2020 Corn Silage Overview

Joe Lawrence, Allison Kerwin – Cornell PRO-DAIRY

The growing season across much of the Northeast started out with below average temperatures. Despite the cool start, relatively dry conditions coupled with warmer temperatures as the month of May progressed provided generally good conditions for corn planting with all trial locations planted between May 5th and May 21st (Table 1). As the season progressed, all locations experienced below average precipitation and above average heat accumulation. Several locations were designated as abnormally dry to moderate drought throughout June and July; however, in most cases, the crop proved quite resilient and rainfall in mid-July was critical to generally successful pollination. It is worth noting that at several locations, seasonal rainfall totals were inflated by extreme rain events that generally pose greater risk (in terms of the potential for strong winds, runoff and other potential crop damage) than benefit to the crop.

It should also be recognized that some areas of the state experienced more severe drought conditions than these locations leading to more significant negative impacts on yield and forage quality. In these areas greater shifts in management strategies will be needed to make adjustments in feeding programs.

Table 1
Maturity Group Location Planting Date Harvest Date Seasonal GDD (86/50) Seasonal Rainfall (inches)

80 – 95 day RM

38 entries

Willsboro, NY

Albion, NY

Alburgh, VT

May 21

May 20

May 13

September 1

September 4

September 9








96 – 110 day RM

52 entries

Madrid, NY

Aurora, NY

Alburgh, VT

May 5

May 13

May 14

September 15

August 31

September 21







As 2020 corn silage sits in storage, hopefully fermenting for the next few months before being fed out, it is helpful to understand how this crop might feed compared to previous years. Using the trial results as an indicator of corn silage performance gives us an idea of average performance. Data for the detailed hybrid specific report of the trials is still being processed, but we do have enough information to look at overall performance trends.

Keep in mind this is an average of certain locations and your conditions may vary. On your own farm, it is helpful to take samples of your forage at harvest and again prior to feed out to understand the opportunities and challenges as you begin to feed this year’s crop. We also need to remember that while fresh samples can be a helpful indicator, some characteristics of the forage will change during fermentation, particularly starch digestibility.

As additional years of data are collected, patterns begin to form. As the 2020 season progressed, there were many similarities to the 2018 growing season (Figure 1a &1b). While total rainfall varied from 2018 at several locations, the rainfall totals are a bit misleading as the pattern and timing of this rainfall led to abnormally dry to drought conditions at all locations at different points in the season.

Fig. 1a
Fig. 1b

The influence of weather on key forage quality parameters, such as fiber digestibility, has been an area of focus in this work. As the season progressed, the similarities to 2018 suggested the potential for a highly digestible crop.  This projection was validated as the 2020 trial data shows a crop with high fiber digestibility as well as high starch levels (Figure 2a & Figure 2b).

Another way to look at these key parameters and to compare with previous years is to look at the sample spread across a range of values for these parameters. Table 2 and Figures 2a and 2b show the differences in undigested neutral detergent fiber after 240 hours of digestion (uNDF240) and starch content, respectively. The data in Figure 2 represents the last four growing seasons (2017 – 2020) with results combined from all locations (Albion, Willsboro, Aurora, Madrid and Alburgh) by year.

Fig. 2a
Fig. 2b

Each year brings its own challenges and opportunities. Given the variation in growing conditions across the region, it is critical to test your own forages to understand the site-specific impacts of the growing season.

It is important to evaluate this data in the context of your farm when selecting hybrids. The top performing hybrid at any one location or in any one category may not be a good fit for your feeding program. Factors that influence this vary by farm but include land base, soil resources, forage inventory, quality of available hay crops, access and cost of supplemental ingredients, and expectations of cow performance.

The trial results and location averages serve as a means to calibrate hybrid performance to a particular growing season. These averages can be used in conjunction with a company’s data on hybrids in their lineup, including hybrids not entered into these trials, to understand how a hybrid performed relative to what is realistic for a given growing season. For example, in Figure 2, we see that the highest percentage of samples have an uNDF240, %DM value in the 9-10% category and over 50% of samples having a starch content of 50% or greater. This can be used to evaluate how close or far away from these values other hybrids performed in 2020.

It is important to recognize the companies that make these trials possible through their entry of hybrids.  The following companies participated in the 2020 trials.

