Sustainable cropping systems for dairy farms in the Northeastern US

2012 Annual Report for LNE09-291

Project Type: Research and Education
Funds awarded in 2009: $400,000.00
Projected End Date: 12/31/2013
Region: Northeast
State: Pennsylvania
Project Leader:
Dr. Heather Karsten
The Pennsylvania State University

Sustainable cropping systems for dairy farms in the Northeastern US


By assessing the performance of the innovative practices and the dairy cropping systems from a multidisciplinary perspective, over the past three years we have gained an understanding of their performance, as well as agroecosystem interactions, benefits, and trade-offs. Overall the cropping systems and the majority of the innovative practices are providing multiple agroecosystem benefits, although a few practices need to be modified to improve their performance. In the case of the green manure crop comparison and strategy to sustain mycorrhizae in canola, we have gathered multiple performance indicators and can conclude which are most successful. We have also identified opportunities to further improve the performance of the cropping systems and test new research hypotheses. The Advisory panel has provided helpful input and was supportive of the changes we proposed. In the 2012 growing season, a few management modifications were made and we plan to implement more significant changes in 2013. We describe the research results and the proposed changes within this report.

Specifically, in the Forage rotation we found that in comparison to broadcasting manure on the surface, shallow-disk manure injection conserved more manure nitrogen, reduced the need for side-dress nitrogen applications and produced similar crop yields. Trade-offs of manure injection compared to surface-applied manure include the higher cost of shallow-disk manure injection and the higher cumulative emissions of the greenhouse gas nitrous oxide following two out of three manure application events. In comparing red clover and hairy vetch as green manure for a subsequent corn crop, we found that underseeding red clover in spring into winter wheat provided multiple benefits over planting hairy vetch after wheat harvest. Further, in both of the rotations, the integration of perennial legumes, green manure and cover crops, and shallow-disk manure injection provided all or the majority of crop nitrogen needs, as indicated by the pre-side dress nitrogen tests and crop yield treatment comparisons.

In the Grain Rotation, compared to “standard” no-till herbicide practices a number of the integrated weed management approaches controlled weeds, reduced herbicide use and also provided additional agroecosystem benefits. For instance, compared to applying an herbicide to terminate alfalfa, plowing alfalfa eliminated an herbicide application and reduced slug activity, resulting in improved establishment of the subsequent winter canola crop compared to no-till canola. Planting annual companion crops with alfalfa and orchardgrass produced more forage in the establishment year in two out of three years and contributed to increased farm profitability. To further improve establishment of alfalfa and orchardgrass and reduce weeds in the second and third harvests in the establishment year, we will remove the peas and use only triticale as a companion crop.

In the corn and soybean row crops, we reduced herbicide use by banding herbicides over the crop-row and cultivating twice to broadcasting herbicides and applying an additional post-emergent herbicide. The reduced herbicide approach resulted in similar corn yields every year, and similar weed control in two of three years. In soybeans, we also rolled down cereal rye to create a high-residue mulch, in addition to banding herbicides and cultivating twice. This did not control weeds as well as the standard herbicide approach and soybean yields were lower in the reduced herbicide treatment, although a number of production differences likely contributed to soybean yield differences. We are working to identify approaches to reduce the soybean treatment differences that we suspect contributed to the lower yields and to identify how to improve weed control. In the grain rotation we also found that planting oats with winter canola did not increase mycorrhizal colonization in bioassy plants in canola, nor in the subsequent rye and soybean crops. Oats planted with canola also did not reduce weed populations, canola seedling slug damage, or influence canola yield. As a result, we have discontinued planting oats with winter canola.

The Forage and Grain rotations also compared two approaches for integrating canola into a dairy crop rotation and revealed a number of factors critical for successful canola production. In the Forage rotation, in two of three years winter canola could not be planted in a timely manner after corn silage, and applying manure at planting after corn silage did not efficiently utilize manure nitrogen or supply canola nitrogen needs. As a result, in 2013, we will rearrange the Forage Rotation and plant winter canola after winter wheat instead of after corn silage. By contrast, applying manure at planting canola after alfalfa did supply winter canola nitrogen needs and resulted in higher winter canola yields in the year when winter canola was planted in both rotations. In addition, in the Grain rotation, canola was planted without tillage in the standard herbicide treatment versus after terminating alfalfa with tillage in the reduced herbicide treatment. In fall of 2011, the no-till canola treatment had higher slug activity density, lower canola populations and lower yields in 2012 than the canola planted after tillage. In fall 2012, the no-till canola also had lower canola populations. Based on these observations and the slug activity seasonal patterns we have documented, we will move canola planting in both rotations to the middle of August prior to the typical period of increased slug activity and when daylenth and temperatures for plant growth tend to be better.

Through intensive sampling over the past three years, we have gained an understanding of slug natural history and potential opportunities to reduce slug damage to crops. For instance, we have found that slug-activity tends to increase with egg hatch in spring and in autumn when many slugs are adults, and particularly during wet weather periods. This has helped us interpret the high incidence of slug herbivory and poor establishment of crops planted in late summer and early fall (alfalfa and winter canola) when daylength and temperatures for seedling growth were declining. As a consequence of a few years of poor fall establishment, we have discontinued planting no-till alfalfa in fall and will plant it instead in early spring. In laboratory studies, we have also found that two ground beetles species collected at the site, are slug predators and that systemic, seed-applied insecticides are toxic to the beetles but not to slugs. These findings are being further investigated by Margaret Douglas. In the first three years, we have also found that with diverse crop rotations and the use of integrated pest management practices, insect pest populations were below economic thresholds with the exception of potato leafhoppers. We have managed the potato leafhoppers with strategic harvesting and one insecticide application per year and will continue to monitor insect pest and predatory insect populations.

We are still simulating and analyzing the virtual dairy herd production and economic performance and plan to conduct additional advanced economic analyses over the next three years. In the first two years, however, both of the sustainable dairy cropping systems (inject manure and reduced herbicide and broadcast manure and standard herbicide) produced almost all of the virtual dairy herd’s feed and forage, and all of farm’s tractor fuel needs along with some additional canola oil to sell. The farms used less fossil fuel compared to typical Pennsylvania dairy farms, and analyses indicate that the dairy farms were profitable. In addition, the inject manure and reduced herbicide farm was more profitable than the broadcast manure and standard herbicide farm. In summary, this research has made numerous scientific contributions to understanding strategies to enhance dairy farm sustainability and provides an educational example for a wide audience. In the next three years, we will continue to monitor the cropping systems, learn how to improve their performance, and share this information through the scientific literature and outreach educational activities and materials.

Objectives/Performance Targets

This project takes an interdisciplinary approach to develop sustainable dairy cropping systems and monitor multiple indicators of systems performance. Utilizing ecological principles and innovative practices, we designed two six-year dairy crop rotations to minimize off-farm inputs and environmental impacts for a typical-sized Pennsylvania dairy farm. Within each rotation we have been comparing innovative manure or weed management strategies, as well as evaluating two green manure crops, and a tactic to sustain mycorrhizae populations in canola. The two crop rotations also compare two approaches to integrating winter canola into a dairy crop rotation. By assessing the performance of the innovative practices and the dairy cropping systems from a multidisciplinary perspective, over time, we seek to gain an understanding of the performance of the cropping systems, as well as agroecosystem interactions, benefits, and trade-offs.


NESARE Dairy Cropping Systems Research Site

For the most part, farm management continued as planned for our dairy cropping systems (Project Schematic; Appendix Tables). In 2011, however, unusually wet weather in spring (10.35 inches in April and May) and early fall (5.62 inches in August) delayed spring operations and delayed or prevented some fall field operations. In 2012, March was unseasonably warm, followed by dry weather, spring frost, and then wet spring weather in spring and in fall which delayed some fall field operations. Details about challenges with crop operations can be found in the sections on yields for the Forage and Grain rotations.

Forage and Feed Quality Laboratory Simulations

At every crop harvest in the NESARE Dairy Cropping Systems Trial, we collect three subsamples for forage or feed quality analysis from each of our main management treatments that compare two strategies for either manure in the Forage rotation, or weed management in the Grain rotation. In many cases, processing is needed to prepare a crop sample that is representative of on-farm storage or processing. We refined our crop post-harvest processing methodology for ensiling forage crops, extracting oil from canola, and roasting soybeans in the laboratory (See details in the 2011 annual report).

Forage Rotation: Yields

Crop yields were collected for each crop entry point in the FORAGE rotation in 2010-2012; data was analyzed with a split-plot, mixed ANOVA model using PROC MIXED of SAS for all crops that received manure in the rotation. Forage crop yields for all harvests were analyzed with a repeated measures split-plot, mixed ANOVA model.

In 2012, the effect of manure management on crop yields across the rotation was significant (p = 0.0360; Table 1), although this was not significant in 2011 or 2010. This significance of manure management in 2012 at the rotation level appears to be a combination effect. The three individual pre-planned contrasts for each of the corn silage and canola crop entries however were not significant. Yield of the two corn silage entries with injected manure only tended to yield 9% more than the corn silage with broadcast manure (p values = 0.09 and 0.12). By contrast, the canola yield with the injected manure (IM) tended to yield less than the broadcast manure treatment (p =0.07). Over the years, we have observed inconsistent canola populations in the injected manure treatment that we suspect is due to the difficulty of using the no-till drill to plant canola at a shallow depth (~ 1/8 to ½ inch) into the uneven micro-topography created by the manure injection operations. In 2012, a John Deere no-till drill was purchased through collaboration with many researchers. It is reputed to have better seed depth control particularly into residue and we plan to use this no-till drill to plant canola in 2013.

For the corn crop entry points, in 2010 and 2012, the pre-sidedress nitrogen tests indicated that less sidedress nitrogen was needed where manure had been injected (Table 2). By 2012, little or no sidedress nitrogen was needed following a green manure or perennial legume crop compared to rye, no cover crop, and in the first year of the project (Table 2). In 2010, rye preceded all corn crops and we applied less manure to our corn crops because we thought the farm could support fewer cows than in 2012. Nonetheless, considering that each unit of manure solids comprises ~0.5% nitrogen, the slightly higher manure rate in 2012 does not explain the large drop in the need for sidedress nitrogen. Likely, the legumes in combination with manure injection are increasing soil nitrogen pools and reducing or eliminating the need for sidedress nitrogen applications.

Due to the unusually wet spring and fall weather in 2011, the corn silage that follows red clover and hairy vetch was planted later than intended (FORAGE rotation; Fig. 1) and harvest in 2011 of this short-season corn silage hybrid was further delayed by rainy fall weather. As a result, winter canola was not planted after the corn silage. Because our virtual dairy farm needed to empty its manure storage facility prior to winter, we injected and broadcast the manure treatments, planted winter rye in the fall 2011, and spring canola in 2012. In fall 2012, wet weather again delayed corn silage harvest, winter canola was not planted, and winter rye was planted instead after manure treatments were applied. In spring 2013, we will terminate the winter rye early and plant spring canola.

