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Expanding from within

Even with drought and the vagaries of the market, continued strong calf prices and the knowledge that calf supplies will tighten even more when national herd expansion begins is tempting many cow-calf producers to begin thinking about expansion.

Unfortunately, if breeding females are purchased when cattle prices are at or near cyclical peaks, they can have a couple of economic strikes against them from the first day of ownership. For one thing, their higher cost means they have more ground to cover just to breakeven. And, secondly, the fact their first several calves will likely be sold into a market featuring prices that are trending down makes covering that distance even tougher.

For cyclical perspective, 2003 marked the eighth year of liquidation in the current cattle cycle, making it the longest on record. Derrell Peel, Oklahoma State University livestock marketing specialist, points out the liquidation that began in 1996 can really be defined by two phases.

From 1996 through 2000, he says, the 5.5% decline was classical and widespread with 14 of the top 20 beef cow states showing either no growth or reduced growth. Driven primarily by drought, he says 2001-2003 has featured net liquidation of another 2%, although expansion has occurred in several states. These include Kansas, Missouri, Oklahoma and Tennessee.

Whenever expansion begins, it will take more cattle out of the market and further boost prices. The good news is that since as many as 20% of the nation's cows fail to wean a calf in any given year, there appears to be plenty of opportunity for many cow-calf producers to grow their cow factory simply by increasing the efficiency of the resources they already have.

A couple of years ago, James McGrann an economist at Texas A&M University (TAMU), underscored the rule of thumb of 90% of cows getting bred and 90% of those calving and weaning a calf. The confirmation came via his delving into USDA inventory data, corroborated by a decade's worth of data from Southwest Standard Performance Analysis (SPA) participants.

Using Southwest SPA data for 1991-2000, the average weaning rate (weighted by herd size) was 79.5%. Across 363 herds and 241,884 cows, the annual cow cost for the 25% most profitable producers was $317.

Therefore, in a herd of 100 head, if one increased weaning percent by 5%, you decreased lost opportunity by 25% through cost alone. Never mind the returns from five more calves.

Multiple Returns

Moreover, selecting and managing cattle so that more of them conceive and calve earlier can make a significant difference in the annual bottom line. In an example offered up by the Noble Foundation in Oklahoma (see Table 1), for instance, the difference in getting 80% bred within the first 45 days, compared to 30% (assuming 50-head herds and that all wean a calf) can be equivalent to weaning five more calves. The gain comes from the opportunity to sell calves that are older at weaning time and thus, hopefully, weigh more.

All of that is before the upward spiral that can occur in subsequent breed-back rates courtesy of more time between calving and breeding for cows to recover and gain back some condition. Plus, females that are inherently more fertile are more likely to conceive in the earliest part of breeding season.

For instance, work by TAMU's L.R. Sprott showed the most fertile cows bred earliest, with the fewest services by the bull and produced the highest percentage of conception within the herd.

Additive Returns

Combine the increased weaning percentage with the increased number of early-bred cows cited here and you've increased production by 10% with the same number of cows. You've expanded without buying or retaining one other female.

Obviously, there are no free lunches. It's possible the cost of achieving such gains outweighs the returns. However, it's just as possible that gains in one area of production leverage more gains in another area for the same cost.

That SPA data mentioned earlier? The 25% most profitable herds in terms of net income weaned 4% more calves and weaned calves that weighed 47 lbs. more on average compared to the 25% least profitable herds. The most profitable herds also spent 70% less for annual cow carrying costs ($317) than the least profitable ($539).

All told, the most profitable herds netted an average of $139/cow, vs. the average of $216/cow lost by the least profitable ones.

Table 1. Differences in weaning distribution, projected weaning weight and total pounds weaned for two 50-head herds with different calving distributions in a 90-day breeding season.

Example 1
Breeding Cycle (days) (lbs.) # Born (head) Days to Weaning Weight per Day of Age (lbs.) Projected Weaning Weight (lbs.) Total Weight at Weaning
1-21 30 210 2.65 557 16,710
21-42 10 189 2.65 501 5,010
42-63 5 168 2.65 445 2,225
63-90 5 147 2.65 390 1,950
Total 25,895
Example 2
1-21 5 210 2.65 557 2,785
21-42 10 189 2.65 501 5,010
42-63 30 168 2.65 445 13,350
63-90 5 147 2.65 390 1,950
Total 23,095
Source: The Samuel Roberts Noble Foundation, Inc.

Great Expectations

This will make you pull your hair out. Based on the pull rates of several million head of stocker and feeder-weight cattle over the years, Dee Griffin says morbidity rates seem to always hover around 15%.

The perfect set of low-risk calves might run 12-15%, while the sorriest set of trade bait walking, which should run 100%, will on average only have 15-20% pulled for treatment, explains Griffin, a veterinarian recognized industry-wide for blending common sense with science in treating stocker and feeder cattle. He's also a professor of beef cattle production management at the University of Nebraska.

Griffin has a theory on why this is, which we'll get to, but the fact underscores vexing questions common among backgrounders and stocker operators. These include: How much sickness is too much? How much response rate is too little? And, how much money should you pour into treatment, and when, to know whether or not the strategy is both effective and cost effective?

At least part of the answer lies in the fact that although endemic challenges like bovine respiratory disease (BRD) occur at a variable rate, they have a predictable pattern. That's why you expect a percentage of each load of calves to break with BRD. The percentage will vary, but you know up front that the pathogens involved, and the stress on young cattle during the marketing and delivery process, means you'll see it.

This is epidemiology in a nutshell — understanding the cause and incidence of disease from the standpoint of entire populations.

Managing Source Is Key

“I suppose the non-epidemiological approach is where everybody starts,” Griffin says. “You have to start someplace, so you put together treatments that make sense based on historic problems, isolations of specific pathogens, the timing of them, and sensitivity of pathogens to certain products in the past.”

So, everybody starts with past experience, common sense, hope and, hopefully, an understanding of what Griffin terms the “three S's of disease” — source, source and source.

“You put together cattle, commingle them, that's a source issue. The stress associated with transportation and distance in delivering cattle is a source issue. The timing of when cattle are available that fit a particular breakeven pattern is a source issue, too,” Griffin says. Consequently, minimizing a challenge like BRD begins with managing these source issues.

Immunological preparation of cattle via preconditioning programs is one example. So is working to reduce the time stress of procurement and delivery.

“From an epidemiological standpoint, we know precisely what the pathogens are and what the sources are. All we don't know on a set of calves is how well-prepared their immune systems are,” Griffin explains. Consequently, he says the industry relies on receiving programs as the first line of defense.

“I don't think you can afford not to mass-medicate off the truck if they're put-together cattle, high-stress cattle or both,” he says.

Moreover, Griffin is adamant that what people believe to be animal health product failure is usually human failure.

“With the drugs available today — the best the industry has ever had — failure of response is not failure of the drug. It's our failure to give the drug a chance to work,” he says. “When drugs don't work, it's usually a matter of the immunological preparation of the cattle and/or the timing of therapy.”

In fact, time continues to be the primary disease weapon over which producers have some control.

Griffin points out that cattle — as prey animals — have a genetic heritage to hide illness. “The cattle have to get to know and trust us so they'll be less likely to hide disease symptoms from us for as long,” he says.

Beyond that, Griffin emphasizes: “The only other ace is to pull the trigger quick, and the best trigger you can pull is to intercept the pathogenesis with mass medication coming off the truck.”

Once infected, time of treatment is crucial. Since at least 10% of pulls won't respond to first treatment, Griffin suggests using long-acting antibiotics, and he never returns cattle to their home bunch the first day. He keeps them in the hospital. If they're improving on Day 3, he gives them a second round and sends them home. The industry has found this four-day approach increases response rate and reduces re-pulls, but the economics of this approach must be considered.

Value Of Deads And Records

Griffin says taking an epidemiological approach to fighting disease begins with finding out why cattle die and keeping records to build specific knowledge.

“You need to take a hard look at cattle that die. They might be the most valuable cattle you've got because they can help you evaluate timing effects, whether the treatment you've used is appropriate for the bugs isolated, and how that compares to what others are seeing,” he says.

He adds that necropsy and culture results obtained from diagnostic labs offer little or no help in treating existing groups of cattle. But the data helps make better decisions down the road.

Next, come the records. Real epidemiology requires loads of observations of cattle that exist in the same population. Think in terms of 4-weight Holstein steers from a particular part of the country and stockered during a particular season, rather than 4-weight cattle in general. Such data is invaluable, but acquiring it takes lots of years, even for the largest operations.

