Buckeye Dairy News : Volume 16 Issue 4

  1. U.S. Dairy Markets and Policy Update

    Dr. Cameron S. Thraen, Associate Professor and OSUE State Dairy Markets and Policy Specialist, Department of Agricultural, Environmental and Development Economics, The Ohio State University

    Policy Update: Margin Protection Program (MPP)

    On August 28, 2014, USDA Secretary Vilsack officially announced the start of the new Margin Protection Program (MPP). Here are some of the highlights. If you elect to participate, you will be required to establish a production history (PH) based on the highest annual production from the calendar years 2011, 2012, or 2013.  Once established, your production history will be allowed to increase by the U.S. average production growth.  There is no penalty for increasing production over this level other than the stipulation that extra production will not be eligible for the coverage under the MPP.  Selecting coverage above the lowest level of $4 will require you to pay a premium.  Premiums follow a two tier schedule.  For a production base at 4 million pounds or less, there is one schedule, and for those farms with a production base over 4 million pounds, another more expensive schedule exists.  For those producers whose annual production is at or below 4 million pounds, the cost of coverage all the way up to $6.50 remains very reasonable, only becoming more expensive at the $7 to $8 levels.  For a producer whose annual production base is above the 4 million pounds, the cost is still modest up to the $5 level, but then it increases rather significantly above that point.  There are provisions for new farms, farms with multiple owners and owners with multiple farms.  You will not be allowed to simultaneously use Livestock Gross Margin (LGM) Insurance and this MPP program.  There are rules in place that spell out very clearly how MPP and LGM-dairy will coexist.  As the program is now officially launched, you will be able to register with your local USDA Farm Services Agency beginning September 2, 2014 up through November 28, 2014.  At the time of registration, you will be able to select a coverage percentage (25 to 90%, 5% increments) and a coverage level ($4 to $8, 50 cent increments).  During this initial period, you will be able to make this selection for the remainder of 2014 and all of 2015. A producer does not have to make this decision now but can wait until the following registration period.  However, once the decision is made to register and participate in the program, you are obligated to pay the $100 administrative fee each year until September 2018.  Elections of coverage percentage and coverage level are made each year and can be changed during the enrollment period for each year.  After November 2014, enrollment will occur from July through September for calendar years 2016, 2017, and 2018.

    In addition to the MPP, the farm bill language directs the Secretary of Agriculture to implement a dairy product purchase and donation program to augment commercial demand with the intent of increasing the milk price in times of low margins.

    The new dairy program published in the U.S. Federal Register can be found at: http://www.gpo.gov/fdsys/pkg/FR-2014-08-29/pdf/2014-20567.pdf If you do not enjoy reading the U.S. Federal Register, you will find a very readable exposition on the new dairy program at this link: http://dairymarkets.org/PubPod/Pubs/IL14-02.pdf. Information about the dairy margin tool as administered by the USDA Farm Service Agency can be found at: http://www.fsa.usda.gov/FSA/pages/content/farmBill/fb_MPPDTool.jsp

    National U.S. Dairy Margin Update

    The MPP margin is forecasted to stay above $10.00/cwt through the next 15 months.  This forecast is updated daily.  If you wish to follow the Dairy Markets and Policy DPMPP margin forecast, go to the DmaP website (http://dairy.wisc.edu/Tools/MILC-MPP.html).

    Figure 1

    If you would like to read more about these programs, link into the Dairy Markets and Policy website (http://dairymarkets.org/MPP/).  Here you will find a wide assortment of support information on this new program.

  2. Milk Prices, Costs of Nutrients, Margins and Comparison of Feedstuffs Prices

    Dr. Normand St-Pierre, Extension Dairy Management Specialist, Department of Animal Sciences, The Ohio State University

    The Good Side: Milk Prices

    As I write this column in late August, the Class III futures have just closed at $22.24/cwt for August and $23.89/cwt for September.  Last month, the Class III milk settled at $21.60/cwt, an increase of $4.20 over July of last year.  For the balance of 2014, the Class III futures are averaging $21.84/cwt.  On the feed side, corn has come down from a peak this spring with Chicago Mercantile Exchange (CME) September futures now at about $3.56/bu and December futures at $3.63/bu.  Soybean meal futures for September are currently trading around $435/ton, steadily dropping to $349/ton by next December.  Using prevailing cash prices for feeds, we estimate that the feed costs to produce a hundredweight of milk in Ohio are in the $9.50 to $10.50/cwt range.  This leaves milk margin over feed costs somewhere between $12.00 and $14.00/cwt, resulting in net margins between $5.00 and $6.00/cwt.  Clearly, milking cows is currently a profitable business, but much of the additional margins are being used to replenish cash reserves that were depleted during the difficult time that the industry went through until late summer of 2013, and also to make much needed re-investments in machinery and equipment.

