What’s Cropping Up? – Volume 26 No. 5 – September/October Edition

Organic Wheat Looked Great but Yielded 7.5% Less Than Conventional Wheat in 2015/2016

By Bill Cox1, Eric Sandsted1, Jeff Stayton2, and Wes Baum2
1Soil and Crop Sciences Section – School of Integrated Plant Science, Cornell University; 2Cornell University Agricultural Experiment Station

The lower leaves of wheat were senescing in mid-June, despite more N being applied to high input conventional wheat (right), because of exceedingly dry conditions at Aurora and the droughty soil of the experimental area.
The lower leaves of wheat were senescing in mid-June, despite more N being applied to high input conventional wheat (right), because of exceedingly dry conditions at Aurora and the droughty soil of the experimental area.

We initiated a 3-year study at the Aurora Research Farm in 2015 to compare the corn, soybean, and wheat/red clover rotation with different crop sequences in conventional and organic cropping systems during the 3-year transition period (2015-2017) to an organic cropping system. Three of the many objectives of the study are to determine 1) the best entry or 1st year crop (2015) to plant during the transition, 2) the best crop sequence during the 3-year transition (soybean-wheat/red clover-corn, corn-soybean, wheat/red clover, or plowed in red clover-corn-soybean) and 3) do corn, soybean, and wheat respond similarly to management inputs (high and recommended) in conventional and organic cropping systems? This article will compare the agronomic performance of organic wheat with conventional wheat following soybean in a soybean-wheat/red clover-corn sequence during the second year of the transition from conventional to an organic cropping system.

We used a John Deere 1590 No-Till Grain Drill (7.5 inch spacing between drills) to plant the treated (insecticide/fungicide seed treatment) Pioneer soft red wheat variety, 25R46, in the conventional cropping system; and the untreated 25R46, in the organic cropping system at two seeding rates, ~1.2 million seeds/acre (recommended input) and ~1.6 million seeds/acre (high input treatment) on September 24, the day after soybean harvest. We applied about 200 lbs. /acre of 10-20-20 as a starter fertilizer to wheat in both conventional treatments. We also applied Harmony Extra (~0.75 oz. /acre) to the high input conventional treatment at the GS 2 stage (November 5) for control of winter perennials (dandelion in particular).

In both organic treatments, we applied the maximum amount of Kreher’s composted chicken manure (5-4-3 analysis), as a starter fertilizer, that would flow through the drill, or about 150 lbs. of material/acre. We also broadcast Kreher’s composted manure to provide ~60 lbs. of actual N /acre (assuming 50% available N from the composted manure) in the high input treatment in the organic cropping system immediately after planting. In addition, we also added Sabrex, an organic seed treatment with Tricoderma strains, to the seed hopper of 25R46 in the high input treatment in the organic cropping system.

We frost-seeded red clover into all the wheat treatments on March 9 to provide N to the subsequent corn crop in 2017. We applied ~60 lbs. of actual N/acre (33-0-0, ammonium nitrate) in the recommended input treatment in the conventional cropping system on March 21, about a week after green-up. In the high input conventional treatment, we applied ~45 lbs. of actual N/acre (33-0-0) on March 21 and then applied another 45 lbs. of actual N/acre on April 25 about a week before the jointing stage (GS 6). We also applied a fungicide (Prosaro) to the high input treatment on May 31.

We applied Kreher’s composted chicken manure to provide 75 lbs. of available N/acre in the recommended input treatment on March 21. Also, we applied an additional 55 lbs. of available N/acre to the high input treatment in the organic cropping system on March 21. All the plots were harvested with an Almaco plot combine on July 6. We collected a 500 gram from each plot to determine kernel moisture and test weight in the laboratory.

We presented data on wheat emergence as well as wheat densities and weed densities in the fall (http://blogs.cornell.edu/whatscroppingup/2015/11/23/wheat-emergence-early-plant-populations-and-weed-densities-following-soybeans-in-conventional-and-organic-cropping-systems/) and weed densities in the early spring (http://blogs.cornell.edu/whatscroppingup/2016/04/05/no-till-organic-wheat-continues-to-have-low-weed-densities-in-early-spring-march-31-at-the-tillering-stage-gs-2-3/) in previous news articles. Briefly, organic wheat emerged about 1 day earlier, had ~10% more plants/acre, and fewer weeds in the fall. In the spring, organic wheat also had lower weed densities when compared with the recommended input treatment in conventional wheat (no herbicide) and the same weed density as the high input conventional wheat (received an herbicide after fall weed counts) in the spring (Table 1). Consequently, organic compared with conventional wheat had a similar or higher yield potential in early April, the beginning the active spring tillering period, based on stand and weed densities.