That said, Griffin believes there are records producers can use to their benefit along the way. In addition to traditional kinds of group records, such as source, supplier, in-weight, shrink, individual records for each head pulled and treated, etc., Griffin recommends keeping a daily weather log.

“Producers should record the daily high and low temperatures and a description of the weather conditions that day,” Griffin says. It helps put pulls and response rate in context.

Griffin also cautions: “The only objective hospital cattle data we can collect is their temperature, but that can also be our Achilles' heel.” Since time of day can affect cattle temperatures by 2° F, and cattle sickest the longest will typically have lower temperatures than those just breaking with a disease, Griffin suggests using temperature to gauge disease progress, not whether cattle should be treated if pulled to begin with.

He recommends pen riders use their eyes and experience to pull cattle, then score them on a 5-point scale, with 1 being “just in case,” and 5 being, “Lord, I doubt he'll make it to the hospital.”

“I believe you should score cattle independent of the thermometer because all too often people let the thermometer do their thinking for them,” Griffin says.

Response Rules Of Thumb

Even when everything is done just right, about 15% are going to end up sick. Griffin believes the logic-defying similarity in morbidity between low-risk calves and high-risk ones — based on closeouts — boils down to human nature. He contends pull rates for low-risk cattle are artificially high because folks will often pull and treat cattle out of habit, rather than actual need.

But, Griffin notes that more than half of high-risk cattle have lung lesions at the packing plant — an indication of respiratory pneumonia — compared to 20-30% for low-risk cattle.

“A thumb rule I've used for 20 years is that if 18 of 20 head pulled are getting better (90% response rate), then I'm doing a good job. Below 90%, I either have the wrong therapy or, more likely, I got a late start because of a source problem,” he says.

He adds that of the non-responders, he expects 10-20% mortality (equivalent to 1-2% respiratory death loss overall).

“Anytime I'm consistently experiencing death loss more than 2%, I most likely have a source problem. That's when epidemiology and the economics of its application to the correction kicks in to high gear,” Griffin says. “I think we know enough about disease, and have good enough animal health products, that we can accomplish that provided the source-related health problems don't dig the grave.

“Epidemiology can help clarify the value of money spent on cattle and their cattle health problems. Throwing dollars at processing and treatment won't fix source-related health problems but, on the other hand, a profit opportunity can be missed trying to starve, discount or penny-pinch cattle,” he adds.

Finally, Griffin figures spending 6-8% of the animal's purchase cost for treatment, excluding processing costs, is the outer limit.

“You've got to know when to let them go,” he says. “My regimen is to give them two rounds of therapy, then if they're improving, it's between them and God.”

Mass Med Math

As far as Dee Griffin is concerned, decades of research support the fact that metaphylactic treatment (mass medication) of feeder- and stocker-weight cattle upon arrival significantly reduces the number of pulls and subsequent re-pulls for bovine respiratory disease.

“There's no question mass medication works,” says Griffin, a veterinarian and University of Nebraska professor. The only question about metaphylaxis is whether the gains it offers will provide a net economic return in a particular situation. And, that boils down to simple math, including the cost of lost performance.

“If metaphylactic treatment costs $10 per head, and if you're planning to put 200 lbs. on cattle in the stocker pasture, then the treatment adds 5¢/lb. to the cost of gain,” he says.

But, say you figure that without such treatment you'll have 20% morbidity in a group of 100 head, $20/head treatment cost. That's the equivalent of $4/head or $2/cwt. of gain.

At first glance, doing nothing seems economically prudent. But, Griffin says, “You can also expect any calf that gets sick to lose 28 days' worth of gain. So, it's reasonable to expect a calf that got sick to weigh 30 lbs. less than one that didn't get sick.”

Thus, 30 lbs. at $90/cwt. for a seven-weight calf is $27. Across 20 calves that's $540, or about $2.80/cwt., added cost to the entire group. So, factor in the lost performance and doing nothing costs $4.80/cwt., vs. $5/cwt. for treating cattle on arrival.

Obviously, this is a simplistic scenario. Outcomes will vary by actual metaphylactic cost, morbidity rate, treatment costs and response rates, how many of the sicks turn out to be re-pulls and chronics and so on. The point is when figuring the cost of a preventive treatment like metaphylaxis, producers must also consider the price of lost performance — the opportunity cost — of ignoring preventive treatment.

Typical Composition of Feeds for Cattle and Sheep, 2004

Accompanying this discussion is a table showing the typical composition of feedstuffs and ingredients commonly used in the feeding of cattle and sheep in North America. What is the purpose of this information? Nutrition research spanning more than 100 years has defined the nutrients required by animals. Using this information, diets can be formulated from feedstuffs and ingredients to meet these requirements with the expectation that animals will not only remain healthy but will also be productive and efficient. The ultimate goal of feedstuff analysis is to predict the productive response of animals when they are fed diets of a given composition. This is the real reason for information on feedstuff composition.

Table composition values

Feedstuffs are not of constant composition. Unlike chemicals that are “chemically pure” and therefore have a constant composition, feeds vary in their composition for many reasons. What is the value, then, of showing composition data for feedstuffs?

No one will argue that an actual analysis of a feed to be used in a diet is much more accurate than the use of tabulated composition data. Actual analysis should be obtained and used whenever possible.

Often, however, it is either impossible to determine actual composition or there is insufficient time to obtain such analysis. Therefore tabulated data are the next best source of information.

In using tabulated data, understand that feeds vary in their composition. Using the data shown in the accompanying table, one can expect the organic constituents (e.g., crude protein, ether extract, crude fiber, acid detergent fiber and neutral detergent fiber) to vary as much as ±15%, the mineral constituents to vary as much as ±30% and the energy values to vary up to ±10%. Therefore, values shown can only be guides.

For this reason they are called “typical values.” They are not averages of published information since judgment was used in arriving at some of the values in the hope these values will be realistic for use in formulating diets.

New crop varieties usually result in nutrient composition changes. Crops modified through genetic engineering will result in feeds with generally improved nutrient content and availability and/or decreased anti-nutrient factors.

Chemical constituents vs. biological attributes

Feeds can be chemically analyzed for many things that may or may not be related to the response of an animal when fed the feed. Thus, in the accompanying table, certain chemical constituents are shown. The response of cattle and sheep when fed a feed, however, can be termed the biological response to the feed that is a function of its chemical composition and the ability of the animal to derive useful nutrient value from the feed.

The latter relates to the digestibility or availability of a nutrient in the feed for absorption into the body and its ultimate efficiency of use depending upon the nutrient status of the animal and the productive or physiological function being performed by the animal. Thus, ground fence posts and shelled corn may have the same gross energy value but have markedly different useful energy value [total digestible nutrients (TDN) or net energy] when consumed by the animal.

Therefore, biological attributes of a feed have much greater meaning in predicting the productive response of animals but are more difficult to accurately determine because there is an interaction between the chemical composition of a feed with the digestive and metabolic capabilities of the animal being fed. Biological attributes of feeds are more laborious and costly to determine and are more variable than chemical constituents. They are generally more predictive, however, since they relate to the response of an animal being fed the feed or diet.

Source of information shown in the table

Several sources of information were used in arriving at the “typical values” shown in the table. Where information was not available but a reasonable estimate could be made from similar feeds or stage of maturity, this has been done since it is not too helpful to have a table with considerable missing information. Where zeros appear, the amount is so small that it can be considered insignificant in practical diet formulation. Blanks indicate that the value is unknown. The table this year contains revisions as well as values for feeds not included in previous tables.

Using information contained in the table

Feed names: The most obvious or commonly used feed names are given in the table. Feeds designated as “fresh” are feeds that are grazed or fed as fresh-cut materials.

Dry matter: Typical dry matter (DM) values are shown; however, the moisture content of feeds can vary greatly. Therefore, DM content can be the biggest reason for variation in feedstuff composition on an “as-fed basis.” For this reason, chemical constituents and biological attributes of feeds shown in the table are on a DM basis.

Since DM can vary greatly and since one of the factors regulating total feed intake is the DM content of feeds, diet formulation on a DM basis is sounder than using “as-fed basis.” If one wants to convert a value shown to an “as-fed basis,” multiply the decimal equivalent of the DM content times the compositional value shown in the table.

Energy: Four measures of the energy value of feeds are shown in the table. TDN is shown because there are more determined TDN values for feeds, and because this has been the standard system for expressing the energy value of feeds for cattle and sheep.

