Headlands often reduce overall field yield. Are they worth fixing?

S. Sunoja, Dilip Kharela, Tulsi Kharela, Jason Choa, Karl J. Czymmeka,b, Quirine M. Ketteringsa
aNutrient Management Spear Program, bPRODAIRY, Department of Animal Science, Cornell University

Introduction

Headland areas are defined as the outer edges of the field where farm equipment turns during field operations such as planting, sidedressing and harvest and where hedgerows or other physical features separate a field from adjacent fields or other land uses. The equipment traffic areas can be compacted which can cause considerable yield loss. Beyond compaction, yield loss in headland areas may also reflect edge-feeding of pests such as birds, rodents and deer, and competition for light, water, and nutrient resources with adjacent tree lines. Better decisions about headland management including investments to improve production potential, planting of other crops, or reductions in fertility or other crop inputs can be made when we know how much yield is given up on headlands. In the past several years, we have provided farm specific yield reports to farmers who have shared their corn silage and grain yield data with us.  The reports included yield by field with and without headland areas included.  Here we put all that information together, across farms, to evaluate how much corn grain and silage yield may be lost on headland areas across fields.

Corn Grain and Silage Yield Data

Corn yield data from 2648 fields representing ~49000 acres across 63 farms in New York were analyzed. This included 1281 corn grain fields and 1367 corn silage fields across two years (2017 & 2018). The yield data from each field were processed and cleaned using Yield Editor (free software from USDA-ARS) following the cleaning protocol developed by the Nutrient Management Spear Program at Cornell University (Kharel et al., 2020). Headland removal was performed in Yield Editor by manually selecting the outer edge passes and deleting the data points (Figure 1).

maps of headlands
Figure 1. Headland areas were removed using Yield Editor. Shown are (a) cleaned yield data including headland areas, (b) selected headland areas represented in black, and (c) yield in non-headland areas (i.e. after removal of headlands). Adapted from Sunoj et al. (2020).

Average field size ranged from 18.5 acres per field for grain and 19.3 acres per field for silage. Corn grain yields averaged 181 ± 33 bu/acre versus 22 ± 5 tons/acre for corn silage. We calculated optimal production, defined as production that could be obtained if the headland portion had yielded the same as the non-headland portion. We calculated production gain as the percentage increase between the actual and optimal production.

Results

Across all fields, the yield in the headland area was lower than the yield of the non-headland area (Figure 2A) for 94% of the grain fields and 91% of the silage fields. For some fields, the headland area yielded more than the non-headland area, possibly due to: (1) within-field features (e.g., trees, wet spots, alley ways), (2) irregular shapes of fields with short passes (as typically seen in New York agriculture), and (3) multiple directions of harvest within a field. The average yields were 188 bu/acre (non-headland area) and 161 bu/acre (headland areas) for corn grain. For silage, the average yields were 22.6 tons/acre (non-headland area) and 18.9 tons/acre (headland areas). Thus, headland yields were 14% (grain) and 16% (silage) lower than yields in the non-headland areas.

yield in scatter plot and bar graph
Figure 2. (A) Field scale yield in headland versus non-headland for corn grain and silage; and (B) distribution of production gain across all fields. Each circular marker in (A) represents a field. Adapted from Sunoj et al. (2020).

If the headlands yielded as much as the non-headland area, the production gain ranged from -8 to 32% for corn grain, and from -17 to 42% for corn silage (Figure 2B). The negative production gains reflected field that yielded more on the headland areas than the non-headland areas (points below the 1:1 line in Figure 2A). Averaging across all fields, the production gain amounted to about 4% for both corn grain and silage fields. However, 1% of the grain and silage fields had a potential production gain that exceeded 20%; 25% of the grain fields and 28% of the silage fields had gains between 5 and 20%, while for the rest of the fields (74% and 71%) potential yield gains were less than 5%. Production gains exceeding 20% were obtained on fields with the total field area was less than 25 acres, and with corn grain yields less than 143 bu/acre and silage yield less than 24 tons/acre. Such yield differences can, depending on the farm, reflect a considerable loss of yield and opportunity to improve total returns per cropland area.

