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

Project Overview

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

Annual Reports

Information Products


  • Agronomic: corn
  • Animal Products: dairy


  • Animal Production: feed formulation, feed rations, stockpiled forages, winter forage
  • Crop Production: nutrient cycling, tissue analysis
  • Education and Training: demonstration, extension, participatory research
  • Farm Business Management: whole farm planning
  • Production Systems: integrated crop and livestock systems

    Proposal abstract:

    Current Issue

    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 & 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 from proposal:

    In theory, the simplest and best method for determining shrink in any silage is to determine the DM weight of everything going into and coming out of the silo with the difference being the DM loss. With the advent of the total mixed ration (TMR), most farms can with reasonable accuracy determine the amount of corn silage DM coming out of a silo. However, very few farms try to determine the amount of chopped corn DM going into a silo, and of those farms that do make an estimate, a very small number weigh every load of chopped corn going into a silo. Further, determining overall DM loss in a silo may not be helpful when considering the use of certain shrink reducing technologies (e.g. low oxygen permeable plastic, inoculants, preservatives, etc.), especially since DM loss will vary by location within a silo (Holmes, 2006). Our proposed solution is to use DM density as an estimator of corn silage shrink within a silo through simple, on-farm methods.

    Dry matter loss in silage is inversely related to DM density, measured as lbs of DM/ft3 or kg of DM/m3 of silage (Holmes, 2006). Silage density is determined by a number of factors including: DM content, storage structure, location within storage structure, packing time and frequency, packing weight, grain percentage, corn maturity, particle size, crop type, harvest method, surface cover, and degree of overfilling (Holmes, 2006). The current recommendation for average DM density in bunker silos is 14 lbs DM/ft3 or 225 kg DM/m3 (Holmes and Muck, 2004). The associated DM losses for not achieving this goal were derived almost solely from the inverse relationship of DM loss to DM density described by the field research of Ruppel (1992). However, this research was with hay crop silages, not corn silage, and has never been replicated. Dry matter densities vary by geographic region of the country due presumably to different growing conditions, and harvest, storage and packing methods (Holmes, 2006; Craig and Roth, 2005). Further, harvest, storage and packing methods have changed dramatically since the work of Ruppel (1992) was published. Also, over this time period, the methodology for determining DM density has been refined to improve accuracy and precision (Muck and Holmes, 2000).

    The current accepted method (Muck and Holmes, 2000) for determining silage DM density is removal of a 12” silage core by use a 2” dia. stainless steel tube perpendicular to the silage feed out surface. The silage core is removed, weighed, and dried to determine DM content. The core DM weight is divided by the known volume of the core to determine DM density as lbs/ft3. Based on our experience with this method, the DM density of silage within a silo can be determined on-farm in approximately 1 to 2 hours depending on the equipment available.

    In order to use this method of DM density determination as an estimator of DM loss in corn silage, we must be able to clearly establish the relationship between DM density determined by coring and DM loss of the silage being cored. From this relationship, we can develop a formula that can be used to estimate DM loss in a silo from a known DM density.

    Therefore, as a preliminary study, we will utilize four silos (two upright, two bunker) on three farms in Lancaster County, PA. We will place fresh chopped corn samples of known weight in porous nylon bags at known locations within each silo during filling. Then, during feed out, we will collect the sample bags and retrieve silage cores at those locations. Samples bags will be weighed and dried to determine DM loss and the silage core DM density will be determined. Nutrient and fermentation acid analyses will be conducted on initial chopped corn and recovered corn silage samples. These data will be analyzed to calculate the relationship of DM density to DM loss and changes in nutrient and fermentation acid profile. Given a strong relationship, these results will be used to promote the use of silage core DM density as an estimator of DM loss and provide a starting point for future research to further refine the relationship.

    Literature Cited
    Beck, T. 2008. Personal communication on enterprise costs of producing corn silage in Southeastern PA based on FINPAK analysis of 35 dairy farms during 2008.

    Craig, P. H. and G. Roth. 2005. Penn State University Bunker Silo Density Study Summary Report 2004-2005. Pennsylvania State Univ. Cooperative Extension – Dauphin County,

    Cropper, J. B. and C. A. DuPoldt, Jr. 1995. Environmental Quality Technical Note No. N_5_Silage Leachate and Water Quality. NRCS.

    FAPRI. 2007. Estimating Water Quality, Air Quality, and Soil Carbon Benefits of the Conservation Reserve Program. FAPRI-UMC Report #01-07.

    Holmes, B. J. 2006. Density in silage storage. NRAES-181 “Silage for Dairy Farms” Conference Proceedings. pg 214-238.

    Holmes, B. J. and R. E. Muck. 2004. Managing and designing bunker and trench silos (AED-43). Ames, IA: Midwest Plan Service,

    Muck, R. E. and B. J. Holmes. 2000. Factors affecting bunker silo densities. Appl. Engr. In Agric. 16(6):613-619.

    NASS. 2008. Website accessed on 8-20-08.

    Ruppel, K. A. 1992. Effect of bunker silo management on hay crop nutrient management. M.S. Thesis, Cornell University, Ithaca, NY.

    Ruppel, K. A., R. E. Pitt, L. E. Chase, and D. M. Galton. 1995. Bunker silo management and its relationship to forage preservation on dairy farms. J. Dairy Sci. 78:141-153.

    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.