH blueberries are cold-stored for two weeks or more, but both Draper and Legacy blueberries picked by the OTR machine fitted with the SOFTSurface kit maintained better fruit firmness (>160 g/mm) values and lower internal bruise ratings in cold storage (Table 1). The improvements in fruit quality may well have been from a 70% reduction in hard catch surface area in the SOFTSurface kit compared to the hard polycarbonate fruit catching surfaces in the regular harvesters. A laboratory test determined the effects of dropping blueberries from different heights onto either a hard (e.g., polycarbonate catch plate on conventional harvesters) or soft catch surface (e.g., prototype SOFTSurface kit) on internal bruise development (Table 1). Blueberries were sliced to visually assess bruise damage on the day of the drop test and after cold storage for two weeks.


Young (~3-ft-tall) and mature (6-ft-tall) trellised Last Call blueberry plants were either HH or picked with a modified OTR machine. Fruit samples from both methods were manually sorted and evaluated for internal bruise damage on the day of harvest and the remaining samples were placed in cold storage. Cold-stored samples were taken out after two and four weeks and evaluated for internal bruise damage (Table 2). On the day of harvest (zero days after harvest), about 80% of blueberries showed no bruise damage, and the remainder showed damage ranging from 1% to more than 50%. There was little change in internal bruise for samples from matures bushes that were either HH or MH. However, there was a dramatic decline in the percentage of fruit with no internal damage among the samples from machine harvesting of young plants.

Table 2. Percent of blueberries in each internal bruise damage (IBD) category as affected by hand harvesting and harvesting with a modified OTR machine and the age of ‘Last Call’ northern highbush blueberry immediately after harvesting and after two and four weeks in cold storage.

Our field observations of the Last Call bushes used in this study indicated that the canes of young plants were upright during the harvest and detached fruit fell straight down. In contrast, on the taller, mature bushes, the canes had grown well above the height of the trellis and they were leaning outward at the time of harvest. This placed the fruit away from the crown and less than 30 inches above the catching surface and may have contributed to reducing mechanical impacts in terms of numbers and magnitude, thus reducing the amount of internal bruise damage.


Sorting Out Bruised Berries

Blueberry growers in the Pacific Northwest and in Chile have expressed an interest in machine harvesting blueberries for the export market. The consensus among them is that the varieties for the export market must be firm and arrive at the destination in excellent condition after more than three weeks of cold storage and a transoceanic travel period. Our machine harvesting research has consistently shown that the MH blueberries generally had more internal bruise damage and shorter shelf life than the HH blueberries.

Commercial optical sorting equipment are now available for grading blueberries. In the last three years, HH and MH blueberries have been processed on commercial blueberry packing lines in Oregon and Washington equipped with an optical sorter (e.g., UNITEC, BBC and MAF). For each packing line, samples of Draper and Legacy were taken from lugs prior to unloading onto the conveyor system, and a second group of samples were collected after the fruit had gone through the optical sorting machine. Samples from both locations were assessed for bruise damage (% bruised area). The bruise data are presented in Table 3 in which the data are expressed in terms of how the samples were distributed (e.g., blueberries with no damage to those that were severely bruised.) The analysis indicated that sorting by optical sorters did not remove blueberries with moderate to severe internal bruise damage.

Table 3. Determination of internal bruise damage in machine-harvested Draper and Legacy blueberry samples collected from packing line locations either before or after inspection with an optical sorter. Samples were sliced through their equator and the bruised area was assessed visually as the percentage of sliced area and converted to a value between 0 and 5 using a 5rating scale: 0= no bruise, 1= 1% to 5% bruised, 2= 6% to 10%, 3= 11% to 20%, 4=21% to 50% and 5= greater than 50%.

Next, we compared the blueberry fruit firmness value with the area of internal bruise damage on the sliced surface. One would likely assume that softer fruit will have more bruise damage. Our results and those from a report by Chilean researchers showed that this was not the case as shown by the low correlation coefficient (r-value) for these two fruit quality parameters. Whether the fruit had been collected from the packing line before or after the optical sorting machine, the correlation coefficients for berry firmness and bruise damage were less than 0.4 in NHB cultivars. This suggested that optical sorters in commercial blueberry packing houses were not effective in removing blueberries with internal bruise damage.

Once more in the laboratory, we conducted drop tests in which HH Duke blueberries were dropped from a height of 62 inches to ensure that the samples would be bruised. A hyperspectral imaging system was used to locate and quantify bruise damage in each whole fruit (25 berries at a time). We then measured fruit firmness with a FirmTech II at the site of the bruise impact as determined by the imaging system. Then, the same fruit was rotated and additional firmness measurements were taken at 90 and 180 degrees from the bruised site.

The analysis showed that at the site of the bruise damage, the average fruit firmness was 149 g/mm. However, at the sites that were 90 and 180 degrees from the impacted location, the firmness was greater than 162 g/mm. This meant that a lower firmness value was detected when the damaged area was purposely used to determine firmness, resulting in a much higher r-value between fruit firmness and internal bruise damage values. Fruit that were firm at the time of packing (e.g., >180 g/mm value using a FirmTech II instrument) were found to have internal bruise damage exceeding 15%. In the near future, our research team will sort MH blueberries with this imaging system to separate whole unbruised and bruised blueberries and conduct postharvest quality evaluation for unbruised and bruised MH blueberries to determine the shelf life of each group with an eye toward exporting MH blueberries to distant Asian markets. Of course, taking this non-destructive imaging system from the laboratory bench to integrating it into commercial optical sorting machines for IBD detection and sorting is a challenge facing the machine manufacturers.



More blueberries for fresh market are being machine harvested.

Machine harvested blueberries have more internal bruise damage.

On-going research is developing a better understanding of what causes bruising and working with harvest machine manufacturer to reduce bruise damage.

New sensor technologies for blueberry sorting could assist in reducing bruised berries in fresh packs.

Our research has shown that to make MH more profitable for blueberry growers, the current OTR harvesters must be modified to reduce impact damage and ground loss. Cultivars with superior machine harvestability are being released by blueberry breeding programs, and research must continue to develop equipment capable of harvesting blueberries with less bruise damage. The sorting system on the packing line for MH fruit must be improved with a greater precision to eliminate fruit with severe internal bruise damage. This would ensure that the quality of MH blueberries going into clamshells would be as good as HH fruit. Blueberry growers in some regions can then contemplate having MH blueberries packed for export. Also, proper training and pruning of blueberry bushes to maintain a small crown can increase MH efficiency. These changes will help in making small, incremental improvements in increasing pack-outs and fresh quality of packed blueberries.

Finally, in order for MH blueberries to have quality that is as good as HH fruit, the blueberry industry needs to be willing to make changes by growing superior varieties, modifying how blueberry bushes are grown and harvested, and improving how the fruit is sorted. This will take a concerted effort from growers, breeders, horticulturists, engineers and supply chain specialists. These changes could lead to blueberry fields that look different from what we see today, with radically different ways of harvesting blueberries and technological advancements for sorting blueberries with the goal of improving the quality of MH blueberries going into clamshells.

In terms of harvesting and packing technology, it is envisioned that U.S. blueberry growers will be using robotic harvesting systems in the field or in warehouses with specialized automated or semi-automated harvesting machines that will avoid damaging berries, have better selectivity to reduce green berries picked and sort out over-ripe and diseased berries in the field. In packing houses, new non-destructive technologies are needed that will be capable of analyzing the blueberry fruit surface and below the skin and sort fruit for quality (large size, high sweetness, flavor, bloom, no bruise damage and color). These advances will facilitate market segmentation and high prices as one U.S. and several European blueberry distributors are doing already with HH blueberries.

This research was supported in part by the U.S. Department of Agriculture agencies (Agricultural Research Service (Project No. 8080-21000-028, National Institute for Food and Agriculture (Agreement No. : 2008-51180-19579 and 2014-51181-22471), Agricultural Marketing Service (FY 18 Oregon Department of Agriculture SCBG to WQY and FY18 Washington SCBG to LWD), U.S. Highbush Blueberry Council, Chilean Blueberry Committee and Naturipe Farms Blue Challenge.

Our gratitude goes to blueberry growers and packers in Waldo, Fla.; Alma and Homerville, Ga.; South Haven and Grand Junction, Mich.; Kingsburg and Stockton, Calif.; Hillsboro, Independence and Roseburg, Ore.; and Burlington, Prosser, Lynden and Sumas, Wash., and in Chile who provided much needed in-kind support to the harvest project. A special thanks goes to Oxbo International Corporation which has collaborated with the group since 2014.

Authors are employees of USDA-ARS (FT, fumi.takeda@usda.gov) Oregon State University (WQY, wei.yang@oregonstate.edu), University of Georgia (CL, cyli@uga.edu), Washington State University (LWV, lisa.devetter@wsu.edu) and University of Florida (SS, sasa@ufl.edu and JW, jgrw@ufl.edu).

Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

A New Generation of Precision Spray Technology

Fruit, nut, ornamental nursery, horticultural and greenhouse industries are among the fastest-growing enterprises in US agriculture. Application of pesticides and other production strategies have ensured their high-quality products meet stringent market requirements. However, low-efficiency, decades-old spray technologies are commonly used to treat these specialty crops and have caused an enormous amount of pesticide waste, additional costs in crop production and concerns around worker safety. The pesticide waste has also caused environmental contamination and ecosystem damage because pesticide sprays indiscriminately kill both pests and beneficial insects. Spray drift and off-target loss will likely remain a major problem as long as pesticides are applied using indiscriminate spray equipment.