Conclusions and Implications

Yield in headland areas was, on average, 14% (grain) and 16% (silage) lower than in the non-headland areas of the field. Taking into account the total percentage of a field in headland, at the field and farm levels, the potential yield gain amounted to 4%. The overall averages conceal the wide range of production gain values obtained in New York fields, from negative up to 32% for corn grain and up to 42% for some corn silage fields. Based on production gain for specific fields, farmers can either choose to ‘repair’ the headland with management (e.g., vertical tillage or subsoiling) to increase overall productivity and return on investment in seed and crop inputs, reduce crop inputs without further loss of yield in headlands, or ‘retire’ the headland from main crop farming and opt for perennial hay crop and conservation uses.

Additional Resources

Full Citation

This article is summarized from our peer-reviewed publication: Sunoj, S., D. Kharel, T.P. Kharel, J. Cho, K.J. Czymmek, and Q.M. Ketterings (2020). Impact of headland area on whole field and farm corn silage and grain yield. Agronomy Journal (in press). https://doi.org/10.1002/agj2.20489.

Acknowledgements

This research was funded with grants from the Northern New York Agricultural Development Program (NNYADP), New York State Corn Growers Association (NYSCGA), and federal formula funds. We thank the farmers and crop consultants for sharing whole-farm corn silage and grain yield data. For questions about these results, contact Quirine M. Ketterings at 607-255-3061 or qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/.

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What’s Cropping Up? Volume 30, No. 3 – May/June 2020

The full version of What’s Cropping Up? Volume 30 No. 3 is available as a downloadable PDF on issuu. This issue includes links to COVID-19 resources on the back page. And as always, individual articles are available below:

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What’s Cropping Up? Volume 30 No. 2 – March/April 2020 Now Available!

New York State Soil Health Characterization | Part I: Soil Health and Texture

Joseph Amsili, Harold van Es, Bob Schindelbeck, and Kirsten Kurtz
Soil and Crop Sciences Section, Cornell University

Take-aways:

    • Soil biological indicators (organic matter, active carbon and respiration) were higher in finer textured soils than coarser textured soils, but organic matter quality was higher in coarser textured soils.
    • Soil texture exerted a strong control on a soil’s available water capacity.
    • Organic matter improvements are more likely to increase available water capacity in coarse textured soils compared to fine textured categories.

As progress is made in characterizing the biological and physical health of soils nationwide, soil health labs will be able to develop regionally specific scoring functions that correspond to inherent differences in soil properties and processes, which are shaped by the complex interplay of local climate, geology, biology, and time. The Cornell Soil Health Program has recognized this need and is developing scoring functions by region, soil type, and cropping system. Naturally, we have begun these efforts by focusing on New York State soils. In this first preview of the New York State Soil Health Characterization Report, we focus on the effects of soil texture on biological and physical soil health parameters. Stay tuned for the full technical report, titled “New York State Soil Health Characterization Report”, which will be published soon.

Methods
The Cornell Soil Health Laboratory analyzed 1,456 samples from across New York State between 2014-2018. Soil samples were analyzed for the standard Comprehensive Analysis of Soil Health (CASH) package, which included two physical indicators – wet aggregate stability (AgStab), and available water capacity (AWC); four biological indicators – soil organic matter (SOM), active carbon (ActC), autoclavable citrate extractable protein (Protein), and respiration (Resp); and seven chemical measurements. Results were summarized by four textural groups: coarse, loam, silt loam, and fine (Figure 1). Additionally, NY SH results were compared across five cropping systems which included annual grain, dairy system, process vegetables, mixed vegetables, and pasture (Part II will include a summary of the effects of cropping systems on soil health).

