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Economic Trends in Almond Production

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The University of California Agricultural Issues Center (UC AIC) and the Department of Agricultural and Resource Economics at UC Davis work with UC Cooperative Extension Farm Advisors and Specialists to compile cost studies for crops and livestock produced in California. These costs and return studies are used by growers, bankers, crop consultants and many others to aid in a range of farm decisions from what to plant to production specifics. Often policy makers and researchers use these cost studies as well.  The current and archived cost studies can be found at: https://coststudies.ucdavis.edu/

UC AIC recently released new cost and return studies for almond production in California. These 2019 regional cost and return studies for almonds are available for the Sacramento Valley, and the Northern and Southern San Joaquin Valley. This recent update of almond studies presents an opportune time to explore trends in almond cost and returns for the most recent two decades.

Before digging into graphs and figures, it’s important to discuss the elements of the cost study. The cost and return studies are meant to be used as a guide for growers, and actual costs and returns will vary depending on the specifics of the operation, growing conditions, and orchard characteristics. Therefore, it is necessary to specify underlying assumptions for orchards represented.  It is not feasible to represent the infinite number of almond production scenarios out there. The following are some of the basic assumptions of 2019 cost study for the Northern San Joaquin Valley. For the full list of assumptions for each study listed in the charts, see the cost and return studies themselves.

  • The orchard consists of 100 acres of almonds with a density of 130 trees per acre.
  • No specific variety is listed.
  • The useful life of the orchard is expected to be 25 years.
  • A new micro-sprinkler irrigation system is installed during orchard establishment.
  • The expected yield at maturity is 2200 lbs per acre at an expected price of $2.50/lb.
  • Interest rates are 5.25% for operating loans and 6% for long-term investments.
  • Land value is $25,200 per producing acre.
  • Cost of pumping irrigation water from an established well is $100 per acre-foot.
  • Cost of pollination is 2 hives per acre at $200 per hive.

The cost studies go into detail about the following cost categories, and provide a look at costs and returns at various yield and price combinations.

Operating costs: Any costs associated with almond production practices in a given year, including pesticide and fertilizer applications, irrigation water, labor, harvesting, interest on operating loan.

Cash overhead costs: Expenses paid that are not for a particular enterprise and should be assigned to the whole farm operation, such as office and accounting expenses, assessments, field sanitation, or equipment repairs.

Non-cash overhead costs: Annual depreciation and interest cost for farm investments. Examples include depreciation on farm machinery, well/irrigation systems, annual establishment costs, etc.

Establishment costs: Total pre-plant, planting and accumulated costs for non-bearing years. Establishment costs are amortized (spread out) over the useful life of the orchard.

Total costs: Sum of operating, cash overhead, interest and non-cash overhead costs.

Looking over these cost studies can help growers and crop advisors make sure they are incorporating all costs when making crop production decisions.

Trends in Almond Costs

To outline the trends in almond production costs, I use the 1998, 2002, 2006, 2011, 2016 and 2019 UC AIC cost and return studies for establishing and producing an almond orchard in the Northern San Joaquin Valley using micro-sprinkler irrigation. This provides an approximate idea of how costs have developed over time. The trends in most cost categories should be similar across the state, however there may be noticeable differences in certain aspects across regions, ex: land values, water costs, etc.

Figure 1 displays per-acre costs of almond production over time. All costs are adjusted to 2019 dollars to account for inflation. It is clear from the figure that from 1998 to 2016, inflation-adjusted total costs of almond production remained similar at around $4,500 per acre.

Figure 1: Sample Per-Acre Costs of Establishing and Producing Almonds in the Northern San Joaquin Valley Using Micro-Sprinkler Irrigation, 1998, 2002, 2006, 2011, 2016, and 2019 (in 2019 dollars)
Sources: University of California Agricultural Issues Center Sample Cost and Returns Studies: https://coststudies.ucdavis.edu/.  US Bureau of Economic Analysis, GDP Price Deflator.

Between 2016 and 2019, total costs of almond production per-acre increased substantially (See Figure 1). The driver of this is a large increase in non-cash overhead costs. The primary increases in this cost category between 2016 and 2019 are increases in establishment costs and land values. Interest rates in 2016 were 3.25 percent compared with 6 percent in 2019, increasing establishment costs substantially. According to USDA National Agricultural Statistics Service, average irrigated land values in California increased by 8 percent on average from 2016 to 2019. Factoring land values into the cost of production allows growers to consider the opportunity cost of their investment in the almond orchard. Even if a grower owns the land he or she plans to establish an orchard on, he or she might be better off renting out the orchard and investing those rental revenues elsewhere.

Figure 2: Cost Categories as a Percentage of Total Operating Costs for Almond Production in the Northern San Joaquin Valley Using Micro-Sprinkler Irrigation, 2002, 2011 and 2019
Source: University of California Agricultural Issues Center Sample Cost and Returns Studies: https://coststudies.ucdavis.edu/

Operating costs per acre also increased between 2016 to 2019. Much of the increase in operating costs was due to increasing labor and pesticide costs, as well as increases in the operating loan interest rates. Figure 2 shows various cost categories as a percentage of total operating costs for 2002, 2011 and 2019 almond production. In 2002, pesticides, labor and harvest comprised more than 60 percent of total operating costs. While that number dropped to roughly 43 percent in 2019, over time, pollination, irrigation and fertilizer costs have increased to make up a much larger portion of total operating costs for almond growers. Irrigation costs may continue increasing as a percentage of total operating costs given implementation of the Sustainable Groundwater Management Act (SGMA), however it is unclear what the effects of this regulation will be (for SGMA resources see http://groundwater.ucdavis.edu/SGMA/). Pollination fees will likely continue their trend upward as well, though growers may be able to reduce pollination costs through decreasing the number of colonies per acre, planting self-fertile varieties or making mutually beneficial contractual arrangements with the beekeeper (Goodrich, 2019; Champetier, Lee, and Sumner, 2019).

Trends in Almond Returns

Figure 3: Planted Almond Acreage by Region and Nonpareil Average Base Rate ($/lb in 2019 dollars), 2004-2018
Sources: 2018 Almond Acreage Report, USDA NASS, CDFA. Blue Diamond Payment History 2004-2018. US Bureau of Economic Analysis, GDP Price Deflator.

Figure 3 shows the Blue Diamond average base rate for nonpareil meats from 2004 to 2018 (in 2019 dollars to adjust for inflation). Since 2016, prices have been lower than the 2004-2018 average of $3 per pound. Uncertainty in trade issues have resulted in decreased demand for almonds in a number of countries (Sumner, Hanon and Matthews, 2019). For example, almond exports to China were down 24 percent between 2018 and 2019 (Almond Board of California, 2019). This decreased demand has led to lower almond prices, and with future trade agreements still uncertain, it is unclear how prices will move going forward.

Figure 4: Variety Price as a Percentage of Nonpareil Price and Nonpareil Total Yield as Percentage of Butte/Padre, Butte, Monterey, Carmel, and Fritz Yield
Sources: Blue Diamond Payment History 2013-2018. Almond Board of California Almond Almanac 2013-2019.

The prices a grower receives will vary by quality, size and variety. Figure 4 shows average variety prices as a percentage of nonpareil. In 2016 and 2017, other varieties were discounted fairly heavily in comparison to nonpareil, while in other years discounts were not quite as large. What impacts the size of these discounts? The relative supply and demand of nonpareil compared with other varieties. Figure 4 also displays nonpareil production as a percentage of total production from Butte/Padre, Butte, Monterey, Carmel, and Fritz. In 2017 and 2018, nonpareil production was relatively high compared to these other varieties. The large supply of nonpareil almonds drives down the price relative to other varieties, shrinking the associated premium.

Trends in Planted Acreage

Figure 3 also shows planted acreage from 2004 to 2018 by region along with the average price of nonpareil. The planted acreage trends by region look relatively similar. Over the last five years, the largest almond producing region (Southern San Joaquin Valley) has seen planted acreage drop off significantly. Water availability concerns as well as relatively low prices are likely the driving issues here. The Northern San Joaquin Valley has also seen acreage drop off, but not as substantially as its southern counterpart. Planting in the Sacramento Valley has stayed relatively consistent over the last decade or so.

Figure 5: Planted Almond Acreage by Variety, 1998-2018
Source: 2018 Almond Acreage Report, USDA NASS, CDFA.

Figure 5 shows planted acreage for some of the main almond varieties. Toward the middle of the series, one sees the large planted acreage for most varieties due to relatively high prices in 2004-05. Over time, acreage plantings have stabilized at lower levels. The increase in self-fertile almond acreage is noticeable in the mid 2010s. Operating cost savings from pollination and fewer equipment passes through the orchard were likely driving this trend (Champetier, Lee and Sumner, 2019). Price discounts for the Independence variety in comparison to nonpareil have stabilized, from as low as 2 to 4 percent discount in 2013-14, to on average of 11 percent over the last four years for Independence compared to nonpareil.

Closing Remarks

Overall, net returns from almond production have likely narrowed over the last decade due to increasing costs of production. Land values and interest rates have increased, increasing the costs of establishing an almond orchard. Pollination, irrigation and fertilizer costs have increased as a percentage of total operating costs, while almond prices have remained at relatively low levels over the last few years.  The fact that acreage is still being planted suggests that the potential net returns remain relatively strong compared with other crops in California.

 References:

Almond Board of California. 2019. “Almond Almanac 2019”

Champetier, A., H. Lee, and D.A. Sumner. 2019. “Are the Almond and Beekeeping Industries Gaining Independence?” Choices. Quarter 4.

Goodrich, B.K. 2019. “Contracting for Pollination Services: Overview and Emerging Issues.” Choices. Quarter 4.

Sumner, D.A., T. Hanon and W.A. Matthews. 2019. “Implication of Trade Policy Turmoil for Perennial Crops” Choices. Quarter 4. Available online:

University of California Agricultural Issues Center Sample Cost and Returns Studies. Available online: https://coststudies.ucdavis.edu/

The Start of Irrigation in Almonds: Early Season Irrigation Management Impact Tree Health All Season

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Prolonged wet early season conditions have been linked to the “yellowing Krymsk” and “yellowing Rootpac-R” problem in young orchards. A yellowing ‘Monterey’ almond tree on ‘Rootpac-R’ rootstock in July of 2017. Similar yellowing symptoms have been seen in some young Monterey on ‘Krymsk 86’ trees, particularly in wet springs. All photos courtesy of Luke Milliron.

One of the motivations for making good water management decisions early in the growing season is to reduce the risk of root and crown diseases that can eventually kill almond and other tree species. These diseases need three elements to infect and damage a tree: a susceptible host plant, a pathogen, and favorable environmental conditions.

A second motivation for diligent early season water management is that even in the absence of a pathogen like Phytophthora, root death due to waterlogging alone can damage or kill trees. Prolonged wet early season conditions have been linked to the “yellowing Krymsk” and “yellowing Rootpac-R” problem in young orchards. This problem which is most often associated with the ‘Monterey’ variety, often resolves itself with careful soil moisture monitoring. Similarly, in older orchards, over-watered conditions in March through May have been linked to the lower limb dieback (LLD) problem. Both conditions show that early season water management can greatly impact tree health much later in the season.

