Introduction
Attaining a high density in a silo is important to limit silage porosity and to maximize storage capacity. Porosity influences the rate at which air moves into the silo and subsequently the amount of spoilage that occurs during storage and feedout. Ruppel (1992) measured dry matter loss for alfalfa silage and developed an equation to relate the loss to density. Table 1 summarizes those results. Higher silage densities generally reduce the annual cost of storage per ton of crop by increasing the amount of crop stored in the silo and by reducing crop losses during storage. Factors that affect density in bunker and pile silos are not well understood. The objectives in our study were to measure density in a wide range of bunker silos and correlate those densities with filling practices.
Table 1. Dry matter loss as influenced by silage density (Ruppel 1992).
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* DM=Dry Matter
Nineteen collaborating county extension agents in Wisconsin measured densities in more than 160 bunker silos containing either corn or hay (largely alfalfa) silage. Density was measured with a 2-inch diameter corer (Holmes, 1996), taking cores at approximately chest height at four locations across the silage face. Core depth, distance from the top, and distance from the floor were recorded. Cores and a grab sample were mailed to the U.S. Dairy Forage Research Center to determine weight, dry matter content, and particle size distribution. A survey was completed for each silo sampled. Information requested from farmers included: number of packing tractors, tractor weight, number of tires per tractor, tire pressure, tire condition, number of drive wheels, silage delivery rate, packing time per day, harvest time per day, filling time, filling technique, initial layer thickness, silo dimensions, maximum silage height, crop, crop maturity, and theoretical length of cut. These factors were then correlated with measured dry matter densities.
Results
Densities were positively correlated with the height of silage above the core, indicating the effect of self-compaction in bunkers. To put densities on a common basis, all densities were adjusted to the median depth below the surface (7.1 ft) using Eq. 15 of Pitt (1983) and assuming a compressibility of 2.2 x 10-9/psi. Adjusted dry matter density was positively correlated with average packing tractor weight, packing time, and dry matter content. Density was inversely correlated with the initial depth of the crop layer when spread in the silo.
The linear regression which explains 18% of the variation (Fig. 1) of estimated dry matter density (DMD) is expressed as:
Est. DMD (lbs DM/ft3) = [8.5 + (PF x 0.0155)] x [0.818 + (0.0136 x D)] [1]
where average depth (D) and packing factor (PF) are calculated as:
D = average silage depth (ft) = (height at wall + height at center)/ 2 [2]
PF= (W/L) x square root[(N x DM)/C]
W= Proportioned average tractor weight (lbs) for all tractors packing silage. Example: Two tractors pack 100% of the filling time; tractor #1 weighs 25,000 lbs and tractor #2 weighs 15,000 lbs. Then the proportioned average tractor weight is 20,000 lbs = (25,000 + 15,000)/2. If tractor #1 packs 90% of filling time and tractor #2 is used 50% of the time, the propor-tioned average tractor weight becomes:
19,286 lbs = [(25,000 x 0.9) + (15,000 x 0.5)] x [90/(90 + 50)] = 19,286 lbs
L = Layer thickness (inches) of the spread but unpacked crop in the silo prior to driving over it during the first packing pass.
N = Number of tractor-packing equivalents, where N = 1 when one tractor packs continuously during the filling process. This value can be fractional, reflecting one or more tractors packing intermittently. For example, if one tractor packs continuously during the silo-filling process and another packs 50% of the filling time, N = 1 + 0.5 = 1.5. If there is only one packing tractor and it packs for 11 hr/day and the silo is filled 10 hr/day, then N = 11/10 = 1.1.
DM= Dry matter content (decimal).
For example, 35% dry matter forage is used as 0.35 in the
equation.
C = Crop delivery rate to the silo (wet tons, or tons as-fed, per hour, T AF/hr).
Use of rear duals or all duals on packing tractors had little effect on density (Fig. 1). Other factors such as tire pressure, crop, and average particle size were not significantly correlated with density. Thus, the low r2 of the regression of dry matter density vs. the 5-parameter packing factor probably reflects variability in accurately estimating parameters such as initial depth of the crop and packing time per ton rather than missing factors important to determining density.
One practical issue raised in the study was packing time relative to crop delivery rate to the silo. Packing time per ton was highest (1 to 4 min/T AF) under low delivery rates (<30 T AF/hr) and generally declined with increasing delivery rate. Packing times were consistently less than 1 min/T AF at delivery rates above 60 T AF/hr in our survey. These results suggest that farmers using contractors to harvest their silage crops will need to pay particular attention to spreading the crop in thin layers and would benefit from using several packing tractors simultaneously.
If a producer is concerned about the density achieved in a bunker silo, the following changes should be considered the next time a bunker silo is filled.
An Excel spreadsheet has been developed to make the calculation procedure for estimated dry matter density easier. Download the spreadsheet from the Team Forage website located at:
http://www.uwex.edu/ces/crops/uwforage/h&s-fp.htm
A more complete discussion of this topic is located at the website.
Fig. 1. Adjusted dry matter density as related to the packing factor (PF) and use of dual wheels on packing tractors. The regression equation is based on average depth of silage of 7.1 ft above chest height.
References
Holmes, B.J. 1996. Probe for silage profit. Minnesota/Wisconsin Engineering Notes Newsletter, Fall. www.bae.umn.edu/extens/
Pitt, R.E. 1983. Mathematical prediction of density and temperature of ensiled forage. Transactions of the ASAE 26:1522-1527,1532.
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.
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