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* Department of Dairy and Animal Science
Department of Agricultural and Biological Engineering The Pennsylvania State University University Park, PA 16802
| ABSTRACT |
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Key Words: moisture particle size sieve
Abbreviation key: Sgm = geometric standard deviation, PSPS = Penn State Particle Separator, Xgm = geometric mean
| INTRODUCTION |
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Based on properties of the standard S424 of the American Society of Agricultural Engineers (2001) for forage particle size determination, the Penn State Particle Separator (PSPS) is a quick and cost-effective method of analysis. The manually operated PSPS is constructed out of two sieves and a bottom pan. Apertures of the two sieves measure 19.0- and 8.0-mm with a thickness of 12.2 and 6.4 mm. With its simple construction and size, the PSPS sieving method may be implemented on farm and used at the time of harvest or feeding to determine particle size of forages or TMR (Lammers et al., 1996). Even though the apparatus has been widely accepted and particle size measurements using the PSPS are now commonly reported in the literature, TMR typically contain 40 to 60% concentrate, most of which passes through the 8.0-mm sieve. Measurement of smaller particles may be useful in understanding the effects of ration particle size on rumen function and fermentation, as it has been suggested that 1.18 mm is the critical length governing retention in the reticulo-rumen (Poppi and Norton, 1980).
Although the rationale behind all published sieving methods is similar, the equipment, method, or physical form of the sample may vary and affect particle size measurement (Murphy and Zhu, 1997). Operation of the PSPS has been previously described (Lammers et al., 1996); however, during our field experience we have observed that the rate of shaking, and, as a result, the effectiveness of separation often differs between users. This observation suggests that directions for use of the PSPS may require further refinement. Furthermore, because the PSPS has been adopted as an analytical technique by some feed testing laboratories, the procedure must be clearly defined so that calibration is possible. Few studies have evaluated the effect of sample moisture content on particle size measurements. Because moisture content often differs depending on harvest time, weather and other factors, the effect of moisture content on particle size measurements should be further investigated.
The objectives of this project were as follows: 1) to modify the PSPS so that smaller particles can be further partitioned during measurement, 2) to define optimal sieving motion for the PSPS, and 3) to determine the effect of sample moisture on sieving results.
| MATERIALS AND METHODS |
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Method of Separation
In testing the effects of shaking frequency and sample moisture on measurements taken by the PSPS, operation of the device was similar to that described by Lammers et al. (1996). The sieves were stacked in the following order: 19.0-mm plastic sieve on top, 8.0-mm plastic sieve second, followed by 1.18-mm metal sieve, and the plastic pan fitted to the bottom of the last sieve. Approximately 1.4 ± 0.5 L of sample was spread out on the top 19.0-mm sieve. The sieve set was shaken horizontally five times in one direction, then rotated one fourth turn, and again shaken five times. The procedure was repeated for eight sets of five replications for a total of 40 shakes. Rotation of the separator ensured that the sample was thoroughly shaken and that particles were not stacked upon each other. One shake was considered as a forward and backward motion over a distance of 17 cm. Particles were assumed to be logarithmically normally distributed and geometric mean (Xgm) and standard deviation (Sgm) were calculated as outlined by the ASAE Standard (2001).
Testing Effect of Sieving Frequency on Particle Size Measurement
To test the effect of shaking frequency on particle size measurement, samples of alfalfa haylage, corn, silage and a TMR were collected and analyzed in duplicate for particle size using three different frequencies. The three frequencies used in the experiment were 0.9 (slow), 1.1 (medium), and 1.6 Hz (fast). All replications were timed so that sieving frequencies were consistent between duplications. Sample moisture contents of alfalfa haylage, corn silage, and a TMR were 64.6, 67.4, and 46.0%, respectively.
Testing Effect of Sample Moisture in Particle Size Measurement
Approximately 1.4 L subsamples of alfalfa haylage and corn silage were evenly spread out on individual aluminum pans and placed in a large forced air oven set at 55°C. Five times over a 48-h period approximately three subsamples, each contained in individual pans, were removed from the oven and analyzed for particle size. Alfalfa haylage samples were removed from the oven and analyzed for particle size after drying 0, 2, 6, 12, and 48 h, while corn silage samples were dried for 0, 3, 6, 18, and 48 h.
Statistical Analysis
All data were analyzed as a completely randomized design using the REML variance component and MIXED procedure of SAS Version 8.1 (2001). Mean separation was determined using the PDIFF procedure and significance was declared at P < 0.05. The model used to evaluate effect of sieving frequency and sample moisture content on particle size measurements was:
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where:
| yij | = | percent of sample retained on each sieve, geometric mean or standard deviation,
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| µ | = | overall mean,
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i | = | fixed effect of treatment (sieving frequency or percent moisture)
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ij | = | residual error, assumed to be normally distributed.
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| RESULTS AND DISCUSSION |
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Presentation of Sieving Results and Particle Size Measurements
Particle size analysis attempts to determine the actual frequency distribution of particles according to size (Irani and Callis, 1964). Material retained on each sieve is expressed in tabular form as seen in Tables 1
, 2
, and 3
. Because of the wide variety of feeds analyzed and the various types of sieving techniques employed, a variety of mathematical forms of particle size distribution have been investigated. Finner et al. (1978) described a method of sieving based on a lognormal distribution, which was subsequently adopted by the American Society of Engineers for describing forage particle size (ASAE, 2001). Smith et al. (1984) determined that an exponential distribution might fit data for alfalfa, grass and corn silages. Fisher et al. (1987) found an exponential distribution fit particle size data of digesta of cattle grazing bermudagrass and Allen et al. (1984) reported a gamma fit distribution was more accurate than lognormal distributions in describing ground hay. Lastly, the original description of the PSPS recommended a Weibull distribution rather than lognormal because plots were more linear and did not require transformation, thereby simplifying plotting and interpretation (Lammers et al., 1996). The use of a Weibull distribution was in agreement with the analysis of Pitt (1987).
