Developing an on-farm method to estimate DM loss in corn silage silos

Final Report for ONE09-100

Project Type: Partnership
Funds awarded in 2009: $9,572.00
Projected End Date: 12/31/2011
Region: Northeast
State: Pennsylvania
Project Leader:
Dr. Kenneth Griswold
Kemin AgriFoods North America
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Project Information


The goal of the project is to develop a simple on-farm method for estimating “shrink” (i.e. dry matter (DM) loss) in corn silage silos. Silage DM loss is inversely related to silage DM density, and estimations of silage DM density are fairly standardized and can be performed on-farm. To clearly relate DM loss to DM density, we proposed to measure both in 2 bunker silos and 2 upright silos. We are in the process of finishing the second bunker silo and both upright silos. Data from the first bunker silo has been combined with previous preliminary work to develop regression equations describing the relationship of DM loss to DM density. The results have been presented at 5 local and regional meetings to approximately 600 dairy farmers and 100 dairy industry professionals. The findings have also been presented at the 15th International Silage Conference and American Dairy Science Association National Meetings. Our preliminary results would suggest that while DM loss is inversely related to DM density, there is a tremendous amount of variation in DM loss within a silo that can be accounted for solely by DM density. However, overall average DM density of a silo does appear to be highly inversely related to DM loss. Under excellent management conditions, DM losses in upright conventional silos appear to be less than half of those in bunker silos.


When corn is chopped and ensiled to produce corn silage, there are associated losses of dry matter (DM), also termed “shrink”, and deterioration in nutrient quality and availability (Ruppel et al., 1995). The range in DM loss during ensiling and storage in silos can be < 1.0 to >3.3 % per month (Holmes, 2006). Given a typical 6 to 12 month storage period for dairy farm silos, the range in potential DM loss can range from roughly 6 to 40% of original DM in the harvested corn crop. The problem is the lack of a simple on-farm method for estimating shrink (i.e. DM loss) in corn silage silos. Without an accurate method for estimating shrink, farmers have no reliable starting point from which to combat shrink. This problem of measuring shrink is important because corn silage shrink can negatively impact the environment and the economic well-being of dairy farmers.

Environmentally, there is a direct relationship between corn silage shrink and acreage needed for corn production. If the average shrink for corn silage is 15%, it would mean that 15% more acres of corn are planted, harvested, and ensiled than needed for actual feeding to a dairy herd. Conversely, a reduction in shrink would reduce corn acreage needs. Reducing row-crop acreage has been identified as a method to reduce N and P runoff into surface waters, thereby, improving water quality (FAPRI, 2007). For example, in 2007, Pennsylvania farmers harvested 410,000 acres of corn for silage (NASS, 2008). A 1% reduction in corn silage shrink would have reduced the acreage needed for silage production by 4,100 acres. Further, the ensiling process of corn produces leachate with a heavy biological oxygen demand (BOD), which can impair the quality of surface waters (Cropper &amp; DuPoldt, 1995). Subsequently, reducing shrink would diminish excessive leachate production and provide more protection of surface waters.

Economically, corn silage is an important feedstuff for Pennsylvania dairy farms and can represent 50% or more of the forage fed to dairy cattle on a daily basis. As such, the cost of corn silage has a dramatic effect of the cost of feeding a dairy cow. For example in 2008, based on nutrient content, and harvesting and storage costs, a ton of 35% DM corn silage was approximately $45/ton (Beck, personal communication, 2008). Using the range of DM loss identified above, the value of the corn silage coming out of the silo would be approximately $47.25 to $75/ton. This range in corn silage cost would increase the cost of a typical ration up to 18% depending on the amount of corn silage fed per cow per day. Therefore, minimizing shrink reduces the feeding cost of corn silage and can improve the overall profitability of the dairy farm. On a statewide basis, an average shrink of 15% for corn silage would equal approximately $45.7 million in economic loss to the dairy industry.