Albert Lea – Viking, Blue River Organic, Brevant, Channel, Dekalb, Growmark FS, Hubner, King Fisher (King’s Agri-seed), Local Seed Company, Masters Choice, Nutrien Ag Solutions – Dyna-Gro, Pioneer, Redtail (King’s Agri-seed), Schlessman (Gold Star Feed & Grain), Seed Consultants, Seedway, Syngenta – NK


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

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


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

Corn Grain and Silage Yield Data

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

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

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


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

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

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

Conclusions and Implications

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

Additional Resources

Full Citation

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


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

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Double-Cropping with Forage Sorghum and Forage Triticale in New York: Best Timing for Sorghum Harvest and Triticale Planting

Sarah E. Lyonsa*, Quirine M. Ketteringsa, Greg Godwina, Jerome H. Cherneyb, Debbie J. Cherneyc, John J. Meisingerd and Thomas F. Kilcere

aNutrient Management Spear Program, Department of Animal Science, Cornell University, Ithaca, NY, bSoil and Crop Sciences Section of the School of Integrative Plant Science, Cornell University, Ithaca, NY, cDepartment of Animal Science, Cornell University, Ithaca, NY, dUSDA-ARS Beltsville Agricultural Research Center, Beltsville, MD (retired), eAdvanced Agricultural Systems, LLC, Kinderhook, NY. *Current affiliation: Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC


Double cropping with both warm- and cool-season forages in New York can have many benefits, including providing a source of forage yield in the spring potentially leading to greater total season yields than a monocrop system, increasing rotation diversity, and providing year-round soil cover. Winter cereals such as triticale are great options for double cropping in the northeast, as they overwinter and can produce high forage yields in the spring. Yet, depending on weather and growing season condition, a winter cereal crop harvested for forage can delay corn silage planting to mid-May or later. Sorghum is a potentially useful alternative to corn silage for double cropping rotations as sorghum can be planted later than corn. While it is possible to harvest forage sorghum earlier than the recommended soft dough growth stage without compromising yield (Lyons et al., 2019a), it was not known how sorghum harvest timing would impact total season yield of both forage crops in the rotation. Here we present the findings of a field trial to evaluate the impact of sorghum harvest timing on the combined yield of forage triticale and forage sorghum in a double cropping rotation.

Field Research

This double cropping study with forage sorghum (brachytic dwarf brown midrib variety ‘AF7102’) and forage triticale (‘Trical 815’) was conducted at the Musgrave Research Farm in Aurora, NY from October 2015 to June 2018. The study was initiated with triticale planting in mid-October, 2015. Each spring, the triticale received multiple rates of nitrogen (N) at dormancy break in mid- to late-April and was harvested in mid- to late-May at flag-leaf stage. Sorghum was planted between early and mid-June once the soil temperature stayed consistently above 60°F. Sorghum received either no N or 200 lbs N/acre at planting, and was harvested four times in the fall between early September and mid-October, approximately 2 weeks apart. Triticale was planted a day after sorghum harvest. Here we present the data from the plots that received 120 lbs N/acre for triticale and 200 lbs N/acre for sorghum, where N supply was not expected to limit yield of either crop.


In 2016, sorghum yield was highest when harvested after mid-September (late-flower to early-milk growth stage or later), and the following triticale yield was highest when planted in mid-September (Figure 1). Because of the larger contribution that sorghum had, overall total season yield did not increase after the mid-September sorghum harvest and triticale planting date that year. In the second year of the study (fall 2017-spring 2018), sorghum yield was maximized at the last harvest date, and, as with the year before, triticale yielded highest when planted in mid-September. Total season yields were lower in the second year compared to the first year, most likely reflecting weather; fall 2016 was warmer and drier, while fall 2017 was cooler with higher rainfall. There were more growing degree days (GDDs) by mid-September 2016 than by the last harvest in mid-October 2017 (Figure 2).

yield bar chart
Figure 1. Total season yield for a double-crop rotation study with forage sorghum and triticale in central New York from 2016 to 2018. Triticale was planted the day after sorghum harvests in the fall. Triticale was harvested at the flag-leaf stage in May. Sorghum was fertilized with N at planting (200 lbs N/ac) and triticale was fertilized with N at dormancy break in the spring (120 lbs N/ac).
yield graph
Figure 2. Forage sorghum yield as related to growing degree days (GDDs) from 2016 to 2017. The GDDs were calculated by subtracting the lower threshold growing temperature for sorghum (10°C) from the average daily temperature (in °C). The average daily temperature was calculated by subtracting the minimum temperature from the maximum temperature and dividing by two: (Temperaturemax – Temperaturemin)/2. To convert from GDD in °C used here to GDD in °F, multiply by GDDs in °C by 1.8.