Soil texture chart
Figure 1. Soil health indicators were characterized by coarse (sand, loamy sand, sandy loam), loam (sandy clay loam, loam), silt loam (silt loam, silt), and fine (sandy clay, clay loam, silty clay loam, silty clay, clay) texture groups.

Results and Discussion
Soil texture is a dominant inherent soil property that exerts strong controls on a soil’s ability to function. Specifically, soil texture influences the amount of storable carbon and nutrients, a soil’s water holding capacity, erodibility, and drainage, and the habitat that soil provides to organisms. In order to evaluate the impacts of human land management (tillage, crop rotation, organic amendments) on the soil, it’s critical to understand the effects of the underlying inherent soil properties, like soil texture, on these soil health parameters.

Effects of soil texture on biological soil health indicators

Soil texture influences the quantity and quality of organic matter a soil can hold. Soils with higher concentrations of silt and clay (fine-textured) can store more organic matter than sandy (coarse-textured) soils due to the large amount of surface area available to bind with organic molecules. In the NYS database, SOM, ActC, and Resp were highest in fine textured soils, followed by silt loam, loam, and coarse textured soils. Fine textured soils in fact had 79%, 59%, and 56% higher SOM, Resp, and Act C than coarse textured soils, respectively (Table 1). Protein did not follow the pattern of an increasing concentration in finer texture groups. This is likely because it is more difficult to extract proteins from soils with high amounts of clay. Additionally, two ratios, Protein/SOM and ActC/SOM, exhibited lower values in finer textured soils (data not shown), which also suggests a lower ability to extract protein and active carbon in fine textured soils despite high OM levels. Alternatively, it suggests higher proportions of higher-quality organic carbon and nitrogen relative to the stable organic matter, i.e., relatively more “fresh” organic matter than stable mineral-bound organic matter in coarse textured soils.

Biological soil health indicators table

Effects of soil texture on physical soil health indicators

Soil texture exerts a dominant control on a soil’s available water capacity, which is the amount of water that a soil can hold and make available to plants. Coarse textured soils store the least amount of water because large pores between sand particles are unable to hold on to water against gravity. Specifically, as sand content increases, AWC goes down (r = -0.70). In contrast, clayey soils can store the most water, but some of that is tightly held in micropores and plants can’t access it. Therefore, soils with intermediate textures, like silt loams and to a slightly lesser extent loams, are known to store the most plant available water. We indeed found that silt content was positively correlated with AWC (r = 0.72), and silt loams and silty clay loam soils had the highest AWC. Silt loam soils had 273%, 139%, 47%, 28%, higher AWC than sand, loamy sand, sandy loam, and loam soil textures (Figure 2).

The strong textural control on AWC has implications for trying to improve a soil’s AWC with sustainable soil management strategies. The claim that, “one percent of organic matter in the top six inches of soil would hold approximately 27,000 gallons of water per acre” is often used to promote soil organic matter management. While this number is likely an over exaggeration of reality as evidenced by a recent study by Libohova, et al, 2018, who found that this number was closer to 2,850 gallons of available water stored per acre, it is true that increasing SOM is an important strategy to increase AWC. Furthermore, our research and other’s research show that SOM was more strongly related to AWC in coarse textured soils (r = 0.48) compared to loam (r = 0.14) or silt loam (r = 0.12) textured soils. This finding demonstrates that improved organic matter management can lead to increases in AWC in coarse textured soils to a much greater extent than for silt loams or finer soil textures.

Available water capacity chart
Figure 2. Bar chart of mean AWC for different soil texture classes. Error bars represent 1 SD of the mean. Unlike the other soil health indicators in the Cornell Soil Health Test, AWC was highly related to soil texture to the degree that more texture classes were required to understand the effect of soil texture on AWC.