There are several technical problems with TDN, however. The digestibility of crude fiber may be higher than for nitrogen-free extract in certain feeds. TDN also overestimates the value of roughages compared to concentrates in producing animals. Some have argued that energy is not measured in pounds or percent and therefore TDN is not a valid measure of energy. However, this is more a scientific argument than a criticism of the predictive value of TDN.

Digestible energy (DE) values are not included in the table. There is a constant relationship between TDN and digestible energy (DE) in cattle and sheep; DE (Mcal/cwt.) can be calculated by multiplying the %TDN content by 2. It should be apparent, therefore, that the ability of TDN and DE to predict animal performance is equal.

Interest in the use of net energy (NE) in evaluating feeds for cattle and sheep was renewed with the development of the California net energy system. The main reason for this is the improved predictability of results depending on whether feed energy is being used for maintenance (NEM), growth (NEG) or lactation (NEL). The major problem in using these NE values for growing cattle and sheep is predicting feed intake and, therefore, the proportion of feed that will be used maintenance and growth.

Some only use the NEG values but it should be obvious that this suffers the equal, but opposite, criticism mentioned for TDN; NEG will overestimate the feeding value of concentrates relative to roughages. The average of the two NE values can be used, but this would be true only for cattle and sheep eating twice their maintenance requirement.

The most accurate way to use these NE values to formulate diets would be to use the NEM value plus, a multiplier, times the NEG value, all divided by one plus the multiplier; the multiplier is the level of feed intake above maintenance relative to maintenance. For example, if 700-lb. cattle are expected to eat 18 lbs. of DM, 8 lbs. of which will be required for maintenance, then the NE value of the diet would be:

NE = [NEM + (10/8)(NEG)]/[1 + (10/8)]

Such a calculation can be easily introduced into computer programs designed to formulate diets and predict performance.

In deciding on the energy system to use, there is no question on the theoretical superiority of NE over TDN in predicting animal performance. This superiority is lost, however, if only NEG is used in formulating diets. If NE is used, some combination of NEM and NEG is required. NEL values are also shown. Few NEL values have actually been determined. However, NEL values are similar to NEM values except for very high and low energy feeds.

Protein: Crude protein (CP) values are shown for each feed, which are Kjeldahl nitrogen times 100/16 or 6.25, since proteins contain 16% nitrogen on the average. CP does not give any information on the actual protein and non-protein nitrogen content of a feed.

Digestible protein (DP) has been included in many tables of feed composition but because of the contribution of microbial and body protein to the protein in feces, DP is more misleading than CP. One can estimate DP from the CP content of the diet fed to cattle or sheep by the following equation: %DP = 0.9(%CP) -3; where %DP and %CP are the diet values on a DM basis.

Undegradable intake protein [(UIP) rumen “bypass” or escape protein] values are shown. This value represents the percent of CP that passes through the rumen without being degraded by the rumen microorganisms. Degradable intake protein (DIP) is the percent of CP that is degraded in the rumen and is equal to 100 minus UIP. Like other biological attributes, these values are not constant. UIP values on many feeds have not been determined and reasonable estimates are difficult to make.

How should these values be used to improve the predictability of animal response when fed various feeds? Generally, DIP can supply CP up to 7% of the diet. If the CP required in the diet exceeds 7% of the DM, all CP above this amount should be UIP. In other words, if the final diet is to contain 13% CP, 6 of the 13 percentage units, or 46% of the CP should be in the form of UIP. Once the relationships between UIP and DIP have been better quantified, CP requirements may be lowered especially at higher CP levels. On diets high in rumen fermentable carbohydrate, DIP requirements may determine the total CP required in the diet.

Crude, acid detergent and neutral detergent fiber: After more than 125 years, crude fiber (CF) is declining in popularity as a measure of poorly digestible carbohydrates in feeds. CF's major problem is that variable amounts of lignin, which isn't digestible, are removed in the CF procedure. In the old scheme, the remaining carbohydrates [nitrogen-free extract; (NFE)] were thought to be more digestible than CF even though many feeds have been shown to have a higher digestibility for CF than NFE. One reason CF remained in the analytical scheme was its apparent requirement for the calculation of TDN.

Improved analytical procedures for fiber have been developed, namely acid detergent fiber (ADF) and neutral detergent fiber (NDF). ADF is related to digestibility and NDF is also somewhat related to voluntary intake and the availability of net energy. Both of these measures relate more directly to predicted animal performance and, therefore, are more valuable than CF. Lignification of NDF, however, alters availability of surface area to fiber digesting rumen microorganisms; therefore, lignin may be added to future tables.

Recently, effective NDF (eNDF) has been proposed to better describe the dietary fiber function in high-concentrate, feedlot-type diets. While eNDF is defined as the percent of NDF that is retained on a screen similar in size to particles that will pass from the rumen, this value is further modified based on feed density and degree of hydration.

Rumen pH is correlated with dietary eNDF when diets contain less than 26% eNDF. Thus when formulating high concentrate diets, including eNDF will help to prevent acidosis in the rumen.

Recommended eNDF levels for feedlot diets from range from 5 to 20% depending on bunk management, inclusion of ionophores, digestion of NDF and/or microbial protein synthesis in the rumen. Therefore, estimated eNDF values are shown for many feeds.

These values must be modified, however, depending on degree of feed processing (eg., chopping, grinding, pelleting) and hydration (fresh forage, silages, high-moisture grains) if these feed forms are not specified in the table.

Ether extract: Ether extract (EE) shows the crude fat content of the feed.

Minerals: Values are shown for only certain minerals. Calcium (Ca) and phosphorus (P) are important minerals to consider in most feeding situations. Potassium (K) becomes more important as the level of concentrate increases and when non-protein nitrogen is substituted for intact protein in the diet.

Sulfur (S) also becomes more important as the level of non-protein nitrogen increases in the diet; high S levels in diets compounded by high S levels in drinking water can be detrimental. Zinc (Zn) is shown because it is less variable and is more generally near a deficient level in cattle and sheep diets. Chlorine (Cl) is of increasing interest for its role in dietary acid-base relationships.

Several other minerals could logically be included in the table. The level of many trace minerals in feeds is largely determined by the level in the soil on which the feeds are grown or other environmental factors that preclude showing a single value in a table of feed composition.

Iodine and selenium are required nutrients that may be deficient in many diets, yet their level in feed is more related to the conditions under which the feed is grown than to a characteristic of the feed itself. Trace-mineralized salt and trace mineral premixes are generally used to supplement trace minerals. The use of these supplements is encouraged where there are known deficiencies of certain trace minerals.

Vitamins: Vitamins have been omitted from the table. The only vitamin of general practical importance in cattle and sheep feeding is the vitamin A value (vitamin A and carotene) in feeds that depend largely on maturity and conditions at harvest, and the length and conditions of storage. Therefore, it is probably unwise to rely entirely on harvested feeds as a source of vitamin A value.

Where roughages are being fed that contain good green color or are being fed as immature fresh forages (e.g., pasture), there will probably be sufficient vitamin A value to meet the animal's requirement. Other vitamins, if required, should be supplied as supplements.

Future revisions, additions and deletions

A table of feed composition is of value only if it is relatively complete, contains feeds commonly fed and the data are updated with new compositional values. I welcome suggestions and compositional data to keep this table useful to the cattle and sheep feeding industry. When sending compositional data, please adequately describe the feed, indicate the dry matter or moisture content and whether analytical values are given on an as-fed or dry-matter basis. If more than one sample of a feedstuff was analyzed, the number of samples analyzed should be indicated.

Editor's Note: Since 1957, R.L. Preston has taught and conducted animal nutrition research in the areas of protein, minerals, growth and body composition. He also has conducted cattle feeding research on the energy value of feeds, growth promotants and nutrition management.

Preston has been a member of the NRC Committee on Animal Nutrition and president of the American Society of Animal Science. Retired as Emeritus Professor from Texas Tech University, where he was Horn Distinguished Professor and held the Thornton Endowed Chair, Preston's current address is 191 Columbia Court, Pagosa Springs, CO, 81147-7650.

Feeds affected by the BSE feed regulation

Because of the threat of bovine spongiform encephalopathy (BSE), the Food and Drug Administration (FDA) has issued regulations that affect the feeding of certain feeds to ruminants (cattle and sheep) as a precautionary measure to help prevent this disease in the U.S. Blood meal, bone meal, meat-and-bone meal and poultry litter are the regulated feeds. Therefore, poultry litter has been removed from this feed table, since ruminant protein feeds can be fed to poultry and feed waste can become incorporated into poultry litter. Blood meal, bone meal and meat-and-bone meal can be fed to ruminants only if it is derived from swine or poultry. Therefore, the description for these feeds in the feed table has been changed to reflect this requirement.