Nevertheless, the 10% greater plant density and lower weed density in organic compared with conventional wheat, especially in the recommended input treatment, did not translate into a yield advantage. In fact, organic wheat yielded ~7.5% lower than conventional wheat (Table 2) when averaged across input treatments (no response to high input treatments in either cropping system). We suspect that the use of an organic N source may have resulted in less available N to the organic wheat crop, although visual symptoms of N deficiency were not observed. We did sub-sample before harvest (two 1.52 m2 areas/plot) to determine yield components. Organic compared with conventional wheat did have higher spike densities (533 to 509/m2, respectively) probably because of its higher plant density. Organic wheat, however, had fewer kernels/spike (22.1 vs. 24.5, respectively) and lower kernel weight (311 vs.315 mg, respectively), which indicates that the organic wheat may have been short of N, similar to organic corn in 2015 (http://blogs.cornell.edu/whatscroppingup/2016/03/29/why-did-organic-compared-with-conventional-corn-yield-30-lower-during-the-first-transition-year/).


On the other hand, the recommended input (~75 lbs. of N/acre applied in late March) treatment yielded the same as the high input (~60 lbs. of N/acre in the fall followed by another ~55 lbs. /acre of N in late March) treatment in the organic cropping system. If available N were the limiting factor in organic wheat yields, then we would expect the high input treatment to yield higher because it received more total N (albeit at different timings). We will submit our wheat samples for total kernel N analysis. If total kernel N in organic and conventional wheat is similar, then total N availability may not have resulted in the 7.5% lower yields. Then we would have to explore the idea that perhaps the use of Kreher’s composted chicken manure as a starter fertilizer may not have provided adequate P or K to organic wheat.

In conclusion, organic wheat, despite not receiving an insecticide/fungicide seed treatment, had better stands than conventional wheat and fewer weeds in both the fall and spring. Organic wheat, however, yielded 7.5% lower than conventional wheat in the second year of the transition from conventional to an organic cropping system. We expect that net returns will also be ~7.5% lower for organic compared with the recommended input conventional treatment because the lower seed costs, associated with no insecticide/fungicide seed treatment, will be offset by the higher costs for N, associated with the cost of Kreher’s composted chicken manure vs. ammonium nitrate. Many growers, however, practice high input wheat (high seeding rates, fall herbicide application, split N application, and a fungicide application), which provided no additional yield response to conventional wheat in the dry 2016 growing season. Consequently, organic wheat with recommended inputs will provide a greater return to conventional wheat with high inputs in this study in 2016.

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NYCSGA Precision Ag Project Update

Authored by: Savanna Crossman, Research Coordinator, CCA
Statistical Analysis by: Margaret Krause, Cornell University PhD Student

 *This article is part of an ongoing series.  Previous articles can be found at www.nycornsoy.org/research*

crossman-fig-1New York State has always presented a unique challenge to grain growers due to the large amount of in field variability.  In recent years, growers have also added adverse weather conditions to that list.  From the project’s perspective, two of the past three growing seasons have fallen far outside the conditions of a normal year.  The 2015 season brought early precipitation amounts far above than the historical average while the 2016 season is setting up to be one of the driest in decades.  These conditions have resulted in significantly lower, less uniform yields than a typical year such as 2014 (Figure 1).  Variable rate seeding technology is one of the many tools that NYS growers can use to help overcome these challenging conditions.  However, mainstream companies have yet to design a prescription writing software that is developed to meet the unique conditions of New York State and the Northeast.  This project seeks to address this void by developing a software that will do just that.

The project has been collecting data on a large scale since 2014 in order to create a model that will select hybrids and population rates given certain soil properties and characteristics.  To do this, six major data types are being examined; seeding rate, hybrid, topographical information, NRCS soil survey maps, Veris soil sampling data, and grid soil sampling data.  Each data type consists of many variables which are analyzed individually and as interacting networks.

Figure 2. This example random forest regression analysis demonstrates that phosphorus is the variable with the largest effect on yield in this field.
Figure 2. This example random forest regression analysis demonstrates that phosphorus is the variable with the largest effect on yield in this field.