Conclusions
Soil texture is a critical inherent soil property that exerts strong control on a soil’s ability to function, including its potential to store organic matter and retain plant available water. For biological indicators, SOM, ActC, and Resp values were higher in finer texture groups. Furthermore, AWC, an important physical indicator, was strongly controlled by texture. Our data suggest that coarse textured soils with low inherent AWC respond to increases in SOM to a much larger degree than silt loam soils. This NYS soil health database analysis demonstrates that soil texture is an essential variable to include in developing soil health targets at the policy or conservation planner level. Stay tuned for the full technical report titled, “New York State Soil Health Characterization Report” and for part II in the next WCU issue on the effects of cropping system on soil health indicators.

Acknowledgements
We acknowledge support from the New York State Environmental Protection Fund (administered through the Department of New York Agriculture and Markets).

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Statewide herbicide resistance screening to start in 2020: Help us to help you!

Lynn M Sosnoskie, Weed Ecology and Management for Specialty Crops
School of Integrative Plant Science – Horticulture Section

Weeds compete with crops for light, water, and nutrients, which can result in yield reductions. Weeds can also interfere with crop production by serving as alternate hosts for pests and pathogens, providing habitat for rodents, and impeding harvest operations. Consequently, growers employ a variety of control strategies, including the application of herbicides, to manage unwanted vegetation. Although herbicides can be extremely effective at controlling undesirable plants, failures can and do occur. Weeds may escape chemical treatments for many reasons including the evolution of herbicide resistance.

Worldwide, there are 512 confirmed cases (species x site of action) of herbicide resistance. With respect to the United States, 165 unique instances of resistance have been documented. In New York, there are only four formally reported occurrences; these include common lambsquarters (Chenopodium album), smooth pigweed (Amaranthus hybridus), common ragweed (Ambrosia artemisiifolia) and common groundsel (Senecio vulgaris). All were described as being insensitive to the photosystem II inhibitors (e.g. atrazine and simazine).

Chart showing herbicide resistance over time in the world
Current status of herbicide resistance, globally, over time according to the International Survey of Herbicide Resistant Weeds (weedscience.org)

This, however, does not reflect the current on-the-ground situation in the state; work done by Drs. Julie Kikkert (CCE) and Robin Bellinder (Cornell) indicates resistance to linuron in some populations of Powell amaranth (Amaranthus powelli). Recent studies by Drs. Bryan Brown (NYS IPM) and Antonio DiTommaso (Cornell) suggest that horseweed (Conyza canadensis) and waterhemp (Amaranthus tuberculatus) populations may be resistant to one or more herbicide active ingredients. Pennsylvania has nine reported cases of herbicide resistance including glyphosate resistance in Palmer amaranth (Amaranthus palmeri), which was recently identified here in NY. While it is tempting to believe that herbicide resistance is a hallmark of agronomic cropping systems, resistance can and has developed in orchards, vineyards, vegetable crops, pastures, and along roadsides.

Beginning in 2020, we will undertake a screening effort to describe the distribution of herbicide resistance in the state. This coming summer and fall, growers, crop consultants and allied industry personnel who suspect they have herbicide resistance are encouraged to contact Dr. Lynn Sosnoskie (lms438@cornell.edu, 315-787-2231) to arrange for weed seed collection. Indicators of possible herbicide resistance include:

    • Dead weeds intermixed with live plants of the same species.
    • A weed patch that occurs in the same place and continues to expand, yearly.
    • A field where many weed species are controlled but a previously susceptible species is not.
    • Reduced weed control that cannot be explained by skips, nozzle clogs, weather events, herbicide rate or adjuvant selection, and calibration or application issues.

Growers can take several actions to stop the spread of herbicide resistant weeds and to prevent the development of new ones. First and foremost is scouting fields following herbicide applications and keeping careful records of herbicide performance to quickly identify weed control failure. Pesticide applicators should ensure that their equipment is properly calibrated and that they are applying effective herbicides at appropriate rates to manage the target species. Whenever possible, diversify herbicides to reduce chemical selection pressures that result from the repeated use of a single herbicide or site of action. If possible, incorporate physical and cultural weed control practices into a vegetation management plan. Be sure to control unwanted plants when they are small and never allow escapes to set seed. Clean equipment to prevent seeds of herbicide-resistant weed species from moving between infested and non-infested sites and harvest areas with suspected resistant populations, last.