Also, in 2010 and 2011, the alfalfa and orchard grass planted in late summer after canola in the FORAGE Rotation failed to establish and although canola residue allelopathy may have contributed, high slug activity also appears to explain the poor seedling establishment. After these observations, our advisory panel farmers explained that due to slug pressure, they prefer to plant no-till alfalfa in early spring rather than late summer. The alfalfa and orchardgrass were replanted in spring 2011 and 2012 and established successfully in spring 2011. In spring of 2012, replanted alfalfa and orchardgrass failed to establish twice, so we planted an emergency crop of BMR sorghum sudangrass which established well and provided two forage harvests (see Table 3). These repeated challenges in establishing winter canola after corn silage and alfalfa and orchard grass after canola has convinced the team to reorganize the FORAGE rotation. Rather than planting winter canola after corn silage, we will plant winter wheat after corn silage and then canola will follow winter wheat when if it can be planted earlier. Alfalfa and orchardgrass will be established in spring after corn silage followed by a oats cover crop rather than in late summer after canola (see the revised cropping system plan in Figure 1 of the Proposal).

In all three years, annual yields for the manure management comparison were not statistically different for any of the crop entry points (Table 1). For each forage harvest in 2010-2012, the manure management comparison was not significantly different for either the 1st or 2nd year alfalfa + orchardgrass stands (Table 3). This was not surprising for either crop entry point since neither receives manure. Also not surprising, the 1st year alfalfa and orchardgrass yielded half as much forage as the established 2nd year alfalfa and orchardgrass stands in both years.

Forage Rotation: Forage and Feed Quality

To compare the main management treatment effects on crop quality we compared a common set of forage and feed quality variables, including % crude protein (CP), % neutral detergent fiber (NDF), and net energy of lactation (NEL/Mcal/lb) and used the same statistical model that we used to analyze crop yields. There were no statistical differences between main management treatments for % CP, % NDF, or NEL (Mcal/lb) for all crops in the FORAGE rotation in 2010 (Table 4), 2011 (see Table 7 in 2011 Annual Report) or in 2012 (Table 4).

Forage Rotation: Green Manure Comparison

Within the inject and broadcast manure management treatments, we also compared two green manure crops for nitrogen production prior to planting corn silage (Corn silage-Ca). While designed as a comparison between green manure crops, the red clover (RC)-hairy vetch (HV) comparison between winter wheat and corn for silage (Fig. 2), also represents two different weed management systems. Red clover was drilled in one half of the wheat plots in early spring of each year; hairy vetch was planted in the other half 4 to 6 weeks following wheat harvest. The mulch provided by cover crops can suppress weeds during the fall and winter and in the subsequent corn; to lengthen the persistence and improve the weed suppression of the mulch in the HV treatment, triticale was added at 34 kg*ha-1 in mixture beginning in 2011.

The wheat that would be rotated to HV received an early April herbicide application of 0.04 kg*ha-1 Harmony Xtra (thifensulfuron-methyl + tribenuron-methyl). Red clover has the capacity to compete with weeds in wheat and following wheat harvest and herbicide use in wheat could damage RC, so no herbicide was used in the RC wheat. Prior to seeding the HV, a burndown application of 1.26 kg*ha-1 glyphosate plus 0.56 kg*ha-1 2,4-D LVE was applied about 14 days prior to sowing hairy vetch and triticale. Thus, two extra herbicide applications (spring wheat and late summer burndown) were applied to the HV plots that were not needed with RC.

Weed biomass in wheat was sampled in June before wheat harvest, and weed density and biomass after wheat harvest, but before hairy vetch seeding. Weeds in wheat and in corn silage were sampled both from the resident weed population and from subplots within the crop plots that were supplemented with three weed species (see Grain Rotation Methods) the preceding fall. Before cover crop termination, cover crops were sampled for biomass and separated into percent cover crop and weeds. Nutrient analyses were performed on cover crop tissue samples to estimate nitrogen contribution at the time of corn planting. Manure was applied before corn planting to supplement fertility, and PSNTs (pre-sidedress soil nitrate tests) were performed in June to determine if the corn needed side-dress N. Weeds and the cover crops in corn were managed with the preemergence herbicides (glyphosate plus 2,4-DLVE plus dicamba) and with glufosinate postemergence. In 2011, halosulfuron plus nicosulfuron was added to glufosinate for improved yellow nutsedge (Cyperus esculentus L.) and orchardgrass control.


We began the experiment in fall 2009 by planting winter rye to all plots, and the green manure crops were not planted prior to the 2010 corn silage and accordingly yields did not differ between “the treatments” (Table 1).

In both 2011 and 2012, wheat yield did not differ between treatments, and resident weed biomass was not high enough to suggest an impact on yield from weeds (Table 5). In 2011, there was a large population of winter annuals that emerged in one block of the RC wheat, which explains the high average weed biomass in 2011 (60.2 g*m-2). This phenomenon was only observed in one block of wheat and was likely a residual effect from a past experiment, and thus differences were not statistically significant. These weeds were mowed off with wheat harvest, then cut again in the fall forage harvest of red clover, and did not result in higher weed biomass in the subsequent corn silage.
In 2011 and 2012, RC biomass at corn planting averaged 4.0 Mg*ha-1, while HV biomass ranged from 2.1 to 3.9 Mg*ha-1. Red clover biomass was 1.8 Mg*ha-1 higher than HV biomass in 2011 and they were almost equal in 2012 (Table 5). In both 2011 and 2012, weed control was good and we found no differences in weed biomass in corn due to cover crop (Table 5). In 2011, corn yield did not differ between cover crop treatments, but in 2012, corn silage yield was higher following RC compared to HV (Table 5). The yield difference in 2012 may be partly explained by higher corn populations in 2012 corn following RC than in corn following HV (Table 17). Both crops received manure before corn planting, and PSNTs (pre-sidedress soil nitrate tests) were used to determine the amount of nitrogen fertilizer that should be added to the corn early-season. While corn following red clover had more soil nitrate at that time, the soil nitrate levels were deemed adequate in both cover crop treatments. The RC treatment produced greater cover crop biomass prior to termination only in 2011, but not 2012. In 2012, manure application occurred prior to cover crop termination and this operation appeared to suppress HV growth and recovery more than RC. In addition, corn plant populations were significantly lower in the HV treatment compared to the RC treatment, perhaps due to slug herbivory. These factors might have contributed to the differences observed in corn silage yield.

One notable difference between treatments is the ability to obtain a forage harvest from the red clover in fall. This was possible in all three years (fall of 2010-2012), and did not result in lower corn yield compared to hairy vetch in subsequent seasons when spring manure was also applied. While harvesting red clover requires labor, it can be valuable for mixed operations where livestock forage is needed. Red clover seed is often less expensive than hairy vetch. Because of hard seed, hairy vetch is known to persist in soil and return as a weed pest in subsequent years to planting. Because one of our research goals was to identify ways to reduce herbicide use in a no-till system, it appears that a wheat-red clover-corn system is one way to obtain good yields, adequate weed control, and forage, while minimizing costs and inputs, in this cropping system.

In summary, the red clover cover crop eliminated two herbicide applications necessary in the hairy vetch management system. Wheat yields were equal and red clover provided additional forage compared to hairy vetch. Weed control in corn was similar for the two cover crops and corn yield was either equal or greater for the red clover based system. Based on results from this two-year study, the red clover cover crop system appears to have several advantages that were not realized when using hairy vetch. To document this comparison for an additional year, we planted hairy vetch and triticale in fall 2012. We will discontinue planting hairy vetch in 2013 and use red clover only as a green manure. Red clover will be planted with canola prior to corn silage, and the split-split-plot comparison will be changed to compare time of manure application to canola to identify how to improve canola manure nitrogen utilization.

Lysimeter Plots: Trade-offs in Nitrogen Conservation Under Alternative Manure Management Strategies


Plot-scale lysimeters were constructed to allow calculation of nutrient balances associated with injected and broadcast (unincorporated) manure applications. Construction of twelve hydrologically-isolated plots (each ~400m2) was completed in the late spring of 2012 on a site overlying shallow bedrock. Drainage tiles were installed in each plot at the level of the bedrock to intercept groundwater flow. Earthen bermes were constructed around each plot to direct surface runoff water to tile outlets. Tiles collecting both surface and ground water from each plot were directed to collection houses. Full instrumentation of the site was finalized in the spring of 2012, including the installation of flumes and pressure transducers in the houses to automate water flow measurement. An automated weather station has been installed, and instrumentation was also added to track soil moisture at 8, 16 and 30 inches in four of the 12 lysimeters. A landscaping project to improve appearances and access for demonstration events was completed in 2012. After observing evidence of bypass flow following the spring manure application, a smoke tracer study was conducted to identify rodent burrows and other macropores that were potentially biasing subsurface runoff monitoring. These macropores were then sealed with bentonite.
In addition to infrastructure for water collection and associated nutrient loss measurements, nitrogen gas flux measurements were made using portable chambers. Ammonia (NH3) emission measurement were made in the period immediately following manure application, while weekly or twice-weekly nitrous oxide (N2O) measurements were made for several weeks after applications.

Changes have been made to cropping and manure application treatments associated with the field lysimeters during the course of the experiment. Weather delayed corn silage harvest in 2012, preventing timely canola planting. Instead, winter wheat was planted, which will create a much larger window of opportunity for canola planting in 2013. In addition, the manure aerator treatment was dropped in order to increase the number of lysimeter replications from 4 to 6 for the two principle manure application treatments (i.e., broadcast and inject).


Undoubtedly the single greatest nutrient management benefit of injecting manure is the conservation of ammoniacal-N that stems from incorporating manure into soil. Ammonia emissions were more than one order of magnitude lower with injection than with conventional broadcast application in both 2011 and 2012 (Fig. 3A and B). These reductions in ammonia emissions were comparable to the 90% or more reduction with injection reported for a previous experiment at the research farm (Dell et al., 2012). The emission rate magnitudes differed greatly, most likely due to the difference in general weather conditions. In 2011 we applied manure on June 9 with a high temperature of 31°C. Hot temperatures and wind typically accelerate ammonia emissions. In 2012 weather conditions were much different, with overcast skies and a high temperature of 18°C.
Although the greatest ammonia flux associated with broadcast application was observed shortly after application, substantial differences in emissions were observed through the 24 hour observation period in 2012 (Fig. 3B). Because a method for cumulative ammonia emission measurement was not available, our ammonia emission results are best used an indicator of relative differences in emissions between treatments. However, ammonia losses typically account for 30-70% of the ammonium-N content of manure depending on soil and weather conditions (Thompson and Meisinger, 2002). Given additions of about 80 kg ha-1 ammonium-N with our manure and application rate, we estimate manure injection at our location can reduce ammonia emission by 20-50 kg ha-1 year-1. Negative air quality impacts of ammonia emissions (such as contribution to particulate matter formation and associated human respiratory problems) are reduced with manure injection. Moreover, our results point to the potential for significant fertilizer nitrogen savings, assuming efficient use of the conserved nitrogen by crops.