Possible lower limb dieback symptoms in July of 2019 in a mature orchard in Durham, CA. In older orchards, over-watered conditions in March through May have been linked to the lower limb dieback (LLD) problem.

You can read more about “yellowing Krymsk” at: sacvalleyorchards.com/almonds/foliar-diseases/yellowing-krymsk/ and about LLD at: thealmonddoctor.com/2014/05/16/lower-limb-dieback-almond/

Early season water management influences the environment where roots grow by affecting soil temperature and aeration and can be pivotal in how much tree decline occurs. Trees are expensive. The money and effort spent to establish them is lost, more costs lie ahead to replace them, and production is lost.

Choosing the Best Time to Start Irrigating

Each season you need to decide when to start irrigating. It can be difficult to choose the best time to start irrigation. There are a lot of different information sources you can use to make this decision. You can copy practices that you observe around you, evaluate soil moisture, consider the weather and evapotranspiration loss of the crop (ETc), or take a plant-based approach. Utilizing multiple information sources is highly recommended. However, utilizing the plant-based monitoring approach of stem water potential readings with a pressure chamber (or “pressure bomb”) has a distinct advantage over the others.

Schematic showing how water potential is measured in a severed leaf and stem (petiole) using a hand-held pump-up pressure chamber. Source: Adapted from Plant Moisture Stress (PMS) Instrument Company.

The pressure chamber directly determines the water status experienced by the trees, while the other sources, such as ET or soil moisture, although helpful, are indirect. The pressure chamber gauges the amount of positive gas pressure (in pressure units, e.g. bars) required to balance the level of water tension in a plant sample (e.g. leaf; see related graphic). The level of water tension in a leaf expresses the degree of effort utilized to pull water all the way through the tree from the soil.

Relying on an indirect information source, particularly an approach like beginning irrigation when your neighbor does, when the surface soil has dried out, or irrigating on the first hot day, could result in irrigating too soon.

Using Information to Delay the First Irrigation

Research in walnut orchards in California’s Tehama and Stanislaus counties has found that the start of irrigation can be delayed by waiting for mild to moderate water status when measured with the pressure chamber. Some observed benefits have been a minimum 10-percent reduction in energy for pumping, less tree stress during harvest season, and no impact on edible kernel yield. A managed (informed) delay in the start of irrigation may allow for deeper root activity late in the season. It’s possible that a strategy that starts the irrigation season too early promotes a shallow root system at the expense of deeper root development. This is completely contradictory to the conventional wisdom in walnut and almond production that early season irrigation allows for “banking of water” to help avoid high water stress at harvest. UC researchers plan to investigate this managed irrigation delay in almonds in the northern Sacramento Valley.

Before UC researchers begin to see results from this work in almonds, it is best to be cautious in choosing a level of stem water potential with the pressure chamber to trigger the first irrigation of the season. From everything we currently understand, waiting for a tree water status of -2 bars below the fully watered baseline before applying the first irrigation represents a low risk irrigation decision that could benefit long term tree and root health. To learn more about the pressure chamber, stem water potential, the fully watered baseline, and how to go about getting equipment and taking measurements, check out our series at: sacvalleyorchards.com/manuals/stem-water-potential/

Monitoring Weather—Crop Evapotranspiration (ETc)

If using the pressure chamber isn’t appealing, or a second source of information is desired, monitoring the weather and evapotranspiration crop losses is an option. This method is sometimes called a “water budget,” because it is analogous to budgeting money. Soil water storage in the crop root zone equates to a balance in a checking or savings account. ET equates to a debit from the account and significant rainfall or irrigation equates to a deposit or credit into the account. Water budgeting approximates the soil moisture level in the root zone rather than measuring it with soil moisture sensors.

Weekly ET reports are available during the irrigation season online or can be delivered weekly by email. ET is estimated based upon real-time weather measurements at regional CIMIS weather stations. Estimates are for trees with at least 50 percent canopy cover and need to be adjusted downward for smaller trees. Each report provides a real-time estimate of ET in inches for the past seven days, an estimate for the next seven days, and keeps a running total for the season. Accumulations begin at leaf-out for each crop which enables their use to help decide when to begin the irrigation season. It is important to know the hourly water application rate (inches/hour) of your irrigation system.

Using an example from the 2018 season, if we followed each weekly report from February 16 to May 3 for the Gerber South CIMIS weather station, it showed that cumulative ET for almonds was 7.51 inches while cumulative rainfall for the same period was 5.26 inches and resulted in a 2.25-inch soil moisture deficit. This assumed that all of the rainfall was effectively used in the orchard which is a site-specific consideration that needs to be adjusted accordingly in the water budget. Dividing this 2.25-inch soil moisture deficit by a water application rate of 0.07 inch per hour (i.e. an almond orchard with 124 trees per acre with one 16 gph microsprinkler per tree) equates to 32 hours of irrigation or the equivalent of two 16-hour irrigation sets that suit PG&E off-peak rates. Choice of set length is site-specific depending on irrigation system and soil type; however, it is best to minimize ponding conditions that can starve roots of oxygen and provide favorable disease conditions.

For help with your own ET calculations see:  sacvalleyorchards.com/et-reports/

The previous example provides context on how this deficit relates to the irrigation system capacity. It is left to the irrigation manager’s judgement to continue to delay the beginning of irrigation to protect tree and root health, begin irrigation by partially refilling the soil moisture deficit (i.e. one 16-hour irrigation set), or begin irrigation and fully replace the soil moisture deficit. If this information were paired with the pressure chamber measurements and the stem water potential measurements were still within -2 bars of the fully irrigated baseline, the manager may have more peace of mind about continuing to delay the first irrigation.

Monitoring Soil Moisture Depletion

If neither the pressure chamber nor water budgeting appeal to you or you are looking for a supplement to one or both methods, directly monitoring soil moisture is an option. Checking soil moisture by hand is a very basic method to evaluate soil moisture conditions. There are many online stores where soil augers can be purchased (examples include: JMC Backsaver, AMS samplers, Forestry Suppliers, and Ben Meadows). For interpretation of soil moisture in collected samples, the USDA-National Resource Conservation Service also offers a nicely prepared publication with color pictures titled Estimate Soil Moisture by Feel and Appearance.

There are also a wide variety of soil moisture sensors that can also be used. Refer to the UC ANR article Soil Moisture Sensor Selection is Confusing for more insight: sacvalleyorchards.com/blog/soil-moisture-sensor-selection-is-confusing/

The Judgment of the Irrigation Manager

Stem water potential readings with a pressure chamber, evapotranspiration-based water budgets and soil moisture monitoring all bring different and valuable information to the decision of when to first irrigate almonds. Stem water potential readings with the pressure chamber offer the most direct measure of tree irrigation need. In addition, adopting this practice may both save water and encourage valuable deep root development. No matter if you choose to adopt one, or all three of these monitoring approaches, the irrigation-manager’s careful judgement is most important.

Spray Calibration and Coverage: The Basics of Spray Application

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Air-assisted sprayers discharge tank mix as tiny spray droplets into an airstream that transports the droplets to the target tree or vine canopy. The mixture of air and spray droplets, known as the spray cloud, expands in both the vertical and horizontal dimensions as it moves away from the sprayer’s outlet. The speed of the air reduces drastically after exiting the sprayer and then continues to reduce gradually with distance away from the sprayer. Because the sprayer is moving, however, the spray cloud appears as having been bent backwards.

If we consider the continuous forward movement of the sprayer to be in short steps of equal lengths, we can determine the time the sprayer spends in each step by dividing the step length by the travel speed. We can then multiply the time by the flow rates of the air and spray liquid to know the volumes of air and spray discharged in each step movement. The volume of spray is what is applied in each forward step and the volume of air is how much is available to carry the applied spray. The slower the travel speed, the higher the volume discharged; the faster the travel speed, the lower the volume discharged.

During the spray application, immediate tree or vine canopies adjacent to the sprayer are the target canopies (Figure 1, below). Each tree or vine is bound by a ground area equal to row spacing times tree spacing. It is sufficient and most efficient for the air to carry spray droplets to the target, not beyond. This is because spray droplets carried beyond the target tend to either fall to the ground or potentially drift away by the wind when they miss canopies in the subsequent rows. However, the air speed and volume should be enough to cause the spray to penetrate the target canopy. This means that travel speed and air volume of the sprayer should be matched to the canopy size and density. Also, the number of nozzles used should not result in too much spray applied over and/or under the canopy. Effective spraying will result if the spray is strategically directed toward the target.

Figure 1. Basics of spray application

 

Sprayer Calibration: What, Why, When and How

What is it? Sprayer calibration is the adjustments made to a sprayer based on measurements taken to ensure that the correct amount of material (spray mix or active ingredient) is applied.

Why is it important? Calibration is best practice in pesticide spray application. When done correctly, it is a sure way to know how much material you would actually be applying to your crop. Incorrect calibration or not calibrating at all can result in inaccurate application rate, ineffective application, and illegal residues on the treated crop. Accurate calibration will lead to effective pest control while minimizing waste and negative environmental impact. Above all, accurate sprayer calibration will ensure compliance with the law as represented by the pesticide label.

 When should it be done? Ideally, sprayer calibration should be done at the beginning of the growing season and whenever there is a significant change in conditions. Examples of changes in condition that may require calibration include: Change in ground condition (e.g. soil type, soil wetness, ground cover); change in target condition (e.g. crop type, canopy size, canopy density); change in spray material condition (e.g. density). Although not all the calibration steps may be necessary in response to a change, adjustments should be made to the components that are directly affected by the change. For instance, if only ground condition has changed, then only travel speed would have to be determined again and appropriate adjustments made. However, if a global positioning system (GPS) based speedometer device or mobile app is in use, then it may not be necessary to check speed again. This is because readings of GPS-based speedometers are not affected by changes in tire traction due to ground cover.

How should it be done? A major objective of sprayer calibration is the idea of optimizing the application. There are different ways to do it, but with the same or similar outcome. The steps could be as follow: 1) determine travel speed; 2) assess air profile to determine number of nozzles; 3) select nozzles; 4) measure sprayer output; 5) adjust sprayer output; and 6) assess spray coverage.

STEP 1: Determine Travel Speed
This should be done with the sprayer tank about half-full and the fan running.

Materials needed: Measuring tape, flagging flags, stopwatch, calculator, clipboard, GPS device (e.g. smartphone).

Method 1 – Manual known distance method: Measure a known distance, D, (typically 100 or 200 feet) with a measuring tape in the orchard or vineyard where you would be spraying. Use marking flags to clearly indicate the distance. Using a stopwatch, measure the time, T, it takes for the sprayer to travel the marked distance at a preselected gear setting. Repeat this for at least three times in total and determine the average time. Calculate the speed, S, as:

When two people are available, in addition to the operator, person A should stand adjacent to the starting flag with one hand up (Figure 2a, below). Provide enough distance for the sprayer to attain the speed before reaching the starting flag. Once a predetermined feature on the tractor/sprayer (e.g. front of tractor/sprayer, center of front wheel, etc.) reaches the starting point, person A should lower the raised hand to indicate to person B to start measuring the time with a stopwatch. Once the predetermined feature on the tractor/sprayer reaches the ending flag, person B should stop measuring the time and then record the elapsed time on a clipboard.