Need for Efficient Technologies

Pesticide application is the most complicated operation in crop production because there are many variables affecting spray strategies and practices. In many cases, when decisions must be made to apply chemicals within a very narrow time window in response to escalating pest pressure, a simple “best guess” practice is often under vague labeling of pesticide rates to control pests that may result in excessive application of pesticides.

Given constrained environments for specialty crop production, an ideal spray management program for pests and diseases should include improved delivery systems that are flexible for spraying the amount of chemicals to match tree structures instead of acreage base. Such spray application will also produce minimum spray drift and off-target loss of pesticide on the ground and in the air.

To achieve this goal, a new automated universal intelligent spray control system was developed as a retrofit kit to attach on existing sprayers. With the intelligent control system, the conventional spraying systems can determine the presence, size, shape, and foliage density of target plants such as trees and grape vines, and then automatically apply the amount of pesticides as needed according to plant architectures in real time. With the control system, growers themselves can upgrade their own sprayers to precision sprayers with intelligent functions rather than buying new sprayers, and sprayer manufacturers do not need to change their current sprayer designs. The primary requirement for the upgrade action is to connect a variable-flowrate solenoid valve to each nozzle, and all other components are attached to the sprayer body without changing the sprayer structure.

This new system is the product of a decade of research and development by engineers at USDA-ARS at Wooster, Ohio in collaboration with researchers at The Ohio State University, Oregon State University, University of Tennessee, Clemson University, Texas A&M University, Iowa State University, Washington State University, Penn State University, University of Queensland and USDA-ARS.

Since 2013, the system has been tested as a retrofit on different types of the air-blast sprayers for pest control effectiveness, reliability and repeatability on real farm fields. Comparative field biological tests were also conducted to evaluate insect and disease control for the sprayers with and without the intelligent-decision control capabilities in commercial nurseries, apple orchards, peach orchards, pecan orchards, vineyards and small fruit productions as well as university research farms in Ohio, Oregon, Tennessee, South Carolina, Texas, California and Washington.

These activities were voluntarily held by UCCE in Napa County and University of Queensland in Australia.

Figure 1. Integration of universal intelligent spray control system as a retrofit kit into existing sprayers (photo courtesy S. Booher.)


System Features

Spray deposition uniformity insidecanopies, chemical usage and off-target losses were investigated for the plants at different growth stages in ornamental nurseries, apple orchards, peach orchards and vineyards. Multi-year field tests have demonstrated the intelligent spray system is reliable and can reduce pesticide use in a range between 30% and 90%, reduce airborne spray drift between 60% and 90%, and reduce spray loss to the ground between 40% and 80%, resulting in chemical savings in a range of $56 to $812 per acre annually. At the same time, the insect and disease control efficiencies are comparable or even better than standard sprayer practices. Because it uses less spray volume, it can spray more acres with the same amount of tank mixtures, thus reducing tank refilling times and reducing labor and fuel costs.

As a result, Smart Guided Systems, LLC commercialized the intelligent spray system, and a commercial version of the product has been developed with joint efforts between USDA-ARS and Smart Guided Systems, LLC. The new control system (See Figure 1) includes a new laser sensor, an Android Samsung tablet, a GPS navigator, an automatic flow rate controller, air filtration unit, a toggle switch box and a universal mounting kit.

The laser sensor is mounted between the tractor and the sprayer to “see” plants on both sides of the sprayer. It releases 54,000 detection signals per second with a 270-degree and 164-ft radial detection range. The laser signals bounced back from the plant canopies is used to determine the presence of a plant canopy and measure the canopy height, width, foliage density and canopy foliage volume (Figure 2). The GPS navigation device (or the radar speed sensor mounted at the bottom of the sprayer) measures sprayer travel speeds and location of each plant in the field. Based on the plant canopy foliage volume and the sprayer ground speed, the amount of spray for each nozzle is determined and then discharged to different parts of each plant in real time. Each nozzle is connected to a 10 Hz pulse width modulation (PWM) solenoid valve, and the nozzle flow rates are controlled by manipulating the duty cycle of the PWM waveforms with the flow controller. The flow controller consists of microprocessors to generate flow rate commands for each nozzle to discharge variable spray rates. Field data collected and processed with the intelligent spray system are synchronized through the tablet WiFi to the cloud.

Figure 2. Laser sensor signals are used to measure canopy architecture and then manipulate individual nozzle flow rates as the function of the sectional canopy foliage volume and travel speed in real time.

The Android tablet provides the information for operators to communicate with the spray control system. The screen displays the sprayer travel speed, total discharged spray volume, spray width, and active nozzles. The operator can use the touch screen to modify the spray parameters as needed. The tablet allows the operator to activate the sprayer output on one or both sides in manual or automatic mode. All the electronic devices are powered by a 12V DC tractor battery. Another precaution includes the air filtration unit to discharge filtered air to prevent the laser sensor surface from getting dust and droplets. The toggle switches on the switch box are used to turn on/off main power, turn on/off the air filtration unit manually and override the automatic controller to activate nozzles as needed. Because sprayer travel speeds are automatically measured and included in the spray output control, applicators do not need to specify how fast they drive the tractor. However, travel speeds are not suggested to be higher than 5 MPH for orchard spray applications.

Features in the commercial system also include tree counting, tree size, foliage density heat map comparison capability, liquid volume sprayed per plant, maps of sprayed plant locations, ability to turn nozzles on/off independently through the tablet screen, cloud sync feature, web portal for configuration settings and spray coverage report view, system log files, five different languages (English, Spanish, French, German and Italian), and options for choosing metric or imperial units. The commercial products have been used by growers in the US and other countries with crops including citrus, nursery, pecan, blueberry, peach, almond, apple and pear with pesticide usage reductions in the range between 30% to 85% depending on crop types and growth stages. John Deere also established an agreement with Smart Guided Systems to sell the commercial intelligent spray control system for use in high-value crop applications through their dealer network.

The intelligent spray control system advances conventional standard pesticide application systems with the flexibility to spray specific positions on the plants. It reduces human involvement in decisions on how much spray volume is needed because the spray volume applied in the field is automatically controlled by the plant foliage volume instead of the antiquated gallons per acre.

The conventional air-blast spray system has been used from generation to generation for almost 80 years because of its robustness. Growers have accumulated extensive experience on using it to control pests in accommodation with their own crops. After being retrofitted with the intelligent spray control system, the conventional sprayers are able to turn on and off each nozzle and will stop spraying non-target areas such as gaps between trees, on the ground and above trees while their capabilities of spray penetration, spray range and spray deposition quality on plants remain the same. This new generation of spray technology is anticipated to be a primary precision spray technology for future decades to save chemicals for growers and provide a sustainable and environmentally responsible approach to protecting crops.

Understanding CCA Certification Exams


I never really understood what certification means until I heard it described by a psychometrician. I have been a Certified Crop Advisor (CCA) for nearly two decades and felt I knew what it means to be a certified professional. I recently attended the North American Certified Crop Advisors On-line Board Meeting. I listened to a presentation by Scott Thayn, Ph.D., CMS, a psychometrician, or a statistician specializing in distinguishing the differences between individuals. Thayn is the president of Certification Management Services, the third-party agency hired by the Agronomy Society to help develop and manage the testing required for certification. The presentation addressed a proposal to give rankings on how well a test taker did on the CCA exam. Board members were hearing from potential members who were unable to pass the exams and wanted more feedback to help them study for their next attempt. The proposal, and the way the statistician took it apart, were a revelation, and it got me thinking that the mechanics behind certification are not well understood.


Certification Exam Intricacies

The Home page for Certifications under the website Agronomy.org states, “Certification is the standard by which professionals are judged. The purpose of a certification program is to protect the public and the profession. It is a voluntary enhancement to a person’s career credentials. Being certified adds credibility and shows that you are serious about what you do.”

A prospective candidate digging deeper would find they need to meet certain criteria to be considered a CCA: academic, experience and examination. Simply speaking, certification indicates one has demonstrated the knowledge and experience to perform at a higher level than their peers.

Hearing the proposal to give test takers feedback on their performance was familiar to me as a board member who participates on the Exam Committee for the Western Region. I have heard from many colleagues who did not pass one or both certification exams and are frustrated by the lack of a score or indication where they underperformed. I struggled to explain to my friends why the exams were pass/fail and why they just had to keep trying. I believe the frustration lies in the expectations of an academic testing experience clashing with the reality of certification exams.

Data indicates most people who take the certification exams are recent college graduates. Having a college degree in agriculture is a requirement for becoming a certified crop advisor. College graduates have spent most of their lives with graded exams. Academic testing presents a broad range of questions to both examine a student’s proficiency and encourage them to improve. A student who gets a low grade on a test will hopefully review the questions marked incorrect and study the subject to raise their grade on the final exam. This familiar approach to testing is contrary to certification exams.