Our findings point to a potential trade-off with manure injection. Some of the benefits of reducing ammonia volatilization with injected manure may be offset by increased N2O emissions relative to broadcasting in the days shortly after application. While its emission generally accounts for only a small portion of the manure N, N2O is a potent greenhouse gas with important implications for climate change. Nitrous oxide is primarily produced through denitrification of nitrate under anaerobic conditions, which are more likely to develop within manure injection bands. The combination of greater water content and the rapid depletion of oxygen, because of accelerated microbial activity, in the concentrated band of manure can lead to formation of anaerobic conditions needed for denitrification. In addition, denitrification can result in the complete reduction of nitrate to dinitrogen gas resulting in additional potential for loss of manure-N. Unfortunately, methods for direct measurement of dinitrogen emissions are not available.

The N2O emissions from 2011 clearly show the expected increase with injection (Fig. 4C). Spikes in N2O emissions from injected manure, 4 to 5 times greater than those from broadcast, were observed approximately one week after manure application in 2011 (Fig. 4C) The delayed emission spike likely occurs because time is required for accumulation of nitrate and the creation of anaerobic conditions needed for denitrification within the manure band. However, 2012 data is not as straight forward. In May 2012 manure was applied on two different dates due to difficult weather conditions. Nitrous oxide emissions trends following application on May 21, 2012 were similar to 2011 (Fig. 5C), however the emissions in response to the manure application to the remaining replicates on May 25, 2012 were similar for injection and broadcasting. The higher emissions with manure broadcasting on May 25, relative to broadcast application on earlier dates, appears to have resulted from frequent rainfall and higher soil water content near the time of the last manure application (Figures 4A, 4B, 5A, and 5B). These observations indicate rainfall increases the overall potential for denitrification from the field and reduces the relative contribution of N2O from manure bands compared to drier soils. The largest emissions from broadcast manure were observed 3 days after the May 25, 2012 application, but at that time most manure-N was probably still in the ammonium form and not susceptible to denitrification. Therefore, the relative greater emissions from broadcast manure with the second 2012 application were likely derived from residual soil nitrate rather than newly added manure- N. Cumulative N2O emissions during the month following manure application show a doubling of N2O from injected manures for the June 2011 and May 21, 2012 application dates, while the increased emissions from broadcast lead to similar cumulative emissions for the two methods with the May 25, 2012 applications (Table 6).


Water data (surface and subsurface) are currently being summarized, particularly with regard to runoff chemistry and hydrology. At the conclusion of this effort, a complete water balance and associated mass balance of N and P will be produced allowing for comparison of runoff, leaching, and atmospheric (N only) losses.

Existing data point to significant trade-offs in N enrichment between the two manure treatments. For instance, results for May 2012 (just after manure was applied) reveal a notable spike in ammonium-N in runoff from broadcast manure relative to injected manure (Fig. 6B), but higher nitrate-N concentrations with injection than with broadcasting (Fig. 6A). These trends suggest greater sorption of ammonium-N when manure is placed below the soil surface. In contrast, both ammonium and nitrate-N concentrations tended to increase in subsurface flow from plots where manure was broadcast (Fig. 6C and D). These greater N concentrations with broadcast manure were unexpected and may be related to the rodent burrows and other preferential flow pathways which have since been sealed.


Late season stalk nitrate test provides a season-long indicator of N sufficiency in corn production. When determined 2012, stalk nitrate concentrations were approximately 5-fold greater in injected plots (Fig. 7), highlighting greater nitrogen uptake and providing evidence of greater nitrogen use-efficiency and storage in the injected plots. However, corn silage yields were similar for the two manure application treatments, indicating both manure application methods provided adequate N at the manure application rate used. This suggests that lower manure application rates could be used with injection while still providing the crop’s N requirement. The substantially greater stalk nitrate levels with injection also indicate that much of the N conserved by reducing NH3 volatilization remained available to the crop and was not lost to denitrification or leaching.

Grain Rotation: Weed Management & Yields


The 2011 growing season marked the first comprehensive comparison of the weed management programs. The two treatments were compared primarily in the GRAIN rotation. The “Standard Herbicide” (SH) treatment utilized broadcast herbicide applications to manage weeds in corn grain, soybeans, and alfalfa. The “Reduced Herbicide” (RH) treatment combined banding herbicide, rolling a cover crop with a roller crimper to form a weed-suppressive mat, using a high-residue cultivator for weed control in corn and soybeans; and planting companion crops for weed suppression when establishing an alfalfa-orchardgrass mix (Fig. 1). The SH alfalfa was seeded to only alfalfa as a forage; RH alfalfa was seeded to alfalfa, orchardgrass, triticale (x Triticosecale), and peas (Pisum sativum L.) as forage species. In addition, in the RH treatment, alfalfa was terminated with a moldboard plow before planting canola, while no-till and herbicides were used to terminate alfalfa in the SH treatment (Fig. 1).

To quantify weed severity and treatment effects, weed density and biomass were collected throughout the growing season. Weeds were sampled both from the resident weed population and from subplots within the crop plots that were supplemented with three weed species (giant foxtail (Setaria faberi Herrm.), smooth pigweed (Amaranthus hybridus L.), and common ragweed (Ambrosia artemiisifolia L.), each at a rate of 1500 seeds per m2, in fall of 2010 and 2011. Weeds in corn grain, soybean, and canola were sampled for density at 4 and 8 weeks after planting, and then for biomass at 12 weeks after planting. Weed density was measured by identifying and counting weeds in two randomly placed 0.7 m2 quadrats from the resident weed population and/or from supplemented weed subplots. Weed biomass was sampled by collecting above-ground weed biomass from two randomly placed 2.48 m2 areas between crop rows from resident weeds (0.7 m2 quadrats in weed subplots), drying the samples at 60?C for at least 48 hours and weighing. For alfalfa, sampling occurred at the time of alfalfa harvest. Weeds in forage crop entry points were quantified by separating aboveground biomass into forage and weeds, weighing dry biomass, and calculating percent composition of each within the forage crop. Weed species were separated by species, and also into four categories by life cycle: annual broadleaf, annual grass, perennial broadleaf, and perennial grass. Crop yields were collected for each crop entry point in the GRAIN rotation in 2010, 2011, and 2012; data was analyzed with a split-plot, mixed ANOVA model with PROC MIXED of SAS. Forage crop yields by cutting were analyzed with a repeated measures split-plot, mixed ANOVA model.


In 2010 and 2012, but not in 2011, the weed management comparisons, reduced herbicide (RH) and standard herbicide (SH), were significantly different across crop entry points in the GRAIN rotation (2010: p = 0.008 and 2012: p = 0.002; Table 7). In all three years, a ‘weed management x crop interaction’ significant effect was observed (Table 7), mainly due to differences in the forage crop entry points.


In 2010, pure alfalfa in the SH treatment yielded more than alfalfa with companion crops in the 1st and 3rd year forage crop entry points (1st year: p=0.001; 3rd year: p=0.001; Fig. 8). For the 1st year forage crop entry point, this is likely due to the fact that although alfalfa, pea, triticale, and orchardgrass in the RH treatment had a higher yield than the pure alfalfa in the SH treatment in the 1st cutting in May (p=0.013; Fig.8), we decided not to harvest a third cutting in the RH treatment in fall. The pea and triticale companion crops had suppressed the alfalfa and orchardgrass to the extent that growth by the perennials was reduced that year. For the 3rd year forage crop entry point, we terminated the crop before a third cutting was taken in the fall to plant winter canola. It appears that the SH alfalfa alone treatment yielded better than the RH, alfalfa and orchardgrass, because the alfalfa produced more in mid-summer than the cool-season orchardgrass, and there were no fall harvests where orchardgrass could have contributed higher yields. Supporting this hypothesis is the fact that there were no significant differences between the RH and SH treatments in the 2nd year forage crop entry, which did include fall harvests.

In 2011 and 2012, reducing the seeding rate of pea/triticale from 39+78 kg*ha-1 to 34+34 kg*ha-1 improved alfalfa-grass recovery in the second and third harvests. In 2011 and 2012, the RH alfalfa and orchardgrass with triticale in the 1st year crop entry point yielded more annually than the SH treatment (2011: p=0.020; 2012: p=0.043; Table 7). In the new seeding, the companion crops of pea and triticale, with the alfalfa and orchardgrass in the RH treatment yielded 7.5 times more than the pure alfalfa in the 1st cutting in May 2011 and 4 times more in June 2012 (2011: p=0.001; 2012: p=0.001; Fig. 8) and although the reverse was true for the June cutting, pure alfalfa in the SH treatment yielded only twice as much as alfalfa + orchardgrass in the RH treatment in 2011 (p=0.005; Fig. 8) and 1.7 times as much in 2012 (Fig. 8). We also chose to harvest a 3rd cutting in both RH and SH treatments in the fall, and there was no difference in yield between weed management treatments. while the reverse was true in the 3rd year forage crop entry (p=0.026; Table 7) We also chose to harvest a 3rd cutting in both RH and SH treatments in the fall 2011 and 2012, and there was no difference in annual yield between weed management treatments. Thus, as seen the previous year, the companion mix did a nice job suppressing weeds in the first cutting, but it also slightly suppressed alfalfa-orchardgrass growth in subsequent cuttings. The weed component of the forage was the same across weed management treatments at all cuttings in 2011 and at the first harvest in 2012, but was greater in the RH treatment in the second, third, and seasonal total compared to the SH herbicide-based treatment in 2012 (Fig. 8). In 2012, this enabled some weeds to recover after the initial harvest and persist for the remainder of the establishment year. Finally, forage quality was lower for some cuttings during the establishment year with the companion mix compared to pure alfalfa, which was more likely due to the difference in forage composition rather than weeds since the proportion of weeds was similar across most cuts in most years (Table 11; Fig. 8). To reduce the suppression we have observed of alfalfa establishment by the peas and triticale, enhance alfalfa’s regrowth, and compete with weeds during the typically dry warm July weather when leafhopper pressure tends to be high, we have decided to remove the peas from the companion crops and only use triticale beginning in 2013.