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Controlling Herbicide Resistant Weeds in Soybeans: 2019 Trials

Project Leaders: Bryan Brown, NYS IPM Program; Venancio Fernandez, Bayer Crop Sciences; Mike Hunter, Cornell Cooperative Extension; Jeff Miller, Oneida County Cooperative Extension; Mike Stanyard, Cornell Cooperative Extension

Collaborators: Dan Conable, Preferred Quality Grain LLC; Jaime Cummings, NYS IPM Program; Antonio DiTommaso, Cornell University; Quentin Good, Quentin Good Farms; Clinton van Hatten, Flowing Spring Farm; Kathleen Howard, Cornell University; Julie Kikkert, Cornell Cooperative Extension; Chuck Kyle, Preferred Quality Grain LLC; Grace Marshall, NYS IPM Program; Scott Morris, Cornell University; Ali Nafchi, Cornell Cooperative Extension; Jodi Putman, Cornell Cooperative Extension; Joshua Putman, Cornell Cooperative Extension; Emily Reiss, Kreher Family Farms; Matthew Ryan, Cornell University; Lynn Sosnoskie, Cornell University; Ken Wise, NYS IPM Program

Summary:
Herbicide resistant weeds have become a major problem for New York soybean farmers. This project aimed to regain control of these weeds through a mix of chemical, physical, and electrical tactics. From our replicated field trials attempting to control waterhemp in soybeans, the programs that included herbicides from WSSA groups 4, 14, or 15 were most effective, and our only treatment that provided 100% control included all three of those groups. Row cultivation performed well between-rows but missed some in-row weeds. Soybean yields generally reflected the effectiveness of each weed control treatment, with untreated plots incurring a 56% yield loss. Unfortunately, the most effective two-pass treatments were also the most expensive. In a separate demonstration, our informal evaluation of an electric discharge system was successful, with most of the herbicide resistant horseweed (marestail) exhibiting complete necrosis two weeks after application.

Background and justification:
In the past few years, herbicide resistant weeds have become a large problem for New York soybean farmers (Figure 1). Horseweed that is likely resistant to glyphosate (WSSA 9) and ALS inhibitor (WSSA 2) herbicides has spread through much of the state. Herbicide resistant waterhemp, which was initially found in a few isolated cases where farms had purchased contaminated inputs or equipment from other states, has now been observed in 12 counties. Waterhemp is more competitive than horseweed and based on our initial greenhouse spray chamber trials, it is likely resistant to glyphosate, ALS inhibitors, and photosystem II inhibitors (WSSA 5). In Seneca County NY, waterhemp was reported to have caused 50% yield loss in a field where the farmer had attempted to control it with several different herbicide applications.

Control of weeds that have exhibited herbicide resistance in other states has been improved by adding more herbicide sites of action, or WSSA groups, to the spray mixes – especially if more than one effective herbicide group is used – such as synthetic auxins (WSSA 4), PPO Inhibitors (WSSA 14), or long chain fatty acid inhibitors (WSSA 15). There has also been an increased emphasis on residual herbicide applications to decrease the burden on the post-emergence applications. Furthermore, due to the extended emergence period of waterhemp, residual chemistries are recommended additions to post-emergence applications.

Beyond the diversification of herbicides, non-chemical tactics are also necessary. Horseweed and waterhemp emerge from very small seeds and are susceptible to physical control through tillage/cultivation or suppression by cover crop residue. Due to the short longevity of both species’ seeds in soil, weed seedbank manipulation, sanitation, and practices that limit seed dispersal are also effective. In response to herbicide resistant weeds, one tactic that has been gaining in popularity in the last few years is the use of electrical discharge systems, which involve a front-mounted rod charged by a PTO-powered generator that is driven over the crop to electrocute weeds that escaped earlier controls.

In an attempt to regain control of these herbicide-resistant weeds in New York, we evaluated several strategies that integrated chemical, physical, and electrical tactics.