Conclusions and Implications

Forage double cropping can be both economically and environmentally beneficial in upstate New York. Sorghum, a crop well-adapted to warm and dry climates, planted in early or mid-June will likely reach maximum yields earlier in years with more GDD (by 1151 GDD in oC or 2072 GDD in oF in mid-September 2016 in this study) compared to years with fewer GDD (such as 2017 in this study). We recommend that sorghum grown in New York during warm, dry years can be harvested once ~1150 GDD (°C scale; 2070 GDD in oF scale) have accumulated. This can support both sorghum and triticale yields. If 1150 GDD have not accumulated by the soft-dough growth stage (cool, wet years), harvesting sorghum at soft dough is recommended to maximize total season yield.

Additional Resources

Full Citation

The information summarized here comes from a 2019 publication in the Agronomy Journal: Lyons, S.E., Q.M. Ketterings, G.S. Godwin, J.H. Cherney, D.J. Cherney, J.J. Meisinger, and T.F. Kilcer (2019). Double-cropping with forage sorghum and forage triticale in New York. Agronomy Journal 111:3374-3382. doi:10.2134/agronj2019.05.0386.


Cornell logo, NMSP logo, pro-dairy logoThis work was supported by Federal Formula Funds, and grants from the New York Farm Viability Institute (NYFVI) and Northeast Sustainable Agriculture Research and Education (NESARE). For questions about these results, contact Quirine M. Ketterings at 607-255-3061 or qmk2@cornell.edu, and/or visit the Cornell Nutrient Management Spear Program website at: http://nmsp.cals.cornell.edu/

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Disease Susceptibility of Brown Midrib (BMR) Silage Corn

Judith M. Kolkman1 , Rebecca J. Nelson1, 2, and Gary C. Bergstrom1
Sections of Plant Pathology and Plant-Microbe Biology1, and Plant Breeding and Genetics2 – School of Integrative Plant Science – Cornell University

What to know about BMR silage corn and diseases

Brown midrib (BMR) corn is a market class within silage corn that is desirable due to its significantly decreased lignin content.  As the name suggests, midrib veins of BMR corn leaves have a distinctive brown color.  Decreased lignin is desirable in corn silage because it increases feed digestibility for ruminant animals.  BMR corn carries naturally derived mutations in single genes that affect the plant’s lignin biosynthetic pathway.

The biosynthetic pathway that produces lignin also makes compounds that contribute to active plant defense mechanisms.  Some of these active defenses include small molecules called secondary metabolites that confer resistance against pests and diseases.  Structurally, lignin is a major component of the cell wall and serves as a barrier against fungal pathogens.  Lignin is also actively produced to strengthen cell walls that are being attacked.

To date, six BMR mutations have been identified in corn, and are designated as bm1 through bm6.  The causal gene has been identified for five of the BMR mutations.  Lines carrying two of these mutations, bm1 and bm3, are used as inbred parents for the production of commercially available hybrids known as BMR1 and BMR3, respectively.  Commercial BMR silage corn hybrids have been gaining in popularity.

There is concern that the same bm gene(s) that confer greater digestibility to BMR silage hybrids may also confer increased susceptibility to fungal diseases.  Some of these hybrids are more vulnerable to stalk lodging.  Northern leaf blight severely affected commercial BMR hybrids in 2013 and other recent growing seasons.

To determine the effect of the brown midrib mutations on disease susceptibility, we used replicated trials across multiple years to test the reaction of bm1 – bm4 mutants in a uniform inbred line background, W64A, to leaf, stalk and ear diseases (Fig. 1, Fig. 2 and Fig. 3).  Corn lines containing the four BMR mutations were all found to have heightened susceptibility to foliar fungal diseases, including northern leaf blight, gray leaf spot and anthracnose leaf blight (Fig. 1 and Fig. 2).

diseased corn leaves
Figure 1. Examples of lesions of (left to right): northern leaf blight, anthracnose leaf blight, Stewart’s bacterial wilt and gray leaf spot in corn.
graphs of corn disease reactions
Figure 2. Reactions to foliar fungal (NLB, GLS and ALB) and bacterial (SW) diseases in W64A inbred lines containing bm1, bm2, bm3 or bm4 mutations in comparison with W64A which does not contain a BMR mutation.
Graphs of disease reactions in corn
Figure 3. Reactions to anthracnose stalk rot and Gibberella ear rot in W64A inbred lines containing bm1, bm2, bm3 or bm4 mutations in comparison with W64A which does not contain a BMR mutation.