For the 3rd year forage crop entry point, we terminated the crop before fall cuttings were taken to plant winter canola. Similar to 2010, alfalfa in the SH treatment for the third year forage crop entry yielded more annually in 2011 and 2012 due to the better growth of alfalfa as compared to orchardgrass in mid-summer (2011: p=0.026; 2012: p=0.003; Table 7). In August 2011, for instance, the alfalfa + orchardgrass yielded ~50% less than pure alfalfa in the SH treatment. One difference in 2012 compared to 2010 and 2011 is that the SH alfalfa yielded more than the RH alfalfa in the second year forage stand (p=0.005; Fig. 9). Even though we took 5 cuttings of RH alfalfa and only 4 of SH alfalfa, SH alfalfa significantly out yielded RH alfalfa for every cutting, except for July. In May, an early cutting of alfalfa and orchard grass was taken to improve forage quality and in June, an early cutting of alfalfa and orchard grass was taken in response to leaf hopper pressure that was above economic thresholds.


Cereal rye biomass in 2011 ranged from 0.3 to 0.5 Mg*ha-1 in corn and 3.5 and 4.4 Mg*ha-1 in soybean (Tables 8 and 9). In corn grain and soybean, weed density and biomass were higher in the RH treatment as compared with the SH treatment. Weeds that emerged in the RH soybean crop row were not controlled with the cultivation, but those weeds between rows were controlled. Both the post-emergence herbicide application in SH corn and soybean and the inter-row cultivation in RH reduced the number of weeds. Grain yield did not differ between weed management treatments when analyzed with both crops in the model (Tables 7).

When individual crop yields were analyzed, the SH soybean yield was 0.6 Mg*ha-1 more than the RH soybean in 2011 (Table 9). Although the drilled SH soybean initially established poorly in May 2011 (106,250 plants*ha-1 when desired population was 370,650 plants*ha-1), the SH soybeans were replanted in early June, and when combined with post-emergence glyphosate, they quickly provided a closed canopy that was competitive with the weeds. The RH soybean were planted in 76 cm rows about 10 days after the SH soybean and used banded herbicide at planting and inter-row cultivation for post-emergence weed control. We can only speculate why RH yield was reduced, but increased rye cover crop biomass and delayed planting, wider row spacing, lower soybean population and less effective weed control may have all contributed to the lower RH soybean yield compared to SH soybean. The drilled soybean in the CORN-SOY rotation was similar to RH soybean (Table 13). Planting date of CORN-SOY soybean was more similar to that of the RH soybeans, further suggesting that yield was related to planting date as well as row spacing and population and less impacted by weed management.

In 2012, an additional split that included a comparison between 19 and 76 cm row spacing (7.5 and 30 inch) was included in the SH treatments to assess if soybean row spacing might contribute to treatment yield differences we observed in 2011. In addition, to improve soybean establishment in heavy crop residue, some farmers have transitioned using a no-till drill set at 19 cm row spacing to using a no-till planter with wider rows (76 cm or 38 cm). Cereal rye biomass in the SH treatments ranged between 4.5 and 4.9 Mg*ha-1 at termination (Table 9). In contrast, cereal rye biomass in the RH treatment which was terminated 21 days later produced 7.9 Mg*ha-1 dry matter (Table 9). Achieving the targeted soybean population of 480,000 plants*ha-1 was again a problem. The drilled SH soybean were again reseeded which helped achieve about 290,000 plants*ha-1. This was significantly higher than the 76-cm row soybean which were about 152,000 and 111,000 for SH and RH management, respectively. This was only 23 to 32% of the targeted population. Cold wet soil, cover crop residue, and slug damage likely reduced soybean population in 2012.
There was no difference in weed control due to weed management and control was excellent in both the SH and RH treatments with late season weed biomass of 1.2 g*m-2or less (Table 9). However, soybean yield was influenced by SH versus RH management with the highest yield in the SH drilled soybean, intermediate in the SH 76-cm rows, and lowest in the RH 76-cm rows. The RH yield was significantly less than the SH drilled soybean. Weed competition did not influence yield, but poor soybean population (perhaps limited by residue interference and slugs) and possibly inter-row cultivation (RH soybean only) lowered grain yield. We can only speculate, but the dry mid-summer weather combined with inter-row cultivation may have helped deplete key soil moisture reserves and reduce grain yield compared to non-cultivated treatments.

In 2012, weed control was good in both SH and RH corn although weed biomass was higher in the RH compared to the SH treatment (15.7 vs. 0.3 g*m-2) (Table 8). This level of weed biomass is generally not sufficient to impact corn yield. Corn grain yields for 2012 were not impacted by weed management (Table 8).

In summary, over the three years, weed control in soybean was either equivalent or better in SH vs. RH management. Only in 2011, was weed biomass greater in RH vs. SH management, although end of season dry matter levels were still less than 100 g*m-2. Achieving adequate soybean plant populations proved to be problematic in two of three years and drilled soybeans were reseeded in both 2011 and 2012. Soybean populations in 76 cm rows were reduced in 2012. Soybean grain yield was reduced in 2011 and 2012 in RH management compared to SH 19-cm row soybean. However, differences in weed control were likely not responsible for the differences in observed yield, but rather reduced soybean population, differing planting dates, and depleted soil moisture reserves resulting from inter-row cultivation may have contributed to these differences.

For corn, weed control was better in SH vs. RH management in one of three years, although weed biomass never exceeded 21 g*m-2, generally not enough to impact yield. In fact, corn grain yields were equal in SH and RH management all three years indicating that differences in weed management did not impact yield.


The winter canola crop that was planted in fall of 2010 and 2011 followed either alfalfa (SH), terminated with herbicide, or alfalfa and orchardgrass (RH), terminated by a moldboard plow. There were no subsequent weed management tactics applied in canola; however, half of the canola in each of these treatments was planted with oats. There were no differences in treatments differences applied to the 2010 spring canola planted in the grain rotation and harvested in summer 2010. In 2011, no difference in canola yield was detected between SH and RH treatments for winter canola. In 2012, winter canola yield in the plowed RH treatment was greater than in the no-tillage SH treatment (p=0.045; Table 7) due to poor establishment and slug pressure in the no-tillage canola plots. Weed biomass was sampled immediately following canola harvest in 2011, and there was no difference in weed biomass between SH and RH canola crops. There also was no difference in weed biomass between canola alone and canola plus oats, under either main management. Because winter canola grows and develops a canopy before many important weeds in the spring, it successfully competed with the weeds. In 2012, since slug damage decimated plants in two experimental blocks in the SH treatment, we lacked a good comparison of weed pressure for RH and SH treatments.


The RH treatments lowered herbicide inputs in corn and soybean by banding the herbicide over the crop row and supplementing with inter-row cultivation and using a companion crop (triticale + pea) in alfalfa compared to a post-emergence herbicide. With one exception, all crops were no-till seeded, so the burndown herbicide program was the same across SH and RH treatments. The exception was canola which was either no-tilled (SH) or seeded after plowing, disking, and field cultivating (RH). To summarize, the reduction in herbicide active ingredient in RH alfalfa, canola, soybean, and corn was 60, 100, 33, and 48% compared to SH management respectively. Across the six-year cropping system, a total of 12.8 vs. 7.4 kg*ha-1 active ingredient was applied in the SH and RH treatments. Overall, RH management used about 42% less active ingredient compared with the SH management (Table 10).

Grain Rotation: Forage and Feed Quality

For the majority of crop entry points, we found no significant differences between main management treatments for % CP, % NDF, or NEL (Mcal/lb) for all crops in the GRAIN rotation in 2010 (Table 11A), 2011(see Table 10 in 2011 Annual Report) and in 2012 (Table 11B). The exception in 2011 and 2012 in the GRAIN rotation is for the forage crop entry points. This is because in the ‘reduced herbicide’ alfalfa, orchardgrass, pea, and triticale are planted in year 1, with pea and triticale removed after the first cutting and leaving an alfalfa + orchardgrass mix as compared to pure alfalfa in the ‘standard’ herbicide management. In addition, differences in weed pressure (Fig. 8), may contribute to differences we found in forage quality in the GRAIN rotation. For detailed information regarding differences in forage quality by cutting for 2011, please see the annual report for that year. In 2012, for the new seeding, significant interaction effects between main management and harvest month were found for % CP (SH > RH in June; p=0.0005), % NDF (SH < RH in June and July; p=0.002), and NEL (SH > RH in June; p=0,0043; Table 11B). In 2012, for the 2nd year stand, significant interaction effects between main management and harvest month were found for % CP (SH > RH in July; p=0.0045), % NDF (SH < RH in July; p<0.0001), and NEL (SH > RH in May and August; p<0.00; Table 11B). In 2012, for the 3rd year stand, % CP was larger for SH pure alfalfa than RH alfalfa + grass (p=0.0107) and % NDF was lower for SH than RH (p=0.0437; Table 11B). Aside from forage quality differences found in the GRAIN rotation, the forage and feed quality analyses indicate that the sustainable management practices (IM, RH) we use in our cropping rotations do not result in a reduction in crop quality compared to using more standard management practices (BM, SH).

Across Rotations Yields:


We have a number of opportunities to make comparisons among our two diverse rotations (GRAIN and FORAGE rotations) and the one low-diversity rotation (C-S rotation) (Fig. 1). In 2010, there were no rotation history differences and no differences in canola yield between the rotations or the main management comparisons nested in the FORAGE or GRAIN rotation (Table 12). In 2011, however, canola in the GRAIN rotation yielded 26% more than in the FORAGE rotation (Table 12). In the GRAIN rotation, canola was planted after alfalfa as opposed to after corn silage in the FORAGE rotation, and although 10 T/A more dairy manure was applied after the corn silage, it appears that more N was available and taken up by the canola from the alfalfa N in the GRAIN rotation. This is supported by the observation that at flowering, canola plant tissue N levels in the grain rotation averaged 2.41% versus 2.15% in the Forage rotation. Sufficient N levels for canola at flowering have been reported as 2.4% by the Council of Canada, Chapt.9: Soil Fertility and Canola Nutrition (; accessed: June, 2011). Unlike in 2011, canola yields in the GRAIN and FORAGE rotations did not differ from one another in 2012 (Table 12). This is likely due to the high variability we had in the GRAIN rotation where canola yields in blocks III and IV in the SH treatment were zero due to poor establishment in fall 2011 in the no-tillage treatment, where seedlings emerged but high slug feeding and very few days with sun for plant growth appear to explain the winter canola crop failure. Canola yields were also limited in 2012 due to unseasonably warm temperatures in March that caused plants to flower at an unusually early stage of development in the first week of April.

Canola oil production (gallons/acre) in 2011 and 2012 was also lower
in the FORAGE rotation compared with canola in the GRAIN Rotation (Fig. 10). In total, the FORAGE rotation produced 11,877 liters of canola oil in 2011 and 8801 liters in 2012, while the GRAIN rotation produced 15,133 liters of canola oil in 2011 and 11,828 liters in 2012. Canola oil production was influenced by main management treatments as it paralleled canola grain yields in 2011 and 2012. Since canola yields were lower than we anticipated in 2010 and 2011 in both rotations, we sampled the seed lost prior to harvest with shatter sampling boxes placed in the canola stands and during combine harvesting by collecting all seed lost from within two 1/8 m2 quadrats in each canola plot. In 2011, yield losses that occurred during harvest were significant (35-40%). Through research and a series of combine and harvest operation adjustments in 2012, we reduced canola seed loss in 2012 to 29% when winter canola was harvested, and then further with additional combine adjustments to 14% when spring canola was harvested later.