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) resulting in estimates of the sample geometric mean (Xgm) and standard deviation (Sgm) (ODogherty, 1984). Consequently, if the lognormal fits the actual distribution closely, information to describe the distribution can be calculated, interpreted and reported easily. Data presention in this study includes both geometric mean and standard deviation with data assumed to be logarithmically normally distributed, an idea concurrent to the ASAE standard (ASAE, 2001).
Sieving Frequency and Particle Size Measurement
The force and frequency of shaking motion must be sufficient so that the particles slide over the sieve surface allowing those smaller than the aperture to fall through. According to the ASAE standard (S424) the sieve stack should be driven with a frequency of 2.4 ± 0.08 Hz (144 ± 5 cycles/min); however, the PSPS is manually operated, and this specification is not practically possible and may explain occasional differences between the devices (Lammers et al., 1996). Because sieving frequency of the PSPS has never been specified, we evaluated the effect of frequency on particle size measurements so that recommendations could be formulated. Sieving alfalfa haylage, corn silage and TMR at different frequencies results in significant (P < 0.05) differences in particle size measurements (Table 1
). Reducing sieving frequency below 1.1 Hz to 0.9 Hz resulted in significantly (P < 0.05) more material being retained on the 19.0-mm sieve and less on the 8.0- and 1.18-mm sieves for all sample types. As a consequence of these results, Xgm was significantly (P < 0.05) greater when material was sieved at 0.9 Hz compared to 1.1 Hz. In contrast, increasing sieving frequency from 1.1 to 1.6 Hz did not result in significant differences (P > 0.05) in particle size measurements of Xgm calculations for either alfalfa haylage or TMR samples. Although increasing sieving frequency from 1.1 to 1.6 Hz for corn silage significantly increased the amount of material falling through the 1.18 mm sieve, these differences were not reflected in Xsm which were not significantly (P > 0.05) different (11.2 and 11.6 mm).
As a result of this study, we recommend the PSPS to be shaken at 1.1 Hz (66 cycles/min) or greater with a stroke length of 17 cm. It is recommended that operators of the device calibrate the frequency of movement over a distance of 17 cm for a specified number of times. Number of full movements divided by time in seconds results in a frequency value that can be compared to this recommendation.
Sample Moisture Content and Particle Size Measurement
Although moisture content may affect sieving properties, it is not practical to recommend analysis at a standard moisture content during field measurements (Finner et al., 1978). The PSPS is designed to describe particle size of the feed offered to the animal; thus it is recommended that samples should not be chemically or physically altered before sieving. Because sample moisture loss may occur during storage or transport, a study was carried out to determine the effects of forage moisture on particle size measurements made by the PSPS. Tables 2
and 3
outline the effect of forage moisture content on particle size measurement for both alfalfa haylage and corn silage. For alfalfa haylage oven drying times of 0, 2, 6, 12, and 48 h resulted in moisture concentration 57.4, 35.6, 10.4, 2.5, and 0.0%, respectively. Similarly, for corn silage oven drying times of 0, 3, 6, 18, and 48 h resulted in moisture concentrations of 58.0, 34.4, 14.6, 3.5, and 0.0%, respectively. For alfalfa haylage samples, particle size measurements were not significantly different (P > 0.05) between 57.4 and 35.6% moisture indicating that moisture loss in samples within this range will not affect particle size measurements. Conversely, for corn silage the amount of particle mass <1.18 mm was significantly different (P < 0.05) between 58.0 and 34.4% moisture and resulted in small but significant differences in Xgm. These results suggest that moisture loss from corn silage may affect particle size results; but these differences, when observed, are small. For alfalfa haylage, comparing to 57.4 and 35.6% moisture, the amount of material >19.0 mm was significantly lower in samples containing 10.4, 2.5, and 0.0% but this difference was not observed for corn silage as most material >19.0 mm contained cob particles for which size measurement appeared to be unaffected (P > 0.05) by moisture content. For both forages, amount of material <1.18 mm was greatest at 0.0% moisture content while Xgm decreased with decreasing moisture content. These results are similar to Finner et al. (1978) who suggested that completely drying a sample results in shattering of particles and further size reduction during the sieving process. Differences in sieving results associated with sample drying may have been due to brittle particles that shatter during shaking or to decreased adhesion of small particles to larger ones when materials are dry.
Because it would be impractical to recommend a constant sample moisture for measuring forage or TMR particle size during field measurement, it is advantageous to know that slight losses of moisture have only limited effects on measurements according to the moisture range of this study. Although it is recommended that samples be analyzed in the same physical form as that fed to the animal and moisture loss in the samples should be minimized, based on our results only small differences result when sample moisture loss is approximately 40% of the original sample.
| CONCLUSIONS |
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| ACKNOWLEDGEMENTS |
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Corresponding author: A. J. Heinrichs; e-mail:
ajh{at}psu.edu.
Received for publication January 16, 2002. Accepted for publication July 18, 2002.
| REFERENCES |
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