(All values except dry matter are shown on a dry matter basis)

FEEDSTUFF ENERGY PROTEIN FIBER
DM TDN NEM NEG NEL CP BYPASS CF ADF NDF eNDF EE ASH CA P K CL S ZN
% % Mcal/cwt. % % % % % % % % % % % % % ppm
Alfalfa Cubes 91 57 57 25 57 18 30 29 36 46 40 2.0 11 1.30 0.23 1.9 0.37 0.35 20
Alfalfa Dehydrated 17% CP 92 61 62 31 61 19 60 26 34 45 6 3.0 11 1.42 0.25 2.5 0.45 0.24 21
Alfalfa Fresh 24 61 62 31 61 19 18 27 34 46 41 3.0 9 1.35 0.27 2.6 0.40 0.28 18
Alfalfa Hay Early Bloom 90 59 59 28 59 19 20 28 35 45 92 2.5 8 1.41 0.26 2.5 0.38 0.27 22
Alfalfa Hay Midbloom 89 58 58 26 58 17 23 30 36 47 92 2.3 9 1.40 0.24 2.0 0.38 0.26 24
Alfalfa Hay Full Bloom 88 54 54 20 54 16 25 34 40 52 92 2.0 8 1.20 0.23 1.7 0.37 0.23 23
Alfalfa Hay Mature 88 50 50 12 49 13 30 38 45 59 92 1.3 8 1.18 0.19 1.5 0.35 0.20 23
Alfalfa Seed Screenings 91 84 92 61 87 34 13 15 10.5 6 0.30 0.67
Alfalfa Silage 30 55 55 21 55 18 19 28 37 49 82 3.0 9 1.40 0.29 2.6 0.41 0.29 26
Alfalfa Silage Wilted 39 58 58 26 58 18 22 28 37 49 82 3.0 9 1.40 0.29 2.6 0.41 0.29 26
Alfalfa Leaf Meal 89 69 71 43 70 28 15 15 25 34 35 2.7 15 2.88 0.34 2.2 0.32 39
Alfalfa Stems 89 47 47 7 46 11 44 44 51 68 100 1.3 6 0.90 0.18 2.5
Almond Hulls 89 59 59 28 59 5 60 16 27 35 100 3.3 7 0.25 0.10 2.0 0.03 0.07 20
Ammonium Chloride 99 0 0 0 0 163 0 0 0 0 0 0.0 0.00 0.00 0.0 66.00 0.00 0
Ammonium Sulfate 99 0 0 0 0 132 0 0 0 0 0 0.0 24.15
Apple Pomace Wet 20 68 70 41 69 6 10 17 34 40 34 5.6 4 0.14 0.14 0.6 0.06 11
Apple Pomace Dried 89 65 66 37 66 5 15 19 35 45 34 5.2 4 0.13 0.12 0.5 0.02
Artichoke Tops (Jerusalem) 27 61 62 31 61 6 18 30 41 40 1.1 10 1.62 0.11 1.4
Avocado Seed Meal 91 52 52 16 51 20 19 24 1.2 16
Bahiagrass Hay 90 51 51 14 50 8 37 32 41 72 98 1.9 8 0.48 0.20 1.4 0.21
Bakery Product Dried 90 90 100 68 94 12 30 4 6 14 0 11.0 4 0.18 0.28 0.3 2.25 0.15 33
Barley Hay 90 57 57 25 57 9 28 37 65 98 2.1 8 0.30 0.28 1.6 0.19 25
Barley Silage 35 59 58 26 58 12 22 34 37 58 61 3.0 9 0.46 0.30 2.4 0.22 28
Barley Silage Mature 35 58 58 26 58 12 25 30 34 50 61 3.5 9 0.30 0.20 1.5 0.15 25
Barley Straw 90 43 44 0 42 4 70 42 52 78 100 1.9 7 0.33 0.08 2.1 0.67 0.16 7
Barley Grain 89 84 92 61 87 12 28 5 7 19 34 2.1 3 0.06 0.38 0.6 0.18 0.16 23
Barley Grain, Steam-Flaked 85 90 100 70 100 12 39 5 7 19 30 2.1 3 0.06 0.35 0.6 0.18 0.16 23.00
Barley Grain, Steam-Rolled 86 84 92 61 87 12 38 5 7 19 27 2.1 3 0.06 0.41 0.6 0.18 0.17 30
Barley Grain 2-row 87 84 92 61 87 12 6 8 24 34 2.3 2 0.05 0.31 0.6 0.18 0.17
Barley Grain 6-row 87 84 92 61 87 11 6 8 24 34 2.2 3 0.05 0.36 0.6 0.18 0.15
Barley Grain Lt. Wt. (42-44 lbs./bu.) 88 78 83 54 80 13 30 9 12 30 34 2.3 4
Barley Feed Pearl By-product 90 73 77 48 75 15 12 15 3.9 5 0.05 0.45 0.7 0.06
Barley Grain Screenings 89 77 82 53 79 12 9 11 2.6 4 0.30 0.33 0.7 0.15
Beans Navy Cull 90 84 92 61 87 24 25 5 8 20 0 1.4 5 0.15 0.59 1.4 0.06 0.26 45
Beet Pulp Wet 17 76 81 52 78 11 35 20 23 48 33 0.7 6 0.68 0.08 1.4 0.40 0.21 20
Beet Pulp Dried 91 75 79 50 77 11 44 21 21 41 33 0.7 6 0.65 0.08 1.4 0.40 0.22 22
Beet Pulp Wet with Molasses 24 77 82 53 79 11 25 16 21 39 33 0.6 6 0.60 0.10 1.8 0.42 11
Beet Pulp Dried with Molasses 92 76 81 52 78 11 34 17 22 40 33 0.6 6 0.60 0.10 1.8 0.42 11
Beet Tops (Sugar) 20 58 58 26 58 14 10 14 25 41 1.5 24 1.20 0.23 5.1 0.20 0.45 20
Beet Top Silage 25 52 52 16 51 12 12 2.0 32 1.38 0.22 5.7 0.57 20
Bermudagrass Coastal Dehydrated 90 62 63 33 63 16 40 26 29 40 10 3.8 7 0.40 0.25 1.8 0.23 18
Bermudagrass Coastal Hay 89 56 56 23 56 10 20 30 36 73 98 2.1 6 0.47 0.21 1.5 0.22 16
Bermudagrass Hay 89 53 53 18 53 10 18 30 39 78 98 1.9 8 0.46 0.20 1.5 0.25 33
Bermudagrass Silage 26 50 50 12 49 10 15 30 37 77 48 1.9 8 0.46 0.20 1.5 0.25 33
Birdsfoot Trefoil Fresh 22 66 68 38 67 21 20 21 31 47 41 4.4 9 1.78 0.25 2.6 0.25 31
Birdsfoot Trefoil Hay 89 57 57 25 57 16 22 31 38 50 92 2.2 8 1.73 0.24 1.8 0.25 28
Biuret 99 0 0 0 0 248 0 0 0 0 0 0.0 0 0.00 0.00 0.0 0.00 0.00 0
Blood Meal, Swine/Poultry 91 66 68 38 67 92 80 1 2 10 0 1.4 3 0.32 0.28 0.2 0.30 0.70 22
Bluegrass KY Fresh Early Bloom 36 69 71 43 70 15 20 27 32 60 41 3.9 7 0.37 0.30 1.9 0.42 0.19 25
Bluegrass Straw 93 45 45 3 44 6 40 50 78 90 1.1 6 0.20 0.10
Bluestem Fresh Mature 61 50 50 12 49 6 34 2.5 5 0.40 0.12 0.8 0.05 28
Bone Meal Steamed, Swine/Poultry 95 16 27 0 11 13 1 0 0 0 11.6 77 27.00 12.74 0.2 2.50 290
Bread By-product 68 91 102 69 95 14 24 1 2 3 0 3.2 3 0.09 0.18 0.2 0.76 0.15 40
Brewers Grains Wet 23 85 93 62 88 26 52 13 21 44 18 7.6 4 0.29 0.61 0.1 0.15 0.32 78
Brewers Grains Dried 92 84 92 61 87 24 54 14 24 50 18 9.2 4 0.29 0.60 0.1 0.15 0.32 78
Brewers Yeast Dried 94 79 85 55 81 48 3 1.0 7 0.10 1.56 1.8 0.41 41
Bromegrass Fresh Immature 30 64 65 36 65 15 22 28 33 54 40 4.1 10 0.45 0.34 2.3 0.21 20
Bromegrass Hay 89 55 55 21 55 10 33 35 41 66 98 2.3 9 0.40 0.23 1.9 0.40 0.18 19
Bromegrass Haylage 35 57 57 25 57 11 26 36 44 69 61 2.5 8 0.38 0.30 2.0 0.20 19
Buckwheat Grain 88 77 82 53 79 12 12 17 2.8 2 0.11 0.36 0.5 0.05 0.16 10
Buttermilk Dried 92 88 98 65 91 34 0 5 0 0 0 5.0 10 1.44 1.00 0.9 0.09 44
Cactus 26 63 64 34 64 5 18 23 29 2.1 17 3.50 0.10 1.7 0.20
Calcium Carbonate 99 0 0 0 0 0 0 0 0 0 0.0 99 38.50 0.04 0.1 0.00 0
Canarygrass Hay 91 53 53 18 53 9 26 32 34 67 98 2.7 8 0.38 0.25 2.7 0.14 18