To examine the effect that each variable has on yield, a statistical approach called random forest regression is being used.  This method essentially ranks each variable based on its importance to yield.  The greater the importance number that is assigned to a variable, the larger effect that variable has on yield (Figure 2).

The project has seen that the variables can rank very differently given the field, crop type, or year.  Each field location is unique and thus has a unique combination of variables influencing yield.  Some fields exhibit a very strong yield response to seeding rate, while others exhibit a strong yield response to fertility factors or topography.

Figure 3. 2014 and 2015 resulted in similar population curves on this corn field in Clyde, NY.
Figure 3. 2014 and 2015 resulted in similar population curves on this corn field in Clyde, NY.

Though each field may be different, it is important to see stability within a field across years.  For example, this 80 acre corn field in Clyde, NY produced similar population curves in two drastically different seasons.  The first year, 2014, resulted in high and uniform yields across the field.  The second year, 2015, yielded dramatically lower with a large variance in yield uniformity.  Though the two seasons were very different, both demonstrated a negative yield response to increased seeding rate (Figure 3).  The lowest rate of 27,000 sds/ac yielded the highest across the two years and which was 5,000 sds/ac lower than the grower’s typical rate.  The random forest regression confirmed that seeding rate was the most important variable influencing yield across both years.

This year to year stability in yield response to seeding rate has been seen between crop types as well.  This 60 acre field in Pavilion, NY is managed as a conventional till field in a corn-soybean rotation.  In 2014, its soybean crop exhibited a strong positive yield response to increased seeding rate.  The random forest regression confirmed that seeding rate held a dramatically greater importance than any of the other variables.  The next year, 2015, the field was planted with corn and again exhibited a positive yield response to seeding rate.  This time, the analysis showed that while seeding rate was still the most important variable, many other factors were also important.  This difference could be due physiological preferences between the two crops or the different weather conditions between the two years. (Figure 4)

Figure 4. Random forest regression analysis of 2014 soybean and 2015 corn of a sixty acre field in Pavilion, NY.
Figure 4. Random forest regression analysis of 2014 soybean and 2015 corn of a sixty acre field in Pavilion, NY.

To explore the idea of physiological differences between corn and soybean, some further analysis was conducted.  In this same Pavilion field, soybean exhibited positive relationships with calcium and pH, while corn exhibited negative relationships with the same variables.  These observations are likely related to the differences in crop preference for pH.  Soybeans grow best in more neutral soils where the rhizobia bacteria that provide the soybean plant nitrogen are most active.  Whereas the corn plant is known to prefer a slightly acidic soil where some key micronutrients, such as zinc and manganese, are more available.  It is understanding relationships such as these from an agronomic and a statistical perspective that will result in a reliable model for NYS growers.

This year has marked the first infield testing of the model which will provide side by side comparison of grower practice to the model’s prescriptions.  Each year of additional data collected will serve to further the development of the model into a robust and reliable resource to growers of the State.

The project is currently looking to bring on additional participants for the 2017 season and encourages any interested growers to contact Savanna Crossman at (802) 393-0709 or savanna@nycornsoy.com .


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What’s Cropping Up? Volume 26 No. 4 – July/August Edition

Recent results from the Cornell Organic Cropping Systems Experiment

Brian Caldwell, Matthew Ryan, and Charles Mohler
Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University

In 2015, over 1000 certified organic farms were operating in New York State (NYS Dept. of Agriculture and Markets).   Nationwide, New York ranks third in number of organic farms and organic cropland harvested (USDA 2011).  Of the approximately 5000 dairy farmers in NYS, about 430 are currently certified organic.  This number is expected to rise to 500 within two years (Fay Benson, Cornell Cooperative Extension, personal communication).  Thus 10% of NYS dairy farms will then be organic.  However, organic grain production has not kept up with demand, and well over half of feed grains sold to New York livestock farmers are from out of state (Mary-Howell Martens, Lakeview Organic Grain, personal communication). Consequently, land-grant university research is needed to support more organic feed and forage production in NYS.

The Cornell Organic Cropping Systems Grain Experiment (OCS) was initiated in 2005 at the Musgrave Research Farm in Aurora, NY. The purpose of this long-term experiment is to compare four approaches to organic production. Results from 2005-2010, including the 3-year transition period, were documented previously (Caldwell et al. 2014).  This article discusses recent findings from the experiment and its future prospects.