Figure 2. Various ways to determine travel speed.

When only one person is available, in addition to the operator, fix the marking flags in the sprayer’s path (Figure 2b, above). Provide enough distance for the sprayer to attain the speed before reaching the starting flag. Once the front of the tractor touches the starting flag, start measuring the time with a stopwatch. Again, once the front of the tractor touches the ending flag, stop measuring the time and then record the elapsed time on a clipboard.

When only the operator is available, fix the marking flags in the sprayer’s path. Provide enough distance for the sprayer to attain the speed before reaching the starting flag. Maintaining sitting posture, start measuring the time with a stopwatch the moment the starting flag disappears and stop measuring just when the ending flag disappears. Record the elapsed time on a clipboard.

Method 2 – Manual tree passed method: Count about 10 or more trees or vines and fix two marking flags in an adjacent mid-row in the path of the sprayer (Figure 2c, above). Additionally, you can tie pieces of flagging tape on the vine adjacent to the marking flag to aid the operator’s visibility. Note the tree spacing, TS. Providing enough distance for the sprayer to attain speed before reaching the starting flag, measure the time it takes for the sprayer to travel the marked distance at a preselected gear setting. The number of trees passed by the sprayer, NT, is the count excluding the starting tree but including the ending tree. Repeat time measurement for a total of at least three times and determine the average. Calculate the speed as:

 

Method 3 – Automatic tracking method: Drive the sprayer for about 100 ft or more while observing the speed reading on a GPS device (a smartphone with a GPS speedometer app can be used for this). Repeat the observation for at least three times in total and determine the average. If the tractor pulling the sprayer is equipped with a GPS monitor, then speed measurement may not be necessary.

STEP 2: Assess Air Profile to Determine Number of Nozzles

Materials needed: Flagging tape, digital camera (e.g. smartphone).

Method:
Attach about 4 feet of flagging tape to each nozzle on the sprayer manifolds. Start the fan and observe the aloft flagging tapes from behind the sprayer, see Figure 3, below. Take a photo of the scene with a camera for reviewing. From the photo, determine the number of nozzles and their position that are well directed on the target canopy. Turn off nozzles that miss the target canopy. To better understand why this is necessary, see Figure 4, below.

Figure 3. To assess the air profile, attach about 4 feet of flagging tape to each nozzle on the sprayer manifolds. Start the fan and observe the aloft flagging tapes from behind the sprayer. (All photos courtesy of P. Larbi.)

 

Figure 4. Various nozzle configurations with different degrees of missing target canopy.

Also, attach a piece of flagging tape to the target tree or vine canopy and the next adjacent canopy in the path of the air. Drive the sprayer across the taped locations at the determined travel speed with the air running and observe the tapes on the canopies. If the tape on both canopies are sufficiently aloft, the air might be too much (Figure 5a, below). Adjust the air if the sprayer is equipped for that, considering the target canopy size and density. Otherwise, increase the travel speed to adjust the air (Figure 5b, below). Another option is to partially cover the fan inlet using a so called ‘Cornell doughnut’ (Figure 5c and 5d, below). Ideally, an automated means of adjusting the fan intake would be best.

 

Figure 5. A look at various ways of adjusting air
volume.

STEP 3: Select Nozzles

Materials needed: Calculator, clipboard, nozzle catalog, nozzle selection mobile app

Method:
Knowing the desired application rate, AR, and row spacing, RS, determine the total sprayer output per side, SO, from all open nozzles as:

If the spray volume is intended to be uniform on each side, then divide SO by the determined number of nozzles to get the desired nozzle flow rate. Use this number to select the nozzle from a nozzle catalog.

However, SO can be split into different fractions for upper nozzles and lower nozzles. A common configuration for trees is 2/3 for upper nozzles and 1/3 for lower nozzles. Whatever the split ratio, the total should amount to the calculated SO. Various available software applications and mobile apps can be used to aid this determination.

STEP 4: Measure Sprayer Output
This should be done with the sprayer stationary. Alternate methods to that presented here exist.

Materials needed: Measuring pitcher, stopwatch, calculator, clipboard, automatic nozzle calibrator, flow meter, pressure tester.

Method:
With the sprayer running in a fixed position, confirm that the pressure gauge reading is accurate using a tool. Start spraying and collect spray water from each nozzle for 1 min using a measuring pitcher (see figure 6) and record the values in fluid ounces (oz). These should be the nozzles that will be used for the spray application. Calculate the flow rate of each nozzle as:

Repeat the measurement and determine the average.

Calculate the sprayer output by multiplying the average FR by N, for uniform application. For non-uniform application, do this separately for the upper and lower sections and sum them up.

Alternatively, you can automatically measure the flow rate by using a flow meter (e.g. SpotOn™ calibrator). Also, you can use a manifold patternator to observe uniformity of nozzle flow across all nozzles.

STEP 5: Adjust Sprayer Output
There are two adjustments that can be applied to the sprayer output in order to achieve the desired application rate, if the measure sprayer output is off. The first is adjusting the travel speed, while the second is adjusting the pressure.

Adjusting travel speed:
The adjusted travel speed, S2 can be obtained as:

where,
AR1 = application rate obtained with the actual measured sprayer output in Step 4
AR2 = desired application rate in Step 3
S1 = travel speed measured in Step 1.

Adjusting operating pressure:
The adjusted operating, P2, can be obtained as:

where,
SO1 = measured sprayer output in Step 4
SO2 = desired sprayer output in Step 3
P1 = initial operating pressure

STEP 6: Assess Spray Coverage
Attach water sensitive cards (yellow cards that turn blue when moist) to different locations
in the target canopy. Run the sprayer and apply water similar to the intended application. Evaluate the spray coverage to ensure that it is suitable. Make adjustments as necessary to obtain a suitable coverage.

Water sensitive card for spray coverage assessment

Once the proper settings have been obtained, maintain these settings in the actual application, making sure to factor in weather conditions. It is also important to clean the sprayer and maintain it in good working condition to ensure good performance.

Selecting the Right Rootstock in California Prune Production

A tree at the Yuba rootstock trial site that likely died of a bacterial canker infection sometime after leaf-out in 2018 (photo: Luke Milliron).

Roots are the unsung heroes of orchard plantings. They operate out of sight and are relatively difficult to examine and characterize. The roots of course anchor the trees to the soil and take up water and essential mineral elements. They also store carbohydrates and synthesize materials. Because roots play these key roles, rootstocks can influence scion vigor, growth and performance. Rootstocks vary in their tolerance to different soil types and conditions and their resistance to soil borne diseases and nematodes

As soil treatment options become increasingly limited, more restrictive and less effective, the priority to identify a genetic solution to solve or reduce the replant issue is of increasing interest. One genetic solution is to find or develop rootstocks to help manage soil related problems, such as soil borne fungi/bacteria, nematodes and soil acidity and excess salts. Of additional interest are root and tree characteristics imparting canopy size control, good anchorage and little or no root suckering.

The California prune industry has historically utilized just five rootstocks, Myrobalan 29C, Myrobalan seedling, Marianna 2624, Lovell peach and Marianna 40. The Prune Production Manual (UC ANR # 3507) has a very good chapter describing the traditional rootstock choices. You can find the production manual for sale at anrcatalog.ucanr.edu and as an e-version through Google Books. Recognizing the need for identifying additional rootstocks for California prune production, University of California farm advisors and campus-based faculty with funding from the California Prune Board designed and planted two replicated rootstock experiments in 2011 to evaluate 15 rootstocks for prune production. These rootstocks have diverse genetic backgrounds within the Prunus family (plum, peach, almond, etc.).

Replicated rootstock trials in growers’ orchards in Butte County and Yuba Counties allow UC researchers to evaluate a total of 15 rootstocks (Table 1, below) under very different soil, irrigation, and yield potential. The Butte plot is planted on Farwell clay adobe and the lighter textured Nord Loam soil types; this ground was previously planted to almonds on Lovell (peach) rootstock. In contrast, the Yuba site is planted on more typical prune ground (Kilga clay loam) and is prune following prune. The Butte site has tighter spacing at 12.5 feet in-row and 17 feet between rows (205 trees per acre), compared to 16 feet in-row and 18 feet between rows (151 trees per acre) at Yuba. The Butte plot is drip irrigated, while the Yuba plot has micro sprinklers. The differences in soil, crop history, tree density, irrigation, and resulting vigor at the two replicated trial sites allows for a rigorous evaluation of these rootstocks.

 

Tree Survival

Roger Duncan a pomology farm advisor based in Stanislaus County, who has done extensive trialing of rootstocks for almond production, has noted that rootstock choice is like an insurance policy. Although there is no perfect rootstock, careful rootstock selection can help guard against disaster. These two trial sites have illustrated an incredible range in rootstock survival, which helps illustrate a varying ability of these rootstocks to guard against disaster at two very different sites. Following a wet winter which delayed soil preparation in 2011, both the Butte and Yuba sites experienced extensive mortality and were significantly replanted in 2012. However, even after replanting in 2012, the rootstocks have experienced very different rates of survival.

Percent tree survival since the 2012 replanting was assessed at both sites in 2019 (Table 2, below). Survival ranged from 10 percent (Empyrean 2) to 97 percent (Atlas) at the Butte site, and 37 percent (HBOK 50) to 100 percent (Viking and Lovell) at the Yuba site. The two rootstocks that are only planted at a single site each have had dramatically different results, with the disastrous 10 percent survival of Empyrean 2 at Butte, compared to the 93 percent survival of Rootpac-R at Yuba.

Table 2: Percent tree survival at the Butte (September) and Yuba (June) sites in 2019. Values followed by the same letters are not significantly different at 95 percent using Tukey’s HSD. The numerically highest and lowest values are highlighted in each column.

There are other notable differences and similarities in survival between the two sites. Myrobalan 29C, Myrobalan seedling, and HBOK 50 have all had higher survival rates at the Butte site, potentially due to bacterial canker susceptibility at the Yuba location. At both sites, Atlas and Viking, which were planted in 2012 (not available in 2011), have had excellent survival (97 to 100 percent).  Marianna 40 and Marianna 2624 have also had decent survival (80 to 87 percent). Finally, Marianna 30 has had very low survival at both sites (43 and 37 percent at Butte and Yuba, respectively).

Bacterial canker susceptibility has greatly colored the results at the Yuba location. Land with a history of the disease likely has ring nematode, and may also have sandy or low pH soils, low tree nitrogen status, or a clay/shallow hardpan. For land with a history of bacterial canker, having a prune orchard with a high rate of survival at maturity is no small feat.

Satellite image of the UCCE prune rootstock plot in Yuba County. Although tree loss was likely from multiple causes, bacterial canker was a significant player. Note gaps of six trees (number of trees in a replicate), despite rootstock treatments with large, healthy canopies surrounding these gaps (Google©, Imagery Maxar Technologies ©2019, and U.S. Geological Survey map data ©2019).