Canola Meal Solvent 90 71 74 46 73 40 30 12 20 29 23 4.0 8 0.75 1.16 1.3 0.07 0.78 68
Carrot Pulp 14 62 63 33 63 6 19 23 40 0 7.8 9
Carrot Root Fresh 12 83 90 60 86 10 9 11 20 0 1.4 10 0.60 0.30 2.4 0.50 0.17
Carrot Tops 16 73 77 48 75 13 18 23 45 41 3.8 15 1.94 0.19 1.9
Cattle Manure Dried 92 38 40 0 36 17 34 37 55 0 2.6 14 1.35 1.00 0.6 1.78 240
Cheatgrass Fresh Immature 21 68 70 41 69 16 23 2.7 10 0.60 0.28
Citrus Pulp Dried 90 79 85 55 81 7 38 13 18 21 33 2.2 7 1.81 0.12 0.8 0.04 0.08 14
Clover Ladino Fresh 19 69 71 43 70 25 20 14 33 35 41 4.8 11 1.27 0.38 2.4 0.20 20
Clover Ladino Hay 90 61 62 31 61 21 25 22 32 36 92 2.0 9 1.35 0.32 2.4 0.30 0.20 17
Clover Red Fresh 24 64 65 36 65 18 21 24 33 44 41 4.0 9 1.70 0.30 2.0 0.60 0.17 23
Clover Red Hay 88 55 55 21 55 15 28 30 39 51 92 2.5 8 1.50 0.25 1.7 0.32 0.17 17
Clover Sweet Hay 91 53 53 18 53 16 30 30 38 50 92 2.4 9 1.27 0.25 1.8 0.37 0.46
Coconut Meal 92 71 74 46 73 21 56 12 22 56 23 6.7 7 0.63 0.21 0.6 0.33 0.04
Coffee Grounds 88 20 36 0 16 13 41 68 77 10 15.0 2 0.10 0.08
Corn Whole Plant Pelleted 91 63 64 34 64 9 45 21 24 40 6 2.4 6 0.50 0.24 0.9 0.14
Corn Fodder 80 67 69 40 68 9 45 25 29 48 100 2.4 7 0.50 0.25 0.9 0.20 0.14
Corn Stover Mature (Stalks) 80 59 59 28 59 5 30 35 44 70 100 1.3 7 0.35 0.19 1.1 0.30 0.14 22
Corn Silage Milk Stage 26 65 66 66 8 18 26 32 54 60 2.8 6 0.40 0.27 1.6 0.11 20
Corn Silage Mature Well Eared 34 72 75 47 74 8 28 21 27 46 70 3.1 5 0.28 0.23 1.1 0.20 0.12 22
Corn Silage Sweet Corn 24 65 66 37 66 11 20 32 57 60 5.0 5 0.24 0.26 1.2 0.17 0.16 39
Corn Grain, Whole 88 88 98 65 91 9 58 2 3 9 60 4.3 2 0.02 0.30 0.4 0.05 0.12 18
Corn Grain, Rolled 88 88 98 65 91 9 54 2 3 9 34 4.3 2 0.02 0.30 0.4 0.05 0.12 18
Corn Grain, Steam Flaked 85 93 104 71 97 9 59 2 3 9 40 4.1 2 0.02 0.27 0.4 0.05 0.12 18
Corn Grain, High Moisture 74 93 104 71 97 10 42 2 3 9 0 4.0 2 0.02 0.30 0.4 0.06 0.13 20
Corn Grain, High Oil 88 91 102 69 95 8 54 2 3 8 60 6.9 2 0.01 0.30 0.3 0.05 0.13 18
Corn Grain, Hi-Lysine 92 87 96 64 90 12 58 4 4 11 60 4.4 2 0.03 0.24 0.4 0.05 0.11 18
Corn and Cob Meal 87 82 89 59 85 9 52 9 10 26 56 3.7 2 0.06 0.28 0.5 0.05 0.13 16
Corn Cobs 90 48 48 9 47 3 50 36 39 88 56 0.5 2 0.12 0.04 0.8 0.40 5
Corn Screenings 86 91 102 69 95 10 52 3 4 9 20 4.3 2 0.04 0.27 0.4 0.05 0.12 16
Corn Bran 91 76 81 52 78 11 10 17 51 0 6.3 3 0.04 0.15 0.1 0.13 0.08 18
Corn Gluten Feed 90 80 86 56 83 22 25 9 12 40 36 3.2 7 0.12 0.85 1.3 0.25 0.33 84
Corn Gluten Meal 41% CP 91 85 93 62 88 46 58 5 9 32 23 3.2 3 0.13 0.55 0.2 0.07 0.55 35
Corn Gluten Meal 60% CP 91 89 99 67 93 67 60 4 6 11 23 2.6 3 0.06 0.54 0.2 0.10 0.82 40
Corn Cannery Waste 29 68 70 41 69 8 15 28 36 59 0 3.0 5 0.10 0.29 1.0 0.13 25
Cottonseed, Whole 91 95 107 73 99 23 38 29 39 47 100 17.8 4 0.14 0.64 1.1 0.06 0.24 34
Cottonseed, Whole, Extruded 92 87 98 67 91 26 50 32 44 53 33 9.5 5 0.17 0.68 1.3 0.24 38
Cottonseed, Whole, Delinted 90 95 107 73 99 24 39 20 29 40 100 22.2 4 0.13 0.55 1.2 0.24 36
Cotton Gin Trash (Burrs) 91 42 43 0 40 10 34 51 70 100 2.0 14 1.70 0.25 1.9 0.14 25
Cottonseed Hulls 90 45 45 3 44 5 45 48 68 87 100 1.9 3 0.15 0.08 1.1 0.02 0.05 10
Cottonseed Meal, CP Mech. 41% 92 80 86 56 83 46 50 13 18 31 23 5.0 7 0.21 1.19 1.7 0.05 0.42 64
Cottonseed Meal, Solvent 41% CP 90 77 82 53 79 48 42 13 17 25 23 1.8 7 0.22 1.25 1.7 0.05 0.44 66
Crab Waste Meal 91 29 37 0 30 32 65 11 13 3.0 43 15.00 1.88 0.5 1.63 0.27 107
Crambe Meal, Solvent 91 81 88 58 84 31 45 25 35 47 23 1.4 8 1.27 0.86 1.1 0.70 1.26 44
Crambe Meal, Mech. 92 88 98 65 91 28 50 24 33 42 25 17.0 7 1.22 0.78 1.0 0.65 1.18 41
Cranberry Pulp Meal 88 49 49 11 48 7 26 47 54 33 15.7 2
Crawfish Waste Meal 94 25 36 0 29 35 74 15 42 13.10 0.85
Curacao Phosphate 99 0 0 0 0 0 0 0 0 0 0.0 95 34.00 15.00
Defluorinated Phosphate 99 0 0 0 0 0 0 0 0 0 0.0 95 32.60 18.07 1.0 100
Diammonium Phosphate 98 0 0 0 0 115 0 0 0 0 0 0.0 35 0.52 20.41 0.0 2.16
Dicalcium Phosphate 96 0 0 0 0 0 0 0 0 0 0.0 94 22.00 18.65 0.1 1.00 70
Distillers Grains, Wet 25 90 100 68 94 28 52 8 18 40 4 9.6 6 0.28 0.78 1.2 0.28 0.40 95
Distillers Grain, Barley 90 77 82 53 79 30 56 18 22 45 4 3.7 4 0.15 0.67 1.0 0.18 0.43 50
Distillers Grain, Corn, Dry 91 95 107 73 99 29 60 8 21 44 4 10.5 4 0.15 0.78 0.9 0.14 0.45 65
Distillers Grain, Corn, Wet 36 95 107 73 99 29 55 8 21 43 4 10.5 4 0.15 0.78 0.9 0.14 0.45 65
Distillers Grain, Corn with Solubles 90 92 103 70 96 29 50 9 17 43 4 10.6 6 0.28 0.79 1.0 0.18 0.39 80
Distillers Corn Stillage 7 92 103 70 96 22 55 8 10 21 0 8.1 5 0.14 0.72 0.2 0.60 60
Distillers Grain, Sorghum, Dry 91 87 96 64 90 32 62 13 22 44 4 10.0 3 0.22 0.63 0.3 0.45 50
Distillers Grain, Sorghum, Wet 35 87 96 64 90 32 55 13 22 44 4 10.0 3 0.22 0.63 0.3 0.45 50
Distillers Grain, Sorghum with Solubles 92 85 93 62 88 31 53 13 19 47 4 10.0 3 0.25 0.65 0.5 0.40 55
Distillers Dried Solubles 93 88 98 65 91 29 0 4 7 22 4 9.2 7 0.33 1.38 1.8 0.28 0.40 91
Elephant (Napier) grass hay, chopped 92 55 55 21 54 9 24 46 63 85 2.0 10 0.35 0.30 1.3 0.10
Fat, Animal, Poultry, Vegetable 99 195 285 230 285 0 0 0 0 0 99.0 0 0.00 0.00 0.0
Feather Meal Hydrolyzed 92 69 71 43 70 86 73 2 16 44 23 6.5 4 0.60 0.62 0.2 0.30 1.85 95