    A Greatly Improved Picture: Nutrient Prices

    As usual in this column, I used the software SESAME™ that we developed at Ohio State to price the important nutrients in dairy rations to estimate break-even prices of all major commodities traded in Ohio and to identify feedstuffs that currently are significantly underpriced as of August 25, 2014.  Price estimates of net energy lactation (NEL,$/Mcal), metabolizable protein (MP, $/lb – MP is the sum of the digestible microbial protein and digestible rumen-undegradable protein of a feed), non-effective NDF (ne-NDF, $/lb), and effective NDF (e-NDF, $/lb) are reported in Table 1. Compared to its historical 6-year average of about 10¢/Mcal, NEL is now priced much more reasonably (11.0¢/Mcal) than it has been over the last 12 months.  This is important because a cow producing 70 lb/day of milk requires in the neighborhood of 33 Mcals of NEL/day.  This means that providing the required dietary energy for an average cow should cost in the neighborhood of 33 x 0.11 = $3.63/day.  For MP, its current price (63.3¢/lb) is more than 2 times greater than its 6-year average (28¢/lb).  Thus, we are currently in a period of normal energy prices, but considerably above average protein prices.  The cost of ne-NDF is currently discounted by the markets (i.e., feeds with a significant content of ne-NDF are priced at a discount), and the discount of -21.1¢/lb is much above the 6-year average (-9¢/lb).  It is summer time, a period when high fiber byproducts are typically a bargain.  Meanwhile, unit cost of e-NDF is at about 3 times its 6-year average, being priced at 9.4¢/lb compared to the 6-year average (3.3¢/lb).  Fortunately, a dairy cow requires only 10 to 11 lb of e-NDF, so the daily cost of providing this nutrient is about $0.99/cow per day (i.e., 10.5 lb × $0.094 per lb).  So from a historical basis (i.e., using averages from the last 6 years as the bases of comparison), feeds and their nutrients are still expensive but not as much as last year.

    Table 1.  Prices of dairy nutrients for Ohio dairy farms,
    mid-August 2014.
    Table 1

    Economic Value of Feeds

    Results of the Sesame analysis for central Ohio in mid-August are presented in Table 2. Detailed results for all 27 feed commodities are reported.  The lower and upper limits mark the 75% confidence range for the predicted (break-even) prices.  Feeds in the “Appraisal Set” were those for which we didn’t have a price.  One must remember that Sesame compares all commodities at one point in time, mid-August in this case.  Thus, the results do not imply that the bargain feeds are cheap on a historical basis.

    Table 2.  Actual, breakeven (predicted) and 75% confidence limits of 27 feed commodities used on
    Ohio dairy farms, mid-June 2014.
    Table 2

    For convenience, Table 3 summarizes the economic classification of feeds according to their outcome in the Sesame analysis.

    Table 3. Partitioning of feedstuffs, Ohio, mid-August 2014.


    At Breakeven


    Alfalfa hay – 40% NDF
    Bakery byproducts
    Corn, ground, shelled
    Corn silage
    Distillers dried grains
    Feather meal
    Gluten feed
    Gluten meal
    Soybean meal – expeller

    41% Cottonseed meal
    Cottonseed, whole
    Roasted soybeans
    Wheat middlings

    Beet pulp
    Blood meal
    Brewers grains, wet
    Canola meal
    Citrus pulp
    Meat meal
    Soybean hulls
    44% soybean meal
    48% soybean meal
    Wheat bran

    As usual, I must remind the readers that these results do not mean that you can formulate a balanced diet using only feeds in the “bargains” column.  Feeds in the “bargains” column offer savings opportunity and their usage should be maximized within the limits of a properly balanced diet.  In addition, prices within a commodity type can vary considerably because of quality differences, as well as non-nutritional value added by some suppliers in the form of nutritional services, blending, terms of credit, etc.  Also, there are reasons that a feed might be a very good fit in your feeding program while not appearing in the “bargains” column.