The satellite image of this plot clearly shows several gaps of missing trees that are six trees in length (i.e. the number of trees in a rootstock treatment replicate, see related photo). Although there are several causes of tree loss in the plot, certain rootstocks have had very low survival in the same areas of the orchard where other rootstocks have 100-percent survival and vigorous growth. For example, Myroblan 29C an industry standard, had a mere 63-percent survival as of 2019, while Marianna 30 and HBOK 50 fared even worse, each at 37-percent survival. In contrast, Viking, Atlas, Krymsk 86, Lovell and Rootpac-R all had between 93- and 100-percent survival.

Vigor and Yield

The first mechanical harvest in the two trials was in 2017 and yield data continues to be taken. In addition to the Butte site having tighter spacing (205 trees/acre, compared to 151 at Yuba), the tree trunks have generally been larger, and yields per tree higher than Yuba. The 2017 yield results at Butte offer a valuable glimpse into the vigor of these rootstocks, since it was a very high yielding and unthinned crop, which helps illustrate the yield potential of these rootstocks. These high, unthinned yields were unsustainable and in 2018 there was poor return bloom at the site and low yields.

The 2017 harvest at the Butte site shows that a larger trunk, measured as trunk cross sectional area (cm2), generally higher dry yield (pounds per tree), and smaller fruit size (table 3). Among the smaller trunk size and lower yielding trees were Krymsk 1, HBOK 50, Marianna 58, Empyrean 2 and Citation. Among the largest and highest yielding were Myrobalan 29C, Atlas, Viking, Marianna 30 and Lovell. Similar yield and trunk size differences between rootstocks have been found subsequently at both sites. Of course, all rootstock trials that impose the same spacing across the plot disadvantage lower vigor rootstocks that could have been placed at a higher density.

Although there are similarities in yield performance of the rootstocks at both sites, there are some notable differences between sites. Rootpac-R, which isn’t planted at the Butte site, has had middle of the pack trunk size and yield at Yuba. Another notable difference is that Krymsk 86 is a fairly average vigor and yield rootstock at Butte but is among the largest and highest yielding at Yuba.

Table 3: 2016 trunk size (trunk cross sectional area in cm2) and ‘Improved French’ prune yield characteristics for the Butte County rootstock experiment harvested 8/29/17. Values are treatment means for the five replicates. Values followed by different letters are significantly different.

Anchorage & Suckering

In addition to survival and vigor (and resulting yield potential), there are other attributes that are important to growers. Anchorage is key since growers need trees to stand up on their own and not be blown over, as well as provide a straight up-and-down trunk for shaker harvesting. Degree of lean was measured with the level feature in the iPhone at both rootstock plots with one person pushing against the tree and another person measuring the deflection. Although rootstocks at the Yuba site had greater lean (there were notable wet soil conditions at the time of measurement), the rootstocks had similar relative lean to one-another at the two sites. Marianna 58 and Krymsk 1 had among the greatest angles of deflection, while Viking and especially Krymsk 86 showed little deflection at either site.

Removing suckers is a costly and cumbersome activity. In addition, rootstock suckers may offer a route for systemic herbicides to be taken up and damage the tree. Rootstocks suckers were rated on a one to five scale, with one being the fewest suckers and five being extensive and large suckers. Again, the two sites offered many similarities in rootstock performance. Myroblan seedling had the most rootstock suckers at both sites, while many rootstocks including Atlas, HBOK 50, Viking, Citation, Marianna 58, Lovell and Marianna 40 had few, if any suckers.

Rootstocks with Potential Problems

Many of the rootstocks haven’t performed well when survival, lean, and suckering were evaluated. Many of those same underperforming rootstocks also tend to be on the lower vigor and lower yielding end of the spectrum. Krymsk 1 and Marianna 58 had among the highest lean, and in-addition Krymsk 1 had low survival at Butte and was among the lowest yielding rootstocks. HBOK 50 also had high lean, poor survival at Yuba, and poor yield at Butte. Empyrean 2 which was only at Butte, had a mere 10-percent survival by 2019. Myroblan seedling had the worst suckering and had high lean at Yuba. The industry standard Myroblan 29C has performed well at Butte but has had low survival under the bacterial canker conditions in Yuba. Marianna 30, despite been among the highest yielding rootstocks per tree at Butte has had very low survival at both sites.

Rootstocks with Evident Strengths

Krymsk 86, Viking, and Atlas have all had very high survival at both rootstock trial sites. In addition, Krymsk 86 has been among the highest yielding at Yuba, and Atlas and Viking have been high yielding at both sites. Krymsk 86 has maintained its reputation for excellent anchorage, while Viking also showed little lean at both sites. Finally, both Viking and Atlas had a sucker rating of zero at both rootstock plots.

Where is Rootstock Selection in the Industry Headed?

Atlas, Viking, and Krymsk 86 have all shined at these two rootstock plots. Krymsk 86 is the only one of these that is so far seeing significant adoption in the prune industry. Following widespread adoption of Krymsk 86 in the Sacramento Valley for almond production, Krymsk 86, known for its superior anchorage and tolerance to wet feet, has been planted now in many new prune orchards. Like the higher vigor at the Yuba site and in contrast to the middling vigor at Butte, we have heard from growers that Krymsk 86 has been a high vigor rootstock in their plantings. Just as with growing almonds on Krymsk 86, growers should test for and be wary of planting Krymsk 86 where nematodes, particularly root-knot, are present.

As described in an article in the September/October issue of Progressive Crop Consultant (progressivecrop.com/2019/10/californias-prune-orchard-of-the-future) choosing a higher vigor rootstock and/or planting at a tighter spacing leads to capturing more sunlight and having a higher yield potential. However, when hand pruning large prune trees can cost $1,000 per acre, many growers are adopting mechanical hedging, and some progressive growers have had an increased interest in low vigor rootstocks. A couple of these growers have begun trialing low vigor inducing rootstocks in high density plantings, in hopes that low vigor rootstocks will reduce pruning expenses. Low vigor, high density and potentially trellised plantings, stand in stark contrast to the vigorous rootstocks that have stood out in these two trials. The choice between high and low vigor rootstock may prove to be one of the key defining choices where the California prune industry heads in the coming years.

We want to sincerely thank an amazing team of UC researchers, as well as support from dryer managers at Sunsweet Growers Inc. This work is made possible by the generous funding support of the California Prune Board.

The Botrytis Gray Mold Fungus: Pervasive Pathogen, Formidable Foe

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. Strawberry fruit are very susceptible to gray mold caused by Botrytis.

Introduction and Significance

When evaluating the impact and importance of a plant pathogen, one could consult various metrics to make such an assessment. One could consider the values of the affected crops, the acreages planted, the geographic distribution (how widespread is it?) of the pathogen, the mode of pathogen attack (does it affect leaves, flowers, both?), the persistence and staying-power of the organism, and the difficulty in controlling the pathogen. The Botrytis fungus, causal agent of gray mold and other related diseases, is one of the few plant pathogens that could arguably be placed at or near the top of a key pathogen list based on all of these criteria. Field professionals likely are familiar with the challenges of gray mold for the crops they oversee. However, what may be overlooked is the impact of Botrytis throughout a broad spectrum of many agricultural commodities and settings. Botrytis is an unusually dangerous threat due to its ability to infect dozens of crops, uncommon versatility as a microorganism, and propensity to change genetically in adapting to fungicide chemistry.

Table 1. Examples of Vegetative, Flower, and Fruit diseases caused by Botrytis on diverse crops.
*In contrast to most other crops diseases on onion are not primarily caused by Botrytis cinerea but by other Botrytis species.

Broad Spectrum Impact on Crops Worldwide

Botrytis is a highly ranked plant pathogen due to its broad host range that includes hundreds of plants. Such hosts are in almost all commodity groups: annuals and perennials, herbaceous and woody plants, food and ornamental crops, vegetable and fruit and field crops. Included within this diverse list are dozens of high value vegetable, fruit, and ornamental commodities (examples are listed in Table 1 and seen in Photos 1 to 4), for which gray mold can inflict sizeable economic losses. This broad spectrum of activity can also be described based on the type of plant tissue affected. Depending on the crop host, Botrytis can infect the vegetative portions (stems, petioles, leaves), flowering parts (buds, sepals, petals, reproductive tissues), and fruit (immature and ripe phases).

The Botrytis impact on all these crops and commodity groups is further compounded by two factors. First, the gray mold fungus can cause significant disease both before and after harvest. Pre-harvest disease occurs when Botrytis is active on developing plants in the field and greenhouse, resulting in blight, decay, and rot that reduces crop quality and harvestability. In addition, for many crops the Botrytis fungus can be a contaminant on or even inside the harvested plant commodity. Once these contaminated commodities are stored, the Botrytis fungus can become activated under certain postharvest conditions and cause rots and decay in storage (Photo 5). Secondly, we note that Botrytis is found throughout most agricultural and horticultural production regions in the world. In the USA, there are only a few states where an official report of Botrytis is lacking. Likewise, Botrytis is found throughout the world and is reported to cause disease on a huge number of crops and plants.

On pea, Botrytis can cause a pre-harvest disease but is perhaps more important as a postharvest problem, as seen by these lesions on stored pea pods.

Versatility as a Microorganism

A notable feature about Botrytis is the organism’s ability to function in different modes or survival strategies. This diversity of biological activity is not commonly seen in plant pathogens and points to the extreme versatility of Botrytis as a microorganism. Pathogen: We are most aware of Botrytis as an aggressive, difficult to control primary pathogen of plants. From an agricultural point of view, this is the most prominent role for Botrytis. Saprophyte: In a different mode, Botrytis does not even need a living plant. As a saprophyte, the gray mold fungus can grow, thrive, and reproduce on senescent, dying, and dead organic plant tissue. Spores that land on decaying matter can readily germinate and colonize such substrates. Secondary invader: If a plant is injured from weather extremes, damaged from mishaps in the field, or has symptoms caused by other pathogens, spores of Botrytis can drop onto such compromised plant tissues and aggressively grow on and overwhelm the injured plant. In such situations Botrytis did not initially cause the problem but is a secondary invader that can make the overall problem worse.

Dormant sleeper: Botrytis can be a sneaky adversary. This pathogen can infect and penetrate plant tissues but remain dormant within the protection of its host. Later, when the conditions change, the weather warms, or the plant tissues mature and grow, the once dormant Botrytis wakes up and begins to colonize the host, resulting in gray mold disease. Such dormant infections are called latent or “quiescent” infections. Opportunist: Botrytis is an opportunist because it can switch from being a harmless saprophyte, growing on dead tissue that growers do not care about, to an aggressive pathogen causing problems. Numerous examples exist of this switching. The Botrytis starts by colonizing dead parts of plants, such as old flower parts; if these Botrytis-laden dead pieces are in contact with healthy tissue, the Botrytis is able to bridge over from the dead to the living, resulting in a primary disease problem (Photo 6).