The distribution of difficulty of certification exam questions is quite narrow compared to an academic exam (See Figure 1). The certification exam begins by defining competency areas, the major subjects that define the everyday work of the crop advisor. Performance objectives rest under the competency areas. Each performance objective spawns several possible exam questions. Each exam question must be tied to a performance objective to accurately test one’s comprehensive knowledge of agronomy.

Where an academic exam contains a large variation in question difficulty, certification exam questions ask, “What is the minimum knowledge a professional must have to be proficient in this area.” This is determined by groups of volunteer CCAs, with guidance by the Agronomy Society’s excellent statistician Dawn Gibas, Ph.D., who reviews the performance of each exam question. Questions that nearly everyone gets right are eliminated as well as those that almost no one answers correctly. A complete exam review process takes place every four to five years.

An illustration of the difference between academic and certification exams can be given with a sports analogy. An academic exam is comparable to a high school physical education track and field program, where everyone is expected and encouraged to participate. A certification exam, on the other hand, is like the selection process for the Olympic high jumping team. The high school physical education program sets the bar low and gradually raises it to help students practice their technique and jump higher. But when the world competition is jumping over seven feet, the US team would set the bar at a level near that to select the most competitive team. During the selection process, if the bar is set too high, then they don’t have a team, but set the bar too low and the team has a poor chance of winning. When the psychometrician used this example, the proposal to classify the specific abilities of test takers was withdrawn.

The complexity of 21st-century agriculture practiced in the Western Region of the US supports the need for the most qualified field people providing the best recommendations for our growers so we can continue to deliver the highest-quality, safest agricultural products in the world.

Vegetable Growers Express Impressions, Concerns and Hope for Crop Biostimulants


Crop biostimulants are many things. First, they are claimed to be multi-functional, including enhancement of soil and crop health, acceleration of soil nutrient cycling and improvement of crop productivity and fruit quality, among other benefits. Second, they are categorized by the active ingredient, application method, cost and target crops. Third, they are popular among ever-greater numbers of vegetable farmers regardless of production system, scale and commodity. Finally, some of their performance/efficacy is variable, while many others are unknown.

According to Grand View Research Inc., the global revenue generated by biostimulants was $1.74 billion in 2016, dominated by European and North American companies. Projections indicate that the market value will reach $4.14 billion by 2025.

Though it is difficult to obtain an exact number of biostimulant products currently on the market, the estimate is over 600 with more becoming available each year. However, this grand prosperity of crop biostimulants is not shared equally among people who use them. Particularly to vegetable growers who operate farming at every scale that differs widely in climates, production timing, marketable portion, planting techniques, field preparation and maturity, it can be extremely complex to choose the right product from the long list and use it at the right time in the right way. The first and maybe the foremost step toward a more effective use of crop biostimulants among vegetable growers is to understand their current use, experience, concerns and hopes. To accomplish the task, a survey was sent out to collect the specific information from vegetable growers mainly in the San Joaquin Valley and other counties in California.

Tomato (46) and watermelon (16) each represented crops with more than 10 submitted responses (photos by Z. Wang.)


The Survey and Respondent

The survey was sent to approximately 648 vegetable growers in late October 2020 with the help of other UCCE advisors and commodity boards. The survey was then closed about two months thereafter before the responses were summarized. The original survey can be found at cestanislaus.ucanr.edu/Agriculture/Vegetable_Crops/Biostimulant_Survey/. The survey contains eight questions with the first four asking growers how they farm and the last four related to their experience and opinions to crop biostimulants. By the end of December 2020, we received a total of 83 responses (12.8%), with 74 of them being valid responses (11.4%). Nine responses were not included because there were two replies without an answer to any of the question, five responses from oversea, and two responses from counties outside California. Details about the composition and production of the 74 respondents are included below and in Table 1.

By production, there were 10, 27 and 37 growers claiming organic only, conventional only and mix of both.

By scale, there were 31, 7 and 36 growers with vegetable production scale below 100 acres, 100 to 500 acres and over 500 acres.

By commodity, crops with more than 10 responses included tomato (46), pepper (23), melon (21), summer/winter squash (21), leafy greens/herbs (21), cole crops (16), watermelon (16) and onion (13).

By production location, the 74 growers claimed to have their vegetable fields in 21 counties across California. For details, see Table 1.

Table 1. List of counties for the respondents’ vegetable field locations.


Responses Regarding Biostimulants

The responses indicated that over half of respondents (40) know some knowledge about biostimulants, of which 37 applied biostimulants to at least one or two of their vegetable crops. There were nine growers who claimed having the highest knowledge level (very well), but two of them did not use biostimulants to any of their vegetable crops. There is no surprise that the majority of growers who responded with just a little knowledge or not knowing anything about crop biostimulants did not apply any biostimulant to any of their vegetable crops. The respondents were almost equally distributed by the application level of biostimulants (Table 2). The survey also asked the previous experience or future impression regarding the efficacy of biostimulants on improving vegetable growth. From the results, 50 growers, representing 68% of total respondents, shared the experience or impression that biostimulants could conditionally confer their efficacy. Less than 20% of the respondents indicated a consistent, positive performance on improving their vegetable crops, while only 13% gave the negative impression on biostimulant efficacy (Figure 1).

Figure 1. Responses to previous experience or future impression regarding biostimulant efficacy.
Table 2. Number of grower responses to the understanding/knowledge level of biostimulants and how much of vegetable crops growers apply biostimulants to.


Concerns and Hopes

I have received numerous questions in the past years from vegetable growers, their advisors and colleagues regarding the biostimulant selection, effect evaluation, quality control and incompatibility with other field activities. “Going in blind”, “Unable to identify the benefits”, and “Snake oil” are common complaints. One of the main objectives for the survey is to identify the biggest concerns of using biostimulants on vegetable crops among growers. The survey results showed that about half of the respondents identified the difficulty of choosing a proper product as one of the main concerns followed by the risk of low or no return on investment. In addition, concerns of incomplete label and interference with fertilization and pesticide plans received 20 responses (Figure 2). Lastly, the survey asked growers their agreement level to future actions of improving the use of crop biostimulants. For all future measures, an average of 89% of the respondents agreed/strongly agreed that they will be helpful and important to improve future use of crop biostimulants (Table 3). These responses reflect the hopes from growers, and their voices should be heard by academia, industry, extension and other sectors to outline future efforts aiding a practical and profitable use of these biologics.

Figure 2. Growers’ concerns regarding the use of crop biostimulants on vegetable crops.
Table 3. Number of responses to the agreement on the importance of future measures in improving the use of biostimulants.


UCCE Biostimulant Testing Trials

The UCCE farm advisors from Stanislaus County are actively working with vegetable growers and biostimulant companies to conduct various testing trials each year. The main goal is to fill the data gap with more unbiased, statistically-viable product efficacy data on various vegetable commodities in the Central Valley. Since 2019, we have evaluated numerous biostimulants on processing tomato and watermelon productivity, fruit quality and plant health. Stay tuned to our newsletter and check for previous results (Veg Views: cestanislaus.ucanr.edu/news_102/Veg_Views/).


Biofertilizers Market Size, Share & Trends Analysis Report By Product, By Application, And Segment Forecasts, 2012 – 2022. grandviewresearch.com/industry-analysis/biofertilizers-industry.

Enhancing Diamondback Moth Management with Mating Disruption


Brassica crops such as broccoli, brussels sprouts, cabbage, canola, cauliflower, collards, kale, kohlrabi, turnip and mustards are important vegetable or oilseed crops. The value of brassica vegetables, also known as cole crops, is more than $1.2 billion in California, which is the leading producer of these crops. Among various arthropod pests that attack brassica crops, the diamondback moth (DBM), Plutella xylostella (Lepidoptera: Plutellidae), is of significant importance. Thought to be of European origin, now with worldwide distribution, DBM exclusively feeds on cultivated and weedy crucifers. DBM can have up to 12 generations per year, especially under warmer climate.

Female moths deposit 150 eggs on average. Four larval instars feed on foliage and growing parts of young plants or bore into heads or flower buds, resulting in skeletonization of leaves, stunting of the plants or failure of head formation in some hosts. Pupation occurs on the lower surface of leaves or in florets. Adult moths are grayish-brown, and when at rest, a light-colored diamond-shaped pattern can be seen on the upper side of the wings.

Farmers typically rely on synthetic and biological insecticidal applications for controlling DBM. Multiple species of parasitoids and predatory arthropods also provide some control. Due to a heavy reliance on insecticidal control, DBM resistance to several insecticides is a common problem. Resistance of DBM to Bacillus thuringiensis (Ferré et al., 1991), abamectin (Pu et al., 2009), emamectin benzoate, indoxacarb and spinosad (Zhao et al., 2006), pyrethroids and other insecticides (Leibee and Savage, 1992; Endersby et al., 2011) have been reported from around the world. Excessive use of any kind of pesticide leads to resistance problems (Dara, 2020) to an individual pesticide or multiple pesticides.

Diamondback moth larva and adult (photos by Jack Kelly Clark, UC IPM.)