Fescue KY 31 Fresh 29 64 65 36 65 15 20 25 32 64 40 5.5 9 0.48 0.37 2.5 0.18 22
Fescue KY 31 Hay Early Bloom 88 65 66 37 66 18 22 25 31 64 98 6.6 8 0.45 0.37 2.7 0.24 24
Fescue KY 31 Hay Mature 88 52 52 16 51 11 30 30 42 73 98 5.0 6 0.45 0.26 1.7 0.14 22
Fescue (Red) Straw 94 43 44 0 41 4 41 1.1 6 0.00 0.06
Fish Meal 90 74 78 49 76 66 60 1 2 12 10 8.0 20 5.50 3.15 0.7 0.76 0.80 130
Garbage Municipal Cooked 23 80 86 56 83 16 9 50 59 30 20.0 10 1.20 0.43 0.6 0.67
Grain Screenings 90 65 66 37 66 14 14 5.5 9 0.25 0.34 30
Grain Dust 92 73 77 48 75 10 11 2.2 10 0.30 0.18 42
Grape Pomace Stemless 91 30 38 0 27 12 45 32 48 53 34 7.5 9 0.50 0.08 0.5 0.01 24
Grass Hay 88 58 58 26 58 10 30 33 41 63 98 3.0 6 0.60 0.21 2.0 0.20 28
Grass Silage 30 61 62 31 61 11 24 32 39 60 61 3.4 8 0.70 0.24 2.1 0.22 29
Guar Meal 90 72 75 47 74 39 34 16 3.9 5
Hominy Feed 90 89 99 67 93 11 48 5 7 21 9 6.1 3 0.04 0.54 0.6 0.06 0.10 32
Hop Leaves 37 49 49 11 48 15 15 3.6 35 2.80 0.64
Hop Vine Silage 30 53 53 18 53 15 21 24 3.1 20 3.30 0.37 1.8 0.22 44
Hops Spent 89 37 40 0 35 23 26 30 4.5 7 1.60 0.60
Kelp Dried 91 32 38 0 29 7 7 10 0.5 39 2.72 0.31
Kenaf Hay 92 48 48 9 47 10 31 44 56 98 2.9 12
Kochia Fresh 29 55 55 21 55 16 23 1.2 18 1.10 0.30
Kochia Hay 90 53 53 18 53 14 27 1.7 14 1.00 0.20
Kudzu Hay 90 54 54 20 54 16 33 2.6 7 3.00 0.23
Lespedeza, Fresh Early Bloom 25 60 60 30 60 16 50 32 2.0 10 1.20 0.24 1.1 0.21
Lespedeza Hay 92 54 54 20 54 14 60 30 3.0 7 1.10 0.22 1.0 0.19 29
Limestone Ground 98 0 0 0 0 0 0 0 0 0 0 0.0 98 34.00 0.02 0.03
Limestone Dolomitic Ground 99 0 0 0 0 0 0 0 0 0 0 0.0 98 22.30 0.04 0.4
Linseed Meal Solvent 91 76 81 52 78 39 36 10 18 25 23 1.9 6 0.43 0.93 1.5 0.04 0.47 60
Meadow Hay 90 50 50 12 49 7 23 33 44 70 98 2.5 9 0.61 0.18 1.6 0.17 24
Meat Meal, Swine/Poultry 93 71 74 46 73 56 64 2 7 48 0 10.5 24 9.00 4.42 0.5 1.27 0.48 190
Meat and Bone Meal, Swine/Poultry 93 72 75 47 74 56 24 1 5 34 0 10.0 29 13.50 6.50
Milk, Dry, Skim 94 87 96 64 90 36 0 0 0 0 0 1.0 8.4 1.36 1.09 1.7 0.96 0.34 41
Mint Slug Silage 27 55 55 21 55 14 24 1.8 16 1.10 0.57
Molasses Beet 77 75 79 50 77 9 0 0 0 0 0 0.2 12 0.12 0.03 6.0 1.64 0.60 18
Molasses Cane 76 75 79 50 77 6 0 0 0 0 0 0.8 12 0.97 0.10 3.7 2.50 0.55 25
Molasses Cane Dried 94 74 78 49 76 9 0 2 3 7 0 0.3 14 1.10 0.15 3.6 3.00 0.47 30
Molasses, Cond. Fermentation Solubles 46 80 16 0.25 12.60
Molasses Citrus 65 77 82 53 79 10 0 0 0 0 0 0.3 8 1.90 0.17 0.2 0.11 0.23 137
Molasses Wood, Hemicellulose 61 76 81 52 78 1 0 1 2 4 0 0.7 9 1.30 0.09 0.1 0.05
Monoammonium Phosphate 98 0 0 0 0 70 0 0 0 0 0 0.0 24 0.30 24.70 0.0 1.42 81
Mono-Dicalcium Phosphate 97 0 0 0 0 0 0 0 0 0 0.0 94 16.70 21.10 0.1 1.20 70
Oat Hay 90 54 54 20 54 10 25 31 39 63 98 2.3 8 0.40 0.27 1.6 0.42 0.21 28
Oat Silage 35 60 60 30 60 12 21 31 39 59 61 3.2 10 0.34 0.30 2.4 0.50 0.25 27
Oat Straw 91 48 48 9 47 4 40 41 48 73 98 2.3 8 0.24 0.07 2.4 0.78 0.22 6
Oat Grain 89 76 81 52 78 13 18 11 15 28 34 5.0 4 0.05 0.41 0.5 0.11 0.20 40
Oat Grain, Steam Flaked 84 88 98 65 91 13 26 11 15 30 32 4.9 4 0.05 0.37 0.5 0.11 0.20 40.00
Oat Groats 91 91 102 69 95 18 15 3 6.6 2 0.08 0.47 0.4 0.10 0.20
Oat Middlings 90 90 100 68 94 17 20 3 4 6.0 3 0.06 0.48 0.5 0.23
Oat Mill By-product 89 33 38 0 30 8 25 37 2.6 6 0.12 0.23 0.6 0.24
Oat Hulls 93 40 42 0 38 4 25 32 40 75 90 1.5 7 0.16 0.15 0.6 0.08 0.14 31
Orange Pulp Dried 89 80 86 56 83 9 9 16 20 33 1.8 4 0.71 0.11 0.6 0.05
Orchardgrass Fresh Early Bloom 24 65 66 37 66 14 23 30 32 54 41 4.0 9 0.33 0.39 2.7 0.08 0.20 21
Orchardgrass Hay 88 59 59 28 59 10 27 34 40 67 98 3.3 8 0.32 0.30 2.6 0.41 0.20 26
Pea Vine Hay 89 60 60 30 60 10 32 52 62 92 1.8 7 1.20 0.21 1.2 0.20 20
Pea Vine Silage 25 58 58 26 58 16 29 44 55 61 3.3 8 1.25 0.28 1.6 0.29 32
Pea Straw 89 50 50 12 49 7 42 49 72 98 1.3 7 0.60 0.15 1.1 0.15
Peas Cull 89 86 95 63 89 25 22 7 9 15 0 1.5 4 0.15 0.45 1.1 0.06 0.26 30
Peanut Hulls 91 22 36 0 18 7 63 65 74 98 1.5 5 0.20 0.07 0.9
Peanut Meal Solvent 91 77 82 53 79 50 27 8 15 27 23 3.6 6 0.24 0.58 1.0 0.03 0.30 38
Peanut Skins 92 0 0 0 0 17 13 20 28 0 22.0 3 0.19 0.20
Pearl Millet Grain 87 82 89 59 85 13 2 6 18 34 4.5 3 0.03 0.36 0.5
Pineapple Greenchop 17 45 45 3 44 8 23 35 64 41 2.6 7 0.28 0.08
Pineapple Bran 89 71 74 46 73 5 19 31 66 20 1.5 3 0.26 0.12
Pineapple Presscake 21 72 75 47 74 5 23 35 69 20 0.9 3 0.24 0.10
Potato Vine Silage 15 59 59 28 59 15 26 3.7 19 2.10 0.29 4.0 0.37
Potatoes Cull 21 80 86 56 83 10 0 2 3 4 0 0.4 5 0.03 0.24 2.2 0.30 0.09
Potato Waste Wet 14 82 89 59 85 7 0 9 11 15 0 1.5 3 0.16 0.25 1.2 0.36 0.11 12
Potato Waste Dried 89 85 93 62 88 8 0 7 9 12 0 0.5 5 0.16 0.25 1.2 0.39 0.11 12
Potato Waste Wet with Lime 17 80 86 56 83 5 0 10 12 16 0 0.3 9 4.20 0.18
Potato Waste Filter Cake 14 77 82 53 79 5 0 2 7.7 3 0.10 0.19 0.2
Poultry By-product Meal 93 79 85 55 81 62 49 2 14.5 17 4.00 2.25 0.5 0.58 0.56 129
Poultry Manure Dried 89 38 40 0 36 28 22 13 15 35 0 2.1 33 10.20 2.80 2.3 1.05 0.20 520
Prairie Hay 91 50 50 12 49 7 37 34 47 67 98 2.0 8 0.40 0.15 1.1 0.06 0.06 34
Pumpkins, Cull 10 85 93 62 88 16 14 18 25 0 8.9 9 0.24 0.43 3.3
Rice Straw 91 40 42 0 38 4 40 55 72 100 1.4 12 0.25 0.08 1.1 0.11
Rice Straw Ammoniated 87 45 45 3 44 9 39 53 68 100 1.3 12 0.25 0.08 1.1 0.11
