A simple separator was developed to determine the particle sizes of forage and TMR that allows for easy separation of wet forage into three fractions and also allows plotting of the particle size distribution. The device was designed to mimic the laboratory-scale separator for forage particle sizes that was specified by Standard S424 of the American Society of Agricultural Engineers. A comparison of results using the standard device and the newly developed separator indicated no difference in ability to predict fractions of particles with maximum length of less than 8 and 19 mm. The separator requires a small quantity of sample (1.4 L) and is manually operated. The materials on the screens and bottom pan were weighed to obtain the cumulative percentage of sample that was undersize for the two fractions. The results were then plotted using the Weibull distribution, which proved to be the best fit for the data. Convenience samples of haycrop silage, corn silage, and TMR from farms in the northeastern US were analyzed using the forage and TMR separator, and the range of observed values are given.

The Penn State Particle Separator has led to widespread measurement of forage and total mixed ration (TMR) particle size. However, a large proportion of small particles may pass through both sieves when a TMR is analyzed, and field research has suggested that both shaking frequency and sample dry matter may affect the results. The objectives of this project were to test the effects of an additional sieve with a smaller aperture size, shaking frequency, and sample moisture content on results obtained. A sieve was constructed out of wire with a nominal size aperture of 1.18 mm. Samples of alfalfa haylage, corn silage, and a TMR were shaken at frequencies of 0.9, 1.1, and 1.6 Hz with a 17-cm stroke length. Reducing shaking frequency to 0.9 Hz resulted in more material being retained on the 19.0-mm sieve for all sample types, increasing the geometric mean. Increasing frequency to 1.6 Hz did not affect the geometric mean, but did result in a greater amount of corn silage falling through the 1.18-mm sieve. For alfalfa haylage, moisture content between 57.4 and 35.6% did not affect results; however, for corn silage, less moisture increased the percentage of particles less than 1.18 mm and decreased the geometric mean. For both sample types, further drying caused a greater proportion of small particles and a smaller geometric mean. We suggest using a third sieve and shaking at 1.1 Hz or greater with a stroke length of 17 cm when using the Penn State Particle Separator to analyze forage particle size.

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A dairy herd submodel was created for integration with other farm submodels to form DAFOSYM, a dairy farm simulation model. The herd submodel determines the best mix of available feeds to meet the fiber, energy, and protein requirements for each of six animal groups. The groups are early-, mid-, late-, and nonlactating cows, heifers over 1 yr old, and younger heifers. Feed intake, milk production, and manure dry matter and nutrient (N, P, and K) excretions are functions of the nutrient content of the diets. Required feed characteristics include crude protein, rumen degradable protein, acid detergent insoluble protein, net energy of lactation, neutral detergent fiber, total digestible nutrients, P, and K concentrations. Feed intake is predicted with fill and roughage units. These units are functions of feed neutral detergent fiber adjusted for particle size distribution and the relative rate of ruminal digestibility or physical effectiveness of the fiber. The herd submodel predicted feed intakes, nutrient requirements, diets, and manure excretions similar to those recommended or measured for dairy animals. When integrated with other farm components in DAFOSYM, the comprehensive model provides a useful tool for evaluating the long-term performance and economics of alternative dairy farm systems.