Integrated pest management (IPM) strategy encourages the use of various control options for maintaining pest control efficacy and reducing the risk of resistance development (Dara, 2019). Regularly monitoring pest populations to make treatment decisions, rotating pesticides with different modes of action, exploring the potential of biocontrol agents, and other non-chemical control approaches such as mating disruption with pheromones are some of the IPM strategies for controlling the DBM. While sex pheromones are effectively used to manage several lepidopteran pests and are proven to be a critical IPM tool, mating disruption is not fully explored for controlling DBM. A study was conducted in Brussels sprouts to evaluate the efficacy of a sprayable pheromone against the DBM and to enhance current IPM strategies.



The study was conducted on a 10-acre Brussels sprouts field in Santa Maria. Cultivar Marte was planted in early July for harvesting in December 2020. A typical diamondback control program includes monitoring DBM populations with the help of sticky traps and lures and applying various combinations of biological and synthetic pesticides at regular intervals. This study evaluated the efficacy of adding CheckMate DBM-F to the grower standard practice of monitoring the DBM populations with traps and lures and applying pesticides. Treatments included 1.) grower standard pesticide program (See Table 1) grower standard pesticide program with two applications of 3.1 fl oz of CheckMate DBM-F on August 9 and September 11. Treatment materials were applied by a tractor-mounted sprayer using a 100 gpa spray volume and necessary buffering agents and surfactants. Each treatment was five acres and divided into four quadrants representing four replications.

Table 1. Pesticides, buffering agents and surfactants, their active ingredients, rates/ac (along with the IRAC mode of action groups) and retail pricing for those applied in the grower standard diamondback moth control program. *Applied diamondback moth and aphid control

In the middle of each quadrant, one Suterra Wing Trap was set up with a Trécé Pherocon Diamondback Moth Lure. Lures were replaced once a month in early September and early October. Sticky liners of the traps were replaced every week to count the number of moths trapped. Traps were placed on Aug. 1, 12 and 24, Sept. 1, 11, 18 and 27, and Oct 6, and the moth counts were taken from respective traps on Aug. 8 and 20, Sept. 1, 11, 18 and 27, and Oct. 6 and 15. CheckMate DBM-F was applied at 3.1 fl oz/ac on Aug. 9 and Sept. 11. The number of larvae and their feeding damage on a scale of 0 to 4 (where 0=no damage, 1=light damage, 2=moderate damage, 3=high damage, 4=extensive/irrecoverable) were recorded from 25 random plants within each replication on Aug. 30 and Oct. 6 and 18. Data were subjected to analysis of variance using Statistix software and significant means were separated using Tukey’s HSD test. The retail value of various pesticides was also obtained to compare the cost of treatments.

When CheckMate DBM-F[(Z)-11-Hexadecenal (3) , (Z)-11-Hexadecen-1-yl Acetate (1)] was applied the first time on Aug. 9, Dibrom 8 Emulsive was replaced with Warrior II, the buffering agent Quest was not used, and the surfactant Dyne-Amic was replaced with Induce (dimethylpolysiloxane) to avoid potential compatibility issues. The impact of this substitution is expected to be negligible within the scope of this study. The retail cost of 3.1 fl oz CheckMate DBM-F is $45.60. The cost of lures and traps would be about $4 to $8 per acre for a six-month crop like Brussels sprouts.


Results and Discussion

Traps in replication 4 in both treatments on August 8 and replication 1 in the grower standard were missing, probably knocked down by a tractor. The day before CheckMate DBM-F was first applied, the mean number of adult DMB caught was 227 in the grower standard and 271 in the plots that would receive the pheromone application (Figure 1). There was a gradual decline in moth counts during the rest of the observation period in both treatments. However, the decline was higher in the plots that received CheckMate DBM-F. The number of moths per trap were about 19% higher in the pheromone-treated plots compared to the grower standard before the study but were nearly 98% lower by the end of the study (Figure 2). The reduction in moth populations from mating disruption was significant on September 18 (P =0.039) and October 15 (P = 0.006).

Figure 1. Mean number of diamondback moth adults found in the traps.
Figure 2. Reduction in moth populations by adding pheromone for mating disruption.

The mean number of larvae per 25 plants in a replication was zero on all observation dates except for 0.01 on Aug. 30 in the plots that received CheckMate. Four insecticide applications made by the time the study was initiated and the remaining six applications effectively suppressed larval populations.

Larval feeding damage ratings were consistently low (P < 0.0001) in the plants that did not receive CheckMate DBM-F (Figure 3). The damage was limited to the older leaves at the bottom of the plants and must have been from early feeding before the initiation of the study. The lack of larvae and the evidence of new feeding damage also confirm that the crop remained healthy and pest-free.

Figure 3. Feeding damage by diamondback moth larvae.


Yield and Cost Comparisons

Since frequent pesticide applications effectively suppressed larval populations and prevented their feeding damage, the effectiveness of mating disruption on larval populations or their damage could not be determined in this study. Moths found in the traps probably developed from the larvae in the field or could have been those that flew in from other areas.

However, lower moth populations in CheckMate DBM-F treatment demonstrated the overall influence of mating disruption and pest suppression.

It is common to make about 10 to 12 pesticide sprays during the six-month crop cycle of Brussels sprouts. The cost of each application varied from about $73 to $192 depending on the materials used with an average cost of about $128 per application in this study. The cost of two CheckMate DBM-F applications is $91. If diamondback moth populations could be reduced with mating disruption, it is estimated that two to three pesticide applications could be eliminated. That results in $164 to $292 of saving for the pesticide costs and additional savings in the application costs per acre by investing $91 in the mating disruption. Since DBM can develop resistance to several chemical and natural pesticides, eliminating some applications as a result of mating disruption also contributes to resistance management along with potential negative impact of pesticides on the environment. Compared to other mating disruption strategies, a sprayable formulation compatible with other agricultural inputs is easier and more cost-effective to use.

The grower’s yield data showed 762 cartons/acre from the grower standard block with pesticides alone and 814 cartons/acre from the block that received pesticide and pheromone applications. Although there seems to be a 7% yield difference, since data from individual plots could not be collected for statistical analysis, the impact of DBM mating disruption on yield improvement is inconclusive.

This study demonstrated that mating disruption with CheckMate DBM-F will significantly enhance the current IPM practices by reducing pest populations, contributing to insecticide resistance management, and reducing pest management costs. Additional studies with fewer pesticide applications that allow larvae to survive and cause some damage might further help to understand the role of mating disruption where pest populations are not managed as effectively as in this field.

Thanks to the PCA and grower for their research collaboration, Tamas Zold for his technical assistance in data collection, Ingrid Schumann for market research of pesticide pricing and Suterra for the financial support.

Feeding damage in cauliflower (photo by S.K. Dara.)



Dara, S. K. 2019. The new integrated pest management paradigm for the modern age. J. Int. Pest Manag. 10: 12.
Dara, S. K. 2020. Arthropod resistance to biopesticides. Organic Farmer 3 (4): 16-19.
Endersby, N. M., K. Viduka, S. W. Baxter, J. Saw, D. G. Heckel, and S. W. McKechnie. 2011. Widespread pyrethroid resistance in Australian diamondback moth, Plutella xylostella (L.), is related to multiple mutations in the para soidum channel gene. Bull. Entomol. Res. 101: 393.
Ferré, J., M. D., Real, J. Van Rie, S. Jansens, and M. Peferoen. 1991. Resistance to the Bacillus thuringiensis bioinsecticide in a field population of Plutella xylostella is due to a change in a midgut membrane receptor. Proc. Nat. Acad. Sci. 88: 5119-5123.
Leibee, G. L. and K. E. Savage. 1992. Evaluation of selected insecticides for control of diamondback moth and cabbage looper in cabbage in Central Florida with observations on insecticide resistance in the diamondback moth. Fla. Entomol. 75: 585-591.
Pu, X., Y. Yang, S. Wu, and Y. Wu. 2009. Characterisation of abamectin resistance in a field-evolved multiresistant population of Plutella xylostella. Pest Manag. Sci. 66: 371-378.
Zhao, J-Z., H. L. Collins, Y-X. Li, R.F.L. Mau, G. D. Thompson, M. Hertlein, J. T. Andaloro, R. Boykin, and A. M. Shelton. 2006. Monitoring of diamondback moth (Lepidoptera: Plutellidae) resistance to spinosad, indoxacarb, and emamectin benzoate. J. Econ. Entomol. 99: 176-181.

Plastic Mulches Reduce Spotted-Wing Drosophila Infestation in Fall-Bearing Raspberry

Spotted-wing drosophila (SWD), Drosophila suzukii, is an invasive vinegar fly and a major pest of soft-skinned fruit crops. The fly was first detected in the continental U.S. in 20081 and has quickly spread from its native range in Eastern Asia throughout the U.S. and into most major fruit-producing regions of the world2. For small-scale fruit growers, damage from this pest substantially reduces the yield of marketable fruit, making susceptible crops challenging to grow economically and sustainably3,4. For large-scale growers, the presence of SWD can lead to complete crop loss due to processors’ zero-tolerance policies for insect infestation5.



Vinegar flies typically lay their eggs in damaged or rotting fruit, but female SWD have a highly serrated ovipositor that allows them to saw through the skin of undamaged, ripening fruit6,7, which makes SWD an especially detrimental pest. Larvae emerge inside of and feed on the fruit, making it mushy and unmarketable. Recent research showed that around 80% of larvae drop from the fruit to pupate in the top layer of soil and that they are more likely to drop from the fruit if the fruit is overcrowded8,9. Larvae and pupae can also reach the ground when damaged fruit becomes mushy and falls to the ground.