Gray mold is also versatile in how it survives and is moved around in the agricultural environment. Airborne spores: The gray color of the fungus, as it appears on infected plants, indicates Botrytis is producing millions of spores. These spore masses (Photo 7) are readily spread long distances by winds, splashing water, and physical contact. Sclerotia: Under certain conditions Botrytis can produce a survival structure, the sclerotium, which is a hard, black, oblong to spherical structure that can be up to ½ inch long. Sclerotia can withstand dry, warm, or cold conditions and can survive inside dead crop debris or buried in the soil; under conducive conditions these sclerotia can germinate and produce mycelium that infects the host. Sclerotia can form within the hollow stems of plant hosts and be carried with the plant if these stems are moved to other locations. Sclerotia can become mixed in with seed and become a seedborne contaminant. Embedded mycelium: In another survival mode, the hyphal strands of Botrytis can penetrate and be buried inside the living flowers, buds, or stems of plant hosts. This strategy allows the gray mold fungus to be protected from harsh environmental conditions, giving it an opportunity to wait for more favorable situations.

Botrytis can cause a brown decay on orange fruit by first colonizing dead flower parts that stick to the fruit; here the old blossom has been moved aside to show the developing brown lesion.

Genetic Plasticity and Loss of Fungicide Efficacy

Botrytis is notorious for becoming resistant (insensitive) to fungicides because of its high genetic variability and adaptability, profuse production of spores, and multiple cycles of spore production. Molecular recombination, mixing of genes between strains, and mutations provide the raw genetic material for resistance to develop. When fungicides are applied numerous times to a susceptible crop, the presence of the chemical challenges Botrytis and can result in the selection of individual strains that are no longer affected by that chemistry. Fungicides with single-site modes of action are especially at risk for inducing resistance in Botrytis. Worldwide, resistant isolates of Botrytis have been confirmed for all of the single-site fungicide categories used to manage gray mold (Table 2). Even more alarming are the research findings that show individual isolates of Botrytis can possess resistance to multiple fungicide classes; there are even isolates that are shown to be resistant to seven different fungicides, each of which has a different mode of action.

Table 2. Fungicide classes for use against Botrytis and for which resistance has been reported. *FRAC = Fungicide Resistance Action Committee

A Note About Botrytis Species

This article is addressing the broad topic of gray mold caused by Botrytis, and for most crops the pathogen species is Botrytis cinerea. However, examining the DNA of Botrytis from different crops in different parts of the world, powerful molecular tools and innovative techniques are detecting multiple, diverse genetic signatures which indicate that B. cinerea is not the only gray mold species out there. For example, a series of studies documents that strawberry can be infected by one or more of the following Botrytis species: B. cinerea, B. fragariae, B. caroliniana, B. mali, B. pseudocinerea. Such findings can have implications for the farmer and the field. On grapes in France, for example, the B. pseudocinerea species is more active in the early spring, while B. cinerea is active in both spring and fall. There are indications that a higher percentage of B. pseudocinerea isolates are resistant to some fungicides than B. cinerea isolates. So in the future it might be critical to know exactly which species is causing gray mold, since different species may require slightly different management approaches.

Management of Gray Mold

Controlling gray mold diseases requires the implementation of IPM practices. Fungicides: Judicious and strategic use of fungicides remains the primary means of managing gray mold. Multiple applications usually are needed, throughout the season, using diverse products having different modes of action. Fungicides with single-site modes of action are especially at risk for inducing resistance in Botrytis, so multi-site products should be integrated into spray programs. Sanitation: Sanitation measures, such as the removal of dead leaves and diseased fruit, appear to only slightly decrease gray mold incidence and cannot replace reliance on fungicide programs. Given the logistical difficulty and expense of such measures, these sanitation steps are not practical for most commercial growers but could be a consideration in certain circumstances, such as for greenhouse crop production.

Botrytis produces masses of airborne spores that readily land on host crops.

Modifying the environment: Because Botrytis is dependent on free moisture and high humidity, reducing such factors can help reduce disease severity. The venting out of moist air in a greenhouse is one example of such environmental modifications. Use of drip irrigation is a field equivalent of reducing water on foliage and can reduce gray mold severity. Canopy modification (pruning to remove leaves and laterals and increase air flow and light penetration) can help with bunch rot control in grapes. Resistant or tolerant cultivars: For most crops there are no cultivars that are genetically resistant to Botrytis. However, some cultivars may experience less gray mold for other reasons. For example, some strawberry cultivars suffer less gray mold due to the upright growth habit of leaves and flowers. Use such cultivars if available. Reduce damage: Reducing damage to crops in the field will reduce the opportunities for Botrytis to invade as a secondary decay organism. Proper harvesting and postharvest handling of fruit are critical to reducing fruit injury and lowering the impact from gray mold. Storing fruit at low temperatures is also necessary to retard gray mold and slow down the aging and senescing of fruit.

Screening of 1,000 Acala Cotton Lines

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Photos taken right after planting and again at harvest time. (Photos courtesy of J. Olvey.)

Work Completed

  • Selected 1,100 Acala Cotton Lines to be screened.
  • Prepared seed (ginned, delinted, treated, and packaged) for planting.
  • Planted seed in multiple testing locations.
  • Took multiple stand evaluations to determine the degree of FOV-4 damage.

Findings to Date

  • The year started off well with good stands on all Acala Lines.
  • Upon the completion of stand evaluations, we eliminated over 800 Acala Lines as being susceptible to FOV-4.

Work to Be Completed

  • Determine the degree of vascular staining in each Acala Line that has not already been eliminated from stand evaluations.
  • Rate each Acala Line based on productivity.
  • Assemble data and analysis throughout the year.
  • Complete Final Report.

Maintaining Fusarium Wilt Race 4 (FOV4) Resistance/Tolerance of Cotton

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The funded amount for this project from CCGGA is devoted to support travel to California for Dr. Ulloa and to assist in evaluation, progeny development, breeding and coordination of seed increases of selected developed progeny and breeding lines of Pima and Upland cotton for future testing and germplasm public releases with improved resistance/tolerance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 (FOV4), a soil borne fungal pathogen. These FOV4 breeding research efforts and activities are coordinated and supported by the California team. In addition, funding partially pays for professional research/services support needed to increase our understanding of plant FOV4 defense mechanisms.

Over the past 14 years, the fungus that causes FOV4 has impacted fields in California’s San Joaquin Valley.  This fungus is particularly difficult to control in cotton as the hyphae or fungus- overwintering structures reside in the woody vascular tissues, preventing the penetration of fungicides. These structures can survive in soils indefinitely. In the United States, FOV4 was first confirmed in California cotton fields in 2003, however, in 2017 it was also identified in far-west Texas and in 2019 in New Mexico.

Cultivars with relatively high levels of resistance to FOV4 were originally identified in commercial Pima cotton (Gossypium barbadense L.), ‘Phytogen 800’, and originated-pool germplasm, ‘Pima S-6’. Field evaluation of cotton cultivars in FOV4-infested fields have provided information to develop a number of generalizations:  (1) most Pima cultivars show more severe symptoms and suffer higher levels of stunting and plant mortality from FOV4 than with most Upland and Acala cottons; (2) some moderate to highly-resistant commercial Pima cultivars have been developed from several seed companies and private breeders; and (3) several USDA-ARS experimental Pima germplasm or breeding lines with moderate to high resistance to FOV4 have been identified, developed, and publicly released (SJ-FR01 to SJ-FR09). These germplasm lines have helped to increase the genetic base for FOV4 resistance in Pima Cotton. Typical FOV4 symptoms are shown in Figure 1. Disease symptoms of this pathogen have been observed to differ between Pima and Upland cotton.

Figure 1. Foliar and root symptoms of Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 (FOV4). A) Foliar symptoms for Pima (Gossypium barbadense L.) cotton and B) Foliar with no visual symptoms and root with vascular root staining symptoms for Upland (G. hirsutum L.) cotton. (All photos courtesy of M. Ulloa.)

From 2006-18, we have been evaluating Pima germplasm from the USDA ARS and international breeding collections, and Upland germplasm from the USDA ARS Cotton Germplasm Collection College Station, Texas or breeding lines from around 13 public (universities and USDA) cotton breeding programs across the Belt through the regional breeder testing network or RBTN sponsored by Cotton Inc. and have provided information about the level of FOV4 tolerance of these breeding lines and germplasm. In addition, since 2013, more than 4,000 entries and developed progeny have been evaluated in infested FOV4 fields and a portion (1/4) in the greenhouse using artificial FOV4 inoculation.

During the growing season, plant responses to fungus-inoculum pressure were assessed through evaluations of root and stem vascular staining levels, plant mortality, foliar wilt symptoms and measures of relative plant vigor. In Upland cotton, germplasm with good levels of tolerance have been identified, and new breeding lines are being developed by USDA-ARS and the University of California. After FOV4 artificial-greenhouse and natural-infested FOV4 evaluations of these accessions, less than 0.1% were selected to develop highly resistant FOV4 progeny. Two sources (NM12Y1004 – NM12Y1005 and SA-3208) of Asiatic breeding origin were identified with tolerance to FOV4 and used to introgress and increase resistance. Pedigree information from additional parental lines or breeding stocks used to develop progeny revealed their sources to be exotic and wild Upland germplasm – triple/multiple crosses, deriving these SA-obsolete cultivars named ‘Auburn M’, ‘DES 920’, ‘MARSPD202085’, ‘S.N.0503-1’, PD 2165, and ‘Stoneville 14’, among others.

In 2019, around 130 selected breeding lines were ginned, acid delinted, and planted at two infested field sites in California [Los Palos (Figure 2) and Tipton Co. (Figure 3)] to validate their resistance/tolerance against FOV4.

Figure 2. Infested Fusarium wilt race 4 (FOV4) field site around Dos Palos, CA. planted with selected breeding lines to validate their tolerance level before public releases. Photos showing Dr. Ulloa next to one of the FOV4 highly resistant Upland lines surrounded by empty research plots from a susceptible FOV4 variety-check.

These selected lines were also planted at the Tipton FOV4 infested site (Figure 3). In addition, evaluations were performed on more than 500 additional Pima and Upland cotton lines from progeny and breeding lines with different levels of FOV4 tolerance/resistance. Most of these lines were derived from multi-cross-combinations between and within Pima and Upland cultivars or germplasm lines with known FOV4 resistance to develop progeny and new populations to assess FOV4 resistance.

Figure 3. Infested Fusarium wilt race 4 (FOV4) field site around Tipton, CA. planted with selected breeding lines to validate their FOV4 resistance/tolerance level before public releases, with an additional 500 Pima and Upland entries. Photos showing evaluation site and roots with no vascular root staining, a typical diagnostic infection sign of FOV4.

In addition, a subset of these entries was also planted in the El Paso, TX area in FOV4 infested field (Figure 4).  Following are images from the FOV4 infested field site near El Paso, TX.  We planted lines with known levels of FOV4 tolerance, and resistant and susceptible FOV4 check-cultivars using a RCBD with three replications (Figures 1-3).