    A few people have asked that I publish the results using the 5-nutrient group (i.e., replace metabolizable protein by rumen degradable protein and digestible rumen undegradable protein).  A table containing these results is provided herewith.

    Table 4. Prices of dairy nutrients using the
    5-nutrient solution for Ohio dairy farms,
    mid-August 2014.
    Table 4

  3. A Diet Is Only as Good as the Data Used to Formulate I

    Drs. Bill Weiss and Normand St-Pierre, Professors and Extension Dairy Specialists, Department of Animal Sciences, The Ohio State University

    The typical process of formulating a diet for dairy cows goes as follows: (1) sample the forages on the farm, (2) send the samples to a good lab, (3) when the lab results are available then enter the data into a computer, and (4) formulate the diet using a good dairy cow nutrition model.  Because forages usually make up more than half the diet dry matter (DM), using incorrect nutrient composition data for the forages could result in an unbalanced diet, which could reduce yields of milk or components, or increase health problems.

              We have been conducting a large project evaluating variation in nutrient composition of feeds. Commonly, silages on a farm are sampled about once monthly and the data from that single sample are used to formulate or re-formulate diets.  One objective we had was to determine if that approach is in fact adequate. We sampled corn and haycrop (mostly alfalfa but some farms fed mixed grass and alfalfa) silages on several Ohio dairy farms and on a few farms in Vermont each day for 14 consecutive days.  Each day, we took 2 independent samples from each silage. Independent means that we took several handfuls of silage, put them in a bucket, mixed that and then took a few handfuls, and put them in a bag to be sent to the lab.  We then repeated that process to get the 2 independent samples.  All samples were sent to the OARDC dairy nutrition lab and each sample was assayed in duplicate for DM and neutral detergent fiber (NDF). Haycrop silage was also assayed for crude protein (CP), and corn silage was assayed for starch. By taking duplicate samples from multiple farms, over multiple days and then analyzing everything in duplicate, we could partition the variation into that caused by farm, sampling, analytical, and day.

    Sources of Variation

    The nutrient composition of feeds can vary for a number of reasons.  It is important to know what caused the variation when formulating diets.

    • Farm variation in nutrient composition of silages reflects different growing conditions on different farms, different hybrids, different harvest times, etc. Because of the numerous factors that differ among farms, this variation is usually very large.
    • Analytical variation is usually caused by human error (for example very small differences in weighing), instrument calibrations, reaction conditions, etc. It could also be caused by different labs. In this study, all samples were analyzed in a single lab.  So the analytical variation that we observed is less than what would be experienced if samples were sent to different labs.
    • Sampling variation can be a difficult concept to understand. If you have a pile of corn silage that will be fed today and you grab 5 handfuls of silage and put each into a separate bag and send each bag to a lab, you will likely get 5 different values for CP, NDF, starch, and DM concentrations.  These differences represent sampling variation (sometimes referred to as sampling error). For corn silage, two samples could have different NDF concentrations because one sample had a little more corn cob in it than the other sample.  Although one should always try to take representative samples, multiple samples of different feeds will never be identical.
    • Day variation can also be called true day-to-day variation.  This means that the composition of the feed really did change over time. This change could be caused by differences in harvest time (for example, the sample of alfalfa silage taken on Monday may have been harvested late in the afternoon, but the sample taken on Wednesday was harvested in the morning), field location (e.g., a weedy or dry spot in the field was sampled on a specific day).

    Since forages are almost always sampled for each specific farm, farm-to-farm variation is not that important. In this study, farm variation was very large, meaning that silages should be sampled for each farm. However, separating true day-to-day variation from sampling and analytical variation within each farm is important. If a sample of silage is taken this week and it has 40% NDF and another sample is taken next week and it is 45% NDF, if that difference was caused by sampling error (in other words, the silage really did not change) and you reformulate the diet to match the new NDF concentration, the new diet is not going to be properly balanced. On the other hand, if the silage really did change (a true day-to-day change) and the diet is not reformulated, the diet being fed also is not properly balanced.