For corn grain yields in 2011 and 2012, there were no significant differences between main management comparisons nested in the GRAIN or C-S rotation (Table 13). Interestingly, corn grain yields were significantly higher in the GRAIN rotation compared to the C-S rotation in 2011 (p=0.01; Table 13), as indicated by a ‘Crop(Rotation)’ interaction effect when all corn and soy grain crop entries points were included in the nested split plot ANOVA model. This same trend was not found, however, in 2010 or 2012 (Table 13). When the corn grain yields in the C-S rotation were compared on their own, there was no significant difference between manure management strategies in 2010 or 2012, while yields in the inject manure (IM) strategy were higher than in the broadcast manure (BM) strategy in 2011 (p=0.037; Table 13).

For soy grain yields in 2010, 2011, and 2012, there were no significant differences between main management comparisons nested in the GRAIN or C-S rotation (Table 13). In 2012 only, however, the yields of both corn and soybean in the SH treatment were higher than the RH treatment (p = 0.05; Table 13). This effect was mainly driven by the lower soybean yields in the RH compared with the SH treatment (Table 7) because corn grain yields compared along with a pre-planned contrast were not significantly different between RH and SH (Table 7). This same comparison was not made in 2010 because the experiment had just begun and there was no legacy from main management strategies to compare. When the soy grain yields in the C-S rotation were compared on their own, there was no significant difference between manure management strategies in 2010, 2011, or 2012.

Across Rotations: Insects and Slugs

In 2012, we continued to assess the influence of crop management strategies on insects and slugs in the Sustainable Dairy Cropping Systems Trial. Because all of the treatments (e.g. cover crops, prior crops, etc.) have now been in place for two years, we were able to measure the accumulated impact of the diverse rotations on populations of pest and beneficial invertebrates. For detailed information on pest management in 2010 and on pest populations and management in 2011 and 2011, please see the annual reports for those years. As in 2010 and 2011, we implemented scouting protocols to guide IPM decision-making for key pest species including potato leafhopper in alfalfa and early-season pest species attacking corn and the later-occurring European corn borer. To continue building knowledge about slug biology and management, we again monitored over 160 shelter traps in corn, alfalfa, and canola over the growing season. Finally, we measured the influence of management practices on beneficial invertebrates in two ways: 1) using 160 pitfall traps in corn and alfalfa plots, and 2) using sentinel caterpillars to measure the ecosystem service of predation.


Our efforts to implement IPM in the experiment provided an opportunity to assess the impact of our cropping strategies on the incidence and severity of a variety of pest species attacking a diversity of crops species. In alfalfa, potato leafhoppers remain a challenging pest. In the grain rotation, as was seen in 2011, newly established alfalfa-grass stands with a nurse crop hosted slightly lower potato leafhopper populations than alfalfa-only stands (Fig. 11A). A similar effect was not evident in the second-year stands; in fact, the opposite pattern emerged with leafhoppers more abundant in the alfalfa-grass mixtures (Fig. 11B). It is not clear why alfalfa-grass plots in the forage rotation experienced higher leafhopper populations. We hypothesized that natural enemy populations would build in these more diverse plots and help suppress leafhopper populations; however, 2012 was a particularly high leafhopper year and all the alfalfa plots, whether mixed with other species or not, generated economically significant populations that in June needed to be harvested early and/or treated with an insecticide.


In corn, true armyworm caterpillars inflicted significant, early-season damage. True armyworm tends to damage crops annually in Pennsylvania, typically in isolated fields where small grain cover crops are not killed at least two weeks prior to corn planting. In contrast, true armyworm populations in 2012 were remarkable and overwhelmed untold fields, even those that used best management practices. Much of central and western Pennsylvania and western New York suffered from a widespread outbreak of true armyworm caterpillars in corn and grass hay fields. At our site, we had significant infestations of true armyworm caterpillars in corn plots in the grain rotation, where corn followed a rye cover crop. Smaller populations developed in the forage rotation where corn silage followed red clover, but these lower populations did not require treatment. Similar high populations did not infest corn in the control rotation, likely because these plots did not host the grassy vegetation where adult moths prefer to lay their eggs. The high populations in the grain plot clearly exceeded economic thresholds and required treatment with an insecticide. To adhere to the principles of IPM, we applied a selective insecticide, Intrepid 2F, that has activity only against caterpillar species. The active ingredient in this product is a new type of insect growth regulator which causes caterpillars to molt early and die, but importantly is benign to the predators and parasitoids we are trying to conserve with our diverse rotations.

Black Cutworm and European Cutworm

A more typical annual threat to corn plants is black cutworm and European corn borer caterpillars. Black cutworm caterpillars are damaging because they cut down corn seedlings at soil level. In 2012, we found damage from cutworms to be equal across the three rotations (Table 14). As with populations in 2010 and 2011, cutworm damage at growth stage V5 was mild and well below the economic threshold of 7% cut plants. Damage from European corn borer, which feeds in the stems of corn plants, disrupting vascular transport and weakening stems, was low in 2012, as it was in 2010 and 2011. As expected, corn borer damage was greater in the non-Bt corn in the forage and grain rotations than in the transgenic Bt corn in the control corn-soy rotation (Fig. 14). However, in both rotations corn borer damage was low (~1.5 tunnels per plant) and would not be expected to reduce yield.


As with previous years, we continued to build knowledge about slugs, which are the most consistent and challenging invertebrate pest that we have faced in the project. Surprising little is known about the life history and ecology of slugs in field crops, so our project is providing some valuable insight on these uncharismatic mollusks that often get ignored in traditional field experiments. Unlike spring2011, when slug populations were relatively low, slug populations in 2012 were substantial. Significantly, winter of 2012 was much warmer than average possibly allowing more adult slugs to survive until spring. Spring 2012 was also warmer than normal permitting slugs to be active much earlier than normal. Moreover, May was quite wet, providing perfect conditions for slugs. Together these factors contributed to slug populations that were quite high and problematic.

As we saw in previous years, the gray garden slug (Deroceras reticulatum) was again the dominant slug species at our site in 2012, especially during times of crop establishment in spring and fall. In alfalfa, gray garden slugs in spring peaked in abundance in mid-May, and then after their summer quiescence, populations grew even further in fall (Fig. 13A). Notably, the fall population peak in alfalfa was about two times the spring population peak, reflecting ample cover and food sources in alfalfa fields. In corn, slug activity-density peaked in May and June and did not have a similar fall peak (Fig. 13B). In 2012, higher slug population peaks in both spring and fall were observed in the new alfalfa seedings than in 2010 and 2011 in the GRAIN Rotation, possibly due to the preceding mild winter (Fig. 13C). This higher than typical slug-activity density correlates with crop damage and crop establishment failure observed in 2012 (see below).

Due to the high slug populations, nearly 100% of plants in corn plots in the control rotation had slug damage by the V2 and V5 grow stages, but fewer plants in the forage and grain rotations were damaged, though this difference was not statistically significant (Table 15). Similarly, corn plants in the control rotation had higher amounts of damage at V2 than the two diverse rotations, but this difference also was not statistically significant. This equivalent damage among the three rotations conflicts with our hypothesis that the diverse rotations should receive less herbivore damage compared to the high input control rotation. It may be that the generally high slug populations experienced in 2012 overwhelmed any higher natural-enemy populations resident in the diverse rotations. Heavy slug damage suffered by all the corn plots could contribute to lower stand establishment.

In fact, 2012 corn establishment in the forage plots was significantly lower than establishment in the two other rotations (Table 16). However, given that the percentage of plants damaged, as well as the damage to individual plants, was similar between the two diverse rotations and less than the damage seen in the control rotation, it is likely that some other factors contributed to the poor establishment of corn in forage plots. For instance, the corn in the forage rotation following red clover or alfalfa + orchard grass was planted on 18 May and 7 June respectively, while the corn in the grain and corn-soy control rotations was planted on 1 May. It is possible that more slugs had hatched and were actively feeding by 18 May and that the difference in planting date explains differences in slug damage.

Within the forage rotation, slug damage to maize following the two cover crops, hairy vetch and red clover, was equivalent at both the V2 and V5 growth stages for the percentage of plants damaged and damage to individual plants, although these indices were significantly higher after hairy vetch in 2011 (Table 17). In 2012, however, corn population numbers were lower following hairy vetch than they were following red clover (Table 17), which may have contributed to lower corn silage yields following hairy vetch compared with corn following red clover (Table 5). This difference might suggest a difference in slug preference for hairy vetch residue as compared with red clover residue, and suggests future research may be merited. Corn populations following alfalfa in the FORAGE rotation were also low (50,543 plants/ha) but this value fell between population numbers following either red clover or hairy vetch.
Also partly due to high slug populations, we failed to establish alfalfa plus orchardgrass in fall 2011 and in spring 2012 following canola (Table 18). It is possible that allelopathy from canola residue may have inhibited alfalfa and grass seedling growth since it was shown to reduce yields in corn by our team member, Roger Koide (unpublished data). In 2011, we replanted half of the alfalfa and grass crop after canola due to crop failure.


In addition to our efforts to measure pest populations, we tested the influence of our treatments on natural enemies and the predation services they provide. In 2012, we collected pitfall trap samples in corn and alfalfa plots on seven occasions spread over the season. We are in the process of sorting and identifying these samples (no small task), and expect them to provide valuable information on treatment effects on natural enemies. In addition, we measured predation on sentinel waxworm caterpillars in corn plots in all three rotations in May, July and August. Each plot received 32 pinned caterpillars, half under exclusion cages (allowing access by arthropods only) and half open to vertebrates (e.g., mice, birds) as well as arthropods. In late May, predation in the uncaged treatment during the day was significantly lower than the two complex rotations than in the control rotation (Fig. 14A), and our observations suggested that birds (e.g., robins) were more active in the diverse plots. At night, more uncaged waxworms were killed in the grain rotation, suggesting that mice were more active in those plots (Fig. 14B). In the caged waxworm treatments, which should reflect activity of arthropod predators, predation was equivalent during day and night (Fig. 14C and D), suggesting that early in the season the natural enemy populations were equally effective.