SWD has a quick generation time, with many generations per year in most regions. The fly develops fastest in temperatures between 68 to 83 degrees F, but is unable to develop at temperatures above about 87 degrees F10,11. In temperate regions like the Upper Midwest or Pacific Northwest, SWD populations are highest during summer months. In hotter regions like California or Florida, fly populations are highest in the spring and fall and are much lower during their hot and dry summer months12.

SWD thrives in high humidity, developing fastest around 94% humidity13. Researchers found that females laid more eggs in the inner canopy of blackberry and blueberry plants, likely because the environment is more humid, cooler and darker14,15.

(Left) Spotted-wing drosophila adult female and male on a raspberry. Male flies are easy to identify by the large black spots on their wings. (Right) Spotted-wing drosophila females have a serrated ovipositor that allows them to lay eggs in undamaged, ripening fruit (photos courtesy Agri-Mag and Chris Thomas.)

Fruit crops that are the most susceptible to SWD include raspberries, blackberries, blueberries, strawberries, sweet and tart cherries, and some cultivars of wine grapes16-18. However, SWD can survive on alternative hosts like wild blackberries and apples, buckthorn and honeysuckle. It remains largely unknown how SWD survive in the winter and spring before fruit is available in the landscape and on farms, but one study found that SWD can develop on non-fruit hosts like mushrooms and bird manure19.


Traditional Management

Pest pressure from SWD is often very high due to the fly’s fast development time, optimal development conditions in the summer and high availability of host plants and food in the agroecosystem. Management relies heavily on chemical control in organic and conventional systems, which is costly to growers. In California, chemical controls for SWD cost around $470/acre for conventional and $1,210/acre for organic growers3.

Only a few insecticides approved for use in organic systems are effective at controlling SWD, limiting organic growers’ options for control20. Unfortunately, recent reports show evidence of insecticide resistance developing for some active ingredients in some regions, including spinosad (the main insecticide used to control SWD in organic systems)21,22.

Cultural practices can help reduce the fly’s population and are often used in tandem with chemical controls. Such practices include harvesting fruit promptly (every one to two days), frequent field sanitation, burial or composting of infested fruit and exclusion netting23,24. However, these methods are labor-intensive and expensive.

Since SWD is sensitive to temperature and humidity, cultural practices that modify the crop canopy microclimate have the potential to reduce infestation by deterring adults from laying eggs or disrupting larval development inside of fruit. Management strategies for SWD typically target adult flies in the canopy, but since the majority of SWD larvae fall to the ground before pupation, ground-based cultural management practices could also be important for reducing populations.

Spotted-wing drosophila life cycle (courtesy Jana Lee, USDA-ARS.)

Growers have used plastic mulches since the 1960s to modify the microclimate in fruit and vegetable agroecosystems. Plastic mulches are commonly used for weed control, promoting earlier ripening, improving fruit quality or color and increasing yield25,26. Different colors of plastic mulches have also been shown to successfully control insect pests including aphids, whiteflies, Asian citrus psyllid and Mexican bean beetles27-30.


Plastic Mulches for SWD

Based on the extensive body of literature reporting that plastic mulches can modify the crop microclimate, control some insect pests and provide other horticultural benefits, we tested the impact of three colors of plastic mulches on SWD adult and larval populations. Our study was conducted in 2019 and 2020 on a small fruit and vegetable farm in South Central Wisconsin in fall-bearing raspberries.

In this study, we tested black and white-on-black biodegradable plastic mulches (Organix Solutions AG film), metallic polyethylene mulch (Imaflex SHINE N’ RIPE) and a grower-standard control where grass filled in the space between the alleyway and the raspberry plants. We assessed the three mulches’ impact on SWD adult and larval populations in fall-bearing raspberry.

We laid the mulches by hand when the raspberry canes were just emerging from the soil in late April. We laid two mulch strips (25 feet long by 2.3 feet wide) along each side of the row, leaving a six-inch gap between the strips for the canes to grow. The edges of the mulches were secured with biodegradable sod stakes. All four treatments were randomly distributed in each of four rows of fall-bearing raspberries (cultivars “Polana” and “Caroline”), totaling 16 plots.

Starting when the first flies were detected in June, we measured the adult SWD populations passively using clear sticky cards placed in the fruiting zone, which were replaced weekly to estimate fly populations by week.

Larval infestation of fruit was evaluated by counting the number of larvae using the salt float method31. The evaluations were done two to four times per month starting in August.

Adult and larval populations were measured throughout the season until adult populations reached zero, usually in mid-October.

We also did a preliminary experiment to test whether plastic mulches could kill larvae that fell onto the mulch surface. We put lab-reared larvae into ‘corrals’ made from plastic sandwich containers and recorded their mortality and movement over three hours.

‘Corrals’ made from plastic sandwich containers used to test mortality of larvae on the mulch surface (photo by H. McIntosh.)


Population Reductions

In both years of our study, we found significantly lower SWD populations above all three plastic mulches compared to the control plots. Over the two-year period, the black and metallic mulches reduced the adult population of SWD by 51% and the white mulch reduced flies by 42% compared to the control.

Interestingly, the plastic mulches only reduced female fly populations and did not impact the number of male flies caught on the sticky cards. With fewer female flies in the canopy above the plastic mulches, it was unsurprising that we also found fewer larvae infesting the fruit in the mulched plots. Over the two-year study, the black mulch decreased the number of larvae in fruit by 72%, the metallic mulch by 61%, and the white mulch by 52% compared to the control.

Plastic mulches may be more effective than other types of mulches tested for managing SWD. In our study, we recorded the lowest adult fly populations and larval infestation of fruit above the black plastic mulch. A 2019 study tested black fabric weedmat as a cultural control for SWD in blueberry in several states and found no effect of the weedmat on SWD infestation of blueberries32. It is possible that some quality of the plastic mulch material (such as reflectivity or lack of permeability) makes it more deterrent to SWD than the weedmat.

In our preliminary experiment, larvae placed on the plastic mulches died quickly. Larvae on the black mulch died in less than one hour, and larvae on the white and metallic mulches died in less than three hours. We recorded high surface temperatures on the mulches, with all mulches heating up above 87 degrees F (SWD’s threshold for development) for two to four hours each day. On hot days, the black mulch got above 150 degrees F.

When placed on the mulch, we observed larvae struggling to crawl and visibly desiccating within minutes, making it unlikely that larvae could crawl off the mulch into the safety of the soil. We will collect more data in summer 2021 to confirm these promising results.

The results of our study provide evidence that black, white and metallic plastic mulches can reduce SWD adult and larval populations in fall-bearing raspberry in the Upper Midwest, showing promise for use of plastic mulches in sustainable pest management.

Combining plastic mulches with other cultural practices including short harvest intervals (every one to two days) and frequent field sanitation could have an additive effect on reducing SWD populations, potentially reducing the need for chemical controls in conventional and organic cropping systems.


Next Steps

Although the use of plastic mulches reduces SWD populations in the canopy of raspberry plants, the specific mechanisms causing this reduction are still unknown. We are still investigating how canopy light conditions, temperature and humidity are
influenced by the plastic mulches and whether these factors can explain the reduction in SWD populations we measured.

In the next two years of this project, we will conduct field experiments to determine whether the three plastic mulches we tested influence beneficial insects, including pollinators, and how the mulches impact soil health, raspberry plant growth, fruit quality and yield in Wisconsin’s climate.

Testing these mulches in other regions and fruit crops is warranted to determine if the reduction of SWD is maintained in different climates and other susceptible crops. Overall, plastic mulches are a promising new tool for more sustainable management of SWD in raspberry in the Upper Midwest.



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A Review of Pythium Diseases in Row Crops


It is highly likely that growers, PCAs and other field professionals are familiar with the word “Pythium”. Pythium is the name of a soilborne, fungus-like organism that is notorious for primarily causing seedling diseases. Pythium is notable because many row crops are susceptible to it, the pathogen is very widely distributed and occurs in most cropped ground, and despite the use of IPM tools and strategies, Pythium problems can still show up in row crop production systems.


What is Pythium?

Pythium is a fungus-like organism. Previously considered to be a true fungus, molecular studies in recent years indicate that Pythium—as well as closely related organisms like Phytophthora and downy mildew—is more closely related to brown algae and diatoms. Formally, therefore, Pythium species are no longer part of the fungal taxonomic group but are classified in the kingdom Chromista, or Stramenopila. The Pythium genus contains over 200 species, most of which are not plant pathogens. There are Pythium species that are pathogens of animals (some of which can infect humans), and many species are saprophytes and only grow on dead and decaying organic material. Pythium species are mostly found in soil environments but are also present in aquatic habitats.

Plant pathogenic Pythium species are well equipped to cause problems on row crops. Most of these species form resilient, thick-walled sexual spores (oospores) that can withstand periods of unfavorable dry and warm conditions. These structures enable Pythium to persist in the soil for a long time. When favorable soil conditions are present, mostly in the form of abundant soil water, these Pythium organisms either produce hyphae that grow toward the roots or swimming spores (zoospores) that move through the soil water in search of susceptible plant tissues. Another feature that makes Pythium problematic for growers is the extremely fast growth rate of these organisms. Given suitable soil conditions, Pythium pathogens can rapidly grow from seed-to-seed, seedling-to-seedling and root-to-root.