Experimental Design

The OCS compares organic cropping systems: high fertility (HF), low fertility (LF), enhanced weed management (EWM) and reduced tillage (RT) organic cropping systems.  We consider them systems because they are different in multiple ways.  They have evolved over time to address production challenges with help from our organic farmer advisory board.  Currently, HF employs higher nutrient additions during each rotation than the others, and uses both belly-mounted and rear-mounted cultivators.  LF receives only corn starter fertilizer once during every 3-year rotation and only rear-mounted cultivators are used.  EWM has an intermediate nutrient regimen and employs both types of cultivators, short tilled fallows, and extra cultivation to reduce weeds.  In contrast to the moldboard plow-based tillage program of the other systems, RT uses a mixture of deep zone tillage, ridge tillage, and chisel plowing depending on the crop.  It has an intermediate soil nutrient regimen.

The experiment includes four replications and two rotation entry points of each system.  Plots are 30 x 100 feet and are managed with farm scale equipment. Soils are in the Lima series, relatively flat calcareous silt loams with fair internal drainage.  All systems started with a

Caldwell - Arrow 1


rotation for the first six years (RT used other legumes instead of red clover in the spelt year).  A group of local organic farmers and extension educators advise on the management of this experiment.

Weed biomass in HF and RT systems was much higher than in LF and EWM by 2010 (Figure 1), and was reducing yields significantly.  It was decided by the OCS researchers based on advisory group input to change the rotation for HF and RT to address this issue.  The rotation for HF and RT was lengthened to six years:

Caldwell - Arrow 2


In essence, a double crop of winter barley and buckwheat was substituted instead of corn at year 4 (2013 for EP A and 2014 for EP B).  This enabled extra mid-season tillage to reduce weeds, particularly perennials.  It also meant that no red clover was grown that year.  In the other years of the rotation, crops were similar to those in LF and EWM.

Figure 1. Weed biomass in soybeans before and after 2013-2014 crop years, average of entry points.

Results 2005-2010

Results from 2005 to 2010 were reported in Caldwell et al. (2014).  Briefly, applied organic chicken manure compost increased spelt yields but not corn yields.  The LF system had the best overall financial returns.  Corn was a poor choice during the transition period to certified organic production, but soybeans performed relatively well and spelt was intermediate.  After the transition period, corn yields increased and were similar to Cayuga County averages.  Organic crops with an arbitrary 30% price premium (chosen to reflect a conservative value) were more profitable than analogous conventional crops with County average yields.  In recent years, the organic premium for corn and soybeans has often been higher than 30%.  Currently (7/8/16) it is over 100% for corn and about 50% for soybeans (USDA, Chicago Board of Trade).

Results 2011-2016

Weather extremes

The current six-year cycle, starting in 2011, will finish at the end of this season for both entry points.  HF and RT will complete one 6-year rotation and LF and EWM will complete two, 3-year rotations.  The period 2011-15 was marked with a dry July (2011) and August (2012) and two very wet Junes (2013 and 2015).  OCS stands were poor and areas of crops were severely stunted in 2013 and 2015 due to insufficient drainage, but crops tolerated the dry spells.  Figure 2 shows yields of OCS crops over the period.  Yields were normalized as a percentage of Cayuga County (if available) or NYS average yields for each year and crop, then placed in two groups based on wet or “normal” years.  Buckwheat yields were not included due to lack of State or County averages.  In 2011, 2012, and 2014, yields were close to County averages for the conventionally tilled systems, whereas in 2013 and 2015 they were quite reduced.  The RT system had about 60% of County yields in all years, regardless of June precipitation.  In the wet years, the low fertility system was affected most severely.

Figure 2. OCS yields, 2011-2015. Buckwheat not included due to lack of published County or State yields. “Normal” years were 2011, 2012, and 2014. Wet June years were 2013 and 2015.

In 2015, 8 inches of rain fell in June, whereas in 2016, the June total was only 0.74 inch, the lowest growing season monthly precipitation during this experiment.  It appears likely that such extreme weather periods will be common in the future.   Our results indicate that under organic management on this soil type, higher nutrients can ameliorate some of the negative effects of excess rainfall.  The extremely dry June of 2016 was preceded by a dry May, and drought continued into July.  Whereas the winter spelt crop looks excellent in HF, EWM, and RT as of this writing, corn growth has been slowed dramatically.  Corn harvest this fall will give us insight into whether any of these systems are better able to withstand severe dry spells.