Stocking rate is a key management variable in determining productivity and profitability of grazing systems, but it has not been adequately researched in the USA with high producing dairy cows. A replicated farmlet study was conducted to investigate the potential for improving dairy profitability through increasing stocking rates without influencing milk yield per cow. The study was conducted at the Pennsylvania State University Dairy Research and Education Center in University Park, on pasture dominated by orchardgrass (`Dactylis glomerata L.) and Kentucky bluegrass (Poa pratensis L.). Forty‐eight high‐producing Holstein cows (Bos taurus) were rotationally grazed at seasonal stocking rates of 1.0 (low, LSR), 1.3 (medium, MSR), and 1.6 (high, HSR) cows/acre, and were fed grain at the rate of approximately 1 lb grain DM to 4 lb milk production during a 2 yr study. Stocking rate had a positive effect on pasture nutritional quality, particularly when growth was more vigorous, and had a negative relationship with the percentage of the pasture rejected by cows. Seasonal milk yield per cow (approximately 10 000 lb) and milk composition were not affected by treatments in either year. Consequently, milk production per acre was directly related to stocking rate. An economic analysis of costs and returns indicated that profits per unit area of land increase with stocking rate—a $481/acre advantage was shown for the HSR over the LSR. In contrast, profits per cow decrease with stocking rate—the LSR showed a $36/cow advantage over the HSR. The optimal stocking rate for a given farm therefore will depend on individual farm resources (e.g., land, buildings, cows, etc.), and can be adjusted to meet the constraints of those resources without fear of significant adverse economic impact. Research Question Stocking rate, defined as the relationship between the number of animals and the grazing management unit used over a specified time (a grazing season, for example), is key to determining the potential for production and the profitability of a grazing system. The objective of this trial was to compare forage production and quality, milk production, and profitability on a per cow and per acre basis for three different stocking rates, using high‐producing Holstein cows grazing grass pasture. Literature Summary Where pastures are the primary source of feed for dairy cows, research consistently has shown that stocking rate is a major factor in determining the efficiency of the system. It determines the amount of the pasture that is available per cow, the proportion of the pasture that is consumed, and also influences the quality and long‐term productivity of the sward. Stocking rate is a crucial variable in New Zealand because pasture systems there are designed to maximize returns per acre. In contrast, dairy production in the USA traditionally focuses on returns per cow, and even where pastures are used, concentrates and supplemental forage are fed to maintain high levels of milk production per cow. Although grazing is increasing in t...

Adequate forage amounts in both physical and chemical forms are necessary for proper ruminal function in dairy cows. Under conditions in which total amounts of forage or particle size of the forage are reduced, cows spend less time ruminating and have a decreased amount of buoyant digesta in the rumen. These factors reduce saliva production and allow ruminal pH to fall, depressing activity of cellulolytic bacteria and causing a prolonged period of low ruminal pH. Insufficient particle size of the diet decreases the ruminal acetate-to-propionate ratio and reduces ruminal pH. The mean particle size of the diet, the variation in particle size, and the amount of chemical fiber (i.e., NDF or ADF) are all nutritionally important for dairy cows. Defining amounts and physical characteristics of fiber is important in balancing dairy cattle diets. Because particle size plays such an important role in digestion and animal performance, it must be an important consideration from harvest through feeding. Forages should not be reduced in particle size beyond what is necessary to achieve minimal storage losses and what can be accommodated by existing equipment. Forage and total mixed ration (TMR) particle sizes are potentially reduced in size by all phases of harvesting, storing, taking out of storage, mixing, and delivery of feed to the dairy cow. Mixing feed causes a reduction in size of all feed particles and is directly related to TMR mixing time; field studies show that the longest particles (>27 mm) may be reduced in size by 50%. Forage and TMR particle size as fed to the cows should be periodically monitored to maintain adequate nutrition for the dairy cow.

A beef herd submodel was created for integration with other farm components to form a whole-farm model capable of simulating a wide range of beef production systems. This herd submodel determined the best available feed or feed mix to meet the fiber, energy, and protein requirements for each of up to six animal groups on the farm. The groups comprised any combination of cows, nursing calves, young heifers, yearling heifers, stockers, and finishing cattle. Protein, energy, and mineral requirements were determined for each group using the Cornell Net Carbohydrate and Protein System, Level 1. Diets were formulated to meet these requirements with available feeds, and the resulting feed intake, growth, and manure DM and nutrient (N, P, and K) excretions were predicted. Required feed characteristics included CP, ruminally degradable protein, acid detergent insoluble protein, NDF, P, and K concentrations. Feed intake was predicted by considering energy intake, potentially limited by fill, and exceeding a minimum roughage requirement. Fill and roughage limits were functions of feed NDF concentrations adjusted to consider particle size distribution and the relative rate of ruminal digestibility or the physical effectiveness of the fiber. The herd submodel was verified to predict feed intakes, nutrient requirements, diets, and manure excretions similar to those recommended or measured for beef animals. Incorporation of the beef herd submodel with other farm components, including crop growth (alfalfa, grass, corn, small grain, and soybean), harvest, storage, feeding, grazing, and manure handling, provided the Integrated Farm System Model. This comprehensive farm-simulation model is a useful research and teaching tool for evaluating and comparing the long-term performance, economics, and environmental impact of beef, dairy, and crop production systems.

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