The primary symptom of Pythium diseases is the dark discoloration and decay of roots, pictured here on lettuce.



Diverse Pythium Diseases

In contrast to many plant pathogens, Pythium causes several different types of problems on crops (Table 1). First, Pythium is a seed pathogen. Once placed in the ground, seed can be exposed to Pythium that is residing in the soil. If conditions are favorable for the pathogen, Pythium can invade and colonize the seed, causing it to rot before it can germinate. If the seed germinates, Pythium can cause a decay of the roots and shoots that just grew out of the seed. This early disease stage is often called damping-off. Damping-off is further divided into two phases. If the newly germinated seedling is infected so early and so severely that it dies before being able to break through the soil surface, this situation is called pre-emergent damping-off. However, post-emergent damping-off occurs if the diseased seedling is strong enough to emerge above the soil surface, only to succumb and collapse shortly afterwards. Collectively, seed decay, pre-emergent damping-off, and post-emergent damping-off can result in loss of plants very early in the production cycle, causing stand loss in the field.

Table 1. Categories of Pythium diseases of row crops

Healthy seedlings that escape death at the seed and newly germinated stages remain vulnerable to this pathogen; established seedlings can still be infected and become stunted and die due to diseased roots and crowns. Older, established plants have escaped the damping-off phase that kills seedlings but can be subject to infections that prune back the roots, leading to reduced plant vigor and yield. For example, Pythium can cause late infections in cauliflower and result in weakened roots and poorly yielding plants. This soilborne pathogen can even cause a foliar blight of leaves and shoots, though this type of disease is not very common. Bits of soil carrying Pythium can be splashed or moved up onto foliage and cause blights on crops such as spinach and bean. Finally, the fleshy parts of some vegetable crops are subject to Pythium pathogens. If in contact with infested soil, cucurbit fruits, sweet potato storage roots and potato tubers can develop a soft, watery rot that will result in a non-marketable commodity.

Of the hundreds of Pythium species worldwide, relatively few species infect row crops. These plant pathogens can be conveniently placed into two categories. One group consists of Pythium species that have a relatively narrow host range and infect only a few crops, with those few crops tending to mostly be within a particular plant family. Examples are Pythium mastophorum, which primarily infects celery and parsley (Apiaceae family), and Pythium uncinulatum, which reportedly only causes significant disease on lettuce (Table 2). The second group contains Pythium organisms that have very large host ranges. The two main species, P. aphanidermatum and P. ultimum, both infect scores of plants, including dozens of vegetable and row crops.

Table 2. Examples of Pythium pathogens with broad vs. narrow host ranges

Disease Development Development of Pythium diseases is straightforward. Initial inoculum is almost always linked with infested field soils and associated soil water. Pythium is a soilborne pathogen that resides in the soil primarily as dormant resting structures. Pythium inoculum is not seedborne or airborne. For Pythium to become active, grow, and produce those swimming zoospores, the soil must be wet for prolonged periods. Once susceptible seed, seedlings, and other plant parts are in close contact with Pythium inoculum, infection can take place and disease will be initiated. If wet soil conditions persist and temperatures are optimum for the pathogen, disease losses can be significant.

Pythium pathogens form thick-walled oospores that enable the pathogen to survive in soil for prolonged periods.


Diagnostic Considerations

Pythium is not the only soilborne pathogen that causes seedling damping-off and root rots of row crops. On spinach, damping-off and root rot can be caused by both Pythium and Fusarium; visually, one cannot distinguish between the symptoms caused by these two pathogens. Pythium and Phytophthora pathogens both cause dark, discolored roots of lettuce and cannot be differentiated in the field. Cauliflower transplants are susceptible to both Pythium and Rhizoctonia pathogens, both of which caused the roots to become discolored. Precise and accurate diagnosis of Pythium diseases will therefore require lab-based tests and assays.

When sufficient soil water is present, Pythium forms swimming spores that are released and search for host roots. Pictured here is a cluster of zoospores just prior to release.


Managing Pythium

Controlling diseases caused by Pythium requires the implementation of IPM practices.

Site selection: Choose to plant in fields that do not have a history of Pythium problems and have well-draining soils.

Crop rotation: If Pythium is an issue, avoid planting the same susceptible crop in the infested field. Rotate to crops that are not known to be susceptible to the Pythium species present at that location. However, remember that some Pythium species have very broad host ranges (Table 2).

Irrigation management: Because the Pythium pathogen is so strongly dependent on wet soil conditions, carefully schedule and limit irrigations to prevent overwatered, saturated soils.

Time of planting: In some cases, moving the planting date to a different time of year may help reduce losses to Pythium. For example, depending on the Pythium species of concern, planting the crop in the warmer, drier summer may be preferred to seeding the crop in the cooler, wetter spring.

Fungicides: Plant seed treated with a fungicide that is active against Pythium. Note that the fungicides used to control Rhizoctonia or Fusarium have no effect on Pythium. For some crops, applying fungicides to the emergent crop may provide additional protection. The repeated use of products having the same mode of action can result in Pythium isolates that are insensitive (=resistant) to those products; therefore, IPM strategies will require that thought be given to deploying different fungicides.

Resistant or tolerant cultivars: Unfortunately, there do not appear to be any row crop cultivars that have genetic resistance to Pythium.

Pythium plant pathogens can grow very rapidly. Pictured here are three-day-old cultures of Pythium, Phytophthora, Fusarium and Verticillium. The diameter of the petri dish is 85 mm.

New Findings on Limb Dieback of Figs in California

Back in 2004, and again in recent years, there were concerns by fig growers mainly in Madera and Merced counties about an excessive killing of major branches of their fig trees (Figure 1). Visits to some orchards back then and recently indicated that indeed they had a major problem. Initial close examinations of the dead branches showed symptoms which were similar to another disease: branch wilt of walnut.

Figure 1. Left, Fig tree affected by severe limb dieback; top right, still active canker; bottom right, inactive canker (branch is dead) (all photos courtesy G. Gusella.)

The bark of dead fig branches had cracks and one could easily remove large pieces of the bark, exposing the woody tissues underneath which were covered by a black powder. Rubbing this black powder with your finger could easily remove masses of it (Figure 2). The inner surface of the broken and removed bark pieces were also black due to these powder masses. A lot of trees had many dead major branches while others had one or two dead along with other branches bearing chlorotic and thin canopy, distinct from the green and dense canopy of healthy branches.

Figure 2. Top, Neoscytalidium dimitiatum, the cause of limb dieback producing spores (arthrospores) as the mycelia dried up and separate to small segments under the bark; bottom, easily rubbing off the spores under the bark (photo courtesy Beth Teviotdale.)


Pathogen Activity

To collect samples, we cut some of the symptomatic branches close to the interface of dead and alive-looking (green) tissues. We noticed that in a cross section, the dead woody tissues were delineated from the healthy tissues by a dark brown line while the living woody tissues were white (Figure 1).

Slices of these woody tissues from the branches were taken, isolations were made in the laboratory and a fungus known to be a pathogen of woody tissues was consistently recovered. The name of this pathogen is Neoscytalidium dimidiatum, which is a new taxonomic name of Hendersonula toruloidea fungus, which represents the pathogen first reported to cause the branch wilt disease of walnut.

Checking the literature, the same fungus under a different name (i.e. Nattrassia mangifera) was reported in 1945 on commercial figs in California as well as on Ficus religiosa and Ficus bengalensis, causing dieback and trunk cankers. In addition to walnut branch wilt, which is a common disease of walnuts grown in the San Joaquin Valley, the same fungus was reported in causing branch wilt and dieback of poplar, eucalyptus and mango. In other reports, we found out that this pathogen can cause killing of major branches of walnut, ash trees and grapefruit. More recently, it has been reported causing cankers and hull rot of almond. On fig shoots, the pathogen grows and infects injured bark (i.e. mechanical wounds, wounds by hail or sunburn), invades the woody tissues and kills the branch. When the branch is killed, it dries and usually the bark cracks, exposing large masses of black spores. These are not true spores but are small segments of mycelia that become black as the tissues dry up and break down into small pieces, producing a layer of black powder under the bark. The fungus also produces pycnidia that protrude through small cracks of the bark (See Figure 3). However, it is the spores produced in masses by the breaking mycelia called arthrospores. that can be spread readily by air and/or splashing rain and can cause infections of pruning wounds and other injuries of branches.

Figure 3. Left, pycnidia protruding through bark cracks; right, arthrospores of Neoscytalidium dimidiatum causing limb dieback of fig (photos courtesy T. Michailedes.)


Survey of Affected Areas

Before doing pathogenicity studies with the Neoscytalidium fungus, we wanted to make sure that this fungus was found frequently throughout the area where fig trees showed similar symptoms to the ones we initially observed in Madera County. Therefore, a survey of 16 fig orchards with branch dieback symptoms, representing all the major fig varieties (Black Mission, Calimyrna, Conadria and the male trees (Roeding and Stanford caprifig varieties)) was done in Fresno, Madera and Kern counties. Neoscytalidium was isolated in all of these orchards.