Caldwell - Fig 3
Figure 3. Spelt prior to harvest in the High Fertility (HF) system on July 5, 2016.

New crop rotation

Weed biomass was reduced in HF and RT after the barley/buckwheat year in their expanded rotations (Figure 1).  Whether weed biomass will remain lower in these systems is not yet clear.  However, this strategy under our constraints was likely unprofitable.  The introduction of new crops such as winter barley and buckwheat into the crop mix often requires new equipment and knowledge.  Our buckwheat yields in particular were low because of equipment limitations and unfamiliarity with harvesting this crop. Local organic buckwheat farmers often use a swather and combine pickup head to harvest buckwheat.  The swather mows and gently windrows the buckwheat, allowing it to remain in the field to fully mature and dry. The windrows are then gathered into the combine using the pickup head.  Instead, we direct-harvested the crop, a method that can result in field losses (Bjorkman 2010).  Similarly, our inexperience with barley also resulted in some harvest losses.  Although we have not yet put together financial budgets for these crops, net returns for the barley and buckwheat with our yields would likely have been much lower than those from corn achieved in LF and EWM in corresponding years.  Our experiences mirrored those of many farmers when starting out with new crops.

Future plans

The OCS grain experiment begins a new phase in 2017.The first twelve years have yielded valuable insights into nutrient regimens, crop yields, and weed dynamics, but farmers are now facing additional challenges and attractive opportunities.  For example, climate change seems to make “normal” seasons rarer and rarer.  Extremes of rainfall and drought are encountered more frequently.  On the plus side, markets for organic dairy feed including balage and other forages are strengthening.  Buyers for crops such as sunflowers (Bob Gelser, personal communication) are looking for local producers.  Over the next year, we will work with our organic farmer advisory group to plan out the next 12 years of the experiment.  It will start in 2017 with a uniformity trial in which the same crop (sorghum sudangrass) will be grown over all plots.  This will allow us to assess cumulative effects on soil nutrients and weeds from 12 years of management using four different organic management systems.  In addition to updating management practices and data collection protocols, we will also work to improve the research site by installing new tile drainage in the alleyways between plots

This new phase of the Organic Cropping Systems Grain Experiment will explore scenarios and issues that we and our advisors anticipate will impact farmers in our region in coming years.

Bjorkman, T. 2010. Buckwheat Production: Harvesting.  Agronomy Fact Sheet 51.  Cornell Cooperative Extension.  Ithaca, NY.

Caldwell, B., C. L. Mohler, Q. M. Ketterings, and A. DiTommaso. 2014. Yields and Profitability during and after Transition in Organic Grain Cropping Systems. Agron. J. 106:871-880.

Chicago Board of Trade (accessed 7/25/16).    http://quotes.ino.com/exchanges/exchange.html?e=CBOT

NASS. USDA National Agricultural Statistics Service (accessed 7/25/16).https://quickstats.nass.usda.gov/

Schipanski, M.E. & Drinkwater, L.E. 2011. Nitrogen fixation of red clover interseeded with winter cereals across a management-induced fertility gradient.NutrCyclAgroecosyst 90: 105-119.

USDA. National Organic Grain Feedstuffs online price list(accessed 7/25/16).https://www.ams.usda.gov/mnreports/lsbnof.pdf






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Winthrop Square Park Project: Using Cornell University’s Comprehensive Assessment of Soil Health in an Urban Environment

Lindsay Fennell, Bob Schindelbeck, Aaron Ristow, and Harold van Es
Soil and Crop Sciences Section, Cornell University

Chuck Sherzi Jr.
Sherzi & Company, LLC


Soil health has recently captured the attention of farmers in the U.S. and internationally, yet there are many applications that expand beyond the field of agriculture. The green urban landscape has great potential for improving soil quality. In city parks and greenways, compaction from both human and machine activity, and the mixing of topsoil and subsoil during routine park maintenance can affect soil functions such as plant growth, water infiltration, and the support of biological life.  Although soil degradation is visible in many parks, a systematic approach to characterize soil health has only recently been applied to urban landscapes.

Cornell University’s Comprehensive Assessment of Soil Health (CASH) provides an assessment of soil health relative to important soil physical, chemical and biological processes. In both rural and urban settings, chemical indicators such as pH and macro/micro nutrients are often at optimal levels due to lime and fertilizer applications, yet the soil itself can still be physically and biologically degraded. CASH provides a full picture of what’s going on below the surface.  It outlines the interconnected processes causing constraints, which in turn empowers land managers to make informed decisions about soil amelioration and future maintenance.