Our results for the July sentinel prey experiments were very similar to the August results, thus we share the details of only one month. In August, predation in the uncaged treatments was somewhat similar after 12 hr of exposure during day and night (Fig. 15A and B), suggesting that vertebrates (birds and mice) were more or less equally active in all the plots day over 24 hr. For caged waxworms during the day, predation by arthropods was similar across rotations (Fig. 15C), but as we saw in 2011, at night the diverse rotations received a stronger predation service than then the control plots (Fig. 15D) and our observations indicate that nocturnal arthropods were responsible for killing waxworms. Dominant arthropod predators included ground beetles (esp. Pterostichus melanarius), ants, wolf spiders and harvestmen. The reduced predation in the corn-soy rotation may have been a lingering influence of a typical at-planting insecticide treatment that was not used in the other rotations, and/or it may have been related to the lack of residue in the corn-soy rotation, providing poor habitat for natural enemies.


Our results thus far across year continue to support the hypothesis that diverse crop rotations using conservation practices and IPM can reduce the need for insecticides while preventing economic damage to crops. In the forage and grain rotations, the only crops to receive insecticide sprays in 2012 were alfalfa, for potato leafhoppers and a few corn grain plots to manage the extreme regional outbreak of true armyworms. While infestations of this latter pest are far from typical, potato leafhopper populations are annual risks. To reduce the number of sprays for this pest, we used regular scouting and early cutting whenever possible to manage leafhopper populations. As a result we were able to spray only once over the season and maintain forage quality (Tables 4 and 11), contrary to the common practice of spraying shortly after each cutting. In the future, we plan to further reduce our insecticide use in alfalfa by planting a potato leaf-hopper resistant variety of alfalfa (selected via traditional breeding not via transgenic breeding). Marvin Hall, the Penn State forage extension specialist informed us that the variety has been improved over time and no longer has a yield lag compared to conventional varieties; seed cost is also similar. In corn, we compared our diverse rotations with a simple corn-soy rotation reliant on pre-emptive pest management practices. In the corn-soy rotation, the use of transgenic Bt corn and an at-planting pyrethroid insecticide did not result in tangible pest control benefits relative to the forage and grain rotations. In fact, at-planting insecticides may have been counter-productive, if they contributed to low predation services by arthropods in July and August, and high slug populations in the fall. Continued data collection in this system will allow us to test this concept further. We also used untreated seed for our corn and soybean crops in the complex rotations, while using treated seed for the corn and soybean in the Control rotation in 2012. We did this because we were concerned with the possibility of indirect effects on beneficial insect populations from slugs feeding on systemic seedlings from treated seeds. We plan to continue using untreated corn and soybean seed in the coming years of the project. Slugs continue to be the least manageable pest in our system, particularly in fall crops. We hope to use what we have learned so far to further modify these systems to avoid slug problems. For instance, planting canola earlier in late summer rather than fall may allow plants to become established before slug pressure is heavy.

Across Rotations: Mycorrhizae


In 2010, to determine if the genetically modified corn used in the experiment had an impact on mycorrhizal colonization we compared sister varieties of conventional and genetically modified corn. The genetically modified corn was pioneer variety 35F48AM with HXX, LL, and RR2 traits. The conventional and genetically modified corn varieties were planted in paired locations and were harvested approximately 10 days after germination to assess colonization. Colonization rates were compared using a paired t-test. There was no difference in the colonization of the two varieties by arbuscular mycorrhizal fungi (p = 0.25).


In the summer of 2011, all corn entry points in the grain, forage, and corn-soy rotations were sampled to determine if there was an overall impact of rotation and management on mycorrhizal colonization. In all plots, corn seedlings were harvested at the third leaf stage and assessed for arbuscular mycorrhizal colonization. Colonization data was analyzed using a split plot ANOVA with rotation and block as factors. Colonization of corn plants in the corn-soy rotation and the grain rotation were reduced compared to the two corn silage plots (following alfalfa in one case and red clover or hairy vetch in the other) in the forage rotation (Fig.16; p = 0.01). The reduction in colonization observed in the corn-soy rotation and the grain rotation plots is likely the result of field management the prior winter. The plots in the corn-soy rotation were left fallow and the plots in the grain rotation had a rye cover crop over the winter. Rye does not form strong mycorrhizal associations, so in both of these scenarios the mycorrhizal fungal populations may not have been supported over the fall and winter. Conversely, in the forage rotation, corn silage plots had legumes present in fall and winter and some since the prior spring. Specifically, one crop entry had alfalfa and orchardgrass growing the prior year, fall and winter; the other had either red clover present since the prior spring or hairy vetch present since fall. Each of these legumes form mycorrhizal associations and likely supported the fungal populations over the winter resulting in the higher levels of trap plant colonization that we observed.


In 2012, we successfully assessed the impact of increasing the diversity of mycorrhizal crops planted during a single crop entry point. Specifically, within the grain rotation we compared the inoculum potential of arbuscular mycorrhizal fungi in the split plot treatments of first and second year alfalfa entry points. The split plot comparison in the first year of alfalfa was between alfalfa (1 mycorrhizal crop) and alfalfa, orchard grass, triticale, and pea (4 mycorrhizal crops). The split plot comparison in the second year of alfalfa was between with alfalfa (1 mycorrhizal crop) to split plots with alfalfa and orchardgrass (2 mycorrhizal crops). This experiment was attempted in 2010 and 2011 but we had been unable to complete it due to delayed harvest (2010) and drought (2011).

To assess the inoculum potential of alfalfa plot within the grain rotation, corn bioassay plants were planted from seed in all plots in 2012. The trap plants were harvested approximately ten days after germination and assessed for percent colonization, shoot dry weight, shoot phosphorus concentration, and shoot nitrogen concentration. Data was analyzed using a split plot ANOVA with rotation and block as factors. When comparing treatments in the first year alfalfa plots, we found no difference in colonization (Fig. 17A, p = 0.278), shoot dry weight (Fig. 17B, p = 0.979), shoot phosphorus concentration (Fig. 17C, p = 0.954) and shoot nitrogen concentration (Fig. 17D, p = 0.872) between split plots with 1 mycorrhizal crop and split plots with 4 mycorrhizal crops.

Unlike the first year alfalfa plots, there were treatment effects in the second year alfalfa plots. The difference between the treatment effects in the first and second year stands of alfalfa might be explained by the increased length of time that inoculum potential had to build up in the second year stands compared to the first year stands. In the second year stands of alfalfa, bioassay plants in split plots with two mycorrhizal crops were colonized to a greater extent than bioassay plants in split plots with a single mycorrhizal crop. (Fig. 18A, p = 0.008). One possibility for this finding is that the two crops planted may form associations with different complements of arbuscular mycorrhizal fungi. In this case, each host plant would help build the inoculum potential of different fungal species. A second possible explanation is that increasing the overall number of host species increases the probability of finding a strong host for the existing fungal community. Despite the difference in percent colonization of bioassay plants harvested from split plots with 1 mycorrhizal crop and split plots with 2 mycorrhizal crops, there was no difference in bioassay plant weight (Fig. 18B, p = 0.078) or bioassay plant phosphorus concentration (Fig. 18C, p = 0.803). However, there was a difference in bioassay plant nitrogen concentration. Bioassay plants in split plots with 1 mycorrhizal crop had a higher nitrogen concentration than those in slit plots with 2 mycorrhizal crops (Fig. 18D, P = 0.031). This is likely related to increased legume biomass in pure alfalfa stands compared to mixed alfalfa – orchardgrass stands.


Canola is a non-mycorrhizal crop and has been shown to reduce arbuscular mycorrhizal fungal populations and their ability to form associations with subsequently planted crops. Oats, a mycorrhizal species, were intercropped with canola in an attempt to support mycorrhizal fungal populations. In 2011, we compared the extent of arbuscular mycorrhizal colonization of 10-day old corn bioassay plants grown after canola to those grown after canola and oats. We saw no difference in the colonization of the corn bioassay plants in the canola and the canola plus oats plots (Fig. 19A, p = 0.07). However, there was a reduction in the colonization of the corn bioassay plants in the reduced herbicide treatment compared to the standard herbicide treatment in the canola plots (Figure 3, p = 0.04). The reduced herbicide treatment was tilled with a moldboard plow and this soil disturbance probably accounts for the observed reduction in colonization. The standard herbicide treatment was not tilled.

We continued to follow these plots as they were planted to rye in the September of 2011 and to soybeans in May of 2012 to see if there was a legacy effect of tillage on mycorrhizal fungi inoculum potential. Since rye and soybeans are both arbuscular mycorrhizal fungi host species, we sampled rye and soybean seedlings directly approximately 10 days after emergence. Rye roots do not typically become highly colonized by arbuscular mycorrhizal fungi so it was not surprising that average percent colonization in all treatments was below 10 percent and that there was no difference in percent colonization between herbicide treatments (Fig. 19B, p = 0.324). Conversely, soybeans typically have much greater rates of colonization by arbuscular mycorrhizal fungi and the average percent colonization for all treatments was greater than 45 percent. Still, there was no difference in percent colonization of soybean plants between herbicide treatments (Fig. 19C, p = 0.229).

Whole Farm Scale: Energetic Analysis

Penn State’s Farm Energy Analysis Tool (FEAT; was used to quantify the fossil energy inputs of the NESARE dairy cropping systems. Fossil energy inputs quantified include the fossil energy required to: i. produce and transport N, P, K, lime, seeds, herbicides, pesticides, and diesel fuel; ii. dry grain crops, iii. transport grain crops to a regional grain bank, and iv. process canola grain into straight vegetable oil and left-over seed meal. In 2011, for instance, with 40 acres of canola in the virtual farm, 13,835 liters of canola straight vegetable oil were produced, of which 9720 liters are used for tractor-pulled crop operations with 4115 liters excess that can be sold (Fig. 20). Many farmers in Pennsylvania employ custom operators for some crop operations, and so we assumed that our virtual dairy farm will rely on custom operators for manure injection, grain crop combining, corn silage chopping, lime application, and forage crop baylage wrapping and Ag-bagging. Therefore, we can only power 2/3 of our crop operations with our canola straight vegetable tractor. We used FEAT to estimate the tractor fossil energy input of the NESARE virtual dairy farm that includes the ‘Reduced Herbicide’ portion of the GRAIN rotation and the ‘Injection Manure’ portion of the FORAGE rotation as if the farm was completely powered by diesel fuel. Then we assumed that the tractor diesel fuel could be replaced with renewable canola straight vegetable oil and subtracted it from the overall fuel use (Fig. 21).

As a result of growing fuel on farm, the NESARE virtual dairy farm required 20% less fossil energy input for crop operations (Fig. 21).
Additionally, since the NESARE dairy cropping systems and virtual farm are not typical for Pennsylvania, we also used FEAT to estimate the fossil energy inputs, on a milk production basis, for two typical Pennsylvania farms that require fewer hectares to grow ‘Forage + Feed’ (but not fuel) and to grow ‘Forage Only’, for the same sized dairy herd (Table 19). We assumed that the dairy herd received the same total mixed ration on all three farms and produced 34 kg milk cow-1 day-1. The fossil energy inputs per unit of milk produced were similar for the ‘NESARE SVO’ farm and the ‘Forage + Feed’ farm but were 17% higher for the ‘Forage Only’ farm in comparison with the NESARE farm (Fig. 22). As fossil fuel and feed prices continue to rise in the future, growing fuel, feed, and forage on farm rather than importing feed for cows may become a more favorable option.