Limb and branch samples from the majority of these orchards had 60% to 100% Neoscytalidium, while three had 7% to 11%, and two 26% to 32%. In 12 of these orchards, a second pathogen, Phomopsis spp., was isolated along with Neoscytalidium in the first year of the survey. Phomopsis sinarencis has been reported in California causing an epidemic on Kadota figs back in 1935 and in other countries as an important fig canker pathogen. By the third year of this survey, less Phomopsis was isolated, and, very recently, almost none was isolated, probably because the very susceptible Kadota variety is rarely now planted in California. Phomopsis is known as a pathogen fungus associated with canker diseases in many other crops around the world, but more investigations are needed to figure out its role in fig limb dieback.


Differences in Susceptibility

To determine if there were any differences in susceptibility to the limb dieback pathogen, we inoculated six cultivars directly in the field. We found that three months after inoculations, the cultivars Kadota, Black Mission and Sierra developed twice as long canker size than the cultivars Brown Turkey, Calimyrna and Conadria (Figure 4). Growers also reported that they see the problem to be more severe in Black Mission than other cultivars. Inoculations of six cultivars showed that Neoscytalidium is a plant pathogen that likes high temperatures. For instance, it cannot grow below 50 degrees F; its optimum temperature for growth is 90 to 95 degrees F, and it can even grow at 104 degrees F to some extent. Therefore, this fungus likes hot summer temperatures and prefers to infect sunburned branches and pruning wounds.

Figure 4. Susceptibility of various fig cultivars to limb dieback pathogen Neoscytalidium dimidiatum.

In experiments, we inoculated shoots of fig of different ages, including current growth (green) shoots, one-year, two-year and three-year-old shoots, by wounding and inoculating with either a mycelial plug or a spore suspension. Interestingly, the three-year-old shoots developed almost three-fold larger cankers than the cankers on current and the one-year-old shoots. This suggests that larger cuts in the field during pruning seem to be more susceptible to infection than cuts made in current or one-year-old shoots. Also, inoculations done in May, June and July resulted in larger cankers than those done from August to November. ‘

When we compared infection on pruning wounds done in winter vs. those done in summer, pruning wounds in the summer developed almost threefold larger cankers than those done during winter months. Therefore, it is recommended that pruning of figs should be done in winter when pruning wounds seem to be less susceptible. Figs can be protected from infections of the branch wilt pathogen if shoots are painted with whitewash to protect them from sunburn. Applying Surround® on shoots also protected the shoots from infection, and this is recommended to become a routine practice by fig growers. Figure 5 shows results of inoculation experiments done following various treatments in the field and artificial inoculation with the pathogen.

Although wounding by only mallet or only sunburn resulted in larger canker than the non-inoculated, un-wounded/un-treated shoots, the shoots that were damaged by mallet wounding and sunburn at the same time resulted in the longest cankers. White wash or spraying with Surround protected the shoots even after wounding with mallets and inoculation (Figure 5 and 6). Therefore, pruning that exposes the shoots to sunburn and or any other type of wounding should be avoided, and spraying with Surround will help protect the fig shoots from the limb dieback pathogen.

The authors thank the California Fig Institute for funding this research and a number of fig growers who allowed us to sample their orchards.

Figure 5. Effect of stress factors (mallet wounding and sunburn) and treatment with white wash affecting the severity of limb dieback of fig.


Figure 6. Effect of Surround® spray on the severity of limb dieback of fig.

Life After Methyl Bromide in California Berries

When methyl bromide was banned in 2005, California strawberry growers lost an effective tool in their crop care toolbox to control weeds, soilborne diseases, nematodes and symphylans. Special-use permits allowed them to continue using the fumigant through 2016, but growers feared final loss of the powerful soil fumigant might be the end of profitable production.

The California Strawberry Commission agreed, noting that elimination of methyl bromide fumigation brought forth several soilborne diseases for which there is no post-plant control. Of particular concern were Fusarium wilt (Fusarium oxysporum f.sp. fragariae), Verticillium wilt (Verticillium dahlia) and charcoal rot (Macrophomina phaseolina), according to the California Strawberry Commission.

But once again, necessity proved to be the “mother of invention,” said independent agronomist and PCA Lee Stoeckle, owner of Stoeckle Agricultural Consulting in Ventura, Calif.

Stoeckle has advised strawberry and caneberry growers for more than 30 years, and he noted that effective alternative fumigants have taken up the methyl bromide void and are now widely and successfully used. While California strawberry acreage has fallen, total production has actually increased thanks to innovation and application of new technology.

Stoeckle’s family-owned business provides recommendations on 3,000 acres of strawberries and 100 acres of blackberries in Santa Barbara County and San Luis Obispo County and 2,000 acres of strawberries in Ventura County. In addition, he consults on production of 800 acres of strawberry and 250 acres of raspberries in Baja Mexico. While he is primarily responsible for above-ground insect and disease control, he doesn’t write fumigation recommendations but instead advises based on what he learns about weeds and soil pathogens.

 A strawberry field at the beginning of the growing season in Oxnard, California.


A One-Two Punch

Top problem soilborne diseases, according to Stoeckle, are Fusarium, Macrophomina, Phytophthora, Anthracnose and Verticillium wilt. Top problem above-ground pests include two-spotted spider mites, Lygus bug, Botrytis fruit rot/gray mold and powdery mildew, depending on varietal susceptibility. Other pests necessary to watch include worms and aphids.

“The optimum disease and weed control program is a one-two punch,” Stoeckle says. “Hit it at the end of the season as a burndown and at the beginning before next planting via drip irrigation. The backbone of our control program is Pic-Chlor 60 EC (1,3-dichloropropene plus chloropicrin) at the max recommended rate (350 lbs/ac), going after the heavy hitting ‘big boys’ (soilborne diseases) when applied in August or September before planting.” He recommends Vapam or K-Pam to get the additional benefits to control these diseases (Fusarium, Verticillium, Macrophomina phacelia) and eliminate the inoculum reservoir in the crown.

Stoeckle says emulsified formulations of Telone® C-35 and chloropicrin can be applied with irrigation water through drip irrigation systems. Metam sodium is the active ingredient in Vapam® HL™ and metam potassium in the active ingredient in K-Pam® HL™. Both are AMVAC® soil fumigants, which give off methyl isothiocyanate (MITC) when combined with water via drip or otherwise. If drip fumigation is planned, good results have been obtained with a sequential application of chloropicrin or 1,3-dichloropropene plus chloropicrin, followed 7 days later with metam sodium or metam potassium.

Stoeckle considers fumigants essential and offers the math: “If we equate the value of every plant to be $2 each and you lose 10% of your plants, that’s 2,500 plants on a population of 25,000 per acre. Your choice is to fumigate or take a $5,000 loss. That’s an easy decision. The return on investment on fumigation is huge. We expect to see a 20% to 30% return on fumigant investment.”

He is quick to add there are other management decisions that help maximize production, noting, “I could go on and on about using the best plastic mulch or optimum fertilization practices.”


Best Practice Weed Control Reduces Production Costs

Fifth-generation Santa Barbara County grower Brett Ferini, owner of Rancho Laguna Farms, grows 400 acres of strawberries (300 fall plant, 100 summer plant) and 20 acres (adding another 20 for 40 total) of blackberries. Plus, he grows 35 acres of organic blackberries. He used Vapam on blackberries in February 2020.

“Vapam worked out really well in controlling nutgrass/nutsedge,” he said. “Pic-Clor 60 has no effect.”

For weed and disease control, “we hit everything at fall pre-plant with Pic-Clor 60 through drip tape and seven days after that we follow with Vapam,” he said. “It does a terrific job on nutsedge and other weeds, as well as the soilborne diseases including Verticillium, Phytophthora and, anecdotally, Macrophomina.”

Ferini says the operation plans to add a Vapam burndown at the end of the 2020 growing season

“We definitely [have] cut weeding by 60% on summer plant,” he says. “Labor is our highest cost. We saw $1,050 savings per acre vs. our normal costs of $1,800/acre. The big test will be on the fall plant when we get more rain. Our fall weeding cost normally runs $2,800 to $3,000 per acre. Using Pic-Clor 60 followed by Vapam treatment, I expect weeding cost savings of $1,000 to $1,500 per acre.”

Also seeing results with soil fumigants is Santa Barbara grower Josh Ford. He is COO of Ocean Breeze Ag Management LLC in Ventura, which grows 450 acres of strawberries, 50 acres of blackberries, and 25 acres of raspberries. Ford’s biggest soilborne pests are Macrophomina, Fusarium, and Phytophthora cactorum. Nutgrass is his most difficult weed to control.

“We’ve been using soil fumigants for many years,” he says. “We were using methyl bromide, but now we apply chloropicrin once a year and K-Pam once to twice a season. If nut grass is a bad problem, we will knock it down at the end of the season with K-Pam and also pre-plant K-Pam. Our ROI is good when you consider the increased cost of labor to manually remove nut grass.”