Objectives:
Objective 1. Evaluate the effectiveness of several different programs for controlling waterhemp in soybeans.

Objective 2. Evaluate the potential for an electrical discharge system to control weeds that survived prior chemical control efforts in soybeans.

Weeds in soybean field
Figure 1. Waterhemp competing with soybeans at a farm in Seneca County, NY.

Procedures:
Objective 1.

Two trial sites were established. Site A was in Seneca County, NY on a field of Odessa silt loam soil where waterhemp had survived various herbicide applications and produced seed in 2018. In 2019, the ground was prepared for planting with a field cultivator on May 22, and planted with soybeans (Channel 2119R2X, maturity group 2.1) on May 24. Pre-emergence applications were made on May 27. Post-emergence treatments were applied on July 8. All treatments are listed in Table 1. For fertilizer, muriate of potash (0-0-60, 125 lbs K2O/A) was applied prior to tillage and urea nitrogen (46-0-0, 100 lbs N/A) was broadcast on July 12.

Table of herbicides for use in soybeansSite B was in Oneida County, NY on a field of Conesus silt loam soil where a large patch of waterhemp had escaped herbicide applications and was hand removed the previous year. In 2019, soybeans (Asgrow 19×8, maturity group 1.9) were planted no-till on May 22 immediately followed by pre-emergence applications. Post-emergence treatments were applied July 5. All treatments listed in Table 1 except for treatments 4 and 8 were implemented at Site B. For fertility, muriate of potash (0-0-60, 120 lbs K2O/A) was applied prior to planting and starter fertilizer added 20 lbs N/A, 60 lbs P2O5/A, and 20 lbs K2O/A.

Plots were 25’ long and 10’ wide. Each treatment was replicated four times per site in a randomized complete block design. Spraying was conducted using a backpack CO2 sprayer with a 10’ boom. Spray volume was 20 gal/A applied at 40 psi. Row cultivation was achieved using a Double Wheel Hoe (Hoss Tools) with two staggered 6” sweeps (12” effective width). Two passes were made per row so that 24” of the 30” rows were cultivated.

Weed control was assessed in mid-August by collecting all aboveground weed biomass within a 2 ft2 quadrat. The quadrat was used four times per plot, placed randomly in the two middle rows of each plot. Weeds were placed in paper bags and dried at 113 degrees F for 7 days, then weighed. Control was calculated by subtracting the biomass of each treated plot from biomass of the untreated plots, dividing by the biomass of the untreated plots, and multiplying by 100. All waterhemp was manually removed immediately after the weed control assessments in order to prevent it from producing seeds.

Soybean yield was measured in mid-October by hand harvesting the pods from 10-row-feet of a middle row of each plot. Beans were separated from pods and collected using an Almaco thresher, then weighed. Yield loss in the treatments with single herbicide sites of action was determined by comparison to the more extensive treatments (Treatments 6-13). Yield loss of Treatment 11 was determined by comparison to the other extensive treatments. To provide an economic basis for comparison of each treatment, costs were estimated based on personal communications with several local custom applicators.

Objective 2.

In 2019, a 20-foot-wide electrical discharge system (“Weed Zapper ANNIHILATOR 8R30,” Old School Manufacturing LLC) was used in Cato, NY on August 1 in a soybean (R1) field with several different weed species that had survived an earlier herbicide application and were protruding up to 2’ above the crop canopy. The tractor was operated at 3 mph with 1000 rpm PTO speed, allowing the electrical discharge system to generate about 500 volts and up to 200 amps of alternating current electricity. Weed mortality was not evident on the day of implementation, therefore we returned on August 13 to informally assess control.

Results and discussion:
Weed control was greatest for the two-pass treatments (Table 2) and for the treatments that included more than one herbicide from WSSA groups other than 2, 5, and 9. One exception was that the addition of Warrant to the tank mix of Roundup and XtendiMax may have caused a slight antagonistic effect on waterhemp control.