Continuing with the breeding efforts of this cooperative project next year, we anticipate additional visits to California by Dr. Ulloa to coordinate and support the selection, harvest, ginning of breeding lines with good to excellent FOV4 tolerance/resistance for the 2020 year’s season.

Figure 4. Infested Fusarium wilt race 4 (FOV4) field site around El Paso, TX area planted with selected breeding lines to validate their tolerance level before public releases.

 

Management of Key Cotton Arthropod Pests with Insecticides and Acaricides

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Objectives of Research

1.) Develop an expanded database on the current efficacy of labeled/recommended insecticide and acaricide products on key insect and mite pests of cotton in the San Joaquin Valley and document the influence of these products on beneficial arthropods with the objective of providing better guidelines on pesticide use.

2.) Evaluate the effectiveness of new candidate insecticide/acaricide products on key San Joaquin Valley cotton pests, the impact of these new compounds on populations of beneficial arthropods, and devise strategies for deploying these new products.

3.) Examine factors, including insecticide-related, environmental, and agronomic factors, which influence management of cotton arthropod pests with registered and experimental insecticides, emphasizing insects that threaten lint quality.

Introduction

We must maintain a multifaceted IPM approach to sustain an efficient and stable system of pest management in California cotton and to improve overall profitability. Insecticides remain a key component of effective management of arthropod pests in cotton. Furthermore, management of insect pests is a critical aspect of managing sticky cotton. California has a reputation for producing high-quality cotton, and successfully managing whiteflies and aphids and the resulting havoc they can create with lint quality is key to maintaining this reputation. Up-to-date data on insecticide efficacy are in constant demand by growers and PCAs, as are data on how given insecticides can fit within an IPM program. The results from this project will clearly be used nearly immediately.

Regulatory actions involving insecticides are ongoing and likely inevitable in California’s agricultural sector, which can lead to uncertainty and changes to what tools are available to control arthropod pests. In recent years, several insecticides, such as several organophosphates, Temik®, and endosulfan, have been lost due to marketing decisions (probably hastened by regulations). Use of several EC formulations in cotton have been limited due to VOC regulations in the SJV – dimethoate, abamectin, etc. Concerns about off-site movement (via water and air) have threatened registrations and use of chlorpyrifos and pyrethroid products (and several premixes that contain a pyrethoid). Belt® insecticide was removed from the market although it was promoted and thought to be a reduced-risk material for beet armyworm (and other species) control. Recently, numerous insecticides, especially neonicotinoid products, are being scrutinized due to the ongoing honeybee/pollinator concerns with proposed regulations potentially having significant impacts. There are a variety of neonicotinoid products used by the industry that could be influenced by future regulations. Registrations of “new” insecticide products such as Transform® are threatened and have been delayed (on again and off again) as well due to the pollinator issue. Transform will not be available for the upcoming season in California. During the last growing season, chlorpyrifos was slated from removal from the marketplace. This has clearly left a gap in tools for late-season management of aphids and whiteflies. The overall effect of the losses or lack of registrations is very problematic and makes pest management more challenging.

Products are also being removed from the “toolbox” because of the build-up of insecticide resistance in pests, which are constantly evolving. Organophosphates are typically not useful for lygus management, and pyrethroid insecticides may be useful for lygus for one application per season due to resistance. Spider mite control options have been available and numerous, but there appears to be some slippage in performance in recent years in other field crops. Given the ability of spider mites to develop resistance in multiple regions and cropping systems, this is not a surprise. Presently, whitefly control options are still in place although during some “application windows” there are now a shortage of options. Mid-season aphid management is still viable as long as the neonicotinoid products are available, but late-season there is a critical void with the loss of chlorpyrifos. Maintaining effective aphid and whitefly IPM programs is essential to addressing the threat of sticky cotton to the industry.

The challenges from development of insecticide resistance and regulatory actions are best addressed with well-planned research and interaction/collaboration with all concerned industry representatives. Fortunately, new materials are developed to facilitate IPM programs. These new products must be evaluated under California conditions. This development of new products appears to have slowed somewhat recently with the consolidation of the agrichemical industry and changes in ownership that have disrupted and delayed research plans. In the interim, available experimental products will be evaluated, registered products will be researched and evaluated for efficacy, and other IPM tactics will be studied and developed. This research has allowed and will continue to allow a thorough evaluation of the applicability of experimental materials for the California cotton system before they appear on the market. By examining the complete “big picture” of California cotton IPM, this project helps to determine the applicability and fit of these products. The pests of interest in this project include cotton aphids, spider mites, thrips, whiteflies, lepidopteran larvae, and lygus bugs. Emerging and invasive pests will also be addressed, as needed and relevant. The integration of insecticides and acaricides with other management approaches (biological control, etc.) will be emphasized.

Summary: Insecticide/Acaricide Efficacy

The research season in 2019 progressed well, despite some weather challenges early in the season that made research challenging when trying to get cotton planted, although this was something that commercial growers faced as well. Late-season rains prevented us from getting out cotton planted “on time”, especially at the Shafter Research Station. Planting at West Side Rec was less affected. Whitefly populations were low but were relatively consistent over the course of the trial. Our aphid populations steadily declined after the first application, leading to very low populations after the second application. In the past year, we continued conducting the research trials at the locations (West Side REC and Shafter Research Station) where they have been conducted for the past several years. Field and laboratory work was split between both locations, with the lygus and mite trials conducted at West Side REC and the aphid/whitefly study at Shafter Research Station.

Lygus

Objective: To evaluate Lygus bug management tactics, including newly registered insecticides, combinations of materials and varied timings, and industry standard (registered) insecticides, as well as the effect of treatments beneficial insects and secondary pest populations.

  • Application Dates:2 applications, July 9 and July 14
  • Study Location:West Side Research and Extension Center, Five Points, CA; Fresno County
  • Application Equipment: pull-behind tractor sprayer, CO2 propellant, Spraying Systems TX-VS10 nozzles (5 nozzles per row)
  • Application Parameters:20 GPA, 40 PSI, 3.5 MPH
  • Plot Size: 10 rows x 68′ feet, 4 replications
  • Plot Design: randomized complete block
  • Plot Condition:irrigated Acala cotton (PhytoGen 764 WideStrike RF) planted on 38 in rows
  • Insect Sampling: Lygus: Adults and nymphs per 50 sweeps per plot at various days after treatment (DAT). Secondary pests: 10 leaves/plot (5th main stem node leaf from top) were collected and aphids and spider mites counted in the lab 10 DAT1). Natural enemies were assessed once at 7 DAT1 using the same sweep net sampling used for lygus sampling. Later sampling using the same technique was not possible because of the growth habit of the cotton.
  • Yield: We picked the middle two rows with a commercial picker. We weighed seed cotton and calculated yield per acre, accounting for exact feet of row that were harvested.

For all results, see tables and figures for full analysis details and means.

Lygus nymphs: Pre-treatment populations of nymphs were 7.75 per 50 sweeps. At 2 DAT1, only Warrior and Vydate provided any level of control (70 and 76 percent). At 6 DAT1 Vydate provided 80 percent control, while both Transform treatments, Carbine, and Diamond+Carbine all provided 70-80 percent control. Differences were more pronounced 10 DAT1, with the same treatments (other than Transform-L) providing 80-90 percent control. Only Vydate had high levels of control 13 DAT1.

At 2 DAT2, a number of treatments had 80-90 percent control. At 6DAT2, Diamond+Carbine, Orthene, Transform (L and H) and Vydate all had 90-100 percent control. Diamond alone provided 80 percent. At 10 DAT2, only Orthene and Vydate had above 80 percent (83) control. The pattern was similar 13 DAT2 and at 21 DAT2, Diamond provided 90 percent control, Orthene 97 percent, and all remaining 51 percent and lower.

Lygus adults: At the first sampling (2 DAT1), Transform-L and Vydate provided a degree of control (70 and 80 percent). At 6 DAT2, only Transform-L provided any degree of control (75 percent). At 10 DAT2, many of the materials provided some degree of control in the 40-50 percent range, and Carbine, Diamond, Transform-H, and Warrior all provided 64 to 68 percent control. At 13 DAT1, Transform-H provided the best level of control (70 percent), with some control (54 and 59 percent) still offered by Carbine and Diamond+Carbine. 2 DAT2 Orthene provided 86 percent control. At 6 DAT2, both Transform rates provide 88 percent control. At 10 DAT2, a number of materials provide 45-60 percent control.

Natural enemies: We have not yet attempted to analyze the natural enemy data using multivariate statistics, so we present analysis of summed counts of natural enemies. At 2 DAT1, there were significant differences among treatments based on the overall analysis, but none in pairwise comparisons (numerically lowest in Belay, highest in Diamond+Carbine). At 10 DAT1, natural enemies were least abundant in the Belay and Sivanto-High treatments and highest in the Brigade and Untreated. At 13 DAT1, natural enemy populations had increased across most treatments, with the untreated having the most, followed by Brigade and Baythroid. Orthene, Assail, and Belay all still had low natural enemy populations.

Secondary pests: Aphid and mite populations were low during this trial and none of the treatments led to very high levels. Populations of aphids did differ significantly between treatments (F14,42 = 2.67, P = 0.007). At 10 DAT1 when they were assessed, aphid populations were highest in the Brigade plots (~1 per leaf), followed by Baythroid, Vydate, and then the Untreated. The only significant differences were between Baythroid and Assail, the latter which had the fewest. Mites were extremely low overall, with no significant differences among treatments (F14,42 = 0.57, P = 0.87). After the second application (6 DAT2), the untreated had the most natural enemies, followed by Vydate. Orthene, Transform-ow, and Assail all had few natural enemies. These patterns generally persisted through the end of the study. At 13 DAT2, the untreated had by far the most natural enemies, followed by Warrior and the Admire/Carbine treatment.

Yield: Yield was highest in the Vydate treatment with 3,254 pounds seed cotton per acre. This was followed by Diamond+Carbine with 3,152, Carbine with 3,093, Transform-H with 3,090. Brigade had the lowest yield at 2,015, followed by Baythroid at 2,148.

Bioassays

Similar to previous years, we have continued to monitor insecticide resistance in lygus populations for key insecticides. This includes older materials like Vydate and Capture, and newer materials that have been increasingly relied upon for lygus management, Capture and Carbine. For Vydate and Capture, these assays consisted of exposure of insects to the material in insecticide coated plastic bags. The Carbine method relies on dipped green beans, while Transform uses floral foam soaked with a solution containing the insecticide.

The data are still being processed for these assays, but we can report on the number of assays that were completed. To mirror prior years, we conducted both early and late season assays. For the early season assays, we had four locations, with insects collected between May 31 and June 13. For the late season assays, we again attempted assays at four locations, but lygus were no abundant enough for the full complement of assays. At two of the locations, we could run all four materials. At one site, we only had enough for two materials, so we focused on Carbine and Transform. At the other, site, we were unable to collect enough lygus for assays.

Aphids and Whiteflies
Objective: To compare the efficacy of selected registered insecticides and
experimental materials against cotton aphids and whiteflies during the midand
late-season period in Pima cotton.