    What We Found

    1. Analytical variation for all nutrients and both types of silages was low, meaning you do not have to pay labs to analyze a given silage sample in
    2. For corn silage NDF and starch and for haycrop NDF and CP, sampling errors were much greater than true day-to-day variation. This means that over a short period (a few weeks), differences between samples in nutrient composition are likely not a real change. The data for the samples should be averaged and the average values should be used in ration formulation.
    3. True day-to-day variation was the major source of variation for DM concentrations of haycrop silage. This means that when DM concentrations change among samples, the change is likely real and diets should be modified.  For corn silage DM, true day-to-day variation was about equal to sampling plus analytical variations. This means you should probably measure DM on duplicate samples and if the averages between 2 sets of samples are different, the silage DM really changed and the diet should be modified.

    Bottom Line

    The nutrient composition of silages is variable.  However many times when we think that the silage has changed, it really is simply sampling error. Good sampling techniques should reduce sampling variation, but taking duplicate samples and averaging the results will greatly reduce sampling variation. Be careful when making diet changes based on lab results; make sure the feeds have actually changed.

  4. Corn Silage Harvest Timing

    Dr. Mark Sulc, Professor, Department of Horticulture and Crop Science; Dr. Peter Thomison, Professor, Department of Horticulture and Crop Sciences; and Dr. Bill Weiss, Professor and Extension Dairy Specialists, Department of Animal Sciences, The Ohio State University

    Corn development has accelerated with the recent warm temperatures. Silage harvest has begun in some parts of Ohio with earlier planting dates. Proper harvest timing is critical because it ensures the proper dry matter (DM) content required for high quality preservation, which in turn results in good animal performance and lower feed costs.

    Harvesting corn too wet (low DM content) results in souring, seepage, and storage losses of the silage with reduced animal intake. Harvesting too dry (high DM content) promotes mold development because the silage cannot be adequately packed to exclude oxygen. Harvesting too dry also results in lower energy concentrations and reduced protein digestibility.

    Corn silage that is too dry is almost always worse than corn silage that is slightly too wet. So if you are uncertain about the DM content, it is usually better to err on chopping a little early rather than a little late. Follow the guidelines below to be more confident in your assessment.

    Harvest Moisture Guidelines

    Corn preserved between 30 and 38% DM (62 to 70% moisture) generally provides excellent silage fermentation and animal performance. The optimal DM content varies with type of storage structure (Table 1).

    Table 1. Optimal dry matter (DM) contents for different storage structures.

    Type of Structure Optimal % DM
    Horizontal bunkers 30 to 35


    30 to 38

    Upright, top unloading

    33 to 38

    Upright, bottom unloading

    35 to 40*

    *The higher DM concentration for bottom unloading silos is a compromise
    between forage quality and unloader requirements.

    Kernel Stage Not a Reliable Guide for Timing Silage Harvest

    Dry matter content of whole plant corn varies with maturity.  Research has shown that the position of the kernel milk-line is NOT a reliable indicator for determining harvest timing. Geographic location, planting date, hybrid selection, and weather conditions affect the relationship between kernel milk-line position and whole plant DM content. In a Wisconsin study, 82% of the hybrids tested exhibited a poor relationship between kernel milk-line stage and whole-plant percentage of DM. In Ohio, we have seen considerable variation in plant DM content within a given kernel milk-line stage.

    Appearance of the kernels should only be used as a guide of when to begin sampling for DM content, see section below When to Begin Field Sampling.

    Determining Silage Moisture

    The only reliable method of determining the optimal time to harvest corn silage is to sample and directly measure the percentage DM of whole plants. This information, combined with average whole plant dry-down rates, can be used to roughly predict the proper time to chop corn silage.

    How to Sample Fields

    Collect about 5 representative plants from the entire field, from areas with representative plant population and not from edge rows. Collect separate samples from areas that may have different dry down rates, such as swales, knolls, etc. The moisture concentrations of plants can vary within a field (plants will be wetter in low lying area and drier on knolls), and this should be considered when collecting your sample plants.
    As soon as the plants are collected, chop them uniformly (using a cleaver, machete, chipper shredder, or silage chopper) and mix thoroughly to obtain a sample with representative grain to stover ratios for DM determination. Put the representative sample in a plastic bag and keep it cool (refrigerate if possible). Some farmers prefer sampling only 2 or 3 plants without any additional sub-sampling to reduce the chances of a non-representative grain to stover ratio that can affect the results. In this case, choosing representative plants is even more critical.