By promoting urban soil health, cities can create positive environmental outcomes such as flood protection, groundwater recharge, and sequestration of dust and carbon, while providing a more comfortable urban climate through healthy plants. Recently, CASH was evaluated as a tool for a renovation project in Boston, Massachusetts, which is a notable example of the application of the test for soil health management in city parks.

Case Study: Winthrop Square Park

Pocket parks (or mini parks) play an important role in city life, whether it’s sitting on a park bench, strolling through a bit of green in an urban jungle, or the neighborhood kids playing a game of kickball. These small parks, sometimes no larger than ¼ acre, provide a safe and inviting environment for community members. They support the overall ecology of the surrounding environment, landscape and heritage, and empower local residents to make decisions that affect their community. Boston has hundreds of these outdoor parks all over the city, and one of the oldest and most beloved is Charlestown’s Winthrop Square Park.

Figure 1 1852 McIntyre map of Boston showing the Training Field in relation to City Square and the Bunker Hill monument. By this time the Training Field site was becoming more park-like. Photo taken from the Cultural Landscape Plan for Winthrop Square Park.
Figure 1 1852 McIntyre map of Boston showing the Training Field in relation to City Square and the Bunker Hill monument. By this time the Training Field site was becoming more park-like. Photo taken from the Cultural Landscape Plan for Winthrop Square Park.

The park, also known as the “Training Field”, is a .89 acre green space with a 400 year history. It was a training ground for colonial militia in the 1640’s, was witness to the Battle of Bunker Hill in 1775, served multiple functions as a civic space throughout the centuries, and most recently became a hotspot for Charlestown residents and a stop along the Freedom Trail. Although this space is deeply significant to the community and the city itself, it has been many years since restorations took place. Along with other much needed rehabilitation work, it faced drainage and erosion problems, and the overall soil health was lacking in many areas.

The park renovation project developed out of a cultural landscape report, prepared by Kyle Zick, Landscape Architect, and Shary Page Berg, Landscape Preservationist, in partnership with two local community groups, the Charlestown Preservation Society and the Friends of the Training Field. The Boston Parks and Recreation Department led the way and a park renovation proposal was approved by the City, along with $690,000 from its Capital Budget.

Site Analysis

Figure 2 Aerial view of the park and the six unique sampled areas
Figure 2 Aerial view of the park and the six unique sampled areas

Sherzi & Company LLC was part of the consulting team brought in to address the drainage and soil health issues at the site. Owner Chuck Sherzi had extensively used the CASH approach in previous projects, and recommended to employ this holistic approach to address the concerns facing the park. The complete diagnostic report included data analysis and interpretations from the Cornell Soil Health lab, site observations, and a detailed summaries of suggested recommendations and appropriate construction materials. Since the site is naturally divided into six unique areas and each had a specific set of challenges (foot traffic, grade elevation, water flow, etc.), separate soil samples were collected from each area (Figure 2).

The Comprehensive Assessment of Soil Health

The CASH approach emphasizes the integration of soil biological, physical, and chemical measurements. These include soil texture, available water capacity, soil penetration resistance (compaction), wet aggregate stability, organic matter content, soil proteins, respiration, active carbon, and macro- and micro-nutrient content (see soilhealth.cals.cornell.edu/ for more details). The results are synthesized into a comprehensive soil health report with indicator scores, constraint identification, and management suggestions. The report can be used by consultants and managers as a baseline assessment and to guide soil amelioration and future management.

Winthrop Square Soil Health Results

The entire site showed soil health concerns, with overall quality scores of low to medium. Specifically, the CASH reports (Figure 3) showed:

Physical Indicators

  • Figure 3 Summary page from the Area 5 Soil Health report
    Figure 3 Summary page from the Area 5 Soil Health report

    Aggregate stability (indicating soil resistance to disintegration from rainfall) and available water capacity (indicating the soil’s ability to store water) scored high on all six assessments, possibly a result of minimal soil disturbance at the site over the years.

  • Surface (0 – 6 inches) and subsurface (6 – 18 inches) hardness (indicating compaction that limits root growth, water transmission and plant access to nutrients and water) scored mostly low and medium throughout the site.