Farmers are aware of and actively combat shrink in silage by employing a number of different methods from harvesting at proper moisture to use of plastic to seal silos to inoculants to preservatives, etc. And, while most of these methods have well-documented, University-conducted research to support their use, it is extremely difficult to quantitatively measure how effective these methods are at reducing silage shrink on the dairy farm. Without a consistent, usable method to establish a starting point or track shrink over time, farmers can not make informed decisions on how best to reduce corn silage shrink. With an overall goal of reducing DM loss in corn silage, we need a valid on-farm method for estimating shrink in order to create meaningful benchmarks and develop improved methods of reducing shrink.

Project Objectives:
  • Our proposed solution is to use DM density as an estimator of corn silage shrink within a silo through simple, on-farm methods. • Place and retrieve poly-weave nylon bags of silage from 2 bunker silos and 2 upright silos. • Measure DM loss within each bag and assess DM density of silage at each bag location within each silo. • Analyze data on DM loss and nutrient changes and develop regression equations to clearly relate DM loss to DM density. • Deliver the research results to dairy farmers in a practical manner that they can then utilize to improve their corn silage storage and feeding management. Delivery will be through presentations, articles in lay journals, and training of industry professionals and extension educators.


Click linked name(s) to expand
  • John Beiler
  • Arlin Benner
  • Paul Craig
  • Sarah Dinh
  • Daniel Esch
  • Tom Nauman


Materials and methods:
Silo Management Variables

Each silo will be filled with chopped corn according to the normal procedures of the farm. Harvest and packing variables will be recorded including corn varieties, planting and harvest dates, acreage and estimated tonnage harvested, make and model of harvester and packing tractors, packing tractor weights, delivery rate of chopped corn to silo, packing time and frequency, surface cover, and degree of overfilling. Once the silo is filled, packed and sealed, the silage will be allowed to ferment for at least 6 weeks prior to feed-out.

Experimental Design

The experimental design will be a replicated, randomized complete block with repeated measures. To minimize variation, sample bags will be blocked by approximate level related to the silo floor. For the bunker silos, three sets of 12 bags each (N = 36) will be blocked by height, 2’ (Bottom), 5’ (Middle), and 7’ (Top). Each 12-bag set will be randomly divided into groups of 4 bags, and each group will be randomly assigned to one of three depths from the feed-out end of the silo, 35’ (Front), 90’ (Center), and 145’ (Back). Bags within each group will be distributed across the width of the silo in relation to distance from the left wall, 3’ (I), 15.25’ (II), 27.75’ (III), and 40’ (IV). For the upright silos, three sets of 3 bags each (N = 9) will be blocked by height, 15’ (Bottom), 35’ (Middle), and 55’ (Top). Each 3-bag set will be distributed across the silo diameter with one bag 2’ from each side and one bag in the center.

Dry Matter Loss & Density Determination

The rate and extent of DM loss during fermentation and storage will be determined using a nylon bag technique (Ruppel et al., 1995) with modifications. Briefly, pre-labeled, poly-weave nylon bags (2’ x 3.5’) will be filled with roughly 12 lbs wet weight of chopped corn. Chopped corn will be collected from the height within the silo where the bags are to be placed (e.g. Bottom, Middle, and Top). Actual wet weights will be determined using a 75 lb capacity electronic platform scale accurate to 0.02 lbs. Chopped corn DM will be determined to calculate the amount of DM contained in each bag. Bags will be sealed with cable-ties, attached to a 2’ fluorescent marker, and buried in the chopped corn with the marker extended toward the feed-out end of the silo. As silage is removed from the silo, all bags within a set will be retrieved when the fluorescent markers becomes visible. Wet weight of each bag will be determined, and subsamples collected for DM and nutrient analysis. Extent of DM loss (% of original DM) will be determined by subtracting the dry weight of the corn silage from the dry weight of chopped corn within each bag and dividing by dry weight of the chopped corn. Rate of DM loss (% per day of storage) will be calculated by dividing total DM loss by the number of days of fermentation and storage. Dry matter density of the silage surrounding each bag will be determined by the coring method described previously (Muck and Holmes, 2000).

Sampling and Analyses

Subsamples of chopped corn and corn silage will be sent to a certified forage analysis laboratory for wet chemistry analysis of standard nutrients and fermentation acids. Chopped corn and corn silage DM will be determined using a Koster Moisture Tester (Koster Crop Tester, Inc., Brunswick, OH) and a digital scale that measures to 0.1 g to increase precision compared to the spring scale normally use with a Koster Tester.