Using N-Rich Reference Zones to Inform In-Season Nitrogen Fertilization Practices in California Small Grains

Over the last year, a team from UCCE has been working with California small grains growers on practices that can improve nitrogen (N) use efficiency. At demonstration sites, we have implemented practices that UC Grain Cropping Systems Specialist Mark Lundy has been investigating for several years, namely N-rich reference zones, a soil nitrate quick test, handheld reflectance devices and aerial imagery. We demonstrate how to use these tools to manage N fertilizers in small grain crops across variable soil and climatic conditions in the Sacramento Valley, Delta, San Joaquin Valley and Intermountain Region.

The demonstrations are funded by the CDFA Fertilizer Research and Education Program and a USDA-NRCS California Conservation Innovation Grant. Our goal is to help growers and consultants learn and implement these practices to guide N fertilization in small grains, thereby increasing crop productivity and N use efficiency while reducing potential for N loss to the environment.


What are “N-Rich Reference Zones”?

Reference zones are most useful to growers who can apply the majority of their seasonal N budget during or after the tillering stage of growth. Previous work has shown that N fertilizer applied during the season−between the tillering and heading stages of small grain development−results in higher yields, higher protein and increased fertilizer use efficiency compared to pre-plant applications. The reference zone is a relatively small area within the field where extra N fertilizer is added at the beginning of the season. This extra fertilizer ensures that the reference zone will not be N-limited from planting until an in-season fertilizer decision is made. When a grower is determining whether and how much N fertilizer to add in-season, measurements from both the reference zone and the broader field are compared to understand whether the broader field is sufficient in plant-available N.


Fertilizer N Rate and Field Variability

Fertilizer N rate and field variability are two important considerations when creating N-rich reference zones. The amount of N to apply in the N-rich zone will depend on several factors such as yield goal, protein goal and when the expected in-season fertilizer application will take place. There should be sufficient N applied to the reference zone at planting to ensure that the plants in the zone are not limited by N at the stages of growth when the in-season fertilizer is applied. Table 1 gives some examples of how much N fertilizer to apply to the N-rich zone for a range of potential yields.

Table 1. Approximate N fertilizer application rates suggested for use in N-rich reference zones based on a range of average yields and two stages of crop growth. Suggested rates ensure that crops within the reference zone are not N-limited when an in-season fertilizer application decision is being made at the crop stage indicated.

It is important to establish the N-rich zones in representative parts of the field. Areas of the field that are unique (i.e. low areas, high areas, gravel strips, etc.) should be avoided. It is also important that the zones capture field variability. If certain areas have distinct soil types or known patterns of yield or management differences, a grower should establish multiple zones to account for these sources of spatial variability if they represent large areas in the field. Soil maps (available from casoilresource.lawr.ucdavis.edu/soilweb-apps/) and historical aerial imagery can often help in identifying field patterns and good location(s) for reference zones.


How and When to Apply the N-Rich Zone Fertilizer

A grower can establish N-rich zones during the pre-plant fertilizer application. For example, a grower may apply 50 pounds N per acre across the field and then make another pass or two in the zone to apply an additional 50 to 100 pounds N per acre (depending on what the grower calculates is necessary, as described above.) This method might be most easily adopted by growers. We have observed, however, that if the fertilizer is placed too deep in the soil profile, the N may not be readily available to the seedling crop early in the season because it is below the root zone. Therefore, N-rich zones established by this method may not provide a reliable early-season point of comparison. Instead, we have found that broadcasting urea is the most effective way to establish N-rich zones. At our demonstration sites, we broadcasted urea after tillage or shortly after planting, but always ahead of a storm or irrigation event that could incorporate the fertilizer. Orienting the zones perpendicular to the rows or tractor passes also helps to capture field variability. When the zones are too narrow and run in the same direction as the field work, it can be hard to differentiate between a field pattern associated with equipment passes and a N effect, particularly early in the season.


Monitoring the Field

Once the crop begins to grow, the field should be monitored periodically to assess whether the crop is likely to respond to a N fertilizer application. A combination of the soil nitrate quick test (SNQT) and plant reflectance measurements taken from both the N-rich zones and the broader field can indicate when a top-dress fertilizer application may be beneficial. The soil nitrate quick test and plant reflectance measurements complement other important information like current crop growth stage, crop yield and protein goals, and local weather records to inform a site-specific N fertilizer recommendation.

The SNQT is a simple and low-cost test that provides a ballpark estimate of the soil nitrate-N concentration in the root zone. Nitrate is a highly plant-available form of N. Using the SNQT when N fertilizer decisions are being made will help to narrow a range of fertilizer rates appropriate for that field. More information on using the SNQT in small grains, including a sample protocol and demonstration video, is available at smallgrains.ucanr.edu/Nutrient_Management/snqt/. Over the past several years, UCCE agronomists have developed a strong relationship between the value measured using the SNQT and an estimate of fertilizer N equivalence.

Crop reflectance can be measured using a number of tools, including handheld devices, drones and satellite imagery. Common indices that result from measurements of canopy reflectance are normalized difference vegetation index (NDVI) and normalized difference red edge index (NDRE). These indices represent measurements of light reflected from the crop canopy at key wavelengths indicative of plant vigor. Relative differences in vigor among plants in the same field can be captured by comparing canopy reflectance measurements like NDVI and NDRE. We have been using handheld devices, drones and satellite imagery at our demonstration sites to compare crop reflectance values in the N-rich zones and the broader field.

One of the tools we are using is the GreenSeeker by Trimble Agriculture. This is a hand-held NDVI meter (See Figure 1) that emits light and detects how much is reflected from the crop canopy in the red and infrared wavelengths. The GreenSeeker’s canopy measurement indicates how well the plants are growing and covering the soil with greenness. This information about vigor is important early in the crop’s growth because it indicates the ability of plants to support grain production and yield potential.

We are obtaining similar information as from the GreenSeeker by measuring NDRE with a five-band multispectral camera (MicaSense RedEdge-MX) mounted on a drone (DJI Matrice M200 V2). NDRE is similar to NDVI but replaces the reflectance from the red wavelength with reflectance from the red edge wavelength. Because the drone is able to capture data from hundreds of feet above the ground, it allows us to measure a large area quickly and under conditions when entering the field is not possible. Figure 2 depicts side-by-side images from a field in Solano County where N-rich reference zones were implemented during the 2019-20 season.

Figure 2. A field in Solano County where three N-rich reference zones are visible at tillering using NDRE captured via drone (left), but not visible to the naked eye (right) (all photos courtesy M. Leinfelder-Miles.)

Another device we are using to monitor plant N is the atLEAF CHL by FT Green LLC, which is a chlorophyll meter that measures light absorbed by a single leaf (Figure 3). Like the GreenSeeker, it also emits and detects light. The atLEAF CHL, however, measures how much light passes through a single leaf instead of measuring reflected light. This information becomes increasingly valuable as an indicator of whether or not the crop has sufficient N as it begins heading out and filling grain.

Step-by-step instructions for using both the GreenSeeker and atLEAF CHL in small grains are available at ucanr.edu/blogs/blogcore/postdetail.cfm?postnum=42903.

Since plant N is strongly related to plant greenness and chlorophyll content, measurements of NDVI, NDRE and leaf chlorophyll can serve as proxies for relative plant N status within a field. Many factors can affect absolute greenness or chlorophyll values, including variety, crop injury and environmental factors. Because of this, it is important to remember that the absolute values given by these devices are only meaningful when compared to a reference zone like the N-rich zone.

Figure 3. Small grain leaf inserted in the sampling area of the at LEAF showing a chlorophyll reading in the lower right corner of the display while the user’s back shades the device.


What do the Readings Mean?

Plant reflectance and transmittance measurements are best interpreted by expressing values measured in the broader field relative to the N-rich reference zones, according to the following equation:

Relative value= (Production area value)/(N-rich zone value)

The relative value is sometimes referred to as a Sufficiency Index (SI) and will usually result in a decimal value between 0 and 1. When the SI is below a certain threshold, it indicates that the production area is experiencing detectable N deficiency relative to the N-rich zone. Table 2 shows SI ranges for proximal and remotely-sensed data and the associated plant N status.

Table 2. Sufficiency Index (SI) values and associated plant N sufficiency status, calculated as the production area value divided by the N-rich zone value.

When it comes to deciding on N fertilization in California small grains, a N fertilizer response is almost certain when plant N status is “Highly Deficient”, very likely when the status is “Deficient” and uncertain when the status is “Sufficient”. The SNQT supplements the plant measurements with information about the current nitrate concentration in the root zone.

If a grower decides that a N fertilizer application is warranted based on the combination of plant and soil measurements, the next step is to figure how much N is necessary. This can be determined using a crop growth and N uptake model in conjunction with yield and protein goals. As part of our larger demonstration project, we will be releasing an online decision support tool in 2021 that integrates these components and provides customized predictions of crop response to in-season N fertilizer.



California farmers are under pressure to increase N use efficiency and reduce the potential for N loss to the environment. N-rich reference zones are a tool that can assist in these goals while considering and managing the risk of reduced yields. By implementing N-rich reference zones, using a suite of tools to monitor them during the season and comparing results to the broader field, a grower gets real-time knowledge to inform N fertilizer management in small grains. The information gained from implementing N-rich reference zones can help growers make fertilizer applications when increased yield and/or protein benefits are likely and avoid them when they are not. These improvements in N fertilizer decision-making can yield better economic and environmental outcomes in California small grain systems.