Rice Grain 89 79 85 55 81 8 30 10 12 16 34 1.9 5 0.07 0.32 0.4 0.09 0.05 17
Rice Polishings 90 90 100 68 94 14 4 5 14.0 9 0.05 1.36 1.2 0.12 0.19 28
Rice Bran 91 72 75 47 74 14 30 13 18 23 0 19.0 11 0.07 1.70 1.8 0.09 0.19 40
Rice Hulls 92 13 35 0 8 3 45 44 70 81 90 0.9 20 0.14 0.07 0.5 0.08 0.08 24
Rice Mill By-product 91 42 43 0 40 7 32 48 60 0 5.7 0.40 0.31 2.2 0.30 31
Rye Grass Hay 90 58 58 26 58 10 30 33 38 65 98 3.3 8 0.45 0.30 2.2 0.18 27
Rye Grass Silage 32 59 59 28 59 14 25 22 37 59 61 3.3 8 0.43 0.38 2.9 0.73 0.23 29
Rye Straw 89 44 44 1 43 4 44 55 71 100 1.5 6 0.24 0.09 1.0 0.24 0.11
Rye Grain 89 82 89 59 85 12 20 2 9 19 34 1.7 2 0.07 0.39 0.5 0.03 0.17 33
Safflower Meal Solvent 91 55 55 21 55 24 33 41 57 36 1.2 6 0.35 0.78 1.0 0.21 0.23 65
Safflower Meal Dehulled Solvent 91 76 81 52 78 48 9 0.6 7 0.38 1.60 1.2 0.18 0.22 36
Sagebrush Fresh 50 50 50 12 49 13 25 28 36 9.2 10 1.00 0.25 0.22
Sanfoin Hay 88 61 62 31 62 14 60 24 3.1 9
Shrimp Waste Meal 90 48 48 9 47 50 60 11 5.5 25 8.50 1.75 1.15
Sodium Tripolyphosphate 96 0 0 0 0 0 0 0 0 0 0.0 96 0.00 25.98 0.0 0.00
Sorghum Stover 87 55 55 21 55 5 33 41 65 100 1.9 10 0.49 0.12 1.2
Sorghum Silage 32 59 59 28 59 9 30 27 38 59 70 2.7 6 0.48 0.21 1.7 0.45 0.11 30
Sorghum Grain (Milo) Ground 89 82 89 59 85 11 55 3 6 16 5 3.1 2 0.04 0.32 0.4 0.10 0.14 18
Sorhum Grain (Milo) Flaked 82 90 100 68 94 11 62 3 6 20 38 3.1 2 0.04 0.28 0.4 0.10 0.14 18
Soybean Hay 89 52 52 16 51 15 35 40 55 92 2.2 8 1.29 0.30 1.1 0.15 0.24 24
Soybean Straw 88 42 43 0 40 5 44 54 70 100 1.4 6 1.59 0.06 0.6 0.26
Soybeans Whole 88 93 104 71 97 40 28 9 11 15 100 18.8 5 0.27 0.64 2.0 0.03 0.34 56
Soybeans Whole, Extruded 88 93 104 71 97 40 35 9 11 15 100 18.8 5 0.27 0.64 2.0 0.03 0.34 56
Soybeans Whole, Roasted 88 93 104 71 97 40 48 9 11 15 100 18.8 5 0.27 0.64 2.0 0.03 0.34 56
Soybean Hulls 90 77 82 52 79 12 28 38 46 64 28 2.6 5 0.55 0.17 1.4 0.02 0.12 38
Soybean Meal Solvent 44% CP 91 84 92 61 87 49 35 6 10 15 23 1.6 7 0.38 0.71 2.3 0.07 0.43 62
Soybean Meal CP Solvent 49% 91 87 96 64 90 54 36 3 6 9 23 1.2 6 0.28 0.71 2.2 0.08 0.47 61
Soybean Mill Feed 90 51 51 14 50 15 36 46 2.0 6 0.49 0.18 1.7 0.07
Spelt Grain 88 75 79 50 77 13 27 10 17 21 34 2.1 4 0.04 0.40 0.4 0.15 47
Sudangrass Fresh Immature 18 70 73 44 71 17 23 29 55 41 3.9 9 0.46 0.36 2.0 0.11 24
Sudangrass Hay 88 57 57 25 57 9 30 36 43 67 98 1.8 10 0.50 0.22 2.2 0.80 0.12 26
Sudangrass Silage 31 58 58 26 58 10 28 30 42 64 61 3.1 10 0.58 0.27 2.4 0.52 0.14 29
Sunflower Seed Meal Solvent 92 65 66 37 66 38 27 20 24 36 23 2.5 8 0.44 0.97 1.2 0.15 0.33 55
Sunflower Seed Meal with Hulls 91 57 57 25 57 31 35 27 32 44 37 2.4 7 0.40 1.03 1.0 0.30 85
Sunflower Seed Hulls 90 40 42 0 38 4 65 52 63 73 90 2.2 3 0.00 0.11 0.2 0.19 200
Sugar Cane Bagasse 91 36 39 0 34 1 49 59 86 100 0.7 3 0.90 0.29 0.5 0.10
Tapioca Meal 89 83 90 60 86 2 5 8 34 0.8 3 0.03 0.05
Timothy Fresh Pre-bloom 26 64 65 36 65 11 20 31 36 59 41 3.8 7 0.40 0.28 1.9 0.57 0.15 28
Timothy Hay Early Bloom 88 59 59 28 59 11 22 32 39 63 98 2.7 6 0.58 0.26 1.9 0.51 0.21 30
Timothy Hay Full Bloom 88 57 57 25 57 8 30 34 40 65 98 2.6 5 0.43 0.20 1.8 0.62 0.13 25
Timothy Silage 34 59 59 28 59 10 25 34 45 70 61 3.4 7 0.50 0.27 1.7 0.15
Tomato Pomace Dried 92 64 65 36 65 23 26 50 55 34 10.6 6 0.43 0.59 3.6
Triticale Hay 90 56 56 23 56 10 34 41 69 98 0.30 0.26 2.3 25
Triticale Silage 34 58 58 26 58 14 30 39 56 61 3.6 0.58 0.34 2.7 0.28 36
Triticale Grain 89 85 93 62 88 14 25 4 5 22 34 2.4 2 0.07 0.39 0.5 0.17 37
Turnip Tops (Purple) 18 69 71 43 70 16 10 13 2.6 13 3.20 0.31 3.0 1.80 0.27
Turnip Roots 9 86 95 63 89 12 0 11 34 44 40 1.5 8 0.70 0.34 3.2 0.65 0.43 40
Urea 46% N 99 0 0 0 0 288 0 0 0 0 0 0.0 0 0.00 0.00 0.0 0.00 0.00 0
Vetch Hay 89 58 58 26 58 18 14 30 33 48 92 1.8 8 1.25 0.34 2.4 0.13
Wheat Fresh, Pasture 21 71 74 46 73 20 16 18 30 50 41 4.0 13 0.35 0.36 3.1 0.67 0.22
Wheat Hay 90 57 57 25 57 9 25 29 38 66 98 2.0 8 0.21 0.22 1.4 0.50 0.19 23
Wheat Silage 33 59 59 28 59 12 21 28 37 62 61 3.2 8 0.40 0.28 2.1 0.50 0.21 27
Wheat Straw 91 42 43 0 40 3 60 43 58 81 98 1.8 8 0.16 0.05 1.3 0.32 0.17 6
Wheat Straw Ammoniated 85 50 50 12 49 9 25 40 55 76 98 1.5 9 0.15 0.05 1.3 0.30 0.16 6
Wheat Grain 89 88 98 65 91 14 23 3 4 12 0 2.3 2 0.05 0.43 0.4 0.09 0.15 40
Wheat Grain Hard 89 88 98 65 91 14 28 3 6 14 0 2.0 2 0.05 0.43 0.5 0.16 45
Wheat Grain Soft 89 88 98 65 91 12 23 3 4 12 0 2.0 2 0.06 0.40 0.4 0.15 30
Wheat Grain, Steam Flaked 85 91 102 69 95 14 29 3 4 12 0 2.3 2 0.05 0.39 0.4 0.15 40
Wheat Grain Sprouted 86 88 98 65 91 12 18 3 4 13 0 2.0 2 0.04 0.36 0.4 0.17 45
Wheat Bran 89 70 73 44 71 17 28 11 13 46 4 4.5 7 0.13 1.29 1.4 0.05 0.24 96
Wheat Middlings 89 82 89 59 85 19 22 8 12 36 2 4.6 5 0.15 1.02 1.4 0.05 0.21 98
Wheat Mill Run 90 75 79 50 77 17 28 9 12 37 0 4.4 5 0.12 1.00 1.2 0.07 0.22 90
Wheat Shorts 89 80 86 56 83 20 25 7 7 30 0 5.4 5 0.10 0.95 1.1 0.08 0.20 118
Wheatgrass Crested Fresh Early Bloom 37 60 60 30 60 11 25 26 28 50 41 1.6 7 0.46 0.32 2.4
Wheatgrass Crested Fresh Full Bloom 50 55 55 21 55 10 33 33 36 65 41 1.6 7 0.39 0.28 2.1
Wheatgrass Crested Hay 92 54 54 20 54 10 33 33 36 65 98 2.4 7 0.33 0.20 2.0 32
Whey Dried 94 82 89 59 85 14 15 0 0 0 0 1.0 9 1.00 0.90 1.4 1.20 0.92 10