Figure 4 depicts a dramatic increase in W64A with the bm3 mutation.  The lines were also found to be more susceptible to the foliar bacterial disease, Stewart’s bacterial wilt (Fig. 2).  After two years of trials, our evidence suggests that BMR corn inbreds have higher susceptiblity to anthracnose stalk rot as well (Fig. 3).  Additionally, the bm1 and bm3 containing inbreds were more susceptible to Gibberella ear rot, caused by Fusarium graminearum, when compared to their non-BMR counterparts (Fig. 3).

diseased corn comparison
Figure 4. Increased severity in an inoculated trial of northern leaf blight in a W64A corn inbred with the bm3 gene (right) compared to a W64A inbred lacking the mutant gene (left).

The benefits of BMR silage corn are huge for the dairy industry.  While individual hybrids may vary, BMR corn, appears to be more susceptible to diseases than non-BMR corn. The degree of susceptibility does vary by bm mutation and specific pathogen (Fig. 2 and Fig. 3).  Breeders are constantly working to improve disease tolerance, and disease ratings should be factored into hybrid choices.  BMR hybrids in the market show a wide range of suceptibilities to individual diseases.

How to manage diseases in BMR silage hybrids

Knowing that BMR silage corn can be more vulnerable to foliar, stalk, and ear diseases means that a proactive and integrated strategy is needed to maintain optimal plant health in these hybrids.  Elements of integrated management include:

Be aware of corn diseases on your farm and in your area.  Scout your fields annually for foliar diseases from tassel emergence through grain formation.  Check for ear rots (by pulling back husks) and stalk rots (squeeze lower stalks or attempt to push stalks over) prior to harvest.  Seeing diseases even late in the season gives you an indication of what pathogens may survive in corn residues into the next growing season and helps you to plan rotations and select hybrids.

Fungi that cause anthracnose, gray leaf spot, northern leaf blight, and Gibberella ear rot and stalk rot survive between crop seasons in corn residues on the soil surface; therefore rotation of corn with non-host crops can help to reduce the spore inoculum potential for these diseases.  Northern leaf blight has been the most widespread and injurious foliar disease in New York in the past decade and can be a problem anywhere in any given year.

Consider disease susceptibility when selecting BMR hybrids. Select BMR hybrids with the least susceptibility to specific diseases that have been problematic on your farm or in your region. If disease risk is extreme, e.g., in a humid river valley with a history of severe gray leaf spot, it may be preferable to grow non-BMR hybrids with documented resistance.

BMR hybrids, especially BMR1 and BMR3, have the potential to have severe ear rot and mycotoxin contamination in years with persistent moisture during silk emergence.  Be sure to check seed company guides for the latest disease ratings for BMR hybrids.

Apply foliar fungicide based on disease detection and forecast risk. There is a wide choice of foliar fungicide products labeled for control of fungal leaf blights in New York.  Table 3.5.1 in the 2020 Cornell Guide for Integrated Field Crop Management (https://www.cornellstore.com/2020-PMEP-Guide-for-Integrated-Field-Crop-Mgmt) notes the relative efficacy of labeled fungicides against different corn diseases.  To slow down the development of resistance to fungicides in pathogen populations, it is best  to use products with different modes of action (FRAC groups) in alternating years or to apply combination products with more than one mode of action.

The optimal timing for applying foliar fungicides is between tassel emergence (VT) and brown silk (R2) stages.  Observation of foliar fungal diseases in the middle leaf canopy (at lowest ear level) and a forecast of significant precipitation in the following week are the best indicators that fungicide application will be result in disease suppression and yield increase.  Suppression of foliar diseases also helps to preserve stalk health, standability, and quality, including lower levels of fungus-produced mycotoxins.

Consider longer term and regional effects of growing BMR hybrids. Year after year of growing a susceptible BMR hybrid can increase the disease inoculum load in a particular field and locale, thus affecting neighboring fields of non-BMR silage, dent, and sweet corn.  Occasional rotation out of BMR corn should be considered.


BMR silage corn is increasing in popularity and acreage as it provides a high quality, digestible feedstock for dairy nutrition.  Its positive attributes need to be balanced with proactive disease management to insure plant health and sustained productivity in dairy cropping systems.


This work was supported by the USDA National Institute of Food and Agriculture Hatch accession #1004040.

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

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

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