  • Application Dates: 28 August and 11 September – Insecticides – 21 treatments
  • Study Location: Shafter Research Station near Shafter, CA; Kern County
  • Application Equipment: High-clearance trailer spryer pulled with a tractor, CO2 propellant, Spraying Systems TX-VS6 nozzles (5 nozzles per row)
  • Application Parameters: 30 GPA, 40 PSI, 3 MPH
  • Plot Size: 5 rows x ~55′ feet, 4 replications, 38 in. rows
  • Plot Design: Randomized Complete Block
  • Plot Condition: irrigated Pima cotton (‘Phytogen 841 RF’)
  • Insect Sampling: All insect data were collected from 10-leaf samples (5th main stem node leaf down from terminal) per plot. Cotton aphids (Aphis gossypii) and whitefly nymphs Bemisia tabaci Biotype B, (formerly B. argentifolii): visually counted on leaves using a dissecting microscope. Data on WF nymphs were collected per entire leaf as well as per “quarter-sized” disk (between the main leaf veins; not reported here). This is the area that the treatment threshold is based upon. Whitefly adults: leaves were carefully examined and turned over in the field and adults counted.
  • Yield: We picked the middle two rows with a commercial picker. We weighed seed cotton and calculated yield per acre, accounting for exact feet of row that were harvested. We did not harvest any plots in the first block because vigor was extremely poor, and this would have not been useful yield data. Yield was very low overall.

For all results, see tables and figures for full analysis details and means.

Aphids: On the day of application, aphids averaged 116/leaf. At 2 DAT, The low rate of Transform was most effective (91 percent control), followed by Lorsban+Dibrom and the high rate of transform. At 7 DAT1, both Transform rates performed well, with 98 and 97 percent control of the high and low rates respectively. Lorsban and Sefina-Low both provided 89 to 90-percent control. At 13 DAT1, many of the treatments provided excellent levels of control (many over 90 percent 80 percent). This included all of the newer materials (Sefina, Sivanto, Transform, PQZ, Carbine; all rates) as well as Assail, Lorsban+Dibrom, and Knack. Meanwhile, by this point, Vydate, Lorsban, and Courier had increased numbers of aphids relative to the control (numerically, not significantly different). Immediately after the 2nd application (2 DAT2), the Lorsban+Dibrom had the fewest aphids. At 7 DAT2, aphid populations in the untreated had started to crash and were only 9 per leaf. The following sampling dates were somewhat less useful because of the low untreated numbers, with one exception being that these patterns showed which treatments otherwise maintained aphid populations (see Vydate in particular).

Whitefly nymphs: On the day of applications, whitefly nymph populations were low at 0.9/leaf. At 2 DAT1, only Knack provided >50 percent control at 56 percent. At 7 DAT1, a number of the other treatments began to provide some level of control, with Sivanto-Low provided the best at 83 percent, followed by Assail+Bifenture at 76 percent. A number of other treatments provided 60 to 70 percent control. At 13 DAT1, the untreated had fairly low numbers, so percent control was poor across treatments (other than Courier). At 2 DAT2, Sivanto-High provided the best control (82 percent), followed by Assail and Sefina-High.  Lorsban provided the least level of control at this time point. At 14 DAT2, Cormoran provided the most control, followed by Assail, Carbine (although this appears to aberrant), Sefina-Low and Assail+Bifenture. Across dates, Vydate and Admire Pro performed poorly, several times having more nymphs than the untreated.

Whitefly adults: Whitefly adult counts typically ranged between 1 and 2 per leaf in the untreated over the course of the study. There were only significant differences among treatments for several of the assessment dates (7 DAT1, 2 DAT2, and 21 DAT-2 – at α = 0.10). Posthoc comparisons did not indicate any significant differences except on 7 DAT1 when the untreated was significantly different from over half of the treatments.  No individual treatment appeared to stand out when viewed across dates.

Secondary pests: Spider mites were evaluated as a secondary pest that could be flared by treatments for aphids/whiteflies. Mite counts were very low over the course of the study. We therefore analyzed counts summed by plot across the entire study. There were not significant differences among treatments for these counts (F19,57 = 1.17, P = 0.31).

Yield: Measuring yield was not one of the key aspects of this study because we are focused on managing aphids and whiteflies because of the way they threaten quality of lint (via sticky cotton) rather than quantity of lint. We did not detect significant differences in yield quantity (F19,38 = 0.41, P = 0.97).

 

Evaluation Of Effectiveness Of Varying Rates and Application Methods Using Cotton Clean ™ Technology

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The purpose of this study was to evaluate the effectiveness of the Cotton Clean™ product when applied with various methods and at various rates. The results confirmed what our preliminary research indicated.  Generally, the study indicates that Cotton Clean™ shows significant benefit in reducing stickiness on cotton that is at a level of moderate to heavy levels of stickiness.  Where stickiness is light or nearly absent, Cotton Clean™ does not have any significant effect on reducing stickiness.  From these findings, one may conclude that where stickiness levels are very low to begin with, there may be insufficient food source (deposited insect sugar) for enzymatic sugar reduction through the use of Cotton Clean™.  Therefore, the stickiness of cotton with low levels of stickiness do not change with any degree of significance.  This is true statistically, as well as economically, as extremely low levels of stickiness generally cause no detectible difference in textile processing or quality of output.

Also, we determined cotton ginned at commercial gins where Cotton Clean™ was applied at time of ginning was significantly less sticky than cotton from the same farm that was ginned at a facility where no Cotton Clean™ was applied at time of ginning.

Introduction

Aphid and whitefly pests are well distributed throughout the San Joaquin Valley and in many other irrigated upland and pima cotton producing regions, particularly where arid conditions exist.  It is well documented that several species of these pests can deposit objectionable levels of sugars through their excreta which can make processing seed cotton (in ginning) and cotton lint (in carding and spinning) very difficult and time consuming if sugar deposits reach moderate to high levels.  Growers have used many methods and approaches in keeping sticky cotton producing pests to a manageable level, but there are instances where their efforts are ineffective in the avoidance of problematic stickiness levels.  When this occurs, gins and spinning mills have severe problems in handling cottons in this condition.

It is believed that if the deposited insect sugar was converted into a substance with little or no viscous properties at ginning or spinning operational temperatures, without harming the cotton fiber onto which it was deposited, then ginning and spinning processes would be improved and lint quality preserved.

In 2016 San Joaquin Valley Quality Cotton Growers Association began work to identify ways to combat the ill effects of sticky cotton beyond control of the insect source itself.  A biological agent was introduced on problematic seed cotton that had been plugging up stands at a roller ginning facility.  It was sprayed on seed cotton at the module feeder in an aqueous solution.  Cotton so treated did not exhibit problems with plug ups at the stands.  After that initial trial further study was conducted and it was determined that a more precise formulation could be developed to address Trehalulose and Melizitose even more effectively.  In 2017 Cotton Clean™ was developed in conjunction with the manufacturer and their principal dealer.  Cotton Clean was provided to 12 different growers for use in applying at harvest and 1 gin used the material applied at the module feeder.

Lint samples were collected from bales treated with Cotton Clean™ and those bales not treated with Cotton Clean™.  Those lint samples were tested using Thermodetector, Mini card, and Mesdan ConTest stickiness testing methods.  Most test data sets indicated reduced stickiness on samples treated with Cotton Clean™, while a few sets were more inconclusive.  Whether or not influential factors not recognized had impacted the results was unclear.  Some of those factors are the subject of this project proposal, including rates of application and methods of application.  What is known is that ginning personnel report anecdotally that there were no problems with gin stand plugging on cotton treated with Cotton Clean™, whereas, untreated cotton from the same field continued to exhibit plugging problems.

A better understanding of the proper rate of use of Cotton Clean™ and most effective method for application will help growers and ginners make the most of this contamination mitigation tool.

Methods and Materials

Plan of work:

  1. Identify sources of seed cotton to be included in the study. Growers and ginners in the San Joaquin Valley were contacted to participate as volunteers in the study.  In addition to commercial locations, research plots were used as a source of seed cotton.
    1. Cotton was collected from and ginned at:
      1. The Shafter Research Station – Farmers Co-Op Gin
      2. Armstead Ranch – Westhaven Cotton Gin
  • Woolf Farming – Huron Gin
  1. Errotabere Ranches – West Island Gin
  2. J. Polder Co. – West Island Gin
  1. Seed cotton samples (both Upland and Pima) were collected from the fields prior to harvest, identified and segregated so as to preserve identity for both test and control sample sets.
  2. Varying rates (25 to 90 bales per pound) of Cotton Clean™ were applied through picker moistener systems at time of harvest as well as varying rates applied at time of ginning.
  3. Lint samples were collected at the gins and transported to secure storage until fiber testing is conducted.
  4. Lint samples were tested for stickiness using Mesdan Contest instrumentation and recorded.
  5. Randomly selected lint samples were procured for testing at USDA ARS New Orleans for additional confirmation of results.
  6. Results were analyzed and reported.

Results

The results from this experiment generally support our hypothesis that Cotton Clean™ reduces the stickiness grades determined by the Mesdan Contest Cotton Quality Testing machine. The overall results from all stickiness levels of cotton in the experiment were slightly in favor of the sample group that had Cotton Clean™ applied. The average stickiness level of the fields without Cotton Clean™ applied during ginning was 102. The average stickiness level of the fields with Cotton Clean™ applied during ginning was 97. A difference of 5 points on the measurement system of the Mesdan Contest machine is insignificant. While it is noted that some field stickiness grade averages were higher with Cotton Clean™ applied than without, those only occurred in samples with low (<100 stickiness grade).

However, when fields with lower levels of stickiness (<100 stickiness grade) were removed from the averaging process, the result is dramatically different.  When only those fields with medium to heavy stickiness were considered, Cotton Clean™ applied at ginning reduced measured stickiness significantly, from 147 down to 97, a reduction of 34%.

In order to confirm validity of results measured by the Contest instrument, a random selection of samples from each field was sent to USDA-ARS in New Orleans for blind testing using the standard minicard stickiness test. The minicard test uses a different method of measurement to gauge stickiness levels than the Contest instrument, but has shown relatively good correlation of stickiness between the two measurement technologies.  That being said, due to the variability of stickiness among samples within a field the results may also illustrate some degree of variation. The measurements reported by USDA are None, Light, Medium, Heavy, and Very Heavy. In order to make relevant those designations to Contest values, we assigned values we believe to be consistent with similar levels of stickiness as measured by the Contest instrument.  None = 10, Light = 75, Medium = 125, Heavy = 200 and Very Heavy = 375.  We assigned a numeric value of 10 for None in order to present it graphically, but for all intents and purposes Contest levels of 0 and 10 are effectively indistinguishable.

The results by field for the samples without Cotton Clean™ applied during ginning were 4 fields were None, 10 fields were Light, and 1 field was Heavy. The results by field for the samples with Cotton Clean™ applied during ginning were 1 field was None and 14 fields were Light.  None of the samples treated with Cotton Clean™ measured above a Light designation. It should be noted that the minicard designations are subjective evaluations of the technician conducting the test.  The difference between Light and None in some instances can be almost indistinguishable.  Medium, Heavy, and Very Heavy designations tend to be much more pronounced.  So as indicated by the Chart 3, one can see that only where stickiness is more than Light, (in this case Heavy in field 18), can we see significant improvement with Cotton Clean™.  This is consistent with the results developed independently with the Contest instrument and so therefore, we conclude the independent results confirm one another.