Health challenges in grass cattle

Responding to health problems out on pasture presents some unique challenges beyond those related to therapy in feedlots or other more confined environments. Two of the biggest issues are safety for man and beast, and continuing to adhere to quality assurance guidelines in a less controlled environment.

We suggest these discussion points as you sit down with your veterinarian to plan responses to challenges cattle face while on grass.

The Usual Suspects

Which diseases are the most likely in pasture cattle? This answer depends on your specific area, but there are some diseases we should watch for almost anywhere. In this column, we'll focus on infectious diseases. Be sure you know the signs to watch for and plan your responses in advance.

  • Respiratory disease

    Here we're dealing with a potential combination of viral and bacterial pathogens. Work with your veterinarian to classify groups of stocker cattle as low or high risk, based on history and appearance. High-risk cattle are often described as those we expect to present a 10% or greater morbidity (illness) rate related to respiratory disease.

    Such cattle often do better on grass, but are still capable of presenting significant health challenges. You may want to consider a longer confinement time to more easily deal with health issues as they arise. Smaller grass traps close to treatment facilities are one option.

    Typically, most of the morbidity occurs in the first 30 days with high-risk cattle. It may be helpful for you to feed a little grain to these cattle during the first 20-30 days of ownership to more quickly find cattle that have BRD. These cattle will tend to be slow to come to the bunk just like feedlot cattle with BRD.

    Another respiratory disease occurs when cattle are suddenly exposed to lush, rapidly growing pastures. Acute interstitial pneumonia, also known as fog fever, results in lungs that rapidly fill with fluid and cause severe respiratory distress in the animal. A different therapeutic approach is required as compared to infectious respiratory disease, with response to therapy often poor unless instituted early and combined with removal from the offending feed source.

  • Clostridial diseases

    Clostridial genus of bacteria is responsible for diseases such as blackleg, malignant edema, overeating disease and tetanus. These bacteria are capable of forming spores and waiting out unfavorable conditions only to revive when conditions are favorable.

    If you've had tetanus (lock jaw) in your cattle, it will likely be a potential problem any time you castrate or dehorn, as it can survive long periods in the soil as a spore. Seven-way clostridial vaccines don't contain the tetanus antigen, so this must be added to your program when needed. Prevention of clostridial diseases is the best option because response to therapy is often poor.

  • Footrot

    This disease is often seen when wet conditions are combined with compromised skin between the claws of the feet. However, outbreaks in dry conditions may occur as well. Treatment response is usually quite good when started at the first signs of lameness.

  • Pinkeye

    Prevention of this disease involves fly control, pasture trimming and vaccination, although you should discuss the potential of vaccines with your veterinarian. Some literature reports mixed or minimal results for common therapies of pinkeye.

  • Anaplasmosis

    Flies or contaminated needles are commonly responsible for transmitting this blood parasite. Younger animals can spike a fever and recover.

The disease may be fatal to older cows and bulls, however. They lose the ability to carry oxygen in the blood due to the loss of red blood cells, with resulting signs of exercise intolerance and rapid breathing. Rapid treatment is key to saving the animal. Most cases appear late in the summer and in the fall.

Drug Choices

Should drug choices for grass cattle be different than for feedlot cattle?

Most producers place a premium on single-injection drug options in pasture situations. Effective, single-injection therapies are available for respiratory disease and are also possible for early treatment of footrot and pinkeye.

This is a more difficult goal for clostridial diseases. Whatever drugs are chosen, be sure to protect drug quality. Storage on pickup dashboards or in interiors that reach extreme temperatures will degrade drug quality and affect results.

Your veterinarian can help you evaluate the safety of different drugs in situations where restraint isn't optimal. Drugs labeled only for intravenous (IV) use should not be administered intramuscularly (IM) just because proper restraint isn't possible.

Not only are slaughter withdrawal time and effectiveness potentially altered but many IV-only labeled drugs may cause significant tissue damage when injected in other sites. The same principles apply when drugs labeled only for subcutaneous use are injected IM.

What About Quality Assurance?

Paying attention to needles on pasture is especially important. Bent needles are prone to break off in the animal. Discard them immediately. Never straighten a bent needle. Discard needles with burrs on the tips.

Volume per injection site is sometimes compromised when we're in a hurry. Increasing volume per site can result in increased injection-site damage, as well as altered drug absorption and increased slaughter withdrawal times.

In addition, be sure to routinely bring non-disposable syringes and equipment in from the truck or saddlebags for cleaning. Clean injection systems result in fewer injection-site reactions and improved drug efficacy.

Discuss these points with your veterinarian and ask for additional advice on being prepared for spotting and treating diseases in pasture cattle.

Editor's Note: For more on these diseases go to www.beefcowcalf.com and enter the disease name into the “Title Search” box on the opening page.

Mike Apley, DVM, PhD, is an associate professor of beef production medicine at Iowa State University in Ames. W. Mark Hilton, DVM, is clinical assistant professor of beef production medicine at Purdue University in West Lafayette, IN.