Site A did not have complete soybean canopy closure, which likely reduced the effectiveness of most treatments. Additionally, much of the waterhemp present in the post-emergence applications was likely larger than the suggested maximum height of 4”.

Although waterhemp was abundant at Site B in 2018, hand removal efforts prevented most of the weed seed production and very little waterhemp emerged for the trial in 2019. Therefore, waterhemp control is not shown for Site B. Conversely, few weeds other than waterhemp were present at Site A.

Table of waterhemp effectiveness by treatmentSoybean yield at Site A generally reflected effectiveness of waterhemp control. Yield losses would likely have been greater if the waterhemp had not been removed in mid-August. We found yield losses in Treatments 1, 2, 3, and 5 of 56%, 26%, 34%, and 20% respectively. Yields at Site B were less effected, reflecting less weed competition. Crop injury was visible from Cobra, with yield losses of 12% and 17% at Site A and Site B, respectively. Yield loss would likely have been greater in most treatments if waterhemp had not been manually removed in mid-August to prevent seed production.

 The total cost for the materials and application of the more extensive treatments was generally more expensive (Table 2). But given that uncontrolled waterhemp could result in a loss of $300/A, more expensive weed control programs are justified. Even the most expensive treatment ($75/A) may make economic sense due to the short-lived seeds of waterhemp. That treatment provided 100% control of waterhemp, preventing the return of waterhemp seeds to the soil, thereby allowing the depletion of most of the waterhemp seedbank in four years (Mark Loux, personal communication) and return to less expensive control programs. Nonetheless, additional treatments will be investigated in 2020 to attempt to achieve 100% control with less cost.

Objective 2.

The electrical discharge system was very effective in controlling the contacted horseweed (marestail). Complete necrosis was observed for most treated plants. Some plants had green leaves near their base, but no new growth or lateral branching was observed. Common ragweed was also very effectively controlled. Annual sowthistle was mostly controlled, but green leaves persisted on about 25% of the plant. The highest branches of bull thistle (a biennial) exhibited complete necrosis, but lower branches that were untouched by the weed zapper remained unharmed.

It was evident that our August 1 application of the electrical discharge system was earlier than optimal because most of the horseweed had not yet exceeded the height of the crop canopy and was not contacted by the electrified rod. Therefore, to maximize the weed control from a single pass, scouting should be used to delay the application as late as possible, but before the weeds initiate seed production – likely mid- to late-August for most New York farms. For interested farmers, custom application of the electrical discharge system is available through Preferred Quality Grain LLC of Cato, NY.

Project location(s):
Central and western New York.

Samples of resources developed:
Online articles:
Brown, B., DiTommaso, A., Howard, K., Hunter, M., Miller, J., Morris, S., Putman, J., Sikkema, P., Stanyard, M. Waterhemp Herbicide Resistance Tests: Preliminary Results. Cornell Field Crops Blog. May 15, 2019. https://blogs.cornell.edu/ccefieldcropnews/2019/05/15/waterhemp-herbicide-resistance-tests-preliminary-results/

Video:
Marshall, G., Brown, B. Waterhemp Control in Soybeans: 2019 Trials. NYSIPM. December 20, 2019. Accessed December 28, 2019. https://www.youtube.com/watch?v=WSAmMn2P7Wc

Marshall, G., Brown, B. Weed Zapper Demo 2019. NYSIPM. October 1, 2019. Accessed December 28, 2019. https://www.youtube.com/watch?v=GVB33hB8Nes

Acknowledgements:
Thank you to the New York Farm Viability Institute for supporting this project.

Disclaimer: Read pesticide labels prior to use. The information contained here is not a substitute for a pesticide label. Trade names used herein are for convenience only; no endorsement of products is intended, nor is criticism of unnamed products implied. Laws and labels change. It is your responsibility to use pesticides legally. Always consult with your local Cooperative Extension office for legal and recommended practices and products. cce.cornell.edu/localoffices

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