CHART 3

Since only one commercial gin applied Cotton Clean™ uniformly on cotton of a large scale (>10,000 bales) we were only able to evaluate stickiness grades of cotton ginned commercially at one rate (80 bales ginned per pound of Cotton Clean™ applied).  At this rate stickiness grades averaged 32 versus an average of 58 for those bales ginned from the same farm but ginned at a ginning facility that did not use Cotton Clean™.  Even though all the stickiness levels in this instance were not considered heavily sticky, this large scale test from a farm producing > 10,000 bales indicated that stickiness grades were significantly reduced when Cotton Clean™ was applied at the time of ginning.

Conclusion

Cotton Clean™ shows significant benefit in reducing measured stickiness in instances where stickiness levels in the field are expected to be medium or moderate levels and above. Even when cotton stickiness levels are below moderate, proper application of Cotton Clean™ at manufacturers suggested rates at time of ginning shows significant reduction in measured stickiness.

Acknowledgements

This study could not have been conducted without the assistance and cooperation of many individuals and organizations.  We wish to thank all who contributed something to this effort, especially the following:  Armstead Ranch, California Cotton Ginners and Growers Association, California State University, Bakersfield, Errotabere Ranches, J. Polder Co., Stone Land Co., USDA ARS New Orleans, Westhaven Cotton Co., and Woolf Farming Co.

 

 

Assessment of Fusarium in SJV Cotton: Field Evaluation Support, Identification and Commercial Variety Screening Evaluations

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This project covers two primary purposes: 1) Conduct germplasm screening trials of commercially-available cultivars plus evaluations of experimental cultivars seed companies submit to us for FOV resistance evaluations.  In these evaluations, all entries in all University of CA variety trials (Acala/Upland, Upland Advanced Strains, Pima, Pima experimental cultivars, National Standards trials) are included, plus experimental entries submitted by seed company breeders. 2) Support field efforts to collect samples and evaluate fields to determine and characterize the race of Fusarium (race 4 or others) in SJV cotton fields when growers, seed company reps or consultants contact us for assistance with plant evaluations and fusarium race identification.

Prior and Current Work

Resistance Screening Work – Commercially Released Cultivars and Company Experimentals. This work has been directed toward identification of relative levels of resistance/susceptibility to race 4 FOV, including both indices of severity of disease impacts and survival under moderate to severe FOV race 4 pressure, with focus on evaluations of newer experimental and commercially-available cultivars. The two objectives mentioned above are at least somewhat related, as we conduct field trials to evaluate germplasm resistance to FOV, and we need to identify and access fields and cooperative growers if field screening trials are to be conducted.

Field evaluations in the resistance screening program each of the years of the trials have included:

  1. Commercially-available germplasm of Pima varieties included in our variety trials
  2. Commercially available germplasm of CA Upland and any remaining Acala varieties included in our variety trials,
  3. Experimental germplasm from company commercial development and improvement programs, plus
  4. Entries from cotton breeders at a variety of locations, including those from the RBTN tests done nationwide, plus efforts will be made to solicit entries from private company breeders working with Pima or hybrids (we have some funding through Cotton Incorporated CORE that helps cover some of the costs for the other agronomic evaluations (yield, fiber quality) for the Regional Breeder entries from U.S. public breeders – but the costs of the FOV race 4 screening work are not provided by that funding)

Field Sample Evaluations Work

Some support has been utilized to facilitate travel to field sites and allow us to be in the fields to physically do the visual surveys and collect samples, and to provide county and UC support for repeated trips to screening sites/fields as well as to grower fields where the Principal Investigator for this study gets requests for field evaluations to assess presence of Fusarium race 4.  Efforts beginning in 2002 and continuing through current efforts have been in repeated field visits to grower field sites, collection and evaluation of stem and hypocotyl samples for evidence of vascular staining, and AgDia test evaluations when growers/consultants make the request for Fusarium race identification.

The varieties tested include all commercial and public breeder entries in our variety trial program plus company/breeder submitted experimental cultivars. This screening effort is separate from, and in addition to, the work covered in a separate breeding program effort supported through cotton industry funding for a project entitled  “FOV race 4 Germplasm Development” that in recent years has been jointly funded by CA Cotton Alliance and CA Cotton Growers Association Research Funds. That project is a cooperative project with Dr. Mauricio Ulloa of USDA-ARS in Lubbock, Texas.  The cooperative work with Dr. Ulloa is somewhat different from the screening efforts supported by this proposal in that this project is more focused on maintaining: (a) support for FOV race 4 resistance screening for commercial entry commercial and experimental entries, plus entries from public breeders; and (b) some funds to continue support for field race 4 evaluations requested from growers, consultants and seed companies for which we need to purchase AgDia test kits and cover related other expenses.

Field Sample Evaluations

Since 2013, we have been using the AgDia company race 4 FOV quick test on root and lower stem samples in these field evaluations.  For some FOV race identification pathology work for samples when we request additional evaluations over and above what can be done using the AgDia quick tests, we are working with Dr. Maggie Ellis at CSU Fresno to determine local capabilities for identification of other races of FOV if that becomes necessary and useful. The funds from this proposal/project help provide funds to purchase the FOV-4 AgDia kits, which cost approximately $35 for each sample run (just for the supplies, not other lab costs or staff time).

Summary Report of 2018-19 Activities

For 2019, sites for field evaluations and sampling were located in 4 cotton producing San Joaquin Valley counties  (Fresno, Merced, Kings, Tulare Counties), with the most new confirmed sites located in Merced County. There were 27 fields visited and evaluated visually for FOV4 evaluation, and sampling for Fusarium race 4 done in 19 fields, and confirmations of FOV4 in 16 of the fields visited. Unless we see significant increases in different variants of FOV (race 4, others) in cotton, we expect a downward trend in requests for field visits to continue in the next years.

The number of requests for field evaluations compares with sampling in earlier years: (1) 2018—48 fields evaluated, with 37 confirmed as race 4 FOV; (2) 2017—66 fields evaluated; (3) 2016—89 fields evaluated; (4) 2015—89 fields were visited for in-field evaluations, with AgDia tests run on 47, and 21 positive determinations in tests for race 4.  These numbers most likely do not represent the full number of additional fields that could have been identified as race 4 FOV, as some fields were visited where samples were not collected due to lack of grower desire or approval to collect samples needed to provide an assessment.

Results 2019 – Field Resistance Screening Evaluations

Field varietal screens were planted and completed at both field screening sites at the time of this report, both in fields confirmed to be infested with FOV race 4.  The field tests were done only in a part of the field where a prior cotton crop showed consistent, significant plant losses due to FOV race 4 (greater than 50 percent mortality in susceptible Pima entries). An initial plant population count was done within 2 weeks after planting in plots at both sites, followed by plant survival counts done a minimum of two times during an evaluation period of 7 to 8 weeks after emergence of cultivars being tested for resistance at the Tulare County site and a Dos Palos area (Merced County) site.

In addition to plant survival percentages, we evaluated plants for root vascular staining, foliar damage index rating, and plant size / height and node counts as a measure of vigor. At both sites, major hand weeding efforts were required to keep weeds under control in these sites due to restricted use of herbicides necessitated by working with conventional cotton varieties.

The commercial varieties and company and RBTN program breeder experimental materials evaluated in our Commercial Entry and Company/RBTN Experimentals screening trials for 2019 are shown in the following figures in this report.  Average root vascular stain values for the TULARE COUNTY SITE are the only 2019 date summaries available and ready to share at the time of preparation of this report. Data analyses on the rest of the data sets are underway and will be made available to seed companies, breeders and industry partners in the fall.

The following tables (Figures 1-4) show the average Root vascular stain index ratings for all of the Pima and Upland cotton entries in the commercial screening trial for FOV-4 resistance conducted at the Tulare County site in 2019.  As with prior years, check varieties are included in the screen: more susceptible varieties such as DP-340 and DP-744 Pima, and some more highly resistant commercial Pima varieties such as Phy 888RF, Phy 841 RF, DP 348 RF, DP 359 RF and others). Also included in this screen are all varieties entered in the following variety trials for 2019:  CA Uplands/Acala trial, CA Uplands Advanced Strains trial, National Standards Uplands trial, Pima variety trial, and RBTN (Regional Breeder Testing Network) entries.

Other than the previously mentioned Pima cultivars with higher levels of FOV-4 resistance, there are a limited number of entries in this commercial screen that appear worth a follow-up evaluation as potential higher FOV-4 resistance varieties, including:  Group figure 1: FM 2398, ST 4550, PX 8504 Pima; Group figure 2: DGX 19014, BX 2037, FM 162; Group figure 3: Phy-60, Phy 64 through Phy 67; Group figure 4: Ark 1112-59, TAM LBB 15905, CSX 8308.

When data is compiled for the second trial location (which includes most commercial entries other than the RBTN program entries), there will also be an opportunity to determine consistency of resistance screen results for two sites.

                            Figure 2
                          Figure 1
                        Figure 3

 

 

 

 

                       Figure 4

 

 

 

 

 

 

Data Summaries for 2018

As examples of the full data sets that are provided each year as a result of this project, the following tables of this report show the summary averages for the Tipton area site (Tulare County) in 2018. Similar data will be developed and posted when 2019 results are completed.  These 2018 tables and those from prior year summaries are shown on the UC cotton web site at http://cottoninfo.ucdavis.edu . This information includes foliar Fusarium ratings, root vascular stain ratings, plant height and node number as indicators of vigor.  In coming weeks as data is processed, we will add the plant survival percentage for each entry, but it is not included in this summary.  Data shown are determined from five plants evaluated in each of three field replications per entry.  The tests include all entries in University of CA cotton variety trials, additional commercial germplasm (company selected varieties plus experimentals they submitted) plus entries from the Regional Public Breeders testing program (including check varieties, organized nationally by Dr. Ted Wallace of Mississippi).

Information to focus on in reviewing the tables as best indicators of overall responses to FOV-4 infection are: (a) root vascular stain index; and (b) survival percent at 7 weeks, since they indicate relative severity of infection and impacts on plant mortality (this data, as mentioned above, is not summarized and available at this time).

“Check” varieties that are moderately to highly susceptible include: Phy-725RF, DP-340 (moderate), while a quite tolerant check variety would be Phy-802RF.  The scale for Foliar FOV index and root vascular stain index ratings is 0 to 5, with 0 being no symptoms, 5 being severe (usually reserved for dead, near-dead plants).  Keep in mind that ratings are done at 7+ weeks post emergence, so they are done on plants surviving at the time of the rating, which in the most severely impacted  entries  can be some of the few survivor plants, with most others dead. It is recommended that the combination of lower vascular stain ratings as a relative indicator of disease severity in tested plants must be considered in combination with survival of the plants in order to assess relative levels of resistance.

 

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