Biological Indicators

  • The indicators generally scored medium or low, suggesting marginal soil biological activity. Although several areas tested within range for total organic matter, active carbon was constrained at four sites, indicating a lack of biologically available food and energy within the organic matter.
  • All six areas scored medium in the root health rating, most likely due to compaction.

Chemical Indicators

  • pH and minor elements scored low or medium in five of the six areas.
  • Heavy metals in all areas were found to be within the allowable concentrations for garden soil and were therefore not a concern for this project.

Example of Detailed Problem Spot: Area #5 (Figure 3)

Area 5 was the second largest of the areas assessed, experiencing a high amount of foot traffic and patchy consistency throughout. It had the lowest soil health score, with the major constraints being surface and subsurface compaction. While the organic matter scored high, other biological indicators were relatively low. The sandy loam texture could be a factor in the loss of nutrients through leaching, and the low nutrient base cations Mg++ and Ca++ could be associated with a low pH. A layered approach was proposed for Area 5 and all other areas assessed.

Recommendations and Implementations

Results of the assessment highlighted soil compaction as the major underlying constraint common to all six of the Winthrop Square areas. Issues with the physical structure of soil eventually leads to negative impacts of both biological and chemical components. Compacted soils have decreased pore space that can limit infiltration, increase runoff and erosion potential, and allow for anaerobic conditions that are unfavorable for beneficial microbial communities. They can also limit plant access to nutrients and water. Given these results, recommendations for the site were focused on decompaction measures followed by incorporation of organic amendments to improve nutrient cycling, pH, and the overall biological health of the soil. Sherzi also recommended amending the sandy loam soil with biochar and a green manure to break up the surface hardness, aid in nutrient retention and further prevent runoff and erosion.

Soil Decompaction Techniques

A multi-tiered approach was used to addressing soil compaction. Due to the natural slope at the site, any remediation effort had to be careful not to destabilize the existing upper soil profile. The project was done in phases where Areas 1, 2, 3 and 4 were done together as they do not impact the daily flow of foot traffic in the park. Areas 5 and 6 were addressed separately as they are the two largest spaces and have the most foot traffic (Figure 2). The compaction issues were addressed using the following tools/techniques:

  • Figure 4 Air spade used to aerate and break up soil at Winthrop Square Park.
    Figure 4 Air spade used to aerate and break up soil at Winthrop Square Park.

    Air Spading: Useful for tree root collar work and excising of girdling roots. The specialized tool uses compressed air to dislodge, breakup, and aerate compacted soil. Soil amendments are then added and “stirred” into the existing soil using the air tool.

  • Figure 5 Example of vertical composting.
    Figure 5 Example of vertical composting.

    Vertical Composting: Utilizes air tools to open up holes in the soil along a predetermined grid pattern in turf areas. Soil amendments are then added to these holes and graded over. The compaction layer is slowly broken up by the microbes as the holes begin to coalesce, reducing compaction and improving the overall soil health.

  • Figure 6 Radial trenching pattern around tree at Winthrop Square.
    Figure 6 Radial trenching pattern around tree at Winthrop Square.

    Radial Trenching: much like the root collar technique, this approach works on a pattern of trenches, radiating from the trunk of the tree, either dug by hand, by machine or by air tool. Soil amendments are then added to help stimulate fibrous roots of the tree.

In addition to the physical decompaction work, incorporating organic matter, both dry and liquid, was critical for maintaining balanced soil biological communities. Dry and liquid soil amendments used in conjunction with the de-compaction work: compost, calcitic lime, bio-char, fish hydrolysate.

Maintenance Recommendations

Potential long term management solutions for the park include top dressing with compost, adding fertilizer, limestone for pH, and fungal foods, grass mowing at 3.5-4” height, and keeping pedestrian foot traffic on walkways. An irrigation system was installed along with moisture sensors to determine proper watering amounts.

Project Progress

The Winthrop Park Project is scheduled for completion in summer 2016, including attention to the hardscape –new concrete, relining the ‘Freedom Trail’, fencing, etc. CASH, with its site-specific soil health analysis and holistic management approach, proved to be effective for soil testing in the urban environment. Using this method, a cherished piece of green-scape for the Charlestown community set an example for how cities can approach future soil health monitoring in city parks.

For more information about CASH, please visit soilhealth.cals.cornell.edu. For more information about the project contact Chuck Sherzi Jr. at csherzi@comcast.net.


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