Statistical Analyses

Regression analysis of DM density, DM loss, DM content, nutrient content, and fermentation profile will be performed using Proc REG in SAS (SAS Inst. Inc., Cary, NC) with a significance level of P < 0.05. All other statistical analyses will be performed using the MIXED procedures of SAS.

Research results and discussion:
Relationship of Dry Matter Density to Dry Matter Loss in Bunker Silos
  • Dry matter density was significantly affected by depth, level and location within the bunk (Tables 1, 2, &amp; 3). Dry matter loss was significantly affected by depth and level, but not location. There were no significant interactions of depth, level, or location on DM density or loss. These results would suggest that sealing the sidewalls with plastic reduced DM losses along the walls where silage is less packed. There was an inverse relationship between DM density and DM loss (Figure 3), but the relationship was weak (R2=0.18). The large degree of variation in DM loss within the silos suggests that factors other than density play a role in DM losses. Response surface regression of DM loss in relation to DM % and DM density (Figure 4) also showed an inverse relationship and the model accounted for a larger proportion of the variation in DM loss (R2=0.28). Using the response surface regression prediction, it would appear that silage with higher DM content exhibited a more linear inverse relationship between DM density and DM loss compared to wetter silage.
    Relationship of DM density & DM content to DM loss in Corn Silage Bunker Silos
    Relationship of DM density & DM content to DM loss in Corn Silage Bunker Silos
Effect of DM Density on Fermentation & Nutrient Preservation
  • Dry matter density was significantly affected by depth, level and location within the silo (Tables 1, 2, and 3) There were no significant interactions of depth, level, or location on DM density. Soluble protein (as a % of CP) was the only nutrient affected by depth, level and location within the silo (Tables 1, 2, and 3), and was lower at the front, on the top, and along the sides of the silo. Fermentation was affected by depth and level within the bunker silo (Tables 1, 2, and 3) as total VFA were lower at the front and top of the silo. There was an inverse relationship between DM density and NDF content (Figure 3), but the relationship was weak (R2=0.05). Overall, these data would suggest that DM density may affect fermentation, but likely does not alter nutrient content of BMR corn silage.


Participation Summary

Education & Outreach Activities and Participation Summary

Participation Summary

Education/outreach description:
  • Results have been presented at 5 local and regional meetings for dairy farmers and industry professionals. These meetings included: International Silo Association Annual Meeting – January 2010 – 50 attendees Lykens Valley Dairy Day – February 2010 – 50 attendees Hoober Feeds Winter Dairy Seminar – February 2010 – 300 attendees Pennsylvania Dairy Summit – February 2010 – 250 attendees Renaissance Nutrition, Inc. Meeting – April 2010 – 50 attendees Penn State Dairy Nutrition Workshop – November 2010 – 50 attendees Patz Mixer Field Day – December 2010 – 50 attendees MM Weaver Open House – January 2011 – 500 attendees University of Delaware Silage Meeting – February 2011 – 15 attendees Vita Plus Customer Harvester Meeting – February 2011 – 80 attendees Cargill Nutrition Winter Meeting – March 2011 – 200 attendees New Jersey Dairy Extension Farm Meeting – March 2011 – 50 attendees Patz Mixer Field Day – April 2011 – 75 attendees Corn silage harvest and storage management meetings were held in January 2010 in Lancaster, PA, in February 2011 in Troy, PA, and in March 2011 in East Earl, PA. A total of 320 attendees participated in the meetings. The meetings combined the results of the current study with speakers from the University of Wisconsin and University of Delaware. Results were presented at the 15th International Silage Conference in Madison WI, the 2010 American Dairy Science Association Meetings in Denver CO, and the 2011 American Dairy Science Association Meetings in New Orleans, LA. Articles have been published in Progressive Forage Grower, Lancaster Farming and Farmshine.

Project Outcomes

Project outcomes:

Farmer Adoption

It is too early to determine if farmers participating in the study have changed their management practices due to the results of the study.

Assessment of Project Approach and Areas of Further Study:

Areas needing additional study

Several of the participating farmers have expressed interest in the plastic used to seal silos and how these plastics might be improved or replaced with an edible silage cover.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.