    Determine the DM content by drying the plant material using a Koster oven tester, microwave oven, convection oven, a vortex dryer, or taking it to a lab. For more details on these and other methods, see the following links:

    Make sure the sample does not dry down and keep it cool until the DM determination is performed. The accuracy of the DM value is largely affected by the care taken in sampling, drying, and weighing the samples. Whole kernels and cob pieces can be difficult to dry completely without burning the leaf tissue.

    From our work, on-farm measurement of DM is probably only accurate to +/- 2 units. So if you measure a DM of 30%, it could easily be 28 to 32%. Keep this in mind as you plan harvest timing.

    When to Begin Field Sampling

    We know that kernel milk stage is NOT reliable for determining the actual harvest date, but its appearance is a useful indicator of when to begin sampling fields to measure plant DM content.

    Corn in Ohio should be first sampled to measure DM at full dent stage (100% milk, no kernel milk-line) for conventional tower or bunker silos. Full dent stage happens about 40 days after silking in Ohio. For sealed (oxygen-limited) tower silos, begin sampling when the milk-line is one-fourth down the kernel (75% milk remaining). It is important to begin sampling early as a precaution against variation in dry down.

    The milk-line of on these ears is about one-fourth to one-third down the kernel. This stage might be about right for oxygen limited silos but could be too late for conventional tower or bunker silos.

    Predicting the Harvest Date

    Once whole-plant percentage of DM is determined, use an average dry down rate of 0.5% unit per day to estimate days until the optimal harvest moisture is reached. For example, if a given field measures 30% DM at the first sampling date, and the target DM is 35% for harvest, then the field must gain an additional 5% units of DM, thus requiring an estimated 10 days (5% units divided by 0.5 unit change per day).This procedure provides only a rough estimate for the harvest date. Many factors affect dry down rate, such as hybrid, planting date, general health of the crop, landscape position, soil type, and weather conditions. Early planted fields and hot and dry conditions can accelerate dry down rates to 0.8 to 1.0 % unit per day. Fields should be monitored closely and more frequently under those conditions. As mentioned above, corn silage that is slightly too dry is usually worse than corn silage that is slightly too wet.  So harvesting a little early is usually better than waiting too long.

    More Management Guidelines

    For additional details on management of corn silage, see the article by Bill Weiss in the Buckeye Dairy News (August 2010), available online at https://dairy.osu.edu/bdnews/Volume%2012%20issue%203%20files/Volume%2012%20Issue%203.html#Harvesting.

  5. The Ohio State University Receives Several Recognitions During the 2014 Joint Annual Meeting of the American Dairy Science Association (ADSA) and the American Society of Animal Science (ASAS)

    Maurice Eastridge, Extension Dairy Specialist, Department of Animal Sciences, The Ohio State University

    The 2014 Annual Meetings of ADSA and ASAS were held jointly July 20-24, 2014 in Kansas City, Missouri and also included the Canadian Society of Animal Science. The meetings attracted nearly 80 students and advisors in addition to the more than 3500 professionals and guests from the US, Mexico, Canada, and beyond. Among the many awards announced during the meeting, The Ohio State University faculty and students were certainly in the winners’ court.

    Dr. Joe Hogan received the Elanco Award for Excellence in Dairy Science at the awards ceremony of the ADSA Annual Meeting. "The Elanco Award for Excellence in Dairy Science was created to recognize outstanding research in dairy production or manufacturing contributing to improvement or care of dairy cattle, development and improvement of processes, products, equipment, methods, handling, and sanitation."

    Dr. Donald Palmquist received the ADSA Distinguished Service Award. "The ADSA Distinguished Service Award was created to recognize unusually outstanding and consistent contributions to the welfare of the dairy industry, either directly or indirectly. The award is based upon a broad, even nonscientific, contribution. Thus, outstanding achievements by those in industry, public administration, or academic administration qualify.”