The Virtual Dairy Farm: Economics of Feeding the Herd

The virtual dairy operation was designed to represent a typical Pennsylvania tie-stall barn for the lactating herd and a bedded pack for young-stock and dry cows. Upright silos and Ag Bags are used to ensile forages. All forages, corn grain, soybeans and canola meal are fed to the herd, as a total mixed ration. Rations for all the animal groups are formulated based on the 2001 NRC model and reflect very closely what is fed to the Penn State Dairy Cattle Research Center dairy herd. The financial evaluation of the virtual farm includes enterprise crop budgets, cash flow plans, and FINPACK year-end financial analysis. The virtual farm is divided into two scenarios: broadcast manure/standard herbicide (BMSH) and injected manure/reduced herbicide (IMRH). The same assumptions regarding the herd size, equipment, and farmstead are constant between the two scenarios. The economic analyses evaluate how feed inventory and forage quality affect the profitability of the virtual farm. These two indicators have significant implications for crop sales and purchased feed costs, which strongly influence if a dairy operation is sustainable and profitable.

The cropping enterprise budgets are used to determine the costs for each crop entry for seed, fertilizer, chemical and custom hire. At the beginning of the project we determined the equipment that the farm owns and what is custom hired based on what is typical for a Pennsylvania farm of this size. Custom field operations costs are based on the Dept. of Pennsylvania annual published regional custom farm rates, and prices of custom operators whom were contacted in the central region of Pennsylvania. All other costs are real as they relate to the prices paid for the planting and harvesting of all the crops grown. For example, Table 20 shows the costs for crops harvested in 2011 and fed in 2011 and 2012. One caveat is that diesel fuel input costs have not been adjusted for a reduction of that due to use of straight vegetable oil grown on farm. We are gathering data to estimate this cost of processing canola grain to straight vegetable oil and meal, and will account for this also.

The cash flow plan ties together all the rations fed to the entire dairy herd, the costs to produce the feeds, and the income and expenses incurred during each year for the virtual farm. Each scenario produced different quality and quantities of feeds that directly impacts feed costs. Actual input costs/ton, for crops fed to the herd, were higher for canola in 2010 and 2011 (Tables 21 and 22) and for forage crops in 2010 (Table 21) compared to market costs/ton for those crops. In the case of canola, this is likely because the market price is for the canola meal only and does not reflect the value of the canola oil and meal that we produced. Canola yields were also lower than expected due to harvest losses which may also explain the higher than expected input cost/ton. In 2010, the higher cost of production for the forages crops reflects the fact that all forage crop entry points were new seedings that were only harvested 2-3 times. Actual input costs/ton for the forages in 2011 and the corn and soybeans in 2010 and 2011 were lower than market costs/ton. (Tables 21 and 22). In both 2010 and 2011, the low input costs/ton for corn and soybeans contribute to making both the IMRH and BMSH profitable.

The cost to produce all the home raised feeds is figured into the lactating cow diet so an accurate feed cost per cow per day can be determined. Based on the milk income, income over feed cost (IOFC) can be calculated (milk income/cow – feed cost/cow = IOFC/cow). This is the amount of money that is left over to pay all expenses minus the lactating cow feed costs. The cash flow plan also determines what the farm’s breakeven IOFC is and if the farm is making or losing money. For instance, in 2011, the feed cost per cow was lower in the IMRH scenario compared to BMSH and coupled with the lower breakeven IOFC, the IMRH showed an additional profit of $0.71/cow (Table 23). The IMRH scenario had the advantage of the production of the alfalfa, orchardgrass, triticale, and pea forage, which was harvested and stored in an Ag Bag. This was used to feed heifers and dry cows freeing up the much needed corn silage that was used to feed only the lactating cows.


The Center for Farm Financial Management (CFFM) at the University of Minnesota produced the software tool FINPACK, which helps guide producers to sound financial decisions. For the virtual farm we developed a balance sheet, an annual cash flow, financial analysis, and a historic database. We will focus on use of the FINAN year-end analysis module for the virtual farm. FINAN provides the tools to conduct detailed analysis of farm financial data and calculate the twenty-one financial measures defined by the Farm Financial Standards Task force. These measures will allow us to compare the financial performance of each scenario across five essential areas: liquidity, solvency, profitability, repayment capacity, and efficiency, and provide a full assessment for all the critical areas that affect farm financial sustainability.

The analysis requires a beginning and ending balance sheet to calculate inventory adjustments and the cash income and expenses for each business year. The cash costs and income are accrual adjusted with the balance sheet data and the financial measures are then calculated for each year of the study. These measures become part of the historical trend analysis for the virtual farm and are also presented graphically to demonstrate trends in financial performance over time.

The historical database will track all financial and production trends of the operation over time. Data is automatically added to the database as each additional year of data is added to the software. The financial measures will provide a complete and accurate assessment of the financial performance of the BMSH and IMRH scenarios over time.

In addition to the financial measures, the software also calculates enterprise budgets on a profit and loss basis for each of the crops and the dairy enterprise. The cash flow spreadsheet calculates the crop production and dairy costs on both a cash flow and a profit/loss basis. Both analyses will complement one another and provide a very complete picture of the virtual farm’s financial progress over time. With this whole-farm economic analysis, we will be able to share profit margins and deficits for both farm scenarios for a long enough period of time to examine whether one is more risky (i.e. not profitable more of the time) or more stable (i.e. profitable more consistently over time).

Impacts and Contributions/Outcomes



The outreach highlight of 2012 year was the June 27 “Strategies for Soil Health and Nutrient Conservation Research Tour” at the Agronomy Research Farm at the Russell E. Larson Agricultural Research Center. We collaborated with two other cropping system projects, ROSE and OREI-CC, to engage participants with hands-on activities and field demonstrations. There were 103 participants including farmers, farmer advisors, government agency personnel, non-governmental organizations, industry, and researchers from other institutions. The participants were split into five groups to tour five hands-on learning stations. One of the five learning stations was “Winning Over Weeds with Cover Crops,” which focused on how to use high-residue cover crops to control weeds without herbicides. Participants learned how much cover crop residue was needed to effectively control weeds as well as how the cover crop C:N ratio affects nitrogen supply and residue persistence. At the “Cover Crop Mixture for Corn Success” station, participants used a chlorophyll meter and a soil nitrate quick-test to collect data on how last winter’s cover crop mixtures were performing at supplying nitrogen to this year’s corn crop. A no-till manure injector was on display at the “Minding Manure to Conserve Nutrients” station and a rainfall simulator demonstrated how manure injection technology can reduce nutrient runoff. At the “Creative Cover Cropping” station Penn State’s newly developed cover crop interseeder was displayed to demonstrate how cover crops could be seeded into a standing corn crop. Other opportunities to integrate cover crops into a crop rotation, such as frost-seeding into small grains and using alternative crop rotations were also discussed. Finally, at the “Power of Predators” site participants learned how to conserve and promote the beneficial insects that naturally contribute to the control of crop pests.

We had a 57% response rate or 59 out of 103 participants. Ninety-eight percent of participants in the field tour rated the tour as good to excellent. Knowledge increased for participants at all 5 stations with a 15% increase for “Improving Manure Management”, a 26% increase for “Nitrogen Supply from cover crop mixtures”, a 34% increase for “Strategies to integrate cover crops and their characteristics”, a 52% increase for “The relationship between a cover crop’s C:N ratio &amp; its persistence”, and a 64% increase for “The value of predators for pest control & ways to increase predator activity”.


In 2012, we met on March 28, 2012 to update the advisory panel on recent project activities, management changes we had made or were considering, and plans for the June 2012 Field Tour and the NESARE Advisory Council July 2012 field tour. The advisory panel member comments were extremely appreciated as the team deliberated some proposed cropping system management changes in our study.


This NESARE Agroecosystems project is one of three sustainable cropping systems research and outreach projects currently underway at Penn State. The project on “Weed Management, Environmental Quality, and Profitability in Organic Feed and Forage Production Systems” (funded by USDA Risk Avoidance and Mitigation Program, or RAMP) project entered its final field season in 2012, while another project began. The “Finding the Right Mix: Multifunctional Cover Crop Cocktails for Organic Systems” (OREI-CCC) experiment seeks to identify benefits and costs of using different cover crop mixtures in organic crop production. The Reduced-Tillage Organic Systems Experiment (ROSE), also funded by USDA-OREI, completed its first full field season in 2011 and is investigating pest and soil management challenges associated with reduced-tillage organic feed grain production systems.

In 2012, the annual TRIAD symposia were held on the Penn State Campus with team members from RAMP, ROSE, and NESARE dairy cropping system projects. In 2012, the team members from OREI-CCC cropping system projects also participated. The symposium is a joint meeting of all faculty, graduate students, and post-doctoral researchers from the cropping systems projects as well as others interested from the College of Agriculture at Penn State. The goal of the event was to share project objectives, methods of investigation, and current results to promote synergy among the teams. Posters were developed and graduate students and post-doctoral researchers gave brief presentations. Brian Caldwell visited from Cornell University to foster synergies across universities. Nearly thirty people attended in 2012: Outcomes from this symposium included a collaborative field day and Ag Progress Days tours in 2012, between two of the project teams.


Conservation practices in our project have been demonstrated for three years on multiple farms through our Natural Resource Conservation Service (NRCS) Conservation Innovation Grant that was funded in summer of 2009. Practices that farmers were most interested to try were shallow-disk manure injection in no-till cropping systems and the cover-crop roller to manage tall cover crops and create a high residue mulch. With funds from the 2009 CIG NRCS grant, shallow-disk manure injection equipment was purchased for four manure haulers to use on cooperating demonstration farms and to promote manure injection on additional farms. Two cover-crop roller crimpers were also purchased for farmers in two counties. The manure haulers in three counties have demonstrated and encouraged shallow disk injection adoption on many farms and the cover crop roller crimper has been adopted for regular use by one farmer. Field days were hosted at the Penn State Landisville Research farm in Lancaster PA and farms in all four counties.

Due to the challenges of very wet weather in recent years and poor soil drainage in the fourth northern tier county, the equipment was not well-utilized, and a no-cost extension of the grant was approved for 2013 for one county. We are making arrangements to move the shallow disk injection equipment in December to an impaired, EPA-targeted watershed in Mifflin and Juniata Counties where farmers have expressed an interest in manure injection. We are also in the process of identifying a location to relocate the cover crop roller crimper. Through the on-farm demonstrations we have learned about factors that may limit shallow-disk manure injection as well as conditions that may increase adoption.