    Dr. Normand St-Pierre received the DeLaval Dairy Extension Award at the ADSA Annual Meeting. "The DeLaval Dairy Extension Award was created to recognize outstanding achievements in dairy Extension. The winner must have made a valuable and noteworthy contribution to the dairy industry through dairy Extension in the broad areas of production, manufacturing, marketing, and youth work."

    The Ohio State Academic Quadrathlon (AQ) team won the national ASAS Undergraduate Academic Quadrathlon competition at the joint meeting! The competition was held July 20-21 in Kansas City, Missouri. Congratulations goes to Garth Ruff, Joey Brown, Keirsten Harris, and Logan Morris, as well as AQ advisor Dr. Joe Ottobre.

    The Ohio State Dairy Product Development Team from the Department of Food Science and Technology won first place during the competition held during the ADSA meeting. The product developed by the team was Trifle Au Lait. Team members included Anastasia Purgianto, Hardy Castada, Liz Green, Sara Burcham, Alex Milligan, and Ty Thammakulkrajang.

    Rachel Townsley, a dairy 4-H member from Champaign County, is majoring in food science at Ohio State and she works in the Animal Sciences Extension office. During the 2013 summer, she was a research intern for Dr. Kristy Daniels in Wooster. Rachel won the ADSA undergraduate original research poster competition, presenting her research on “Health of Holstein bull calves fed a fermentation extract of Aspergillus Oryzae”.

  6. Personnel Changes in the Department of Animal Sciences at The Ohio State University

    Maurice Eastridge, Extension Dairy Specialist, Department of Animal Sciences, The Ohio State University

    Zerby Dr. Henry Zerby became the new Chair of Animal Sciences in May. Dr. Zerby joined the faculty in December 1999 and was promoted to Professor in 2011. He received the PhD and MS degrees in meat science from Colorado State University and a BS from Penn State University. He has received many recognitions for his meat science program and teaching accomplishments. His contact information is: 110B Animal Science Building, 2029 Fyffe Court, Columbus, OH 43120, zerby.8@osu.edu, 614-292-6401.

    Pairis-GarciaDr. Monique Pairis-Garcia arrived on the faculty in August in the position of animal welfare and behavior. She received her PhD and DVM from Iowa State University and a BS degree from Grinnell College in IA. Her position is a 65% Extension and 35% appointment. Her instructional role will include teaching the course on “Animal Welfare and Behavior in Livestock Industries”. Her contact information is: 222E Animal Science Building, 2029 Fyffe Court, Columbus, OH 43120, pairis-garcia.1@osu.edu, 614-688-1968.

    • Dr. Kristy Daniels left in July to join the Department of Dairy Science at Virginia Tech.
    • Reagan Bluel, Waterman Dairy Farm manager, departed in June to become a regional dairy Extension specialist in southeast, MO. John Lemmermen was promoted to the position of manager of the unit, and Rebecca (Bekah) Meller, an OSU BS graduate and current MS student, has been hired as the assistant manager.

    With several retirements in recent years, the Department has positioned for hiring some additional faculty. We will be interviewing three candidates for a nutrient management position in September. We are presently advertising four available positions relating to ruminant nutrition, non-ruminant nutrition, intestinal microbiology, and meat science. With the administrative duties for Dr. Zerby, additional assistance is needed in teaching meat science courses. Thus, the Department has been interviewing for a professional faculty track position, a non-tenure track position to help with the immediate teaching needs.

  7. Dairy Youth Program Updates

    Ms. Bonnie Ayars, Dairy Judging Teams Coach and Extension Youth Specialist, The Ohio State University

    The 2014 edition of the Ohio State Fair was a success when we think of youth activities.  It was a wonderful moment to see so many dairy kids represented at the Sale of Champions.  There were also two dairy judging clinics with over 40 individuals attending each. It also is good to point out that our dairy skillathon was one of the larger ones with just about 130 participants. Results for these events are located at: www.4hansci.osu.edu/dairy.

    OSU dairy judging prospects also capably managed the parlor, the Milk-A-Cow activity, the birthing area, and the baby calf display. Each provided excellent educational experiences beyond the traditional classroom. Television stations stopped by often to conduct interviews.

    As I write this brief article, there are 45 of us on a charter bus headed to the Maryland State Fair for our annual dairy judging boot camp trip.