This CIG NRCS project is described on a webpage linked to our NESARE Sustainable Dairy Cropping Systems project website. The website provides information about the four cooperating commercial manure haulers and county extension educators on a series of webpages (See: With the NRCS CIG funds we created internet links to an alphabetically ordered list of extension publications on the sustainable agriculture practices employed in our cropping systems and other relevant information. We also created a webpage with links to short videos of the cooperating farms employing shallow-disk manure injection and the cover crop roller-crimper. Additional videos are being created by a videographer and the cooperative extension educators with funds from a 2010 CIG NRCS grant that is demonstrating cover crop mixtures and manure injection on farms in multiple counties, and involves working with farmer networks to promote adoption of conservation practices.


In 2012, NESARE Agroecosystem and ROSE cropping system collaborated to host a tour at Penn State’s annual Ag Progress Days event on August 14 – 16, 2012. Participants engaged in tours on topics such as “Improving Manure Management” and “Winning Over Weeds With Cover Crops” at two field stations. In 2012, a reporter from Lancaster farmer attended the field tours on the final day and described the NESARE Sustainable Dairy Cropping Systems project. The 2012 article can be found at: The insect &amp; slug management team used data from this project in 12 extension presentations on slugs and slug management. These presentations were attended by 1,083 growers and associated agricultural professionals. Approximately 75 individuals attended the tours.


Our project team continues to make use of our website. It can be found at: As of November 28, 2011, there had been 2600 hits on our website. The website describes the project, the treatments being investigated at our research site, brief biographies of personnel involved, and outreach activities that are being planned (see below), links to the NRCS CIG project, and a list of useful documents and videos including a new handout, called ‘Canola Fueled Tractors’, that was created collaboratively by Doug Shauffler, the researcher and manager of the oil seed pressing at Penn State University, Andrew Kirk, an undergraduate student who worked on our project this summer, and Heather Karsten who mentored Andrew Kirk. Andrew Kirk also created a video in summer 2011 detailing the process of pressing canola seed for oil to run a straight vegetable oil powered tractor, which will be to the website soon when it has been completed with closed captioning. In 2012, the canola pressing video was edited and prepared formerly for the web at:


We also hosted the USDA NESARE Summer Tour for the NESARE Advisory and Management Team for approximately 60 people. One stop on the tour was at Doug Schaufler’s oilseed pressing and processing facility. The tour visited the dairy farm of our Advisory panel member Byron Hawthorne who has, a medium-sized dairy farm, using highly diverse crop rotations to maintain permanent soil cover, seasonal grazing, and no-till practices to balance production, profitability, and environmental stewardship. Then they visited The Harpster’s Evergreen Farm, where Andrew Harpster described how three brothers manage a 2,000 cow dairy and several thousand acres of cropland using no-till, cover crops, and nutrient management, and how they successfully transitioned the herd off of rBST to improve herd health. In the afternoon, field tours were given by the NE-SARE Agroecosystem and ROSE cropping system projects. The tour finished with refreshments and an opportunity to view posters of graduate students whom are part of the NE-SARE Agroecosystem Sustainable Dairy Cropping Systems Project as well as students funded by NESARE Graduate Student Research fellowships.


All teams presented at the June 2012 field days held at the Russell E. Larson Agricultural Center. Additionally, from 2010-2012, each team presented sustainable management strategies and results from our project at grower and professional meetings (see 2011 Annual Report and below). For instance, in 2012, the insect/slug management team used data from this project in 9 extension presentations on slugs and slug management. These presentations were attended by 535 growers and associated agricultural professionals. Also in 2012, project team members presented 14 times to professional audiences. Graduate students working on this project also received awards for presentations of their research from this project.


Canola and Energy Management Team:

Karsten, H.D., W. Verbeten, G. Malcolm, M. Douglas and J. Tooker. 2012. No-till Establishment of Alfalfa and Canola and Slug Herbivory. Proc. Amer. Soc. Agron. 337-25.

Karsten, H.D., Organic Crop Rotation Design. In review for The Organic Agronomy Guide. The Pennsylvania State University.

Malcolm, G., G. Camargo, T.L. Richard and H. Karsten. 2012. Energetic Analysis of a Diverse Dairy Operation, Producing Fuel, Feed, and Forage As Compared to a Typical Dairy Farms of the Same Size. Proc. Amer. Soc. Agron. 187-11.

Malcolm, G., G. Camargo, T.L. Richard, V. Ishler, and H. Karsten. 2012. Energetic Analysis of Dairy Cropping Systems That Use Straight Vegetable Oil Fuel Grown On Farm. Pennsylvania State University Post-doctoral Research Exposition.

Insect/Slug Management Team:

Douglas, M. R., and John F. Tooker. Insights on the ecology and management of slugs in Pennsylvania no-till crop fields. Annual Meeting of the American Malacological Society, Cherry Hill, NJ, 18 June 2012

Lysimeter Team:

Duncan, E. 2011. Nutrient Cycling Trade-offs Associated With Different Manure Management Strategies. Soil and Water Conservation Society Annual Meeting.

Duncan, E., P. Kleinman, C. Dell, D. Beegle, and H. Karsten. 2012. Improving manure management to balance nitrogen use efficiency and environmental trade-offs. Proc. Soil Sci. Soc. Am. 151-11

Weed Management Team:

Curran W. and D. Lingenfelter. 2012. Exploring opportunities to diversify burndown options in no-till crop production systems. Proc. Northeast Weed Sci. 66.

Curran, W. and D. Lingenfelter. 2012. Challenges to diversifying herbicide options in continuous no-till production systems. Abstr. WSSA 56:346.

Keene, C.L. and W.S. Curran. 2012. Effectiveness of shallow high residue cultivation in no-till soybean. Proc. Northeast Weed Sci. Soc. 66.

Snyder, E., H. Karsten, W. Curran and G. Malcolm 2012. Reducing herbicide use in a no-till dairy cropping system. Proc. Amer. Soc. Agron. 200-9.

Snyder, E.M. 2012. Reducing Herbicide Use in a No-Till Dairy Cropping System. Gamma Sigma Delta Student Poster Exhibition, March 2012, University Park, PA.

Snyder, E.M., W.S. Curran, H.D. Karsten, and G.M. Malcolm. 2012. Reducing Herbicide Use in a No-Till Dairy Cropping System. International Soil Tillage Research Organization Conference, Montevideo Uruguay.

Snyder, E.M., W.S. Curran, H.D. Karsten, and G.M. Malcolm. 2012. Evaluating integrated weed management for no-till dairy cropping systems. Proc. Northeast Weed Sci. Soc. 66.


Masters student, Maggie Douglas (Entomology), received the following awards in part for her contributions to the NE-SARE project:

• Outstanding MSc Student in Biological Control Award from the International Organization for Biological Control-Neartic Regional Section
• Legends of Entomology Masters Award from the Plant-Insect Ecosystems section of the Entomological Society of America
• Monsanto Student Travel Award, which was awarded to graduate student presenting invited talks.

Masters student, Emily Duncan (Plant Science), received the following awards in part for her contributions to the NE-SARE project:

• Graduate student poster competition, S-04, Third place. 2011. Presented at the ASA-CSSA-SSSA annual meetings, San Antonio, TX, Oct. 16-19.
• Graduate student poster competition, S-08, First place. 2012. Presented at the ASA-CSSA-SSSA annual meetings, Cincinnati, OH, Oct. 21-24.

Masters student, Elina Snyder (Plant Science), received three travel awards from the Pennsylvania State University to travel to Uruguay to present her NESARE related research: 1. College of Ag. Sciences Tag-Along Award 2. College of Agricultural Sciences Graduate Student Travel Award (Sahakian Fund) and 3. Department Graduate Student Travel Fund (Bernardier Fund).

Post-doctoral researcher, Glenna Malcolm (Plant Sciences), received a travel award from the Pennsylvania State University Post-doctoral Affairs office to present on energetics of the NESARE dairy cropping systems at the 2012 Tri-Society meeting.


Peter Kleinman
Soil Scientist and Adjunct Professor
USDA-ARS-Pasture Systems and Watershed Management
Building 3702, Curtin Road
University Park, PA 16802
Office Phone: 8148653184
Timothy Beck
Extension Educator
Penn State Cooperative Extension
310 Allen Rd. University Park
Carlisle, PA 17013
Office Phone: 7172406500
Craig Altemose
Cooperative Extension Director, Centre & Clinton
PSU Cooperative Extension, Centre County
Room 322, Willowbank Building
420 Holmes Avenue
Bellefonte, PA 16823
Office Phone: 8143554897
Ronald Hoover
Senior Research Associate
Department of Crop and Soil Sciences
116 ASI Building
University Park, PA 16802
Office Phone: 8148656672
Dr. Glenna Malcolm
Post-doctoral researcher
The Pennsylvania State University
Dept. of Crop and Soil Sciences
116 ASI Building; The Pennsylvania State University
University Park, PA 16802
Office Phone: 8148673021
Douglas Beegle
Professor Soil Science
Department of Crop and Soil Sciences
116 ASI Building
University Park, PA 16802
Office Phone: 8148631016
John Tooker
Assistant Professor of Entomlogy
Dept. of Entomology
506 Ag Sciences & Industries Building
University Park, PA 16802
Office Phone: 8148657082
Rita Seidel
The Rodale Institute
611 Siegfriedale Road
Kutztown, PA 19530
Office Phone: 6106831491
Thomas Richard
Associate Professor of Agricultural Engineering
The Pennsylvania State University
Dept. Agricultural & Biological Engineering
246 Agricultural Engineering Bldg.
University Park, PA 16802
Curtis Dell
Soil Scientist and Adjunct Associate Professor
USDA-ARS-Pasture Systems Watershed Management Rese
Building 3702, Curtin Road
University Park, PA 16802
Office Phone: 8148630984
Roger Koide
Professor of Horticultural Ecology
Dept. of Horticulture
102 Tyson Building
University Park, PA 16802
Office Phone: 8148630710
Timothy Beck
Extension Educator
Penn State Cooperative Extension
310 Allen Rd. University Park
Carlisle, PA 17013
Office Phone: 7172406500
Virginia Ishler
Nutrient Management Specialist
Dept. of Dairy and Animal Science
343 Agricultural Sciences and Industries Building
University Park, PA 16802
Office Phone: 8148633912
Jeffrey Hyde
Associate Professor of Agricultural Economics
Dept. Agricultural Economics & Rural Sociology
210B Armsby Building
University Park, PA 16802
Office Phone: 8148655666
Steven Mirsky
Research Ecologist
Sustainable Agricultural Systems Lab USDA ARS
Bldg 001, Rm 117, BARC-West
10300 Baltimore Avenue
Beltsville, MD 20705
Office Phone: 3015045324
William Curran
Professor Weed Science
Department of Crop and Soil Sciences
116 ASI Building
University Park, PA 16802
Office Phone: 8148631014